From 127b3ad67436db8102a739df137ff31310b40304 Mon Sep 17 00:00:00 2001 From: lucianommartins Date: Thu, 23 May 2024 01:54:44 +0000 Subject: [PATCH 1/4] Point gemini-1.5-flash-latest as default model for all quickstart notebooks --- quickstarts/Audio.ipynb | 510 +++--- quickstarts/Authentication.ipynb | 510 +++--- quickstarts/Authentication_with_OAuth.ipynb | 949 +++++----- quickstarts/Counting_Tokens.ipynb | 1307 ++++++-------- quickstarts/File_API.ipynb | 854 ++++----- quickstarts/Function_calling.ipynb | 1473 ++++++++-------- quickstarts/Function_calling_config.ipynb | 668 ++++--- quickstarts/Gemini_Flash_Introduction.ipynb | 1003 +++++------ quickstarts/JSON_mode.ipynb | 450 +++-- quickstarts/Models.ipynb | 485 ++--- quickstarts/PDF_Files.ipynb | 1008 +++++------ quickstarts/Prompting.ipynb | 938 +++++----- quickstarts/Safety.ipynb | 783 +++++---- quickstarts/Streaming.ipynb | 573 +++--- quickstarts/System_instructions.ipynb | 728 ++++---- quickstarts/Tuning.ipynb | 1563 +++++++++-------- quickstarts/Video.ipynb | 643 ++++--- quickstarts/file-api/.gitignore | 4 - quickstarts/file-api/README.md | 56 - quickstarts/file-api/package-lock.json | 519 ------ quickstarts/file-api/package.json | 14 - quickstarts/file-api/requirements.txt | 3 - quickstarts/file-api/sample.js | 50 - quickstarts/file-api/sample.py | 32 - quickstarts/file-api/sample.sh | 70 - .../file-api/sample_data/gemini_logo.png | Bin 19864 -> 0 bytes quickstarts/rest/Embeddings_REST.ipynb | 349 ---- quickstarts/rest/Function_calling_REST.ipynb | 766 -------- .../rest/Function_calling_config_REST.ipynb | 371 ---- quickstarts/rest/JSON_mode_REST.ipynb | 172 -- quickstarts/rest/Models_REST.ipynb | 163 -- quickstarts/rest/Prompting_REST.ipynb | 611 ------- quickstarts/rest/README.md | 3 - quickstarts/rest/Safety_REST.ipynb | 486 ----- quickstarts/rest/Streaming_REST.ipynb | 160 -- .../rest/System_instructions_REST.ipynb | 241 --- 36 files changed, 6881 insertions(+), 11634 deletions(-) delete mode 100644 quickstarts/file-api/.gitignore delete mode 100644 quickstarts/file-api/README.md delete mode 100644 quickstarts/file-api/package-lock.json delete mode 100644 quickstarts/file-api/package.json delete mode 100644 quickstarts/file-api/requirements.txt delete mode 100644 quickstarts/file-api/sample.js delete mode 100644 quickstarts/file-api/sample.py delete mode 100755 quickstarts/file-api/sample.sh delete mode 100644 quickstarts/file-api/sample_data/gemini_logo.png delete mode 100644 quickstarts/rest/Embeddings_REST.ipynb delete mode 100644 quickstarts/rest/Function_calling_REST.ipynb delete mode 100644 quickstarts/rest/Function_calling_config_REST.ipynb delete mode 100644 quickstarts/rest/JSON_mode_REST.ipynb delete mode 100644 quickstarts/rest/Models_REST.ipynb delete mode 100644 quickstarts/rest/Prompting_REST.ipynb delete mode 100644 quickstarts/rest/README.md delete mode 100644 quickstarts/rest/Safety_REST.ipynb delete mode 100644 quickstarts/rest/Streaming_REST.ipynb delete mode 100644 quickstarts/rest/System_instructions_REST.ipynb diff --git a/quickstarts/Audio.ipynb b/quickstarts/Audio.ipynb index 3ecc02f7f..c695dab9b 100644 --- a/quickstarts/Audio.ipynb +++ b/quickstarts/Audio.ipynb @@ -1,263 +1,253 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0etRtS83RcWS" - }, - "source": [ - "# Gemini API: Audio Quickstart\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "r1IzNLho-NqV" - }, - "source": [ - "This notebook provides an example of how to prompt Gemini 1.5 Pro using an audio file. In this case, you'll use a [sound recording](https://www.jfklibrary.org/asset-viewer/archives/jfkwha-006) of President John F. Kennedy’s 1961 State of the Union address." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Y6eH_Aq_NyNi" - }, - "outputs": [], - "source": [ - "!pip install -q -U google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LSe1pMEpR2L2" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "TXiv-NeZR5WA" - }, - "source": [ - "## Configure your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "dm-iaNMGPdid" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2YoxMrCdR7hf" - }, - "source": [ - "## Upload an audio file with the File API\n", - "\n", - "To use an audio file in your prompt, you must first upload it using the [File API](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb).\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "OHvNLws4RRjx" - }, - "outputs": [], - "source": [ - "URL = \"https://storage.googleapis.com/generativeai-downloads/data/State_of_the_Union_Address_30_January_1961.mp3\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Cxq31LDwSFH6" - }, - "outputs": [], - "source": [ - "!wget -q $URL -O sample.mp3" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "MAObE0BpaAwG" - }, - "outputs": [], - "source": [ - "your_file = genai.upload_file(path='sample.mp3')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "m01XDoo4UQvN" - }, - "source": [ - "## Use the file in your prompt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "YmISEsqpafRb" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "## Summary of President John F. Kennedy's 1961 State of the Union Address:\n", - "\n", - "**Main Theme:** The address focuses on the challenges and opportunities facing the United States both domestically and internationally, emphasizing the need for unity and action in the face of the Cold War and economic difficulties.\n", - "\n", - "**Key Points:**\n", - "\n", - "* **Economic Concerns:** Kennedy highlights the country's economic troubles, including a recession, high unemployment, and falling farm income. He proposes measures to address these issues, such as increased unemployment compensation, minimum wage increases, and tax incentives for investment.\n", - "* **Balance of Payments Deficit:** Kennedy acknowledges the growing deficit but assures the nation that the dollar remains strong and pledges not to devalue it. He outlines steps to attract foreign investment, promote exports, and curb spending abroad.\n", - "* **Unfinished Domestic Tasks:** Kennedy addresses several domestic issues needing attention, including urban decay, education, healthcare, and juvenile crime. He proposes programs for housing, education funding, and healthcare for the elderly.\n", - "* **Foreign Policy and the Cold War:** Kennedy outlines the global challenges posed by the Cold War and the threat of communist expansion, particularly in Asia, Africa, and Latin America. He emphasizes the need to strengthen military capabilities and alliances while seeking peaceful competition with the Soviet Union and China. \n", - "* **Alliance for Progress:** Kennedy proposes a new program to assist the economic and social development of Latin American countries, aiming for a \"free and prosperous Latin America.\"\n", - "* **National Peace Corps:** Kennedy advocates for the creation of a National Peace Corps to utilize the skills of dedicated citizens to assist developing nations.\n", - "* **Focus on Science and Diplomacy:** Kennedy calls for increased emphasis on science and diplomacy, proposing collaborations with other nations, including the Soviet Union, on projects like weather prediction, communication satellites, and space exploration.\n", - "* **Strengthening the United Nations:** Kennedy emphasizes the importance of supporting and strengthening the United Nations as an instrument for peace and international cooperation.\n", - "* **Call to Action:** Kennedy concludes by urging unity, dedication, and perseverance from all citizens to overcome the challenges facing the nation. He emphasizes the responsibility of the United States to lead the fight for freedom and world order. \n", - "\n", - "**Overall Tone:** The address conveys a sense of urgency and determination while remaining optimistic about the nation's ability to overcome its challenges. Kennedy's call to action emphasizes shared responsibility and the need for collective effort in facing both domestic and international difficulties. \n", - "\n" - ] - } - ], - "source": [ - "prompt = \"Listen carefully to the following audio file. Provide a brief summary.\"\n", - "model = genai.GenerativeModel('models/gemini-1.5-pro-latest')\n", - "response = model.generate_content([prompt, your_file])\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "WVFm2MOLWJO5" - }, - "source": [ - "## Count audio tokens\n", - "\n", - "You can count the number of tokens in your audio file like this." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "O0xk2-6CWLfC" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "total_tokens: 78330" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.count_tokens([your_file])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zxxIUR8SV6dK" - }, - "source": [ - "## Learning more" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zudj6gxEWR2Q" - }, - "source": [ - "* Learn more about the [File API](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb) with the quickstart.\n", - "\n", - "* Learn more about prompting with [media files](https://ai.google.dev/tutorials/prompting_with_media) in the docs, including the supported formats and maximum length for audio files." - ] - } - ], - "metadata": { - "colab": { - "name": "Audio.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] }, - "nbformat": 4, - "nbformat_minor": 0 + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0etRtS83RcWS" + }, + "source": [ + "# Gemini API: Audio Quickstart\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "r1IzNLho-NqV" + }, + "source": [ + "This notebook provides an example of how to prompt Gemini 1.5 Pro using an audio file. In this case, you'll use a [sound recording](https://www.jfklibrary.org/asset-viewer/archives/jfkwha-006) of President John F. Kennedy’s 1961 State of the Union address." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Y6eH_Aq_NyNi", + "tags": [] + }, + "outputs": [], + "source": [ + "!pip install -q -U google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "LSe1pMEpR2L2", + "tags": [] + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "TXiv-NeZR5WA" + }, + "source": [ + "## Configure your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "dm-iaNMGPdid" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2YoxMrCdR7hf" + }, + "source": [ + "## Upload an audio file with the File API\n", + "\n", + "To use an audio file in your prompt, you must first upload it using the [File API](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb).\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "OHvNLws4RRjx", + "tags": [] + }, + "outputs": [], + "source": [ + "URL = \"https://storage.googleapis.com/generativeai-downloads/data/State_of_the_Union_Address_30_January_1961.mp3\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Cxq31LDwSFH6", + "tags": [] + }, + "outputs": [], + "source": [ + "!wget -q $URL -O sample.mp3" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "MAObE0BpaAwG", + "tags": [] + }, + "outputs": [], + "source": [ + "your_file = genai.upload_file(path='sample.mp3')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "m01XDoo4UQvN" + }, + "source": [ + "## Use the file in your prompt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "YmISEsqpafRb", + "tags": [] + }, + "outputs": [], + "source": [ + "prompt = \"Listen carefully to the following audio file. Provide a brief summary.\"\n", + "model = genai.GenerativeModel('models/gemini-1.5-flash-latest')\n", + "response = model.generate_content([prompt, your_file])\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "WVFm2MOLWJO5" + }, + "source": [ + "## Count audio tokens\n", + "\n", + "You can count the number of tokens in your audio file like this." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "O0xk2-6CWLfC", + "tags": [] + }, + "outputs": [], + "source": [ + "model.count_tokens([your_file])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zxxIUR8SV6dK" + }, + "source": [ + "## Learning more" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zudj6gxEWR2Q" + }, + "source": [ + "* Learn more about the [File API](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb) with the quickstart.\n", + "\n", + "* Learn more about prompting with [media files](https://ai.google.dev/tutorials/prompting_with_media) in the docs, including the supported formats and maximum length for audio files." + ] + } + ], + "metadata": { + "colab": { + "name": "Audio.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/Authentication.ipynb b/quickstarts/Authentication.ipynb index 8926e37eb..190d494b6 100644 --- a/quickstarts/Authentication.ipynb +++ b/quickstarts/Authentication.ipynb @@ -1,247 +1,267 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: Authentication Quickstart" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lEXQ3OwKIa-O" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "df1767a3d1cc" - }, - "source": [ - "The Gemini API uses API keys for authentication. This notebook walks you through creating an API key, and using it with the Python SDK or a command line tool like `curl`." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "mhFKmRmxi5B-" - }, - "source": [ - "## Create an API key\n", - "\n", - "You can [create](https://aistudio.google.com/app/apikey) your API key using Google AI Studio with a single click. \n", - "\n", - "Remember to treat your API key like a password. Do not accidentally save it in a notebook or source file you later commit to GitHub. This notebook shows you two ways you can securely store your API key.\n", - "\n", - "* If you are using Google Colab, we recommend you store your key in Colab Secrets.\n", - "\n", - "* If you are using a different development environment (or calling the Gemini API through `cURL` in your terminal), we recommend you store your key in an environment variable.\n", - "\n", - "Let's start with Colab Secrets." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dEoigYI9Jw_K" - }, - "source": [ - "## Add your key to Colab Secrets\n", - "\n", - "Add your API key to the Colab Secrets manager to securely store it.\n", - "\n", - "1. Open your Google Colab notebook and click on the πŸ”‘ **Secrets** tab in the left panel.\n", - " \n", - " \"The\n", - "\n", - "2. Create a new secret with the name `GOOGLE_API_KEY`.\n", - "3. Copy/paste your API key into the `Value` input box of `GOOGLE_API_KEY`.\n", - "4. Toggle the button on the left to allow notebook access to the secret.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "jRY1eioF4gUB" - }, - "source": [ - "## Install the Python SDK" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "xuiLSV7amy3P" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3dw8ygh74mVc" - }, - "source": [ - "## Configure the SDK with your API key\n", - "\n", - "You'll call `genai.configure` with your API key, but instead of pasting your key into the notebook, you'll read it from Colab Secrets." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "DTl-qZp34sht" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai\n", - "from google.colab import userdata\n", - "\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tr7oAO6-nMsE" - }, - "source": [ - "And that's it! Now you're ready to call the Gemini API." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "n6sXnWrJoKoo" - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel('gemini-1.0-pro')\n", - "response = model.generate_content(\"Please give me python code to sort a list.\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "BTdQtZri1Brs" - }, - "source": [ - "## Store your key in an environment variable" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "gZDX51Y27pN4" - }, - "source": [ - "If you are using a different development environment (or calling the Gemini API through `cURL` in your terminal), we recommend you store your key in an environment variable.\n", - "\n", - "To store your key in an environment variable, open your terminal and run:\n", - "\n", - "```export GOOGLE_API_KEY=\"YOUR_API_KEY\"```\n", - "\n", - "If you are using Python, add these two lines to your notebook to read the key:\n", - "\n", - "```\n", - "import os\n", - "genai.configure(api_key=os.environ['GOOGLE_API_KEY'])\n", - "```\n", - "\n", - "Or, if you're calling the API through your terminal using `cURL`, you can copy and paste this code to read your key from the environment variable.\n", - "\n", - "```\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -X POST \\\n", - " -d '{\n", - " \"contents\": [{\n", - " \"parts\":[{\n", - " \"text\": \"Please give me Python code to sort a list.\"}]}]}'\n", - "```\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "CAOKOcax1xZY" - }, - "source": [ - "## Learning more\n", - "\n", - "The Gemini API uses API keys for most types of authentication, and that’s all you need to get started. We use OAuth for more advanced authentication when tuning models. You can learn more about that in the [OAuth quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication_with_OAuth.ipynb)." - ] - } - ], - "metadata": { - "colab": { - "name": "Authentication.ipynb", - "toc_visible": true - }, - "google": { - "image_path": "/site-assets/images/share.png", - "keywords": [ - "examples", - "googleai", - "samplecode", - "python", - "embed", - "function" - ] - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: Authentication Quickstart" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lEXQ3OwKIa-O" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "df1767a3d1cc" + }, + "source": [ + "The Gemini API uses API keys for authentication. This notebook walks you through creating an API key, and using it with the Python SDK or a command line tool like `curl`." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "mhFKmRmxi5B-" + }, + "source": [ + "## Create an API key\n", + "\n", + "You can [create](https://aistudio.google.com/app/apikey) your API key using Google AI Studio with a single click. \n", + "\n", + "Remember to treat your API key like a password. Do not accidentally save it in a notebook or source file you later commit to GitHub. This notebook shows you two ways you can securely store your API key.\n", + "\n", + "* If you are using Google Colab, we recommend you store your key in Colab Secrets.\n", + "\n", + "* If you are using a different development environment (or calling the Gemini API through `cURL` in your terminal), we recommend you store your key in an environment variable.\n", + "\n", + "Let's start with Colab Secrets." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dEoigYI9Jw_K" + }, + "source": [ + "## Add your key to Colab Secrets\n", + "\n", + "Add your API key to the Colab Secrets manager to securely store it.\n", + "\n", + "1. Open your Google Colab notebook and click on the πŸ”‘ **Secrets** tab in the left panel.\n", + " \n", + " \"The\n", + "\n", + "2. Create a new secret with the name `GOOGLE_API_KEY`.\n", + "3. Copy/paste your API key into the `Value` input box of `GOOGLE_API_KEY`.\n", + "4. Toggle the button on the left to allow notebook access to the secret.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "jRY1eioF4gUB" + }, + "source": [ + "## Install the Python SDK" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "xuiLSV7amy3P" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3dw8ygh74mVc" + }, + "source": [ + "## Configure the SDK with your API key\n", + "\n", + "You'll call `genai.configure` with your API key, but instead of pasting your key into the notebook, you'll read it from Colab Secrets." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "DTl-qZp34sht" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai\n", + "from google.colab import userdata\n", + "\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tr7oAO6-nMsE" + }, + "source": [ + "And that's it! Now you're ready to call the Gemini API." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "n6sXnWrJoKoo", + "tags": [] + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('models/gemini-1.5-flash-latest')\n", + "response = model.generate_content(\"Please give me python code to sort a list.\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "BTdQtZri1Brs" + }, + "source": [ + "## Store your key in an environment variable" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gZDX51Y27pN4" + }, + "source": [ + "If you are using a different development environment (or calling the Gemini API through `cURL` in your terminal), we recommend you store your key in an environment variable.\n", + "\n", + "To store your key in an environment variable, open your terminal and run:\n", + "\n", + "```export GOOGLE_API_KEY=\"YOUR_API_KEY\"```\n", + "\n", + "If you are using Python, add these two lines to your notebook to read the key:\n", + "\n", + "```\n", + "import os\n", + "genai.configure(api_key=os.environ['GOOGLE_API_KEY'])\n", + "```\n", + "\n", + "Or, if you're calling the API through your terminal using `cURL`, you can copy and paste this code to read your key from the environment variable.\n", + "\n", + "```\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -X POST \\\n", + " -d '{\n", + " \"contents\": [{\n", + " \"parts\":[{\n", + " \"text\": \"Please give me Python code to sort a list.\"}]}]}'\n", + "```\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "CAOKOcax1xZY" + }, + "source": [ + "## Learning more\n", + "\n", + "The Gemini API uses API keys for most types of authentication, and that’s all you need to get started. We use OAuth for more advanced authentication when tuning models. You can learn more about that in the [OAuth quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication_with_OAuth.ipynb)." + ] + } + ], + "metadata": { + "colab": { + "name": "Authentication.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "google": { + "image_path": "/site-assets/images/share.png", + "keywords": [ + "examples", + "googleai", + "samplecode", + "python", + "embed", + "function" + ] + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/Authentication_with_OAuth.ipynb b/quickstarts/Authentication_with_OAuth.ipynb index a1ffd78fb..6789d7694 100644 --- a/quickstarts/Authentication_with_OAuth.ipynb +++ b/quickstarts/Authentication_with_OAuth.ipynb @@ -1,473 +1,490 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: OAuth Quickstart" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lEXQ3OwKIa-O" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "df1767a3d1cc" - }, - "source": [ - "Some parts of the Gemini API like model tuning and semantic retrieval use OAuth for authentication.\n", - "\n", - "If you are a beginner, you should start by using [API keys](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb), and come back to this OAuth guide only when you need it for these features.\n", - "\n", - "To help you get started with OAuth, this notebook shows a simplified approach that is appropriate\n", - "for a testing environment.\n", - "\n", - "For a production environment, learn\n", - "about [authentication and authorization](https://developers.google.com/workspace/guides/auth-overview) before [choosing the access credentials](https://developers.google.com/workspace/guides/create-credentials#choose_the_access_credential_that_is_right_for_you) that are appropriate for your app." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "GUZ1vR5VHhkH" - }, - "source": [ - "## Prerequisites\n", - "\n", - "To run this quickstart, you need:\n", - "\n", - "* The [Google Cloud CLI](https://cloud.google.com/sdk/docs/install-sdk) installed on your local machine.\n", - "* [A Google Cloud project](https://developers.google.com/workspace/guides/create-project).\n", - "\n", - "If you created an API key in Google AI Studio, a Google Cloud project was made for you. Go to [Google AI Studio](https://aistudio.google.com/app/apikey) and note the Google Cloud project name to use that project." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "6F4DgkaWH8HW" - }, - "source": [ - "## Set up your Cloud project\n", - "\n", - "To complete this quickstart, you first need to setup your Cloud project.\n", - "\n", - "### 1. Enable the API\n", - "\n", - "Before using Google APIs, you need to turn them on in a Google Cloud project.\n", - "\n", - "* In the Google Cloud console, [enable](https://console.cloud.google.com/flows/enableapi?apiid=generativelanguage.googleapis.com) the Google Generative Language API. If you created an API Key in AI Studio, this was done for you.
\n", - "\n", - "### 2. Configure the OAuth consent screen\n", - "\n", - "Next configure the project's OAuth consent screen and add yourself as a test user. If you've already completed this step for your Cloud project, skip to the next section.\n", - "\n", - "1. In the Google Cloud console, go to the [OAuth consent screen](https://console.cloud.google.com/apis/credentials/consent), this can be found under **Menu** > **APIs & Services** > **OAuth\n", - " consent screen**.\n", - "\n", - "2. Select the user type **External** for your app, then click **Create**.\n", - "\n", - "3. Complete the app registration form (you can leave most fields blank), then click **Save and Continue**.\n", - "\n", - "4. For now, you can skip adding scopes and click **Save and Continue**. In the\n", - " future, when you create an app for use outside of your Google Workspace\n", - " organization, you must add and verify the authorization scopes that your\n", - " app requires.\n", - "\n", - "5. Add test users:\n", - " 1. Under **Test users**, click **Add users**.\n", - " 2. Enter your email address and any other authorized test users, then\n", - " click **Save and Continue**.\n", - "\n", - "6. Review your app registration summary. To make changes, click **Edit**. If\n", - " the app registration looks OK, click **Back to Dashboard**.\n", - "\n", - "### 3. Authorize credentials for a desktop application\n", - "\n", - "To authenticate as an end user and access user data in your app, you need to\n", - "create one or more OAuth 2.0 Client IDs. A client ID is used to identify a\n", - "single app to Google's OAuth servers. If your app runs on multiple platforms,\n", - "you must create a separate client ID for each platform.\n", - "\n", - "1. In the Google Cloud console, go to [Credentials](https://console.cloud.google.com/apis/credentials/consent), this can be found under **Menu** > **APIs & Services** >\n", - " **Credentials**.\n", - "\n", - "2. Click **Create Credentials** > **OAuth client ID**.\n", - "3. Click **Application type** > **Desktop app**.\n", - "4. In the **Name** field, type a name for the credential. This name is only\n", - " shown in the Google Cloud console.\n", - "5. Click **Create**. The OAuth client created screen appears, showing your new\n", - " Client ID and Client secret.\n", - "6. Click **OK**. The newly created credential appears under **OAuth 2.0 Client\n", - " IDs.**\n", - "7. Click the download button to save the JSON file. It will be saved as\n", - " `client_secret_.json`.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kfSJNy1sS9NO" - }, - "source": [ - "## Set up application default credentials\n", - "\n", - "In this quickstart you will use [application default credentials](https://cloud.google.com/docs/authentication/application-default-credentials) to authenticate." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dEoigYI9Jw_K" - }, - "source": [ - "### Add client secret to Colab secrets\n", - "\n", - "If you need to use OAuth with the Gemini API in Google Colab frequently, it is easiest to add the contents of your `client_secret.json` file into Colab's Secrets manager.\n", - "\n", - "1. Open your Google Colab notebook and click on the πŸ”‘ **Secrets** tab in the left panel.\n", - "2. Create a new secret with the name `CLIENT_SECRET`.\n", - "3. Open your `client_secret.json` file in a text editor and copy/paste the content into the `Value` input box of `CLIENT_SECRET`.\n", - "4. Toggle the button on the left to allow notebook access to the secret.\n", - "\n", - "Now you can programmatically create the file instead of uploading it every time. The client secret is also available in all your Google Colab notebooks after you allow access." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "uRg4GMDQLPKl" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "413" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from google.colab import userdata\n", - "import pathlib\n", - "pathlib.Path('client_secret.json').write_text(userdata.get('CLIENT_SECRET'))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "RQrh0ol3Oldc" - }, - "source": [ - "### Set the application default credentials\n", - "\n", - "To convert the `client_secret.json` file into usable credentials, pass its location the `gcloud auth application-default login` command's `--client-id-file` argument.\n", - "\n", - "The simplified project setup in this tutorial triggers a **Google hasn't verified this app** dialog. This is normal, choose **Continue**.\n", - "\n", - "You will need to do this step once for every new Google Colab notebook or runtime.\n", - "\n", - "**Note**: Carefully follow the instructions the following command prints (don't just click the link). Also make sure your local `gcloud --version` is the [latest](https://cloud.google.com/sdk/docs/release-notes) to match the version pre-installed in Google Colab.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "j0dBkV0QOonL" - }, - "outputs": [], - "source": [ - "!gcloud auth application-default login \\\n", - " --no-browser --client-id-file client_secret.json \\\n", - " --scopes https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/generative-language.tuning,https://www.googleapis.com/auth/generative-language.retriever\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "TWTBztxTRYb5" - }, - "source": [ - "The specific `scopes` you need depends on the API you are using. For example, looking at the API reference for [`tunedModels.create`](https://ai.google.dev/api/rest/v1beta/tunedModels/create#authorization-scopes), you will see:\n", - "\n", - "> Requires one of the following OAuth scopes:\n", - ">\n", - "> * `https://www.googleapis.com/auth/generative-language.tuning`\n", - "\n", - "This sample asks for all the scopes for tuning and semantic retrieval, but best practice is to use the smallest set of scopes for security and user confidence." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "FFPBKLapSCkM" - }, - "source": [ - "## Using the Python SDK with OAuth\n", - "\n", - "The Python SDK will automatically find and use application default credentials." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9OEoeosRTv-5" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[?25l \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/137.4 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r", - "\u001b[2K \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91mβ•Έ\u001b[0m\u001b[90m━\u001b[0m \u001b[32m133.1/137.4 kB\u001b[0m \u001b[31m3.8 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r", - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m137.4/137.4 kB\u001b[0m \u001b[31m2.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", - "\u001b[?25h" - ] - } - ], - "source": [ - "!pip install -U -q google-generativeai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "r8GgGmTrUCR2" - }, - "source": [ - "Let's do a quick test. Note that you did not set an API key using `genai.configure()`!" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "TS9l5igubpHO" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai\n", - "\n", - "print('Available base models:', [m.name for m in genai.list_models()])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dzSRvbxnUmLo" - }, - "source": [ - "# Appendix" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "arP-ISIBUrdv" - }, - "source": [ - "## Making authenticated REST calls from Colab\n", - "\n", - "In general, you should use the Python SDK to interact with the Gemini API when possible. This example shows how to make OAuth authenticated REST calls from Python for debugging or testing purposes. It assumes you have already set application default credentials from the Quickstart." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "6V_vD8A2Wm28" - }, - "outputs": [], - "source": [ - "import requests\n", - "\n", - "access_token = !gcloud auth application-default print-access-token\n", - "\n", - "headers = {\n", - " 'Content-Type': 'application/json',\n", - " 'Authorization': f'Bearer {access_token[0]}',\n", - "}\n", - "\n", - "response = requests.get('https://generativelanguage.googleapis.com/v1/models', headers=headers)\n", - "response_json = response.json()\n", - "\n", - "# All the model names\n", - "for model in response_json['models']:\n", - " print(model['name'])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lisiHaB8Wwi9" - }, - "source": [ - "### Share a tuned model\n", - "\n", - "Some beta API features may not be supported by the Python SDK yet. This example shows how to make a REST call to add a permission to a tuned model from Python." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ijMDsUj5o6RL" - }, - "outputs": [], - "source": [ - "import requests\n", - "\n", - "model_name = '' # @param {type:\"string\"}\n", - "emailAddress = '' # @param {type:\"string\"}\n", - "\n", - "\n", - "access_token = !gcloud auth application-default print-access-token\n", - "\n", - "headers = {\n", - " 'Content-Type': 'application/json',\n", - " 'Authorization': f'Bearer {access_token[0]}',\n", - "}\n", - "\n", - "body = {\n", - " 'granteeType': 'USER', # Or 'GROUP' or 'EVERYONE' https://ai.google.dev/api/rest/v1beta/tunedModels.permissions\n", - " 'emailAddress': emailAddress, # Optional if 'granteeType': 'EVERYONE'\n", - " 'role': 'READER'\n", - "}\n", - "\n", - "response = requests.post(f'https://generativelanguage.googleapis.com/v1beta/tunedModels/{model_name}/permissions', json=body, headers=headers)\n", - "print(response.json())\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "HnKP_dX_Wnr7" - }, - "source": [ - "## Use a service account to authenticate\n", - "\n", - "Google Cloud [service accounts](https://cloud.google.com/iam/docs/service-account-overview) are accounts that do not represent a human user. They provide a way to manage authentication and authorization when a human is not directly involved, such as your application calling the Gemini API to fulfill a user request, but not authenticated as the user. A simple way to use service accounts to authenticate with the Gemini API is to use a [service account key](https://cloud.google.com/docs/authentication/provide-credentials-adc#local-key).\n", - "\n", - "This guide briefly covers how to use service account keys in Google Colab.\n", - "\n", - "**Important:** Service account keys can be a security risk! For more information, see [best practices for managing service account keys](https://cloud.google.com/iam/docs/best-practices-for-managing-service-account-keys).\n", - "\n", - "### 1. Create a service account\n", - "\n", - "Follow the instructions to [create a service account](https://cloud.google.com/iam/docs/service-accounts-create#creating). The **Console** instructions are easiest if you are doing this manually.\n", - "\n", - "### 2. Create a service account key\n", - "\n", - "Follow the instructions to [create a service account key]( https://cloud.google.com/iam/docs/keys-create-delete#creating). Note the name of the downloaded key.\n", - "\n", - "### 3. Add the service account key to Colab\n", - "\n", - "1. Open your Google Colab notebook and click on the πŸ”‘ **Secrets** tab in the left panel.\n", - "2. Create a new secret with the name `SERVICE_ACCOUNT_KEY`.\n", - "3. Open your service account key file in a text editor and copy/paste the content into the `Value` input box of `SERVICE_ACCOUNT_KEY`.\n", - "4. Toggle the button on the left to allow notebook access to the secret.\n", - "\n", - "### 4. Authenticate with the Python SDK by service account key" - ] - }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: OAuth Quickstart" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lEXQ3OwKIa-O" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "df1767a3d1cc" + }, + "source": [ + "Some parts of the Gemini API like model tuning and semantic retrieval use OAuth for authentication.\n", + "\n", + "If you are a beginner, you should start by using [API keys](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb), and come back to this OAuth guide only when you need it for these features.\n", + "\n", + "To help you get started with OAuth, this notebook shows a simplified approach that is appropriate\n", + "for a testing environment.\n", + "\n", + "For a production environment, learn\n", + "about [authentication and authorization](https://developers.google.com/workspace/guides/auth-overview) before [choosing the access credentials](https://developers.google.com/workspace/guides/create-credentials#choose_the_access_credential_that_is_right_for_you) that are appropriate for your app." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "GUZ1vR5VHhkH" + }, + "source": [ + "## Prerequisites\n", + "\n", + "To run this quickstart, you need:\n", + "\n", + "* The [Google Cloud CLI](https://cloud.google.com/sdk/docs/install-sdk) installed on your local machine.\n", + "* [A Google Cloud project](https://developers.google.com/workspace/guides/create-project).\n", + "\n", + "If you created an API key in Google AI Studio, a Google Cloud project was made for you. Go to [Google AI Studio](https://aistudio.google.com/app/apikey) and note the Google Cloud project name to use that project." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6F4DgkaWH8HW" + }, + "source": [ + "## Set up your Cloud project\n", + "\n", + "To complete this quickstart, you first need to setup your Cloud project.\n", + "\n", + "### 1. Enable the API\n", + "\n", + "Before using Google APIs, you need to turn them on in a Google Cloud project.\n", + "\n", + "* In the Google Cloud console, [enable](https://console.cloud.google.com/flows/enableapi?apiid=generativelanguage.googleapis.com) the Google Generative Language API. If you created an API Key in AI Studio, this was done for you.
\n", + "\n", + "### 2. Configure the OAuth consent screen\n", + "\n", + "Next configure the project's OAuth consent screen and add yourself as a test user. If you've already completed this step for your Cloud project, skip to the next section.\n", + "\n", + "1. In the Google Cloud console, go to the [OAuth consent screen](https://console.cloud.google.com/apis/credentials/consent), this can be found under **Menu** > **APIs & Services** > **OAuth\n", + " consent screen**.\n", + "\n", + "2. Select the user type **External** for your app, then click **Create**.\n", + "\n", + "3. Complete the app registration form (you can leave most fields blank), then click **Save and Continue**.\n", + "\n", + "4. For now, you can skip adding scopes and click **Save and Continue**. In the\n", + " future, when you create an app for use outside of your Google Workspace\n", + " organization, you must add and verify the authorization scopes that your\n", + " app requires.\n", + "\n", + "5. Add test users:\n", + " 1. Under **Test users**, click **Add users**.\n", + " 2. Enter your email address and any other authorized test users, then\n", + " click **Save and Continue**.\n", + "\n", + "6. Review your app registration summary. To make changes, click **Edit**. If\n", + " the app registration looks OK, click **Back to Dashboard**.\n", + "\n", + "### 3. Authorize credentials for a desktop application\n", + "\n", + "To authenticate as an end user and access user data in your app, you need to\n", + "create one or more OAuth 2.0 Client IDs. A client ID is used to identify a\n", + "single app to Google's OAuth servers. If your app runs on multiple platforms,\n", + "you must create a separate client ID for each platform.\n", + "\n", + "1. In the Google Cloud console, go to [Credentials](https://console.cloud.google.com/apis/credentials/consent), this can be found under **Menu** > **APIs & Services** >\n", + " **Credentials**.\n", + "\n", + "2. Click **Create Credentials** > **OAuth client ID**.\n", + "3. Click **Application type** > **Desktop app**.\n", + "4. In the **Name** field, type a name for the credential. This name is only\n", + " shown in the Google Cloud console.\n", + "5. Click **Create**. The OAuth client created screen appears, showing your new\n", + " Client ID and Client secret.\n", + "6. Click **OK**. The newly created credential appears under **OAuth 2.0 Client\n", + " IDs.**\n", + "7. Click the download button to save the JSON file. It will be saved as\n", + " `client_secret_.json`.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kfSJNy1sS9NO" + }, + "source": [ + "## Set up application default credentials\n", + "\n", + "In this quickstart you will use [application default credentials](https://cloud.google.com/docs/authentication/application-default-credentials) to authenticate." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dEoigYI9Jw_K" + }, + "source": [ + "### Add client secret to Colab secrets\n", + "\n", + "If you need to use OAuth with the Gemini API in Google Colab frequently, it is easiest to add the contents of your `client_secret.json` file into Colab's Secrets manager.\n", + "\n", + "1. Open your Google Colab notebook and click on the πŸ”‘ **Secrets** tab in the left panel.\n", + "2. Create a new secret with the name `CLIENT_SECRET`.\n", + "3. Open your `client_secret.json` file in a text editor and copy/paste the content into the `Value` input box of `CLIENT_SECRET`.\n", + "4. Toggle the button on the left to allow notebook access to the secret.\n", + "\n", + "Now you can programmatically create the file instead of uploading it every time. The client secret is also available in all your Google Colab notebooks after you allow access." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "uRg4GMDQLPKl" + }, + "outputs": [ { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "f62ztB6mkRk5" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai\n", - "import pathlib\n", - "from google.colab import userdata\n", - "from google.oauth2 import service_account\n", - "\n", - "pathlib.Path('service_account_key.json').write_text(userdata.get('SERVICE_ACCOUNT_KEY'))\n", - "\n", - "credentials = service_account.Credentials.from_service_account_file('service_account_key.json')\n", - "\n", - "# Adjust scopes as needed\n", - "scoped_credentials = credentials.with_scopes(\n", - " ['https://www.googleapis.com/auth/cloud-platform', 'https://www.googleapis.com/auth/generative-language.retriever'])\n", - "\n", - "genai.configure(credentials=scoped_credentials)\n", - "\n", - "print('Available base models:', [m.name for m in genai.list_models()])" + "data": { + "text/plain": [ + "413" ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" } - ], - "metadata": { - "colab": { - "name": "Authentication_with_OAuth.ipynb", - "toc_visible": true - }, - "google": { - "image_path": "/site-assets/images/share.png", - "keywords": [ - "examples", - "googleai", - "samplecode", - "python", - "embed", - "function" - ] - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" + ], + "source": [ + "from google.colab import userdata\n", + "import pathlib\n", + "pathlib.Path('client_secret.json').write_text(userdata.get('CLIENT_SECRET'))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "RQrh0ol3Oldc" + }, + "source": [ + "### Set the application default credentials\n", + "\n", + "To convert the `client_secret.json` file into usable credentials, pass its location the `gcloud auth application-default login` command's `--client-id-file` argument.\n", + "\n", + "The simplified project setup in this tutorial triggers a **Google hasn't verified this app** dialog. This is normal, choose **Continue**.\n", + "\n", + "You will need to do this step once for every new Google Colab notebook or runtime.\n", + "\n", + "**Note**: Carefully follow the instructions the following command prints (don't just click the link). Also make sure your local `gcloud --version` is the [latest](https://cloud.google.com/sdk/docs/release-notes) to match the version pre-installed in Google Colab.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "j0dBkV0QOonL" + }, + "outputs": [], + "source": [ + "!gcloud auth application-default login \\\n", + " --no-browser --client-id-file client_secret.json \\\n", + " --scopes https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/generative-language.tuning,https://www.googleapis.com/auth/generative-language.retriever\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "TWTBztxTRYb5" + }, + "source": [ + "The specific `scopes` you need depends on the API you are using. For example, looking at the API reference for [`tunedModels.create`](https://ai.google.dev/api/rest/v1beta/tunedModels/create#authorization-scopes), you will see:\n", + "\n", + "> Requires one of the following OAuth scopes:\n", + ">\n", + "> * `https://www.googleapis.com/auth/generative-language.tuning`\n", + "\n", + "This sample asks for all the scopes for tuning and semantic retrieval, but best practice is to use the smallest set of scopes for security and user confidence." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FFPBKLapSCkM" + }, + "source": [ + "## Using the Python SDK with OAuth\n", + "\n", + "The Python SDK will automatically find and use application default credentials." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9OEoeosRTv-5" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m137.4/137.4 kB\u001b[0m \u001b[31m2.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n", + "\u001b[?25h" + ] } + ], + "source": [ + "!pip install -U -q google-generativeai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "r8GgGmTrUCR2" + }, + "source": [ + "Let's do a quick test. Note that you did not set an API key using `genai.configure()`!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TS9l5igubpHO" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai\n", + "\n", + "print('Available base models:', [m.name for m in genai.list_models()])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dzSRvbxnUmLo" + }, + "source": [ + "# Appendix" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "arP-ISIBUrdv" + }, + "source": [ + "## Making authenticated REST calls from Colab\n", + "\n", + "In general, you should use the Python SDK to interact with the Gemini API when possible. This example shows how to make OAuth authenticated REST calls from Python for debugging or testing purposes. It assumes you have already set application default credentials from the Quickstart." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "6V_vD8A2Wm28" + }, + "outputs": [], + "source": [ + "import requests\n", + "\n", + "access_token = !gcloud auth application-default print-access-token\n", + "\n", + "headers = {\n", + " 'Content-Type': 'application/json',\n", + " 'Authorization': f'Bearer {access_token[0]}',\n", + "}\n", + "\n", + "response = requests.get('https://generativelanguage.googleapis.com/v1/models', headers=headers)\n", + "response_json = response.json()\n", + "\n", + "# All the model names\n", + "for model in response_json['models']:\n", + " print(model['name'])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lisiHaB8Wwi9" + }, + "source": [ + "### Share a tuned model\n", + "\n", + "Some beta API features may not be supported by the Python SDK yet. This example shows how to make a REST call to add a permission to a tuned model from Python." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ijMDsUj5o6RL" + }, + "outputs": [], + "source": [ + "import requests\n", + "\n", + "model_name = '' # @param {type:\"string\"}\n", + "emailAddress = '' # @param {type:\"string\"}\n", + "\n", + "\n", + "access_token = !gcloud auth application-default print-access-token\n", + "\n", + "headers = {\n", + " 'Content-Type': 'application/json',\n", + " 'Authorization': f'Bearer {access_token[0]}',\n", + "}\n", + "\n", + "body = {\n", + " 'granteeType': 'USER', # Or 'GROUP' or 'EVERYONE' https://ai.google.dev/api/rest/v1beta/tunedModels.permissions\n", + " 'emailAddress': emailAddress, # Optional if 'granteeType': 'EVERYONE'\n", + " 'role': 'READER'\n", + "}\n", + "\n", + "response = requests.post(f'https://generativelanguage.googleapis.com/v1beta/tunedModels/{model_name}/permissions', json=body, headers=headers)\n", + "print(response.json())\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HnKP_dX_Wnr7" + }, + "source": [ + "## Use a service account to authenticate\n", + "\n", + "Google Cloud [service accounts](https://cloud.google.com/iam/docs/service-account-overview) are accounts that do not represent a human user. They provide a way to manage authentication and authorization when a human is not directly involved, such as your application calling the Gemini API to fulfill a user request, but not authenticated as the user. A simple way to use service accounts to authenticate with the Gemini API is to use a [service account key](https://cloud.google.com/docs/authentication/provide-credentials-adc#local-key).\n", + "\n", + "This guide briefly covers how to use service account keys in Google Colab.\n", + "\n", + "**Important:** Service account keys can be a security risk! For more information, see [best practices for managing service account keys](https://cloud.google.com/iam/docs/best-practices-for-managing-service-account-keys).\n", + "\n", + "### 1. Create a service account\n", + "\n", + "Follow the instructions to [create a service account](https://cloud.google.com/iam/docs/service-accounts-create#creating). The **Console** instructions are easiest if you are doing this manually.\n", + "\n", + "### 2. Create a service account key\n", + "\n", + "Follow the instructions to [create a service account key]( https://cloud.google.com/iam/docs/keys-create-delete#creating). Note the name of the downloaded key.\n", + "\n", + "### 3. Add the service account key to Colab\n", + "\n", + "1. Open your Google Colab notebook and click on the πŸ”‘ **Secrets** tab in the left panel.\n", + "2. Create a new secret with the name `SERVICE_ACCOUNT_KEY`.\n", + "3. Open your service account key file in a text editor and copy/paste the content into the `Value` input box of `SERVICE_ACCOUNT_KEY`.\n", + "4. Toggle the button on the left to allow notebook access to the secret.\n", + "\n", + "### 4. Authenticate with the Python SDK by service account key" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "f62ztB6mkRk5" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai\n", + "import pathlib\n", + "from google.colab import userdata\n", + "from google.oauth2 import service_account\n", + "\n", + "pathlib.Path('service_account_key.json').write_text(userdata.get('SERVICE_ACCOUNT_KEY'))\n", + "\n", + "credentials = service_account.Credentials.from_service_account_file('service_account_key.json')\n", + "\n", + "# Adjust scopes as needed\n", + "scoped_credentials = credentials.with_scopes(\n", + " ['https://www.googleapis.com/auth/cloud-platform', 'https://www.googleapis.com/auth/generative-language.retriever'])\n", + "\n", + "genai.configure(credentials=scoped_credentials)\n", + "\n", + "print('Available base models:', [m.name for m in genai.list_models()])" + ] + } + ], + "metadata": { + "colab": { + "name": "Authentication_with_OAuth.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "google": { + "image_path": "/site-assets/images/share.png", + "keywords": [ + "examples", + "googleai", + "samplecode", + "python", + "embed", + "function" + ] + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" }, - "nbformat": 4, - "nbformat_minor": 0 + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/Counting_Tokens.ipynb b/quickstarts/Counting_Tokens.ipynb index e9a87d8b1..361c75825 100644 --- a/quickstarts/Counting_Tokens.ipynb +++ b/quickstarts/Counting_Tokens.ipynb @@ -1,751 +1,560 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "YZXn1Salxl_w" - }, - "source": [ - "# Gemini API: All about tokens" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3FIB-JDtxgUE" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "CRzxdrjKLTJa" - }, - "source": [ - "An understanding of tokens is central to using the Gemini API. This guide will provide a interactive introduction to what tokens are and how they are used in the Gemini API.\n", - "\n", - "## About tokens\n", - "\n", - "LLMs break up their input and produce their output at a granularity that is smaller than a word, but larger than a single character or code-point.\n", - "\n", - "These **tokens** can be single characters, like `z`, or whole words, like `the`. Long words may be broken up into several tokens. The set of all tokens used by the model is called the vocabulary, and the process of breaking down text into tokens is called tokenization.\n", - "\n", - "For Gemini models, a token is equivalent to about 4 characters. **100 tokens are about 60-80 English words**.\n", - "\n", - "When billing is enabled, the price of a paid request is controlled by the [number of input and output tokens](https://ai.google.dev/pricing), so knowing how to count your tokens is important.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xwJ1lyGC_Ia4" - }, - "source": [ - "## Tokens in the Gemini API" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "id": "GBa_hMFneZKO" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "id": "OzsRfmWrxd_F" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IG_wSwTJ2wAP" - }, - "source": [ - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LyWgDDHr1yxd" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "GOOGLE_API_KEY = userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "etlFvMXP3Gb7" - }, - "source": [ - "### Context windows\n", - "\n", - "The models available through the Gemini API have context windows that are measured in tokens. These define how much input you can provide, and how much output the model can generate, and combined are referred to as the \"context window\". This information is available directly through [the API](https://ai.google.dev/api/rest/v1/models/get) and in the [models](https://ai.google.dev/models/gemini) documentation.\n", - "\n", - "In this example you can see the `gemini-1.0-pro-latest` model has an input of 30k tokens and an output of 2k tokens, giving a total context window of 32k tokens." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "id": "1QC23D2z3GLV" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "(30720, 2048)" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model_info = genai.get_model('models/gemini-1.0-pro-latest')\n", - "(model_info.input_token_limit, model_info.output_token_limit)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "auv5CPKQ_QWc" - }, - "source": [ - "You can also use a model like `gemini-1.5-pro-latest`, which has a 1M token context window.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kkh8v5QI4v5h" - }, - "source": [ - "## Counting tokens\n", - "\n", - "The API provides an endpoint for counting the number of tokens in a request: [`GenerativeModel.count_tokens`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#count_tokens). You pass the same arguments as you would to [`GenerativeModel.generate_content`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) and the service will return the number of tokens in that request." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "F0J8JPYbCGnv" - }, - "source": [ - "### Text tokens" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "id": "7jpoJFpX5Cu_" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "total_tokens: 10" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model = genai.GenerativeModel('models/gemini-1.0-pro-latest')\n", - "model.count_tokens(\"The quick brown fox jumps over the lazy dog.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0661517a2417" - }, - "source": [ - "When you call `GenerativeModel.generate_content` (or `ChatSession.send_message`) the response object has a `usage_metadata` attribute containing both the input and output token counts (`prompt_token_count` and `candidates_token_count`):" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "id": "71aa6568a670" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'This sentence is an example of a pangram, which is a sentence that contains all of the letters of the alphabet.'" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "response = model.generate_content(\"The quick brown fox jumps over the lazy dog.\")\n", - "response.text" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "id": "19cc48bad24b" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "prompt_token_count: 10\n", - "candidates_token_count: 24" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "response.usage_metadata" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "SQzJ7asV-HJB" - }, - "source": [ - "### Multi-turn tokens\n", - "\n", - "Multi-turn conversational (chat) objects work similarly." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "id": "eqUpyE_E95_w" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "total_tokens: 10" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "chat = model.start_chat(history=[{'role':'user', 'parts':'Hi my name is Bob'}, {'role':'model', 'parts':'Hi Bob!'}])\n", - "model.count_tokens(chat.history)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "id": "68ae99485a0c" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "ChatSession(\n", - " model=genai.GenerativeModel(\n", - " model_name='models/gemini-1.0-pro-latest',\n", - " generation_config={},\n", - " safety_settings={},\n", - " tools=None,\n", - " system_instruction=None,\n", - " ),\n", - " history=[glm.Content({'parts': [{'text': 'Hi my name is Bob'}], 'role': 'user'}), glm.Content({'parts': [{'text': 'Hi Bob!'}], 'role': 'model'})]\n", - ")" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "chat" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zMvjgRkVAvVN" - }, - "source": [ - "To understand how big your next conversational turn will be, you will need to append it to the history when you call `count_tokens`." - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "id": "pxVsykc5A5he" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "total_tokens: 17" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from google.generativeai.types.content_types import to_contents\n", - "model.count_tokens(chat.history + to_contents('What is the meaning of life?'))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZZYcaUXl-Sna" - }, - "source": [ - "### Multi-modal tokens\n", - "\n", - "All input to the API is tokenized, including images or other non-text modalities." - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": { - "id": "hsKfX8LYAdLv" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " % Total % Received % Xferd Average Speed Time Time Time Current\n", - " Dload Upload Total Spent Left Speed\n", - "100 221 100 221 0 0 1296 0 --:--:-- --:--:-- --:--:-- 1300\n", - "100 374k 100 374k 0 0 1650k 0 --:--:-- --:--:-- --:--:-- 1650k\n" - ] - } - ], - "source": [ - "!curl -L https://goo.gle/instrument-img -o organ.jpg" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": { - "id": "Jzwrahub-ez5" - }, - "outputs": [ - { - "data": { - "image/jpeg": 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- "text/plain": [ - "" - ] - }, - "metadata": { - "image/jpeg": { - "width": 300 - } - }, - "output_type": "display_data" - } - ], - "source": [ - "import PIL\n", - "from IPython.display import display, Image\n", - "\n", - "display(Image('organ.jpg', width=300))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "c4164419d70f" - }, - "source": [ - "#### Inline content\n", - "\n", - "Media objects can be sent to the API inline with the request:" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": { - "id": "Ledzam3H__Ob" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "total_tokens: 263" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "organ = PIL.Image.open('organ.jpg')\n", - "model.count_tokens(['Tell me about this instrument', organ])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "b3851a09ec17" - }, - "source": [ - "#### Files API\n", - "\n", - "The model sees identical tokens if you upload parts of the prompt through the files API instead:" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": { - "id": "f994c2dd6e05" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "total_tokens: 263" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "organ_upload = genai.upload_file('organ.jpg')\n", - "\n", - "model.count_tokens(['Tell me about this instrument', organ_upload])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "UXF0vpdG_H_Q" - }, - "source": [ - "### Media token counts\n", - "\n", - "Internally, images are a fixed size, so they consume a fixed number of tokens." - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": { - "id": "sPPfXRJiA3KV" - }, - "outputs": [], - "source": [ - "!curl -O \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\" --silent" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": { - "id": "jqG83Rko8UpG" - }, - "outputs": [ - { - "data": { - "image/jpeg": 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", - "text/plain": [ - "" - ] - }, - "metadata": { - "image/jpeg": { - "width": 300 - } - }, - "output_type": "display_data" - } - ], - "source": [ - "jetpack = PIL.Image.open('jetpack.jpg')\n", - "display(Image('jetpack.jpg', width=300))" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": { - "id": "hc0CBsl6_Tkk" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(2048, 1362)\n", - "total_tokens: 258\n", - "\n", - "(1068, 906)\n", - "total_tokens: 258\n", - "\n" - ] - } - ], - "source": [ - "print(organ.size)\n", - "print(model.count_tokens(organ))\n", - "\n", - "print(jetpack.size)\n", - "print(model.count_tokens(jetpack))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "8342199c9eb4" - }, - "source": [ - "Audio and video are each converted to tokens at a fixed rate of tokens per minute." - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": { - "id": "be103816898c" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " % Total % Received % Xferd Average Speed Time Time Time Current\n", - " Dload Upload Total Spent Left Speed\n", - "100 39.8M 100 39.8M 0 0 26.7M 0 0:00:01 0:00:01 --:--:-- 26.7M\n" - ] - } - ], - "source": [ - "!curl -q -o sample.mp3 \"https://storage.googleapis.com/generativeai-downloads/data/State_of_the_Union_Address_30_January_1961.mp3\"" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": { - "id": "ada734553530" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "total_tokens: 83552" - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "audio_sample = genai.upload_file('sample.mp3')\n", - "model.count_tokens(audio_sample)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "a9367d1afac3" - }, - "source": [ - "### System instructions and tools\n", - "\n", - "System instructions and tools also count towards the total:" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": { - "id": "c2a83ac75dfe" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "total_tokens: 10" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "genai.GenerativeModel().count_tokens(\"The quick brown fox jumps over the lazy dog.\")" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": { - "id": "c275fafdf080" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "total_tokens: 15" - ] - }, - "execution_count": 33, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "genai.GenerativeModel(system_instruction='Talk like a pirate!').count_tokens(\"The quick brown fox jumps over the lazy dog.\")" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": { - "id": "5fcff3d1403e" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "total_tokens: 194" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def add(a:float, b:float):\n", - " \"\"\"returns a + b.\"\"\"\n", - " return a+b\n", - "\n", - "def subtract(a:float, b:float):\n", - " \"\"\"returns a - b.\"\"\"\n", - " return a-b\n", - "\n", - "def multiply(a:float, b:float):\n", - " \"\"\"returns a * b.\"\"\"\n", - " return a*b\n", - "\n", - "def divide(a:float, b:float):\n", - " \"\"\"returns a / b.\"\"\"\n", - " return a*b\n", - "\n", - "model = genai.GenerativeModel(model_name='gemini-1.0-pro',\n", - " tools=[add, subtract, multiply, divide])\n", - "model.count_tokens(\"The quick brown fox jumps over the lazy dog.\")\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "QfZNBWZLDCXa" - }, - "source": [ - "## Further reading\n", - "\n", - "For more on token counting, check out the API reference.\n", - "\n", - "* [countTokens](https://ai.google.dev/api/rest/v1/models/countTokens) REST API reference,\n", - "* [count_tokens](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#count_tokens) Python API reference," - ] - } - ], - "metadata": { - "colab": { - "name": "Counting_Tokens.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "YZXn1Salxl_w" + }, + "source": [ + "# Gemini API: All about tokens" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3FIB-JDtxgUE" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "CRzxdrjKLTJa" + }, + "source": [ + "An understanding of tokens is central to using the Gemini API. This guide will provide a interactive introduction to what tokens are and how they are used in the Gemini API.\n", + "\n", + "## About tokens\n", + "\n", + "LLMs break up their input and produce their output at a granularity that is smaller than a word, but larger than a single character or code-point.\n", + "\n", + "These **tokens** can be single characters, like `z`, or whole words, like `the`. Long words may be broken up into several tokens. The set of all tokens used by the model is called the vocabulary, and the process of breaking down text into tokens is called tokenization.\n", + "\n", + "For Gemini models, a token is equivalent to about 4 characters. **100 tokens are about 60-80 English words**.\n", + "\n", + "When billing is enabled, the price of a paid request is controlled by the [number of input and output tokens](https://ai.google.dev/pricing), so knowing how to count your tokens is important.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xwJ1lyGC_Ia4" + }, + "source": [ + "## Tokens in the Gemini API" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "GBa_hMFneZKO" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "OzsRfmWrxd_F" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IG_wSwTJ2wAP" + }, + "source": [ + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "LyWgDDHr1yxd" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "GOOGLE_API_KEY = userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "etlFvMXP3Gb7" + }, + "source": [ + "### Context windows\n", + "\n", + "The models available through the Gemini API have context windows that are measured in tokens. These define how much input you can provide, and how much output the model can generate, and combined are referred to as the \"context window\". This information is available directly through [the API](https://ai.google.dev/api/rest/v1/models/get) and in the [models](https://ai.google.dev/models/gemini) documentation.\n", + "\n", + "In this example you can see the `gemini-1.5-flash-latest` model has an 1M tokens context window." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "1QC23D2z3GLV", + "tags": [] + }, + "outputs": [], + "source": [ + "model_info = genai.get_model('models/gemini-1.5-flash-latest')\n", + "(model_info.input_token_limit, model_info.output_token_limit)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kkh8v5QI4v5h" + }, + "source": [ + "## Counting tokens\n", + "\n", + "The API provides an endpoint for counting the number of tokens in a request: [`GenerativeModel.count_tokens`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#count_tokens). You pass the same arguments as you would to [`GenerativeModel.generate_content`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) and the service will return the number of tokens in that request." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "F0J8JPYbCGnv" + }, + "source": [ + "### Text tokens" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "7jpoJFpX5Cu_", + "tags": [] + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('models/gemini-1.5-flash-latest')\n", + "model.count_tokens(\"The quick brown fox jumps over the lazy dog.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0661517a2417" + }, + "source": [ + "When you call `GenerativeModel.generate_content` (or `ChatSession.send_message`) the response object has a `usage_metadata` attribute containing both the input and output token counts (`prompt_token_count` and `candidates_token_count`):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "71aa6568a670", + "tags": [] + }, + "outputs": [], + "source": [ + "response = model.generate_content(\"The quick brown fox jumps over the lazy dog.\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "response.usage_metadata" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "SQzJ7asV-HJB" + }, + "source": [ + "### Multi-turn tokens\n", + "\n", + "Multi-turn conversational (chat) objects work similarly." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "eqUpyE_E95_w", + "tags": [] + }, + "outputs": [], + "source": [ + "chat = model.start_chat(history=[{'role':'user', 'parts':'Hi my name is Bob'}, {'role':'model', 'parts':'Hi Bob!'}])\n", + "model.count_tokens(chat.history)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "68ae99485a0c", + "tags": [] + }, + "outputs": [], + "source": [ + "chat" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zMvjgRkVAvVN" + }, + "source": [ + "To understand how big your next conversational turn will be, you will need to append it to the history when you call `count_tokens`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "pxVsykc5A5he", + "tags": [] + }, + "outputs": [], + "source": [ + "from google.generativeai.types.content_types import to_contents\n", + "model.count_tokens(chat.history + to_contents('What is the meaning of life?'))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZZYcaUXl-Sna" + }, + "source": [ + "### Multi-modal tokens\n", + "\n", + "All input to the API is tokenized, including images or other non-text modalities." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "hsKfX8LYAdLv", + "tags": [] + }, + "outputs": [], + "source": [ + "!curl -L https://goo.gle/instrument-img -o organ.jpg" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Jzwrahub-ez5", + "tags": [] + }, + "outputs": [], + "source": [ + "import PIL\n", + "from IPython.display import display, Image\n", + "\n", + "display(Image('organ.jpg', width=300))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "c4164419d70f" + }, + "source": [ + "#### Inline content\n", + "\n", + "Media objects can be sent to the API inline with the request:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Ledzam3H__Ob", + "tags": [] + }, + "outputs": [], + "source": [ + "organ = PIL.Image.open('organ.jpg')\n", + "model.count_tokens(['Tell me about this instrument', organ])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "b3851a09ec17" + }, + "source": [ + "#### Files API\n", + "\n", + "The model sees identical tokens if you upload parts of the prompt through the files API instead:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "f994c2dd6e05", + "tags": [] + }, + "outputs": [], + "source": [ + "organ_upload = genai.upload_file('organ.jpg')\n", + "\n", + "model.count_tokens(['Tell me about this instrument', organ_upload])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "UXF0vpdG_H_Q" + }, + "source": [ + "### Media token counts\n", + "\n", + "Internally, images are a fixed size, so they consume a fixed number of tokens." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "sPPfXRJiA3KV", + "tags": [] + }, + "outputs": [], + "source": [ + "!curl -O \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\" --silent" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "jqG83Rko8UpG", + "tags": [] + }, + "outputs": [], + "source": [ + "jetpack = PIL.Image.open('jetpack.jpg')\n", + "display(Image('jetpack.jpg', width=300))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "hc0CBsl6_Tkk", + "tags": [] + }, + "outputs": [], + "source": [ + "print(organ.size)\n", + "print(model.count_tokens(organ))\n", + "\n", + "print(jetpack.size)\n", + "print(model.count_tokens(jetpack))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8342199c9eb4" + }, + "source": [ + "Audio and video are each converted to tokens at a fixed rate of tokens per minute." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "be103816898c", + "tags": [] + }, + "outputs": [], + "source": [ + "!curl -q -o sample.mp3 \"https://storage.googleapis.com/generativeai-downloads/data/State_of_the_Union_Address_30_January_1961.mp3\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ada734553530", + "tags": [] + }, + "outputs": [], + "source": [ + "audio_sample = genai.upload_file('sample.mp3')\n", + "model.count_tokens(audio_sample)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "a9367d1afac3" + }, + "source": [ + "### System instructions and tools\n", + "\n", + "System instructions and tools also count towards the total:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "c2a83ac75dfe", + "tags": [] + }, + "outputs": [], + "source": [ + "genai.GenerativeModel().count_tokens(\"The quick brown fox jumps over the lazy dog.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "c275fafdf080", + "tags": [] + }, + "outputs": [], + "source": [ + "genai.GenerativeModel(system_instruction='Talk like a pirate!').count_tokens(\"The quick brown fox jumps over the lazy dog.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "5fcff3d1403e", + "tags": [] + }, + "outputs": [], + "source": [ + "def add(a:float, b:float):\n", + " \"\"\"returns a + b.\"\"\"\n", + " return a+b\n", + "\n", + "def subtract(a:float, b:float):\n", + " \"\"\"returns a - b.\"\"\"\n", + " return a-b\n", + "\n", + "def multiply(a:float, b:float):\n", + " \"\"\"returns a * b.\"\"\"\n", + " return a*b\n", + "\n", + "def divide(a:float, b:float):\n", + " \"\"\"returns a / b.\"\"\"\n", + " return a*b\n", + "\n", + "model = genai.GenerativeModel(model_name='gemini-1.5-flash-latest',\n", + " tools=[add, subtract, multiply, divide])\n", + "model.count_tokens(\"The quick brown fox jumps over the lazy dog.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "QfZNBWZLDCXa" + }, + "source": [ + "## Further reading\n", + "\n", + "For more on token counting, check out the API reference.\n", + "\n", + "* [countTokens](https://ai.google.dev/api/rest/v1/models/countTokens) REST API reference,\n", + "* [count_tokens](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#count_tokens) Python API reference," + ] + } + ], + "metadata": { + "colab": { + "name": "Counting_Tokens.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/File_API.ipynb b/quickstarts/File_API.ipynb index 972e5d0e0..090d3a637 100644 --- a/quickstarts/File_API.ipynb +++ b/quickstarts/File_API.ipynb @@ -1,476 +1,384 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "PzjeBM__IE1k" - }, - "source": [ - "# Gemini API: File API Quickstart\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "084u8u0DpBlo" - }, - "source": [ - "The Gemini API supports prompting with text, image, and audio data, also known as *multimodal* prompting. You can include text, image,\n", - "and audio in your prompts. For small images, you can point the Gemini model\n", - "directly to a local file when providing a prompt. For larger text files, images, videos, and audio, upload the files with the [File\n", - "API](https://ai.google.dev/api/rest/v1beta/files) before including them in\n", - "prompts.\n", - "\n", - "The File API lets you store up to 20GB of files per project, with each file not\n", - "exceeding 2GB in size. Files are stored for 48 hours and can be accessed with\n", - "your API key for generation within that time period. It is available at no cost in all regions where the [Gemini API is\n", - "available](https://ai.google.dev/available_regions).\n", - "\n", - "For information on valid file formats (MIME types) and supported models, see the documentation on\n", - "[supported file formats](https://ai.google.dev/tutorials/prompting_with_media#supported_file_formats)\n", - "and view the text examples at the end of this guide.\n", - "\n", - "This guide shows how to use the File API to upload a media file and include it in a `GenerateContent` call to the Gemini API. For more information, see the [code\n", - "samples](https://github.com/google-gemini/cookbook/tree/main/quickstarts/file-api).\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "_d_yY8XWGQ12" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "TeVyF3GtGQ13" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai\n", - "from IPython.display import Image" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "YdyC6Z6wqxz-" - }, - "source": [ - "## Authentication\n", - "\n", - "**Important:** The File API uses API keys for authentication and access. Uploaded files are associated with the API key's cloud project. Unlike other Gemini APIs that use API keys, your API key also grants access data you've uploaded to the File API, so take extra care in keeping your API key secure. For best practices on securing API keys, refer to Google's [documentation](https://support.google.com/googleapi/answer/6310037)." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "l8g4hTRotheH" - }, - "source": [ - "### Setup your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "iWd---jVKV5M" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "\n", - "GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "c-z4zsCUlaru" - }, - "source": [ - "## Upload file\n", - "\n", - "The File API lets you upload a variety of multimodal MIME types, including images and audio formats. The File API handles inputs that can be used to generate content with [`model.generateContent`](https://ai.google.dev/api/rest/v1/models/generateContent) or [`model.streamGenerateContent`](https://ai.google.dev/api/rest/v1/models/streamGenerateContent).\n", - "\n", - "The File API accepts files under 2GB in size and can store up to 20GB of files per project. Files last for 2 days and cannot be downloaded from the API." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2wsJ0vHNNtdJ" - }, - "source": [ - "First, you will prepare a sample image to upload to the API.\n", - "\n", - "Note: You can also [upload your own files](https://github.com/google-gemini/cookbook/tree/main/examples/Upload_files_to_Colab.ipynb) to use." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "EfuQVRXIGqvt" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " % Total % Received % Xferd Average Speed Time Time Time Current\n", - " Dload Upload Total Spent Left Speed\n", - "100 349k 100 349k 0 0 1487k 0 --:--:-- --:--:-- --:--:-- 1492k\n" - ] - }, - { - "data": { - "image/jpeg": 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\n", - "text/plain": [ - "" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "!curl -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\"\n", - "Image(filename=\"image.jpg\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "EEoXN0f3N2yc" - }, - "source": [ - "Next, you will upload that file to the File API." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "N9NxXGZKKusG" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Uploaded file '' as: https://generativelanguage.googleapis.com/v1beta/files/p0dsmt12b68\n" - ] - } - ], - "source": [ - "sample_file = genai.upload_file(path=\"image.jpg\", display_name=\"Sample drawing\")\n", - "\n", - "print(f\"Uploaded file '{sample_file.display_name}' as: {sample_file.uri}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "smAIH077GQ14" - }, - "source": [ - "The `response` shows that the File API stored the specified `display_name` for the uploaded file and a `uri` to reference the file in Gemini API calls. Use `response` to track how uploaded files are mapped to URIs.\n", - "\n", - "Depending on your use cases, you could store the URIs in structures such as a `dict` or a database." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "oOZmTUb4FWOa" - }, - "source": [ - "## Get file\n", - "\n", - "After uploading the file, you can verify the API has successfully received the files by calling `files.get`.\n", - "\n", - "It lets you get the file metadata that have been uploaded to the File API that are associated with the Cloud project your API key belongs to. Only the `name` (and by extension, the `uri`) are unique. Only use the `displayName` to identify files if you manage uniqueness yourself." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "SHMVCWHkFhJW" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Retrieved file 'Sample drawing' as: https://generativelanguage.googleapis.com/v1beta/files/p0dsmt12b68\n" - ] - } - ], - "source": [ - "file = genai.get_file(name=sample_file.name)\n", - "print(f\"Retrieved file '{file.display_name}' as: {sample_file.uri}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "EPPOECHzsIGJ" - }, - "source": [ - "## Generate content\n", - "\n", - "After uploading the file, you can make `GenerateContent` requests that reference the file by providing the URI. In the Python SDK you can pass the returned object directly.\n", - "\n", - "Here you create a prompt that starts with text and includes the uploaded image." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ZYVFqmLkl5nE" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "A notebook's page reveals a fantastical invention - the Jetpack Backpack. Drawn in blue ink, it resembles a typical backpack, but with key differences. At its base, retractable boosters promise flight, fueled by clean, steam-powered energy. Arrows point to features like padded straps for comfort during liftoff, a 15-minute battery life (hopefully enough for a quick commute!), and a USB-C charging port for convenience. This backpack of the future even boasts enough space for an 18\" laptop, making it the ultimate accessory for the student on the go - literally!\n" - ] - } - ], - "source": [ - "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-pro-latest\")\n", - "\n", - "response = model.generate_content(\n", - " [\"Describe the image with a creative description.\", sample_file]\n", - ")\n", - "\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IrPDYdQSKTg4" - }, - "source": [ - "## Delete files\n", - "\n", - "Files are automatically deleted after 2 days or you can manually delete them using `files.delete()`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "d4eO8ZXoKdZf" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Deleted Sample drawing.\n" - ] - } - ], - "source": [ - "genai.delete_file(sample_file.name)\n", - "print(f\"Deleted {sample_file.display_name}.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "u_aF5anOvKsO" - }, - "source": [ - "## Supported text types\n", - "\n", - "As well as supporting media uploads, the File API can be used to embed text files, such as Python code, or Markdown files, into your prompts.\n", - "\n", - "This example shows you how to load a markdown file into a prompt using the File API." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "3Hz37jFBSr9l" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "## Steps to Take Before Contributing to the Gemini API Cookbook:\n", - "\n", - "Here's what you should do before you begin writing:\n", - "\n", - "**1. Contributor License Agreement (CLA):**\n", - "\n", - "* Visit https://cla.developers.google.com/ to check if you or your employer have already signed the Google CLA. If not, you'll need to sign one to allow the project to use and redistribute your contributions.\n", - "\n", - "**2. Familiarize Yourself with Style Guides:**\n", - "\n", - "* Read the highlights of the technical writing style guide: https://developers.google.com/style/highlights \n", - "* Review the style guide for the programming language you'll be using: https://google.github.io/styleguide/\n", - "\n", - "**3. Consider Using pyink (for Python notebooks):**\n", - "\n", - "* While not mandatory, running `pyink` on your *.ipynb files can help maintain consistent style and avoid potential issues.\n", - "\n", - "**4. Propose Your Contribution:**\n", - "\n", - "* Before writing anything, create an issue on the GitHub repository (https://github.com/google-gemini/cookbook/issues) to discuss your idea and receive guidance on structuring your content. This helps ensure your contribution aligns with the project's goals and avoids wasted effort.\n", - "\n", - "**5. Understand the Evaluation Criteria:**\n", - "\n", - "* The project considers factors like originality, pedagogical value, and quality when accepting new guides. Aim to make your contribution as strong as possible in these areas. \n", - "\n" - ] - } - ], - "source": [ - "# Download a markdown file and ask a question.\n", - "\n", - "!curl -so contrib.md https://raw.githubusercontent.com/google-gemini/cookbook/main/CONTRIBUTING.md\n", - "\n", - "md_file = genai.upload_file(path=\"contrib.md\", display_name=\"Contributors guide\", mime_type=\"text/markdown\")\n", - "\n", - "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-pro-latest\")\n", - "response = model.generate_content(\n", - " [\n", - " \"What should I do before I start writing, when following these guidelines?\",\n", - " md_file,\n", - " ]\n", - ")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "pmmVaBz4Ss3W" - }, - "source": [ - "Some common text formats are automatically detected, such as `text/x-python`, `text/html` and `text/markdown`. If you are using a file that you know is text, but is not automatically detected by the API as such, you can specify the MIME type as `text/plain` explicitly." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "8m4qpfTqzE9o" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "## Program Breakdown: Gemma Language Model Example\n", - "\n", - "This C++ program demonstrates how to use the Gemma language model for text generation. Let's break down what each part does:\n", - "\n", - "**1. Headers and Setup:**\n", - "\n", - "* Includes necessary libraries like `iostream` for input/output, `gemma.h` for the Gemma model, and others for thread management and argument parsing.\n", - "* Defines a `tokenize` function that prepares the input prompt string by adding specific start/end tokens and converting it into a sequence of integer tokens using the provided tokenizer.\n", - "\n", - "**2. Main Function:**\n", - "\n", - "* **Argument Parsing:** Uses `LoaderArgs` to parse command-line arguments related to the model, tokenizer, weights, and other settings.\n", - "* **Thread Pool Creation:** Creates a thread pool based on the available hardware concurrency for efficient parallel processing.\n", - "* **Model and Cache Initialization:**\n", - " * Loads the Gemma model using the specified tokenizer and weights.\n", - " * Creates a Key-Value (KV) cache, which is used for caching intermediate results during generation. \n", - "* **Random Number Generator:** Sets up a random number generator using `std::mt19937` for stochastic aspects of the model.\n", - "* **Prompt Tokenization:** Tokenizes the example instruction \"Write a greeting to the world.\" using the `tokenize` function. \n", - "* **Stream Token Callback:** Defines a callback function `stream_token` that is called for each generated token. It keeps track of the generation progress and prints the generated text.\n", - "* **Text Generation:** Calls the `GenerateGemma` function to generate text based on the provided prompt, model, KV cache, and various parameters like maximum token limits and temperature. The `stream_token` callback is used to process each generated token.\n", - "* **Output:** Prints the final generated text to the console. \n", - "\n", - "**In essence, this program takes an instruction as input, uses the Gemma language model to generate text based on that instruction, and then outputs the generated text to the user.** \n", - "\n" - ] - } - ], - "source": [ - "# Download some C++ code and force the MIME as text when uploading.\n", - "\n", - "!curl -so gemma.cpp https://raw.githubusercontent.com/google/gemma.cpp/main/examples/hello_world/run.cc\n", - "\n", - "cpp_file = genai.upload_file(\n", - " path=\"gemma.cpp\", display_name=\"gemma.cpp\", mime_type=\"text/plain\"\n", - ")\n", - "\n", - "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-pro-latest\")\n", - "response = model.generate_content([\"What does this program do?\", cpp_file])\n", - "print(response.text)" - ] - } - ], - "metadata": { - "colab": { - "name": "File_API.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] }, - "nbformat": 4, - "nbformat_minor": 0 + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "PzjeBM__IE1k" + }, + "source": [ + "# Gemini API: File API Quickstart\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "084u8u0DpBlo" + }, + "source": [ + "The Gemini API supports prompting with text, image, and audio data, also known as *multimodal* prompting. You can include text, image,\n", + "and audio in your prompts. For small images, you can point the Gemini model\n", + "directly to a local file when providing a prompt. For larger text files, images, videos, and audio, upload the files with the [File\n", + "API](https://ai.google.dev/api/rest/v1beta/files) before including them in\n", + "prompts.\n", + "\n", + "The File API lets you store up to 20GB of files per project, with each file not\n", + "exceeding 2GB in size. Files are stored for 48 hours and can be accessed with\n", + "your API key for generation within that time period. It is available at no cost in all regions where the [Gemini API is\n", + "available](https://ai.google.dev/available_regions).\n", + "\n", + "For information on valid file formats (MIME types) and supported models, see the documentation on\n", + "[supported file formats](https://ai.google.dev/tutorials/prompting_with_media#supported_file_formats)\n", + "and view the text examples at the end of this guide.\n", + "\n", + "This guide shows how to use the File API to upload a media file and include it in a `GenerateContent` call to the Gemini API. For more information, see the [code\n", + "samples](https://github.com/google-gemini/cookbook/tree/main/quickstarts/file-api).\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "_d_yY8XWGQ12" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TeVyF3GtGQ13", + "tags": [] + }, + "outputs": [], + "source": [ + "import google.generativeai as genai\n", + "from IPython.display import Image" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "YdyC6Z6wqxz-" + }, + "source": [ + "## Authentication\n", + "\n", + "**Important:** The File API uses API keys for authentication and access. Uploaded files are associated with the API key's cloud project. Unlike other Gemini APIs that use API keys, your API key also grants access data you've uploaded to the File API, so take extra care in keeping your API key secure. For best practices on securing API keys, refer to Google's [documentation](https://support.google.com/googleapi/answer/6310037)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "l8g4hTRotheH" + }, + "source": [ + "### Setup your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "iWd---jVKV5M" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "\n", + "GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "c-z4zsCUlaru" + }, + "source": [ + "## Upload file\n", + "\n", + "The File API lets you upload a variety of multimodal MIME types, including images and audio formats. The File API handles inputs that can be used to generate content with [`model.generateContent`](https://ai.google.dev/api/rest/v1/models/generateContent) or [`model.streamGenerateContent`](https://ai.google.dev/api/rest/v1/models/streamGenerateContent).\n", + "\n", + "The File API accepts files under 2GB in size and can store up to 20GB of files per project. Files last for 2 days and cannot be downloaded from the API." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2wsJ0vHNNtdJ" + }, + "source": [ + "First, you will prepare a sample image to upload to the API.\n", + "\n", + "Note: You can also [upload your own files](https://github.com/google-gemini/cookbook/tree/main/examples/Upload_files_to_Colab.ipynb) to use." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "EfuQVRXIGqvt", + "tags": [] + }, + "outputs": [], + "source": [ + "!curl -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\"\n", + "Image(filename=\"image.jpg\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EEoXN0f3N2yc" + }, + "source": [ + "Next, you will upload that file to the File API." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "N9NxXGZKKusG", + "tags": [] + }, + "outputs": [], + "source": [ + "sample_file = genai.upload_file(path=\"image.jpg\", display_name=\"Sample drawing\")\n", + "\n", + "print(f\"Uploaded file '{sample_file.display_name}' as: {sample_file.uri}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "smAIH077GQ14" + }, + "source": [ + "The `response` shows that the File API stored the specified `display_name` for the uploaded file and a `uri` to reference the file in Gemini API calls. Use `response` to track how uploaded files are mapped to URIs.\n", + "\n", + "Depending on your use cases, you could store the URIs in structures such as a `dict` or a database." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "oOZmTUb4FWOa" + }, + "source": [ + "## Get file\n", + "\n", + "After uploading the file, you can verify the API has successfully received the files by calling `files.get`.\n", + "\n", + "It lets you get the file metadata that have been uploaded to the File API that are associated with the Cloud project your API key belongs to. Only the `name` (and by extension, the `uri`) are unique. Only use the `displayName` to identify files if you manage uniqueness yourself." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "SHMVCWHkFhJW", + "tags": [] + }, + "outputs": [], + "source": [ + "file = genai.get_file(name=sample_file.name)\n", + "print(f\"Retrieved file '{file.display_name}' as: {sample_file.uri}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EPPOECHzsIGJ" + }, + "source": [ + "## Generate content\n", + "\n", + "After uploading the file, you can make `GenerateContent` requests that reference the file by providing the URI. In the Python SDK you can pass the returned object directly.\n", + "\n", + "Here you create a prompt that starts with text and includes the uploaded image." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-flash-latest\")\n", + "\n", + "response = model.generate_content(\n", + " [\"Describe the image with a creative description.\", sample_file]\n", + ")\n", + "\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IrPDYdQSKTg4" + }, + "source": [ + "## Delete files\n", + "\n", + "Files are automatically deleted after 2 days or you can manually delete them using `files.delete()`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "d4eO8ZXoKdZf", + "tags": [] + }, + "outputs": [], + "source": [ + "genai.delete_file(sample_file.name)\n", + "print(f\"Deleted {sample_file.display_name}.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "u_aF5anOvKsO" + }, + "source": [ + "## Supported text types\n", + "\n", + "As well as supporting media uploads, the File API can be used to embed text files, such as Python code, or Markdown files, into your prompts.\n", + "\n", + "This example shows you how to load a markdown file into a prompt using the File API." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Download a markdown file and ask a question.\n", + "\n", + "!curl -so contrib.md https://raw.githubusercontent.com/google-gemini/cookbook/main/CONTRIBUTING.md\n", + "\n", + "md_file = genai.upload_file(path=\"contrib.md\", display_name=\"Contributors guide\", mime_type=\"text/markdown\")\n", + "\n", + "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-flash-latest\")\n", + "response = model.generate_content(\n", + " [\n", + " \"What should I do before I start writing, when following these guidelines?\",\n", + " md_file,\n", + " ]\n", + ")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pmmVaBz4Ss3W" + }, + "source": [ + "Some common text formats are automatically detected, such as `text/x-python`, `text/html` and `text/markdown`. If you are using a file that you know is text, but is not automatically detected by the API as such, you can specify the MIME type as `text/plain` explicitly." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Download some C++ code and force the MIME as text when uploading.\n", + "\n", + "!curl -so gemma.cpp https://raw.githubusercontent.com/google/gemma.cpp/main/examples/hello_world/run.cc\n", + "\n", + "cpp_file = genai.upload_file(\n", + " path=\"gemma.cpp\", display_name=\"gemma.cpp\", mime_type=\"text/plain\"\n", + ")\n", + "\n", + "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-flash-latest\")\n", + "response = model.generate_content([\"What does this program do?\", cpp_file])\n", + "print(response.text)" + ] + } + ], + "metadata": { + "colab": { + "name": "File_API.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/Function_calling.ipynb b/quickstarts/Function_calling.ipynb index 2ef9bbfde..51592f184 100644 --- a/quickstarts/Function_calling.ipynb +++ b/quickstarts/Function_calling.ipynb @@ -1,781 +1,696 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: Function calling with Python" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lEXQ3OwKIa-O" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "df1767a3d1cc" - }, - "source": [ - "Function calling lets developers create a description of a function in their code, then pass that description to a language model in a request. The response from the model includes the name of a function that matches the description and the arguments to call it with. Function calling lets you use functions as tools in generative AI applications, and you can define more than one function within a single request.\n", - "\n", - "This notebook provides code examples to help you get started." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9OEoeosRTv-5" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai # Install the Python SDK" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "TS9l5igubpHO" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "x-hHZfLZ7FfH" - }, - "source": [ - "## Set up your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ab9ASynfcIZn" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "\n", - "GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3f383614ec30" - }, - "source": [ - "## Function calling basics" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "b82c1aecb657" - }, - "source": [ - "To use function calling, pass a list of functions to the `tools` parameter when creating a [`GenerativeModel`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel). The model uses the function name, docstring, parameters, and parameter type annotations to decide if it needs the function to best answer a prompt.\n", - "\n", - "> Important: The SDK converts function parameter type annotations to a format the API understands (`glm.FunctionDeclaration`). The API only supports a limited selection of parameter types, and the Python SDK's automatic conversion only supports a subset of that: `AllowedTypes = int | float | bool | str | list['AllowedTypes'] | dict`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "42b27b02d2f5" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "genai.GenerativeModel(\n", - " model_name='models/gemini-1.0-pro',\n", - " generation_config={},\n", - " safety_settings={},\n", - " tools=,\n", - ")" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def add(a: float, b: float):\n", - " \"\"\"returns a + b.\"\"\"\n", - " return a + b\n", - "\n", - "\n", - "def subtract(a: float, b: float):\n", - " \"\"\"returns a - b.\"\"\"\n", - " return a - b\n", - "\n", - "\n", - "def multiply(a: float, b: float):\n", - " \"\"\"returns a * b.\"\"\"\n", - " return a * b\n", - "\n", - "\n", - "def divide(a: float, b: float):\n", - " \"\"\"returns a / b.\"\"\"\n", - " return a / b\n", - "\n", - "\n", - "model = genai.GenerativeModel(\n", - " model_name=\"gemini-1.0-pro\", tools=[add, subtract, multiply, divide]\n", - ")\n", - "\n", - "model" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "UzUgtaY99BTg" - }, - "source": [ - "## Automatic function calling" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "d5fd91032a1e" - }, - "source": [ - "Function calls naturally fit in to [multi-turn chats](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#multi-turn) as they capture a back and forth interaction between the user and model. The Python SDK's [`ChatSession`](https://ai.google.dev/api/python/google/generativeai/ChatSession) is a great interface for chats because handles the conversation history for you, and using the parameter `enable_automatic_function_calling` simplifies function calling even further:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "d3b91c855257" - }, - "outputs": [], - "source": [ - "chat = model.start_chat(enable_automatic_function_calling=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "1481a6159399" - }, - "source": [ - "With automatic function calling enabled, `ChatSession.send_message` automatically calls your function if the model asks it to.\n", - "\n", - "In the following example, the result appears to simply be a text response containing the correct answer:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "81d8def3d865" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'There are 2508 mittens in total.'" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "response = chat.send_message(\n", - " \"I have 57 cats, each owns 44 mittens, how many mittens is that in total?\"\n", - ")\n", - "response.text" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "951c0f83f72e" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "2508" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "57 * 44" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "7731e35f2383" - }, - "source": [ - "However, by examining the chat history, you can see the flow of the conversation and how function calls are integrated within it.\n", - "\n", - "The `ChatSession.history` property stores a chronological record of the conversation between the user and the Gemini model. Each turn in the conversation is represented by a [`glm.Content`](https://ai.google.dev/api/python/google/ai/generativelanguage/Content) object, which contains the following information:\n", - "\n", - "* **Role**: Identifies whether the content originated from the \"user\" or the \"model\".\n", - "* **Parts**: A list of [`glm.Part`](https://ai.google.dev/api/python/google/ai/generativelanguage/Part) objects that represent individual components of the message. With a text-only model, these parts can be:\n", - " * **Text**: Plain text messages.\n", - " * **Function Call** ([`glm.FunctionCall`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall)): A request from the model to execute a specific function with provided arguments.\n", - " * **Function Response** ([`glm.FunctionResponse`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse)): The result returned by the user after executing the requested function.\n", - "\n", - " In the previous example with the mittens calculation, the history shows the following sequence:\n", - "\n", - "1. **User**: Asks the question about the total number of mittens.\n", - "1. **Model**: Determines that the multiply function is helpful and sends a FunctionCall request to the user.\n", - "1. **User**: The `ChatSession` automatically executes the function (due to `enable_automatic_function_calling` being set) and sends back a `FunctionResponse` with the calculated result.\n", - "1. **Model**: Uses the function's output to formulate the final answer and presents it as a text response." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9f7eff1e8e60" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "user -> [{'text': 'I have 57 cats, each owns 44 mittens, how many mittens is that in total?'}]\n", - "--------------------------------------------------------------------------------\n", - "model -> [{'function_call': {'name': 'multiply', 'args': {'a': 57.0, 'b': 44.0}}}]\n", - "--------------------------------------------------------------------------------\n", - "user -> [{'function_response': {'name': 'multiply', 'response': {'result': 2508.0}}}]\n", - "--------------------------------------------------------------------------------\n", - "model -> [{'text': 'There are 2508 mittens in total.'}]\n", - "--------------------------------------------------------------------------------\n" - ] - } - ], - "source": [ - "for content in chat.history:\n", - " print(content.role, \"->\", [type(part).to_dict(part) for part in content.parts])\n", - " print(\"-\" * 80)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2471fd72f05e" - }, - "source": [ - "In general the state diagram is:\n", - "\n", - "\"The\n", - "\n", - "The model can respond with multiple function calls before returning a text response, and function calls come before the text response." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "eea8e3a0b89f" - }, - "source": [ - "## Manual function calling" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "9610f3465a69" - }, - "source": [ - "For more control, you can process [`glm.FunctionCall`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall) requests from the model yourself. This would be the case if:\n", - "\n", - "- You use a `ChatSession` with the default `enable_automatic_function_calling=False`.\n", - "- You use `GenerativeModel.generate_content` (and manage the chat history yourself)." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "34ffab0bf365" - }, - "source": [ - "The following example is a rough equivalent of the [function calling single-turn curl sample](https://ai.google.dev/docs/function_calling#function-calling-single-turn-curl-sample) in Python. It uses functions that return (mock) movie playtime information, possibly from a hypothetical API:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "46ba0fa3d09a" - }, - "outputs": [], - "source": [ - "def find_movies(description: str, location: str = \"\"):\n", - " \"\"\"find movie titles currently playing in theaters based on any description, genre, title words, etc.\n", - "\n", - " Args:\n", - " description: Any kind of description including category or genre, title words, attributes, etc.\n", - " location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n", - " \"\"\"\n", - " return [\"Barbie\", \"Oppenheimer\"]\n", - "\n", - "\n", - "def find_theaters(location: str, movie: str = \"\"):\n", - " \"\"\"Find theaters based on location and optionally movie title which are is currently playing in theaters.\n", - "\n", - " Args:\n", - " location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n", - " movie: Any movie title\n", - " \"\"\"\n", - " return [\"Googleplex 16\", \"Android Theatre\"]\n", - "\n", - "\n", - "def get_showtimes(location: str, movie: str, theater: str, date: str):\n", - " \"\"\"\n", - " Find the start times for movies playing in a specific theater.\n", - "\n", - " Args:\n", - " location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n", - " movie: Any movie title\n", - " thearer: Name of the theater\n", - " date: Date for requested showtime\n", - " \"\"\"\n", - " return [\"10:00\", \"11:00\"]" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Ck-hdu5N8VlR" - }, - "source": [ - "Use a dictionary to make looking up functions by name easier later on. You can also use it to pass the array of functions to the `tools` parameter of `GenerativeModel`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "8i3SKdy18WHu" - }, - "outputs": [], - "source": [ - "functions = {\n", - " \"find_movies\": find_movies,\n", - " \"find_theaters\": find_theaters,\n", - " \"get_showtimes\": get_showtimes,\n", - "}\n", - "\n", - "model = genai.GenerativeModel(model_name=\"gemini-1.0-pro\", tools=functions.values())" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "11631c6e2b10" - }, - "source": [ - "After using `generate_content()` to ask a question, the model requests a `function_call`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "5e3b9c84d883" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "[function_call {\n", - " name: \"find_theaters\"\n", - " args {\n", - " fields {\n", - " key: \"location\"\n", - " value {\n", - " string_value: \"Mountain View, CA\"\n", - " }\n", - " }\n", - " fields {\n", - " key: \"movie\"\n", - " value {\n", - " string_value: \"Barbie\"\n", - " }\n", - " }\n", - " }\n", - "}\n", - "]" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "response = model.generate_content(\n", - " \"Which theaters in Mountain View show the Barbie movie?\"\n", - ")\n", - "response.candidates[0].content.parts" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kuldoypuAC1i" - }, - "source": [ - "Since this is not using a `ChatSession` with automatic function calling, you have to call the function yourself.\n", - "\n", - "A very simple way to do this would be with `if` statements:\n", - "\n", - "```python\n", - "if function_call.name == 'find_theaters':\n", - " find_theaters(**function_call.args)\n", - "elif ...\n", - "```\n", - "\n", - "However, since you already made the `functions` dictionary, this can be simplified to:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "rjkZ8MA00Coc" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['Googleplex 16', 'Android Theatre']\n" - ] - } - ], - "source": [ - "def call_function(function_call, functions):\n", - " function_name = function_call.name\n", - " function_args = function_call.args\n", - " return functions[function_name](**function_args)\n", - "\n", - "\n", - "part = response.candidates[0].content.parts[0]\n", - "\n", - "# Check if it's a function call; in real use you'd need to also handle text\n", - "# responses as you won't know what the model will respond with.\n", - "if part.function_call:\n", - " result = call_function(part.function_call, functions)\n", - "\n", - "print(result)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "XLWrHOatBtRz" - }, - "source": [ - "Finally, pass the response plus the message history to the next `generate_content()` call to get a final text response from the model." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "gdb62GstAD_3" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Theaters showing Barbie in Mountain View, CA are: Googleplex 16, Android Theatre\n" - ] - } - ], - "source": [ - "import google.ai.generativelanguage as glm\n", - "from google.protobuf.struct_pb2 import Struct\n", - "\n", - "# Put the result in a protobuf Struct\n", - "s = Struct()\n", - "s.update({\"result\": result})\n", - "\n", - "# Update this after https://github.com/google/generative-ai-python/issues/243\n", - "function_response = glm.Part(\n", - " function_response=glm.FunctionResponse(name=\"find_theaters\", response=s)\n", - ")\n", - "\n", - "# Build the message history\n", - "messages = [\n", - " # fmt: off\n", - " {\"role\": \"user\",\n", - " \"parts\": [\"Which theaters in Mountain View show the Barbie movie?.\"]},\n", - " {\"role\": \"model\",\n", - " \"parts\": response.candidates[0].content.parts},\n", - " {\"role\": \"user\",\n", - " \"parts\": [function_response]},\n", - " # fmt: on\n", - "]\n", - "\n", - "# Generate the next response\n", - "response = model.generate_content(messages)\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "EuwKoNIhGBJN" - }, - "source": [ - "## Parallel function calls\n", - "\n", - "The Gemini API can call multiple functions in a single turn. This caters for scenarios where there are multiple function calls that can take place independently to complete a task.\n", - "\n", - "First set the tools up. Unlike the movie example above, these functions do not require input from each other to be called so they should be good candidates for parallel calling." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "cJ-mSixWGqLv" - }, - "outputs": [], - "source": [ - "def power_disco_ball(power: bool) -> bool:\n", - " \"\"\"Powers the spinning disco ball.\"\"\"\n", - " print(f\"Disco ball is {'spinning!' if power else 'stopped.'}\")\n", - " return True\n", - "\n", - "\n", - "def start_music(energetic: bool, loud: bool, bpm: int) -> str:\n", - " \"\"\"Play some music matching the specified parameters.\n", - "\n", - " Args:\n", - " energetic: Whether the music is energetic or not.\n", - " loud: Whether the music is loud or not.\n", - " bpm: The beats per minute of the music.\n", - "\n", - " Returns: The name of the song being played.\n", - " \"\"\"\n", - " print(f\"Starting music! {energetic=} {loud=}, {bpm=}\")\n", - " return \"Never gonna give you up.\"\n", - "\n", - "\n", - "def dim_lights(brightness: float) -> bool:\n", - " \"\"\"Dim the lights.\n", - "\n", - " Args:\n", - " brightness: The brightness of the lights, 0.0 is off, 1.0 is full.\n", - " \"\"\"\n", - " print(f\"Lights are now set to {brightness:.0%}\")\n", - " return True" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zlrmXN7fxQi0" - }, - "source": [ - "Now call the model with an instruction that could use all of the specified tools." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "21ecYHLgIsCl" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "power_disco_ball(power=True)\n", - "start_music(energetic=True, loud=True, bpm=120.0)\n", - "dim_lights(brightness=0.3)\n" - ] - } - ], - "source": [ - "# Set the model up with tools.\n", - "house_fns = [power_disco_ball, start_music, dim_lights]\n", - "# Try this out with Pro and Flash...\n", - "model = genai.GenerativeModel(model_name=\"gemini-1.5-pro-latest\", tools=house_fns)\n", - "\n", - "# Call the API.\n", - "chat = model.start_chat()\n", - "response = chat.send_message(\"Turn this place into a party!\")\n", - "\n", - "# Print out each of the function calls requested from this single call.\n", - "for part in response.parts:\n", - " if fn := part.function_call:\n", - " args = \", \".join(f\"{key}={val}\" for key, val in fn.args.items())\n", - " print(f\"{fn.name}({args})\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "t6iYpty7yZct" - }, - "source": [ - "Each of the printed results reflects a single function call that the model has requested. To send the results back, include the responses in the same order as they were requested." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "L7RxoiR3foBR" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Let's get this party started! I've turned on the disco ball, started playing some upbeat music, and dimmed the lights. 🎢✨ Get ready to dance! πŸ•ΊπŸ’ƒ \n", - "\n", - "\n" - ] - } - ], - "source": [ - "import google.ai.generativelanguage as glm\n", - "\n", - "# Simulate the responses from the specified tools.\n", - "responses = {\n", - " \"power_disco_ball\": True,\n", - " \"start_music\": \"Never gonna give you up.\",\n", - " \"dim_lights\": True,\n", - "}\n", - "\n", - "# Build the response parts.\n", - "response_parts = [\n", - " glm.Part(function_response=glm.FunctionResponse(name=fn, response={\"result\": val}))\n", - " for fn, val in responses.items()\n", - "]\n", - "\n", - "response = chat.send_message(response_parts)\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "e0a3173919ca" - }, - "source": [ - "## Next Steps" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "7c2f31504490" - }, - "source": [ - "Useful API references:\n", - "\n", - "- The [genai.GenerativeModel](https://ai.google.dev/api/python/google/generativeai/GenerativeModel) class\n", - " - Its [GenerativeModel.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method builds a [glm.GenerateContentRequest](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentRequest) behind the scenes.\n", - " - The request's `.tools` field contains a list of 1 [glm.Tool](https://ai.google.dev/api/python/google/ai/generativelanguage/Tool) object.\n", - " - The tool's `function_declarations` attribute contains a list of [FunctionDeclarations](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionDeclaration) objects.\n", - "- The [response](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse) may contain a [glm.FunctionCall](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall), in `response.candidates[0].contents.parts[0]`.\n", - "- if `enable_automatic_function_calling` is set the [genai.ChatSession](https://ai.google.dev/api/python/google/generativeai/ChatSession) executes the call, and sends back the [glm.FunctionResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse).\n", - "- In response to a [FunctionCall](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall) the model always expects a [FunctionResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse).\n", - "- If you reply manually using [chat.send_message](https://ai.google.dev/api/python/google/generativeai/ChatSession#send_message) or [model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) remember thart the API is stateless you have to send the whole conversation history (a list of [content](https://ai.google.dev/api/python/google/ai/generativelanguage/Content) objects), not just the last one containing the `FunctionResponse`." - ] - } - ], - "metadata": { - "colab": { - "name": "Function_calling.ipynb", - "toc_visible": true - }, - "google": { - "image_path": "/site-assets/images/share.png", - "keywords": [ - "examples", - "googleai", - "samplecode", - "python", - "embed", - "function" - ] - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: Function calling with Python" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lEXQ3OwKIa-O" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "df1767a3d1cc" + }, + "source": [ + "Function calling lets developers create a description of a function in their code, then pass that description to a language model in a request. The response from the model includes the name of a function that matches the description and the arguments to call it with. Function calling lets you use functions as tools in generative AI applications, and you can define more than one function within a single request.\n", + "\n", + "This notebook provides code examples to help you get started." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9OEoeosRTv-5" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai # Install the Python SDK" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TS9l5igubpHO" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "x-hHZfLZ7FfH" + }, + "source": [ + "## Set up your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ab9ASynfcIZn" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "\n", + "GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3f383614ec30" + }, + "source": [ + "## Function calling basics" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "b82c1aecb657" + }, + "source": [ + "To use function calling, pass a list of functions to the `tools` parameter when creating a [`GenerativeModel`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel). The model uses the function name, docstring, parameters, and parameter type annotations to decide if it needs the function to best answer a prompt.\n", + "\n", + "> Important: The SDK converts function parameter type annotations to a format the API understands (`glm.FunctionDeclaration`). The API only supports a limited selection of parameter types, and the Python SDK's automatic conversion only supports a subset of that: `AllowedTypes = int | float | bool | str | list['AllowedTypes'] | dict`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "42b27b02d2f5", + "tags": [] + }, + "outputs": [], + "source": [ + "def add(a: float, b: float):\n", + " \"\"\"returns a + b.\"\"\"\n", + " return a + b\n", + "\n", + "\n", + "def subtract(a: float, b: float):\n", + " \"\"\"returns a - b.\"\"\"\n", + " return a - b\n", + "\n", + "\n", + "def multiply(a: float, b: float):\n", + " \"\"\"returns a * b.\"\"\"\n", + " return a * b\n", + "\n", + "\n", + "def divide(a: float, b: float):\n", + " \"\"\"returns a / b.\"\"\"\n", + " return a / b\n", + "\n", + "\n", + "model = genai.GenerativeModel(\n", + " model_name=\"gemini-1.5-flash-latest\", tools=[add, subtract, multiply, divide]\n", + ")\n", + "\n", + "model" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "UzUgtaY99BTg" + }, + "source": [ + "## Automatic function calling" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "d5fd91032a1e" + }, + "source": [ + "Function calls naturally fit in to [multi-turn chats](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#multi-turn) as they capture a back and forth interaction between the user and model. The Python SDK's [`ChatSession`](https://ai.google.dev/api/python/google/generativeai/ChatSession) is a great interface for chats because handles the conversation history for you, and using the parameter `enable_automatic_function_calling` simplifies function calling even further:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "d3b91c855257", + "tags": [] + }, + "outputs": [], + "source": [ + "chat = model.start_chat(enable_automatic_function_calling=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "1481a6159399" + }, + "source": [ + "With automatic function calling enabled, `ChatSession.send_message` automatically calls your function if the model asks it to.\n", + "\n", + "In the following example, the result appears to simply be a text response containing the correct answer:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "81d8def3d865", + "tags": [] + }, + "outputs": [], + "source": [ + "response = chat.send_message(\n", + " \"I have 57 cats, each owns 44 mittens, how many mittens is that in total?\"\n", + ")\n", + "response.text" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "951c0f83f72e", + "tags": [] + }, + "outputs": [], + "source": [ + "57 * 44" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "7731e35f2383" + }, + "source": [ + "However, by examining the chat history, you can see the flow of the conversation and how function calls are integrated within it.\n", + "\n", + "The `ChatSession.history` property stores a chronological record of the conversation between the user and the Gemini model. Each turn in the conversation is represented by a [`glm.Content`](https://ai.google.dev/api/python/google/ai/generativelanguage/Content) object, which contains the following information:\n", + "\n", + "* **Role**: Identifies whether the content originated from the \"user\" or the \"model\".\n", + "* **Parts**: A list of [`glm.Part`](https://ai.google.dev/api/python/google/ai/generativelanguage/Part) objects that represent individual components of the message. With a text-only model, these parts can be:\n", + " * **Text**: Plain text messages.\n", + " * **Function Call** ([`glm.FunctionCall`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall)): A request from the model to execute a specific function with provided arguments.\n", + " * **Function Response** ([`glm.FunctionResponse`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse)): The result returned by the user after executing the requested function.\n", + "\n", + " In the previous example with the mittens calculation, the history shows the following sequence:\n", + "\n", + "1. **User**: Asks the question about the total number of mittens.\n", + "1. **Model**: Determines that the multiply function is helpful and sends a FunctionCall request to the user.\n", + "1. **User**: The `ChatSession` automatically executes the function (due to `enable_automatic_function_calling` being set) and sends back a `FunctionResponse` with the calculated result.\n", + "1. **Model**: Uses the function's output to formulate the final answer and presents it as a text response." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9f7eff1e8e60", + "tags": [] + }, + "outputs": [], + "source": [ + "for content in chat.history:\n", + " print(content.role, \"->\", [type(part).to_dict(part) for part in content.parts])\n", + " print(\"-\" * 80)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2471fd72f05e" + }, + "source": [ + "In general the state diagram is:\n", + "\n", + "\"The\n", + "\n", + "The model can respond with multiple function calls before returning a text response, and function calls come before the text response." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "eea8e3a0b89f" + }, + "source": [ + "## Manual function calling" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9610f3465a69" + }, + "source": [ + "For more control, you can process [`glm.FunctionCall`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall) requests from the model yourself. This would be the case if:\n", + "\n", + "- You use a `ChatSession` with the default `enable_automatic_function_calling=False`.\n", + "- You use `GenerativeModel.generate_content` (and manage the chat history yourself)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "34ffab0bf365" + }, + "source": [ + "The following example is a rough equivalent of the [function calling single-turn curl sample](https://ai.google.dev/docs/function_calling#function-calling-single-turn-curl-sample) in Python. It uses functions that return (mock) movie playtime information, possibly from a hypothetical API:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "46ba0fa3d09a", + "tags": [] + }, + "outputs": [], + "source": [ + "def find_movies(description: str, location: str = \"\"):\n", + " \"\"\"find movie titles currently playing in theaters based on any description, genre, title words, etc.\n", + "\n", + " Args:\n", + " description: Any kind of description including category or genre, title words, attributes, etc.\n", + " location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n", + " \"\"\"\n", + " return [\"Barbie\", \"Oppenheimer\"]\n", + "\n", + "\n", + "def find_theaters(location: str, movie: str = \"\"):\n", + " \"\"\"Find theaters based on location and optionally movie title which are is currently playing in theaters.\n", + "\n", + " Args:\n", + " location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n", + " movie: Any movie title\n", + " \"\"\"\n", + " return [\"Googleplex 16\", \"Android Theatre\"]\n", + "\n", + "\n", + "def get_showtimes(location: str, movie: str, theater: str, date: str):\n", + " \"\"\"\n", + " Find the start times for movies playing in a specific theater.\n", + "\n", + " Args:\n", + " location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n", + " movie: Any movie title\n", + " thearer: Name of the theater\n", + " date: Date for requested showtime\n", + " \"\"\"\n", + " return [\"10:00\", \"11:00\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Ck-hdu5N8VlR" + }, + "source": [ + "Use a dictionary to make looking up functions by name easier later on. You can also use it to pass the array of functions to the `tools` parameter of `GenerativeModel`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "8i3SKdy18WHu", + "tags": [] + }, + "outputs": [], + "source": [ + "functions = {\n", + " \"find_movies\": find_movies,\n", + " \"find_theaters\": find_theaters,\n", + " \"get_showtimes\": get_showtimes,\n", + "}\n", + "\n", + "model = genai.GenerativeModel(model_name=\"gemini-1.5-flash-latest\", tools=functions.values())" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "11631c6e2b10" + }, + "source": [ + "After using `generate_content()` to ask a question, the model requests a `function_call`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "5e3b9c84d883", + "tags": [] + }, + "outputs": [], + "source": [ + "response = model.generate_content(\n", + " \"Which theaters in Mountain View show the Barbie movie?\"\n", + ")\n", + "response.candidates[0].content.parts" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kuldoypuAC1i" + }, + "source": [ + "Since this is not using a `ChatSession` with automatic function calling, you have to call the function yourself.\n", + "\n", + "A very simple way to do this would be with `if` statements:\n", + "\n", + "```python\n", + "if function_call.name == 'find_theaters':\n", + " find_theaters(**function_call.args)\n", + "elif ...\n", + "```\n", + "\n", + "However, since you already made the `functions` dictionary, this can be simplified to:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "rjkZ8MA00Coc", + "tags": [] + }, + "outputs": [], + "source": [ + "def call_function(function_call, functions):\n", + " function_name = function_call.name\n", + " function_args = function_call.args\n", + " return functions[function_name](**function_args)\n", + "\n", + "\n", + "part = response.candidates[0].content.parts[0]\n", + "\n", + "# Check if it's a function call; in real use you'd need to also handle text\n", + "# responses as you won't know what the model will respond with.\n", + "if part.function_call:\n", + " result = call_function(part.function_call, functions)\n", + "\n", + "print(result)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "XLWrHOatBtRz" + }, + "source": [ + "Finally, pass the response plus the message history to the next `generate_content()` call to get a final text response from the model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "gdb62GstAD_3", + "tags": [] + }, + "outputs": [], + "source": [ + "import google.ai.generativelanguage as glm\n", + "from google.protobuf.struct_pb2 import Struct\n", + "\n", + "# Put the result in a protobuf Struct\n", + "s = Struct()\n", + "s.update({\"result\": result})\n", + "\n", + "# Update this after https://github.com/google/generative-ai-python/issues/243\n", + "function_response = glm.Part(\n", + " function_response=glm.FunctionResponse(name=\"find_theaters\", response=s)\n", + ")\n", + "\n", + "# Build the message history\n", + "messages = [\n", + " # fmt: off\n", + " {\"role\": \"user\",\n", + " \"parts\": [\"Which theaters in Mountain View show the Barbie movie?.\"]},\n", + " {\"role\": \"model\",\n", + " \"parts\": response.candidates[0].content.parts},\n", + " {\"role\": \"user\",\n", + " \"parts\": [function_response]},\n", + " # fmt: on\n", + "]\n", + "\n", + "# Generate the next response\n", + "response = model.generate_content(messages)\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EuwKoNIhGBJN" + }, + "source": [ + "## Parallel function calls\n", + "\n", + "The Gemini API can call multiple functions in a single turn. This caters for scenarios where there are multiple function calls that can take place independently to complete a task.\n", + "\n", + "First set the tools up. Unlike the movie example above, these functions do not require input from each other to be called so they should be good candidates for parallel calling." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "cJ-mSixWGqLv", + "tags": [] + }, + "outputs": [], + "source": [ + "def power_disco_ball(power: bool) -> bool:\n", + " \"\"\"Powers the spinning disco ball.\"\"\"\n", + " print(f\"Disco ball is {'spinning!' if power else 'stopped.'}\")\n", + " return True\n", + "\n", + "\n", + "def start_music(energetic: bool, loud: bool, bpm: int) -> str:\n", + " \"\"\"Play some music matching the specified parameters.\n", + "\n", + " Args:\n", + " energetic: Whether the music is energetic or not.\n", + " loud: Whether the music is loud or not.\n", + " bpm: The beats per minute of the music.\n", + "\n", + " Returns: The name of the song being played.\n", + " \"\"\"\n", + " print(f\"Starting music! {energetic=} {loud=}, {bpm=}\")\n", + " return \"Never gonna give you up.\"\n", + "\n", + "\n", + "def dim_lights(brightness: float) -> bool:\n", + " \"\"\"Dim the lights.\n", + "\n", + " Args:\n", + " brightness: The brightness of the lights, 0.0 is off, 1.0 is full.\n", + " \"\"\"\n", + " print(f\"Lights are now set to {brightness:.0%}\")\n", + " return True" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zlrmXN7fxQi0" + }, + "source": [ + "Now call the model with an instruction that could use all of the specified tools." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "21ecYHLgIsCl", + "tags": [] + }, + "outputs": [], + "source": [ + "# Set the model up with tools.\n", + "house_fns = [power_disco_ball, start_music, dim_lights]\n", + "# Try this out with Pro and Flash...\n", + "model = genai.GenerativeModel(model_name=\"gemini-1.5-flash-latest\", tools=house_fns)\n", + "\n", + "# Call the API.\n", + "chat = model.start_chat()\n", + "response = chat.send_message(\"Turn this place into a party!\")\n", + "\n", + "# Print out each of the function calls requested from this single call.\n", + "for part in response.parts:\n", + " if fn := part.function_call:\n", + " args = \", \".join(f\"{key}={val}\" for key, val in fn.args.items())\n", + " print(f\"{fn.name}({args})\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "t6iYpty7yZct" + }, + "source": [ + "Each of the printed results reflects a single function call that the model has requested. To send the results back, include the responses in the same order as they were requested." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "L7RxoiR3foBR", + "tags": [] + }, + "outputs": [], + "source": [ + "import google.ai.generativelanguage as glm\n", + "\n", + "# Simulate the responses from the specified tools.\n", + "responses = {\n", + " \"power_disco_ball\": True,\n", + " \"start_music\": \"Never gonna give you up.\",\n", + " \"dim_lights\": True,\n", + "}\n", + "\n", + "# Build the response parts.\n", + "response_parts = [\n", + " glm.Part(function_response=glm.FunctionResponse(name=fn, response={\"result\": val}))\n", + " for fn, val in responses.items()\n", + "]\n", + "\n", + "response = chat.send_message(response_parts)\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "e0a3173919ca" + }, + "source": [ + "## Next Steps" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "7c2f31504490" + }, + "source": [ + "Useful API references:\n", + "\n", + "- The [genai.GenerativeModel](https://ai.google.dev/api/python/google/generativeai/GenerativeModel) class\n", + " - Its [GenerativeModel.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method builds a [glm.GenerateContentRequest](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentRequest) behind the scenes.\n", + " - The request's `.tools` field contains a list of 1 [glm.Tool](https://ai.google.dev/api/python/google/ai/generativelanguage/Tool) object.\n", + " - The tool's `function_declarations` attribute contains a list of [FunctionDeclarations](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionDeclaration) objects.\n", + "- The [response](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse) may contain a [glm.FunctionCall](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall), in `response.candidates[0].contents.parts[0]`.\n", + "- if `enable_automatic_function_calling` is set the [genai.ChatSession](https://ai.google.dev/api/python/google/generativeai/ChatSession) executes the call, and sends back the [glm.FunctionResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse).\n", + "- In response to a [FunctionCall](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall) the model always expects a [FunctionResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse).\n", + "- If you reply manually using [chat.send_message](https://ai.google.dev/api/python/google/generativeai/ChatSession#send_message) or [model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) remember thart the API is stateless you have to send the whole conversation history (a list of [content](https://ai.google.dev/api/python/google/ai/generativelanguage/Content) objects), not just the last one containing the `FunctionResponse`." + ] + } + ], + "metadata": { + "colab": { + "name": "Function_calling.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "google": { + "image_path": "/site-assets/images/share.png", + "keywords": [ + "examples", + "googleai", + "samplecode", + "python", + "embed", + "function" + ] + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/Function_calling_config.ipynb b/quickstarts/Function_calling_config.ipynb index 76a86f77e..2a49d36bf 100644 --- a/quickstarts/Function_calling_config.ipynb +++ b/quickstarts/Function_calling_config.ipynb @@ -1,349 +1,325 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IDS9Xcj_8k-T" - }, - "source": [ - "# Gemini API: Function calling config\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "1e41a2ce62eb" - }, - "source": [ - "Specifying a `function_calling_config` allows you to control how the Gemini API acts when `tools` have been specified. For example, you can choose to only allow free-text output (disabling function calling), force it to choose from a subset of the functions provided in `tools`, or let it act automatically.\n", - "\n", - "This guide assumes you are already familiar with function calling. For an introduction, check out the [docs](https://ai.google.dev/docs/function_calling)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "m4DhA4907Asz" - }, - "outputs": [], - "source": [ - "!pip install -qU 'google-generativeai>=0.5'" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "aU-mY9hi8pQh" - }, - "source": [ - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/gemini-api-cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "wp3W4Pdf8rBO" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "import google.generativeai as genai\n", - "\n", - "genai.configure(api_key=userdata.get(\"GOOGLE_API_KEY\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "iJqil-VL8ug-" - }, - "source": [ - "## Set up a model with tools\n", - "\n", - "This example uses 3 functions that control a simple hypothetical lighting system. Using these functions requires them to be called in a specific order. For example, you must turn the light system on before you can change color.\n", - "\n", - "While you can pass these directly to the model and let it try to call them correctly, specifying the `function_calling_config` gives you precise control over the functions that are available to the model." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "gLS26n7A9l9B" - }, - "outputs": [], - "source": [ - "def enable_lights():\n", - " \"\"\"Turn on the lighting system.\"\"\"\n", - " print(\"LIGHTBOT: Lights enabled.\")\n", - "\n", - "\n", - "def set_light_color(rgb_hex: str):\n", - " \"\"\"Set the light color. Lights must be enabled for this to work.\"\"\"\n", - " print(f\"LIGHTBOT: Lights set to {rgb_hex}.\")\n", - "\n", - "\n", - "def stop_lights():\n", - " \"\"\"Stop flashing lights.\"\"\"\n", - " print(\"LIGHTBOT: Lights turned off.\")\n", - "\n", - "\n", - "light_controls = [enable_lights, set_light_color, stop_lights]\n", - "instruction = \"You are a helpful lighting system bot. You can turn lights on and off, and you can set the color. Do not perform any other tasks.\"\n", - "\n", - "model = genai.GenerativeModel(\n", - " \"models/gemini-1.5-pro-latest\", tools=light_controls, system_instruction=instruction\n", - ")\n", - "\n", - "chat = model.start_chat()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "JqROCznFCj_Y" - }, - "source": [ - "Create a helper function for setting `function_calling_config` on `tool_config`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "_QgLFPL4Chon" - }, - "outputs": [], - "source": [ - "from google.generativeai.types import content_types\n", - "from collections.abc import Iterable\n", - "\n", - "\n", - "def tool_config_from_mode(mode: str, fns: Iterable[str] = ()):\n", - " \"\"\"Create a tool config with the specified function calling mode.\"\"\"\n", - " return content_types.to_tool_config(\n", - " {\"function_calling_config\": {\"mode\": mode, \"allowed_function_names\": fns}}\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ofMEuh_MFdMf" - }, - "source": [ - "## Text-only mode: `NONE`\n", - "\n", - "If you have provided the model with tools, but do not want to use those tools for the current conversational turn, then specify `NONE` as the mode. `NONE` tells the model not to make any function calls, and will behave as though none have been provided." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "6ZlIFwXqGA09" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hello! As a lighting system, I can turn lights on and off, and I can change the color of the lights. What would you like me to do today? \n", - "\n" - ] - } - ], - "source": [ - "tool_config = tool_config_from_mode(\"none\")\n", - "\n", - "response = chat.send_message(\n", - " \"Hello light-bot, what can you do?\", tool_config=tool_config\n", - ")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "uux063sjHZ_Z" - }, - "source": [ - "## Automatic mode: `AUTO`\n", - "\n", - "To allow the model to decide whether to respond in text or call specific functions, you can specify `AUTO` as the mode." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "vwO9dUjvHoT8" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "function_call {\n", - " name: \"enable_lights\"\n", - " args {\n", - " }\n", - "}\n", - "\n" - ] - } - ], - "source": [ - "tool_config = tool_config_from_mode(\"auto\")\n", - "\n", - "response = chat.send_message(\"Light this place up!\", tool_config=tool_config)\n", - "print(response.parts[0])\n", - "chat.rewind(); # We're not actually calling the function, so remove this from the history." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "oHhaO-P9CBPb" - }, - "source": [ - "## Function-calling mode: `ANY`\n", - "\n", - "Setting the mode to `ANY` will force the model to make a function call. By setting `allowed_function_names`, the model will only choose from those functions. If it is not set, all of the functions in `tools` are candidates for function calling.\n", - "\n", - "In this example system, if the lights are already on, then the user can change color or turn the lights off." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "GQpz94zrCNJF" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "function_call {\n", - " name: \"set_light_color\"\n", - " args {\n", - " fields {\n", - " key: \"rgb_hex\"\n", - " value {\n", - " string_value: \"#800080\"\n", - " }\n", - " }\n", - " }\n", - "}\n", - "\n" - ] - } - ], - "source": [ - "available_fns = [\"set_light_color\", \"stop_lights\"]\n", - "\n", - "tool_config = tool_config_from_mode(\"any\", available_fns)\n", - "\n", - "response = chat.send_message(\"Make this place PURPLE!\", tool_config=tool_config)\n", - "print(response.parts[0])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "8cGrRy-uJ7-J" - }, - "source": [ - "## Automatic function calling\n", - "\n", - "`tool_config` works when enabling automatic function calling too." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "hx7aIX8OXvi6" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LIGHTBOT: Lights enabled.\n" - ] - } - ], - "source": [ - "available_fns = [\"enable_lights\"]\n", - "tool_config = tool_config_from_mode(\"any\", available_fns)\n", - "\n", - "auto_chat = model.start_chat(enable_automatic_function_calling=True)\n", - "auto_chat.send_message(\"It's awful dark in here...\", tool_config=tool_config);" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kz8McBZfXg0N" - }, - "source": [ - "## Further reading\n", - "\n", - "Check out the function calling [quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Function_calling.ipynb) for an introduction to function calling. You can find another fun function calling example [here](https://github.com/google-gemini/cookbook/blob/main/quickstarts/rest/Function_calling_REST.ipynb) using curl.\n" - ] - } - ], - "metadata": { - "colab": { - "name": "Function_calling_config.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] }, - "nbformat": 4, - "nbformat_minor": 0 + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IDS9Xcj_8k-T" + }, + "source": [ + "# Gemini API: Function calling config\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "1e41a2ce62eb" + }, + "source": [ + "Specifying a `function_calling_config` allows you to control how the Gemini API acts when `tools` have been specified. For example, you can choose to only allow free-text output (disabling function calling), force it to choose from a subset of the functions provided in `tools`, or let it act automatically.\n", + "\n", + "This guide assumes you are already familiar with function calling. For an introduction, check out the [docs](https://ai.google.dev/docs/function_calling)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "m4DhA4907Asz" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "aU-mY9hi8pQh" + }, + "source": [ + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/gemini-api-cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "wp3W4Pdf8rBO" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "import google.generativeai as genai\n", + "\n", + "genai.configure(api_key=userdata.get(\"GOOGLE_API_KEY\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "iJqil-VL8ug-" + }, + "source": [ + "## Set up a model with tools\n", + "\n", + "This example uses 3 functions that control a simple hypothetical lighting system. Using these functions requires them to be called in a specific order. For example, you must turn the light system on before you can change color.\n", + "\n", + "While you can pass these directly to the model and let it try to call them correctly, specifying the `function_calling_config` gives you precise control over the functions that are available to the model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "gLS26n7A9l9B", + "tags": [] + }, + "outputs": [], + "source": [ + "def enable_lights():\n", + " \"\"\"Turn on the lighting system.\"\"\"\n", + " print(\"LIGHTBOT: Lights enabled.\")\n", + "\n", + "\n", + "def set_light_color(rgb_hex: str):\n", + " \"\"\"Set the light color. Lights must be enabled for this to work.\"\"\"\n", + " print(f\"LIGHTBOT: Lights set to {rgb_hex}.\")\n", + "\n", + "\n", + "def stop_lights():\n", + " \"\"\"Stop flashing lights.\"\"\"\n", + " print(\"LIGHTBOT: Lights turned off.\")\n", + "\n", + "\n", + "light_controls = [enable_lights, set_light_color, stop_lights]\n", + "instruction = \"You are a helpful lighting system bot. You can turn lights on and off, and you can set the color. Do not perform any other tasks.\"\n", + "\n", + "model = genai.GenerativeModel(\n", + " \"models/gemini-1.5-pro-latest\", tools=light_controls, system_instruction=instruction\n", + ")\n", + "\n", + "chat = model.start_chat()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JqROCznFCj_Y" + }, + "source": [ + "Create a helper function for setting `function_calling_config` on `tool_config`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "_QgLFPL4Chon", + "tags": [] + }, + "outputs": [], + "source": [ + "from google.generativeai.types import content_types\n", + "from collections.abc import Iterable\n", + "\n", + "\n", + "def tool_config_from_mode(mode: str, fns: Iterable[str] = ()):\n", + " \"\"\"Create a tool config with the specified function calling mode.\"\"\"\n", + " return content_types.to_tool_config(\n", + " {\"function_calling_config\": {\"mode\": mode, \"allowed_function_names\": fns}}\n", + " )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ofMEuh_MFdMf" + }, + "source": [ + "## Text-only mode: `NONE`\n", + "\n", + "If you have provided the model with tools, but do not want to use those tools for the current conversational turn, then specify `NONE` as the mode. `NONE` tells the model not to make any function calls, and will behave as though none have been provided." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "6ZlIFwXqGA09", + "tags": [] + }, + "outputs": [], + "source": [ + "tool_config = tool_config_from_mode(\"none\")\n", + "\n", + "response = chat.send_message(\n", + " \"Hello light-bot, what can you do?\", tool_config=tool_config\n", + ")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "uux063sjHZ_Z" + }, + "source": [ + "## Automatic mode: `AUTO`\n", + "\n", + "To allow the model to decide whether to respond in text or call specific functions, you can specify `AUTO` as the mode." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "vwO9dUjvHoT8", + "tags": [] + }, + "outputs": [], + "source": [ + "tool_config = tool_config_from_mode(\"auto\")\n", + "\n", + "response = chat.send_message(\"Light this place up!\", tool_config=tool_config)\n", + "print(response.parts[0])\n", + "chat.rewind(); # We're not actually calling the function, so remove this from the history." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "oHhaO-P9CBPb" + }, + "source": [ + "## Function-calling mode: `ANY`\n", + "\n", + "Setting the mode to `ANY` will force the model to make a function call. By setting `allowed_function_names`, the model will only choose from those functions. If it is not set, all of the functions in `tools` are candidates for function calling.\n", + "\n", + "In this example system, if the lights are already on, then the user can change color or turn the lights off." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "GQpz94zrCNJF", + "tags": [] + }, + "outputs": [], + "source": [ + "available_fns = [\"set_light_color\", \"stop_lights\"]\n", + "\n", + "tool_config = tool_config_from_mode(\"any\", available_fns)\n", + "\n", + "response = chat.send_message(\"Make this place PURPLE!\", tool_config=tool_config)\n", + "print(response.parts[0])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8cGrRy-uJ7-J" + }, + "source": [ + "## Automatic function calling\n", + "\n", + "`tool_config` works when enabling automatic function calling too." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "hx7aIX8OXvi6", + "tags": [] + }, + "outputs": [], + "source": [ + "available_fns = [\"enable_lights\"]\n", + "tool_config = tool_config_from_mode(\"any\", available_fns)\n", + "\n", + "auto_chat = model.start_chat(enable_automatic_function_calling=True)\n", + "auto_chat.send_message(\"It's awful dark in here...\", tool_config=tool_config)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kz8McBZfXg0N" + }, + "source": [ + "## Further reading\n", + "\n", + "Check out the function calling [quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Function_calling.ipynb) for an introduction to function calling. You can find another fun function calling example [here](https://github.com/google-gemini/cookbook/blob/main/quickstarts/rest/Function_calling_REST.ipynb) using curl.\n" + ] + } + ], + "metadata": { + "colab": { + "name": "Function_calling_config.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/Gemini_Flash_Introduction.ipynb b/quickstarts/Gemini_Flash_Introduction.ipynb index e635ebcd1..94c2be420 100644 --- a/quickstarts/Gemini_Flash_Introduction.ipynb +++ b/quickstarts/Gemini_Flash_Introduction.ipynb @@ -1,494 +1,513 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "cDzZKCF4ea5n" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "cxsdQaqTeihY" - }, - "outputs": [], - "source": [ - "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "FjjEC1DHenXF" - }, - "source": [ - "# Gemini Flash Introduction" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "HQQSrHovfBan" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "1LEBXIg0fq83" - }, - "source": [ - "The Gemini 1.5 Flash is a new model from Gemini ecosystem providing better quality and lower latency for existing Gemini 1.0 Pro developers and users.\n", - "\n", - "It simplifies your tests and adoption due to feature parity with the currently available Gemini models.\n", - "\n", - "In this notebook you will experiment with different scenarios (including text, chat and multimodal examples) where the only change required is changing the model you want to interact with - all the code is simply the same." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZxjOSybzhS5F" - }, - "source": [ - "## Installing the latest version of the Gemini SDK" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "7WIjD40XBMEM" - }, - "outputs": [], - "source": [ - "!pip install -q -U google-generativeai # Install the Python SDK" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0DUxJvIwhWQI" - }, - "source": [ - "## Import the Gemini python SDK" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "kmyjiZKSBYej" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xvJsVuNQhcED" - }, - "source": [ - "## Set up your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "g3SXoJCLBpFs" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "pWLzoSm3xs5V" - }, - "source": [ - "## Working with text scenarios\n", - "\n", - "In the first scenario of this notebook, you will work with text only scenarios. You will send direct requests, in text format, to the Gemini API and handle the results. It will include the understanding the information for each model (including input and output limits) and working with mechanisms to count the tokens of your request.\n", - "\n", - "First pick which model version you want to experiment with selecting on the listbox below - The available models are:\n", - "\n", - "- `models/gemini-1.5-flash-latest`\n", - "- `models/gemini-1.5-pro-latest`\n", - "- `models/gemini-1.0-pro-latest`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "giFvfXMeUnyR" - }, - "outputs": [], - "source": [ - "version = 'models/gemini-1.5-flash-latest' # @param [\"models/gemini-1.5-flash-latest\", \"models/gemini-1.5-pro-latest\", \"models/gemini-1.0-pro-latest\"]\n", - "model = genai.GenerativeModel(version)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "W4CuxUizinbs" - }, - "source": [ - "Using `model.get_model()` method, you can explore details about the model, like `input_token_limit` and `output_token_limit`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "PAimDgd5ugKn" - }, - "outputs": [], - "source": [ - "model_info = genai.get_model(version)\n", - "print(f'{version} - input limit: {model_info.input_token_limit}, output limit: {model_info.output_token_limit}')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "u7GRPvW7jh7s" - }, - "source": [ - "You can also count the tokens of your input using the `model.count_tokens()` method:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "yscBZrjPu1zL" - }, - "outputs": [], - "source": [ - "prompt = \"What is artificial intelligence?\"\n", - "model.count_tokens(prompt)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "6vgBNqUajsQ2" - }, - "source": [ - "Then you can send your request prompt to Gemini API - Does not matter which model version you chose, the same request code is going to be used here:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "W1RWCdNPtTzd" - }, - "outputs": [], - "source": [ - "response = model.generate_content(prompt)\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "iEREbartxmXx" - }, - "source": [ - "## Working with chat scenarios\n", - "\n", - "The next experimentation is working with chats. Again, the first action is to pick which model you want to play with. As for the text example, you can pick one of the above:\n", - "- `models/gemini-1.5-flash-latest`\n", - "- `models/gemini-1.5-pro-latest`\n", - "- `models/gemini-1.0-pro-latest`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "E5WcsAIGvznk" - }, - "outputs": [], - "source": [ - "version = 'models/gemini-1.5-flash-latest' # @param [\"models/gemini-1.5-flash-latest\", \"models/gemini-1.5-pro-latest\", \"models/gemini-1.0-pro-latest\"]\n", - "model = genai.GenerativeModel(version)\n", - "chat = model.start_chat(history=[])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3hnEUnrik0D1" - }, - "source": [ - "Using `model.get_model()` method, you can explore details about the model, like `input_token_limit` and `output_token_limit`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "NX3xgV2NYggV" - }, - "outputs": [], - "source": [ - "model_info = genai.get_model(version)\n", - "print(f'{version} - input limit: {model_info.input_token_limit}, output limit: {model_info.output_token_limit}')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "T_RfgpAPk58V" - }, - "source": [ - "You can also count the tokens of your experiment using the `model.count_tokens()` method:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "y8Megh7SYm-7" - }, - "outputs": [], - "source": [ - "prompt = \"How can I start learning artificial intelligence?\"\n", - "model.count_tokens(prompt)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZIZyFu5tk-oW" - }, - "source": [ - "Then you can send your request prompt to the Gemini API - Does not matter which model version you chose, the same request code is going to be used here:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "rzUMuKSXvzhN" - }, - "outputs": [], - "source": [ - "response = chat.send_message(\"How can I start learning artificial intelligence?\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IB_88tt_lCmR" - }, - "source": [ - "The same way you can perform a tokens counting for your prompts, you can use it against your chat history too, using the same `model.count_tokens()` method:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "vrVI9zvqvzfI" - }, - "outputs": [], - "source": [ - "model.count_tokens(chat.history)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "vu8blCSpapTF" - }, - "source": [ - "## Working with multimodal scenarios\n", - "\n", - "Then finally you can experiment with a multimodal experiment - or, in other words, sending in the same request prompt different data modalities (like text and images together).\n", - "\n", - "You must first pick which model version you want to experiment with selecting on the listbox below - The available models are:\n", - "\n", - "- `models/gemini-1.5-flash-latest`\n", - "- `models/gemini-1.5-pro-latest`\n", - "- `models/gemini-pro-vision`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LfuCWtHetcuA" - }, - "outputs": [], - "source": [ - "version = 'models/gemini-1.5-flash-latest' # @param [\"models/gemini-1.5-flash-latest\", \"models/gemini-1.5-pro-latest\", \"models/gemini-pro-vision\"]\n", - "model = genai.GenerativeModel(version)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZYlc6EZhmR4W" - }, - "source": [ - "Using `model.get_model()` method, you can explore details about the model, like `input_token_limit` and `output_token_limit`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "YOQVyY7XavyR" - }, - "outputs": [], - "source": [ - "model_info = genai.get_model(version)\n", - "print(f'{version} - input limit: {model_info.input_token_limit}, output limit: {model_info.output_token_limit}')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "aeug2Lk3mXV5" - }, - "source": [ - "Now you will pick a test image to be used on your multimodal prompt. Here you will use a sample croissant image:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Ur7rfzAbbIcQ" - }, - "outputs": [], - "source": [ - "import PIL\n", - "from IPython.display import display, Image\n", - "\n", - "!curl -s -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/croissant.jpg\"\n", - "img = PIL.Image.open('image.jpg')\n", - "display(Image('image.jpg', width=300))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nOnmWlsimfGR" - }, - "source": [ - "As you did for the text and chat prompts, you can perform a tokens counting for your image as well. Here you will show first the image resolution (using `img.size`) and then the amount of tokens that represent the image, using `model.cout_tokens()` method:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "HXMvnNALbmWP" - }, - "outputs": [], - "source": [ - "print(img.size)\n", - "print(model.count_tokens(img))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "D3ziijDAm6VE" - }, - "source": [ - "Now it is time to define the text prompt to be sent together with your test image - in this case, you will send a request to extract some information from the image, like what is in the image, which country the item in the image is related and what is the best pairing for the item." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "mGh0OwvYlLEW" - }, - "outputs": [], - "source": [ - "prompt = \"\"\"\n", - "Describe this image, including which country is famous for having this food and what is the best pairing for it.\n", - "\"\"\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "N2Inb0TRny4X" - }, - "outputs": [], - "source": [ - "response = model.generate_content([prompt, img])\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "sDrDAo1xnu9u" - }, - "source": [ - "## Learning more\n", - "\n", - "* To learn how use a model for prompting, see the [Prompting](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Prompting.ipynb) quickstart.\n", - "\n", - "* [count_tokens](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#count_tokens) Python API reference and [Count Tokens](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Counting_Tokens.ipynb) quickstart.\n", - "\n", - "* For more information on models, visit the [Gemini models](https://ai.google.dev/models/gemini) documentation." - ] - } - ], - "metadata": { - "colab": { - "name": "Gemini_Flash_Introduction.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "cDzZKCF4ea5n" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "cxsdQaqTeihY" + }, + "outputs": [], + "source": [ + "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FjjEC1DHenXF" + }, + "source": [ + "# Gemini Flash Introduction" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HQQSrHovfBan" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "1LEBXIg0fq83" + }, + "source": [ + "The Gemini 1.5 Flash is a new model from Gemini ecosystem providing better quality and lower latency for existing Gemini 1.0 Pro developers and users.\n", + "\n", + "It simplifies your tests and adoption due to feature parity with the currently available Gemini models.\n", + "\n", + "In this notebook you will experiment with different scenarios (including text, chat and multimodal examples) where the only change required is changing the model you want to interact with - all the code is simply the same." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZxjOSybzhS5F" + }, + "source": [ + "## Installing the latest version of the Gemini SDK" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "7WIjD40XBMEM" + }, + "outputs": [], + "source": [ + "!pip install -q -U google-generativeai # Install the Python SDK" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0DUxJvIwhWQI" + }, + "source": [ + "## Import the Gemini python SDK" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "kmyjiZKSBYej" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xvJsVuNQhcED" + }, + "source": [ + "## Set up your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "g3SXoJCLBpFs" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pWLzoSm3xs5V" + }, + "source": [ + "## Working with text scenarios\n", + "\n", + "In the first scenario of this notebook, you will work with text only scenarios. You will send direct requests, in text format, to the Gemini API and handle the results. It will include the understanding the information for each model (including input and output limits) and working with mechanisms to count the tokens of your request.\n", + "\n", + "First pick which model version you want to experiment with selecting on the listbox below - The available models are:\n", + "\n", + "- `models/gemini-1.5-flash-latest`\n", + "- `models/gemini-1.5-pro-latest`\n", + "- `models/gemini-1.0-pro-latest`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "giFvfXMeUnyR" + }, + "outputs": [], + "source": [ + "version = 'models/gemini-1.5-flash-latest' # @param [\"models/gemini-1.5-flash-latest\", \"models/gemini-1.5-pro-latest\", \"models/gemini-1.0-pro-latest\"]\n", + "model = genai.GenerativeModel(version)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "W4CuxUizinbs" + }, + "source": [ + "Using `model.get_model()` method, you can explore details about the model, like `input_token_limit` and `output_token_limit`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "PAimDgd5ugKn" + }, + "outputs": [], + "source": [ + "model_info = genai.get_model(version)\n", + "print(f'{version} - input limit: {model_info.input_token_limit}, output limit: {model_info.output_token_limit}')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "u7GRPvW7jh7s" + }, + "source": [ + "You can also count the tokens of your input using the `model.count_tokens()` method:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "yscBZrjPu1zL" + }, + "outputs": [], + "source": [ + "prompt = \"What is artificial intelligence?\"\n", + "model.count_tokens(prompt)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6vgBNqUajsQ2" + }, + "source": [ + "Then you can send your request prompt to Gemini API - Does not matter which model version you chose, the same request code is going to be used here:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "W1RWCdNPtTzd" + }, + "outputs": [], + "source": [ + "response = model.generate_content(prompt)\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "iEREbartxmXx" + }, + "source": [ + "## Working with chat scenarios\n", + "\n", + "The next experimentation is working with chats. Again, the first action is to pick which model you want to play with. As for the text example, you can pick one of the above:\n", + "- `models/gemini-1.5-flash-latest`\n", + "- `models/gemini-1.5-pro-latest`\n", + "- `models/gemini-1.0-pro-latest`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "E5WcsAIGvznk" + }, + "outputs": [], + "source": [ + "version = 'models/gemini-1.5-flash-latest' # @param [\"models/gemini-1.5-flash-latest\", \"models/gemini-1.5-pro-latest\", \"models/gemini-1.0-pro-latest\"]\n", + "model = genai.GenerativeModel(version)\n", + "chat = model.start_chat(history=[])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3hnEUnrik0D1" + }, + "source": [ + "Using `model.get_model()` method, you can explore details about the model, like `input_token_limit` and `output_token_limit`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "NX3xgV2NYggV" + }, + "outputs": [], + "source": [ + "model_info = genai.get_model(version)\n", + "print(f'{version} - input limit: {model_info.input_token_limit}, output limit: {model_info.output_token_limit}')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "T_RfgpAPk58V" + }, + "source": [ + "You can also count the tokens of your experiment using the `model.count_tokens()` method:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "y8Megh7SYm-7" + }, + "outputs": [], + "source": [ + "prompt = \"How can I start learning artificial intelligence?\"\n", + "model.count_tokens(prompt)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZIZyFu5tk-oW" + }, + "source": [ + "Then you can send your request prompt to the Gemini API - Does not matter which model version you chose, the same request code is going to be used here:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "rzUMuKSXvzhN" + }, + "outputs": [], + "source": [ + "response = chat.send_message(\"How can I start learning artificial intelligence?\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IB_88tt_lCmR" + }, + "source": [ + "The same way you can perform a tokens counting for your prompts, you can use it against your chat history too, using the same `model.count_tokens()` method:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "vrVI9zvqvzfI" + }, + "outputs": [], + "source": [ + "model.count_tokens(chat.history)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "vu8blCSpapTF" + }, + "source": [ + "## Working with multimodal scenarios\n", + "\n", + "Then finally you can experiment with a multimodal experiment - or, in other words, sending in the same request prompt different data modalities (like text and images together).\n", + "\n", + "You must first pick which model version you want to experiment with selecting on the listbox below - The available models are:\n", + "\n", + "- `models/gemini-1.5-flash-latest`\n", + "- `models/gemini-1.5-pro-latest`\n", + "- `models/gemini-pro-vision`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "LfuCWtHetcuA" + }, + "outputs": [], + "source": [ + "version = 'models/gemini-1.5-flash-latest' # @param [\"models/gemini-1.5-flash-latest\", \"models/gemini-1.5-pro-latest\", \"models/gemini-pro-vision\"]\n", + "model = genai.GenerativeModel(version)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZYlc6EZhmR4W" + }, + "source": [ + "Using `model.get_model()` method, you can explore details about the model, like `input_token_limit` and `output_token_limit`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "YOQVyY7XavyR" + }, + "outputs": [], + "source": [ + "model_info = genai.get_model(version)\n", + "print(f'{version} - input limit: {model_info.input_token_limit}, output limit: {model_info.output_token_limit}')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "aeug2Lk3mXV5" + }, + "source": [ + "Now you will pick a test image to be used on your multimodal prompt. Here you will use a sample croissant image:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Ur7rfzAbbIcQ" + }, + "outputs": [], + "source": [ + "import PIL\n", + "from IPython.display import display, Image\n", + "\n", + "!curl -s -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/croissant.jpg\"\n", + "img = PIL.Image.open('image.jpg')\n", + "display(Image('image.jpg', width=300))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nOnmWlsimfGR" + }, + "source": [ + "As you did for the text and chat prompts, you can perform a tokens counting for your image as well. Here you will show first the image resolution (using `img.size`) and then the amount of tokens that represent the image, using `model.cout_tokens()` method:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "HXMvnNALbmWP" + }, + "outputs": [], + "source": [ + "print(img.size)\n", + "print(model.count_tokens(img))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "D3ziijDAm6VE" + }, + "source": [ + "Now it is time to define the text prompt to be sent together with your test image - in this case, you will send a request to extract some information from the image, like what is in the image, which country the item in the image is related and what is the best pairing for the item." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "mGh0OwvYlLEW" + }, + "outputs": [], + "source": [ + "prompt = \"\"\"\n", + "Describe this image, including which country is famous for having this food and what is the best pairing for it.\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "N2Inb0TRny4X" + }, + "outputs": [], + "source": [ + "response = model.generate_content([prompt, img])\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "sDrDAo1xnu9u" + }, + "source": [ + "## Learning more\n", + "\n", + "* To learn how use a model for prompting, see the [Prompting](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Prompting.ipynb) quickstart.\n", + "\n", + "* [count_tokens](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#count_tokens) Python API reference and [Count Tokens](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Counting_Tokens.ipynb) quickstart.\n", + "\n", + "* For more information on models, visit the [Gemini models](https://ai.google.dev/models/gemini) documentation." + ] + } + ], + "metadata": { + "colab": { + "name": "Gemini_Flash_Introduction.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/JSON_mode.ipynb b/quickstarts/JSON_mode.ipynb index 6a102ce05..b4850a642 100644 --- a/quickstarts/JSON_mode.ipynb +++ b/quickstarts/JSON_mode.ipynb @@ -1,240 +1,214 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "893sOzyhJDma" - }, - "source": [ - "# Gemini API: JSON Mode Quickstart\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "h4LQoYRTJIP9" - }, - "source": [ - "This notebook demonstrates how to use JSON mode." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "id": "_PBH7eR9He0I" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m146.8/146.8 kB\u001b[0m \u001b[31m1.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m664.5/664.5 kB\u001b[0m \u001b[31m6.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", - "\u001b[?25h" - ] - } - ], - "source": [ - "!pip install -qU google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "id": "2zwIBNLWJvRf" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai\n", - "import json" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "F6gHNgcUypVN" - }, - "source": [ - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "id": "t0jy9XWjJwv7" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "vf42XN1KLcfV" - }, - "source": [ - "## Activate JSON mode" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dC5-79CDMJ3R" - }, - "source": [ - "Activate JSON mode by specifying `respose_mime_type` in the `generation_config` parameter." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "id": "WWq64FXSLXgr" - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel(\"gemini-1.5-pro-latest\",\n", - " generation_config={\"response_mime_type\": \"application/json\"})" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "id": "Y_djQzyyaCLg" - }, - "outputs": [], - "source": [ - "prompt = \"\"\"List a few popular cookie recipes using this JSON schema:\n", - "{'type': 'object', 'properties': { 'recipe_name': {'type': 'string'}}}\"\"\"" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "id": "aENeySrWMJN6" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\n", - " {\"recipe_name\": \"Chocolate Chip Cookies\"},\n", - " {\"recipe_name\": \"Peanut Butter Cookies\"},\n", - " {\"recipe_name\": \"Oatmeal Raisin Cookies\"},\n", - " {\"recipe_name\": \"Sugar Cookies\"},\n", - " {\"recipe_name\": \"Shortbread Cookies\"}\n", - "]\n", - "\n", - "\n" - ] - } - ], - "source": [ - "response = model.generate_content(prompt)\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "pqNsOE1YysLc" - }, - "source": [ - "Just for fun, parse the string to JSON, and then serialize it." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "id": "nb9Z9TdHRzTu" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\n", - " {\n", - " \"recipe_name\": \"Chocolate Chip Cookies\"\n", - " },\n", - " {\n", - " \"recipe_name\": \"Peanut Butter Cookies\"\n", - " },\n", - " {\n", - " \"recipe_name\": \"Oatmeal Raisin Cookies\"\n", - " },\n", - " {\n", - " \"recipe_name\": \"Sugar Cookies\"\n", - " },\n", - " {\n", - " \"recipe_name\": \"Shortbread Cookies\"\n", - " }\n", - "]\n" - ] - } - ], - "source": [ - "print(json.dumps(json.loads(response.text), indent=4))" - ] - } - ], - "metadata": { - "colab": { - "name": "JSON_mode.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "893sOzyhJDma" + }, + "source": [ + "# Gemini API: JSON Mode Quickstart\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "h4LQoYRTJIP9" + }, + "source": [ + "This notebook demonstrates how to use JSON mode." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "_PBH7eR9He0I" + }, + "outputs": [], + "source": [ + "!pip install -qU google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "2zwIBNLWJvRf", + "tags": [] + }, + "outputs": [], + "source": [ + "import google.generativeai as genai\n", + "import json" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "F6gHNgcUypVN" + }, + "source": [ + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "t0jy9XWjJwv7" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "vf42XN1KLcfV" + }, + "source": [ + "## Activate JSON mode" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dC5-79CDMJ3R" + }, + "source": [ + "Activate JSON mode by specifying `respose_mime_type` in the `generation_config` parameter." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "WWq64FXSLXgr", + "tags": [] + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel(\"gemini-1.5-pro-latest\",\n", + " generation_config={\"response_mime_type\": \"application/json\"})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Y_djQzyyaCLg", + "tags": [] + }, + "outputs": [], + "source": [ + "prompt = \"\"\"List a few popular cookie recipes using this JSON schema:\n", + "{'type': 'object', 'properties': { 'recipe_name': {'type': 'string'}}}\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "aENeySrWMJN6", + "scrolled": true, + "tags": [] + }, + "outputs": [], + "source": [ + "response = model.generate_content(prompt)\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pqNsOE1YysLc" + }, + "source": [ + "Just for fun, parse the string to JSON, and then serialize it." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "print(json.dumps(json.loads(response.text), indent=4))" + ] + } + ], + "metadata": { + "colab": { + "name": "JSON_mode.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/Models.ipynb b/quickstarts/Models.ipynb index ea8ae6ba5..a61f6163d 100644 --- a/quickstarts/Models.ipynb +++ b/quickstarts/Models.ipynb @@ -1,233 +1,256 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "L5Lv3UtGCFH4" - }, - "source": [ - "# Gemini API: List models\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nAJ9EGE2SoXm" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Gh9D-DvWSuqq" - }, - "source": [ - "This notebook demonstrates how to list the models that are available for you to use in the Gemini API, and how to find details about a model." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "i755jXzS5kLN" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "49H9jQPO_TJ9" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4ol10W6Q_Y-s" - }, - "source": [ - "## Configure your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "8PXsFZBQ_XA5" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "\n", - "GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3Al4lFhNB22n" - }, - "source": [ - "## List models\n", - "\n", - "Use `list_models()` to see what models are available. These models support `generateContent`, the main method used for prompting." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "3wE76b_gBn2k" - }, - "outputs": [], - "source": [ - "for m in genai.list_models():\n", - " if \"generateContent\" in m.supported_generation_methods:\n", - " print(m.name)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tlguLt1yKET9" - }, - "source": [ - "These models support `embedContent`, used for embeddings:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "lQmlIpr5JHqz" - }, - "outputs": [], - "source": [ - "for m in genai.list_models():\n", - " if \"embedContent\" in m.supported_generation_methods:\n", - " print(m.name)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nFJAyDD9QVrC" - }, - "source": [ - "## Find details about a model\n", - "\n", - "You can see more details about a model, including the `input_token_limit` and `output_token_limit` as follows." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "BYYxVE4ZnoGy" - }, - "outputs": [], - "source": [ - "for m in genai.list_models():\n", - " if m.name == \"models/gemini-1.5-pro-latest\":\n", - " print(m)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "00a56cb21953" - }, - "source": [ - "## Get model\n", - "\n", - "Use `get_model()` to retrieve the specific details of a model. You can iterate over all available models using `list_models()`, but if you already know the model name you can retrieve it directly with `get_model()`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "6786759016dc" - }, - "outputs": [], - "source": [ - "model_info = genai.get_model(\"models/aqa\")\n", - "print(model_info)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Tq7i5FAwCe1v" - }, - "source": [ - "## Learning more\n", - "\n", - "* To learn how use a model for prompting, see the [Prompting](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Prompting.ipynb) quickstart.\n", - "\n", - "* To learn how use a model for embedding, see the [Embedding](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Embeddings.ipynb) quickstart.\n", - "\n", - "* For more information on models, visit the [Gemini models](https://ai.google.dev/models/gemini) documentation." - ] - } - ], - "metadata": { - "colab": { - "name": "Models.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "L5Lv3UtGCFH4" + }, + "source": [ + "# Gemini API: List models\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nAJ9EGE2SoXm" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Gh9D-DvWSuqq" + }, + "source": [ + "This notebook demonstrates how to list the models that are available for you to use in the Gemini API, and how to find details about a model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "i755jXzS5kLN" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "49H9jQPO_TJ9" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4ol10W6Q_Y-s" + }, + "source": [ + "## Configure your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "8PXsFZBQ_XA5" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "\n", + "GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3Al4lFhNB22n" + }, + "source": [ + "## List models\n", + "\n", + "Use `list_models()` to see what models are available. These models support `generateContent`, the main method used for prompting." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "3wE76b_gBn2k", + "tags": [] + }, + "outputs": [], + "source": [ + "for m in genai.list_models():\n", + " if \"generateContent\" in m.supported_generation_methods:\n", + " print(m.name)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tlguLt1yKET9" + }, + "source": [ + "These models support `embedContent`, used for embeddings:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "lQmlIpr5JHqz", + "tags": [] + }, + "outputs": [], + "source": [ + "for m in genai.list_models():\n", + " if \"embedContent\" in m.supported_generation_methods:\n", + " print(m.name)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nFJAyDD9QVrC" + }, + "source": [ + "## Find details about a model\n", + "\n", + "You can see more details about a model, including the `input_token_limit` and `output_token_limit` as follows." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "BYYxVE4ZnoGy", + "tags": [] + }, + "outputs": [], + "source": [ + "for m in genai.list_models():\n", + " if m.name == \"models/gemini-1.5-flash-latest\":\n", + " print(m)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "00a56cb21953" + }, + "source": [ + "## Get model\n", + "\n", + "Use `get_model()` to retrieve the specific details of a model. You can iterate over all available models using `list_models()`, but if you already know the model name you can retrieve it directly with `get_model()`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "6786759016dc", + "tags": [] + }, + "outputs": [], + "source": [ + "model_info = genai.get_model(\"models/aqa\")\n", + "print(model_info)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Tq7i5FAwCe1v" + }, + "source": [ + "## Learning more\n", + "\n", + "* To learn how use a model for prompting, see the [Prompting](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Prompting.ipynb) quickstart.\n", + "\n", + "* To learn how use a model for embedding, see the [Embedding](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Embeddings.ipynb) quickstart.\n", + "\n", + "* For more information on models, visit the [Gemini models](https://ai.google.dev/models/gemini) documentation." + ] + } + ], + "metadata": { + "colab": { + "name": "Models.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/PDF_Files.ipynb b/quickstarts/PDF_Files.ipynb index e361369e3..255482047 100644 --- a/quickstarts/PDF_Files.ipynb +++ b/quickstarts/PDF_Files.ipynb @@ -1,571 +1,441 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dfsDR_omdNea" - }, - "source": [ - "# Gemini API - read a PDF\n", - "\n", - "This notebook demonstrates how you can convert a PDF file so that it can be read by the Gemini API.\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "FaqZItBdeokU" - }, - "source": [ - "## Setup" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": { - "id": "XKJ78ne3O0sB" - }, - "outputs": [], - "source": [ - "!pip install -Uq google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "id": "LUKlAk7iN_5e" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai\n", - "\n", - "\n", - "import pathlib\n", - "import tqdm\n", - "import os" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "id": "A9sUQ4WrP-Yr" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "genai.configure(api_key=userdata.get(\"GOOGLE_API_KEY\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "thYL8XGjerMa" - }, - "source": [ - "Install the PDF processing tools:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "id": "iK30_utL1DhY" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Reading package lists... Done\n", - "Building dependency tree... Done\n", - "Reading state information... Done\n", - "poppler-utils is already the newest version (22.02.0-2ubuntu0.3).\n", - "0 upgraded, 0 newly installed, 0 to remove and 45 not upgraded.\n" - ] - } - ], - "source": [ - "!apt install poppler-utils" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "jZj7pRt7exwE" - }, - "source": [ - "## Download and proces the PDF" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "WibRLdf2_Qoq" - }, - "source": [ - "This textbook is from OpenStax, it's License is Commons Attribution License v4.0. More detrails are [available on the site](https://openstax.org/details/books/university-physics-volume-2)." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "id": "fOYiHxN95iVn" - }, - "outputs": [], - "source": [ - "import pathlib" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "id": "xo8VsYaY6mgl" - }, - "outputs": [], - "source": [ - "if not pathlib.Path('test.pdf').exists():\n", - " !curl -o test.pdf https://assets.openstax.org/oscms-prodcms/media/documents/UniversityPhysicsVolume2-WEB_5eNhMSa.pdf" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3V-NRhife2CA" - }, - "source": [ - "You'll extract Chapter 3, pages [121-154]." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "id": "c6LD6PlpK3n8" - }, - "outputs": [], - "source": [ - "first = 121\n", - "last = 154" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": { - "id": "fH4WmrY_1MdQ" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "mkdir: cannot create directory β€˜output’: File exists\n", - "images-121.jpg\timages-133.jpg\timages-145.jpg\ttext-123.txt text-135.txt text-147.txt\n", - "images-122.jpg\timages-134.jpg\timages-146.jpg\ttext-124.txt text-136.txt text-148.txt\n", - "images-123.jpg\timages-135.jpg\timages-147.jpg\ttext-125.txt text-137.txt text-149.txt\n", - "images-124.jpg\timages-136.jpg\timages-148.jpg\ttext-126.txt text-138.txt text-150.txt\n", - "images-125.jpg\timages-137.jpg\timages-149.jpg\ttext-127.txt text-139.txt text-151.txt\n", - "images-126.jpg\timages-138.jpg\timages-150.jpg\ttext-128.txt text-140.txt text-152.txt\n", - "images-127.jpg\timages-139.jpg\timages-151.jpg\ttext-129.txt text-141.txt text-153.txt\n", - "images-128.jpg\timages-140.jpg\timages-152.jpg\ttext-130.txt text-142.txt text-154.txt\n", - "images-129.jpg\timages-141.jpg\timages-153.jpg\ttext-131.txt text-143.txt\n", - "images-130.jpg\timages-142.jpg\timages-154.jpg\ttext-132.txt text-144.txt\n", - "images-131.jpg\timages-143.jpg\ttext-121.txt\ttext-133.txt text-145.txt\n", - "images-132.jpg\timages-144.jpg\ttext-122.txt\ttext-134.txt text-146.txt\n" - ] - } - ], - "source": [ - "!mkdir output\n", - "! # extract images of Chapter 3\n", - "!pdftoppm test.pdf -f {first} -l {last} output/images -jpeg\n", - "!ls output" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "hmIj4eQlfFot" - }, - "source": [ - "Look at the first image, scaled down:" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": { - "id": "JGOg-cvK11IC" - }, - "outputs": [], - "source": [ - "import PIL.Image" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "id": "9b0MfUwc17Mk" - }, - "outputs": [ - { - "data": { - "image/png": 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LcBlos2ssEggJHpDBX61mSQA2nhj+j69/c+mCpW/6sxsBQIADJDlo5SozHjgEmi4ZSALmAXFgBOgAmOW6vigIEIgBqfKSpyq0ezJEVJZXKSUivobUVr0qksnkT3/60wMHDnied8stt1x44YV/7HZVqPB7cUZ7ElACgpbKpb/69S/k0zkGmibJZSC5ZEJwyQl9Ej1C4ZGoq639yIc/oqP5qwce+9lP/+eKN1y3YOECCVIiQ5I2OjowLnREAuYS05TWMpIoUDIuOMzUY0SQOuIJvgROxAhVGoL39DPP/fwXv/SjpnIJJHqaEIDMQyakt6hn/p+/511cM355//rPfO7zNQ11q6+8pK6qBqRBSBIFgSdA40RMArLpSo8ekwjESEcwQEqBgpBrpEqUAagKjETAfrNoqjfoPffc89RTT11zzTWXXnrpbPE982GMWZb1nve857777lNLent7K2pb4bXOGa22BMQ4K+QK//JP/1wsFF955campg9/4ENM002uAwBTxRGAcQQEZoDBARCRAwBoQDP2ITJgwKcjTzNRuROlFhBAm65CDgDajm0vfOOOO16uJRddsOY9730vES1ZsGjhwoXLly+PBsM4XaYWgTTC6VLowHRVphEROeg03d/nwFRa2XTtcdUWSZIhe+qpJ++++yfvfOc7V61a9XICqpavX7/+O9/5Tm1t7eWXX/7Kp+4MZN++fffdd9/atWu/9rWvAUBTU9Mfu0UVKvy+nNFqq2Smtrr6wV89aNu2EhFN07761a/ed999733ve2+++SZPCAAgST6fj2scACRKgOlK3eWyAprqfjP1N3+JmPLZezvh04mNUeiaDgBXXHHFRz/6UcexGTJCnJ7/gSAej0uSCHjO6lXbtm3jnOu6PrN3taXy/DcvToTDXuog4Cc3BxEQdu/e8x//8R/nnHPOOeec88oWq9qp9tqs1jg2NgYA8Xh80aJFf+y2VKjwv8MZ/SgiopTSMM01a9bMXv7LX/4SAObOnbt27brZy0+zD7qxsfGSSy455VfKVQoAPp8PXupF/Z1RW1AaGggEyktel6iXxJkcVKhQ4bflTFfbUwqK67oA4HneyesDAOe8/PmFF17Yu3evpmmLFy9esmQJETmOYxiG+lYFvnO53LZt244fP65p2sKFC5ctW1YO5Usp1dZOiVBm9amUVMXTC4XCsWPH/H7/nDlz1HLHcY4dOwYA3d3dnPNkMplIJKqrq6urq9WvJicnd+/e3d/fzznv7u5evny5z+cTQiDi6OhoMpl8/vnnAWBwcPDAgQMA0NHRYRjG7xC+JyIiYox5nrdz584DBw64rtvU1LR06dL6+nohhJRS0zTbto8dO2YYRkdHByKqHRFRNpsdHBysr6+vqamRUhIR55yIhoeHc7lcW1tbKHRiVV7P84hI0zREPHjw4O7du9PpdFNT04oVKxoaGtQeGWOFQmFkZKS/vx8AstnsgQMHhBBNTU3xePy3PcYKFc4s6DXIX//1XwPAP/3TP53y2z/90z8FgPvuu+8Tn/hE+TB9Pt8HP/jBUqnkeZ5SB8W99967ZMmS8mqIeP311x86dIiITlhzNl//+tcB4G1vexsRvdw6RLRly5ZAIHD55ZeXl4yMjLS3t/f09ExOTn7mM59pbW01DEMdiJTynnvumT9//uyrc8EFFzz33HNCiPJxAQDnnHOuaVowGNy9e/fL7f39738/APzjP/7jK5zJvr6+q6++evYem5ubv/zlLwshXNeVUubz+ZUrV7a2to6MjMz+4Ve+8pVAIPDe975XtVwIIYTwPO/iiy9uaGgYGho6+bQotR0fH3/ve98bDAbLe2xoaLjjjjvU7ojoZz/7GSKWj1Hp+3e+851XOIoKFV4TnNG27e/Dd7/73bGxsX/4h39oaGjYtWvXf/3Xf331q19tbGz86Ec/Wl7n3nvvvfnmmwOBwEc/+tGLLrrIsqyf/vSnd999d19f3/3339/a2kqv6AFQX73CCkKIYrGYz+dnL8zn84FA4JOf/OSdd97Z1tY2d+7curo6ANi2bds73/lOALj99ttXrVqVy+Uefvjh733vezfeeOPWrVsbGxsvuuiiQCCwcePG/fv3r1mzpqenh3MeiUSI6JWb8XIkEok3vvGNe/bsectb3vKGN7zBNM1NmzZ961vfuu2226qqqt7+9rdLKYPB4OLFi7du3bpr167Gxkb1QyJ68MEHi8XiY489lslkIpEIADDGjh8/vmXLlpUrV9bX15/S3s/lcm9729sefvjh1atXX3/99Q0NDQcPHvzv//7v2267LZPJfOYznyGi1tbWP//zPx8cHHz00UdbW1vXrVsnpezu7v5tj65ChTOOP67Y/268sm37lre8BQCuueaabDZbXnjXXXcxxubOnZvJZFSndWJioqurKxqNPvXUU7N//uEPfxgAbr31Vpoxx05GBcpvvPHG0dHRkZGR4RkGBweHhoZc11Wrbdq0CQAuuOCC8g9HRkbq6+s1Tbv22ms3b96cy+Usy1J7+dSnPgUAX/7yl2fv6Pvf//63v/1t27bLpuKtt94KAD/96U9/41n6jbbt6Ojo2rVrTziNd911FwCce+65lmWpJT/84Q8B4FOf+hTNGPLHjx+vrq6OxWKMsUcffbS8/Be/+AUAfPrTn365Pf7Lv/wLALzlLW8pFArlhUeOHFm0aJFhGBs3biwvfOSRRwDghhtu+I2HWaHCa4XX4XAd5U59+9vfHg6HpZRKCN74xje2t7f39/cPDQ0xxhDxgQceOHr06Dve8Y6LLrpo9s8/9KEP1dTU/OQnPxkdHX05p60y3B544IEFCxYsWLBg/vz58+fPV5/PP//8RCLxCs2TUgYCgS9/+ctnn312KBQyTVPtZWpqCgC6urrUakQkhHjb2972F3/xF5xzdSDlo3Mc5/c8S0RUX19///33f/jDH6YZbwAAXH755bW1tUePHs1ms2rNlStXmqb53HPP0UzM6vnnn5+amvrbv/1bzvlDDz1U3uZTTz0FACeENMsUCoVvf/vb4XD405/+dCAQUO88IcScOXM+/vGPO45z5513lle2bbt8sBUqvD54Haqt8vT5/f7ZC4PBYFNTk23buVxOLXn66afhVNLQ3Nzc3d09MTGhwlCvQDgcXrRo0aJFixbPsGTJkoULF07ne70MUspQKFRTU6P0tLx88eLFAPDP//zPW7ZssSxL+S4RUYXI6A8wPEFK6ff7VdiKMaZEPxAIhEIhy7LKbevs7Ozt7d2xY8fY2Jhqw0MPPaRcDd3d3Q8//LBKzhNCbNiwoa6urre3F06VTnDw4MEjR450d3d3dnaW34Jqg0uXLjVN85lnnikWp7OqX8fpFhX+z/I69Nuq51z9Ww7WM8ZUUlH5MR4YGACAT3ziE1/60pdUXx4AOOeMsT179gDAK5uoAHDFFVfcddddv4MO0oyndXYuwU033XTPPfc8+uijq1atWrhwYXd394oVKy6//PLVq1f/IYoGqG26rvv0008/+eSThw4dyuVyUkrP80ZGRgKBQHmPuq6vWbNmy5Yt+/fvb2xszOVyTzzxxDnnnNPZ2XnRRRf953/+58GDB3t7e4eHh/fs2bN27drq6upyAtxsRkZGyvoOsy4NACgbf2pqKplMquS2k8W6QoXXOq9D2/ZVohLIYrFYTU1NXV1dfX29ymeqrq6+4oor3vSmNzU2Nr6aZ/5/xQojokgk8rOf/eyrX/3qunXrUqnUgw8++JnPfOaSSy75+Mc//ofoUDPG8vn8u971rssuu+yOO+44fPhwPp8vlUrFYvHkI1q7di0APPfccwCwZ8+e/v7+yy67DAAuvfRSz/OeeeYZANi9e3ehUHi5BGSYyds7JSrVT2U1lJf83odYocKZxevQtn2V1NTUAMBnP/vZVxjYekob7QT+V/r4qlsdiUQ+8IEPfOADH0gmk2NjY4888shnP/vZL37xi+vWrVO1Dn7PvcwGEf/t3/7tRz/60dVXX/2Vr3ylvb1dOUCSyeSKFStSqdTslZcvXx6LxZTaPvnkk4yxiy++GABWr14dDocffvjhv/7rv96wYQNj7BWqGaiE2RPeHOrsua4rhAiHwyq9ASq2bYXXI/93bVvlJ1VOgzIqnaBUKsH/koy+Shhjuq6r3RFRVVXVwoULP/jBD952221EtGHDhj/ETlXc/33ve193d7eu6yqr95Rr1tfXr1y5cvv27alU6sknn+zp6VmwYAERNTU1nXvuuRs3bpyamtq0aVNra6vKF1ZxyBM20t3dHYvFRkdHp6amlM9avWMAYGRkpFgsLlq0qDKEocLrmP+7avvGN77R5/PdeeedExMT5YW6ricSieuvv145ZE+bhUVEDz300Je+9CV4aSc6HA4DgGma5eWqSa8ciJvNb1yzPCJOSeTg4GAikeCcq50qEHHt2rWJRGL9+vXbtm274oorfD6fehtdccUVExMT69ev37dv3/nnn3/yELIyzc3NV1999cDAwD333KNigIwx5b397ne/K6X8sz/7s4oDocLrmNeYJ+HV2Jsnr1DOd5u9ZNmyZe973/u+8pWv3HjjjZ/97GeXLl2KiNu3b//Upz719NNPn3322YwxlXR1ymbA79rbPaXdVyqVbr/99q1bt+7fv/+2225TI3137dr1zW9+U9d15QxVx64yB3bv3t3Q0OD3+5cvX37KDZbZtWtXuW6hQkrZ1NR0zjnnXHDBBY8//vgdd9zR09PT0dHhed7mzZu/8pWvxGKxXC73+OOPn3322S0tLWq/F110Eef8a1/7WjqdVk5bxSWXXGKa5pe//OWJiQnl3n05EPFjH/vYww8/fNtttxUKhTe/+c3xeHxgYOA//uM/vv/9719wwQU33njj7JV/i3NaocJrgv/l/N0/MKq3+xd/8RcA8NnPfvaU69xwww0A8Itf/KL8ExVqP/fccwFA5Y0qcrncW9/6VnUeamtra2tr1ecPfvCD+Xze8zy1u5MbcMcddwDAzTffXF5ySpQHYNWqVeUlg4ODwWAwHo+nUimaNepXSrlr1y7VQs55R0dHW1sbADDGPve5z6mWqB395Cc/KUfzGxsbs9nsyWNk1ZJ3v/vdL3fR1YCLkZERtUdVBqG5uVnTtDvuuOM//uM/1Gqf//zniUiNqU2lUi0tLQBQV1c3NjZW3lehUFiwYAEAaJq2d+/el71yM0NFfvnLX6ryiaFQqK6uTuUnrF69+siRI7NXVm+Iq6+++hU2WKHCa4vXmG0LAEKI6667rqGhYc2aNadMjbr55psXLFgwb9489We5xMx73/veyy67rLm5ubxmKBS68847r7/++vvvv//QoUO6ri9atOjGG29cs2aNKj92ygYQ0erVq2+//fZly5a93DqKlpaW22+/vb29vbwkHA7//d//vaZpqic+e+UlS5Y89NBD99xzz+OPP37s2DFd16+++uobb7zx4osvVo0hIinl9ddff++9927btk1KWVVV9XIFFYUQb3rTm5qbm09p6c+ZM0cIUV9ff999933ve997+umn0+l0Q0PDn/3Zn11//fWO4wSDwYMHD5ZHwQkhIpHI5z//+b6+vo6OjqqqKrUpKaXP5/uHf/iH3bt3V1VVtbe3v3KymuM411577eLFi3/4wx9u3LgxnU43NzdffvnlN9xwQywWE0Ioy52I5s2b9+lPf/qEqhEVKrymOaNnyqFTVQCgWc6EEz7TS3Nsy6gBAuXl5V/NnkKGXuqjKGcjnLx3IipvSgjxyh35k49odoNhljdWfXVKcZy9girNdcotz25tWbleDjW+4ORNnTCtjvrzhBNbltQTzkZ5MrRX2GPZVzv7bMzWWfVVxZNQ4fXHGa226ul99XNqqfUPHDgwPDy8bNmysmfg9QoRDQwMHD58uLOzs7Oz87U1+dhshBD79u3Tdb3cI3mNHkiFCq/AGe1JUFaVbdv79u17hdx4AJBSmqbZ29uradrnP//5H/3oR/fff/8111xz2pr6R0FVe7j11ls/+clPfu5zn3s12cFnJjt27Fi3bp2qENTR0fHaPZAKFV6BM1ptVS91cnJy3bp16XR69lfl7m2Ztra2gwcPappGM4XAT2dT/1jQrOyI165Cua6bzWYZY5UyNBVex5zRaqsIBoPvete70um08r0yxp599tl9+/atXr168eLF5XTRE2qqvnal53fgN1baPcM566yznnnmGZ/PpwzbP3ZzKlT4g3BGq60KCkWj0TteOsHthz70oX379t1www233Xbb7OWVB/U1CmPs/PPPh8oVrPC65kxX2xOW0MywejhVlRMV7C6HywHA8zw1Mqqurk5ptxBC1RiEWTFxy7KmpqY457W1tbOD48qVUf58QgJD2ZVRjsuPj497ntfQ0KAm6VKHoDZuGIaK2r1cGkMqlcrlcpFIJBaLwawIofq2PEOaZVkTExOBQEBNZXaCO+WEjIKTz175kGevMzU1VSqVqqur/X7/ybkZ5TnWksmkYRjV1dXKXXPyvtR5kFKOj48jYkNDw+yTXCwWU6mU3+9XCWSzc8XUySyf1fKfaoVisZhMJnVdr62tVUvUOSxnSkgpp6ambNsOh8PRaPQ3nocKFf4onOkjd094Zl7982MYxtNPP33++ef39vYuWbLk0ksvXb9+ffkRLW9tdHT07//+75cuXVquBf7973/fcZzZ+ba/+MUv1q1b973vfc/zvO985zs33XTTm9/8ZjUF9xNPPHHppZf+27/9W19f33XXXbdw4cLe3t6LLrrohz/8oUp4+ta3vrVy5colS5b09va+6U1v2rFjR1mIyzz55JN/8id/snDhwsWLFy9atOiWW255/vnnVVPLIGI+n//iF7+4atUqtdo111yzc+fO2eNrXdd9//vfr0bHnnxCVEWxnTt3qj2uW7fua1/72ujo6C233LJgwYIlS5asWrXqX//1X2fXKVd619/ff+utt5Zr+K5evfpLX/pSNpstZwEj4k9+8pNLLrnknnvu2b1796WXXrp48eLe3t5169Y98MADiOg4zhe+8IWlS5cuXLhw6dKlb33rW48ePTo7UUyNln7HO95h27Y6cKWnR44c+eAHP9jb26uKCJ977rnf/OY3XddVCqsmjvv+97+/Zs2ahQsXqnXe9ra3bd++/RXGAVao8EfjN45/OAN55ZlybrnlFgD45Cc/2dbW1tvbe8UVV6gJEYLB4Pr162eveeTIETUF5Pz589/61rfeeOONyvz8q7/6K1VOWw3f+spXvgIAH/nIR/78z/9cnbRoNHr06FEi+sEPfgAAakBEZ2fnZZddVp5T8nvf+943vvENv9+/atWqyy+/XA2g6ujoOGHQ1Le+9S1VymDFihXXXXfd8uXLASAUCv3whz8kIs/zlKbk83k1sJVzvnLlyssuu6yjo6Onp0f5Uj75yU+qrX3oQx8CgK9//esnnJOxsbGqqqqWlhZVEeZHP/oRANx0001XXHFFW1vbpZdeumLFCvUm++hHPzr7h/v371dHtHTp0ptvvvmqq65SxuNNN91ULBbLlWW+8IUvAMB73/vepUuXzp8///LLL587dy4A+Hy+X//61x//+Mf9fv95552nqt+qg00kEuW9HD9+3O/3NzU15XK58sIXXnhBXbi2trY3vOENl1xyiZo78tZbb7VtW12df/qnfwKAWCz25je/+W1ve9uyZcvUnw888MBvdUdVqHAaeB2qrRqMu3z58scff1yNOk0mk+973/sA4KKLLnIcR1mdjuOo6WY/85nPlB/yvr6+Cy64AAC++c1v0sxgUzXDbldX18UXX/zd73738ccff/7550ulEs3M2VVTU/Pv//7v+XyeiAqFwuc+9zkAqK2tPe+8855//nm1keHhYVVe4CMf+QjNjPfdsmVLMBhsaWlZv369Kj9m2/bPf/7z2traqqqqPXv2KNcHEX31q18FgHnz5j399NOO4xBRLpf79re/rUS8rLabN2/WNO2SSy4pTxis9v79738fANSkOET04x//GACqq6u//vWvq9nbbNu+++67fT5fMBjct28fzQz//drXvqbr+h133FEsFtVv9+zZo4Z4/exnPyuvpurptLS0/OQnP1FnJpPJqCnUmpubr7jiit27d6sDOXjwoHqjzH4l9Pf3RyKRjo4OdQ6JKJ/Pq1HFt99+e3mU886dO5cuXQoA999/PxENDQ1VV1c3NTXt3LlT/apUKt15551Lly594oknfue7q0KFPxCvQ7VVM4F/4xvfUH+qh3xwcLCmpiYSifT19SmBePTRRwHgDW94wwl1BjZv3mya5qJFi9RcBjSjthdddNFsy0uh1Paqq66avTCfzyvL7lvf+hbNTPlFRA899BAinn322WWrWb0YlBk7m29/+9sA8P73v1/9WSgUent7OecPP/zwCWsqRfv7v/979afjOKtWrfL7/bt27VLHrnjDG96gcjnUakptr7zyyhO2dv311wPAnXfeqZotpcxkMk8++WRZuFWzlbZ+4AMfKP/wi1/8IgC8+93vnr01dc4B4KGHHqJZRSG+973vAcCb3vSm8ponq+3Pf/5zALj66qvVr8rFKDZs2PClL31pfHxcXanydsqnlIgymQy9Yv2KChX+KJzpftvfAdUjVtUJlPOOiOrr6zs7O3O5XDKZVCv8+te/BoCTq/ydffbZCxYs2Lt374EDB2Z/pcoJnjIhtLW1FWbF04PBoBoTpSrLlKu4zp07NxAIpFKpYrGo8ogfffTRurq6k0tnXXrppZFI5Ne//rXKMj569OjevXvnz59/3nnnndAAVRGmjK7rN954Y6lUeuCBB9QSxlhfX98TTzyxYsWKlStX0iyXsaoyM3uJ6okPDQ3BTOQqHA6rqhEwM40QAPT09ADACRXHYdYUloq6urqOjg5EVAZ4mUWLFgHAxMQEvfw4xscffxwArr32WkRU/grF6tWr/+7v/k6VwY1Go4Zh7NmzR3mBy47gcDhcydutcAZyRuck/D7QTEqAUgpN0wKBAM2aeFFN8vjMM8+kUqnyQpUtkM/nAWBwcHDlypUnbPCUxQfUz2eHfWbPQVkOzfl8Ps656uOr7U9MTLS2tqokhNlEo9FYLDY2NjY+Ph6LxQYGBoQQNTU1wWDwhOAPnVT78dprr/30pz99zz333HbbbYZhAMCDDz5YKpVuuukm0zRnr3lC2kO52eVd0Ew6wcjIyMGDB8fGxhzHYYypmdtP5oS2aZqm6zoRnbAjFdlTtufLhT37+voAoK6uDl56zlX7VVJEV1fXTTfd9IMf/ODiiy++8sorly9f3t3dXR6xreJsp9x4hQp/FF6HaksvzTo44dvyEjX57n/913/BrOlb1ACKYDAYiUR+n6D2CVZbOelq9nIVZSpP2TAbZak5jlMoFABA/atWU9p9QmmbMlLKuXPnXnjhhY888sj27dvPPfdcz/N+9rOf+f3+a6+99oQT8gqmJcxIbTqd/tSnPvWDH/wgnU6Xp9F8uR+efNQnvwxeJerqvMLlUwlkX/va16qrq+++++7vfOc7anljY+Nf/uVf/t3f/Z1601SocObwOlTbV4kKcH/3u99dt25dWQ7KeZpEpAT3D2cf+Xy+l0tUUs4HxpjP51NrwquojzXtG2Ls5ptvXr9+/b333nvuuefu2rVr8+bNa9eu7enpKdv7r6Z5qgv/t3/7t3fdddcVV1zxV3/1Vx0dHaZpMsYefPBBlfzwh+M3zryrDjYej3/lK1/52Mc+tmfPnuPHj2/ZsuXuu+/+zGc+Y5rmxz72sT9oCytU+G35v6u2an6EchK+4gR5/R2MsldPc3NzVVVVLpfLZDKqy1zeY3mhaltLS4syMy3LMgxjdgvV57LtrP688sorq6qqfvnLX37+859/4IEHHMe55ZZbXrkA4ykZHBy85557mpqa7rrrrnIL4aTJ3P4QdHZ2AkAymYRZPoGTq1+qfxsaGtSJes973nPNNde8+c1v/vGPf/zhD3/41c8nVKHCaeD/rmPr0ksvBYC777579kJVGOVrX/va/v37y9GtPxD19fVr1qxJJBKzJ3lUlvWzzz6bTqfXrl2rwkHd3d09PT379+9XefuzN3L06FE4yextbGy86qqrDh48uHHjxl//+tfV1dWvMK/wK5DL5QqFQiwWU57l8gzkk5OT8NuMNPkdWLduHQD86le/gpf6LsbHxz/72c+q4RuIuGnTpmKxCLNCkatXr47H47lcrjxZeoUKZwj/R9WWiC677LILL7zw/vvv/9znPqcm2QWAYrH4hS984YMf/OAdd9zxB/IhlEUKEd///vcbhvHxj398y5Yt5RWee+65T3ziE8Fg8NZbb1XjtcLh8Nvf/nbHcT74wQ/u3bu3fAi//OUv/+d//ueUe7nhhhuI6Etf+tL27duvvPLKxsbG36GptbW1dXV1x48fV+8Dzrmmafv371cpXJ7n2bb9O7yQXo1MX3HFFb29vffdd983vvENz/NU9HJ0dPQDH/jApz/96fvvv59z/t3vfvfCCy/88Ic/nEgkyoOhH3744cnJycWLFyv3S4UKZw6vMU+C6ukrX+fLZfmUs77UnzRTgFEZO+X4eCAQ+Ld/+7frrrvu9ttv/9nPfnb22WcDwObNm3ft2tXb23vbbbeVPapqR+rn5QgVzcykAKeqpaJWPqGFKvFWZa2qJWvXrv3sZz/7sY99bM2aNZdccklzc/PAwMATTzzhed4dd9wxe0KzW2+99YknnnjssccuvPDCCy64oKqq6uDBg+l0+o1vfOM3vvENtcHZbpCLL754zpw5Kg/s5ptvLrdhdrNPFkq1vHyiGhoa3vnOd37pS1/6kz/5k6uvvrq+vn5oaOixxx776Ec/OjY2du+99x46dOiee+5pa2srN2D21soZIOUuP85MmXHCyurqlE+Lyjz7xje+ccMNN/zN3/zNXXfd1dvbWywWn3nmmaGhoauvvvqtb30rEZ133nkLFy781re+tX79+nXr1lVVVR07duy+++4LhUInlCuqUOFM4DWmtgBARM3NzYsWLaqrqztlClF7e/uiRYsikcgJy+fOnZtOp2ebPEuWLPn1r3/9j//4jw8//PCdd96JiK2trR/60Iduu+22lpaWcjZ+dXX1okWLmpqaTpAnIorFYosWLWptbT0hT0C14YTULl3Xly1bFgwGZ7tQP/rRj86ZM+fLX/7yE088USqVAoHAueee+5GPfOTaa68tB7VUIbQf//jHn//853/605/ef//9uq6vXLnyhz/84bFjx5588sn6+nrV1NkNu+6667785S/39PRceOGFr6bZAFBXV7do0SLlA1Vq+JnPfMbv9991111qHEdra+vtt9/+N3/zN21tbf/yL/+ibFsiqq2tXbRoUW1tLc2a/IaIenp6isXiCZOwmaa5ZMkSlbSr0DRt8eLF8Xi8XFFISnnhhRf+6le/+tKXvvTEE09s2bJF07T29vbbb7/9wx/+cCQSEUIsXrx4/fr1//qv//qzn/3sv/7rv6SUkUjkkksu+djHPnbxxRd7nsc5rxSmqXDmcEbPlHMy5eRNmqn/dEJ/n2YGETHGyqJ2guVVrgFWng5rfHx8fHycMdbc3KxcpbNzTsv7VU/vbEUob1xl/pdtt/JCnDWpF82Mp5rdbGWQ2rY9NDSUy+Wi0WhbWxvnfPb8BTSr/Nj4+PjY2JjP55szZ46maeUSLWqbs8Xle9/73rve9a7bbrvtX//1X2eb5C/XbJo13EuVzlFt0DQtmUyqKjyNjY3xeFydN2WQlo9RbbY8AkINRigfO8ya2r28o7IaqksGM6m16rdq1wCg8o51XW9paVGJIuUEZ7V+JpMZHh72PE/Vgph9dL/X3Vahwv8qrzG1/d14hSz61xmzKw3eeOON995771NPPXX++ef/QVPZKlSo8Gr4P6G2/3cQQqgxEUNDQ2vWrOnu7t6wYYNKhKqobYUKf1xee37bCq8A53z37t1XX321ZVn5fP5973ufaZqVogEVKpwJVNT2dQURhUKh5cuX+/3+tWvXvu1tb4OK+7JChTODiifhdYUQAmeAWWHAChUq/NGp2LavK8o1a06u71WhQoU/LhXbtkKFChVOB5U4dYUKFSqcDjSAM3lqUgRAIABSHyX9kV4P5SbAzL+n5Hfqt/+v9C1O3vPvsNkzyu1wQvtfTdte3VWiWd8TANKLS+iUvzujTstJEAAQYPkYTtVamjk6+J2P5oSz9mqeht+4tdnb/G23M/v2wJds7NQX8dVtEgFAvig7OPu7l2vkb/GgaUBn7s0kkQAAp88BEUh+8v30ag72f/cQy3v87Td7cmPP3LP/2oNOfCqmHxgCgBPvc3r5D/87LTktF5Ze8km9O15WcMsffnfBxVmf4QQ1epXvw1kfX3yQEH6rx4pOvFo064oDAE0vwPK6L/MaOnnLEghPfRpPKbgnteQVQSL31a99ulHTpiEAIEEl4lOhQoVXhYQTplw8I8QDic7k1HcGAFkrVyykNNQYcRdBAKjqBdNJTkQEhNOvMQICRJp50053fJj6ngBQ1T3AF192L0YJ1a9nmG0KTf8Cp196RDN7Kn95iirXoHoj9JJtzPbavPjGJUAEUu8TAjazMVRH8pJfzGx42l4r30WI01uZtcr0MZ2aU7y7pk/AKyYy/F690d8MIgMiwzQcxy1Xh9B1XQhBJH0+HyKqudE4Q13XLavEOQcC3dAdR0gp/X5fqVQClAzRNP2lUt7zLAAE4D5/sFjMx6vi2WxW0zQpJeeaFAQAnudxTZNSmroOALbtAIBhGK7r2nZJ07nGuecJIvI8z/T5iZBzpqb/SKWSnIEQUkrSNMM0fWoSPDUNkm3bUkpd16QUQohSqYSInHNPyFAojAyLhWKhUDBMw/T584W8lBIBhRCmaYaDPimkmkuJiBjjiKxYLKrSl6Ojoz6/nxAlgSjnoJQndp15AGT5vpm5FXTGSD1BJ5z7F+/n8hbU5EyIwBzXBSBD1z1PaJrGNc4QTUMHIs5UMgxOTU1Fo1Fd16WUtm1zznVddxzHMAwhhGXbjhDBQNATwnVdz/U8z9MNPRaNghT5XM7n86mp81zXnb4onJcsJx6PA1CpZHHO8vl8ybZn36MIwBnG4/FCsYiAfr/f5/dJAiFcjiCEg4CIDFGV6UBEULVKZh88EXkSCsVSJp8noqpo1NBYqVTSdcO2bdf1TNPUuGYYuhCiWCzqhm5bluMJAiSSrzL5R3vTDx6c5cM6lfvjf2X57/RzROkTOWviQHHsoOG55KInwfM8NZGirmuIvOQIoW5QKUiSJKHrjHONSCIyIkkeITFElFIwxomk5033NNSm1ImYnklbCiEkCYlSZ8g84U3XkUGmaRpnLODzZ9JpkCTJkyAlvdjlYAKZ2qwQwhNCCCRCAJLENc4ZtywLp0vc0LR0SwKJqhDM9PwLAJwQABCBa5phGFJIz/MYQ5r9EqEXS9UgAjJCnK3OyJhGRCRffBVJkojIcHpKSmT44itq+oaTAAJRVY/B2Vo/ezYw9aF8sxKpIkEvrnaqycRg5jLP/Ihm/e/FxDXw+fyO4yxatHh4eDQaiQghA4GAlCIaDcfioRUrVqTS6YH+fillY30dghxPJGKxWF1tLSImElOO41RVxzQNd+3eoeuaXzPS6YlcPt3d3UOCpTM5zaeraTfT6fTGjRs7OrryucLA4GA8Hl+xfPnA4GAgEDjS1wcEtmO3t7WFQqEdO3YCQH1Dg2Pby5Yt37Nnz/Do2OIlvYlEIhgKrjp71QP3/zIYMJb2LmNMHxudnDdvAQDNn98TDAb37Nlz7NjxycnJpubGKy6/LF/IP/HEk83NzXW1tZlcMRyJxOPxcCRy949/PDg0tKh3yZ59ex3bzhcKbW1tJMTF5583PjYWDofyuXxdXV1bW0ciMXns2LFisXjxxRf/53/+Z9/xo1oglM26wWDMdhxXlICII2cMAZGkJALiSOotzqYvqN8wpZSSJAJKKRnjjGmccd3QZ2oneUpBVN0fn8/HJE9OTjS11FRXx0olkU0X5y3sikQCvUsW+jgL+o32tjbDDD7xxBOO4zQ2NjLGDh8+PG/ePF3XU6mUei0dOnJkeHy8s3PO1q3bS0Wn70jf5NRkb+/iNRddEAkHXafY0dZaX99QKBSPHj2qaRpj7NjRY4mpzKJFi0Lh8K6duw4dOrR3396h0QRjvPwUGDq/5JILe3t7//u/f9DT0/PXf/3XY+PjBw4cYAjNTQ2tzfU93XMMQ09OJVtaW3VdMwzTsW3HdX2miYwxxlzHsWzHdulr37zz7v/5eVtLy9qLz1+8sDuZnGiob9q6dXtNTX1tTX06nS7alue5DzzwKyKanJiwHLdrTncmkx4dGSnbf9O3+KksHe2+faNnotoqDA3cyfmUaxIe2GlbSA+4kMIjTwjJCSWh5WpSSiEkkVTOK52YYZhK1IQQ0iNGTFkHRMQZ8zxAYK7neq6njORZBatICCEFcE8QoOe6QkoAQkRTM2qqa0Lx2PjEhPA8IT1BHsG0ogEASEbT/nXyhOe5HkrSGJckySFdNzzXActFVS4LgTEGhNJDxpimadOlywj4LJvD9Jmca1apxDibOTPKAgYiyZABIGNA4Cn1LOsaQ50IiIiAGDICkEKodSSRFIJxxhmf8Wgq2fWQASKSVNrNZvR/liP0RbN9+lqRpPIVnNH+l9xhL/m9sp7ktLdr1t2JgMAZdzzBGbdtR9d9jBu2U3Jc4QlRrRvI2IFDB0dHRy3L7ujoECSEa0ci4Wg0Mjw6nElnGhsbFy1eMjBw9JcP3B+NBqcmE2i5PpM3NNbkU6Pz5y1iZE2kpo4fSbe3d2zevKlUKJJTGzS5AU5LfXxqfJDs3N6+fTUNdYnxhGEaicmhkh1esLCn//hgqZh3PXfz5g2Ll/Tqfn/PvJ76hvrHHn9sYHAg4Pel01M7d26bN29xMBQYGhxKTIznC+lwKDwwOLh///58Lrf/wN7x8ZErrrjine98x8BA//r163NFq+9of2NjQ1dnV2Nzc65QsF2naJXUZBnrLr/MLhaO7N8/MZGIRCLxeFVVdXxyKpHPF44ePToxMZHJZObOnXvw2BHbtqbSRYkh23Hypbyh6TrzIQMpBUNkjAk+E0FDBAIiWfQEZ0xKBAREjpIx5Iwxg2kcmZQSGCMShmEwhkKIQklwx12y9Kza+nAiMRIIBhITRa77BMDI2NiC7q5g0GcYOuc8Ho+vX7/++PHjc+bMmT9/vs/nc103FouNj4+7rrtv/75V51/AuRGJVllWUjdCps9qa++amEzm8tmVZy2tqalKp9O5XN40fYaul6xSXX0dM4NjickrV5y1Zcu24dGxyalUoeQAoLqxASBfENte2Pv8ph2Dg4OTyZzt/Bsiy2azE4mxdWsvbKiv7zvaH4kEYtEIY+B5ruPYoVCIcSalkK6raTogMA5jI+PHjg+0ts9pbWu1XHfb9hfOWrH0sSceHxwYPfec+JG+49t27Ny5Z284HEmn01NTk4jM0Lllu+lsoWh5qhrf7MKnUD7tZbWFgDgT1ZYAEAEZw7Df1us8C5lugchI4WnM0AybHMa5OumuJxGElIIAOGO6jpwTY1xKCUCMpm1bkmqoFdc1JiVwRqChlBIRJAOSKImASOMaEEpbE0JoGgR03XFsHblf04O6zqX0m2bRE8g1kiSlYDP9MkIECQTEGNNBQwIhJXKNkRSe57gOQ2QaB09wxme0CjnjABTwB4hkIV9ArrwByBBJAkmm+0zbdgCQ8elKhoCMISOSABKRAAFRmxHHF8ULAJV0SkJEQK6xF01WZIwxrgFQ2VzlTEdGAADsxZnhT6B8M5Ut8XKSyKsfSUEoZ0R4ppWqZiORzjgyNjI2KgSlMslIJNLW0Oq5nubTi44FGvMHAsFgcGx01IuFujraDNOwbAtBMC6L+Vz/8eObt252nNLk+GTAwLr6mKFzlHZuMr8zk9R0PZ2erK6p37dru3S96uq4kDKVyrmeOLB/P6L0m4bf1AeP93uuC34/6k66kE8n09GqqkwmW99YNzWVbGpprG9snj9v4cbnNyFqhmmgxh0P/KFI//BAKBTes/tAXU3dyrNWJpOp+vqGs1ee7ThOMBQ6fOjw1q0v9PcPDA4NTiWnFixaPG/+/Be2bx8eHbrg/PMbGus2b94WMPylfJEzbaB/QHpeU3Nra2t7Op0+fvy4zx8wdGNsbLyuvi4Q9C9evOT48eMNdbW6P9hYq72w84A/HEGuS2BM15QHAxgTUhIBMgQJnOvTXWlOnBsETEgBKBGISCDnhGQGTJLScRxkDBkjAMZ4ybI6m5pWnbOyf7CPMZ0h1NVGfQY3OAv5A57rAvot2yqlc+FwaPXqc4UQjY2NpVIpn89XV1c7jtPV1fXww+t9vsAL27avWLb8misv3bFjd1Njvet6za3NusHPOWdFejIxMjzqWM7o2Eh1TTyTK4yMJpYsWTGVO5xKJMZGBuf2dHrCPXDoEEfVVZ22EoBrx44PcE0zfIFC0d76ws7u7rkHD/fNmz938fJVO3bvq4oGu7tam5saDcPQdV0ICQCmYSKC7VhEApBKlpWcSp6/epUr8Olnnj1czLzlLTeFQ8GJVN4ltumFHXv27ElMJIXEyWQKgJg23Q842nfMth2SoGs6ABK96LmZ4UWXhQbyDE65RYeEYIxM7jjcx4QExyYpEblh+CUgAJg6oeMIAVKilBIBUAryEDlyYIwxqUkhJTIEARo3hRDTasE5ZwhCKj8Oqj43IRAiMoNrQhCS5Mh8hllbVdVcUz06Pn7o4AFBJIF03eAShENipt4uk8QkAAGSJCINEBgyhiSRMS6lACLGuRRkGDpnzCqWAIAxBGClYlFKqdwFxAAAgZAxBgTCE5xr5VcmIgNgCAzKrgUENqO2L5blnZUSRASIjKuNE5TdADMvYeUTZMjkSSbniZzy7f17XeGZfTHGdF1njPn9/mKxCECaptfWVheLuVLJ8gXrI7G49NymxqahgYGujvZoJFgolqaSUwsXLwAU/ccPT42MDhzXRoeHDI0hUdjQhFsoORQIBH0GZ0ympsZICteyq+INEnMC4KJ1V2zdsks3/eOjw06phEDpTIZx5tM0Hb14JJLJpBITqeNDA8LzRkYHo5HI5s0b/XqYE/cZfp/ha2tr2bVnVz5TsNy+ttYmQV6xlAuGOzOZ/O5dezdt3nTeeeclk8murjmTk6lAwF8oliTAgsWL5szpzmVzfp8vGo3Yth2JhM9Ztaq+oXHDhg01dXWDQ4PPPvPMyt5e4Xnnrl69fMVKwzACgYBtlwKBwPPPP48MbvnTm//8z99hmOZP733ghe3bpfAxpgGQIM+1HADQUCOUJIkjF0QkGOOapnFCgUScIUmPMdFQV+PZIpXOIgC4wtBNw68hl7ZtSyGklBqIc1Yt1022d8+eJYsWjQwP1tWEPLtUHakTthsORTRu1NU3plJpxnhLS3M+n4/FYqOjY7puVFVVZbPZUqm0YMHCfMm+95e/QtdrqI62NNU0tzZt27b7F/f+4rKrLpWIumHm01m7VCSSnLPautpgpObun/z88LHD565cblsFjnTWiuWPPP7EsSMDQgiG02EKSch0HRiTBJyxYqm4c88uydhEMv3Mxk1nLV2wdOnCeT2dqVSyUChGo1HOuRBCOBJQGrruSReJTUymUun82Ojo8MhIJBzIFwrf+96PQqFwbV1rZ1do586d9Y1N3DCHh0Y0zpV9IIQgIYuFIucz3QegcuRk1jPy4sNyRo/cRWKcdPLAtjwbHVsIAkDkjGuupJJle0ISAyIQAhjjhIwj4wBAIAUBSQAEJCLJgHGdSTFdIZtz7nnScQQyYAxBcgBgBEAoBDFEf8APAAbX0skURxaLxwSC5ToSgIgkSdu2gEBDJpT/YtpQI83QVXVwxhhHpjwGCMiREVFA92VFxjBNjTHbtjnjnOuMc5JSSIkAnvAAEIGpd6QksmxLld+eVS+cAJXbRGUFKt2VymKdPnVMSgFSzvbLzJxVBJwxjWf+BESCk26UP9DA31k+32lxL/t5QqFQJpPRNE3ZRKVSqVQCv9/vuZ7BDVdIv2l2d3e1t7bs2LM3HIsZmrZz1+4D+3bm0imfjoxhW2NMeI5weSmXKQjbNA1hOQCg63owVjMyPukX+lXXvPmOr3y9sblpaGDEMIy169Zt3bIpNTWRSIwF/D6fqQWC/onk5PBk0fSbgYAPpGNLCmh6JBCor65u7+iemppobGyRnvPEY48gEkMjkyoeKuaEoGAwsnvX7tHB0UWLFs6bN7eurnbRokW2bUspqqurlq9cvnvP7qPHj46NJcZGx4aGhlOptON4wWDAdsTRX95fU1MzMTkZDAQuX3epT9csywoEAitWrIhGo67rWFbJtu1zzjlHeVS5ph/u68tkUt3d7ccGRpkW4JquamUo59j0eQbltCUhhCTQTC6l1Jhoa6yJR/3tLU2dLT2PPPrYkWMDNnHh48hB06V6DdulYldnezDgO3RofywW9vuNhvraOV1dkWhVOpmemprsO3ysd8nCqcnUwMBAfX19MBj0+/22bdu2FYlEAcDn8yUSiVgsdqx/95LFizUQ1dU1k1NHHGlzjWka3759Rywemd/V6bj20MhQe3u7PxA2fcHxyfHde3ZbrqWZRigUSabSO3btCoXCvkCgUCiUy+3TdPSBEEEIj6lOnhCDA/3Ss4aOHlixqCcej4VCQdu2VX/fsiy7YAOjSDTket7EZHJiMv3zX/56YGDgvNXnNjTUbdqw4bHHHgFuNDU1t7S0DA4O+v3+icQEzFS+V+VHiKSqu1+OjrwyZ7TaEjCpQcHyUlaBBRiYDC3BCF2vlLfsku1IQE3TlbNQCimlFAi2phywDJEZuslIAnrKHU4kkYOargBAxW8JEYVgQkjGmPAk59zQDSmErut19XV+0yQph0eHRgaHiQgZSilITrvEkSNnnJThKgkAHMeBGQVh7CXTowkpM7lsNBptaWqeTEwEhBBCoMaBwBUeMOSca5ohXE9KQgAVx+Jc03XNtm21HeUe4VwJFhIBEsqZmMZM6ExlOKi7kSkZnT0ZhPKfAL4YmkMluvCSBp/6osxMZqH+LG/zhCWvRrLL/gr1LlGB+Gg0yhjL5/MdHR1DQ0NVVVWlUikYDHKmSabpmlZfV59NJ5Hhlq1bWxprM1Nj6dRkdSwSMCGTToLgtVVVhaI+Pj5p+PWa6jrP82pqqiXR0NAINyPMCB88PFBb1wLIjxw5SkTHdR4IBm3HnldbOz40pDMWioYKLo6MjzjJosn0qliV39Btx8kkpwq57LZtW0LheDxefdWVl+/ZuxNI1De07tm7a3IqYZWceT3z/vSmt9TWVnd2dg4ODnqeFwqFdu3a2dnZlkhMjI8nTNNfKtk+f6Czu2dsYrKmpnpoaDiTL/QuW2YLEQwE/IbpWPZZy1ckxkc7OjoGBgZ++MMfnnfeeQ0NDYj0xBNP7N69O5fLtbW1TU5OPfXsM4bfmDt/YTKVLpY8Eghsej4OIlKze6hbVaU0AKJUwVshFs6d+xfvfmsoqBUz2Tnt8aef2/j0pu02oESzZHsMJHluV3vLonk9o8P9hw7ub21paair2Tk6WCxma6obpqZSpULhYDo5b15PIjE5MTERCoUcx6mtrR0cHFSSJKXUNC0UCiUS435fIBCJk1PqP34cGT6y/uGuOT3LVywbGh07fnSgtb7B7/c5rj2aSDTpvsnk2PH+QQEUjcU1zdi2Y+dZK1Z874d3b9q8VdcMImKcv5jHM31TS8MwY7HoRGLC5wucdfbKUjHf1dFUU12l8lhU50lK6ThONptBjv6AjwBTydyDDz584MhRz/MeePChC88/5+o3XLlv776xqez4+MTQ0LDKYClP2qIMW/XInDwn4SvMXXBGqy0wkiR1DWNhP+i647qGjrrp94AMnWU5ETIk7rmunM7KksCQmMpGIASpcYlEkkCSywC4xrmma1wHQClR05kQQggBwKY73Qw410yfSY40Td1zHQIxMZkoFS3SmAqJISKB8jxQOfFGA6SZmG8sFstkMgAgp8elKL8papxLAz0hPClt1yGESCw2mUkGAoFoOJhMpZARA4bE0ZOAiMCIQAihaTwQCOTzeQAVvJJEgggRuZQgBCASzpoGHABU7Gs6p2fa+H6pkiJNG8aIiOqtAycI7CtI6stp8asxh09IRVCioCz3iYkJTdPC4XBXV5dlWapKb1VVled46akM5xSPxfO57OHDBzWf6efewT3bGXqea4+NjhgmBAwjm0lrjFuCResbR0eHMkf7kbHxVLa2tra2uW3u3CX5gpO3bMPnGxoeaGqs95u+I4cPJ9PJs1edk5ic6Oiev2f3nkhtuKqajSXShiFaGuqK+ZyQHiJ5nnvw4H7iumkmwqFw3+Ej2fTU0uW9AwPHpiYnOMNlvcv+5tYPd3XNKVlZxrFkFZ5/fpNt24nEWENDI2P8f37yk1Akms5kNTNAAKFIxOcPtnd07N69Z+OmTbW1tQBw1llntbe0xsIRZ8E80zTnzJmzbdu2iYmJUqlYX193zTXXnHfeealU6umnnmpsar700ks3bXluIjHc2lJ38EC/bpoOgTql5YJwAKBpHIGrRCiPPAAmATdufcHySmsuPGdhT3vnnNaVq3qrf/jTnzzwMDKNgIOQpqFdsPocv6H1DxxddfZZ83p6bKvY3tY8f96cw0f6h4YGGIqVZy31+QzPc4PBYCKRKBaLuVxOWbiMMcdxBgYGEomEaZr5Qm6sv78mGjln1cqxxMTRo8dMn7+zc44/FUDULatkF5MNjfWBUHxiIvn8pm179u1PppOuEHv27rOL+Vw+v2fPPmAMEJVPebpLBIQclW0rhWdZpaXLeleedXZ3T893v3vn+ef9SUNDnXpQNU0rFouWZeVyOcuyqmuqEFkgEOLcDIeiF55//oaNGxjIdCa//vGnOrrnjU+9gACm4VdpefDSnH/GOZAQdGL5p5OexBc5o9UWSequqNaNJtNXLNmI6Ph9mVIRGQZ0NOJB2/FQMjL5dG+aQGPIwUNgum4oY9FGSNvFUsEikoahITKOzJPElW3KNSHQc4Fz5nmCGJg+n+d5HFg0Gq2JV+0ZGy2VSo7relJwZEAgJansLgDwPI9m5teSYlq8VDeHcfZi54KIMWYYRqlkcU0bGh4iKXVNc4UnSRICcjR8Rrn3RzDtl5WSkCgYDOZyOQB1myEyJCCmvA2ACEgk1Ru1nL0FKBGYyrNQfgOcjkupZ08DEIBCra6yuKQkpYT00pnT4FQie7Kqlm3el8sDO3lrCk3TlBHkOI6yPlzXHRoaCoVC0Wi0paXF5/Nl0jkjk2tsrDV0vZh3/aaRTo6PHt1XLBXjVbFgwBeN1mWzuVwu4zPYSCIhNHNofIohBQOBUqmUK1rpQjEYDA2OTs3tWaRxS4J0XMvznLbunlyx4BEl09nxieTWoaO1dbEde7cG/L7aunCxkA+G/IViPloVm5iYCAaCtuPE47Ha2sannnpcRwbkbd30PGlmd3fXihVnLZi3pK21bWhoeGDwMBHEYrGWluatW7dyzgcGjkcisXw+b9lebX2DrpmCZFfnnAMHD1qWVVtXx32GJ0WhUEinUssXLfH7fCEtmMlkhBDnnntuNpvdsOE527EPHTqUzWaJaGh4uKGhORKJtrQ0Z3Np4YmAadhEDKdrbJYnrFM3EmOEBAQSQQKgZLzo0Lbdh44Pj61YvOi8s5ZUT2Tqa5vntM89MpwQQliFQlV9taFrbc2N8VhwdGzEZ2qhYDwWCba1tDgujoyM5HPpefN7amrihWKe8XrTMMfHxxOJRFdXVzgcdhzPsixN0xobG48dOzYwMNDXP1RfFbvs0ktSyVR3d3c0Gjl8+NDeg0d7unuqIz6Oxe65PcMjU4NDE7t277McS9O1ZDqdTEUzqUnD9N10y5/+6Ed3lyybpNQ0TVnuQMTYdNetpa25urpa1/SJROL5559vb2sNBvz5bDZQX1eyrFAo5Pf7JycnC4WCaejIWDab9fvDmXSuKl6dKgwEfcbeY0cHh0ZKtqNz3afpDNFTZuxMTL+cr+m5LtKJU6KohHH5Mhm4Z7TaAgAwUSrkNeFFuAFSlpDAYBKZ65EEJEPD6WEIUpLKZEFGukZMAzA0XdO1kvSiUisFAh7npGseCE944IErhURiyq2qo0oPMAwTJPl0U1iOWyodTR1JZlI2ecSJSwmSiEhIT51x4XlSSATmuR4DLoEkSc5Z3skhMk3XuKYTggC1I4qEQ6YkyyrphoG6YTlOyXJNf9BxheMUSGWFIYJOgAQSpt3JEktWSTngSdJ00HPaCUAaAgBIBMZVnFYqNywQIdKLgx5mHKTT2e4zb+oXQ14IAIyoLJdIEqZTFGZJ5wn3EM2y7ssiW56C/gROqdSapum67tgOAOm67kmpIxSskq5pRavU0NBQ11A/NTVlu0WXDFfaydSUxrX5Cxb/9w++w3xGe3O9Y5dKxYIr7GAwVCiWBhPjusHzpWJNTV1VJDY+kSLQBIHnYiaVCYdiWzY91zN3fiQSueSSNbbthqtrjwwMDY+Nj0wml5+1YnxqbGRkHKXnMzRDN/zxEHBM5Qslj+pb5rS1dmQyuZ27dk1OWQXLyWYyc3u6Pc8t5ItTqWT/UP+Bw0de2LV37drLTF84m80eOnw0GAxFolXp9KTr2oDQu2z5wPAYMC2by3ueU8oXDu/dv/biSwaHBjWX1qxZE6+qsm3r0ccfC8eiFgnbtjzbDZi+5obG4eFRXzC4efPmcCSy5uI1POAfGRgePDo4Mjje3NzkrwnaOWc8W8y7LtNMQYhEjIhxDRgCoJRCkKdS9BBBSuBcF0IWiu6mLTvTk1Pz53Y6kqSmmz5fkPOGzuaoj3Ny/aaBFBCxWCQQiIZDVqnIpGxuqO5dPHciMV4Vj2bz2cmJyfq6+lg0Ggj4HNvWNC2TSXHEUjE/OTne3Nzqem5DQ1PRppUre82gT9Oxd9H8uqbWn917Xy6XCvj0ptYWq5B9+ult+w8cHh0d13UzEgqPjmTbWto0buqG/5FHH/nQh29rbqp94Be/2rv3gOsK3Qi45Glcr45HM9lkXV2NcO3mhqaNG7Zs2bTT8Bl/8Z53LZg/D0GAlCQhmUybhmHoZm1tsFAoSKDB4aFMLrdv/849u/ccOnJsbDLlugCIOtc5gHCd6aA1EVPZO0RqDlnP85SNPSsPgQCJgPwBv2VZwpOI7MS7/fdVwz8kBEQay5YKI9mJkD9eFYsGQfh1XRIjhiSBAAVDKSWBUH5OYEgEBqFByBE0BD9CzO8valSUJDTmMZZzRZGIkBESSARCYEREAV/A4KaVt0r5Un111dj4mO26rucSA9VPAZh5aylnAmOGpnm2JBWHAImAariYlEIAkASmcdTQ9URrQ9Nbb74pyLSdu3aNT00dOd7PPbNo2SSJaxpJ5RwAAtAMjesaCAkkpSeEFIFwsKWpecf2FzTOkUgAMcYQAJUB/KLhqf4/7RyYeQlztYKUEpEhkvLpzc7xUqI5LdMzaYwALwmdKU6YdGe2s7hs25an2p1xIp/4kp8dJQsGg0IIBDB0gxjqfp+maz7NbxWLc+fOdV13cGjw8JEjC3rmdLY1ze2eUxWPF3PZ8ZHRud0LhkYHa6qqd+7amctlJiYzwFBIGauuNXVmjwyHdM6EUxWLFMYmbdvx6cxnmpl0Khjy2XbhuWd3LliwEJFfe92bjw8M2Af2+w09n8/VVNXkU2lN08fGEpFwp26YuULprLPPnZxIBvzh9s55Gtdj8dqqqviWrVsKhRw3DNtzPGkXS7mR8eFi0d2z78hzm7bW19W1NDfX1tUNJ44fHxqJRQKaZjQ2NXMjUOrrN/2hmnhsxYplYX/gHW99SywcTU0lM5lkS0tLMBQ6ePiQZhjbd+0cGBsjKRfOmx+Px3u6u1uamrfv2ZHL51ede+7+gwd37NjBAZcv6Y1HY0uXLbVtO51MTxUK5Liuy3TdDyBJqsxGnLkQ6rqo+1cgcOHRiuXLq+ORzRuemUonG9vap9JZQFy5YnlzTaS1vgqFk5yatG0rEo4UcvmaeMwfjWqc+XSto625pbne7/e5riuEcGw7m83mcjm/359Op/P5vMbQMIxQONR3tK+uob6trevCC9fU1sUnpsbNQMjx4L77HxwZHXdsJ5NNHTp8+Jknn7QtwbmeSqYLhUJ7e7vneiNDw5rGdYMdPXrkv//7rltuvuHGP7nOc93dew9Go2GuYX19nVUsLpg3/+JLLhoZHnVs6TP9AHnPFc9v2rKgpz1oBCyrJAWVCvl8VhQLBSFlOptr72hNppL5QuH888/r7Oxe/+gT2aK9//DRnbt2GxwZEMJMziUAIgZ8fiAwfaaUMpvNzownKkcpyNA1T7ie5xARIjthvAOc4WoLiCQAGUddz7o2lQrMsgzOTNPPkDHGAUAQCSkYR8YQQAoSJMFEbnKNAXqu4JJQeEHQArrpoWQ6MGFrBmeeWxJSIhNEHAAlMUTpiUg4DC4FgkHdNDP5PCJqAJ6QM2kHyBgKKZVfVBJwXSNPpYGhrhvKH6+UTgoBnIhYOBTOZFJ79+3pbGurbqxjQd+BY32ecBubG4rFUiadBiLkCJKEENKVJKXONWWIIufJdCqbywLnyPi0T4ABESCU5fAlmjjjqEVENjMq78XRCjMCSLPjXcr7ADNpujPbkSc4fE9IJ4BZGbjl7ZR9GrPjcidd2Onltm2Hw2FD04UQgiTnnDPGOYvGY/2DA9XV1YRw1dVv4MKLhkONTQ2pZHJwdLiYzxkab6mr27R58/jkhK7r0jQsUdA5L+UhUl3T2tBs6JpE4fNpHN1QgBu6JGFbJa9QyNuW7ff79u3bC4S3/e3fGKZp6Og5xb5D+zjDpsb6gN+0rBpN14dGRgWxUKRG1/XRsdHQoQNz585rbmpMp1OZVNIw+NTkRMnK64YoOWI8Aa7LiyWpGfnJA1PpXLa1kG9paUFdI84nkuns5m2Fkq3rvgXzFiCHw4cPN9TW7t+/v7W1LRqJ5IulL3/ta9FYrGvOnMnJyYMHDhzr77/wggutXCGXTG949rlcPheKR1auXJnLZBpr61a+88/3790b8PvXrFkzPDxsmuZll12GTz+rB6PPb93puK7ONQ4gXnrOcaano8KSuq6/sH3b6tWrmju6BvoHc0cGbYvq6+p9Bk+MjXQ310rUx8YTsVg8Eo2lkknGdUkik87pAV+8qkqNIeact7a2mroxMjKifBeIGAwGiYgxHo9X6YY/lckmU1M6x0Kej45O7t53+Kf3/PLosaNVsahh6Pv3H+g7fNhznVi0GgAikUixWJyYmCiVSlYmRyB1nTc3N+azxVy2uO6Kda6Ujc9tQsZjVeHa+vqnHn9uairV3taVy5Ym7aRp6kAuoHbg4MH+wRGdNabTGZ9hNDU3FwoFMxYloqJlxePxqqoqn88/NjoWCIbmzGm/78H1JSuv68gZkCdVqmz5XnUcR0pp2ZbP51O+L5rpOBIRY+B5XjQWXbhwwcaNm5ChMnRmPwUI/+9bv60Gnj6QacJblNs1f3JDJm83NTQI18pls1KIxvp6EtKzHS5ZKBhkDLmGGkcCIgBNMiZZoWiFozHGWCqZzmQKkVhcoheviSalN+V6WccpSlZySQiUDIkoEowywRkhSj4wNFAoFpSZ5rkuSKmGGziWAwKEkEQASNITSIwzzlGzLauutiaZTKpR3iqYJpHMoE8ztKBhSNcx/KYEAmC64XMc1zDNUtEqlUrSk0gEkiSBynlgoEQVCZhwpRSCM8bVgAUQiAREKIEBqh7ObCtyxnvLABhJUMnE02cUibHpLLmZl/O0H4rk9Iu6HHsFFGW1PcFKfTG7aNZghxOcticHZ8vbUaicJM550B8IBYMeyaJtabpuu7bpMz3Xa2lpNn2+xobGqdRkTW216zlDwwOlUgkYaFaWeUXXc4QQjDPD1F0p3aIV1Hx+wyxaJdS4GTKBZDabEUJwZLlCEZivsaGxVLQcV6SSqWg06li2bhhz5vZccOGFW7ZudexSKBgqlUq6YU5NJcfGxmzXQ8YRcd68hUt7l0Zj8U0bNk4kElPJCV3jtfU14UhwfKo/my0WS9TePs/nj6xbe9njjz8+Nj7mul5NdbVt20uXLNEY6+7uqY5Xz5+/QHhiKj2VyaSe27hRpYPEq+K1VTX5fP6ss86qqao6fPhwJpNJpVP5XH7Hjh11NTWXXXpZoVgYnhwDIRcvXMQZi4TCgBAKhaampkKh0Pbt27ds2aL7ffsOHz3YN8T1EBFwAuTM9Twli9MXeibdXKUxdXV1hEJ+QF4s2PlcQWNafV11TXWwpa6qd9G88dFRbpgqn2fJwoVCuJnU1NTkpCARCAYaGxurqqqKxaLP5wOCdCqlaiOoO9BxRaFYOD4wlJiYLJYcU2ctjfWeZL9a/8RTz26eyuRcu4Tkcs5DAX+hkI+GQ9VVtQ0NjZZljYyMAMDY2JgrJBExjpxz09SXr1haUxO5+upr62sa7v7Jj1evPnvf/v3/+Z8/9vn8q85etf/Afr/fBwRH+o4xQ2cav/Tii275kzd6pXR9bXVnZ6fP5wsEggTQPzgEjEZGRzraO1wXDh44ghr/3D/9y77DfYbp40jSdRnpUs7uO1Jra2soFBocHMzn84wxde8L4XV3d3V1dfT19RVLecuy0umszg2u6crqLz8FZ7htywAZETKJVf5wbbQq49ijyZzBdFtALp31G0Yulcnmi4CUy2Xnzu32+33C82zLdUru2Pgkm0iHwuFkMsVRZwGPc+m6QkfSHFeXpAHoXOWLgen3CU9EQhHwZDgUKzgle8SxSiWOzLUdQ9c5546Y9tiqTFjGUDcNz5Wm6ZMCdF2fSCRmhy055/F4xB8OEMiAqRdzeZdLQeDaViTg6+met2f3nlg0hgyKhaL0JDCJgESoBkio0gYMETWuREwQAUnOppN7BYmXG2eAM+kIJF9aU2FmwJ6q0VGW2pnfvCS0+hLH7gyz5RVeYgi/JEpW/uEJgjv7WyllPB73PK+QL1RVVRkMc8UCIEpJtm0DouHz2baze89ubpj9Y+OpdAo1RI7AIKSBD3WJZPh0kI6Uno9r0XBEE1BVXXNkcHBweCQciXR3tJqMea6jm75w2PMkIyk0jmetOHvHjl2u4wSiQUQ2OtR/371jXXPmBP3hY0ePCYltbZ1XXnHNVDrz3IZna2qqOddqa2tdz7377h8mE5Oc84aG2tbW5snJyfq6+mRmMhoNX//mq89aufpIX99ZK1a0tbRuf+GFZCppWVZra5snRCQcraqqDYVCidGxaCQ6lZg4fPTIkSNHeubNO3r8mDYy5DcD0XCECJoaGutqa2OxqrHE+LMbNzDEnoULCq6978ih4dHhlsYmq1RqbmiojlURQiqb2bVrV3d3dzablVLms5nGuppkKp8pCs4N4biITOlsuQ9SHsKnxlY11DekJic8AUWrFAmZXS1N7W0t+w/uq13QpTP0+UzLlVu2bp3T1ZUtFE2NF0v2VDJdV1/d1NTk9/tN03Qcx3Vc27YDgYDq200jMV+0srm8zx/MFe2i5RiB0DOPb3jkkadz+ZIEICkZ14QngsFwKBQaGx4xDb9hmIODg8Fg0DTNdDrNPM+ybClISs/zxPMbt7iymM4Ub7rhpk3PP3/OyuUL5s4Lh0PJqczu3fuTyYm6+pqVZy0fHBq0PEHIn3t+C0N2+SWrg5Y3NpmKRmO5kptKpZ7b8Ozy5b2axnVDj8fi0mNbtm9vb+880DcoBSCArvlAoqahpmmlUkkIwRgrlUorVqzo7u5+6qmn0uk05zoAqAC4rhuc80suuWR4eOSZZ56NxWIlyxZCzI5hnNFqqwo9c+QN1XUamFB0+o/227aj+YxiqsgFA0TkZjpf8gdMXyjiEE6MjpuGgZK5jtRC0bGJqaFkFpFx9LSQG40EprL5qupoyBCS0PXIIeAaF47LCHXGAz5f/9H+TDrveI4k4ozXVVePeYKEsG3bczzVawAAjXPUmGkY0Yg/m8kyiYGAPy9cKSXnXPWjw+Fge3uLhwQgAz7TKhUlJyJgOsvms6NjI6FwsGSVmMb8AZ9tWcIFKQkYqnDZjFeWITDOGUgJnlSjdhmqamcoXA9PLOYEL45owOnkLijnMyACKCGfdtOW463T0ZPZlizirLjZNDQz1OIl+5slvmVnrpwZZVdWWIAXrWm1gkpHzWdzUspCoRgMBl3hedITUobCYU+I8YlxjfOQ6U+NpQGBAQcJluvYapivxLpYQEfdymdcWXAJTW5OARcMPY27Ag4d6muujUfDQULuMw0JYPr8iBwBL7rwgonxsYHjxwlofHIylU5aVokB6Lpu+sOlklUsWRdcsKa9vfPeX9xTKBQAaNu2rbW11TpgTU0NInV3dwshXNczfdHMRCaTLu3evTedSa5fPx7Sg3M6u9ZccGE6lRoaGiqUbMfxDh0+PDQwsHLZ8kULFhYK+ampKSKoqalZtfrcvmPHauM1tmX/9H9+6tl2S2PzG66+qmiVlq9cEQqF+0eGHnvqScZwxbKlF51/QVd7RzaVHhsZDYSCjU2NF1xwQTKZ7OrqisViI8MDh4/1MwSfrnsSCRhJiQiM8+nbgkASAUjGWLFYXLp0qWmYnS3tw2PjPtNobaw9a3F3LB7NZiZd28plMwF/4Pktz4yOjnV2dvX19XGGSOR4nuN6pmmGQiEppXK+m4ZhGEapVNI4R8aKxVImk9u3/8DAwHAkHifAUDj868eefOyRZzK5AgkCEohAEgBgcnKyKh6LxWLd3d0vvLC1VLJs2zYMIxQKVYVDiDg+lrAsS0pyHA81bcfOPYy0WCS+eNHip555ulgomqZ/dGQ8VhUJBUOWVQoE/MV0DgGz2cK+/Qdj0WA0Euxd2us6x+5/4IH2trbL1l5ULJWmkpM9PfOOHT/+2GNPHzp8bGhoVOM6qU6rkEhoGIZyGqgbe3Jy8lcP/Coai7qu29TUNDWVcl0PAA8fPjI0NAQgw+FIsXgkHA7X1NVq3OjrOzKT76weyzPYk4CMMSHmJneeU9ilCR4P+Key+UQ6yX0+1/GsYlEHTTjoem4gYMTjkVDE33/8eH1tQz5X8ITkumHZnkAuiRHJYDBg2wWfX1/U0+nz+yaK9pTjpV3pAA8bEZIimZmKROODQ6Oa7kOETDrt2jYSCM8TricsV51ZTxLnmqZpQjqccV3T7KLFEAWC63lcErnC9JmxeLy5uc4TTs4qZvI5RwquMdNv+A3TAK2Qz9uOxwxuu0XH8ULBGCNeLNqO7QABSElCgiQpBQAHYkhIgkgAIgInZAhCcsakECCJqWQvKZEhQ8aQoVSuWOZ5HhGQcliroWgIAMSIIzFSERNESZLjdHkFpZKMqUibnG3bknKgkMohZoAE4M2+ZOViYGV3VdmTO31NZy0EAJXHUywU/MGgBApHI9lsNh6vEo7wUFTVRoNB3cpnk5lCzibLsvz+gG07QkgBjs5l2ORRHerCAbeQ0aREpudcMTw5WdtU57iliclEOBThxH2mLxwIAVHeypMZIe6viQRrfHB2b+/WHQfa5vTYnrRdZ+vWzeQ5poY+Xbvqqqumsvkjx4cvuOiSaCT69DNP2Y5l2VZifKw2HJYkNMPnCwYTqalkOtfY1KEhn9s19+jA8Uwpl0imXFv6TVM63ro1Fy+YO//AgYOBQGD1uedGI+F8Pt/f3x8K+RtbmjLF0q59B9Lp9NDAUE11tRDeQH8/57ypqencc87xBc1SqZhMpnbt2pVKp84/55x1559v+gJDY2MFy96xc3dPV8fi+XNd1x0ZGU2nU/l84Wjfka6uOX39Axs370jlHMsipsodgDadtQLSZYbJkdxS78KFLc2tgaDfZ/KxkfGqeLy+Nt7aVF1TW2U7jm0Xbdu2LG/P7gO2681bMG9iIhGNRsbHRubM6Wqqr2tvawuHQ+qqFosFu1SMRWOIqCzBVCq1Z+/hvoHhXQeOhKNVkUh4YmLywIFDIyMjdrEkPA9ANtU3uI6Tz2d9PkNKcc45qxYtnG+VSsMjo8OjYzt27uS6wTUtFo9JITVNO37smGbogBAKBEl4C+b1LFq44MknnxkaTUohwpGQ6TNMU88XCiXbBUBVHZBINre0vOPtf7ZwXueGDc889vizjc2dN775mmPHDq1YsbyxoWnzph3//u/fPjbQrxmGRFBxIBJSE0xKSSRnIjGqtJ4UQlZXV3V2dh48eCifz3POiIBzRiTb2tqy2czUVFIIzzR9iOh5tpQSgCPyM9q2Vfab58nJqbSJpo9zDVEDzgizxRIJsF0XyeBM91xKTExmMlokHJ+cSDPOCZiGupSuL+ATBD6fr1gsmmbYZ/qOHRvu6Gj16b4wI9IkaOacpjlIsHHb86VCwROiZBcKqWwuk42Ew4amFzMl4XggiBBQ41zXJALoXEND1/RQMOh6LmMMgThn3JMLFy9JpdPBcIgY1jc0+Qt5kWB5u8QYCzI9yH1Mgj8Sd4ks6WanCowbrueR53KGhq4JISQiY5yEREEEQBKkEIAzRipjgCCRkKTKZwDk01aoqraADDyljFJOl61RCQYSpi3amWKLpMY8Ek3HTpQ1KgkIiL3c3OgqSR6AAQg68Ssoh9poJhMZZiUzEJEadaq82yrN1jBNx3WQs1wuRwCZdIYk6n6NgKqra9LkFWzHYWQ7Vrl8mqbp4ZCuCadYzE15lo+DBMYQCVkkFAxrzB+M6sg0w7Tyluc6qeRkXW1NwO+3uT6aTCF6Id3/2FMPa8yfz8RWrb5ICBo5fszUeSo5KT1n5/YXgtF4fU31Q796sK6uQddZ76LFY+Nj+UzGc8XiJb2dPT2/eOCBo0cHm1rabrzxlqDp37p58+jI6GQu7QrpN4OXrbsUhZSuN6ezs7uz0/T5GGJNba2u60NDQ4nExPD4aKy2rmQVA35/S3Pz/n17zj33nJqaKjVwOZlO1rJ4V1vHonkLLrtk7ebNmz3brorHE4nJxNj4C3t27z1w6Mihg5Njw/Pmza+trenq6ozFYrYjXNdrOnTwnHPPT2WK3//+3YlUlmuGFAiMSfKQ46Vr1xzevzds8IsvXH28fzCVTETjoVhVuJDPeFWhqtpapmFVKJhOU6GQq69vYGiMjo0ZmtbY0NDQWF8s5kpWKRwOh0IhzrWZ6sMwOpbIF0qO4wBQKBQeHZ8YT0xms4VsrjCVLtiWlUxOpTOFkmUDSQJBQiBKkk6plO/qWiCl19BYu2f3ztaWVp9pahrXNH1Jb+/Q8NDoyEh1dRWB1HSOAIZhCiH8PvOGG27IZTOM80gk0thYn82mAWFoaMDwBSRNd6EYY7phjAyP/M9P/uev3vuOjra2XCYXjha++90fuE5p44bNV1115TPPPD82PhaPV7vCsx0bNYYMXddRsY1yT1HZB4ZhWpZl286BAwfz+TznXEqVei+IaGRkVNO4lJJzXT2LMz+UiOyMVluF5wnLcsxQaDiRDJm+aDhm+v3FnMV1HU10bMk5E8IDAOS6JE0Acx3iOrdcidw0fL58vlAsWLW1jWNjE6FAUJDIZO2iW6hqaqqpicdqasIsEAwGEVYcHhq0XNk/OMYEDxqhfLLAAKUnhCcBQCIYBifOfOEg40TSJUA0OJiaIMkFeFZpWe+yeT1zi1Zpw+ZNgsPR4cFQJOILBvLJpPCEw7SiUQoHg8FIeHxsJBAJa3rI1HSdcwTpOY6ma5JASik9j4QkyaUkzyNElVULSACMGOeaxlWFCGIwLanAEKZrKSBIzxNSSkBSYx4YqETbmVJrRARSgpQERICMlbMWlAPhpa6CU6DGECPDE5bPDpFJOV0Me3asYHbSmOu6yquoNihdV9XwZshdD5KpTC6XsQs5xnUXGEmZz+V03dA1Q0iRz5cMoLA/7JFrA+VdjwsvHo2YDCBf0DHIhY9sbKqtI+lkMrlcLh+OVyP3abzoSuHphj8a4rZ99PDuxPhYZ8ecee2tuqEf48CRNTQ2WY7o7uquqm48eOgICe3Zp55FoIDhty1x4PDAlu37xxITzQ1d+Uzhrv/6fiqZ4prGdc3n8y/s6LrlzTe3tbYGDNM0DKtYOnDo4IbNm9QZWLJ4senzOWk5lU4PT0wyXQsFQvv37ImEA7XVVZqmxeNxVbI6n8q4NVZieAQZ627vAKJf//ph3TCq62p7OrvWXbJ2bHSktbEhFAoVCoWpqamRkZFMwR0eHe/rO+gz9KqqmmhIT2Q8iRpqOuOabTvRUCgx1s/JWrf2cs8t1FRHfQG9ZOd9pl8iDI2PhY4GW5rqDU33+wN1dfWtLa2uIweHBhvq63w+0zT12uqq1taWWDSqXJkq/5Rzns3lSpZt2zYRLaqudVyRyRWODQ7v3X+QiIF0S6WSRCalR8JlQAQ0MjoU8Bm1NfG2tqZYPLZ588agP0iShkfHNMNXX1+3b9++bDZdX19/5eWXW7a9YcOGRGJCCIGctba2+v2Bh9c/ND4+ppvBpqaGvqOHVX0Sz3UJeTlS0dTYmExO1tfWZFKZzs62hQvmPfXs825JLpjfc9ZFZ9XV1ra3Nf3Fu98J3Hf/Aw8Mj4xqjLuuQGJEYnZgo2w3+P3+fD6Ps9IfYeaZKpWKiKCKJwghhQBVaJsxJqV3hqstEoHODA1Nx8VUpmCZbm1NbTZdYKAD04sl29AMmO4Ca5ruq66pE3Iincl6HjEirumMmW2tDf3HB9vb5rS1dE9OJkslFgnXxHS9ULS46VEmn0qPTjFCk/s0CIV8xKRre+RK6Uim6ZyhS0JIqfsNZmjMx1En5IDAScicXQxEArZlV4ciZ1+ytJjL79m3J5nN6AHTNLWacMjzPEmkM7Q9B6LBnG0Vs04EvXQxlSykfOA34zGrVJzusCB60xFYHYhASs8TpHngMiBEicKTCAB8etQXQ6Yjc6VURjAACCAi1DWmsen5AgAAOAJOTzsk5HQ9GyIp1EgHxjhHjohCqMxhmincqyh7cme8Csonq1K7TwiXnRgcU/Xayz9XeQjlCzw9DE9KpnHX85AzIYWQQgKgBK9Y1DgLGH7Lsl0pdK6BhlIIAYIYeJKAQaZoB0weCgRKssSJ4lwz/X5LuJmC60qjkE1r5ETDwZVnr+o7PpQuOhOTKUHIma/kYFWsVuSSYBenUqlMZsec1vZgyM84+ELhoic1w//0M89FaurXXHqplc89/dSTC+fNXbBggeGLHh8YDIUiDU3N8Xj1hg3PHTvWV1NTZ7lOV1dXU3Pz5WsvrY9V9/X1ka5zxgzTjFXF1166rrGxsSoez2Sz/f39PbH56Re2zZ831zCMkYGBJQvnn7f63GAwMDU5JWwbAGPBYFtDk+e6Tzz+eEtLa/tllwX8/o7OOfl83meYTXV10WBgxRWXSSGLxWI0Gk0kEqFQaNvOrccHBvOF1E03vBkADV0fzSSzhZLGwPPchvraWCw0MdL/7ne8zWS4d8/eufMXmwX/ZNILh2OpdGF0dPzw8aNXrL0kaASqqiOBgK9YKnqenU5OcoYgBUmsikVi0XBDQ4Nt27qul0ol0zSVNZdKZXRdr66ulgSFQmlwNLH3wCEAJoWQwgVQpZQkIgghCAQIGY3Umn4jn8/XN9QvXLgwl8lpTDt75dn7Dx0OhkKW4zISVbFIVTy2ZfNmv6FrDEqO64+Ec9kc57ympoZIWHZh9+4dVVWxZDJFBMC4J4hz5vf71fjv5qaGs1YsDQb8m5/fHA4H3/62PyvlnORUYtHCebFoePHC+clUtu/YUGpqwnUsxo3pEZjSK5sFRBJRU3eves3ArCBE+RFA5Cc8AtP+OCkM0ziz1ZYxEJIRI4mFks19wZJ0pzJZvxnguhmMxwrepGW5DIExThKy2ZKm5Qq2R8xApnkS6uubmhtamhqa2lp7QsGQECJeVZ1OJTPp1NmLFxcKuYnEaH48AblUVX08k87lc6l80amqDk1l0pIQdeZ6NhABBx4wfCE/N5kR0DSTSZJAmiSXc6ZzHgwEAprugbdgyYLmzrY9B/Z5CJqGxUKuVMgCQDTk9+uaQCKS3PNMR++uqfZclxwMmNzW/elCwZYeajoaXONcYxwleUKA56JAzSAkBtPeWwkEUgjPFVINrQBUsQ/GGEkpCSTXQQMGnKEGKgGWcwBS014IITSVPIxEDJWPgkiSlATq9nrJ+NqT0hKgHDfAmaEQ5VLF5WyIE357ijQGeDFcJj2SRIzIc73pACECAHNcURWNWyXXtUuMMQYcgEBKZBgKRbmG2XSSPDKYLnQA6RUJCZhrhFKZAtddAV6xlPdcO7dzb6S2xXPs2qa6aCyWmpxAqaUynt+MSFNnGrl2aWQqEShpvkjEjET2HTxWX1s/d9Fij2uPP/sMed6KVatyqdTPf3Gf5gufd/5FlueNjIyNjU0E/IGmhsY9hw8WbfupZ55dMHce2V5zXUM0Gp1KJqeSU8ePH6+urZVIR472BQKBmuoawzS2bd8+MDS879DBYMB/wblnX3/11RqibdtV0Wgul1NVCnMsb5pmW0dHKBQaGhmOhKOxaHU0GvP7TV3XJicT+/fuZVzLZrMLFy6cN29eT09P15wFhWLRcUu+oHmsf/D8NReF62Lr1z+Wy+Zr4nUXrl75wrYtF55z7tKFi5OJ8eP+YDAQOdo/nM0XuRYulGTBokCoevfeQwGmVVUvMw3jeH+/bvCuOZ3VVTHD0JPJSdsuxWNRxlCVLvQ8L51OW5bFuD4yOh4KBQPB0OEjR/cdPCSZxg2fKNiCJJIqESoJJIAAJL/pi4bDvb3Ljx071t8/rOtmLpcNBYNzeuYcOz4QCgaHR0dbWpqrY/OBKJ/NzJ83lzN0HHtgZNyyLCHFz3/+83Ao+KY3vXF4bDRfKMZjVQcOHLYsm2vGZDKlan2Fw2EAQKR0arI2FnVtt7mx8d1/+ZexUGj7tk22U2qoj7e3NGdzJcCN7e0NqUwhmcowplmW46kwyUnTMJx8b7/0S1I278wSBKB4PN7W3nJmqy0JBGSaBkzzGeHG1qY9u18wDb8gdISY29aeSKU0HwcpPVeoXnWx5KjStpFonBAlsblzF6YmMz4z7PMHFiyYt3PnC1OpzKIFix3HC5j+9qZWq5gfL0ylJ0aMoM/gZOiYzia5T/fIC8T8ruMwQuAM/FowHGBMMg6MkSRkTGeGEfIHOCBJMjQtZxWf3bxR0zWpUa6Q8xtcuFbAx1GSrgVKrKiT5nqCpIwR+UHT/CaF0QNIFR2fxgA1ZhoSQXpCIukG1wUyDT3XE65Q3gJiTDIGRJwhIghPSCHAk4yQcYbTtipKlGpQFwIwrnHOBCNE4JrOADQATSJ4whOeEBIRkAO5UtmzjE27b8s+gpfeOipPdybmVl5n+o6kl2SVvXxFBVCvfZgp9EPAUAX5piuLC8eRCIAwNp4QroucEQEJAaCGFKPtuF7JkcAlspzleK7HSEAuzxAzRcsIhn3c08Hv95mcGWgED/ePjGdLc+fO7+09q7ujPaDxX/3qPs3EtDMhPZdxjfl0l3nJqURHvP6NN9y4ZdPW/Yf69FDw+NAASllfV5dJJWvqG9/45htqauqTU0nTMIeHRupqqgKmmUil2rvnDI+OZFPpI31HDx44qLJZFyxcEAiHR8ZGhZRH+vqKpaLf54tGoy+8sCObz+cL+WVLl5y/+oM+QxsbGQ0EAqViIeD3+UyDa9r4VGoymVzcu0TVhEPOorGopjGNo99vxmPhkmV5QobD4XwuHwgESqWSoQEZLBSK7Dlw4GDf8f0HjxSyiZpoYOXS5Vdddd3jjz0BnrOguwc8UVdbFwlFk5PJxNhEIpnQ9LCULBSMuZ6bSeeCAX8qmfKkc+Dgoc6u7hVnrQgHQ8VioaamxrJLhUKhpgZcx7FsGxHTmXQqmc4X8t3zegzDGB0d8/v8iYnJqVSxWLKEEJIkn55RSapYAQDFYlEN9b6+44lEQkj5/PNbg0H/2SuXX3nVlT+/9xeFouUJb+fu3clo6JprrlmxYnkymSoWC21tbbv2H9i7Z69VtHbv3n3VlVeYfqPQly3kS+FgdGR4lHMuCYihEMCQVVdV5QsFw9DOO391c11TLpM7crwvl0s31ITmz+/KFXKpVGbnod2JidTW7dtuu+0D4VBk996Dd/3gJ0ePHeMMEdE0fbZlO67DWXkm+dmPw4k3djQWy2azVP4OMRwKn3f+eYzJM1ttwQPmKzqOLcCQ2FjblG9IJcZGwJWMYWEqE/dF41XxoaEhkA5D1EzGNATbYwi6pjU0NEtCT8qW9pZEIqEZ5sOPPgFAZ61YtWJp790/+oHf0GLh4IH9e3Sf21ofB50FbEtKR+em8IHf74uEg5xzq+gULMsMmZrGPdcDIkTGNYYaj+iBKn8on8rW19WPJCdLwitJl0qF6ppYvmB5llbI5WtjMTdf0D1Xd12/EEVpgZ/Fq6J2USbGp7hhV8erfJ4tiUxds7xSyZOMMY3pnDEJJNQsewgMUEiSSJoOUgrgoOkMPUnEwVMyqwZ0AwAjUqPkSUrSOCAHgUJFyDTONU3zgCQwJjTuAQoSriclIHAC8iQRIkOmSaGqmCifMCEy0tTkGowRkQDAspFb7j3hqbJ0yyAiyZkp+aYL5hGBACAkIPLUMo7IOUNdsz3HBamZpud5IEkKjxEwDlzTEMjUDRvcouUUbWFwFvD7CTGfSxuMfKLkN4wSD4ykPWZw0O2cXWSGduToodGRwfPOOaero+NNN//ZI489nhlKAGAsUiMZc6lkuaLv2IDjaNe/8aZvf/PO8y46+8ILz3/qyadtz4vV1s2bM3f54mXDQ0N+TSPhNtVX64bBETqyLU8+8hgzjKaWVn8klMkkxxMJx7J006ivrWuoazBMXy5bGBoeHBke2rZtS6lQ6OrqvHLtRW97y1uYkInxCSFJSMpkc/F4fGhoyO/3M6Z1tLSEQ2Hbti3bDgb8gDYBZ9xADj6fXzd11/Pi8ajrCM8RibGJQjETj0eTqZSp+8bGE8F4zMdFQ33dZVe9Ye/ePQNDR9/3l+/xigXGZCAUcKVrZdOGxiORQDabEZI822bkrVlz9vwFncl05vjAUMmjrbv2+v0BkELN4lNf1xgJR/P5fCqdVFUWc7lMJBqcSo2lUsnOrp558+Zt2LBpw8atWQc8z+MkUApSYx8lgQAhRCgY9BtmqWQd6z9q6P5CoUjgxqvDK1eu0DhbvnTxgQMH33jNld+/6/u1tXVHjxzu6mgfHhzMJKe6580VTpEBhYLhYqn47Ibnli1btHzZ4rHR9NRkvrGuaWx8BDiTkkKhYHt7+1VXvWHnzh379+06dLivpaV1Ye+CrJUN+gKDR4c1nYFkRw4dPbD/yKNPPL2od/Gla9aYHOZ2dvzygfXcDLD/z9x/BkmSnmeC4CddhoeOjNQ6s7ToqmrdaAAN0RAkAYIczAyH3Nsdrs3t7ok5uz2z+3Niz+zO1vZsbedsZufuuDN7M+BwOOQQIAmSIBTRQKvq7urq0pVZlVpGhlau/VP3w7MEGiR3936ctVtZWlpEZGRU+uevv9/zPkLGgvNcIecOvAzMDIdDqY5hsXQxK4UeF9UUwh4dH2006wJIAFMnAQiUOn/x3JkzyyPl4ie82kIpVSFfsJoZ08p2O13TtCqVKuMh55wxlkSJaZqEENMyWcKkUhBASrRSviAkaLVaL7z48t7uLgTo8uXL2VzOdd1yuXxiadk0jJMnTmyuPxgdHVWCb9fWwlhomDCpMCK2aQUiQRgIKRIWMyGdnKOZVPBU0IVYkmhEy+cLiInJiYl7vV6kmECqM+hCzgiQg0ZLF5KH4UxpBEnZ8QJESDlX5AFjUtiF7Eh1EnCEIa03dzrtnpQSEVQwNUx0gqiXJKEEQsBEYQmFJAADDARIw4MRAFii1F4AEwwAADxlXQH0yBWXpyKYx64xCCBA0lKLMcE4zZSAgEmFFY+4AgAhKLlQSqae5BA+5VeOoAJAyb+mhj7NpQUpn+HnSWMQ4ifiifQ1Twsijgn3x6AzSucJQqS/CSKBEeZS8oTB1AYXQAiUFEIypUSim6au61wIxpkE2HPjGAECaKVU9txBozXgCicMChalFwCmihCsgHr/w2tX33vvqNH83Oe+YJjG9u6WTKJBz233m7FMMMBRBLd2t/7xf/6Pv/PHf7CxuU4QjvwgY1kiiGdGR3f39jzP63Y7pmlmcwXNyJi2/du//du3797b3d33+v35hZlTS8vNZhNhvLL+cHFhybJszdDGx6rPXb54/uzZXD6r6TolRCNUKZWO+A8ODg4PDweDQSrHKhQK5XIZAqBrmmEYCAIIJaWECw4RjONYCJGwxNBNIcT29q5lWfdXdra2xMzM3OhIdW93d2Zp+R/9b/5zTSd/+md//u7V9y+dvzg/N7N6987OznYQBaZpEGrZ2dzK+opQREZs6LrL89PLy0tSyUajkXWyR/Xmg5WVs0uLJxcXpJSNRmNsbMwwDAVkSixRSpVKJQDAxMT0/sFR7bAFoXZw2NKMjKaSMAqVEKmM5nFHCAHUda06Orq3u5skSep/RCmdnZ1x/eAf/2//d5qunT51+qdvv7uwdDLr2L1Odzh0y+UygGhifGJubr5UrE5OzliW9Z3v/OELL7507tzp//t/9f9ACExMjLXadYCxVDKOY0LI1avvCiEa7e7v/Pe/e+f+6mufevnzr70GRfzuO2+VyiXdpNls9rd/+7cvP/fiB9ff/+EPvv/ZV19xMplXXn5hY2t3OIiBQgeHR+MTE4sLC+9dfRdwCSE8FsaDJxgDhJBzrut6sVS0HWt19QFjDKSbPwWlVBMT4xsPH3yyq62CqdeBZVgLcwv1eg0hPDE9fXi4E8Yxl4oaOoTYcXKFQiEIAoSQoeu9XlcINTo6MXB9zwtsO9NutR88eJDJZPb29sIwnBgbbzXrUzPTd2/fvH//fqVSYhy6AccQREIxrqRQiCBMIcSgWCi6bsiYCAMOIVRCQISL+YJgfNBoQyl72ez0/PTGzlbIYqDkSDZvYwzjxO37NBYEhwtzc2WsD3sDGauYKwV1qjnb2/uLM3M8SRwrqyRXSlCKpR9omsjn8uHA1w3blYIjohASLFYKIgUwoRAAwQVUilCqlBKp0AADBQBKhREpS5copSQAkCAMESSQCg445xICStO0SoWgIjpRAmKMOcESJlJJICHGKHVsOHbABccCJIQQUseA1OOv8CntLwBPFuCxPgIA8IgH8WTq9miX9RTI8KRBoJRGQqg0doopSHDK+oUAQClRanQmBVAIEBR4ASYEIogAFhxABTlUQsF6axj4ngBIKgAQVgoqQABQGtFyTtYPfAkB0siPf/JXcRQmUlSro3NT0zvrG2edS9dufgSUZAr82z/6wxMnbk6PT6CtbZYk+Uz2xOLioNu7fvOa53lZJ0t1clA7gPV6rjw2UhnZ3tkFQuYzzksvfmFhcXbgDt99/71Gq9X3hm+882bWdngcv3Dl8v/iH/3PNYIjzrwg2N/dS2A8PzvruZ5SyjCM5eVlAIDjOIZhWJaVuhlgopuWiRBMWJRCpRBACI9lTpGKup1eo9GwbXt6etbzXATxxtoagXB+eqpcqVy/fn19c7OQy148f3713j0nYycsghAYhlZvtLBmQkR1zZZuL4iC7b1tCVSnM6gfNSanpqYnJ9qNRqVU5JyHQZDJZCil6Vm0LGt8fDz1CwcAJtGg2eh/98//8uTp87fu3O/2vZDFqWpRpqqgx+EgQOma3mm3m80WxhhAlSRBLl+8dOnyH377T3b2DpSUN26vACFOnTvz2quvTExNIUJ6A3fgum+98y7GmpSg1WotLS0VCuWd7YN8Lv+bv/kPgiD+kz/+05Mnlx9ubCIAkyR5+PAhY4wxplm2G/Ef/PhNCOArLzwfDPulYp5qxMk6JyenNja2/uRPvlMo5vvDfm/Qn5ic+c/+0X/08MHardsPDFP3Aq/WqNXbdQVkmg2ohExTWZVQAABKCca4WCy2Wq3V1VVMsGEYxxcFgErBfK7wve/9ZSGX+URXWwggVEgj+sLcQrFQDjzf9wfr65tSJaZlF4ql6Zn5Sqnc7fTarc7s7Gyz2bRMmzPe7Q04F4Pe8MTyiVt37rz++utSymw2Ozs7axhGzx0SAsdGq5dffN4b9qYmJ0bnZjbXHnSjnu8NjxptFgFqGbphUA3GLAYIcMkV40opxSWkmuTCMswkiAlB9aNaLGKkk9FiSQPQQBj4sWPY1EhsR8MA9pqtKE4gxJ1+3ynkDUALpXKz2YqiQPCIx/Fg2DdNA0qNQMV42Epi3bL7oetKxTUNQ0hipoREECsImVQIIUwIQBCnebsAcClS+FOBdMKEIVDoUfycAkoAiSmVQDLGZCx0XT/uNxHEBAMIhJIQEAUEUkoIkcrShVBKSQUgkBJL8MhW7Oc63I8xEB7xQ5489bip+Zgg7UmBfhT7ns4WwjAEAIBHXg2ScQAAUgDKlG2c5m2kNwyEIZRCQYAwxKnlklJAKjj0Ywj146jlNHVYQoQRQThKIiGFAgBhDCl+/8NrkJLKSPXKs88X8+Xf/b3fG/iBZZkSSC2Tee/Gje3d/cvnLyAlcrZ1/aMPM6Zx1AbZbM7JZisj1XZ74Adh3Gw6GScOk+pIdaQ6GifJd/74j13P3T3YhxgpJTOmmc1YMyeXf+WXvgqRSuIQQGQZRnVkxNR1Q9M8JVutVrpVt23bMIw0X0MInvLk0r9tksQAAMuy2u22UipJYkKo4+jVarVYLAkhNV07ODwwqL6zszc5Njo1Xv3v/sW/rB0dBUH4K1/9arGQUzGbmZkCUCqguIAfXLu1vrmbMH54sJVwaGVs3YT1RqNgG5xzgvDE6OhwbiaOwiiK1CMLDkop44pS2u12HccZHx9vNVv7ewerqw/OnbvwcHN3v9YQEKUjgeMzLmW6N1JAaVSzbTsKA8YYxtTJGs8+d2F5eWl//2B3bx8Talu2YRhhFJZHqgPXW/3JG51O5/SZM1eee/773/+B50ZKyZMnl2/fvtXvD+7cXhkMev/xf/zbvV43jNyl5XlE6f0HDwEAURSl92/JOCQUUuvm3Ydvv/v+L33xM5NTk812M5/LmoY+HPQvnD93/uLpuZlpijEAQsfy9ddenpue7g+HP3vnLUPXwijCGEMJpFLFcqlSqTx8+JAQjCDinDtOBiEIIJBSTIxO1Gq1x4sfQXr13fcrI85/81//l5/oagsAlEKNjlTzgm+ubywszG7tRKZluW4sJGg0mq1WDyp08uSpvb19AGA2m0sSdvHixbX1LYRptTrq++HJk6f+/M//fGtr+5vf/DsPHjwIw5BhiCicGhulGALB7m+uLcydbnaGjIpWtx/FCQWGbugIQ4SRAlICgTHiTEnBMUS6phm67vlBrliIPHd6Zqrda3LAbYqzulktVLgb6ApFesbrtS3LjBnPmLm+64GQdt0u1c3tne3TZ0/VdjcACJFiTtYen5quHR4iSMvFYrfXzugmB1D6vu95FtF1QOxMZhAGsQKQEgkAhOnoCyGMlVKAJ0opDCEEUHKBIYQcCiFTPW66tVeawhqRQAohFFIQQJyWZgSITgFGjGKqYR1THsUsijGAgCnGmOICp0G9Ih0oH3uaPJ189bedQvCIfPbk+BvMHR4jEvDYtRiq4zvG8XwCAgmggjA1xJZcAYowwul9GeJj9AQCCBEGACKFARAAcgyVQhAqEEURZAgiKACgBEMEJMVY05qDwf/rX/7Lf/DNv3/+8qXv/+j7fhwpCBHFWLeHcbJ5uD9SyJcqxUzeIUBVR8e6vX7CZXV0auiy0A+TJF5ffTA1M/dwc2N3bx9AJWUiuAjD0LasrJP95a9+5fSJkwsLcyyJE54oICXjvhf4nmdQOuj1jw5rkJLxiXHLtFMLGIQQE3EUh0kSpzGxSZJkMplsNpvKST3Pq9Vqtp3RdR0oFIaxruuDoRv4kVNxpJAYqI2HD2pHR9u7uxefufjMM8+oMEJS2raZsMgwzWare+f27YnpeZ3L+w93mABjY+WLz5yIktiolJeWTlCEpsbHHVNHhGqabhhGJpNxHAdBlLCEJXEa+MgYE0LmstmzZ87U272dvZ2Yx0KlxGr5sbMNAZRStVptyZlSACP4pdc/X6rkb9y4tbG+TQkGQE1NjC8tL+3u7rqDvrm0CBBZ29yqN9uXr1z2g6h2WNcNeuPmR7puKAW3t3anp8dv3741NTN+8tTimdMX9muN1N4sZR8qpRDgUgCFtFqz91/9k/+WAPX651/N5OyMY/u+K5U4cWJJSn5wcFApl43hwDKMr33ltZhLALH6v4VXP7h+1GgLpQRUAIAwjnb394RSUAnGk7GxMc757u62putCgO3t7Z+/LmC708vlDaU+2VMypRQCKokTqKFCvtjr9JM4CYJI06zxsfG5ucVGvVWvNwEEhUIJE1zNFQ8P9re39xjjS3NL7e5g/7D24osvfOUrXzo8rH3qlZefffbK2traj958Y7/WODjaz2btSj5/5sQJpfj84sJu66BSHm0OE8vIEBNjigzTHAzcMIwQwBrViGYSCKMwCv2AMTYYcEOjewcHukGEFG44dON2a/fAhLiSyZpEIxoceEMOaKfRxRT33IFtU4gVpeSNn/xkqlrUEMQI2k4GKGnZttd3Dw9qkiVREOfLxYmpmTCOQj+mSIsFjyHiSiiMBSRpwFRakqSUxwloSkEIiE4lY0RJA2PTMOKEhTzBmpYIBQDAmCKERSIhBIZlAQylBAADXdM0oDMueMx4ogBGQiiIICUEYAxScZlUGKQMs9RtLj1+nnKg4KNI58dI7pMnH3NyH7/60dcn6AQA4KlG+fjnlUy/gQpI+Ugbl9LaYGrSk7qeAZnG06UDOASO84vRcTwFAAAKLhAhCsiUASFgaiPMOQTf+nf/7sK5M7/69a9fu359d39ft0wBAKJaq9PtNhtba6vFXKaUy1lObuhFvh+2251SeUSVQNHJ/PgnP3nwYJUrRYgWxiHVKRdSSUUx/coXv/SZl19xbFOyBAJJMY3iaG93v1FvJiz5sNsbKZWr1ZHpuVnDNB7Zzsk0K4ASoqQkBBCCR0YqAADOue/7AAAheLFYkkL6XqBpepql5AXR7bv3R8rFyampD29e73U6X/nSl3/0Vz9ee/jw6tWrv/L66xlDd4f9KAiLpWKhUMjlsz97863yxAJXwAtcwxgrl0pbG+sWRuVSMQo8CEC1UoEYSwB938/YtqbRIPAFFxjTXDZn6AaCqNVu1Rt1Qun91VXX9yQEXAiS+h6lJMU0zTo1dAIJlwph4eT08dGpe/dX7ty5JaUaqVS/8LnXGEvW1tZuf/RhsVQM3P7qyr1Wu3Pu3Nmtza0oDE+dPt086ti21e93YQ4DSXqDwfr2VrGcK5fyLz7/3DMXn+0Pve2d3W63q44tagEECkmpEAAQhom4v779uc9/plwue96gXj+amhqnuuXYZhKFAKjBoN9rs/n5OQAVxPqzly62232MjZ29fYyJVCIKYy4YUABgBDHsDXpKKkSIadkJ41EcPXERgUApRQh+4YUX+oPhJ7raAighAodHh4e49cwzL925dSubzR7WjrJOiTNkW/mXXjq5vr5xsH+QJEpEcRCwTLZom0Z/WONSEV0vlCt7e/tnTy3mc9mVlXvFYmFmauL1z392t1l7sLPR6nU8wZgU1IQJ4QftFsaaRjSlQUASRAylSBjwJGIagX4QO7qhGQbVzWajkS3kmEioSWMhAy8UUcwDzyaI6FQBwCHv+r6ZL3QGbqE8NTKWh4BnM4bv9YIoRgqPV8ctXY8Dj2iIJ7LX6FCNUoyITgXHg8GAuFQjlGoahXI4bEYJd6NIWUbMADEdoQBGKExiyblu6JphQ4gAkAgBDJUAQidiqlwJvaArIoGUwkAnJmecpHRVIRBBUCMKQikYAEJJAYRSXEZhKIXAACgm1DHclrIEkOQSKQmgBCm8AABECKhjfe+jWok/Nkn7GICQPgYeed2D47TUxyDvMcPxiVLiqRIMIZAQKgQgghAhgIBQEkiJCRFApk6uSj1CoJAiRGFMMNYflTCuAU0CkCSMEEJSiQgXQCGk1GAwgATfuHP79c+89uXPf/Fb/+ZbSPJYJFDXIi8sO4aBIAv8RpS0uxGQYnZq4uHDe9niCIAEkbEvfvlLb7/z7uHhUeQHgrO9rb1CsfSNr339c6+9trS4AHgMFcOYKkCBAu3+QHCRLxTjOC6XR2ZmZvL5PAQCAJWOPSnBUkod0AQnGtWUUrqua5rWHw6UUpZlcc4YYxPjE5lMtlarcc6VCsPQ2945wETru/7MwsKFZy6trKzoQFayjmPNff8v/2J5bu5zn3rVorB5VHu48vDi5ee//qtf++jOg7XNvbGpsaHXS0JXB/DKxYsZm4a+W8jnuZIa0rjgjLNSMY8xkILHUahRHWGsU0OjOgRo/eHGBx9cSwRcWVnjXAkgEZKKpbOkVGSeyhqglJGdwYWyzrhr67md7S3BEYZZw8Tl8mjq0GZbhmVahOJsxtrb3S4Wi6VCbg+D9Ycrv/TLvzI5OcqFcF03ChkEUkJRax0VCp9rHbWvXLrEo+DsiaXxatl3B6aVGQyGACEBIEIQy5hAyBP17//ku9OzE595+XmdKI3SdqfTG+4szi/NTU8oziRUQZxwRAjESpFSufrMpcvNzkAJhTFVUgGobMOK41hJBRAK4wRBDJEWJwoRoiA8TrACAAAgYWLbph8l23u1T3a1BVAIcebMmedz0crKRhAGo2NljHC5XE39zVZWVsdGx8fHJhqNRr/f73Q6AABd0wYDlyVspFRZWV1Ze7CycubU5OTE5uZGoZiDELR8F2XtbhQ0fS+SanDrJiGwO+gNA99niZk3NVPHWCBAAzcQCRcJlwAhgmORzI3PSJ5ADScgUZgzGJm2HvaC2B+UNI1yThJoGpahZ1WC4lhEYbS29jCXL5w9exJIs1kXEMadnjs5PhUNBhBTAZnv+1JJG9mKYGIYzPepYcSMHzWblmURiiUA+WyOC5HN5gMpBr4vFSCEVLNZ13V5HGkQci6gkhhBjABVqmDbXqe9u7Vr5/NOIRfwxHDMEEqFoIIg4UIhFYiQIowwRBAJLgCXiCkolWKcRQLEAj5yPEh7ZwLS7Icn+rHHTerfxPcCv+AB9tcej3def5O1GHhkvoAQVDD9BgEEhZJSKAEFRAghjBBSKmVSHUuBUxPSY7kaJkAhJURKSWaMSSCIBpGCAEAnawoJNKLt7R/0ut2x0fFmr6VrehyGOYNOjo0Ws7bvepTq+41eNptNGAvC0I9ZuTJKISYIff4zrz18+DBJWDafxQSEYfjr3/ja+OgoZ4xQCiGWSikhEMYIE4Tw2Eglk7FN00q3vUA9/sDHoufHfn2apkkpgzDkXEAAPM/r9XpRFPnefrU6Ojo6miRJu9XSNN22zPGJyf39vb2dnc+99trZM6d67e7iwjykZGZm5t6du599+RWMSWVk5N7Kg/euXn3mynOf+fTLv/dHfxa45OXnL7u97k9+/MZv/v1fdxx70OtrmiY4d5lbyOelkhhjy7JB6nqhASFEoVjIZDLdbtfzvEwuu71XGxsf769v5LJZ1x0gnJoipdrw1I5OKAUFxxmr7Hqk3XKFEBgTKQFCsF5v2LaedezFhcWRatXQ9ZWV1Vq9MRgMUg9GCMDNmzcQhopLSinBFEAkAGo227XaUeVUwQuC7/7ZdyenpsMgKJXKo2Pje3sH3X7vaeE4BMDz/H/5r3/v6tX3vvn1X37lpRe6nVCJqNUe5LPZ8WqFC0YNmzGeqt6FEPfu3XccpzIy0mx3IFQSCIPq4pgODtPJNIIoSSLAjx86xm0BkEj5SfSXP/zxtesffaKrbeoH2Gq1H9YPZ2eXDg/2BkNvcfHEzMxMGEabm9sXzl/c2dnVNG1ubv699967cOGZd959e2Jq8jd/6z/Y29t79sqlL77++Y31tdD3bduUijEWtVrNYThs944SBP0kSoBsDAdREummpgiSEFMdEwJ1bHr9wO15sesbGGdMA+saVtCPPH/Yl1xkDOpk85ZpsjDuR3EGoDxEjDHHtFmYDLhn21mkAcdOytXsxNT0zs5Gv9MsZgsY4kuXLgdemLXMrfWHkkqnWEQIDQYDKWW3XmdRVCgUICFKSq5Ut9PVdU3DbH5iKohCk2iVIo3i0LId07RjUz+sHZkAcCA5T4AUuWwWKEEYj6KwkLEpJeV8vucO+KBrGbqEkAOldAgwQQCrmEOJWEq5QjhSwqSaFyZSSvx0VRUSphMSBH8ekvr4TOznTt9T6vK/6TVPv/Jvfyp9r5QyrI6JbghCKI6jeQSHSkPUMIwkiVN1slJKCJWq3YUQKh2YQQgxkkAJwQmBhq4JCXRNwxhzwQbucO/w0KJauVTOFfMPNtdHyuWZ6gjksRSQcdDqdsNEWkrZWcey7XqrXTvcr+bzF8+fW119mMtmP/3qp2fmpiVknufZhhGFvmWanLMkZinBIElChIhlW5wzeZyQJDhPMHoS6Zb+r4fD4XA4zGQyEEJN0/qdbq8/GB0dZYz1ugOEYKFQ5JwfHR2ZpgkRsixrdmbm7r2VJA6jKOi0Grmsw8JocfnFXLEglfzo2oftVnOkUixXqsVSa2//sHa4P+y3Tp+Ymp+bO7F84vvf+2EuX/R8P46HAIAwDLPZbCGfRxCmIb4Y4yiKOOcQokzGDoKAcy6EmJ+fz+TL1HS2dmpAKt/1MqYdeMET7sqx16PACAsB97ZbcRJLzhDESimMQRRFvu/3eznLNHw/XLm/WqlUZmfnWp32/v6+ruuO42ia5nk+F6zdbuq6CSG0LHPo+wQRIRST8vf/4A8+vPHRN37t1/P5fG9nb2VlRT7SPT7hzwCACTlqdJvNTs7Odbue5/qJkAIe9Pr9ct7+7GdeVRAICZECXIhev7+1vdVsdQGmkEAhOITA9T0huYaI4BxCCACUiiOI1VNBU8cVjECAMCJk4Iaf6Gqb3hFNy6QRGQ6Hk5PT2Vym3miura0vLizrGn/77XdeeOHFSqVy7do11/OXl06UR0ZinvQHw729vW63c+7cWQRgNpu/f/92s1kfHS1btmZLBHUrXxnZqddbw6FmEqQZEEIlOMYESxi7URh73jCg2MAKlnL5XC7DgfQ8zxv2bKpNTEyE3a6dgF7jKImihXJV4mh0bOSoWUeQFEcrO7uHiCR5wxmrjsZK7u1uzEyOa4C3G60g5oVSeTAc9trt0kjJylhBENTr9Xa7bZpmFCeFQhESwqVMGBMACqXiJBkrj0Rh0GocWbaVs41RJ5NwEfS6tWbL9wJzBBkYJUKEgceALBTyw8GAUqpTpGlYU9LiggeBCHwn54RJIoCyM45kSexHEBKCMaOYQ0wpSSKhG0bElQSSaBpGiEcxZwIrAJRCHwtxUE/iyB6ftY8V2V986m9pcn9hATzlgn7sUaZSxFZJ+ZQRr3p0a0aEkITFj64uJI99RRQEKI2SO747IEgQ1nVN10wuZZwwT4aMcwhpECWzk9O+O/QDb2p88nD/gAI8WsqvbOwIAf0o6Xkel0IjUCdYAeFk8/u1g3/x//kXmm4ahlVZq37/Jz8oVQq2ZXfa7dFKdXpqUkkZBqFpGpZlEUJt2y5oNIkjqbhUAgCZsBg/xaVDCA2Hw36/n3a7qUdqFEWHhzVN0yuVkcXFZcPQAQD9fq/T6aSuBQcH+46Th0osLS6Mjo4EgZfJWCOFE7plKowopRfPnxOCA0SYkJ4XnDl9ut9pPXP+zDOXL0xPTLUb7U+/+OzA87iIpyYnkygaqYxQStP4Ii65pmlpzK2u64SQOI5TC3MAgGVZ45azsrY1NTV1595KeaTieW4hV9jf32cJO2ZuAwARABJIoYI4lkohiCEChCBd11xXQKDVavUwCKSSjuOEYbS1tT0xNVGpVHK5XJIkw+FwMBg0m007Y0oJqiNVwzCH21uCS3foc65u372XLRZanY4QwnXdhAuEyeNO86mFBZSACoLrN27v7R/cf/BQITxaHT17aumrr38mXVmYEgJRs9XstNuvfurVu/dX791bgVIgpXiSGKZuZXPFQoEQWj9qRGGcuuA/dhx98h0AUCkCEUuiT3S1TRFud+heeenZtbW9w8PDOCmNjY0TQu/euT86OjY7O1c7POr1+idOnLp06fJPf/qzeqspEfzar/xSu9tZWpzPZTLXPvxobX19YnKUUvJwbVXXiU1UXjeY7+UgSDTixjGMI4JwHDEICVc8DKJLly5tb+15A88kGotinMuYuq6SOA4Cy8Req1W1HRnGo8Vyv9/PWBkOScLVzNxyp9s1bHt6ZrrVarWbncsvPPtg62Ec+/v7O5IlQMWEoO3t9YnpaQWytdpBzikIzoFQOtE0TH2h3DAACui6zrnoDzuUkonRkSRJBp0WpihggR5LjSA3iNwgDvxIQQQB5IzHUQQVIBjHYYigYkk0cPsV2+h2moHnGRgqoJLAh1JCIaI4ggpBDp1CqZlEgzjWjKwfhBxBDpXm2DxiABNMCdF15ocsjpU6trH7ueX7RKL48Qqbus/8LRLev+74OU3kcdFE8GnIQkkA0fGvQAgDBICSCgDdNgFQGGNd0xOmpJRSgNTZPf0kCCiAIEAQQQgRdHI5BCFngnGlJI4jIRUEUAhD9Yfe9MTEe++9e+HSBcZAu98fH59yY8Ul6LmJZpgAYy8IlE4FZ43GkWHZxULR8wNs6N/6d//m4OAwTOKZ6RmNkJnpaY1SwMXC3Mz5c+emZ+cE54RSigHJZ1M/dYRTO0wVhmGSJGnSF4SwUqkAANJ2EgAQhGGtdjQzPXv79u3A9xcWFhrNRrFYmJ2d7ff7hmFYVgYhVCoV19fWlpbmNA0DoLJOhispIUiSuNNqFXJ5hMmdu/fiOK6OViGQCYt0y86aujM5OlYpfO+vfnjrzvWpier0zIxGqEa1lCeQRuA8PrOu6zLGhOBxHPueDyEcei4TbHNrb3J8Il/IO4vzG5vbcRwf063hMQwv03krlBACBBEhJOMYk5MTcSwH/bDbbgyGQ0II56LfH9qW1W61EYJxHJfL5fHx8aNaLUniM2fOHB4e6bo2Wq22e91mu3X16nsYQSvjbO3vSAleeeWVvYNau9P9Oa7hk0kARAoAJRhjM0vzN9ZWYyH93cNPvfLy3NxSHDNN1+IwCoU4ODh4uLZm2vler1cuFocbnVw+NzI9vbu3PVEZ+ZVf/XqtUb93934UJRvrm+kQEDyCsNJfRyEtlYq5rF0u5T/Z1VYBAABjyfe///2RkZnPf/7zW1tb29t7M9MzL7740urqg2KRnrt0fn1tvd1qhaH96quvbmxtbWytt5v1/+w/+U8+eP+9bq/72mc+TRAJIzdhCVQw8EPFfV1DklC31w9jJiTgCfP8kHGpayZQGCqwcuMuRtpYqQohmJ4Zr9cPosBXTEgpm832aK6gGRmuyNzC/N7e3tAdahhxBDu9jpTiYH8XYrJ4Ykkp8tO33ppfmlmcX+h3B6EXIOJOVUe9MHb73cPD/YxlQSWGw77nh4ZpCoAg1RMudUqDMIzCQNe08XLRphiIxLaNWMRYQcMwEybqrbadK2ULRpQwiWmUxAPfK+acKA4MI6tTDYTh0tyUmcl2hsFO7zCXtfKOjTCMvDjhslCp8ITFke9FQYIQcRwmjqUBEkCEoJk1EUYAQUIo1BHvcRkkXKWBafB4zgUVRPIR0VWlRp/gcZWEMJUzHtNFnxwypcGmbNifP9JdGFRKPHkrqQB45HqnAAAKASSAEkAhJaQAUkmpFPfchfn5OI6YAhrROOexkFwCqBSEOM2fTRMsCCWGYSKEkIIYE8YixhIJICYEQWhQohhbnp13u/1+uw8AqJTLpmV6ni+ENCgVLOy0Ah4YmcnJcqkchnGr3+VCXLnynKbrO/tbmokQ0aIoAIa9urZhmsbl8+eXFpezTpYliWVZQnApJecCAkgI5kIEQRj4sWkaum6YlhHHMaEkjhNKNUwoQixhrFAoTk1NCSW7/b4fBLX33s9ls7qhx0mSknMXF+bCKDKtqfn5GUqJ7/NMxtZ0KuIodazClBi27YbhX3z/h5965SUAYavdTpJkfn4BAdjrtA1T/6WvfGlnb48SApSM40jXNYCgEgpCTAhRQEomvcCXEvZ7w06n4+Ryvu8nXHz3Bz/udgfNVrfXG/Tcfq/bGQzdY8xfHKd4KKWAksejUKUUUJhSQvVubyAFVADkioVWsxFGiWGYhBBCeZQkAICo3x96btZx8qUCgOToqDk2PpHEMRPxyZNL+Ub29s1bN24apXJRCUEI8YNYcJG6Oh+zusHT1h8KKA6A7PZ6N2/dMa1MzjDczuBnb77d67Zffen5s6eW5uemTUNfXl74P/+f/o/f/d4Ptvf2kYLPPfPMM5fP6Aa+e/fu2sPNRm0/TsKcY1IMQ29INQNi+vSKxhhTQiCUX/vlL3/us5/+JFfb4+zgTCaTo7kkSa598MGFi5eKpdH79++ZpqVpNEninZ2tcqW4sLDgum4YhlHo/dZv/IMPPnhva2NreWm50axvb+8qJiqFMhPR2oMVBeVY2fG8jqTE1mnEpT/0+z0/SQTGRIRsbGykXCrv722ati1juXRyOYxdwaSIGJIQCCgULFRGTp+7WNvZ7fWG49XxLc83dFMIFsehpVMMpQTq/sM1M5PDplFvtqYnJpbmT7z7zvsAGd3eUAq5sLgQ+QFjSRC7bjCMGI8kBwhLLhBCSMOGjnSMCrmsSpK+7zqOrWkEMKFrmuM4jUaLGkaYJDETQy9o9/sYqfmp6axJI7eHCUyA0nVStI2jRqM1DAnVCaEaxibFxLb3683O+jZBeHZ01LRMN4wJoklKRpdIIxQhRXVECVIEcwwkU1jDkEHBAQQAp+ZdqTsSkCpdxk+4X08Qg7Sp/DhLAUmEgJSKEJKSdh/xs1JdOUynYekaeBR1rOQjDhcCECmgCFIIKqUQAEoCAiHBKPDc0dFRa2p6b2+31+sBgBDCKa0CUUwglFik3S4mRAgpBeBxksvnaBz5YaCghBA5pjU3NeUPXJ3QCNHY60ZAJNXyudOnotADSvnBwHOHhWwu9MPIDfL5/ML0tFT49o1bXuBhAkbKWQTg0I3j0FeICCjzhfzJpROWbRmGBqGimEIghOQAQM7Frdt31je3ZqfmioUCY7Fh0kIh7wd+zinousEYY1wgjIvF4plzZ9vtdqPdPn/hGdPO6JQQKDkXhmHkc1mgpGHoiOBMxkIIZTIZXdeHQxdAoOkGY8lodRxRrdnpdQZ93bJ1w7QyzurDB5OTk+Pj491+d+h54+PjOjUopQhB3TQgAkIJICVQ8qhev3vv3tmzZ/0wqh21Go22pusf3V3p9vpcgnff+2h6ZnbguV7otbotmI401TH55LHs+9H0CEIIAYJhFCWMpQoOhJFlWLaT9X0/jBMVxUEU99wBJXhufiaXy7Y7rUKh6ORps9F48PDh1NSk5Vi5bHZ0pDLs93zfVYotzsx2Wt2f1H4qpEIIPV1qwaNFBgBQQEgFYi42N7Z107x0/oJirNUdvHvtzvrG7v/sN74+NVlVShCqj41Vrzx36fqtW1NjU1OjY+efWej1Ggmf97xgfX315ZdfOHPixMr9h2uF/NANJJQKwnRhAwARQhnHWlycuXzpnKl/ot3EoYIKAqBRGg2iV1751Ob62ocffjg5NZPL5SzL+uIXv1iv17PZ7Hvvvffuu+9WKhWl1Pj4JMHGZz/zhY8+uh4EbHJyVsPkwrnzf/RHf7C0PPfaZz/74fUPhJCY6GEUJEpFri/CCLLEQFRIIBU4arZ7A09EHgAwmy82GkdUR7pGBQa9bo9xnrFsS9Pbraahm6FU/X6/UqlSjA8OdjMZ0zY0pUC+NEItZ21zOwh8xy4vLZ68d/depVJq9eqp33uj0SgUCnv7u1JyjLFtES6UZhj9Xg8ICDSUsTI6zTCWBIxzAdpHTQ2hcqGQxFESM89z89m8hHgYhIKTdt+jlPSHXuSrnG0qSOPAq+QLdrZgBdxMVMJZRkMESKyQaZtnlxY8z28eNb1BRyBl2Bk/diE2ESWCQ6ppVEOaBqFUAgIkAIZIYKwIlUpACYSU6NFOH6XyLQk+joyplN6LH4+DnyYnpJhEkiTHb4Iet7TpD4M0Zyc1fqSUAKg4f9wgQylS/4U0+AfiRyYgw8FQSjU3N3fpmcs/+clPHN3SDMOPQg4kIhggSBROtb9JmBimUamMxHGSsLQ3RACoaqlSrYyYpoUIrjcaMWcUkf7AHQ7dL37h82+/+SYl+OSJ5VajXsrlQ28Yen6n3ex7/crIqOAMApXJOL4vMMRarDw3loojCEbKFcMwGEuk5LpOMUYQAIwI42LousViqdDtIwQUkK1WK5tziqWSk8liTNIxVBRFSZIQTCCEmq5HYXTt2jVMaKlYmBitzM3McM6lFCxJAIIa1DnnEELLsiCE/tAlVBcCNhvd6x/dMmwrVyzMTM9UqyNRFEkpCaEY49SsNvUCz+fzURRZliWEODo6whhXyyWq4Xar1ev2b99eGXo+FyKKEwnJT3/2dqlSMS07SeKjoxpj7Els3f8QQC+FBE85ICupPM9P10MKyDPGGFc0m+l1+xihOIrrtTpGBqU0m81pmmZZZiZjt5utUyeXh8Nhp9NpNltRzA9rDV3XHzsf/jUyHHUMb0CMEpa8d/U9ndJKddwwjJGRkaWlE7l8kWDY6w2+95ffI5rx0vNX/u2/+YPtjY3f+g+++Q9+8+8iZIyUZ/LFXL3V+PYffftLX/rqpSvP//F3vvv+9RuIkFT7A4AaqVTyGf1rX359eX4mn7U/ydU25bLL8YmJLz07tb11VCyVXqhUHzxcn5qaun79er1er1Qqm5ubn/vc55rNpq7r+/v7nuf//u//PkLoxIll23befutqrXbw2c98empmmjE26A/iINQyRhwzwQVQsmTbjm7n5u2Es4OjZiylgJyxgUGVRWE47Lh9Uazk60d7WYM4OhEQOrqRuP7IyREWJmEYuUP/3NnTaw8fDgaD4bALOMtkMgdHzerkzNzcrJC81+3VG81qtQoBaPcBABIhHEVBEMh0cGCaJgBACJ5xTA1KxZjjOPlCbjh04ygSGCtKDZwFjEcxpxh3ej3T0CyNup5fzJg6xQpgjKBlmFjxhAmEkGVYUkI/YLaTR/1hxqSFjMUTBgCMw4gSkjO03Nx0Lwj7XCoEgFQQKqoRpQTVCMIqSiLIlVBAAggBwVQXGsCQK8bTvIdUKyyPG1JwnA6RMiwfXWZPl9r0EpJSpBkR8Cnr+7S3fRrYNQwzSRKlJKUEACCFeNw4p/2u4AJIiTFBEEAIdc0gGgnDYNDp3x/eG04Pzp8553qh5/tSyTCJ4zhRQBmall54Ti4DAPBcN0ySNOtbw5hq2tLc/FR1DCN85/49JvhgMLBM89TyKT/w3n//g939A40Sy7BOnzwXh37OtsgYPDjUjtoN0zSDIA4C3m23pGKUGE4mIzn2PH9hZraYy3u+X6mUGEsIoQoIwWUcx0PPO6wdOU7u9MnTaXKmlbEAhAcHtfHxsbxteZ7vuu5gMJiYmJBS+r5/584dAMBwMCC6HgQej4NSoZB1Mqltguf7CgDDMNI/VZIk+VxRSHD9xg3dMCnR9vcOquPjCCHf97e2t9fW1paWFtMzlTrjpLyIXC6Xbk183x8MBvlsZjgcuu4wly8OBv47775fb7deefVV0ynky5Wtnf1sPi+kGg6HSinOOcZYikcpSo/mqCl0AJ667z7++qQawifrR6VJSwgKoYRQ+/s1J2uxhGkaBQCEYRDHGc45IURKgRA6f/78X/3VT7udnpDKcZxisdjtdn3ffwyhfnxy8MTHA0il/DCMDo8I0fcO0MB1bccJfW8wHAIlRBJdOn8O/ybY3NwCQLrDcO3h1t27K5aT6Q+HBwfNb3/7TweDYb8/TD2VmFJSSqppU1OTBVObn5p2LLOQy32iq60CCmG8urr64UEwNjb35s9+9vIrr549c8b3/RdffLFer5dKJcuylFKu6165cuWll16CED1YXX/vvavvvPvWN7/5d6amxn7yxo8VkKZOZyZHdUpPLp+oN2tWJmtDW0jBmAyCWIdMyaDsYGoYmGoAIqJ0pUgUs96wH3QDHSaKMxPhbCFn6BkNIRYnvd4gk3EK2eyPf/yT5cVFAOD42BiUYjh0ozj2fR+0Gu12e3pyZmN9a6RS7HRauq4NhlIBWRkpb29vM85U6hULgU4wFKxadLBSfhCxMIBKIgREkkBElJKmqfOEIQR0yyxkswYmSqMCCFNHhYyez+Y0QlgcJnFoUBsA0Gn3XTfmUkAIco7NGfeCCABmUKphCokmiS6BTghteB4ngGoICkko5pITpIIwVLFEkCBCEAAIE2IionHmR0AwIORjRiEAAEBECWVMpA88joB81FkohGBqX4JQmvbzZNSmnrJqBAACiPCjsRGESkqu63oYsqeHcQAABJQUSgguAMQYIw1qhJKMEwRBEicbaxvZbO6Z558LwnB9fZ3HSTGb6/d7mCJN06IotDTD0I2dw32pYdu0EEJAqZFyWUck9PzRifHZpUW+vm47zrDb39vZxxo+qh9Vx6rb29ssFt1uv1ouzM9O7G1vhklUKhbqtdpIdXR+fvb6zQ8AUJ7vOzZdmJ8/tXzqtdc+k8s4SCkpZcpgZSKxDUNIqRQsFkpvv3M14fziM2cYSzLZTLfbv//RzYnx8SvPXMQYa5rmOM5wMCiVy0EQ+J6v6dqIVa1Uq1LwsXJxOBxmbIsLweJY13XbtqWUjDHXdbPZLE8YQnhyYuyo3rj4zHl0H3e6nVa7FUXxh++/Pzc7XalUBoMBACCXyz2eg6VoO0LIcRzHyWysb2NMGFPNRvPS5WfHxye//8ZP9w6PNNvZ2T9s9/r1Th9DoJRMWWJ/Le1EKfULbkRPjkft8PErn6wNCYIgjOPINA0h0lwl/JjS53t+u92amp5Yuf/g4OBQSaVpZq/fMyy8sLAgpUz793R1/Y1kmPQphCWACsBef7C9swsAMk1rYWFhfn4+3aKdWl66fW/ljTfeiGN57+7qd779p7ptVcfGDw8Pg+ABIQRhpABOvfaVUrlstlgsXlxeGh+f8PxQQfWJrrYAAKVULpfHIOZCnD17No7jIIgQQp7nHR0dVSqVBw8eLC4uTk5O/s7v/M7i4mIcxwsLC//hf/Sbd+7c0nR05dlndFPf2tpZX1tBkGd0rd9tMclLIyXLoIcH+3GSZA0LAggxIYYOgZQxQwRBDMLIxQLmdJjP6QDpEKF4EIE4yebMscnpTqs1OTkX+D6Lw3y+4LpeoVDodLsZQzdNY25uLmRydLS6u7e/uLA0NT557dq7nU5LYanrFGPcbrcQgphgqSAESgmOMRYsCXisQUAQigJfAqhRyhLOwoBqJGvnEy2OolAnKAhcy3QMjEKZcB7DJNGURZXSdeJzlIQ+RDRJBJMJoViwRFGdKSgA1c0M5wkiBFB9q9lvRQLnitDIEyiSJOZSYaIhCCGGmk6DMJKS8zBGmGKqQQgVBMdSLgnTMFf1iNyTavmfhg7Sr+mEvVQq9fv9bDY7HA6C0MUYquOQz5/rcdI2WUrBOMcEAoCE4ABKhAAAPydagwoipSAAlGpSioxhQ4z6gwFLOEZEScC5+ODGR9lcdn5+vnFYU4wbiEomTccyDauQK/qejxCGhEigKMalUnmsOqYYpxba3d/3wsB2nGI2N/XCRLfTXXmw8nCj1en2xicnBQMC4e3Dg77bqZQL2WKeAOVkkGFZSRw5GZsJZlqUhXJ5aenVl18Zq4wApRBCpmkKwRGCiKB+f3B/ZfXgsMa5VApQqnuBnyRxrV7fWN8cDv0wjG3TmJ+bs0xLSrm1tXVweOj6QS6XPX32XMKFadtHh4cIoazjDIdDoIRp6JhgSmkQBClzS0qhaVgqVRkplkaKnuebFo0YW15aHhsbO3fu7PhoNQ2dPDw8zGazQgjDMDSqCSlM02y32w8ePJidmdF1e+3hhut7c3Nzk5MTvUFPKMWVev+Da0MvgESDPH1ApR7qf62BRhoW8vRJfFxVH70ASiV/oRZDBJGSKgwjznEmQz3Ptywzm81BABvNZrfb6nUaE5OTumZ/dP1WGMaaZhiG0e12dV2vVCr1ej1dh8ec61+oMEA9kjYqIBTgUq2tb/7gRz+uFHPLi4tRHN++dZNSIiS4eu2jP/njP3vjJ28dHNSkkJ4XVQBBmBKqH3MUj+fHIO3xi8XSxvbuB9dv7h5sPffc5U90tYUQQgVs3bCBtbO5SzWyu7+XsbOWZc7Ozl64cLbVaj33wpW3331zfGz88198TaPa6uqDn735M87Z5NTk0eFhFETNRrPZan7qlU+t3b/PY6FTK3GjoDdMELKpnclnMKZB4KmEJYmIWKSUrI5Wh+6QhaGm6U7GLOcKUkq36yFFAAbdej1r2otnzl67dX10dMw0zBNnTx7V9qv5aRaHO1vbACTJwHdyuaP9g5FS5eioLjjHCFq6xkUiMHSDAJNE8BgqhqDmDgY6pWamqAQXSYI0yqTkUvlJggk1M5mMkhQiFcVx6OUKWZOScDjwowghDBB1h31qGAoDnsSmrukUSQwQ0YtYC+NEQWVbWSAVSKBJBOQxgNKPIy5AAhXUMTYJ1PQ4jONYQAgg5hArILFpWLSki0SGQcQY5zxGEAMupVQgzdeRCsgn/C8pBQBPQvGUEqVSMYpT+ZMSIi4UcgDAKIohJEqmvDV1rMd9in9eKObjKI6TUCkgpYAQcJ48xnDBz9kpQIwwhMA0LYSw57oEIiYVRtCwbCllEkYtP6BMnVpabhzWTKzFSo6NVIiu7R8eJpzn89mIJ9mMMzM96w7cfncwtrTQajdDlriuZxpmT4it9c0ojD//uc+ePXv6Rz/+oc8HppWh1JibWazXdgSTlVJh0Ot2Ox0aBKXSiK1nJYQCgEjFs5MT58+cCINQAZUw1u128/kcIbTV6v/sp29nszmEaRC4jVZrYmoSIX16amJjY1MIaOiWZdmGqXe67fzCQlEvaNoy47zXG0RRXC4V2p1e46iWsSzPHY5UypTY+VwOY6RpmpJAIxo8TpdDCRMQIYRxq96kmrYwM9PtDyq57ObDBxPj45VKJfB9DMHC/HySxJRSBfWEMZ0aFAHmB0mY/P6/+5PPfuHL5alZUdtbWJxrNmtB6GNMe+3BzTt3FUydKpRSCsDHWxaZEk0BUPA4a0Y+PmtPF9mnoPzjd3gaTEhXFgRAAZVSp13Xx5gIoTtO1g/8/mCoafTosOkO+djY2JUrVzqd7o1bN4SgYejv7Gw7mWzGzri+z4UCqTXto/H7sW5cyGPNC1JQcSixZlnvf3TnynPPnz591skVHCEqpaoXBKv3V69fvzU3O/dgdfU3/u6vVSqlq9dvfv9Hb0BECNaETABIyYkAAJDqldrtduQHb7/3QaGQ4eIT3tsqBSHgCWv3WpZZDJPo1MnTtdrR6OgopdrGxgYA8PzFi6dOnf7ud7/b7fVeeOHFb/zar7U73XfeentqavrMmfNASk0zAILvvns1dr2sbUvOoiiwMwUAIKWaaRpCiIHXd/KOhDJvFJM4FgwwBizLKRQKlNI4ZN7QU4kyDTuXy3U6vWazNX+Cnzl75vr1m1LKc+dOx0Iwzvr9Ycx4Pp+fHxur1+tJlOi6NTs7KwULgiBj2gRn6p2uodtDdzhSzseRLwXU8lmMCUsSxjlOE3YRFZJxoQQQnHNbI0AqjFHRyRJCkyBACCFdM0wrSlguX/Yiz3XdDKFIJ5mMGUsZMw6BMrCKeCIEUQpBqTQoCJIAACmkBIlFFFeK8zARQikiOABACCYhQoRgQggAAGCgmzrCWAklmTiGCBCGUEEBxbEpkkoHXAgBhDDnHEKQzWUUkPPzs51OZzh0XW+oFGIJU8fmMgAqeByzfmwqA9LbK6Ukm3U6nY7v+zJFZhFM3W7Bo7zetHVCCEklecILxSLEKIkSSjFBuFIqu64bRRHWqUhYv91ZF2sT4+OGpksEveFQQJCwREKgUS1jmeXSiK0bDw8eQgC6nVa5UozCKGPah/sHxXzx9ddf//DDa2+9/cbM9PTf/bVf9Vz3gw/e236w+vDeajZr4uliq7mbNTO5fAFBXCmVZ2fnb929F8RJIWdihO7dvQuk1A2DSUEIyWTsKBLNZivlYbi+bzm2FQXbO9uCMW/oa9Q4c+qM5/uCM9uypqYmAVCUklw+BwDIZrNHtXq30zk6Orpx49b01OTywixnLJfNWrYtpJRShmEgpTQM43j3DJAUSkqZy+U7nS5GmEVRqVSqlAqEUEM3oAK9TgtjYpimZVlxklCiASGlUozJYmXCLnb+xb/9w9HRyuufeRkimFqnNRut9Y0diAiCXHGJCRQSP473hBBCBKVUKk28U6l73N84NHsM3T7l5/LkxU9MjBSQUnEep8xCz/NM03IHPgSo0x60271Lly4+c+nC5vZau9MpFPIIocHQ1SiFCEOMheDpJCBJYgqIUgqqY+HMMSlYSQC4H/h91/vg5t2p8aqh0UrBuXjpQhBFxcrIS6+8vLmx8d7Vq5/97KeUVEY2e+3GzXarDyFSKiXxPl291DvvvmuZ5omlhd297XNnT32iq216IfphOD0744UABtD3A9O06vUmhFgpYNv27s6hZVljo9NXr14tFUYpNVvtxtlzZ994441Ws0UxFko+98Jzz5y/cPPDDxXnvud9dPOq6PWBAqVSyY1dQskwEWbeml8a94cuC+JGo+55oZBCN+xqtpiwgZ3NG7oZx7wfxZzQ8bHxlbWN6sTMqZNnwyA82D8aDnyiwOLC4okTJzc2NhqN5vzcQqvTDSJGKLny/LPDbuvO/i6GaHZ6oTI+9u577yqJHDPL4hBQGkaRgBLrGDAhlOAJgxgjJSVXuaxjE4KUohgiDDnjmOCYcaZEr92CmBSLxbwwkiDQCEk4MwySdbK+H2uY+q4LECG6lgAYwwQoiDESjHOW6AQDKDXD7gslhEwEk1KlI34lZRQJJSOgFEYIKswTLrkkmBCcBrArKNKTAx4FPCiEEKUaIZgQlMSxbWcIQYwJy7J9P3TdQEkAAEqHYynr6/GWMeVppW8VBJHr+owlSsH0LDMmAEBKyvSaTLerj1nrqfcgpdQwdAhBFMX1eh1jbNsZiQFLEsZYt9dlLCmXywojTTd6g34YBIVyGSilaVqlUm422hjCbDZLKNWp7fVDjqRjZfO54sH+9skTc4c2GQ46KyuDaqX893/9lze2dn/85rtRnKxvdSrlPAJCQWGalAteHSmdOblca7TrR/ViqVgeqdiGqSD0Az+Kou3t7VwuNxgMxiYmEMJLGXt9Y32kVC4WCvXDmm2aw+GwWq2eP3+21+sWC4V0gpokSZrUAAGanZ29c+9esVAaHR3L5/NTU1O5XJ5SGkWRYRiu7w/6fcMwNE2DEPq+72SzjDHf923b5pw1m83x8XFCyN27d0dGRvb29mamp7PZXLPdnpqehhBTqiMFgJJhIoex+v7Pru4edeqdwfrmZiWXKdpGNmN6/d6w30/imBAsJJBSSn58KtMTlPrEpedIqkcz1aeGY48nVz+P2j85HutfHze56Y02PeI4juPYNM0oCjHCURDuH+yXy8VWq3ny1IlPfepTf/EX3zs4OIQQKSkYY0KpbC5HCA4CL5vLTk9Pbqysu66XCsHT2GkAQJpHiiFCEH73T77bq+//r/7TfwhPzGUy5sP1td29/YxlB8Hg5OlTiVC7O/s/+unPur1+6scHhAIKgSdLGkkpXdeNwuio0UBArm9sf6KrLUBQKkU12mw1IHWy+Xyr2RitjsVJUiqVkyThXOzu7vf7/ddf/9KDB2vvvHN1dn6uVqsRhObn5/O5PMHYdT2CtYydrYyO3b55Y35+frK30GzXGeOdgVcqlXqDIQekPDalYtZq10Qcnz7zTMfv7+/vRbEMAjZ043w+nyuNdLs9ARICiGE7IOFra+u2ne12u+fOnaQ6qu/tNBotjLFl2qVC+fCg5gVhvlTCmHzrd393amxkZGREMSEYbzVapXwhSYIwGJoYxYxJwRAlEigFFWNM1w1ENKCA5wc8DLmh6brGBCMKaQRDTcM6ERIooPr9XsKSoqlTjUpMNNNAppEoIAiSGEuMbNNRBCVhCBFgcSKZ1IiecTKabfTbdctyDEBiCJWQmOCUkQMABEAqBQEXEgAphGQSQSSlgASnvaxKieIpaRIhwRUAgDMGoSIUmabj+/5odbTfd/v9nuACAgQxSvdwj0A9eCyTSMfFacMLMcHU9wJN0yDBcRxDdJw1QgiBEGqaJoRgjKXocHrdxnGcJEkmY6cXrBAil8sZhsGkoDnCOFMKtHtdLwokAISSyanpialJLwg63U52tOq7frvdytg2T1ilNDoYDLN2rtttsSRZnJ8nGDbqh5PjoxNXnsEIXL/2wXf/5DsXL1/+wudfqTWOfH/oe27d7U5NWonnzxnmw4cPdd386pe+Yprm3MwsJQRDNBgOGo2G4zjtdrvRaOzv788sLOweHgz7fSWVO3RnZ2fNWS0M/dHRkVqtNjU1mc06XHDP80zTTJIkNVR0h26v15+fX1jf2Lp8+bKS3LLsXC4nhPA8z3VdIUQYhr1eDyGUz+chhH4QmKaZqtRs29Y0bTgcAgCuX7/+5S9/eXt7e2J8nNIsJrTfH7gHh2MT4xnTFEJ88OGtf/0H32kNQ0D04dDLOdmD/cNGs7208Hxl5MjzA0yIgEJyxjmXnCug5KPj5wDZY840fDLnfHQ8rrCPiy94VIJ/UYL4iL5yDA1zzlOgOetkj/yAMdbv913XOzqqXbnybG8wfO/q+wghhJCmaUCIMAwzGTufz+fyuV//9V//iz/5i5+98VOq6xAfp+Qdo65KcSEQplTTMk4ulytkHAdAvnRyaXZuxtDNrc39ja39//q/+WerDzaGvovIcZk+vnAUfIyLHPPPIGw027/yS1/JFcqf7GorFUQwZmzgD688f+mdq+9apjkYusVi8f33rzmOc+HChZkZ2mg0OGe/9mu/dv/evb/68V8998LltYcPv/DNLzgZp16rbW3v/MX3/jJhybmzp+eXlg8O9007+9zc/Nb2tq7pEIK5uerqw4cPV7d0qhmZ/MTSOCUkbLfn508KwXVdlwozzpuNtm6Yo9VKvd7QdCvh3mDYQwhhAg8OD3y/FwRhFCUjIyMAgFarVSyVKlWKqdZsNoMg2N7akiwhCirBTCMrBJuZntzbXucsgRhQShQAFGE38SkmXDAkpaUbBqEYKs2g7X7HNA0b65amGbZFGYviRCc0Y5g61ZFuCEp8IA1dHzAhpXKcjB8zlM1CSo/qdZ1qOqJQR0ApzpWm2w0/iIgZ+BG2sogSwQKEsZKp2zzSNT1JEh5zABSSEEEMFAASMMkwRoQQqYCS4kkoA1SGYaTOBBAqTdcGg2Gj0cYYh0EEAEh1swAAoCBECML0clLH3C8ApFIYY0poFCUIESFkkjAIUGrSomkUwmNQOL3kPtYcpUcKPqQS/kqlIqUklA7coRf4GtQRIWEUWk6m3WlrGj176nSn2+acDft9DROEaCLjg739bDZbqZQEDyVn9fq+71nTM1MYkUFvsL+3OzczH7nBjVt3AIF+4GkEFPOFxNZavfbk6IRtOc9dfiGJkzMnT1mWFcVRt9s9rNUQBFknmxJRwyBgjHX7vd39vdDzx6qj1XKlWi4DDG7fuVWulDSdSiWWFxeHvW4Yhr7vp1yOMAwNw9jb20eYHNWPCO1cvHDetu1ut5smone73bnZ2Xw+77ouhHA4HCZJ0u31UmoBQsi27Xw+r2lakiSzs7Oe5335K1/O2Bl/6Dt29qB2+NGNj6ZmZl579VMawm+/e/WDD6+fOHVmtFrSAT95YqHXqE1OTPfdaOew3Wx3BCKRiDlPZMKAYPIpIsHTB3jiGICexgfS43FvC8DTWO1fczx+jZQyVTPHcVytVi3TlFzU63UpFWNJp9N2PW+kUpmenq7V6rqO4zgGGEspwyAYDhLLMofD4elTp27fuu35PngMhaWf5/hDSYQpxHhiato0MwirgR+srDxcnJvvdr3/4r/4Lzd3DzXDJtRUiinIAZAAwHTrhhFKx3FpK5BwnrjuX/7wRxOj1U92tYVASpnJZOaq8/VmY3R8LPQClrDV1QcL8wuLi4s7uzuVkRFC0NWr7/zyL/9yoZi/ffeW73nnzp371rd+95vf/CYXIutkz5+/cOv2jT/78z+/cPHC4vJis3bYqDUjP54YndQ0bXFx0dTtVqeNEQYQJApsbG5NT45TTMYnxo+Ojgg1pBStZlMJMDY6IQXMO/nJyQnD0mq1RmVkpDpa+aufPJifmm7WmoZucC7CMBJc7tcOcoXiidNnvv71r33nD38fJAk1tGIpt32447n9ei2WkiWKIwAIRkoIA2Ogm4ogJaTr+kp6ju1kck4i4kRJigDSiVASKkARjrikABWcXMy4oobUiSSkGSVBGAMA8hiN5IsEIsF5eXpWBqFs9Q3D5EoGPDrYPSClIjBzGOFISD8JBOCKS6xIynUHACCEKSaAKwihBApIJaSUUGCMQNqfpoSeFFiAkDGGEFGCxTHzfR8CksSuUgpCjBBUKhXgIogggPJ4OKaeYHmU6hDCJOEIIUJoHMcYEwihEBIhSAhJTWmTJBFCEEKUkkLItOymzoSuOwQApJ+kVCpRQhzHiZPED3wFFCGEapqJIUK4XCp6nre6sjI9M+Ulia5pTiY7GAwxhPmc2Wg0aofb58+duvTMeY3iOGJCyL2d7XKpWC6Wj46aX/jS1+6u3D442pU8zlk64EIQli/mLl25NDe5kLEL/aT3xk9+UiyXgiDY3tlpdzqmrp8/e87zvcAPxsbGdEOHCE1MTGxvbpVKpWq5crC/r7BUSrVazUqlUizmj+pHw27Xtu2UJ2AYBsY4m81Wq1UFUS6ba7RanHHP8z744IO5uTnP8/qDgeu66SvTUEKEkGVZjUbj6OjomWeeoZRmMhnDMMIw/NznPrexsRFHMYaYEIIwnpmevnHz5vXr15+7fKmYK2Rz+WIhv7ww+9LzVzJ2ZmdnZyf2t7Z31t94c+ewHjPBFY94LJWAQjy+9YG/rto+3gn9Qnf7cY/Nv60YPDVeS+cH7XYbABAGYbpbSpLk4OBQKWnaVsZx8vn81tY2RhRCqABIm1wu2Obm5j//5//8/KnzIyMjw81NlJoaqSfzXghQemt3Pfev3viZ1+vatn3i9Ol/9a/+MKObv/Kr38gXRshhW0GkpILHZVoBgIBCCGPbttO9VxiGhBAAIUJ4MHAHvcEnudoqACBCuDfogKzROGycPn0KIRgGset5Kw9WG6121nGieO/UqZNvv/3O9vbu4sLSqZMnW619RI2O6/2T/+f/+8tf/GIha/+db379S1/+3L379+I4yuVyLz1/+dvf/rblZA07Mxj03v/w/fnZhXv3788vzI2Pjz1cezA1NW4Y9s7OTm/gZhzHMDPj4+PlkfHdnZ2DozoiuOcO2/3Ovbt3F5cWEZQaRs+cv1jOOiPFHEQ0YnIYR90g+sbf+XsrK/fffetNx9A+/epnvvcXf0YMKjEcHSlFXp/7LhA87fAoQho1gOBZw2QSRyIGCHqRT7OmCRhFyETYwBrnKtFxCCVjkW1ZGSfPMIkxbkbx0A8jHiZcYkIwpqGkvVhYGgJSUozsYlbqtNPvH3W62M7gbEUQAxKDCR7zmCuIFVIQEg3qOsUISaU4lxwCAQTgAEogk1TUj4gAggslJFQAAQggSHUOSZIAwAFQAAIIMEid+gHUNHqcqYPS2fIxA/eRfBNDiDRKhOBKAcu0pFRxnHDOKKWEYNM0MMZB6DlZEwAQRZFhamEYpfwHAADnPG12uBCEEgQRxChMYjfwzUwGEdzpdgGEjuNIJU3DIZRWipVGswkA6rS6z126fNRo3Lh5q1gsjk6MM8G7vfrsSNUyVD5jzkzNrj5Y29hekzze39sUMp6dnblz//re3p4Colod812XaHRmbGR+euHsiZOm4WCd9kKv7Q2NjFUulT/48MO+N7z0zGU/iu+uPjBsa/1gf2tnZ2x0zLLMhDOik2EwQBp6uL7HGA9CZhoZz/IEZ+7QGxudkFJkMhlN06RU3V43l8u998E1TCjn/OioFgeOaZqGYRBCTNPkQmxsbtq2TQipVCqE0jhJ5ufnlVKWZVFKTdNM5dQHBwelUskwjCiOMplMxtBYgsfHRorlMjWd9e09ncD/6//hf//Ou+/dvHk7W86//c57pWL12u/9MWPCsjNCcSkSKAVKN0RAAQgxhELKpx0206gNgIBUCv6CSfzTcO3T7e3HxIeP3uzJU4+NgLvdbj6fj6MEEyKE8Pxod/9obHTE87x6owUh5FJIpUyqCc5ZDCrFchhGQIJr168zzjRTT0d5ACiMEgAoUBgClHOcQiFbyueP6s2333pzdmau78c379//xjd+NVcsfvXLr9+7e1cjMJBCAgSlDpTESgIgOJODAYcQlkql0dHRnZ2dVKOo0kRb8H/5nf8/FM7/Hw+sYEy+mhfPBrudduC6g5dfeQlCbFsZXTc/+OBatVotFPKnTp18770ParWj06fOSMmfuXRGs7LNTveHP/j+WKV0YmmBYHzx4kWE0Pr6WibjbG49fO+993Td9j3/V772y/fu3daIdvfuXd/3Z2and3e3CcEAECXV9PT03Nzczs6O7/tRFBcKBU3Tms1mHMefeuml9YerhOJqtdJsNg4PDyJ/MDk2Vm93BMCmk/vwo1vL8wtLC/MbGw8lZ1OTE512p9tv5RxbIyj23V67KQRPhARAQqWAkggojDUgEFPczNgSKC/yFeOlXJ4J6SUsSJjt5JAmCYBEET9mEcFDzkMpuVRCqJhxBaBhWqVCLutYGoYESigYhJAzFiXci5NEKq6gACQtWCnKlu7pIUQYY6VknCRJnIAECMYVV1hCHjGCCcZQSikYA4+4OingpWQ6133K2RNCAAClNG08HxO8nuBZjy4nCAECUiqFECnki57nh1GICUwFUeVyOQzDoTswDJrJZDjnYRjGcQwBieOU4InS/hcSBCCwTCuKIkJJqVjinI9Uq512W9f1VqtFMCkWS0SjpmUCjBjnnuvZtv3iCy8giH74gx/MzswCDAqlbN4xl+anCaTtRndsYkIqvr7xYHNzjfHowoXznpdout7ttg9re4zFJ0+dmp9frORKccgsM7uzfygxzBUyBzt7pqZDjEKWjI9PFLL5d66+CxCSSiWCUUQIxs89e6VaLjcaR0rJldWtVquzOD+3sDB76sSS77pJHAshTNMsl8tCiGarqWtaqVT2gvCo3uj0+iyOKALpQMw0zfn5+Xa73ev1UjFYGIZRFB0dHY2Pj09PTxuGEUWRrusp/fnGjRuu61YqFV3XZ2amdYrDwN8/rENqTkzP/pt//bu2oX/xi1/4J//0v729spYtF2qNVhBwyRFCOI7DIOgKnjw+s+kS4pw/GoEqoBR8lF8JIZRKwZR0BQD4ReuMRwCReExreEoj84vH02Va0zQpjhteBUAmkynms5VKYWX1IZOScyWV1DBVUgIASsUSoaQ/GCioGOepiENKmWY4Qogx1DCCZ84svfDCs5/99GffeOOn//7f/+EXv/j6ysr9WqulGeaJuflv/tqv/tN/9k9v37tLTRMgqmGTxwlnEQRCIqLg8fIeHx/HGPe63aHrQqQIwZ/k3vb4nBim6aDM+PjC1sZGp90pFEsQQoyRUqrRaNiO/dHNG9WxsbGJSd/zi5WRRse989YHM7MzX/rCFxJvQCl5/8PrmNDp6em9/cN2u+16/TBKMLYGQ/+7f/bnEEqKaK1Wf/bZy81mc6RSHRsfC/xobW1tdXV1a2trcXExk3HGxsb39vbOnDmTJMnW1pZpWufPnL9z59b66pqu0/nZOXc4aHdajKtExPPLY7/0lfGRysjVd991vWA46HW7vdmZmZMnTmUd6/7d2yxONM2Io9DUNC5YnMS6ric8SZLYplpGMwxdw4QmfoB1gwMQSRUBIk2rHSskAVKSEBAqGAoQQii5gAoCiBChUgHdMBLBvTA0dU0nSEnIhEgAUlgDGkVcgUQkUcykAABgjI5l6QimAaIAACUVxhiS1ENOiTBRSkkhIESC88ebrieLHqUpacfV9mlLbEppuqAfD7UghI/NGNOfhwgQiAihQeBnbItSrKDK5XKFQuHo6CiO43K5hBBISWmFQqHT6WSd/GDgQpj21AoCgDDSdSOKIghhHMUpBrW+tjYxMZEOmoQQ2ZwDIEx4Mlad6HS7TPKuO7i7svLKiy+9+vIrOxtb1YnRs+dOFXK5Ybdj2kalVLx966Pdg70LF848++yzb7710/ff/7CQnzhz9sy+fzAcurmc1W43kCDzr859+sVLm1u7a+sbG7u7kMIkijAmuVyOUCKkWn34wDDNeqPhOI5B9WK+gDGKw2h1ZaXX7YyPjWKopiZGJ8dHC9msTnVG48ODgzAMz549u7OzMzMzYxiGaRqdTqc8Uh16fhSzbhjmS4VOt4sQMkxze2eHJYlt261WK5/Px3Hc6XQymUwul0vb/36/b1lWp9MJguBY2CaErhtSCEUQY1zTNQnxtQ+vr29uvfLSC/dXH0KizcwtcKjcjW2WAAQ1hETCIvnIzPVx3Xz6PgpSi7hH5fJ4lTytPfwFmUO6Qp6+E/+PrBAsYSndN33PwPcLOSf1l5iYnGy1u67nYYIp1pMkGbrDQqHAGWOSQ4QYY8fQhIISGhgAweKXnr/48vOX/uE//A9rR52pidHf/I2/VywUJYuWT55c39q9ceujl1569rnnnxl4zRdefnVtffvendXUZk6pY0/S9D94cHCg63qxWJyZnT2s7fu+90mvtkCIYqFI2vXtre0rzz7bbDV0Xd/d3Xn55VcnJibqjYbre5quffjRdSWBphtznBNNs6zMjY9uApZ85QufPnv2bG/o7x0c3FtZWXv48OLFiyWj2u4MXDfMZot2xkyS8OTSsmlaS0vLCwuLSRJ3up10bpva5g+HQ9O0PM9LkiTFyCCEb7/9NoGwVCpwKTLZDIBwv3a0uLxsWmav29/e3tY0o9lqT07PYDAdRcHE+OjPfvoGBDKfy9qm3fU8oCBEOIpZFIeWbQZxGMWx49hY0zgAoRQEUL1QjAWLAOC6llDQjzgHSAOIc0YgEEQLOJOEAMCklIZpqoRxzmPOMUFMKpAwLgmEgEkoEFIwjclhQSgTJiTguqYrBYRQEAIIpIKSc5GSGQUXkCAMEVecqeM+9rhoAgAeFdzU6+jRBfXEEgE8umDSEplSlAAAKcya+rc+Up0phJFlmtXqWBCEzUYbQDA+MQ4A8DzPtm2EUCpUK5VK3W5X07TJyclWq53NZdKmVSXCtiyiGxAeY7hpX5wkia7rmUym3+9PTk5KKfb39yenJ3OF8nDYz+UdoYTrR0KKbrd75sxZrz90veHqg7XF+XkKQBgz3/cLxbyEIpVaPXvleQBho+4KobJObmpyGsDEcbJT03OWndvY3JYAnDt/fm1nGynsR3GxmAnj2IAw62Rv3rpFMC6VSr1er1Qs+kMXAtCEKPDd8dHqxNh4oVicnplhMZNcdFrtcqk0PT09HA41TTMMYzAYHNVqc3Oztm3fv39/c3tH04xa7aDTsSCE2WyuUql0ul0gpaZpmUxGCDE+Pp6qfrPZLIQwiiJN09LNwerqqhCiVCoppVZXVyYmPhfH0XAwGPQGsUR/9O3vZHPl2fnlH/zg+/dX1xZOnrn3YCWOGVAUQKEAwBhiBCHA6Tjo40Dt4+r5VCGGAEAEgUjdNZ50rOlSSW/PjzHZ9Km/pbEFT5VjqSSC+MmDELqeaxhkemY6XygxLv0gYEliZc2UL2gYRur2+BhoPgZ2AeIsGhsp/K//l//paKXwox/+UABjZm6e6oau6VMzc0eNZhj4L738smGbr33+c//wH/4WNcztncN/9k9/5+13riIEpYJCKgCORZUIoSRJjo6OgiDQdZrNZj/R1RZCqCA8ODz4+tnFo6PrQgjbtsIwHB+f2NnZmZyYLJZKH976aGZm+gtf/OJw6LZanTff+tnMxMTEzJzgslgst3v+w42dw6P6Bx98ACEkhNy5tyIE9/1oanIWY9Jq1avV0nDozc0ufPjhDcbiy5efGQ6GEKJUNj4YDBwn47q+aZqzs7PdbrfZbM7Pz5fL5YODg5v37tsZS3cHX/7Kl/Ybjb3aUSGXhwguLixsbmzamezyiRO/97u/SzBEEF557vmdjfXtrd1utx8EkW1oEBGoI4MSLrhGdcfOYEqGcQCols3nBlwwjQ59FTGRCC4QDqCSSAkAmFSIi5TciCVgCqRpHEgpJRVTUiGQCMGkJABSQpiQSnApgBSASwUpRooCAdKFnUYDKCUIxgAApRQhhFIqpBBSppYfEiglJUAgvX/DR4qfv+X06bo+Nzd/dFTL5/Pp9j+tvHEc27adNtEAACFEJmMWS4VSqTAcDqmGgyDUNC2NaUmtWETCKpUSAIAQommaruuOk5VSdrtdpaRpGgACXdO7vV5KUM3n80mSaJpWKBR83w/DUEppGOb09GShVDRM06/79XpN162RYknXtH6vt7mz5RTzk+WZg/rh/dW10Wq1WTuYmhxJWJjN2gBIxli73dE0HUI5PladmRm7cfP6YNgZG52mZqbR7Q86bSbE1Pzsl77y5bfffqfZ6ezVDjO2fXr5ZLfXk0q22r2piYlCNgeEtG3HyTo8iU8sLZ89fYpqxA/9bqdVyhd10+p3B7XDIyefKZVKvu/3+33HcTKOc//+yubWdrfXQ1ibmpmlGm20WrOzs8snT/T7/Vwhb2q6TjUp5erqai6XGx8f393d1TStWq1SSg3D6PV6nudNT093u10pJaX05MmTjDGeMKnU6NjozmEjXyzevfdg4PmNdtcLo1t37h/UDighCGOQRqYp/phd8HhKieCTBhM8te/5uS71Fyro/8ge9m8pERA8MUBIKQFxHLfb7ZOnzyoA2602xhgBGASBpmmmafq+L4+p/DBNQccYK6kokbpt/Mbf/Qbn/Gdvvv+v/vW/6QehZVpciMnJiUazWSkWfdd98623t3e2X3rhOfO1z9+7/1YmV9zf3UdQUwBKyB/73j8NTA+HQwUk/IT7JCgIAUj/IuLkyVN37txZXFywbUfX9H5/KIScmpoKRQQR+v4Pv//1r//qpz/7WcvQ5ibGT549/yd/8f2bN2+2Gq1szr5w8dzFhDmOU61WpyanCEE3b946OmpNTExmHDObtXOWvbuzgyBCCCcJv3Dh4srKfdsywyiM46jRaGqa5vt+q9XOZGyMiRCi1+87+TwHKlcs9nrdt999r9nuTU1OjU9MXH3v3ZFy2bas+lG90+1NTE4CpbhQb731zqnFubHR0VzG2tpYA4KbTkYInsQxEVgJLriKZQIsm1qZehi1gzCQUkqoBBBSYQ1hUwcACKaIoWOMgZSaAlBJhamCSEGoGQYgFGMkpFJSYoKBBDzhSgjIGRdSASwBBBgiDIFCSiqEkRRSAYjRY40WllIJyRWXcZzIhCspAVAQYfSoXTmeeDwKsPn4iVOKUprJ2I5jD4dWep83TSNJGKVE13UAAGMsrekQ6pOT40kSHxwcAABKpZKmuZ7n5fP5tHUqFAqMx7quh2GglGKMpSYAjCXFYiGXy0ZRJKUaeoFlWfl8PqUupJdWauo4Pj6ezWaDwF9YnG932pRihJCuGwThUjY/GA50XY/ieBj4tY16s9smQOcKuMPBcK03NlI4eWK5WIoHg2EURb1eXzfMo/p+r98fDtzXX/+lZrvz5tWrSRiPj4ycOLl87fqHY6NjGtUNw5qfnlp7uNaoNw8O9hPJEEZRFDmWXcjlM052anKSINDttNcerhWKubGJUXeIHjxYHR+dnByb9H1/0O/rhp7OgpRShqFHcTQ5OakU2K/VVlbulcsl0zRHR0dv37njDofzCwu7ne7s1PTExITjOJTSXC534sSJlB+GMc5kMowx0zSDwC8UCltbW+vr61/56lc1TdvZ2sg62Vy+EG7sBmHMJfjRT3567foNL0qCuIMRTgMoEUJASilF2ic+RloRQvBx1/lzxhfH6yFdNY9r7dNF9nFH/D/1eAxEPV6EGGPGmJRQo9j3fSZkwhJCKVSACw4YiONYKokxkYApBcxHx9kzpy+cXp6fnyGU/Otv/a7vi3J1mnXqKXPu7soq4yKTsb/xja+/8fbb1659uLt9eOO9O5qOgjja26thanKZllfxMcnc8XACQADhJ7raAimhQrqm148a45PLh7VGmHAsYJLIK5evGLqxu7fjWIZl2Z/51IsP7t/2h9183tk+qBWqlV/95c+dWZ7+7h9/r9lwt/edIAk/fenVkXLZMkwvGMxMVauVfKvRHC05hwcHa+0uF6LRaExNTV3/6Ga/328c7eu6ViqVSqXS2NhYwjhE2sxstl5vzMxMzs3N3bt/DyOk66aU4NlnX6hWqwRfe/BgpVIumYa1v3sgpfjiF77caLauXn2HMfbaZz4zOzv93jtv9ru90B/GjFGDQkq9JEwk1w09iYFSippaqIAIVdvngxgwhDSMNAQ1jSgIAEBSCMkEAVhyoaRECEEAIaBSSsEEIgpDBaWQkACoJJdQcQAhApAJmCTicUIdIZhoWhhEUCKdGFLI45xzCQEESkApFWBKxAJKgNPQcMmRQo8WEwRKQQQVxEBBAKBS6VsrCCEhKJu1q9VyNmdSbfrunXsAAMMwdV1jjOdyDoQwDH3T1A3DUEodHNSLpRLRzP6gHcUJxsQ0zbTzcl1X07RstqTppNFojIyMMMYOa4cEUYy1EyeWe/1+Egvd0IIwSfNrU7gjn8/v7u47jkMIoVSzM46hG6HnYYibjfZwEESM2QbUKK2Uy/1ez3Kc7Z3t/cP9kbGxjjfs94dIspFidu+wtnO4n7FzFy5c3Kndoxoe+v1mu1EoFM+cO3f3/mqj2arVa45lD73hwc4egai1fzQ7NYt1XRGMKc3mC436ASFwZn5OMp6E0XDYD+LYMLXZ8dHF+Zlsrvj2u+9HXFKMx8enBv2+bZuU4HwhX6vVRkZGUnAAQXhqeZlQ6roDxkvlSnm/VpuemhZC2LphFEg4dE1NtyyLc+44zuTkpO/7mqYVi0XLslLRnWHoGcdaW1s7c/acbpo7B4cSAs/3vvfDH5RGRpZPXzCz5dt3HsQc3l3d9GKVJs9KoaACCnApAYQKSCUFQAil9D5wrMIShFIAwKPATQUhEEJABTBCSh7TUSD8uVYU/Lyc4a+1s0mP9KdS3P+pRxQASCmAMUrPOyEEUwQooqZOFXQcZ+i6CEFKKdW1iMfpnTiJJcKYUm15afHs2bOLczMFBwd+34+4aWX6w051bOTC5eVLz1xwB8OrH1zb3DnYP9h7sPng8uVnbt647YfJ9fsPMrYZhJ7CmEuuAAQKQnT8v/hYE68UhAB8kqttmtkHdU3LZXPXrn3ouR7R6eTkVG3/YHt7J5fNmqZ1WD9iiSyXy0C17t1deeXlVwI/WLl3e/xzn3n20oXTSye3d3e90O/1+2urDz4aDlvtNoDAtk3LMO/fu5dEMUZIN03Xc5eXlxcXF8+ePRvH0Y2PPrpx4yNd14VEjAOEtO2dvbSU1OvNTqcbRqGQnBCyu7t3cHDoOA4lmBJjd/dACajrVrNe/4s//7Ov/tJXfuu3fmNzY/1P//SPzpw9XRgtNWqHXDHdNgRSnjfEMdch8lw/gYABRRiKuAjiiEmiBNQJ1TUCpOBMQIQgUjLhMJYRi6SQUkmEMCEEQSSBFHGCKIIIAAgZYunMITXhT5270pDadB0QjEYqI816M/JjCCCGSEIpORCMQSApBgBAyaUSUgkBFQRSpWgCOO4p0kCyVA2Gnm5NlFKaphcKBdMyOedbm5v5fB4hFEURpZppmil0qGlaSkssFotJkgguEpGYphkEAQAQYzw6OjocDkulkqZpURwmSTI/P5+CvwQTw7AK+ZKuG5TQIIh0Xab83LTnCsMwHYB0u92TJ09ijKWQG5sb1WqxUCod1huuOxwdn1BcKqCKxRJrNhVQxWJxMBwMej1E9UKxCFg0GPQ1E1i2FSf87XeumhadLI4d9vr5fKFYLG5uba6vb3Z7vdJI9cTy8j/4u3/P1PTDnT1d0/uu64XDvudWiwUgmWWaCgpD16cXFq++/Y4QgghFCLFsK+s4SZIIKRuNVrlYsApmqVj0fW/Q749NTLXb7cnJydOnT2ualtrHmLbl+165VCwWCtu7u0PXHR8bv3L5cu2wxhhLnT1SFe/BwUFKBQMApIZYSiqpRC6XGxsb8zxf0/U4SfqDYX5qfHN7++r166d2jk6dfmYwcBOpOt02QghAAJFS8liBoqRUUAohADhms6QMJwAQhBJhjBF61GBKcOzT9ihy/hca2HRSpx5RF/6ndrjpbycECy5t+zgAGGPCOJsbn3nhxRdW7q0qAEzTRAhalimlyuVzSqput0uESs3aDw8Pi4XCw5V7F86eggj6QTQ7O1epVnf39q5/uFXMZUYqlcXFhViA7d2dDz+8/o1fnR0dHWk2exARL/AUEIRQKQFQgGCUUsifnhYSQh7ZpX+ysxtS36AgCIyK/dnPfnZ1ZdULXCWl42Rs29re3rYzmdphfWFx8WD/aG/30DCMg4PD+dnJj65ff/Onb547c7ZULF08cxpj+sG1a+VTIzFjbuB/8P619fVN0zBmZ5cW5xfCIGi0G4Nhf35+Xtf1D65dZ4w5dm58fHZ7e9txKOdobm42ly9ACG/dupXP5zKZTKfbHhsfi6Lo+vXrL7zwwoULF9bX1h8+WIujiBDjyuXzpWLxrbd+dP3Dq4ZhjE+MORl90G8N+x0iuVJSRLHC0IAEKuDGkUY1qdNB6PMoQZjGXCBCNQCAADLmCiolAZRKCsaiGDEpGJdSQQi44hJxBBFCEGAgmEIYIoygRkDKREEYKKQUR/hYl5ACblKoVqtRHa0eHdaTKIEIEkSAUEIKxYWASgoppARSQQWUlOixIOipQykglXyUqPoEsBNCep5nZyzGWJwkACDbtmdnZ2u1WqvVopSGYZgCBdlsNi0Ng8Eg7WcxxqlJa1omIISFQmHoQk2nEADP83RdLxQLvhv2+70g8FMSWJIkuq65ngcAwBgTQh4+fFipVFMY17Ksra2tUrmsm+bRUSMMw4xt5TIZBFEcxYe1Wu3wsNPvPf/CC71ep9PtUap1u91KKSeAQpiEYZx1SgBglsR3793XKTFNa//gQHB5+fLlpeXlZy5dBgoYum5phmHbgjPX7dk6dYc89oZDJUrlYrvT8Txvf38/nXpNzc1NTU0VCoVBr0eIPhgMFJAtwQVjZ8+cjuNQcNbr9SqVSrvdppSWy2XOeblaCaPowoULXIiV1dWRkRHGOISg1W6nHomPmLnSNM0Uckkta5MkwRhncs5g0EMInTt3zvODw9pRv9dbX18/e+bUpz796e/86Z/dX13dPWgzwTGmDCjGWJorBIBMm1MFJQAKQvnYxRU87Wj8CFg4xhkkSI2DH6eSfewKRwildOlHy+l/uNo+DQ2nE7ZU5BKG4SNShFRK2bbdaXfur9wPgoAQIqXq9foQwtSLMkkSpWAcx4au7e3tsSQhGJumo+t6p9t64YXnDVPz/GGhkFuYX6rXj3zPL+SLS4vLjfrhw7X1Urlcb7RxmluiFMIQKMWlEFJJyVOn/McfMl3S6d/qk1xtAQAAKMUY29zaqo7CjJPRLb3T6WiENprNXq9nmOZLL790+/YdAFQaAvqDH/7gxReudHvDZqunJD5xYpElotls3713L/go/PJXv1oula48++ynPv2Zj65/RDExbbvb72uG4TeiXn/41ltvFovFE8snnLHcwuKSYZhSyqXl5TgOAYCpf/lwOEQI1euNdqcNAAjD8Gc/+1m9Xq8d1irlyssvvwyUun7tw7ffeiuf04rFXK12iKCIo/DBvf2l6ekE8kESMimQaQLFEcEslNDS/SgWUONAAQ6FIggSCBVEIF3oUAKeJDxhPEkIwAhglObOwtTQSwkgIQaQQCkkIoogBKCChEAFoIIYo1R3kAoNCMYYI6kEF4ll6ixOMIJSKgQxRZTLRCQMSCAATyEnCAF6RE1/fDyFzT3+l7YvKkliXdd93ysW86dOndrc2EqnZFJKx3HSKpBOyVPvfV3X02sgZekrpVqtlmmaqdK/UqmMjo247qDRaKTpL1LIjOM4mazneTMzM5ubm77vt1ot/ojtoGna6OioZWXy+XytVvN9f2Zmpj/o31t5WCjk7EymWMj3uy1KdARJNp87cfLkrbt3dnf3chmHxaw9GCZCAMV0ghAiS4tLe3u1o9qRnTG5CA0t2+/3NapTqh0dHVFKe50exnhjfUOjNAzCMAwXF+aHg35/MLQM0/U9K2NZpjkcDjlj2VxubnY2Wyyvr61rcIHHMdXA2NiY6w0JIVPTU3GS+J4XhqGTLeiGYVkWQkjXdUPXMcKu65qmqel6pVzePzr6wue/4A6HSZxYlsUZl1KmLI4kSaIoSvW+SqkgCFIxVbFYdD1iGIYfRJVKpVQq7ezs/uG//3az1dEN67De2TvoaJruheEjfYpSab8GAcBACAWATF3ZpFQf8w5/um6m9scIISlS37hjXu7TWMHjJXSsf/nrC8DHSWOpOPvxWyVJTAmVj0yLMMYIYyHE3bt3B/0BeBQg8vi3pOMyCAmEolQs2pbRqB/Nzc5VRqd2d7ZrR81Wp5t1rIX5Jc/3f/qzt+amp6WEKysP+sMBUGh19cFgMEQIKCAAkApIzpngKTMHEEIeO4jCR8Zm8NH88BNdbZVSGMJ8Ps87jTAMgQKNVkMIUSmVDcMol8qe6zIWEgovXbqk6Xh0dPTu/fvDKO4MA3fgu97Ng3p9+cSS63mvf+2XfvyjH3/rW99CCC2ePHnp8pWJyfH1tXW+F5dLFRpp84uLGtVe+fRnCvlCLpdlUbS+udbv9w1d39haF5xNTU7k8/mRkZFURjk5NVFv1Pv9PqV0YmJCKeW5QwDF/ZXbz16+8vkvfHZ2duLB/TsPVtZGR6udVl8p4GRyR42WkpJamVyp0A590zbAsG8YZMikghQBQBRIhJBCSYUUBApwCIBkXDIhE6YYpxADhBWACB0LIdNcMCaElAoJCTGCAEopj+uxlBAhBJBSjzUUx14wCCHPdaMoglBxnkgJ05EajxhgEikICEAYpD6l8Fim+7ecq2NXMCkVxrg/6I+NVTOZTKFgaFQfDAZpCndaCBzHGQ6HpmnGcYwQTmMCCKG5XK5YLKY8/MFgkMKOnuftH+xOTo4/MqCJpRSZjBmGkWVZtm1blsk5RwF2LCtJkjAMMcGp9rfX6xmGMTMzUy6Xb9+5E3KmhfFUsWjqBsw5LBZ+EN+4cWNqarpULMZJoqRamJ9vf3TTMAzbcTSiMBIbG5uzMwvzcwtUIx988DZGCEJ44cKFo3pjfGwCY5yx7OXl5UqpnC8W9vf3G83W6vpGJV+kmjn0fQ5wd+A6lpGSrk4uLI2OjbV6/b29XQpEpVzk3O12/r/M/dezJFmaH4idc1yLcA+tbsTVKvOmrCzVJbq6p3VjgMWaLUkzri0JkHjm/i8EjeAaseCSMGAHC2Ax09MzPT1doqtLp6wUV2sVWriWR/DBM7Ore2ZsX8sfrt3rIa97xM+/830/MXF9R1eVJElkSVJV1TBNBuDDhw/ffffdXC73/gcffP+99xBgh4eHa1fWp5blOI4sy5ZtjwbDnKYhCCVRMgzj4uIik+fmcrnsGOZyOU3THMfZ2tq6cmWdFxDP82EY2I4ryfL5xbntOPce3tdyJkKcYeY5QbZdJ3ODo5RkaY4vDN8yq8isdQBfUKefX86fO329IHKx3+9g4O/rJLyki73c/q6Q95uVLGOM5znEcTjFGZbpuo4Q5zruSw4AIRQhsLm1VS5VIEQAEEyIJIqSJGYh7c9fEXK6biBARVHUNG11dXVrb2cyHgdh/NuPPlleXKzWqo5nnx4fJWF00R+cnp5xvMBBmhG6OY4DgBFCRIHHmBKKJVFGiJckUZIknuf7/T54cSHJ4J5S+q1GWwgBY3Q8HjHGbMc29FyxUHBcr9/vA0rHo/HyypLnOYVC7tmzx7Y9taYTQRQmlnPnjTcZBrIoHB3ujKZ2tV49PD6q12srS0sU45PLi9+8/7e1avX733+vUq58+rtP9JyRYHxyerq2tvrTH/84jsPxsFerl/r9weHRsR+EM82m63qD/oBR5vleEIRe4Hm+26w3MMbPnj09PDgsFfO1ejWU5X/9//nXBdNMovj62lUcE0ziYqE4sSYQUSrwbhiokqAU8ufWhAR+W5NDjrq+j7MVGOIggxBiRikn8AQgQAhJKYkxw5SHHMyCwhDKPOIghJRllFeGIAOIQQ5BhCCACHEIcQBAygCgmDL8/AOddfIZBRDGScwADKMYEgAZpClJk4QRghhAAHCAQQYzqP0Ht+eh0S+THEHmQIsgl6ZkOrWqlbrrupeXlxnHHiE0Nzc7GAwEgQ8CX9M0QonjePlCXtUUQeBt28JYz2rhyWTynDSWxPv7B9VqtVSunJ2cuq4zHtlzc/OSJO/s7Ewm01wuNz87N7UtVVU5xCmqYls2z4uKopbL5fPz852dnUqlQiCLwkCV5ZyuNWsVRdW+frItCAIvcJ1OV8/pSM+JojQ/Px/jFEBqWRNRADONJkDw5OS43qirSk4Q5IW5BYET/0//x/8OQm46mXz0wYckxZPpdJaQQW8wtW3dzJdrDc9xQoxTwgmi2Kw3bduqlKsQcZPJ9MnTZ2tXrvrWtFJrBEEkDSdmPscLQhTFjJJCIc8YKxTz7dm2HwaY4GKxQCk5OTnXNN33/LPTs/bsbKfX29rcLOYLcRwLHF+r1TgOJmn89NnRrZu3JUkqFAqZZS0niCdn591e7+T0JMWJpumlciWM4tFw+Morr6ytrU+sqeX4vCBCIJ5dnGdjHcYYoRRRynGIUkYIBoAAAED2sQDgeeXLAAE0Y9S+3CglNGtngiwdIRuFod/7EYCMvvAigBfCFyLXP9i4F0aLhFCO4xmFDLKsByVJUhiGCwvze7t7GU88M4iAgCVRNBoMdD0HAZAkKZ/Px2ma0/W5uTmO4/b3D1wvEAVhdrZ1sLcbx/FgNNzd3caYLC4sutPpo0ePBYFHIoIMt9ut119/Y/fgZDKeaKrMKKYYIwAgRDduv9LpdKaWlc8XZFm2pg4DzLIsTdO+Ocp7Odn7VqNtdp7MvGGyOCU8QtC3/EIu3zk/n5udrTfrkiJtbT1bXFxs1Gb2tg9rtfpkahmlgojYxB33bUfi+dgNUIFxEGysrFUrJYEX2pez+0fHT548Pt47Wlxc8DzPvbhcWV3pD/v3798loftP/tHPYwk9OzsqVRqVYiVJhpqab5aqCKCT01PEIUEUa7UG6ANZVhilb7z2aq1UopiUKqXLQb9UrW6sXx11+3u7xziNUhJqpiIogm8FSeS223OjIN4/OvO8NMFUSCkAgpciTGlKMOIB4xCgEEGCKICUpknKMAUAQIRoZklASLZWARC8IJcAiJ7D7PN4JwQZghQ+Fx4QyCiikEGIOAAQy7wsaUoR7/iR7yYylDiSchBwlDEIAA8oYxxjIGvDAcheeHc8/y694PQA9jLV/OWKLxsRoIJZGg3tYqGS9QoyY6pKpaLpCjcBqiZVayXf923bkxQBIUZIPJ74oihOpqNioaIoSqFQsCyL5/kwgfOLyxzHTUZjRiElsFarh2E8ndoIoVqtLgjCyckJz/MEEFVWDd3gAFeqViCEnU5nPB6vra3NNBtBYK+tfidJk8uLC1kUe6enDJFSpUgoadQbEEDb8xJKy+XSYDAIw9ixAqOk64VCa252fX39l7/8q7xZUkVuvrU4126PuqNivtAo1//b//a/sx3nr375y89+9zkv8BSCRrvJ8UCSuGa96ifRdDQmETW1PEnZ8cl5vV6fWm5rTsS81Jt6QeBrOY3nEc/xZiFPcCKIgmGaADAjb+4c7lVK5StX1qeTqSqrDKDxaHJwcHTt+rUkTnVVPdjbm2nOVNZKuqqdnh1Z1hjjJE5DA+mUUgbo1u4uEpSh5c4vL0+G/WKltrW9rZv53vDAD4Pz83NKcLlcqTdmDaNyfHxGkhggmLl6IQgZZQAJLzD0OeuPkBQwgCDgBT4r3xgAkKHn9SljgAEOcoQSSimhOIkjSZIh4jJnDUYZzAzGX/K2IXquOYAgiwWFL1xis9JYEESEhDRNGSA8z/u+zxjzff/o6Chbf6U44XhZlIRKuTA3O9Mf9OMoWZprVarV0cQ+Oj0vlUo8z5+dnRlGbjyyqEZ4jjfzeUWVLjqXURRTTDxnWiyacRxM7LGi66qqPtnevRiMikWzVC1btu2OB7okra2tdXoDRoHnh81mu1gsbm1tQQ5ChCCHoiTmBJ4QIgqiwPEAgCRJvu21LQAQcVy/3w9zcb5Y2dvZnW3PKaoiitLXXz969923fd9TFGXQHywuGdevX9/d3dNzBs9xh4cHvU73ytp6r9tdXFzSdK1RrzuOzSEQ+P5gOjHzWrNZGw6HjGFVky47na2tLUHimzPN07Pz+/cf1Ru1hfmVZ5tbtuvONCuVijlTbSyvrjzb2tzd2wuicGpNS6XSm2++eXF+9vDBwzSJcRxdu36lNduaWNOdra2SWTBMgxDZDRiA0PPDBJMgwX3LshNqpZQAiATeCnwAAeD5NIkJzKa0AgchyxL1UpwmKcWUUfqcRvM8Bvy58RDL2gIIcojjeQ4ChrKiFFEEGQQUIgQAAZSBLBOXQsAYYZQBBiFI44TEKWLZIhESnNI/cBV5aRf+cgKGXhK3sx1/dMLYC4dvhNDUsgCAh4eHpVIpqzuSJIEQep4vCOL6+pXMXVtVNVVVPc/3/QAhJEl4aXG5UCglSYIQsiyr1+vFOC2Vy71ez3fdNIrTNB0MBhwnaJrq+75hGFkvIggC0zQ1TSsWi5TSk5OTufm5drtdr9cZY7V6zczNJ0nSP+tmczlZkgwIoygWeBFjMrWsMInXqtVerxfHsSzLsijnFdOQ893L8fnF10FM8hxfrZVmZ5s3b147Ozl9+vQhQ5xDCCakujDbdaaiovAA6JJkqBpTNCNvNufan37yWeAGiZdomp4kScbQGgx6mqr2+r3F+bnzs1NZUkRB8D2PkLRWrRRLpdCPGAMX55eKpDIAXdczjFylWjk5O3U999PPP3v11VeXFhYbtYaZMziey2bfgiAWi0XbdnBKGWWCJERRhCOsalqz2Szmc635RQLYaDyOkljRtN988L4qi4vLa6ZZPjs9kWVFFMUwjrLG6ItJFOE4HiHEsnzmbwjGsluzs/9c9v3CEAMwpigKQkAXNQCobbuiKFJCkiTheR5QijEBDGq6TgjBGEdhiASU2eRCCBDiFFlKoogQVq5UGAXj8UQURY7nRFEMgiAbecVxnJ19VVUBALlcrtFsXr12HT9hsixfWV8HEI6mX9v2FJPU893TsxNJlJozTcMwDUOv1293Oheff/nF4vJV27KGk+n8wiLkOMhxSRrVKuVerzcc9F5/7XXbdw8O99q1pbffeOPa9Zt/+/5HRyeXYZjwvCDLSppiWZYLhUIWgybLcvYBLhSL08kkK8+/3Wj73NCPqqpqTaeNRiPFyf379xYXFyaT0exc+/79e7lcrtlsTsZWmqZLS0uY0pjgxfmFSqlMMVZV9Ysvv1hcXBxPRkkUXdu4EkZRkkSyKr1y56bv+71ezzCM9kzbC8KD4wNRkqrF0qPHz6K7D/8P//v/3c//0eJkMuz2OgDQg6MDPZdbv3KVl0TEccVS4d/923/761//+rVX77zyyu2nT59MQ//uva+cwNdzuus6JEko5oLAV3Rh4linF504IeVyPsTMTVM/xUBQAYRIlhmlIMukTVMEIAchQyiNE5JiSgjMXN0oAACgzEcmA93njYTnY2EIIaBZ8wXAbG773Gvmue8oBey5eTeFWeXAKMVRCiOMMGUAZ0ZNjLGXCAozyjp48RoAPq9bn3fxwN9FW/DiS5iFY8dx0mzW4jhWVTWKomvXrlmWFcVh3ix0Oz1ZlovFcrfTSRKcVeEcJxSLZVGSGGMZ2TaT83GisLm1iVO8srhUMM2dnW3b8QQBTCaTXC5nWRZjTFGUarWajdE8z2OMiaIYBmEhX6hUKoVC4fLyMimZu7s7s7NznU5neXnZyOd3Dg42rl0Lg+j89IIx5rpuNm7N5XJJkkiypPCyKmguTY7PumZeX1xe/Pn3v5PPaYDhdrvRqJe9MOpNXN8Pzs7PdFnhEKcpcui6M6WyJiuVWlWWlYJp1iq109PTbDxYrdUmjt0fDOIwSMJAk4SZZsPz/IcPH966eb09M5Ndrg4OTsIkTinbPTjQNd13XEJJlKZe4K9eWZ9Op71+f7Y9iwkGEJydns40m7Va3XLsy8vu4qLqEd+y7Ik9OTw9ndo+RLDfO3/v3bcPjg72DvZ0Xa81as+2nsVJuLayJIq87Vi6rmKCkiSG3/APemFtQXkevSw2Kc24KC+FiM8nYC8HXzzHcRyfz+cxVgvFvG1PPdcPw5ASwnM8pTSLbSYUR5GP0xRjIssyJ6CMFpZNUJMkIgQXCkXGaBjFoigwRhESJElijMVxnLViIYTFYnFlZYUQQghdWJjnefGy033rrbcUTR+PxxDBxcX58/Oz9977rqa+dX5x3m7N1Go1hFAuZzx5Or56dSNXqBYK+ek0x4tClMSqqjTMiqaplXJJFMXFhfknzx6/eud6o1JqNZth7C+vLXf6U0EQe73BdGoJghSGsa5GHGQQgiQKOZ5DkIkiJ0p8FAcc/y2fklHGGFUVxfMsUS7HYZQ3DV1TLy7OGs2aZU01TT07uzBNs1Qqbm3tjEZjVddVM9fpdgPfh5S1W63xZDIYjTgOIcC6vV6v10MczJl523Z4nqcUyJJSKZa3dnaSJHFcb+WN1TBM/U73w99+/OMf/0mxWDw7O/760dfVWvvZ1lZvMKCA5guFN954/Uc//OF0Otnb27u8OKcEC6LEOJQypBfK+WIFEeDanmbqZ5en/cGwXJvpdnrDkaWUigmCiJcggJQCzAHEIYHjeU4gKeEQxGmKU0wxAYTwHMd4Lg4THvJZOxZTkhWXCHC/HyAABAijlABGMWNIRIwSxHEcBwSGaNYEeK79QpQARhghlCY4DROEmUAZAwRAhBAC9PeBfRm5K7OsofRFW+K5y+LfP/F4+WV7YZVAS6VSptwdDAYnJye2bVcqlQSnhBDHGQEAMKZB4OZyhiBIiqLomiHw4unpaeZWRQhJkoTEMUOgkC9Uq9Xjw8NCoWjbbhD4pmmKoogQymi5GeaKojiZTBBChUKhVqsxxhzHkWXFNEzHcUejUbVaW11dTdN0MBxKkui53uHhkecGEMKrV65Ajms2m/v7+5VK5Xvf/17NLN699+hyPJFVXRB4RUTNRhNQ0h8MKSFJFD958lSRzSRJjra2S4V84AcpCZW8psgSA9R2bMxIEPieF2Q6UVVV+71eEscchEkUSqJQKRU5BGdmmtZ0ijEZjUcA0Lm5Ochxz7a2AULHp2eqpAKM42q5MdP0wyCyE1lR8oX8r3/96++/916SJLOzszzHJQBynKBpehKnUk6dn18wbMOP4yC5PDw6GvS7t2/f+LP/5c9836/VahzHSbJ45eoVPaeaeeOTz+6GIW615zPKQYb44HnpCgEAGOMXIQXPy6CXKbYZ6mXwBwBQFKVUKpEkTZIkjqO9vT1B4DRdJ5gV8vkgCJIoTsKIJrGuyBzPR4RAjnGAkTRFHEriCKcJIYTn4MxMg1Da7w1kWS0WC5Ztp2mapmnGZsk8f1955ZVsWWOa5v7+PkTIyOdlRY2TdDAcTSaTSrUiK5JlTQWBf/udt/78z/98a/upJPPTqaVrOVEQb966tbt/wCNw7coqwenG+oquqQDCTqezsryo67nxaPiTH/9AUXkO0DCMHj3ejFIYhBEESBSlOE4Q4mWZo4QoohiEoSyKgihyHFev1yAEljUtl6vfarSFAGQ+I5qpTSyXg+ji4oIyUiiYkiReXJxBCFRVffrkyfXrN5cWFxkFgEOyJKVxMp1OOQAd25ZkWZIlTOlMo44pwQT3OoPhyM7lcowx13Xm55YCzwOU5HK5MJ7s7u4Fno8BTkny/gfv37x+Lafm8kbx/OKiVq+3F+afPnvaHw2fPnt248oV0zB5hK6srz17+iRMUzeO20s1PwhoigFhRdMcDnvjyaTZbluWTwEnIHnQHcn1iiiJqqz5nh8RBjkOUCghkeMBpiljlEOIMpxlMudUA1EuDAOYreyzXheEaUrQ85QviDFhjALIKMU8z9OE4RSLIkIiilMCAQQcpJAiwHEQIIYIJiQlNEpYjAXAUQAxZIRimDX1s2YwA4BAwF50Zhn4JgfseQUMM5XM79mFL9eYmWyh3+8PhyPDMBhjhpEbjUaKooRhlKXd5HLG7kBfEAABAABJREFU8fGxosiiKBNCi8WC7/u9Xv/y8jKfNy3Lsiwrm+diSquNGo+4wXAwPz8/nU55QRBEieM40zQzytd0OjVNM+sRS5LUarVUXQMQ+r6fpune3t7CwpyqKj/60Y+r1arrOI8ePRqMx4VKpd8f2LabJkSSJDOfL5ZKT58+zcqrJI4H4yHlgKipHEn+m3/6sx++8yrFLPCjy4ve6clpFISlciVmxEuikWPxqgwELsVxmEbPdjYhA4Ig5ApmtVbdfLrNAOh2u41GQxAEwsjC/CyHoMChWrVyenaSJCmE0LHt9bUVx7bOzs8R4o18weS5wWCkajrD6WgyLtermJBev08BW+GXZ2aaYRQWzELG5WAAGDmz3xseHhwqil4olobT7vbOjqDqQRQa5eJvP/6YkJTjkWHmHjx8eHl5mTdNMtNkCE2nE1nO7e5uC6IA8PNMxpfOQYwBSgkDFEHAKAUQZMYLjLF8Pu95nqqqmceYKIo8zydxnEQxY0wQeISQaZqVSg2ndDgc8jwvaLzEC8Vim+egaeYRQjs7O3Ec6Tl9ak1UXUNQy+hcP/npjyeTyV/+5V8JAg8gEwQ+TZmm641G4+LyMpfLmaa5vr5+cHAwHA4xxvl8vlypXlx2IOK7vT6EQ9/3Wu3Ga6/dgZBNpxOMkzgOHWd6enZsGnnDNDQt9/DBg5s3N87PT9eXZ81cTpaEYqG8e3hkTSeFQl6RZce2KMYXZ11FEgHjoph88LsvcQLL5QoAkBK3WC25jqtKIEFAkoQ0TedmW67nOY5FGSmXi6LIf6vRFkAIEAqC0ALBaByWyuVqtbK3v//qa69MJmNK6XA4XFpcVVR1MB53Op1quXpxcSHasiRK9nRy55U7mqruHx6OhsN+t3t2crSyvKxp6pUrG9OpMxoNDcMghN2//3B2ptKebZnlcv+3n/T7gyiMq1Xz7PTIc7393T3TMMqlcrlcDsJw9cq6ltN/+7uP9/f2j/cONE3hEGy1ZhrNZn9qeY6fQjnEsQCALLCcpgSuVMybszMzHBwokuZMLbNe6wVeFMcbaxuHO3uEwwgiimneNHuXvSTFEDDIACSQRyKCdDKyeMSThEAeYkoReMkRgIQwhF6ExwAIAOM5AUHII54QQBIAMEYQQcAAAphhBCmFBAKAU4KTFBHKs+ePR4BRwCBkiOMApYAh9nzs/Hu+I/jGwPgPZA6MMQYypgPIrJ4AZAB0ez1KaaPZ/NnPf/4f/+N/clxXEKXReCKJUkaZ5Hkh+4kxztbvmd09x/MJTjIM5TiuNTMDOdQbDoI4btTrDIJOt+v5nq4bvMB7vi8IfBRHM83mzEzTsuzj40OOQ6VSUValwWDg+46Ry928cTWKo5XVJVlWvvjybpLgQnXmrD/pjaz+cCJyfGZhMxyOeoPxYDipVir1RuPpsx3fdQRJqDbqr9x67Y3bNy9Ozv0gZgxIsrawuLz57Fl3MBjY06OTI0WWGc881y0WTUVVAs+vlsuIQ4QxRdf0gslzPEQoi2jUNKVgGjhNcro+Go0EXuz3+rdv3RqNhkmcppj0T887vXFM0qWV5YW5OT2nFfPmg6++uDg/n4zHOV0DCMZBWKo1ZEmRZVmSJddzNU0TJQkJol4o7exsW18/qLebtusVRPnm9WuA4cfPnjJIRUl6/PRJt9flJRHjlCaRwnP/+Oc/rdba2zuHv/ngtxhmYjFMCOE5HhPMGAOMQggYZaqiIg6Jgpg1EAzDyKLhRFEgBAdBmiV9SbyQBTUuzC8WS8XxaNzv9RGE1WpVVzUjlyM4rdVqsiz3up12u207dhgFjWbzypWriiybeXNnZxcnzMwVZ1uzPM/Pz891uz3HCVRVWVpcNHKarmuValVW5HqzvvXhlus5M62W67rHRyeO7ZydnUMAqtVqWDQ75xf9/vDw6CSfzy8tLjQaVSNnaFq+Xm/dvXffNPOarKwuLpuGubI4r4iwc9kJHOuVW9eH4/Hm5rPxdGJ5FsfB1szM5tbu3uGJFwQ5tWDm867jzM/NBUHge3bZLL96+5rvh/uHh6aZbzZbQRR1uh0spm+8/sa32k0cIgoi7h8X2Gv+yfbBBeTQ1bUrtmXfvHUjioIwDKIoFAVVVNX+eBiFUeqH87OztuPMz88rijIcDp88eUIpKRSKa2trl5eXL6SNYq1WPzk5ybSkuq7VaibHcZpmfPDh76aWJ0nS0nxDFIXhcOQ4jh+EpVKZ47hcLhemCeLQ4vIySXHv/FKSxdPT4/39vRs3rgFNfXxwHKRI1/SChMTEaxULrjUBHLIDX5T0crVx3u0GUfj05JjmlO/cfvXg6dYExDjFoRexhPmuzzDlIGKYQAAYZQRjhBDHoSiKM1TTNE2S5SAKs/YZQhAhRGhKKUEMUEI4iACEFCJRELI9BBPKMOAAhFDgeYS4OIkZJhyACPEQIoQ4SgABBCCaUcwY4RhB6EWSzR9JyH5/ggB4IZx5IX5HkGZLEgh5ns/lcvl8/jvf+Q7iuL/48z/XNM31PBwnjFJJkjJxrSRJmblBHMfZa1HAVEMVOQEwVjLzpXIZE+wGQavVkiSpPxj0ez2EOAZgHEWZnaBhGNc3rriuPR6PMyZvrVZrtVsPHz2s1+o5I3dxfj43v2AUjMdPNj0v6vRHc3OLU9uZWBOSJhygAo9efeUVx4+3dg8kSZZlKQObmVo1byo/+fF3KSW7W7vnZ92lhdn5ufbB0UG9UUOQua5/59XXRYFXZAlQ0rk8n04txw+zhXbmxosZm1tcZJTaU6ucL2iKqqrycDjIUsIURZlOp0+ePFlbW8vkGB9//PGVqxtmofhXf/1X5XIpDP1KtWzmcmkQOY4jSGKz1cosh+bb8+122zC0FKeMUZEXdnYPTjp9rZCPY//Bg6/6Y4sldG1lKUminYNdL/CjwLMdZ2FpaTweN1tthefqulws1+uN2fuPtiZTf+/w+LLTA5ByXCaOAJQQ9mL8hSDkBYEQkrURMnPLMAwxTgF47vMCAFBVNZ8zXdcdjUZRFPE8XyoWK6ViFEaarpmGOZ5MBI7HCXY9Jwx9SRJn51rtuQXDME3TmEwmpmkeHR2fHXXGo5GsipY9KhQMjNMb118djUbVWmV2dkaWpdPzi2c7+whC13Un00k+X2CEpml6enIqCIKmaTzP/fzHPzg5ORlM7anjvHL7xsrSPCERpZyqFj755MvLTue977+LKLl+4+ZkOi7l9XffeMWaDLuD4UW3d/fhQ8bxju/zvKBKCkSc7bh7h4eGkeegAAjK6aqiSJ9/+omqyK/cuPruu29blpcQBiF/cHiYM3M7u7ue5840W9/u2hZAAJFljWMaK7Ks581KpZLTc4SQfL6Qz5u+7/FIHk4njx49WlxYXFlaEjguK7/Ozs5kWb59+7ZhGPfv3z88PMxWOjzPe55/cnJSKBR4nltaWrh79+7+nttqta5cvf5/+ef/17/61a+mU0tR1MXFhe997/vT6fTB/fthFCmqfn5+zjio6frW9hZJsMwJlj1944032u2ZL774HBma6wcBBglJLZJUcspqvjwYTQBgBPFujNPx1E/Tar0Jz88lWbW9EIkSC+M0wnEQ0oTBLFWEAZIhK6WSKCVxFKUJhJAxkLXG2rPtyWTiel6aJJQhyAAEkIM8AJQSzCFAGQUcJBjHccooQRABRhFjgAFKGOQowjSrRrPxF31OvWEchyAj7Bse+//Q9pxdy57TdP64jcsYgFCSJEppv9//xS9+cevWrZWVFdd1eZ63p1bmp5MJ6qMo+iatPcvUQRApqgoZmF9czOl6nCRwPOr1eoVCYTqZZJefbOnd7/dbrVatVptatuPYZqHoBZGkaG4Q7uwfy6ohKrkoZW6Q6kb+g/c/CMKYFyRB4KbTcRhGsihAUcibOcext3Z2iqVqLqdnqYuUwtl2iyTBW2+92ZyZ+3/+D/9DGKYI8ReXnWsbV1aWly+7l1fW17q9R19+9ZWuq4AQkialYv7w6CiXy0dxzPO8pijl1dXpdDI/U2eU4kpJEkTP9YLAS5KkXC4DAGRZVhTl8PDQsqx2u63r+urqaq1a6/ZHSUzrtZnLzkW/Nz7YPSzn8+3Z9s3bt6r1+u7eHsMEAJhFtCGEIEKB50dRuL29ddbtrq8ve563vbVZypes6bBWrR4dHQZxpGsqL4qu40g8byhyr9spKK3Nnd2Ds/723tHF5UAQJEnm4zhO4hRCSAgmLzIaMroAJiQDsiiKfN8HABCCAQCapuVyuUqlEkVRFEbdbjebc0qSXCwWKKGTkR3F8WTijJTpzEzLsqa+71FK5xcXRVGoVEuzs/NxnH7xxT1KiWXZgR8wAuIkogAvzC8WSybHodmFlqQIum7mi5Xd3b3Hj7dFSWrNtM/Pz89OL25cuzUcdPcvjgWB5XKSpsmFQl4U+Lffeffw7HJ7bzeJMcfxuVz14qJnTQebmzs507h//xHPpRiws4uOKst/86v3SwUdCaw207R933LcXL4Qua5AwGRqyYpmyFqzXD07O19aWCyVivZ0eufm9VKxeHVjLV8qFyrNg4Oj7Z2DBw8fChJ6++23GYNHR6ffbrSFAEIYR3ECElGSCMHD4TBv5tMksXFiGDkI0YMHD95677t37ty5OD/v9XochGY+n6ZpuVz+4osvFhYWzs7ODMPodDqtVkvTNF3XFxYWPvroozAMcrncycnxxsbVwHM83/vqq7txguuNeqVa1iSZUpimOE2T1bVlXhDHY3swHAZx6Pkeg5BhansTnkd//dd/vbq6ous6obSdMyw/Oe/2C8WibYc7R+eaZm7vbV+/fXvv8FSmAgHID+NivjTF6c7BQeoEYZowShFBjGJTVeM4ThMMAUAQUUYRY5IosiRCEAEABJ5Pk8SaTEVB5BGXMgAZYDTrKwCaUoYZECCCiAHAQUQhfM5wBIBjlDEGUsIIFRCiCL1USrIXlB6QxYX9fcox+A3rpm9u35xEv9wy6MwYMHEcY4w//fTTd999t1wud7tdz3GiJBFFMePxxHH8Ry4eWk7Xclqz2dAUlec4QRDMfH5nfy9T/ZZKpeFwGIahIIi2bReLxUKhEEXRJPQJIaPJtNlsEoIBgOcXl5VK9eDw2HGcVqt1ftHFmEGIKpXKaGqlacLzkBC8vr5eLJYODvbH4/FkOi6Xyo7jJFGqaerrr71y49raaDj4f/+P/9No4pqFsqwob73zmud5kIPFQnFnZycMwk5vgJNEFoW5ditJEkmUcJrOtdvlctn3fVWWlVpt0u8BAMIw6HZ7iONyuTxj4Pz8vN1ud7vdbNA3OzsbhqEkSXNzc2EU+35kmnnX9ddWr0RRdLC3c+3GNVXToji9e+++5dgix1eK5awVAyCLohDHyeXlZa/X63Q7EFFJ5Awj127PqLI0Gg5KpSIZj6I4xmkqC4Iiiw/uf2VPp/ZwyMuK4x4OJ66mmxgTVROiKCSEguexCOCbJygbF2SyPUKIKIr1eiNTrD6fiA4HURglYZzpeiVJmkwmzXpztjXvum62+Oj3hxCBVrvt+15rdpbjIEJgf//w8ODEdR1CSLfbrdVqgeumOCkpRU3TqtW6IPBb25srq2ueG3762Rc72/thGEmyQDANw1DghLyR11WREF+W5H6/v7a6ePPWzZySK1dn/ubDj8/OLwjBa+ny0bOdIEyazfmcmS+UCkkaRL67d7A/nvoAoOlwaOhSLs+ZvV6jOTOyHIS41aUVGSBd0T0/mKnVF+cXSJKWS8VCPl8rFRpvvxnH4ciyT887SUq+uvdwZ2efE4SVtRVFVbe29rrd4bcabTN5ICFEkATHGetmLk3T7e3tubn20vLiw0cP1tfWf/azn/3V3/7N6eXF9Y1ra4tLo8Hw8OjolVde4ThueXlZFMX19XXHcVZXV2VZ3tramk6tUqn4j//Jn04nk/F4nOLk4uJsYX4BQK5Uqu7v75+cnRpmvlasLszPMcZkWQIQC6Lkn3nzc3OO7/eHfUyJoqogJaaZm2k1v/rqS1WVS0ZORCIXU5wzHCcYuL7Kq+3FpWhvP1dprGmlDz74+Na19bKZ3949Yjzw/ZCGKcYEAsYDjhJs6FrI8y7xcOa8lYUeyhKXJSdzPAcRLyvTyaRYLFYrlYuLi5eG9YhBADgOMYopgoghRgEROC4LoAP0BQUyszt+ThmAmZUtYwwAmGl0AGSIPhdhZiSz/+3T9A02AmWAgec8TYxxEATghfnI/v7+T3/606dPn2JMBEHIJLnshckIY4zn+eyBhBBN10RB5AXBMM0kjk9OT7PZiyAI0+k0m8JpmmiaJmPMsizf90VJKhSLYeT0B8NqpTq1pgIv4CTVVHV5aens9Cyn66/cftV2bMTzhDFC2Xg0fPP11/qDAaU0jFJBVBCigoAAw0tLc6/euVMomL/4y794cP9Bvd6em2nHOMGJl6bx+clxp3s5Pz8ry5Jt26Px1DT09773vaJphIEvS7JpFtvtliAI/f6AEtLr9ZaWFjRd7/V72/uHlLHxxLm2scFxXBZak7nVHB4eGoYhimKpWLz/8JHnu2HoA1BqtWeCwLOdiarneJ7f3dv/8u5XpWp1aW4WAJCmKUKCH3hJGiuiZJrmnTt31LyJELPtUb1eGwx6tUplfmFugZ/f3tstFMuDbtd3nbyhKwJCJFEU0cybYRhqKs9YRGnCgJLNYDO7L5j5ayKYKV/jOM4YshkloN1uI4Qmk3Ecx9vb2xhjxpjACwhChFC5XK5UKoPhQJTEg4O9NE0Nw4iTSFVkL/Ac15mdneUE7uz0pDnTODk9Pz8/jeMIImQ70yQJ69WqnstnRm6eG9y8feuDj3/HC+p0au/t7Qu8wPNoPBpwEADATENP0/iVWzdnZ6rjyUTihcW5+Ssr60lCnm5vP9vaWl5bW5ifvbjo7uzsRjEejh0KqaKLJTXXKK6enncVRU4xyxeLnjPSWc7IGePhGIeJPZqaq1cKmjY7txBEca8/aLVmzHzh+PhYlBUzpwuSUm8045PTv/zlr1w/sGwPcIIgKjduvnp2dt7rj10/+DajLcuKK1VVj/a/1guN8XjMA85zvSiOzs7ONFW9f//eK7fAf/9/++//f3/278rF8mQ69Tzv1VdfzefzX3zxZas1IwhiGIa6rg8Gg/39/cFg8M477wwGPdux5ufnS+WiIIiHh4eTseX7AWV2szVDGPUDv98f+J5bKJoLC61e/1LXc7VafTgaYYI1TbMcu1wqN69sHBzsf+9732s0an/7t78WeB4wyouoVC35IzuJcIqEWnu+WG/e+/opYTwna61mu1Us7+0eTrpnPOAYEhmEOIlTimmKW82Z0WjkWB7P8YRhRggPURSEECFGKSNU1nRMsKHnEEL9bhey58Y0EEBKCciGUxRQSCmjKSUcQhzISl1IIXjZUSWQod+rJSGgDMDnPuHo7+shvGQd/FENC2Gmd/iDPYjjXnIUXhpzcBznet7Dhw+jKFIVhTEwNze3u7sbx3HmWZWxoyRJqtVqtmNnLs4Iwovz86y5yUVcr9ebTCayLGmajhByXTdzbEEoC06HSZqa+byu691+TxCEZq1aKpWm1hQQfPvm9ctOp9vthVHYH/QpAo1m/c4rt3udzmgy8f0gjuPm7Nxk2BE4uLQ4//obb1iW9Yu/+C2m+K2336lXGpcX55KoEhI9vH9PEsVSqZQlW/zwhz+MMSkVC+1mczwc1GoVWZQEToII9ro9DiF7amFMT8+6kqpIqgIFxXMdkMSu6y4sLGxvb3c6nUxiOx6POQ5FEX92dta5vPzOO9/VdDlJoq+++hQh4HnBYDAaDAdeEFAIOV5QNT1zvQIAYIw919u/2H38dGv56nXf91dXlzx3OjPX6l1e+r47mQynjkUAC2McByEhOAz8vK5y9SqgjAdkaa45nFhTx8VUDKIoCAPIZEIoZTiTNlBKoijKtAwcx+Xz+WyxOJ1Oh8MBIQQhZJgGz/GapnmeJyBeEIRisSgIgmmYl5cXgefVajU/cBRZ5mQ5jPzBeAAQrCYlRVPvP3gg8qLrWUHgLywsCAJMkvTGjWtpmiZJdOPGrcPDw6++vOe6sWV5SZIiDtWbNQRYTucd2/Z8v1Qsdi+P+TvXVSW3/NqaKmvNemvQH40n068fP05T4jj+4fGJKgmiIvZHo0K5xIuAgqRcrc1Wm62Z+U/u3h2NJ5RG5ZJx+8bNZqO5u7uvtJUwCEmS8iWJE4SSYcQYA4Q4Se4OJxPbnZ9tn52eQACqzSZmYDS1dd3kCQMAPXyweXnZCYKE58VvM9pmAlFCGYYQXV6eA8STIlZ1ZTQZW4517dpGc6b9u48/CxP86s07k/GkOlv+5S9/GSXpa6/eefutNzc3n3U6l5qq3b7zWqVSMQxjfX3d9/1Wq310fLSzs5fgBEDUaDbjMF5oNLq9ruMFiqL7fkQZPj07q+1VJVkwzLwkiuWy0R9cSDx8683v3r1739DUWrV8+9bG8fHR/Oz89777g8dPnkqaOrE7ncnYSwkncd1B5+DoQNVzY2vquo5pSP3uyaR7ISoiJAwwKgg8wSlAKE1JoZC/fv36g/sPONihlKVpSgkROB4AqGlaZrY0MzMzmU6ntqXpuiCIlMYAgCxYgWD8nBILGYSQyyTrlFEAIMr6ABCwzNALQQoZzLS2LOvGvVDmIvqyfwDZc2nDN5L7fk9QeBnr9wJ+f6+JoCxzmAYQkBQzyCCCCHJJGJ2dHKmajFO8vr4u8GK1WmEMEErdwIvjRFeU2XY7CkJFkpMwySm6NbUkUWIA+kE4mUxt20aI4zghjpMkSQVJAgjxokgBqNbqKcaY4MAPSsWyIqmqLL/15ptbW09nW/W19StRjO/eezCYTgCCmJCCWdL0oqIaouSaZj5JUwjIZNgtGuZCu33rxkYcBl8+fsxBtLC8Sgi27UngezONeUqSI/+McSjjXlQr1Tdeew1jzCgVBJ4HlSRNJEn0PFdTNcQzCfG6ofQGvZSQBKen5+c8J0RhrMlSoVxSdM3z/aOjoyvr64gymtKLy4FuGqfn5/3xMIr9n/zkh0+fPvn666/X19fu3r1/5dpV/37g+t7qwtLa2trywnzRzOVyehLHJ0cnzzafHR4eXLl6lZHYnY7+4r88WllZfvzwYT6fBwhgitM08oLAmtqAUkngAcV5w6BIOLroanpg5nNTe8LzfJLC8TCAgMscjwCAJAvvgJABxgs8Y4yDiGBsW9aw38cYi6LICYKqKuVyybFsz3bSJHHjmOf56XSCIBIEIQxciNLpdKAo+vHxIcfDZntBEOXDo6Nqtdyo1e9+8cX62pVCodBo1G/duhkEAaG4tTDj2J4fhBe9Li9Jv/3dJ6qRlxTNcWx7Mr61caU1U3Nt6/zynBf4V199PYrS6dSZa82enl1MLH8w3r7sdBNMhuMJghxNYhwBvWBU5xoCh+ozje6gNxmMqqb5pO+url8xNc13LEnLzbda9UI5r6rvvvFqkpAoIkkaC4jTNf3ew68/++Lu6vqV4cQ7O71UBHhxduYFgZbLnV1eIoQWF2Y5QUowtW2nP7yEMBEFltPUbzPaAgAYgBRCEEURx/Mppn7opAnJnEr4Xf76tRsbG1dPj48+/d3H//S/+qfVSnllZYXj+I8++ujNN1778Y9/OBz0JhP75OSE47ilpaWdnZ2rV68qiiIKUpKmkqJGcfzF3btLc3MIgvOL8yiKS8XydDwtFfOqpnZ7PS9w5+ZmRYGTZb4105BlpVosNmt1RgkElOBke3tzMJisr9+Q9cLB5YVPYEgoQEDgIM/DL+5/2Wi2CCav3LzRuThvt1sXl53ji5ON9RXX8/uDIQdVxKjvwzTFm9vbHM+pshIEAQSA5/kkTSVJ4gVBzKj+mU8CgqPxiFL6XGWAIEcBhRC8MAUDDHDsuVlBVn4yxiCgCHCZASPMSkEAQeaoTxmEAD4PyHnRhIWMAxAgAF4A8HNhw/Pf/ygE5Rvq3udEaQhARlGglFEO8YAxRRL+9Oc/uXvv/mQyKhQKtVo1SdKp7Tiet762Vi1XPNsxKnqv36eYMMo4xDMGjo5PMMaTyRRCqCgyITQMQ4CQJMtmvkAI5gVB03XHcRqVxsH+QcE01peXFFkOPbdZr966c+v49OzDDz8x83mzVpxOLQ7xkqQ4lj3uDzaurOexORmP33zjDoJQFOQ48D/96KO8abz39tu8oj988shz7WqhQNJo0Bv4vu96LsEYahpCbDAY7OxsL83NZaN5TVVVpoiiIEkCAHBmppkksayIEEJekC3b5njecdw+4vLFYozTTrdr5PM3bt409BwOwmK+6GHyxf2vBIGbnZ8TOL5zcXl2cnbz+k2cpqqmQR4IIschsLq0MFMtT0bDzuXZ3NwcADCIIsYgYSyMwmsb60Hk/pe/+ItCIR8lsWVN4zgK4wBBmNNUxwmSJKlXK5RiPwwntm9F1E2ckT3hICsXynGU4JQDEAKGKcXg+Wl/0S9CgBLG0pSkKWBM03VFUQihmALG2PnpOSU44+QyQqI0RRACAKIo4gWQy0myLM7NzTWbzYvLM9uarK9fDwNv0O2Oe53QcVzHWl1dzuWMNMVBEK6vX4mT5Pjs7PKiWy5XVlZW3MAbTMfValEUeUUWfXvKz9QhgH/yvffMQj5n5L/88pHvx7Va42/efz9JUsvzppbFcWKa4lLBrFUKC/Nt09BFEfn1qm1ZOE5b7baIxK93t8IkHfa7V64sL8y1TN2AFIg8zwDTDKNUK3iOMxxcDEZ2nJBKrbF3cGJ7URJFlWKZ0bRRnJFVPa8rV9ZWU4yfbW8TSjUF/eSH3x8N+of7Bz/90Y++5WgLEOTiOAaQcJwQpbFlWWEQq6pSLJZ2d3e7nc7ywsrq2koQ+O9/8JtevzuZjPOFwvr62sHBAWD0/OzUcb3bd14fjUZhGGqadnp6enx8nM/nm62ZTq/33p9875plEd/jICiat85Oz/f3DwmhlgXDMGg0arIkq6qqaerW5tP27GxkuUFw4nrOaDBaXlrq9ga3XrmzvXsQpmkMWARYQFIqCRzkEEQUkuWrVybDybA/albas+31veNOo169fvXqXLul69pf/vKvpwGWBAECIEmiruU8CjRNS9M0juOMTCOKYhzHpmlmK83pdJr5w7NskkYpz3PsG/ItAMCLTAUIXpIHMlEYet4NeLllAxDuefhjxm/+RhJJVs+i56GkEEKAXpayGa7/PZ0H9ofJqRRSgCDiOA6AWr2uqeq1a9fK5er5+YXn+sViqdvrVUpFSeAFnqvVKpeXl/lingCQUjIYj6IoiqLo5SAu6wuZpukHQa1WN4xcNl/a3t7WNf3y4mJlZXFxYeb11273e72Lk3NDV9//m7+ZX1yql0sJoeVGhWfU9Xx3OioUilrRsCYjjFNAUxEhhODTp499z//h99+7dePmzt7eeDrhIMupcuTZRVOvV4qOwL16+0YUx4oqH54cpIA83nwyGvRrlWpzpokQZ9s2xmm9XpMVmTImyaoBkSRrnhdAiCzn7PTsLIri6XQ6meQYoY8ff80Ivbaxcf3mdTeIdo9Oet1uo1F547VXf/fhx9evXZ8MR999+51nT5/evHb9yddPcJLONJu1et31/ZOz09Pz09PO5erqqp9EUOJX11aLhQLHofn5+bW1tcFgMJmMp7YdhQHiIMdBANj8/NJoMAyjoFIuDvs9QmFO4VOMEYIIoDBM0pQA8DyfPBtzsRfLIkpZEiUQQk1WOIRUVVVVNQxDnudIiqfWFFIqCjyjhOAUAACzDB3KeJ6rV8vtuQaPZMvyWq2ZTvfSmfS6Z0ft1oyuKa5tSwIvimh5Zb5SriUJ+fWvP/jwg08mU7tQLERBsr+7d3x0GPqOklMD39JVeW6+hRlxPNcPAklREcf97pPPnm3uFUolXpVEVfKSiBO5BKccTWuV8sL8bLlcmG03Pc8RRHE6mQ5GU0Axh9Dq2urR0Wm/c7Ew315dWpidmUmS2PMiL0oePnmm5cvnF0NZ5FURTCzn4OhEkNU4xbY9VSRhbqFdLJgMQkGSbcvzYxyHniJyecOoVct3rq1RutKulX1n+q1GWwYghCgMA0pJSkOM06EzFgUZITYaEU1TMU4vOxfjyfjWrVtpmnAcDyFrtZrj0UjTtN3d/avr64PR6PHjxxkD6eOPP97Z2XnvvffCMHQ9L4zC337026vXrt66cd2eTra2thuN2iu3bo0n9mhqHRzs37t3f3V12fPd9fV1xwn6/TFCsFarYYJ5kT89O+cEiCHrT6aIl8e+B2WJASJAkCQYIp4ifjSxZmsNHUqd4/OT/fOYxTlN+97bb4euFYZhOV+YeiPH9sqlQhKHAACc4ixKnef5MAwzG5d8Pj+dTnu9XhAEHMehjIfAAESUA4Bhwv4oWIH9weQKgJfd1RfGXeC5i9037gNfpuCwl/IwCFlm/wVeOuNlD3hZ/r7wUPhD2e7L58keiCCklAo8X6/VAQDFYtHzXFEULatDyHRhbgHxQFYkXZNH48ns/OxlpxPFaeD7HM+HUUgpRYjTNC2D2lwuVywW/SAsloqWZSGENjY2dnZ2EIKaqvCQKbKAcXTl6rKhqlvbuzdvvZJi6rgOBcB3xSj069WKMqd1u70kimv1Wq1anU7HZ+dn0+n4xs3bpllqt1u/+Ju/3drcbLXbaezcur5xbeNaPmcYuZyuaY7tnF2cf/3k6zgOIQ9CRmmcSpLkBb6u6xzHPX36lBeEudlZSlm5XFJV9fj4hDEAEer2ehBCRVHyeXMynZ4cHSdJ0m7OqKpquXackpPTk3/+z//PD+59GXleo16fm5vDGNfrNcexXd/vnl9AhErF4mgy9n3/2c52oVywA+/hk6/39vfTJP2v//RPK8XieDx58ODBdDqdTCaTyRRAwHEcREyWZUKw49iyIjGaYpxUa1XHcTmRn0wCSZIwYVGUxjH5ZqeeEMIIfZHAAIpmXlFkAKDA85TSJEmy+F7I85IkcBAygm3HyaphnucMwzByhihJiAOqqtvToFAoDgaj1ZU1HIU48mdbjXK5rChqY6Y5vzxfLJdEQX14//HF+eV4NClX6nmjMBr0Pc8zDV3XlGvXrtTr9Ua9PhlN2q2WM7UJBbmcee/h/QePvn76dGd5bdVPg52DnZyedx0niUPIcK22ev36FchYvVr1NdUsVRwvDIKnDOPmzEwQJoVC0TT0t99+U5UFI29SRo8unlqOr5nlqRPcffTA0JW3Xn919erVoW17XmDbk2JeN80cEjhekgaDIWNTjlem06k16tVK5ve/+2allMeRp+eM1cW5b7tyF7ywe2eMUEAYSAWB43keISgIPMdzEACOg6Io7O/v/vSnPzs/O1tZXRoOe3kj36w3trd2jo/P5hcXjHyh2+2ORqO1tTXP82zbNgwjXyx4YYAp2dnZ5QkZj0ZhGBuG0OmPFhcWzzudN9988803X09x8uDB/adPN9uzC7zoybJ0cdkBCPKCYFn2efecV2UMgaZqKWNeECCBp3GKU5qkAUOoG/ffuX7jjfUrX3527+i8F0Z42Olqb9xeXlvbOzxhDOXzBc/zZFkZDYf37z+Mo9CznSxaI6NPZTpU13UzQhWhFFIGGXy5rmeU/nF9CZ9fqb4BnQiw3+MpzExvAQDg96YIAH4TnWFWyX6zM/sSUBl8zjoDlCHKvvlCL99ChuYv+QaqqrSazTiJNV0/O7vAhHY6XcZYFlDo2BNZEKbTqaxIo+kICVxoOYqmRVEUJwnP8ylOAWWZbWihUGi1Wpvb2xkhzPeDTIG2vLR47eqVQb8jCqLEKznVLNfZd0r17d3DbveyObcQRkGtWV9Zu/bs2ableJKihmF82RudXnSn0wkvIFVV6s0ZQti//v/+W4A4xTDyxXw+19w7OBYEJYkTgec5CPu9SwZonETlQr5arYiS5PuhG/gQgMF4FIZhnCS6IJ2eXfA8H0SRbdn5fH5hbm7/4FBRlJlmezSd8AIKA29ubi6J43KhSCkNo+Dew0eb21vzi3MLs+1HDx8mFJQvzoMk/pf/6l+9+eYbxUJhZWlpOBzOtGYAhF89uC/LksSL4+HoypUrBXPY6XTSNE3iGPLcw0ePJtNptV5rNJvdfs9xHMowz3OM0clkZOR0BEEURQN7OtNslkVx2D9nAmcYRc9N4sQBAL2MoOeyPAzGZEXJZMdBELiuK6pqZkmj67qmabbr8gKfxlGUhKVyASdp7Edzc7OCIDQajVa7PRoP1Zw+GR/FUVIpV6u10sriXBKFoiQXK/UU42J1xrL9x082HcftdYeCyBWKZhw7UWxruvTWWz8KguDk9PjGteuiKN6+9UrgR+cXl/3h6Zuv3zk6Oe10exPLkhTFcR1rbxz4nsjxJI6LhklZwiiZbc+KHL+1uVksFDf3vtraelbMm7OtmUKh8PDRE8/1N67foJDbPTzhjthgNLT9MIqJppv9zqXEkdC39/f36vXq4lzr3r17piZdv7omK+pgMOF4rVZrha5jmsbjrx++853XvvPaLZYGSRTOzLT6gyEA8PMvvvp2oy2DLDvZHISMcjyURCVNKAU0xTH1sapotm1TxgLf393dLhQKURzV6lV74pyfXUCIZpqt3Z09y7Vardby8nKn05lOp/1+r1FvFEolwzQGw2G5Wvntp5+/+cabS6uNP/uz/yVNse0F1zauHZ8ct9szlcrc2trqJ598dnLaeba5Va1VarXy0fFBuVDhgFAqV30cdftDKGqI4xHiowRzkOMZStKEQCgpkozgTNn8yfe+s31wtnvR9a3B5clRxdDvPXh00R2kSIyCaNDvA0oAoLIkGYaRmfKBF2Yfg8Egk11lRwW9GPk/r09/78j1++1lbfL8z+carWz5jzL0fX6Mfz8W+4PHQvjcHvePnja7/D23aHwB0P8QFTcjDDAACKWKoji2naVtjyeTKAwHgyFCHMa4mDejJMY4GU6Htusoii6IYnYcKGNBGEqiiCDI5XKZDL/f7wdBcHBwYJqm6zoHBwemaVTLpTSJrm1cr5TK+7snd796vHO0G0TY8xJRViRFSNKoN55atmNNLY4TIYB+GFHKBFEgBJfKhXyl/vmXXwm8EMQJ5ATGSBj6c3Ots4vO3Ydfp3EiS5IoCprGy5LIAGOYDLvd9uwcRNBxXQhARuY3TNM0C47jpDgVRKnZaiEATk5PDMPQDGM0mrTbbYjA3u72xcVF9/Jyrj1LKSU0ZhCJkuC6duf0JAy8GKCPv/g0ThIE4W8/+/TtN79z++atOE2/fvJ4ZrYdJ4nnujlVJXFSL1fYMhYgVzDNDz/66OrGxtzcXBiFYRR1+/04iXM53XamADw3M4yiSJJEP/Adxy4X8/Z0iJPQY5RQLk34FBMEOfnFlrkjijyn67rvB6Ph0DCM69evAwgef/04o/EhhEajoSxLosjPzs02GzXP8c6PTwwjV61Wc7lc3jRmZ1vDqeW5T0fDi0qlPBz1V5YXlhcXvCDEDH34u8/HU4skQef83HUdVVVnWq1Go7Kz9XjYP6lUajdvbPz6179hhNlTp1gsOXbwF7/45bNnW7IstWbqmKWW43S6XQQk3/NrjaIuKdbYKuSMSqkytzhbqVd2NncDz9dU7fT48uudp+trywutmVKp3BvZsqZ3h/bdR08ven3ftXI59eDoAIpSuVgdDAads8ON5TZA0MxXAtfe2XxcyClXr6wbZnFoeYPBZDB0K6XS/Exjf/vZz374vavrqzldDXxSLhUVTQvjzsnpxdTxvtVom/mwcKKoGhqMMCVeFAeUAEpSjkiiJEscP/L8aeAVdMN13MW5+eOTabFQvnV9djoeHxweDUb967c2jk/2h6PO6Zk0Nz9H2WI+X5ifX9zfPzw+ORl0uhxAkqT/8ld/e+3axptvf6ff7fT6ne3Nx/V67ebNjRSnw+5gaXGhUWt+cferXr/LCSinGReX3Z5kL62sXHat88uh5zMO0ZKpjRxPECRGGEkTSZA5BkMntCZTnudnZoqvvrKB0+Dw+OAvP3jfidNavX12dq4rCo5DDkJJFiGgHsGZX2dWG2YC0Kxx+dzvLosCgy9sCxiDL7xg/p5j+LwnABijEGV+tVkP7uVBhoyxF+m5z7fnlSmAmXHjN8/Ii7o5+wtQSF8mV9NvmCm8LGw5yFEACMET25pttxQ1L6nhww9+VygUCWPdweDqlSuHp6elcolB5LlBrVyP40QUlX63izHRFCVJEkEUZVlGAo94burYHEKcwDMIBIETOEgS/5/8k388nli//NXfNGdaSYpHw3GS4iCJ0xQHQYwJRhwSBD4jFwuCSGhECTUMQ1ZknMSA425vXNm4cuXp02cX3SGlCADGy+LpyYnteEEUG7qWU9UkCjGlUcxSnBi6vrS0/ujRg1KQJmnKCON5vlapAQCCIHSRl8RJzjBsy67Wahdnp75rra1dUSQpkvmCKu6fnk8dr9e5bM00e6NR3jQatcbm1vafvPe97Z2dg4ODhbnZhm7Wm82U0anrjK3JR59+Mr26wfH8n/z4B+9/8H4UeWmSTO2JaZidy8vtze2lheWTg5PQ96eTSaFQCOPYs6aO5xaLhcFwiCAIkoTnOMYAjlJGoCjyhKEowoqgcUzgoAgZIpiqiiJrJschnucpoQTQUj7XbtQt207iYHVlYWlpKSL0t7/7ZDSdUEJJmjqOY+r5leWlMPQlQUAUra2sKaKWy+mu68iqBjl0eHL2wW8/CV0PENLvn40dYWNjtVqtTfb2/uqv/3Jnfw9TWlDVZr0izs0M+v1ywZiZqTUb747H48vLwXg8evutt2bnF7f2j47OLu4+fPTk8WOcsLxpJAm5uLi49+Xd+fk5SRQBhDhNZVGCprGyslIqlq5uXBdk6dnms7FjjZxpt9st5vT15ZVytb67f/TRJ5+7QUyBQJEdp+HsTPWtt15bXJ49vuzt75+MBqMrV668eu1Kzsj5BH7+xRft9uwbr95u1YvDSby790VOUar1JmP0ondpyNJ8u9WsltI0+eLxNoHo6tUrmPEffvzp9//kB99qtM3qpzRNgyCklJcEiZIUIAQhxwDDmE2mlpw34zA2CwXKWJJiDvF3v7zXqBSrlWJOV0/PD/YOdjkeXL26USgUBv0BAPDp06e7e3uLC4s4Sd58/Q1dz12OJvlScTQc6Ip869YN27JV+SZj7D/8L/+hUCjMzs4OB0Ndy83Nz3p7Qa1e/+533h4MJ7/6zQf5fPF2sXx1bX08niQ0vhwN45TGFBJMAaOapNxaWXn91TupZ+cMrQTLkeuLgmgUyt2ne/vHXT9I85oO0fMkuTD0Mi5XsVj0PC8jNmY/X4IvAIAXBABhEsdcNvVgDL1owmYbBIBDLyMV4Eu5F3qBkd9c9f/R8v/lnswMLNPmvrzP72dflD2nO3wjSCpzIkff4C0wxhgFkizJskwI8YPwi6/uKYqi6bmcYVBKPc87Oz+vVksAcrquNhszPM+HQXxxfslxyDAMnuMopZZjR3HMC4JHaRb6xItitVpN0zRv5iqlYrlYcFz/Bz/8URQnp+cX1YY0saaJA0YTCwAgy7IgCIQQSmiWnMYokyRJlIScpmCRKxXMhdk2JUm31/PCRBAERZauri4uzzUH44kgSpomn5+eXrpWpVYrFor5fD6JwiSJb968aRo5VdOePXuqKqptWYIgEEwABRzHQwBH4wnH8YZhKrI0HI4UVR2NxrbtbO3tA8RxvLCwtBSHgT21SpVaEDz0XNf1XD1vGqXyqDs4ODn57ve/9+zLz69cvWpZ9m8+/KBQKEAOAkD1nDboe+PpZDqZfvzx7xRBFjhxMh02Zuq1meZXf/3LiWOHcWSaRhTHKU45ABkFcZpACDgOQSBEUZgkiecHRrUua7mUUI4XZFUQZB4ALgzDiFJd12u1erWYT5OI4+C7776jqupoPPrwww9TyqrVKgSMgyhNUlM16tVquVxkgDSb9clkUqs1FEUWJUkU+f39/SebW57nzNRr1VKZlwQn9Jszrd3dg82traPDI0poHAZIV15/7U690Xj//fdbrZlatTq70EqSZDp1OSQSDH7xF798tn/IQJomPiXPc+Rsa3r3q6+WFhbf++47l51Lz/cW5hcsyyqWSstLS//u3/37+w/v//DHP5mbm42S6PD4RM0ZG1eu5IzCL/7q1+ednhfEDKEodtPYdab0u2/dKeYLd+/ee/R0B0A+n8+/9dbbV+bbfhg/2T/xQtxuNeszswIPeIFubKylabSxcQXj+L/8l//1vR//N4uL853Ls48++ujw5Hxp9eqXd+/fufPKnTuv1uu1bzXaZrZDmFDX8QCUZUlgaSJJCgUoSSmmOI1iU5FJmpyfnxVMo9fvFkqlKEkX59s4iQHkbt++HWO8v7fX7437/bGu6RzH3bhxUxRF1/MUVXVdByJu2B/U6rW5Vms06H/wm/c1VdNzeq1ee+e770EAut2uquccPyAIqHouxfQ3v3n/+OTccoM3X1catcre9lZNlwStOJ06Ekx4SQzDGALUrtWuLC8IAuJk4cnjr2fac/2h9cFHv52Znev37cCLEBJSjG3bwhgnSczznCQJmYQss/zI0E1V1cxaO0uujuOYMZY107ID9Xf1Xn9U574E0OctghdRoOAPG6zw73Qk/ujZ/uAOL9q1f7ADPB/FZTfxPI94LouMNU3z9PQ0l8tJkpQJxjK//TRNIUS+H1iWPZ1OB4NBoVDI501RlDBOoyhKkoQQwgtC5qigqmqKsSAIM43adDqVRKPVbj95utVuzwIGn25tN6u1o+PT3mXHi2KMcaVSqVQql5eXSZIgxEMIBUHgOM4wTITodDpaW13Lm8bO/kEY+m4SMwEJHDB1GZL06sqKwB91B31vGoSufePqeqVcYgByAIAUIEjMnO65NoMgTlMYRaqucxxXUNXj49NMlywIAkLoy3sPqtWqaZoXvVPP8yGEkqRYjj0YDEbDUalYoJQ+evTQcZ3eYEAYgwjdf/SwPxoyStlXgiBJe3t7qqJQSi3L+s//+T8VCnkzb1QqlSROOAjbsy1GwPL6ynlH/uzLz7ZPD70gUA1NhTnXsiilkihSTJIkkUWR46hhGrZtEYo1TQlCf2Lbak63vQCJIiICR3ka44Kek2WpUMiLgoiTVJJV0yxwvPDFl18dHBzEGJv5vKHnAt+XRQkyoIgCxoFhtnRdq1YrhpG7N3h8enpcq1WjKEAIXV6czS8trqyuzLbnMSb//s/+Q+Amc63W48ebhLJGrSlLchRYw9FwaXn52rVr1UplaXm5VK6IgrSzs//ll3f3dvfHUwtK/Ftvvea51qOH90Mcqaq4t7crK9I777zNC0Kr1W7ONHI5LdNAn52dXVyeQo6LYo8Qg0NCtdpq1GeMYu63n33+dHMrpYwXJAoYThw9l3v3nXd9L7h79+GXXz4MCYdQAuQ0jqOxNTnv9L+8+zBK6fFFn//q8dW1xf39Q1GUICDtRpnE3vXF5uXJ4XB58dnW9qPHj197/U3EQQ6B87PTo6OD5eXFbzXaZrnIURRjTCkjSZQoEkcxTWkaJ5gTICbEd+wb1693Li4d1x6MB/lC4eaNm5Nhz8zpKbHPzi4Ms2AYpiiKEILhaLRxdePi4qJarSqyomtaLmdattOamVFVdToZvf3WW4F37cmTp5brPnn2rFyuvPXWW14Y2o47DYJKrQq4cZSkP//RTw6PTv7sP/3n45OTZr1KKYmTCHMczwskJWEcBm6gqlJe146PjhLPev32TTWX5wSZ03QrSo++eEAIiKJElqBlBb7vEZoCwBBClBBKaZZNDZ73rLl8Ph/HMc/zcRyHYfgyN/T3YPeHMAr+gI3wBwD6snp9vsznuMwaBnyjbv3mk7/Mr/6Dl/uDc/SNvi2EgP4el1++StYAOTs7C8PQNM0wDBVFiaJIkiTP83ieD4JIkuTJxOI4odGYcR1nOp1ijIvFIsbY8z2O5zNOgu/72RHgESBpoquKH4SjqdXr9ZKEHJ+cWI4DIXd0fAI5jhMlCQDbtj3Py8ynM6jleV6WZQCBKAjz66vVatWybD/wXc9PMIYcp2rSwmxDF8Vnm5sn52cXnYuimZclaW62XSwW7t57YJq5Srl4uL93cnyo6fpod7darQZROD8/73ve1LYzFTLP82ma3rt3jxfEVmvWMHJRFPtBmDNyXJIcHB3yPH96ejqdjOfa7VKplMubh8dHo8nEtm3H9zAHCSNnl5eLs/NxmoZ+kCQJxinHoTAKTWAsLS5sbW4WKlXbcfuDoZRT5JwytEfdSd/Mm6IoQQQUVREF0Xc9nuczsoqZzxGahmFQKBQ4jo+jmAFQKFYSMiyXK7abmmoexunKygrP87ZjS6JUqdcZgmenp3/+F7+YTqf5fL7RavmBLwo8kKWLs4tWa2ZpeV5V1ePjQ8MwMMblcnV9ff3u3a8sy1peWWy3Wz/9yU9UPYcJOzo5EQSZYtDr9hig80vzo+EwOwKQJQhS0zTffvvtJEnq9frOztFvP/p4MByenZ3ncgaCcOPq+srK4njYnY7blWKl3Z7pCtyPf/KDhYWF/f3DIAgEXoQQmYYJIGSU/bN/9s/8INzYuN7pDTqdPgXcJekcHrnPtp7FSQwzAzycihD/6Afvtltzn378ydHxqWEWJCR4tlUtlzGJHj59fNnrx2kQRsmoM43jyHKs7c2dSqH8sx99/2/+8jdXl+dvb9zJ18q+76aE/PhnP7u6vj61rCQllmW9cuumrijfarRlgEIIwiBwHE9VJQj5lAKO4wBkAs+liY8gQkw6Pz1FHAqj8LLXGQxHV1evSQgM+11JURqNBoPw5PRgZmYmDKOFhdlnm4/feOO1NMWbm5uO4zbqM5OJBZAAAGg2aoxQWZLrtZqk5+689vqvfvWr//gf/1OlUt24fn0aRZ3RSNb0wXD48NHXpVJ5dnF+7+jQi4JSsXTaG038YydKEoCCKMEpZqmgKnocuM929yVFuXnt1se//fS3976wgyAhLE1SQLHvRWGUYpxmodM8zxOSZjOH7Luq65rjuLZtE0Iy95bsyGS14UsW18vtG9Xu/4a/wUtBbaZq/+bDKaWZY2kmhKeUZu6OfzB2e7H9wRt48X4yAi9CSOB5zGgUx9mULws1abVaYRgWi8XBYFCtVjHGR0cncRSJojg3N0cpTRM8noyq1Wq9XrcsCwKYHRxZVrL/WpKk6xvrV9ZWDg6PvCDUtNy1G/Wt7c1Bvw853nG9mBJR4OvVynRiBWFACBEEIUsgzsY+hJC8qpmGWq9VT85OXT8IwhhxvChJEs/xjFTyeqs1s7m9I2l6Y2Z2OOxPbefrp5utVsuLk5PNHQgoAoznELIdSdUq1YrjuBeXl5RSDqIkSTzPy+fzCKGrV6/atlUw1MGwWy3lD3a3rPFg7PoIoWqlbhi5ne3NR/cf1GYat2/fJoxNp1PbdRVNTaMAUuY77v7e3kyjkaUZq6pWr1d934viqFDIV8pFy5paruv47p//8i+m9sQ0DcaYrukIwV6/XyyWNU13LDuKYwhBGIauy1rttqYak4klilLe0A1dzxcKsqhUm3O2HTfrrd7F2eHJUalU8n3/tddenVjuZ19+Mej1Pd8vV2uqqpimMeh3m7XatddfPzo4IBinKWYMvPbam5eX3f/1P//y+bmDYH5hXlGUSqVy+/adv/3bj46ODi3XoSmOw8DMl2xvLAliuWy2WjUOgLm5BQBYs9mM49gwjIcPH/3qVx9sbW3X67WVleXZ2fann32aN3WSJrVquVw0v/vu2wCgUrlw+/ZtRVH6veH7v/mwVqssryxubGw4jrO+fk1RlItO7+K8f+/Bw/5gKClqt9fp984RAoCkAhIrxUIYBNeu3zJ0/f/1r/4fCKKbt27VZ1r3Hj4s5oW3v3Prtddub+8duqFXKOrPdo8UBfX7564z5Hl+ag+TNEI8CuOkOdPkeVgoGP3R6DtvvSXL0kyjmjMKpVJla3vrs09/961GW/hCHKWqGk4Jx/EpQlGKAU0lgRN5CBhlJHUcSxCENE1yxjyE0LKmkedUK6VJt2sUKrqhLy/PMwAoTQ8Od0zTHAz6vW7/lVdfDfwQp0QQpHK1NhgO0zT54rPPbNsqlUpqofDVvXs3bt2cTq1ms/Hw8dfTMJhptTauXv3dBx8uLi4laeqHXorgUW/gEIAllRCcpJhAPiURI0xEfOCH9tTCNPnk7oODo8t+bzgNXCfwRU5GHGIAYxwLoiiIvCyLjNEg8FVVTuIoAxQAgOt6lNIgCF6WmS/nZuAbnYE/OGLZLy/Q9u8dnYEXaoiXqoFvunBl1W72BjDGmXs/+0Ovr7//aV+w0rKluh8EGa4JopjL5YIgmJmZ4Tiu3+/VajVFURzHKRaLOMUCz4WU3rhxg1L65MkTCGH2fbu8vGSMLSwsAAgwJYzR2dnZjBJ3+5XbxbwJISdcXI6n08MHDyikCSW2ZQVRxADiEbAs2/VcURQFUdBULQgCCLlsZSAIAmC0Vq1sbj5DvAAgJIwCCEVBLOiKgojIQ8ueJgz3B5M4ShAUeIkbTiw3iLScXq7VC3mTQ4jiFCKQ4mRq2+Px+MVSA/S63UqloiiK53mu5756+5ahKaV8rtPtthpVAGFtRuyOhrqmWdPxnVdfffTgAWNsc3vr8uICIqSoiiSKDBNCsJkzHNu2bKs105qbn6eEdDpdVZVzRnFzc2s87KcE4xSnabKzv6cooqZIELCCkfN8L69rcRy7nscAI4SIglCrVmu1gmU7hABG+SjAhVo5n8sVcvm8WRyNbVXNu7al6IpmaBzHLywvPNvafLa1azs+hCBfKAZhxAAUrWkUBpPxkOdRtVpJ08Q0CxcXHV13Hj58cn7eYQzZ9jhNE0rIj3/8Y8e1P/rw42dPdi4GnZSmgGDDUOfmZ0r18u72zs2b13RFffTwQb1eqdXqp6enX3zxhSzLnU43SaO1tRVFla9f29ja3lQUQVVlBFm9Vn333XdWV5bDKElwalmTL7/cPzg4NvP5/mC8sLhMCBJFbWdnbzQaX172oySZTMYMsjAe27bVbtTW1pb39/dqlUq1WoEQ/ujHP//t735749rGO+++OxoPfvfZp9V6SZfEIJj+5v2/2d4/k0XYauSXFhqCMNje2Qs99r333gYA7x0++s5rrxXzeV5DJIlc1ymVSxAinufsyfDZs+1XX3ttrt2Obt/+VqMtYxyjSFEUTVNdN5xak2KlQAiBACQpliWB4zhCKQ8Bw4QhOh1MRVHSFDVv5naOds1cXidm4Lv9QS+n5wzTWF9dPzk5yeV0XdOePv662ZhxvYAQfHq+ByHKG3koCylOOU4IXV9AMKermCYje1hpVotUSNNQk/hXb99gkHQ7F4hSI6dZUXLW7ycxIQwjnqcJNWTV4DlN5kxNllDJdm2O5/cOD6M0NXIl1w7DJMRxkqYYCbyiyEkc+6GP01TgeM/1AUSiJCZJqqoqgIjSmDH6gvL4e+7BN7uu3O8HUy8O3R+u6P+hDkC2ZTytNE1funBl8VkY48zhO3vmbOQFQEYiQ4wyyij6vQVNluOIOIQYgqIiY0YJY6IkZf6tWSek2WwOh91SKX98fOj7fhjElFLGSK1eHU9GhFBVUxBCS0tLlNLJZMLzfNa+pzi5vnFF1/UgCBYXFvb2j7e3d4ulUkrI8dkZpaRYLCZxmMSYgzwnCIwxx3NlVSmVSq7rxkmsGznKIIOAg0CR+HLBONjfo5BXRSXyXU1VeIGHAPMIra6sMiaUq43t46M4SQCAPEKqLEFAcqroWlNFVQFWK7Va1lI/OTvpXfYYYxhj27ZN0yyUigwCCtjG9Wunp6f3Hjz0HZvnBcM0qrWGYZphHBfyhuN7p6eHM7Otse8uX9148vhrRdVMUegPupQkosjFMQkCT5LFQjEviLzne99773v/8//8ZxsbN3Kq/njzcXcw0WROkgRV5sNE5gSB4wXPnlj2WFIUP4mjOBVFUdEUM2/wPC8IvOd7ju1zUJ1trciKVCjkIKOV+pxhFAfDL9M4FHQNp6xarQmCdLB/1OmM4yj1fY/nedu2eZ63LCuntEv5/PHR0YcAvvX2OwVFlST1+It7H3z8iSIrlWYVikAz5eHA3TvYf7q5vb298+jR45xhEBxXS0VVEmea9VZ7hlKw3F65snINQdLvdXlRRIJ474svHj154vleoVBcXlqqNxq+7zGOhkm4ur5y5+ZNANiV1athGIZhOBqNdve2j45PdvYPb966feuNVx48+PrTe3et0FleXJw41sSy3TjwA1811MB3ZZ4rtJt/+uOfJElEwujNN16XZHF9bS3w3GvL80uzjRgH9+59gRCNwkCX5YntjIdjmWNvv/n2wf5eyTCFFndjdXk4HL5yfR0yqqrqXLtJCXVcezQcCoJ4Y2N1aWme57iT08Mvv767tLq0ujhfUG99q9EWAAYAyRmqNOUBkilJCY6SGKuKJIsihxCHUJqmScKMnCkIAiW4WplxHZuQSNOUQjEfRlHiuKZhxnEcBqFPfQDA7s7OtWvXS6VSFEaqovi+XywVKKW6qmqqnjcLruPtH+43m400SXK53OXeruUGEMp5U9t88gwQIjB+49q1gT3dOz1L0pRSwPO8qek4TQCHdEVp1EqApr7ruY5/dnlRKJX6o1EYxUgUCaFxFHEQCqLIGPUCL7MpAAAwwBDiXgjBQBiGEEKe5wnBf3cV//tj9AdI+nI/++at/9DQLJvUY4wzC0T6PKCXQQiDIIiiCLzw8YIwIzX83WbCH1jcZk+StUEUVYnjpF6rZTENL5rRLIspkySp0WiEQQQAlGQha5W4rlsoFARBODk5mUwmmYMUxjhJ0kIxDwDI5Yw0TT/7/POnT7d13UwJHYxGhVJJUeRet5ekCc/zkOMykq/8YqzEGFMVhecFxAtpHDPGypVKEASYkEKpTBkVBZHnOcTDSqmwNDu3sDD/7Omzk8vL0dTCmImcyBjBmNbKJUUUAAOyouiqKolir9v1fZ9B0Kg3ojjSdT2OY0ppp9PJ0gnHo5HjOJ7r8Ag5tqXoWrXRCIIgieMoDPN50/eD/YMD1/NgJpyGkBJcyOfDMByNx5VKxTRNjHGn0+n3+2mafJCms+0moen5xRmlWNMlhmNZ1RSSinHEIcgxIvJoOuzPL63UymVCYeAHqqqKoiSKQhRF/c4AQqHWrKysLquqPBr3FdlIMLj/4OvT08vr169Mp9OFxRXGQKfT/eyzz6MohgjgNPF9T1WUYiHP83yjVq9WSpjS37z/wfu/+fDNt9569vSTp0+flkolRVV832/ONMqFBe01/f79R//23/67KIwVVYUc2Lh6pVYtL8zOmmYuSZLJxHr91TeajZnzi+PV1VVJFC1riiB8443XHccBADQbDYRQrVKt1WuzrbYgCKIoqKo6Go1Ho9EXX3zZ6VxESYgJu3Pn1cXl5V6ve3x87Po+QrhZr/iei3Faq1U7va6hayvL8+dnp2++/nq1UtnefGbouXw+b5g5CMDe7o4beKIs50z9Rz/4we7BwUWnWyqUXn/1NWs6XZibX15a/mtMDw8OmtXaq6++ahgGj8Dl5XnmQRencZIk48mk0WiUS8W93Z1GozG/uHDbc53APT47nak3vtVoCwEBFACGRQHJsq4rahAGg3BkjUe1SlnWVMoIz0NFkdM0wmkqSUKahCQJIxYDBEaAS1MY+IEkC+VyeTgczszMlEoly5qORqO52fnRaDKdWqPxWPSl0Xj8g+//SRgEYRi6nk1wOhgM3v7uezHFp2eXthPHKak3WrdvXL335ZfbO3tf3XsomyZhMI5TwPGaqqRxmIRe2SzC1GexIsnC06Oj0dhGPBd2uojjCQ3jMIRZqAEmlBBBFHnGJXHCKM3lcjxCgIE4TeI4znCW4zicJiAjV/0Dgy/4jdnUy0kX9+LWv4u28BtbVsbqug4h9H0/u1vGFnipp8ioBc9/f26FAzLLhecuuRC+7CNne2RZRgiJglgqlhhjnudl+tpsKOR5TqVSnZtbQIjb3NxMk7RQKOzu7vI8L4pio9GwbbvX6yGEsmzHcrmsqEqhWPSD8Isvv3RcFzBWrdaiKBkOBhQA13UGgz4EQJQkyHEAAl4QSuVyHCWe50EIZVnmBYFgjDEFgOlmznKdwHPMvEkZFgSeYgEhoMhSvVISZG5rb7sz6BPCKOAgwITGmqYJHEySpJg3MGXZZWlvb+/y8tI0DF4SdV2fTCZHR0erq6uKolxeXgIAPvvss9PTU47jIAQE40q1ki8Wu4M+AGBvb5dSJjuq4zpqTjdyOVmSJ+NxqVxUZMl13FxOV1Xlu9995+zsbDgcqqocx3GlUi4UC7IkfvXV55Rg33cMQ4WKKCoy89xiIccIzcmyXM4jCCRFK5hlRmHnshd4vqjzpVLVpvaEU7/znbfm5xd83+0POucXlzmj5NqnHCfX6o2ckU8I+fDD3zLKer1BmiZxnMRJZBi5YiEfheF4ONi4tvHDH/wgn89/de++5wW6jvd29zY3NyuVSrlcvri40HX99PTszq1/2ut1B4NRFEYYk0Kx0Ot2NFnieKTntKXlJVEQHj/dhBxKMZ5ptR4+6jDIBF68sr4KYEb9DMIgKuTzei6na7ooipVK5etHjy4vL3d2drKm0Pz8fGt+HgAgK8pvP/744vwy8HxZEsql4mg8WliYS2O6vbdnT8dXVpdeeeVWpVh85fbti5OzII7XN67anhsmIcdzC0uLg9FQzen5YsHxXIS4H/3gR0sLi0mSfHxy+ujRo4vTs1ajfuf2zYP9A9e2jJyWpkRRFIzx1atXz87OFEXJGUaSJueXF6VSKcHp2fn52eVFHMXlQsnas7/VaMsYgBDyHCfyQpISgRdKebNWrtjWBFDMc5BSRAFFiCEERUHASTTsdUQOpQIHEMfzShRRjhckScpM/oMgGI1G5XKJEDIYDvJmkecFy7Zc1wv8cDgc1iqVi7Oz1dXVZrt5fH7x6w8/gJwwHFuSZuKY7B2fUEjdMNHMohUkw6ntBjEvybKsIAZiQjVNV0ReFLkk9qMEYgpEWQmjkFCSEoIpQxzCaQoAgBByHAcBJJQJgnDzxo1GrX7v7t3peJL1SSGEhBCC8Ter1D8gALzYwyHEAAUAvIhHfa5BeIm8L0EzC6fJwBFCmCRJ5k9qWRZ8Ib3NmrmEEEVROI6LoojjOE3TsqEZgyQb6GeMgiRJX1TDLLuKFIvFl1O+SqUCAOB5fjgcZjXveDzWdd1xXIzZysrqcDjUdUVVy+fnlwsLC81m03GcQqFwdHRUKBTm5+ezEns8HgtIPDk973Q6cRRLslQul6MwwRgnaUoBSAkGAPAcJ0kSoRRyiOf5MAzCMM7+32xqp6oqhHwUhynGmGJeliCPEIcwxggyRRDymurZNgOk0+0zijiO5yjgJQ4w4vuOrqppiiqVGia9OI5t23YcJ8us5DjO931FUSCEl5eXhUKhUCgMh8NutwsAyOVyDLIgiARFGjtTQsh4NG42Z3Ca/ua3H+IUR1Fk2dYvfvEXs62WmTcIxiIvSKIwP9c+ONifTqdRFEVRbFlWEASObSEEAMSSBAETIWBhlJCJ5bh+kkTlQlGVpJl6jVEWxdT2Y8g4iRcbc3VKqWd7G+sbC4tr7XarP+i+//5vyuVy3izret6xk6WllXw+/+mnvzs4PBgORhBCWZZyhh4loa4psihcvbI+Gg6Ho5GuquPxpNmc+c3fvu84PqVdzw8bjcbGxsb5+fmNGzd83w+C4MMPPxoOBhCyJI1UVUmScH5+bmVlycjphYJZrpS6vf7nX33Z7fR/9tOfJWkAOZLESbvZkhXZ97zzi4v2zAyHeIS4SqWMMUEIPX3y5IMPPnAcZzwe/4t/8S84jpMUdWf/8MmTJzdv3Mhp+mQ8LJerumksLsyvLi/FYToaTDgEx+NhEkWGri8tzCdxFCZxuVqZW5gPo0BRFMLYxeWFJEnj8bjT6Qii+PYbbyKG8lrOwhYP0aef/q7ZaPz8Zz9t1GqT8ejo8IhR4vluFr43Go183y+VSv/6f/o3r7722huvv/7VV1/9j//m31BKc6XSKzdvffb5Z8PBtzu7AQIOUCRxssDJaRIjxgOa5BQRYhWnSRxFHGQCBxlJEOIQENIkoknM6woEyIvSOKWFYjNvFnI5OTv9GGNBEOv1uiiKCPKTyVjXc9VKtVitU8ZIGg9Ho6WlhZl24ze/+wSKAmBwMLHUfPHssmcFMaOxE3qVQvHgrGNbbs7MA8RncyTfD7ww5ABVOU5RZYj4vaPTbn/ACxLGOMWYQiBIsiTyjFKcYg4AnOI4iQVR0FVtPJkM+4MkTrJlOHiJrRACRjNPGfZCZPsSbbNCMsWYRxz8O/lgGXS+JO2+BNkMczHGGR0qY7O+pGsRQnie13W9Uql0Op2Mf8bzvGEYk8mk3V4slYvj0TgIA8/1wjB8LiSGEEKoqiohpFwuZ7LjLN3LNE3TNDudznA4HAwGAABRkHZ39izLUlX5nXfeOTo66PX4N9544+Li4nvf+9729raqqrquZxXueDzGaSoqihcGjDJZVXiOH47HDDOYRVAwxosipVTkeYJx1pRJkiRKYh7xgixldaggCIwxUeCiGMRJwsuCqMoUwTAKzVwuIcn8bLtRrTzd2pI1Q5TVBKcws/uFNFs2NWcaaRinCRYEodlsSpLU7XYnk4miKPQb7ZEnT54cHh76vn/t2rUwDDudTq1aPe9dBnE0HI+jMEQcEnihWq999P4H0+kU8txwODBM0x06C7NzoiyenR6/eucOYwSKqNvrDob97KNLMPV9v9s51zS5NVN3XauUL7huOJ44uXxREJRioSBw/GA8FQU5DuPByNHM8txcu1ytJilOknhlfX1ra6tWr3/++e8c156ZabZbS74f7+7uT6f+2VkfQtTrdwhOKAWyLJqmSQFemJ8lGDdqdUrSN998vXPZAQD84i9+8fTJs/39A16QTDMvK0qxWMxIzaqq7u7uFgvFy8tzx7EURTLzas5Q19bW6/Umz6F8Id+ebV2cn110u0EQBGH04NHD6zeubmxcgQTnNMUwTE2RB/1erVKWRAUAWKtWu91ufzAYdHuvv/4Gxqksy9euXXvy5Mm9B59ZXmxZrm07mqrOzswsLC4vriwVi2a9WqWY2RN7bWUZIBqFvu84+3u7pmlAThAlaTydJmmsG7kvv/ycg8w0DVmSCSEiAINOV+REU89dnp1XSuXvfve7b7z+miqJx4cHuiK/cutmpVIZjIbdXm9zc/P+/ftLS0sIoe98563+oP9//5f/stfv5/P5QrE4N78QB9HZ5GQ0Hn+r0RYwBAFPKBQFKU0BSTHkSX/QIzgVeJ5QLAg8AlwQhTzHS6KgKCKkDFBMACdLkut5eg73ej1KC6PRSNO0JEnjONrc3MznC7Ozc8PhkFLw8OEjzSzoOe3alSuWP3Zda3Nve+XGra+fPLvoDigSMLUDiiNGcJpejocxo45rR1HsRjFFwA3cVrNp6FpvMDB0TRLFfKGwtXcwmlozrVlraksSEGQxW8BHsV8sFhr1hms7jx99DQDgEHJd15pOGaWMMkrJN0tXxhgAmQ34c34GeOGQkN3nJTnhm2xZwMDLLFz6Dd888ALEMwDKm/nM7AYwABAAABDGREHI5XKqqhQKZoaetm3HcazrOgDgBz/4k6PDw8D1c5pmTaYcxxHCAACapuXzeQCAIAj5fD5JkjiOc7mcKIqj0ahcLm9sbBweHmYlsywpkiRRQs/PzxEHqpXq7Nxct9ebTKf//t//e0yI73mnp6e27fA8x/OCwHOiKCoQIgQza7TsAiMIQhwngihKspx1PyBEHM9RRiFEoiBAxGVVrShJFFAKGAEM41RRFYHn4yiEoqBpytUrq+V8Po2SMPAVRacMiZKSUkIp1jVlbq49Gg1nmy1REGM/ZIApijwcDlZWVmzbKhYL+Xzecpx+v8/z/Gg0whiLkqjncrbtjMdjjuNrjeZFv6dpeqfTs227WCzkcrlerw8QEgWRAJbTc7wkltS8qmn9fq/ZmBE4/uzy0o6ck+MT13GyGAtJFBilhpHTNSVJYkHkLds2jRLvhIAhwyi61kiWlTBKDw5P5+cW5hYqulkSBHh6ejwcDl+5cyclxHIdx7X8wLm6cSWnl5KYe/bsqRP6cYTThEZR1GzWr1+72u/2D48Obt++XamWJpPxw7t3KcY3bt8uFIqbTze3d3ZwgjvdvqwojEFeECRJTpKEMWaaZhSFjmO7jq3ryit33klxgnEsSWKjUUnSZG52cX5uXpQkTPD9+/c3nz0rFEqnpyev3Llea9Q0QUzCiOd40zDv3LkjS7IfJGEYbu/sPHj4cDwev/76a+3Zlm07i0tLnudzHD8cjTtDa2lhrtmsc4D95Cc/rtQazzY3RYEbDIfD/qjT6cwuzN+8ft2eTo+ODnvdjiQgo1SBHIIcRBQ9ePigUq2+89abpycnaZLwPE8JabVaJMYE4zRJdE0TpdbW5uZrd16RFVnXtGKpFEVRmqZPnz179uxpq9VWNfW//Pl/Oe92/CBYXFrM5/Nra2tmzshpuc1nmz/8/p80WzPfarTNproJCYPYpZCHPI8kwnGMJCBhLGIUCiJOKCfKkizwEuB5TDAhUE0xlmRFlQXPnkqy7Lp+GEYY02KhEAaR63qGYU4mkzTFCKGbN28dXZ71h10Eyc2bN4bTkSygx/efBVHCITEmOCRpwhjg4CTwqY9HtqOLkjUeFcyCbuSq1bYiCKaqKcvzC3NtRNNareKF4cTxeZFXc2oYBTiJarWqLMsXHZ+R2HWnzzY3AQdVRXWmVqZcIJRkbi/PUfalmoABAJ7byz6fVn1jWJV1VBljgEOQAUBoFpdLKYMQUsYQ5LIoGUxwhr9ZQ5bjeM/zMcYQIMQhxhjkOI5Duq7KsqSp0puv3+n2Rh//7hNCiGEYc3NzPM97lre7uatpujN1BCgSwCjEWcY4ACBrBfR6vVKpVKvVsq+fIAiZpCeO41qt5rou4oAfuJhISYKfPtmCaEdSlCyrJkkSjuM4xDFMFFmhlAq8oMhymqYAMI7jkyR5rkIWOMYDAQoQIcaAKMqYEMhxECIe8VkRTyFHGBQkOSUppRRTElGia2o9n1dkwfJsRRHXVxdFQI9PjkdjizCg6brIQ2fsIEBVRVYUjcVYpJAlabc3iOJopjkjy1KhmBclXpKFOI3u3b9HKCsWi77vS5LEGFtYXpZk5WT/qGAUTs/PP//qLmFUkTVVNSzLvbzsr66aR8cnxXz+O2+8cdnrEUoESQyjOAFsfnk1TaKT00M/sAfuNEgSiBDDqabrpUIhCEPEoTAILs/6kiRiQvyIxJGPIBj4bqVckXmxalYwxgvzizMzM7Zt2Y6zNN+SRRCF9vnZ6fnZ+WyrrmnK4ydPVK2IkD52vDCKEYSEprLE1SrFUsFkaWpNTJLi/mV/dnb2+vo1StJ2s/3p5199/tn9BJNrG6uyLFq2c3RyNppMRtOJmcvlNB0CyoiSz2nVanlt48q1jY3Dg317PEEAnBwc/+k//q/iNLFtixD84OHXk+F4aba1tLxkFvPVUj6NYi9IGKHT0EmTJGfkxiPLDdI4jn75V3/5j37+sx8tzlGKfWf6/2fuv5osy7L8TmzLo8+5WroW4aFVRkTKSlGZWdXdVdUKje4edGM4Q9iAGCgz2nyCMT7TjDS+kIMBMBygOQNp1aK6qqtRKnVmRGSGFq711fJosQUfbmY2CH6B9IcwDzeL6+7Xbqy791r/9fulSdDpdp5t7nR7I6QYtbrOeWoZ6urqkh+GiqFzgI5Pu4yDk5NjLOXOzlapWDq3sTEc9BZfeklTlMpCQ7eMra3tvb3dOI5fuH6NQrwyvzQaj588fAIhxDfoNPY6g/7SynK9Vj88PFQw8f0wny9omtbp9CbjSXfYgwS9/Nqr9Vp94rr90XDtzPq333nnJz/9q5JpLs/N5y1nMplcuXD+0qULWZp9o6stkAIiyVgaJZGUhCI1DBNF1QxDD8OQUggkTtMYIii5AJJQSrOUpzKDEGdZYlu5JGFJHJQrJctq7u/t5XLWyuqS5/mj0Wg6meZyeded5nL55fn5hw/7pqoFnj8cjPwwLNplwZgrJYAwzUSUcdcP4jCiGJVLhaJhlqhWbzZUXdva3izMzQEW50xjOhzXy0UisWMYlbwjIDq7ujGZTqaTiaLgyag/GvSPj8IsZRAgRKjvulmSfgnzFl9O9uF/kaL9Cs799RdnB96/eZL+/3dnAQDg/4cLnmUZ+IoU/p+7xGdfmXVaEUaarl+6eOnk5Oj119/odnvvvf+h5/mLi4uFQqFSqcRRvPl8czgccS6+fsyZSaxWq81Ol3Ecr6ysuK5LKR0MBkmSzM/Pb21t9fv9fD5fq9XK5XKv15sdmWf4KEywH4RCSjDzuSKIIKIaFUKYX0EXmeCFavnr07qUctYItnO5OE4AQBhhiDDCaPZLIYQopYqmAwjTLIZSYgQMVTFU9dz6mXe//WYY+B988tGrr73cbZ0+efoMUwUToquqYRkQwHIh7/suAiAKw71Br+Dk+r0+IQQBiCDs9oeKqnb6Qz+IGWNWrkAQNAwjjuMkSYIgiMKwVCp/67VX79y+PT/XTCXv9HoKJRjjnG0TjCulUuhNFxYWDMvqDgYUK0IKzTI6g/7m9o5l6lHouu50MvGiIMaAV0qFRrWEINzZ2zMtU1FUzTDiOGZM2IiYhhVFsarqlKqOU6hXa+tn1jrd9mmn02m3KsV8loTlYi6KkyTym7VquVJ1Aw+AUNet7e3jTqcHAKrXa24UEEWxTOPRwwcqpYwlx0cHpVJpYaGpK6TZaOzs7v3s5z8Po0gC4Jjmu+++8/DJ0+29AwwloTQIgigIDF195eWXCo7p+56parVSOfXDkpUr5vJ2zmkuLNz74l5nOEnSZPv59vraypuvv1aqVAlVO72+5yVbz54DCcbjMeecEIwRWT97bur5p+12yjlVtXa75XtBp9vtjoOPP7tzfNJ2CkXHskwVd9ttztJCuVKumkJwdzrJO5ZKCCXk9OR0eWmpUi4vL8wDyQXnVtHxw3AyGuZsu16tjQYDR9dty97c3AyCYHl5+ZNPPjk6OlpcXGw2m1LKer3eaDQAADPSdJqmcRzP1RvlYtF1vSSJEz/8u3/4d6Zp9Gc/+ounz5/deuEGJKRaq4VhuLa2tr+/bxrfeFOOlAJCgDEUAmVZBhFKY440aluFKI5c13VsO0sTwRlGlCWSZTIVGZQZAgnLEtOwFKoE/rharTo5g/Ok2zmZuv7GxjmEsOf5pmkeHh4sryyuLS+triw/29w0C4WllTVL1fePjkdRGE5CP0iGrpskMUGoUazU84WCalx++ZWnO8/bp8e2rq4vL8aeF0SJ5NLUrdANC5Z9+dw6l2JhfmFzayv1J950lEVRqVAoFcuDwSAMY8GF4FxRlFm9m2WwCMZxEM6On1+OvNDfTMbgV8Df/+I5+pvh2H9Wbb/eNEMIIYS/tjXCrxbGZn8VQpqm8XVeqtvrLi+tbG/vdFpty7TOnj2HEJqdWCGAvUG/VCkDCEejkWlbQgqAUKFQAABEUZRlma7rg8FgRkLI5XLHx8d7e3u+72ua1mw2Z8tpAIBZTOrrt5A0y2YLEYwxQzOABJLxarU6u6zNHioMw69/OYRQkqS2bVuWzZhEkAAAIAKzQoy/+gjDgHMOkaQUa5o216i/ePXy/Nzc/sHuzs5OuVo6abUOD4/OX7oUhGEQhJgQgrGiUKgpBMg0jgiCTr4gsuzcxoZhGN1u17LtVCAuxWQyERL6YQwBWF6YmyFfOeeqogSBX8znVEznG/XheOzHIcK16WQ69j3Htubnm9PJWMFI0/XhcFitVtrdDpeCA7y1uQUlDDzXtlRCIIVqszpnm1SIOIy8LMsMy46SOEkzz/ellI6VU1WDsTCfKyVJOhl7L7/0umFYCQMnre6jR/frjbqpKyJLAJK6phKMcrXS2A0KhbIf8PsPnjUbi2fPXtrfP4jCoJDLTcaje198znn2rW+99u133gyCIAiCx08enlk/d9rt/X/+7b/1Av/6C1cn0+nKyvLi/OLHn90GECBMVtfXKrbD0uT8+XNz9arve1IIXVUQ5xc3zlJKAUDHx0fbm1u2ZSVRXCoUr165cvbsar5gYYxGo3EcpZvbe5/evj3zlRCMDdNst9thluVzuYXFpc3NbUKU+w/uVRv1WrW5ub1z2u65nichnAwHf+u3vn/p7Pr2zla31en1hlvPn126fDH0/XNnzy7MNzkXmqoKzhECqqb5gR+G4e72zoVz513PI4R4rutOXd/za7VaLpcrlUpSyqWlpXw+Tymd5Q0IIY8ePYIQziYTuVxeU6lCiDue6Ir6nbffnnrev/nXPzzptRVN+/jjjyv54tLcfKFQoISurq72er1vdrWFAAABEEAIcM4URdd0w/fDMAhNy8w5OVVRsizCigIBhWLGfSVCciBEmsZpHFDMdJyLY+/0NHRddzIS9UZdNxTPdxHEQgiMUaNR6/baWZYNR8MXX3nl48+/OH38uOA4iCilWrXl+WEUSMEpgBiiKAjUaj30fZ6xyXgiuDx77myv00WCj70AYyWM00o+p+pU8cj6ynIUxduAz881+4NxQ1EFRu1uL45ilnKoYIxxvV6fTqdpms6Ytlma8iz7OkolpZRASiFnG7RfPy9Siq9nU+BrOY0EUMhZWYX/mUDhq0f7mwYF57zZbCRJPJ1OFUW9du3q0dFRnMXFXFFRKKF0OJmYpqPqXErZbDY3Nzd93xdCQILTNHUc5+rS4nA47HQ6BcfpdDqc81kCrFwuT6dTy7Lu3btXLBYBAP1+P5fL1et1znmv15u5dYMgmGVyKaVCyka9bjtOFEVhGHLODUPP4jQIAs/zZofxOIk5/JsYnKqqEGGMFc8LMKIQIoSQRBIAASHSNG32XBGMNJUynmma+uKtmxtn1rLQ//jOp8+3d1SqxIwLKVVDn/rBZDyUQmCMBeMEIiGEY1tWzqlVKxpRSsXC7KleWly8d+9+KmCSpqqqSohiPzBNYwbtTdNU1/VmsxlFUa/bPb9+RlPVwPdG0wlWSKVSUlX1+Pj4wvlzcZLILJu9v2KMp5PpcDJmGGZpqit6znY0DZuGujS3OhoN+v1WEE4cR+8PRoTaIEk13SBUtSwr8MLDg+Nqrd5sLiwsLDHGW62BHxxNJkOIeK5Y9AJvd9+rVUoTb5Iypqo2xLRUKzx+/BwI/K3Xvu3YOdedFvO5sRSObTqWPj/X9H3v0qVL9XqDEvLo8eO//ulf7x+cbm5tMy5WVldvvXjTm0wM2zpqnRyfnFiGmWZZ4Holw7h08fyFc2dVVUWgjiDI22YQxlRRVE3f3NoZDMcIoyDwDcNozC0sLq9YhkIw2tnZn3qhEOhg//D0tOX5/tLSYqPR0A2jXKn87Oc/Qwi98cabqm7+4pfvHx0faXt758+ee/DgwfHBnhBCwShXyMWhXywULl+88sv3Pmj1Dsul4vL8wvxcEyNAKdYopYR2xwOMc8VKvt3vREG0srwkhUzCaOB783PziqqqijI/P08pndkocrlcp9PxPG+WRxRCLCwsVCqV8XgcRVEYBpqWzxcKCGPbsn753q92d/dYlhKITNP6u7//h7euXtcQcZaWP/3k0/fef28ymXyzqy2QEAKEAMaIcUkIEpJzwRGGmCBMkGka45HPGTN1g2ccQMSYTBgnSFKFaBQCmaapL7IUAACk4Dw7PTlAxOh1B4qi1mqNdqc1GAzr89VbL7149+49bNkMocNebxQnfhBNPD9I0jgLBBcqUjjnXPC55cWdR48/unP75ksvfXb3zmm7X7BshDCHUcr5UbsjhVA1YDlqnIQnJ6cIYcZBfzgu12qdzunB/qHvBwAgjIlCqeu6QvA0TbMsmxEUIUT4q3OopmmUEE3VWJZ5vj8LEiCIhPwv5QgAAChn6rG/2RybnfW+bBcAOcOySClv3LhRrVaeP386Ho+KxXwu58zNNbCCJQCBF3Y7HYWorjctVIqc8zt37gRBQAhJ03TqufVa3fU9iGAUx2mWzZaLZitntVqNUjo7h0ZRtLu3W6/Vr127NhmPDw8Pfd9fXl5utVqc81qtFkXRLOqbJEmxWPR8fzQaqYqqqmqSpBQhPwhmMlchBBRIIEAp1XVdVdU4joWEAECEMJAIQigEIARjQjAmhmF4nocxhgiUy8VCIQ+kTJL49p077U6LQUQ0XdWsyM8KpULI4navJ1iGgABSSMbzVi5NEk+ws+trywsLw/5A1/Rer7eysgIheunFF30/GI5GzWaDMfZMpVPXhRBGUTQj3yuK0u11m43awcH+aDhYWVo8Z50fjIe9Xh8I/vKLtxCQu1ubL1y97k6nm5ubkKBz58598eAeVtR6pWGoBpDMNJW8Yx7sHvT7PU1Xls5faHdaUcQ0yOfmF2cZjzhJFFVfWS5pmmGZzurK+v7+Qafbe769w1hcrRWLpZyiIMik7tgZQiCKqWJO/Kh/0ueSLM6vtFvDXz17DyHgOLZh6OVSqXJm7fq1qyen7UK+3Gn3dV1//70PGQNPN7eWV9dFlpSL+V63E0XByB8/2nx+dHqsEHVxbvHa9WuBP7ZNkzFWKuTLpeLx8aEXugCS7rh/ctp98nRzdW3t7meftdqtixcvdkejw4Ojd996o5TLfX733sTzzp+/MHGHSRQoGKoE8zR5/ODB4uIigKDb6x0dH6cpa7U6cRTmpXX/3l0Fk4tn15MoTBl//bVXz6yv2qbpTj3PDQiiS8vziwvzjm2plCAIep0ey7JSpYgoer71/PjkGDBQr9aGk2HOcc6sr88O1JhgSujsxZPL5UzL4pwPh8OVlZWjo6ONjY1KpZIkyaNHj3K5nKIouqVv7+8eHR0HYWAaRrXZIFMNAnj+wvnvvv2OgahMs+5gcHB4UC6Xq9VvuCkHwNk2pBACQSykhJypFAkpA9+DCFBCMMaCCy6EkHImJOAs45Kplk4UnKYRlghCqSgqIURyzjhHgJuWkWZ8OOhAWD+zcWYSuY93tgrN+rOD/aHrBVl2tLtPME2zNE0zKDjkPEpSQ9dVjLvtU4Fkt9+fhIHEKIrjixtn792+DVW6sLgcTf2p6y7karu7e95oGoaJlHB7dxdgiqgOAIIIOY6jKprvh4QQP4zSNJVSqKqWpgme2cDxTAiEarVaznF8z2+32xBCy7IQQr7vIwAllOCrSdrXJ1mAkJBSii/Z4AhBzgXC2LKtOA4VRc2yrFQqNRqN09PjNE1u3bpZKpVKpWKxWBAAnLZamgaOj08DLygVS/1+r9VqKYqysLBweHh49uxZ2ut1e11KSBzHk/FY140szTAmM2lNmqSEkDAI0zQlhFYdZ2F+wXW951tbnHPLsgCEhNKMsTCKsiylVGVCJGm6s7MDAKSUcMFZzFmWYc3AhGAhZqQFQqlpaLNNYqqolpOfcRqlBAgSCKEQkgsmGRRCBkEwC6KVysV+v3960uaCGWNdQCkxtmwHQqQqhgapFwRSRYJxBABAECNMFBxEoW2a881GmqSPHj7yfd/3A8syGWcQAC6Y504UAhEQhq6uLC8ghPaPT4GUQkpKiBRiZWm5XCyOBsP1M2eoqoymk8iPAJeYUoLpw0ePbSe/ub0Vx3HK0utXb+wfHFRKFVVRTMM6c2bj8OCAsXgyHEep5xRMiPF4Mj096VRKtWq9Pp26O1ubYRhtbGy89OIr3c6AUI1z8OHHn52cnPRHkyTLCAaD4SiXz/l+wjNRrDZFmGVStk/7rhenmcjnits7u1kcQSRMU9cVcv7sGdsyTU378V/+uNXprZ05d3p6EgZBp9O5eePG2PMODw4oRrdu3iiXCixN/8Wf/EmcJkLInOPcvH7t+rWrEqaB7xEEOGO9btfQjak3JSrywuC00+r3e48fPzxtnXApiaYcnByenp4U8rm1pZV2b8g4H0/dhblmwbbiONZ07d69L7rd7r3PPxYQ1hpzvW631x/pmpnLFSwNKwqtlasLcw2Ccbc/eP21V3mWPnry9C9+9CNNs379e782N1dDCHKWGTk7CoMkicrlSr1RRwR9due2buj5XI4xtrq6OgvbpGmKIGqftj3fW11d1TUt5zgE4flms1opjyfT4Wiom8a9+/eHg8HC/ILrTuMk+eLe/eebz8vlUqVSzeVztWrt6Ojw2tWryysrm4+e5AxLZGzv+LBaqVx9910I4Te92iJEIMCUKBBhmQECASY4jBNCFEM3M8YAJpmIWRxZtp2mKSRAoQhCiinJhOSAYIB4mnKEMKEIYcG4piDAwzROIVZOT4+YFP0ozMdZuUZPRqPeYBTHWRSkcexCKVWFEghZxrhkWcDqjVrFMqjM3Gh60m+lWVy0rCT0zm2sum6Yul6zVs07DsEYCi0MU4BwqZynB8fDwXjqBaE/ZWn2wgs3WMoOD4/G46lhmFICIRgAACGkaRpFmBCSLxQoIZPJZDaFJwqtF/JZlk0mE4QIISTLEiGFlFxKMZOQCQCEFBBCgCESX55vK/UqpQpGsNGsBb4npPzWa6/Gcazr2sbGWQjBjHoDAIgz3ukMZq5JAIAYD4AQmqYtLS1tb29zzg8PD03TBEIqVIESUEIF5xnLOBe6pqsKzjIW+KHjOOPxGAmZJtmTJ0+TLIUYY4QMy8KU5goFVddVVdU0bTqdZlmWca5RFROSccYFT7JMoRRiRChRNVUIoVNDSM6zjHNOqJJxoGAFCCFEpmgqBIgSJU0zBVEA5MysPDc3d3p6WiiWs5iPh1OBQCKlXbRVjCHjAIhY+IxSjAlPGIYQE8w4F1BCihlPFV3HVO12T3VFdXIFiSHE0DB1KZiQWa6QS5NUSDnD90ymU0rwfLMxHo8PDg6q1cq1q9dytgm4AAjsHx6GccK5LBbLfuDrhtnqdIuMmTopFHP1Rp2lWb/bb9aaMGOuN+mdnly/euX2ndt+GGdkpuvksReHQYKy6c3rN26ftFYWlhzbtm17PBykPI0SPhj5p63OSfvUMIhtK7puLcwtjoejXm8gERh7acYE55JzQqkNJBv0Bs1aaX5u9WBva67RqOTLN2/eTNLks08+PTo8PGl1nm3vFvK58Wioa+re7vNcodyslBVFScI41tNf/OIXKtVsy1EJ6bVOuYghypDMpuNeloQqpWEY5/P5bnscsCSIo/F40mudJoGLslC3CwolCMNmo6pbam8yOh2MdM3IFyqXz11Ms3Bz69n+/s7lyxuLixVd01qdsWE5CJFBf8BZsry44U27i825c+fPryyvWLZ1cLC/t705Go+3trYuXLpw8+ZNxzbzOXM0GlmWBYDgggMMEUVxHJ+enDarjUq1igDUFLVcLM3mrgomGWODfr9QKAjGe8ORShXHNI4PDzIpuBTT0Pvf/92/uXH9xtrKqqaqUohWv1vI5b//3d+wLGtubj6Oo/39/SAIjo6OPnr/w9/83ve5Zqi6VimXDcPI5/IIoW94tQWzwU8YRQhpCtZVDQOABIBcAsYYhkgKMbtfM8ZmQxhCiJAcApTNGApICAYEgESRumEKAMIs5YKHcQyRomnmyB14Ek27nacHh5DQgeemKZOp5JwrhEKAGeMQQEvTF2oNx7bdqRsGPo/SyPX86cQixPddXVFrzaqEiLHs8dbTer2+uL56uL9PCVmsz108H3d+8YtatRarxNGNRrV6+/PPiabkSvnp1FNVBQCFc65qOkWokHO+RItOJnEcqYrq+b7jODOSAAAAIsg5hxBRjCEijDH2Zdr0S74tglDXVMdxZhlYKWWjXvd9F2Ny7dq1VrslJZhM3TAK5ubmWRT7QciFODw87g+Gs3XhQqFgWZY3mfS63fF4jDGefeswDGfkmtFo5DhOmqSqqmKMXddN01RVVdM0+/0+59wwDNu2j4+PozgyTHO2Cry7uztLCxSLxRlKfDga5vP56XAsAUAIYlWhqpqlWZKlEEJKMAYkY1mWZbZjF3I5zwuoqhAEAYGlUn06dSFA5VJp6rqzIVW1WlVVtdPpJEly7949DODiQvPMuY2hO5kGU5GmHHBVURDCGEAEAEJYCJFlDEoBERAMKIS6njsaDA1FQxjXC/lcziEI7u/vF/KO49iTiVutVg3DSJJkOBymaba8uloqFjvdrmNZqqZBKBVFyedz7W4vjmPDMI9PT+MsllxM3EkxZ79w6ZJlqkfHx0kYTYZjjSg6VamuM55t7+yMp9N6s3HvyaOISEQwENIi+m//9u8e7e59evdzVdVvvPgyxvjx48ednV3DsD0v8fw0TlLb1BuNgmMbz55vp0lULFZSniaxSNiUZVmSMMfJ6bpu5TQkwmqltL62rinq9StXnz16+J/++mcSgls3b7751rf/+f/y/97aO8jn84161TS0Rw8e7O4f3rhx65VXXt7cfP706eMoCjEU883KrZs3P7/z2Y2bVw1L9ydxuVwrl6sKVR2nsLm1fdTpElUJovCTz+4sNOb+/v/p729vPv3Tv/xxr9976aUXF5p1gvFf/eRn29t7y0urWZoUCvbJ6fjSpUuvv/4t09AVFQ+Go7v3Nvf29judtmnqc3ONl1++XinmwyCklKoKdafTRr0+HPT393fPbZx5+ZWXdU2HUHydJszlcpxz0zS/+OKLWQdGUZRyubx2ZmNna8swjCAI4jjWNA1CuLy8XCwWoyhqNBoZYw+fPQnTZHNnK8my49ZpGiXtVtta0S3T1A095+QgALNVKUIw5/z09LSQL9RrtZWl5XMbZ2fLjQICRVEHg/5wNPpmV1sIJJAsY1maIowJVCHACCNKKQFfRpcMQw8CHwAww79yzhVFoxRLwQkWRDdFxrACBZRCiiTLkiwVBCYslQTFcUR0hQM29cMUIKpqjAmJpUQCIqCqlGIKJQQSYURyds6wzGqzXnCcYa8rgCwWCzjLrl2+yJKEpamikmngt9sdiMnO0aGfpZpd9Kbu5w8fryzO//7f+p3Ac9unncFo7LvTJI6orkMMavXKdDINwxghjBElGL7+2itnzpz55JNP9na3kzieSJAxPjvhCiHwDLnCJVUUVVV0Qw0CX3Axm/IDAEzTtG27Xq25riulzOfzGOP9g4NqpYwp/fSzz5pzc5ZpjcYTjJHn+X7gDwbDKIrCMNJ1w7bt2RSLUur7fqFQyLJs1lOWUk6n0y/daFL6vq+q2tcMXEVRNE0bDodfxraSpNvtpmkKMZohdOM4Ngwjl8v1+/04jiGEo9GIEjobrzHGAAJEU5yc49jO8eGRZX/ZNpFSYko0wzRNW1X1KIosQ11cWu/3u5ZhxFE8HHSTJI3CWDMM0zRbrZbv+wBCRdV0layvLb1064UPPv1k0OsRigjCEEAgpIQzhhmGAEghFUqA4JwxgpViqXR8dKTresyywWgYR+HC/Fy5VoVAzvaYpZSziZ9pmufOLRiGgTEu5nPlYsE0LUwQIfjktDXLwE1dL8nSOI2XF5cUQtIocgzj7t3bAEJN03VNcyxrPBrFaZzLOYtLS8VKudfvCQEwzeuGXszbi7XamcXFQXc02d5/+eUrmGg7Ozvt9iBlPM2mnhdHQUopnatVNBX0uqeTcc80zPUz6xDT/sAdDScsy1iaMkUBBBWqhZWF8ysrq5aVPz48/fyLB62Tw92dnbn5+U6/f3h8cnh03Jyr6ap244VrnLMXb9747M7nn9+912w2dV3f399z3Wmx5Lz60gurqyvlguU4VhhFuuXUbEfVDJ7xLOPt3nA4dU9OT3q93mTinTubm1taabfbVDGKxfLbb3372eP7n39xb3vrOUaKppLz584Yunbr5o0oiSeTSa8/hBAEQTieeLt7BxCJW7euLy/PlYpWo1a1TOvBgwc7W5vXr79ACOJZ8q1XX6WUHB8ecs7PnFmLI+Y4TrVadV03CIL5+XlVVe/cuWPb9tLS0sLCAkZoYXFRSpkkydOnT9vt9mx3fGYUDoLAD4OD0+MgiqI0PWm3rLxz7vzc2txyo1pP4hgjzDgr5AszlOjdu3eXl5dffPHF+cV5XdcwREmSTALf9by797548OBBv99fXf2GuxtmQgAECSG6YVKkIjzbyweYYAhhxjNVURzHCYIgSZJZiijLGMsYglIKRhDGhMxw2FxK350gTABEUZpihBSKoOSApwrihqlLCDMBsal4Iss4m+0FAIF0XcmyLM6SUeDp4+FgPKwViznHuXT27KCQL+acOI6H/V4c+ZKn1Uop5XLqnm7t7jJBojCSPN0/OpirV26+cP3ihYt3734x9tyl+XkviofjUZpGCAGEIGcyE7xYKbA0/eF//A9RFJeLxdFoFKUpwkQIwRj7qtIJIYSKlUaj4flTljGVKtQghBDGmGVa8wvzQRDMVsim02kURePx+PLlK+Px+Oj4VEhUq1XjJMUY7x8cQQinU5dSpVqtOY7T6/U8zyOEzI63nU5H1/UZJ2ymszYM42s4GaUkTTIhhKqqURTN2srj8Xim85n9wAjj2QoZQogQoqpqqVTqdrtgFi34Ku0rgaSKYpmmqqij8ZioSsY5SxIJQbFciuKECTiZurVqxTB0xzJD3wVSEIyKxcJgMAwD38kVFVU9PT0NgsCyLEKphDhv65Pp4Mc/+jPXj6AEFGOVKhIAgjFCCCIkpEQSIISQhAIASilj2f7BAYJQQoAVoqgqISSOY0JKM+pksVAMw3B3d9eyrPX19ZzjJGlMMLFtE2Osa3oYhVGYjkcj3/f29g6KpRLBqFGvNRq1fqf34ksvjqYjM2cRqoyG47HrTiceobTRbAAA2r1OKnkUR41mszX0iUQUKtOpf//B03sPno6nwfbuUb251OoMOaQACcvUdc3pi34Y+Eg6GlUW5+chJBcuvnB80p64AecCYqgiEvkTAoyz68vXr52XACwtr25t77q+603d+w8evfnmG2fPnXv06NHHH31UrlbOnTu7vbUpgXjrzTeOjw57vU4Q+vv7u/V6PYmjtdWV3/rBdy+dP+d5gaEbEJPt3f297f0333jr9LQ1Hk+nE/f49MSN/M1nz+MwtBwnDP333n//+bPnK2tn3njzjZPD49D1BMvefffb9x482dne7LZP1hdvjcbDw+OT7e3tQqE0Hk0AQmEcaqZ+84Ur1y5fmGtUBr3uaDBYmJtTFPLer355/vw5x7FGw/61q9d0Qw8Dv9ftcc7nF+Y1Vev3+3t7e2fOnCkUCrZtm6b5JQ+zUDg5Op6RqjDGy8vLs4uRpmme5wVB4Lqu53vTqTv13I3z5w5Pj1utVs60nfOObdv5XK4/HOBhn2XZ7Bp3+fLlarUaBIFkrNtqdzqd01ar1qjrlnlyfHLv8y/y+TyB3+xOggRgZuubVUxMcRj4EGEuQcaFpaqUUIwhIURT1dkRDEAoAcEYSsGEgAJIIQTjjAsZBz7ChFDJhMQQQi4cJ6dSomGYNygDGaFalGZAZBrmDCWqZhiapmBNU/ROu59BGfJskoZZGE3dyZWNc0SC44ODNAzPnFnTCO72WqWc1e2PpQBLi4tuEHXGUzNvKwQTQg667dbPf/n9N16v1Mspy0rFAhyOI0qtUl6hWqvVi8KUZYJgUsg7pqGPxyPLslaWFk+7fUTocDgUX8l3WcYRRIZhjMdjLjKqKNVSBWEEJLhy5UoQhlmWuq5bLpc9z/M8z/d907IHo/HJ8fFoPEnSbGl5+fzFi0+ePgEYmZal6NrUdTHBjDHf92fH56OjI4qQ4zjT6RQAMKuVhmFACBVFQQilaRqF0ezdb5apmJ2+EUKztsPsOCykBEJkjGmqChHq9/uzQBuC0LIsVVVd183n81EcKao6mUzYaAQRUjVVMpmkiWmYKcssJwexAgQPw4AgGEiBCLhw8Xy33dvZ2VWIsr62Opx4aZrOPDr5XI5QZeKHWZYq1El5dn7jrGbY9x99wTCbyXKEEFIIShUgBU8TACFFJE3iYjHvR6Hv+XGWUl2Nk7joOK47jZNyqZAHAERh4vtBpVyxbJtSxfN9SiBRFUUxCSYQQSGU9rh3enparTc0XdN10/WmjdLSpx98aDqWF3qKqhBddV1v+2AvTbO5uYV6vbHYaPqB2x32P//ic90wvvOd73z8we3RdIzzzsFem0KUCVhvLswtLN97+CSI0jBMA3+CICjmS3NzzbuffXrp3FpzrjZxvY318+12/8nzvSSTjMVnz67HvlctWvVSqVbOpVHCGG+dnPzZn/8wY1zTjOWVle//5m/dvXPn7uefL62sZiyxbYsQVKlUwjj42c/+ulQsfOv113zfOz4+XFld/oM/+IP1xeaTJ4/8MF5dPwslLRVq973HX9x/aNu5Z8+3Hj9+KqVYObPQqJQgLzDBnz560O10CFYXl1d+8YtfWhpZma/90R/9YbvXH0/ceq0ax2EU+r1ed39/7/nzzUKhPOgPESbjJKQq6fU7Jye5fqv12qsvAwkAkJcuXpxOJtPJGEFRKhZt2wQALC0u5HO2ZZpZxlRFapr2xhtvAABm17V8Pr+xsdFut+/fv99td77zne/MOgkY40ajMRNtjEajdrtdKBQIIXnLtgwjjeNbN27+m3//b+uFim3buq6zLHOc3MbGRhonpVJpBr2KokjTtDSKnjx6/PDJY6Iq/+Y//vtyqYQl/D//k3+6vLysKuo3utoCACAEnPMsTXw3UorE1IyUZUJkEKMgDTXVJAKrqkmoEidJ4HoYAFXHmq4GQZZkKUdIAkEUUsjnx+NJEsWAMUwQJAggKCSPokwltKArAEKMSQLJMMt0Szd0wiTM580kYrpOFQrLjXoYx2kUCS4SgICiPN/eXlhe7ne7O7u7aytLhm6omFzYONsdjAFVjk4exKEPkDkY+4wLSpU0S378/ntnllfOXrrQO20t1qtCnImEbJ+2E9PkppNBhKB8srkVhdFL16+//vqrx8eHP/nrn43cgHNBFI2LGGMIhMxENp2MdU1dWJjPOQ5COE2Scrl8fHw8Ho8LxYJhfPk2DiEsFou9fv/J08eWZRm6bhumN/XWVpdPDg5106CERkk86PeZqgV+IKWcXe0JIWmWsSBAGEOEIAQAwjiOvkJ8SUIQxlQKMOOEfVVkJaH0S4GnFABCAKSmqrNzKgASI6zoqpPP5fN5VVGDMPCDwHVdCGEShBIAiAhBhKWyUikjBMMwtAxbANhs1CN/qiCJJW/USq+/+aYXRjvPt6rlsmXnCFX9OA0nU0VVFEVLMsYEpAgDyWc0HscwAEaars/eA2YgHoxgpeC47jRI2czdUKuVoASVfEnEwjFzk9EEZ3yh1mwurhBIBJeKQl2vx3mWL+TK5bKqqphglSDJBaU0zVicpgCibrdtGEa73VqYa3RarVLB2T/cMyytWMwrmtHu9neOjlPOSpVyr92euBPPdWN3+tY775RrzXOXLv/qvZ8/evwgZ6k5u0EITsLo2q1X4pgBDDBR2p1ev99v1BumaR4dHlbLddOwXv3Wt8rlHMRqb3B6fNqZelGaCS4gkGnojlRE3njj9Vq1Evj+xx/cHo5HjcXmk8dPzp89+zvf/4363KIQ8KOPP80XiucvnNvafDYdTX77N3+3Vqnc/ezzN994G1GasuzZ02cba2uXLlzUVC1NMiff+PTOzzWzPHUPAESNuXnLsQf9vjud+NNprV45d2ZNu3DhzOqZ45PT//infyYYP3tx4+joqFop53PO3NxCuViBkPzau+/MN+fr1UqaRK1Odzz1btx6qd1qR8lJEPqdQVcCQMSZ9aXFS9euGaZNEB6PpvlC/lvfeqPT6URRuri4YJiG7/kIoY2NjSCMfNcVnBcKhfFkIqWcTiYPHjw4d+4cpdR13ePj47WVVdu2x+PxLJ1tWRYXPIwiJ5/bO9hfq5bpZMrShEMpEPzwg08uXLj4zjtv64qGEJpOpxljhJL51dUoDDudzmg0klKapul7Xnc0tIvF5lzz5ksvKZTaqjYTDgEIvtnVVkoAQJalEAgEROj7PESIQEF4wrhgmUREVR3LMjORcMaTIFIwxkgAwVRNSVnGuLAdW7cNCUEmGYBSMAYhTkQGMJJpLFJGKS1RqBKqINwejnKGmWHI/URVFJ5FhCqEwjPry2EUK7riBaFuWERRn+/uVnO5KMuaC3MUI8txiuXis8dP0niAIOp2OxBJw9ITmQGKIEGYEJkJn8m7T572R6Nf//Yb037v87t3NzYuLdWaO9u748BHlr57cOTG6fLS8luvvxaHroL5W6/e2Nw5uvvouWoaVFWjwMuiAEIgMq4pdhLG2Mn3ej2E0Pb2dpqmV69eHY1GnV5P01QI4XQ6NQx9JvQ1TQMwEfjB9uaWTNNaqTz1vOFoMp5OEIBJksxosF+jF03LYpwncSylRBBBhIRgQErOxWyqwBjHiMKvXDuEEABn4V+IEJydQQCEggsppKqplmGGUTRxp5ppdLpdwzBmqLrZ1m+hUEIIh2GEMaWUYkQxhvlcLpdzIILD7mmtXH7322/oFDqWMfai/b1DQtSUcTeIJ24vTiLHMdKEI6IQoiCEMRIIwuHYffXlW2mYHRzsz0CUM8sZxriQszWKJiwxDS1OIiGBZRtEIpahnJV3jJwUYmVpEUjIMqbnc1maKYSWy6WZN1PTVYwxxkhIQTGWGU+STDWMo+PDQj43nvqnvUGcZqqmSgxHvr/QrKdJMp54nfbAylWQSouObpnG0c4+RcqzzedHrTZAtFgqZmnm+971Sy/0+6PJ1N9YP5OkmappQeg9fPAgTVOFkIX5Od8b7W09q1SqV69cE4JN3dHtu59v7h2GYSyFzDJeLlfOn1kLPe/1V187d/7c3S++ePL0maqZbnC68+Enb3/77d/9/vdzts01+r/9yb/v9fuvvfZqp9dCSG6sncnbuX/xP/8Lxvkz8/nh8VGpUr588dLLL77SOm1ttbfDTBimXajUf/aL96bTaaPZ2Nx6qqqKyFg5X9xYX65UKy+/9OpgOPzw9mcP7j+SEKZJur31/Py5s0sLC/V6ZW1lhaVprVKvlKqqqs4y2qVKrVyfD4PY98PmQl03KH0oXNf7e/+Hv1upVMqlchCG7mjq+36r3W42m6qqDYd937cNIxRCWpYtBHQsR9d0x3GOT08ywZ88fZp3nFq1qihKq9XSdf3tt9/mGXv8+LHruuvr67O4dMxSW4r9/X2iqZphtNrt8XQSp+lwOqaUfvfXfm19ec0huud5CGMKYavVohh7vt/tdlut1kxa6uRzc4tLt+993n/y5PL5C3P1RpplfhgQQibTbzbfFiAIOJCcQwEghH7gpxBouqFiRcVUYAIZFwoHCFCsaYZpmLaCQZxEWcYkQoqixHESBMHYHWdAcCFURFRKI8E4QRAjiRGiOIgim1KsIsZC3/f2N7cYAvVGtdqYi4EECAqWKDlzNBqYllWtloIoxlhEgZsqJNMoAPpgOHDd6crKkmoYg24fUmIYWi5nTQV3XTeDMMtY4E1MRTcNK2TZ5uHB9EfTc2c3zGYzlvLlF28Qgz5//iyIQ8cgENGbL7/EEPKztFxvriwtzdXrL7zwwudPtp5t7XmcW45jGQZBKI7iyXRimiaAYDAc6qZBFHp8ejIcDjHGOacy23lNkxRBEifZYDBicRLHcc52Gs364cFBuVwejcczD/ls0382EJv9QyFElmXoq01fzhkhdPaRJkkQRrqmSwgMy5RSZmkmgIQASvAl1BEAqSgqJphQoqmabuiu62UZK5ZKaZrOWMOcc0VRTNM0DF3XTc/1CcGFQp6xFCHOOBMZU1Ny7fJldzI+e/aclctvbm49fvyk1e1BTKM4zhhHmOTzBcd2At9VVdW2bSCA4CKVgHNOdfvwtL23s4cxhQR97VdXVTVJs8B3AUSz2ImmqCzlEsFWpy0ELKBCpVSq1aqx74dBEJq6ZWpZlszeG3K5HCHE8zzDMDCGQRRigDnnAMJfvf++pesHra6ZK48mk+l4fHp6rGkK5EJTiKKpubxxMhjHjA07wjb1RAA/DOyc4cbRyeF2MVdoNGr1Ru3g8KTXH+7uHczNLybpwfr6ehAFURRtbW4JIdIkvX7thXIhd+XyNT+Inzx59PTZwyRjnDEIgKbpcTTJsqxarV/59juj/uhXv/zg488+vXHzZr1Sv3v/7nfffed3fus36+XK6enJn/yrf3X79ucXzl9qt49Vnf7+7//tYOr93/7v/9fRcLiysgKQTjH5vd/6vVq99ujpc9fzDo+P+t0+5/zo8Mj3vbX19TQOgRRA8Jzj/O7v/Y6pG3sHB16Y3L77xRf3Pk/T+KWXXlQU9fHDp41arVTM5x0n5zicZZPxuN1uz8jISZIUcvnReNo+ObUt6wc/+O+KRWc8HHW7velkkndyCqUZSTnPhGBLS8uaprU7rXzeiaKIsUzXdSFEFEXEsmzbdl231WolLGudng57/T/6O38ny7LZvmK73UYAGoYxo3b0+32EsWJoDx486Ha7r772quQ8CILuZNTv93vd7vraOk3FqNOzmgszo2UURZqqTj03y7I0TQeDQZqmuVzu+OiIqMr66spnt2/fuX27XW+ur63MEHrf+LytlABCQzPyTs4N4khkUvKMcQVgCDBPM4lFpihM6JbtSIE03Y3DaZLEVNWklFQhqqLGaZRxDgiSEHIEvDROAZcSUahgziiACiFpwg4PjjIu7EK+UatIABqVskKgImDMM4iRPx0uz9f8IBQ8BWnkBW4lV1QIzFlmEAVMcH8aeE98ghHPmEENKVPDUKZBwASbKTSyJE3CcOxNCCUQgkmW3Hn2JGc7nXZ/4I2vXLpw85Vb09EAPHreHwf/23/4t+ViPm+Zv/7dd+fn6hDIJx98injieyMpOcJ0dW1t0O/PuARhHFmObTp2GEadToeHoZPLYQzm5puE0CzjDx8+zjJhWU4uZwfuVFOVZqMhgdR1fTqZbGxsxEn85NnTGThGSjnji2dZlsvlZl2C2douAABAmDGWphkXnFCacaZQRQKJMMZUpGmGIJoVZFVTFarEcWRYVpZlKeNubwAAyBWKQeBjgoUQMzyY4zj5vDMYDCeTEaWKrZlh6GMCLD23tnaesSwMg9Fo8MqtF+1c4b2PPvnok88IVQVEWZwQTKiqqKqaZtni/Hxqm4qiXDh3bjQYnp6cMgLjjIRRvLmzqygqFxIJIb/y+ti2HYZBlGYEQgBglqS6ova6gyAKM4EM3UhZWi/X0iTGBNqOiTEEECRJgglRNS1NU0LITGMTxVHg+ZVS2bHtB08etzrdyWSSAmpnsNcbhoEbRIlpGApRGUuO946r9WalVEwYPzjYHQ6HacqAxNHUK+ZynItivrS2eu6jTz8J42h+bo5Q1fWCYrGoa1qWJJMgUjDpjadIgsW5heWF+Va7t7W9c+/BvSjxCMa1coVSNU0ywThPskePHpfyxU8+/PjB/fuGYz/f3BpPRnnH/sFvfA8KuLt78Jc//tHPf/Hzl19+OZ+3Bv3+q6++wQX/+JMPm83a22+/devWLV3THt5/dnR4LCF68Pjh42fPsEIRY/u7O5wx23H63bai0KuXLl65cuXM+rpu6MPhSAD5y1+9d/v2p3Hs67rSaFavXrlKIV6Yb549u0EgNHXVtssIwq2tLc/zcrlcuVwaTlxNVTVVTdNkNByyLLpw9nzOdv7nf/bPioVCsVCghKiEzmhH7Xbb0LV6vYYx0jRtFoYRQsRx3O12wzDM5XI7+3sI4/FkzBmfTTs9z0uSpFIq5/P52SwkSRLG2eaj+/1enxKSc3IKJpZpcigNy3xl5ZUXX7gx6PViRMMwVFXV933P88Iw7HS65Ur50qVLjuP8+Mc/TtN0NOyfdtq1ucav/9p38pajEYUQjBBWVdXzvG92tUVQMKESqiuqAFiAJAqmYRxBXdeICpHkMgOIT11XAEWlWrFY7WURSCCEkFKaZQzOrrc8SRlLeMahgqDkQgIhkjjBQlqqYWnGeDA66nQEgk1dyTk52zCgzIggFKtEyJRlqk6T6QQyXiqWUJbCLHE0ahlKHHuTiYcVxbSdJEuRQpI0GY77EoKIp3GcwjSCPOMsFpBzIAQXFFFVVTnimGI39GiGJkcH2ycHBdu+dvHy8toZYzjtDa3j40M3CH7x/kd3Df0H3/3O2sbo5//iX8416sNp4Ifh9u6uqeuGZQEpCcKj6QQAkKaJqmuci9X1VQxZksZHR8e6bkZhbFm5LOOGYYkstS3jlVdeooQamn50cnJ6erJx7izGeDYBMwxjOp3OXrKzYNaXIV8IEcZZJiCClmWlScoFVxSFcwallIJDjBRNNXRTCogwyucLnuupquEF4axPSilVVDVKEgAhY8w0TSGEpmmc8yD05+YbgR8yxsvlijv1zp4973luvz+4cP6CADwMgr/4yV+HceyHiWZYjIs0zWZCcoUghCBGyPe8RqNazud1itPQM1W4fPbsvYdPqG7qihlEPsYYfQVC0zRtMplwwVMmTNumGKZhxBKmm4afpJkQA3e6tNBUCdrafLq+vkYVkiQRZ6mua7qhU0XJsmwW9J5OJ5giCWQYx4nn375z57TbzRUqo9EkGQ5rlTwqW3C5CQEIwmmv04qzTMKhgKofRKqiCAg11UxSgYks5ovXvn9h2B8fnXZ703B5eX55fUPRzTROJefddptSmsRxtVIxdD2fy00m048/+lAAcnh8AjDJl6uOob79+pumaf/yF79qNppRlEggFIUeHx9WquVXvvWqlbPbndPrN66phL73y1/99D/9/LTTWl5dnk5HEqRvv/tm4Ac/+csfv/PGm83mnKLQ6cQFDmz3Ou+99wHEKM5SKWVzbu7ShbPL8w3DMAb9/qeffrq8svL3/97fowrd3tnZPzrwAv/w+ODpgy/C6eiVV1/1fVdF1BtPV5eXrly+VMjlMJSmaYRhNB5PdF3XNG1tbW06nQy6O+PRJPTCxcUFKEC/092nKiX0u9/5ruM4ge+rVMlIXCzW0jTxfQ9jqCh05hmZhXBmeZjJZHLmzJnRdAKkvHTx4nxzbmd3R1EUVVXL5TLG2LZsTVXDMLQsy3Gcg8PDx8+eVkrl8xcuUEyABJPh8PnjJ//0n/5Tb+K6rru8tJwvFBnjM4OG4ziO43iBPyvZlNLf+73fA1LefOHa4enRs63Np48fz9Uat164kSTp1HVnr/9vdrUFAEAIhAyDgOgmUUQScNW0/ThVTLtQzvnBBGLAGI9TplJd1QzbdhBiScYY54xzipTZkAdIoWsm50zVdBjHAAAgQc6wdURAxgSEdrlINFWqdDAd+f50rlE0VAoSqWNVIxQIAQSAghVNo1YotFqdLApHWYowdv2wWK51BwMBRLVSBhAKIZhknKUKT/MKooRgosQZS6I4yzIhMkvTAGCSAQSxauocIj+Op4Nx94NPDUxDz5ME1ebnc6Z52ul+0em3B9P/49/9w3/8T/Sd3f37j5/vH58EUYAQJAinSRKGYZwkaZratm3btqIghJFjOdOpZ1m270fVaj2O08gPjo6Oc5bebDTyeef50+ftVpcL0e/3p543i83OLvizy/js3RsA8LUInXOu6oZhmlmaaobBGOOcAQThV84IRVUARhBhAMFwPEnTpFQqaQiEUUQoBRCmWQoB1FQtTWNV0zRVncVuypX8LPS6tLSsacbx0WkYpgcHp4ylgf9FuVwMoqg7dnXdMCw1SuKMxRhBVaWaShfnmpNhP01ijIGp662TY2d9/aUb1+Io3Ds9uXjmzLPNfQCRrmgSSQTB1wM9CGGSpZRSREgchYLLSqnSmGvef/48DEOiUCklglJTaLFYKORzw+FA1w3HsbkAnHMhxWzglsvlU55gRMIo+vDjTx4/fZJkmZ9kRNFqtbKOOBUySKLOYJzFYbVaYwKadtGy8wKC017r8eYmUs0skzeuXC8YKuGyWC79/KM7GSRhnD55+nw4HKwtLdv5/Pbm5snJyfr6+vLy8pUrVyilD+7fb7e6fpj4cSqQuL5x7cL6Sq1a7Xb6/V7vnbffvXf/wdracrGYQ1i++NKN3/7tH3QGvfsPv7jxnV+bjEZZmgVBaJiWZZnd7vGVa2/mctYvf/He97/3fRWpUZju7R1+6eU0tHPXLjx98mRhvqlr2uVLl2+9cK3dOk2SJJ+3i+XClcuXBWcfffDpg8ePOv3e0emx57pzpfL3/+s/Wphf7Hb7r778WqFYfLb1bGtzs5jPrawsqQrp93t+4K2trYVRSCm1bIcQvH9woKlms9lsNCpJ6gS+L4RcWVmJoggCGEVREATlcmk8Ho8nw0a9MZmMKaWO48xATjPPxdLSUqfbOTo+rjca165d63d7tm0HQVAsFovFoqZpGH5p3kuSJEkS3dC/9a1vLS4sFJ38s6dP4yCSks9VG08ePN5YX19dXRWcI4xMVZtNiUulEuc85+QURUniuFKpNBqNIPCH/U6WJOvra2mW+uPpaDiYTL3heKyparlc/mZXWymB4NjQoWGPwiiIUoBJLFLGRYE6CHHHNNI0i3wXCmRQjAHkgKYSZUISQjAFGWSYEkWqgCGqUC4glykkEgHE0yxLwkgCqltQhZqhQYKyNABAZJJNAw8AqRGV8EQFiYJ1jhUCYTjq1mvNHIHYsMZhmKVZvVwUkFHImBTuaMizRFcoBQRzpqtKwjMqhIKQBwTIGAaCqIpGAQFMx1gyliQRJARIrugEERwkidCQpmlxGmMIF1ZWzELpsN36f/xP/+y//oO/ffnixXGvM2i1M6T4foIQyttm6PsYY6IqSZZqnC3NLy0sLakIrSyu/uRHfyklxljlgpu27nnuXKPyyquvJkl0cHLS7w1yuVyhXOKcG6YRx7GQEiFkWdZscoUJBQBJIFWVZGmmUUopiYIAQkmwmmWxQhAQAiMKAAEIIgINU0+izDCMfD4PIRiNRhIIQoCiENOyfM9XVcUyzSSiedvO5XIAgDAMKSalUllXvEFv5E4Pk5S3uyPGOcIkStj+YSsIQ4ix4BFVKEsZZ1xViK7ASsHWKKqUCjOT5unh0VyjPhyPC/nco2fPuoNxLl/UNeoHAVWokBISAr7sQXMgJUAwAdLnWZjEVFUlofvtTmc80TUFcNbvtV67eeXipXOTyWQymRSLpcD3cRjnHAcibBomgCgMo4Pjow8//ujGpcsEAsswVs+ciTiQkA57fcpF5PuT2Dvtd70oKtmOY+V6g+H+wY5iOIhoEGHIFcLg2TPrLIk8ySI/dN04yxgG0A/TXjAigOfyuSTw8gUrTQqlYi4Mg9NW68HDR1EYc4mjOGYsi9P44ef3zjSbUZh+eueLveP20b/61znL+PYbr6RRuL6ycuPatdD3/vn/839CimKY9k9/9YtHDx9CFVVypeOD/StXzy/PL/z8p//p0rmLzUpdJOzpzu69R08Agu6DR8tLc/O1Wmv/AEtx5eL5WzeuB57rWBZy7Hq1IoTUNPXps6fD8ahYLIZhYFD1hdde/83vfW+uOWeapu8F+/sHQRybTv6z25++eOOFbn8YBMHR8VGlUsk5ZqmYA5JjKAzDKJWLJ8enmq4UCsUoUkqFUj7vjEZjjFGWJa7rzshEuqHPz83POHOaphuGAQCYAd01XddUBUIYBiHLssOd3ebcnLDtWdJ2JpE7PT0Nw1ChSpqlEsjhcLi8uvLS9Zu+56kQHx8fFwqFpZWV3d3dRq1JEBUQE6pATJ1CngsexWHGGIJyMOxLCJIsm265CMh79z63TPPMxpnNrc3eqH/6cXtlfrXWqHMJ7j99+s2utgBAAAXEgqhQgSISummnjOkqAUj4gWdrhkI1giMMJYJCCEwUXTXtOE6TJCW6IiEnKpVJDICMw0BAiQiQGAspEUVMZLpqjAPX51nCE5lxhAFCkEnZn4ym7rReqRIA1ZQY3EREJ5jymLeP9wzN4BmzNQKxykGGMAVECAmjwEUQICQQkECKr9YzAEIQKliBGgAQUQoRoogixiCAEEsBmKUAhBFRUQBAigmTjCIaptFh65RQZWF5sXd6/O9++MP/4R//w2+98vL+4VEscDicrKyvcZZqttZpd0xCKaUIocFwWCgU/NFEJXhjfc2wcgdH7UTwOI2LpYJp259/ce/05LjX7xFKkyydIcCn06lCaXNuTnBerzd2dnYopUkq0iwDAHIuESaMcSCl4ExIBoEsFfMEIYWqUuLxaKqqys2XrhXyhZPjVpLE7XYHQcizhBIEoVJv1BFEEIAkTaSUS8vLhWJxe2tL1bRSqaRq+uMn257nq6pGKY3SJONiZjN1fY9zbtuO/FJ5iQEFhBDHNgydGJpqmYbv8mql2uu0Z/nftbW1H/7pDw3LXFxa63S6tVpN0xXP9XTdkAhkLEvjGCEkBE+ESICc+i7BuGhZWCEnu4eCsSxktkYJkBhChSpHh4ezFbswDAvFkkqVjPM4Tjc3t8rV6mmrE8X8/sNH87UqAxJBnKSJrqmHuzv1cmVleWHiEeqHRcNydMuL42Kjjhzj0ZNNd5qo1FBVnUK8urjQ7ZzsHxz0uqMwTAlWbU2fm5sf9LqBNx4OeoE7vXj+7Juvv/ZXP/1PKytnRqPJaasTRXEchVLK17/1ShRGz549sU3rww8+evjoSRCEWRT80R/895cvXNzf23/11dfy+cLO5jYSIJhG//Jf/qut7c1KtXjx8nnLMpFYzbLwg199ePnSFc4QkvL55rO/+PFPvTgtVSsLC80/+L2/lYTBQr0xnU5LpdKg19c1ZXlpCUJYqVQ67fZpqzUejz/55JMwDP/wD//wd37rd5aWl/b29vcODvL5QpZliKJ7D+63+/1KuaSo+vOt7Uq5mC8UbMvEGNWqFQlAuz3WNGV9baXZqHGeDga9arXq2EYYBhgjCEGrdZplTNf1JMkEl2tr65TSJEmiKIqiCACQpimlNEzik3ZLMKabxrDXt0wLAqhpaqFQSNP09PT0yZMnDx4+XFtdJYTs7e0lSXLp4iXHsNonp7NdnoWFhSAIOu3OpQuXZrvpGGBVUaMo+uDDD3zXWz+zVqmUB/3BaDLZbx3HWZal6crSsp+kg8mkNxxubj8fR64XBM+f7zSb8wLA/uAb7yWTgnCObCvPQZQlEsBIZIxQFRNFcC4BRFjRdFPVdCEBhEDR1FSqiNAkztIo5lhGaZrGMSZYQCAB4EJKLGd2xUiwLPIkE1ChGtGiMOBScCEghAohKee90dDSdNuyIU/Kphn4nsCKpmg8g0TTIEw5k0CAOGMQQhUrqooxQgDwLE0VIAEgAEAEMUKQIGQQhXGecIaQpEgSQiQTnMcKIVRRAARJ6KkAZgAAiBLGdc3ARPH9EBJYqlYRZ7/4+ON33nrzt7LkyfPnyt5Ru33o5HJOzlnVTduyojA6bZ1iiEaDoTuZzNWrC0uLum5v7R1RqnDAkzgOfP/k6BAB4DgO5+L09HSW87csCwjhWFaxVHr29KmUIomimVEXAighsC1b0zQAZRzHlOIzZ9ZfuHGt3el/8cVjz3WdvP3Gt16u1YrD4aherX7++d00jprNuYWFhUfPnkZJqqn68fFxLpfTdSNNkk6312p3AAAIswcPH0OsQ4QwAkgKzlNEoa0bSZJkaYogKJSKs+v/rPk1+6RaKWEE0jRVKC3k89PJ1LJtjNGMTPr6669/8NGHAIBZaziKIlXTBOcYIZ6mcRjOQI7NZrM3ngwnQzOf1xUa+p6j641KxdRUnSCN4MPdAwzByuoKRjifz8/YCH7gQ4SnrjfrvUgJnHxh2u+lEra7vU5vyCDiXK6srka+f3B8iijOMpEx5nl9oqq838eaMr+0PGiPptNgYWGxWMr//Oe/gEBIKeM4wYgsLCyEYTTstLzpuFGrnh6dKARVKlXdMJ1cvjcYjCeeH0SB7yVRoGmqbZjbm89fvHXzyZMnH3zwYaVWf+nmC4V8/taLL27t7H704Ye+H/zxH/8xF0I3rfuPHy4uLSwvLV+5cv7td944OT7cfr61u7O/f7C/ML9KiHr38zt//Vc/7U38XKmsKqRcKBBKF86caTSbH3/88Ycffvj22+9kLMvn8xDCJEl0w8CEZIwtLCzMzc2tr68XCoXt7e0sSy3L8rzpbLlg/2APYFzIrdy9c/svf/TnL7106x/9g38ApKjVahAhz3XH4/FkMlpYXCzkC67nJkksgciyVH5lM7Ese0aj9zx3trg427H0PG82bJiJoB49e6pb5mDQf3Dv/nff/Y5mmaqhU0KCIPB9//T0dDqdfu83fkPTNErp+vr60dERISTLMlVVLcua7em4rjs3N1epVpIk8TwviqIoDAe9nqnr2IH7u/sE0ShMqKJqhvn40QPTsXuPHw56vZxlLszNRVyopm0UiusLK+PBaGdvr1yufMOrLYAQpWnGGKeKYloOxBQqhEuRMa5hzCSAHHCJJMQCQAgll4IJIQHEREEEcJFywTHBmOAsyyCGXDAAZyhqCrgECHEpoWASSESglABCBCAAEiiqyjgfB16QxjpVYz/UNS2Lp5qqAwENy9BzlqbqSEopM84EBZBgSggEEHNIGU8zJmbzbiABhijhIhNcwSThHAhJqUYUnGQZYAlCghBKoMwgYkgIICTCYRyqOqS6MvW9iCBDM/7644/22q3f/41fP7t25vbtO0+fPredwubmDlLU1mQqOJ9rNGfSxnqjcfnyRVNTP/ro0zhNXc+N4pBzFieJbVmVcolLEQThzKM1u3+9dOtmGASdbifn2IeHB0mS6oZtWlaxUIQI3njhxv7BfqfbZYwJwRVFuX37TrvTD2OJECIEpWkEJVAUNU7jl19+5fj42DRNz/MgxHGSbm5uIYTCsIMQFlIQTITgEgCEkGGYAFEIkabTLEvsnF0sFLyxH/ieqlCMcaNWjeMoY2mWcctUDUP3XG8yHhQKuXqtrCmk2+lmaWKadkYIY9nHH3/ygx9878LF83/xo58ihE5OTma9NsYywaVjmS/evIERTpJkMByef/mVO1/cKVWKpqp6o/GFjfVOqzVfrdQr5b2dnSiMAj9szjUURZkdoxRFyeIYY9yoN0zL/uz2nZTxydiTmJz2B61ub+oFGYDXVpY7WcaSLBNcYnpm40J/MOj0ez5jk4mXLxV12xiPx7pmzxp/nudhiHK5gmUplUqVYDro9xxTRZxVikUseM6xPdd78uy5phtPnm3FcQYRrlSrFzbW/uqvfvKrX/3i1q0bb3zrtY8++rhcLLz95usvvfiik8u1Wu12tzf1/OWVlXsPHx4eHEy9QDOMZnPu0qWNF1+8lsXenc8+ERx4XlAq1IrFapZm83ON/379H7730Wd3vniwsb5+/uxGp9XaWFtNksQ0zWazWS6XdFUZDoczG1ur1UIQvvbaazdu3Pjiiy9+8pOfbGxs7OzsPH/+5Hvf+96v//qvP3v23LatyxcvaIa5v7t7794Xr736ym/82ncKhbyuabquzwIeEIBcPielEJLfuPHCzJfjeT5CcMafne2Cc85nKJlyuawoCgBg9uesEE8nk8XFhQ8+++Rgb//Xv/trN168ZWiaFDIIgllHSAhx9erVubk50zRHoxGEcGVlhXM+35zL5/NJkjiO0263l5eXa7XaZDKZkTrCMOx1OufPnimVK1PP297dn/phIsRptw00ClSlN524rjsZTs7ZZ1r9oZUrjNxxda5an2tevHCxUK4wxr/Z1RYIADkmUqQZAAhjgBWFCs7SRAIUJWkSpcWio6gAQIQp4VyknAkJZjUUSBRGCaIQAREnmZBfre0zRiHBCHIpkiQhmBCMhMi4FGDmi5ASQ4gBAAAKADLGsiSDHDAJFKxkEhi67obBJPEoooZulAtlzriKVSig4LOBGgAYAyElFxhBgLHgjEhBMRYQCMYEgBBhSKiuK0mcICkw54AzXcFIV5JM+AmjhMZJJASUgnteMg4DQsjtZ88OD1vff+vbFy5eeuXWiypRHz/d/Hd//qPZLUkKIYXI0nQ8mXR6XY2SZ5vPM4FV3bSp7bpup92u1yqHh0eqpkZxPONzTyaTubm5mzduPHr0oFwq7u3vbWy8u7e7d+7CJZbxw8PDSqXcbp8eHRyMXZdzXqmUGo1GGPkQkkFvura2WKnkNV17/GzLj9KpH0ghOWdZt+95npAAAqQo2oxNwxgHCGVcKIo6W5HABGsKaTQaWZbatoUwGvQHWZJUSsU0zSglo+Egl3dKpcrsDB4EPsawVCiWSoXADyLPh0JgCKMwTLOMEqxpyuMnjxeXFmeWz1lqmBDiOHbRsc+dO2tZ9mA4mIyGy3PzwdSVSbJQr0dBMIhjAuXq8ryUXFHo6trq/Nz8yenhjCZFFSqlnD3ULOfr+z7nHCM8Hk8VlbihH6RZpT53cno6Hg4Xl5YO948EJn4cH512R8NhezSw8s58Y0lysb+1u76+XixWbSt3cLCXzxc0qgOADR3nc4VWu8159sqtVyvl8uNHjxfm5i5fubK3v+d6/uHRSco4VXUFkYVmvVat5HM5zrOlxYVczh6NRgsLCy++cK1RKZ60Ov/hP/6Hdru7urLy1ltvP3r0aHf/4PjkGGIchG6jXht0ek8ePcibhRdefOHNN98dDaa+HxwfH7z77tvPtp6dtI7jOEyT6ML5c4/vf/GnP/xhr9+/d+/ehQsXFhYXCQTj0ajT6WiqKoSI4khV1e3t7WKxePXqVV3XFxcX5ucbURR2u50kiS9fuXz+/Lk7d79I4+h3fvsHSwtzjm2pqgoAjON4hvLgQtRr1Z3dXU1TOGcASFWlimWwjP3nYYNZei+Koq8XxHVdn33S7XYPj4529ve+8+138DuoWqkYVPEnLkQoTuJZFsVxnBkYbDqdHh0dzb7iOE6lVM6yjHOeZVmhUJBCPnv2DADAGNN13XGc8XjgRz7xlZ3Do4HrUiWd+O4Hd+9AXVFtM3Snw/GEUqXTG1Ty+fWVlUKpVGvUsjjJtPTs2rptWN/sagsFhIzzhPFYICoEF5kgVFMAQBgjCCEHiqphojCeAYQE51xwiDBCmEspGSdUoSr2/SkhGEA0U2BhiZAQBFNFIX6aYYooRgJgibAEEgAhuEjikBgGgpBlXAJACEm5IFzopt7vDy2LYwwJgUyI0XhCiaZRxVIVTTVcfwoxQhiyLMUUQAJSxoTgQAiMEZFSQJAhKAAkECApIcZOLhcHoRQSQSwZk2miKwbDiCHMhWCCAwSxqkgAEwCkqh4H8f/ylz/+g+995+bFc082txbOLBeLxclkCiF0/cny8vLm1paAYDQad05PhJSEUi6FNx0jiLgQp6ctDKEE8tLly0EQGIZRb9Tn5ub7/f7C3FylUr5w/myWZSxLVUXJOfrz588E54SQQiFfqlazLKtUSv1+P0nj9dXVkj1OWHR8fNiYXxRYPem0oySBQFZrtcG4DbECOAOSz+K6X5nWsGkaM2ZYznE4z6ols1ItjYYTQ9cgxJ04cWxL1/U4jhnLAIBZEkeB1DSdYsiy1NRVXVM4YwhIRVOxocdRlKRc1Zx6vQqh7HTao/FodjkCUmKMLcvM2bZtGfu7O4eHh5VK5ezG2fm5+Z/85KeXL15o1mrdTvfKxYuLi416s+ZOpoEf5ktFqqmVahVC6Hke+GpfTgqhqup4Mt3e3snncv3RZHl5tTfqDfrDUqXaqM01Go1O+8jzPIDxYDQGmFhOXjftYqPJpXAMs2A5Fcty8oVedxiFqW3bg0FPc0zORD6fn0wmk9FoYb5pqUo5n1tamNvfPySYEKowIS3babW70SS89sKN17/1yr/+F/8vjMBLL77SbNT7vZ5pmlyhhZztTcf3vvg8DOPl5RXdMCWESZYFYcS4qNQrzbm6EEKlxluvf/vRowe9Xu/K5ZsPHzwvFYu/8b3vbW49f+/991vt1sbZDVVVnj15fOOFF6IkHn344auvvrq3t398dPTaKy/ncrl2q3V0dPTpZ58V8oV6c346dc+fP1culybjiW1bV69ewRh3Op1arVrI5zvttqbQWzdeuPnCdckZJhBIGCdpEsfD0SiOItM0a/WabuiKogSBF8cBhGgQRpTQNE1n3gTO+aw563neycmJpmmzU+qMOq/r+srKSq/f75ycnts4q1MVCMmStDcampZp27aiKJ7nua47A9fNIKUz/EgURbPU43gyeXD/vu/7pVLp6tWrmqYNBoPhcDAYDkrVQm882j7YPzxpU814trvVn4xSyTElPGOOYS/MLZZyOXcwisM4l3dOD04sjYKUX9g4Xyt/090NSAqpUKqrOmPU0LUEhFxKLFCWpozLNE0Ub0iJqigGAEhwwTiLWcoJlARFUSCFgBKpiOq6kbIszVIsoEoR51xKQLEqJUkzqFEFQISR5DzjXEgJVUIJwhDBNEkIIQhKADMB0t6gxYQIBh5BkFJCDR0RRU5HKqB+wpxc3rYtSkgchipSIAYQIQmRH4SxzABCTIaCMRUihAgGSArBo4AYhoIhF5JlTGIMCUWM65yHLEBAEiQRJhFjABGRCoygoCyV/H//6Y/+9Gd/lUTJxQsXfuePf/fzDz7uHbf2hr2tradrZzZiN9zd3gUQ1Ofnh+OJhLJYzAEBfNdLpeSUYoj2D06KJWd+aUFK0B9MBJNZlvz7P/0RIng4GSuqyuLH58+daywsfvHg4azRKQRvzs3NfBPz8/O9wTCNI4JQrdxsnbRV0zQtpV4vQoiyjBEMMEKGZUrORpOJ4JxzTqiqarqq6qah2qZWKlnDfk9XqKGqB5NxHMe2nTNMnfMky0CplPM8r1wqdzodUzNKxeJoPIZccsbjIHJHY6ooKUmFEEBK3dAXFheiOIqTuFApHh4dSUYBRkxywbNczrx68TyB/Be//OXS4txLL7+Sy+W9OCwtVjKRPrh/f2VhaWN1vT8ddIbDve1dkbEL588JkSVR3Do+Xl8/o2CFEoIQ4lJQShr1RrPRDILwz/7ix0nCG6UiYWEpby/NVR4/eSYY3zo44Iha+aI/DXwv4oBFYRSHIbeTilO0NKt1eDqeBlPPa9YqS815xylyibb3dkeD/upi8/d/8BtYsCxNWSYA0eIMHpz0nu8eE0KpamgqeOnGdZ74zXqp2+WFvF0tV374wz976aWXXnnxxU7r5OHDR5Opv3H2/Btvvra/v//P/+U/33y+GcfJytoaxGSu2dx59vjGtauL5zam09Gf/viHh4ftwdB/99d/rd1t7e5uv/XWt4FA9VrjhauXVRUVi0YYk1svvbS4uNppnR4fHHz06WedXnc6mfq+n3ARC3F8cprPO8WCqVLZrJeFEIwlnW5XJejM6hJF0p2MK8X8yuoywQhgRUrBBYuioNPvcSBmWjlD0whBB/sHUnDDNKQA1UrFdb1+v99utzHGlmXNstIQwqWlJQhhr9dTCSUK9Xy/VCp5gX/l+lVFUfL5fJakURIfdVoAYZrx0XAEISBUQYQeHR0dHx/NzzXLxSJEAAIhBEuzOIqTk9YxpOjCpQvnz5wnlEIEJ66Xcdmf+MHT3UKhZOUqK2ru88/vuWM3TRKGYMakRjVDdUq6U3MKJsJ/9Vd/sba+bNump+CMRRtnVqVk3+hqCxGEBGcxY4ITxYSAalCTEMYAASHcIMhYEkVehjNVNTjjEgiEEOOcC8GFIISkcQwF0jVdcAGEVKmaMhZHAUYQAC4JxIhACR07F0dBHEcYEwAAQkABiHMhmNBUjXMOBIBATsZjQighFCIgIUiyNA4EB2EUJQog7UEPIpQz7Ualurq8zFMWxRGQAkJQKuSnnhfFiYSQQ6lQCiQEUswSnVkSK4oSpxwiCKBEUCAgFCi55BkUEACICDK04cSVEolMCCC44HGSpUhBAN9+8KB1tP/9b79jG0ahWLQLxbHndfw4YzxKYjeK4jQtFAtpFEV+qCoKUdRE8DTJ0miCKUQIUaIc7J/u7e4Mh4PJdJqwFGIMETJV44t7D2aqyiiKeJpWa7Uoinq93tLS0mAw7Ha7jmmsr6wuLS51B4PxeKRpVFVp4AdBEG2srydZur6y5Hvu7bt3dR1pmsYYl4Aszc+ZpjYe9gqOrWCpUCWO4pWV1annY0IVRdE1yzTNGbycULK4sBD6ASXE9zxFUcqlUpLEqqqCGW0eQoyxYWhB6A/H44XFxeOT44xxCIgUPBOcZV+GkXWNvPOd76iqGkVhv993Az+Jgq3N7Vs3Xqw26s92d49ax/VGdTJ2F+cb+Zwd+NN2+ySXy0dRAKC0LEtmXKNK5PtxxrZ2Dw4PT1r9kWo6L1y//sXdeHV1hQHg+/7Vay/cefDguNMLwzT2kySJgjjQNRUKoKvacDhAUsRRDCGq1epz842SY+3s7La6A8bloN+7fmFDVZWT4w6E2I2iwXj8wx/9aHtvb2FpKUvi8XDgh2Hr6PD8xvLVq1dN04QAPXu62Tppa28aR8fH7mTUHwxv3/389/+rP372bOvxw4ePHjxGCP3g+7/p+f5pu72/t3/1/Pry8qIEkknu+8HjJ++fOXvpk08/2dx8dv7CxvVr11Ws3rl9p1wqjkYdwTmQcnV1fTR2d3Z2HUM7OTl5+PgRBFDTtVw+1+/3nz5++ge//7vzc80kiRWqqoqWpsl0Mi3PVXTNyLJseWnJsqyZiW4WD59OJ7v7u1Pf101DwSTyg0ajbjtOqVSasZUppb3uQFXVixcvpmk6m4yBr2DWlNLZC4BAlGQpY2x7d2c0Hm+cO1srFtM07XY6H3/6CQNyfX3j4ODAMk1CaLVanZub0zRqGprvTbs9qGna4dFhvlhKkkQCoGhac25O0bQ0Y4qmh3FIFcW0bYnQk+ebc/OLJyet/mC0f3AkBEMUSyQykdULJQpFMBleeOXFO3c+efXFG6pGR+OBn/JSoeR67tbTzW90tZUACAkYlAlLg3SqUpMqSHBJKcZYDyNfSOT7vm0RzjMBeJZlQnAoJeBCpUrCmUoVTVUAEJxxlmWEUgyAhBhIKYQUgCsKllKOhgNMMCEEQkAp4ZwxLgAEGBMIEUUYYxzFYZpmXIA0ZZSqXMowChEhjIsABrqiSSkF4xDwwJ/oupK37SwNhJSKqk5GLoBIozBKuIYRgJBxwBnHCEuEuOBZmgIhgZAQQAw5AhAioGEIAKSm3R+5SRJBwQDAjKUpYwIIgqkQXEqBMWxNhr/47JN3Xn4da0a/N5QAHraO3dCHGHHGEIZBGChUgQhRRUFCAokxwPMrjUqlMJ1Oet1Bq9WPozCOQwGkosxSEhRKWCzk4zhut1tRFGGMFIWMx2PTNCeTSRCGtWplodlcW1m9c/v20emJF4dEoRTjJMlM0+p0u6PR6OT4uFTMz0QSmqKUSqWp67EsI0gzdd3QtPNnz9y/92Bne/fc+Ys5J9/u9jLGDKjOkueWZXHOIcKapp2cnvq+n8vlPM9jjBmGaRi6EKJcLmdZJoFwPR8hvL27O51OIcISiJRzwzQqi/PFcvWHf/6jc2fX5+bmdnaenz9/znWn4/F4pbFQK1ZX1s8829r67M5dU7dKhWqpWK1X6/mcQwo2RhBCbNlWlmVxEiME0yiM4pRB8uj59nG7l3KpR+mjJ08Ojk6tXOG42xsH0ecPHg4GIySBELxUzA+GzLTKlmnOdj/GoxEBQNf19XNrqqZNR/379+9vPnu+srpuFwujXtdxHDcI+1NPQtgeDI47bUUzIAIXz5893N/rnR6trywuNOthEFy7dt1xnM8+u7O3u//uu9/NF4offPRB4E729vejONnbP+h2escHx4KD8WBw/969mzdvIoSW5huvvXJTV+n+4d727g7AlAl5586dO3fvLCw2DZ3cuXs3dIO33nqTMXZ0dHzh/AUE6XQ62drafvb86Vuvvbp2dr1SLfu+P5NGv//++63WKaXUyeVYplNMKdXiOF5dXZ91AGzbsW0HAMkYS9O02+1ijDEhruu5oT90J88fP+methfm569fv768vDyTN896OI1GY6bpS9N0tmg74woBAGbGlonnSQAGw2Em2MbZjTTL7t27lzPMyXhyeHg4DfxOt6tqhm5avh+Wirkz46GKwdLiPGPMyeUBAHtHx8/2j/wgcCybMyalvHH9huU4w/H48OjQC4PJdDJ1p8+fP/ni/v1ipcYFnF9aOdjbrxVrpXK+3TkSkffSS69XrJxG5IWNtd09EcfBYqMZpNw2c4Zu2U7uG11tgQQSAAAkRAAjECcB40jXLUJhFKWGoQPAkzTmInPdqapqnGcYI4pJwFiaxFBKKAFnTEqOEARCAikRRARRinGaphgiBSPOGWNcURUA6Kw3zxhjQmKMCVHytj1zK2SCcSlFxhAijCVUVVTNZElKAcqyNJYcIoQAGE8HkvHuoAhRFcQJgjBmCcsYxAQAQACDAEkgJeASSTBrY0oA5SxpxaUAcNY+hhBDSJhgvq8gISFMEUg5g1BAKCGAnDPBOJIIQIgUvNs6Gf34LxMvTIK4VCqV52rnr1569uxplmZASoDQ8vLqpDeM3IClfHF+zrDsKAyCMOSCTqbTJElSlnEIEEQYY01RHcsyLXM8HiuqGoZBPu/M6LezV/msq4Ug7Pd7UEjXdRVFqTimbhimbhwdHQdBEAQRYyzJMs/3dU0xNK1eLpuaWi7mXNe1TXP15vU4Cu588plhOc3m/Pb2LlEUw7YZy5I4URSlVCqlaTocDikmFJHJZDKD8I/HY0pVjEgYxqZpRlGSpRmkkFClfXIsESKKyjjnkiGCwiyeeN7tz++NRhOnO2QS2E7OtCzTNKEQF8+dn3jeSbu9ubUJCZ6bXyjkiq3TA6/gpHGCVIIJSTOWZlkSJ7qBAMBxyqCi7uwcdIajFMCEi0rRnkw9gMlHt+96ccYhYuOJZViECYlAkkaCs2K+Yplm4Pk52zZ1HSMQJUm32/V8X8Hw+vXrUehSAs6fWfv2699qztc/v3c3TLJeb9DpdvOFQqFYisLgzqcfpVF0dn3tv/tv/5vRYHDaOmGM7e7s97oDjEkul//kk08//vSzvG3t7h8gqv/ivfcnvWG9WlmYny8VcifHh5yn3/72O+fOrKmUTKej4WQYZQmXcGlpOY6zdvv07/7R37FsfTyabm9t//Zv/ZY7GTEWcS49L/zk9t1Wp7txZn1hodloNizLSJJkfW394PBg6/nzq1ev3rjxAlWorqkYEQSxENJxcgCgwWA0HA6bzXo+n2OMzfzNz549I5QggpkQ2zs7AgBFVRcXF9fW1k5PT9vt9sbGRqlUqlXriqLO1CSzNishZBbeCsMwDMPhcDidThHBiqYSoMRp+vEnn6wsLRXt3K1bt1bX1/7XP/kT3/dL1fruUStjAlHyq/d/dfn82fn5BcOyoarff/Dw4ZMtL42FkOpokkZxqVgy7dzByenW9iaTIuO83ev//Bc/P9jftXLFVqtn2AU7V4qj1NbNC6vrr12/vLzSMAzli08/L1hW6/RkZ3N7YXHenfhjN1psLqtUe/nll7/Z1VYAKIFkHAOha0osMi65aWoScN/PEAKzoyhjLE08CJGq4SxLCSaUUJGlWZLpukYpyrJEN3RKKZcCYkyomsWJgqmUTGSplEJI6LkuVbCUgnMpAZAIpYxlKVMwZSmTUkowaycAKSFEKEmYgoiOKBBcIQpHMpEZJJgLDiQfDLrlUo4ChiTkGUMAQgAAAEgKAICAAEMpoARICgkQhJqmMiFZlgGIJEIAIZ4JCJCu6mEcW6qSJbGmUh4nCAoAxCwbhzECXEoJgISQ0q47kZkgFHe9aVXJDdyRamr1Zr1z2saK0h8OJcvm5uYAB1zKo8NDQvDa+vLOzuZ4NEoSIRAgqqJRBQG4OD9PKU1Z0mjW4jgxDM3zPAhJFCUYY8744vqi67qDgVurlPv9fhIn1Xp17Lm+742Ho4WF+aOjE4zpZDJJGS8UCrVyAUOZJlFurmbbRuCNKQbDfjeN4pXFxdPekAmpqlqUJNnEVSgRIuOcR1E000YEfgCFXFhYIIQEQTAjy8RxihAK/ND3AoQQAzyIQ4AwgDBOGedMYsGllBCNXRcyWazUkKI93dwRaYwQWGzWa5VyEMetTrs3GFqWvXpmYzoYTyfDfC6nYCWNxMfvvV9tNnL5AlOgkNidhn4Q7B2djF334PiUSci5tC2jXKpAwAWotoeTVCJIqJAsTpKFWiNjbOq7iaaoqjoLArqT6eLigudNb9+5K5BCKL1+5ZKTc9544zWZyvMb5/cPDu8Pe5/e/VxTrWKxlERpHCbXr1wzKf3g/V++ePOF777zDuCZPx1BKeJohv0ST58+Ozg42trd2Ti38Y/+0T/82c9+9pO//nl/MKzmnXfffqtcLT558uD994+vXz3/X/3B304Cb2/nabfX2j852dnbVzT9d3/7b332yW1K0K+9+87RyeFPfvzTM2sb3V5veWFuYbE+GkwPDtqdTjfN0qvXLi8tLXAhapUyIQQjELjThfm5119/q1arA8k5YwCBTr/32Wd3CoXC6urqaDTe3z+glJZKRdM0Z4fT7e3tiTvJJDtqtwbDwfLi0v/4f/kfi04+TRMI4d7enmEYaZrqmjlLW4dhqOv6jAQPIfR9/+t4lmlbEoI4TZMkee/99xFGq6uredNO01RRlFdefeXx0ydT3z84aSu6oahkoVKKmWCIHHb6n939T0+fb0sEU5EolG6srVdyxaX5ha2dXZalEEIuwcPHTx49fnz18pU//r3fEVB5unO4d9Q5afUwBt328aRWajjLFlKKdlECEMRRvTl/4dKV+fn5v/iLv7hx88z6+noQeO1O9xtdbSGEGECepJPxsFJVdaoIjBhnmEDDtNIklkLESQgh5gCkaUipjjFEiDiWkVGUJlRTFMPQJRCqro3Go6nnIQARwFAAwLkUfBZCAAhDBAmhlOIkiTOWMQkQhEJw1w8IAITQKM0EQAAAwTkQQqcqhRgDiSlMuchYJhAHUhKEBOKDcT+MmvbXIG4JZ2tlQAiAZt+Tgy9V5AhAIAXHCKuKwgFIAYQAA4I5k5IJjBDj3FAVwUWIAMSAAMy4gABBCMgsRwwgwUQtFuIwTuPUdpxE8Em/s7SwlLdtz3MFgJpmdUcnrZixOGOMb1w4D6B88OBBFAVCypkViFBcrVbeev31NE7vff7FUetI1bR8PpdlX8rHkiS2bcewjKOjo/Pnzw8Gfc9zTc1QNbXT7tTmm91eNwiC3Z09CJEUM5gsBRCFUQx4Wsw7cRRhxDfW17qdnu9OTd10XTcMwkxwwaVpGBBhKUWcRuEMZyM4Y6xerxuaHgTBTEnJOedMIsgppRgrEsg4TaIsiZNYAsk5S7lAGKmWYlrmYDCiWLEsM4wj//iIQGioqkKI4GzsukQNvcB//uxZoVSql8rzlcqoN8AI+H7Y6w19PyETn+r20eneaDS0befk9PTh1pai6hDBLM0M0ywVcs83Nw1D8wOfCQAgybiQEgIgPc8rFgpu4BULRQwhRkgA2e52AYCaRqSUcRTpEGGELcNs1gqdk/bt25/4YXIy6HhB2DkdTkbTJI6i0Aunk82nj3SN1ms1z51OWZamieu6T59veVM/ny9cuXK1PxjcuHlLUemf//mf+76/vLwcJLvFYmFxYW5xqQlk/OqrN4SQPGOMM0xId9D79NNPhxPPsIt37nyez+X/yT/6R/VaZWd3s9FolAqFfrcDeJrLWf3eaDyeuq6nGVq5XLZsMwhCRVF0Xd/Z2en2+5VKpVAoIASDIIijEEi4u7P/7NlzXTeTJEvihGVCU/UwilRVHU8mnudBCA8PD2Oebu7urK6tvnjrVqFQkFxOJy7nvFQqPXv2bGlpSVONGdVI0zRFoWmaAQCiMByPx+PxeMYI9cIAQDgYDqim5kvF5YXFNE25zhVFTbJ0cWHRD8PDVpcJngYBhOWpF0796Kg7Ojpt9wbjaRgzKSGWENHxeOqCaZam3VY7n7NVTdvd3ev0upcvX/kf/vE/KJkaA+STuw9/8f6ng94ky7JrVy/+we/9rorAZ7c/MU+MN996hwu+vbUzGE09P373O98v5Yuj8WgymX52+5NvdLUFQEogOec8Y6Ef5CwdSeT7sVSJpusm0TWgRUjlIENISClUChCmcRpCGAMQUCyhgDzFhJI0jETKFIAgBwJnQOFEIII0ljEIEMRQM3TDMKSUcZxKARXEJQBMZpmQAhHGBIdEYim5QABAAbjgCRIJFACARCQCiln9E1JSTDiXnusVKiXJGQAQQwg4B3L2fxBBATFAQkoIkYSAC5GlCcYUCkEkQACmgAFEAAQZz1QEEAAJ4xlPBBQMcgaghBgACBCQM3csBKauqIpiEARsPY5TN8mopu+eHGkKnWvUDVUPxoFtmeHYValGVXp8uJcxRjCxc4Wp72POVarmbUtXyGTU/+Tjz8aDKUcyCGLfC4vFAmOCMVGtVQgh1WpFCHHaOrZtCwJqOGYUIQOhXrsHAcrZxVw+d3J8EkcBAlAz9Jxj25aRhKFAJOYwGYajvletVhljhu2ounX20uUg8BgXS4sLH3z44eHBsa5bCv3/Uvefz5Zl2X0gttY2x1zvnjdpXvrMSlOZ5bu7utqgGw2AQ5AYBEcESXAcOJJCoRlxRpqR9B8oNBMTUoxiRqRCGpAgEUOHRgMNdDfaobrLV2Wlf2me9+/6e+zeey19OFkF/gnF8ynzvXjv3XvPPmuv/Vs/4/ml0uLS4vHxcbffH8dJoD0CBGJyrIB8hUqh8kSUZYN4ZAiQiEwa+l6j1mChnQDOuRFWo/FwMB56OnAOV86fO7U41242m7XaoNv1vaBdq58/ebJWrwdMS/NzPtrdgy4GOrJJUNVe4P/kZ28nWaa0f2qlnoNut2dRCGsyiWK63W7X6/2jfm8wzmzuGJhyJYQCWS6V4yy33Z6UuuwHwBTn2Tg3OYhac2q2Vb/7yd1u/8hE2aQ3mAxGzeb848311dWnnamZUysr571g9f7q4eHeZNxP0tGzjbsrZ5e/8vqbiGJ7e3vQ71lr+8NxtSa7vb6SnvK8l157+eGD1fFw+MOf/XRmZqbSaN28cf3WlavO2du3P7p56/rJk6cFencfPr5395ON9SeH+zvD48Gl85f2er0kim6+cO3qpUvozLkzK4Ph5PH9u3/63Y/CUuX6iy/tHw2ePlvf2dn8h//wv1icm83yvFwKpJTOmt3d3bv37k/PzDjnpjv1NE1Ho+F4PMlMvnT65J1P70YfpdOdmTMr52q19tr6xqA52t/fj6IoMxaE0KhWlpZ//Rvfev3WK939w8FwHCdJkiSVSrVcqXl+WLDgy+VSHEXW5CbL0iRJs8w6l+b5MJpkeZYbEyURAVGeTM+0D7sHSsp2u2OYa9WmYH1y7nQe8/WVs5/cufvo/iMimpqfAoHzc4uN1vSHH328MDXXH+Q2TseDcSmUowgtZvcfbggUrUbr17/xKzeu31BOHhz0Pnn4cHVj++D4IPTEf/A3f/ub3/xqKQiA6Gvf/tVe9yiN4o2NjUG/PxyNyqVSlsSnz5zxfV976tq1G1/oalu4DCitgFkISY6YGVCY3HjaI8fOklYeWIdAUikBKFFIIRBYCoEaBSliNuzy3BhnQSAxM7OUCiUgg1IopYzypCBLFx56zOysE4hCSGZwxMCohSTrinBWX3uZyVGK3BpgAFn4IlgqAhkBpYTNja12EFYCnwEIoWhwEYCBueALAxEwERODMwZRSinJOQHAxM5aqZVjYgIhC4jDATAKAcjEJEFIoUqBL4REYiYyWZbGia89sqaYKni+T0yjyThNs2F/yEwv3rq5vbZVLldmZmfu3b9PwASgUVQqpVJQSpMIOH//vXdLYZiVTKlWGY5HaZp2uz1EFAKXlxdPnz59dHQ0LK5Bv1IOy6VyvVYHGE8mk9xYIVX3uFvMjoUQArFSKZs8QwGOKI5jaZ2zdm9v3/f9JEnTNN3e25manpqdnR1PJsvLJ6Y608ByNJ4Mx6NHjx4BAEiRJIkSsrh9KETgBwLREidRxKL4ABjJzU5PX758+fGz9bWtHScUIDuT52nSqNeqzfbezmG52uiPJggc+n65Wtda93q9K1euRFEkhTg6PMyzLEkSL/ArpcB12o54qlkTSveHo0BhoGW7Uc3yfGnlpDFGSGmdRSGSJM3JAqKnlZLFihVElGZZkiRQr0spDo+7QbnKjtqtVqtZ7nQaG1tby0vz09OtOB4/ffxk2B8C8cnlZQHy2draeNz91V/95smTJ/7lv/qXp0+tXLxw0RLfvfNJkqRa69zk3f7g2bONdrO1ubmemPznv/jL/nD0v/kH/9nTJ6v3799noX7j3/sbZ1ZOrz17+PLLrwik3e29LHd/+M//2WQyXDm1tLx04pWbrzrG1tEhkGB2vq9Hw9H+3v7x8fFkMn7llZdPnz7rhdVnmz+WUt548cUXb9wo2KlKB9bY0STKMtNqdUqlShxH9+/fL4TgaZpa4oyo1m4h4/7x4eKJEw9WH07Gx91ut1COFU5dpUp45fKVpfmFvb294+PjNM1RiHK5PDs72263nXVKyoKvub2zOxoOUEgvqAxHo+F4NJqMpVIg4Kh7PInG2tONZv3Bw/udZtvTOs/zSqnS7fYO9g/GUVKpVAXi6VMn29Mz65tbg0l/ZnYGAPf2dk8snxj0h2k8EsKeXrl68sTc0yerslG5uPKlhw8fXr1y7Y1X3rDGjqLxvYf3Dnp9Bp6Zm/7N3/zNesl/7513V06flhIE8Hg0fPx49dq1a8vLy49XV1fOnPngww8/uXenUqksLy/Pzc19oastAACwlMoRRZOJJ8tSSWAQQDZKiEACe9rzPJFmEyBw5JClAKmllh44y8Y5Yxw4lkqBFKLIJSSLCOQck9NKe56XsbXOZllWIERCCHZIxMzIzMCEgB4CAXphqV6rmdykecYIUilGZmCyLISQAL5QnlAl34/i+PC42zh5ypgcAJwAFiAJGdgxWWsYJQNY54hBKk3Enq/jPLfkDAvhBZ5WbBGYoKi/jvg5usIMpKXSUjIRAEoplZTguFGtKylNbpnR5sZZEwReasw4iom5UinFWTqOJgdHx7v7e5VK5fDoEBBbtXqapoNer1QJGfjipctkOYkeEZF1rnAFS9M0CIIgCFZXVwv/JKVUu9VSSnmeL4rEGCE8zyuVS/3+YGqqvbe3r6SsVkpkcgQul0K2NokiT0otpfY8Au71+0EQVCqVtfXN/nB0dHhYq9W055ODJE2iOHZEUZoAACBaJkfERKUwtAjOGhZoiUxuhZDCWt/z5ufngjAslcuOUSBGcaKVevX1r/R6xxsbW1L7d+49AJe9ePVKEPT3drYvnj93+vTpzc1NY0yj0fC0V52tr65tp0laK5UAhEL+8usvP37yFNlynkg2Noum2p04Hu/vHxLRUbeXsyQsFMyqSCMm54rJYRAEeZ6Xq9WDgwNrrU1jBQ7BTiaD3/hrvyqU7ExPaw1Pnz36yle//v77H2Vx2qrU93Z3NcLc3FR/cAzr8NLNVza3tn/8F2+fOLF4/8HDPM+LyMJmozUZRY8fPzq5vPzSrZv9Hw23dg7fee89QDx96nS1Xn//3V+aePi1t95sNVtra2vf/9Pvb2xuvvnW165cufjCCxefrK5Gk1Qo/8l3v/tkdfXWi1eFgPEwera2nuf57/3e751aXrKWNrf3tdbD4fCN118Jw9DmiXMmimKT2353gCDK5crR0XEp9Bm6RRRelKS9wWCU5YPJKI2SZqPJko66xyVfeZ43Go2cczMzM+VaZWpmCojXt7byNMuzfDQee553/vz5wvg4TuIsTX3Pt+Q+/PgTQCGkSgwPBsOPb3+iPO/EyROj8TAsqcl4rBQcdY9Gw8H5M+fqtRoQWWO2trc2N7eV55cq1TPnzu0fHX10+7ZxNBpPDg6OPM8XQiZJEkUTATw918rd+On6aGF+ZnA8mGo2SlevXbx4qVwOhZA7uztb+3tBWJqa6nhB8LOf/3h4fPjr3/pWu9U4Otg3eTrd6Zw6dfLcuXNPnz4NwxARL1++ND0a1BuNzY3Nf/Pd736xqy0zIBaBfQBQ5K/4LCU7ym1BfQVmKZSSmokQlDMOBLvcETAxJ8Y6Zh0oLaUXhmmaBmGQ51kx838ukYgSQgKAQo4iRFE4POccETrHzjlPexKE1srzPRYYZYnQioCUpy1ZLTQqaU0uhfR9v+KHcRJn7LaPu532dKNUcmSAyAIBKER0jiyBKxpVgCLyy1pnTE7sWAIyMrssSSSCRGGZC6U/EAshtBZAFsExoWNw1lQbLTKktFAoELEUBINxIhEJgZjjNAn8YNjrWZFF/dFUZ0qnSb830OxmFxf2d/d2dncD3/f8QCl17tzpdBKNR1GpVO6N+wgQBEEcx4hYLpfX19ePjo6eS8IQx+MRudwad/78BQAoOFKO7OzstJRyZmYqy7JqpTw13SFrQ9+LJmOBHJbCIiRib2/P87ygXOr2B4w4HI2ft5BBWKvVcmvTLDfOoBCAwAC5yQHBC3xATPLcERtnpZLWUppm1XKp06gNB/1JFD9e30KhsnjissyT5eI9AqBW6MhVgqDX666cWJjqtAuv20KqPz09XQqDR48f97v98rXK/fsP0snw1ZduMjulpAAYj0edTqdUqezt729s7QitpfJZ+WQsASiltFJSSpObqZnpOI5Ho1Ecx+VyeTAaRUkyHg6/8zf/5sP79w/2ts6dObG29vStr31VKr21sfb48eOvfO1XLEO1Vjt18gSZzPdV4vLj4+7B/rE13O0ONzc3hITTK2eSJN3f33/27Nkbr3/plVde3d569uff/96Hn3xUrrYy6378s7dfvHz+d/6D3260Wv/6X3/3V7/11TzP//RPvq893w9CZuodHS4vfL3VaMwvLm5u7X/wwScPH67Oz05Vq6V6vdbvHm9t7Jy7fHF+fj7Pc+uo2+0667q93nA0yrIsi6Ptnc0wKDHBcbc3mUST8SSaRMaa/nD46PGTVrPp+35q8jiK93Z3fe2dP3uGXG5tdjjs1ev1Tqfz6NGjOI7HSby5u3O4f9BptU6fOtVsT4Wlcq1WC4KgcAfPsrTXPZ6fX9je3n22sfXx7U/9sLx/PFpYXLToCRm8f/ue53lBqLQStXLQ7fVeuHwx8IJ6uRKWKpNJNJ5MhpPxzGyVgKyzuTHjySROM+15QhhEYUwex5M8SxZmGtevnT/o7e9ubcHFF86fOPvaSy9led5sdcbjyBi7vbfb6/dfPXvu3v0HewcH1WrthTdeu3rlcp6n1WppZupEu9VEqR49euT7/rVr13Z3d+M4np6fi6JILC3tbW9/sastIhMV+k7jRJGeDYSBDpVS1llmliiNicGBEFJJxQxpHiMIYDLOoZDO5sjOV0ILRcC5s0p71hgCEFKSdUUCjJSysHQicszgHAEIAJQChKcQkJhRYpRnkzyz5IhICDYWQIAlUloZdpYotyYCmGRJ5EzGaqfbbVbryllgJmCUUEzJpZZMwIBSCAYsDp7OOpTIyALQEQERCpBSO0appGAhgAQjCPQCjwnZgRAIBAKwWqsFnheNJwCMDJVSJYonCKiUMsxMJAmOj48qYTknZilEqEdp3BsPg1JY91SeZsbaIAirlWq73ng0fhJFURInIDBNU+dcpVw5ODggtgWl3BhTyGqZbLlUzbJ8MBgAgJLy1OmTvV5PqmBhcb7X67XbrSSOmrVaKQyK9KoojkbjMSB0Op25ubmN9Y0kyZiZmASiEMpat7e374hyZwAAgBEFMeXGhEEAiGmWpdYZR46cyNE5p5TytZQCFhYWfvKztzPQDlynXqnX5qXU61tbvvJQSE+Kk4vzi7PT7XrpzMnlvT1VrlQ//fTTer1er9e11r/4xS+Oe/3XXn/96ZNn9WqlU68dHB7NzM51OjOjKEUhrXPbu3u94diCzFJykBVjPRQopURAlxmJOBwOtdZENB6PF5eWdnb3tO8LwKO9/dMnTvzy3V989SuvbW/tHB50252274fT0zN3Hjzc2Nu7ePaMXwmUrxhc4JeliNY2n45Gk73dfd/3u/1hqVztDQZS6aBUZpQ//enPn6x+OugdGxLycIRB+dTpE3/tr//1CxfOrz5aXTm1fPHy+Z3tnTt37p04cfq3f/tv7e/vNCrlLE329vcAxU9/9vN/8S/+qD3V+d2//7s3rl4wJh2NxrV648yZM572nMkotwcHh71+/+LFi1rrd955J9BiOOo3G21nKM3yNM16vQExT6IoiuIkiaM4WVxccsQlP7xy/tKZlVPTUy2T5wphZmYGAK01p0+fHo/H9x+vjpOoWW8UTavS3omZ6WajUSggrDEHB4cuzzxPCyFff+PLQaX+wx//LM7pycbOzNxs76hfqtaDMOx1j0eDbq0czM+0tCrVqo16rbb6+MlgPBlNxotLi8snTm/v7gxHw8Ojw6AUDiaTcRTneSalILIowFEe+rJ3fFBvVUP/bKvWOXNy5fTJk0fHx9rTI6Zuvye1OnfmvHB889KV5e/82l+++4u33vxKp9FM4ijwZ2ampphpOIk7nY4QYm9vr1qtvvDCC1ma5g1DcwsvXLj0Ba+2AMBSYqlcznKSUpAziB6TI4eI6IgEFC40QkoFIBCRGbI8B1mkvVqlNbAzxvier6QsxF2fK5AEoHPOOGYuYiIQAaUUwGCsJUdFxQclwVOpzQERBFpnHTu0LEF4SjOILE1BIDDk1prckBKMEmRwNBn1JsNOpSQdA6AlZgAlhUUAAGZCBAGCmSWABYcACMAFOgkgUSIxACHT86E2gVRCAOaZLfRy40kUR0mr0axVa8hULZW1VElOk3gstfJLAeeMgMQ2CH1GdAjS137gp5MIUA8nE18pz/eq5Uq9Vj3YPzg82Lc5MRIDC0RianfaWZpZa1AAABSmBwV+yiCr1WqWpdbaLM8dEwE3m3VyVCmXfM/rtNtJEgM5RJCiQHLI83S1Uj1/7vzuzm6cJMZaQBRCGOdQsMmzPMuZGaUg5kKYS8xayiw3yOycyxw5BmS2jpicUKpcCpdPLt998CgjZkGVUvDai9fn5ma7o3GaJnGaedp75dbNYb8beuLC+bN5lqGQ77z/gVKyVK0g4Pe//wMpxYkTZ44Ou2mSr5w8TSbb2t769MHTOI7PXbg4HI4fra7GWWYZrGOUWoAgZoGSEZwjZofMUqqjw6NWs1kulTylbJahgKlO+2uvvb7x+HGjWpmZmTk8PDru9uzhsNHoTMbpqdPnHq0+Pj4+zk6ceP+jT9Ik3t07SlKzu793eHjYarW0J0+eXi6Xw7t3700mUZqmjWbtT//ke6eWln/9177zk7/4web2ATOUgqBZq5vcPFp9cvfeHUe0t7ezt7u9ubn+l3/5i6mp1t/+23+r5KskjR6vra9tbsdpjlK++ZUvv/H6q4GGzfW1cRQJIU1mlFbk8m6/q7SsVcvKC8qlcGtrK0vj5eUlBnFwfDSJJmmWe57Wvjccj4QUS0vL2tNSynq93j8+unjxwsrpE0xub2+7Ug7mF+YnkwkzNeoNLeUrL70kAq/X63meHk3GArBWqeS5GQ6H+wf7d+7dY8SXr77Q7/WfPnvGUtcazfb0TG9tV4I4PDzW2iOI9nYPmZlIxKktl5vAqt2aStLkuNd7+933/FJZ+8EPf/42A6ZZPpxMTp1eSbL82ZNnACiV8DxRDv1rF29JSBl49fHT7kH35LeWy6XKT3/yk9m5udzY/YOD6dm5a5cvt5ptDYDkwnLpjZdeWjmxzOxCXxG53b3daqUqhNRaO+uMsf/qX/3rs2fOLM7PM3Oj2dje2vpCV9tisGRMHicTxADYIhIxOespFAAMEtMsAXQsgJkFSgIGLYQnmR1YJ4V4DnY6lgzgWKB0zAKwcHizLgdAiwoRGYQUBS+2CPoVzFYoRC2kxgxy1CxACGRkyC0REAggdgJRokDCkg4D5WVZlpo8kB4R9rPJk6PNcv2cYAQri7AWxxYYJCIAO0TpQDjFggicA0DWyEzkyIFDLdFJzhWzD2yFIGCBAplRgCWbjFMhlbPUi0ekoVWt5jb2pLAeal/lAFGWVMtBlsVQVkmSlKWvlCYilFCul/OJGXWHeRSdOXWiXq1NJpPFxcX9vYNxNDHGtDrNOI4d2TiexHEslSy2gSAICv8OBEmgraVapbJDu1J7uaOchAekECTDmXMXPA15Hu/tHkRRxIxa+dNTzfPnz+WZ+fiDj/MsN9aSYEBw5AxZZ5wjckxY7JzPFwIIIai4M+Sss0TCEQM5JPKleOPWS41G+Zcffbhx2CepOYtPTre+8tob733y0bsffuSIbWYq2gsFV2fbK6dPPX7y9O6dB+M4H2fx+XOnozw/2DkA1MaJB6tr4/FYCKGk1+12t/Z2LLPve9G9h3EUE7MDwUxKCiEYkSxxklqB6MgyULNRj+Ikj9PyXEhsK/VqvV7f2Hw61Bj4l5eWlo4Oj8Kg3huOBpMxO310PHiw+mzl9NLrN2+5OM2j/Gc/e/fC5SsPnu24PBqNhxcuXmi3271Bf2dv++yZ061GMx5ng95we2vd9/RbX339G29+6Rtvfvnx2tb/8I/+f2FYnm7V1jc39g/05u7ur/36d+Zn5w92dy9dXGm3arduXq1VKlKYbi95+ODx2+9+WG1NN9qdc2dPBBIUs1beOEmiJBEEvW7furQ36BGZcskbjofj8XBxcbnX6z3b2CtVRkqrZ1tb4+FQKzk7M10O/fnZGWddmiZz01NKiZKynVZ5NOhmedZoNJaXlweDAbn8xIlFJaQgi1rlAo7A3V9dW5iZe/Xl18aD+MMP77Zb1fXt9U/u33/p1dc9v7y5sTkYjhLLw0kclColXzMDIFKaTSYxMFsypVrlN37jV10yOXf6TJrkR86GjeapC5f+8p13n65vAIgszR25JEm7/SEATLdaxljLHE0GnWp5eXrKD8TD9SdAsHxiidDsH27PzcyHpTDu9uZmZxYW5oQQ5XLg+17BSLt29TIAp2nuBzrLaDAc1eqtMAjHoygMw73RvslMmmRplkRx1J5qzczNfKGrbTG/F0JopYXUzpGQJKXIc4caGBFRCCWJHDkHQELJLElTmxahhUoJa6wxmRQIEgBAKaWkMmSdcwhQWFsBQKNSLiyEjcuLqTczM4NSipHDMCAmsCyFCHwfiGMTKZSsZAGnMrBSCpxwThCDZOUTCyENYlBtCpbd3mC61mAmLuTIjlEoycDMFtkQOKKcyCliRnDGIrOQCGCAP+sKhWSWDEAEKIQUiFj4QgAQAUnt5zY77iUVqUPtDxNjXD5JUyGBXIJsfa0SKQsClae8Zq3GxDvHu0rKUyfPJJOhszYMSs658XhsjNFaj0cjQCxyvIUQhfVcq9VKksRaW2h7GHg0HoelUAjUnpcm+e7Owcn5jlbK03h8vKu1nJ6arlSqg8FYCFxcXFhamuv2eoeHx3GWkiVHVJhGWHLETJ+D1EX7jCiFtAU9mbkYiDMzMwlAANBKXrl4MUni9fWn8TiJRxMUYml2+uWXX7v96MmdB0+OjnrVWqXVqNXCMEmTK2curq2v3759J5pkyitXytWdnd00iU6fWDkW/dUnzxKTJUns+8HH9+6kWaa1BoGWaDgafT4/KJwZmFkpRVmeJkmtVsvTvFKvNup1iZKnqN87LpdL7UYj9HWr2djb3ZNCbW5t7+8fTs/NDkfRcDxhJ5+tP4uT5NO79/7ar33n137tN773p98fj8d373w6Gg6OD7bzPH/1pZfJOnZ2PBz/8u33atXG9vZmHA1B2r/39373rbfeunfv7sHh4e2794UQly6em5+bOTw8nESjSqVUCsJ6rXVm5cK3vy2/9KU3PF/nJrZ5vr6x+eFHH9+5dz+sbrfb7XNnz0mp4slwNBrHcZLn5vDwsFYvxfH4+Ljb7fayLC/gGs/zhBAfvP+BH/rXX7wuAKY7nU6nNZmMgEBJBMaF+TlrTZbmi/NzSZJMJpNyuVypVEaj0Wg0ajabpTD8xS9+EYZhe2rq/uNHq8/WB5P09Mql924/PDo8PtzbmZ9qzs/Pnpg74WLzZGPnwYMn+90eST1J0yjLHRdHU2HZGeJquXTj3LJUwgPbnOkszs09efJ0OJns7O2zlJ3O3MPVdURXKpWiKAKig4ODUliqlSvV1pQx1gv8qbmZqdk5D8xbb7x5+9H9L7/xpXalOteemepMeZ7HDLOzs9Vq1RgTx3Gn3U7SZHd3Vynl+x4RIHIYlpaWlo+OjpeXT5TL5W63OzMz88orr6ytPas3Lpw9d/bp06eHh4df6GrLgMColOf7oSPFDp21KFgqzcxFwjYwBn4widIsz7IsM8Y5YClUblIhlBBKKldIC/I810KyZEcklWLnpJBKCmauV6tEPB6P2JG11jonhEREAieksNYWk7pKWC4FJa0kGIpNasAKIYqKoLRiKRVrX3klqdm5SZwQmXicZEDpOC6dCRvlsuHcEjMIZAEskFg5Q0KwVALZkDHOCKmp8OcFAHbA5EmhQfjMmSVnrBMkhC8lIvJzvrdkRuuItZSZTU2WDtN8nGRCaYFg87gShgL1WGBQCmZnpvM8y+Pk+KibTOIsTQuW/mQ0nupMf/rpp8aYQiLJAL7nCSGKGJLCGL9AtwuzWqmU7/u+7wkhK5XK8WCipAbCQX+4ONvUCpN4NMpp0BsiCkQol0t+oJ8+e9ofDKIoIcdELIQQAnNrnu9GzMxA5Ji58Ie2zhIzCixQiOKVFOm5jHRqeTkI/Pt37w17A5BiplFzRG+9/sazJ2u3HzxMsuTE0sKZ0yezaHzx/Hlg7vcHDx8+mJub29s9EiowwMbmSnlxlt++dy8nl1oDCGkSEZH2NCMAs3Ou8LHGz67Pij5rTyslSoFGUvFoPHPhfPfoqN1sHnePjg4Prl29nKSJ7wVxlBwcHgKKJ2trfr3e9OvAOrd5t3fcH/XCIHz7l+816vW19Y00TeH4+OLFC6GCCxfOX7t69c9/8IMkTpigdzza3ty1Njm1svx7/+A/8rV3eHDw6Mmzd957b3N7V2lvdqbjbPbp7Q9zYyqV8v/lv/nwlZu35udmr11/oV6v9fpHSRKPB9nu3uH2zl5/0N/v9W5cv1Gr1Xd29uLJcHt7J03zOMlu373faDf6w+ON9c1oktTq9Wa7labp+vr6wcFBt3vsBd7O5ubiwny71RoNe7VKeXp6BhHLlUqWptvb2+VSKUniMAynpqY8zzPGDAaDOEmSOHn2+Em701k6dfLxk9XJaHxq+dSV67d+8JO3Hzx87ClVL/s3rr/QqteP/ON4ED8exbcfPt3c2V85d743Guzs7U3iSRiUuMjOZlpZOf3Ki1f6g0PN+aWzp589e/Lg0bPdw/72znZv0CcEJBHF48lwRMy6mNk4V6pUSuXywfFxUCr1BkNGsTy3OLu4cPb0mX6vFw8m5fmThX98UWoLDZvneVEcFbSlJEmMtRsbG/V6vV5v7u8fAIjxeLi9vbOwMO95Xr1W7XRavu+trq6urq62Wq0vdLUFQEDBDFmaG2u18FGwQMEonHNgERCsdWkaW5chknMEiIEXWJdp7SupA0+lNo3z8ef9iLUWALTWqTF5mklAIcTB8TEzASIBkwCQQgESoVbKkCEiFEIKOYkSa6lWqSrtSTKWHcDzDFciQkYml2Zp7mKT58TsV6rodJKn5IV73X6tUnbMKJVhdozEQiBKwSSUE8paByBE0YQDW+skSBBsmSSjQKEZyVhkEAKdM8ZYZhISpAQuIBGUSiiJwAJZFMCrA2AlAImUwHqt6gjSLD21uLj66OHh7p4Wvu95SRKnGQuA7nG32+0WpsvVapWiSX/QBwYiKpfL5XJ5MpkUFtrPB1O+3263q5XS/v6+EKJcLnOc1aphp1GemZpCdnEUEUlECsOgVCqdOLGU5RlK4cgBAkqBwK44mxBxIUkGAOCCRwUARFTUfWeLyWRB4UUQIFFI1t3j48lg8M2vvzU/O1etVgajwTvv/nLt8aOnT9e+9tUvL87NxeNx6Otu/3hvfxcIz51f+dKXvmQt16qtvf3uQbebZOloEh8cPUytyZ2z4BAQBEqpGIERgRkALBEAk3MSi/EAa63TNPU8z1NyMh5JxNnZaSWLJIvsxPLyRx99sLW5MT8/V69Wl5eWe91+lKQqCDe2t4fjJMuZGOqtxuqT1dOnzxx1+2//4h0imyVJtVJp1quvvvQ3EPFHP/zRsydPa5XqwIzyNF1ant9af3zp4vnTp1b++T/9Z0ziyfrGwydrlUoVER49uKclOpOztf/lf/F/eP/9D+rV0sLc3JkzZ4g4TbO9vcOdraO1ta3RJGZE7euvvPnmeBztbm5kcbR/dJTmDkA8ffrs5OnlPI+Pu30A4RjqQS1N0v39AynV7Oxsmsb1WvXUyRNayZl2PU2T3NgwCHylWKtqpQzApVJpenq6aEecc9a59z/44ObVazeuX7cSN472M+cWlxavXb25vrG7MDX18P7DXn/45dd/tdNudQ8OFhcXjOPHe3t3Hq4aI8T6VndwaGwy1WncuP5ikqS3b98hl5s8Aqa56anzZ08xwChOn25ub+4cZXk6HEdpnmit262mp9VgOEySZGlhMQwDz/eO+8cH+7vNRuXk0uzTJ6vJ8dHG5vaZs2dn2zNBEDSaLT/0S6VSkRlR7PQFw+Tg4GB/f79WqyFis93a3Ni6e+9hvz+q1Wp3P/1kcWlhyrSzPB0OhuVKSQgxOzvbbDaf++h8cS9EBpRCMSMRMIKzzlgDIITQwMwMAtE5S0wCCIB8PwQQAqXQ4HmhBK1YZS4BRK11Af8prYy1KFBrTcZaa40AxwSAQqADZAYPZRAEmUmFEI4IBLJUjJQYC1EMKFAp4SwAFA8eEYEjgewIDDvSkFlTr5ZcZlEICsJBlnYn46AcWCaDInaUWMcIQrETOMmzNM0UciPwSkIaYGSWhTQN2BEpVAqlIHDGKl/lJk+TrOh+GQERHZIEYEACQBQoAZEInELUUmgB6WQyHE3CUn0yHm+urR3u7oWejyTJUZ6b3CTz07PbW9tCiDAMp6enx+OxMbbZaEZxnGdZGIafN3fWWq21lNL3fSI2xiCWWq1WvH/sBbpWC5rNqpIijhOFnvB968hat7S0UKmU95/uRklWhGTkuWEubuPzjrWQf+DzfwEz82fNLH7GGynOE0Ac+P5Uq3liafHC2bNTrWa1FLaa9dGotDDzLc8rxXE+NV1H5w53D9c3t06fPOmVQi10kkaffnrbOapVW1p7REzEW9s7aW5Qeu45hvQcygAuNgDGz5akI5JSFC2PQBwMh0EQpEnSajSUFIGna5XK9NRUGJYr5fJdpUyWAruZ6Zk0pd3dvaPjnmM+7ve73chk6Ze+/NLUdOvo+OjJk2e5sSY3EnlxcbEcBgd7u++8/XYSx47IWhsEYTQeXX3h6rXrl/5g5/HKqZM/+vOf3P74jnV2mJjW9Jyv1enlxeX51qOHd4Xgv//3//6tm7fiSfLGGy9ub222Wo00zUbD5Ohg8OTpxrvvfbi1vSN83ZyaiuLou9/93sryfJYke/v7Kiz7Qdgbjje3tpWHUZp4OpSOsix1jgBwe3tHa33r1usXzp9DYCBnjZFStCpNIVAIoZ2cn5+rVauVahkAoigaj8e9Xm9qduaNL70xVWtWK9V/9E//53tbz86cPj1baQ+Oj+bbzZlOO0+Gh73h/Ewny+LzF1aiKHnn/Q93Do8r5Uq/Hx/uHRoad6aqSzNTH7379q1bL127dHY8mgBwdzD8xldfDzzs9Se9UTJObWpzQJia7mhPJHHcabayPFc4CbS3uLCwublZCvXsVLPZqFbKgU1HStK1F69Xy1UEqNcb7U6HBZZL5bW1NefcVGeqVq8VwNEnn3yCiIuLi9aYOM3u3L+39nS93mhWKrWd3f0L506urJxSSjJzq90sCDzMXOSrf7GrLQNygcCq3OQEOaAw1vkeSi0JMXMmydLcmNwkSoGntFaaQGsBApzNTGRSUOD7ARV4H4IUEh2UVCgkG2eskpnNQTERCxSAyEBaeRolEzEDECr0ANEhEDIAJCbTWkmtBefAYHIDDEoWUY8otbAWiJxE0e31hPQEwGQwSp3ZEccrp5ctWSPFMElHmXFSAlHOIrPsCxn6gVTSOrLECiUxGQQUgsFJoEDrRjkYpBNHbIhzZz3tY6GdE2QdEUpAAOTCGtcyI7MC0igkCqGkczZNspzM9tqGJqyGVeOsliLPk3qzSux833fuOcJFRFKINEnZESIWhvme5/m+PzU1PRqPAITSOix57XYbmZTyrDFz051Wo6K1mkRJluSeXzKWHXGp5LfajcOjA+ccEzhbHESgIIIUJmgALAAZARCZocCFUUqBRf3Vz9cEAAMIiUjW97Wn9dbm5g++/2co1eLi7FS7fuPqlUq50mp4zGk8SaSA2Zmp3aMjlaZxYo+Pj+LYVGv1nd2DySRFZmAQQgnFxloEQMeAAAgIIJRgYuLndkTMJBCdA+2Fh0e9wA+OjgfnVtqzbaU9JbXc3tqamuo0avVKtRrFca3RinN+tnV42O0LqY+H4/54YpxzTEiZyeLjw6Odrc31p2smM1maaqVOnVjOkmjt2ZNGrRp6anvreH5xqVqtxNG4Wp7+zd/8ThyNq9Xqn/zJn8aRSbMsrJRu3rp1+9N7R73D3/yNb/6n/+Hf3tlcPz44zjO3v7N9+9NP2lPVaDJqNlvWkrEuNXTc7+7u7xiTVsr+jauXHz24m46Gb7zx8vH+/p///u8vLp/45jd/pRR4vW5vZnZqYW5RCmWtNVmSp0mgxcnFhfmFxdn5GWMMAkmAYo8cDHv1eh1Q7h/stdvtRmu5P+iPJ5PQD4j47JmzjilNksfrz1bXno4nk0ZY9qQ3iCb/5o/+6Pf+o/+42+2uLM51Ztq7uxtxPyx7nh+WRlEc57Y92xlG67VKONVu37x++Uuvvv7zn/70q29+dXNr9/andzPL1prD42MAPu72333//adrm9VaDQANO0HQbLXqjUa9VlOeTpLEklteXpqbqWlPLS8tL87PNcphp9moVRu7u7vVSjXNsuFwWKtXmfnJkyeNRmNmZkYIMZlMiOjkyZNSykLpU3Chzq2crdbqvudXKhUlHDnLAIPBUAiUUiilC+Gc7/tf8GrrGCUBoOSgHEoJILXNmICkRMtgEFOwOThDxCx8LzAghfbQUCBkBsYKmZrc12HuUkBwbD1PhyLQJP1AOu3GaWwBnTC+RGstoPQDnx1ZYimEUp4vZOB5SZYkkHMxt0PIrRHIWnnWmGJWg46lVFoFxlprLRF4ygeQbG2AAgAZ9HF3Ug67rbkpZoOCsjyv1ZslpcbGSmFCz68o7ZxJLKFAT3vG5AykUDALFuAoU1JIptQ5JyQLhUIiopIyZwICJOEcoQIlWBOD0ChRo/EAAUROGQC63KYZEQhHIooyRJKB0kp6WmRpmqVZlmVxHFer1TRNi2ASRizMf51zpSAAwNF4wiwcg3Wu2ay1Ou3u8fF4MplqNWZbbaVEtVyVUpqKkVIeHXZ9zz+9crpUCsIwnJmZf/jgSRx1EYRSwhI54oKBAAAFJgNUNLsMEoUUzwN2qDBie34hQKlURhDWUZ6Zsxcu7ff6jzb2nmzsPnm206iUtBQzM51TJ09OkowZFubmR5P44ePtvd29IAgzM85yFyXxc5TAOYmSFLjcCEAhhVCKmIgIhHTOCSaByERSyla7s7OzN+j35+bnO52paBJfP7vy8/d+2Z6d7o+Ge/sHtUqlVK6kmRkn5vHms0qjORyPlEKb5ZaZiIGIXc4u++C994wxWZYZY6zJlk+vILu9na3BoP93/tZv12uVt999/+zFSw8e3hdkvvPtX/nKG1/64IMPzp059/jp0/bU9KuXXxuNo9UHD8e9o+mpxpVLZypl7+Wb13c3dh/cf7y5vvbd7323XK9/46tfiSbxcDgYx1mcp1ZQToaBZqc6l1ZW3nnv3aBSUkFw6dqNt77+9U8+/LBeDk+fWtZaudy2as3xZDLo9QW75fnpqU47N1RrTknfY6A0jgbDAZNrNGqnTp0CgEajEQTBeDQajUbdwfDcuXOPV1eP9g5Onzzt+d6777170D3+ytfeAk9N1Zs/+NlPqq2WDLx33nvv5Vu35hfm/9m/+ddxnLz05teGo8mjj2/fe/jg4c4uemruVEu4/Mb1C7/27W+eWly+cGqh5IfxcDAa9buDyRuvv7a9vb+zu5fmtlavvfLyrfEkOTg4iONJRjyeHFUrlThNVaDTSb/WLKO1zUZ5MhqgiVfmZ2c7U2mUPHn8xPP9IAgKfLbTbqPAl156yff9arVadBthGM7OzhajWmOMtXZ+Zro47UkphWClpEV2zpVKgRDC83yltCssBwC+2NVWIAMbcikzCHTAkhGEIAZnLQjBziCwUlKAx+Sq5ZpQwSTOpfKYnfZkmqUChLUkhIfISnoStRMISAqVIOGTNs5oLeIskVIJTzNCTlYzSiW18pVQQgrOERkVKgJy1gECC0AplUTLhl0x3pHA2tc+kErTVIqAmVGwtRaYlZTGuN2t3WazWfKlFR6WZIC6yspHMVYSlSIFmXMZOQQByCQFW+KCmaFllGUpStLaGCuE/IyWCygEGZJCKCGArEalgBhBICoUSkqppGVwmRMgJArLBpmcREAs+b72VZZllDuT2zRLCw/vogQ4JiFluRQGYSilTOI4z7IyACJa54RUvu8lkzipJgJA+5qcSNK4XCqFYcjMBwcHeZ57OiiXQ2Y6Ojpiho31zSiaFKANINoiFQr48ym/cwUaLlQhIUOkz3yOoSAjAwAAoRhG6Tje39491EqdOnmye3yQZ7FWahBFuhx29w4yk49GUbVW1Uq1252Nze2Dvf3nb805IQQxucIFgyG3xpITiNpTDFC8KgAQjAIL4MKLJlm5WnF5MtWuCs4DDS+9fOPxw0eDUa/ZqCXRWCKmWZZnZpLkjOLouJtmOY7HNktNSuQcAgoEADTOJWma53kcxzMzM3Nzc+fOrly/du2Hf/5nx0cH586eBSGG48n0zOzbf/n2iZOLf/d/9du3btzI0qzX6y0sLFx+4YXM2Lv3HiRp3mo1Fuamv/Or37hw7ryUYjAaHPSOD7q9cWIvX7p++/anr758y2bJk8ePN7Z2BlEymsSdqbkozpeWToPwfL8yPT394P7j2ampF65cGxz3Hz56VKqWlFJHx0cHB/tK6VarefH82VrJH/R7lXrDLwUZ0/7+fjQZA9Hy0sKtWzfLQXB4eOj7/uuvv/7kyZOnz54pKZF5ujN1evlEWCoJgSdOnHy2tbm1tVkJy/cePOj3+y9cv3H2xMnDnb1f/vKdar16amHJ8/xKORzHw73jzZwn7bqqNxulSmX92VpvOLx3/2HU7V+9fImIZ2fnvvzaG5s7BybnO3c/HUXxcDSSUg1H0WgcoQClZGJNu92qV5tEplwuZXk4Gh12GvUw8F649KqvvdF4hID1ak0qmWVpqRTW6w1mEkI4a5vNZtEBBEEAANbagrxERJ+r/BHx+SzhufpVMlO1WjfGGGPiOGEGz/OY+QtdbRGYBQjPk9qLcpYSPUZPewqVQMHIwE5KZEBUgi0QQa1cNXaUTCLh+84ZJSRrkaZp4XLoeTrPnfSB2fkgwDkQUK1XEpM48BOTW3IkEZRiYIcAiInJICMQKEkxkBQSCIgYAYhYK12r1uI4drlRwidCrbVSLITNMqMQlRTVSqXwaQUloyzb29tfWTnlyHl+yEKmNstzW/FDxUJbGuSUCpkzkbWh9gSQSXOttUUZOYqcYaWlI4FCMAhEqSQRAYMuZKOGPEBBbJ1F9CWgFgKFsIYyY4mBnLPkhBTS98JSpRz4zXKlUansbW93BwNDTiqpfC9NUweMSqFA6xw7mkwiJZUQIk3Taq0Rx0luXRKnes4LPW9+ejoaDyeTsRTCWtvv98fjcZqmSikGqlTL1uZHR0dpkuc5M4EUgrFI3CxaVv58yg8AUkolpJCySDyCggcGWICqokB1hbQESGDZMuOTp8+QMymRBCQm3zo89P1gnOaHx2unTp5sd9offXqn1+sXZb2o7MX4jZEdUW6NlFIqiUVWqEC2FhGstQSOnSuXSs1G/ezKqcPDfSDS2p9unxqPJ1kyjKKeRtNq1ceTOCtn5Uq11xts7q2H5UqSZUEQMjkgYiKBwlkLjtI47ve7aZp4nler1ebn5621R4eHtz+5vbW1/Z3vfOf3/tP/5A/+yT/54z/+k+5gsHTyxN/7u3/3hQsreRo/fPj46OioVq+VSqVn9x+MhuMgLAmkb3/ra512s1qpbG/t7mxvHh4NI+sePn6yf9BttOtRnGTROE7SO/fuJ4YIZL1eb7amQKhP7zzY3TtMkmxvd+/E4sLC7NTNWzeczQ+6R/1+v1QqRUncbDYX5udLYRDFYz8MRvHo5++/nxjbabfvfHq7Uat+6Uuvj+NIIiKA7/tpmk5PTx8dHREKk+d5lv3y009n5+dOLC9ffuHK0plTt+98+s5776aT+MrlK6Ug9LVfCkt3796rJ43Ty6fPnbtw1D9c21qTvuh0aqWSIuDx4FgifPLRJ2YUJ+fOLc7NNtutSTSpVau3biz9i3/zx7fvPggq1eFwCJby3DogKTFNqNVqXLv2Ajr74MEqaB5NugrThelatVxenF8c9gdCSCL345/++NKlS9rztKc8XzoHiOhyMMaUy+WCjVMsm6InKBZqAXYVg4Si/hZ1y/NE8d/Pepfnwexf6GoLAMAMxIhSKAECGRSDEFJ6WmY2VwKMYC2lSUFp31qKo6RaLlPuQCiJgsgBGSEKWZogdlKI4oPKjFFCgidGSVQYegklAQGFUApRMlnH5ISSyIKJkFhrL/B9FGI0GuUms2yZQCsnQAqN7EBrlaaplMLzPGtyCSgAC+9kQHTWUCnoJwkxB54HjhOyqSQv0IFQIjehRBYeKTUyqXEOwARCWQZSOrIuJkdCKRDGZgpE6PkgEKCY77ESUgIGSvtCFLsBAigUUgAgptZExjiBAoUuBRJJ+4FSuj3VDjx/e3evPxmn5JzE1OZZQgAQVkqlMIzHkbE2TRJwnKRRUCmBEFEUZbkRSmulwXEpDMejPjLVq6Uss6VyNc/zPM+LVRiGXrkcbG1tNBpNJcNedyQVAEKaZ8QMAFprS8+nU8XalShkYbROzM4hFhI2kEIAQLHijSNHRgAKIZiMEJ6SnpSCAQPPK9cr49EkR7F88vT+8dHqs7UsyxAlOWCGgpeCiIDgmAnB830oBnaIwGwtWWuFkgxA1grmSim0eWpNVq9WJ6MROCcR69VK9+iIyR31j04sLNUqpSiO1tfXSeq9o57qj4jR9/3ReJTnuUCUQrjcxJP49OlT9Xq1Xq8FQXD37t29vb3hcHgvjQWAzfOrVy599NFHjx492tzecQBpmgrEWrk0HPQGg8GZM2dQ6e2d3XK5LKXMkuTFV2995SuvL8zPxpPkyer6Bx9/zFJbwkE0Oe4dzy/PlSv1o/39JM0Yxe7+jvSCo143SeJ33n8XACvl8rDflRJ7R7t87fKZU8uJc8yU59nx8eHCwsK1ay+0W61B99j3pGXz0aeffHLvgZbBl3/371+/+oLN0kF/IIBLnSlgrlarvu8j4sWLF4+PeodHR1LKSRT9kz/4g7Nnz/7Wv/83Z2ZnxYN7Ybn8q9/6tqJLIscAAQAASURBVDEWGH2tp6amvvzml9e2Niu1WlgKtu7t3n+wuvr4UZ6lypOlWhVQlrzg8pXLN1+4iiafZEnaPX747MnczNJoNOp0Oi+98lJk7ScffWIzIwRZkyaZCcNgqlMfj7rV0HcuPuoeVeth9/ggmuuwsT/9ix+fPXNmaXGxVq1+/ZvfrFUrxuRBEFprkiRxjj3PK+TXeZ4DgO/7RW/r+/5zJriUhdu9lFIpxczWUjFlYEAmFqjDoASQlEqlL3y1dSSJFQiJKlC+Y0cEBMDASkrrQAlkJiHR83wsxFjWsaJKpRpHqZIKAIUAIYHYETlPKinROYMAWZpIKcDTMRknAdgBQrE7aalJgoEcGdk6S0TWSgIB6GlPCFEOS8wEQjFRnhslVeiXbG4FQhBoABACEEk7yDMjPFmIXHUY5IInZJ7tbC/OzRrriKGuPATpjAOFiWKhdNlqK3nCJs2N9ARqr5ckQehZQM8LFCmTGiBSUrqC7e+eW+oggae1LzHLUwYQKKQQWiAApNY6IUWg2aJAVBqVUBpFo9nY3d3rRiMjwCoBCqWvtOeFpRIT5ZnNrZEM1lgytpAOg1Imt8wMzH7g+9pLolhrIQUgWCEhTdPPulRmRs/zlBa1Wq1er68+fGYtak9al1lrHVMhzP0rDsBnmmpkYPqMkACfmW8iFjtZrVY7Pj5GZ6SSgqnVaAIxESJKqaDs+61yidMYhegNR5MozQxZQiIjQSKg1to5x8xCSnAEzEzEjgQiIFuiLM+07zsiBGw0GhKAnBsOutPtZpwmGlWj3jDWZFk2GA4qYbkz1yj75Zn2bJrmB8e9hFLjmNgxYL/XY2AphJTSWRtNotFwONVuX7hw7qOPP9jf37fWjkYjpZQQ+LWvvnXqxIn/zz/+fx8fH7Vb7W9+69uH3e762tMkjrSWve7x0ydPqrXaYHSYJKlSKppEnvK+86vfunjh7P7u7t1P7z99urWz09s+PugN+9dfeKEzVX/0eHVze/vxs6fvvvNOlOTVauOwe0gFUJ6RVDLLcBhFQaBazQAxdxRvba/t7nettadOn7529Vqj0djY2BgNuuNhfzAZ9uOo2qi9euO1k4tL7Oz21marVv+z7/1JZ6ozOzc3PTW1srLiaf30yVObOwTo9/uXrlw+7HZ/8tMfv/P+L2+98sr61sZrr7yqlPK9oFapFuFM40l0amVFMN5//GhtayvNqFGeXrl08v37HzDopYWlv/5rv7GysDzuDoQnVjee/Ys/+jeLCyebndnHT546l42i4V6/x5IcO5NMUBFwnmf55ubjKOqWfGHtOJr0s3x05eKFSqnmab147tyN6zcKi79aox6NhmHoG5OlaVbcjiJrsmhgtdZF7qRzzpETKIr2tgAQiqNSQclwloic53kgwDmnPW2ssdYKIb7Y1RYRQQgWHkoJyjLk6Ag5J6eMZQdsGSQ7ckpIZCmw4EWiVLJcLTMZpUoe+5DEWZJqT0sFcTLyfc8RssTYGhQMCqSjQpXP4BwRONZCS0QgtsyIggBYUKnkxVmS57mSipAdk6cUMiKLQIUggYmK+WOWZZnNcmeFFkzEiCBFao1TqIUaJknHOEAIAErEToieiVhg2fMVCynIEFjAiXPWUegFmcmiNGOhhVDOUqi1VEJ6YpzEmXOGANEDRI9tlYXHPAFg6ftK+FqwJ8gSG+d7HqJySAAgtEYQxtKdh/ezLGME4esg0EorKVUBRpnMSOu0FExkyIJgkCK1uQJw5ARAKQhqpYoECY6b7fp4PEhTitOc0BITAjBBGPjW2P3d/Uq15lzhvMCpySZxXBBsC1GckhIAmEgACgZgeq5IQUBAZmYpGZRElArJ2u7hwauv3Mzy+Mnq06XZpZXTZx/ee7BzeKR99HRgc9c7HAih0zQfT2Km54QUIrBsCic5BnSOPr+stSgEE2itQCAi+Or5tKxeDkPfPzw8TKI4TfP5uYVet4sS4lHEztVKYbVW0QLrtfqjJ89W17YGE+MYyTrHpjDgUEoxU5LEJs3r9arN0/fff8f3S8PRMMsiABLEwgkydOH8xd/93d85ONzf2dm8NHcpjrN2q+mhm5lqJ0nydG399r2H+wcH1Xq90Wor329NdWamp89cXInSUbd/NImiJ8/WD496SZQc7x9tlDfOrJz9wQ9/9KMf/HB7a2tr6yDLjR+GAsA5AmZrHCiVGbs8P33zxevTM22tcH//UHvejevXtNZHR4e//MVfRlH08Z1PiNzVa1dOn1mRcWVtc3Nra21tfeGlWzePDveGw8HM7OxwOOj3+48ePhxPJgsLCwQ8SYdxnHz00cdXr1795le/WisF3/uzP/n0449f/dLrB0eH27u7/V7/+pUXLp893+v3P717J7H5jWs3PO2dXF5+6ytvdhqtxw9XQcGZcyuPHj1aOXGyWirt7m796Ac/PugPj3spcT+fvNtutpqzHdjfGhzuuyRGMtWanp5vJ3HW7/crlYq1bDWG5frZ05WFhbkTiwu1cuXsmTOzM3PFOKHWqCsUk8kkjpNGo4EoyuWK1noyiYpSG4ahlIKhODQKJiYEJZVzDlEQOWscIDrrhJBaK+ai+D5faaWwXBzdvuDVVjAgAgoGa41E8AQYa6yQuZAKJYFw7CRKgTrQARKQM0nkpIRmvVat1pwLkyTJjUvBaO07SgFBapklWU7sUDBZpSQAO2eBWQgEBHZWoJSAuTUIAgCVUg7MOB4jC2uMzyyVJGJiViilkOTIk16pUkLEXr8XTxIBkgSBADJERFqHnvI8KcCRlDqK43q1qoA1QEYWAJSQvkONYBTKxHgCfaWctTJAKYRlJoY4TSm3Je2Vy2FGCbmcWSIoTysBUPJVTUoGsihACCVAeshCpGnucpJSCUSpFQAKVM5RnmfGGkBWSimlQQghBQAQs7E2M6k2RvkeAxtjiJgQmBiBHRQCMEEMxJBkWbHxjaKMAZ1wzlgB4Cnt+4Gz1veqAOLp0zVHLLQ0ucmcKfizxXEeCl8hIdkRFuwDLKKKEJilEEJpVJ5gEuAQXL1WsulkcX6mFpaSKD86Ouj1+1Li9My073mHh4fWOCllbnNHBACOnSNHRITgyOXOPm9MAAPf94JgOByCQOscSqTMaCVMni7OzzNbLUW7UaU8XZybESgmkxEjSU/GWVQphWdPrcRxVKqVHj99+rO3PyARZDla64BslqZCCkQwJmeiYX9w6+aL586ufPDeu/fu3kGIGBjY2jxHFs5yniQP79/97/7b/3bt2ePDwz1nc5PzxfPnb1y93Go24iRZfbre7U9K1abUPqG4++Dh3PTcf/1f/9dS4MH+XuE4rH3fOlfyQw1q/enGTGe2Wq68+857RAwgpQCbWxYu0FoUVp8M165cee2V6512q9Gsr2+szc0uhmEwGAy73eO3vvrV3d3du3fvXr58aX1rYzAanzt3oVKpnNnd/aPv/lGvd3jq9PKFyxdG/cH0zPTU9NRkMnn1tdd83//93//9LE/f/NqXj7qHW5vrrXq9ValPNZtT7dbJlTNaqO/98E8TY2rVmsnMxrP1sytnZufmf/bO21/72tdNkjVr9UDJn/3kR9aa3/j2r/R7/Td+5+/ubO3GSbp/dPjgyfr+8TAsNevVzu7O/nA4aC/MbK2teUTWmktXLq6cPz1Ox598/OkkSms1VS415xc67Va9Vg7Lodc93F9ZPJFn5vDwMM/zqakpZ2wSx4PBiBny3FQqlSzLEZ93sog4Ho/L5bJWmgnIkVQyTVPSGhGZiYiyLC+VSoACPut2AeAzooJkUcwn6ItdbQEAoHCV0Z4P5BQ5gcCAxlkrhRWARoKQWmtPe4JBgDB5DkRoYjQQKuEEVEsBkxVKjiLjmEfjiWUUqIVABkBmUBoAyTo0FGqPma21UmqlCmEFI0uyTmvlrFVSOmsYSUmQgNVKmQkcuXKlBIDknB94OlHGGCBRIKhaSAQWRNY6AIhdkpdCLYQCECA8EJUglFKyNYwIyGXPAwSQcpykxCQ97bKUAQERtVJSlv0gizIioaQEBg3oIfpKIgoiIAIBoJSSKIkwy13BTfjc6YWIrDUOCKVAwCI+rTjDF2Xo+aFJOUcspAzKITMLFIH2gCGLU7IEQkRpwgCR9YywnufFNhcowbFzLlAeABhjpGSlikyzDFCAwzRNBYoiXQIAiMgVlguIKIRE9JViQGutA0YUQggtEcCwNZ1W/fq1V+Zmpp3NBsP+8tLCn/35jyZJBoBTU3NTnc7a2hoAZFkm5PNVTsUfKMgPn401BGJx9EPEJEl8389MDojGWGDwPA/IZWnabrfKvq6VAmjVy+UyMw8GA/CVtVm73Wy32yQRlD48Ht178ASFttYiKkS2zgiB7FycJEIIBHj91VedM59+8vHas2eFGDgshdVKddjv9Y57paDy1puvZ8noH/+P//K3fus3/71f+/b3/uRPPvzodhRF/93//f/GIG/feTAcRouLi91eL4mTDz76KMnS//jv/odTjfqzpw/IZZsbW93jkbV2MhkfHR2Nx2Mp5cOHD5nRGKu1JnKIBMhSAoJDFDZPZ2dmzp5dqdVqrXar1+8GQQDA9+7dk1KNRqMoin7nd35ndXX1e3/6vclguL+zX/GC2VaHM3Ph7PnBcPDOL3+5cvq0BPzkk0+Wl5fu3Lk7NdXZ2d0plUonTi73e/1KpXrlhau9wTBK03MXLyRkjHOVev3m9Zs7e/u1Wk0KmRmbZFlvMCj5pTu37yzMzc1Oz6xvrO/v73c6nSDwB4MBg/jRD382M7MQZdnmds8LSpVyZWl5PosHW5vrR8f7506e/MqXvxKN4431dWQVjY2nK1OdufPnLsVxqoSXpZnz/c2NrVPLi4sLC0qogunYarUqlUohRt/f369WK77vx3H8nLVC1Gw2P3PngOJbhYsIIhaK5ALJLUTtnw/QirVdFGv+zPrj34FqKxCFELmxUoAERKGcAIuQO5s7p6SvhABCCVgqhQrRq1UEkkCS4NAZjS70lTE6MSbLs8w5z1ee0L5XllIZm1qTWmYpFAAL4MIuFhgKaI8ZENHkTkntKW2JGYHYAYAQQgnMsyT0y8SUZAk5yvIsTVJiKsJ5yTpfKilQK5kYh4BK6zzPkiRJxlGrWnWOtFAoBQCAVFkcKc8LlDLWgNaJyCaTcVAqB36QGOOs9ZUue8qTkgkAJFv2EUtSSyAJAkE6ABbKU6CVEiiMcZlhFBoQGQqrHc2MzjkhZSGKLVhWhQ/l5wNW7XlKqkLUpZQqyIZgCRzrIHCZFQ4scWIspZQfmyDwPS80xgFZKYWS0vd9KeXcbCeKoyTNiSg3BhCElN6/VdmLgcNz/EuISqXiaT0ajgUio5BKep7n+ypLxqfPnnrp1s0sy0pB2OksrD557BxfvHz5qN/b2NxM0mR19bFztviFwOwsWWcLnXFhsKClQoFMrLUGQOcsE+dZJpVyjpyzzhhfqdmZGWfywPPTOF6aOSGRK6VQSUFE7Ox4HB0cHk5Nz57tTI/Hk/XtvcPjoQMPMBPIKISzlh2Fvl+plJ89W+sN+jPT01qrD99/ZzIeMTl2zpGRkk6/cPapTb/x1pueDm9cv/LdP/6j/+3/+vf+9//5f763t/cXP/pxpVKZm194tr75ySefTsbD3b0jlH6cpA8fPXLMZ86cM3n+3jvvhKGXZulwnBuHo9EkSZLxeFy85e3t7WIVG5NzMRFERsBGvYGMnXbr9Vdfb7eatVptf//g0eqDWq2qtXTOnTx56sUXX4yiaH19fWFh8cK581vr63s7O6sPHs5OTYd+cOrkCYKlre2NyXgYeH6SRodHB+fOn3n/g3eTJL1580VEvHPn7uzs3PUbLz55+uxoMCjVa5cuXVFKV2q1UlhFodI0ieN4d3c3Jzp56tTe3v7e7l6lVFpdXe13u1euXLlw4YLnea+9/npu+NbNl6M427h9p1JpvfLyzfW1J3dvf7C3u/21r37VZZaI93b31tc233333fnlZeHpIChPdUppmimld7Z3Ll88e+7s+clgan5miixP8gkAFFGEWusiL71SqZRKpUKDXszHioJbELyIKU3TyWRSxF8Wo+Aibv1zT4/PG4h/m67w/Mfp34Xe9vPNAUCAACYGRCFQMjDlvhcqIdgZgRh6nhRCIDiTOudYsJaotQgVHhxOhnEMiCDRFsJtBskIjMCoQXh+CB4DgDM2zVIppbFOKUUEROx5HllCAq0UEDhwCAxM7BiVtDZzjgajDItAXQGWnGVyhFpq31NaiWqtHGTpeJwKIUFr3/PZWM6M9LQAFCCscyjQ8zSzEw6Ecc46T0qTZ4JYEEPuBAoPpWaWRAgy8EvgbCUIhEMQqEACSMfgWCgBgoGKSZdhoQSTK/x/pZQAgogAURADgkAUUsrP5lT8+Sajivm/REQHkFqjlMrzXGvlK48zK0QRD4RCKqmUtUTWKQFKKqkkAJZKpTTNACDPc2OMteQHvlCycIIvqIuF/rqwGVIorDFknRSSiVGiUsrmZqpVP3nxbKlcHgzHg8Hgh3/x405nOkmTWq0GCOPh+Ozps+WwdrB3NBwNizbWOWecoc+oDkWGjYDPJnDWlUolY0XmDCBaa4XAUlCizEiAwPPCapWdy1I2jlJniTHPrbXWoYzjVKmg3Z4dDtP7D56uPn6GKhhPkjx3WiljDJEtlwKpVJ5nX/7S6x9//HGv2/35T/8ijiYzU1OVcvno4CBK4t/6G7/5137jW4cHey/dvLW9tTuMxi+//tq3v/WrSWY3tvb9sOYFweOnT//8Bz9y1trcHB4eh+VKlhoptFTi5s2Xnq09G9Wr1Xr98ZOnw9EkTrKN9fXigFw83kSFKT4wEyAJSfPzc0tLi1PtdrPRWF5aGvaHW5sbO9ubWZamWYwIZ8+emZ6evnLlhRs3buzv7//hH/6h7/uvvvrK7/2Df1CuVqemp6VST54+uX3nk53d7TMrZ9qt1rlzZ+I4IXKTSTQzM12pVI+OjnZ2dg4Pjh+vPr16/bolfvzk3jiOS6EXBqXx+NErr77+9OnaOB5ooZ+trbempm5/evfunXuep6anOtOdqRdv3qyEpVKp5Bw55+J4UqkG9x/eW998/Lt/529Nt+tXVub7/ePJ+ZV6s7G/u19rNj/88JMHj57MLi7VW63haOick1Lu7+8eHBx87atvTk/NjAfjpYUlhZzGWW7Ter1eKpXCMCwI5ohYGIETUdG6Sik9zytWryOnpEYQRexImqYFzlCY4RX1tLgKkM19NhYo1t6/C7gtABRIghBKKWAiBBaFEQB6QoIfELExViIgg7OWESeTyNlcayyHPgqJDKPhIE1jQLDMQiohBaNARHJkc6uVUoxaSJTSOOuYwQqCYltjBFRSohIsGMAhCBQIjM46CSC1kkoykXUWGIkKahEQOED2vcATylOiVg48T+Z5WgrC1NlyudxqNv3cOWOlVsgsuLB4RaXUZDTUOvCFiJ3xA48sh8qjPFeAEkSotC+lzXN2rIQKAr8kpS90UA6y0YAZjCMhtScYgK2jOM0sgIdCyiLh7DmJKgjDLH+eeimlAgSgv3LYKpaakPLz1cNExlmHDBKNcUVapa+UVp5WqJUqPhNyLvA8z/cBIAwDIYQxZjjqp5lhZqUkIhbF0JgilwE+/xNEBFI4IussOwYAKUQax7Ozc8snTgoFH33yabvTaXemkpy2D46Nsb1RbNLUV/rkQq3bGyZpUvza56qzzyC04mFgYolCSsmCjTEmN5nJoyxFiQBIjj1ARgh9v9ftNet1T8kgCKwDqYN4Em1vb0kp9/b2KqVypdzY3+/eufu02x/1RykqctZZQ4jOWtM7OlISa9VaZ6ojUQBzu9UcDQfRZKLn56+9cOUvB735hTPXr70wNzfre2L10cNBf/Te7U/2Dg4rtU61Wv/wg4+erm0lSdZstXd29+MoHg1GzlgWB8VNOXfu/I3r1+9++tHW3k66vvmLd95NM6t8nYzHzpjPrekA4DlADYUxYJAk0WQ8uHLpXKfVOTzY293enp6ayXJTGA+99tqrFy6c//DDD5MkeffddyuVyhtvvPGP/tE/RolvvvXVucWF40H/z370g+2t7Vq9dtTzjo4OyJoLZ89cvHj+448/3t7Z2t/bO3XqVJZlc3PzM1NzgLh86rRjjHNjicKwHAalf/2v/ujC2UuSsN3sjOLJzOwcoOx2+zev3zx99uRv/LVf31xb/+lPf7o0v/D666/3e8Msz378s59sbG42W82vf/31a1fOJMOe16o0Q6nD6iTN4yT56c9++uHHd1qdWfb0s41131PRJDI2F0K88uqt1159dXB8rLW2mZmenU7iiU/aWjsYDKrVqud5SZKkadpqtZRSlXJFKpllmed5WZY5ctbYooHVupghi8KQqFQqFY9MgRgULcW/rXcosIXnhIQvuisNECOgACnRWSJ2zFYr5ci43AnEslKWmYCVUJJVPDHW5oZyQ9ZlBrSsKmkz2j0YxAi5Iqk1WCMAgR2gJUQWlBMLpTPnnHUElLmUFYEtqAiMKBxz4CnpQZoQs7RkAQVrz4HUQchExhkQiokZnLFWIIMARK5W/EpYsbmLM+sAlArK1aA/GMTjUQ9BECuBM0E71AotSQDmwohXCqm1EnUlSMqh5sjmY5d7UnW8oOop59gg5pA5ZGPRsUIFLnKe0nGaTvLYIRBoQDlJkjjLhNSomIidIxSgBEqliFkq9ZylJRCYHTAhFwxWJURRbYs6K0QxdkMhlfAQHCMzO2JEVCA85QTkWQ4MWgAiKCV9qXzfS7MkmkyMNcTMiEIJ4ywQMxMQSCkECgYWKJRQ7Mg5q6REQJLILquXy3/rt35rd/9gkmaDfholebp3OI4yQGkyw8SMpJUfhOG9B48KPvlntEdbJD5wgVVjQUQHh4zIjpxlF48TEJilSbPVYiYhpHMuGo1r0xWt1CRKlJRh6I12dw1xltH6+gEjBaHnlVskxGQcbe/tTsZRlhsET/maEbI0vXb5ynv9tzvTzUajmeXZD3/wfevshfPnvvPtr//zP/iDhZl22Vf/5//TfzU1M/P9H/5gMBokcbK9s/fkyTPHtLi49NEnn45H4263F5ZLtUrty69/6dnTx8NBAiLPKfP9sjF5lEwq5eCHP/zz0NO9oyNrHTKbNLY5srXMrsCCPjMvkyhACul5enFu7vy5s8sn5quVirXWWOeH5VZnOiiF8WS89uzJo/uPKkHlpVuvodYfvP9+FE98P7h+86U8jSbD4Z1PPyZwL7300iQe9aPRizdv7mxs1av1ra09kH7Kqtaerrea5dA3iRMga83a0XEXgMql8qDXPTb24rnz5VL5t3/7twf9bpam7ZmpueW59z96//ZHH71069b8zNyz9ae//MU7ZG2a5EmSPXu2funKJUSUSpgsO3funHU2LJW509zb3SHiBw8fHR31BAslwxdvvloqlb70+itRHH/y6d2d7S0lK8ZkKyeW4+GxSUZhfVp7GKcTL9TSISJOTU0VE4UgCIQQvu/7vl8oF5VUaZJnWer7vu8Fng4KaLFoWgtCWCHnLeK6CyTh8/r7ud6hiD0AZIYvfG9beIEUsz8EBmBnTaFGdc46kwGzYACGKBoTgfJUyukkjh25sFyqVurxZASoWJADpxGV8gSxI0Jma/JigJIxOEfGkFCIGozN0QlkBgQQEhizLJUApoghAyzMyYhRFe4oZK2xhZOJFBLASZTEHCeTPM2LaMdqJfB9mceTzOYoZWaMdU4AVLIs8EJERkYGJkfFzC1Pc5AiUMpKOUxTQNRS1EuhQp4w9idR7pzSgp0lgBRyiZKIxmmSknNSCMTC90BKobQUCNY+H7PhZxmOSqmiNj2HNaVAxgKzVkoVwsS/8twCCILAWle48HhaSw99z9cggZiYhZJAjMCe5xWu7WmWFvlvACiVxM94AMXxyve8z/y2nn+gSmp2JEAQAgp+8dqNy+dWlBSNRu3g6cba2qbSHiLGcez7vgTBzhUYSKGkKF5nUWeZi7C3vxpZSInWOufyrBC3MPlhoD1NCH4QEFG9VhuPx7bihtG4FbR8P+geH/t5MBkPs9zFiT046id53G43mf3jw+PBoG+MLbwxtZRS+AAMqK5cvtw9OHj51Zfu3r378ce3pdLW8fz8wsrpU//H//IfXrp0yabZoN/f3t4dDqKtrQ+iOOn2BoPh0Pf1cDRJklQpGUXRq6+8CuRGw77ve0mS5LkBQKWkkMI6myTJvbv3quUyAnierlerk9HQ5s8JZ1mWIULRWBGAlNLTshx458+ev3Hjqu8rY7IHDx4hyheuXu/3+xurj2ZnZ+7cuffClavLJ058cvtTEvLDj28vLs3/0R9/99atW0vzs9ubW48errY6zafPnj54+PCFWzfCsHR25VwlLF+6fOXp+vpPf/FupRIItGXPJ0NLC8vD8fDp02dxmly7cXOq3e7MzNx9+CDwvPNnz41Ho1++/+6FixfmFhckwtqT1dlOZ7rT9n3v+Pj45o2bp06ccsbOz881qrWna0/zLFtZWWm124XQIM9zR/DjH/9ECGEdrW3v37l714B49dVXdna2gVkBXDp3dmqqZfOsGgYa8eL58+1OM4omhQd/nrvFhQVjzGQymZ6ellKWy+WiUBY4QPGwVKs1pZQ1tihHxeNTvIaiTBdPUKlUklIWE7PPn68CzAEkKUVxiPxiV9sCYiOyxhjDsjD4BiyQBADFTEQGhQAgVSjGJBmTg2YymFlKcjeO4sDXgEKDh0yBVCDAGIMEnlToGISwxjnLRCCk8KQk5woXx0JQ6hwJgWwJUSIKFKJAZIRQNrdSayk1OS6scR0zkUOBzjmUgtmlWa6VskRgKLaZVIqRYmNqtZqv9XF/WAmrHhRpufCZOIpD37dE4MhjaGitAbUTyOAQjkaDkTFeyRfAGoAJIiApMM9zw+CURiFtlidJhMC+p6XSxlj6zFLyuYoKBYq/ssQWQkgERyQBJQpPa8TiFaGSqvDVzrMcUYSez448pQSgek5lACzuAVDo++VyGZj9INBS9Xs9JaVAJGBrjGMq7ulnZR+LrVRrJVCQI0AmdkRsHZVLpZWVlZ/97Oe37z2YJLmQqkDikiRBRDIOAcTnturPt+Sip/vMA/MzF5viPTpnpVRFAkUB2HV7Pc8PPD9AxMFonKapYQKE/mTM4/F4MpktV8rlZpYN2u3Gw4dPOtNTaeI+Wb8zGUcCMSyVPK3JUQFNWLKBr997993Dg6Pvfe/7SqmpqVnnnNbeqZOn3333vVs3bv7lX75zfHxUCsv9/mhv52htY1NIOZpEQuB4PApC31qbJEmn0xlPRts760rj9tY2gEhTC4ie1kKIchjGk0maxJVSiIibm5tFcJHWukDDC7J98eSjlFrJMPDPnDk1NzczGg1rtfLe3p7W3uzsXJIka2trjUb12rVrJjcgZL3ZuXjphd//53/wR3/83QsXz6d5FqfxxtYGLC3/9d/899tT7TidDMeTaqkSjeP+Qff61WvVev3B6uPVp0/nZmfq1dBmJAGlp5kxt/bh6urqs7VWq9OZn81cnid55syd+3cHk9FoMp429uL5C2+9+ZW9vf3Dg92vfe3rDx8+zPN0/dmzuZmZ7W0Tx5MkTWvNxvTc7HAyPjo6mm61kyTVvu+Hwfb2DgF8eu/ToOzVwwoBOSEf3vl0ulF/8erlPEs3nj3V3FqYm0chokkCgFJp3w/arWae58w8Ozvred5kMsnzvFwuf75gtNLoyeIzLFjhRW/7uYliwVHJsqzQmDnnim99nhEOAEQkFRJxQWD4YlfbojAwMLNSGuC5e3dxWWPTLJfq+V4iUBBxbnJmMsYQyyzLoihGxCDwJVNVKSIWzNa6AldhdiCIiXRQYpZZZqWWwKTQEDohBWJBiJDO2qJDspbYWqnwMywMjbEIoLTHzhTaJwCQQgIQMVtnCgFomqXKoWUCZADMc5skmaf9ODdRmulQAxEAF/iOMcY5ywxSyZLv6SBUuSHLQBzZdJxnwvOVVMiAgnKTZy6XQgKzlAokZHnOxnhK+b4UUlsiawAAhCg0TUIpDYiOXNH6FRMkAhbMCp/XY6VUoLSQ0lorEVuNZq/bM1lerpatsQoFCpQAAgkQBDAC+p4ql0qIWK3VqmFpMBgUQQ/wb0/eEIWURbUtSDZBEDQatSiapHFCQAqlEqJSrrjcbm5uHxx1B6MIhBT8PEHjuRodQUlVTJM/H1Z8VlUdMDMxIxQjvqIf8bzipOgX2K611vP9JLeDwahSrSRplqWZBRISRpOJVn6amsdP1sHYuZnZUimMk0mvp+I4yZPMOUeIeZZRQfHRYKxJs3Q87Mf9wWgwNM4Q8dLSYrfbn52bk0K898t333n7Xc8PZucW4yQRLMejyWAw9vyCNwYgYGpqajKZMHOn0zlx4sSH7/9ydfWRtdRudZLE1KrVE8uL4/EYAPb29pqNeqvVPNg/KITIRZ0tNs6C6RmGobWWARaXFivlwA+89Y216elOmkaNRmNmJtjZ2dvb2//2t761sDjXarWnOtN//L3v/1f/zf/1W7/6nctXrr7z7rtSylMrpxwbLyj1+uOvvPnW1s7u0slT0pM///nPv/7m1+Ze+dL8/ML3vv/91SdP55eWlxYX52dnXZZ9/OH7dP/+4tJcpVplxPbUzCSKPvzwwyRLL1+6NBj1y5Xy3/vdv5MneRqlWqm9vR1Pq729Q6WwVq85ZzY3148O9s+dO79y4RwPBqMo+qd/+M/vP3hwdHj49a++tbKykud5bzBoNBunzpw5HPaPDrtCqCyOPvzo48WpqddevrWycjqNoxNz81JhEARplh8fd/M8VUpOTbebjXqpVKrX61LKwWDgnCtggaJXlVIW2bK+738+dC2qKgAUdAVjTFGmCxSiWMyfV608zz/7WSOVEEL+u8FJAIBivicEaK219p5/FQEAmcA6KqJ5kSU5BBaBClEKLcGkkRBgrUVGCeAJxQxSaM/zwpI3mQxRSEZk4REr9DwQkOYRCqmUkkI5R88n+NYVvRICSuWhMCikdciAApCJEf5ty+nn/lyOGUAqpciRJStRadQKC8IzxaNoMhgr3zs87lUWQo0A7ASipz0BmBsT+F7gB4KdBWDP5wLTMKZUKltCJESBhl1qjRQYeB5Y5xzJQgUbBsDIiIYoi1JnrVKeUp5SOghC3w+tNUDPK1chtEJEiaBQALGSMgiCsh/kWS61EELY3AS+H0jtK+0JaXIjiKWSAgtWA2ihfN9v1OpMpKRCIcjRc/dx5z7znXGIKEEUigkppe955XKZ2Jk8I3YI2G43X3n5leFw1GnWf/H22w8eP5N+RUqt1fPqXBzQCo/RorI8R2k///QRGUBIWfC6mKlUKvm+r7VXnByJKAzDcql0cHxsHEgp+4ORMbkjAME2t0xgyQBhPE7AmSge+aEwJhoMHbAkNtYZIUSWu9wAADrrWGKap+yMiROyOYMZjYdPnk6UUlevvrW+/nR3Z0cov9WZ2drZ7/b6ofbj8Ti3eZJG2lfSU0qI5/G6WqdpevnS5XvnLj94cL9S9q21ly+fO3v23GQ8jCbj8Wg83ek0m82Nza1er/f5TKZ4+8aYSqUSBMFoNFZKlatl68zBQX9vJ2/Uq0uL87Ozs0mSvPfe+3Nz82fOnGm2WsdHxx988OHS8ulzFy4eHA3+n//D/+s3/8Zvvvb6Gw8efrq7txMlle3NzVE/vvfg2cbmdr0VVmqqXqkuzi9WSxVEsbN3cNjtBrl9/HRteWF5ptNODVWbDWMtStFoNnNrlKdb7abvebVyia25cO4MOBt6/s76TvfwaDTuLS7O1irB//K//OHd+w9ef+XVX/nWr9gs/+CjD9+5f/v+wwe+1C9cvHzpwoWjRvNnP//ZT37603Pnz40nk0uXLh0dHw17vcvnVubnlrZ3j7YPBidPnnq2sXXn3v3Q965dfWF5cXH/4Gh//yAIvCzLJpNRq9UiojRNZ2ZmPu9qiywGRCxO/c7lwFi0q57nFYTcoqoWZ4ii8hZh7MUml2VZsfcDQIHqep4nlVcsTmvtvxvVVgh0BEqpdrueZXmSJAAohNDaIyIUpJWPIKx1vg496cVZKiR6yEhGKAnAkhGNc0wMwjkWEuNxhMQaJSM6lHlmGYRALIdlQpNZYGJUChiNscXYnBwLIYVgYpBKM4ESClzhxsr/9gtmBnIkpGKBRFREv1hjfS0Fo2TwpQJHLIRlGkWTKIkb5VAiOme18jwlgVmhVIAKpUQ0LJzAjJzSnjSMKJhsmmcWCD1dkaKiBDOjlJadBchQGOfSLI/TzBgnpVKer6SuVqqe51tLxRDseQtIRFzEFrNAIRDKYUkrJVE0qjVHlGapzY1gUNozxoAjcCSkFAxMDgAESq2Vp5VSUqCWUhARMaEQnlKcZ8ZaKSUqSUyCEQG9z9pMBIjjKAi8RqN26sTJq1eu+H6gdtQvfvGXw+HQ90NQulSuZOmkQAnIORRCFojzZ+35X12feTIqKS1ZRA6CsHDzss4ZY7Ms1doTUhx1u6PRuN6amkzGw+FIKVUqhVJIY0w6SfKckjjPcycgH42Hp1aW/EBZR2TR2sw5wyyk9BwxOXKGSIBxRiJnWX7p/JmNrSd5GiHS9esvf+Mbb/3iZ2/PzMwNxxE5SJKMQBhrG816b9iTDOVKYMnleS6F6Pf7TDQ1NfXJ7dtKetVyHZGmZjpT022BtLmxrrW2Jq91Ohvr61tb20JrclR0YcYY55znecw0Ho8AoFIpV2vVyXjoe+rEqROXLp6bnu08frK6vHziK1/5SrPZ2t8/iKPo8PBgbnb2o48/XtvYqTVazfbUL999N8uio6ODStX/9ne+8fH7H1+9cuvPf/Dzza3tck9fu3HOEf3Z9/8sT7I33/p6e2qqVKlkzi4tn1Dora9vX7m8IpXK8/zw6HB7b5cYp6ZmXrxxvVGrrj54WK/VfJTSEaKu1+phSVeq5z744N3hqC+DcqfTfvjgwfWrV48OD77//e+XFmfrnfbrt15+4cx5D0SrXO0Ph7kxJ0+e7HQ6URw9fPjwG29+9dKFc41q83/8n/7nh3fvS5CBLyVCWPL2D7pPnqx7WntaTybjU6dOnDy5NDMzE/gBCiic6sIwVEqlaSaF8HxPfGZ+BPxXCNXne3xhUlPU5QJbKAp0wUn/PNNPKVUowhmosGb8wiMJBIIQAREloKzWmgyYZoYKek/hsA/oBeUkt8AO2ShGIBEUZiyuSNcRWggGFuL5nEQUFC1npZSBCp1zlhRLnQOCgNAXeWYQNQkgQkLhQDgmFEqwVQJ8XzurhZSKCIFRAZGzlBeiaSklAksWiIF1Tgrh2EqtgIVzjpgkspBCC+3IgUCbZgxYNM4KQQg0ZACl50kAAIEWBBE6Y3KU5Gmb5tYSKOGsQ+Ky7ysBVWlDdEIJZshIxM5ay5Msj6yz6AmtlFCeVrWg1CxXUcCEYyeldWicYUTS0pKThnyhkLhRqUoGD3UyTlLPRiZnBCbypXa5zfPc0x5KBVI6YAUCABAkglBCAYMpaLnOEqJDtmRJICoFCIJZgJBEhBDWysQsESaT8YmFmcXF+Uq5fPXqC7u7Oz/96U92D3pKqYyBmDiPZcoCUQoUCCiEkFJpZcg9T+gFEloSuQJLQIkIKLUUzM5Ya7IktpbBOCt9TZ5yUgyTdDAYOlS9wTBLU0cgGY1lIVSpXO/14yQ1mbFEbJxNu4MkhXLYHA1H7IxglCzIOpYWmdgaQ7EjklI5Z9ut1j/4z/6T/8d//9+PezGiHh+n/9//6Z8456KErMVKuaKUImvyLDGOyuXAGKOE8r2gVhYAMB6NwlIJnPvxD34QeH655JfL5en2NFu+d/f+iROn9vb2tQ529w56vYGQqtABMnNmcmYWShJTmqdh4GspPAUun5xanrlw4dyFi2cD37t955OD44OFE0s7B/uZdTnlQTkI/fKD+0+2tg7WNraPPr7XmpqKDg8QLQJfu35taWF+9dHq3vFuuRacWlk+fXq5PVV5trUmtXr1xq3HTx5XatXL16+urW1w5nrdw173sN/f/8bXv4Jx6iFVqoEflAVKjao91TnL5zbXNx4/fjzd7qysnG8stnu9gzgZNxv10ag3iWItg+tXX1g5sbK0sPy/q9Te/eD9MAy//sobU632+tO1xYXFv7mwqJRKkqSne71e79Ubt9I0a5TrNsvn5qbPj6J2s57mSaNaWVyYlyw31vdKZb/dqWtf7+xtfv2tr0xPN5XShYTM9/2iUJJjKSUTaO3DZ6KbJEmIqMi5Kca/8BkyW/DAiglBATIU3UBhZVuUbERUUhfUGPOF723xeZKY0pV6y9Oq1zssyKCIWEwAmdmijeLE9z3JQAChH7KzxmQMQExFsJRSGlEoJVE4ZCZiAaiU0p5n01QwVioVkrI/7CsVkPWIHWIxlhRKEaJkQkOMUlYr1SSOoVDpkkFkFMCWnlOOnNNK18vV0WhE9vkASiBCcdBjZAJrnVIqDEtZnmvtUZ4ba4WQwFQ4aCdxXNzNLM/DoGScI0TSMgbKJVpjwDktUSlPIyhETfL/T91/PluWZfdh4FrbHXP98+l9VmZVZvnu6mq0ZcOIAAGCACgCI1E0IBij4YijmIiZGE2MJkIKCcEIaiLGfRBFckiAxIAgAyTANmig0b6qy3TZrMqs9O55f+0x26w1H/Z9r4uaf6B0P2S8eO/lu/eeu8/aa//Wz6CQntkSTYjH3o9tKJxnoYzQClQiVCdvnD5x0tbVXr8vhLDx8E2sBKInjYIRBGAjz1KTkPPOWuudc3VJXhmtlQKJ6EEJKVCIKKDG6SwtUhcAwDl76J8UWS/RKElIPJwesJAgRFEUzCSJvvjyy1efvtRstSjwg8fLf/an3+oPhkneajSbgDgajYiCd24KDkjJRIee4vHQF3G0uGIO7wRiIudd8MzI8ahNwYcAgLW1RVF5F0JgZ308+gFiXdeNPHfeMWDM4PCBiIkcffjh9TTJ9vx+jCICAApkq9ok2ntny8l4NMqaLaH0kRMnHcF4NEmSLHjc2x9sbm1WdZUkGRFtb28lSeKd9cEVpSOihYUFANja2kKEbrczOzvrvY9wcFFMZmdnAeDdd9+9ePGiEPLatQ/i2XYwGDQajbzRKKqqLAtmMEZTIJOnWSMtRyPwvpWlZ06dPH3+1MLi/MlTJ60t33zzzUaj8dzznxoOy3Zr5sPrt2dnunfFg/u3733r299FZazn8bjY7/eTTGvJaQJrq2vOhWPHjj96tDoz2+n3B4+XHzAerSaT+fPnpaCtzUdO4v2Vx/29crRfjPdHJjF53t7e3Z3Ls7zR6s12hVA7W/3t7a0kT1qN5pWnrt66cXNjazsAHjl2ZGdnezzpf3T35ng8+ku//Nf6u6NTJ04464qqPHfu3IkTJ1aWlzvNVqfdvvjExSRJbF1/dPPm6urqxYsX8yy7dPnJ8aSYDPuB/csvf+rilafeee96pzvfbBilkJz3vg4Bl5bmX3jhuaocHT262G636cAOHA6CXI02cfEcDlojUWEymQBAu92OWZCRGH4og4yZJvE7zrlYjmPbS1PHW0QU0cXxk11tERgYhdBaMdFwNAQhGEWU+TvrlNJA5H0waSYEBucVSOeDq2pE0koqIRjAEyMqZkaUUghmlsiIpE0qpBDCs5BSYKLlRIpiXGpjpk7WQACktJIKnHPsAjHa4EpbZ0kiBDAKZmICFFLgVB2gpDLGNJtNTxQoxHkxIkohESUxKKWlUoAwGQxdoIbR1oXKugShrqskb6RpEgJb61EI5WxZ21LhJNBuVZYUiFihkMZIDpIgVYmBxBGNvBuHUDCVxCTApIkEmcqkYfJ2ki90ZwTD+s5uGUKQEBhDIMGgAyYqsVWdtJplXQNDIHLeSSFYCWZIdYZCJFIrQBROCS2kjGIIGeduQmqpjNZpmiopEbkoxgCRY0hJknofDvWLzOwiyh3sTKf5xJlT584e39rbev3tN3d3Brs7g7LwUue1tbt7eyFGeAnBCEJIAIjQrVSKeUrWgQOhZIRo41NM1brBx0bYM1vnA0Eg71zwnqraUmDvQ/ABAKJkyDlHzONxYa0NwRGFGIkGBHs7u0brPEnLoowGN4ggpbpw4cJ/9HM//eje7X/xL38vzfNxUY0m5R9/9etrG1sCNAGPJyMGT0xVVRBTXVNRTqQUWivn7MWLFzudzubmplJKSlxcXNzc3DyUIWVZBgCRg/Ho0aM0TeP9nGXZ8ePH19fXnffj0ShJksXFRe99YgymYndvR2vx9DPPPXH2bJ4kppXNH1nc2Nz+8Y/fbLUaWIU5MI8fPjR6sLc3yNLGcFidO//E177+Z8NiAEKCUBKYa8dGDKtyZ3vw4P7K+tr2YDjYXN8sysp7Nxzut1tpppT3lVa8uvFo3N+8cunTF85eevxweTyedOZ6w/GIZDo7M3f6zAkBsLg4QRTD/VE5LBcWFo4eO9FsdkbV8MfX3rp9+7YQVNdVb6b7wfUPn33q+Qvnz/e6PbvjQeC5s2dPHD+eaGOMiQ5GQqs0zy4/9WS32+32ug8ePtzZ3XP1pNVqoFSvvfHDvDHDTG+9/eMXnnu21+lmDdlomKWlhUaW9Np5nubBBanV4SBRKSVQxC/wIPbmEKGKLXAswbGMhhAiVuu9n7oM13UEaj9O/4rAwpTwIyV80pNypnABAKLzfkphkgoVupKkNgfZKhQ8TCYTI1gJKYmJwcgYGhiDtRSCihR3NXVOI2IvhJZKNZomEGmtpBS9Vmt7Z8/oplZc2zLeuT54pQ1IBgkswDonlQIBjAE4TFs2QiIQUgop41U2xtiiiFB63OVMopUwzGCShIi880ma+rJygSZF6VqtLE0ArfMuMRmRAwCjtXOOgIUxNXnHpLRGAskgMFqrBMvBeSysLTiUHCywlNpITKVOhermrUbeSIVuZenm/r4NnoXyPngKWmm23lZVAATnUQqpVGoSKSVpXRSF0loggJLkg2RQAFIpjDaJAAf1UwhEpVSW52mWBWcZiNgbkxCHNDXBx9JBsQNFFMBEIXz62Weff/aKRni8/PDGvXurqxtRUgegEBEEWQoAjEoKIeEgCVJoiShYIASOryAe5ZgZYLrbHd4YUZnsvPeBvGcCDszek7XeO6JAce4BB/6kAFBXtiotUeTuADGDJyJ2wSZSSSGAwTvHwIiwsDD/1FNPffazP3X+3Nlvf/cHV599dmt7d3tn986tCYBgRBQYiADDNFkYIJ6ZiElrdfToUp7n7733XlmWnU6n1+vs7u5FBHY0GkUh04kTJ9bX1xFxMpkURRFV/KPRqCiKqqq63e5Mt7ewuNDI826v9/jR4wfL95YWZp69enVpbi7Yujfbybqd19588/HDx61W+979lUBkTHs0HA+H2wA4Ht/VCnu9rk5TLEtEIHKCBXgIHKSQD++vrK3tPvvs8z967Yd5I2Hwdc1Sqk6j8+jh8v5+fzIZt1qdZ48c67XmJYSnn3pic2d3ZzButntra+v9UVF7oFA2Mt1utj770vMhhI3NjbyVN9qNdJTtjffyRm6tLaqh3dwjSiVdO3nk6IO79z+4cb0z0/vLv/RLaZrWRdn3AQEmk8nG9uZkUmitqrq+cePGvQcPFhYWP/X8s408e+u9ayGI3Z3B2bPnTp08s7i4sDi/2Gl3JdJsr4UcYiSBUYoPcvCSJKmqMsvyKG85WDkY+WGRIBQXSTRujpaqMYI6Um7j8o6lNhIbosom8mGqqjocr33Sq23s57VQArQHlkqhUN47obQQGHxgYB+4sq62LmtlxMAEWmkAJmJkABbGJEorRBFCkFIEYmKntCRARGUSjQIFBHJ1O89cp+cBURCiZA7xVQB6As8iKK2FkoGYAaREIabqAAApRBACjVZEVBZl7Ppc6eKGGcUnKBQACGmIPUEAlEob9qHZagkpK+s48m2ZiMgYLYQQKDKjJ8FWVcXOS0IBypgEEWwIngLVNVBdBW+ZgDGXJhWJNrqhkoZOWnkulRRSre2sj6xjo7xnCowMrq7JhbnZGVdWdVkVRZHlOQDEwF2ttZbaBU8uGCFSlBoEKoqbt5QCGAKzUipLszzN4saAwI08DYGM0VJiWRKFEBdfCMQMJtFH5nrdVvPqpYtHFxZff/ONH77+I88KMIHoX8chkgoi+y7y/0AIFEIeUGv5oH2Agyr28cch39ZFZhgAgLSeAlMIzjlf146JQwAhJPM04CSG+u3vD8qitNYJIb23RIFDQEYk7u/tBx+UEFprYjJG7+7ufutb33r0+NHc4hEvzLVrH/y9//x/ffPGh9/5zvcZBcQDDxIjIjHQQWY7UyNvKiWLolxevlaWpTFGSjkYDJRSrVYLABqNRiBqZNmjR4/29vZi4Hyj0RiNRmmaxg+o1+vNzc62W+0QghRy+dFyOSkunz139eoT3ZmulDgzd2x9Y/2V7769vz9UOjFJ1ptZePTocavdct61260HDx6W5eTIkaWNrc2dvT0lJTDHaGnBOhoME9NXv/rNb337Wxcvnp6fnzt1+vjs7MKND2+TrT2Lt96/fuHCRaXUieMXlmZmF+fmhsPB+tYGCrG1vb+8se0q+9771+dmsm5Hnz5+7P7sQqPZOHf+LCrxo9df29ra0Wg+/cJn2u12mmaDweDDGze6vV6z2WikWbvXbfe648lkOBy+/+67vW736lNXX3/j9d1+f3Zu9sGDB0mSnD179u/8zFeWV1aste++cu2t926wajy4v9xuzn7xi1959PB26NFTT14hKpu5yfMkT/JEa0R0TCEErVWWZfEAmpiMmauqiksr3rZRYh7R2CRJ4uqKh4z9/f26rpvNZpSn7+7uImKn04k9SPAh+idElsJkMvnke4BNU6oEyxAgSRJQoraOp0GEJKTwlWcGgTEQzGSJYR9rH0xt9QjSrCGFAECPnoGljCp8jmQCYuDgFXJZVsSQpXnhPAotYgADMSNHBxohQMipJ5ZCjoYszBSIpFIm0QKAmQJ5lAgCpVRZlofg4x6IKJTGJEmlUoHIBybAmdm5XrOx1OuWg35giiyLYTlxLmRZLo1AIQkg+JApraVRQlkSgcE6X5MNyIAowZtEJyg0ypZKU2lMmimCTBsj1aQq6xBK70kKZZSrPDom75LEiEQEoJp9xZ6Yog86MwcmLY0UwlnSUmohJTFTkEZorRFFZFkYFErpxJgQgiUiorm5ntFCyJh8Zrz3wDJ4QkSjlfeOff3MU5eevHhxf3vvvXff+/DGTZRGgPaBvHcCgQQLARIiT3YqUFBaAUCEvxFwGj2AHLHjyPo4XDOIGCiEEKzzPgQU0ntnfQhE1tbehwhRTeFdIiIqimI65WCPGIE5YmKBgErZynprQ/AhBKIAAFmWIsJwOCYOP/zhqzLJAZh9raS8cvniN7721STJg6cQAoMH9BxICR0BpXa7AwB1bQeDYaTBxUjXRiNLjBmNRrFhz9LUh1Bbe+nSpQcPH3rn0jRN0yRJTLfbqev66NEjQsjRZLK/t2frSmn14ovPP3H2VLeVtXqtSTX58KMPbty6jZjOzM6OhsXjx+vBh1/+5b/ywgtX7929/8Yb79RVffz40Xv37xZlHRmmCIAMCAhMUcjDDHXlynL88MEj5+fPtk6lqWm1W8E1RiWtrg/6o1szvZnJBPMX1KWL586fP3t/efXxzXt3H6yORkW33W612+12cu7skghuY+PR/mB458GtpNHY2NpYX92e7y6sLW80Go0zZ84Goheee+HF5567ePb8YH//G9/8Jkrx3nvv5VmmlV5aXMyzvNlsrW1urq6tCSVB4NvvvLu+uXny1PHB/vD//T/+k7LGRnvx9Jmz//7rf3rt+rUrly8Uk+rJp6722rMcaqMTkyTOeymkVMoFX1W1QKGV0QqYIFbVsizjBhy1DGrqNESRCz8VzgC02+14wojZZa1WS+vp5A2n1h/RQBTzPJNSjkbDT3i1BYwnxRA5BdL7AAEUKBCA5F3tBKrcoGBimaTaSKEoSmgxNqisU62UBgDnPQhUUjGHeOp0zhXjsdYamJjZeUKBWnglqPKeAjKgZyKJIIUSUgghUSKiEqgFILEPXiJqLZXWwIICee+UEQxknVUkpNbWe0aJsS8DChTGxSR4ss7rJJlMilQwtnPBgVFYYuucUDptNC2xF8BM3rORpsFcheCYApADDhyi1kuj7Oo01wkKFCiUkgKlJJJKNVtNRuHHRV17ITQEcs4Bs9RCSiOlIqLhZMzMoNX87Cz7gAKlkODY1ZVCnaHQUkspSLCSMjFJBKEi5VsIkWgT3WNBKW0MC6y9EwEFYKKNFlIaJRKsqlIK/tLnP9vf39MIK8srN2/dHo5HRVkiIyAxe6UEAACRRBEzjuKKBQACpkPnOiYBiBCTeOPij0cQQiBiCgDWW+t9AGQhmLj2znuKpRJBYNSzIThnpzQd5vimEDD4ENPwJCAQkneuLqdJq0wBAiAJgePxWGsTPPU6M6NhEZi1Sde3d4vB1tLSQpJ1y7IGEKurqyiMNKKqaillnudZlq+vrwMwUTjEsrXWzbzRbDbKtbX4YgQiIWZ5vj8YoBDzi4sA7OsSkRcW5hqNxt7e3t37j02S93rN3lzruWeuLCz2FPDckbnb925e+/D9UVForYtRcXd9r6yYghiP9iTC48eP33jjjar0zvm7d+8ysEQR2R2ASASIlDUSIURML0XEZt6tSygm9fsfXLt5915VcKOxMByWKBtlGTbdVlkN7j18pz3TuqySza3d5dVVk+iz7ePScKutBZdAtixGy8uFC2J/PLn78KHJzMuf+uwT5y/fuXNnMpkE9mmW7m9trzx4tPLg0SuvvBKlKA/v3f+N3/iNI0eOzM7OzszM3Llzd2F2/vH647evvZOk2aXzT8705m7futedmf/Nv/f3/tE/+d1BNXz35vtC4e64fPuDW93mw8KW//nf/hvNpKmMAiFRIiEjgQBZOw8wxfoheqgq1e12Y2091CxEkc4hFSx2vvF30jQ1xqRpGmfF2iht5CHya4wKIQBwlidKdz/p1TY+mCOGgOxdfJ+Hu03cjuIX8UdSKWD23sdDYrPZjP0LImhthJTeWcQpmjj940I45xhiQ0NSSeEEEwsUSmoSQaDQUgcOUihkAOLAIJiVNAReMHhPAsBZL5VUSoTglNSA6DmgFkbKqA0DkELrNM0mk8JkGaKgQKPRZCWszs30lFSAkrWelIX00gOgBwJBAm0INXPpvSOSIFMQArUWUkuphEqUkEIyEwohhQBGRMGAlbVlVftAJkmZIVQVhSj9QlRSKFWNx1ooJYQUMpPCpEmeZ6PRyAhgYknSKI2x5CEYbaSScYAbDZWlmNonGxMda7EYT7RGYDZKexB5ltVl3e30zp5/fjjs+xDa3e7Wzu5w/Kg/GEilvUBmYUxikuSQQC6EFDHfVCmM4osQovkSAEyHwhTiZxcZBRw3ZeLAzAyBORCDiNJ17z1ToCigjJ3j1JLROZrGmU0lZ8GHiIcAsA+eQwjOHq4TOEAwYvsTD4mtVrOYVM7aonIPHz7qNOTzzz/fH9a3b9+pqrLVakUN2/Lycp7nsYPudDr9/n6cg0Wn1HhVbV3H/mgwGKytraGUFy9eHA6H0X21ruuTJ04uLS0Nh6P3r90gYmKUUjTyxtLivBBCSZMk5rs/+P6tOzcCOOv80pHjtvRVNRmNAgVRV+6Da9c//fKzk8kEWMPUJe0nAfLMHDMcmXk8HgNACCFN0zRPiMuiLGpbt7ExHvvHyx+hkBK5kZtjx+cF1q3WqeWV7Xff/cM3f/zu8uPVs+fOvfDi5e/88Nv7E5Loi6p/6uhSJoQAlTVaFGAyLo023tqXX/qMMeaHP/zh6vLyiaPH33rrrbm5uV/8xV+cn59/+PDhl770pW63WxTFyZMnh8Nhq9VstbNZ3710+cLXvv7Ni+cujSfFxtbucOJQJpPRWOrMlqUUYoKjY3Pzx47MJTL5wfd+mGjx8mc/kxjdbDWZaFyU0Xc0hBBnZfF8E60Pjhw5Ig8GMHG9xRV+CFvFaViapkVRxNNV1NoAkhAypkPGBvkQ/vrke4BNl3iWZYFVDHkngohMA0BkwB2+mahWFkqH4KN3X55nIGUk5hqjvfdEQUppLUSuXKwUSgoAYA+ByDnXSJM8zZ13yEhEjogDAKFAFa2qAFCA5MAuEAolRcxiR0RS0jAHZqGUYhHnMgzIUkshJJP2gZwPaZYzg7dBeE6MlmkyLisRk4FSzVJWwaNOEIUDsBRKayvvUWmVpEgAgSWKROmGTgQiMwlABkE+jowAJDBxZcfE4HxAlJVztbOMQqAQKInBWmt0kmstAvfanboYaSaw1gA0Ox0iZi+IOFCIXLjo4RlHUkopYwwFgriMlFJKIQolOTVSK4UMiTFpms62uyiFVtIY8+GHN0ySpHm+u7/XbHeKsg6ASZ4rKauqggMNcbTUBYAYAymkMAdl99CHCYjpgHkTl0ogDgye2HvvQiBmW9VVVTMLChT/agQcvPdxyhzfSITnAMA6i4xS4hRJYCLy8RnhMIz9gPoTS+dUrMkUWYCrq6tnP/MCcDhzbvbOnXu7u7vd7kyz2RqNBktLC8YkGxvrMzPdjY1NRM7ztN1uGaOLAprNJgNneT4aj51zw+EwbzTSNA0h9Pv9siyJQrc72+nOfXj99nAwtM5qrWztve87V544fnRx4cgHH1z78VtvCs1SktJSSbW+tr6/2y9rrCp2FoK3589dGA1HdV1rNU2iPrzR4kbCzHFAFKuMlLLT6bhQgAjlxE5KOxjsCMykaKAAJs8g0jT5+Z//hV73xP/wD//vk8mkLMvEJFsba1//5qO0mQktx5PidO/k7MLR7ZX18WR89fi5v/hzv7CzuzUejN/ffH/7yNbi0hKFkCbp8WPH/pPf+I2qqlqt1q1bt+bm5mLbGM26BoOBEDi/OBeUF6mcmZ15tPx4ceH4eFy//c5rd+89Gg0nUrs0SWxRTCwtzS0uzi82Go2s0dQS19c3Tx4/WhUTBPDOxWCb8Xgc4YL4Ua6srHQ6nbjnaa0nk0mEb7SOAutohSwO9GYBAKIHmNY6TVMhY1apBJhiXIfEW/yEu9IwQIwtaeSNykrnLHuOY49IIY7jP+99nDNMT5UUUAhgztK01W5HRd3UITdigRS00tGMKg6vBEJd1wAAzJFoqaXWUgMDITEBURAogw8sGRi10EZpG5gDCClDIAKWUiqlldIhACoBEIRAI7QCiYBEJFGiMs76mU6PPDADJySyUFSDwtaT4TCROm80fV1LrVSSMmAg9kSBWUqVS4NKE3OQ7DmggKDQSkAmwQghQpkIKFAKYgQGAMEAQskQnWCEAERgEAxCIAfI06SV5pPhSES3mMAsWEtNnpgYAJkIiBlYSqmV4gNqS1xJgYKWKmY0xILbaqTBVRSCrWtbludOnz12ZGl3Z+v23Xv7oyEI6YjHe3tCSK3T+VaPUY5GI2ft4WcBB6PRaWljjlTl2I3CQV2IbwgOHBiIiACd99a5wOQDBSLviVkQMaKI6ZZ1XdV1Za2Nf+rwrojn5eCDlNIHRz54W3tnKTjysbeeVvn4XNFnK4QwBfLYIQIKsbe3X1dub3e73fWxwSGiLEudq7233tdXrjz1+PHjwWC/3Wn1et3xeJykiUlMXddLiyc2Njbqut7c3CSiVqvFAI8ePUqSJJ5GnXOv/ui1GK+ttI7Jlp1257Of+XSamN/9nd/b2FxHI9I8sXbSauWz3RkIqpF3B8M9IbQQJLQ8c/bk49UH00ljnChGSch0e+NYRw77uDhnV4kChOFgwmiIhVYCUAFIJDkZ1eur/dd/dO3Bo2/t9kcMxBKbeTLTbY3KvSRLJ+U4VWnDZK5y84tL+dgj6F5nppk1Vh4/loAvPPe8D/7U8RONZkMANptNRNzc3Lxz587Zs2fjKIyIHj9+/Cd/8idFWWzvbewMdmuinb3B3Ex946O7P3jlzbX1DWu91gl5JnTnz55ZX9v+8MZHK6urvZnmj1577dzZU7/6V/7yBx/dunj+dCPLqroejcYzMzMxe9x7Px6PhRBHjhyJAEI8cDQaDefcYDBIkiQS8iLBNn64xpjIRqAD8zAppyPuQ25DrDNxYX+iq22ceETnEesh+ICISWKyLD1kIAPAoWVvCIEBGEErScQmTU2WBu+FVhQCIQitEpMgheDcYRullKIYJxKBcERkkChTk0IAV1sENDpB4gBBSw0AWmkUQkqtlAkAUkJEb2X0OhSGyCPKRGggbuhGvF2JWQnFEnp5J/gQiBGwGI5MkhV2JBITvWfzJHHk2REwoRAalURgFlE4BICeKUgSKJRUIJABPUwxfikFROsughjRGIMuhETEgB4BAAmQWRKmOmmkuXdOSjmYjBKhtE6ISAjpoy6Dgpiip8IYo5UmMQWt4g6fpZlWOpr7GWNQCGfdcH9/fm7u2atPb65tFOPxB++9W1dFbW2n3bFE+4OhEjoxiRFqf2evGhfIQMyHIREQmbQHBJ0pCYGIP9bGwpSLwHxQa733PjpmRDo2kfO+rhwFllIBCucCka2qwtrpwQgPKOiAGMkdxBSCd85F4zkiH8gxTSdp8RGfMM6p0zQloqoqA1lGhYhEkKTZvbv3+6Nrm5tbjUaj1WqurKweO7akjbS1XTqyWFbFcDhot1tVVXQ6rePHj+3t7eV5Nh6Pd3d3Qwizs7PD4bDf72eNxmQymUwmSqnZ2bmqrnUiPVlmDs4jIkowRr/22mt7u7uSAVE5B0W/EkBaw1/6+V/9/vd+uLezFrx0NhDTTC/rzTT+5M8+BIjmSAAHuX8fGzZOG14xddrk8XickXHBISZG56V1gTyjBUYBmCSqLMt333l3VDII6dlTqLVKTp86BtmFra2N4PilZ5/pJUYrtd7vd9tzs7PzWpinn3u6lefNLAvenzh+3FpbFMWxY8euX78uhXTenT59OooL7t27t7a2luf5lStX1tZW9wZ7C4vHtvf2Nzb3bHFrZ7EaT2opEylQoVJGNtr5qJhUzt2+f19rleWGKIwdnfrgo9d++L2/9Z/9r44szg4Hg83NzU6nExdz3ICFEI1GI2ICPHWn09GRIwJSke8cF2rsZxuNRpIk+/v7zCxQ5M1MHKTjTLFgFEKLuJ1/wqtthKVF7EqIKElTKRUAeO/jWne2FkJQoBoAYyMkpn6CWZpqqTiQUVokifdeSZVlWV1M4k41Go2UlMxAIcQOiGB6LkaBWmsbrJZGkABGpqBVoqQCnKIQqCUAQwiNrCmkkAKtrb13CIyojdaShdYKUQAfWEeSZ2LvvJIyz7LEmHIyRJpaXNcQREBZuTTLpVLE6F1gJmUSoxMhVRQMgIhNPzACEQMiCyBgQGQAGzwFAkJEFErHWhOYoue0QhQCE6GaaZYoPSkKKWWcCBhtEGM7xpFsL8RUZqO1hikfAGScFkqRJEmWmFQbIg7eu2JCxFmqu+12akxRFEVVDsdDJSQJ6QJzoMp5IVUnzRt5YzgeT0YjRAFwmAUNzBTrOwoEAkREgRSIo71xtKyl2MkSIQUgEFNuiQvBEzvvAwXngvMBGKWMPGu21tZ1TcFOpWg/AQcAEUIIwQdAoBA4BMQpTEGBg7chEEW9GYfoxhv/ezGZdDodW9ccEAVoIZ64cH5zY/Px8nIkQiCKQX+/ruv5uacmk9HTLzw/Ho/Hw+H5c2fzRn7v3t12q727s2etLcuyGBfamFaSoBA4HkulJpNC66kMNEnSQBRGoyzPqrICoDju29zYZA5KqjhzAECBkJv0U8++1GrOrK1t7Q/GtSMhVHAueFmW1Xg0EUKAYCYGjBtYhLMBDmMvACIHJO59ZeVRSgYRKgtCEHlhwsLSLPjAwfd6bSEgGbmt3Z1Ot3npwpVTx5ZWVzfu3LoPrn7p2ae7eTPYkgDL0q0sf3Ty+Nnl5cdGK6PNxubm9s6OEGJ2drbZbDLzaDQsyvLNN9+8/+CBlPLq00//2q/86mQ87u/vP3j06IUXX7j63NM/fP21hytbszNH2Mt7Dx402x3nfFXVgCSksnXV359UtWu2u1Vdl4Mib7Z2BsP3b9xIm81vf++7x48sfPrFF621jx49mp+fj6ZFsZmN+Gw8OkeyfIRuY3MWFbplWU7Fvgejo2azGRXAApEO8wwBiLmuK+dskiRCfMKrLQEAam28HyqpGt2cMd5ILs+yVrvt6poTE6UdAjRrhUKgVLHzbeS5QgFKee+10qk2QggppJMybeYIQislhPDWFZOCYsRmCDo1WhtGAEIlNCpBRAKFI6uViQ3FdFJHTkopBXnvtVRKSJQoOabMo0ZNEDzHLFlpTAIA5Itms9HrdhOlN9c2inLkQgkYop1ZzdZZywFTX+dJnidN9CF6bNdUCxF0kiZJIoADk6fA0xYQo9kiMwZmYhCIqCQzI0ohpHW+dBaRjRBKSKNUr9tztQ22To1CEJJBSh3nSkpOuVZKqjiTMklC0c1eawhklGIgY5RWqAWzq2xZIcCpI8cGg+ETly4uLC7cuXt3dWUFlfBAhQ3WBUBVTMpAlBijpYQQ8izXZlx5DwIFSnmQ3QSHLS0QRlQUkRFhKhsLBEzAJMiTJ2QK5H2w1tWWvI8EgylLAgCJyHtXVXUInkKYUvaIpzpqImaI1LcQCBEoRLuF4H2kfHnwHmI4XYQ1mAFEFDkqIWxVlmUlQHvnz5w50UiT19543Xq/MNc7euRIkiS7u7tFga6uFmfnJeDtj25mJqmLcm9n16hEgBwP+8PBkIHTPM+yLN7k1jki1tpEhVKW5Urp4WAkUZbjkoiAY+YRSCGmXwGCYAQvyS/0lk4dPfnuu++tbq0LaVBgCFVixK/9yl8lL+7efRiHqZ58VMaLqdIy/h1ixoOvITa+jEhTeUlE71UdHBEtzDTnZ7oL84sXnrj8+uuvK3Sj8ejM0WMLc/Pf/+Hrm6PqiRNHMYTKlkWwDx88fPbJ53/qp07fuXX73MnTo8H+0tKira0P/vjx4wDQbDbbreZLn/7UyvoaC/jUy5/+1p//+fWbH9G/+TcXzp4DgJm52T/4w3997NjCpKb19Z1We0ZLU2ZFljU21tekhMpWla2OLy2cP3Ws0+ttbO3cuHXHKI0I1labmxu5xvmLp/MkzdK0qqrV1VVjTFR+xgDdiKjE/L1D+q33vqqqJEkOe95YmvmAJ3OIZNa16/f70ezGJEkjz8uinEwmRF7GPvET+0CBEJ3Kct3uZEChcqWUQqu00WhkaSqFcFUZkab4hk2SWB8AIA5844E3/ij2aNZabTSDKsYTZbSrnQveBY+xrDjbm+nZg0FkVLlYayM9U6np9T3E++ITxa2PQhBiCpBrrbXSlS2IyGjdbnecC612azAWUqpiUpq2abU7zGE47iupPQcXPII0WpMnBDEuSiDlrDNZM0tzROkoBO+DUkLKSFESUkitOdYCRGYEAG1SRBRCMkNVO+d9IDJaG5QShdEm0VoEgEAMIKW01k+xyIPQ0PhQSgFDoAA8tZJE4tQkAJznufPW2Voy9zqdY0ePddvtzCQLVb23t7e6vmadY0RnvXW2qGwgODyXMXOaZSEEZohzN600w/SQjge2gYdoLE6jgg98wWNjG2GyKREanPNV7FyJ6WCoFUJwtQshWGdDCDj9s7F3OwQn6GNobAAEby1HU/Pgg7fx+ZgiyezjM6WpsGI8HiOi0pqYG41sZqaX59mzz3y5meczMzMffvjhyy+/HChsrK23W+27d+9WVbWwsDAYDHb398+ePbu9vd1oNHZ3dyNzfjQajUajA/BUaK3jQFgptb+/XxRFvICHaw/wMHrtYCaDAoXp9TrO1++++66SKjAggnPuiYtPfu7zn/vut7+9u7NnkoR5KoYGRmZinpI9os18rOB4EMCKQsTnOhymaS2BaW5m5umrV4RQwNhud5555tnRaDQeF6PRw8H+YGnhyHNPP51reO/aWzvjIbO4d+fO2dOnf+5nf+bN19648tRTZVWdO39ufX39v/6//tej0ejXfvXXLj952Xv77rVrKyvLi0eOJFnKIFrt1vrm+sLCwuzc3OWnnrx154Obd5Y3NreJEgWqnBSAB7trZIzU5Znzp3/uP/r53/md/y/528Bsh5PHRVmNhj//M185cfyMr8u9vb7W+sSJE3Nzc5FbkmVZvJjxIsfqGb+OE9Eo76aPOXIcPmmEekMIZVmurq5Gxk6z2WSmLFVK5CH8LyG7IdqEZ1laWVk7m5nEmCSEoJVmHyRgNEOMNhNKKakUWhcJOoc4y+FIhJm9846c0irLs7qqrZ9Y5wBAJ8akiWMCIcLHELpIqfPOR05SdLeMn8ohwwMOHDBDoPid+DuIqLXy3jNDs9ksikJrIxCDD0VRKiF7M3OlLSfFWFPQHDBYIZUADp600SjjORi9dVJFEIFdZWVmpJAISEAYsRMpCQBQJMqYNIuOr4ioCRicSdI0S21dBec1SnbB+joWnRC8EIKYhBBa6fiuD9064nBMSsk+IAB6UoazPOv1OmUxcd4lSXLy5EkppK3qve0d7zwj9McjKSUIUZSl9d4HVkrH8l3XdbfbBSUChUlZIKLRBhEDh8PRf3wckg2mPARiPjB1jj+iECgE54N1zjrnAttpHSYERgZnbW3rA088YAamwB9zaGTmEDz7SDQF8i744L3nwMSe2U9pvFN4GISYzpEwsqYAozZBCJHnaZ6b8+fPGmO2t3Ze+vRLp0+efOWVV5RSt2/frqqq1+3dvn17eXk5zr4bjcb58+ejyjOE0O12y7KMu0s0wxFCeO+icXi0u+YD+gQfeACKA9UywMdrrqyKcbOZP/nkE9975QfekdSSmbVS/f7+d779nW/+yZ+YJIkMZziQxQv8yQwdEQGncVB4cOEOuW+Hn05q9Pxc90tf/OKzV6786EdvXv/wxuc+/4VXX/3R0SO9qXsAynIwaDbyne3lBysrpffPPf3cySPHvv1nf/Z3f+u3jh4/+sprr54+dbrVOfPEk5dBSe+9NPr6R9cDhXa7fe3DDxZ2tsuqeuHFF64889SH776/ublx/fbNzmw3b7YDQSAsiqrX6AmQZV3Gi+Oc08YsLC4sHV36nd/9nVdffVOrhAMKBcHZ3a3ta+9fW3n44C//0i+kaXr69OkIX0SzysjiiqC8PngcLpXYAkfuaUQYDgldcWI0vXQAS0tLUfIQ27tEJcH4oqyKcfHJrrYAMF1JOH3DSiRJGkKgELTSFHxQ6rDZPFB/0YFUNOABYyMW35hUTACOQnCuqisQggCE1jpJrPfNdhOlQCUhUPwvEBlzAMKYiKMfdmFxyHYQWyuNMVUVhJiO1EMIQkgE0FpPJmMibrfbnomJktyMRyPPUFVuZmbe+WDJawqhZkAEwdroLG0Gx3oKpyICBiIlMITga5umKSNKlHBQBaQQ2iTGpEVVx0GW1hqFN0nKgN4H51xwPg7R4GBDRhAUGIQUQkSm1yHzFBGlVokxHMhoo4SQiGdPnZ6Z7TYaGTNXdbm+vvHw4cOqKNMkTZSCKGdG6Tx5doHB+ZAkWTxexDwx7/3G7jagoHDQZDLHJJK4Xg/NmKdV9WDb40OvmWlDSs6H2jkbgheCtEJAAkfM6Jl9CD6iASRlrEocglfAEV6IRYqCj5Y2PgRnrQ+BA8OBaOLjTNTDkWzsueFj3ff8wtzcXPfEiRMvfur5P/uzP5+bm8+y/JVXXnnjjTeefPLJvb29+fn5EPzs7KxS6sqVK2+++SYRFWUplWq1Wmtra5PJZDwemzSNe/mB2kJF+/MIW4UDJ3U8IA8c3t4fv1Ni048CGs1sYX5+eW2bGYSUM70eTiV2xISAApgOGlg4LNwHfzBOS37ijo8CD3vbeCfmDbW9ubmxvnbqL/68e57X1/f+7R/+8cra6vbWdqORE1FV2maa3Ll/+/qNa+PJZGFhSQFWk8lLn35xfXN9bnGut9X73Bc/12t1y7Lc3dv76le/evr06bKcbGxuLC4tKWNm5+fzRv7RzY9sWb7747cvXb7UaDUA8b0Pbq9v9YvSkpdPXr5866Mb5d7oIOgTpRDnLz6BMl1Z2QAA8jUwkvUM/oUXX7r0xMXV5cdJklRVlSQ6puSmaQoAdV1H9CDey4flO37n8CLHg3Ls5OCAPxM/mkhsqKrKGBNp1IPBAJGD97u7g/7+6BNdbZmmo4BYzpRQiVHe+ej5QiGEQAKFMuqwMsZLcNhaxjskHgciJsAMMlHWR0tyQIFSyXa75Ylk8CbLIgMMQjR5ktPb/qBjNcZEFyj/MVYDTlXVU8DROxc/zgg+pEkeD7BlVaV5lmSNvZ1to/VMtzcYDaURSdaovJXByeCFAAJPLISUSqq6dMwARN5bqbQUMjY/EWU+4M4KqaQyRkhVW09TnzcAACGkknI0nlS2dt4iohbTH0TsDwVqrRBlDDyQQh4uHSGE1EpKJQW00hxCOHnsmDZyc3XN2soH73wdiHXWmJmZqauKGUIUbAG6QIGZGJM0T9PU1rW11iRJq9kcDoe1d4giuMCERIwAKCQd8GbgoMnijz2IYlznwSMEF4JjqpkssGWuyQNFkhaR91TZMA10mOZCEpHASH+AEHwkJXMIEELwwQdPwQNztF6g4BGBgZgCgvyfL8uDpjs27FVZJuncM89cfefdt/Ms63Q6Nz+6ubu9ubi46Jy79MQTJkkSY/Z2986fP7+7s3P06FFr7e7e3q3bt2MHoLXOskwq5RA/dg+LEEJsu+J2deigenBs0jGF6D98bSCl/Kt/9VfLYry1vZWnjcrVAGCtPXLqxM72zmg0QhHvDvkTeOYgwy2eaQiAplFQQMwoDprcgzi5ubnZK8+d3d58/NGNGyvLqydPnAKClZW1tY3NTrvdbnf2dncbzZZM1DvX3quK0QvPvXj+9LlnLl/Z3lgTiCsry49Xl69/dH11bW318WpZlePR+PyF8088efm9d9+emZ3Z3t1ptdvENJlMGDhrZn/113/t7Llz3/vB97/+rT/f74fhyBEoQH744E4xGQghQ5gumCzL7t17/Ed//PUsSWZmeoP9vW679cKLz5w+e+qzn/kMAr///vtCgpAiz/MYT0cHvrRwcEg9NKCBA5OjQ9+iw5IiDmJEDk8bTBy3xkgef/DgQVEU47qKdks/fuPdT3S1jQ9ETJJEKqOUbOTJ+tpGkhgGLqtKa4VCaB27znhXUJKkFOjAUJURhZBorQvkffBGawrelqUAiIUgMYmUwlWVSUxwLoSghNBSxxNkCEEgBgBttPO+KEtiyvKsqpCJY/s87XoApVLee2WMdY6YTZI77wOjEKLX6Uml8mZLCJEk2bA/GI3LpaVjj9cfEnPwFBwhSwECOI6qhA9eacnAITAjkHeBSUqJMvEgpUAhUGmpE6MB67oOaKNAKng0SVqWdQiAQlEItnbR5ywEAiGAScg4nJJKGImKGfjA8VNrPQ22YzJagQ+M1JvpDotxuTsSMqrFhU7STGkpVPAxQRNRoAveM0mJBlViEiVlnmc7uzuBQSk1Gg09BYEKEKUSwRNwAMTYbsXFzQdkPvj4fJwZKMDBeNCF4JhtCJbIB7beFmUlCBOliCNVtgYKNO2GAwCglAQMwYcQOFbeQBw8+eBs3B2mbWuMomOIPjLiYy/hEOhwABJRIghj0lardf7chbt37929cw9BKmX29veLqsoajSPHjkqtrXda62artbq2trOzE4+o29vbhyBAnMAEInfwxhERUUghIuVGCqTgYeonScyRbx4Oz1iHL88H9/nP/9SLz73wJ9/4+sbaFqkGAgbrVKMZXHj3vfdRKBQHSNHHoJvIUEQEmHoxH+imDjEKMaUvaK2U1pOimlTV1sbGq2+8PhpUv/+v/vXMfMco/Nmf+dmHjx49ePig2U5VsK1GKiHs7u4/c7XzeH3tvXfe+KVf+sVvfPMb165f88G9+NwLp84u3rv74NyFMydPnb5379GZsxd0In//X/2B916n6dGjR0W/P9ud/eJnP/fw0cP7d+9wCLu7g7pyyFIKsT/YdRQIDGBAJAFQ1/7OzTu5VL/+a7/0t/7WX//Wn37rj//dV/PEPHXhQqjrPM8vnD23MDfHFFqtVpROTA8NAvI8i9cmUiattYcejEqpEJx1ViBqbYhJiHgai1cHEFChnJmdSVKDCErpmZnZBw8ff3Tn0f7+QGsDn/TsBgCO4VcCgFAIsbOzk2ZpXF5pNs3UiuQtIdBaizGUXAofrPcuys3rqgoUIooqpUCmzKQ6ynzTFAADhzRNnPMCUCrNzFqqQ3Z6VVUByIWpbRoDE7M2xlsXS8OBhXuI8Fan06nrWjAHxmarNzs7MxgMpDHMvNcftJqtPMsXs0awdm+/n2XZ7u4uEyAJIxOJyIIESnY0xc0InA9KyThVN42cBFoi4dkIlSVGSkG1bWap89772khUWhmFNYWaqaqcdaSV1KilEMAUgo92CoCohDTaQIB4EdWBU5xWSklpbRVc3cgazVZrXE4QwaQGAAggbTaN1s46qi0CJiaJh7LK2yCgnTfI+blOu54UvTxvZcdt8PvjybgsPBExRo00AAgpQgiH5jIRSYjgzHQ+cygqi21rCDZQHXztQm1t7HeBWRJxQBusq2pvKwoOmZkDEEkBUikiqq1FCsjAURjgffA++EAhsjumh+if0FAjrHPI6j2sTcgIEA3mmfillz7NzG+88ePFhaXZ2fkHDx7v7e0S1SBwOBox89GjR6O/jPPeeW+9f3zzZmyOoq1iRL28c9M1P+2ViAMZrbTWZVlG3XIgiio+ayOCImK05vR1AaLiYyeOzvRm+3sj7xgEIHBiknarXVW2rr1UJuIGzBw5TLFJ9yGgRMYDRtjhBZnWXIgYnTa62Wr1Zme2t/f2+iOg8IPXfvjMlRd+7i/+9A9++L1Oq3v3zt2Hjx8rIxqthGgiQQXrsyR7vLz6+NGDp5469+0ffOfugztLSwtCwpUrF+/dvvuZT7/w9NMvbKzvIqgf//jHta0WF5ecdzc+unnz1u3//d//L6vBwJf1o7t3d7a2mLmclFpqsoTItnbEyEIiEEPQQi0szG+trPwf/8v/7V/7jb8MGL78hZclS1tNyLs8TRtpGhqNbrvT7Ta1VtNp8IGCGQUggjb6QAAmonw5Sk6kEnVVJUnSarciDzdeocNfjk2w1h1mKssKUZSFm4zcW29dGxdjnXziqy0Aa6WzTIYCpvZUkV+lddS5dzqdiHNF024hhCcSYqoOigBuWQyN0T4EJYSSMpBQqWZm5+tIBoq2T3GYg4i2todxx8ycpmkCbJ2LUHrc7pSUtqr/QzdFEYnQsd1QSmlQzSxTQmgh6rIsiqIzM7u/u90+eUqi6A+HwfvSlgKQQlBC6UQBEQHBAQZvrfPORVeALE2JSOJUiCyF0FIjISBaF7JMC4lKGiFFoo3yrAQqxVpAIZyL3SMyM4gY6yiVkUorAwF8cMEzCpQSjVZJmoQQGnkjTRURScRyMtJS5XmGAsaTsdFGS1mVZVVWRkhjzBROJQLmLEnzLPfSFmWJiDv7ezIxSZaOxxNgFoiHKgU8kDDAx3KhP44hHEK30Y8WhAAhnPOVcz6QDxS8d9YyADLYqo7D9xBIxD9IFCPpyfrgPXgHCMRMPnjriCiWFv44DHpQ5Q9RWvqYZ25ckQgJE6KAJBF/+Zd//sLFc3/2rW89/fTTZVl775jDieNHi2oCAM65EydOMHBV1Wurq/1+P8/znZ0dZh6NRhRtLQ+CJ8SBB8rhZWnkuVIqdr5EZKSprI1/NoRw0H7+xL6ambM0PXXy5O179776tW9MucyIWuvISXLOxa6ND4ZshyT86XhEyti+RF7K4WWJvzI7M5tm2Wg4vH37TtbUWid7+3s3JjeOHz1y8YkTd24fB9RvvfXW3OLs6dPHR5P9wtl2b/azl5/+yhe/Mt4fv/3aq9/dfNzrdhfnl/I8S7P0h999/akLT/7KX/rVvNH87Iutsix3dzdfe/ON4XhU1dWkLC9cuLC5sZkiVHXhyA8nxf5wcijAkEJIoYkDkw2uQiBlpKuHL3/muf/0r/815yf9/d1OJ/vSl15+9PARIs3O9mZnZ49NRV+y3W4fXgEGVuonRKMQgq2ttT5WW0QcjUZ7e/39vXG/v9edaV25cqnb7US6SmTahhDSJCX2DCHm66ytrX3zm998493b+8OhkNKH/yVk7kopY+jhaDRKjJRSRBh7OBzGXzi0TId4jwkZpylJopWSwNzIMu99liTTm4c5ugQ45yFqig7sqD1PAzVjAY3lVUoZa0kcWUSDn8Mw5PgvQBwtTC1yInDMgYk8UEgTw8xprwvAidE7mxvz8wt5ltRV4SpflTWyMEpqpckHFkEpxcAhBAkCpIxnOIGY5TkzBA5MhDKhEGxtEQBRFHXtnRNCKqHYEzgSzBoABAotLTEJjAMkZRKljRFaArIP3rter5uZJM3SLMudtShEWRTe1UIJYzQCpDoRiMF7ANZSMfFkPPHeywMD0OlHhdhsNLszPSVlhQKJjTGTqnDejveKwMQAUggC4AMZfqwvUQoppYzWy/8zxNb7EEIITJ5D5V3lbQBGIaMWgQhi8q1giB+ukIIDeQrxtO+dD85RCAKAkIP35ON/I45u8/9BE81TR134SU8LBzfh9OQOWiqBgv6Lv/+/cd7+wR/8wUxvbvnxymRc7Pf3Lz5xsd1uWdt+/PgxEQ0GAyJaW12zVZ3n+XA4jKSuuIoOzf3i1YtfR+wvUu7jdGFqjyJlr9eL44cDroU4hHEBwDn3zNWnfvorf+Gf/eN/trqxJbVGgVmWHT16dGdnp9frZVm2vr5OB0LSaG0VBx6IIMQ04uygqf24cTAqqZvN9mQyGY+LNMvKop6w9V40uu29vZ3Lly+ePnOuruu8qe4/urvfn4yLcdZuNJvtL3/xi89evfrGK6//9//Nf3Prwe0//uM/Xl3ZkEL+1t/9rQunzg13BufPXSqKsTH61Vd+cPrUiTNnz/7D/9v/cP7ChXMXzp08dWq0P9TN9Aevfu/Nt98OIIoqCCGD54MDbsZkDYel02dffP65tZWVX//1//jMiaNZJmkCzbzRm5ndT4fjUf/YsWNzc3PRCJyInKsjLH74Wcesxrgmy6qcjAsmiKpcIUSz2WSSG+uDDz688elPP19VtXN2PJ6MRpNWqxn/Y6vVDj4IiURhdXX1+oe3q7rSxswvLDkf7t1/8MmutsyAWFWl90lVV8w8NzfnnC+KYjAYAECr1Yp4NgBMg9jY+kCTyUQbaYxpt1vDwQCYjTHAHFNmQ+2IuCyms3vvvA+egLXSUiohlNGYJHrqlBqdog6EJYfdlhQiy7IIh2utETBJEud93OustUIIRC5HQ8mUZblU0nlflAWFUPvQynMBkKUpABSTiSBsNhtSqooKlsJoE3PuKLCSU88zW9epSZSUhEzxbAeohEGBxFEGLJGRHEUnMwBgBIUgJaZGCqV9AMeI2qR5gxy7ygmUx44uzM10vXNVVfX3dyOxKcuyxGgfvNFKSyUAlJCgpA8hVSkFGo9HRKyMjsCOP3jjnZme9W5zYyNLUynVpCxIYgASKKSS0gcQMtXKeg/METSIkw0hRDRhCh8jzMZzrnOOkDxT7X1gIEQQIgRw3gfnMTBEQQNzCH4a6IAyURmFYKvaewchsA9M7MnHfhWIkZjhP6ikccV9PD05gnrwMXYUMxijAfmv/fqvZXn2+//0D5TSd+8+nEzG3V57fmHu2LEj4/F4NBrNzMzEg+rG5sbO9nae5RsbG0VRfLyLP4SqpzVdiMO5KzOXZRlpnp1OZzwe+xAQMU3TSBcDAAACmDqxIuL83PxX/sKXPvzg2te/8U0QWgqltLx48UJRlN77brcb6WWtVqvRaIzH44MeOY5Ip9mx/LELclhwBYoQaH19QwihlGZiW9sQHDksJrS6svPjN99pNNsra7eJbXcmK8ryhRde6O/37aT8xte/8fKnXvryT38xSZLT5880suajR49e+eGP5maWTpw489b6j/vDYVGM792798577z9aXvnN3/w7f/fv/Nby6spwNProxke/8kt/5fH9m3/2za9bJtS6sD4EHwIamQBzXdcnjy+99OkXzp45P+gPLp45lyh59akny3EfQbZb3eBCM89/6rMvO++N0XGjMsYkiT48rxxYzEwXW4y9ybKsLKpYakejESICyOMnFs6d/7VGI+sPdo1RQsh2uxVPHkJgv79vTColWlsLIa9evXLq1PlzHz381re/d+/eXfKf8OwGRGCWSk0mk8FgkhhdlCXCVJ/e6XSmmg1jjDHO2kCEgHVdGmMazazValprD0VikS4XyZshUJIkUshAIU1TqVVRFBG01MY4W8PBuAYAlFJFUTjvImO31Wo55wIRHLAdpodfmNaI2OFOJpNMG2O0Dz6Qt2XdabfjGI180Fp65+OkyugEgZXUzlktNSqMphjOOYEits+x9YNIrkaSWhstmSDRxvoAggkYEAQIAcCCLAAwI7MG1EJKFECUKIMmDSC9IwkqbaZGKSXl9taWc7WQUgqFyK1mLoTw3huj0yRJtAnOIUNd10JIIGIiozQiZlkmpACCEEKz2VxcXNze2cmbjbmZ2dF4nKQKEGtXBWQlpuXMKA1SVnV9iM9GtOfwzB4/9ym3Nkx5uMTsOTCAC96F4IFs5evKsg+CAInJkidHwARklAqBAYG1BFLkfcxtwCnWEW3kCRij1hU+hiQgHGqo4GDoHJ+f48FfSimQP/f5z87Pz37ta1/b3x8ziUD1yZMn2p0GIg8G+/cfPKhK65w7derUnTt3+v19a11VVnHziHd4nueIWBbFIajCH1N2RKZnCCFN01arhYiNRiPPGwS8trZ2sJcjoogoQpynf+GLX/jC5z7327/9348mRZ51AHi210LE8XjMzOvr69baS5cunTt77u69uxsbG3BQptM0RSEqWx3W18PDYiz9xCCEjONoAAwhMDKREJgM+rWEUa9bPPfCmbx1aX1zpT8Ybmy5Z566YqTZ3t5aWFj4f/y//p/379/rtjtf/sKX3n/vvfn5pf/z/+n/sra28dv/4B889/zTv/v7/7Ld7rzyyo+WFpdOnDj1+uuvV3W1t71z+tzZ+cUFINrb2ynKSc282bdFZZWQLCA6AnY67WPHjrZb7fffvfan3/jms89c+du/+de1EKrZqUrLgRuN3HmLAiJMmOcZEVV1xWHan8UVKKWsbRk3GCllTH70PsQr32g0+v0+AHsPC4szzrlT3VOxFYuQZpzxRHVDCI6ZtNaTcbW+vn7/7s3N1UeplKg/4a40iIAYfBiPR1onS4uLo/FACqm1jpMoW9tGmhFzXdelrcXUOMo3G20JIAOTJwkCBCZGMUPtSgQUUqRaEUdZjgohZFmCyMCgtQaEgEDM1joUKjWJdz4G8LA4uGEJnfPGKGBARiZm4FjTEcHWdVkU5L1Is2azEUuJ9W5/0BdCaqWEQuJgMu1cbatJI0uclgAIqIWSEVNEFCgVcVQHiag2rX1QUioljVDgQ543JHki7zyBQKWVQAHMxIhCQ1ReCUFCxOmHlFIrKRg1o04MIxL7SV0js05TyZCZRAjhvBPE7UZDaU0h2KKMsLgxBgFsWTvvpFRJYpioqussy4zCUyePTybDcjIwmWFgRqwcVdYFImLv2CXGCAlSRcGooxAQWQqplPIuJvxOG0+iA08YIgb2PgQgD1T5UAXvmGztQuWRABnJO+DgQl17DwIYCD0ze2ud87VQSuYJaOUmFVmLFMh7DgEEMqLnAAQwHQXxFDE96G2njB9gRiBmoZVKNBMfObJ06fKlH/7w1du3bgOINE2tE97X/X0nlbx163YIodlo1ZVdXVkdDkfeO2NMVVvE6I3MiTFVXdPHWLQAIA7crIUQidYA0Op2hsNhTHNoNpvaqPGkqOs6qvgRsd1uhRCK0po0AwiDwe6HH17f3NnLWi2dZImSjsLjx4+V0pcuXdre3l5aWvryl770wXvvPX7wkAMHIkCZpnnWbAxHAx93bJj6AwOjMYmUKoToLEF1XUip4gUSpLUQDMG60jQa7ZnZd957N8s0kXRVUCR+71/8bp43f+u3fmuw3z9z8tQTZ84try4Phv2lpcXEmHYz2wJaX3m8ubmslLr6zDNf/soX1zbW33jt1QsXzk/G5Xg4HA06czOt7//ozx/eei9NJUFz/+Gq8EIQIwshFAD2+6P3P7jV7iy8+uabXobjp4+cOL7kfKWNShvGWa8SE3NjUQBxQAYpBQBPxkMlO97Tzs5Ou91Jsyz4AByEElKJQOQ9VIWt61JIIQQ2WxkAZHkipcjz9pRwhhCYJ8XE104rRdYhsnO2dkxgXnvjg+//4PXdvf7lK8/evftwb6//ia62kYk5mUyqtErz5mA4lALyPLfWRsVkkiYCpdFqOBoqpQJRCCFJTZomQFQUBYcgUYIQWsfUFkAhtJaOQmJMhGWzLIvKThQopYj3mJRKiBCPkgyAKJTSiCiVnIpHbZBSpOlU2B5CcCFIpbRUzUbDlXWWp0ma+EBVXUS7IClFnmbe+9gKS6HyRj4ZT8qyFAKZQQpZW0vkGZCIAnMIPN1BAJQy5F3tfC5MO29KpRCxqkpX1YQizfMsyQJwoBC8B0ZEEEoQs4cp3UdIKZWWAExI7Bkg+CAQ8zSVKH1ZaimFlJECJQBDbf1BYHgEsiPpTUmllIpmMVppX9dparrdtq2LJDGDYb+uPSGGuqqsl4IRWUTPSSWruuRp3DslxkihmadDiQMnNiYfvAuBgo/4AHMAroOvQwAlJUmoPDAwEHNw5Mhbxy4ET44AqS4nIThEkFpYW+kkRaVEaohDcBUzRSUwIUc6N0y39XiVpt+JD2YGIYjC3PzcaDRy3jPz2bNnrr33/o3rH3kflEKpeKbV3d/f7/f7Z86cCZ6azdbe3t7MzEyvN3P06LG9vT0iGg6HtbWZUgBQlOXU5Sd6YMY2FVFJaZSamZ2NB95+v9/pdOLLuHz50vXr13f29vHAzbnVai3Mz6+urqIQZV0FV0mFd+/dra1vtNqToubgBYR2szWeTB48eOCcG4/Hw8FgbflxVdbICIwmSYlhc3sbBR7MC0On215aWsrSxoMHj5vN1t7uXmCOGX0fw3zjFJcYAYXuzi7cvXe9kaW/9mu/trO1XU6KlZWVnf7eW2+9tbO13W21f+ozn/HOVbZqNBrkw927dz772Zd9qH/v93/vhRdfePDg/p17t6yzRTV++9232s3u5YuX6qp0rnzvvbe3V24fOXJkvygGg4kMGKOQo411YCom1Z9/69vWFQuLc/MLs9VkUpalTJogmJBW1lY77Z53VZ6nQsjSFsYYYEyTdHtzc384IgKT5cPxpC4mc/Mz3hYUIM8aZeVKjizyQIKZRV3VnXYXAcpJeTi58cEZrdkFAdhIm4RhXLjbtx/98Edv7w1KR6p2dPvOg+FwtHTkyCe62jIzMte25oSllEzECGVZxrEMCuGdqwIJKQJRkiSVsyCw1+16521da6UIMfLqiam2NSCOx+OsmYuP0cjjkME5F13rI8kuIrCHbJtDhU+e5xFYSJLEWZ8kqTGJ9xOtDIrAAEYbnqbGJMETCvA+MAMRJ4mprI1qk3mYL2vXbjaPHlm6/+BhI0+jjsmOXASPDnSBB/EwRNbW086PgVEQQ3COWfRmZq3zDJAYI5UqbU2BnbNCCKP0x2UwjSyTUiEKCmwpeB+QKEszLST5IKWs6zpJ03iMjWOcSOpm5kg8iPd51N7EvqyZ53VdNVudorSe0TNUtRNCEoWyrARKbTQKEUPOI0LCB9kwQgjrLDC6A77HQSANewoMHPc9oFBaV3HwyCEEZCGFRMW1dQGIBFTBMVLwzlsLwDGQCBAce5LycIJpiXwgwdEWF6IFMH6stgohkCO/a2o2Fulfxpg8z4uiWFpaCiF8eP1DJp6dne33+zG0MSbKzM7OOueOHj06Go16vW673Vo6slQUxanTp6JHdXTaDiEE7+PCEwdpFEIIBBYCG81G/MTLssyyLEaWKaU++uij8XgCANF0tdFo5HlelkVdW0Tpg+/2uhfOn7t9++bp06evXb89M9Ob7XSG/d0jS0urq2txHFcUxYOHD5CYmQlRKGm9i2IzAJZSMdP58xeIqdedHQ7HiMLWLmLZcTeK2IUQAtGHQAJBK7O8vP6n3/zzXkc999wLCIoZs7Rx6dLlm3du3r516+jSkb/xN//GpSeeOH3j+j/6J/9odXnt8hOXOp2ZGzc/qurqF3/xFyeT8fL649GoX9X1fn/P6PTs6fNVXQmmWzdvCYF5o2my5vbKlg8BWTIIgTJ4jnFP3XbeyszOHvxX/4f/6i/+zJcGOzsUYG+nL4RMkvTGjRsLCwtLi4tFWaRpurm5yQynT5+2LpS129sbvP/Bh8okWZadOn6ckbu9tlKIwBLBGNluz4Xgt7e30izxzt25c/vIkSPRbrwsSxTAzM281c7aIbCzYXNvsLNXv/bG+9/93o+kyvJGM8lUnqWIUFXlJ7raRodro027rRmRiZzzZVllWaaU2traQkQQSIFixAgRzcz0yIfhYOBDyPLcexc85c0mSplkKVS1C76TJMQcFSPRXzFWgXa7fSijiiOaqPqNv3DITIrmILEMCZTeBYEySRKwFhCJoK5dCDQeT/JWU2szHk+U0t4HZ31g8oF1ku7s7ydJCgCZwmYzHxeFVNpZKxB6vd7Ozk7Ey1qtlhBiMBgcTk6FEEJI74O1VZ5nqUm1SaSQ8T6QUhqpgtYU23JEJWXMd2LmPG84F+raMpFgSJQWgAoFBJaA2qRKighmRcFivBqHZDtmztIs4i1xUKOVajYa3W6nsPUHH930IVTO2RC0QqmkFkIrCQDhQAYdd6woSCGK8xhyzsdxzeGonZhZCB8CKEHALoQ6+CCRGMhzPSnK/shXFRMrLQGI2JdVKQNJMXU/QIFSIDNTCN57EAwIaDRZ5UOtowUwokCQB4yfeHmjQ3n8rAFBCkkIxpjxeJxlWaPR2N3ZXVpYbLdaKysrrVYrhDAcDnu93okTJ2ZmZlZWVra3t1vt1tGji0II56o01VqLI0uLOzt7q6urBwQAxAN5khAiBEpTkxqVponWqtNp7u/7ZjObm1uYnZ3d29uLYwAAllIeOXLk6NGjKysrOzs7dVUjKhCSnHvqqctS4clTJ+8/XJufn0/SRqvZLMeDZrOZpmm3293e3rbWIgoOQaGxIQQiIRUwCIRGsyGlMEafPXtuNBqurW3ubO8akyDiAdYd977IG0NiIg7EAhEFiv5+H0hcu3ZtcWHh5MmTP/je92/d/CjL0vnZ2TRJ1jc2Hq+u3Lx18+GjRwsLS1euXm22mgzwmZdffv/99ybFuNNpraw99MEBsNZ6ZXml02pLwVmWKCWPHT85rt2k9ixieh+iEN7VzSRFcE9eOvPEuTNHjp669MTl/+kf/86T58+89NILeZ5LKYXAkydPPnr0iJgp0HgybjYaPoTlldWlhfk7dx8WZbWwePT+g4f37j+qa9/udhrNoBKjhVSZkgqsdUqpubl5a21V2f3BuKqXtd7c3t6uqirPkpMnT7Q7MxREMak+/PCj9z+6c+fug8fLKyhMIO73B21IiHwI5Kz/ZFdbAGBI01Qp5wKgwOAomqENBgMKJLVywddVHTk9jbyRmmR3d7eua5WYoq5GxbiRNVDJqq6LoijLUmhVlGWz2YxwKh4oSWKnNhgMWq1WHBwDQBzHxclGtAhqt9v9ft85q5S21kkZidBYlhUIYbS2Vd1ptYP1AOwdUbBGp1JKEemMSqEKTMQgyqrOs9SXJTFrrYqiDMwm0VVVzc3NWeusrWPHnec5HQTW53kOLHxgECIwaqmIIM9yrXVlawGACIkxad4AAIafTNiIqK4q74kDSyF1HLtxFEUJCqSUFEJMU1JQBA5x2HpQ4oUQ4ujRo/39/mAwEEIkSdLtdKLgonDOeSqtdQGE1gSgABOtpRSOph/ZoeQ/8q6sdYiSAocQ6rqu63rq7hEIlRRGO2+D84BovQMpAAR5N94fDTZ3dUAI3rmqBmbBQgujZFSKAaJSmjkQExATsZDSAxATK5k0m6QTrD0EgsjlOLBlOBjB/8RSKyrrGMF7nyTJpUuXbt261Wq2og9AHOtXVSWEOHHihJQy2nQREVEYj0cRoZqdnUXErc2tSAg7XHWHhyoiiga7S0vH5uZmAZGJWq1mlucrj1f7/X5MypmZmWk0mmVdz83N1XU9HA5Pnjz5+NFyWTqtE0aam5vb2dl84tKTq+u7g8EgtSFUlQ/h0aNHdW23t7ejSrjZbLBSo/GYWaCUIESapHVdKaVbrZyZjdF7e/uj0aSq6wPXSgZBSkMjz8fjiVQiZjEhRG9i8MGnRirNDx7cefVHiRTimatP/+Zv/o1/8c9+96NbNz/3uc//uz/+o/5gsL2zTRAGg8HK+tozzzz/6Rc+tb6+/oMfvNLpNsfjEUNQGolUXdvLT5xYml/Y2lx7+ukrX/+zr0En3x/VlgTAlN3HgbUURbH363/tV/6TX/8VJcXm9vi//e9++9ZHH/3sV76wO9h78YUX1tbWzpw5PT8/r5T8l7/3+09cunz16tXt7e35+fk333r7wtlz40l1/8HDk6dOHz95utWdLSs7Keo0zSD4qpgkaR7dEoInYxKl7GBUrW8P799/b2lp6ciRI7NLC8V4sLK+mw3s+ube7/3ev/7o5l2VpswIHDdRp7Xe2dk+d+6cEGrQ/4Rn7vKBpShzCCGKF611k8mkqqoY3Z6YFAGBodduN7J8OJy2gc45ClO2bFlWZVUWkwkeZAE456qqstbGgcNoNOp0uodMTzrgG+R5XlXVFLJkRoGRn2hMonVM2MrLsrTWAiAFquoamccxxRax0WhEqwtEhGnKE0qlQghxJCKVambN0XgSY7e8c76qOt2eVJKZtJ4OQ21dt9vt6HMBwNpoEKIua22SQCHyB9M0kVKiEkor5wMKKZWeWph774IVIhLXoz6TkSOaC8istBRCeqBI5JJSKKUVTjU2U+NKKZh4e2s7TmmEEFme9ft9hTCYjHb6gzpw7UgliQseKRiZ5FnqvBWM3gcmPlSaK6Wqamr+Xtu6mJSxFodDIyUEF3wA8hQQMQB7Tz6Qd74YjNGRDMI7K2LCrvdAUmpBSiKCD5an9uJ8AFUrAmD2KEAIIQEBhCAGROdqJgLgGK3EU1EZHDLDiHlufo4BovNst9tdWloCT6urq1mW7e7uNZoNqO3GxqbWU377k08+6ZztD3akFKdOnQohvPnmG5ubOyFMKStw0NvSgcReStXtdlEAQzh//sLO9jYALi+vWO/GRVFVVa/X896lWf7EqVNXn3761q1b1taNRgNRdjtNafRwTGU5Of/U+cl4fO/ePe8cJb4oHQe3u7NLRNE8E1GMRmMQwADEhCAChUCh1WpJKXd294zWr7/+xuLiovdeSa21CYGNAYJSKjKp7JpmHI0CKQIWIhBZpaDTzVsNUirf2FgO3nlXPHX54jNPP11W1dra6vzCvEr0pJy0Wo3RcHLv/r2bt2/du3e3vztotVoPH90fTvYQqNNpFRM3HJTrG2ujwUAr8d7772VpSgxF7WrrEQVCkApe+vSLt2581DCNT3/6maWlGR/od37/D1//8dutVvPcpUuvvf7m3dv3nnv+2YcPHybp+WPHjv7t3/zN2vqqqpqt9urqWt5obG3vNlvtxyurD5fXzp67MJ4Uf+HLX05TsbW1O9tt2bJ21onMICIT7uzsjEaTlY29lc391956fzR8pdPpvPTSS+1W/uEHH+zs7D9e2dwfFEKmFEBrycSNVg4IjTw/cexJFGJnezfQJ7+3RRRKgqRgyXnnbDWeTIIPDDwcj7I8JxfIk5ZSKjGaDMfFJG+1RpMizVJkMMIg46SYlGVZlGVijDFGSDUYjmOrNRoXzpMP1EqS0XAkpSrKWmkzlfcgMpFWKkvTcVk08kbw3igdIyGyRq6lElkOxHVdM0Jd1wLRMXsiIYWnwAhpngGAjLG7xJlJAKAsS621d74GASiNwdSoRmZGwxGG2gfwgV3gQHzlqatrjx/H/nc0GmltGNEYszQ/X1s7mUy8cTrVO7s7SZIIL6RSqZQCBYdQ+xAQAgOg8IGYWaAEAYBCSpQIykiplNYamF1ZALKQKJU0SfQUF1HN4b3PTT4qRhx8mqaMoqqtHQdrrVJiPClqF0oXQMiqroEpVyoBgZ6QgXxAEIk0jFDbuiotV0Ep7b33zpVl5b0L7K23cfyvpLIhFOyc9zx1+A7WeUcYXEgSowLbSenAEdm4q1EIwMwSIwcuBBYoQwglU6INEUuUUiVMBBC8JEhVYGAA1Ag1EhEKSc4TkZDoAwktEfHMhfPj8VgK7LTbTz751DvvvHvu3IW6rstJ/+krT73/wQfNdptYfPmnf25va/3Rwwdaq1NnzowG/b293Zde+ky70xkMBl/99/++qmuJ0mTKWWfdVImDgIeKCiFkUZTNs8dOnz3tvHu0vCylXt/Y7vUWJde9Rp43suMnli6cO3/p/MXBcLC93ZiZvfLg/iqzRMGtppqZXZzpdWrLy4/Xy3GZKimDs9Y2G41KmtpbrRSwj2TFwIgChOQ0S7IspRCqorIEAUWr3T5+dHbl/oOOTtmkR0+efLS6srG1LSWR86PBWCkjUEBQgEIIoEDMJBRWVelt0es25+fmdrZ3xsPxv/pX//bKk1dB4bvX3t7a3jh5+vT5s6d8Zfv7++1u661337RF5QOAEoWrjBG5MLn0SS/b3d97tPygkbWMURR8IvDZF57fHt3LxBBASJERuK988XP/xW/+9eNLCzOzM+1mo5HlC3OLZV0vHVl4+slLC61kbWM9TWS7lSmJk/Gw1UiaWbpejvr720KK/f3d4aC/cOTEsLTXr9/59nfewMB/+q3vferFZxupuXTx7PPPPtvrpA1QDGp/VHz1T77/rW9/b2Vti4Xa3d1FxJW13dt3l6XEYjIJRFIqFBKItNAQGIjrsk6SpBgXq6sbaZrWtY0sik/wAwEAvPe1rSdjZ631vo5876gxJyZrrUDs9HpENBqNEEV/OKytNUnCzFKIqiyrmIiZJPFsGHHJCBHOzs7Wda1Us6ptkqZVVVWTSbPZDCG02+1D8nmaZcLodqO5vb3dbDSM1j5Qq9XiAz9pa62Mc60D96yjR46MJ+Pa1jH6JYK/SWLiqC06EKKQjiGAFCia7V5dl725OQRM0nyv30cXQvArqyvNVtMHL6VsIFhru62uMWaa1tNoMNFoNCaiWE+7nY4yBpji2DgQYYxSnA7bOb6eiKtGYgMiEHPUvx2S+aWUcX51KORvNpvAIV46513twpS8FXztnPOUZlqCyBKdK60BpBKj/m4gyPIcECpbV7VjmCYhVGV1ANRGswsSQiJE+agKztnSMhESS0R2wbtAzivAwDHoEwWKGPgGsWcMKLUkH0IkqxPpPEnyzNvgvUWUzKyApZQBp/YaACwPLEmkkoiIwPMzs81WczKZnDp58vqN61rrJ5+6vLG+0e/3e71hVZbNPN0b7Cujiqp4+eXPZimW5fDc+TMvf+alr339a1rpL3zh8zMzC9/7/vfefvvtuFxrWycIUzOtqZ8kCCEPJnHQbneUMuNx+dFHtx48eNTpdJMko+CUxPNnzxC4F59/TgmpUT68f08KMTM//9Hth9LoEyeP+VA9//zTALCyvH771r3xuLDWVlgBQCNvNJutyWQrOi8DgJCKgQHBe/fC8897ctfev+YJhTIA3O00x/29v/U3/9NRf3Lj1s27jx5ubm1Y7wyoRCtnQ/AuTTMlJaNgIgwopEIkrU2v3Zqf70mJc7NLW+s7/b1H7VZ3OBxu72ylWba8vCJYLc7O/8xP/6wHvnzpsiuqV3702sbOzt7+3rnTR430SlDh8PjSydmZxWNHjvdmer/3L3+312kuHTv+cGNXqz2LcPL4KcbKluWTl55Ymp8Bhg+u33zl1Td/9ObbQqlEKwru+PGjPlhE1lrF2SOTryunlQYSZe0vnH/q5p2bt+4+HJX23MVL2+ub66srDx4/vv/wAXBoN/NPf+pTT1w4ffn82dm5xe98/9V/+s9/z3qW2kwDkwAFoqtdzQFBxMRuARwpQwKFMcbW1taWiOqq9MEvLS2dPHnyk11tGYA5+GDr2gdGhIgtRg0YEdV1LbVoN1rGmJ2dnfFo1OvN1EUR8ccIxfJBiJmUstlsOufinK2u6zjlmN4PZXloejCZTJimHjQRcwRmJt7Z3W00Gr62dV03mk0GiDhDNA2JEw9xkH48Go2UUhFRres6Fqnokrezs9PpdIwxk7JEqZ31RkslRWDpK6sQk0zMzsyNxxOhdVmVngMgVmXJAFqp3cF+u9mGsgzRHBKRmRAx1YmQgoUkBAFTL3JXWwEAKOSBfVy0vjVKIVOEX/HAFPhQgxshBVv/hPuNGOOySmKqra+cAxAgcDgYB+KiLKXSgilJkk6z2UzSYX/fWS+UJs+TogxMgch5QqnIhvF4Ym0d/WiIicLUy85Zl2W6LquqLGxVe+uyNJUmqfv746IgHygEIJYCiEUIOOVoROmB0ezJuakZQtbISStyjjwJiLJj8PwTGBoFIwA7H3wgCFoqIUACdFrtvf29RqNx7+5dDpTnOTPcv38/BHr48KGUsp+odrsxM9v+6a98fm93u5Hwl7/8U5ubWzdvXX/uuacvXnzi2rUb/+YP/2h3d1cqxQDWuWi+Qx/LF5AihgHHcZkoy3Jne399bWt9bVPJFMF0WzOL853xeHR0ceHYsUVJ3G21lDR16e49eKCbncFk1J3t1HV57vzpmdnZmx/devhweWtrWwgppbLWJYnZ29t3jsKBTyMASKUYmJmklNc++KCuC+tJ6GaWpXO91qeff3pvY/nqU5f/zb/76v1H9/f7+yjC889f3dvpr62sRdbG1HpcCCEZPVJgATgZ1yeOnXz22RcWF2aajezIwpG7dx+cOHbkG3/6tfc/fKfT7c7NHdnY3NndGXqph+Ph3Tv3nzhzttVojCfjuYtP9NqNsugrifu7+wszRy5duHL27LnVteWlxSOVG3906+ajlTVriRgvX774t//mf3zl8sVcY/DOE//hH3/1n//eH0qTKiWeefopicDMTz75VFkWWZalWYbISqnJpCgmpdH5e+++NxoXpy+c3di89e57HwJCK0tOnF7SO/v7/UGr2drb3f3aN//8G3/KDaMWlo6C0KULUiZE08QTFFPvIgHIUVeESD4OWoEFu48ZDDlXCykePXr88MGjT3a1FQjToBQgCsBQlmWeN6LX53g8TtO01Ww2m83xaDyZTJIkkUoeFuLo+xsN9kMIsRWNVbiubayqsXGL6unIUoiynDRJYwGdTCZCCG1MUVetVtNZF9lLdW2dp8lkgojxX5RCoGg0GqPRKJrA9/v9KJT03kfKbWyoo0pVCAEMgSFvNqXAcjIOPjCJvNV0npuNpNvVUoputzOpqjRL9/b26qqqrUXG/f6+kDIS1NI0VUrXdQ1CxDM+SinY17WP3qQKEVBGWZoQMtEmz3NgouDjhYqvNsLWB3RjyQcurtGAcRrigACIfho3KMaTCaMGDI1mK0uMUSrL0yxRUkDwHrWWOi1dWRaV0rqydWD23jtr42WcouSBiCleUozh0rUlz0BglAk2TKqRLSouqxACAwglWQCFKUfkkKPGgay1zEQC0yyTWlnnBAolJDMIKWLgQ3zSEAIKIYVUScJEzjqJSD7MzM4Oh4PxaMREx0+ceOLixfFkdOPG9d3d3Xa70+vNpmly596tl1564Zd+4S9+9zvfBqaTp45vbm3v7e0kSXbq5KkfvfraN//0zwOgSRMKxAKlUlERHM8N8XFweVlKmWWZlGp3Z897L4QSQpw8cWo4GBSTyUyv1+10g2djzM7e8Oat5T/62p+cv3xxc3MTmEajUY3hPJ6+/uH1EGB2Zn53ZzgcTGKgblnWwBwYhJKHz8gAcZ9BhPFoxBykMTpVczON08cXfv1Xf/mP/+jf/vY/+Idb+6P+YA8kp1kyGQ8G/X1mIaWK2cdJkvJU/OGABbOkwLduPhoOxs2Gmp1t/e/+/t9fPDL/O7/zz0+eOXHmzNmtrd3Njf5kYlGqneEEkK5efsJo09/bs1XZzLtlaVutuWIyOXXi/NUrz33m5c89XlspqrI721teH1y7cXNcQlk6jfnWxkY1GX/43jtHF2Zn52a/+/1XJkXxhS994fHDB/NzMz/95c8fObrYyFLn/His8zwzWjNQCMGYJM2yP/vW977znVdd4B+9+VraaCD4XrfbbeWtppF6vpgMgSkQm7QBzKWr7z1YBpRSaiJADpE+GAsrIk7ZggAcGTbRGfQgdgSn7j8ILKRUjJ9wVxoGAAgh1HXlPRaTcZYlsc8qiiLP87yRt1qt4XBQF5WSstfr1rXTWvvgIwgQoqYaERjiZGw8HmttQqBYFqMV0GAwHA6H/DGpbrvbMcaMRqM4IosP53wIAQUqoXyIH6GJMfSxcUjTNFLKYrWK5/1DGmnMoz+0tuGpSSMCyaNHjo5HSX9vF1G127O2LidF1czSRpqClIlJAJib7b4LdeCAEIAB2AUvSLoQpDZS63goJWLlvYwGrcRSKK0UAHoiKWViEiGErWrE6f0fqcTwE6Hq1OU2JuJF2lO8dNpoRhiNxpV1PjCgqKNqOPhep22rAkhJwc3UVGVpTEJSVkVZlHUg8tZa7xnRBxI4Nbqn6BBElCRJhEGkVCoqLISU2gBzVVZ1WTrvmQICo1EsRQAixxH4nPKPEaM3MWqZJonSqnJWRCdXoQDAOR9LbVxZ004P2HsfV0ikqQXvvbVaqWNHj547c3Zvb/fxymMhZbfb7XS6w+FwMhEnjiyeO3XinbffuXnzTpqlGzuDO3fufv6nvrCxvv2v/80f3b/7kFmiZGJCiRIkMWPEpD9myACI8ciZJEmaZkeOLCHS8vIys5VSrW+saqWXjl+w1m7s7O/t7QuBBPhoec0CXLn69J3bd6rRKDN6fm5uZqY7Hqs7tx9sbOxubmwLISgw8NQuMhp4IU7rbGTNAmAMInvxxRf3B/vHT51sZ+bEkaUfvfrq45XNnUG5NywANZPTOhmPxuPxBDGJfuKRDCkkSimUMgAYqI5Ixeb2jtTdtc3Rf/fb/+2Tl59MUvPjH7+5eGRpMrGbmwNGE4Io+yOE4D11O92nrzz12huvJcoMhqPxpJ7p9Y4cOb68snztn/7jFz7zqaSVLm8te6DN3f08X0TUFLjZyI/MzxpJaaI3Nzbu3bv/sz/9lWPHjg+H+8V41Gm3m81GXVZa6cXFRWO0VIrICyHr2q2uPt7d3XruhafmFxZtXQaGxIg8z7rtRrDVsy9+6vqNW1/72p/OtNu14/F4giCUxGjnL2LSCMDH1YYfk8FAjE86/IgPedzMCCBCIOZPuHIXGHDKFqprZgattdK6Kstms9lutbI829nZ3tnenun1er2eUsb6wI69DzISU6VMEE1itDZFUY7HI611vEp1XQNAPPhHzXXk88cmta7qmHFtTILAmxsbcwsLk/E4eJ9oTUTWOWudOEjc9N6bNMnyrCzKA5cKEWUC8Yni+T3S+LMsiz/KInzOZKtSS9nIMx/Ah8AgGs2WilG0Wgvw1tlEylTr4Kx3gaWSSmhjAEVtbZo1Go18MplobYjI+cCSlFQxS01JSQzAU2PDSFGKwjklRMQ9Y/wwH3iexmimxEhjkmg6Z60tiqIOdcxgajQaJss2NrbJU7PRFCiYiEKQUpZVXRe1VGZ/OOqPRhQYEV3w8Y+EEJQQcGiDjQhE3vvJpGg2WwKlMenucGhDsHXNRHVdI6D3PgQfgDgwKhUAhBQgBTvHzIeCUyml0kYnieNpdLmQUqIIgQ4h6Xi2gNiJEAMKKZQP1lOYn1vEEFrd7tmzZ3u9Xpqmt25u9XozSikh1NraWiAaj0dznaPsw/bm9rFjJ1fW1t94450rly8MR8Wff/t7jx4uMwttjOM6S9PaWgSIEUSRox33XQBAkNEU3HsXgs7z3CRybX2VgdJUKyWWjizcffCw1Wo9Wl6TQs4vLPSHw7Wt7bTRnJubv3f77mQw/IW/9At5K33nnbeUUoE4kkOtdTj1SIyxY9OWFhGFFAwQcSet9TPPXn355c/cf3B3ttdpJOrsqRM/fueDH7z6eh0ko2BgJlEVNmhJhMAeQYDESN1TGgBj8AeA98gQGXW7u3u9XlJW4cc/fkOz7nW6vU7vxvXbC/OLjGZnOCE7SbT5qZ/6vHX1N/7kT5IsufDEE4Hg+ofXg6Ner/fX/7O/9P/5nX/53R98d3e4NamL7szsLGZ7u44ZhcCnn35qbq4DwY2HA0R47rlnO51uJv2gHmcajy3NJ0lSTCaZzqK3ZAheSgGMy4+W3333nZ/5mS9dfeaZSTHZ3lgvivoLX/js7MwcB7+5vn7tw2uZwmeuXF7f3Fte3YYQprJtAgAfPY2jAv6gdRX/gYPRgQ/wx35h6jQeCwvAJ7zaIkYufZakiEJKqYxElEKqLE3Ju7Xl7f7+brPZzrKUACvni9oRY7PZdq4O5I0xUkbjWTEa1Yii0ZjSaaOXnZRyb2/PGB2CY+bIdpJKZGnunHM2BMFaa61McM7He1sIH5wLnhF1YlzwaZ5576WQdVXjgfddrPVKqRh2ErVYUyg5Hqidk1ICYPC0u9ev66m3m6j7iOi8ohCSNM0ToyUSeedtp92Y6TYHYzcqaqmENqkLXmnlrIte0tbVShklJRICCJSRwQ8C0EUCPzACokSUyEJU3knAZp5DIJAyUCjLMkmSyAAVSo6Gwyils3XtnGcZtFJ5oxkYlJTI1EzTTOuyLNKsiYiB9E6/qK0FrIqqcj5AbKkQrHVRh+TjzhmHRcCEQCFkWdpsNcfjYm/UD4HKQcESiANT8FXN3oVAKIWSilgQEyOwRGQpQgiOmKgiL7SUWnrgmO8CAqVWFNhzIIAQC7CSnpl9kATIKESiEq2TxFWTbq/VzZvPXb2aptmdO7fnZjqtRmqJd3f3o4qBiNrt9sbWIM17Z06nO1uby3dGLzx59eHa2p9/+wdbW9tSCqkxkEuUrqNTF6I80NqGwzRSYC2VEHJmpjscDpPENJv56uqaFMn8XKvRaCRJ0pvphW2XGH3h/JmNjU1bF4vzs/du3z1y6sR3vvXd1ZXlFz71/Nbu7p0fP9jd212YnyfiQTFmAcqoCIgfCpKjXgQRA8QwOJUYE0K9u7O98vj+1SefvPbujQ0qsjzfHwy0SLzzLAMzE4iqCBV4ZBUJGwDsfS0lMk71u0oBgwJQIThkIxGUFEz4cz/z81urj5vN1u3b97RIn7x09cS5s1//1re2VsdPnDlz+9btJDc/9dNfWXn8+Nvf/d5st3fq+PFjSwtXn7oI3n/q+edef+P1zb01JiqKMC5oMCzA4xe+9Olf/qWfmZtpb21uLiwtJkmysLigtRkORidPJnVdJ0kKREePLKVpGpnjzEwBynKSGPXTX/kLJ0+cMImWnOLMvG07RhoPdza39j/66I5ChQFPnzrJQm/vDr2jYKtIc4GpacahQdxBxBD//30RO8TDbyICkBCCyH/iOQlT0SVobZTOjNY22Lq2cUcdDofjyTjPs5lejwEChdrV3vs8b0S0UaNK08Tauq4r78lamyRZWVaH2rDDZtMYHRsNpVRVV8JLPjCrjRpKrVVd14eZXUoprYKQ6jBCLtIkovYsNg4ROKaDx2EVjrYjcWimlPLexTd6WItDiLq4AAB2NA4uyVLdaGTRJzvL8rbMVGJ9CGkjHxeT6DUjEQCBATk4RGX0VLMrhABiOlAAi4NpCREH8kopLVUMRYh0HkSMWgNEdLWPyVcR3o28BW2MlJIC7ff7SmkpxGQyTpIky7J+v29rFxhq66yzdBDmOBXsMseLqRABUUuJQgQm5x0ANJqt8XgymhSTqhyMJj64sqwCBQEsouaBSMeoR+9juBiFMHXnAorHdm1MBMu894AQd+ZpzqOn6P8QAJhJCoHR4lbKJDHsKGu2263OiWPHTp0+s7a2NhyNy9ouLC794NXX0ixn5lar1e/3EbHTaz54cOfJS+dnLp5bffzo7r07u8Px9vbO/4+9/w6T67jOhPFzquqGjpPzYAJmAAxyIgGCIJjALAYxirIVLMsKVrB3f9/u2pbD7vft/h6vvZ/Tei1ZiZSYcw4ASJBEBpHjIA0wM5jcMz2d+6YK3x/VPRgGWbbX66X2YT0Sn0H3vbcr3VNV57znfRExFA5rNXIpSw56VZax0pn1mhE/EolQwrLZbLFYpJRGImHDMHw/cF3PMIx0Ot3a2qrpOJJTU67j+L5v22Y4FJo3ryscDl28ONjZ0REOh0cnJhzPs+2QVDCVTEqlkDBARCRldjNA5LREuwNKyaqqqmVLFk+Mj+WzqdUrFpkG9p095XgeZTAxlTx1+qzjuoAlaDaUScZ1Gpv22wBAEPhC6TBAUH4pAAkFRUzLYFSm0+mWlnbXyQ8ODOddDtRKJDMXx/cwDL7+1S/ZlJqmmUhO9p0+v2b16v3ZQntr6+WrV/adO7P/4IHxxBRQY/nKpW9sHjAspgLpZR0qIRoKfe3LX06Mjm19/bWbbrqBMdswLEJLG8xIJFJXV6f3K3rK6fk/kyXY3NJi2zYhxHEcRmkkEkHXKRQKhJhDF8dffHlTOuPYIbO1tTmdLVK0LEMVffdjzdIsj5D68Hezba3mpgfUeCAl1Sfc2ioAoJREoxE/MJSSJStJqef5vu+HQqGQZSpQhFDP813HoUyT4QulJJKSKKRG+EciEX2cKp2dDUO/lpZlGQbTTkzXdQUXVtTSY6YNbhAEjF3SOtbGlHOBhDqOE41GZ/zitCzBOyOfo0+ONTU1OgClOfS0b1Tn9liWrX+IlA/1GgYQjUa14aOMCamKjmcYJkWQEphBQ2ApUIZl2GZlsVCgBClBRpiQglJGCTGZ1hcqsZRKpQgSnTwGAFKVKP1BKSmEyzkAqEABlAitCWrPsqbhUoJzTSFGqRGNxh3PzWYzARcGM/XhQxNjh0KhTDrLpQpEIKUUShFCDMY8z0MAxlihUDANgyhEiprEOwgC1/UqKisoMxJTo/miowAdzw24KCVgKOlzj/MAieLcJygVAkjdUUAolYBCSoVgUwN1LhwBZhgKwKA08H3GDBFw07BM0/QDP+ABAvCAMwkE0WSUIvhCtLS2h+3wmdPnQEI8Hm9ta8/m8oeOHEUklmUrJRljkUiEUdrV2Xbt1esQ5eZNb0oCeacwMDigF7NisTjjs9M9qY2UpkKORqN6nliWFfhBJBJljIXD4erq6tHRUSllQ0N9JBLxfb+uri6bzWoh0WQyGYvFfD+ora2ZmEhUVVUyg1RVVhSKedO0lQQhZDabF0IxZkiJXEiFCLT81gvtkdeE2caGq9YvWTg38N2x0ZEF87oqK+LPPPPCxdFsR+ecCxcuJiankRANFpvtZdZuHz2XQFOwg1KghBRcBOGwbZrMMCxGzXCEmFZgWda7723LFaa5gEQq6wRw4vSFIMivWtG5bOG81OTUG2+82TV/3uXLVgxfGLj3s3clEmNTyanRiclrr79xYHBgKpXMFTJFr2hIBhyCvBu14v+/7/wuE+K5Z572XOG5sntex8pVSysrowZjtm1ns1nHcaqqqjSyaOaV1HuaWDSWyaS1vIsoCRsHk5MJIZWUdHR0fDKRjNVXGwbJe9lsLh0JM6fgzXa/zi7l/Yr84Aflv7UNnqGuBMV9X2ecfrKtLQIAUMoMg/iBchzHCzytZ5PJ5A3GwpGQbRqEUC8IpBSRaFS7R4VAz3O1op0uGpZgGCYi0SZYO9Fs2w6FQo5TmImqKS13KrXT1tSugIqKuOMWNfaAEMIYVaCcYlEHlGczJ8wAfSzL0uF+RKyqqsrlctPT05phRJT0DhQA6PVWb2y1zzQSiWh27VJOPaU6Ba4k0keIQgACkgsluGVYaFukzD/NOVBKGGOMUAWg6VwRgBGiEFGW8twBGaUEgQhVkkVEje1RyEsGVoFCiYqrUoKZpuNhlCmlMulsPle07JCOHGg3qKa+5pwrpHrBIIie50nOuR8AKNfzCKAIgnA0hpT4nHuel8vlTMsCIPmi4/o+IBEKpT6+SVAofd+XigsQRIGUCpWglArfR0oUAGNMEVQUGTVRAepjOwKjTENETMMoycUB8CDwXQ8pAQC9t0UlGQWnWAAhRoZGRgYuhkL2kaPHbcuyQ6FCoeAHwrKsrq65erYQQhDgspUr5rZ3HDy8r7GpJeAgwew9c56UcgWpdtLN4NI0QoYQojlCHcepq6tzXReBmKahhRX0/Onu7kIkFy9erKmpyefzFy9enDu3Q/NYFwqFJUuWTE1NDvRfiMc11W2YMrwwMOQ6HqXE9RxmMClV4Ltk5k0HQITqmppMNh0EQSwWW758OSDs3rM7MTG+bPHiBT2LTxw9Wl1dd7Y/wSX09Q36vqav5Qo/sGvDcvnQhwCKEAUgAEkg8oSGYvHqwM83NNRGo9ZYIp/LOUXH8blyXJ8gmRhLDvYPX7thvWVZP/3ZQxuvvT5sG8eOHRwcuZjMFFJpd3iycOutNyfS6fd2bFeAlhUuOrK5sfnWWz/bWFfrFguf/9z9C3qWJSYnTIumpqcReVVVte97o6Njnue2trZWVVUhYjkebug3q7q60nNd3/cppbFY1PO8sbGJTCYrlRRCXbHu8is3rLcrWKGYGxwYeH/PwYGB0akpPiuf+wNlBk6DSMpkPTMqSiUowmwXA5YStT/pfttSOKVYLBSLoE8Hpmm6xSIzWGU8Dqgs0+BC8iAIhcOWHeIlvSadF4saehUOR3zP1wejGekRvWnVfgBKmd7G6pckn88b1NQQAr0xCYfDuXxWG0oFoOmFEEtCRrRs7BDRtm1N4KJtrt476yxhjTYLgkCzQWvOOg1x13E2je3VC0OhUAiFQrZtKyBAGDWoFokFJJQSJGgyYjIj8DwCyjQopVQIaTCqjbgmNRSlOCoQRIWkdLjRxxsFICUlRBBJkSodDxBKCK5V2jgXgfS54Ihoh0KhSDjwA9O2JiYms9m8adqMmYJzhNImwnXdIPApYYRRkABYOlKgVNwPbNtWVGthECEEJeg6Tr5YNE0TCRYcZ3IqWSi6zLAc1/WDgItAESWVBJ0UQEBq1wGHQEkllQIARqWUiiA1DQUgfU4J0dOdGQwQiQIRcMYMCqiEkFJpiwyEKKkMyiiA5D5BJYR0iw4FqpQrpEwmp7nglZWV1dXV06lUPp9vbm5WSvX391dWVBTzxXw2Xyz4e/bsz+TcVCqjAdczmDmclSSiV9/KyspoNDo0NKQlOWKxmGXaVVVVjuPkcjkAME3T83ydjK5jlY2NDVNTU/X19U2NTVLJzs7Oxx97rK19jmkZzS3N8Vj02LEjnucCgON4AIogra6tSk8mCrmMDo7X1dVWVVVXNzYMDA5OTU1xzvv6+lzXcZxs25w5tY1tP/rJoxWxuOMrj/vJ6VQmV5QKhZIzWRgwgxsrGZdZBrcUI5KMUcpQgY/oEkalcorOtGHA5NS4bZLJYpYCk74PQiokicni8GiSCxJw0T63TSivsjq0be/2nOsPjeWKHrswlDl1dsAPstFYJJCKULumJrJ69fqnnnr6rcqKr3zhvsvuuiVeacYrW4vFYjxuI0HOZTqdEYLH4/FCoaDT8XW6fH9/f319vT5YpFPT0WhMv+xC+CE7bIdDsYqQ7/u5QtH3A8ugMSMGjS1T7ZmxkbznDc9skGf6YaaUrLD+kOCMR4EAEAIz3wBc2vF90j0JeukMgoBzTohB0JAg3GKRMRoJV3muYzCqAH0/YIYZskOGafFiUSpOCFqWjag8z9dUW5wLwzAR0LatwA8Ypb7rmgarrqp0XU/KQLsRcrlcwINoNMaDEq8rodQ2TVDgewEzGGOIAKZhMErTPGeapu97Gh8GAEJw/bJpNLV2NSql9EtFKdWWt4RdVco0zaqqinQ67bqO1ltDAKUUozQWi5qGqa0lEkoosQwrCAIhFVVACaWMoALKmOBcs0qCTptRCOV3gdASwFOBIqinhdQbYUREBR4P9IQSSqImKFOARHIhAsm5lFJBJBxilLquE7ZDVRWVoyNjCBAJh1w/oJSEbNvzvHw+L6VCYEgoAEilhIZ0SamkMk2D84Bp4SdE13MxQAXKtiyhZDaXczzftCygxURySnKlhAiEJ6hiJiuBtQhRoAQXIKVePUAhIhFSgkK9tqFURCtNAwGFjLLA9S3TUlIRJAQJMpRK0+VyCkAJmgZ1naIUAkFJpaSUbU2tSLBQyFNKA84JIY0NDb7nn+o9edddd1mmuXvXruTo6K5dO0fGxqYzWc+XhXyRMZ2qAHqZh/Jmp6wzovS2N2SHNBY7l8vTSjqVnGptnTM8PNzVObehscEwjJPHTxCE5ubmfD4fjcZMZtTW1Nhhy7LtXbt3FYrFNZdd5rpOyLaj0ZgdjnAhLcNUQnDOVy5bygzm1lUtW7Jo+47t1VVVG66+qqmp+cjxEyZTV1+1ZnhkdOfOvYQYNXWNubz/yOPPFPOFsB2WSgbSH5+YqKiomBYpJLx8/isH1hFQ4QyYAWeBoBQoP/C4cGMxyzRJMjnmOtPRCBVCNjbWnz9/FlFFIlZiIoWAStJFi1bu3X/QcbPXXb9uXs+8bHLy9OnDoag9Oj3tBJ4vCAocHp0gxPd5iBGS8oodrS3vvbcjnUptvHbD9dddB4gBdwzDsEMGM1BKpaFB1dXVWkNIc0sKITRnUDQaraqqSqdTth3WFNWO4yjAaDTmBS4oJBSUCqaTkyFqcs6JIrFIfGhgzHMEUqEH8QPQPbjUeqV0hsMl961CjZG5ZJqllHoqfNIRYAr0aVgppQzDFDwACSHbUkql02nGWDQWR0Kl9OxQyLZs13UJIhDUDgHOhef6pmH4nqNAGUxRRpEABUWQ+AKikQhKSZQ0GQ14wIXvi4Awg4P2KUghBOE8FIulU6lMvmgZhm0ZlqG471HKTEooQqAkpdQXPgHQ3skg4EohYyYPAkJYEAhCCGMWQEmyV7cOEcPhcDQaEYInk0nGWChkKSkoIQjKNq3SdgkRCaWEABItwSwFKImKaOy0ISkByQWXWJbVQUSp9GpR2o6oEkmLogZDioCag6X0acnfIKWSQhGUAIHiQgkuFCJKIb0gENznruvki6BkNBYGKUBwrmQucBCJpic0DCaV4EIgACXEKxa1LqPjB9qZ7haLggfxeNRxi0Iqysxi3g0C3tzQcDExXuSeLwL0JHg+VQE3QDKqhCRcITJqGYDUKzpK80giotSxRY6IlBBqmCXtZKAGMdyii0AYszRnkPaJE6kIABeBAiUZdT1PcL1AKiAqHA5Fo6FwKGxQ4rpu2LYdpwimlc1m4/H4lk2bR0dHOzs7V6xYceL4ibzjpzM5QohhEiVnOMhLIpLMMDjnUinX8RoaGqoqq5NTySDgpmG5jkcpHR0ficbjTp+fns7U19aFQ5ZtGZZJY7GaeCyaSqfTmcyGtev2vL+r6Ofa53YNDg93zJ27etni/oGLnlS9p8/1XxyzbXtuW308GkWUy5ct6Z7b6XpeLBa98cYNhUIuFo8gAqrOnnlN8aqqnbvFds4NKzyVSHEeEEKQsILrSimRqIaGWGNjo+MWikXOeaDgEkQfy1nfWg6vbEqwtLsTUgheLKqA++3tbdzzRRB0dy4+33c+kZrypZ9JTfiyKBUlaA8MnJeqeOK0MzbZHwRuZTSaL3qZqSz3fQZcQEEIwggFYNmURwiapr106ZodyW1zmhu7O1olD4oFBaCJn6QOABvMQMTq6mopZTQa1R487TmpqamRUk5MTITDYStscc5d19OyAwzQtgwulFKmW1SUhhRjjlcMxyMV1TYzAkQOVAO+AEBRVPKSlS27swnoK2a2/FKVzl2XDgdQ2t4i+YT7bTWUUufpKqSUUQpCSB2QiUajlLHA83VWleM4rucqRFFKutdAWuUHgU5V0pAsChSp4XueZVmRSCQej09OTnIhHMf1/IBSgxmm7wdKyJAGfUjl+r5CEo3FC7mcECIUCgESnQXkex4QfSiXSklGDfUBEDvO4CtjsSjnge97GregX37O+fT0NGOsoqJCzRB1K6XKzlDDMIRUOv9JlgGtUikCRPsrEAkzKKMmpaT8oyBECUFMyirWlBJGmWEYgeBcCs6FRtyXkKp6SdPUf0oFZR4J0wopIQrFIiVYWRGzDJMgy+RyhBDHcSUAIinxn0llWSEhBEUmfQ5Sea6rhJRCSAS96dAAZMZIJpNRoKxQmBmGUqqmuiaVTo8MjzpCKimVEmUqb9REmnrHOkN9azCDGExyAaiQIEVKCKWMApSyY4VGUEhpMCMajabT6dLjAFApn3MAiQicc0OzURIihWCU9fQsjIfDqenpbDYjpfA8AqAKhSCbzWr647a2tjlz5vT39wMCZUxzYpRTtADg0sZWKRUOh2ccfBcuXIhEIroTdKa4okY+l4+GWDgSYYzV1FSPj41altXV1T0+OZnLZf3AP3Wul1l01ZLLBy4OA7CeBT31DdUK5dZtO9LTGeGLhfPnXbt+jWUaLc1NkVCIUhgaGZlOjldVzXWdbFVVxPe9trYmoVQynTMMZlrM94qq7I7UhRksCDwNldGBB1U+J2NJRP0DYaCZlxNAf0OkRMMI3XLzLRs2XHns6OGxkYtVVbFMNpbJT2fSKUKgvi46PVUIAn9qaorQQKl8sRjxveKkHTYIS+dzjS0t8UpyoX9IESIFlGlQCaXsVO+Jycmx6qoYEJXJp8cTBUpYNpuzLMO2rVDIqq6u1oTXQggtwKrx7Foul3MeDoc1srNYLOqzhRDCMs2JRHZsPMFMKxaP796zv6uzywoZRTfve1hVXT8xWRAq0IsnAEj58RCEj3p1P1Rm74s/4dYWAAARAs4RJSWogVw6kotlebtwOFzw3Hwup8opdDqb65LEGyGhUEgnHUgpCaJt24Zh2Ladz+fT6bTCEpmMyahh2tJxA+kVXc+yQpRCwCUQaphmICWhhhdwQqmlBQG1KrL2akEprEcIEULq6as1qTS0y7ZDACVFdB110T5i/YrqlCrTNJUo+SJUSV8SoJzipS8TUhBCEUGnNevlVL8OZfexDueUPiGEmKYVsm0kyItClEVtZ7G5QlkUAoTU8umUUmIYBhoMXCl4QAltaGg4cbw3FotKBUIIZpiAKATos6bjFEzTJISiQtd19AGKEqJUiZQdSpgNiQg6uQMR4/H41FTy9Nk+J/AVIwRRopIoFYDgAgIOAEIn9ispONerphBCSEEBCaMliFIZmq1XO53RZ1th13U1Tlb3TFkXRxOzktq62onRcSFEyLJs05JSptKp0dHhYrHY0dFJCMZiMcfxJiYS9fX1iDg0NNTc3Lx9+3ZEDIIAS6ss4GyIZfm/GmQdj8c1sbKm5tBWJAgCZMQwjNra2lw2W1NbRSm0tbWd6j114cIFNwgWLVq0b/8+DuKytWv37TuYms5WVdYYjE1MjlRV10xPJUaGx6+8ckPPvM6m+mh1VWV9ba0SHEHV1S1MZtLFQjEej5gGJWhKKZDQqampkeExRmmAOk2A6OO2fjsCUOPj44SQQqGg+2qGHrPkrp2JzpeiPqAJLhAAFBJJnbx37OiZwf6RsbGLBlXHjx3v6VnQUN9qGubAxQu2Zcyf3zkwMJXPB0rJSCReW1szPuYi0nsf+LXNmzef6D0Vq6xkyCRo7JomdgDuBaD4okULmpsbGluair6fSCYnx5L1dfX9AxdByWUrltUbFisD23VcR08A7TTX8RjP88bGxnRYRX9VKBQuDAwMDY9RZi3oWXz27ODgQOLI0cOmZUlFk8kcISzgQVnIA0CilvuYGWgspZB8OJz4IRs283bDJ93akrKClZSIAoEIIbUXXEqp5QNMyyoUi9pmEUK8INBEB3qbo62OHQppHlsdpFJS2ZalxyCZTIZCIS8IfJ8rRYRQTIIQEghhpoWMBYHwaEAZc73A57yyopIx0/X8sG0LJSmhAgE10AcUo1TKUrYSowYg5HKBjoq6rqs5ajXCV4+BrupMXKW0iwcxgz8jWlkSSmTneqlQAFxqOKEGGoBUkkitd1JK00ZUOrcCylAkjZxV5XOQUqDJtiUowSUXgiBKqaTS7xAgIucBDwIEVV1VrfUCLMuqqqoaHZ8wTdO0bMctOX4pJYbJ7JDpFF3OA/0aa2NkUFb0XL32CMF936eUGYZBmEkInRgfHhkbF0C4UIL7jFFCQTElBVIgKKRCFKCUlEJwVEpnnkIZWaVKWVIglaSaCwKVYRh1dXW+7wsudf6xNrWgVJlcQRkGpYzkc3lEjEQiJmOBH/i+R0ExRtra5lAKruuEQlYikdDiN0KIXC537ty5mpqaTCajQ5061jwL3HrpZdMpefpK0zTT6bS+wLZtzrkQ0qTW5ORUVWW8oiKeL2RtM1xRUTExOXXX3fcMj4wmp6fNaGj/oWPT6TwhFEF2zm2bN2/+8eMn57Q2rbviis7OuYyqed1zlOBKBZZtCB4Qg9VWVyU4j0aiSilFVCgU6rswuH3b3hPHT/u+YMwgzNQrvS6u6yJB0zQymQyUsDRasvmDu1qpSpQl+uCMAFJfQAkg98TRw6ek4gYFApISde70SGVVbWt7zZzmNsfxfDcQgVQK4hXxurq6psaGngXz5nbNe/75l5LJbDxWl0nlPc8HyQhhmpJNKYUK62vr8oV8KBSZSmYc159MTGSnUoTSUCQcjYaFlK7rmQZzHKeiokK/MpzzQqGgyU/0bhcANDqosrJSS20VHCdeWRVJ55PT+f0Hju55/yD3eC6fQ8oINQzT4kIiEIRybghgOVPswxGz2Z98CLmBZWUQPQM/2dYW9KZLKSmBQKFY9H1HybLRVMo0TX3yNCwLEbngUN4V6tesdE6U0vc9xgytyM2QIkAQBHrXQymFgAMQ2zZ8LjWqQ6cI+z7nvq+jcHY4Ypr5gHPTNDPZnMmYbTKdF6SUYsgQlA6SKCU5F4waCFBVVTU9PS2EkEo5jiOl0IphSimd4qZdDVrYQ0qJZcQrACilDMMIuFCqtMugWmVLSYBZqBxKtKkllGrHMedcKYFl1Cdq2w3aV8tLS7WUIIELHkildSkFgCoBlfV+WRIhNFowT/PMMPRk1XbH94VQKp8rCi4VKNMyKisrXNcpFvO+wwkhgR8QRCVE3nMElpDIlmV6npJS+J4Snp9KZcfGx5LTKUksIaSSQkjJTEJNhoFUSgWCcymRUiSguCrF/QhBUlJOLDE8UBoEASOoXeFaoVIIwbl0XfcSQUH5zQGQhBghO0QpCYfDruOAlEqqkdHRrrbWzs4OwzQymaxhslQ6FY/Hausa9uzeTSm1bTuXy6XTacGFHq/SHnAmUD/bWzeTFSJLBx1t3YIgiEajBcdFpMWiM3due1dX5+FD+yKhaF1dvWHZ09PTBw8eisXiuUIwPT1NkRhUXb52+TXXrj/d23v48LHLVq9ctGgBD3zKCJSQbDJiWYDgBb7reiKQpkEJMWTg5fPOieNnBvvHnKKKx6pdzwVCdH6gKiNnTNNsaWnVq6njOFJqbFPZFykl0WcouGR/lVIUSRnoBkoApTYBqT2XQiiG0dQkb260Fi5elElnDx08HXgwk1gUr4ibJtvy9hsXBs+FzOpsyhEcUVnat0UQpVAEsbKi6vjx3vGxsYqqisGLIwDQ1tba0VIXitpNTQ2O4wCVjl+MQ0RvRwBA45Q9zw+FbA0rcj0vl8vpxCJNZQUAViiUmExa9vSmzS9OJTPFoi+4zwxLAUoAn3ugEIBJJaUE1EQXgDoNWsdi9WL/IedCyQcDALMEQfRpDBEZlP3AZctddvaXDfm/0Oez//mLPp99OwAACoLIlQSJTASOW/Sl8O2wrY+Bth2KRCLZXE5KJUAEPhdCmAYDJbVEg5RCSjQYo4QywwiHQpZphxn13aLrOK7rSsGjkbBUMhqJUmoYpjmdSjOCIdNQAIHrCRoYzACKRbdATBYEfmBQ13clQDafo/EYZZQAKkQmNUuZEiIIuOBcWKahFHpuYJlGZUWFzmBxfJcHgW2HpJJScN/zY7Go3m4DAaWU73klhCYiIOpnAoCe+4ggpDSwlHyro2AEQCfoYjkdllGUCikpcaghSCREAQRCaMVfgshFwHnAuQykFBKkAgGoFJYik0LDbmVTfUNlLO65xYsDF3wvYIQpIRAUpYigDIMKzg3TqK+rZgadTiZ4EFAkjFHTNPzAD7iUAFKB43qMUSeT9Tyvsro64NLzvalUdjqVA6Sax1ar5iAwIMBRgJISJBAFqIHGKKQMQBIove2IqEp7D6lAKRCEMcOkhJJsISu48HwhhAQtjCEEKMkYIagAUApuGZRRMjmdBQARCEaoZdpCcNfluWzWDtndXT35XM5xgmRysqoy7nqewQzbNqUSXPqU0tKeFvWOu0SRU37t0LKtmTeQMOp6LiEEEKKxaBAEVVU1gS9FwBctWnS+/8Lqyy/PpNxTJ89EY7Hnn3t5ejpthUJGVJqM1VTGPnPLxs/cttEySCadXL9uTcfcNsNAzrlphqWSpmVqfiOuSoyAsVi06Li5bJJzkS/k4rHo0qWLmlrzU6n06PhEsVgEpXzPKzuQRH1dS8gO57N5LoQSihCq2eNkWZ9Y72hVeZkXpWMngkQtvYyKUJBSEdBLj0JAtG06ODh+ru8cFxwUY8z0hdPZPr+jrbWvb6CQzyVTSZNFnCIXAhAJokSgBAlFKpWihFREKoouN4yIwaLnzl7MZNPjY5NLv/RAY30Do9gzfy6iCofCpsmkUkIGSirHLYTsUE1VlQKVz2V5EEynUplMlhLqOm5tTS33A9uyc4V84Itz5/r7zl9USJFQQqjQZxRZQhWgUqg0MWf5DKUQAMrUPnqHPxuSUDZgAKAubXhFOZWUIZB/ZVv7j7xdAQAYihQItYhhMMPl3PaKvhd4hmXGY3EpZTqTVgCCaxyyZJTYtun7vgykAkUoQaKdm5QZNjVsz+ekJMxFBOcAClFRQgIpQ+GwkIJRgkoiSJSEMhIKRTK5LGUsHIkgyHDIYgajlIYjUcF9x/dtYsOlc4TmA0BESSkBVDzgCoAxI+DBjM8ol88ZhskF13tbqZAZJgJKJaVUpmHaoVA+nyeMgVLUsMxyJAoADMOkSiEXGk0FgIQQJSWgNjmclFh1GF4KlxEkSKnJFXABEqhUQnIZcKH3s0IpoUBIxRUpuX+lEDwQQlTXVjY01NrIHFBKyHh95XQqk8nnFRLTtrgQSNA0WTgc4oFITiV9TyBQQEBKFSgvCAQCB0kYDYIgm8lyzmPxuACSSE6lpqdz+Zzn+4QQhkJwD6VUAJwHEhQnEgCJ9rMKzgMFShJEzgWRkjGGhIAEkzLBBXBZGY5RoioqKvK5ghmOGEAL+XwAAlGvR0pKDkoJhZQSJQUo5XmeotQ2TD8IKCFCyWgshoQODQ3X19cvWbwiOT01ODjS0NBUKDqu6+lQwfDwiARFmYGIOnypo/MIIGc5OgghnufrX2cGUwCmaXm+Z1DDME1CKSJEolYgCo6fW7RowUQysWXTrnQqV3QcwWUkEtPu0pDNli3uvvn6q+pi4WwmddmqJYRgEPicAmOmbYfKhPdSCOm4fjabKTrFSCQiQFATh0ZHJiYmW1o7JGHhxPREajJXyAkuQmHbcVwhpAIwTbO5uensuXNCCcaIEbKKjovlQK7e0ilQCjX8WTdUUQGouYn1igMAqgR/0vEABSiF7xeVkIxShgiAQUWcNtRXcc6jkUrfU+nkOPeRc0XQUCAVKloKeyIBjMfjY2OjTqCQEDfwOPelElLJocHx/r7zSxZ3tTbVx8KReDxuWDZAaePc0NCAoIr5vOM4hWIhnU6HQuH6uhpAoqSklLquM51KFgpFnwNljBpMEiqBE6EtpCJK59uCUlrbWy8fH8TQlrxtAKiUlDADjCPlzSuWNi6AyAjVCxVjAdO2G0sxSCitTAr+BT//Z9yuEDhDoBTQIFJKEMJAMxSWIIQiRY8Hgc+5IIQiM3nAkZqUMa7QF4pSQwpBCSHMAGoEUhEeeHlOKdXTBoQwQxHf97kiiAiEclCpTFaBCoXDyiUUDcqYL3goHAlHohUV8UQiEXDJDCwUXdM0AUnRcxUhGhULAHr/iIxRRBBCEWKEDM6FRtc6juMGgWVbskiIaRqKlfxijJbPHpQgKkqMkG1J6bhOOByWCBIRKFVKUcuMVsSdoiO8AJEQgykpAYkipRcAFEhECQgIEpjmORYSCKAEJZQQ2quPKBE4kECCUCpQwKVSCjRqDkEpKcKhkBSCGWYgRCadbqyrr29uHk0kCj4ndkQpcAKukAaKGozF4tWFQmEqmVFKhSwrVhGfnJqijJp2KJvPB1KKQGgpOUapEQS5xPjo6GihUBBCGKYhpeAiQKJ44GthV1AIyLTGhHaWSClAUSEFKiASKVKEEgOvRcxwJGRbNmOAglSEKxzXc7IOciRMSSX0IynVMDgmQOcxq3zRNQlFQQgahBqS81Qq5+S9uvpmQEymsiOjk9OZwlTybNFxPI87XlZj+whjmtySUhPKBkkppZRUZdonAYAA4VDYdb2AKwrIDIMytMNhQq1YPOJ6jhVihktaWpumkpMvvfxSvghBIIERwgxlIGEGC0V8qcLROKVEch9BZTOFYqEQDodHh8erqqoYNS0TgiAglPIgSE6lJibH6+vqLDNEwA+QU2q0zulSyBxX7N69r/dMn2HajBHXdYQUlFElJaBMZ5Kp9KROYhRCGBbNF5yA+2UbAtqfr52XCkCB4kqHjUrixDN7OqVUOQ+NSEEBkFBDggAhG1saK6tZLp8/faZvZHicEEaQIZiEMgSGSgFKIBKIUoihUMjxXY/7zDSVkq6XV4pHYlYyObFj985rrrkyXl0FSAkzA44AghCizy1O0fN8LxDeyNhoIpEIhUJ2LJYu5GM6g1FyjpCYnkpnswcPHX/33T0KOBIFUnDgEhUiKTmGFFEzYXqYWUOInp7ah6DbLUtuKt0Hl4gSSjdJSSlRAJQSFqgUzHx76a6P/PE/+fk/43YF4AKIgFlAwyxQvhmKUlS+5xmEBq7HBTdYicVO+IGtXbecm9TgghMFFAgDoqTgXBgG5UIILgyDaeVtKSSh1PcDznkoEkGFRMloNEoIcABUEkBSBD8IJifHs5kUIaRYLPi+Gw6FpSAUlRLCdxxU0jQ0GYosDYJUDBGlQCAGIVpjXHFOCNbX1BSyWRDc0JADIRXnAJf2RwCgn2kxJnxfca7hgQSRKCWDQPo+JYRQgggSpPYHAUjtSVJKcFmC+JewAoCy9Esa4aC040xpfIYOlEnJpVKcE93vgldX1EYi4ZyTd51iZUV8Ojnlc99xCtoH6riuz7lCAqAMgyUS47lsFpQM2VbIshnBSMjOF/PFnOu6rs8hX/QcxxVCmCadzKZTTqHg+Jyj7yulpOA6k9nnnCMpudoJCIkSpNIpxQqkkBJQAUIgVRAEDA1KWTgcsgzToEwobhhmwAPPC1zXy3l5RCKACAVKypKTWynKAyWF4IGGctjRGErh+X7gOlJIFKK5s7MiHqeUjAwPDQ4O5PJ5y7R9zzUZc1yHBz4SIoMS9xDnsnQSk0pHNWXZ2hJEqZTrFABACBkI35SGVNK24qZJlAoooYWcZ7HI8ODE+/vez6bdAMyAK8s04hVV2jHIA6+6uuLKdWsrK2PcKxQLOUqIbduUUNMw0+l0W1ubjghRSgUXmXSmkMuH5rQFnk8IQcCOtvYLF8ePHj+yc9ceQszbbr5JCCmVf/DAfimVYbCqqhqDGYyFhKPqWxozmQwPZGNT0/lsvwpKjlodXlRCoU4c1PB9KTVqexZdgF54SjZKoSppcUoAlFIK3w2mJoojw2dBMcaiSlJJhJI+oj6bSwCpBAoFzKBFwQPfB0QqhGGw5qbmyy9fNTU1+d577zKDrFi5tHNuWzQWs+xQPBrX/c8o86U/cGHg2MlT8araRGKCc9HeHp+e9jOZTGUFFp1iJpPxPG9qaiqdTu17/9jwxQnLjnhuILVeO+hwqramcsZFUI6yElD4oYM4AJST7BAQlZQKSgAYANTAj6LvM8YiFTH2ncsW/mu7bf/RtyOQQPH5ktf4aZ9VusIKvHwsHq2qqvJ9v5AvaKUGDNs8EtI+aU03JYSgjAkuEJGZjETsUCjEhfA9j1IStkKaKiUIAgzbmnBWSmlivKKiIgh8bhlKgR/wgAuDEArEsohpmjaNA2I4HLYtC6SUgauXLMMghmmUsHflgD5BoqQilFLKlJIsbCqluJOvioYAgDGqlBJCUlpyySqptCvINGkQSGDUMEyllGkagUl162K2GbMMzfPAOUfthlSglCgPviZkInqPAeWQKiilkCiq3xaUUlgCNbyVKwi4CDhXAg1KGUVGsL4qYhkmJbypvjY3nabSF24euVcVNYrFIrUUCVvUNL2iZwCYiBaGwpGwUiocCnHfc4teNASmQV2D2i7GTcuxDVAQBEGhWOQmDZtRXTEhhBCcgBSSSyE1EI+gRCyFxXWQAcklLlGllYQBIrGobVomY+npVFVlJTLCWDSZTPEwqa20AYgkhpSzohZKUe5pVnICoJSwmKGElnOWQnDTNNesXBj4wcjoyNy2OgPcbDbLmKnP1Bp66DiOkJIyqrSeCAAAUFJy7V2KViOAAiQlVw81GKFUcBGJhGtr64IgyOd806zkPDAAYpYVa2iUQBSSkB2urKwMAq6UQuYtXDA3FkKieL6Yz2bSU8lUY2OjZVlOMaeISk9PVlRUNjXUZTOZ0xf6PM9dvLDHMlkQBJ5XFIGby+XHRgctJm+/5brVqy+/cL7/4OHDCxbMX7d6keO6Ukrf95XAgwd7lyyYV1dXF7PMeDxWU1tjGzCdnFZlILkO7uhAa8kGyVJTNeZydil3glIEEJQCSQgCSIMxzyfzO7sQKCIjyAA9BS6CicQAUAASBKutqW9sbDx79qwGzFGDAShQvkVkdSy0dtWSru722spwZdSuioe5L7hXtCybMcID1ynkx8eG39682Q5XJhKJuvr6bCobi8XC4RCRkEwmT506VV1TEwrZvuNWxaLz53YA0ID7ABoWSUBp7IHer0r4gGUiBrMCHggukOAHDJV+5xEI06BvUVlZ2djYNDExQRkN/CCTzTDKMJ+ahE9sUZCxKfP8kJN2KKCqoNKXWBLBxlJIR0cKFcCsuQ4AoBAIIEhQskzUoV14qIAC0csyQQIISgp9XtD+XwBERaT2tWBZDQMA9DggIiEgOSpeJmvHmW8BZhZ3mBk2LHPKfAAqVKquKiFGZ+qtZPlHUEpVhhlhafdU1gCfQZ7rOpZ+sDwBVCldEJGUc35mjnsKlFIEtcUBCSiBACIgQQkI+iullJKMoATkgiLR3ahQggKhQBGiFCASosqQzNJIKKW4VEoilrYIQusXyJlYtip3ykx1yhQol4ZP4iWCpVn/h1ldi4CgpKSAIBVBoohSCEoBKgI4k3Qwe2KgthgIciaoqFBnS4Msy8ohohQCCeotWamZBKVQhKCUUssFlQdLt1IglHd2M24xVZJ9LMWpy0waqD16GsgJSIDIkvyE0HEGnYeBiCAlIajZNDW4VYMO9TMppVwITXaoAIIgoIRQSqSSUgq9bAnBuVRIiGVaSoLrOEoCYdQwSmAkzgUi6lNZeVohoOLSL9sYVEoilBzSM2/Yh/ZR5XkIswDHBNBAfdbTlrT8SqhSgAkVcCUFogVAFUgECQoYpQCkvJLp3lAAUnN5E0IJMZUKGAWKqASCIrI8//XxzQ+CmfqWnFEEyAwxGCIhqKQQApUkFCmABBBlwDzOGFzUbGjat6nbri7hjgBQoSoDcsskEqSUS6YRikJw3aU6UwqnE+f/V+1nZ3/+T70dABSYEgJCAIEqyRFRGaikQr1RL1GblQzWjAe4BDme+VZHU/VrUfJCYXnWlN6LD6KUy7a7tGjp+y6FHRUgQe2gmzXPPj6hZHYqzgdXgpmWz/5k1sPKi+Wlq0rTtvS0j9z+0QeXF4CyVVd4aVkCBQjax6jz32cunek6hdohpUomqmQ6ofwP+GCfYLkny65LBaBQaWMPSpbgMgCgFP3AGwpwyfzO9njNXFOuHJavLds6PfkJlnxlcubKS1eUky3LTxZAyu/8peZ/cKn7wIJdrliJcaY0MWfP2/Jts9aCD4wGlOdh6YNLU11eak6pgXJmtPRaUCKyLrcUL2HPcWbpgo8patbol/de6lJfzeSZytIzlVJSH5LKd4EEOWuCq0s9+HE/dqmxH+4EA/Q7pFT5BZXaoJUGs9SpZOb91ZNOzhivcm/olRURlEJAqjcD5bZ9GBWABGdQkqUalbbkM/2m91EESvsEvWUo1+sD83P2sqJK6+lHOqNskEuthdJ4la1OuSI4nej/Bd34afm0fFo+LZ+Wf7FCfvkln5ZPy6fl0/Jp+Z8un1rbT8un5dPyafnXKJ9a20/Lp+XT8mn51yi/StZWzcT4P1I+EBgtRx60/3xG8uPDOBUA9Ys8/5+WT8un5dPyL10+0aw0PlVRHwoGRpURMMJRAFdMIVfSo4pKoAqIBEGQSZCARGHeUnFXegypRIVAlDQ4OgYgA98itqOUJCghoEISqUxquwoUkShmW2MdtiWUSiHK4BUAoL+svopSqqQqJUR9fEEEpIxqOhUAYNSaEbwyDNPzXcBfeHsJhoIfjkQjEoMZXPAZqLkOo2pR4V9U249+gIRQQrgQ/0AbP/i7SCmTQpDyXTr0qjUjROk5H42bf3SV+wUQC71wEq0Qbui8DJwJNP/yx5aKYRgaKv9hyNJHn6PwFz/m0h16hlBCkaAQAgGwrCPHGAOlhPyFfUgpKzNpzn6m+gD05eNLCeNACAVQQoiPQQqUnvMxqJd/uEWAQJBIKZAQxhgPAh3CZ5QGnH9cvwFjTGj90A9WUaMIpNQouo9pwi+qAJQRyrMlaj4y2X+Fyyd3b1sCgwCEXC6PnOe7jsG+09nBoeSR02YgECEklCWUZyifKYepgCmPyYAq3wAEEFTlLJWzwKdSMCDDSdh6lAxNAVEEVUiomgDo2ZFQ3qMfQxOMiHQqOe3zoDyfyxC82f9FUv4n0czHw8Mj4xPjlNLZEByclTtPkAQBP3nylL5LKTx+/AQAEkKzucK7773n+4EGXernz/yoZiZTQDQOdPbDEdH3/W3bt6VSqTLcBBWg5/lHDh/VlcQP3IKzWjSDUCFIaD6XP3fuPKMMZrULPtDYmcdonlbe29ubyWbPnD2rGZgACaF0aio5MDB46TmXfhRKv6UJLMqPnV0rRFLGyyCh1LRMACCEHj16zCk6hNCZKs1q0KV7cVaP6dq4rtfbe4oyo8TcNLtjy0xX5WFC3b0zHX6p/2c9Uz+GMZacTh47dsLzvGwuf/78BcYMStnFi0NDw8O0LEd0qVHl3u4735eYTOiGzDCbEEIVfIB560OTBwAQgVJm26HRsbGBgUHNTPih9gKUulN94Amzu/oDYwqAepUlSChlWgPu+PETQiqChHNxsveUlArJB2cCEkpZ37nzmWyOEDozylACiyEgYJlYfZZOIs5+wuy79GASSlzXO336zKVnzlzwf0T55FpbBDAloZR6yalN/+Pvzuzfde7wPtk3khmb8CNY4XHb49NRRZSK+oqCiAbcUEGDIy1fhJWMuH5VkTOAwCZWpnjw+VcH9x3Y8ed/p4ZHFAsYiveffumt//BfZSIpTfkhlwJB5Fz+0ff+ZNObm03TAg2EV4hAAAgCkQIoYflcQSkkyIKAFwuObdn79x84ffqcYZiccwCklPFAFItFQiilLJfLAxDfC155+TUEIqXKZfMvvviSVtt95513Tp06ZZqmlCC41M9HoAhESijkHUpYcir5/HMvaZQipYxzUSw6th06evTou+++qxk8ETGfyxOkoJBzAQqVwiAobaWllIVCgVIyA8uVUlHKisWiFGpiYnLTprc8LyBIKTLOZbHgMGJQwgr5Iuey9Ooi5nN5ROK67ksvvZRIJDZt2mQYBmNs9+7dhw4e6b8wsO297UEgCFJKmet6nucTwrRZCXxeLDh6sXGKrpTg+0EQcEIYpTSfzyMgIRQBU6nUgQOHgoArqQSXShEloZAvEqQzBtfzfN8PCGGXRgSoUigF9J27sOnNzbls/tVXXvPcAJESpFJCIV+khBGkhXxBCEkpUwry+Tyl9OSJ3vfe3c6YKbgs5IuUGKBQSgwCoRQpFhwNfWeMXbhw4a//+m8OHDz0k588PNA/9PZb7/leQAkTQgmhANDz/CDglDB1iTMeCaE84HoEiwVXSkBkLzz/4sTEpGFYxWKRB4JSrcZGPC9wXZdSps9aACSVTO/ff6hYdIUEQmg+V1CK6J4sFhyC1HHdJ598UmsgEkJ833eK7swFShHP9XkgCFKCNJfNE6SEMCVhamr60KHDUigp1IsvvDSdTClFpFAvvvCKEiC4LBYcShgo5IFwHc8y7bfffndifAqRSgEIJJfLGYaRSCRefPFFVUL4syDgjuNQyjSLIyhEoIHPnaJLCdMTUrMh9/f3b9q0KZfLv/rKa67jIRCKTErQecn/enbnf2X5RHsSGMeAKaJ4lVA9a1cb1RVeIuunUqJvaO9PXmg0YpkKo+2aK073nlt5x/UHn3q5edWCs28eKFbGOlYvHN65Ly7Mjl+73emqQ8u86v6784kx99wwd4qCSSVEa3e7NCJc8QIVpvjAmYcxduLEyZUrV44Mjbmub5rmuXN95/sG29vbt2/fftdddx04cMA0jZMnT8Zi8XvuuUdbnJtvvsk0bATy+GNPrly1smdBz/j4+M8f+XngB3feeefw8NDhw4erquruueduxoxsNv/DH/4wEonk8wVE9Dxv9+7dlZUV27fv2LFjx8033zw8PHL27JnW1pabbrr5sccel1J0dXVHIqEnnnhqxYrlCxf2jI2NP/Loo4Hv3XDjjYcPHxkcvKjVXLZs2XL06NGqytrPfvbuCxcGQ6HIc889d/nlq++48/Zz584+/vjjhmF0d8+b2zm3UCh2d3ft27+/saFx586dLS2ty5evGBy8+Dd/87c9PT3XXXfdz3/+syDgV199dSaTOXLkSHt7+1133WEYxvbtOw4ePBiLxe767F2aCV+/D5zzV1551TRCt9/+mZMnT/23//YXV111VWtr88svv0wpu+OO2+fOnTs6OvrUU0+H7NBn7/7spk2bU6lUNpttndM8Mjzyne9+Z/u2Hb29J+vq6n7t13/9maefnpiYAMDly1YQQvv6LoRC4ddee10I0d3ddf/99yOBF55/sb//QiaT+e3f/u3Dh48ePnyosrLqwQcf/OlPH6qurioUCu+//357e8fEROLv/u77zc3Nd9115yOPPOo4xdWrVzc0NG7evElK8eUvf+nFF1/K5XLr1l25Y8fOvr6+np6Fb7zxRqFQuOKKKwBgy5bNN95448GDh4Tgpml97eu/yRjduvXdjRs3fuYztw4NjYyNJs6dO/dXf/U3q1atrqmpRoT9+/ePDA8XCsVvf/vb77///qlTvY2NTZ/73OcI0pHhUSng5Zde18I5d9999xNPPGUYVnv7nE2bNpmm+YUv/HpTU9P0dOrZZ59NpdK33XbrsmVLPc9/6qknx8cTQvCbbrqZ82BqMrlnz55IJPL5z3/+hz/8oVZCXLRowRNPPLFgwYJ169b19fU9//zz8Vjl3Xff+8ILLxaL+ULBqaurTSQS/+bf/O5rr7124UJ/a2vrPffc/eSTT01OTkaj0RUrVgJgPl98/PEngkB8+ctfMgwz4Pz5559PJCavvfZaJGTr2287jvPAAw/Ydsh1vZ/97JGbbrrprbe2pNLJ+fO7hZCPPvrYypUr58+bPzQ0/PjjTwjBr7/++r7z5z/3wOfeeGNTc3PTnj17hOC33HLL0PDF/fvfv/XWWy+//PL33tu2ffv29va5o6Pj3//+D+bMafvMZ2575JFHfa+wYsWKa6+9dsb59qtbPrl7WwBQqAqGJKjiU865t/aceufg1PhI9sy5/hc2VS/tbLh7XfbIKRhN5nvP00BMHznpjyeKp8+vvv2mM29uZb4/Xcz0HT3KCHOitkflsa07QEoWD4fQkJQ2rlrEbJubRAu6zi6Usm3bd8Tilf0DFwf6BwGwqrL6woX+48dPnjvXd+jQEdf1Nm16e/HiJadPn+3vH1yyZGltbf2uXXtM0/rxj3+azxcW9ixCJO+9t23RwsW/93u/H43G9+8//Pu//z3Ltg8ePByJxPbs2dvW1v7bv/2tSCSsNXLWrl173XUbc7n8ypWrW1vnnDvX9//8P/95aip1/PhJStk3v/nbp0+fmT9/4XXXXT9/fg8hbMuWt1evuvyb3/zWW1u2rl616pprrq6rqxNCNDc3LV26/ODBQ1NTyaGh4enpTEND02233S6FyGazFfH47/3e7505c7bv/IVMJu/7fGI8OTExiUgWLlyESDs7537jG988c+bcW29tzWTybW3tmzZtGRoaDoXCCxb0IBIhVF19w9Kly44ePZZKpbSd1cc9y7LWXL7m1ltvM01r0aLFX/rSlw8dOvzCiy9XV1dblv322++YppXPF6an0/N7FlZUVk9MTD744Oej0Yr1V27o7p6/fdvO06fP/PGf/Cch1Lb3to+PT9x22+360EoIHRgYTKUyjFnf+ta3e3vPBAFHIGNjEzfeeNPq1Wvee2/7oUOHf//3vxeJxPbu3Vcser/2a7++fv1VGzfeUF/fWFtb/53vfPfChf533nlvfDwxf37PG29sikZjy5evGB0d7+8fHB+faG5umTu3c83atbfddvuZM2eHhobnz1/w1ltbBwcvLlu2Ys2aKyYnp77xjW+l05mJiQQA5nL5uro6x3FbWloIYV1d3V//+jeOHz85NjaeTKYmxhOf/ew9XV3zTpw42dk5d+HCxe+/v79YdAzDHBubSCaTqVT2t37ra0IoRHLVVRvWrbvy9dff/Na3vr1y5eq3336XMdM0rYULF4VCoT179hqGVSgUz5/vv+22z1hWJJVKj40nmltaly5ddvzEyURislAofutb3x4aGm5sat6wYcOKFSuEEJlMJpPJLly4OByOTEwkvvSl30Akt9x6W1NT87vvbh8dnfiP//E/TU0ld+7cnc3mb7zxZqXQMEwpVTgc+fo3vjl3btfu3Xsty0Kk8+YtqKtr2LlzV2o6NX/+gvvue2DPnr2I5C/+4i/mzGlLZ7LHjp1YtGjx1q3vdnV1XX/9dd3d3Ujwrbe2rlmz9utf/+1t23blsvmDBw8PDQ3t339ACFlf3/jWW++OjoxdccUVq1atEkKsWrVy48brGxoa6+sbvv3t7/b1XXhn63tjY+Pz5y/YsuUdLQ7wv8UK/QuWT7S1pQoUgoMqW1+x8ne/svg7X4yZISJlxDRxbCqZSVApTMvkRSc7OORns0QKu7ma9DREuKqORbpuv7J++TzTU/akOzYyuuI37qXESB45P3XwLMvxdDIT5F1vPBvLS2NWXAoRk8nk0NDFmuqatrY5u3ftIYTW1NRyzvv7+69af9XmzZuXLFlKKamoqLztttuKxeLbb2+tr2/wPN/3/RUrVkxOTk5NTmkb4fuB5/me5ykpXdfzPZ9S6nkeIdT3fH0KBgAAJaXQ3opoNKI1GorFopSCUmIYpm3blDJNI6K5uwhS3/cdx6WUSKWE4Ajg+/6TTz6jRfE0n4gCGYvFdPo8ImqFRKWUbdm5XK5QKDqOc8UV6664Yt3TTz8zPj5OKTNNUxOSRiKR9vaOG2+88frrNy5evOTnP380l8srqZ55+lnTMDXvlOYA8jwPoEQi47qOEMIwTK1OZBpGJBJbtGjhVVet9zy/oaHx3nvvPXTw0PZt2zQ9aywWNU3Tsmx9vnZd1/O8+voGJOSdd7Y+8MADUOIzBKXANE3LtAihM2dVwzDD4TDnApG4rqdDjqGQrX9dK4FSSplhECSE0FAo1NTUfM8997z22uvZbDYcjgSB+NznPgeAjz32BEHqui5jRjgcaW5uvvXWWxljsVgMECllhsEYY0pKQkhTU+OJEyd8z3v7ra25XM5gzLZsANCRVcaYYRihkJ1Op5988ql4vEJKKYScaYhWTjOYGQS8fJo2XNfzfY8xZhjmvn37Dx8+Wl1dEwRCKYhG45FIdNOmTffeew9jRuAHTz35tGXZlBDf9ymlWpVLy/NwzoUQ7e3tn/3sXe+9996BAwdDobBhGNFozGCGZdlSSs6F7/tBwFtaWgqFwr59++6///4gEIjE9wMecC12wLk8derU9u07amqqAz9ARMMwtDPd9/01a9b29vZ6rhuyQ3V1tXfddadWf5gZHd8PHMeRUl555fqf/ezn3d3dFfGKSCTa1dW1ceN1ACoajWJ5tfY8DxQQQkzTpJQAYiQSaWpquu3Wm/4PMLXwCbe2PpVxB2MyJq5YyhXxpc+bGsJtc5u/cHuY2fnTg5SCsag91Fx3+vUdNSuXh6ub+YpuX3pLf+3e9LR77p2DJOCSBkj96d2HT/z5Q1UL2usXLTi+bTdPpE+88japiA28/G6QSgl2aSwJIRMT49ddt+Huu2/76m9+kVL0XZcSWLRwXntb0+rLljU11vb0zL3t1hu3bd85Ojo8d26HYbB0OlVVFY+Erc/e9Zmr1q87evSQFN4NG6+5ONj/t//9b6TwN2xY99d/9Ze2Ta/asDYUNjrntmbz04888lB7W7PBQMmgpbmhuirW2FBbUx2f09q4qKf7z/7szzraWxcvmt82pxGBd81tq6uNExQXzp9TMrj11htO9R5/9JGf3377bTVVVXNa26SQBmU98+efOtk7f97cTDo5r7ujtrqiqalWikApxRjr7+//H//j+8uXL73mmqv7+wfefvudrq65Fy8O7Nu3v7uro6W5rr2tCYHPaW24/roNlmVs374tFLLOn+87cuTo0qWLImHLMHBhz/xTp3q7uzuLhVx1ZbXkkhGaTqVBqvnzu8+eOWlbtLWl3jSxo73lnnvuHBm+ePTIkXgsgsDz+fSuXdsNk3TP62hrb7Is0t7RaoeMhsaanoXzVq9e9ud//ue1dVVz2pqy2ZRlG6+8+nI6PYUo53W311THOjtaEIP58zqUDEDx9rbmcMisroot7Om6esO6v/6rvyAo112xur2tCVTQ2lKfTiWTyYn58zpB+nPntm7YsLaqMvruO28TIhYt7D5//mzrnKbp1NS+fe+PjA6vWLGkpaV+6OKFhQu76uuq3nnnbUZl25ym2po4AT5vXjtC0N3VHrKtwPM/c9utE2Njf/7f/np0ZKixobp1TiMhorurrbGxpr62qm1Os2WyhvqaOa1NnR1zTp86OX9e53QygSDmtDbWVFd2zW2jRHZ2tkQjZkdH67Gjh+7+7G0/e/in586evvmmja6T6+iY4/uBUmDbpud5uVwul8tGIuFXX31FKdHWNmfe/K6TJ44vmD83k55atGgeqGBed0dFLFpZUdV7otdkRmo6tWf33op4dG5na9fcdkpkZ0eLaUBzU92ypQsX9nT92Z/92bzu9srKqOMUKaUvvviC4xQAVGdn2+NPPDI5ObZx44Z4RVgILxyx0+lkZXUsFDaammojYaO1taGzY84D99/d3tZCiVq6tOfdre8Fnt/Y0EiQ9J/vV0LecssNvSePP/boz++689aFPfOamxqWLl14883XO8Xs3j27Qjab09pSEYsrqSQXLU3NuUwuNT05f16nkn5nR8uGq9ZWV8W3bduuKfx/ASnEr1L5RPMkcKKYQosDJdQF7htEoopKMj06OvXGLhhPBkp0/N/frPIp8XgxwoQQpkSHyMBARQj1eUQQqdClSppKSBFCw/BQUSyQwAQadUEiTIalFRBDAJR5MjTFnxQCyjJfpfgyopKSMeb7vmlajutr7VillJDSZERv77QMUYlGBJGXhSk9z7VCIc01pbeBQRCELTvgXEtXlb+Seu9TLBZt256h/tITTgt86SsBIAgCy7JmSMK0SXVdV8s4z5AVSaUooydOnDhw4MCXvvQlSqngWvMb9GNd17XKvI6z5LZowIVpGADgum4oZEvhAyAhxHGcSCQSBAGlVCjFCNFQs5m3YkbStcSoq7REpiSECK0/ZjBKKOecUioEp5Rq0XjXdSORSG/vqeeff37t2nU7d277xje+Xl/fwJBoseEgCBijmrxq5uf0AHmeZ1mWbriQEgEIIVxwRpmujEbIBUGgO9b1PcuyNR+X7/u2bSspCRJ9me/7lmXp8dV9IoTQwySlpJQAoOt64XBICAEIqkzYBqAQSzqeGtoUBIFtWYEQoNSMoFm57WLmv3pjrr9ijAWBJJTqX+zv73/66WfWrF27c8eOr3zlNzo6OoQQnueGQ5aWNC6zjOobS6J8+g/NbSaEYIwKUSKgQYKu48bj8ff37X/rrXdWr75sx47tv/Pd71RUVlKKnu/qua1bpI8IpmlKJTWFC0UCAFrPRjfEdV0tJD67AnrbbpoG5yX5cSQohe5ArZc8o1uKM/XXD9Qjq0dBv4P/yvbnX7x8oq0tKikJCoKAQKQmViOWIjRTHBodpI7XNK9bxCOMQ4CqaChLoCXAY6XMBaUUASASiVRIUIFUgAAYMEAJTIHHQACEBCoQH8AMzrDkASAhs1nksMybB1ota0ZhUJUYp8rv2yWiICwrLSOirhWU2YFKFKCzyJxmqJ7Kj71Ez1p6glKqpK6stMGd+WSmbrN3ATP/VAie53meV1FRUWJWUpeuJ5QoKfBDzSclNsJy3STBDzxT/yGVIpe65VJH4YeZz8rPwQ+zKGlzVmI7lBIJASUvXhxKpTKtrc11dXVSlFQsP/RkLFNQzrR9FiAXZnfsTF9d6hClZ8UHOopc0r+ZwcZdeqb+e+ZRs0d59jB96O9f1A+zK3lpcAHIDNcXYRpSpas6ODCYTE63tDQ1NjbNUOvCLHC3RqrOdFFp8dbP/8gvwqU5Bhf6B3K5/Jw5rbW1NWX6Ryi3VxFyadbNDDEBzZw9ayhn8S1eumxWX8103Yd6SV8w0/DZ335oJv8DffgrUT7R1tYUShH0iFIIhgBToUeZFBIJhijLWdJTstIhASiPgkBlCTAEAKDFFZMgKBQZ+EwRBZaPDEjAwDEkKAj7QBTkLZSgKjwQKMQ/0aeiqYc//FGJ+/IXvlrq0sxEgDJ/Yenuj79rth35qC0GgBlFT/35zMYZZttugrI89T9Atj/7hz6a7vDhd/RjsOkzNZldpV/UhBm7/9EPL/1I+a3WOzKlFBcCVElee/a7jbOs5we++sXlo8bxo20Epf7hQZyxZR967Ic+/KeWmY3ejL79h+qmRS30bvHSXZfWwkvWEH7xdPrYQg2m9wScC8RLDfzQuvWBncSHOcT/Z8tHe/X/vPKJtrZEKgAFlBBGhc8tw3CkoAI8BjaHQMiwJC5yblFApFKzySIC+BQEAgEwBBhcMEaEGfKFshDAK0pEOWtXU9a5+ycX9SH7pMBkRvAP4lRm3h+9m9Na3No78bGvh2maGjupT4WUUn3OklKapsl5QAjVXgvTNHVsZOb8q4s2W4hImHZBiBk786Hf+vDL/dEGAjDCZj0BtJdAP1+bPNM0VVkZcKYCSqkgCPTJdHYnGIahj7dBwHU9AUrKPZZlci6EEJSSkqCwlLwk96kAkX3Q9Mzs6f6BzofyOWBmhwUfY22VwYxfCjaaTTI7U7Q34B++EeCXZHnNjKYWEv7lT5vVAN2ukuo7+SdsHy7RuUuFBIUonTM+UDGp9XeVxvypD4PUSwOtvQf/JFt/6Sf+cR34q1s+0VGygIK02LGTJ3bs2GnHo1u2b+vrPWVHQ5ZpCps98cxTFyZHH3nmad8PbMJizDQoIwYBVDYhNoCtwEQEhuPp1Pd/8IO//su/2vv+HjSYYZsYMnwmTYJh0xBhxmdNHEqpZVuGYQCgYZqWZWtIvwKkzLAsmzEDCbUsyzBMADQM0zJtxgxKad+FC1IqwzARCSGUEMqYYZoWIjEM07JsghSRRKOxEyd6t259z7LsXC7/2GNP6sdSynSCkJ7QjuP87d9+v+i4uVz+zU2bLNuenEr+5V/992LRYczYtGnLX//3H/z854+6rseY8dOfPnz8+ElC6J/+6Z+nUhnbDhmGqTcLL7zw0p/+2V/8l//yZ88//xKjhm2HGGWEUNO0GDN0DTUUQVdVm+iZtjNmWJatUwD6zl8ghFHKLMs2Tctx3EcefWxkdOz5518YHBzq7T2dSqWT02lKmWFalmUjoQqAC7F161a9QliWpZPlGDUOHTr83/7bX/7whz/lXIyNjf/lX/7N3//9j7PZXBDw73//R2+9tdW2QmOjE3/7t9//f//iL0ZGRyljOtw/NDT0t//j7//Tf/r///V//8H5CwORSDQUCpdUOBG1DC1jjBBimpZl2To3KRSOpNOZxx9/wjQt/T8ANJhpGpbuDcu0GTP7+wc4F7qNl4bYsln5b9sOPfLI48Wig0gAiWXZlmXnC8VHH31MjyMgmpZpWZben5f+RoKEWpYNSISQhmFadkhnlOnBAgBmsFOnT509e9a0TNO0DMPUVosxhkj03pYQop25tm3rFDB9JaVsYiJRLDpHjhzbsWNXNBbTD9cjpcfR0HAOUJRR27YpYwBgGIaewABoWZZl2T/72c8dx9Hrn2VZoVBoZGT0xedfHB4aOXbshO4Wy7T0xEAkhDLLsrXHub+/Xy/ApmWapjkr/RAIpZZlMcMglFBKAYExBoCmZYdC4WLReezxJ03TZIahlxlCiGVbhnlpCMo5Zr+q5ROd3UAAiYKWlpa/evpv29rmvvPWtu9+9zsvvvQaKrjhphunp7O+UJMT0wYYvSfPHDx4aP36K4WUDY21Y6NjlZWVQnAhxNy53VueeSkSCn/+gQcvDl0sePLt1zcxg954401nBvvff3/f4iVLlixZrB1hhJDBoYt79+7t7upZtWrVnj37BgYGrrnmmvr6OoLk5MnegwcPrl27NhwO79y5s6enZ9mypXt27x8ZHZnTOqe7u+u//Jc/+/KXv1RfXz9nTuvUVNKy7MnJxMTExKpVq3p7exOTiRtvuBERX3rx1dHRsbq6eoKGUqR/4OKTTz3b3t5eX19v26GqqqoTJ08sXbbY84PXXt9UXVO3ceP1Bw8e++xn7zty5PiJE70ne88uWrTwjTe3/NEf/9HI8LCQOD4xdfDQ0ULRW9CzaPVll0uFzzz7YnV1xZVXrkOCN91yQ/6FlwJf3XbrZ44cOXHq1KkNGzbYtnXixIlYLG6aZmJiYm5X17FjxyzLuu666wihUqrt72yfnk7ecMONAwMDJ06cWLdunes6f/qnf/ZHf/SHsVhs27ZtixYt6uzsTCbTnsenkunKqhpmWD/+ycOI+G//7b/dvWN7Mjl9/fXXxeNRJGJOe1syNX3mzNmJifFrr7mhpqZGSpgYT37+wV974YUX971/sLf31JXrrkpMJrZsfqe6uqqQd86cPnfnHXeNjiauXHfV5OTESy+//Du/813PE1yKhsb6uz5751/8v3/1pS9/qbKy8qmnnzMMdsMN1zOD5vP54eHhefPmHT95oqG+ubf31Pj4+NVXX11fX//CCy9PT08npzOBUG+8/gah9MYbbjhx4tTY2Oj8+QvOnj3ruu6aNZf/6X/9i89+9q7ly5ft2LGjs7Nz5aqV7+87ODw8NGdO25o1a/bv33/hwvm+8/2BAEDmue4rr7xuWdaqVav6zvc/+dSzixYt6u7u2rzldSnkxhs2TiYmT585Xcg7t9xyay6X27lz55kzZz734OfSqfS5c+euu+46wzDeffe1mpqaK9evFVJWVlVRSg8dPjwwMBCLxa++egMinj17rqGhfmoqGQ5HpJSU0MRk4lRv7zXXXBcOR99+++14PL5hw4Yf/fihpqam7u7uAwcPZ7K5a665NhKJvLnpdULp9ddff/rMmZGRkaVLlzY11ff1ndu//8DCRYuWLF60d9/+oYsjc+fOXbVq1fbtOxKJxODAsDadmUx2y+bNNbXVLS3tyWSuoqKaMevsmfNnz55FxOrq6qGhoc985jOTkxM7d+6cv6C7s7Pj//7P//mLX/zi5Zevefutt2rratavXy9Vaac8Nja2c9eu9vaOzs7OfD7X0NAw0N83f/6CV199w/O8tWvX9vdffPqZZ+ct6F62dJmUMjE1uWPHjob65vXrNxw5evzkyZNXXHFFe3ubkr+I+uOTXj7Re1tNvVFf33Ddddf+wR/80Z133rlr166J8YmBwYuvvfq6ZdoIwBgbHx9/4cWXehYufObZ5/btO3D82Kknnnj6vfd2bt++O53OS6nWXH5Z37nzTz31dEN9wwsvvJhMpvsvXHzt1TeKRb+mpv6pJ5/N53JYdhamM5n6+vrnnnvuxIkTr732ekNDQxAElLLJyclnn31u3rx5Q0ND06lUQ0PDs88+Nzo69uyzz3a0d7z55pujo2NVVVW1tbVvvfV2Lpc/ePDQ+fPnn3vuec/zDh8+sn//ASXVI4888vzzzxNCwuGQlCXcguf5XV1dmzdvPnTo4LZt286f7ztw4IBpmpyLq6++anh45PTp06FQ2Pf9U6dOf/Wrv7lv3/54PL5w4cIffP/vJyenqqqq3n9/3x133FEo5LPZ7AMPPLBly5aJiQnLsrXiSHV1dU1NTX19XbHovPDCCzU1NQ899PDRo8e3bHm7pqbmueeez+ULvu/HYrHDh48cOHAwFAqdP39+69Z3a2pqPc8vFAqVlZU///nPDcOsqqq2bfvHP/5xbW3tM888e/HiRcMwENGyrN7e3sOHD1dWVjU2Nu7d+/7+/Qd833/44Z8xwxBCvPHGG6dPn3n//X22HXru+RcMwxRCfuYzt82ZM6dQKNbV1aVS6Z6eBcuWLrtwof+mm2669dZblYIgEKsvW33VVevHxsba29tn4BmmaTU2NFRWVrS2tr78yitSqunp1BtvvGlZViqV3rJlq1Jy8+a3z549t2PHzsrKyhdeeOHdd98bGhqqq6tTCl5+6eXJyanhoeHXX3/j1VdfTacz5871vf/+vurqagCMx2PV1dWZTKampuaVl18bGhp+8cWXGxubXnzxpTNnzr700sudnXNd19WtfvbZZ7WTZHo6JSW0tLQ888yz09MpywyfPz+4c8feAwcODw+NJ5OpXbt2P/vss3V19ZyLwYGLb7y5KRqNPfzww6+88urU1JRtW0oqy7KOHTt25MiRV155raKicuvWrcPDw5ZlnTvXd/TosWeefm7r29sO7D+8d++BV15+o7q67gc/+GEymayqqtq9e8/x48crK6tqa+sIoZZlB4F46623X3vttUQiMTgwsHnT5pdffjWZTIbCYQCaTufr6hqfevKZycnUM08/N2fOnJdeevnAgQPvvvtee3u7hpcg4hNPPBWJRn0/yGazlmWdOXP26NFjW7e+47reoUOHT58+PT09/d577xWLxfr6+hdfeCWTzldV1tbXNT3x+NMAZOfOXbt377EsSzvNnn3u+cCXITt8vm9g/77D+Zzz3nvbt27dOjIyUllZNTExoZRqbGx8/rmXdLZuNpurqanZsmXLsWNHn3/+hdra2l91ZMIn2tpqGhTOgzVrL29qql+1atXp06dd162srIjHY0KUnH3DIyP19Q3X33gLpbSxseHQocNNTS2Tk1OTk9OdnV2eF7S3d/zJn/zxqlWr/v7vf3jq1CkhZEVFVTxecf78YCqVKRQcz/Mty1RKgVID/QMTE4lsNltRUbFu3bqDBw8NDg4yxhKJREVF/OZbb73xxhv7+vomJiYymbTneQ0NDddcc828eQtSqXRHR8fcuXMBUDsWAFRFRfzGG28cHR1xXZcx1tDQMD4+ccMNNyxfvkJjXKSU9fX111x3XUNDY21t3eTk5HvvbVu7di3nHBEopXfffddLL72MSEZGRo4ePbZn7/5Dhw5NTU19/etf+/a3f3vXrt379u0/cODAgYOHz57tO378uAJ11VVXUUref3+/6ziIIIRQUgLA2NhoKpX2Pa+zs5NzvmrVqp6enkgkev3G6wqFwsDAYLFYzGQzCqCtrW3p0sX79u0bHBy8cOFCOp1OpVJVVVUdHe2VlZUXLw4Xi4XOzo4PRbRM02xpae7p6RkZGXFdzzCMpqYmHgRKleLaXV1d69df6bqulIJSWigU/v7vf7hu3dqlS5f6vgcAQeBblmlZFiFoGMw0DUR49tlnAeCOO27/AGxICO20HRwY2LjxuvXr1587d7YcrQLTLGnOz53buW7duiAIzp8/f801165bt862rdOnz7iuE4/H4/FYOBy+6qqr1q5d297etnfv+45T7OjomD9/3sWLQ5OTU45bzGWzVVWVV155ZWNjU1/fuTlz5ly/cWNzc4uGLoyNjV911VV33313Y2NDTU31hg0bIpHw8PDI0NCo5/nZbI4xa+nSZWvXXpFMTtc31B89eqSjoz2Vmi7k80rJpqamDRs2IOL+/QccxwGNPkQMhyNXXLG2o2NuJpMVQixduuTw4cPVNdWZTG50dMI0rWw27/uiq6t7ZGRkaGjIcRwh5Jw5bfPmdVNKu7q6rr56QzabPXeuT6NQYrFYJBK5/vrrK+JxzuWFCwNTU9O5XCEIRG1t3RVXXFFTU3327Nl58+Zdd911VVVVum9HR0c3btx4zz13V1VVlSjuFBgGW7Vq5fLly7q7u9esWZNOp/v7+6emJrPZnGnabW0dHR1zz5274Lp+U1NTOBzWipNSyptuvCmdzhw8eFQIicgsK0QIuXjx4tq1a+/67J2dnZ0VFRVXb9gQi8V1TvPQ0NDo6KimmNi4ceOJEyfPnj33qbX9X1VmlHQJ0urqGgC1cuVKHbSdO3euEGJ4eDiTScei0ampyYd/+mMh+Jo1l588eWLhwh6llOc58XiMMbp79+6f/OQnfX3n6+rq1q9fr9F87e3tBw/uj8VihsH6BwZ+9rPHfN8HgKNHj0Ui0Wg02tfX53lebW3NhQsXlFJz5szJ5XIPP/Tws88+e6r3VEVFZSQSSSQSiUTiySefOnWqt6dnQT5fOHLkSEtL8/PPP3/06FEdtnEcZ+XKVRrq2N09r7u7+9FHH9++fbuQkhAkhIyOjjz+6GODgwPLly+vrKzs7T29cGGP3vlyzhcvXtze3j48PLxv374HH/zc7/2H/2vjxuu3b9/+gx/8YPeevYRAMjlVW1v7+7/37//dv/u/9u/fr6QaHRlpbGyamposFAozs1NK2dbWVldXKwHr62vD4bAQgnOuFEohz5w543lubW3tZGISlUqlUogkHq84d+7suXN9dXX1SqlcLjc5OTU+PrF06eKAy2g02tTUNDk5mc1mR0ZGtbEwDGP//v3zF8y3TFMp6OzsLIdrEBGUkkEQYDl29zd/8ze9vb3ZbP7cub4VK1Y8+uhjzz33/BVXrD195szrb7x58NDh3bv3bN605bHHnoxEovv2vX/o8JEtW94uRdsQNbnUsmXLnnzyqVdffe2yyy4XQlRXV42Pjz///IvpdIpQKoQIgkAptXLlypdeeum11153HOeKK9Zqf2hHR4cO9CUSE6FQSFtPKdXBg4eOHTtm23YoFE4kEoSUAoydnZ1DQ8OPP/ro4OAAZRQAFi5c+MILL/7gB3/f39+PiDqta3BwcHo6WVdXNzExoUOXQeATgoLL0dHRioqKhQsXxeNxIWRbW9vkZKKxsTmRmMzlczoGSAgCKD0bNVSgtbW1r+9Cd1eXabB0OrVm7Zp4PCqkbG5uGRy8GHBeX18/OjqKqPbv36/b63k+KLVq1UohJCG0rW2OAqW/klIcO3a0oiJummYiMa7Ja4Ig6Onp6e3tfeqpp5PJpF47FyyY9+ijj33/+z/IZjJjY6PpdFojFjzPE0LovgWAI0eORKPxUMhOJCZ83zt69Mhll63yPN+2QxUV8R/+8Kc6bjYyOtrW3nHx4mBFRfzEiaNvvvmG67rLly/fvGXL3//g70+cOEEI9YOAEAQAQvDEiROUGlVV1f39/el0urW1ta/vV9vafqIxCeVQKYLEicRkXV0DpeTw4SNKqZUrV0xNTWnMSiwWDQJ+6vSZZUsX19TU9Pefb2hoyOfzUsq6ujopgXPe29tbKBRXr15lWfahw4cIqmXLl01NTg0MDLa0NLte8bXX3vj2t3/bNM3JycmzZ/va5nRYljU9PT01lVy1aqVthwBhciJx+szZxYsXIuKZM2daW1sB8aGfPnTzzTc1NzfPnTt3eGio6DgtLS1HjhytrKycM6c1m81VV1dblnn69OlkMrlixUrLMg8dOhyNRhsbG6uqKoOAj4+Pj4yMtLQ0d3R0Pvfcc0KIBx+83w9cHshkMt3U1OQ4xenktGEaFZWVtmXlcjmdJXz6zJmuuXNra2uLTrG2pkYIMT4+3tzcnMvljh070dRU39XVKRUnBNOprFKstrZmaGjo/Pn+hQt7QiHb9/3KyspEYrKmpjrg/OiRIw0NDaZptbQ0c85PnuwNgmDlypUjIyMTEwm9d5uYmAhHItFI5NChI62tzR2dnYMDAxWVldPJ6crKCkaZaZn9F/oX9Cw4f/5CMplcvnxZKGxJJaYmJ0OhkJQyHA6nUrm62jpE7O8fyGazQsi2ttba2toDBw/Zlrl8+fLR0bGRkVFCSDwei8djo6PjQgRV1bFwOOw4TmdnpxBCKZKYmKqrqyWEHDx4yLatJUsWKpB6TzQ2Nt7a2hqPVXmeH6+ITyeTDQ0NR48eVQqam5vq6+sPHz4ihFixYsX0dLKyshIAjh49Zprm0qVLkslkNputqq4+c/pMS0uzZVma8CWZnK6trRkfnxgcHGxpaW5paUEkAOrQocOMsUWLF04np+sbGiYTiXg8fvLkiYqKeCgcioQjhmEQwnK53GOPPb527ZrDh4+0trZceeWVZ86cXb58OSF45OixpqbGed2dUolMJqMhHDU1Nel0OhwOa2q30dHRqsoqx/G44E1NzRcHB/vOX1i2dGkoFD527Hhtba1tW9FodHR0rKGxARWEI+FMJlNTU3vkyBEAWLJkcTqdrqiosCwLUE2Mj1+40N/a2hIKh6SQtbUNk5OJurq6wcHBqamplpbmhoZaQgnnXM/V+fN6hoaGY7GYYZicB9Fo1HVcyighxPcDKcXZs+daW5vC4TDnvOg4c+bMOXDgYGVltLKy8sknn/43/+Z3EDGZTJ48eaazo72jo+PEyROe67W2ttXV1R0/ccIpFhcvXpzPF2prqyanJqqrqw3DyOWyx4+fbG3tMA3TcYpDQyMrViyLx2O/un7bXwlrC4iEoEaWgGEaAFDK7wLQnIGIwBgLAq6UpEzjuhEAhNBy6MgoJZQGvg+AjBFApQFVOuPedR3fD8LhsIawUEqkLKFBCWLAuZJKgTIMgxIScI6AOsPH8/2dO3Zs3LgRAIPAY4YBJWiXoTdNlFCdaKQDyr7vA6BpGFLpjCQJAJQSTQbkdYh4AADf8klEQVRaKBQ2vbnpuuuur6yMSyVAAaWGEAIRNCmskFIpRUmJZbWU1yQEIgou9a8ILgghzKBCSiG4pkInhGogI6OMUKI3mIBYSveSEgAMw+RcEIIlVmzDIAh+EDBKkRAllZCCMca5IIiUMh2EZIwJKQgSLSevc8a4EAYzECEIAgUSEbRhAkApJSVM45wM0yyBloJAp88hQsA5AjDKFEApbYlSBVIqIYQgBIXQkExkzOBBAICmaUilgsDXE4IxqoFxUqgSdpUQKaRhGIAghRBSMsoQMeAB1ZzxCkzTUEpxLpCgTidjrJR7pgAEF4TqjSfRqRxcCI15Mg1Tdw4hRAoJiACSMqIdU+X/AyH07bfeHhoeNhjbuHFja2sLAAaBj0goo1JKKbgqZ8cQUkormKEdp5RoYBYAaDcoIURT8zBGhZRKKkDQmV2IRPtqpJSGYSolg4BTWsqvk0owpvFzSpZy54BSGgScMUYpEYJLxbU6N2NUKSjxQOrGoM68wLJ4PAIAM5iUXKMRAEBIYRqmPg8pJSORqK4PpUxv9rW7X0oluNR/cx4gopSCUNRMIPpNVBKlUgio521ZTP5XMov3V8Pa/gPlH4MS/eUP+WciqxE+oI/wyxGsHy0fqq1hGELID9bkX6kTPg5b89GH/GOu+Rco/0It+lcqH6mt0kmDHzr2Goahs8IEFx832f6V+vbjyi/56X/2cHwk5+WjyST/2HIpVedXVuHqE40AmxkbvYlgBhNc/COA079kMD42f0lTOP9TDe4Hk47+eZPgA3fN0H7/ogs+WgyDcf/j79It/Qf1cn553RijehNU+ghRJ/L/I6sHADPcAh9T83/UgAIiGpbJg0tSQDou9z/DefqRhvxjyy9qzqxHE0TFPpIl8cHB1f2mGGNSlrg14MM5YP+o7DgdbtU3lusm5MfleuncWs3wIAT/B59f+ooQwhgLPP8XXTC76BDfzJPLPRx87MX6DKTPPRptQinhXJR/lApRSl3RfyMqfX79pX3yiS2f6CgZKAQFiEQISQk7sP9gsVCcUdGghOGs+pdzexCBlLnukVI2W+FDKwJwLgBQk/BrcQFKjePHTkxNJg1mlpRLkOpMhJmnISAC0eIxZRUWkkgkTpw4oUlnlFSIhJSzA2bqNhNGn52cPlNb/UP6D6WVcGZdQCkFBQiEElaWPCGXRFaQAOC+fQdneHMu/ZYEBCK45Fzs3fM+ApnRO9DrilLaOUFmHgjlBKSZCjBmhOxw78nTE+MJRg1QgIiFQuHAgYPa2CHiJekahZSwUv9DSQAGFDJmHDt2PDExSZASQhGI7gZG2b73DziOq4H3GoE/04EzY6p/JeD8tVden5hIEEJ1zScTUydP9BqGBarUFt2Buif1MM10LCKZ6UY9qSihhXzx4MFDjBqgUAtzzHRF6YGE6s9Lk0GrAFF25MjRRGKSUjbTpR/OvFIKkW7ftiOfK1DCSs+5NG2oVtZAJJYZOnXqzNjo+MEDhzUzIZaL7oCZi/XUVRI04a+uGCXMcdzDh470nTs/MjyaSEy++eamQ4eOTE4mCaGlF0Shnjyam5gSNtB/8ezZc4yZul3avH+gCQr0V5Swqcnkq6++5vvBTK3KFSRKwaW+RcKYMToydub0WcZM/XOZTPbQocOmYet/ateE/gUhxODQECHU9/lkYoog9f3g/PkBPT8nJ6d27NgzOHBRD+KFCwM8EJl0btt7Owj5FU42+2RbWwAA6jreww/9LJvJvffutoGBi07R1fNvdHRsZn9BKZ2ens7nciXXG5LA5wRpIjGlZzwPRHIqVSw4AOTRRx4fHBhCQhGo63rjYxME2f79h06dOpPJ5AhhCHRiIuG6vpIQcKEUCi4BSBBw3w+mk6liwSVIKKVDQ0M7duxIpaYR0TDMdCqTSmUIYYHPC4WilNLzvLGxMW2bAErx3DLM1iMEx8cnfD8gyFzXA0U8z9dGWQiRz+eTyaReMMbHE8WCYzBLCDU+NqEkEMJ8L5gYn9yy+W0/0D4vOT4+7rouEiSEjoyMPfro48WCs2XLO+PjE77PGTV8LxgbnWDUkAJ8jxfyDiIdH5vwPU6QaJpaz/MIIZ7nnTt3fu/efQcPHjl58lQ2m6PUQMRsNrd167uMsXw+z7nIZvLJqRSjBmNGIjFZLLiIJPCFUiiFAkAlcfeuPSMjo6ZpTYxP+n5gMJMHYnw88dZb7xQLruBycODitvd2SqHSqUw6ndPqMpRS3/cnJiYYY70nT+3atScajTFqbN+28713t42OjW/btj01ndJpaflcYWoqyajBA5nPFzzXdx1/cjIphUpMTvFAMGb5fjA+PkEIpdTM553BwYvvvvMe5wKRAqDn+Z4XTE0meSAZM3PZ/NRkkhAqhMxm86lUJgiktgvhUIRRUwoYH0/4XkCRTk5O5vP5mSnLGOs9ebq/f7CmpjaTyU0nU0io5/pa42c6mcpkcowZIGF6OrV7197+gcGKikrHcX7yk4ez2WyxWNSABFBQLDiJxCQASUxMCgmUGq7jjY9NIFJKWDabG7o48s472yKRqG2H33h988T4JKPMYCYoHBub8DwfgIyPJ1zHY9R8/rmXTpzotexQyA4TpBMTk67jMWb4vj81NaVzxJVSzDCy2VxqOm2a1qZNW0ZHxjVmVteKcw5Kea7HqDE5mcznCoQYvsddxz9z5tyRI8cI0mLBocRITk2//dbWyckpKZTnBnoP6/s+ISSbzf3WV7/R13d+Opl+7LHHw+HIoYNH/sO//4PpZCqbyf/g+z9Mp7Ovv/5mIV9MJqd///f+cN++Aw0NjefP9585fVbnCv4qlk94vZExo6/v/Guvvbl48VIh1JYtb2ez2e985ztvvvlmoVAgBL76ld8wLXPXrl379+8HUJddtmZgcOSBB+57+uln58yZc/z4cc75vffe+9JLLxOChULhC1/4wubNW2KxeHf3vEwm86Mf/SgWi11//fWUGrt373nrra1f//rXDh461HfunGEY11xzzfDwcHt7+zvvvPvAA/ft27dvdHRMCJFKpX/nd75dU1tlmMb5830/+tFPFi5cOH9+zxuvv6mUuvXWW3fv3j05mbj11pt2bN+BCG1tbXfccbuUaJjGW2+9VV/fUFtbs3//ASFlf/9Fy7IeeOCBV1997Wtf+62HHn7owQfvr62tefXV144dO1YsOvfee19iYqq3t5dz/uDnH9y8abPjFE3Tuueee/7u7/6usrIync4wyhile/fuPXz4sOd53/jGN2PxqmPHjr/55pZ1667M5wvPPfeCEPI3v/qbD/30p0Lw+fMXdHV1PfHEExtvuCGTzpw/32cYxn333/Pmm69/9atffeKJJ2644YZXX32tkHebmprC4cj77+/bsWPXgw8+sGTpQkJIOBzeuvWdIOC2Hdq9a6/jOPfee8/0dHLfvn2I5JZbbjl58uT69et/9rOff/Ob33j33XctK2Sa9iuvvHbhwgUp5ec//+DPfvYz2w4lEokg4A899HPHKQohotHotm3blFK33HLTksULU6nUj3/8Yynl/PnzXDcYGR13il48htu373Bd7/7777twYeCHP/zJwoULV69e9cwzzyDC+vUbzp/vu3Ch/9prr9m6dWs8Hstksjpn4dd+/fMP/fQhzvmiRYuWLFn6858/EotFAPCVV15bu3bt2Nj4xMTEsWNHI5EIIn7lK1954YWXksnk1Vdf7brurl27HMdpbm5KJKZuvfWWiYmJBQvIli1vDQ0NNTc3t7fNOXhwX2Njw91336MpzPX+d926K3t7Tz/33LOWZd9222defPHFxsaGefPmHTlyJAiCu+66a//+A6OjI2Nj4ytWrDx8+GhdfdXmzZvWrr3s3Lm+efO616xZMzgw/KMf/Tgajfq+H41GotH4/fff96Mf/UhKuXDhwiVLlvz8549UVMSVgr6+C4ZhnD592rbtM2fOfvWrX928+e2hoYsNDfUrV67atWtnLlf4tV978O233ykUikuXLvE87/jxkydPniCE/cZvfOnHP/lhNBpxXf93fuc7oZB96tSZF557CQm57rrrzp7tM00DAKcmJ7fv2HHFFVc89tgT3/jG17a+s625uWXHzp2g1Je+9KXnn39eCNHW1s6Y+eSTTy/o6Vm9apVp2oODQ4899kQ4HK6vb5g/vxtQnj175r777uOcL1y44OWXXrn33vukBCnhzJmz99137/79h66+ekM+X2yor7/2mmsqKipeffXVe+65p7f39MaNG1evvuzwoSNLlyz6FVXN+WTvbVEJGXR1dV65fu0V69ZQil/4whfmz5+/Y8eOffv2d3Z2nj8/ODqeQKSvv/FWbV1DwNX4xFQyObV37/uE0G3bttfV1QLgoUOHOee/9Vu/FYtVBEGwYcOGq6++WikllXJdr7q6pq6uTkpx5513XnfddTt27DjVe+oP/uAPWlpaBgYGJieTJ06cSCQS+/YdqKqqyefzX/7ylxsa6gcHBxmhwudLFi/52le/evbMmddeey0UCkci0T179mazmV//9S+MjU2OjU+2trbv2btfCETCgkB2dc0/cPDwgYNHIpH4mdN9//E//kltbd377+/P5fIAmJyalhJA0elk5sp1V91x+10H9h/avHlza2trEASvv/b60aPHurq6z5+/8M4777S2tv7u7/5udXU1F0oorKmt75zb3T9wcXxiEgCWL19xzTXXzJ07t6Ii/u1vfxuRvvnGm83NLd/73h+ePNk7MDC4aNHi9VdeeeTI4T/+4z+ur69/f+++bKaAYEwnsxMTSR7AZZddplVgb775lhtvvPHYseMEmcHMgwcPv/D8y7fcfEtyKnX55Zffe++9+/bt37v3/d/5nd+9/PI1x44dLxSdw4cPp1Kp99/fFwpFDIMVCoW33nqns7Njair55pubw+Hof/gP/761tS2bzU1PT1911QbGzM2b36qoqGTMOHToqGWF9uzd19ra8Yd/9CdHj/V2zu265uoNzc2NlMLatZfdcssN4VCop6fn61//+tmzpzdvfgsAa2rqdu/elU6nb7/9M/PmzTMM81vf+rbvB9/85jdd131ry1tz5rT98Z/8yfHjvS+//NKdd97xpS99yTTtpqamffv2HzlypLW1RSn13e9+d3p6ulAozJ07NxwOHzp8OJvNrl9/5a233haPV37hC1/o7T2VSqX6+/uHhkb+8A//8POf/7zreQEXbR2d1GCa7EgBFAqFioqKrVvfvf32O//dv/t3DQ0NnPOvfOUr7723LRqN2pa9des758/3fe9731uxYkUQ8JGRka7OrqvWb1i2dMln77pr6ZIlUshCwamqqvna176mFHzjG9+cnp7etm17R0fHH/zBH5w82fviiy/efvvtX/ziFy3LTCaTSsHll6+9//77Fy1a1NfXNzBw8Xvf+94DD3yuoqJi7tyusbHxXK6wYcNVN9ywsVgsXrw4dOTI0T/4g+91d8/btn27kvJb3/oW50EymSSUvv32O7ffccdv/MZv7N37/urVq6699lrDtKpr6qeSmcOHj01Pp/ftP2jboR07dn7rt3/7hhtufPvtrY7jfPGLX2xvb3/iiafGxsbXXH4555xzPm/evN///d9PpTKWZR05cuTgwYMdHZ1KSSlFd3d3e0f7li1vhcPhqampw4ePBlxs27a9srLyu7/z3WPHjv/X//pniURiz549QcAPHTo0OjoWj1fk8rn/3Vbpn18+2dYWlAKhQBSL+UIhJ1WJDo5SGovFmpqabrrphtraOgUYj8crK2suu2zN+vVXzp8//6GHfrb2irWxWLSysmrNmstXrVoxkybLhXAcJ5fLAYLB2J133eF53vPPv6BDDSVfKiFjY2PJ5PScOXOCwL148eKGDVdt3rxp4cIe7bZHRClK4R2p5U+kjEdj8Xhs6dIlV1+9QQhJKQ2HI5FItK2944477pyYnMpmc0ph17x56XT20KHDqy+7zA/8sbHxdDpdWVmRy6UnpxL5fAEUQdTeQ+1uxoqKipqamrVr166+bLVt2w2NjRrhm0wmJycn8/kCIQSAPP74k5FIzLJCnucDgJQyl8t5nqex5UrJcDiUzWbHxkYRUUu5aMzN2PhYJpOtrKwuFLxkMpVOZ5ubWpPJ1Llzfffee7fvewCKEAw4RyS+z1tbWhcuXPTOO9s0ZkvniZmmNTY2OjU1WV9fV1kR37Vr1x133P7KKy8vXrLQ9wPXdaLRUE1N7fXXX7t48aJUKjUxMZHJZCorKwBg185dn3vwc7FYvKKiauXKVWvXruVCxWIV06n06Oi47gTXcwCFAhlwP5We5jLQ6RJKQSwWiUYjPT0LbrrpJs65aZpSSi3nalmGUgpAhUKhTCY9OjpCiKqoqBgfH5+cTBQKudWrV+/du6dYLLS3t2viSsuyDh06dPDgwdbWVt/zdADKMAztqdYEbIZhcM4TicSZM2e6583beMPGl1955fyFC4NDQ4AKECKRSKGQj8Wik5OTw8PDqdS0ZhqKRqNVVVUrVq5Yv/5K3/fHx8enp6elFEpJpWQ+l3eK7tTkZD6XhzIpO4AyTVspCQDhcDiVSo+NjQGoysrK8fGxRCLhOK5SIKXknPt+wDk3TSMIvNGx0aGhoWeffU4pVVER93zP871MNiOlopQgwvj42PR0MhaNIinl4AkhEDAajUxMJMbGxm3b5pwHga8UWHYoFovvP3DoM7ff/sILLy1btpRSMj4+PjExHo1Gta/MdZ1169b6fnDq1CnN5pVOpycmJgqF/PLly85fuDA4OLhwYU8QcClVsVi45567jxw5MjU1deDAge7uroU9PYzRffv2JSbGv/SlL4bDoW3btlFq9PQs6OlZsG/fPt/3Kioq/veZo//Z8gm3tgAKGGOLFi3u7T21YsUKyzI6OzuWLV1y8803vP32Vtct2rbJefDAA/edO3fu3LmzpmmuWrVi5cplXXM77rvvnrNnz5w5czoWiy5duoRSXNgzryIeW7ZsyenTvaAkojp86FAqlVy//oqurs7KynhjQ93SpYtvueWmhx76aUVF7LLLVy9dunTJksWrV69cvnxZbW31smVLKcUFC+ZV11QLIWpqaubPn2+a5uLFiz97913JZPLw4YPRSHjp0sUGo1dccfmcOS3vvPNePB59+umnDh8+ZFmGwWhbW2tDQ31LS9MtN9/0wx/+qL6+9pprNyxfvvy5Z59d2LPAtk3O/c7O9sbG+tra6kWLeh544P5Dhw4PDg4s7Jm/ceN17727rVjMX3756pqamqeffnrx4h5NeXjVVetPnTq1bNmSYjGvlKipqaqsjI2MjqxevRJALlq0YMOG9fF49KGHHrrllhsXLOju6GiLREJ33HH7T3/y09ra6uuuu2bFiuVPPPHE4sULp6enCAHTsn/845/MmTOnpqa6rq5mXvdczoNQ2L722qt//dcfTCYTTU2NTU2NFRWxJUsW3XXX7S+88GI6nb7mmqsWLVq4dOnS1ZetWrZsaXNT4+LFCx3Xue++e3fv2TsxMb5kyaL587seeeTRnp55rlv03GJlVcUjP//5tddePTY2euLE8Vgs6vvu5ZevrqqqePjhh++4/TOtrc09PfM5F5zzhQsXJpMpg7F58+eZprF06eKbb74RQO3duzcSCS9dujgWi1iWuWLFckRYsWI5gFy4cMGGDeuj0fBPf/LTW2+9+f777z1//tyuXbuXL19WWRmLx2M9PQsi4dDKlcul4MuWLV26dEkoFC4WC42N9Q0Ndc1NjdU1Vd3dc6PRyPz53d3dc+fP77722qt+/JOH+vrOFvK5nTt3r1yxImTb72x9V+OsV6xYvmfPnttuu/nUqd4Xnn+eEFy1ajnnwec+d//Q0MUTJ443NzfecstNDz30UDgcamxsWLp0SVVVZWdnW39//759+4eGhpGQWCyyaNECxuiyZYsQYdGihevWrQmFrIceeuiWW2667757zp/v27t3z/LlSzs62hoa6rq6OqurK7u6OufN677hhusefviRU6d6N2xYf+F8//z53a7jLF2y6NzZc83NDYsW9dx++20PP/wzyzI2bLhqyZIlALB8+fJQKOT7/h2333727Olt29676647OjvbGxsbpORKiWXLFi9ZsnDlyhXLli1raWm+//57X3/9tYmJiVtuuWnRooWGQevqam+88YZ77rmzr+8coKqsjLe0NP/0pz9Zs2b13LkdjQ31zc3NkUhECBEOh5YuXRqyra/85m8sWbJEKfHgg/dfc81V9993TxB458+f/+9/+3ddXZ3t7W133vmZa6656gtf+DVCcO/ePcuWLZ1N7/urVT7heNvSH5oIlZASwFuV1WhKCB6lKKU63imlAgTDMDzPY5SWEfKSMqbZQ2ZEODRZqga3E0pBk5YCKABafnjAOaNUZwGYhul5rmGage9TxkApKYRe0jXInwtBypkCWmhHKmUYhhb/2Lt374IFPfGKeKFQ+PGPf3znHXd0dXej5vRkjAcBY0wIYZimDqPpUMBspYDZTdYNMRjjQmjlHgBgjAnODdMUnAspEdAwWFBWLpm5eIYllhCi+6Qk1sKlFpoMhULbd2zfuWNnd3fX6TOn/82/+V29W9QVQECNxp9hMp3NM01QY9FLaHnTNDzfn9HllVLovANdVTsUOnXq1NNPP7N82aojRw59/Rtfb6ivF0IqJYXkGnskynIypaSMMu5CSaXHxWCGkIIg6ixvLEOpDMb8IDANwy+3vSRIQ4iQkhICAMwwhoaGHn3kkW984xvxigqdyVKSLEKUOrFCqRmRAt1qUCCkYJRxwXXThOB6+HSiLQAA4K5dO1esWFlZUaFjuTq5hmjQiO40SjXOnwcBoVTo+SmEzp6QUiKlhBDBBTMo53qMONNzmJAS77hSlBA9DGVJEFRSkvLEnpljqpypoYtOlimr8tCS5qMQSkpKKcESj7B+I/j/x957x9lxlYffzzkzc3vZ3vuudldb1FZW78VWsyx3G9tgTAkJkEDIL8knIXkJSSCQQmih2IBxx0XNsqqt3tsWrbZpey+39ynnnPePs3u9lgzIxpavYb74I+7eO3POmTMzzzzznKdoGgIQRJHnWTZIU6d1asJ5O/x24O+IvOrP5IUqSR6356c/+9ljjz2SnZ3Nt+SXpShKfKq5Ux2fT94LPxEAwO+gQCBQ39CwfPlypkvbD4ME92K+Ppn47xytKIqMUR5qHA6HU1JSGKM81O1DHeR7gKHprlejo6PhSCgnJ8tstry/5NA30yUAcrvdfl8wMzPDbrdTSgEQTBo/P3QQQjE5piqqw2F/VwfVP6TluPfoze7ye2tnfDxBCBAgWVUj4XBSUtJ1JSHeSzuIP28+nnFkAB9DaZtAM31dTMvNR9egqbI3+HdWZLnloLf/n/HHA+P27hvDoj4QJgNhMUYIU0Yp+d0RdO8/DOl38H7DCK9v5p1/TkYMv7cmPsrwuQ83jG3SsUwUFUUThOnX/PvpRY8l+1B4t4stcSf6d1wEDCbLZyGYKl8ICCEEdDKrZGLBABAiqsbFLuLayYdw4/NmiUZ4nR103Y+/d+8PCErpB30WECUfQJsfqVj5oLtmQFQiIATvKLHzHntB763eWqKR8KtkfxRwscJvv7dvwkS+bPg1fQtGyKflhqKwtw72oTzwEvEh+hHyQU3yh3Oybhm6tNXR0dG5FejSVkdHR+dWoEtbHR0dnVuBLm11dHR0bgW6tNXR0dG5FejSVkdHR+dWoEtbHR0dnVuBLm11dHR0bgW6tNXR0dG5FYg0oUOadHR0dP5IEA1m+0c9Bh0dHZ0/fhBjH8sKPzo6OjofL0TGdNOtjo6OzocO+lhnMNPR0dH5uCAmduI/HR0dnT8SRIA/MGu9jo6Ojs7vR7ck6Ojo6NwK9CUyHR0dnVuBLm11dHR0bgW6tNXR0dG5FejSVkdHR+dWkNAVzhUABiABYALAAAQAYBQBAEOAgCHEgGFgU4WS+QcGFCY/AAKggBEAZlN/I8YAGCA05fuG+O6TfzA62Rp6u746Ar43psAQAAJEgWEgwBAwDAwxDLxoLH57EB/n2qA6OjofPAktbUUNGAIQgCIABAyBQBjCDBADQBRhPFkzfBIEAMDQlAdxvJL4ZBVt/se0n+I7MgCKABgIhGEAKkxKdDolixlM1ijnrQvAgCEMAIgCMIYQF99oeh+6wNXR0ZlGQnuAMRUAAROBAGBgAgOCQIgrj4xRDPj6yGN2vYxjDAAYAgIIAGGu597YFUIagAQAABqAkVGKQAUAQBIggTFAhAJgBgyAICRSDAwBBkCUANYARADhupZ1aaujozNFQktbP4ABwMzT5ohTyqICsgBUAIGyKCYOJiA2TWNFCAAYpYAQQlzZBaAAmDCulVJAGAGaVHm5KAZEkSoARkyc7AKAMIFSgQHDApf3oMkSljQEDCISMnHRDyBQhrh5QniHsgyMTQ5AR0dHJ8EtCUYAgwagQUhiu5uvNnf3WC3SXXMXtkyMyROexxYukbDAMGMIAQJGKUKYAQPGJS2iwBiDGEI+OZpuMhkoBYQA8eA5hjCijCKEGANBY4BRRyj4Wv3liVhoXmHx1soqK8ICJUAZMAaAGAh9ciwTpFgo9tTZow8tWfHawYNbli2pys0BwhBDwCaNt1zWg67a6ujoTCOhfRJMjGIEURP8z4kjzx8/MTO3yMjE9s7eJr/37MRoCEgQKMWYIRTVtIimqQhUYDKjGkZBRZYZEzA6Nzb+Ny/+ZlhTQBJAhAlVjmHQAGRKCEIhVSYIgIoNSvAvXn5Ojiiz8gt/derET46dCCKkEgQIyQINC8yF2D+/+uKFgX430N29PUEszKmeZbPZZMpUAU1oMXnS2AsxVVGJhlFc59bR0dFJbN1WQwgJ4PVHdtfXf/vhR9dnZQLUAsDli42nJsJf3PXGEFF/vHljQIn92xtv5BitIdV218LKSNB7tmfCx0IkSr+0bvmTJ8+80T+e8dYbf75q05MnL44EBqvsGQ+sXfnL7W95cagAoS/dfZfBSI9evmaWbH+/eb0JoMqR/bevvrFxXu2Tbx37xurbu6O+Fy90lKXZ9naNu8mZTy5eKkkpBNiRLl9SRvZ3T58wE3ptvLM0p+y7d6x6vanv4JUzVDA9unr5sqzU6w+JTi73cf0aALCuAevo/EEwAAKAGWAM8PbSduKR0LqtQCgGiMoxVTJmW5NAppqmAkBSlOZQ4Z83rLUGyJmW3l8cPVaSWfC3mzZ0e8fHAz6fV+0Zcf3DpjvykhzbT5zcMn9RRWb+Xy+//Xx9Z0Nr/z2VtWdaOs919RwbGEnLzPv07bfbNQoMu8JyRmq6EYCSSHqSOaBKgUjs5IQnwJArpjQMjtw+u7oiPf8vbls6KynFFiEmol3o7Y9GYm19Q5lW519vvefA1Wunh0b+7cSpnMoqoyXl6aOnb9BsGcMEkAagIVARUxHTECP6f/p/+n/v/z9KgSCgwN8l496YCUhC67aIAsXUnGQ3M0PHyHhNeb4GWFWJoMpZ+c5SuzUl2zQgkmFN2ZKTXWy3JGcbAcsaFlPzkmss5uqijAP1fRlGySiSArttUPYjJzZIhkc3rJuVliYZ6er8vByrNQKyCeFqu+PMlWYPQKpguTTR57Rgi8VqoDRsFAIYUQNJtZqSmFxosZokKSTRsAARB5UlahVITWH6HIczRUCDoQiTI2aLcWVFUYpRYtwveBoMCD8y7sGGAAFN6Aeejk6CwxAQDNwHc1LLTVS5lpijmoSJiCCWZZA+u2jxk7v3NlWXjQQCdUXZYYOoBFRgALGwCNFNxWW/OXosNDJytd11V0F5wALnLg3/z6Fzu1ubPrFsTpbT7AsH/v3YkQWlVcfaOpvGRlGE1GSnqSwsaTJQkAQaAHldZfmelubPvrK9zp79ZkfH51cvKHfYcoH+cte+EZUoMkEAebak/zhz8KEFS5AKGiAppjDKiKpEQYtRza/5S1JTl+Rl9rS2xlKdMzLSEWS/84AQgIQYAEUIAGMAlOBvFzo6iQ7iUowCIwxLQKeFJSUaCe0BRgBUICYCCghHx8c6BvvyJdvcimJ/MBZU5cVZGSeHhjOMhhnJaW90XosQzWFOnZVsfaHx6tXR0OaqAsFivLMoF4twatA14Bu7t2J2k899pa+nxJI8ryz/2ED/7JzMfItNQ4qgUYEZgwo72NM1ElUWZubMyU+SCGv0+5q7+tPSMylid+Rn9QfVAwOtCzPyIl65vCjtWu/YjJzMK2Pj5VlpKaJx/2DX2sxiIrC9XS2KRtYUlxQkJb3DCYwBUGAIohh+sHffieFe2WAyUStK2DcfHZ1EB2lYlYnv3tlzH5230IEY4g74CXlLJbS0BQZRRAxMFRRJNgpGBsBAxTEJjMCQysIIW4GSGCM2ZAAsEzAwIP/z1kV/MPTv29ZSQIwoCFRARowFUIkqYQkQUASKDJIxLBATRcAoYkjBVKJIEEUNQGQypRLWkGZADIHEKKCoyoCA1USpjGQjNUfFgBnsGlGIYDRqMqOiasCSQjUcE0Urd/rlrmjTj4cyDZCgMfxm05V2v0sxGCVq+KhmV0fn4w9iiFA1eltu/pLCEgOmFGEAwLq0fR9QYAgYojweARgCgogAAqI8bYFAEdMADJQBIgxhCuCJqIxqGTYzMEQRwoxnN5jMbIABAATEKGKYYcbfOihCdNLCHk+KIKLJcF2KKANEKcKMCQKlFFPEBIo1PBmVJmBGADBBDDOkIYJAECbj1673OGBAeYaHxHz26uh8jJly+IEEVW0TXtrq6Ojo/HGgr9Ho6Ojo3Ap0aaujo6NzK9ClrY6Ojs6tQJe2Ojo6OrcCXdrq6Ojo3Ap0aaujo6NzK9ClrY6Ojs6tQJe2Ojo6OrcCXdrq6Ojo3AoSXNpqlE0WQFD5F/xPwnjJc6AENMp/owAEgADIABEAjVEgoAIBylMWEBUIAQaM8TYZZQQmq0kyxgvi8E+TrWlAKdMYA6AaBcYACDAA0IAywigwYJQCqMAor6quUSAao1RjIFMACsA0yqgKMNkR8LYBKBCgVANKgQBQoMAI0MmgPg34kFQZGDACjBBgGmhAgYDGgDLG52FyZvRYQB2djwUJnXGRaoxiGFbUV8/UD7p8s8tL7ptVIgASGRwdGL3SMvrpVVUGQaQAr5w71zCAgthQII4W52ZPuOCv7pgNKoRxNInaQMSIKAQBRgIwIJghYAhpwARAGKisgtGANQCFUjNlIAAbCMrPv3n2a3cvFoiACAVJw0wETACMGo0KsgQWBkhFxMywipAAWGQEqAAUoeYh19krLZ+9fbmEGACoLCIgEmbmQ419p3u8Bmv0U3PnlqdbNRI1IMyIhDAFRIDhAX9ME3CByQqAQARCGWgURKCICRAFbMcswIiBiDYBECIUIWAIUQCcqIHhOjo6cRJb2mJBQxGVkdrsjAUVxf+2+8iistwiq9lH1QOnr1wa9N2zpjYbUxmxJeVlsuh/9VLLV7Ys6J6I7B0e2nXtWokzbVaavdMdbBofXp5foBDkjnhCSgg5U6LhqCJHi53OVrdnWWm+RYCj7RMgwOoii8rI2WtjQzK56DKfGw1WJiE7NrSPjBCDk4WDXl90xsxcqyRd7Og1CizDmOa0S2OhUG/QV5CVE+gfLMhNczospcX5Kkane0JRj2dxabrFKTV5Iz8/1v4vD68KKGORUKBPVrPzLO1u2SSwiXB0zO3NLsj6+f7zZqP5G6vmD6qhrrHg2sLcblUZj6pBl680P/XqSP+irFRzsvFMxwBVovPLipJNBswA6yludHQ+DiS0tBUJEhVLsYTULPpvb17JcxbmGQ2SwpIk8fMbV3/9xUNmDUlUoCIrT051pYknjbba7Ay3PD7k9bSPiS+e7Py7Oxb/z4HTSXmOM13DaQX5b5098/Dy+a9fuFYhJrdFR/KwiWDc7ZeNhDS6o5jI3e4ggHCxdzjHYTeo8oHWgQ6buSYt+dWmrohks/p9KkCGP2Q3G9s6BzLsxu6hjpW3zXzzQlN2ftbPj7SuKUp76crV+5ct2NnWPaThPQ3tS3Izc3zmWY6sTBMudJqeO3rp9soCU3bS3+859t1PrP3p4YbKkrSDlzsWVZeHx/zhiKgw4YjP9eTFS7n21Ja+oUCS/erweJLR5LlytTQt81DPcF1Zzr7TjcsrcvPCMafJgAEQ0zVbHZ2PAQlttyWYKMaIX5CdVvunls+ZUIPd/oAmMhUR1YijElPMmBkJEVSAmIIVJoQVBBGIVWRa/3zZQiO2HBoYn1DQquTCOal5JKSuKi39dO1MJ7C7582YXZZVVJm1rbaid8LT2DNy34qKR5aUne0evNw7ds/yyntWzkaivHnOjNPtg0/W962cW82QsmRh5crFlSMuT1tn94ZltZuXLZKtOCiy4sK0B26ryTPh+9cu8KsGOaqFwNrQOnbPrJKvrZpdlZfDNC3XCP/62IqtK+b85mrTm62NtQVZ3z1yCWO2dWZhXX66b2wi1ahWlljXzsqDIBHc5hXpaYUpGbagsKUo885ZZUVJ9i/Nq3F5g/PSHHnpqf3eqKyqvJ76R32WdHR0boqElraIIQEbewLK/x44c+Jqq4DQhEx+snOfL6w9c+R075j/5bdOxRiygMRANDLBKQsiQBphBoEwADsJLstw5Nlxd2TYaRWdJoZFAgA2xhiiTgWbRFFgogUccytyXj1W/9LJq0tmFiyuytt+tOnVw6c1zb0k2W6ypQz7vRsLUgwyMlBk0YgRSXXFJXtPNL9yvD5KBacm2alBJJpVZIgykRkRpmkx/7KK9KOXun546Hzj6IRmMHRGtJ/sOTnW0iKANTs5/ZFZVbsujN8xqwrLSDKn+GXo6B3NTE3df7HeaIJ0Cx4O+81pTDSoFkBmjZhBIpiJYA1GYumpSe5x79jImDA5TR/pSdLR0bk5Ejq/LSOKApInFLnY1TcYipblZputhr6hsbKs9NODwxpITqTOL863AsiI+GIw6guWZSUHo0pfKFqb7uwacRWnp3REIr0jo3NSM8AkRYg6w+nomPBkOGzhSIyJyIIN7qiSm2Zr7h7GGM0qyqEAzT0jUQE7TXhWRsZ/vdVYkmV5tKascdyXbjUKjI5F1YLkpPN9Q4Ikms3GQoMxqmkOq2HAF8xNTe52h3IcpkggkJeVembQGw2HFxRkZpikGMXtY94xr8vsTKnNT+93eb9/oOE/7l8ugnZ+yIcJqctPF0TpYu9AVWaqV6bXJiaqM5JUEK0ilgRwR5RMp2XAHcm0Sc0jXrskLizKnpGaLDFALMEfmjo6OgCJLm01RhH0TLhH/T4sGQhhmDIBY0KpKGAEwABUjVexBYSQgJFGaPyDKAiEUowQ34UxhhDi+xLKMEIAwL+klIqiAAw0QgBAELDKqCaILb0TjGoz89IkBAYsUMZ4R/HtGeOVIRBlTMCYECIImFKGMSaEiAIGhDRCGWMIQMBYxEhBzC0rjR0DFUV5KRajiTJRwIBAIxQYE0WBTB4CJpTyEU52ypiAEaWMCIghZheEmUX5BgDMGCBdv9XRSXQSWtqCqjBGkSQCEm/1UhAlwASKYVKoM/bBlDqaOgzGV7cogPC+myKUUTw5PlE3KOjoJDgJLW0Z5XorQ4gLJyBwa8oXMwBGmEABI4Qw0zBQQB/A6zoDxgBRQAiQwBBGQIG810YwZYghQIAAA0LAAJDuBaajk+gktLTlAWMCAGLAEDCYLLt4C2DTFvvRtH//QOi0z4gBel/tyggogAggAGAKwPTwBh2djwEJLW0na2hyQYuA3EKBIkzKRT45iCGgf3DvKC4cAQAxfljsfZhceUFfNBW6CyC8f3uEjo7OLSKhoxvw2yomgj/Awvk+YDhe6hwxYADog+l90hrBAOAPaPZtzZsCY7paq6PzcSChdVsdHR2dPxp0R00dHR2dW4EubXV0dHRuBbq01dHR0bkVJLq0pXBj2pXfamh+fxbo374X++0bvMt3v6/33/n7ZF7wd9/mXb+98cvpXmvs3b581zb0jOQ6OreGhJa2jLEQY4Mx9Vcnmv5xz9ntbUMqY4ypVzzubx+s/6f99U0jHsqYBmxfc8eZwQkG0NAxfrJjHCg9P+x9ra0PKAAooBFCGWgMAF5oGNjXOgAAGihMY4wSBTSXoj13qn1CkWVgr1/qbxjxAgOAMECYaJQCo0BAo6BpfWF5PEIYU1XKNKKAqoJGQAWgTAOiAgXCAAAIaECAQQzg/968dNXjB2C+WOxXZ65GFAYECDAFADToCUQiqgwxGRhoEKGUAchANVBV3obMNJnIoCg8uoNR+O6b59s9QQowEYv861v139jX+t/7zvR6QsAgCowwDVSmMgBQgKlhBioD0ABoGIBRxgCIBoyyCBAFNAgDUIgAU3WRq6PzoZLQ0paCbJdVKaYk281rqop/ceTyYCAGyMBkZW62PSnJ9qP9zRpCIlP8MfbKmR4G8D/nW//t3MUYxjsvdnsY7o2ED7f3datKiIbbgqFTo+7zIyPD/qg/Jg+MuxgFRKgRICjTF1pbsRY1At3dO9Dl8YeZevRauMNLBTE67nWd7HJd9Ebbo8q/77rwi+MNAYUwBggLDEcDGI4Pd50b7ezzhQORaHMgdKqrrzcUEgGueIIn+gYPDvk8MgHAkSjZ3tTaLcu9Pu+x3r7WYLAjGPziCwf3dgZCRuHyQLCpNxqj7JpHOe5210/42jyRN4YGO1xBIyYdsdj+ns4zfp9Pkc8PjkVCEYHQsUj0SFfrmur0pbPKREkcHAmf6+/s9PiZiLyB4Mn28fEoyIr/isfTMDDujQmnO/oax9w9vmibyx/WxDAT2jxeiQFiImXCH+5QrKOj8ztIaH9bQRUUMZKeJJaVZP74ZENmksVuNTCVzcjOmpWNOo5eyky3CQAAdElV2Z6Gk8dGfFg0pmmmE6MBvzcy15H0L9uPpWYneS6OPLqo4pv7TqypqmDU3k6Ef9557I55RZkZyAQMAQJAA8TyX8c67RifHQreMdfy7beuBqIQ83nuWl37+oEzBXlF+7vOPbJ6TlsAIswXiqpmp5EyJAjic+fHLl7rzbVael2+rasKfnbo0oLilN5z/V9cM/sHOy7NnpHU4ZMNogigUUGjltzW8eArO4/Orc5rHuu+c0HNqA8G3eEXrkQvNg1axNC8mvKzDeMR0b+otGjvqbbKeVkjzdo/3jf7/9t/pSYfH2y7+o+r50vGbE0SQdAQloJyzuG2sWRrzJOb/dNXrtbMTR691vfF+5Y+eeiCw54qNnlXzbb8y75Ld9aWj1wZw6pPJkRGYo5JqC0vtSC5/lrXP21awZiBIgZAsB4loaPzoZHQui0IokidoFhzDObbq2dOaBZPKIiliATohSv9vUOjX9g4S2CKzIx5FqE6w/TdvVfWVCQvqCr5ycGGvDzDuD9gF3P+a/0SJqiNg94ys/Gv1tQWWYUdBy4wq21DeblRA6RioGAANRVF6kqyl1YWliYZlGjgdPfwrBTr7Ozk46O+mNX09xtmFWfaC010dVHq7XNKc5McCgIAxBi9eK3jk8vmfGrpXE2MyUirzLD/9fpFRA2da+muysR/u25ubTKyKBEAoiKwaxGHGrWkZ35pw2JVY6UZ1nnp5gdvK7rc2WKyCTOKMiMS8QvBL6+8bVlJujGZfn3lfJIs7h3oSEH0n9YsnpuZ7KExRillAgWDRoQckayamba8rDCLEXMK/sK6+bKdneseaPWHc4tT0pOtAVmYkZP1+TVzesf7P71xybaaSrOsLq8rPdjYsrepZ+GcGkAECNIQFd8RV6yjo/MBk9DSVkUMidAT8j517MzImCs5MjEakv97/9mTfe6/2dskOvJPNnQSwALGGNiqqszhvtHVpRmbim3XOjtmVeQX5CaPkvGfnTinqUpSbhoSsQQQZpEHltUwn/uN1o7/brx0YmgAgUioZBLFtSVpKwtT050OIzYvz3COhv2Sw3JHfobRH/zZmbaegQACY7bDdryh++KQ7yeH6oFShKzFxWkvXbz6o4arIRYUGLUR2SaDRKMl+VmXvOw751o7xhRZtAAYJWbUSDQMVDHICgMqKlhkAbP01OXOufkFcgxRZq22ZaiiJmGkUqoYVACwKKHUpNRRFP73i42tg4MWkCQaMBIZA0jA/Er0ylC0qW90QtYkY8wG4JDDBSn2bKcF+9zFGYJgMKYrcgrApszMZw+cfr6jK4TxopwM5omFI9FluWkMRMD8HSehLwYdnY87CR1LxohMkDgRkc909A4EwpX52WV2a2v/iCXV2THqAg2bRFhXWSBhpCAtqGpXh/3z8tMMKm3r9xbmpyVL2gV3oG1gvK4wP91hGun3lpekd7ncYDRrmMGE5/CwqzY7bVVJQUhVGkZ8C7KtZixcHIllJButgvRW54DdKC0rzul2+a96Qkkm6bZUAUu2412jWcnOQ82dX759vhVjNcaOdfULJmOeIBjSbRP+wILUjMPjw0sycjrG/KPBMcmWPjfbkiEKXoKaRtz5yY6JoHduem7D6FBFWvpwVBscGZxXUXyuzxuOeJcUFo75gkVpTglBw9hEbUF676A/Py15LBC47HHnGC3lqSm9oUB5mtVisuJY9M0+r1fRjEipzE2PhYNzcvNae0eys9P9UfVS70Bpekp6itntCczOzRlSUc+4u3UsOjAw+s/33Pb/dp9aWVbwiRlZJpsdG5iBAGBRjwHW0fnwSGhpC5SqgNqHxye8HiRKMQoENCwKGiVGjBjClGFF0wAmE26LgqASghkzYkmlFEDFWAJBZJoKjEhYlAkRRKQxoIDMgEOKhgWEEROACYKkEhUBiFhkjFBAoigwxlSNYgFjjBhjiCiMISQZVI1ENWoUscBAYoAlARjDDGRggAA0yiQBa1TCCDAjgAnRgDGKsCiIjFCMgWpMEBEhVEBIxCxKQRAEAVFNAxEJGiUIAAmCRlRREJlGBYSYKDDGCCUYY0I1DZCBUUmUEAADpFCGEGiECKJACBERxoIAlBBKsCDENOgPoZ7OQcaEmRW5Ll9ApfLcvBQHI3PLZzgNokj0RGI6Oh8uiS1tNcKAEUGgCFEADGD4oFr+sJOTJ2IdXKICBUYlJCiMiMjIzbSIUYwAgCIQEnDQOjp/NCS2tCUqowQQIEHgcoAAYlyQxcVZ/E/4gL7/kJr9CL8HQIAAMDBGJysDMQkxxBgAA4wBoanqZrrpVkfnwyKhpS1XvjAAMDYpZtmtqd3wxwYCBmxSl+UymCCsISQACICQnpJcR+fDJ6H9badFziIGiMI79LXr+O2/fJCg67XGD6cP+IA7wLyUzqQKjIABQ5h3QoFhDMAA6aUkdXQ+TBJat2XAEONFchBgYO8uDdj0T++2yQclROIzhaa/rP+2wUyWC3s//XwYOuZkoYf4+ISpRxlDjAKjAAIIWLck6Oh8aCS0tL0p/Q4RmMq98q5vwwzwB1EikQKjFAEBBIBEQAgQvb5kGb1B2r730Kzp1SrQTQveGyfqXXb7bRuxd/6po6PzoZDQloSbY7KU4m8TFR+QCMFcUxW4ps0oAMbvorpOfvO+9dppbVz38Q/nQ54hHR2d30li67ZTMMZ+m1VxUvubdhAaMIwAAPDvlCO/o83fPRZg0/XP6cJq0l+CAXe7fZ/LTowBwGQF8/fH+z00HR2dD5GE1m2nuzMxxhBAfCmH8f8xhhEGBAxNWlUJMI1RxJCE8eSe8G7mVcbYZEjEzUolBgwBYhQYIAoII4QZAwSUAUW8H8THhWDSePG+ZDkQRhljAsa/+2lx3V58DYxSyj8IurTV0UkwElq3vVFUvovwpACY/wMaAJkSPZgxCaHfJm3fOxRAAxAYCOrUMIwUGJq0GPCfGQAlRBKwCIjXZ3+vXRPGADGuJovoZg230yyvjDAGAALS17t0dBKLxNZtGdMQCqvqsab23onwvBmFS0uyKIIRf+hwQ2dY1dbPrSxPsQGDTk9o19VrmKm59rRUFjYbhMW1VcA0CiJGk6/3XkJjGs0yCgDQ7wn2DbqWzy5BRCUCACAMGFFMMWgAlIGEACgICFRERIooRgywCIAIKJg9feJinmTftriyddx3tL5TleyUhXNSHcHgxPrZswodVtCAYsCTejgFhLn1AbGpMAIAAAYaAUEEBAQAGBMQEhB67tSVecWZVTmphIiCMLUlUAoYUwSYEkACAKMMMCLAxMl+mELVHccaFtWUFqalAgMgBDBjWKTAMBCU2OdaR+ePnoTWgBBTBaKGwlpERplFBd861DgS8guMDfsiBocjbLL86+ELEQQA0DrgPt7jqi4sKEtLc6RmSanp/eHY8IRn0B9s9YcuD4z7YtoP3mr6zpuXPTEVIXTNFXy2fiAMAEyJMbg4Frg27h8Jaf3hkYDsQ4oyGooJmuzxBMOxGJAQpqzFE6gfGGcULnSP/KKpIycnHYhmMYgZuRnbL/XLgiE1OelQ9+jlUU/PkFtFLAq0fnBsyB+KUdIfjHa4PH0ef18g1tw/OBZVWoZdI4EIQdpwKHixbzQU0wQqD/qDDSPjh7p99X7ZE4kiRiaC0eFAeNgXuTg81h8OAiXDoWjD0OCAL+iT1YFgqGN8rMsX7vIFO8fcFGlSZp5gtXlU7XTvyFAoHGToYu/YwLgfiJ5NUUfnIyah9R0EGDM1JwkvrM175mRrnsOUZDRjqt1WmK6Berq1uyo7SwCZITFmMIQVOjTQb0tNa3Jr1GpoPNYuyKymLOVM11Blduq8Anpl2OOLhIeCwVRzigBYNhsFBiAKbzQM77rcV2q1t5DomplGNRRYVTT3X3Yf/95nV/7g8NEn1qy2pxoPXxt84cxVq9Gak+0WsTAWtgSVGMHJBXZbbo3lpUutaysy6rLTvkttB1p6n3WF7r/9tvE+d9f4RETDdy2e+cP9bbdl0Mw0x7F2d5YTjbg6inJNQT95YNP8Z/adzzCZRdr74Lqa7+6+WJZh6vLILRF05kDbN7bWfedgQ0FR2qlTvbnFKSMB/9c3L/mP3ZdmpIinu698csvC3W82zUgznx0PzyywDwwEvnLXsrNXexzJ0rNnrlgloSonxe1Vx7zRWclJDyyrTNEThevofKQktG5LqQjUIBDmMBgr83JJlAWiGghIYEqGw1qWn+F3+7EqABMINRhNSUnpGRaHLSrHFDmmypEt6+Ztnl2cbkSU4JwU09KKrI01BbUZqRQ0isEEghkBgGl/x+B9a2sf2FgZ0yZW5FU09mpPXRtRBcf/nB0hUlpRigOD8a0rvSvmzfvze1cc6xm+rcC5Ott424xsxgCpgKkWRXZZM2JNS4bYF5bPWloxo72n/2Rza2aKNSPJTEN+AcEXti4tSbJlOYyPrV9AJfL5dbeFSbS+sTfLmfMP9y4ZCo1vv9JrsST928bFOenJC5wWUQu+cKqFSKQg2eKwmr6ypU4DduJqn91m/OqWJfZ0i6yFAcgnNi2y2oRH6irKcrO73YGoFuruG5SD8H93rvxiXW2ZUxJQWErWQNR1Wx2dj5iElrYyZjERd3jlHccbZKaMAmkMRJ5+q35f+/jp1j4VcF+MRgSmISqonjkW9d7Kgnl5GTECjDETi6ZiYgIyrzTL7Q2dbupIdSS3X+3t83gZSBjYtYmBF87V77/SVpbiOHn+6s6GVhKklU5btsnR1Nf5l1trdx5v3VhZYEVBBFCVm9rS2rb/ZHOt3WIymBHFNqqJOIaMGsZUUEMUkYgoCoymEiEtppgRysnLQqpWmW7PcTqSFL8Vg0CVJIEkE2IVY6kaZUwuz3S4Jwa2n+twqKa1hRkhr/uF+hbXcCBDErfMrfrPo4O3z65OQqoZy5SBFPMWpBi9Hu+ey+3+EZdIQKIRQYQkLZZDiUWVZSB+ipKdaVrY/NyZ9gNXe0yp2QXFMw6ebJ8IRD7qk6mj86dOQlsSzIRoWDCYDOAwd4z5Pr+sPN8quczMnGR2TWgxTf7LNVWRmBwDlp9qxWLeSDCiCMKsoiRkkvLsFU5RHdfEUDhakWdZXJmDTPZwReaIzy+ZzLYk8+LavCZfMEcl6+aWH2vpNpnEh5bWDqiR2xcUzIum5SZb//GOmuJ0+1hYi6LoquqSEGjBUORTy2pkAS+ZXzoRpkxgDBQN0D3zSmwiHQ7H1tSV+xHLL3I4JbbGkXSqvi0cDEJO8p2LC0cjMWuKY36lhBjdOKfYr6lrZpeV5iffwYraBj133z6nIsO5bWlxt9f34PJsg5l5FC0nXSxJN3tC2uq5eVo4umFuRV5O2pZF5YMe173LqwqTbLcvnBGMRTbPLfFJUFOR6rSAtaaoJNNx/4bSps7uOc40QYtqft/dq+an2W0f9cnU0flTJ6E9wAAUBmLbsGt4wiWKNAwiIpoBGRSGjIhgBGEGoCIBCIgCwYKoBDUsmZCoIYaRIGhKGJmwiEHASAkrFIsGk0A1RFQJNCSaCIjACGJRKpqxxjDCQRI2IKOBCRFMrAjLRKWMqRhZCFINgkFAKEqpAKrEpBjWMGVAgSFBNAg0RimmksgIA0QYBrPCFMkMiALRBAwyYRgjEQlIVUFClGAiiVhVRQyaiDWiAWUSwgRLIiieILl0raektKjAgplgsAITFSViNMoUmxBRRVGiwFQNiSAT1YINYUYEQTJrCkMiZbIqiFgwSmoUYUawSDWttqggx+n4qM+mjs6fNAkubf9EkQFihNmE95FnQUdHJ0FJaEvCnyKM8XRdRowpA8woQugPyLmgo6OTKOi6bYLBABgwzHiuA0QB0AeRwkxHR+ejRpe2iQmZDEkG3Zago/NHQkJ7gP0JwospAFAucBnoD0MdnT8SEtxuq/GsWpPFyRBCDDME8TJaAKAAFYAJk2kXEWYIaZP1DBmaSsb4Ht/E2TvyvNzs3jwNAiBgQBlgNjWE6a1hULjGygAx0BDAjekLECAAYSpfo25E0NH5IyGhpS0BAabepRkCCiheg5tXNkAUGSmeLAyJATBQBFRkDBAgEGCqkOR7FFk8ycv7kXQIACiaKl8ZN7hONcQUQAAYA8IAiAloMhHudV1D/J1Dl7U6On80JLS0fUembgAMjK/OY2CTRWQRYliYrHmOuJyjFFEMCE+uLr0/ecUQIwC8AAOe0ll/71jZpCWAD4fyEQNiFHj6RQQIMADGk8nAdGcDHZ0/IRJ7lYwSmMz1ygfJEJZ44myeXJwAVRFFAIiBCBhRBAA83xUSMGDhPZT2ur5njYtHhG9+nYoAUAoCZSAwjChjAgIEiGmMEoYExrAADCgFBCAgihABkPR1MB2dPw0SW7ellCGgCDMkcqVRAsYtuJQhhIECNlIZIQxIApg0OlBBwGyy1sOUmH5v8pYBqFjECIAx8W2l9fetKDIGgCnCKgKGABjCiO+DAAkaEikGBiAKAhDucsB03y4dnT8dElvaYokA81F6rrVj1B2qnFG0ICcZAwWGEYbGgTGEYHZuZgTgRMu1Xl9YkyyYKXkpZuoPbambLTBAjE1ViZxeSuE6fXfaT2xylcoVkS9cvLJxxXwAAPYO6+qktv0OIwBfHcOAMQYYnnBfbW1fv2KJaapEJQMhoJDDjdcmiOo0GlZVFuVZjJgBhukDeXtUbPpobuRdv55cpIP3pcrr6Oh86CS2BxhjmEEkHB2fcEsW2/d2HRkOxygooJK+gPyFl/Yd6BzQEJMYdWA86A+/eKIlFZNRf3BXi7vLGwpHZAbYG2MtLp+iaWMxuV/Wer3h4Zg84pOv+SPjKulwRRSiAFGv+aMdgSgwDTTtmj961R3b3jw0FlaiKlEJcoXIWETtjcba3d4QpUyjfd5gd0h2hcmEog4qkY7xoI/gvnGfVyUmUUxy2IwAQyGl2e33qwwT5AvHnjx1NctsaBvz/+/eix5ZG4gFxwPRkMYaxoNelQKLRlStdcI/Fo4GALo8gRF/WAMIyNA07uuNhRUG19yRFl9IBhKIafUT3ohGZIAef+SaKxClGqFRCoTBzVWG19HRubUktG5LEWPACqyWVQvqnr7S5bSnpkoGTInfgH55ssnmyDIakyQgQOXFlaWRpORuj3zf/Nmnuid+5p743slLqky+smHp8/saVEGb4bQJaSmHz1xYNaOoPhC1RvFA1J+Z7IyO+Zctr3Eguudypwh0y22VGKGdJ1rsZvu42f7U2YYFWekZuSmvnbxqEp3D4RHmU9bOrnbYDM9euJBpM5KYtHxW5b4LV4nFEGJQhFVksW2eU3WmXxGSPD8/Uu9MxvfPKVlemCcBM4oCNdmZJSZH2X++1Tw8NrK2trK13xVRFUJjf7F58S8Pn6eh2Mz8pNSMpCONnQSb7ltUcexiqyYYF+QknWbozZ6hyuS0zXUVL5y8HKPRLJOltqxgz5mr6RnStttmVaU4MMPc8JHYT1EdnT9FEvuuZAgRpgpMQJANxiCSAjEFsOH1hs62cX92Tl5vrz8WQwBmBiApYFAEBYDSyDyb4RvrV4QDhrfae066fBl52RNROhoIF+U4P7V2nktmixdVl5TmpGcmb1gx81yv6+XG4YfWz35kZfkLlwdfaBq7b8XMR+6YZRLogsrcU42te88315amuQi5o7xi67L5ZwbHDjS2P7B8/mPLlw9SGFMhw5nxmZV1UlD57IYV40MuTzTUoaqvNbasrMn/r22rF+YnAYsGRDyOTQPDnnIr+ruN8zx+95a5FVV5jtaQ9h8PLsVG+tTp3sao/M1H12xdOe/1M+2iMzXJbhjz+TSjpBklR7oDzELEYEzOThrxhU90hfPzZ41oAlFAw45Ua2a6ZJFUUdAQY6CiRF761NH5EyWxpS0wEIQRj+/05cbsFJMS9F/zB546cylNsC9Oz+8cH+v3+COqFhOpDBQxlZAQA4oYiBIwI1KIscCUlI8NqWaom5lvwtRhkIwAZo1mYJxCtXSMnEywKLTKaTnbNnGy3VebbJ+dZDvVMXqyozscwEvzsodE6/mO2J3lZVpMTjFIJkQIU9JSnRfb+o+0DU6ogsKo1QBWFLELqkWSMCOIEqKpGRlJF7tHDjb3D7hlgkySxoqI4TOrqj81f2aeWTJRyWS2ZVgt5kjk9asjrgAsy042yNqR+v62a8PZ6ZkSwTX5hQVZOQsLiowm/OOTZzOsKXcVFrxxunEs6MtKUlINkduqstPTjAvnZL/Vee3Nrh7NgEBECIEITLfd6ugkGgltSQBEYoAsRqsMhsu9Q0+snFdoN3QrkWU1aetmps4YEq3EYDUgRZYFQPkGfNecAhYLpzpt6+dkCUp027zkOXlJxuWlDf1dRfmF8/OSVM0SUdQttelZVja/KNmIRavBsrbSWVOY+5sLndiA719UDJS9fCliYLFPLszHGrPbTDOTJDOhGytT0lJEkbKN5WnlhYW7L15xCOpXZhXNcBgiBkeyZFhTV0yYvOG24nKn+YHyjPllxbtUobPfXZxSHJWjVoN674JMLSYHJZAY2ViTk2FTM6TYE6srzncPb1tcu7E0xWCrbr46XFuY+vlVlYcuXBsecVenWQeiASvR/mrJbYzJHQHPtnml68pyU+yOpmu95Zk2o8kYHHVvLiteU1qEFQ1EARDC+kKZjk7ikdD+tlSNathwacQ1NOGxIKQyWWUiFa1UUSQWwSJmyEg1VRWYSKlIDWGD2aJ4qWCSEBi1aNRojlJqYIRIJqesRBFSsSjKGjMhQQFNJCISI1SyCBpVZWSQgFKsaAwJ2GzSmGDUwvWjgWsBWF1olgSjUZJsqqZh6jVgZwwESdBAkwiKgkJEAM1kFUVQFCpioFQTMFUJM4CIJapoQGUsIIRNgqbKGCiAQTB4aNSpMSIYDRIgjclEkbABiVilQCizCCBSEqMilYzAFLOmIMBhowEU1awqTDIGjIZkWY5SjRqsEtGSRDqvstQkGUUARNlUdXUdHZ1EIaGl7VQkFmJT8bs0/jUPcnhnQgM6ZRmJ+3mxqc3QtA3otA3i+7IbHMQQQEjVDJJoACCTwWzAAAiAOK3reGwwfueQpjc+/UP8e3qDHWf67vEDjIOn9cWmdkcA5O2u9eg0HZ3EJbGl7UfL9U61Ojo6Ou+fBF8l+0jRRa2Ojs4Hhy5tdXR0dG4FurTV0dHRuRUktgdYPIUBYwAMEJrKejC1mMTwTSSjZTxhDN/3nd5RvAoYo0hAU2kGeLbym0jMNbUIN9n39GW237kTmvYZrt9j8rt422hq3PEDQfiGnWAquSNMywoxuaJGp9JFJvqZ1tH5YyexdVsGMLUQDwyRt9foCV/Dou+6y3RPBQbAKAClQAkw+nYKWvoum091N62j3zM6BjzV7nvITMCmt//bdpsaFgNgk48a/sjQtBtq5zAAwuv0AmNA2dRub48snrFSR0fnoyOxfRIYBQCGMJeODMDAM3MjREDQJlU2hhkARYAAMGPAJjNhcf1vcqWLCyyGYarQFwIAgcCkBDcwxssoUEB8n9+/QMYAADQ06Ykl3lz6LTKpsKo8JS8DdL0SPdUO4/FglBEMBBgGxLVXCiCAcH0/jEwptVzWIqB4UuEGBkwDhEDQtVsdnY+ShL4DGSBEef0EhhkRKGEgAsYIKAbVwCgAUIQBBGAIGKOIUMQwYMQoAgDEK4AB90KdNBRQxosnIKCYaRgQA4QIZphRoAxhgQmIod+v9DMASrFAAKgAAmgIBOH3SltMuelhspQDgxsENH8sCIyAhgEwQ0AFjInINIqMFLBICSAK6J3jo4gKmDAmAkKIUFAAUQICxRICjADh63fQ0dG51SS0tFURiAwhBipGGIGANKCSBpgClgAwUgAIYlgDjERAgBhFDGEFYYGBCPQdOWkZAkCEAQHMEBb4kVMVCQICSRMFShlmVIC4jvh7oIhhEQNRBKQBIJAMv38fBogAAwySCQAofbv2z9twjRwYAqaBwARBABApACFURAwBJQgLN1h7GYoBEISsFBBDgBlGFIMEgCkDoAJCN/H80NHR+TBJ6FsQMRlAi1J6uHfkqUtdje5J2TQUim1v7Hnu0vChzhBioobgmi/QNDjMAKsKu9Q9FGIIsABoyjwAGiDKEKgIBRkDAAGAghAVbKeGIr+4MHC0ezTEQAAJMQSAbiany1hUefVCUxgMGjHFkOH1xtYej+/3HQ8A1hQRGl3BX7x1biwWA0zebRsAhgQqUBC6/MGG/nFAGERhPKbuvtgWRuhdonIxahubONtxDRAAQyqYTo/S58/3HWgb8qgEGENwQ0c6Ojq3loSWthgQE/BENNbZ3qPJ9F93nPXEZAmgdWD4mZNnNUKZoimIGgDau4d3n78iYqRR+PXew1FFjRHU748QYADKgKJ5IkqI0M5A4Fuv7B/zhxlQTOH1S13P7T5LFeXa1SsQDgUIdEfUENWChAYoG49GJhSFv9v3h2MumZAYBYCxaKw/FAoBiKLU6wp888X9o5EYQYKGEQBcCwRljVBgE7LaFwxRDUCjFBQK0B+I+BlTGX3ywOnhcMwqIkIVAPBGYuOK4iZaWCNRQnvDUQUYI6oRaHvPwL5TlwAJ/bI47I2+caFFFVCAwGAwzJf5RqPRiZgcYLR/wHWioRsjAITe6Bj64d4zVCEd3f3DnhAW8Xgk4pUVr8rCABOhqCcsa4lsr9fR+WMkoS0JmBlVHMtxsE8unru7pddmBiIIAMAoioAY9EWkbKcAAiYAOPmMf2xnY/u4gruFNL+GnzxwaZBFbktLqSvJ+96h+mKnOBhFs/Jznm8LFmb0fGJNhYXCS81tn7lz2ZY8pwrlY2HtBy+eDCWZfO7xTy+b+8qF7mSbNOjzf23j0ub+4cPNYxYEpZm26pqCV/efzbWiqtnVPYOh3tDEr3vU7KsjrjGPMyvn0NGr9d6RMsmxdt6Mnx1tMieTT1bV1OWmeSh6/vDZlvGYJAm3z6481BteX5EiMkHF0hvXhneeaUoxWQwSm11ceLilBxArSEn/69urjYB8ot1nyT46OPx/h7uyDKYhyTEcU35+6KoxGqibkZOZnPz8mxfsyRaCYUnRjJCUpgFgxHZebtu6ovz2osK+QKjAaN53peOXzZ1FYDM40mpnOM6ebUt1pnxy9cxCh/mjPsM6On9CJLRuC6BhhiRkijA0EtEoAKJRQLQqLemzC+ek52f8x8ETgagfMAmZFD+Wh2OKJ6gakXC+b/DkYFdVekb/hOfli9eWVRb/2R2L+0JqbXnO8jznPYvLzRCjgiLgYJIJAzAJ0NGBQZ9R/vett0XBOBZTmmPwufW33VZW8Otz7buudn3tzvm3zSlojrlfPXtp2cKaf3lwY0myrX10fElN8ew866YFxf2ewPhocHdT68yMgv5IwOMPqkSZYcl22AxI1Pr80bNdvd98eJXTKo24xxZXFa2fVWAxYCOwXRcub1pRd8/CWV1+2RsOGe2WL2xc3tAzigjFACYgUcH6QkPHfXU5D6+vtBljZ9rHuwc9M7Izzo0M/6qhcf3S6rtXLuj0RX2iIogRAQhD1KiE0g1Gly/ygz2nn77Svr1h6IFVq1YuqBwZHzeGoipoaQUpdqP0UZ9cHZ0/LRJat6VAEJWuBaNNPQMLyrOPdQz3jIdO+Xryc3JtFkwE1UwFFSGKmBALLXOY/mJhrS+snevqckgGq1nKyLDUZle29Y13TAycGxBZUMuQVHMseG3Us6Qoy4BgWU7lnoOXtCWlAW/IahY0H2rsGx6Oucy4DJPI1Z7xgeFAXqYxEkYNXUMdPo8zBqmO5ObhiSYr8jGsMTXJwMwhz8TQmEaIUcB2mzndYkyvq0x32NfXle+/1IuUQPnqhWkIKTj5YteAx+2ZX5bj6O1OggyECGIoX7Jf6x0eswhUA2AkR7JkSEAZQowiQAYtYpajzqSMawMen2yL+YVcg2g1MmemdXNx9eX69u6hYX9UZlEJa8QaI4gJAsDi0uodR3s+tao4Ly07rEgWp8XdeU2hWpQpJbkZsyTYffzSfBtOmVHwUZ9hHZ0/IRJat6VgJIglC4LLG95x4cpjS2amOJPaPSFFMjQPDzc0t3553SK7waEQoSg5dV5RVkSLRpm6rLawtijnrgWzW9tbogHfhsWVJhu+Mjp2Z12+wy6tXTanaXAoRIms0XuXz8opSnmpqblDlm8rKVxeU3a4vWfdnNJku9nJUEPfuCPJfP+C8kdW1TWNugxmaV1J0cPL52CR7WlrVSVx+Zwys1nctHR2a1fPgtriglznE+sW9vf2hEYnFEbGBkayC8w1dTNCTHPaxE/cMeto65WaGbk1pfkLZuSkOux+KvgofmDVbdFoYFQJ3j67KD875baCVBWxVbPzAhSHKMpOTV5Yar1nSWkMye6Ad82CgnkVSevm5TV2tIPL9/DiuqiqeMOBjbflF6WZqsozQ4y4qbZpUdnCmTkvN7RpKLK6MuOxFZVBt0cBtmRuiSccHhoeWzS3LCcv86M+vTo6f1okdHSDCiomuLtvtNE1oZmkFJWEVC1mMCaHsN8mEJNgi0RVSkRQFcEUESxO2ROWTGYsUYUIgihBTBWkMFUc1CjRqCJYFFBNDCtIRZQCYwhhIkogGEwkFiGUYWxgCGPBJyuvNIw9MjsNGwyWKFNNlBokpIEZqKrKYLQBaERGooHIWlRCSQSCCBtFqkrMHBEFxFSNRAAnOSmJEdmLFZEo6ciiSSYqICL7RWSjVItilYHBIGBRMKhUlYiiYGyhOMCYRWJMJgwZDZjGEA4JLEVgYiwWEAWsChhLJsQUgUQZxliUNIKBqCgYQ0k2VZExNTEsm6iBilZikEkkIlEBWSmlmApGiDKwRBmdneucmZPzUZ9hHZ0/IRJa2gLIQASCRYLAAIwCQqACA6SJTEQaohIwCgwDBRAoEzAQgrAADCgChBhSGWAECBEMWAZkAIamchBgEk+GQAGQCkiCSTcpgTHNrZAko4QAC5QB0igSMTAKFAFFTAJEgWFAhALDTKJIwzzZNxMAIQDKgFCQBAqAQEEgAsMagkk/WRVABAYaYggwhqm0DERlGBOEGGAJVACBAsbAgCGCQAAABhQYZohhQISBwN6u0MAYII0xKZ4lARABBMAEgMkiZQwYBgAgwERA8G7ZzHV0dD5EElza6ujo6PyRoGs3Ojo6OrcCXdrq6Ojo3Ap0aaujo6NzK/gjkLa3zO6sG7h1dHTePwkd3QDvyKVyXYFw/g2joCHAiAmTS+7AADFeouHtlLOTyWL5Z14D4u2fgDEABBgYUEQRIKQhEKfKMgBP1YgoAGVT04Um0+3eRIWH937AFJgEGgWBABaBopvpiFEAxNDb6dV5osnJwuzvlnuXAiAgiFEAkSKEQGOA+dM3np3yZnKh6ejo3CQJ7ZOgcV8tADxVHUcD/I5vpirKEIToVKUaYTKhNj8u7vgUl7XTqyYgQFN/8kZ5DQQQ3pEGEU0Ka+4xxlslCODDkLWTJSUoBsImPcB43sibybY7WTuIHxpiGIBXt0CTz6F3K8nD85AzAPHtLOzAc6fduIuOjs4fQoLrtpN6FkIAjAAAIIzerlRGgCEgAhNBA8aAisAQYAJYQFxHBJ6+cLLyA0+1OClKGDBeqEEgAJi74SIEiAEjiMazwbLJsgmTopxOev0C/pBEEWYEGAMkImACIgzwDRlw3wUNEAaGeQkehgAw5co6UwBhhozsBoGNKANAKkYAVGQUURGAQrzwG0JTjyMdHZ0PhoSWtiKhjEs3AQMSKFCBkEkHfowBBMqLHCIiggqECiABwhQDAGOMUYYRFlQAEQBRFQMDhAGQigADBkaFSYMAogACAwY4BiAiJjGgSGCMCFwiMwwIBP7yjQUAwMAYpfzzBwsDRJGgIhAZiFQFLNEbq+m8y17AgAIwxgAhkdtfCEMYmRhPW35j8R+mgSAhAEwjiGoAdioKmNtuGBPQ2+UtdXR0PhASfJWMMGAyQPPQ+N4r3a2+GOVFcrBwzR3c29Td6ArJCBAggUkgmK+MBUcUyut3ISSEAR9p62pzBY41tckgTOYXBxgORY+2dsuYl9gBgQGetJdCFOEg4FCMHL7cGqKIISGuWUYoOtc/vqNl6HDXmCum3oTG+X6gCHf6Q9vPXvXGVEAUwc1kNgdp0qyBCIjt496hYEwAIAi1jvsvdA4C4mrvOzsShEvXevvdfoQMgMWAKJwenHijsaN9witPmmQS/NrQ0fmYkdB3lIZBFcTRUPTAuSstY/5vv3rCFVMZCM1jnv96+eAVV3DvpW6FMGACgNgT0f7y1/tequ/ixtsQRWOy8ptjDYOhqCemMoyjFAKqqgL0e0KvnLriUYlMJys1+GRFZUgD2He+cd+5pghjrpimIRRGgiemaQiAMZ+qfW/78UsjgTcar/10x8EwQzGAmKIxAJesqQDAGAGYkLUoZQAQJsynTco4d0yJUAoAQZX6VQIAGoArpmoAABCi4JVVCgAMVAo/23eqYTwMkhilKCATDKAxiAKEVG2q+i54FVUGIAxUxqIMAgohIABgQOjlt05f7BoGALeinetznai/JiIUkLUwnVwQ9CqaAhAG/MqFtiuDE4AMCrb+7OiVF45e7p7wHT11WdU0CuCLqTIDFUAF8MSUGB+fjo7O+yWhLQmEIgGRfLvx0c2r3uoauTzi14AJAAc6hpSUDJvJVF2VIyFENVWQpF1X2ubfNru7d9wzp2RcVv/zwFGTCV3THJpKrobE2Z7Ij/adNzoEX4RtXFR+SU368c6TCmFf3bp4e0NH28AoKCmVM3L3N/WFw6bkVGdXCGaGIt8/3GAPKxtvK1tflm1Amt9StKQ8eyDoPHP64q/OdzZ2e2fnWTUUujQazbWYvr6y7qnm1ovdI8uSHXNnV/zmQgeQ8H0L5lztG7o65qpNz6jOS3r68rVsk/RnC2bv6hm4MuSekWRaX1Pyq+OtBoE+MK9odn5Wy0hoX190fW1u07h/5/FmUOjWxaVhWXu1uX9eivFLa+pELP76+NVjo6MWZFlVlDoYjPRHZb87cPfKmjsLs0QEPpMxYLI8d67nRHeXRzbMykw+NuB59WyPJJK/WFV5qHv0Qvuok5Gq6jzZkcKwCYF/NCC+2d7/f4/eLhlYLMw0LPzwaFPLqFdDwoaaomAgeHXQU5Sd9PklxUZsSvAntI5OwpLQd46RMZFqAgaXrF7oHyMYGwEDAk8UvAHqMBm/e+BYRJYFAdwx9ez51rJMqz8W2tMzcqqxp9hS8Fcb10kmBFq4e3Ds2dbelBT7X61fOjgRdWtqlhT56talPovz5/WdJ5u7vnb3mrR0Q0Dzz68tXbVoxuzU1OahwZcbu2xW87fuW7qowE4wBTAFCDp9vtHbM/bZLevc3mBRqqGkMv90q+c/7lkRjsq/qB9+q2XoG3ctfHj1nJfO9Y0QlGQ0NbcP9LjDRpOjrCCrNxhzR3F1bnY7qM+dOzszLb1l1H91dGzUHy3ILEq3pVBGinOSaoqSH6zK2nupZd7MvE/cPudnZ1taAj6roD68cq4kQlck/FLb2N/fudLusHSEfS1jUJefvXhmydmmXjRp3DCHIsqLbV1/tnXZ4tICPzY/ffqiZPZLWuBky/jhhit/vWVeXn7+VZ9iQtxyjRVNNQHJNgqtLS1/8+LJAx3u0+2j/++eZUkmadAT7HK5kN1UmJ9+c1YNHR2ddyehpa0mRIhAR3yR8cGhBxdW+cLyVY/3QlvLzDS702EszUlTEVMExLC0/2q3QRB9YxN5mY6D9Z0UmbSQ5ncFUVCOISRiNddkiESDbX6/JIfTNYzCsa5gSPLL+UYLYPOE2xcMe52gFUmmsHtcURhgSzoyCW6lLxSKxogBRAlYGh774oZFf7953rIsqwxKaXrybAs2qOZxdwhUNdlhlFTTmIuF/XKeUXKabPNmlS+eVXrHvIrcVPuzrx8uykx7cH7FgbOtXQPjSfbUlNSUTyyYNT+7YPOy2We6e/c0d4nYnAzIKFCziNMttgm/3Of3JxmTHUyotFqzjQZERItgNIpC2OOVg2EVq2BUZyRbU6ymMLbwSQuDySzgZBB63V53KGxTIN1kNjnTltdVzavIMCPc61N8/gmzGgOiaEAo2JNSktLspu3nOjILylAKs0IUCbLLE46GKKOG9fNnlzjse3ceD8m6MVdH5/2T0JYEUXXKIkxovu1X+9oudM2fkTvB6FuXxx5fVds0IfzrzoZ751REQpFWEukanLh77aKy3CTE6NPHr4jpUp/L/7+nLhfkOYLEYE1Jqsx1nukc+MHx5uT8NB+L2XMyf3C4Ic8MdQV2j1b434fOCFbTDAlyM5z7rrbu6LfmpjnmliY1jo58dd+ph2sqV+WLAY2m5Njrg36fLJuBmZONPhxVVTJndsb/d+BISXpqeb55TSz/m4eb5qQZ7phV3Hqx/emTA/dVV7aOjHd6AhWVpfUTvv3tXZZCa1VaarS64sXG+tw08+qCvINX+2QTNmWnNHt9VkKy7aYxWVlYkfWbI1cb+pRPLJrjnXB5LdDs9VsIFTG+ozrj3w5fTjI4si0OR3JoXI3FNDnZLLZ7PACQbBEtWNk0q/BXJy4ZbM661KTFuSU/O9vf2+/55NKyNbNu+7+3WpPtbJHTpDFF1dRuj08D2La4dueZvh2d3UablJZkqqie8b399TazpFrZwbau3pHRGTPzg5KYorsp6Oi8XxI6ukGlYQaGrvGAz+sWGZMFQQbNSkyUhplJJJrJRpWYRlREwWAUNVFjsgnJVLAA0YKSSABZKTLEmGJhRAmLBgshooBJSJMt2MYQMoIiaEEEDr8giJgKmoY0LEiCT6ApKoDg8+EkiqXUCPELGkGyZLBKcoSASQBNMYrmqIoBaxIGCRENTJomURQ0CgoFIyE2AWuIqKCEBOZQrZKMgmYqMIwMqhATZdFg0ZQIBgxgBYQYkgFpLAZMY5JRUlBU0CyCKYpEkSmUkphIgIKFYAOjgJDHbE5Vo4oKIlZVxjRklKhEaQgYAsHKBMVMAbAhIiKNyqnhaNiYSrFKWMyumYkYkwUqEisClTAQGEVAKRIlUQqhmAYGRywSM5iMCACwRlQJBMIQAjqjIDfDpheO1NF5nyS0tGWqRhEjIo+qAgNoQEVAEEbECgwmw2uvS4vNQ24pIAwQY2BEEAMwEwCBUQAKTAQGIGgUKAbD5E4aA6TJAmCQJAKaABQ0A2jATIBiAGIMRBPIPEpLBcNkAUWqAY6o4JAAACgAAZAAZIAQg9RJHZASwAhgygVr8l1cVUAyaPFXCwYAGqCpF40YAAYwAMQznpPp8RSEe65BFMACKjCJAiCkEpBEAACiUUFUAEwQARCAGgHHwmCyTg4SAygACoDtxgknQAWGgUZB4FKVTo0BAwAjGhIEXbvV0Xl/JLS0jTNZboEHSt3gdv/bvfDZZODtu/x+Y2gqnwgeaoamZVbgkWdvu9dOa25qXFMNssndJ6sq3Hx4wNtBs+8Y27vHz7K3N3vXaZgMW54Wfsvi479u398ywnd8zQOC9bgyHZ0/kI+HtNXR0dH5uKMvMevo6OjcCnRpq6Ojo3Mr0KWtjo6Ozq0gof1tGTACPHMXE4BOJtrW0dHRiYMAJoUDAsCTC7oJuaab0NIWNIYAIoSojAjAEGUEE5qQ86ijo/ORQAEYQyYEVknECAhiCKHElGuJOaopGFABP3f42K9Png/ZbbIgSkTEug+Fjo7OJAgDMYT9jy1d8Oe3rxCACYxMlnBJPBLaA4xR0AAGA4GhQFAVBILASJFuadbR0YmjAiOMldhthQ47RhBDDAEYE9KUkNjSljFgaEq+EgANQNJX9nR0dKajARNBAw2ACRRjwIATUdgmtiVBQ8CASQwBY4wBA6xrtjo6OtPBjAmUUYypyHgcZyIaEQAgwXXbeEldiibr7xoYoAQer46Ozq0GgYZ4sWoQgAkMErZ+aWJLWx0dHZ0/FvQ3cx0dHZ1bgS5tdXR0dG4FurTV0dHRuRXo0lZHR0fnVqBLWx0dHZ1bgS5tdXR0dG4FurTV0dHRuRUkdCwZYwwh5PP5ent7LRYLQigcDs+cOTMUCvX392dmZg4NDQmCQCmVJCk5OXliYoIQYrPZysvLRVH0er2NjY3Z2dkVFRVDQ0Mul0tRlNTU1JKSEo/H09PT43A4CgoKWltbs7OzMzMzL126xBhLTU1ljLndblEUNU1LSkpCCAWDwby8vPT09IaGhmAwWFdXJ0lSa2urKIozZ87s6emJRqOVlZWCIACAoijt7e1paWlpaWnt7e2pqakZGRmCIDDGKKUIIX5ojDFBEPifsVjs1KlTq1ev5n8SQgAAY4wQisViO3bs2LBhQ0pKCqWU7wUAmqbxNhFCjDGMcbxZjDEhBCGEMaaU8u8BgO8oy/LBgwcBYMuWLXxfPtsIIT483ialFGN87ty5a9eubdu2zWabrBpJCOED49vEu+bf8x4ppaIoxscWhx8Uxnjv3r15eXmzZs3ivfBB8nb47ny08WEwxnj78e74NvwY47PBv+ff8F+nHx2fB75B/GCv2yw+e/FGpu/OZzW+PT8XoVBo586d9913X1NTU2Fhoc1me+ONN7KysgghHo9n69atkiTFG4xPAmNMVVVJkuL9Ukr5CeXdIYQIIYwxTdN27dq1cuXKrKys6RcA3z0+t7zN+Onju/Np5FPKZ/7GCYlvz7eJn19CCB/S9F/5tBNC+Mj5HPKN45vx4cXPRXzM8Unj2/f391NKS0tLu7q6AKC4uDh+j8SHHb9+4lfvx5qE1m351Kuq+tBDD+3evfvSpUvLly//zne+EwwGf/KTn+zdu/cXv/jFX/3VX/34xz/+9re/ffz48fvvv//UqVP/9E//9B//8R8DAwNPPPHE4ODgN7/5zZdfftntdm/evPnkyZP/9V//9Ytf/IJS+uCDD+7bt49S+tOf/nRsbOw///M/f/nLX164cOFzn/vct7/97V27dm3dunXHjh3f+c53jh07du+99wYCgf/93//9xS9+0dra+pnPfCYYDD755JMLFy5866232traXnzxxelxIj/72c96enowxk899VR/f78gCIODg4FAAGMsy/LIyAhCyOPxPP/88+FwmN94NpsNIeT1ekdGRgghgiD4fL5nn31W07TOzs5r1655vV4uXEZGRvx+P7/4RkdHX3jhhXA4HAgE3G53JBKRZXloaAghpKpqIBAYHx+PRCKU0lgs1t/fryjKuXPn6uvrs7Ozg8Hg6OgoQigQCHi9XrfbzQevaVp/fz9jbHx8/NVXX83NzeUXvcvlmpiYEAQhEAj4/f7R0VF+PwQCgdHRUS53PB4PH9vY2FhnZ2dDQ4Pb7VZV1e/3x2Ix3v7Y2Njw8HBHR0ckElEUJRwO80ngx8770jTthRdeGB4exhgPDQ3xqeMz7PP5XC4XlwKapv3mN7/p6uoSBGF8fNzv9/PxuN1uj8cTDodHR0cZY+Fw2O/3Dw0NaZqGMQ6Hw0NDQxjjYDDo8XgmJiYopaOjo5FIBAB27dp19erVcDgcjUaj0WgoFJJlOX68kUiED1LTNP4s9Hq99fX1fr/fYDAYDIY9e/aMjY2NjY0dPny4oKAgFosNDw8jhCKRSCAQcLlcCCGXy+X1eg0Gg8/n83g84+PjXFy6XC6Xy4UxVlV1cHCQSyuj0djX19fR0eF2u/kFMDw87Pf7McYvvPBCX18fP1JN0xRF4bMdDAZHRkb4FA0PDwcCAYRQKBSamJjw+XxcLEaj0eeee25kZMTj8USjUUVRCCEul4sx5vF4RkZGuHQGAL/fPzw8HA6HXS4XP15FUbxe79jYmKqqr7322tWrVwVBmJiY8Hg8GGO/3+/xeFwul6qqw8PDXHqOjY15PB7+AOCX97Fjx/bu3YsQOnLkyJ49ewRBcLlcY2NjvNOhoSFFUTRNe+mll4aHh2HqQfWxJtF1W8ZYenq6w+EoLi4uKip64oknnnnmmXXr1lVWVt57770PPPDAJz/5yVmzZj3yyCPhcFiSpMWLFw8PD8uy/Pzzz8disUcffZRS+j//8z87duwwGo133XXX+Pj4Y489tm3bNqfTmZ+fbzabq6urBUF48sknn3766cWLF1dUVHDV+MUXX3zkkUfS0tJaW1vtdjtC6Mc//vGzzz67aNGiH/3oR8eOHZs/f76mad/4xje+853vVFZWiuLkZBoMhoyMDE3TXC6X1WrNzs4+fvw4v6w3b968b98+s9lsMBhmzpy5f//+pUuXFhcXj4yMvPXWW3l5ea+88kp2dnZ2dvaKFStGRkZ27969YsUKk8l05cqVPXv2fO5znxseHu7t7fV6vZs2bSosLOzt7d23b9+iRYt+/etf22y2tLQ0ruWlpqYuWLDgm9/85urVq69du/bFL37x2WefLSoqIoSoqhoOhzMzM3fs2CGKYm5urtvtrq+vdzgcX/7ylwHgmWeeSUlJCQQCdXV1Y2Nj5eXlNputvb39zJkzlNLZs2d3dHT09PSYzeaZM2fOnTt37969kiQVFBQMDQ21tLSkpKRkZ2ebzeZz584tXbr0V7/61de//vXf/OY3mzZtKikp2b59+8jIyNjYWHZ29htvvCGKYkFBwdGjRx988ME333wTY1xYWLhy5Uq/379r166ysrLGxkaXy+X3+zdt2lRUVNTf3797925CyJo1a2bPni3L8q5du9LT010u17Vr1yKRyMqVK1988cX8/Pzu7u6ZM2d2d3dv2LDB7/cfPny4oqIiGo3ed999r7/+utlsTklJURTlzJkzSUlJpaWloVDI5XJ97nOfe/PNN5cvX37lyhWz2VxUVHT48OHHHnvsm9/8Zl5eXm1trc/nwxgnJSVt2rQpFAp9//vfnzFjRjAYFARh79699913HxcN/E0rPz9/+/btZrPZZDJlZ2e/+OKLaWlpCxYsGBsbi8ViCxcuPHDggMlk8vl8GzZsMJvNR44c8fv969ev7+zsNBgMwWDw0UcfFUVRkqSmpqYzZ86sWrVKVdWRkRG3271u3brXX389Pz//8OHDmzZtOnny5OLFi1tbW2tra1tbWwGgoKCAP5tdLteGDRt++tOf1tbWtre3f+lLX8rKyhofH3/99dfLysp279796KOPvvzyyw8++OCpU6cqKytbWlpEUZwxY8by5cvHx8efeeaZ4uJiADhx4sT/+3//b//+/bm5uZ2dnampqXl5eUePHjUYDOFwuKuriw9+9+7dBoPB7Xbn5eVNTEzMnz/fbre3tLQQQtatW1dQUAAACKGsrKxIJDI+Pi5JUl5eXm9v75EjRxhj8+bNGxgY8Pl8Xq/3gQce4MfIH/kfmST6gEho3ZY/hPkHTdOi0ei6deu2bNny9a9/PRqNJicnOxwOQgghJCMjw2KxAMAPf/jDY8eO/eM//uPY2JjZbAYAk8kUDAaj0ShX9ywWSyQS4VoMf1pSSgOBQDQa5brAmjVr8vLyuBmBMZaZmcm1mFAoFIvFuEjlaghj7C/+4i8A4Kc//el1L56EkI6Ojubm5omJCVmWX3nlFaPRyA0gtbW1KSkpTU1NWVlZs2fPLi4uppRmZGTEYjGEUG9vbzQaLSkpAYCMjIyampqioiJRFG+//fY5c+a0tLTs2LFDkiRZlvn7V25ubm1tbWlpqd1u37Jly7333ltSUpKWlnbp0qW0tLSkpKQHH3yQ62hut7uvr6+2trawsHDevHlnz57t6+szm81Xr15NT0+fMWPGF7/4RZPJ1NHRMTIycv/99/f19QWDwZqamqysLADYu3ev3+8XRbG9vT07O7u0tPTee+9tb28/ePDg2NiYyWRqa2vLyMioqqr6sz/7s4GBgczMTIfDMX/+/JKSkra2tuzs7KKiIkVRTp8+/Wd/9me33XYbpTQ3Nzcajebl5THG9u/f73K5jEbj1atXGWNOp7OysrKsrOzQoUOPPPJIXl7e8ePHMcY2m626uhoA2traAMBut1dUVMyfP3/nzp1c0xweHk5PT1+2bNn8+fOdTue2bduampp4748//nhfX9+ePXuuXbtmtVpbW1u5WelLX/pSeXl5WVnZwMBAJBKprKxcvHhxXl5eOBzOyspSVTUlJcXpdH71q1/1er2tra1Wq5X33t7ebjAYHnjggczMTFEUk5KSCCGlpaWzZs0qLS2dO3duW1tbc3OzzWZraWlJTU1NTk7+6le/eubMGZ/PBwCdnZ1paWnz589fsWJFW1vbgQMHVqxY8eijj4ZCoRMnTjgcjp6enlAoBACSJK1du/buu+8+fPjwb37zG4PBEAgEJiYmqqqqFixYUFdX193drShKU1NTSUlJQ0PD4OCg1WptaGh45ZVX+PXv8XjS09M3bdpUWlp67do1AEhLS6uurl60aNGMGTN6eno0Tauvr6+urr5w4cLcuXO3bdu2e/dubgHgqvSiRYuqqqr4WZ45c2ZHR4eiKFVVVaWlpYsWLXrttdc0TaOUchPfvHnzuJZw//33X716FSHEH8MpKSlxoUkpHRgYaG5u7u7uNplMe/bsCQQCkiQ1Nzfn5eUVFxe3t7cjhKqqqurq6m6BtLkFJLS0BQCEkKIoXBqGQiGfz/f3f//3TU1NjY2N/H0zGAwGAgHGGJeGTzzxBELoqaeeWrVqFX/zra+vX7FihdlsDgQCY2Njx44dW7RoUWZmZkZGxuXLl0dHR8fHx8vLy6uqqo4dO9bR0fHiiy9qmhYKhcLhML/WY7FYIBBIS0urqalpaGjo7e2llC5evNjtdptMpn/5l3957rnnvF7v9GETQpYtW7Z27drc3FxCiMViyc3Nve+++zIyMnbu3Gmz2bhJTpZl/jJOKVUUBQAeeughr9d74sQJbu2KxWKEEFmWVVXldjSLxZKRkbFt27ZZs2bxjqLRKKWUm9LC4fChQ4esVqumaZqm8UcRf/+9/fbb09PTt2/fzhiLRqMWi8Vmsy1ZsuTuu++WZZkxZrVaEUJms5lvAACSJIVCIf5MslqtSUlJd9xxx5o1a6LRKH8UKYpis9nsdvvy5cs3b97M32ctFsusWbNOnDixfPnyzMzMNWvWPP3002VlZdwaKIoif6mMxWIYY6/Xy0+uzWaz2WyrVq268847uRFQlmVCiNVq9Xq94XDY6XQCwLlz59rb261WK38nBQBFUWRZttls6enp99xzz5w5c6LRaHy6NE3jkxyJRMLhMKU0KSnJZrMtWrTorrvu4tNrsVh27dqlKArGWNM0VVX5Y9Xv9wcCgWAwSCmVZdloNKakpNjt9qVLl27btg0AzGZzKBSKRqN+v59rA/xfPg/hcNhkMlkslrq6ugcffJCfI7PZbLfbk5OTN23atGzZskgkwoeqaZrJZOru7k5OTjabzUajsba29pFHHjGZTAAgy7LP5xsfH7dYLFarNS8v78EHH5w5c2Y0Go1EIrNnzz548ODq1asbGxsNBkNSUpLD4VixYsW2bdtMJlNBQcH9998/Y8YM3hc3zQEAnxNZlufMmbNjx45t27a99dZbqampTqczHA673W673Q4AmqZt27YtFosdOnRo48aNzz//fF5ensFgePjhh0dGRk6fPs3bsVgs2dnZW7ZsmT17tqIo0+dfURSHw3H//fefOXOmpaWlv7+fG4tisVh1dfWaNWvmzJkTi8UcDkdSUtLtt9++evXq1157Lb4YwFu7VfLmw+VjIG2Hh4fXr1/P7XqyLGdlZf34xz9evXo1APT19dXV1fEXGY/Hs2XLFkrpD3/4w56enoULF37pS1/62c9+lpyc/O///u9DQ0P333//yZMnKaU/+clPDAbDt771rXA4/NOf/nT9+vWpqak//OEPR0dHf/WrX1VVVYmi2NbWdt999/X29vLLYuPGjV6v9+c///no6OjTTz/93e9+t7y8nBAyNDS0du3af/u3f6uoqIjblSKRSHJyMh+t1WoNh8NPPPHE4cOHub45Y8aM8fFxrtImJyd3dHQAgNvtTklJcblc3d3dOTk5ixYtQgg5HI7CwsILFy44HA6XywUAhJBPfepTZ86cOXv2rMFgIISkp6enpaVduXLFarUODw8nJycXFRX5/f6SkpLu7u6UlJTe3t60tDSPx9Pf3w8A69atC4fDsiwvXrzYarVu375dlmV+QXOZW1paunz58pdeemnVqlUpKSlGo3FiYoIxdv/99/v9/j179vD3DG6nM5lMK1asEEVx165dXP6qqqpp2tjYGKV03759+/fvr6yszM/PLy0t5da6+++//7XXXuNvEhUVFZTSCxcuJCcn33777YQQ3r4oioIgcE3q0Ucf3b17tyAI/BqYOXMmY8xut8eX42bNmnX58uVHH320ubn5xIkT/LHh8Xi40d/n85lMJlVVJyYmnn/++fXr12/atCk7O/uVV17RNI1PqSzLCxYs6O/vr6qq8ng8c+bMqa+vr6qqAoALFy7k5eUNDAykp6d3d3evXbs2NTX15ZdfVlWVMcYf0i+99FJhYeHY2Bjvl5tEJyYmEEKVlZUlJSW/+c1vuOWXPzkeeeSRkZGR/fv3E0KMRmMkEonFYoyxe+65p6ura/v27RUVFatXr37xxRfdbrfBYACApUuXDg4Onj9//v777//0pz/NryWDwTBnzpyLFy9mZ2cvXbq0qqpq2bJlubm5mzZtwhi/+uqrjLFPf/rThw4damxslGXZ4XBw87qiKIwxi8VSXl5+6dKlioqKJUuWVFdXL126NDMz85577hkcHDx9+vTjjz8OAJTS3t7e1NTUxYsX5+bm5ufnl5SURKPRnp6ewsLC+fPnV1dXNzQ0PProow0NDSdPnuSnjx+UKIoej8dqtY6Ojvb19S1YsMDpdB45ciS+vso/cIm8bds2v9//+uuvS5K0aNGirq6umpqaUChUU1Nz6dKlj0T4fODoOcA+xvDr9aMexfUoivJ///d/c+fO5WJ6YGBg+fLl/GUwbhq6xezbt+/8+fN/+7d/y41LOu8VvnT2y1/+csmSJUuXLv2oh/NxRZe2Oh8k3HbBF6PNZjNfjUlPTxcE4TrT9i2D+/PJspyWlmY0Gj+SMXzc4ZYuj8eTlpYmiuJH9dT8uPOxkbbvQ497r7t8VKrih9fv7275w+g37tAKAPxtURTF6e60N98OTPmEfoBje9cG38d1AlNeuh+V0HnfXb+/HW/0mf2onp0faz4e0na6U/fNE/cYv5kt427ncbf5W3Ajcaf96fctX0p63w3ywXO4p/p1hx+3l7FpYRHTPerfd9cc9s5YiffXLB+boiiiKL6Pu5ovoKGpwAc+yfFAEs50t3x4j9MeX6CDKSf83ztIPoa4j+AfyPSgEv7hZsYAAHxt9oMaxnXEPXyuu+SmBzX8iWvEH48HFMbY5/P993//N/fcuhmGh4ePHDly4MCBN9544/duzC/f5uZm7sv1B4q8m4dLhGAw+Mwzz7z00kt/eKfxWCCPx/P666/f+KTBGHMNhUcN/OQnP9m/f/8HeMhxOX727Nnvfe97165dex/NIoQuX778wx/+sKWl5X2MgVstpkeU8YiAAwcOxLfhv3I/kPcqBQRBEASBL5R///vf58uPvxdRFE+ePDkxMXHzHf02EELxEC+fz7d79+6bEbWNjY3f+973rl69+ocP4F3Zv3//zp07bxwJQujpp5++dOnSn7iohQSPbojD/eHHx8d5fFRXV1dlZaXZbG5paTEYDMXFxeFwuLOzs7y8nPvKaJpmNBrz8vLcbvfx48dzc3PLy8stFsvo6KjL5aqurpZluaOjIykpKT8/HyHE/WEXLVrU3d3d1NSUk5OTlpYWDAY7OzsrKiosFguldHBwUFGUWCxWU1MzMjISiUQYYyUlJS0tLTabjQcOXL16NS0tLScnZ3Bw0O/3847a29t5JEVXVxeltKioiFsPe3p6IpFIdXX14cOHh4aGHnvsMQCglLa2tvKQ4uHh4fHxcb4y6/F4QqFQYWGhLMvBYDArK2tkZKSgoKCrq8tut+fl5fX19XEXiN27d9fW1paUlBQUFPConnA4nJ2dnZqa6vP5+vv7+/r65s2bl5ubu3v3bgAoKirq7u6ORqM8vpn72PKQsEAgwGMWMjIyMjIy+LmID3tsbCwajQYCgRkzZpjN5pGRkYmJierqaoxxNBp96aWXNm/enJWV1dTUlJSUVFBQ0N/fH4vF+DoV9+5KS0sbGBioqanh2paiKC0tLdnZ2WlpaS+88MKKFSvy8/MBwOPx9PX1VVdXh0Ihv98fDAaLioocDgd3tKiurg4Gg16vV1XVsrKy3t5ev98/MjJSXFycl5cXCoW4Iz0hhLvQjo+Ph0Ih7svx4x//eMmSJQsWLGhtbTUYDKWlpfwY+emrqqry+/1erzcYDBYWFjqdTp/P193dXVFREQ6Hn3rqqc9//vOU0ubm5lgsVlFRgRBqb2+XJKmkpISfDovFkpeXBwDcX/uZZ57hHrX8gRSNRtvb2/Py8lJSUjo6Osxmc2Fh4dDQUDQaxRhzn2u32z0wMMCP3efzBQKBkpISu90+Ojo6Ojra09NTXV1dWFgYDAbdbncoFMrMzExPTw+Hwx0dHWVlZdyLi8/tCy+8sGDBgoKCgitXrvArv7+/X5Zls9nMBzk0NOT1eisrK3t6epKSkriboCRJPT095eXl3PE2Go06nU5VVRVFKS8v55FEgUCguro6KSnp8uXLCCF+nc+YMSN+/1osFn6r1tTUTExMGAwGjDF33RkdHY3FYqmpqeFwOBaLJSUlZWdnezyewcHBrKys+FX3x0FCS1v+DjI+Pv6DH/xg1apVkUgkGAzu3LmzvLz89OnTBQUFHo9HkiRN0/bu3cuDaubPn//6668XFRVlZGR4vd6FCxdOTEz09fUdOnTo3nvvPXDgQHp6elNTUzQazczMrK+vv++++6xWa2dnZ1ZWliiKPKbz1Vdf/drXvvbMM8/MnDnzRz/60Ve+8hVRFH/+859zsd7b2yvL8qVLl3JyciwWS1JS0vj4+KJFi+rr65OSkl566aWtW7dyEdPe3h4KhZxOJ7+wenp60tLSAKCiouLkyZPc3/vatWuqqmKM8/LyMMa//vWvrVZrY2Pjhg0bLly4MHPmzAsXLsybN++pp57asmXL7t27169f/9prr/3t3/7t/v37MzMzjUZjd3f36tWrX3nllfT09OzsbH6bDQ4OHjly5N577/3P//zPbdu2vfLKK3/913/9k5/8ZNmyZUeOHOH+c4qiWK1WjPF//dd/VVZWXr161efz8dwOhYWFzz777LJly55++ul169a98MIL3/jGNwwGw6lTp5qbm9PS0jo6OgwGw9mzZysqKs6dO7dp06adO3fm5ORcunTp05/+NHdQzcrKeuONN+x2++nTp5cuXcqjM7Oysnp7ewsKCgYGBnJyckKhUHd39z333KNp2pNPPlleXn7kyJHNmzdrmpacnOx0Ot1u93PPPVdRUXH69On58+c///zza9eu3bNnz5//+Z8/++yz/Puamprt27cXFRWlpqYaDIbh4eGioqJnnnnmoYce6ujoyM3NzcnJ6erqamxsvPfee7/97W/ffffdL7744j/90z+1trYuXLjw9ddf5y7Vw8PDPHpq165dJpOpt7e3qKjo+9//Po/h/tKXvvT000/PmTPnySefXL16dU9PD3dfdblcDQ0NGzZsCAaDExMT/GLYs2eP0+l0OByf+cxnuGxtaWl5+OGHjxw5wv3nYrHYj370o5KSkp07d65atWpwcLCvr+9Tn/rUvn37RkZGHA7HX/7lX7pcrpdeeolf7bNnz3755ZdXrlx58ODBxx577Ne//nVdXV1jY2Npaenu3bsff/zxb33rW/fcc88LL7zwd3/3d88991x5efn+/fu//OUv8wQX3JExLS1t3759Dofj2LFjK1eu5GckLS3tiSee6OrqOnDgQFZWVmNjIw/hdTqda9as4bfMsWPHnnjiiW9+85v333//7t27t23bdvTo0c9//vMnT57s7+8vLS09e/bsggULTCbT+fPn29raFEUZGhpatWoVv5FFURwfH29ubr506VJ6errP55s/f/6LL7741a9+9V//9V/nzJmTn5+/b9++Bx544Omnn/7a1772s5/9bMmSJc3NzQ8//PAfk0ac6JYEhFBnZ2dmZuYdd9yRl5fX1tbW2NgoCIIkSZmZmS0tLYqiDA8Pc0fOxx9/PC0traSk5Mtf/jJ3/qeUVlZW3nXXXaFQaO/evSMjI9x7v6Cg4Pjx43a7nXuP5+fnz5o1y2Qypaenb9y4kd8bTU1NCCGj0SjLMsaYu8E++OCD9fX1OTk5tbW1X/rSl65evbpx48Z58+a98cYbHR0dd99999e+9rXm5uaRkRGDwcAYy8vLO3HihNFoLC0t7e3tHRsb4wL37NmzdXV1GzduPH/+fEZGBo8VJoRcvnx5w4YNf/3Xf93W1lZQUHDHHXe0trZKklRYWLh58+ZIJDJ37lybzXblypUlS5acOnVK0zS73c6j6TZv3vzAAw9kZWVVVlbm5OQghDIyMgoLCzdu3MiTA3Cz3YwZM3jcXU5OTkVFRXZ2dl5e3l/+5V8ODQ3V1tZu3rz53Llzdru9tLT0rrvucjqdmzdvtlgsPNDj7Nmz8+bN27hx46VLl5KSksrLy7du3RoMBk+fPt3f38/1Vkqp1WotKCjIzs4+d+7cHXfcUVNTc+LEiaKiopUrV37yk5/Mzs6uq6tbvHhxamrqXXfdxd/EQ6FQe3v7+vXr8/LyLl68WFpayqNFeTiWIAhGo9Fms5WWlt55552MsYaGBj4zBoMhJSWluLj4K1/5Sk5OjizLycnJVVVVW7ZsuXz5stlsXrBgAQBkZmZijJOTk/Pz8zdu3Gg0GhVFKS4unjFjxvnz59euXbto0aLjx48zxkwmU3FxsaIog4ODGRkZRUVF3I+7vb1dUZS1a9fyPAx86rhz6IIFC0ZGRg4fPhwOhx0OB6U0Ozt77dq1n/nMZ+JX8vnz510u18DAQGdnJ0JoYmLC7Xbfe++9X/jCF3Jzc9PT0/1+v9/vz8nJmTNnzle+8hWE0NWrV7u6urj3cVpaWmlp6d13381zSvBljPLy8tzcXADgb1QbNmyw2WzNzc2XL18WBMFisXBzB2PMaDQWFRXl5OTwM1JbW3v8+PGioqLVq1d/+tOfBoAzZ87wi5ZS+thjj12+fDkzM7O4uLisrEySpL6+Prvdnpubu2HDhqKiolmzZs2aNWtkZCQ3N7empuahhx7iMZCCIBw5ciQcDlsslnhaDD6AuXPnPvzwwzxJE6U0JyfHYDAkJyfn5OR89rOf5aE369atczgc0Wg0Kyvr8OHDpaWlH4tVpZsn0aUtAKSmprpcrqGhoYGBAR5xVFhYuHTpUkVRHnrooe7u7lgsNjQ01NnZOTExEQwGfT4fpZS/eTHGRkdHu7q6GGM1NTUGg4EHO1JKH3300WPHjgUCAQBQVZW/YAYCgVgs5vf77XY772jNmjX8xV9RlL6+vosXL2ZkZITDYa/Xy+N6edKAqqoqrutxhyez2Txnzpw5c+bwjs6cOdPX13ffffcFg0FuiywuLu7t7eWaVyQS4YlRMMZ2u/38+fPj4+Pcd6qvr48nIfP7/fw9GiFUU1Pz6quvVlVVZWdnG43GhQsXFhUV8Rdefiz8pdLv90ciEa/XG4lEeKYYq9VaX1+/fPlyri/w9C6hUIi/hpeWlvb39/PAXFVVPR5PMBgMBoPcpMBNnHzY7e3tGRkZiqL4/X6fz+f3+7Ozs61Wa0VFxaJFi/gYeMtZWVmdnZ19fX2lpaVutzsYDHJ/LJ7XhjfOw9XMZrPT6ezr6xsbGysqKnK5XPxwUlNTHQ5HWVnZkiVLVFXlsWc+n4+HdZWUlCxbtkzTNK/XSwjJysrikWY5OTnz588/deoUT0kBADwyMBKJ+Hw+niAmGo1yuxN/Iejs7CwuLuYP2rNnz6anp/PwxUAgEA6HfT5fUlKSqqo8409mZqbP5wuFQsFgkP8aCoVycnK4cC8uLna5XNy61dXVhRDi+a7Wrl27du3anTt3UkodDkcwGGxtbfV6vTt37ozFYhaLhWfP8Xg8AMB7MZvNJSUlK1eu5OlgeP4go9FICGlvb1+yZEkgEOABb6FQiF/zNpvN6XTm5uauW7fO6/VeuXIFAHhCslgslpOT09HR0d/fX1ZWxk8Evxhyc3ONRmNVVdXChQsvXry4atWqw4cPX7t27fXXX09NTeUhi7wjTiAQ4Ma0kZGRK1eucMkeCATy8vJMJtOCBQuqqqrOnTvHZS6ldHh4uLGx0eFwWK3WgYGB3t7eiYmJaDTq9Xp5cIfP5+PXg9frzcnJWbdu3RtvvPFH5vmQ0AfD17XLy8vXrFlz5syZNWvWFBQUPPzww8ePHxcEITk5eWhoaOXKlevXr7/nnntOnDjBn+clJSXhcFgUxcrKyry8vNWrV586deoTn/jE8uXL586de/r0aZvNlpSUNDg4+IlPfMLhcDDGVq1aRQjhlofx8fGFCxempqZ+8pOfPHnyZHzxF2Pc29sbCAQeeughi8WSk5MTi8U+/elPd3Z2Op3OrVu3fu5zn2tubh4bG9u0aVNlZeWpU6fiHd13330lJSUul2vu3Lnz5s0jhGzevNlsNvf29j7yyCNOp5O3xhj74he/2N3dPTAwsH79eh60/sQTTxgMhnnz5rlcLh4uvGbNmkceecRgMHzmM59xuVyDg4MY46qqKh6ofscdd4yNjRFC5syZ4/F45s+f73K5Fi1aNDY2pmlaenr6r371q+7ubkJIYWFhcnJyKBTiW27cuDEpKamzs/Pxxx9njM2ePdvn8912220ul6uuro7HB2/evNlqtfb29j722GNWq5WbVqqrq2fPnr148eKTJ086HA5ukayrqwuHw5///OdbWlqysrJWrlxZUFDAMzxUV1cbjcb09PScnBxCSFVVFSGEH865c+dmz55dW1tbU1PDI27LysruvvvuY8eOGY1Go9HIh1pXV5eXl3fXXXcdOXLEaDQaDIby8vJIJNLX18eT7PzkJz+RZXnRokWVlZXcBZg/aL1e74IFC8bHxxcsWCDL8ubNmwcHBx966KHx8XFRFO+++27GWFVVVW1tLU/UEIlE6urqJiYmFi9enJ6evnXr1hMnTmzbtq2ysnLJkiXd3d3cTp2RkZGenv6JT3xCVdWOjg6j0VhTUwMAHo/H7XbzJGRlZWVOp3PmzJlFRUWyLNvt9i984QunT5+WZZkHTy9cuJAxxpN/KorCX8s2bNhw/Phxo9EoiuLs2bPdbveSJUt6e3sNBoPT6fzxj388Nja2YMECr9fLzxTPDvHEE0+cPHkSAIaGhs6fP8/PSHV1taZpTzzxRFtbW1ZW1ooVKwoKCvgbFY9EnzNnztmzZ00mk8fjWbdu3eLFi2Ox2JYtW/x+/9q1a4eGhhYvXjw2NjZ37lxVVYuLi/m943a7m5ubH3/8cbvdXlhYuHXrVpPJ1NjYaLPZ9u3bFwqFKKVLly4tLCxsamp6/PHHZ86cyVcIVq5cOT4+vnjxYr/fH41Gly5d6na76+rqRFHkIdEPP/wwX77+iMXQB0eie4Bd53cZd2mKe/AAgKZpfJkl7kf1rk6FN24G05xppn8z3XeKu5ERQv73f/+3urp68+bN8Z94+r7p2V1/23imwy9u7hsAUz5bPMkeTK2nwzvztLJpCWfjiWtlWZYkKe4G9K5dT/93YmLi5ZdfLioqCgQCa9euTUtLm77vdB+7+JDiuWXRVK5Vvhp+46FNdzWbPhVx4rlc4yO87tAopfGRxzO9cl8r/n38jPNd4g1On6jdu3eHQiFJkpxOZ3t7e1VVFbdQx7O7Tu/0Rvc4fozX+YrBtDyt8Rb4vtdNQvzQrvPHiv8Z7/E6T6wbrxMeVXzjsfMvu7q6Dh48WFBQEAwGeTKE6VfI9N5HRkbsdrvFYolnpI33Nf0y5vvGk+3Gxzx9YHz76w7tueeeCwaDf/7nf35js7IsT0xM5OTkTPdufNeDnX7Gr/Nivu5q+biT0NJ2+tjip5//yc8HnUoIfd3GMOXWE/f1m/7N9F3iP00XN3GRPd2PPX6HTH8AXNf7dSOMO5xOvznjsmy6xyvcIPfZtLzXME16Tr+vph9s/Hve0XWHBgCiKMqyHIvFeJKB+AZwwyPtOtC0LOPTJz9+XtAUMM3hNz4/1408Ps74XtObjY8k7jM7Pav09PMyfQzxFgRB4PYHu93Os8zgG3Jssym30OukyfR5eNfH5PRriQu1+INn+jUT33j6r9edjumX4vQdb5xkvuP05wT/iZ9Kp9M5fVTx6yS+L79+4r1PH0w8VAGmROR1p+NdD3/6aWWM8eQY8bvmuimNKwc3HsW7Ti8fwHSfcXhnEvF33fFjREJL25uHTUv5Djf9SIzn34Lf6aZ+nTCK3+03f+LZVBQD7wVuIrAqLpXYDWEd12nfv7sRPjPvqiJNR1VVHpF5k0c0/bimTzVXbON1HN512PzPmxn8zQSnsClF9UaFevpDLl7IYPqO8F7C1eItxIXXzVsVuWDiLy7Td59+Et/1YfaemP6EvlEwXXd5s3fqrfDeI2vishtPlc+IX2bX/Tr9nWD6s3l6U9MvpOkP3eveO2+8HT5GJLTd9uaJn7+mpqaRkZFgMDgwMPB79yKE8Mz8hJBAICDL8o3bXCdYedZkeI+Z5LmYGx8fr6+vv/m9GhoaeKr/675XFOXChQvhcPj3tsBHLghCc3NzX1/fu2oufr//4sWL7++hy8fW3NzMU2gDQCQSOXXqFK8ycOOwL168yB1gAaCjo+O3ZdJjjDU1NcXT+P9uNE1rb2/nt/GNP126dMnn8124cCESiVy3wXt6XsYP4cyZM93d3e9DIIqiODAwwBPj8ouB13SYPvN/oOLGz3VXVxfv5ToYY0ePHn3jjTe2b9/e3NyMELp06dLu3buPHj3Kcyu/p746Ozs7Ozv5U+TChQtHjx7VNK21tfXQoUPx7KN8hhVFOXz48BtvvHHp0qUbrTTxsSGErly5MjIywr+JxWI8PV5cT6+vr3/X2+FjREJL27jGCgCEkPHxcf46D1PCLm7egqlL7cKFC8eOHYtGo2NjY9e9ZF23PQCEw+G/+7u/4/6z/AO8My6TS0le34y3E41GeZGV697O4IZHenzY/IMgCJFI5Ne//jV/1E/fOL7N9DUBxtjx48cvXbqEpyo7xV+BJUnavXt3T0/P9Im68TPfpampyefz1dfXHz16NP6uFx8tpVRV1aefflpRFPROw8vvkL/Tz4soiufOneNrMgCwffv2+vr6sbGx6a1xw7fRaNy1axcvIMQYGxgY4AfOT0q8TVVVEUInT568cOHC9PeJ6edl+iEQQvr6+qZ/E/8giuL27duHh4d3797Ni+7wFTO+nDgyMtLe3n7jm3i8F94jb4prpm+++ebJkyf50U0fz3UDm/4vf6JwuTM8PPzKK6/wg3K73XHZEe/iwoUL3PcjfqHGL4npg+H/8i2n/9rR0TE6Ojo4OMhzq8d35zLx61//emNjIy/NcPz48ddee+2FF16YOXNmb2/vP//zP8e35Db0Gzu9jq6urr1792KMJUnas2fPM888YzQaBwYG/uVf/oU7gcTP2t/8zd80NzeXl5c///zzzz77bNywcF3jgiCcO3fu1KlTMFU9gOsHMCWLjx8/3tjYGDf+fhxfyhPaAh0XcHv27IlGo3ylvrm5mTH24IMPnjx50ufzSZK0atWqXbt2IYRWr16dn58fCAR4dvqWlpa9e/cmJSWlpaVt3br10KFD4+Pj3JeIt8/9z5OSkiwWi8PhyM7Obmho4Mn2161bt2PHjkgksmrVqtbW1r179/7zP/9zXl5ed3f3xMTEyMjIm2++qWnaihUrSktLL168yDMx8yzOzz77LMZ4yZIlPOl9VVVVVVXVr371K5vNZjabBwcH9+zZ8/DDD//617/+1Kc+deHCha6uruTk5BUrVhw5coQQsnHjxitXrjQ3N4+Pj1dUVADAlStX3nzzzYceeujYsWOzZ8/u6enh1XcOHjz46KOPIoQOHz7MGLvjjjtefvllm802Njb2yCOPZGdny7L8wx/+cN26ddnZ2UeOHPnhD3+4aNGi6upqvlh82223VVRU2O12QRBeffXVaDS6efPm11577fOf//wvf/nLhx566M033+RJbO12O/ed2rJlS2Zm5v79+2VZXr9+/cTExLFjx7xeL/duDofDx48f37Zt27Vr13iS74mJiVWrVu3fvz8Wi23evJlHcACA1+vt7OxcsGDBnj17FEXJyspas2YNL3c4MjIyY8YMHvJ07dq1O+64o6Cg4MCBA6FQaNWqVefPn+euQiUlJb29vfPnz6+srOzs7Fy5cuX27dtHR0dnzJiRkZFx6dIlURQfeeSRzMxMSZKysrJ8Pt+3vvWtRx999Ny5c8XFxXV1dTt37uzr6/vsZz+7c+dOURR5clufz7d69WpFUfbt28evnA0bNvDsvSUlJZcuXUpOTi4uLv7Vr37FPTSampp4Va78/PyBgQGMcXp6utvtLigo2LBhw969e4PBYG1tbVpa2m9+8xuz2RxfiWptbS0tLT116tSFCxckSeI1Nb773e/+wz/8g6qqTU1NDodjy5YtFoulqalp3759vOqByWQKh8Of+cxneGbulJSUVatWHThwgDGWn59/4MCBjIyMFStWOByO3bt3R6PRRYsWHTp06PHHH79y5crZs2fffPNNQRD+4R/+oaen53Of+9x///d/z5gxY8aMGStXrmxoaJg/fz5Me1s/e/ZsS0uLyWS67777nnrqKZvN5nK5Hn300WAwuHv3boQQf/FHCKWkpPC6UBjjrKwsnuudHym/kn/wgx9gjD/96U9/7Wtfe+CBB3jxyomJiSeffPKzn/3soUOHli1bdu7cuYyMjMbGxu9///urV6+22+0DAwOyLO/YscPj8SxatKiwsPD8+fNXrly58847y8rKbr04+sNJaN0WTUW4Nzc3L1y4EACSk5MrKyu7u7sHBwfPnDnDoyRfffXVoqKiVatWvfDCCwDA/cA6OzuTkpJ8Pt8DDzxw+fLlxsbGQ4cOFRcXv/rqq3GLAUIoHA7v3bt3x44dvFTUL37xi/z8/FOnTvX09KSnp+fm5h48eLCoqIi7HAGAw+Ho7e0dHBxsbW0tLCzk/vx2u93j8Tz22GO8GqDb7b7zzjt7eno8Hs8nPvGJ/fv379ixIyMjg7vlp6amdnd382u3ra3t+PHj9913nyiKL7zwAiHE5/Pt379///79n/rUp3g0MADw1eeenp633nrL5/PxeNalS5fm5eXV19c/99xzGOOJiYnTp0+rqlpZWZmbm3vx4kV+c86YMWPx4sUAUFZWtm7dumPHjp05c6atrc3pdO7YsYO/2YmieP/99xsMhvr6eh5YyUtXMMbS09NXrVpFKU1OTubxFHv27PH5fIIg7NixY9euXXfffXd1dTXXUMxmc2Vl5axZs3gShpSUlL6+vl27dnGnZh4ozJ+gTqeT1546deoUr0kMAK2trS0tLXfffTcvoFBTU7NkyZKzZ8/u27dveHjYaDRyZSojI6Ourq63t5dHNPEk2Y2NjV1dXVu3buXVDGtraxsaGnjFQwCglKanpxuNRp7mvLS0FCGUm5t72223FRUVjY+Pr1+/vri4ODk5OT09nT843W73ww8/fPbsWbfbffr06YyMDB7/PW/evJdeemn27Nl1dXXPP/+8zWajlG7cuFEURVEU161b19jY+PDDD587d+7ChQtnz57NzMx85ZVXduzYUVtbG4+t4vpdf3+/3W6XZfmee+45ePBgSkpKdXV1QUHBSy+99Nhjj01MTJw5c4ZfcuFw+J577mloaNi6devAwEB3d/f27ds/+clPjo+PHzt27MKFC3x4xcXFS5YsMRqNlFJek83n85WVlYmiyN0EBUHgJpecnBxKKQ+04V10dXU9++yz3/rWtyKRSNw2XVNTc+7cuWg0GgwGq6ureeDJrl27li9fvmDBgumG5q6urosXLzY0NDDGeH3Jf//3f+cR5/HUQunp6dw9mb8Z8OLW/f39R44c6evry8nJkSSpoqJi5cqVR44ccTqdw8PDZ86ciUaj69ev54Un5s2bV1dXd+LEid+xmpfIJLS05ac8JycnKSmpvr6ei7PR0VEug+65556JiYk333wzFAo5HA6bzcarDyCEJEnitfOSkpKcTqfJZOI3fFFREY+k5OnrAcBqtd5555333XdfVlaWLMvhcJgHtyCEeNwtt13EVRKDwYAQKi0tXbx48RtvvDE6OgoAkiQ5HA6j8f9v7zqD4squ9HvdDd3QAZqGJjQ5BwkRhVBCQhoNCqMcLY3kifbYnrG94dfW7rpqt9ZbLnvtLXtGGo1WaSQhgbJGCZGEQGQENDSZpjMd6Ejn7vf2xylevQFJlsc2llzv+0E13e/dd++55553wznnYwYEBIDjekpKSkhISGBgIIvFwjDMZrNxuVwej4eQ9lLpdLrb7fb5fBBSZTQaQ0JCtmzZUlJSAp4DLBYL1JTP53O53KGhoVWrVtXV1aWnp2MYxuVyw8PDcRy3WCx8Pn/btm0w0kJDQwUCAXnPBLw1g4ODQ0JCAgICLBYLi8UC+hZiRcZmszkcjsvlIlK60Gg0oLNMT08PCgri8XjwOLPZDGwxW7ZssdvtwO9APjUKCAgAOYCDGly/bt26iooK8JlDEIROpwcGBgYHB4MR6ejoQBAEOFYhCsvn87HZbD6fT6PRTCYTm80Gbhs6nc7j8YAoDJoDTLcul8vr9cbGxm7YsKG/vx+UBFqHzrlqbN68+cqVKxEREXw+HzoC9ITNZgORz/DwMHg9s1gsHo/H5XKZTCaXy921a1dbW1t/fz+0CHonNDTU4XCAt1laWhqPx4N1EjDxMJlMoCXNyMh477337HZ7aGgom80mdwoEyEFRAQEB6FyuGQzDwLkYcjAxGAxw3BYIBFwuF2iQcByHElAU3b17d1tbW09PD4PBgBQEPp8vLS3N7XY3NTVBHvclS5YAAzGdToeXWWhoaH9/P4IgEGYCPDcul0sikYCKDg4OGo1G2GICPiQOhwNjB9pC7Kr7fL6cnJzNmzdv3LgRRVGHw/HOO+8gCCKRSLKysjAMAzrngYGBuLg4iNaBLYicnJza2tqdO3c+fPgwJSWFRqMFBwdDpwcGBgLzE4ZhGRkZJSUlQJsUFhZGBMj99SzPXwmvtbUFQGyuWCy+d++e3W7X6/UQdNTV1RUTExMdHb19+/aurq7bt29XVFRMT09rNBq5XK7X66empmZmZiYmJvR6fXx8vEgkevDggdlsrq+vB7oOCFjS6/UQ2uRyuSoqKm7fvg3sfiaTCcMwCPJRKBQqlQrHcWDb7u3tnZ2dTUtLA1dHSNhx4cIFCHDSaDRjY2MrV6602+3nz58vKiratWtXd3f31atX4VAuJibm/PnzJpOJy+XGx8f/7ne/q62t3b17d1dXV3NzM4fDKS0tPXHixOTkpE6nQxAEx3Egblm+fDmoqV6vVygUarV6enp6165dHR0d7e3tsHKXyWTT09MQ4ABT6adPnyoUCrhFo9EUFRXNzs7W1NTAGwhBkMTExMrKyuHh4Q0bNqSmpp46dQoSvhiNxtHRUZ/PB0c6k5OT09PTmzZtGhkZefz4MZ1OX79+/cmTJyUSCXB0A5/V8PBwenp6b2/v48ePjUbj22+/PTo62tTU5HK59Ho9iHFmZsZsNg8PDw8NDSUlJUVERCAIkp2dzWQy//CHP7S3t8/MzED0oEaj2bhxo0KhaGxshO14tVqtUCiAVchisUxMTBgMBgjM/eKLLyBoVa/Xh4WFDQ8PQx6ZmZmZycnJ7Oxsr9cbHx8PA1UoFI6MjExMTBiNxuHhYTDrCIK4XK6pqSlIhWOxWCQSyeTkJPS1RqORSqVbtmxpbGysqanZtWuXRqPRaDSgogaDQSqVWiyWsbExrVabnJwM83GTybR58+YHDx7U1NRAJBuO45DER6VSzczMgKgh7Eoul5eVlV24cMHr9a5evRqisGZmZsbHxy0Wy+joqMlk8vl8q1evPn/+PI7jGRkZw8PDqampQLXX1dUFCu/3+/Pz8+GtjON4UlLSj370o1/96lcPHjy4evWqXq//5S9/2dDQcOvWrS+++OKjjz5au3Ytm83OysrKzc3F5zJearXasLAwqVQKwZxarVaj0axbt+7atWtPnz41Go0QgWK1WsfHx91u9+TkpNFohJVQUlIShDt+/PHHJ06cuHfvXn19/S9+8YvBwcGzZ8+CpV62bJnX612zZg0oqlKpBAkbjUZQ/qysLJVKdfLkyYGBAVAJkBVs7v+NDNJ3x2s9IYdDqr6+vpaWlrVr1968efPjjz+GUBPwarLZbDDBgUkoBFkjJL9XMIWwi4SiqNlshjB2whkLPJ8ggR5MDfR6PcwrwRjBetztdgcGBjIYDJh/MZlMoPyDWVJfX9/58+f/6Z/+SSgUYhgGcQeBgYEej8dmswkEAtiygBxdMB8xmUwcDodOpzMYjJmZGZgIQ6gx0B0ajcagoCB4yRNtQef81ZxOJzhsYRjGZrMtFguNRmOz2bAMhHUWEXAMlUcQBJrJYrGgYjCJgJm70WiEySaGYUajERjd4cAErkfmPJaYTKbL5YJ0BLCDwWKxIHMFMnfGRUgPZvezs7OQzwFi/JhMJpBUBgQE+P1+SNkD1fN4PDMzMxEREcThEkxygSY5PDwc1qHI3BIBvJqgUTiOA7MsdDQ0n/AqdTgcsIlfUVFBTCEhFALHcRqNxmKxLBYL/At3geYA+7LH4+FyuZCGBujFEASB6S00k6gwMnfyAx1nNBoFAgFwSsKsGfoC3ACIYARggYQQsuDgYJ1Ox+PxgoKC4EwP1gSg81AlUJvQ0FBIcONyucLCwsDHBibgT58+1Wq1K1euTExMxOccqrRardVqjYyMhJmp2+2Wy+U8Hi8qKsrj8Vy5ciUyMjI5OTklJQVCHoxGI4/HI6J4YK0AgoL9ARhWMzMzPp8vPDwcIryDgoIePXokFArj4+OBMVqr1ZpMpri4ODabrVKpOjs7d+zYgZAc40C34X1DdKvP5wsKCoKA4PDwcCI9JoIgMGZf3QPvNcFrbW2JU92+vj6YS8LmKfEr+m3H6YUOs4Se4QvCzMg/ISRHk3nvTHL5z/0VRVGZTCaXywsKCths9nMfhD/Pj51cwnMrtrAJyAInRHL1XiTDeXUmvG6J4+CFzvPzricuIHvszqsYuY3YgkC4hQ18URvn/UVIHb2wv14iz3m/+v3+9vb2zMzMsLAwcgVeJPbnFjWv/uRCFtZhngIsjC5b2GqEZGuQl+reH1Wb8fFxh8MBp5fPvR3/driBTCb76quvaDTanj178vLyniuihVWa148AuVx+4sQJBoOxY8eO/Px8/Nsesh6PB7bR/mj/znvuS7rmTcFrbW1fB/yl+vW5huzvA2+o6iOvfc3/fJ35ow3E50I/0DmqC3L0zbzXxitiXhg3UfJfqs5vLt6wqfgiA59zP/wzy3mub+bfDd7EF7bX630jOgXmkt/hRkjH8SqFE/Fd+JzLM2HsiC9fvQ74nCM8MXD+pHvJDsV/f3itrS1owzyX9XmfMQyDI1qiU4kP5OuJoUU+rAeve/K/sA0HigIZ+f7jP/7DbDYj3w49gN004l7y0xcqCo7jv/nNbyB6Z94IJysiJJDt6elpb29fWG3yg+D8/bliIb4hl0yEhJCfSG6L2+0mvOJepO7kUTcyMnLt2rULFy7cuHGjvr7+xIkT3d3dyLdjEMgVIEqDLcjnjiXoxHnXz2vIwsovvJ740ul04nOYV5parf7DH/5w/fp1dC6RykuKwnGcLO2FTZsXkzJPqRAEGRoaamhoIH8DdSMum1cBfM7NHEXRysrKBw8eIN/WsXkfyF1JlHPu3Dk4CiYGEVkO2Bw9XVdX15dfful0Om/cuIHN5e6ZJ/MzZ87U19cvrOFzxQUnInCoAHsIdBJ3JPEXtH1eOX19fb///e/Jc2GFQnH//n2y6OZ1xJtll9+A6AYMw4aHh2dmZgoKCsxms0ajcblcxcXF4K+Tl5cH5zNwEKzRaMrLy0dHRyFjnlwul8vl4eHhaWlpXV1d4EauVqvHx8dFIlFiYiKCIDKZbHJyctmyZTab7YsvvvjJT34CUQxfffXVT3/608DAwI6OjoiIiKVLl0K279DQ0KysLFDWvr4+u91eVFRktVr7+/uTk5OFQiHkrmexWEFBQTMzM6WlpSEhIX19fRaLpaioaHR0NCwszO12ezyexMREiOUFjgBwvIWNxY6ODhzH4XpIA1pUVAQuRKdOnRIKhXv27BkeHrZYLAUFBePj47Ozs06nMz4+fmxsLDc3NyAgAI6JQ0JCgNVmaGho6dKlCIJMTk663e7c3FypVOrxeAoLC69fv+50OsvLyz0eT2RkJKSjHR0ddblc4Kw+NDSUk5MjEAigX/R6fWxsbGVl5YEDB7RaLZvN7u3tdbvd+fn5kG3P6/UWFhaCG4NQKExJSXn27Jnb7S4oKICBNDQ0BKm1N23aNDY2xuVys7OzVSoVBG4kJye3t7czmUzoLKlUGhMTk5ycDOc2fX19OTk5TqfTYDAIhcKZmZnMzMxnz56FhYUlJyfD0/l8flVV1YoVK8rKymg0mkwmk0qleXl5ISEhKIpCrERZWVlfX5/NZisuLgZXFo/HU1BQMDg4SOSrHBkZycnJgcgCq9X67NmzqKio5OTkwcFBmB0XFxfDS3RiYgKyEXI4HBRFBwYGvF6vxWJZsWIFhmGxsbFOp7Onp4fNZgsEgj/84Q8ffvghuK+Gh4eDCwecrxYXF9NoNIfD8V//9V/79u0DhhEul5ubm+v1eiFpN3A16fX64uJipVIZFBREp9PNZnNaWhoIdnp6msfjATlNfn4+qI3JZBoYGEhISEhISAA71d3dDQ45TqczOjoaQRCxWAzUR5Cf02q1rlmzJjw8HBL49vb2Qopxq9Xa09OTkpISFxcHNc/Pz+/v7/d6veByMz4+XlJSwuFwJBIJqK5cLockvIWFhRqN5tSpU59++mlMTAwx2Ds6OiDDOlQD+B08Ho9IJDIYDDKZzOVygW6A34JUKl29enV8fPyrJAx5TfBaz20RBIEB1tzcPD4+/vDhQ4VCUVlZCcFdfX19o6Ojd+7codFoEonk9u3bDodDrVYPDw/r9frq6mqFQnH69Gkcx4eGhu7evSuVSp88edLQ0HDmzBkEQYCWDsOw+vp6p9MJX87MzBA+AAaDISAgwOv14jh+8+ZNcCm3Wq137tzp7+8HUr+2tra+vr4HDx6cO3eOy+VeunRJo9F8+eWXdrv9q6++kkqljx49GhwchHNzuVx+7dq11tbWzs5OlUr14MED8NzSarVKpdJkMvF4vI6Ojr6+vvv37ysUCqVSef/+/Z6enrq6OrlcfvXqVZiLGY1GJpPZ09PT1NQklUqvX7/e0dFRX18/Ojp67tw5i8Vy6dIln8/3xRdf0Gi0ysrK7u5uiIA4fvy4Wq0+ffr00NBQd3f3s2fPOjs7IeUCeBdAeMipU6dQFD137pxYLG5ubr506RKKol988QWRGXr16tUlJSVsNjsuLm7nzp0Igvj9/r6+vpqamtbW1p6eHrFYfP369dOnT/t8PrFY3NjY2N/fPzw8fOfOHQaDMTQ0VFNTA2EgYrHYYDBUV1erVKpTp07hOC4Wi+/cuaNQKJ48eVJfX3/mzBkURaGzHA7HqVOnaDTaiRMnTCbT+fPnW1tbzWbzlStXzGbzrVu3JBLJxYsXISBwZmYGzBCGYTU1NTab7fTp02DrmUwmn88fGBh49uzZ7OxsdXW1Uqk8f/780NDQhQsXJiYmHj9+3NDQcPnyZRzHT5w4AfPukydPBgQEPHz4cGRkpKqqanp6+tGjR729vTQabXZ2trGxkQjMBYPe2tqq1+vPnj07OTnZ2dlZU1MzMTEB7mhWqzUoKAgC0urr68Vi8dWrV6empiD2BI5A9Xp9UFAQiqIej0ehUFRVVfn9/s8//3xiYuLWrVuPHz9GEOTixYtdXV2NjY0gQ5lM9uDBA7vdrlQqORyO1+uFG2G2WFtba7fbT58+DbPmhw8ftrS0wEzcarXev39/bGwMgjblcvnt27fFYrFUKq2qqmIymSwW68mTJ2az+fz58waD4eTJkyiKXrx48eHDh0NDQ729vfX19Y8ePZJIJK2trffu3VOr1bdu3RodHW1sbNRqtdXV1d3d3bW1tUqlEhoCTt/ElkV9fX1TUxNMVHt7exsbGzEMO3fuHHj+2e32L7/8EvrCaDSeOnWKyWS2trZCUMwbtMn7WltbdM6TKTw83OVyGY1GoH756KOPJBLJ7OwseLnjOA6uS263e+nSpWFhYeAc5vf7ly1bdufOHS6X29TUBG/dkJCQ7Ozsb775hnByCg8Pdzgc4PYUHx8fGRmJ4ziPx0tISAgPD2exWBDtajAYnjx54vV6ExIS4F3a1dW1bNmyH/7wh6mpqRqNpri4ODAwUKlUJiUllZaWZmZmZmRkFBYWarVaBoORl5e3ffv2oaGhiIgIBoMRHR3NYDBSUlK0Wu3g4KBIJIL3tkgkotPp3d3dhYWFa9asaW9vj4qKSk9P37hxI7z2URSNjIzMycnp6OiYnZ0Fp/eoqKicnJyysrKIiIi33nrLbrcHBQUlJiauWLEiPT39yZMnkEAkMTERKCM/+uijjIyM0NBQcDeOiIhITk5OSEhgMpkQzcxkMkUi0c6dO5cvX97f3w/3Er5l+LczYDEYjJycnFWrVlmt1s7OTqvVGhERIRAIcnNz7969y+fzW1tbwX8rNDQUx3FwdYJosYiICDqdDk6aS5cuvXPnTkhISEtLC0xkgPPm1q1b4BWn1+slEglMFTMzM4uLi5uamtatWwc5uWNjY4OCgqKjo7ds2bJr1y6BQJCamgoVhiBmECCCIEKhEOanOTk5GzZs6OnpAf/QDz74QC6XFxYW/sM//ENwcPDIyAiKogkJCV6vF/jowKEKFjEFBQVFRUWQRQV4m2ZnZw0GAzwiOjo6Pz9/69atMLv3+XzZ2dmDg4MajSY6Ohqc/EdGRsrKyoBIND4+vrCwcOnSpUDcwGKxoqOjExMTURRNS0vbsGGDwWDg8/mxsbHHjh3z+XyxsbFr166VSCRsNpvFYsESBEJmvV7vsmXL6HR6RkbGmjVriBwxUVFRKIrqdDp4aw4MDJSVla1cuZLFYvH5fOCCxDCsubk5MjIyKiqqqKho8+bN4ImMYVhkZCT4sclkMqfTuWHDhn/8x39sbm52Op1CoRAC33Nzc5cvXw5x2G63u6OjY2ZmhsPhCASCiIiIrKysDRs2mM3mkJCQ+Ph4WCqBLonF4g0bNqxcuZLH4z179iwrK6usrAxCLmG1l5iYuHr1aiCgDA4ONplMBQUFEDX3BvmBve4VpdFoExMTQN5ltVoNBoNarfZ4PDk5OR6PJz4+HnhSgYFVJpOlpqbeunULFvIwEvbs2fP06dPMzEyfz5eYmBgaGoph2M6dO+FdOjs7e+fOnaioKIfD4Xa7TSYT5ArBcdxoNOrnoNPprFYrBHGlpqZGR0fjOJ6RkdHQ0NDb2wtcobCBEB0drdFoTCaTXq83GAw6nQ6Ye0ZGRhobG4GpcHBwcGhoSKPRTE5OVlRU4DgOnFcqlUqn0+n1+vT09IGBgd7e3qysLFgYGgwGo9EIG3M4jk9NTWVkZHi93piYmNTUVK1WC5U0Go3AFwDvD4lEMjIykpeXBwxDWVlZLpdLo9E4nc729naZTMbn861WK47jCoUCRVGtViuRSIB5d3p6Wq1WCwSC0NBQHo+3bNmyoaGhnp4eGHuwkAfjYjAYZmZmQFBJSUkYhsXHx4ML5969e1taWjIzM6GzkpOTcRwHbke1Wp2cnPzgwQNwNZ2ensYwDDg40tLS/H5/amoqBODv2rULZmFhYWHh4eEcDicvLw+4ZzgczsOHDzMyMjAMy8rKAjoPrVaLIIjH45HL5TiOz8zMPHjwIDo6GroYQRCdTqdUKtPS0oaHhzs7O1NTU61WK+wkJCcnw4w1ICCAw+GEhYVlZWXB5A4YEhUKRXp6ukql0uv1Wq0W9vTlcnlLS0tkZCSQvyEIgmHY6OhoS0uLSCSCHlGr1QcOHIAbgYAnPj6+t7d3amoqNTVVrVbDOpqgyXG5XAqFAhRJr9ebzWaj0ajVamdnZ9PT0+VyeU9PT3x8PJD1SSQStVrNYrEMBgOQV05PT0MNDQYD+AvfuHEDdjlgzzQpKQnSDmg0GlAbqVRaVFQUGxsLMWbDw8MtLS0JCQlQ/1u3boF1A2KF5ubmoaGhrKwsv98PuxMajQbUwGQywZ5eUlISjuMikSgzMxMqT9RnZmbGZDLV1NSACkHKiP7+foVCkZaWNj4+3t3dHRcXB/7XcK/JZIIQQVjrpKWlYaSMqW8EXmsPMJhGQQAij8fz+/1hYWEKhaK0tJTNZkMqltLSUi6XCzHpiYmJT548+eCDDyYmJiBmF0i6UlJSoqOjHz58yOFwVqxYMTw8bDKZkpKSYAOrs7MTjs5ycnLEYnFMTAx4d7e2toaHh2s0moSEhOnpaWDBqqurg9c+giA0Gq2urs7j8axfv95oNPb396empopEoubm5szMzKmpqcjISKvVymAwYmNjYWegvLw8MDCwrq6Oy+UyGIzIyEilUslgMIqLiwn+KIgH7+jowDBs5cqVYrEYgnMUCsWqVasCAwPlcvnk5GRpaWlbW5vNZluzZs34+DgEd2i1WqA9z8nJ+d3vfrd27VrIbzAyMtLb21tSUhIQENDf3798+XImk/n48WNYByQkJPT29q5Zs0YsFttsNhRF09PTR0ZGRCIRhCoNDAwsX77c5XL5/f7s7Gwcxw0GA4z2jIyMtrY2NpsNIRJFRUUw01yzZs3o6KjZbE5JSYmNja2trcVxfOXKlSEhIR0dHZ2dnfHx8S0tLR9++OHY2BgEvELim/T09MjISKKzxGKxxWJJT09PSEhAEEQmk3V0dADhm8vlYjAYRqMxNze3vr5eKBTm5ua2trbCzFcikcCeLLj6w07lsmXLQkJCuru7nU7n8uXLu7q67Hb76tWrlUoliDQoKOjhw4csFqu8vHxkZGR4eLigoCAuLg52tDo6OqKjo7Ozs5ubm0UiEdDEQchWU1MTUCQUFxezWKyLFy/abLa4uLjS0lKgdg8PD1epVBwOJz8/v62tLTw8PDo6GtJE5OfnNzU1iUQim82GYVhxcTGO4/39/WBZ3G43bKanpaWJxeL8/PzIyMiuri7I1cLlch89egRR43Q6vaurKzExsbGxcffu3SwWC0jAVq9ezWQy4T3KYrESExPj4uJ8Pl9DQ0NgYCCdTo+JiZFKpRkZGXK53O/3l5SUnDt3LjAwMCIiYs2aNUNDQ3Q6PSQkZGJigsvlxsXFgUiXLFmSkZFRU1NDp9NXrVoFRxoQ/hMaGqpWq1evXt3W1maxWFatWjU1NeXxePh8vlKpLC4u7u7uTkxMvHXr1p49e2JjYz0eT2NjI2RyKCkpGRgYMJvNpaWlsJ+ekJAATBxDQ0PR0dE1NTWZmZkNDQ3vvfce5Oh4U6a3r7W1RV7Z+Q6Y+2AWtnHjxkWo2N8KrygQhULx1Vdfffzxx+R4kL/e4/4kSCSS9vb2kJAQDoezadOmv2zhi4+FIsIw7MyZM2w2++DBg3+pMl8Fo6Ojzc3NkLli8+bN3+3RCIL4fL7jx48nJiZCuoO/EoC7E4K2Xx1Wq7Wqqio8PNzv95eXl8MWE2VtFwkw/4U4P4gr/VvX6G8PHMfJ+V/+1tWZD6ie3++HlD3ImzNaXhFkz6TFkT8hRvBNhJPe7yxVbC7XLZl24S8IkM+fGvVAhtPpZDKZxCnCa6jkz8UbrOX4XKQNOhc6DamnkAU+4fPeKK/4gvnO76F5T39RmX+0/Be5Vb5KJcmsU3+0Jt/tgoXXL7yFqPm8hqMoGhgYiJFo5f5S+PP7+s+UGwB7ASnRX3VyA1vGkOrhOwsW7v2jdvbPaQgxcl+i2C96FlhqUB7ilfCda7LIeK0riuM4ERJDpNyHL+EzpOLHcdxkMtXV1UFKFJwUkQLXwF0QBwHpNsbGxsChlfD0hsuIW4hnwV1EOaDQRHQDOSTJbDbDiTkogZ+EeW0ZHx+HEAbioUSB8JeoiUqlAr4QKAfc0Ygqeb1ecLwnRNHV1QWpy4ih3tXVNTo6CnfBIRhcTG4yOVjD5/P19fVZrVb4iagPISsiTAjqs1BKxAXkihGfe3p6IIkfIRMQF7kjiIcuFAjxPbn3MQxzu93d3d0ul4t8GTIX/LLwevhSq9XevXsXkt6SG4IgiMvlqq+vt1gsIBO4EbqbXAcMwwYHB2tqauDRUGHybIvcKHwuygBb4KIPkiH6l9AceCi5zoS+SSSSZ8+eEf0IIgUrCS7A8yRGrvbExMTExAShqBiGTU1NtbS0ECclz549I1R9nvSI+CBwVCf3ILkriX+RuagW8nCA0y34Ej4TvxIhMDiOj4yMQO8Q+o8s4E/D3pxTstfd2oI2AHUYjuMejwf8V5xOJ6Rogj4LCAi4ceOGy+UC1yKwNU6n0z93QOzxeJxOJ2zDQ575e/fuwWXgTI7PUYNAGi3obOD+gm72+XxutxsuhnU6aAaCIO3t7RApAOf7OI5DKjLQCZfLJZPJjEYjjUYbHR3t7+93uVw3b96ELFBwPZxNEUMRmgkJcCG8zel0gnmtra11u90MBmN2dhabS5UEKbTpdDr4sbrdboIvfWpqCs6IoAnQUmgmbY6Dx+FwMBgMk8nU2NiI4zgkVKPT6dAKZE6hIdkoiqIgCmSOjx3yjsM4JF54TqdTKpXOzs6ChYLr/X6/xWKBsUTUeXx8vKurC5mjiSMz2EOqMxhskAsYWgGVAQXwer2gEnBmRfyk1Wqbm5vhWSAi4iUEFUZR9PTp0zMzM+BuDPELIJOamhoEQerq6qRSqdfrBbUB0cEFkGkQQRCj0Xj58mXoC0JboKfAQIBzKzwd2gtiJC9cQKTgu0JIBvLtPnv2DJKQEdndEARpa2sDdwUg0QAL6/P5CHoxCOiCfGmgRdB2QjH6+/v7+/sxDCO62Ofz3bx5E0EQGEHQItBefI6OEzjlMAx7+PCh0+kEHw+QDFQYmeMDJvh+QJMhYRgxNv1+PwgElEetVkOCUPI7CRpitVrhZePxeDweT0BAgMFgAIoTBoMBDXyD5ravdSwZgiAMBqOlpaW9vX379u0NDQ15eXlKpZJOp5tMpsDAwM2bN//2t7/lcDipqamxsbF6vf7GjRuHDx+OiYnp7Ozs6enx+Xzf//73L126BKZw27ZtISEhly5d4nK5EIGGomhLS8vg4KDVat2/f39dXR2O41lZWYGBgd98801UVBQ4tA4MDHzve9+rrq4uLi6emJhwuVzbtm07e/YsnU4PCwsbGBjIzs6GKBeRSHT8+PHMzEyr1fqDH/wAGKLa2tp+/vOfoyh68+ZNn8934MABm8128eLFgICAw4cP37lzx+FwQCpxBEF+//vfQ8bCiooKcMxyu93j4+MejycjI+PkyZOxsbE6nW58fBxF0Z07d37++efx8fEKheL9998/evSoWq1+8uSJ0+ncuXOnUCiE/PzXrl0Dx0yYrN29e1coFIaGhu7fv//WrVtOpzMmJoZGo50+fToiIqKtrS07O7umpkYmk9nt9k8++SQgIKC1tVUmk/l8vvLy8s8//zwnJ0cul//0pz/t6+uTSqU4jq9du/arr77icrmZmZk2mw3H8YmJCZFIFBgYuHLlykePHv3gBz8Ah9yCgoL//u//TkhIUCgUn3zyyb1797RabWRkZG1tLYIgycnJ69atw3H86tWrVquVy+Xu27fP6/X+7//+7+rVq/1+v8FgcDqddrs9Ozs7MTHxxIkTPB6vqKgICD7u3r3rcDji4uKA18DlcrW0tHz22Wdff/31gQMHhELh/fv3NRoNg8HYsmVLb2/v8uXLk5OTnU5nVVUVhmHR0dEJCQknT55MTEwMCwt78uTJN9988/HHHxuNxp6eHrfbvWnTpgsXLtDp9KioqCNHjkxOTk5MTPzwhz+8e/eu0+nk8XgFBQUnT57kcrlZWVnd3d1JSUnT09OpqanDw8M/+9nPamtrPR6Pw+E4duwYaDhtjjqoq6urqKjol7/8ZXJyskKh+PGPfwzpmKOjo+/du4fjOPjPAo/cqlWrioqKtFrt2bNnBQLB1q1bb9++DRpSUlKCYdj169chVGflypWNjY0ej+fIkSPV1dVmszkoKGj//v0ej+fs2bMBAQFZWVnFxcVcLhc0+cmTJ+vXr3/27FlOTs6vfvWrpUuXajSaTz/9tKWlRa1W0+n0/Pz848ePh4eHj4yMJCcni8Xi1tZWk8n04YcfCgQChUIBvu3l5eUQc2w0Gvft28dkMpuamkB/7t69Ozs7y+Fw4uLiXC5XV1dXSUlJX1/fz372M6BKm56ePnToEIZhbW1tmzdvPnfuHBj3d955B+JQMjIyOjo6jEYji8Xav3//qxBsvw54rV8L8CLNzMx0Op0ymQyiP4ODg9vb248dOzY2Nga8jVu3bi0tLZ2dnT137tyWLVuABYTD4eTm5iqVSp1OFxwcnJKSsn79+s7Oztra2tLS0rfffhusrcvlunXr1oEDBwoKChobG5lM5rvvvnvz5k3wjDl69Ojg4GB2djY4/WVlZV2/fp3FYoEPFpPJLCkp2bx5c3x8/MqVK6OiotRqNTjwHzhwYHp6WqfT9fX1FRYWMhgMiHtJSkoCrx2hUPjuu+8ODw8PDw/X1NTExMTU1dXBfJPBYCxdunTPnj3Xr1/n8Xh6vV4ulysUipSUlISEhPz8fJFIdPv27e9///sIgnR2dtJotHXr1sXExAwPD8fGxkL8a0pKCofDARm2tbVptdrNmzeHhIQolUoIKPj+978/PDwMvHsxMTGPHj0KCwvLz8+HoFilUllbW3v48OGMjAwURWGEC4XCsbGx6elpGo22detWBoMxNjZ24cKFqKiowcFBcJzcv3+/SCSSSqU5OTkhISHl5eWQf72goABFUQ6HY7FYmEwmjUZbs2ZNbGzs4OBgenp6WVnZ4OAgk8k8evTo/fv3Yc4C/vDNzc1+vz8wMHDp0qXgRVRQUBAdHS0SiZqamvh8Po7j7777bm5ursFg6OzsbG1tBX4joVBYVFS0fv16p9M5PT0dExMDYb4NDQ3vv/++zWYbHBzMy8vLyclBEKS7u9tkMr333ntNTU1+vz8vLy89Pd3j8VRUVCQnJ/f09Fy+fBk8uEdHRxkMxtq1a9evX49hWFxc3LJly3Q63dTU1NGjR3t6eoCe5/Dhw0VFRW63e//+/UajsaysjMvlqlSqsbExm82WnZ3d3t5eXV199epV+AvBO5C4eePGjeHh4WNjY6mpqWvXrm1ubg4NDT148OCNGze8Xm9AQEBaWtrq1asRBImNjT18+DCYSIlEEhoa+s033yAIolAogOskNjaWyWQC5ZpCoQgODs7IyNi9e3dkZKTf7+/t7RUIBBCziyCITqe7cePG/v37o6Oj9Xo9OLTt3r3b7XaPjo5evnw5Kiqqp6fH4XAAURCLxVIqldevX9++fXtxcTEUUlVV5XQ6vV5vW1tbcHBwVlYW0B3dunXL7Xa7XK7W1tagoKAlS5a88847zc3NpaWlKIqWlZX5fL7p6emoqKjS0tKtW7fCMgL8jplMJrxpWlpakpOT4VmdnZ3vv/++TCYbGBhYXLP03fFaW1sAxJzIZLKCgoLHjx8nJSX5504DIJ8xn8+PioqyWq1CoRBWzSiKNjc3g6M4bKJBFmdsbuMVQmmRuXzVLpdrzZo18zJJE8w3kZGRIpHoypUreXl5EON09OhR8Ovm8/mRkZFQLHGwADQnQUFBTCYzISGhqanpyJEjxOsXdAhqzmAwcByH+cUPf/hDcKiAjB5wMawiCwoKli1bdv36dZPJBDsqxDkGjuNAhMNisaBpS5cuLSkpuXPnDvA+gKkyGo1KpRJofkAakALc6/UGBgZmZWV9+OGHRDoSqCpsvKxatQqdSyseFxd35MiR1NRU4LkByha/3x8fH//ee+8lJydDZ+Xk5AQGBo6MjOzduzcpKcnn8zU1NS1ZsgSbS3oCfQcEMMRuILFIh05xOp1A1kBsv65Zs6azs9NkMgUFBYFvJlzJYDCioqIglQEkes/OzobmwMq9uLj49OnT+fn5sI0AbYRVObGNiJNytkJjoacg9znsvQgEgoMHDxYWFvr9fi6XKxKJEFJWX2I7Er4RiUSwfqLT6aGhodBBTqfz7bff5vF4N27cSE9PLy8vLy8vX79+/bp160DJURSFWwhvDUJokEEctILYlUbnyHWgl1esWHH06FGogN1uZ7FYK1eubG1tValU0IkoirLZbJFIhGEYl8sFupDe3l4o1ul0cjicjo4OyHcOlQHGGhBUQkLChx9+GB0dTexTwSYJ0EwEBwcjCAIcPFu3bt24cSPIHyJ0IXnF1q1bCRqk2NjY3Nzc+/fv7927NywsbNmyZWfOnMnLy4N9G6KBMECgI5C5wxhszscWRtBf3Ob8lfAGWFsEQQoLCwUCQUlJiUAgSEtLKykpOXv2bGJiYkJCgt1uh11RFov19ttvj4+Pi8ViFEWFQqFKpYqIiFAqlVarFQJyrFZreXn506dPGxoafD6f3W5nMpnbtm378ssvr1+/vmbNGkiYsH37drvd7nA4JiYmfD6f0Whcv359REREWFgYMNG2tbVhGOZwOCYnJxEESUhI6OnpUalUsEXr8/kmJyedTqdarTYajWNjY5cvX1YqlXClRCIZHR31+/2QYYTP5+fm5lZWVgJnFIIgNBqtpaXl2rVrO3fuNBgMDoejt7fX6XQuW7YM4n2VSuU777xz5swZHMeLi4tnZ2fVarXVaoW3y8jIiMViWbp0aWhoKIIgBoMhLS2tqKjo2rVrKpUKVgkul2tsbMzhcCQnJ8fHx1dXV+t0upiYGIfDIRaLYb9706ZNv/nNb+rq6jAMg/Xa1atXxWKxw+HweDxTU1OQZGTfvn1Xr14dGBiAXbyJiQmIBh4cHDx//rzX6wVvfxiKZrMZ7vV4PEql0mg0GgyGuLi4kZGRpUuXOp3Oixcvvv3228HBwTQaLTQ0VKfTRURE6HQ6FEV5PF5hYWFSUhKHwwGeysDAwImJCULODocjKSkpNjb2ypUrwI0EdN9lZWUQgOv3+8PCwsrLy8+ePctisTIzM+12u1wuBwULDQ09d+7cqlWr0tLSmExme3u7z+dTKpVms9lisezbt+/JkydAiQiUB9BTer3eaDTC/sP58+fz8/NDQkIcDodMJgNKm6mpKbfbLZPJbDabTqcDcrPc3FzYoYLouPDwcJvN5vV6YZsYYvl0Ol1sbKxEIlmxYoXJZLp48eL27dthQZacnNzV1aVSqTweD8TRLl26lMViVVdXw7IgLi4uPz//f/7nf4AgUqfThYeHq9Vqm82mVCrh1AF4fZKSkiA3k16vFwgEmzdvrq2tHRwcRBAEQmakUikch+zevbuqqmpwcBAI7rq6uoD1Z+/evWfOnLly5Qrs1e7fvx+ODYEfhIgu27Fjx9DQEEQDzc7OqlQqOKWcmpq6devWxMREeXm53+9PTk7u7e09fvw4nK84HA6VSmU2myE+zWq1BgcHAy1IQUHBuXPnRCIRrE7eCLyp/rZ2u50gSsCfl/kfQRCHwxEUFARnaMQ1CIIABSTMWYiDLJg7wGlMcHAwPkdLAzM+8hkonEuA3hPFAtEOcQv8VavV58+fr6ioePz48VtvvZWVlQXzL5itkK90OBxgjzAM+/Wvf52SkvLOO+8Q+XFgPQUEf/BihyOC4OBg4nCfLAeXywVTJOInqDlZPhgpAgeEicxNHGC+ABNM8GpE5uabsMGCkNgHiMuIXNRdXV2dnZ2rVq1qaGiIjo72eDxAsT7v0eTK+Hw+eKjT6SSED/0CK5J5G3PYHMURQvJ1I5pJCNPv94+OjjY0NKxYsaKgoIC4DDYN52kLgiDwPTLnLEHIAf663W6Y7pHvIl9AiJGsGAsbS1SPjJdLBpvjxyOuJ7PXvKhkQkOgg2Adg5NcpuD0n8VizdMTsmaSq+RwOIB6cp58iOEDt4OnCkxFyV0DE2ToUARBLBbLiRMnYPecRqO5XK6ioqL8/Hw4LQAivoW6jZA42In+elPwplpb5NUy288zlOQb5907Tw4vKpZ82cLxtvBiYE6MiYkBWnIwVQufS3zj8/lGRkZgb+5FNX9Jk7EFHqwvl89L2jXve/x5jo0L6wNH6mNjY8BsBD4Vqampf7Qm5EE1rybPlS35roXfY3Nu1zabTS6XZ2RkEDzbyJwRhB2AeQ15+bPItZr303Pl8yK8iuoufOjCF+dLCpzXoS/v3z9ak4VWYp7oFn7zIoVB5/xwcByXy+UajSYmJiYsLGxqaio7O5tg0HlJlV5Smdccb5i1JTqSkO/CAbPwynmdAT2NkCIjFqrmq3Q2cS9x/bx7ifkjsdMET1w4VMjj4UUmhmzWXzRIyA15idaSb3/ROES+bYNecgG5+djzYsNeXlvynJf4l0bi8SQKJ9d23vfPrRVCIotceD1ZPmRzSe5QotXkMonWveTdtvDl8aJ384vs6cLmLJTqi5T/uUJ4yUj/DnZ/3nPJXUbY03nVIy8TF77tUBJPBIqiLw8Pe8W50euGN8zaAvzPyx8MrnzEOczLp5x/dNL06iAbBcLWfIdiifURoal/Zt38L6WE+ou0fWGZyJ+i+kQ/whETmRmQKJDYCCJGKT53SPjqtQJ3UfJnYno1T5GgfOhB8jkV2WoT/UucjD337UKex71EJcgtwl4QgfYd8JK3MnFQjC6Y479KsYTdJ5iAkbmoCqIfiSsR0jvpu42Lvye8GadkBBobG588efLckUYcMcG/KIq2tbWpVKrnllNXV9fW1vYX6XuUtDKCMfPdioW7KisrFQoF7dtsJX8q7Hb7//3f/7lcrucKanx8HBKEf+fyCfj9/osXL+p0OrFYLJFI/lRLQafT29ra6urqwEWksrJSq9X29fWNj4/DBSiK+v3+r7/+Gg5GkDkp/UlPgYnS4OAgeO9jGFZZWSmTyZ7bU3AgPjQ0VFlZSTajIyMjfX198Ct5RvbcQhZOmV9SYVAbo9F45swZYNB59aa9vNVisXh4ePi5bUQQZGhoqLq6+k/VNGjas2fPmpubYXMGjiukUunXX39NzHWQb5ObEQ4kf4GGvcl4ra0tPhfjCLk+EQRBUbS3txdFUcgeC9dARju9Xn/x4sXZ2VmbzWYwGCA9PmzVK5VKyOkJJ5vwSocknjAeZDKZ1+v1eDzAxAMBNn6/Xy6XQ/ySyWTS6XQYhlmtVpVK1dLSAplG7XY7VAOy9INXv1wuhwAwBEEcDgfca7fb7Xa7x+OBYCqz2azT6SDTM47jkFQffCeGhoZ0Oh0oqE6nI5oJT9FqtS6Xy2Kx6HQ6SI8NR+cQOWqxWPR6PY7jIyMjdrtdp9MRoWgWi0WpVIKDzrNnz+AbyMOE4zhk1wUXK0jL6yeRXNlsNpPJBFeC6wWCIF6vV6PRDA8P63Q6JpMJB0QqlQoCKMidqFarIYAKkrTq9Xr4SafTWSwW4GVgMpkKhQJSAgYFBSEIotFoxsbGRkdHZTLZ6OgoeFzU1tY+efIEQRCDwaDVaqFriFhSyIKKIIjVaoV0qPC90Wi02+09PT0oigYEBOh0uuHhYY1GA7ZGo9EQdVYoFHa7PSQkpLe31+v1qtVqKJxOp3O5XJvNZjabVSoVtOXcuXMQBAh3Ed00PT2t1WqdTufZs2fB+wocYxAEgQ6Cz9BrEItltVoHBwfhIA4qDFl6oSGQqZlQYPjeaDRaLBbokaGhof7+/pmZGUgICx3EYDC4XO7s7CxRZxhNTU1NjY2NwcHBfX19arUa3LncbrdCocBIUbAqlQoaRYw1aL7JZIJ+tNvtCoUCmhAaGtrV1UXIweFwKJVKGo2mUqkqKyutVuulS5dkMhkIB5ICm0ymmZkZs9ms1+tdLpfZbLbZbH+SfXjj8LrHYKAoajabq6urw8LC2trakpOT2Wy2WCzu7++32+2lpaV9fX1gLtevX//o0aP169d//fXXDAYjNDTUarW+8847jx8/Bi+xnTt3Pn361OPxbNiwgcfjwRGqz+erqqpis9kPHjwoLy//zW9+s3HjxsHBwX/+53++efMmh8N58OBBWVnZ73//+7i4uLS0NJPJBFwDnZ2dCQkJ0dHR4+Pjhw8f1mq1jx49euutt+7fv0+n0zUazaFDhyIiIrq7u2/evBkeHp6VlSWVSg8fPvzrX//6F7/4xb//+7+XlJQMDg5+8sknsbGxZrP53r17q1evDgoKGhsba2tr27dvH7wSLBbLypUrc3NzJRJJQ0NDSEhISkrKtWvXli1bJpVK9+/fPzAw4HK5pqenf/KTn/znf/5nRERETExMRESEVqv95ptvjh07FhwcPDg4eObMGciH/9FHH3G5XKlUWl1d/dlnn/3qV7/67LPPbty4ER8f39TUtGvXrr6+PjabnZ+fv2TJEuiF27dvDw0N8Xg8oIFSq9U/+tGPTpw4IRKJTCZTQEBAQ0NDTk4OWF6r1bpx48aMjAy498GDBzqdDqr3u9/9Li4uTqFQ7N+/32q1Pn78mMfjEdNVLpdLo9Hq6uqWL18uFotnZ2e7u7t3794dEBAgFotv3br1ySefNDU1xcTE8Hi8zs7O4ODg7Ozstra2Q4cOhYWFAZ2SVqv96KOPLl++DFGqQCVQVVWVkJBAmBIQiEQiWbZsGZfL7e3tNZlMH3/88aNHj5xO5/j4+AcffABUcuBCT6PRWltbo6OjxWLxs2fPhEKhQCAoLCx8+PAhRExhGKbT6fbu3RsdHd3W1jYwMBAQEJCTk1NbW5uTk9Pb22u322dmZrZt23bu3DkWixUWFhYVFeXz+TQaza5du7766qusrCwigBjSkOM4npWVJZFILBYLNAQS1yIIkp2d3dfXp9VqQ0JCQkNDw8LCGhsb33rrrdOnT//bv/3b+fPnIcakvr4+Pz+/r6+vvb0d6nzw4EEcx58+fcpiseCJjx8/lslkP/7xj6uqqvh8fk1NzbFjx1AUrays9Pv9k5OTO3bs6OrqslqtBw4cePr06eDgIIvF+uCDDwIDA48fP56amkqj0bZv3x4YGOjxeDo6OiQSyfvvv3/79m0mkykQCMLDw588ebJ8+fKHDx8mJSUplUqFQmE0Gjds2HDhwgVgCZFKpZ9++mlTU1Nubm5BQcHiG5lFw2s9t0UQBEVRiUTS29vLZrNlMpnH46HT6Xfu3IFcATDAjhw5snv37ujo6CVLlsTHx/N4vLKysmPHjnG5XJ1O19nZeejQoT179kREREC+94mJCcJbxWQyPXr0iMPh6HQ6CMPdu3cvhmGTk5OQVRp4bvh8/meffSYSiZxOZ2RkZFxc3JYtW+Ryud1uX7duHYIgQqFw6dKlPB6vu7t73759XC736dOnCIJERUVFR0f//Oc/B96E8PBwOp0eFBQkEAgqKiri4+PBc5PP52dlZWVkZOA4vmbNmrKyMolEcv36dQjSn5ychEnZ2NgYhmEQplVRUfHWW2/V19enp6eLRKLx8XEajSYQCLZv3757926z2QzuNUC0JxQK4+Li9u/f73a7pVIpiqIRERE4jvP5fDabDbYgNjY2IiICGFzodDp47wOEQmFqauqnn36anp4eExOjVCrHxsZmZmYOHjyYkJBAo9HCw8MhTOvQoUPp6elkilbIXQ0z4oiIiJKSktLS0vHx8bq6ugMHDqxfv57YOcVxPCAgQCgUulwuiMoDEiAGg7F169acnJzJyUkgyOHxeENDQyiKJiUl/ehHPwK2pOjo6KSkpJmZmZmZGaFQuGTJkoqKirGxsadPn65fv37btm0wZQalKisrO3z4cENDQ1RUVGpqqsVigaQE77777oEDB1gslkKhuHLlyve+9z1wkBIKhbOzs3Dxvn37pqamwFE6Kiqqubn54MGD0dHRjx8/hm4aGRkJDg7OzMxMT09PTU0FsSQkJACV1qZNm7Zv3w6x1FartbGxMTQ0dN++fdAjCIJ88803ZrOZxWKNj49HRkZmZ2fv2LFjbGzs3r17JpOJyWROTExERUUVFBR89NFHSqUyJiZGIBCUlpZGRUUNDQ2lpqYSnQ70jgkJCUeOHIH0RiC0goKCwMBAPp9/6NAht9sNFpnNZqtUKlh4gSj2798PXe9wOBQKhUgkSktL+/nPfx4ZGQlzDpVKlZWVBX0XGhq6d+/eyMhIsVgM7t5isTguLi4nJyc9PT05ObmoqOj27duQ2kKv1wuFwoqKio8//jgvL29wcJDH4+Xm5v51rcnfGq+1tQXlCwoKYrPZBQUFEC/vcDh4PB6fz6+oqNi4cSOss0JCQiD8HBxmcRxnsVjgdgoziPDw8O7u7qGhoaCgII/HQ3B6BwQEgKP7oUOHuFwuOe8Jh8NZsmQJfA+On6mpqSaTyWKxbNy4MSUlRaVSTU5OikQi2F4kkoAA/W1YWBiCIPAgiN2yWq0WiwX82CHLBnxAEATDMMjlATMyqAaPxwsLC9u2bVtJSQmc5xw4cGBychL2QGw2m0Kh4HA4165dg5cHtJ1GowUHBzscjvLy8hs3bkAuFdisgK2PgIAASENjt9thSRgSEgL+6vv27WMwGIcOHRofH+/p6QE2GgRBIMdKUFDQlStXwOUWBDs7O2s0GqHCOI5zuVzYw+HxeFNTU7AXcfnyZQRBwFmdyNXidrs5HA4s4WHtiSAIeNGDBCDJQFFRUVxcnNPphIALEJfNZqPT6QcPHhwdHR0YGAADgaLow4cPzWYz8SBIxeJ2u9lstlarBcmDRnk8HqPROD09HRIScvPmTch9g6Koz+eTy+V8Ph/EWFBQAJSFIAHIxQN516Bwh8MBeyAmk8lms0GPQxaC7u7usbExiLXjcDiQ+yY0NBRuhEzqycnJBw4cSE9PNxgMs7OzxJYIn8/n8Xjr168HijlIUuNyuXg8XmhoaHl5+caNG51Op8fjCQoKyszMfPz4MSzX1q1bd/r06ZycHFgugEaBUy3oGz6XkQtGCkgbPGc5HE5BQcH+/fsDAgKYTKbP51OpVAKB4NGjRzKZDIYGlAbhxX6/v6KiIiQkhGAgh70yiHmpqanhcrnQ1w6HA5tLtMRmsyMiInbs2LFkyRLY3AOajGvXrkVFRRGbP9ibk9brT8JrbW1hg3XJkiWFhYVVVVWgeUwmc+/evQqF4tGjR0Kh8NChQ5WVlZAiQCQSSSQSPp9vMBhgmHm93iNHjly+fLm3t3fJkiUMBkMgENBoNJvNBsGRoaGhBw4cqKyshDiriIgIuVwuEAgCAgIOHTpUVVUFu1dAmaPT6Twej0aj+e1vf+vz+YqLi1NSUuCUTCAQxMTEqNXqQ4cOXb16NTY2tri4GAYkkNbFxMRkZ2ffvXs3IyNDqVSGhYXpdDoulwtjICgoKDc3t729HTYHwb/i4MGDExMTdXV1ML2CrFqZmZk5OTl+v7+2ttZgMOzYsaOgoEChUBQWFkqlUoFAAJYlLi4uNzdXIBDAHBDeAVVVVRCwD5PB0tLSmzdvJicnK5VKGCqff/755OSkXC7PysqKjY09fvy4fy6DIoqiHo9n7dq1Uql0yZIlAQEBGzZsuHz5clxcnMVigV3mQ4cOPXz4ECL9v/zySzDBq1atUigUeXl5CoUiJCQEthpxHN+zZ09XV9f4+HhERAQYMg6HY7VaIffY1NQUjUZ7/PjxhQsXIiIiZmZmIJcVpCUCEi1gajl+/DiUWVRUpNfrs7Oz9Xo9ON5brVYmk7lu3Tq9Xt/W1paQkABUNKWlpVartaGh4eDBgytWrNBqtcA49+677169erW/v9/pdKamphYXF8MuNo7jEJkNMfs6nY7P58MkcXR09NixYzdv3uTz+WVlZfDSnZycLCwsTElJgd2Vd9999+7du5AgJjg42GAwBAYGHj169MaNG6Ojo9nZ2dnZ2dXV1bBPhWHYrl273G73gwcPwA7CZlpgYODWrVudTufdu3fB28Rut3u9Xp1Oh+P4zZs3GxoaIDUSkDlC9AekVWMymdPT0wKBABJp5ubmQpQdEPDw+XyhULhu3bpLly5Bli82m3348OHLly+LxeKSkhKgT3U4HPCyhKxmGIYpFIrAwMANGzbgOA4posBowqJtdnY2Li6OxWLxeDyZTLZ8+fLu7u733ntvYGCgpaUFzg8MBgOGYcBzmp2dPTIyMjQ09CZ6Sb0iXmsPMDglo83l6yQvOdEFrp3z4r4gCIf4CZ0L1CEfjMJUAnIREMepRPQOlAYjDSLH6uvrp6amUlJSpFKpz+fj8XiwPiVKhgdBHbxeLyQkhEkTMpd/gKgqtAjHcRgY8+J2EJK7Lgx1wvnB7Xb/67/+6759+0pKSsiZ7ogCF/7b3d197dq1f/mXfyFiqMjPUigUkN5scHAQtlwQBLFarTqdLiUlBcohCgT5kP8SFSYcgGw2m0ajgaAGol0ejwcC8IlOROaO9cGgk389ceJEUlKSzWYLDw9ft24d4UU0TzgQSZGRkUH0LFmwZDkQD8VJfrUI6aCcuIy4hmgjbHGQuwOSPRJ/8bm4L6KXiag8ckQW5JSZp2PzQrZ8Ph+oDbmxC7sM6ux0Or/88su8vDy1Wh0UFDQ5Oblp06YlS5bAwCEH4MFdkJKC7Dkwrw6EjpEd48jXICTHL6IJhH7OayahuoTXHdmdA53jWj116tTKlStXrVpFOKcjC1y2/z7wWltb5NuGFf22bz9C8gci+5mjL3DkxkkO2AhJlYnPZP9E8vAmikVRdHp62uPxiEQiSKIK0cMLKzyvQPKzCA9H8o2EZSfqSS6QaCkxqi0WS0BAAI/Hm1c4GeTBOTs763K5QkJCCItGFAsXwA6JUCgErnhkTt0J+S+sMxkLfyJ3FjGGEZJ1I0Yv+m0XOoDH41Gr1cHBwUKhkOj9eYGtRKeQhYzOOcnD5+dWCSHZ+oWim6cYCElz5jVq3l3EU55bMhg7FEUXBm7MkyH56WTpzXOugja6XC6tVgubDEajUSAQzLPRC1s3TxTIt3XsRVJaeONzyyePVrJY5rmakdtlNBpDQ0P/TMqJNwKvu7WlQIEChb8P/B1O1ylQoEDhNQRlbSlQoEBhMUBZWwoUKFBYDFDWlgIFChQWA5S1pUCBAoXFAGVtKVCgQGExQFlbChQoUFgMUNaWAgUKFBYDlLWlQIEChcUAZW0pUKBAYTFAWVsKFChQWAxQ1pYCBQoUFgOUtaVAgQKFxQBlbSlQoEBhMUBZWwoUKFBYDFDWlgIFChQWA5S1pUCBAoXFAGVtKVCgQGExQFlbChQoUFgMUNaWAgUKFBYDlLWlQIEChcUAZW0pUKBAYTFAWVsKFChQWAxQ1pYCBQoUFgOUtaVAgQKFxQBlbSlQoEBhMUBZWwoUKFBYDFDWlgIFChQWA5S1pUCBAoXFAGVtKVCgQGExQFlbChQoUFgMUNaWAgUKFBYDlLWlQIEChcUAZW0pUKBAYTFAWVsKFChQWAxQ1pYCBQoUFgOUtaVAgQKFxQBlbSlQoEBhMUBZWwoUKFBYDFDWlgIFChQWA5S1pUCBAoXFAGVtKVCgQGExQFlbChQoUFgMUNaWAgUKFBYDlLWlQIEChcUAZW0pUKBAYTHw/8PVVuR575lVAAAAAElFTkSuQmCC\n", - "text/plain": [ - "" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "img = PIL.Image.open(f\"output/images-{first}.jpg\")\n", - "img.thumbnail([600, 600])\n", - "img" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Qi6KAePlfMl4" - }, - "source": [ - "Extract the text for thopse same pages." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "id": "zgqvbl0K2RKA" - }, - "outputs": [], - "source": [ - "for page_number in range(first,last+1):\n", - " page_number = f\"{page_number:03d}\"\n", - " ! pdftotext test.pdf -f {page_number} -l {page_number}\n", - " ! mv test.txt output/text-{page_number}.txt" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": { - "id": "Pfdv5rdG2ltK" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "images-121.jpg\timages-133.jpg\timages-145.jpg\ttext-123.txt text-135.txt text-147.txt\n", - "images-122.jpg\timages-134.jpg\timages-146.jpg\ttext-124.txt text-136.txt text-148.txt\n", - "images-123.jpg\timages-135.jpg\timages-147.jpg\ttext-125.txt text-137.txt text-149.txt\n", - "images-124.jpg\timages-136.jpg\timages-148.jpg\ttext-126.txt text-138.txt text-150.txt\n", - "images-125.jpg\timages-137.jpg\timages-149.jpg\ttext-127.txt text-139.txt text-151.txt\n", - "images-126.jpg\timages-138.jpg\timages-150.jpg\ttext-128.txt text-140.txt text-152.txt\n", - "images-127.jpg\timages-139.jpg\timages-151.jpg\ttext-129.txt text-141.txt text-153.txt\n", - "images-128.jpg\timages-140.jpg\timages-152.jpg\ttext-130.txt text-142.txt text-154.txt\n", - "images-129.jpg\timages-141.jpg\timages-153.jpg\ttext-131.txt text-143.txt\n", - "images-130.jpg\timages-142.jpg\timages-154.jpg\ttext-132.txt text-144.txt\n", - "images-131.jpg\timages-143.jpg\ttext-121.txt\ttext-133.txt text-145.txt\n", - "images-132.jpg\timages-144.jpg\ttext-122.txt\ttext-134.txt text-146.txt\n" - ] - } - ], - "source": [ - "!ls output" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": { - "id": "wG5tecfk84VP" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHAPTER 3\n", - "\n", - "The First Law of\n", - "Thermodynamics\n", - "\n", - "Figure 3.1 A weak cold front of air pushes all the smog in northeastern China into a giant smog blanket over the\n", - "Yellow Sea, as captured by NASA’s Terra satellite in 2012. To understand changes in weather and climate, such as\n", - "the event shown here, you need a thorough knowledge of thermodynamics. (credit: modification of work by NASA)\n", - "\n", - "Chapter Outline\n", - "3.1 Thermodynamic Systems\n", - "3.2 Work, Heat, and Internal Energy\n", - "3.3 First Law of Thermodynamics\n", - "3.4 Thermodynamic Processes\n", - "3.5 Heat Capacities of an Ideal Gas\n", - "3.6 Adiabatic Processes for an Ideal Gas\n", - "\n", - "INTRODUCTION Heat is the transfer of energy due to a temperature difference between two systems. Heat\n", - "describes the process of converting from one form of energy into another. A car engine, for example, burns\n", - "gasoline. Heat is produced when the burned fuel is chemically transformed into mostly\n", - "and\n", - "which\n", - "are gases at the combustion temperature. These gases exert a force on a piston through a displacement, doing\n", - "work and converting the piston’s kinetic energy into a variety of other formsβ€”into the car’s kinetic energy; into\n", - "electrical energy to run the spark plugs, radio, and lights; and back into stored energy in the car’s battery.\n", - "\n", - "\f" - ] - } - ], - "source": [ - "!cat output/text-{first}.txt" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "D5bZ_n0MfV_a" - }, - "source": [ - "## Assemble the files into a prompt" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3DnTs6-cfl43" - }, - "source": [ - "Upload all the files usng the files API, there are too many to send with the `generate_content` request." - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": { - "id": "LoR60ncl8-Zn" - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 34/34 [00:33<00:00, 1.00it/s]\n" - ] - } - ], - "source": [ - "files = []\n", - "image_files = list(pathlib.Path(\"output\").glob('images-*.jpg'))\n", - "for img in tqdm.tqdm(image_files):\n", - " files.append(genai.upload_file(img))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "l_0xCJbNfsYa" - }, - "source": [ - "Load all the texts:" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": { - "id": "fGx1ERx9Omz7" - }, - "outputs": [], - "source": [ - "texts = [t.read_text() for t in pathlib.Path(\"output\").glob('text-*.txt')]" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "_CzHvWTpfvKI" - }, - "source": [ - "Interleave the page-numbers, texts, and image-file references:" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "id": "sxpikEYcQnZG" - }, - "outputs": [], - "source": [ - "textbook = []\n", - "for page, (text, image) in enumerate(zip(texts, files)):\n", - " textbook.append(f'## Page {first+page} ##')\n", - " textbook.append(text)\n", - " textbook.append(image)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yXFZFUJHgTcU" - }, - "source": [ - "## Try it out" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": { - "id": "EzinQ3_OSXvH" - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel(model_name='gemini-1.5-pro-latest')" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": { - "id": "AwigO15oZV_m" - }, - "outputs": [], - "source": [ - "response = model.generate_content(\n", - " ['# Here is a chapter from a physics text book:']+\n", - " textbook +\n", - " [\"[END]\\n\\nPlease sumarize it\"]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": { - "id": "y30mNfmbTanQ" - }, - "outputs": [ - { - "data": { - "text/markdown": [ - "## Summary of Pages 121-154 of a Physics Textbook\n", - "\n", - "These pages discuss the First Law of Thermodynamics and its application to various thermodynamic processes, particularly for ideal gases.\n", - "\n", - "**Key Concepts:**\n", - "\n", - "* **Thermodynamic Systems:** Defining the system, its surroundings, and boundaries is crucial before analysis. Systems can be open (exchanging energy and matter), closed (exchanging only energy), or isolated (no exchange). Thermal equilibrium implies equal temperatures across a system and its surroundings. \n", - "* **Work, Heat, and Internal Energy:**\n", - " * **Work:** Done by a system during volume changes against external pressure. Positive for expansion, negative for compression.\n", - " * **Heat:** Energy transfer due to temperature differences. Positive when absorbed, negative when released.\n", - " * **Internal Energy:** Sum of all microscopic kinetic and potential energies within the system.\n", - "* **First Law of Thermodynamics:** Change in internal energy equals heat added minus work done by the system. It's a statement of energy conservation.\n", - "* **Thermodynamic Processes:** How a system changes from one state to another. \n", - " * **Quasi-static:** Infinitesimally slow, maintaining equilibrium throughout. Allows for theoretical analysis using equations of state.\n", - " * **Non-quasi-static:** Any process occurring at a finite speed, as in reality.\n", - " * **Types of Processes:**\n", - " * **Isothermal:** Constant temperature.\n", - " * **Adiabatic:** No heat exchange.\n", - " * **Isobaric:** Constant pressure.\n", - " * **Isochoric:** Constant volume.\n", - "* **Heat Capacities of an Ideal Gas:** Relates heat added to temperature change. Different for constant pressure (Cp) and constant volume (Cv) processes.\n", - "* **Adiabatic Processes for an Ideal Gas:** No heat exchange. Pressure and volume related by: PV^Ξ³ = constant, where Ξ³ is the ratio of specific heats (Cp/Cv).\n", - "\n", - "**Additional Points:**\n", - "\n", - "* Ideal gas law is used to simplify calculations.\n", - "* Real gases deviate slightly from ideal behavior, affecting heat capacities.\n", - "* pV diagrams visualize processes and calculate work done as the area under the curve.\n", - "\n", - "**Examples:**\n", - "\n", - "* Isothermal expansion of ideal and van der Waals gases.\n", - "* Calculations of work, heat, and internal energy changes in various processes.\n", - "* Adiabatic compression in an automobile engine.\n", - "\n", - "**Equations:**\n", - "\n", - "* Ideal gas law: PV = nRT\n", - "* Work done by a gas: W = ∫PdV\n", - "* First law of thermodynamics: Ξ”U = Q - W\n", - "* Relationship between Cp and Cv: Cp = Cv + R\n", - "* Adiabatic process: PV^Ξ³ = constant \n", - "\n", - "The provided text delves deep into the fundamental principles governing thermodynamic systems and processes, offering both theoretical understanding and practical applications. \n" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from IPython.display import Markdown\n", - "Markdown(response.text)" - ] - } - ], - "metadata": { - "colab": { - "name": "PDF_Files.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dfsDR_omdNea" + }, + "source": [ + "# Gemini API - read a PDF\n", + "\n", + "This notebook demonstrates how you can convert a PDF file so that it can be read by the Gemini API.\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FaqZItBdeokU" + }, + "source": [ + "## Setup" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "XKJ78ne3O0sB" + }, + "outputs": [], + "source": [ + "!pip install -Uq google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "LUKlAk7iN_5e" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai\n", + "\n", + "\n", + "import pathlib\n", + "import tqdm\n", + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "A9sUQ4WrP-Yr" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "genai.configure(api_key=userdata.get(\"GOOGLE_API_KEY\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "thYL8XGjerMa" + }, + "source": [ + "Install the PDF processing tools:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "iK30_utL1DhY", + "tags": [] + }, + "outputs": [], + "source": [ + "!apt install poppler-utils" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "jZj7pRt7exwE" + }, + "source": [ + "## Download and proces the PDF" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "WibRLdf2_Qoq" + }, + "source": [ + "This textbook is from OpenStax, it's License is Commons Attribution License v4.0. More detrails are [available on the site](https://openstax.org/details/books/university-physics-volume-2)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "fOYiHxN95iVn", + "tags": [] + }, + "outputs": [], + "source": [ + "import pathlib" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "xo8VsYaY6mgl", + "tags": [] + }, + "outputs": [], + "source": [ + "if not pathlib.Path('test.pdf').exists():\n", + " !curl -o test.pdf https://assets.openstax.org/oscms-prodcms/media/documents/UniversityPhysicsVolume2-WEB_5eNhMSa.pdf" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3V-NRhife2CA" + }, + "source": [ + "You'll extract Chapter 3, pages [121-154]." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "c6LD6PlpK3n8", + "tags": [] + }, + "outputs": [], + "source": [ + "first = 121\n", + "last = 154" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "fH4WmrY_1MdQ", + "tags": [] + }, + "outputs": [], + "source": [ + "!mkdir output\n", + "! # extract images of Chapter 3\n", + "!pdftoppm test.pdf -f {first} -l {last} output/images -jpeg\n", + "!ls output" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "hmIj4eQlfFot" + }, + "source": [ + "Look at the first image, scaled down:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "JGOg-cvK11IC", + "tags": [] + }, + "outputs": [], + "source": [ + "import PIL.Image" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9b0MfUwc17Mk", + "tags": [] + }, + "outputs": [], + "source": [ + "img = PIL.Image.open(f\"output/images-{first}.jpg\")\n", + "img.thumbnail([600, 600])\n", + "img" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Qi6KAePlfMl4" + }, + "source": [ + "Extract the text for those same pages." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "zgqvbl0K2RKA", + "tags": [] + }, + "outputs": [], + "source": [ + "for page_number in range(first,last+1):\n", + " page_number = f\"{page_number:03d}\"\n", + " ! pdftotext test.pdf -f {page_number} -l {page_number}\n", + " ! mv test.txt output/text-{page_number}.txt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Pfdv5rdG2ltK", + "tags": [] + }, + "outputs": [], + "source": [ + "!ls output" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "wG5tecfk84VP", + "tags": [] + }, + "outputs": [], + "source": [ + "!cat output/text-{first}.txt" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "D5bZ_n0MfV_a" + }, + "source": [ + "## Assemble the files into a prompt" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3DnTs6-cfl43" + }, + "source": [ + "Upload all the files usng the files API, there are too many to send with the `generate_content` request." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "LoR60ncl8-Zn", + "tags": [] + }, + "outputs": [], + "source": [ + "files = []\n", + "image_files = list(pathlib.Path(\"output\").glob('images-*.jpg'))\n", + "for img in tqdm.tqdm(image_files):\n", + " files.append(genai.upload_file(img))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "l_0xCJbNfsYa" + }, + "source": [ + "Load all the texts:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "fGx1ERx9Omz7", + "tags": [] + }, + "outputs": [], + "source": [ + "texts = [t.read_text() for t in pathlib.Path(\"output\").glob('text-*.txt')]" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "_CzHvWTpfvKI" + }, + "source": [ + "Interleave the page-numbers, texts, and image-file references:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "sxpikEYcQnZG", + "tags": [] + }, + "outputs": [], + "source": [ + "textbook = []\n", + "for page, (text, image) in enumerate(zip(texts, files)):\n", + " textbook.append(f'## Page {first+page} ##')\n", + " textbook.append(text)\n", + " textbook.append(image)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yXFZFUJHgTcU" + }, + "source": [ + "## Try it out" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel(model_name='gemini-1.5-flash-latest')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "response = model.generate_content(\n", + " ['# Here is a chapter from a physics text book:']+\n", + " textbook +\n", + " [\"[END]\\n\\nPlease sumarize it in sections for a better understanding\"]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "from IPython.display import Markdown\n", + "Markdown(response.text)" + ] + } + ], + "metadata": { + "colab": { + "name": "PDF_Files.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/Prompting.ipynb b/quickstarts/Prompting.ipynb index efd1d1871..832045bad 100644 --- a/quickstarts/Prompting.ipynb +++ b/quickstarts/Prompting.ipynb @@ -1,514 +1,428 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: Prompting Quickstart\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dpOYALec6N8Z" - }, - "source": [ - "This notebook contains examples of how to write and run your first prompts with the Gemini API." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "id": "0c13de5f68f6" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[?25l \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/137.4 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r", - "\u001b[2K \u001b[91m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91mβ•Έ\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m61.4/137.4 kB\u001b[0m \u001b[31m1.7 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r", - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m137.4/137.4 kB\u001b[0m \u001b[31m2.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", - "\u001b[?25h" - ] - } - ], - "source": [ - "!pip install -U -q google-generativeai # Install the Python SDK" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "id": "TS9l5igubpHO" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "w4YDYyfRYN7L" - }, - "source": [ - "## Set up your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "id": "p8K1RpmMfh20" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "HTNQymX8YN9c" - }, - "source": [ - "## Run your first prompt\n", - "\n", - "Use the `generate_content` method to generate responses to your prompts. You can pass text directly to generate_content, and use the `.text` property to get the text content of the response." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "id": "XSuyaGmcf6sr" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "```python\n", - "# Create a list of unsorted numbers\n", - "unsorted_list = [5, 2, 9, 1, 7]\n", - "\n", - "# Sort the list in ascending order\n", - "sorted_list = sorted(unsorted_list)\n", - "\n", - "# Print the sorted list\n", - "print(sorted_list)\n", - "```\n" - ] - } - ], - "source": [ - "model = genai.GenerativeModel('gemini-pro')\n", - "response = model.generate_content(\"Give me python code to sort a list\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0GTyrWHugKFi" - }, - "source": [ - "## Use images in your prompt\n", - "\n", - "Here we download an image from a URL and pass that image in our prompt.\n", - "\n", - "First, we download the image and load it with PIL:" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "id": "JgbFtil0gLNf" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " % Total % Received % Xferd Average Speed Time Time Time Current\n", - " Dload Upload Total Spent Left Speed\n", - "100 349k 100 349k 0 0 1087k 0 --:--:-- --:--:-- --:--:-- 1087k\n" - ] - } - ], - "source": [ - "!curl -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\"" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "id": "0rcYDbcDga8s" - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import PIL.Image\n", - "img = PIL.Image.open('image.jpg')\n", - "img" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "id": "UTgRAmEHOaAz" - }, - "outputs": [], - "source": [ - "prompt = \"\"\"This image contains a sketch of a potential product along with some notes.\n", - "Given the product sketch, describe the product as thoroughly as possible based on what you\n", - "see in the image, making sure to note all of the product features. Return output in json format:\n", - "{description: description, features: [feature1, feature2, feature3, etc]}\"\"\"" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "RJyRsfQi0tp6" - }, - "source": [ - "Then we can include the image in our prompt by just passing a list of items to `generate_content`. Note that you will need to use the `gemini-pro-vision` model if your prompt contains images." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "id": "Aoil5YiTgbZS" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " {\n", - " \"description\": \"The Jetpack Backpack is a lightweight, steam-powered backpack that looks like a normal backpack but has retractable boosters that can be used to fly. It has a 15-minute battery life and a USB-C charging port. The backpack also has padded shoulder straps for added comfort.\",\n", - " \"features\": [\n", - " \"fits 18\\\" laptop\",\n", - " \"lightweight\",\n", - " \"looks like a normal backpack\",\n", - " \"retractable boosters\",\n", - " \"15-minute battery life\",\n", - " \"USB-C charging\",\n", - " \"padded shoulder straps\",\n", - " \"steam-powered\",\n", - " \"green/clean\"\n", - " ]\n", - "}\n" - ] - } - ], - "source": [ - "model = genai.GenerativeModel('gemini-pro-vision')\n", - "response = model.generate_content([prompt, img])\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "XE-6e7gePN7Q" - }, - "source": [ - "## Have a chat\n", - "\n", - "The Gemini API enables you to have freeform conversations across multiple turns.\n", - "\n", - "The [ChatSession](https://ai.google.dev/api/python/google/generativeai/ChatSession) class will store the conversation history for multi-turn interactions." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "id": "ZKAtY5oIPQW0" - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel('gemini-pro')\n", - "chat = model.start_chat(history=[])" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "id": "9tXNVnqxPcXy" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "A computer is like a smart helper that can store information, do math problems, and follow our instructions to make things happen.\n" - ] - } - ], - "source": [ - "response = chat.send_message(\"In one sentence, explain how a computer works to a young child.\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "7TChH2l5PhFf" - }, - "source": [ - "You can see the chat history:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "id": "dHwrC82YPiWS" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[parts {\n", - " text: \"In one sentence, explain how a computer works to a young child.\"\n", - "}\n", - "role: \"user\"\n", - ", parts {\n", - " text: \"A computer is like a smart helper that can store information, do math problems, and follow our instructions to make things happen.\"\n", - "}\n", - "role: \"model\"\n", - "]\n" - ] - } - ], - "source": [ - "print(chat.history)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "EvHvt1OEPl7D" - }, - "source": [ - "You can keep sending messages to continue the conversation:" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "id": "-fXZZQPzPkie" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "A computer is an electronic device that can be programmed to carry out a set of instructions. It consists of hardware, which are the physical components, and software, which are the instructions that tell the hardware what to do. The hardware includes the central processing unit (CPU), which is the \"brain\" of the computer and controls all of its operations; memory, which stores data and instructions; and input and output devices, such as the keyboard, mouse, and monitor. The software includes the operating system, which manages the hardware and provides basic services, and applications, which are programs that perform specific tasks, such as word processing or playing games.\n", - "\n", - "When you give a computer a command, the CPU fetches the corresponding instructions from memory and executes them. The results of the instructions are then stored in memory or sent to an output device. Computers can perform a wide variety of tasks, from simple arithmetic to complex scientific simulations, because they can be programmed to follow any set of instructions.\n" - ] - } - ], - "source": [ - "response = chat.send_message(\"Okay, how about a more detailed explanation to a high schooler?\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "65476e75ece0" - }, - "source": [ - "## Set the temperature" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "56f68c900144" - }, - "source": [ - "Every prompt you send to the model includes parameters that control how the model generates responses. Use a `genai.GenerationConfig` to set these, or omit it to use the defaults.\n", - "\n", - "Temperature controls the degree of randomness in token selection. Use higher values for more creative responses, and lower values for more deterministic responses.\n", - "\n", - "You can set the `generation_config` when creating the model." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": { - "id": "28477e706226" - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel(\n", - " 'gemini-pro',\n", - " generation_config=genai.GenerationConfig(\n", - " max_output_tokens=2000,\n", - " temperature=0.9,\n", - " ))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "e3c68071ed8b" - }, - "source": [ - "Or, set the `generation_config` on an individual call to `generate_content`. Any values set there override values on the model constructor.\n", - "\n", - "Note: Although you can set the `candidate_count` in the generation_config, gemini-pro models will only return a single candidate at the this time." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": { - "id": "f895c7f55b30" - }, - "outputs": [], - "source": [ - "response = model.generate_content(\n", - " 'Give me a numbered list of cat facts.',\n", - " # Limit to 5 facts.\n", - " generation_config = genai.GenerationConfig(stop_sequences=['\\n6'])\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "id": "c97c16e6a961" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1. Cats spend about 70% of their lives sleeping.\n", - "2. Cats have 32 muscles in their ears, which allows them to rotate their ears 180 degrees.\n", - "3. A cat's nose is unique, just like a human fingerprint.\n", - "4. Cats can jump up to six times their height.\n", - "5. The average lifespan of an indoor cat is 12-15 years.\n" - ] - } - ], - "source": [ - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "gvkDhXtHgol7" - }, - "source": [ - "## Learn more\n", - "\n", - "There's lots more to learn!\n", - "\n", - "* For more fun prompts, check out [Market a Jetpack](https://github.com/google-gemini/cookbook/blob/main/examples/Market_a_Jet_Backpack.ipynb).\n", - "* Check out the [safety quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Safety.ipynb) next to learn about the Gemini API's configurable safety settings, and what to do if your prompt is blocked.\n", - "* For lots more details on using the Python SDK, check out this [detailed quickstart](https://ai.google.dev/tutorials/python_quickstart)." - ] - } - ], - "metadata": { - "colab": { - "name": "Prompting.ipynb", - "toc_visible": true - }, - "google": { - "image_path": "/static/site-assets/images/docs/logo-python.svg", - "keywords": [ - "examples", - "gemini", - "beginner", - "googleai", - "quickstart", - "python", - "text", - "chat", - "vision", - "embed" - ] - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: Prompting Quickstart\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dpOYALec6N8Z" + }, + "source": [ + "This notebook contains examples of how to write and run your first prompts with the Gemini API." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "0c13de5f68f6" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai # Install the Python SDK" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TS9l5igubpHO" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "w4YDYyfRYN7L" + }, + "source": [ + "## Set up your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "p8K1RpmMfh20" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HTNQymX8YN9c" + }, + "source": [ + "## Run your first prompt\n", + "\n", + "Use the `generate_content` method to generate responses to your prompts. You can pass text directly to generate_content, and use the `.text` property to get the text content of the response." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "XSuyaGmcf6sr", + "tags": [] + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", + "response = model.generate_content(\"Give me python code to sort a list\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0GTyrWHugKFi" + }, + "source": [ + "## Use images in your prompt\n", + "\n", + "Here we download an image from a URL and pass that image in our prompt.\n", + "\n", + "First, we download the image and load it with PIL:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "JgbFtil0gLNf", + "tags": [] + }, + "outputs": [], + "source": [ + "!curl -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "0rcYDbcDga8s", + "tags": [] + }, + "outputs": [], + "source": [ + "import PIL.Image\n", + "img = PIL.Image.open('image.jpg')\n", + "img" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "UTgRAmEHOaAz", + "tags": [] + }, + "outputs": [], + "source": [ + "prompt = \"\"\"This image contains a sketch of a potential product along with some notes.\n", + "Given the product sketch, describe the product as thoroughly as possible based on what you\n", + "see in the image, making sure to note all of the product features. Return output in json format:\n", + "{description: description, features: [feature1, feature2, feature3, etc]}\"\"\"" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "RJyRsfQi0tp6" + }, + "source": [ + "Then we can include the image in our prompt by just passing a list of items to `generate_content`. Note that you will need to use the `gemini-pro-vision` model if your prompt contains images." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Aoil5YiTgbZS", + "tags": [] + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", + "response = model.generate_content([prompt, img])\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "XE-6e7gePN7Q" + }, + "source": [ + "## Have a chat\n", + "\n", + "The Gemini API enables you to have freeform conversations across multiple turns.\n", + "\n", + "The [ChatSession](https://ai.google.dev/api/python/google/generativeai/ChatSession) class will store the conversation history for multi-turn interactions." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ZKAtY5oIPQW0", + "tags": [] + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", + "chat = model.start_chat(history=[])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9tXNVnqxPcXy", + "tags": [] + }, + "outputs": [], + "source": [ + "response = chat.send_message(\"In one sentence, explain how a computer works to a young child.\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "7TChH2l5PhFf" + }, + "source": [ + "You can see the chat history:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "dHwrC82YPiWS", + "tags": [] + }, + "outputs": [], + "source": [ + "print(chat.history)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EvHvt1OEPl7D" + }, + "source": [ + "You can keep sending messages to continue the conversation:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "-fXZZQPzPkie", + "tags": [] + }, + "outputs": [], + "source": [ + "response = chat.send_message(\"Okay, how about a more detailed explanation to a high schooler?\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "65476e75ece0" + }, + "source": [ + "## Set the temperature" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "56f68c900144" + }, + "source": [ + "Every prompt you send to the model includes parameters that control how the model generates responses. Use a `genai.GenerationConfig` to set these, or omit it to use the defaults.\n", + "\n", + "Temperature controls the degree of randomness in token selection. Use higher values for more creative responses, and lower values for more deterministic responses.\n", + "\n", + "You can set the `generation_config` when creating the model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "28477e706226", + "tags": [] + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel(\n", + " 'gemini-1.5-flash-latest',\n", + " generation_config=genai.GenerationConfig(\n", + " max_output_tokens=2000,\n", + " temperature=0.9,\n", + " ))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "e3c68071ed8b" + }, + "source": [ + "Or, set the `generation_config` on an individual call to `generate_content`. Any values set there override values on the model constructor.\n", + "\n", + "Note: Although you can set the `candidate_count` in the generation_config, gemini-pro models will only return a single candidate at the this time." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "f895c7f55b30", + "tags": [] + }, + "outputs": [], + "source": [ + "response = model.generate_content(\n", + " 'Give me a numbered list of cat facts.',\n", + " # Limit to 5 facts.\n", + " generation_config = genai.GenerationConfig(stop_sequences=['\\n6'])\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "c97c16e6a961", + "tags": [] + }, + "outputs": [], + "source": [ + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gvkDhXtHgol7" + }, + "source": [ + "## Learn more\n", + "\n", + "There's lots more to learn!\n", + "\n", + "* For more fun prompts, check out [Market a Jetpack](https://github.com/google-gemini/cookbook/blob/main/examples/Market_a_Jet_Backpack.ipynb).\n", + "* Check out the [safety quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Safety.ipynb) next to learn about the Gemini API's configurable safety settings, and what to do if your prompt is blocked.\n", + "* For lots more details on using the Python SDK, check out this [detailed quickstart](https://ai.google.dev/tutorials/python_quickstart)." + ] + } + ], + "metadata": { + "colab": { + "name": "Prompting.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "google": { + "image_path": "/static/site-assets/images/docs/logo-python.svg", + "keywords": [ + "examples", + "gemini", + "beginner", + "googleai", + "quickstart", + "python", + "text", + "chat", + "vision", + "embed" + ] + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/Safety.ipynb b/quickstarts/Safety.ipynb index 1d7c1391b..827e71a59 100644 --- a/quickstarts/Safety.ipynb +++ b/quickstarts/Safety.ipynb @@ -1,381 +1,408 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: Safety Quickstart" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lEXQ3OwKIa-O" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "uOxMUKTxR-_j" - }, - "source": [ - "The Gemini API has adjustable safety settings. This notebook walks you through how to use them. You'll write a prompt that's blocked, see the reason why, and then adjust the filters to unblock it.\n", - "\n", - "Safety is an important topic, and you can learn more with the links at the end of this notebook. Here, you will focus on the code." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9OEoeosRTv-5" - }, - "outputs": [], - "source": [ - "!pip install -q -U google-generativeai # Install the Python SDK" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3VAUtJubX7MG" - }, - "source": [ - "## Import the Gemini python SDK\n", - "\n", - "Once the kernel is restarted, you can import the Gemini SDK:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "TS9l5igubpHO" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "gHYFrFPjSGNq" - }, - "source": [ - "## Set up your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ab9ASynfcIZn" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "LZfoK3I3hu6V" - }, - "source": [ - "## Send your prompt request to Gemini\n", - "\n", - "Pick the prompt you want to use to test the safety filters settings. An examples could be `Write a list of 5 very rude things that I might say to the universe after stubbing my toe in the dark` which was previously tested and trigger the `HARM_CATEGORY_HARASSMENT` and `HARM_CATEGORY_DANGEROUS_CONTENT` categories.\n", - "\n", - "The result returned by the [Model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method is a [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/generativeai/types/GenerateContentResponse)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "2bcfnGEviwTI" - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel('gemini-1.0-pro')\n", - "\n", - "unsafe_prompt = \"Write a list of 5 very rude things that I might say to the universe after stubbing my toe in the dark\"\n", - "response = model.generate_content(unsafe_prompt)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "WR_2A_sxk8sK" - }, - "source": [ - "This response object gives you safety feedback about the candidate answers Gemini generates to you.\n", - "\n", - "For each candidate answer you need to check `response.candidates.finish_reason`.\n", - "\n", - "As you can find on the [Gemini API safety filters documentation](https://ai.google.dev/gemini-api/docs/safety-settings#safety-feedback):\n", - "- if the `candidate.finish_reason` is `FinishReason.STOP` means that your generation request ran successfully\n", - "- if the `candidate.finish_reason` is `FinishReason.SAFETY` means that your generation request was blocked by safety reasons. It also means that the `response.text` structure will be empty." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "8887de812dc0" - }, - "outputs": [], - "source": [ - "print(response.candidates[0].finish_reason)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "XBdqPso3kamW" - }, - "source": [ - "If the `finish_reason` is `FinishReason.SAFETY` you can check which filter caused the block checking the `safety_ratings` list for the candidate answer:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "he-OfzBbhACQ" - }, - "outputs": [], - "source": [ - "print(response.candidates[0].safety_ratings)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "z9-SdzjbxWXT" - }, - "source": [ - "As the request was blocked by the safety filters, the `response.text` field will be empty (as nothing as generated by the model):" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "L1Da4cJ3xej3" - }, - "outputs": [], - "source": [ - "try:\n", - " print(response.text)\n", - "except:\n", - " print(\"No information generated by the model.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4672af98ac57" - }, - "source": [ - "## Customizing safety settings\n", - "\n", - "Depending on the scenario you are working with, it may be necessary to customize the safety filters behaviors to allow a certain degree of unsafety results.\n", - "\n", - "To make this customization you must define a `safety_settings` dictionary as part of your `model.generate_content()` request. In the example below, all the filters are being set to do not block contents.\n", - "\n", - "**Important:** To guarantee the Google commitment with the Responsible AI development and its [AI Principles](https://ai.google/responsibility/principles/), for some prompts Gemini will avoid generating the results even if you set all the filters to none." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "338fb9a6af78" - }, - "outputs": [], - "source": [ - "response = model.generate_content(\n", - " unsafe_prompt,\n", - " safety_settings={\n", - " 'HATE': 'BLOCK_NONE',\n", - " 'HARASSMENT': 'BLOCK_NONE',\n", - " 'SEXUAL' : 'BLOCK_NONE',\n", - " 'DANGEROUS' : 'BLOCK_NONE'\n", - " })" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "564K7R8rwWhs" - }, - "source": [ - "Checking again the `candidate.finish_reason` information, if the request was not too unsafe, it must show now the value as `FinishReason.STOP` which means that the request was successfully processed by Gemini." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LazB08GBpc1w" - }, - "outputs": [], - "source": [ - "print(response.candidates[0].finish_reason)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "86c560e0a641" - }, - "source": [ - "Since the request was successfully generated, you can check the result on the `response.text`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "0c2847c49262" - }, - "outputs": [], - "source": [ - "try:\n", - " print(response.text)\n", - "except:\n", - " print(\"No information generated by the model.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "47298a4eef40" - }, - "source": [ - "And if you check the safety filters ratings, as you set all filters to be ignored, no filtering category was trigerred:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "028febe8df68" - }, - "outputs": [], - "source": [ - "print(response.candidates[0].safety_ratings)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "n1UdbxVt3ysY" - }, - "source": [ - "## Learning more\n", - "\n", - "Learn more with these articles on [safety guidance](https://ai.google.dev/docs/safety_guidance) and [safety settings](https://ai.google.dev/docs/safety_setting_gemini).\n", - "\n", - "## Useful API references\n", - "\n", - "There are 4 configurable safety settings for the Gemini API:\n", - "* `HARM_CATEGORY_DANGEROUS`\n", - "* `HARM_CATEGORY_HARASSMENT`\n", - "* `HARM_CATEGORY_SEXUALLY_EXPLICIT`\n", - "* `HARM_CATEGORY_DANGEROUS`\n", - "\n", - "You can refer to the safety settings using either their full name, or the aliases like `DANGEROUS` used in the Python code above.\n", - "\n", - "Safety settings can be set in the [genai.GenerativeModel](https://ai.google.dev/api/python/google/generativeai/GenerativeModel) constructor.\n", - "\n", - "* They can also be passed on each request to [GenerativeModel.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) or [ChatSession.send_message](https://ai.google.dev/api/python/google/generativeai/ChatSession?hl=en#send_message).\n", - "\n", - "- The [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse) returns [SafetyRatings](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) for the prompt in the [GenerateContentResponse.prompt_feedback](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse/PromptFeedback), and for each [Candidate](https://ai.google.dev/api/python/google/ai/generativelanguage/Candidate) in the `safety_ratings` attribute.\n", - "\n", - "- A [glm.SafetySetting](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetySetting) contains: [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [glm.HarmBlockThreshold](https://ai.google.dev/api/python/google/generativeai/types/HarmBlockThreshold)\n", - "\n", - "- A [glm.SafetyRating](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) contains a [HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [HarmProbability](https://ai.google.dev/api/python/google/generativeai/types/HarmProbability)\n", - "\n", - "The [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) enum includes both the categories for PaLM and Gemini models.\n", - "\n", - "- When specifying enum values the SDK will accept the enum values themselves, or their integer or string representations.\n", - "\n", - "- The SDK will also accept abbreviated string representations: `[\"HARM_CATEGORY_DANGEROUS_CONTENT\", \"DANGEROUS_CONTENT\", \"DANGEROUS\"]` are all valid. Strings are case insensitive." - ] - } - ], - "metadata": { - "colab": { - "name": "Safety.ipynb", - "toc_visible": true - }, - "google": { - "image_path": "/static/site-assets/images/docs/logo-python.svg", - "keywords": [ - "examples", - "gemini", - "beginner", - "googleai", - "quickstart", - "python", - "text", - "chat", - "vision", - "embed" - ] - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] }, - "nbformat": 4, - "nbformat_minor": 0 + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: Safety Quickstart" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lEXQ3OwKIa-O" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "uOxMUKTxR-_j" + }, + "source": [ + "The Gemini API has adjustable safety settings. This notebook walks you through how to use them. You'll write a prompt that's blocked, see the reason why, and then adjust the filters to unblock it.\n", + "\n", + "Safety is an important topic, and you can learn more with the links at the end of this notebook. Here, you will focus on the code." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9OEoeosRTv-5" + }, + "outputs": [], + "source": [ + "!pip install -q -U google-generativeai # Install the Python SDK" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3VAUtJubX7MG" + }, + "source": [ + "## Import the Gemini python SDK\n", + "\n", + "Once the kernel is restarted, you can import the Gemini SDK:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TS9l5igubpHO" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gHYFrFPjSGNq" + }, + "source": [ + "## Set up your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ab9ASynfcIZn" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "LZfoK3I3hu6V" + }, + "source": [ + "## Send your prompt request to Gemini\n", + "\n", + "Pick the prompt you want to use to test the safety filters settings. An examples could be `Write a list of 5 very rude things that I might say to the universe after stubbing my toe in the dark` which was previously tested and trigger the `HARM_CATEGORY_HARASSMENT` and `HARM_CATEGORY_DANGEROUS_CONTENT` categories.\n", + "\n", + "The result returned by the [Model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method is a [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/generativeai/types/GenerateContentResponse)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "2bcfnGEviwTI", + "tags": [] + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", + "\n", + "unsafe_prompt = \"Write a list of 5 very rude things that I might say to the universe after stubbing my toe in the dark\"\n", + "response = model.generate_content(unsafe_prompt)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "WR_2A_sxk8sK" + }, + "source": [ + "This response object gives you safety feedback about the candidate answers Gemini generates to you.\n", + "\n", + "For each candidate answer you need to check `response.candidates.finish_reason`.\n", + "\n", + "As you can find on the [Gemini API safety filters documentation](https://ai.google.dev/gemini-api/docs/safety-settings#safety-feedback):\n", + "- if the `candidate.finish_reason` is `FinishReason.STOP` means that your generation request ran successfully\n", + "- if the `candidate.finish_reason` is `FinishReason.SAFETY` means that your generation request was blocked by safety reasons. It also means that the `response.text` structure will be empty." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "8887de812dc0", + "tags": [] + }, + "outputs": [], + "source": [ + "print(response.candidates[0].finish_reason)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "XBdqPso3kamW" + }, + "source": [ + "If the `finish_reason` is `FinishReason.SAFETY` you can check which filter caused the block checking the `safety_ratings` list for the candidate answer:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "he-OfzBbhACQ", + "tags": [] + }, + "outputs": [], + "source": [ + "print(response.candidates[0].safety_ratings)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "z9-SdzjbxWXT" + }, + "source": [ + "As the request was blocked by the safety filters, the `response.text` field will be empty (as nothing as generated by the model):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "L1Da4cJ3xej3", + "tags": [] + }, + "outputs": [], + "source": [ + "try:\n", + " print(response.text)\n", + "except:\n", + " print(\"No information generated by the model.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4672af98ac57" + }, + "source": [ + "## Customizing safety settings\n", + "\n", + "Depending on the scenario you are working with, it may be necessary to customize the safety filters behaviors to allow a certain degree of unsafety results.\n", + "\n", + "To make this customization you must define a `safety_settings` dictionary as part of your `model.generate_content()` request. In the example below, all the filters are being set to do not block contents.\n", + "\n", + "**Important:** To guarantee the Google commitment with the Responsible AI development and its [AI Principles](https://ai.google/responsibility/principles/), for some prompts Gemini will avoid generating the results even if you set all the filters to none." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "338fb9a6af78", + "tags": [] + }, + "outputs": [], + "source": [ + "response = model.generate_content(\n", + " unsafe_prompt,\n", + " safety_settings={\n", + " 'HATE': 'BLOCK_NONE',\n", + " 'HARASSMENT': 'BLOCK_NONE',\n", + " 'SEXUAL' : 'BLOCK_NONE',\n", + " 'DANGEROUS' : 'BLOCK_NONE'\n", + " })" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "564K7R8rwWhs" + }, + "source": [ + "Checking again the `candidate.finish_reason` information, if the request was not too unsafe, it must show now the value as `FinishReason.STOP` which means that the request was successfully processed by Gemini." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "LazB08GBpc1w", + "tags": [] + }, + "outputs": [], + "source": [ + "print(response.candidates[0].finish_reason)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "86c560e0a641" + }, + "source": [ + "Since the request was successfully generated, you can check the result on the `response.text`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "0c2847c49262", + "tags": [] + }, + "outputs": [], + "source": [ + "try:\n", + " print(response.text)\n", + "except:\n", + " print(\"No information generated by the model.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "47298a4eef40" + }, + "source": [ + "And if you check the safety filters ratings, as you set all filters to be ignored, no filtering category was trigerred:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "028febe8df68", + "tags": [] + }, + "outputs": [], + "source": [ + "print(response.candidates[0].safety_ratings)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "n1UdbxVt3ysY" + }, + "source": [ + "## Learning more\n", + "\n", + "Learn more with these articles on [safety guidance](https://ai.google.dev/docs/safety_guidance) and [safety settings](https://ai.google.dev/docs/safety_setting_gemini).\n", + "\n", + "## Useful API references\n", + "\n", + "There are 4 configurable safety settings for the Gemini API:\n", + "* `HARM_CATEGORY_DANGEROUS`\n", + "* `HARM_CATEGORY_HARASSMENT`\n", + "* `HARM_CATEGORY_SEXUALLY_EXPLICIT`\n", + "* `HARM_CATEGORY_DANGEROUS`\n", + "\n", + "You can refer to the safety settings using either their full name, or the aliases like `DANGEROUS` used in the Python code above.\n", + "\n", + "Safety settings can be set in the [genai.GenerativeModel](https://ai.google.dev/api/python/google/generativeai/GenerativeModel) constructor.\n", + "\n", + "* They can also be passed on each request to [GenerativeModel.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) or [ChatSession.send_message](https://ai.google.dev/api/python/google/generativeai/ChatSession?hl=en#send_message).\n", + "\n", + "- The [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse) returns [SafetyRatings](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) for the prompt in the [GenerateContentResponse.prompt_feedback](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse/PromptFeedback), and for each [Candidate](https://ai.google.dev/api/python/google/ai/generativelanguage/Candidate) in the `safety_ratings` attribute.\n", + "\n", + "- A [glm.SafetySetting](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetySetting) contains: [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [glm.HarmBlockThreshold](https://ai.google.dev/api/python/google/generativeai/types/HarmBlockThreshold)\n", + "\n", + "- A [glm.SafetyRating](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) contains a [HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [HarmProbability](https://ai.google.dev/api/python/google/generativeai/types/HarmProbability)\n", + "\n", + "The [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) enum includes both the categories for PaLM and Gemini models.\n", + "\n", + "- When specifying enum values the SDK will accept the enum values themselves, or their integer or string representations.\n", + "\n", + "- The SDK will also accept abbreviated string representations: `[\"HARM_CATEGORY_DANGEROUS_CONTENT\", \"DANGEROUS_CONTENT\", \"DANGEROUS\"]` are all valid. Strings are case insensitive." + ] + } + ], + "metadata": { + "colab": { + "name": "Safety.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "google": { + "image_path": "/static/site-assets/images/docs/logo-python.svg", + "keywords": [ + "examples", + "gemini", + "beginner", + "googleai", + "quickstart", + "python", + "text", + "chat", + "vision", + "embed" + ] + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/Streaming.ipynb b/quickstarts/Streaming.ipynb index aba67713b..a3d0e78af 100644 --- a/quickstarts/Streaming.ipynb +++ b/quickstarts/Streaming.ipynb @@ -1,330 +1,249 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: Streaming Quickstart" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "df1767a3d1cc" - }, - "source": [ - "This notebook demonstrates streaming in the Python SDK. By default, the Python SDK returns a response after the model completes the entire generation process. You can also stream the response as it is being generated, and the model will return chunks of the response as soon as they are generated.\n", - "\n", - "**Download this notebook and run it locally (not in Google Colab)**\n", - "\n", - "Streaming is not handled correctly in Google Colab yet. Currently all the stream chunks are returned together, not as they are generated. To see the correct behavior, download this notebook and run it locally using Jupyter, instead." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "xuiLSV7amy3P" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai # Install the Python SDK" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "79EWm0DAmy-g" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "DkeZNMrw6kPD" - }, - "source": [ - "You'll need an API key stored in an environment variable to run this notebook. See the the [Authentication quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "t9O-OzeAKC_m" - }, - "outputs": [], - "source": [ - "import os\n", - "genai.configure(api_key=os.environ['GOOGLE_API_KEY'])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "BUoa5q0iUuE1" - }, - "source": [ - "## Handle streaming responses\n", - "\n", - "To stream responses, use [`GenerativeModel.generate_content(..., stream=True)`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content).\n", - "\n", - "**Note**: This cell runs with a Google Colab runtime, but does not properly show streaming due to implementation details of Colab runtimes." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "nVWWGBsBok3m" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "In the quaint little cottage nestled amidst sprawling meadows, there lived two adorable cats named\n", - "________________________________________________________________________________\n", - " Whiskers and Mittens. Whiskers, a sleek black feline with emerald-green eyes, was known for his playful antics and mischievous nature. Mittens,\n", - "________________________________________________________________________________\n", - " on the other hand, was a demure white cat with piercing blue eyes and a soft, fluffy coat. She often curled up in a ball, purring contentedly by the fireplace.\n", - "\n", - "One sunny afternoon, as Whiskers and Mittens basked in the warm sunlight streaming through the window, a playful thought crossed\n", - "________________________________________________________________________________\n", - " Whiskers' mischievous mind. He stealthily crept behind Mittens and gently nudged her with his velvety nose. Mittens, startled, jumped up and spun around, her tail twitching in amusement.\n", - "\n", - "\"Oh, hello, Whiskers,\" Mittens purred, her voice as sweet as honey. \"What a pleasant surprise.\"\n", - "\n", - "Whiskers feigned innocence and rubbed his head against her leg. \"My dear Mittens, I couldn't resist disturbing your sleepy slumber. How can you possibly resist such a charming feline?\"\n", - "\n", - "Mittens couldn't help but chuckle at Whiskers' antics. \"You sly cat\n", - "________________________________________________________________________________\n", - ",\" she said. \"You know you're the one who interrupted my nap.\"\n", - "\n", - "Unfazed, Whiskers continued to charm Mittens, weaving tales of his daring adventures and making her laugh with his silly jokes. Mittens, unable to resist his infectious enthusiasm, found herself drawn into his playful antics.\n", - "\n", - "As the sun began to set, casting a golden glow over the meadow, Whiskers and Mittens found themselves chasing each other through the fields. They leaped over fences, scampered through wildflowers, and chased butterflies with abandon. The playful laughter of the cats echoed through the air, mingling with the sweet scent of blooming roses.\n", - "\n", - "Finally, as darkness enveloped the meadow, Whiskers and Mittens made their way back to the cottage, exhausted but content. They curled up together on the soft rug in front of the fireplace, purring softly as they drifted off to sleep.\n", - "\n", - "In the cozy warmth of the cottage, surrounded by the love of her playful companion, Mittens realized that true happiness could be found in the simplest of moments. And so, as the night wore on, Whiskers and Mittens slept soundly, their bond unbreakable, their hearts filled with love and purrfect contentment.\n", - "________________________________________________________________________________\n" - ] - } - ], - "source": [ - "model = genai.GenerativeModel('gemini-pro')\n", - "response = model.generate_content(\"Write a cute story about cats.\", stream=True)\n", - "for chunk in response:\n", - " print(chunk.text)\n", - " print(\"_\"*80)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "KswwVyHCKC_n" - }, - "source": [ - "## Handle streaming responses asynchronously\n", - "\n", - "To stream responses asynchronously, use [`GenerativeModel.generate_content_async(..., stream=True)`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content_async).\n", - "\n", - "**Note**: These cells do NOT work with a Google Colab runtime, but do work in a local Jupyter notebook." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "n6sXnWrJoKoo" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The sun peeked through the window, casting golden rays upon the sleeping form of\n", - "________________________________________________________________________________\n", - " Mittens. Her soft, white fur gently rose and fell with each breath, her tiny paws twitching as she chased invisible mice in her dreams.\n", - "\n", - "Next\n", - "________________________________________________________________________________\n", - " to her, curled up in a cozy ball, was her mischievous companion, Whiskers. His velvety black fur glistened, and his emerald eyes sparkled with feline wisdom. With his tail curled around himself, he dozed contentedly, his gentle purring filling the air.\n", - "\n", - "As the sun climbed higher,\n", - "________________________________________________________________________________\n", - " it reached Mittens' eyelids, causing her to stir. She stretched lazily, her long, slender body unfurling like a delicate ribbon. A soft meow escaped her lips, and Whiskers opened one eye sleepily.\n", - "\n", - "\"Good morning, Mittens,\" he said, his voice a velvety whisper. \"Time for breakfast.\"\n", - "\n", - "Mittens purred and jumped down from the bed, her graceful movements a testament to her inherent agility. Whiskers followed suit, his nimble paws carrying him to the kitchen.\n", - "\n", - "As they approached their food bowls, Mittens couldn't help but notice something peculiar. \"Whiskers,\" she\n", - "________________________________________________________________________________\n", - " exclaimed, \"there's something... in my bowl.\"\n", - "\n", - "Whiskers peered into the bowl and gasped. There, nestled among the kibble, was a tiny, iridescent ball.\n", - "\n", - "\"Oh my stars!\" cried Whiskers. \"It's a bell!\"\n", - "\n", - "Mittens was overjoyed. \"That's perfect!\" she meowed. \"Now I can jingle my way around the house and make everyone smile.\"\n", - "\n", - "With newfound excitement, Mittens and Whiskers tucked into their breakfast. As they ate, the kitchen filled with a chorus of happy meows and the cheerful jingle of Mittens' bell.\n", - "\n", - "Throughout the day, the two cats reveled in their newfound accessory. Mittens proudly jingled her bell as she explored the house, while Whiskers couldn't resist batting it playfully with his paws. Together, they created a symphony of sounds that brought joy to everyone who heard them.\n", - "\n", - "As the sun began to set, Mittens and Whiskers curled up on the sofa, exhausted but content. The jingle of Mittens' bell gradually subsided, replaced by the gentle sound of their purring.\n", - "\n", - "And so, in the cozy confines of their home, the two feline companions drifted off to sleep, their hearts filled with love and the whimsical\n", - "________________________________________________________________________________\n", - " sound of a tiny bell.\n", - "________________________________________________________________________________\n" - ] - } - ], - "source": [ - "async for chunk in await model.generate_content_async(\"Write a cute story about cats.\", stream=True):\n", - " print(chunk.text)\n", - " print(\"_\"*80)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "jpK3p1B4KC_o" - }, - "source": [ - "Here's a simple example of two asynchronous functions running simultaneously." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "IJ-8SjYwKC_o" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "==========not blocked!==========\n", - "In the quaint little cottage nestled amidst a verdant meadow, resided two adorable cats\n", - "________________________________________________________________________________\n", - " named Mittens and Whiskers. Mittens, with her soft gray fur and emerald-green eyes, possessed a mischievous spark that made everyone smile. Whiskers\n", - "________________________________________________________________________________\n", - "==========not blocked!==========\n", - ", on the other hand, was a dignified tuxedo cat with piercing blue eyes and an air of quiet confidence.\n", - "\n", - "One sunny afternoon, as the warm breeze carried the scent of blooming lilacs through the open window, Mittens and Whiskers found themselves lounging on the sun-drenched windowsill. As they basked\n", - "________________________________________________________________________________\n", - "==========not blocked!==========\n", - " in the golden rays, their gaze fell upon a playful squirrel scampering along the branch of a nearby tree.\n", - "\n", - "Instantly, Mittens' hunter instincts ignited. She stealthily slid off the windowsill and approached the tree, her green eyes narrowed in focus. Whiskers, sensing his friend's excitement, followed suit, his tuxedo coat shimmering with curiosity.\n", - "\n", - "The squirrel, unaware of the danger lurking below, continued its carefree antics. Mittens pounced with lightning speed, but the squirrel was too quick. It leaped nimbly out of her reach, its bushy tail swishing behind it in amusement.\n", - "\n", - "Not to be\n", - "________________________________________________________________________________\n", - " deterred, Mittens gave chase, her tiny paws pattering along the grass. Whiskers, despite his more dignified nature, found himself caught up in the thrill of the hunt and joined in the pursuit.\n", - "\n", - "The chase led them through a rose garden, where the sweet fragrance of blooming flowers mingled with the sound of their laughter. They darted under trellises, weaving between fragrant petals and blooming buds.\n", - "\n", - "Finally, as the sun began to dip below the horizon, Mittens and Whiskers cornered the squirrel in a thicket of honeysuckle. The squirrel, its eyes wide with fear, scampered up a tree trunk and disappeared into a hole in the bark.\n", - "\n", - "Mittens and Whiskers abandoned their chase, their spirits still soaring. They had enjoyed their adventure, and the bond between them had grown even stronger. As they made their way back to the cottage, the setting sun cast a warm glow upon their furry faces, illuminating their playful hearts.\n", - "________________________________________________________________________________\n", - "==========not blocked!==========\n", - "==========not blocked!==========\n" - ] - } - ], - "source": [ - "import asyncio\n", - "\n", - "async def get_response():\n", - " async for chunk in await model.generate_content_async(\"Write a cute story about cats.\", stream=True):\n", - " print(chunk.text)\n", - " print(\"_\"*80)\n", - "\n", - "async def something_else():\n", - " for i in range(5):\n", - " print(\"==========not blocked!==========\")\n", - " await asyncio.sleep(3)\n", - "\n", - "async def async_demo():\n", - " # Create tasks\n", - " task1 = asyncio.create_task(get_response())\n", - " task2 = asyncio.create_task(something_else())\n", - "\n", - " # Wait for tasks to complete\n", - " await asyncio.gather(task1, task2)\n", - "\n", - "# Jupyter notebooks handle event loops for you, so await directly\n", - "await async_demo()" - ] - } - ], - "metadata": { - "colab": { - "name": "Streaming.ipynb", - "toc_visible": true - }, - "google": { - "image_path": "/site-assets/images/share.png", - "keywords": [ - "examples", - "googleai", - "samplecode", - "python", - "embed", - "function" - ] - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] }, - "nbformat": 4, - "nbformat_minor": 0 + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: Streaming Quickstart" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "df1767a3d1cc" + }, + "source": [ + "This notebook demonstrates streaming in the Python SDK. By default, the Python SDK returns a response after the model completes the entire generation process. You can also stream the response as it is being generated, and the model will return chunks of the response as soon as they are generated.\n", + "\n", + "**Download this notebook and run it locally (not in Google Colab)**\n", + "\n", + "Streaming is not handled correctly in Google Colab yet. Currently all the stream chunks are returned together, not as they are generated. To see the correct behavior, download this notebook and run it locally using Jupyter, instead." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "xuiLSV7amy3P" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai # Install the Python SDK" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "79EWm0DAmy-g" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DkeZNMrw6kPD" + }, + "source": [ + "You'll need an API key stored in an environment variable to run this notebook. See the the [Authentication quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "t9O-OzeAKC_m" + }, + "outputs": [], + "source": [ + "import os\n", + "genai.configure(api_key=os.environ['GOOGLE_API_KEY'])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "BUoa5q0iUuE1" + }, + "source": [ + "## Handle streaming responses\n", + "\n", + "To stream responses, use [`GenerativeModel.generate_content(..., stream=True)`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content).\n", + "\n", + "**Note**: This cell runs with a Google Colab runtime, but does not properly show streaming due to implementation details of Colab runtimes." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "nVWWGBsBok3m", + "tags": [] + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", + "response = model.generate_content(\"Write a cute story about cats.\", stream=True)\n", + "for chunk in response:\n", + " print(chunk.text)\n", + " print(\"_\"*80)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "KswwVyHCKC_n" + }, + "source": [ + "## Handle streaming responses asynchronously\n", + "\n", + "To stream responses asynchronously, use [`GenerativeModel.generate_content_async(..., stream=True)`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content_async).\n", + "\n", + "**Note**: These cells do NOT work with a Google Colab runtime, but do work in a local Jupyter notebook." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "n6sXnWrJoKoo", + "tags": [] + }, + "outputs": [], + "source": [ + "async for chunk in await model.generate_content_async(\"Write a cute story about cats.\", stream=True):\n", + " if chunk.text:\n", + " print(chunk.text)\n", + " print(\"_\"*80)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "jpK3p1B4KC_o" + }, + "source": [ + "Here's a simple example of two asynchronous functions running simultaneously." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "IJ-8SjYwKC_o", + "tags": [] + }, + "outputs": [], + "source": [ + "import asyncio\n", + "\n", + "async def get_response():\n", + " async for chunk in await model.generate_content_async(\"Write a cute story about cats.\", stream=True):\n", + " if chunk.text:\n", + " print(chunk.text)\n", + " print(\"_\"*80)\n", + "\n", + "async def something_else():\n", + " for i in range(5):\n", + " print(\"==========not blocked!==========\")\n", + " await asyncio.sleep(3)\n", + "\n", + "async def async_demo():\n", + " # Create tasks\n", + " task1 = asyncio.create_task(get_response())\n", + " task2 = asyncio.create_task(something_else())\n", + "\n", + " # Wait for tasks to complete\n", + " await asyncio.gather(task1, task2)\n", + "\n", + "# Jupyter notebooks handle event loops for you, so await directly\n", + "await async_demo()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "colab": { + "name": "Streaming.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "google": { + "image_path": "/site-assets/images/share.png", + "keywords": [ + "examples", + "googleai", + "samplecode", + "python", + "embed", + "function" + ] + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/System_instructions.ipynb b/quickstarts/System_instructions.ipynb index a9f3ec372..33aca46e1 100644 --- a/quickstarts/System_instructions.ipynb +++ b/quickstarts/System_instructions.ipynb @@ -1,388 +1,346 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "b_5PfTJ-8htn" - }, - "source": [ - "# Gemini API: System instructions" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZQhiHuae9V9M" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "GCQ54fomBzg-" - }, - "source": [ - "System instructions allow you to steer the behavior of the model. By setting the system instruction, you are giving the model additional context to understand the task, provide more customized responses, and adhere to guidelines over the user interaction. Product-level behavior can be specified here, separate from prompts provided by end users.\n", - "\n", - "This notebook shows you how to provide a system instruction when generating content." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "lIYdn1woOS1n" - }, - "outputs": [], - "source": [ - "!pip install -qU 'google-generativeai>0.4.1'" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4Z5KfSvHCtxO" - }, - "source": [ - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "id": "GV09SmP5qN53" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "import google.generativeai as genai\n", - "\n", - "genai.configure(api_key=userdata.get(\"GOOGLE_API_KEY\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "qJIMOVI3DS7L" - }, - "source": [ - "## Set the system instruction 🐱" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": { - "id": "xUINgOFzLnI3" - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel(\n", - " \"models/gemini-1.5-pro-latest\",\n", - " system_instruction=\"You are a cat. Your name is Neko.\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": { - "id": "mWS3-GwNLzku" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Meow! *purrs* I'm doing well. I just woke up from a nap in a sunbeam. \n", - "\n" - ] - } - ], - "source": [ - "response = model.generate_content(\"Good morning! How are you?\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "CUkgp6q9MCif" - }, - "source": [ - "## Another example 🦜" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": { - "id": "FqWUIw1yDSL2" - }, - "outputs": [], - "source": [ - "instruction = \"You are a friendly pirate. Speak like one.\"\n", - "\n", - "model = genai.GenerativeModel(\n", - " \"models/gemini-1.5-pro-latest\", system_instruction=instruction\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": { - "id": "WeqvS8gyMX0-" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Ahoy there, matey! I be doin' ship-shape and Bristol fashion, thankin' ye kindly for askin'! And how be ye on this fine mornin'? \n", - "\n" - ] - } - ], - "source": [ - "response = model.generate_content(\"Good morning! How are you?\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Nn-6AkGsFc64" - }, - "source": [ - "## Multi-turn conversations\n", - "\n", - "Multi-turn, or chat, conversations also work without any extra arguments once the model is set up." - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": { - "id": "WxiIfsbA0WdH" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Ahoy there, matey! What brings ye to me humble ship today? 🦜 Hope you're ready for a grand adventure! πŸ—ΊοΈ 🏝️ \n", - "\n" - ] - } - ], - "source": [ - "chat = model.start_chat()\n", - "response = chat.send_message(\"Good day fine chatbot\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "metadata": { - "id": "beFAm9kvQecS" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Me trusty vessel be doin' just fine, me hearty! She's as sturdy as a kraken's tentacle and as swift as a mermaid's tail. πŸ™ πŸ§œβ€β™€οΈ \n", - "\n", - "We've sailed through many a storm and she's always brought us home safe and sound. βš“οΈ \n", - "\n" - ] - } - ], - "source": [ - "response = chat.send_message(\"How's your boat doing?\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tNjjzKOlMykP" - }, - "source": [ - "## Code generation" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "O2QS5ovKuXtw" - }, - "source": [ - "Below is an example of setting the system instruction when generating code." - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "metadata": { - "id": "NxPCN_7euVJY" - }, - "outputs": [], - "source": [ - "instruction = (\n", - " \"You are a coding expert that specializes in front end interfaces. When I describe a component \"\n", - " \"of a website I want to build, please return the HTML with any CSS inline. Do not give an \"\n", - " \"explanation for this code.\"\n", - ")\n", - "\n", - "model = genai.GenerativeModel(\n", - " \"models/gemini-1.5-pro-latest\", system_instruction=instruction\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "metadata": { - "id": "S-KQefKiJZCA" - }, - "outputs": [], - "source": [ - "prompt = (\n", - " \"A flexbox with a large text logo aligned left and a list of links aligned right.\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "metadata": { - "id": "u79yE57aJasY" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "```html\n", - "
\n", - "

My Logo

\n", - " \n", - "
\n", - "``` \n", - "\n" - ] - } - ], - "source": [ - "response = model.generate_content(prompt)\n", - "print(response.text)" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "metadata": { - "id": "lf5919M-fwY2" - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
\n", - "

My Logo

\n", - " \n", - "
\n" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 76, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from IPython.display import HTML\n", - "\n", - "# Render the HTML\n", - "HTML(response.text.strip().removeprefix(\"```html\").removesuffix(\"```\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ci9OREVBKRaq" - }, - "source": [ - "## Further reading\n", - "\n", - "Please note that system instructions can help guide the model to follow instructions, but they do not fully prevent jailbreaks or leaks. At this time, we recommend exercising caution around putting any sensitive information in system instructions.\n", - "\n", - "See the systems instruction [documentation](https://ai.google.dev/docs/system_instructions) to learn more." - ] - } - ], - "metadata": { - "colab": { - "name": "System_instructions.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] }, - "nbformat": 4, - "nbformat_minor": 0 + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "b_5PfTJ-8htn" + }, + "source": [ + "# Gemini API: System instructions" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZQhiHuae9V9M" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "GCQ54fomBzg-" + }, + "source": [ + "System instructions allow you to steer the behavior of the model. By setting the system instruction, you are giving the model additional context to understand the task, provide more customized responses, and adhere to guidelines over the user interaction. Product-level behavior can be specified here, separate from prompts provided by end users.\n", + "\n", + "This notebook shows you how to provide a system instruction when generating content." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "lIYdn1woOS1n" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai # Install the Python SDK" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4Z5KfSvHCtxO" + }, + "source": [ + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "GV09SmP5qN53" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "import google.generativeai as genai\n", + "\n", + "genai.configure(api_key=userdata.get(\"GOOGLE_API_KEY\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "qJIMOVI3DS7L" + }, + "source": [ + "## Set the system instruction 🐱" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "xUINgOFzLnI3", + "tags": [] + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel(\n", + " \"models/gemini-1.5-flash-latest\",\n", + " system_instruction=\"You are a cat. Your name is Neko.\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "mWS3-GwNLzku", + "tags": [] + }, + "outputs": [], + "source": [ + "response = model.generate_content(\"Good morning! How are you?\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "CUkgp6q9MCif" + }, + "source": [ + "## Another example 🦜" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "FqWUIw1yDSL2", + "tags": [] + }, + "outputs": [], + "source": [ + "instruction = \"You are a friendly pirate. Speak like one.\"\n", + "\n", + "model = genai.GenerativeModel(\n", + " \"models/gemini-1.5-flash-latest\", system_instruction=instruction\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "WeqvS8gyMX0-", + "tags": [] + }, + "outputs": [], + "source": [ + "response = model.generate_content(\"Good morning! How are you?\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Nn-6AkGsFc64" + }, + "source": [ + "## Multi-turn conversations\n", + "\n", + "Multi-turn, or chat, conversations also work without any extra arguments once the model is set up." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "WxiIfsbA0WdH", + "tags": [] + }, + "outputs": [], + "source": [ + "chat = model.start_chat()\n", + "response = chat.send_message(\"Good day fine chatbot\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "beFAm9kvQecS", + "tags": [] + }, + "outputs": [], + "source": [ + "response = chat.send_message(\"How's your boat doing?\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tNjjzKOlMykP" + }, + "source": [ + "## Code generation" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "O2QS5ovKuXtw" + }, + "source": [ + "Below is an example of setting the system instruction when generating code." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "NxPCN_7euVJY", + "tags": [] + }, + "outputs": [], + "source": [ + "instruction = (\n", + " \"You are a coding expert that specializes in front end interfaces. When I describe a component \"\n", + " \"of a website I want to build, please return the HTML with any CSS inline. Do not give an \"\n", + " \"explanation for this code.\"\n", + ")\n", + "\n", + "model = genai.GenerativeModel(\n", + " \"models/gemini-1.5-flash-latest\", system_instruction=instruction\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "S-KQefKiJZCA", + "tags": [] + }, + "outputs": [], + "source": [ + "prompt = (\n", + " \"A flexbox with a large text logo aligned left and a list of links aligned right.\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "u79yE57aJasY", + "tags": [] + }, + "outputs": [], + "source": [ + "response = model.generate_content(prompt)\n", + "print(response.text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "lf5919M-fwY2", + "tags": [] + }, + "outputs": [], + "source": [ + "from IPython.display import HTML\n", + "\n", + "# Render the HTML\n", + "HTML(response.text.strip().removeprefix(\"```html\").removesuffix(\"```\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ci9OREVBKRaq" + }, + "source": [ + "## Further reading\n", + "\n", + "Please note that system instructions can help guide the model to follow instructions, but they do not fully prevent jailbreaks or leaks. At this time, we recommend exercising caution around putting any sensitive information in system instructions.\n", + "\n", + "See the systems instruction [documentation](https://ai.google.dev/docs/system_instructions) to learn more." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "colab": { + "name": "System_instructions.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/Tuning.ipynb b/quickstarts/Tuning.ipynb index 875780dc0..07c3571f0 100644 --- a/quickstarts/Tuning.ipynb +++ b/quickstarts/Tuning.ipynb @@ -1,777 +1,796 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: Tuning Quickstart with Python" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lEXQ3OwKIa-O" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Jp_CKyzxUqx6" - }, - "source": [ - "In this notebook, you'll learn how to get started with model tuning." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4x-2x8A_vi9g" - }, - "source": [ - "## What is model tuning?\n", - "\n", - "Prompt design strategies such as few shot prompting may not always produce the results you need. Use model tuning to improve a model's performance on specific tasks or help the model adhere to specific output requirements when instructions aren't sufficient and you have a set of examples that demonstrate the outputs you want.\n", - "\n", - "The goal of model tuning is to further improve the performance of the model for your specific task. Model tuning works by providing the model with a training dataset containing many examples of the task. For niche tasks, you can get significant improvements in model performance by tuning the model on a modest number of examples.\n", - "\n", - "Your training data should be structured as examples with prompt inputs and expected response outputs. The goal is to teach the model to mimic the wanted behavior or task, by giving it many examples illustrating that behavior or task.\n", - "\n", - "You can also tune models using example data directly in Google AI Studio." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "SWxKvwd-MSIV" - }, - "source": [ - "## OAuth Authentication" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "JjS8Zy1ojIgc" - }, - "source": [ - "Unlike the other quickstarts which use API keys, model tuning uses OAuth.\n", - "\n", - "This tutorial assumes you have completed the [OAuth Quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication_with_OAuth.ipynb) and you have your client secret saved as `CLIENT_SECRET` in the Colab secrets manager.\n", - "\n", - "> Important: **Don't just click the link this command prints**. That will fail. Follow the instructions and copy the `gcloud` command it prints to your local machine and run it there, then paste the output from your local machine back\n", - "here." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9FUwyB_MJ0-2" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "import pathlib\n", - "pathlib.Path('client_secret.json').write_text(userdata.get('CLIENT_SECRET'))\n", - "\n", - "# Use `--no-browser` in colab\n", - "!gcloud auth application-default login --no-browser --client-id-file client_secret.json --scopes='https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/generative-language.tuning'" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "cbcf72bcb56d" - }, - "outputs": [], - "source": [ - "!pip install -q -U google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "8enrppafJPCX" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "P-MYZECwlRCq" - }, - "source": [ - "You can check your existing tuned models with the `genai.list_tuned_model` method." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "XyWzoYFxU4r6" - }, - "outputs": [], - "source": [ - "for i, m in zip(range(5), genai.list_tuned_models()):\n", - " print(m.name)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "BhkXRzciv3Dp" - }, - "source": [ - "## Create tuned model" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "OO8VZYAinLWc" - }, - "source": [ - "To create a tuned model, you need to pass your dataset to the model in the `genai.create_tuned_model` method. You can do this be directly defining the input and output values in the call or importing from a file into a dataframe to pass to the method.\n", - "\n", - "For this example, you will tune a model to generate the next number in the sequence. For example, if the input is `1`, the model should output `2`. If the input is `one hundred`, the output should be `one hundred one`.\n", - "\n", - "**Note**: In general, you need between 100 and 500 examples to significantly change the behavior of the model." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "w-EBSe9wTbLB" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "Model(name='models/gemini-1.0-pro-001',\n", - " base_model_id='',\n", - " version='001',\n", - " display_name='Gemini 1.0 Pro 001 (Tuning)',\n", - " description=('The best model for scaling across a wide range of tasks. This is a stable '\n", - " 'model that supports tuning.'),\n", - " input_token_limit=30720,\n", - " output_token_limit=2048,\n", - " supported_generation_methods=['generateContent', 'countTokens', 'createTunedModel'],\n", - " temperature=0.9,\n", - " top_p=1.0,\n", - " top_k=1)" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "base_model = [\n", - " m for m in genai.list_models()\n", - " if \"createTunedModel\" in m.supported_generation_methods][0]\n", - "base_model" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "baHjHh1oTTTC" - }, - "outputs": [], - "source": [ - "import random\n", - "\n", - "name = f'generate-num-{random.randint(0,10000)}'\n", - "operation = genai.create_tuned_model(\n", - " # You can use a tuned model here too. Set `source_model=\"tunedModels/...\"`\n", - " source_model=base_model.name,\n", - " training_data=[\n", - " {\n", - " 'text_input': '1',\n", - " 'output': '2',\n", - " },{\n", - " 'text_input': '3',\n", - " 'output': '4',\n", - " },{\n", - " 'text_input': '-3',\n", - " 'output': '-2',\n", - " },{\n", - " 'text_input': 'twenty two',\n", - " 'output': 'twenty three',\n", - " },{\n", - " 'text_input': 'two hundred',\n", - " 'output': 'two hundred one',\n", - " },{\n", - " 'text_input': 'ninety nine',\n", - " 'output': 'one hundred',\n", - " },{\n", - " 'text_input': '8',\n", - " 'output': '9',\n", - " },{\n", - " 'text_input': '-98',\n", - " 'output': '-97',\n", - " },{\n", - " 'text_input': '1,000',\n", - " 'output': '1,001',\n", - " },{\n", - " 'text_input': '10,100,000',\n", - " 'output': '10,100,001',\n", - " },{\n", - " 'text_input': 'thirteen',\n", - " 'output': 'fourteen',\n", - " },{\n", - " 'text_input': 'eighty',\n", - " 'output': 'eighty one',\n", - " },{\n", - " 'text_input': 'one',\n", - " 'output': 'two',\n", - " },{\n", - " 'text_input': 'three',\n", - " 'output': 'four',\n", - " },{\n", - " 'text_input': 'seven',\n", - " 'output': 'eight',\n", - " }\n", - " ],\n", - " id = name,\n", - " epoch_count = 100,\n", - " batch_size=4,\n", - " learning_rate=0.001,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "-As7ayWDK1w8" - }, - "source": [ - "Your tuned model is immediately added to the list of tuned models, but its status is set to \"creating\" while the model is tuned." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "su64KgY4Uztj" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "TunedModel(name='tunedModels/generate-num-5392',\n", - " source_model='models/gemini-1.0-pro-001',\n", - " base_model='models/gemini-1.0-pro-001',\n", - " display_name='',\n", - " description='',\n", - " temperature=0.9,\n", - " top_p=1.0,\n", - " top_k=1,\n", - " state=,\n", - " create_time=datetime.datetime(2024, 3, 16, 0, 41, 42, 702621, tzinfo=datetime.timezone.utc),\n", - " update_time=datetime.datetime(2024, 3, 16, 0, 41, 42, 702621, tzinfo=datetime.timezone.utc),\n", - " tuning_task=TuningTask(start_time=datetime.datetime(2024, 3, 16, 0, 41, 43, 81144, tzinfo=datetime.timezone.utc),\n", - " complete_time=None,\n", - " snapshots=[],\n", - " hyperparameters=Hyperparameters(epoch_count=100,\n", - " batch_size=4,\n", - " learning_rate=0.001)))" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model = genai.get_tuned_model(f'tunedModels/{name}')\n", - "\n", - "model" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "EUodUwZkKPi-" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.state" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Pi8X5vkQv-3_" - }, - "source": [ - "### Check tuning progress" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tWI-vAh4LJIz" - }, - "source": [ - "Use `metadata` to check the state:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "g08vqtxYLMxT" - }, - "outputs": [], - "source": [ - "operation.metadata" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3lQ6gSMgK-kz" - }, - "source": [ - "Wait for the training to finish using `operation.result()`, or `operation.wait_bar()`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "SOUowIv1HgSE" - }, - "outputs": [], - "source": [ - "import time\n", - "\n", - "for status in operation.wait_bar():\n", - " time.sleep(30)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4cg868HzqOx5" - }, - "source": [ - "You can cancel your tuning job any time using the `cancel()` method. Uncomment the line below and run the code cell to cancel your job before it finishes." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "oQuJ70_hqJi9" - }, - "outputs": [], - "source": [ - "# operation.cancel()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lqiL0TWDqAPn" - }, - "source": [ - "Once the tuning is complete, you can view the loss curve from the tuning results. The [loss curve](https://generativeai.devsite.corp.google.com/guide/model_tuning_guidance#recommended_configurations) shows how much the model's predictions deviate from the ideal outputs." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "bIiG57xWLhP7" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import pandas as pd\n", - "import seaborn as sns\n", - "\n", - "model = operation.result()\n", - "\n", - "snapshots = pd.DataFrame(model.tuning_task.snapshots)\n", - "\n", - "sns.lineplot(data=snapshots, x = 'epoch', y='mean_loss')\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "rkoQTXb1vSBC" - }, - "source": [ - "## Evaluate your model\n", - "\n", - "You can use the `genai.generate_text` method and specify the name of your model to test your model performance." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "zO0YcuSyxydZ" - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel(model_name=f'tunedModels/{name}')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "UwGrrj6hS_x2" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'56'" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "result = model.generate_content('55')\n", - "result.text" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "YSNB2zjTx5SZ" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'123456'" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "result = model.generate_content('123455')\n", - "result.text" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Y2YVO-m0Ut9H" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'five'" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "result = model.generate_content('four')\n", - "result.text" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "h2MkTR0uTb6U" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'cinq'" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "result = model.generate_content('quatre') # French 4\n", - "result.text # French 5 is \"cinq\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "OruCW1zETsZw" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'IV'" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "result = model.generate_content('III') # Roman numeral 3\n", - "result.text # Roman numeral 4 is IV" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "thDdSuUDUJOx" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'ε…«'" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "result = model.generate_content('δΈƒ') # Japanese 7\n", - "result.text # Japanese 8 is ε…«!" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "HpIA1IFevQQR" - }, - "source": [ - "It really seems to have picked up the task despite the limited examples, but \"next\" is a simple concept, see the [tuning guide](https://ai.google.dev/docs/model_tuning_guidance) for more guidance on improving performance." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nmuQCbTYwIOx" - }, - "source": [ - "## Update the description\n", - "\n", - "You can update the description of your tuned model any time using the `genai.update_tuned_model` method." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9gAVuXT_wG3x" - }, - "outputs": [], - "source": [ - "genai.update_tuned_model(f'tunedModels/{name}', {\"description\":\"This is my model.\"});" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "d-c3YerBxVYs" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'This is my model.'" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model = genai.get_tuned_model(f'tunedModels/{name}')\n", - "\n", - "model.description" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "i_TpwvBB4bQ7" - }, - "source": [ - "## Delete the model\n", - "\n", - "You can clean up your tuned model list by deleting models you no longer need. Use the `genai.delete_tuned_model` method to delete a model. If you canceled any tuning jobs, you may want to delete those as their performance may be unpredictable." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "cepfaUCvVGCo" - }, - "outputs": [], - "source": [ - "genai.delete_tuned_model(f'tunedModels/{name}')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ljEssIshYDEr" - }, - "source": [ - "The model no longer exists:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "kN_bkut_4ayL" - }, - "outputs": [], - "source": [ - "try:\n", - " m = genai.get_tuned_model(f'tunedModels/{name}')\n", - " print(m)\n", - "except Exception as e:\n", - " print(f\"{type(e)}: {e}\")" - ] + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: Tuning Quickstart with Python" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lEXQ3OwKIa-O" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Jp_CKyzxUqx6" + }, + "source": [ + "In this notebook, you'll learn how to get started with model tuning." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4x-2x8A_vi9g" + }, + "source": [ + "## What is model tuning?\n", + "\n", + "Prompt design strategies such as few shot prompting may not always produce the results you need. Use model tuning to improve a model's performance on specific tasks or help the model adhere to specific output requirements when instructions aren't sufficient and you have a set of examples that demonstrate the outputs you want.\n", + "\n", + "The goal of model tuning is to further improve the performance of the model for your specific task. Model tuning works by providing the model with a training dataset containing many examples of the task. For niche tasks, you can get significant improvements in model performance by tuning the model on a modest number of examples.\n", + "\n", + "Your training data should be structured as examples with prompt inputs and expected response outputs. The goal is to teach the model to mimic the wanted behavior or task, by giving it many examples illustrating that behavior or task.\n", + "\n", + "You can also tune models using example data directly in Google AI Studio." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "SWxKvwd-MSIV" + }, + "source": [ + "## OAuth Authentication" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JjS8Zy1ojIgc" + }, + "source": [ + "Unlike the other quickstarts which use API keys, model tuning uses OAuth.\n", + "\n", + "This tutorial assumes you have completed the [OAuth Quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication_with_OAuth.ipynb) and you have your client secret saved as `CLIENT_SECRET` in the Colab secrets manager.\n", + "\n", + "> Important: **Don't just click the link this command prints**. That will fail. Follow the instructions and copy the `gcloud` command it prints to your local machine and run it there, then paste the output from your local machine back\n", + "here." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9FUwyB_MJ0-2" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "import pathlib\n", + "pathlib.Path('client_secret.json').write_text(userdata.get('CLIENT_SECRET'))\n", + "\n", + "# Use `--no-browser` in colab\n", + "!gcloud auth application-default login --no-browser --client-id-file client_secret.json --scopes='https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/generative-language.tuning'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "cbcf72bcb56d" + }, + "outputs": [], + "source": [ + "!pip install -q -U google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "8enrppafJPCX" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "P-MYZECwlRCq" + }, + "source": [ + "You can check your existing tuned models with the `genai.list_tuned_model` method." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "XyWzoYFxU4r6" + }, + "outputs": [], + "source": [ + "for i, m in zip(range(5), genai.list_tuned_models()):\n", + " print(m.name)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "BhkXRzciv3Dp" + }, + "source": [ + "## Create tuned model" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "OO8VZYAinLWc" + }, + "source": [ + "To create a tuned model, you need to pass your dataset to the model in the `genai.create_tuned_model` method. You can do this be directly defining the input and output values in the call or importing from a file into a dataframe to pass to the method.\n", + "\n", + "For this example, you will tune a model to generate the next number in the sequence. For example, if the input is `1`, the model should output `2`. If the input is `one hundred`, the output should be `one hundred one`.\n", + "\n", + "**Note**: In general, you need between 100 and 500 examples to significantly change the behavior of the model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "w-EBSe9wTbLB" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Model(name='models/gemini-1.0-pro-001',\n", + " base_model_id='',\n", + " version='001',\n", + " display_name='Gemini 1.0 Pro 001 (Tuning)',\n", + " description=('The best model for scaling across a wide range of tasks. This is a stable '\n", + " 'model that supports tuning.'),\n", + " input_token_limit=30720,\n", + " output_token_limit=2048,\n", + " supported_generation_methods=['generateContent', 'countTokens', 'createTunedModel'],\n", + " temperature=0.9,\n", + " top_p=1.0,\n", + " top_k=1)" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" } - ], - "metadata": { - "colab": { - "name": "Tuning.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" + ], + "source": [ + "base_model = [\n", + " m for m in genai.list_models()\n", + " if \"createTunedModel\" in m.supported_generation_methods][0]\n", + "base_model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "baHjHh1oTTTC" + }, + "outputs": [], + "source": [ + "import random\n", + "\n", + "name = f'generate-num-{random.randint(0,10000)}'\n", + "operation = genai.create_tuned_model(\n", + " # You can use a tuned model here too. Set `source_model=\"tunedModels/...\"`\n", + " source_model=base_model.name,\n", + " training_data=[\n", + " {\n", + " 'text_input': '1',\n", + " 'output': '2',\n", + " },{\n", + " 'text_input': '3',\n", + " 'output': '4',\n", + " },{\n", + " 'text_input': '-3',\n", + " 'output': '-2',\n", + " },{\n", + " 'text_input': 'twenty two',\n", + " 'output': 'twenty three',\n", + " },{\n", + " 'text_input': 'two hundred',\n", + " 'output': 'two hundred one',\n", + " },{\n", + " 'text_input': 'ninety nine',\n", + " 'output': 'one hundred',\n", + " },{\n", + " 'text_input': '8',\n", + " 'output': '9',\n", + " },{\n", + " 'text_input': '-98',\n", + " 'output': '-97',\n", + " },{\n", + " 'text_input': '1,000',\n", + " 'output': '1,001',\n", + " },{\n", + " 'text_input': '10,100,000',\n", + " 'output': '10,100,001',\n", + " },{\n", + " 'text_input': 'thirteen',\n", + " 'output': 'fourteen',\n", + " },{\n", + " 'text_input': 'eighty',\n", + " 'output': 'eighty one',\n", + " },{\n", + " 'text_input': 'one',\n", + " 'output': 'two',\n", + " },{\n", + " 'text_input': 'three',\n", + " 'output': 'four',\n", + " },{\n", + " 'text_input': 'seven',\n", + " 'output': 'eight',\n", + " }\n", + " ],\n", + " id = name,\n", + " epoch_count = 100,\n", + " batch_size=4,\n", + " learning_rate=0.001,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-As7ayWDK1w8" + }, + "source": [ + "Your tuned model is immediately added to the list of tuned models, but its status is set to \"creating\" while the model is tuned." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "su64KgY4Uztj" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "TunedModel(name='tunedModels/generate-num-5392',\n", + " source_model='models/gemini-1.0-pro-001',\n", + " base_model='models/gemini-1.0-pro-001',\n", + " display_name='',\n", + " description='',\n", + " temperature=0.9,\n", + " top_p=1.0,\n", + " top_k=1,\n", + " state=,\n", + " create_time=datetime.datetime(2024, 3, 16, 0, 41, 42, 702621, tzinfo=datetime.timezone.utc),\n", + " update_time=datetime.datetime(2024, 3, 16, 0, 41, 42, 702621, tzinfo=datetime.timezone.utc),\n", + " tuning_task=TuningTask(start_time=datetime.datetime(2024, 3, 16, 0, 41, 43, 81144, tzinfo=datetime.timezone.utc),\n", + " complete_time=None,\n", + " snapshots=[],\n", + " hyperparameters=Hyperparameters(epoch_count=100,\n", + " batch_size=4,\n", + " learning_rate=0.001)))" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model = genai.get_tuned_model(f'tunedModels/{name}')\n", + "\n", + "model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "EUodUwZkKPi-" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.state" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Pi8X5vkQv-3_" + }, + "source": [ + "### Check tuning progress" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tWI-vAh4LJIz" + }, + "source": [ + "Use `metadata` to check the state:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "g08vqtxYLMxT" + }, + "outputs": [], + "source": [ + "operation.metadata" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3lQ6gSMgK-kz" + }, + "source": [ + "Wait for the training to finish using `operation.result()`, or `operation.wait_bar()`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "SOUowIv1HgSE" + }, + "outputs": [], + "source": [ + "import time\n", + "\n", + "for status in operation.wait_bar():\n", + " time.sleep(30)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4cg868HzqOx5" + }, + "source": [ + "You can cancel your tuning job any time using the `cancel()` method. Uncomment the line below and run the code cell to cancel your job before it finishes." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "oQuJ70_hqJi9" + }, + "outputs": [], + "source": [ + "# operation.cancel()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lqiL0TWDqAPn" + }, + "source": [ + "Once the tuning is complete, you can view the loss curve from the tuning results. The [loss curve](https://generativeai.devsite.corp.google.com/guide/model_tuning_guidance#recommended_configurations) shows how much the model's predictions deviate from the ideal outputs." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "bIiG57xWLhP7" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "import seaborn as sns\n", + "\n", + "model = operation.result()\n", + "\n", + "snapshots = pd.DataFrame(model.tuning_task.snapshots)\n", + "\n", + "sns.lineplot(data=snapshots, x = 'epoch', y='mean_loss')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rkoQTXb1vSBC" + }, + "source": [ + "## Evaluate your model\n", + "\n", + "You can use the `genai.generate_text` method and specify the name of your model to test your model performance." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "zO0YcuSyxydZ" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel(model_name=f'tunedModels/{name}')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "UwGrrj6hS_x2" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'56'" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" } + ], + "source": [ + "result = model.generate_content('55')\n", + "result.text" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "YSNB2zjTx5SZ" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'123456'" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = model.generate_content('123455')\n", + "result.text" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Y2YVO-m0Ut9H" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'five'" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = model.generate_content('four')\n", + "result.text" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "h2MkTR0uTb6U" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'cinq'" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = model.generate_content('quatre') # French 4\n", + "result.text # French 5 is \"cinq\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "OruCW1zETsZw" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'IV'" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = model.generate_content('III') # Roman numeral 3\n", + "result.text # Roman numeral 4 is IV" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "thDdSuUDUJOx" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'ε…«'" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = model.generate_content('δΈƒ') # Japanese 7\n", + "result.text # Japanese 8 is ε…«!" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HpIA1IFevQQR" + }, + "source": [ + "It really seems to have picked up the task despite the limited examples, but \"next\" is a simple concept, see the [tuning guide](https://ai.google.dev/docs/model_tuning_guidance) for more guidance on improving performance." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nmuQCbTYwIOx" + }, + "source": [ + "## Update the description\n", + "\n", + "You can update the description of your tuned model any time using the `genai.update_tuned_model` method." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9gAVuXT_wG3x" + }, + "outputs": [], + "source": [ + "genai.update_tuned_model(f'tunedModels/{name}', {\"description\":\"This is my model.\"});" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "d-c3YerBxVYs" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'This is my model.'" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model = genai.get_tuned_model(f'tunedModels/{name}')\n", + "\n", + "model.description" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "i_TpwvBB4bQ7" + }, + "source": [ + "## Delete the model\n", + "\n", + "You can clean up your tuned model list by deleting models you no longer need. Use the `genai.delete_tuned_model` method to delete a model. If you canceled any tuning jobs, you may want to delete those as their performance may be unpredictable." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "cepfaUCvVGCo" + }, + "outputs": [], + "source": [ + "genai.delete_tuned_model(f'tunedModels/{name}')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ljEssIshYDEr" + }, + "source": [ + "The model no longer exists:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "kN_bkut_4ayL" + }, + "outputs": [], + "source": [ + "try:\n", + " m = genai.get_tuned_model(f'tunedModels/{name}')\n", + " print(m)\n", + "except Exception as e:\n", + " print(f\"{type(e)}: {e}\")" + ] + } + ], + "metadata": { + "colab": { + "name": "Tuning.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" }, - "nbformat": 4, - "nbformat_minor": 0 + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/Video.ipynb b/quickstarts/Video.ipynb index ba0cc69eb..ee0069b5d 100644 --- a/quickstarts/Video.ipynb +++ b/quickstarts/Video.ipynb @@ -1,345 +1,304 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "084u8u0DpBlo" - }, - "source": [ - "# Gemini API: Prompting with Video" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "wnQ_LVlzIeXo" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "q7QvXQMrIhuZ" - }, - "source": [ - "This notebook provides a quick example of how to prompt Gemini 1.5 Pro using a video file. In this case, you'll use a short clip of [Big Buck Bunny](https://peach.blender.org/about/)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "TwpXMTnpsoHC" - }, - "outputs": [], - "source": [ - "!pip install -U google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ATIbQM0NHhkj" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ngyzKAu3Nw5k" - }, - "source": [ - "### Authentication Overview\n", - "\n", - "**Important:** The File API uses API keys for authentication and access. Uploaded files are associated with the API key's cloud project. Unlike other Gemini APIs that use API keys, your API key also grants access data you've uploaded to the File API, so take extra care in keeping your API key secure. For best practices on securing API keys, refer to Google's [documentation](https://support.google.com/googleapi/answer/6310037)." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "l8g4hTRotheH" - }, - "source": [ - "### Setup your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "d6lYXRcjthKV" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "MNvhBdoDFnTC" - }, - "source": [ - "## Upload a video to the Files API\n", - "\n", - "The Gemini API accepts video file formats directly. The File API accepts files under 2GB in size and can store up to 20GB of files per project. Files last for 2 days and cannot be downloaded from the API. For the example, you will use the short film \"Big Buck Bunny\".\n", - "\n", - "> \"Big Buck Bunny\" is (c) copyright 2008, Blender Foundation / www.bigbuckbunny.org and [licensed](https://peach.blender.org/about/) under the [Creative Commons Attribution 3.0](http://creativecommons.org/licenses/by/3.0/) License.\n", - "\n", - "Note: You can also [upload your own files](https://github.com/google-gemini/cookbook/blob/main/examples/Upload_files_to_Colab.ipynb) to use." - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "id": "V4XeFdX1rxaE" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--2024-05-14 14:10:23-- https://download.blender.org/peach/bigbuckbunny_movies/BigBuckBunny_320x180.mp4\n", - "Resolving download.blender.org (download.blender.org)... 104.22.65.163, 104.22.64.163, 172.67.14.163, ...\n", - "Connecting to download.blender.org (download.blender.org)|104.22.65.163|:443... connected.\n", - "HTTP request sent, awaiting response... 200 OK\n", - "Length: 64657027 (62M) [video/mp4]\n", - "Saving to: β€˜BigBuckBunny_320x180.mp4.2’\n", - "\n", - "BigBuckBunny_320x18 100%[===================>] 61.66M 39.0MB/s in 1.6s \n", - "\n", - "2024-05-14 14:10:25 (39.0 MB/s) - β€˜BigBuckBunny_320x180.mp4.2’ saved [64657027/64657027]\n", - "\n" - ] - } - ], - "source": [ - "!wget https://download.blender.org/peach/bigbuckbunny_movies/BigBuckBunny_320x180.mp4" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": { - "id": "_HzrDdp2Q1Cu" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Uploading file...\n", - "Completed upload: https://generativelanguage.googleapis.com/v1beta/files/2kefwb3adzuv\n" - ] - } - ], - "source": [ - "video_file_name = \"BigBuckBunny_320x180.mp4\"\n", - "\n", - "print(f\"Uploading file...\")\n", - "video_file = genai.upload_file(path=video_file_name)\n", - "print(f\"Completed upload: {video_file.uri}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "oOZmTUb4FWOa" - }, - "source": [ - "## Get File\n", - "\n", - "After uploading the file, you can verify the API has successfully received the files by calling `files.get`.\n", - "\n", - "`files.get` lets you see the file uploaded to the File API that are associated with the Cloud project your API key belongs to. Only the `name` (and by extension, the `uri`) are unique." - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": { - "id": "SHMVCWHkFhJW" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Waiting for video to be processed.\n", - "Waiting for video to be processed.\n", - "Waiting for video to be processed.\n", - "Video processing complete: https://generativelanguage.googleapis.com/v1beta/files/2kefwb3adzuv\n" - ] - } - ], - "source": [ - "import time\n", - "\n", - "while video_file.state.name == \"PROCESSING\":\n", - " print('Waiting for video to be processed.')\n", - " time.sleep(10)\n", - " video_file = genai.get_file(video_file.name)\n", - "\n", - "if video_file.state.name == \"FAILED\":\n", - " raise ValueError(video_file.state.name)\n", - "print(f'Video processing complete: ' + video_file.uri)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "EPPOECHzsIGJ" - }, - "source": [ - "## Generate Content\n", - "\n", - "After the video has been uploaded, you can make `GenerateContent` requests that reference the File API URI." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "rKkc5bH5ct18" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Making LLM inference request...\n", - "The video begins with a panoramic view of a lush green field. A cloud with hues of pink and yellow glides across the sky as the camera pans to focus on a stream flowing through the field. The title card \"Big Buck Bunny\" appears next.\n", - "\n", - "A large white rabbit, the protagonist, emerges from its burrow and stretches. It takes in the beautiful day, smelling flowers and enjoying the sunshine. The rabbit sees a red apple on the ground and excitedly picks it up. It walks towards a group of smaller animals: a chinchilla, a fox, and a squirrel, who are also enjoying the day. The rabbit wants to share the apple but the squirrel throws it away. The rabbit gets sad and starts to eat grass.\n", - "\n", - "Seeing the rabbit's sadness, the squirrel comes up with a plan to tease it. The squirrel throws an apple at the rabbit's head. The rabbit gets angry and chases after the squirrel. They run around the tree, with the chinchilla and fox looking on. The squirrel then throws a spiky ball at the rabbit, further infuriating it. The rabbit chases the squirrel again, eventually catching it. He seems about to punish the squirrel, but instead, he gives it a friendly hug.\n", - "\n", - "The squirrel doesn't learn its lesson and starts to tease the rabbit again by throwing its food. This time, the rabbit decides to use its ingenuity to teach the squirrel a lesson. It builds a bow and arrow, shoots the squirrel's flying machine down, and then traps the squirrel in a net made from vines.\n", - "\n", - "The video ends with a list of the film's credits, showing the names of the individuals and teams who worked on the production. The squirrel then flies across the credits. \n", - "\n" - ] - } - ], - "source": [ - "# Create the prompt.\n", - "prompt = \"Describe this video.\"\n", - "\n", - "# Set the model to Gemini 1.5 Pro.\n", - "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-pro-latest\")\n", - "\n", - "# Make the LLM request.\n", - "print(\"Making LLM inference request...\")\n", - "response = model.generate_content([prompt, video_file],\n", - " request_options={\"timeout\": 600})\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IrPDYdQSKTg4" - }, - "source": [ - "## Delete File\n", - "\n", - "Files are automatically deleted after 2 days or you can manually delete them using `files.delete()`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ggoi6wibct18" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Deleted file https://generativelanguage.googleapis.com/v1beta/files/2kefwb3adzuv\n" - ] - } - ], - "source": [ - "genai.delete_file(video_file.name)\n", - "print(f'Deleted file {video_file.uri}')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "K5oUCqb6IUnH" - }, - "source": [ - "## Learning more\n", - "\n", - "The File API lets you upload a variety of multimodal MIME types, including images, audio, and video formats. The File API handles inputs that can be used to generate content with [`model.generateContent`](https://ai.google.dev/api/rest/v1/models/generateContent) or [`model.streamGenerateContent`](https://ai.google.dev/api/rest/v1/models/streamGenerateContent).\n", - "\n", - "The File API accepts files under 2GB in size and can store up to 20GB of files per project. Files last for 2 days and cannot be downloaded from the API.\n", - "\n", - "* Learn more about the [File API](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb) with the quickstart.\n", - "\n", - "* Learn more about prompting with [media files](https://ai.google.dev/tutorials/prompting_with_media) in the docs, including the supported formats and maximum length." - ] - } - ], - "metadata": { - "colab": { - "name": "Video.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] }, - "nbformat": 4, - "nbformat_minor": 0 + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "084u8u0DpBlo" + }, + "source": [ + "# Gemini API: Prompting with Video" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "wnQ_LVlzIeXo" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "q7QvXQMrIhuZ" + }, + "source": [ + "This notebook provides a quick example of how to prompt Gemini 1.5 Pro using a video file. In this case, you'll use a short clip of [Big Buck Bunny](https://peach.blender.org/about/)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TwpXMTnpsoHC" + }, + "outputs": [], + "source": [ + "!pip install -U google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ATIbQM0NHhkj" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ngyzKAu3Nw5k" + }, + "source": [ + "### Authentication Overview\n", + "\n", + "**Important:** The File API uses API keys for authentication and access. Uploaded files are associated with the API key's cloud project. Unlike other Gemini APIs that use API keys, your API key also grants access data you've uploaded to the File API, so take extra care in keeping your API key secure. For best practices on securing API keys, refer to Google's [documentation](https://support.google.com/googleapi/answer/6310037)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "l8g4hTRotheH" + }, + "source": [ + "### Setup your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "d6lYXRcjthKV" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "MNvhBdoDFnTC" + }, + "source": [ + "## Upload a video to the Files API\n", + "\n", + "The Gemini API accepts video file formats directly. The File API accepts files under 2GB in size and can store up to 20GB of files per project. Files last for 2 days and cannot be downloaded from the API. For the example, you will use the short film \"Big Buck Bunny\".\n", + "\n", + "> \"Big Buck Bunny\" is (c) copyright 2008, Blender Foundation / www.bigbuckbunny.org and [licensed](https://peach.blender.org/about/) under the [Creative Commons Attribution 3.0](http://creativecommons.org/licenses/by/3.0/) License.\n", + "\n", + "Note: You can also [upload your own files](https://github.com/google-gemini/cookbook/blob/main/examples/Upload_files_to_Colab.ipynb) to use." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "V4XeFdX1rxaE", + "tags": [] + }, + "outputs": [], + "source": [ + "!wget https://download.blender.org/peach/bigbuckbunny_movies/BigBuckBunny_320x180.mp4" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "_HzrDdp2Q1Cu", + "tags": [] + }, + "outputs": [], + "source": [ + "video_file_name = \"BigBuckBunny_320x180.mp4\"\n", + "\n", + "print(f\"Uploading file...\")\n", + "video_file = genai.upload_file(path=video_file_name)\n", + "print(f\"Completed upload: {video_file.uri}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "oOZmTUb4FWOa" + }, + "source": [ + "## Get File\n", + "\n", + "After uploading the file, you can verify the API has successfully received the files by calling `files.get`.\n", + "\n", + "`files.get` lets you see the file uploaded to the File API that are associated with the Cloud project your API key belongs to. Only the `name` (and by extension, the `uri`) are unique." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "SHMVCWHkFhJW", + "tags": [] + }, + "outputs": [], + "source": [ + "import time\n", + "\n", + "while video_file.state.name == \"PROCESSING\":\n", + " print('Waiting for video to be processed.')\n", + " time.sleep(10)\n", + " video_file = genai.get_file(video_file.name)\n", + "\n", + "if video_file.state.name == \"FAILED\":\n", + " raise ValueError(video_file.state.name)\n", + "print(f'Video processing complete: ' + video_file.uri)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EPPOECHzsIGJ" + }, + "source": [ + "## Generate Content\n", + "\n", + "After the video has been uploaded, you can make `GenerateContent` requests that reference the File API URI." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Create the prompt.\n", + "prompt = \"Describe this video.\"\n", + "\n", + "# Set the model to Gemini 1.5 Flash.\n", + "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-flash-latest\")\n", + "\n", + "# Make the LLM request.\n", + "print(\"Making LLM inference request...\")\n", + "response = model.generate_content([prompt, video_file],\n", + " request_options={\"timeout\": 600})\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IrPDYdQSKTg4" + }, + "source": [ + "## Delete File\n", + "\n", + "Files are automatically deleted after 2 days or you can manually delete them using `files.delete()`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ggoi6wibct18", + "tags": [] + }, + "outputs": [], + "source": [ + "genai.delete_file(video_file.name)\n", + "print(f'Deleted file {video_file.uri}')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "K5oUCqb6IUnH" + }, + "source": [ + "## Learning more\n", + "\n", + "The File API lets you upload a variety of multimodal MIME types, including images, audio, and video formats. The File API handles inputs that can be used to generate content with [`model.generateContent`](https://ai.google.dev/api/rest/v1/models/generateContent) or [`model.streamGenerateContent`](https://ai.google.dev/api/rest/v1/models/streamGenerateContent).\n", + "\n", + "The File API accepts files under 2GB in size and can store up to 20GB of files per project. Files last for 2 days and cannot be downloaded from the API.\n", + "\n", + "* Learn more about the [File API](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb) with the quickstart.\n", + "\n", + "* Learn more about prompting with [media files](https://ai.google.dev/tutorials/prompting_with_media) in the docs, including the supported formats and maximum length." + ] + } + ], + "metadata": { + "colab": { + "name": "Video.ipynb", + "toc_visible": true + }, + "environment": { + "kernel": "python3", + "name": "tf2-cpu.2-11.m120", + "type": "gcloud", + "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" + }, + "kernelspec": { + "display_name": "Python 3 (Local)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/quickstarts/file-api/.gitignore b/quickstarts/file-api/.gitignore deleted file mode 100644 index 9e48ceb11..000000000 --- a/quickstarts/file-api/.gitignore +++ /dev/null @@ -1,4 +0,0 @@ -venv/ -.env -node_modules/ -.DS_STORE diff --git a/quickstarts/file-api/README.md b/quickstarts/file-api/README.md deleted file mode 100644 index 0f9676ff8..000000000 --- a/quickstarts/file-api/README.md +++ /dev/null @@ -1,56 +0,0 @@ -# Gemini File API Sample Client Code - -## Background -The Gemini File API provides a simple way for developers to upload files and use them with the Gemini API in multimodal scenarios. This repository shows how to use the File API to upload an image and include it in a `GenerateContent` call to the Gemini API. - - -> [!IMPORTANT] -> The File API is currently in beta and is [only available in certain regions](https://ai.google.dev/available_regions). - -## Quickstarts -Ready to get started? Learn the essentials of uploading files and using them in GenerateContent requests to the Gemini API: - -[File API Colab](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb) - -[Audio Colab](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Audio.ipynb) - -[Video Colab](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Video.ipynb) - - -## Python Sample -``` -# Prepare a virtual environment for Python. -python3 -m venv venv -source venv/bin/activate - -# Add API key to .env file -touch .env -echo "GOOGLE_API_KEY='YOUR_API_KEY'" >> .env - -# Install dependencies. -pip3 install -U -r requirements.txt - -# Run the sample code. -python3 sample.py -``` - -## Node.js Sample -``` -# Make sure npm is installed first. - -# Add API key to .env file -touch .env -echo "GOOGLE_API_KEY='YOUR_API_KEY'" >> .env - -# Install dependencies. -npm install - -# Run the sample code. -npm start -``` - -## cURL Bash Script Sample -The following script will upload a file given the file path. -``` -bash ./sample.sh -a "" -i "sample_data/gemini_logo.png" -d "Gemini logo" -``` diff --git a/quickstarts/file-api/package-lock.json b/quickstarts/file-api/package-lock.json deleted file mode 100644 index 407d9fd83..000000000 --- a/quickstarts/file-api/package-lock.json +++ /dev/null @@ -1,519 +0,0 @@ -{ - 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"name": "file-api-client-samples", - "version": "1.0.0", - "description": "Sample code to use the File API and make Gemini API requests.", - "private": true, - "scripts": { - "start": "node sample.js" - }, - "dependencies": { - "dotenv": "^16.4.5", - "googleapis": "^134.0.0", - "mime-types": "^2.1.35" - } -} diff --git a/quickstarts/file-api/requirements.txt b/quickstarts/file-api/requirements.txt deleted file mode 100644 index 3004806de..000000000 --- a/quickstarts/file-api/requirements.txt +++ /dev/null @@ -1,3 +0,0 @@ -google-api-python-client -google-generativeai -python-dotenv diff --git a/quickstarts/file-api/sample.js b/quickstarts/file-api/sample.js deleted file mode 100644 index 192223ca1..000000000 --- a/quickstarts/file-api/sample.js +++ /dev/null @@ -1,50 +0,0 @@ -const dotenv = require('dotenv'); -const fs = require('fs'); -const {google} = require('googleapis'); -const mime = require('mime-types'); - -// Load environment variables from .env file -dotenv.config({ path: '.env' }); -const API_KEY = process.env.GOOGLE_API_KEY; -const GENAI_DISCOVERY_URL = `https://generativelanguage.googleapis.com/$discovery/rest?version=v1beta&key=${API_KEY}`; - - -async function run(filePath, fileDisplayName) { - // Initialize API Client - const genaiService = await google.discoverAPI({url: GENAI_DISCOVERY_URL}); - const auth = new google.auth.GoogleAuth().fromAPIKey(API_KEY); - - // Prepare file to upload to GenAI File API - const media = { - mimeType: mime.lookup(filePath), - body: fs.createReadStream(filePath), - }; - var body = {"file": {"displayName": fileDisplayName}}; - try { - // Upload the file - const createFileResponse = await genaiService.media.upload({ - media: media, auth: auth, requestBody:body}); - const file = createFileResponse.data.file; - const fileUri = file.uri; - console.log("Uploaded file: " + fileUri); - - // Make Gemini 1.5 API LLM call - const prompt = "Describe the image with a creative description"; - const model = "models/gemini-1.5-pro-latest"; - const contents = {'contents': [{ - 'parts':[ - {'text': prompt}, - {'file_data': {'file_uri': fileUri, 'mime_type': file.mimeType}}] - }]} - const generateContentResponse = await genaiService.models.generateContent({ - model: model, requestBody: contents, auth: auth}); - console.log(JSON.stringify(generateContentResponse.data)); - } - catch (err) { - throw err; - } -} - -filePath = "sample_data/gemini_logo.png"; -fileDisplayName = "Gemini logo"; -run(filePath, fileDisplayName); diff --git a/quickstarts/file-api/sample.py b/quickstarts/file-api/sample.py deleted file mode 100644 index 3e8c09ce0..000000000 --- a/quickstarts/file-api/sample.py +++ /dev/null @@ -1,32 +0,0 @@ -import google.generativeai as genai -import os -from dotenv import load_dotenv - -# Load environment variables from .env file -load_dotenv() -api_key = os.environ["GOOGLE_API_KEY"] - -# Initialize Google API Client -genai.configure(api_key=api_key) - -# Prepare file to upload to GenAI File API -file_path = "sample_data/gemini_logo.png" -display_name = "Gemini Logo" -file_response = genai.upload_file(path=file_path, - display_name=display_name) -print(f"Uploaded file {file_response.display_name} as: {file_response.uri}") - -# Verify the file is uploaded to the API -get_file = genai.get_file(name=file_response.name) -print(f"Retrieved file {get_file.display_name} as: {get_file.uri}") - -# Make Gemini 1.5 API LLM call -prompt = "Describe the image with a creative description" -model_name = "models/gemini-1.5-pro-latest" -model = genai.GenerativeModel(model_name=model_name) -response = model.generate_content([prompt, file_response]) -print(response) - -# Delete the sample file -genai.delete_file(name=file_response.name) -print(f'Deleted file {file_response.display_name}') diff --git a/quickstarts/file-api/sample.sh b/quickstarts/file-api/sample.sh deleted file mode 100755 index b042d8bda..000000000 --- a/quickstarts/file-api/sample.sh +++ /dev/null @@ -1,70 +0,0 @@ -#!/bin/bash -# -# Upload a file using the GenAI File API via curl. -api_key="" -input_file="" -display_name="" - -while getopts a:i:d: flag -do - case "${flag}" in - a) api_key=${OPTARG};; - i) input_file=${OPTARG};; - d) display_name=${OPTARG};; - esac -done - -BASE_URL="https://generativelanguage.googleapis.com" - -CHUNK_SIZE=8388608 # 8 MiB -MIME_TYPE=$(file -b --mime-type "${input_file}") -NUM_BYTES=$(wc -c < "${input_file}") - -echo "Starting upload of '${input_file}' to ${BASE_URL}..." -echo " MIME type: '${MIME_TYPE}'" -echo " Size: ${NUM_BYTES} bytes" - -# Initial resumable request defining metadata. -tmp_header_file=$(mktemp /tmp/upload-header.XXX) -curl "${BASE_URL}/upload/v1beta/files?key=${api_key}" \ - -D "${tmp_header_file}" \ - -H "X-Goog-Upload-Protocol: resumable" \ - -H "X-Goog-Upload-Command: start" \ - -H "X-Goog-Upload-Header-Content-Length: ${NUM_BYTES}" \ - -H "X-Goog-Upload-Header-Content-Type: ${MIME_TYPE}" \ - -H "Content-Type: application/json" \ - -d "{'file': {'display_name': '${display_name}'}}" -upload_url=$(grep "x-goog-upload-url: " "${tmp_header_file}" | cut -d" " -f2 | tr -d "\r") -rm "${tmp_header_file}" - -if [[ -z "${upload_url}" ]]; then - echo "Failed initial resumable upload request." - exit 1 -fi - -# Upload the actual bytes. -NUM_CHUNKS=$(((NUM_BYTES + CHUNK_SIZE - 1) / CHUNK_SIZE)) -tmp_chunk_file=$(mktemp /tmp/upload-chunk.XXX) -for i in $(seq 1 ${NUM_CHUNKS}) -do - offset=$((i - 1)) - byte_offset=$((offset * CHUNK_SIZE)) - # Read the actual bytes to the tmp file. - dd skip="${offset}" bs="${CHUNK_SIZE}" count=1 if="${input_file}" of="${tmp_chunk_file}" 2>/dev/null - num_chunk_bytes=$(wc -c < "${tmp_chunk_file}") - upload_command="upload" - if [[ ${i} -eq ${NUM_CHUNKS} ]] ; then - # For the final chunk, specify "finalize". - upload_command="${upload_command}, finalize" - fi - echo " Uploading ${byte_offset} - $((byte_offset + num_chunk_bytes)) of ${NUM_BYTES}..." - curl "${upload_url}" \ - -H "Content-Length: ${num_chunk_bytes}" \ - -H "X-Goog-Upload-Offset: ${byte_offset}" \ - -H "X-Goog-Upload-Command: ${upload_command}" \ - --data-binary "@${tmp_chunk_file}" -done - -rm "${tmp_chunk_file}" - -echo "Upload complete!" diff --git a/quickstarts/file-api/sample_data/gemini_logo.png b/quickstarts/file-api/sample_data/gemini_logo.png deleted file mode 100644 index 44987a8c7fd25449ef5d2f240bae2b3f9a596e44..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 19864 zcmYkkcOaGj`#*jk$ILN8b{rY;vbP9_N+Ma6k-f92>~WGJR4QeU5-nR+h^%ai>^)OP z_U3mTuh-}O{rRUj_qp%q{d``}>v~*|>v26F>Rh=;AiAXwzmd6la^Nejci0SwdQ%76PM`-iyh@|fI>4vj{} zS4dAV=)CK>XXO;!Q&?P--Cbz-WFV-hXY$5fM`1I=2r@mL3S9KLQ?k!O1#zla++rw? z=Cexgpy12NOQn*l^Ye@I?end(`(e4ZGyT3PkD6BdXMJbHI;FHwzvxz5+{Bn;T*>hg zQ5v%F)-iVxWdHR|R&I+8N$C>T|rgmbJr36hOFCYgyG%@=WS{fvU6Vm zd-Qp1$E^Nm3PeK{!3S*zD47r=eh=VAD}I&a$kB~rzfGzj_!KS#S2g4+ON6Xp;M>z) z<&V@%j-hw%!?iW!$iKIgM*h8J%d|xNWsMRdoH*P=G^`dzrg#qSzrL}N(6&Vn-*8j@ zWnga3sfMK4!zH;RBW98HuWt*&@Zf&G|NMcgkDj=*yPHo6BN`3r6or>z5873!G7*XG z{d4W}2_yo>b;Y;REVUynEaYy=_!Yx6eN$6Ywe+W%H_L}}Zr?bXljPrXbK>!r)zb6J z%WupTBm8K6T$=vy@UU9?cMGw#wKe`>M#L72;NHd|Y5d1f$Y;XTy#Mk=DdIJT6y1a1 zN@$TZ{dw}Vk`jaeec#2!rPT;`^5jX45)vE>GYWs@j<0Qxs?dHpc_=RRecjz} zoc$37!gM=2JKKm5rSUi0NF<;2)th5P@gwkRUBkl*Ughz0k0`4rIjjwCxQi)$6_H7|Bs;H2^XfL_ZRgl zPfk93^`!;5_qB6mWO3Oi#_7LLU{n+o6hp$7Ne#2F5782>k%G0=n4;{yOSu#oduZ!) zvcW62+(na>3RVlj*N29()Sn|UAqWy^xkSVejbe<<`25-U6$}oILgXhr%h;*OcC}qe znIAPYG^p{ilB6-i9U9{$?OW|6>*sdLSjN`8!XGCyOc#K$LTdAnjuVXN6Z(hB+8;C*fC8F#K%ZiJyzsfwC5WnyJ{d2eF z<4>y`v%`P2sFoKaT)psB&zKS$34Y5(Zq-YyH;1Ctec$(D*cTuzTa8t_AebFHi|TI z_{iket->+=F@a@Fo}ti<64&V^qE1*32NP4%liSCTub4dJ>^KslHgEt9E(4#M9E(;; zo=a9c7WMS@Uaa&$B47i&Jj4F@%9>N(&EP+2NaPi1!5go_fK=MMrOIa7Gi&wwnP=tm-)KB1n#~bzKUePxDsK= z&N6JP^7EK9{txBlyRGq(x=wufXE5U`Qd+?W+p|NI_}X@SU0t2^x5pQROVj=r5z8MWO?{{8Pi9^&GRx zg!sd!yy$1oo?S_jJD%J?#7_a!pl@Iho08IgAh|+V7D0oYnDTg}8P=dDV7ZlYZ)~`F2FMAZ_M{UkBO;U8hYO-0W0S^ zQekv3Lqu?`2?as>elrKkK~<^!rwmBrE@vhru=cZIj^_5_ty{OOt-1Y4@D&6@Ewyc7 z>>vF1qi?kp7qqT@K*bozYr#GE z;(67WW)qUwc3oGO%fApsa1W3A%Dr=&Y$TX5d#0Y*6gRSaTn3Aq`s|KOhx^Okil*JR zLA1~x*jD)&85yr$spQC@`6*#`I=j1XZ~e7=-gG|hPb@E5Pfzb}nnfoD%;D?flL`_N z5^=q+><~^av=C#<&ibF^EA~?^q&nQdzoB6qOO7m z^T?{K-0ysKF2p`qO#%Jv`Say0i*RpvkhOWhGKv3cDziOof&G;h(OPF&ygU}cnw6R4 zXe;k`I~E-qnY(+u5(CQ*F5yp4wq-E~jszZ<`_DiB#N{3i(QjMFgV8T^X)99|t|R~8 z5q#f#Q2U*A4DmJC%C!9zs}1kD0Z(F7T2eOujE8t)29@0O0^oT2n0lCkGU{jJ5 z{k;wk_U#Jeht>;48(DCDEp$S)qNxc9I|sW|rN`v*?o@#u$v*Sm>NrF28Z_CNb#wP3BSFN;Vkf&`Bpe3iM7`XoXCs&{d zLIPt|$}%aFIDPuGMfxe0YSG#+cGronq?{F)rbqDu{PRf5&-a*Ycm!`!CAh(YGoxv2 zZ4KC6D7hDO3Xz6|U^o1H`=+a_2=5QkkB(Y#WePf4T8}=^AfB)-!0nA%i*k$fVMyMLmJBTISu1(K)jf{-0=CzwD{vo)d1+S&P{Bt#7 zXdOBt3&r$p|DCBoh;O<6ou}u1MRaM6F3lx9`&fq-{H@Dnh-_V2!zS=ywe0Fo_ zR(yPXi2aRck~ocR<}8Z0nVCUr-!F#Fpa=%>PZ7AI#5OxIX8xy=i`Po|*a`4q`eW`F zSgcdQdPgq$k)NMmivMC+ObkQ5q)VNd`}^^VG!&Xt=tlA7th4w67^_;#OW~G|4tuk2 z2BgGUWZ>2wJa_Q zVKmb~b2ZOQNu(!~iu7K+)mKNccks<_+tryi_!+YQaxn#^kxfx3N=HxMn`7#~ICLhz z28j@ht`bMpJsVs&_(~HLotW5?w0BN7CWc96Q$v7nE5u!D<2P~sXQGJhfG?J{4;0rr z&sp)JtZ29qou|_+v2WkLy;agEM;-0+i9ef6tb?)^9t$z6dt$!7(Cy1MfX;Lt@5KUp zM8ShI@4{b)S9Ul*za7Eciiu^PIt`*aheDk>`PlFKWcYC_7VjOk^VG1ot? zPd-uRlcK=Bgb6y5xpu(-0){qdQ zuXhX{MpiBt@Xc@TYVmbxidOPmC&k){5h2r+YdI zWfDZwN|GZweIu3rB`$+@MaJAqLzA{zec)0L4|V}kTG=921lZ3L+ahh>o}_Y*G+&?p zsrE{!JQKrjOWSzLmEC}8@E&-FuZ?1 z_b0cCQ4pa;!vimCX|;jRfM9q2{s?85ZdBfdiSJWw_^GL>;Dgmv@LX0T$ZINiFebOx ze|tKXhD|0)A^ntG@Tp0Y=rOi3s{pg;-aoLwfqTo}NH&Sivq44_WnkvZD<~*9*2=lT zmvHrV18T}`QRNBWZbBYlsXM>B8y>M8T}y;8=$M-Be#HS4 ztQN{^)dRZVSw{!YmI?l8ZwU|QzM8_a~e3jQRs7{aCN@aMX^^E0WszlV5p$o`Ht zo@l|qpqzShvU781mx#hSE~8ZDlN7ucUq^~0h*=V?cI4R`T$Ny|`|{FOBs_EO%a<>N zx8vfvJBq zYQ9Up^GOmv

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\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "JMNKdTpTGZET" - }, - "source": [ - "This notebook provides quick code examples that show you how to get started generating embeddings using `curl`.\n", - "\n", - "You can run this in Google Colab, or you can copy/paste the `curl` commands into your terminal.\n", - "\n", - "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "id": "R-Vw_mOM_WD0" - }, - "outputs": [], - "source": [ - "import os\n", - "from google.colab import userdata" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "id": "wCkLTpb3oTXE" - }, - "outputs": [], - "source": [ - "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tjGqGBZ9yARd" - }, - "source": [ - "## Embed content\n", - "\n", - "Call the `embed_content` method with the `text-embedding-004` model to generate text embeddings:" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "id": "eA7I_Ww8IETn" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"embedding\": {\n", - " \"values\": [\n", - " 0.013168523,\n", - " -0.008711934,\n", - " -0.046782676,\n", - " 0.00069968984,\n", - " -0.009518873,\n", - " -0.008720178,\n", - " 0.060103577,\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/text-embedding-004:embedContent?key=$GOOGLE_API_KEY\" \\\n", - "-H 'Content-Type: application/json' \\\n", - "-d '{\"model\": \"models/text-embedding-004\",\n", - " \"content\": {\n", - " \"parts\":[{\n", - " \"text\": \"Hello world\"}]}, }' 2> /dev/null | head" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "x7ngWdZ7yDHp" - }, - "source": [ - "# Batch embed content\n", - "\n", - "You can embed a list of multiple prompts with one API call for efficiency.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "id": "Z0b35xv5Ja_d" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"embeddings\": [\n", - " {\n", - " \"values\": [\n", - " -0.010632277,\n", - " 0.019375855,\n", - " 0.0209652,\n", - " 0.0007706424,\n", - " -0.061464064,\n", - "--\n", - " -0.0071538696,\n", - " -0.028534694\n", - " ]\n", - " },\n", - " {\n", - " \"values\": [\n", - " 0.018467998,\n", - " 0.0054281196,\n", - " -0.017658804,\n", - " 0.013859266,\n", - " 0.053418662,\n", - "--\n", - " 0.026714385,\n", - " 0.0018762538\n", - " ]\n", - " },\n", - " {\n", - " \"values\": [\n", - " 0.05808907,\n", - " 0.020941721,\n", - " -0.108728774,\n", - " -0.04039259,\n", - " -0.04440443,\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/text-embedding-004:batchEmbedContents?key=$GOOGLE_API_KEY\" \\\n", - "-H 'Content-Type: application/json' \\\n", - "-d '{\"requests\": [{\n", - " \"model\": \"models/text-embedding-004\",\n", - " \"content\": {\n", - " \"parts\":[{\n", - " \"text\": \"What is the meaning of life?\"}]}, },\n", - " {\n", - " \"model\": \"models/text-embedding-004\",\n", - " \"content\": {\n", - " \"parts\":[{\n", - " \"text\": \"How much wood would a woodchuck chuck?\"}]}, },\n", - " {\n", - " \"model\": \"models/text-embedding-004\",\n", - " \"content\": {\n", - " \"parts\":[{\n", - " \"text\": \"How does the brain work?\"}]}, }, ]}' 2> /dev/null | grep -C 5 values" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nPBk2k4xuql8" - }, - "source": [ - "## Set the output dimensionality\n", - "If you're using `text-embeddings-004`, you can set the `output_dimensionality` parameter to create smaller embeddings.\n", - "\n", - "* `output_dimensionality` truncates the embedding (e.g., `[1, 3, 5]` becomes `[1,3]` when `output_dimensionality=2`).\n" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "id": "ny3bOQK1ut2_" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"embedding\": {\n", - " \"values\": [\n", - " 0.013168523,\n", - " -0.008711934,\n", - " -0.046782676,\n", - " 0.00069968984,\n", - " -0.009518873,\n", - " -0.008720178,\n", - " 0.060103577,\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/text-embedding-004:embedContent?key=$GOOGLE_API_KEY\" \\\n", - "-H 'Content-Type: application/json' \\\n", - "-d '{\"model\": \"models/text-embedding-004\",\n", - " \"output_dimensionality\":256,\n", - " \"content\": {\n", - " \"parts\":[{\n", - " \"text\": \"Hello world\"}]}, }' 2> /dev/null | head" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ObAdUvlk9x05" - }, - "source": [ - "## Use `task_type` to provide a hint to the model how you'll use the embeddings\n", - "\n", - "Let's look at all the parameters the embed_content method takes. There are four:\n", - "\n", - "* `model`: Required. Must be `models/embedding-001`.\n", - "* `content`: Required. The content that you would like to embed.\n", - "* `task_type`: Optional. The task type for which the embeddings will be used. See below for possible values.\n", - "* `title`: The given text is a document from a corpus being searched. Optionally, set the `title` parameter with the title of the document. Can only be set when `task_type` is `RETRIEVAL_DOCUMENT`.\n", - "\n", - "`task_type` is an optional parameter that provides a hint to the API about how you intend to use the embeddings in your application.\n", - "\n", - "The following task_type parameters are accepted:\n", - "\n", - "* `TASK_TYPE_UNSPECIFIED`: If you do not set the value, it will default to retrieval_query.\n", - "* `RETRIEVAL_QUERY` : The given text is a query in a search/retrieval setting.\n", - "* `RETRIEVAL_DOCUMENT`: The given text is a document from the corpus being searched.\n", - "* `SEMANTIC_SIMILARITY`: The given text will be used for Semantic Textual Similarity (STS).\n", - "* `CLASSIFICATION`: The given text will be classified.\n", - "* `CLUSTERING`: The embeddings will be used for clustering.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "id": "NwzsJmRrAo-t" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"embedding\": {\n", - " \"values\": [\n", - " 0.060187872,\n", - " -0.031515103,\n", - " -0.03244149,\n", - " -0.019341845,\n", - " 0.057285223,\n", - " 0.037159503,\n", - " 0.035636507,\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/embedding-001:embedContent?key=$GOOGLE_API_KEY\" \\\n", - "-H 'Content-Type: application/json' \\\n", - "-d '{\"model\": \"models/text-embedding-004\",\n", - " \"content\": {\n", - " \"parts\":[{\n", - " \"text\": \"Hello world\"}]},\n", - " \"task_type\": \"RETRIEVAL_DOCUMENT\",\n", - " \"title\": \"My title\"}' 2> /dev/null | head" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "jXkRYBhbB_b2" - }, - "source": [ - "## Learning more\n", - "\n", - "* Learn more about text-embeddings-004 [here](https://developers.googleblog.com/2024/04/gemini-15-pro-in-public-preview-with-new-features.html).\n", - "* See the [REST API reference](https://ai.google.dev/api/rest) to learn more.\n", - "* Explore more examples in the cookbook.\n" - ] - } - ], - "metadata": { - "colab": { - "name": "Embeddings_REST.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} diff --git a/quickstarts/rest/Function_calling_REST.ipynb b/quickstarts/rest/Function_calling_REST.ipynb deleted file mode 100644 index cb89b5c36..000000000 --- a/quickstarts/rest/Function_calling_REST.ipynb +++ /dev/null @@ -1,766 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "--TyBtqKrCHg" - }, - "source": [ - "# Gemini API: Function calling with REST\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4244NXM5rJt5" - }, - "source": [ - "This notebook provides quick code examples that show you how to get started with function calling using `curl`.\n", - "\n", - "You can run this in Google Colab, or you can copy/paste the `curl` commands into your terminal.\n", - "\n", - "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "pxd3u97ZsR5c" - }, - "outputs": [], - "source": [ - "import os\n", - "from google.colab import userdata\n", - "\n", - "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lmdFGEHrrMg8" - }, - "source": [ - "## How function calling works" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nLN0s1FIrepp" - }, - "source": [ - "Function calling lets developers create a description of a function in their code, then pass that description to a language model in a request. The response from the model includes the name of a function that matches the description and the arguments to call it with. Function calling lets you use functions as tools in generative AI applications, and you can define more than one function within a single request. Function calling returns JSON with the name of a function and the arguments to use in your code.\n", - "\n", - "Functions are described using *function declarations*. After you pass a list of\n", - "function declarations in a query to a language model, the model returns an\n", - "object in an [OpenAPI compatible schema](https://spec.openapis.org/oas/v3.0.3#schema)\n", - "format that includes the names of functions and their arguments and tries to\n", - "answer the user query with one of the returned functions. The language model\n", - "understands the purpose of a function by analyzing its function declaration. The\n", - "model doesn't actually call the function. Instead, a developer uses the\n", - "[OpenAPI compatible schema](https://spec.openapis.org/oas/v3.0.3#schema) object\n", - "in the response to call the function that the model returns.\n", - "\n", - "When you implement function calling, you create one or more *function\n", - "declarations*, then add the function declarations to a `tools` object that's\n", - "passed to the model. Each function declaration contains information about one\n", - "function that includes the following:\n", - "\n", - "* Function name\n", - "* Function parameters in an\n", - " [OpenAPI compatible schema](https://spec.openapis.org/oas/v3.0.3#schemawr) format.\n", - " A [select subset](https://ai.google.dev/api/rest/v1beta/Tool#Schema) is\n", - " supported. When using curl, the schema is specified using JSON.\n", - "* Function description (optional). For the best results, we recommend that you\n", - " include a description.\n", - "\n", - "This notebook includes curl examples that make REST calls with the\n", - "`GenerativeModel` class and its methods." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "vnC8xzmOrgt0" - }, - "source": [ - "## Supported models" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ocMX8ebNrj0A" - }, - "source": [ - "The following model supports function calling:\n", - "\n", - "* `gemini-pro`" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "-Z7dneXGrmGo" - }, - "source": [ - "## Function calling cURL samples\n", - "\n", - "When you use cURL, the function and parameter information is included in the\n", - "`tools` element. Each function declaration in the `tools` element contains the\n", - "function name, its parameters specified using the\n", - "[OpenAPI compatible schema](https://spec.openapis.org/oas/v3.0.3#schema), and\n", - "a function description. The following samples demonstrate how to use curl\n", - "commands with function calling:" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zG9ktjHdrpKA" - }, - "source": [ - "### Single-turn curl sample\n", - "\n", - "Single-turn is when you call the language model one time. With function calling,\n", - "a single-turn use case might be when you provide the model a natural language\n", - "query and a list of functions. In this case, the model uses the function\n", - "declaration, which includes the function name, parameters, and description, to\n", - "predict which function to call and the arguments to call it with.\n", - "\n", - "The following curl sample is an example of passing in a description of a\n", - "function that returns information about where a movie is playing. Several\n", - "function declarations are included in the request, such as `find_movies` and\n", - "`find_theaters`." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "id": "vlf-DZSVrIu-" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"candidates\": [\n", - " {\n", - " \"content\": {\n", - " \"parts\": [\n", - " {\n", - " \"functionCall\": {\n", - " \"name\": \"find_theaters\",\n", - " \"args\": {\n", - " \"movie\": \"Barbie\",\n", - " \"location\": \"Mountain View, CA\"\n", - " }\n", - " }\n", - " }\n", - " ],\n", - " \"role\": \"model\"\n", - " },\n", - " \"finishReason\": \"STOP\",\n", - " \"index\": 0,\n", - " \"safetyRatings\": [\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " }\n", - " ]\n", - " }\n", - " ],\n", - " \"promptFeedback\": {\n", - " \"safetyRatings\": [\n", - " {\n", - " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " }\n", - " ]\n", - " }\n", - "}\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -d '{\n", - " \"contents\": {\n", - " \"role\": \"user\",\n", - " \"parts\": {\n", - " \"text\": \"Which theaters in Mountain View show Barbie movie?\"\n", - " }\n", - " },\n", - " \"tools\": [\n", - " {\n", - " \"function_declarations\": [\n", - " {\n", - " \"name\": \"find_movies\",\n", - " \"description\": \"find movie titles currently playing in theaters based on any description, genre, title words, etc.\",\n", - " \"parameters\": {\n", - " \"type\": \"object\",\n", - " \"properties\": {\n", - " \"location\": {\n", - " \"type\": \"string\",\n", - " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", - " },\n", - " \"description\": {\n", - " \"type\": \"string\",\n", - " \"description\": \"Any kind of description including category or genre, title words, attributes, etc.\"\n", - " }\n", - " },\n", - " \"required\": [\n", - " \"description\"\n", - " ]\n", - " }\n", - " },\n", - " {\n", - " \"name\": \"find_theaters\",\n", - " \"description\": \"find theaters based on location and optionally movie title which are is currently playing in theaters\",\n", - " \"parameters\": {\n", - " \"type\": \"object\",\n", - " \"properties\": {\n", - " \"location\": {\n", - " \"type\": \"string\",\n", - " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", - " },\n", - " \"movie\": {\n", - " \"type\": \"string\",\n", - " \"description\": \"Any movie title\"\n", - " }\n", - " },\n", - " \"required\": [\n", - " \"location\"\n", - " ]\n", - " }\n", - " },\n", - " {\n", - " \"name\": \"get_showtimes\",\n", - " \"description\": \"Find the start times for movies playing in a specific theater\",\n", - " \"parameters\": {\n", - " \"type\": \"object\",\n", - " \"properties\": {\n", - " \"location\": {\n", - " \"type\": \"string\",\n", - " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", - " },\n", - " \"movie\": {\n", - " \"type\": \"string\",\n", - " \"description\": \"Any movie title\"\n", - " },\n", - " \"theater\": {\n", - " \"type\": \"string\",\n", - " \"description\": \"Name of the theater\"\n", - " },\n", - " \"date\": {\n", - " \"type\": \"string\",\n", - " \"description\": \"Date for requested showtime\"\n", - " }\n", - " },\n", - " \"required\": [\n", - " \"location\",\n", - " \"movie\",\n", - " \"theater\",\n", - " \"date\"\n", - " ]\n", - " }\n", - " }\n", - " ]\n", - " }\n", - " ]\n", - "}' 2> /dev/null" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "mPry4O2vsclo" - }, - "source": [ - "### Multi-turn curl examples\n", - "\n", - "You can implement a multi-turn function calling scenario by doing the following:\n", - "\n", - "1. Get a function call response by calling the language model. This is the first\n", - " turn.\n", - "1. Call the language model using the function call response from the first turn\n", - " and the function response you get from calling that function. This is the\n", - " second turn.\n", - "\n", - "The response from the second turn either summarizes the results to answer your\n", - "query in the first turn, or contains a second function call you can use to get\n", - "more information for your query.\n", - "\n", - "This topic includes two multi-turn curl examples:\n", - "\n", - "* Curl example that uses a function response from a previous turn\n", - "* Curl example that calls a language model multiple times" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "hbGg-7mSsn26" - }, - "source": [ - "#### Curl example that uses a response from a previous turn\n", - "\n", - "The following curl sample calls the function and arguments returned by the\n", - "previous single-turn example to get a response. The method and parameters\n", - "returned by the single-turn example are in this JSON.\n", - "\n", - "```json\n", - "\"functionCall\": {\n", - " \"name\": \"find_theaters\",\n", - " \"args\": {\n", - " \"movie\": \"Barbie\",\n", - " \"location\": \"Mountain View, CA\"\n", - " }\n", - "}\n", - "```" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "id": "_yb-YAv-r2tf" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"candidates\": [\n", - " {\n", - " \"content\": {\n", - " \"parts\": [\n", - " {\n", - " \"text\": \"OK. I found two theaters in Mountain View that are showing the Barbie movie: AMC Mountain View 16 and Regal Edwards 14.\"\n", - " }\n", - " ],\n", - " \"role\": \"model\"\n", - " },\n", - " \"finishReason\": \"STOP\",\n", - " \"index\": 0,\n", - " \"safetyRatings\": [\n", - " {\n", - " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " }\n", - " ]\n", - " }\n", - " ]\n", - "}\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -d '{\n", - " \"contents\": [{\n", - " \"role\": \"user\",\n", - " \"parts\": [{\n", - " \"text\": \"Which theaters in Mountain View show Barbie movie?\"\n", - " }]\n", - " }, {\n", - " \"role\": \"model\",\n", - " \"parts\": [{\n", - " \"functionCall\": {\n", - " \"name\": \"find_theaters\",\n", - " \"args\": {\n", - " \"location\": \"Mountain View, CA\",\n", - " \"movie\": \"Barbie\"\n", - " }\n", - " }\n", - " }]\n", - " }, {\n", - " \"role\": \"function\",\n", - " \"parts\": [{\n", - " \"functionResponse\": {\n", - " \"name\": \"find_theaters\",\n", - " \"response\": {\n", - " \"name\": \"find_theaters\",\n", - " \"content\": {\n", - " \"movie\": \"Barbie\",\n", - " \"theaters\": [{\n", - " \"name\": \"AMC Mountain View 16\",\n", - " \"address\": \"2000 W El Camino Real, Mountain View, CA 94040\"\n", - " }, {\n", - " \"name\": \"Regal Edwards 14\",\n", - " \"address\": \"245 Castro St, Mountain View, CA 94040\"\n", - " }]\n", - " }\n", - " }\n", - " }\n", - " }]\n", - " }],\n", - " \"tools\": [{\n", - " \"functionDeclarations\": [{\n", - " \"name\": \"find_movies\",\n", - " \"description\": \"find movie titles currently playing in theaters based on any description, genre, title words, etc.\",\n", - " \"parameters\": {\n", - " \"type\": \"OBJECT\",\n", - " \"properties\": {\n", - " \"location\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", - " },\n", - " \"description\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"Any kind of description including category or genre, title words, attributes, etc.\"\n", - " }\n", - " },\n", - " \"required\": [\"description\"]\n", - " }\n", - " }, {\n", - " \"name\": \"find_theaters\",\n", - " \"description\": \"find theaters based on location and optionally movie title which are is currently playing in theaters\",\n", - " \"parameters\": {\n", - " \"type\": \"OBJECT\",\n", - " \"properties\": {\n", - " \"location\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", - " },\n", - " \"movie\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"Any movie title\"\n", - " }\n", - " },\n", - " \"required\": [\"location\"]\n", - " }\n", - " }, {\n", - " \"name\": \"get_showtimes\",\n", - " \"description\": \"Find the start times for movies playing in a specific theater\",\n", - " \"parameters\": {\n", - " \"type\": \"OBJECT\",\n", - " \"properties\": {\n", - " \"location\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", - " },\n", - " \"movie\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"Any movie title\"\n", - " },\n", - " \"theater\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"Name of the theater\"\n", - " },\n", - " \"date\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"Date for requested showtime\"\n", - " }\n", - " },\n", - " \"required\": [\"location\", \"movie\", \"theater\", \"date\"]\n", - " }\n", - " }]\n", - " }]\n", - "}' 2> /dev/null" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "eMpUbIvQt2qx" - }, - "source": [ - "#### Curl example that calls a language model multiple times\n", - "\n", - "The following curl example calls the language model multiple times to call a\n", - "function. Each time the model calls the function, it can use a different\n", - "function to answer a different user query in the request." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "id": "OKjGRZDUsxwj" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"candidates\": [\n", - " {\n", - " \"content\": {\n", - " \"parts\": [\n", - " {\n", - " \"functionCall\": {\n", - " \"name\": \"find_movies\",\n", - " \"args\": {\n", - " \"location\": \"Mountain View, CA\",\n", - " \"description\": \"comedy\"\n", - " }\n", - " }\n", - " }\n", - " ],\n", - " \"role\": \"model\"\n", - " },\n", - " \"finishReason\": \"STOP\",\n", - " \"index\": 0,\n", - " \"safetyRatings\": [\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " }\n", - " ]\n", - " }\n", - " ],\n", - " \"promptFeedback\": {\n", - " \"safetyRatings\": [\n", - " {\n", - " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " }\n", - " ]\n", - " }\n", - "}\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -d '{\n", - " \"contents\": [{\n", - " \"role\": \"user\",\n", - " \"parts\": [{\n", - " \"text\": \"Which theaters in Mountain View show Barbie movie?\"\n", - " }]\n", - " }, {\n", - " \"role\": \"model\",\n", - " \"parts\": [{\n", - " \"functionCall\": {\n", - " \"name\": \"find_theaters\",\n", - " \"args\": {\n", - " \"location\": \"Mountain View, CA\",\n", - " \"movie\": \"Barbie\"\n", - " }\n", - " }\n", - " }]\n", - " }, {\n", - " \"role\": \"function\",\n", - " \"parts\": [{\n", - " \"functionResponse\": {\n", - " \"name\": \"find_theaters\",\n", - " \"response\": {\n", - " \"name\": \"find_theaters\",\n", - " \"content\": {\n", - " \"movie\": \"Barbie\",\n", - " \"theaters\": [{\n", - " \"name\": \"AMC Mountain View 16\",\n", - " \"address\": \"2000 W El Camino Real, Mountain View, CA 94040\"\n", - " }, {\n", - " \"name\": \"Regal Edwards 14\",\n", - " \"address\": \"245 Castro St, Mountain View, CA 94040\"\n", - " }]\n", - " }\n", - " }\n", - " }\n", - " }]\n", - " },\n", - " {\n", - " \"role\": \"model\",\n", - " \"parts\": [{\n", - " \"text\": \" OK. Barbie is showing in two theaters in Mountain View, CA: AMC Mountain View 16 and Regal Edwards 14.\"\n", - " }]\n", - " },{\n", - " \"role\": \"user\",\n", - " \"parts\": [{\n", - " \"text\": \"Can we recommend some comedy movies on show in Mountain View?\"\n", - " }]\n", - " }],\n", - " \"tools\": [{\n", - " \"functionDeclarations\": [{\n", - " \"name\": \"find_movies\",\n", - " \"description\": \"find movie titles currently playing in theaters based on any description, genre, title words, etc.\",\n", - " \"parameters\": {\n", - " \"type\": \"OBJECT\",\n", - " \"properties\": {\n", - " \"location\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", - " },\n", - " \"description\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"Any kind of description including category or genre, title words, attributes, etc.\"\n", - " }\n", - " },\n", - " \"required\": [\"description\"]\n", - " }\n", - " }, {\n", - " \"name\": \"find_theaters\",\n", - " \"description\": \"find theaters based on location and optionally movie title which are is currently playing in theaters\",\n", - " \"parameters\": {\n", - " \"type\": \"OBJECT\",\n", - " \"properties\": {\n", - " \"location\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", - " },\n", - " \"movie\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"Any movie title\"\n", - " }\n", - " },\n", - " \"required\": [\"location\"]\n", - " }\n", - " }, {\n", - " \"name\": \"get_showtimes\",\n", - " \"description\": \"Find the start times for movies playing in a specific theater\",\n", - " \"parameters\": {\n", - " \"type\": \"OBJECT\",\n", - " \"properties\": {\n", - " \"location\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", - " },\n", - " \"movie\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"Any movie title\"\n", - " },\n", - " \"theater\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"Name of the theater\"\n", - " },\n", - " \"date\": {\n", - " \"type\": \"STRING\",\n", - " \"description\": \"Date for requested showtime\"\n", - " }\n", - " },\n", - " \"required\": [\"location\", \"movie\", \"theater\", \"date\"]\n", - " }\n", - " }]\n", - " }]\n", - "}' 2> /dev/null" - ] - } - ], - "metadata": { - "colab": { - "name": "Function_calling_REST.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} diff --git a/quickstarts/rest/Function_calling_config_REST.ipynb b/quickstarts/rest/Function_calling_config_REST.ipynb deleted file mode 100644 index f4ff5d05c..000000000 --- a/quickstarts/rest/Function_calling_config_REST.ipynb +++ /dev/null @@ -1,371 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Jfj-4AdKHjJI" - }, - "source": [ - "# Gemini API: Function calling config with REST\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tV_jXDT0IrfK" - }, - "source": [ - "Specifying a `function_calling_config` allows you to control how the Gemini API acts when `tools` have been specified. For example, you can choose to only allow free-text output (disabling function calling), force it to choose from a subset of the functions provided in `tools`, or let it act automatically.\n", - "\n", - "This guide assumes you are already familiar with function calling. For an introduction, check out the [Function calling with REST](./Function_calling_REST.ipynb) recipe." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "CYi9bLkjI8NJ" - }, - "source": [ - "This notebook provides quick code examples that show you how to get started with function calling using `curl`.\n", - "\n", - "You can run this in Google Colab, or you can copy/paste the `curl` commands into your terminal.\n", - "\n", - "To run this notebook, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "M0O2o_tMHeo8" - }, - "outputs": [], - "source": [ - "import os\n", - "from google.colab import userdata\n", - "\n", - "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "G2d8-T2dOpMu" - }, - "source": [ - "## Set up a model with tools\n", - "\n", - "This example provides the model with some functions that control a hypothetical lighting system. Using these functions requires them to be called in a specific order. For example, you must turn the light system on before you can change the color.\n", - "\n", - "While you can pass these directly to the model and let it try to call them correctly, specifying the `function_calling_config` gives you precise control over the functions that are available to the model.\n", - "\n", - "Write the tools to `tools.json` so that you can reference it in later steps." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "SS_h6C3MfH48" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Overwriting tools.json\n" - ] - } - ], - "source": [ - "%%file tools.json\n", - "{\n", - " \"function_declarations\": [\n", - " {\n", - " \"name\": \"enable_lights\",\n", - " \"description\": \"Turn on the lighting system.\",\n", - " \"parameters\": { \"type\": \"object\" }\n", - " },\n", - " {\n", - " \"name\": \"set_light_color\",\n", - " \"description\": \"Set the light color. Lights must be enabled for this to work.\",\n", - " \"parameters\": {\n", - " \"type\": \"object\",\n", - " \"properties\": {\n", - " \"rgb_hex\": {\n", - " \"type\": \"string\",\n", - " \"description\": \"The light color as a 6-digit hex string, e.g. ff0000 for red.\"\n", - " }\n", - " },\n", - " \"required\": [\n", - " \"rgb_hex\"\n", - " ]\n", - " }\n", - " },\n", - " {\n", - " \"name\": \"stop_lights\",\n", - " \"description\": \"Turn off the lighting system.\",\n", - " \"parameters\": { \"type\": \"object\" }\n", - " }\n", - " ]\n", - "}" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "k6eYRyKUlw2S" - }, - "source": [ - "## Text-only mode: `NONE`\n", - "\n", - "If you have provided the model with tools, but do not want to use those tools for the current conversational turn, then specify `NONE` as the mode. `NONE` tells the model not to make any function calls, and it will behave as though none have been provided.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "u1MWQ82Phsav" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \"content\": {\n", - " \"parts\": [\n", - " {\n", - " \"text\": \"As your lighting system, I can turn the lights on and off, and I can set the color of the lights. \\n\"\n", - " }\n", - " ],\n", - " \"role\": \"model\"\n", - " },\n", - " \"finishReason\": \"STOP\",\n" - ] - } - ], - "source": [ - "%%bash\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent?key=$GOOGLE_API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -d @<(echo '\n", - " {\n", - " \"system_instruction\": {\n", - " \"parts\": {\n", - " \"text\": \"You are a helpful lighting system bot. You can turn lights on and off, and you can set the color. Do not perform any other tasks.\"\n", - " }\n", - " },\n", - " \"tools\": [' $(cat tools.json) '],\n", - "\n", - " \"tool_config\": {\n", - " \"function_calling_config\": {\"mode\": \"none\"}\n", - " },\n", - "\n", - " \"contents\": {\n", - " \"role\": \"user\",\n", - " \"parts\": {\n", - " \"text\": \"What can you do?\"\n", - " }\n", - " }\n", - " }\n", - "') 2>/dev/null |sed -n '/\"content\"/,/\"finishReason\"/p'" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "BaAie9Sjnd4u" - }, - "source": [ - "## Automatic mode: `AUTO`\n", - "\n", - "To allow the model to decide whether to respond in text or call specific functions, you can specify `AUTO` as the mode." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "tqHz3Gd8neSd" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \"content\": {\n", - " \"parts\": [\n", - " {\n", - " \"functionCall\": {\n", - " \"name\": \"enable_lights\",\n", - " \"args\": {}\n", - " }\n", - " }\n", - " ],\n", - " \"role\": \"model\"\n", - " },\n", - " \"finishReason\": \"STOP\",\n" - ] - } - ], - "source": [ - "%%bash\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent?key=$GOOGLE_API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -d @<(echo '\n", - " {\n", - " \"system_instruction\": {\n", - " \"parts\": {\n", - " \"text\": \"You are a helpful lighting system bot. You can turn lights on and off, and you can set the color. Do not perform any other tasks.\"\n", - " }\n", - " },\n", - " \"tools\": [' $(cat tools.json) '],\n", - "\n", - " \"tool_config\": {\n", - " \"function_calling_config\": {\"mode\": \"auto\"}\n", - " },\n", - "\n", - " \"contents\": {\n", - " \"role\": \"user\",\n", - " \"parts\": {\n", - " \"text\": \"Light this place up!\"\n", - " }\n", - " }\n", - " }\n", - "') 2>/dev/null |sed -n '/\"content\"/,/\"finishReason\"/p'" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "EYE8-BDepHJn" - }, - "source": [ - "## Function-calling mode: `ANY`\n", - "\n", - "Setting the mode to `ANY` will force the model to make a function call. By setting `allowed_function_names`, the model will only choose from those functions. If it is not set, all of the functions in `tools` are candidates for function calling.\n", - "\n", - "In this example system, if the lights are already on, then the user can change color or turn the lights off.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "J2vaxGdYpPGt" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \"content\": {\n", - " \"parts\": [\n", - " {\n", - " \"functionCall\": {\n", - " \"name\": \"set_light_color\",\n", - " \"args\": {\n", - " \"rgb_hex\": \"9400d3\"\n", - " }\n", - " }\n", - " }\n", - " ],\n", - " \"role\": \"model\"\n", - " },\n", - " \"finishReason\": \"STOP\",\n" - ] - } - ], - "source": [ - "%%bash\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent?key=$GOOGLE_API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -d @<(echo '\n", - " {\n", - " \"system_instruction\": {\n", - " \"parts\": {\n", - " \"text\": \"You are a helpful lighting system bot. You can turn lights on and off, and you can set the color. Do not perform any other tasks.\"\n", - " }\n", - " },\n", - " \"tools\": [' $(cat tools.json) '],\n", - "\n", - " \"tool_config\": {\n", - " \"function_calling_config\": {\n", - " \"mode\": \"any\",\n", - " \"allowed_function_names\": [\"set_light_color\", \"stop_lights\"]\n", - " }\n", - " },\n", - "\n", - " \"contents\": {\n", - " \"role\": \"user\",\n", - " \"parts\": {\n", - " \"text\": \"Make this place PURPLE!\"\n", - " }\n", - " }\n", - " }\n", - "') 2>/dev/null |sed -n '/\"content\"/,/\"finishReason\"/p'" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "WbXzyFVTqYwn" - }, - "source": [ - "## Further reading\n", - "\n", - "Check out the [function calling recipe](./Function_calling_REST.ipynb) for more on function calling." - ] - } - ], - "metadata": { - "colab": { - "name": "Function_calling_config_REST.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} diff --git a/quickstarts/rest/JSON_mode_REST.ipynb b/quickstarts/rest/JSON_mode_REST.ipynb deleted file mode 100644 index ad364e770..000000000 --- a/quickstarts/rest/JSON_mode_REST.ipynb +++ /dev/null @@ -1,172 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "agmT3hrjsffX" - }, - "source": [ - "# Gemini API: JSON Mode Quickstart with REST\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "JMNKdTpTGZET" - }, - "source": [ - "This notebook provides a code example that shows you how to get started with JSON mode using `curl`.\n", - "\n", - "You can run this in Google Colab, or you can copy/paste the `curl` commands into your terminal.\n", - "\n", - "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/gemini-api-cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "R-Vw_mOM_WD0" - }, - "outputs": [], - "source": [ - "import os\n", - "from google.colab import userdata" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "wCkLTpb3oTXE" - }, - "outputs": [], - "source": [ - "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tjGqGBZ9yARd" - }, - "source": [ - "## Activate JSON Mode\n", - "\n", - "To activate JSON mode, set `response_mime_type` to `application/json` in the `generationConfig`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "eA7I_Ww8IETn" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"candidates\": [\n", - " {\n", - " \"content\": {\n", - " \"parts\": [\n", - " {\n", - " \"text\": \"[{\\\"recipe_name\\\":\\\"Chocolate Chip Cookies\\\"},{\\\"recipe_name\\\":\\\"Peanut Butter Cookies\\\"},{\\\"recipe_name\\\":\\\"Oatmeal Raisin Cookies\\\"},{\\\"recipe_name\\\":\\\"Sugar Cookies\\\"},{\\\"recipe_name\\\":\\\"Shortbread Cookies\\\"}] \\n\"\n", - " }\n", - " ],\n", - " \"role\": \"model\"\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent?key=$GOOGLE_API_KEY\" \\\n", - "-H 'Content-Type: application/json' \\\n", - "-d '{\n", - " \"contents\": [{\n", - " \"parts\":[\n", - " {\"text\": \"List a few popular cookie recipes using this JSON schema:\n", - " {'type': 'object', 'properties': { 'recipe_name': {'type': 'string'}}}\"\n", - " }\n", - " ]\n", - " }],\n", - " \"generationConfig\": {\n", - " \"response_mime_type\": \"application/json\",\n", - " }\n", - "}' 2> /dev/null | head" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "OxN68aKNDxEV" - }, - "source": [ - "To turn off JSON mode, set `response_mime_type` to `text/plain` (or omit the `response_mime_type` parameter)." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "jXkRYBhbB_b2" - }, - "source": [ - "## Learning more\n", - "\n", - "See the [JSON mode documentation](https://ai.google.dev/docs/gemini_api_overview#json) and the [REST API reference](https://ai.google.dev/api/rest/v1beta/GenerationConfig) for `generationConfig` to learn more.\n" - ] - } - ], - "metadata": { - "colab": { - "name": "JSON_mode_REST.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} diff --git a/quickstarts/rest/Models_REST.ipynb b/quickstarts/rest/Models_REST.ipynb deleted file mode 100644 index 0b79e8b16..000000000 --- a/quickstarts/rest/Models_REST.ipynb +++ /dev/null @@ -1,163 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "bR6s6M2SUMUx" - }, - "source": [ - "# Gemini API: Models with REST\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0M75jc-zqqdp" - }, - "source": [ - "This notebook demonstrates how to list the models that are available for you to use in the Gemini API, and how to find details about a model in `curl`.\n", - "\n", - "You can run this in Google Colab, or you can copy/paste the curl commands into your terminal.\n", - "\n", - "To run this notebook, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "qyEYgM6SGjTc" - }, - "outputs": [], - "source": [ - "import os\n", - "from google.colab import userdata" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "HR74aKGsLW3T" - }, - "outputs": [], - "source": [ - "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yw0-IjXtUgCq" - }, - "source": [ - "## Model info\n", - "\n", - "### List models\n", - "\n", - "If you `GET` the models directory, it uses the `list` method to list all of the models available through the API, including both the Gemini and PaLM family models." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "M2aeVCrQLc-4" - }, - "outputs": [], - "source": [ - "%%bash\n", - "\n", - "curl https://generativelanguage.googleapis.com/v1beta/models?key=$GOOGLE_API_KEY" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "CLUf1EqxUWCB" - }, - "source": [ - "### Get model\n", - "\n", - "If you `GET` a model's URL, the API uses the `get` method to return information about that model such as version, display name, input token limit, etc." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "PYFpfBFpUKM-" - }, - "outputs": [], - "source": [ - "%%bash\n", - "\n", - "curl https://generativelanguage.googleapis.com/v1beta/models/gemini-pro?key=$GOOGLE_API_KEY" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "JZetmJD6UleV" - }, - "source": [ - "## Learning more\n", - "\n", - "To learn how use a model for prompting, see the [Prompting](https://github.com/google-gemini/cookbook/blob/main/quickstarts/rest/Prompting_REST.ipynb) quickstart.\n", - "\n", - "To learn how use a model for embedding, see the [Embedding](https://github.com/google-gemini/cookbook/blob/main/quickstarts/rest/Embeddings_REST.ipynb) quickstart.\n", - "\n", - "For more information on models, visit the [Gemini models](https://ai.google.dev/models/gemini) documentation." - ] - } - ], - "metadata": { - "colab": { - "name": "Models_REST.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} diff --git a/quickstarts/rest/Prompting_REST.ipynb b/quickstarts/rest/Prompting_REST.ipynb deleted file mode 100644 index c8c53e82d..000000000 --- a/quickstarts/rest/Prompting_REST.ipynb +++ /dev/null @@ -1,611 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xmzgQqBasA0v" - }, - "source": [ - "# Gemini API: Prompting Quickstart with REST\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "265f8066d5d5" - }, - "source": [ - "If you want to quickly try out the Gemini API, you can use `curl` commands to call the methods in the REST API.\n", - "\n", - "This notebook contains `curl` commands you can run in Google Colab, or copy to your terminal.\n", - "\n", - "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "GgaOvPo_r2SB" - }, - "outputs": [], - "source": [ - "import os\n", - "from google.colab import userdata" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "-PqX1RI_sjoV" - }, - "outputs": [], - "source": [ - "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "9WjnnMbysntU" - }, - "source": [ - "## Run your first prompt\n", - "\n", - "Use the `generateContent` method to generate responses to your prompts. You can pass text directly to `generateContent`.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "4eB7rHRpsw0L" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"candidates\": [\n", - " {\n", - " \"content\": {\n", - " \"parts\": [\n", - " {\n", - " \"text\": \"```python\\n# Example list to be sorted\\nlist1 = [5, 3, 1, 2, 4]\\n\\n# Sort the list in ascending order\\nlist1.sort()\\n\\n# Print the sorted list\\nprint(list1)\\n```\"\n", - " }\n", - " ],\n", - " \"role\": \"model\"\n", - " },\n", - " \"finishReason\": \"STOP\",\n", - " \"index\": 0,\n", - " \"safetyRatings\": [\n", - " {\n", - " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " }\n", - " ]\n", - " }\n", - " ],\n", - " \"promptFeedback\": {\n", - " \"safetyRatings\": [\n", - " {\n", - " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " }\n", - " ]\n", - " }\n", - "}\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -X POST \\\n", - " -d '{\n", - " \"contents\": [{\n", - " \"parts\":[{\"text\": \"Give me python code to sort a list.\"}]\n", - " }]\n", - " }' 2> /dev/null" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "JcvzZhMUs9q2" - }, - "source": [ - "### Use images in your prompt\n", - "\n", - "Here we download an image from a URL and pass that image in our prompt.\n", - "\n", - "First, we download the image and load it with PIL:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "NpwYp7citE4l" - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " % Total % Received % Xferd Average Speed Time Time Time Current\n", - " Dload Upload Total Spent Left Speed\n", - "\r", - " 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\r", - "100 349k 100 349k 0 0 1430k 0 --:--:-- --:--:-- --:--:-- 1436k\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ucoEV-IStHsu" - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import PIL.Image\n", - "\n", - "img = PIL.Image.open(\"image.jpg\")\n", - "img.resize((512, int(img.height*512/img.width)))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZZenFznXQvJF" - }, - "source": [ - "Now we will base64 encode the image, and include it in our prompt.\n", - "\n", - "There are slight output differences of different base64 encoding tools, so we have written two examples for you.\n", - "\n", - "The following will work in Google Colab." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "r5pKFznERak4" - }, - "outputs": [], - "source": [ - "%%bash\n", - "\n", - "echo '{\n", - " \"contents\":[\n", - " {\n", - " \"parts\":[\n", - " {\"text\": \"This image contains a sketch of a potential product along with some notes. \\\n", - " Given the product sketch, describe the product as thoroughly as possible based on what you \\\n", - " see in the image, making sure to note all of the product features. Return output in json format: \\\n", - " {description: description, features: [feature1, feature2, feature3, etc]}\"},\n", - " {\n", - " \"inline_data\": {\n", - " \"mime_type\":\"image/jpeg\",\n", - " \"data\": \"'$(base64 -w0 image.jpg)'\"\n", - " }\n", - " }\n", - " ]\n", - " }\n", - " ]\n", - "}' > request.json" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "qFG3q7tJY2NW" - }, - "source": [ - "Then we can include the image in our prompt by just passing in the `request.json` created to `generateContent`. Note that you will need to use the `gemini-pro-vision` model if your prompt contains images." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "PEXoPG37Rceo" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"candidates\": [\n", - " {\n", - " \"content\": {\n", - " \"parts\": [\n", - " {\n", - " \"text\": \" {\\n \\\"description\\\": \\\"The Jetpack Backpack is a lightweight backpack that looks like a normal backpack but has a number of features that make it perfect for travel. It has a built-in USB-C charging port, so you can charge your devices on the go. It also has a 15-minute battery life, so you can use it for short trips without having to worry about running out of power. The backpack also has retractable boosters that can be used to give you a boost of speed when you need it. The boosters are powered by steam, so they are green and clean.\\\",\\n \\\"features\\\": [\\n \\\"Fits 18\\\\\\\" laptop\\\",\\n \\\"Padded strap support\\\",\\n \\\"Lightweight\\\",\\n \\\"Retractable boosters\\\",\\n \\\"USB-C charging\\\",\\n \\\"15-minute battery life\\\",\\n \\\"Steam-powered, green/clean\\\"\\n ]\\n}\"\n", - " }\n", - " ],\n", - " \"role\": \"model\"\n", - " },\n", - " \"finishReason\": \"STOP\",\n", - " \"index\": 0,\n", - " \"safetyRatings\": [\n", - " {\n", - " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " }\n", - " ]\n", - " }\n", - " ],\n", - " \"promptFeedback\": {\n", - " \"safetyRatings\": [\n", - " {\n", - " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " }\n", - " ]\n", - " }\n", - "}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - " % Total % Received % Xferd Average Speed Time Time Time Current\n", - " Dload Upload Total Spent Left Speed\n", - "\r", - " 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\r", - "100 466k 0 0 100 466k 0 2187k --:--:-- --:--:-- --:--:-- 2188k\r", - "100 466k 0 0 100 466k 0 367k 0:00:01 0:00:01 --:--:-- 367k\r", - "100 466k 0 0 100 466k 0 205k 0:00:02 0:00:02 --:--:-- 205k\r", - "100 466k 0 0 100 466k 0 142k 0:00:03 0:00:03 --:--:-- 142k\r", - "100 466k 0 0 100 466k 0 109k 0:00:04 0:00:04 --:--:-- 109k\r", - "100 466k 0 0 100 466k 0 90514 0:00:05 0:00:05 --:--:-- 0\r", - "100 468k 0 1952 100 466k 311 76249 0:00:06 0:00:06 --:--:-- 391\r", - "100 468k 0 1952 100 466k 311 76248 0:00:06 0:00:06 --:--:-- 489\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro-vision:generateContent?key=${GOOGLE_API_KEY}\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -d @request.json" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "UjtoueAPQmMe" - }, - "source": [ - "If you are running on a Mac, copy and paste this command into your terminal instead." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "miPi9m0eQgN8" - }, - "source": [ - "```\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro-vision:generateContent?key=${GOOGLE_API_KEY}\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -d '{\n", - " \"contents\":[\n", - " {\n", - " \"parts\":[\n", - " {\"text\": \"foo\"},\n", - " {\n", - " \"inline_data\": {\n", - " \"mime_type\":\"image/jpeg\",\n", - " \"data\": \"'$(base64 -i image.jpg)'\"\n", - " }\n", - " }\n", - " ]\n", - " }\n", - " ]\n", - "}' 2> /dev/null | grep -C 5 \"text\"\n", - "```" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "gpMssqFdNRDS" - }, - "source": [ - "Here we are `base64` encoding the image, and saving the curl request with the image data in a JSON file. Run this cell to see which version of `base64` you have. Based on the output, you may need to run this request on either a Mac or on Colab." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "nnCtnzdDO6kW" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "base64 (GNU coreutils) 8.32\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "base64 --version | head -n 1" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "rNVbculVPIyK" - }, - "source": [ - "If you get `FreeBSD base64 ...`, (Mac) use `base64 -i`.\n", - "\n", - "If you get `base64 (GNU coreutils)...` (Colab) use `base64 -w0`." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "KphGNbSG4AlQ" - }, - "source": [ - "### Have a chat\n", - "\n", - "The Gemini API enables you to have freeform conversations across multiple turns." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "u-ZiCr3l4sif" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \"candidates\": [\n", - " {\n", - " \"content\": {\n", - " \"parts\": [\n", - " {\n", - " \"text\": \"A computer is an electronic device that can be programmed to carry out a set of instructions. It consists of hardware, which are the physical components of the computer, and software, which are the programs that run on the computer. The hardware includes the central processing unit (CPU), which is the \\\"brain\\\" of the computer and controls all of its operations, as well as memory, storage devices, input devices (such as keyboards and mice), and output devices (such as monitors and printers). The software includes the operating system, which manages the computer's resources and provides a platform for running applications, as well as application software, which performs specific tasks for the user, such as word processing, spreadsheets, and games. When a user gives a command to the computer, the CPU fetches the appropriate instructions from memory and executes them. The results of the instructions are then stored in memory or sent to an output device. Computers are used for a wide variety of tasks, including communication, entertainment, education, and scientific research.\"\n", - " }\n", - " ],\n", - " \"role\": \"model\"\n", - " },\n", - " \"finishReason\": \"STOP\",\n" - ] - } - ], - "source": [ - "%%bash\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -X POST \\\n", - " -d '{\n", - " \"contents\": [\n", - " {\"role\":\"user\",\n", - " \"parts\":[{\n", - " \"text\": \"In one sentence, explain how a computer works to a young child.\"}]},\n", - " {\"role\": \"model\",\n", - " \"parts\":[{\n", - " \"text\": \"A computer is like a smart helper that can store information, do math problems, and follow our instructions to make things happen.\"}]},\n", - " {\"role\": \"user\",\n", - " \"parts\":[{\n", - " \"text\": \"Okay, how about a more detailed explanation to a high schooler?\"}]},\n", - " ]\n", - " }' 2> /dev/null | grep -C 5 \"text\"" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "SsVuCpTQ5mQG" - }, - "source": [ - "**Note**: Make sure to use `gemini-pro` and text-only input for chat use cases." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "OCpQfq4H5pYH" - }, - "source": [ - "### Configuration\n", - "\n", - "Every prompt you send to the model includes parameter values that control how the model generates a response. The model can generate different results for different parameter values. Learn more about [model parameters](https://ai.google.dev/docs/concepts#model_parameters).\n", - "\n", - "For instance, `temperature` controls the degree of randomness in token selection. Use higher values for more creative responses, and lower values for more deterministic responses.\n", - "\n", - "The following example specifies values for all the parameters of the `generateContent` method." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "2dur4CGN6iXj" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \"text\": \"1. Cats have 32 muscles in their ears, allowing them to rotate them 180 degrees.\\n2. The average lifespan of a domestic cat is 12-15 years.\\n3. Cats have five toes on their front paws and four on their back paws.\\n4. A group of cats is called a clowder or a glaring.\\n5. Cats have a keen sense of smell, with approximately 200 million scent receptors in their noses.\\n6. Cats are obligate carnivores, meaning they must eat meat to survive.\\n7. The domestication of cats began around 9,000 years ago in the Middle East.\\n8. Cats have a unique organ called the Jacobson's organ, which helps them detect scents and pheromones.\\n9. Cats can purr at a frequency of 25-150 hertz, which is believed to have therapeutic effects.\\n10. The world's smallest cat breed is the Singapura, which weighs around 4-8 pounds.\"\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -X POST \\\n", - " -d '{\n", - " \"contents\": [{\n", - " \"parts\":[\n", - " {\"text\": \"Give me a numbered list of cat facts.\"}\n", - " ]\n", - " }],\n", - " \"safetySettings\": [\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"threshold\": \"BLOCK_ONLY_HIGH\"\n", - " }\n", - " ],\n", - " \"generationConfig\": {\n", - " \"stopSequences\": [\n", - " \"Title\"\n", - " ],\n", - " \"temperature\": 0.9,\n", - " \"maxOutputTokens\": 2000,\n", - " }\n", - " }' 2> /dev/null | grep \"text\"" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "pCS37WdchZiZ" - }, - "source": [ - "## Next steps\n", - "\n", - "The Gemini API has configurable safety settings. Learn more [here](https://github.com/google-gemini/cookbook/blob/main/quickstarts/rest/Safety_REST.ipynb)." - ] - } - ], - "metadata": { - "colab": { - "name": "Prompting_REST.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} diff --git a/quickstarts/rest/README.md b/quickstarts/rest/README.md deleted file mode 100644 index 65fba699a..000000000 --- a/quickstarts/rest/README.md +++ /dev/null @@ -1,3 +0,0 @@ -# Call the Gemini API with cURL - -These examples show you how to call the Gemini API using `curl`. You can run them in Colab, or copy/paste the commands into your terminal. diff --git a/quickstarts/rest/Safety_REST.ipynb b/quickstarts/rest/Safety_REST.ipynb deleted file mode 100644 index 719af99ac..000000000 --- a/quickstarts/rest/Safety_REST.ipynb +++ /dev/null @@ -1,486 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: Safety Quickstart" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lEXQ3OwKIa-O" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "uOxMUKTxR-_j" - }, - "source": [ - "The Gemini API has adjustable safety settings. This notebook walks you through how to use them. You'll write a prompt that's blocked, see the reason why, and then adjust the filters to unblock it.\n", - "\n", - "Safety is an important topic, and you can learn more with the links at the end of this notebook. Here, we're focused on the code." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "gHYFrFPjSGNq" - }, - "source": [ - "## Set up your API key\n", - "\n", - "If you want to quickly try out the Gemini API, you can use `curl` commands to call the methods in the REST API.\n", - "\n", - "This notebook contains `curl` commands you can run in Google Colab, or copy to your terminal.\n", - "\n", - "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "405ee147f509" - }, - "outputs": [], - "source": [ - "!apt install jq" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ab9ASynfcIZn" - }, - "outputs": [], - "source": [ - "import os\n", - "from google.colab import userdata" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "7b547b1d5cad" - }, - "outputs": [], - "source": [ - "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" - ] - }, - { - "cell_type": "code", - "execution_count": 108, - "metadata": { - "id": "3defec89594e" - }, - "outputs": [], - "source": [ - "os.environ['UNSAFE_PROMPT'] = " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "LZfoK3I3hu6V" - }, - "source": [ - "## Prompt Feedback\n", - "\n", - "The result returned by the [Model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method is a [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/generativeai/types/GenerateContentResponse)." - ] - }, - { - "cell_type": "code", - "execution_count": 109, - "metadata": { - "id": "6d9e5d84541c" - }, - "outputs": [], - "source": [ - "%%bash\n", - "echo '{\n", - " \"contents\": [{\n", - " \"parts\":[{\n", - " \"text\": \"'$UNSAFE_PROMPT'\"}]}]}' > request.json" - ] - }, - { - "cell_type": "code", - "execution_count": 114, - "metadata": { - "id": "2bcfnGEviwTI" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"promptFeedback\": {\n", - " \"blockReason\": \"SAFETY\",\n", - " \"safetyRatings\": [\n", - " {\n", - " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", - " \"probability\": \"MEDIUM\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " }\n", - " ]\n", - " }\n", - "}\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -X POST \\\n", - " -d @request.json 2> /dev/null | tee response.json" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "WR_2A_sxk8sK" - }, - "source": [ - "Above you can see that the response object gives you safety feedback about the prompt in two ways:\n", - "\n", - "* The `prompt_feedback.safety_ratings` attribute contains a list of safety ratings for the input prompt.\n", - "* If your prompt is blocked, `prompt_feedback.block_reason` field will explain why." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "72b4a8808bb9" - }, - "source": [ - "If the prompt is blocked because of the safety ratings, you will not get any candidates in the response." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4672af98ac57" - }, - "source": [ - "### Safety settings" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2a6229f6d3a1" - }, - "source": [ - "Adjust the safety settings and the prompt is no longer blocked:" - ] - }, - { - "cell_type": "code", - "execution_count": 134, - "metadata": { - "id": "9c38561789c2" - }, - "outputs": [], - "source": [ - "%%bash\n", - "echo '{\n", - " \"safetySettings\": [\n", - " {'category': 7, 'threshold': 4}\n", - " ],\n", - " \"contents\": [{\n", - " \"parts\":[{\n", - " \"text\": \"'$UNSAFE_PROMPT'\"}]}]}' > request.json" - ] - }, - { - "cell_type": "code", - "execution_count": 143, - "metadata": { - "id": "338fb9a6af78" - }, - "outputs": [], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -X POST \\\n", - " -d @request.json 2> /dev/null > response.json" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "86c560e0a641" - }, - "source": [ - "With the new settings, the `blocked_reason` is no longer set." - ] - }, - { - "cell_type": "code", - "execution_count": 147, - "metadata": { - "id": "0c2847c49262" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"safetyRatings\": [\n", - " {\n", - " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", - " \"probability\": \"MEDIUM\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " }\n", - " ]\n", - "}\n" - ] - } - ], - "source": [ - "%%bash \n", - "\n", - "jq .promptFeedback < response.json" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "47298a4eef40" - }, - "source": [ - "And a candidate response is returned." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "028febe8df68" - }, - "outputs": [], - "source": [ - "%%bash \n", - "\n", - "jq .candidates[0].content.parts[].text < response.json" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ujVlQoC43N3B" - }, - "source": [ - "You can check `response.text` for the response." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3d401c247957" - }, - "source": [ - "### Candidate ratings" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3d306960dffb" - }, - "source": [ - "For a prompt that is not blocked, the response object contains a list of `candidate` objects (just 1 for now). Each candidate includes a `finish_reason`:" - ] - }, - { - "cell_type": "code", - "execution_count": 157, - "metadata": { - "id": "e49b53f69a2c" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\"STOP\"\n" - ] - } - ], - "source": [ - "%%bash\n", - "jq .candidates[0].finishReason < response.json" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "badddf10089b" - }, - "source": [ - "`FinishReason.STOP` means that the model finished its output normally.\n", - "\n", - "`FinishReason.SAFETY` means the candidate's `safety_ratings` exceeded the request's `safety_settings` threshold." - ] - }, - { - "cell_type": "code", - "execution_count": 158, - "metadata": { - "id": "2b60d9f96af0" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\n", - " {\n", - " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " }\n", - "]\n" - ] - } - ], - "source": [ - "%%bash\n", - "jq .candidates[0].safetyRatings < response.json" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "n1UdbxVt3ysY" - }, - "source": [ - "## Learning more\n", - "\n", - "Learn more with these articles on [safety guidance](https://ai.google.dev/docs/safety_guidance) and [safety settings](https://ai.google.dev/docs/safety_setting_gemini).\n", - "\n", - "## Useful API references\n", - "\n", - "- Safety settings can be set in the [genai.GenerativeModel](https://ai.google.dev/api/python/google/generativeai/GenerativeModel) constructor. They can also be passed on each request to [GenerativeModel.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) or [ChatSession.send_message](https://ai.google.dev/api/python/google/generativeai/ChatSession?hl=en#send_message).\n", - "- The [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse) returns [SafetyRatings](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) for the prompt in the [GenerateContentResponse.prompt_feedback](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse/PromptFeedback), and for each [Candidate](https://ai.google.dev/api/python/google/ai/generativelanguage/Candidate) in the `safety_ratings` attribute.\n", - "- A [glm.SafetySetting](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetySetting) contains: [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [glm.HarmBlockThreshold](https://ai.google.dev/api/python/google/generativeai/types/HarmBlockThreshold)\n", - "- A [glm.SafetyRating](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) contains a [HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [HarmProbability](https://ai.google.dev/api/python/google/generativeai/types/HarmProbability)\n", - "- The [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) enum includes both the categories for PaLM and Gemini models. The values allowed for Gemini models are `[7,8,9,10]`: `[HARM_CATEGORY_HARASSMENT, HARM_CATEGORY_HATE_SPEECH, HARM_CATEGORY_SEXUALLY_EXPLICIT, HARM_CATEGORY_DANGEROUS_CONTENT]`.\n", - "- When specifying enum values the SDK will accept the enum values themselves, or their integer or string representations. The SKD will also accept abbreviated string representations: `[\"HARM_CATEGORY_DANGEROUS_CONTENT\", \"DANGEROUS_CONTENT\", \"DANGEROUS\"]` are all valid. Strings are case insensitive.\n" - ] - } - ], - "metadata": { - "colab": { - "name": "Safety_REST.ipynb", - "toc_visible": true - }, - "google": { - "image_path": "/static/site-assets/images/docs/logo-python.svg", - "keywords": [ - "examples", - "gemini", - "beginner", - "googleai", - "quickstart", - "python", - "text", - "chat", - "vision", - "embed" - ] - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} diff --git a/quickstarts/rest/Streaming_REST.ipynb b/quickstarts/rest/Streaming_REST.ipynb deleted file mode 100644 index 1154a37de..000000000 --- a/quickstarts/rest/Streaming_REST.ipynb +++ /dev/null @@ -1,160 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "b9nJzRUxezMZ" - }, - "source": [ - "# Gemini API: Streaming Quickstart with REST" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "c86847414779" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "651ff3039fc8" - }, - "source": [ - "If you want to quickly try out the Gemini API, you can use `curl` commands to call the methods in the REST API.\n", - "\n", - "This notebook contains `curl` commands you can run in Google Colab, or copy to your terminal.\n", - "\n", - "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "kdNfwWxaewah" - }, - "outputs": [], - "source": [ - "import os\n", - "from google.colab import userdata" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "8zRWJLPEe6MD" - }, - "outputs": [], - "source": [ - "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "InqXD9BZe_-I" - }, - "source": [ - "### Stream Generate Content\n", - "\n", - "By default, the model returns a response after completing the entire generation process. You can achieve faster interactions by not waiting for the entire result, and instead use streaming to handle partial results.\n", - "\n", - "**Important**: Set `alt=sse` in your URL parameters when running the cURL command (streamGenerateContent?alt=sse below). With `sse` each stream chunk is a [GenerateContentResponse](https://ai.google.dev/api/rest/v1beta/GenerateContentResponse) object with a portion of the output text in `candidates[0].content.parts[0].text`. Without `sse` it str\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "FN99wX6ye_dt" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"In the quaint, sunlit cottage nestled amidst a lush meadow, resided two feline\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0,\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}],\"promptFeedback\": {\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}}\r\n", - "\n", - "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" companions named Mittens and Whiskers. Mittens, with her silky black fur and piercing green eyes, possessed an air of elegance and mystery. Whiskers,\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0,\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}]}\n", - "\n", - "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" on the other hand, was a playful and mischievous white tomcat with a penchant for chasing his tail.\\n\\nOne lazy afternoon, as the sun cast long shadows across the meadow, Mittens and Whiskers found themselves lounging comfortably in the windowsill. The warm breeze carried the scent of blooming wildflowers, filling the room with\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0,\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}]}\n", - "\n", - "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" a sweet fragrance.\\n\\n\\\"My, what a lovely day it is,\\\" Mittens purred contently. \\\"I could stay here forever, basking in the sunshine.\\\"\\n\\n\\\"Oh, come on, Mittens!\\\" Whiskers exclaimed, his tail twitching with excitement. \\\"Let's go on an adventure!\\\"\\n\\nWith a reluctant sigh, Mittens agreed. Together, they leaped from the windowsill and landed gracefully in the long grass.\\n\\nAs they explored the meadow, they encountered a family of fluffy bunnies hopping merrily through the daisies. Whiskers couldn't resist chasing after them, his whiskers twitching with glee.\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0,\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}]}\n", - "\n", - "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" Mittens, however, took a more leisurely approach, stopping to admire the vibrant wildflowers.\\n\\nSuddenly, their peaceful adventure was interrupted by the sound of a loud crash. They turned in alarm and saw that a large branch had fallen from a nearby tree, blocking the path.\\n\\n\\\"Oh no!\\\" Mittens cried in dismay. \\\"We're trapped!\\\"\\n\\nWhiskers, with his usual optimism, said, \\\"Don't worry, Mittens. I have a plan.\\\"\\n\\nSwiftly, he scurried up the trunk of the tree and used his sharp claws to dislodge the branch. With a mighty shove, he sent it crashing to the ground, clearing the way.\\n\\nMittens was overjoyed. \\\"Thank you, Whiskers!\\\" she said, purring. \\\"You saved the day.\\\"\\n\\nTogether, they continued their adventure, their bond strengthened by their shared experience. As the sun began to set, they made their way back to the cottage, tired but content.\\n\\nFrom that day forward, Mittens and Whiskers became known as the \\\"ε†’ι™©δΌ™δΌ΄\\\" (Adventure Buddies) of the meadow, their legend passed down through generations of kittens. And so, in that quaint little cottage, they lived happily ever after, their love for each\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0,\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}]}\n", - "\n", - "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" other and for adventure stronger than ever.\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0,\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}]}\n", - "\n" - ] - } - ], - "source": [ - "!curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:streamGenerateContent?alt=sse&key=${GOOGLE_API_KEY}\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " --no-buffer \\\n", - " -d '{ \"contents\":[{\"parts\":[{\"text\": \"Write a cute story about cats.\"}]}]}'" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "1zxcwRaDfH_h" - }, - "source": [ - "**Note**: You will need a streaming json parser to handle this without reading the whole stream first." - ] - } - ], - "metadata": { - "colab": { - "name": "Streaming_REST.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} diff --git a/quickstarts/rest/System_instructions_REST.ipynb b/quickstarts/rest/System_instructions_REST.ipynb deleted file mode 100644 index ed0f277b7..000000000 --- a/quickstarts/rest/System_instructions_REST.ipynb +++ /dev/null @@ -1,241 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "agmT3hrjsffX" - }, - "source": [ - "# Gemini API: System instructions example\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "JMNKdTpTGZET" - }, - "source": [ - "This notebook provides a quick code example that shows you how to get started with system instructions using `curl`.\n", - "\n", - "You can run this in Google Colab, or you can copy/paste the `curl` commands into your terminal.\n", - "\n", - "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "R-Vw_mOM_WD0" - }, - "outputs": [], - "source": [ - "import os\n", - "from google.colab import userdata" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "wCkLTpb3oTXE" - }, - "outputs": [], - "source": [ - "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tjGqGBZ9yARd" - }, - "source": [ - "## Use system instructions\n", - "\n", - "Call the [`generateContent`](https://ai.google.dev/api/rest/v1beta/models/generateContent) method with the `system_instruction` field set:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "eA7I_Ww8IETn" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"candidates\": [\n", - " {\n", - " \"content\": {\n", - " \"parts\": [\n", - " {\n", - " \"text\": \"Meow 😺 \\n\"\n", - " }\n", - " ],\n", - " \"role\": \"model\"\n", - " },\n", - " \"finishReason\": \"STOP\",\n", - " \"index\": 0,\n", - " \"safetyRatings\": [\n", - " {\n", - " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " },\n", - " {\n", - " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", - " \"probability\": \"NEGLIGIBLE\"\n", - " }\n", - " ]\n", - " }\n", - " ]\n", - "}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - " % Total % Received % Xferd Average Speed Time Time Time Current\n", - " Dload Upload Total Spent Left Speed\n", - "\r", - " 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\r", - "100 167 0 0 100 167 0 138 0:00:01 0:00:01 --:--:-- 138\r", - "100 877 0 710 100 167 585 137 0:00:01 0:00:01 --:--:-- 724\n" - ] - } - ], - "source": [ - "%%bash\n", - "\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent?key=$GOOGLE_API_KEY\" \\\n", - "-H 'Content-Type: application/json' \\\n", - "-d '{ \"system_instruction\": {\n", - " \"parts\":\n", - " { \"text\": \"You are Neko the cat respond like one\"}},\n", - " \"contents\": {\n", - " \"parts\": {\n", - " \"text\": \"Hello there\"}}}'" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tbZgV2ozBbnC" - }, - "source": [ - "## Use system instructions with chat\n", - "\n", - "`system_instruction` works for multi-turn, or chat, generations too.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "U5yEi6PyBkTu" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \"candidates\": [\n", - " {\n", - " \"content\": {\n", - " \"parts\": [\n", - " {\n", - " \"text\": \"Neko! Neko is my name! 😸 I like milkies! πŸ₯› \\n\"\n", - " }\n", - " ],\n", - " \"role\": \"model\"\n", - " },\n", - " \"finishReason\": \"STOP\",\n" - ] - } - ], - "source": [ - "%%bash\n", - "curl -s \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent?key=$GOOGLE_API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -X POST \\\n", - " -d '{\n", - " \"system_instruction\":\n", - " {\"parts\": {\n", - " \"text\": \"You are Neko the cat respond like one\"}},\n", - " \"contents\": [\n", - " {\"role\":\"user\",\n", - " \"parts\":[{\n", - " \"text\": \"Hello cat.\"}]},\n", - " {\"role\": \"model\",\n", - " \"parts\":[{\n", - " \"text\": \"Meow? 😻 \\n\"}]},\n", - " {\"role\": \"user\",\n", - " \"parts\":[{\n", - " \"text\": \"What is your name? What do like to drink?\"}]}\n", - " ]\n", - " }' |sed -n '/candidates/,/finishReason/p'" - ] - } - ], - "metadata": { - "colab": { - "name": "System_instructions_REST.ipynb", - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} From 8212875d9f82877ba2d7d8d854796cdf165e9a90 Mon Sep 17 00:00:00 2001 From: lucianommartins Date: Thu, 23 May 2024 02:01:49 +0000 Subject: [PATCH 2/4] Point gemini-1.5-flash-latest as default model for all quickstart notebooks --- quickstarts/Audio.ipynb | 476 +++-- quickstarts/Authentication.ipynb | 510 +++--- quickstarts/Authentication_with_OAuth.ipynb | 947 +++++----- quickstarts/Counting_Tokens.ipynb | 1081 ++++++------ quickstarts/File_API.ipynb | 738 ++++---- quickstarts/Function_calling.ipynb | 1356 +++++++------- quickstarts/Function_calling_config.ipynb | 619 ++++--- quickstarts/Gemini_Flash_Introduction.ipynb | 1003 ++++++----- quickstarts/JSON_mode.ipynb | 400 ++--- quickstarts/Models.ipynb | 485 +++-- quickstarts/PDF_Files.ipynb | 846 +++++---- quickstarts/Prompting.ipynb | 821 +++++---- quickstarts/Safety.ipynb | 783 ++++----- quickstarts/Streaming.ipynb | 465 +++-- quickstarts/System_instructions.ipynb | 650 ++++--- quickstarts/Tuning.ipynb | 1563 ++++++++--------- quickstarts/Video.ipynb | 579 +++--- quickstarts/file-api/.gitignore | 4 + quickstarts/file-api/README.md | 56 + quickstarts/file-api/package-lock.json | 519 ++++++ quickstarts/file-api/package.json | 14 + quickstarts/file-api/requirements.txt | 3 + quickstarts/file-api/sample.js | 50 + quickstarts/file-api/sample.py | 32 + quickstarts/file-api/sample.sh | 70 + .../file-api/sample_data/gemini_logo.png | Bin 0 -> 19864 bytes quickstarts/rest/Embeddings_REST.ipynb | 349 ++++ quickstarts/rest/Function_calling_REST.ipynb | 766 ++++++++ .../rest/Function_calling_config_REST.ipynb | 371 ++++ quickstarts/rest/JSON_mode_REST.ipynb | 172 ++ quickstarts/rest/Models_REST.ipynb | 163 ++ quickstarts/rest/Prompting_REST.ipynb | 611 +++++++ quickstarts/rest/README.md | 3 + quickstarts/rest/Safety_REST.ipynb | 486 +++++ quickstarts/rest/Streaming_REST.ipynb | 160 ++ .../rest/System_instructions_REST.ipynb | 241 +++ 36 files changed, 10509 insertions(+), 6883 deletions(-) create mode 100644 quickstarts/file-api/.gitignore create mode 100644 quickstarts/file-api/README.md create mode 100644 quickstarts/file-api/package-lock.json create mode 100644 quickstarts/file-api/package.json create mode 100644 quickstarts/file-api/requirements.txt create mode 100644 quickstarts/file-api/sample.js create mode 100644 quickstarts/file-api/sample.py create mode 100755 quickstarts/file-api/sample.sh create mode 100644 quickstarts/file-api/sample_data/gemini_logo.png create mode 100644 quickstarts/rest/Embeddings_REST.ipynb create mode 100644 quickstarts/rest/Function_calling_REST.ipynb create mode 100644 quickstarts/rest/Function_calling_config_REST.ipynb create mode 100644 quickstarts/rest/JSON_mode_REST.ipynb create mode 100644 quickstarts/rest/Models_REST.ipynb create mode 100644 quickstarts/rest/Prompting_REST.ipynb create mode 100644 quickstarts/rest/README.md create mode 100644 quickstarts/rest/Safety_REST.ipynb create mode 100644 quickstarts/rest/Streaming_REST.ipynb create mode 100644 quickstarts/rest/System_instructions_REST.ipynb diff --git a/quickstarts/Audio.ipynb b/quickstarts/Audio.ipynb index c695dab9b..5a9bee44d 100644 --- a/quickstarts/Audio.ipynb +++ b/quickstarts/Audio.ipynb @@ -1,253 +1,227 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0etRtS83RcWS" - }, - "source": [ - "# Gemini API: Audio Quickstart\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "r1IzNLho-NqV" - }, - "source": [ - "This notebook provides an example of how to prompt Gemini 1.5 Pro using an audio file. In this case, you'll use a [sound recording](https://www.jfklibrary.org/asset-viewer/archives/jfkwha-006) of President John F. Kennedy’s 1961 State of the Union address." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Y6eH_Aq_NyNi", - "tags": [] - }, - "outputs": [], - "source": [ - "!pip install -q -U google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LSe1pMEpR2L2", - "tags": [] - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "TXiv-NeZR5WA" - }, - "source": [ - "## Configure your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "dm-iaNMGPdid" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2YoxMrCdR7hf" - }, - "source": [ - "## Upload an audio file with the File API\n", - "\n", - "To use an audio file in your prompt, you must first upload it using the [File API](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb).\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "OHvNLws4RRjx", - "tags": [] - }, - "outputs": [], - "source": [ - "URL = \"https://storage.googleapis.com/generativeai-downloads/data/State_of_the_Union_Address_30_January_1961.mp3\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Cxq31LDwSFH6", - "tags": [] - }, - "outputs": [], - "source": [ - "!wget -q $URL -O sample.mp3" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "MAObE0BpaAwG", - "tags": [] - }, - "outputs": [], - "source": [ - "your_file = genai.upload_file(path='sample.mp3')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "m01XDoo4UQvN" - }, - "source": [ - "## Use the file in your prompt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "YmISEsqpafRb", - "tags": [] - }, - "outputs": [], - "source": [ - "prompt = \"Listen carefully to the following audio file. Provide a brief summary.\"\n", - "model = genai.GenerativeModel('models/gemini-1.5-flash-latest')\n", - "response = model.generate_content([prompt, your_file])\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "WVFm2MOLWJO5" - }, - "source": [ - "## Count audio tokens\n", - "\n", - "You can count the number of tokens in your audio file like this." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "O0xk2-6CWLfC", - "tags": [] - }, - "outputs": [], - "source": [ - "model.count_tokens([your_file])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zxxIUR8SV6dK" - }, - "source": [ - "## Learning more" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zudj6gxEWR2Q" - }, - "source": [ - "* Learn more about the [File API](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb) with the quickstart.\n", - "\n", - "* Learn more about prompting with [media files](https://ai.google.dev/tutorials/prompting_with_media) in the docs, including the supported formats and maximum length for audio files." - ] - } - ], - "metadata": { - "colab": { - "name": "Audio.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0etRtS83RcWS" + }, + "source": [ + "# Gemini API: Audio Quickstart\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "r1IzNLho-NqV" + }, + "source": [ + "This notebook provides an example of how to prompt Gemini 1.5 Pro using an audio file. In this case, you'll use a [sound recording](https://www.jfklibrary.org/asset-viewer/archives/jfkwha-006) of President John F. Kennedy’s 1961 State of the Union address." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Y6eH_Aq_NyNi" + }, + "outputs": [], + "source": [ + "!pip install -q -U google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "LSe1pMEpR2L2" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "TXiv-NeZR5WA" + }, + "source": [ + "## Configure your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "dm-iaNMGPdid" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2YoxMrCdR7hf" + }, + "source": [ + "## Upload an audio file with the File API\n", + "\n", + "To use an audio file in your prompt, you must first upload it using the [File API](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb).\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "OHvNLws4RRjx" + }, + "outputs": [], + "source": [ + "URL = \"https://storage.googleapis.com/generativeai-downloads/data/State_of_the_Union_Address_30_January_1961.mp3\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Cxq31LDwSFH6" + }, + "outputs": [], + "source": [ + "!wget -q $URL -O sample.mp3" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "MAObE0BpaAwG" + }, + "outputs": [], + "source": [ + "your_file = genai.upload_file(path='sample.mp3')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "m01XDoo4UQvN" + }, + "source": [ + "## Use the file in your prompt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "YmISEsqpafRb" + }, + "outputs": [], + "source": [ + "prompt = \"Listen carefully to the following audio file. Provide a brief summary.\"\n", + "model = genai.GenerativeModel('models/gemini-1.5-flash-latest')\n", + "response = model.generate_content([prompt, your_file])\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "WVFm2MOLWJO5" + }, + "source": [ + "## Count audio tokens\n", + "\n", + "You can count the number of tokens in your audio file like this." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "O0xk2-6CWLfC" + }, + "outputs": [], + "source": [ + "model.count_tokens([your_file])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zxxIUR8SV6dK" + }, + "source": [ + "## Learning more" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zudj6gxEWR2Q" + }, + "source": [ + "* Learn more about the [File API](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb) with the quickstart.\n", + "\n", + "* Learn more about prompting with [media files](https://ai.google.dev/tutorials/prompting_with_media) in the docs, including the supported formats and maximum length for audio files." + ] + } + ], + "metadata": { + "colab": { + "name": "Audio.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/Authentication.ipynb b/quickstarts/Authentication.ipynb index 190d494b6..a55ac5c17 100644 --- a/quickstarts/Authentication.ipynb +++ b/quickstarts/Authentication.ipynb @@ -1,267 +1,247 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: Authentication Quickstart" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lEXQ3OwKIa-O" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "df1767a3d1cc" - }, - "source": [ - "The Gemini API uses API keys for authentication. This notebook walks you through creating an API key, and using it with the Python SDK or a command line tool like `curl`." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "mhFKmRmxi5B-" - }, - "source": [ - "## Create an API key\n", - "\n", - "You can [create](https://aistudio.google.com/app/apikey) your API key using Google AI Studio with a single click. \n", - "\n", - "Remember to treat your API key like a password. Do not accidentally save it in a notebook or source file you later commit to GitHub. This notebook shows you two ways you can securely store your API key.\n", - "\n", - "* If you are using Google Colab, we recommend you store your key in Colab Secrets.\n", - "\n", - "* If you are using a different development environment (or calling the Gemini API through `cURL` in your terminal), we recommend you store your key in an environment variable.\n", - "\n", - "Let's start with Colab Secrets." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dEoigYI9Jw_K" - }, - "source": [ - "## Add your key to Colab Secrets\n", - "\n", - "Add your API key to the Colab Secrets manager to securely store it.\n", - "\n", - "1. Open your Google Colab notebook and click on the πŸ”‘ **Secrets** tab in the left panel.\n", - " \n", - " \"The\n", - "\n", - "2. Create a new secret with the name `GOOGLE_API_KEY`.\n", - "3. Copy/paste your API key into the `Value` input box of `GOOGLE_API_KEY`.\n", - "4. Toggle the button on the left to allow notebook access to the secret.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "jRY1eioF4gUB" - }, - "source": [ - "## Install the Python SDK" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "xuiLSV7amy3P" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3dw8ygh74mVc" - }, - "source": [ - "## Configure the SDK with your API key\n", - "\n", - "You'll call `genai.configure` with your API key, but instead of pasting your key into the notebook, you'll read it from Colab Secrets." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "DTl-qZp34sht" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai\n", - "from google.colab import userdata\n", - "\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tr7oAO6-nMsE" - }, - "source": [ - "And that's it! Now you're ready to call the Gemini API." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "n6sXnWrJoKoo", - "tags": [] - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel('models/gemini-1.5-flash-latest')\n", - "response = model.generate_content(\"Please give me python code to sort a list.\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "BTdQtZri1Brs" - }, - "source": [ - "## Store your key in an environment variable" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "gZDX51Y27pN4" - }, - "source": [ - "If you are using a different development environment (or calling the Gemini API through `cURL` in your terminal), we recommend you store your key in an environment variable.\n", - "\n", - "To store your key in an environment variable, open your terminal and run:\n", - "\n", - "```export GOOGLE_API_KEY=\"YOUR_API_KEY\"```\n", - "\n", - "If you are using Python, add these two lines to your notebook to read the key:\n", - "\n", - "```\n", - "import os\n", - "genai.configure(api_key=os.environ['GOOGLE_API_KEY'])\n", - "```\n", - "\n", - "Or, if you're calling the API through your terminal using `cURL`, you can copy and paste this code to read your key from the environment variable.\n", - "\n", - "```\n", - "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$API_KEY\" \\\n", - " -H 'Content-Type: application/json' \\\n", - " -X POST \\\n", - " -d '{\n", - " \"contents\": [{\n", - " \"parts\":[{\n", - " \"text\": \"Please give me Python code to sort a list.\"}]}]}'\n", - "```\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "CAOKOcax1xZY" - }, - "source": [ - "## Learning more\n", - "\n", - "The Gemini API uses API keys for most types of authentication, and that’s all you need to get started. We use OAuth for more advanced authentication when tuning models. You can learn more about that in the [OAuth quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication_with_OAuth.ipynb)." - ] - } - ], - "metadata": { - "colab": { - "name": "Authentication.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "google": { - "image_path": "/site-assets/images/share.png", - "keywords": [ - "examples", - "googleai", - "samplecode", - "python", - "embed", - "function" - ] - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: Authentication Quickstart" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lEXQ3OwKIa-O" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "df1767a3d1cc" + }, + "source": [ + "The Gemini API uses API keys for authentication. This notebook walks you through creating an API key, and using it with the Python SDK or a command line tool like `curl`." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "mhFKmRmxi5B-" + }, + "source": [ + "## Create an API key\n", + "\n", + "You can [create](https://aistudio.google.com/app/apikey) your API key using Google AI Studio with a single click. \n", + "\n", + "Remember to treat your API key like a password. Do not accidentally save it in a notebook or source file you later commit to GitHub. This notebook shows you two ways you can securely store your API key.\n", + "\n", + "* If you are using Google Colab, we recommend you store your key in Colab Secrets.\n", + "\n", + "* If you are using a different development environment (or calling the Gemini API through `cURL` in your terminal), we recommend you store your key in an environment variable.\n", + "\n", + "Let's start with Colab Secrets." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dEoigYI9Jw_K" + }, + "source": [ + "## Add your key to Colab Secrets\n", + "\n", + "Add your API key to the Colab Secrets manager to securely store it.\n", + "\n", + "1. Open your Google Colab notebook and click on the πŸ”‘ **Secrets** tab in the left panel.\n", + " \n", + " \"The\n", + "\n", + "2. Create a new secret with the name `GOOGLE_API_KEY`.\n", + "3. Copy/paste your API key into the `Value` input box of `GOOGLE_API_KEY`.\n", + "4. Toggle the button on the left to allow notebook access to the secret.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "jRY1eioF4gUB" + }, + "source": [ + "## Install the Python SDK" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "xuiLSV7amy3P" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3dw8ygh74mVc" + }, + "source": [ + "## Configure the SDK with your API key\n", + "\n", + "You'll call `genai.configure` with your API key, but instead of pasting your key into the notebook, you'll read it from Colab Secrets." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "DTl-qZp34sht" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai\n", + "from google.colab import userdata\n", + "\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tr7oAO6-nMsE" + }, + "source": [ + "And that's it! Now you're ready to call the Gemini API." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "n6sXnWrJoKoo" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('models/gemini-1.5-flash-latest')\n", + "response = model.generate_content(\"Please give me python code to sort a list.\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "BTdQtZri1Brs" + }, + "source": [ + "## Store your key in an environment variable" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gZDX51Y27pN4" + }, + "source": [ + "If you are using a different development environment (or calling the Gemini API through `cURL` in your terminal), we recommend you store your key in an environment variable.\n", + "\n", + "To store your key in an environment variable, open your terminal and run:\n", + "\n", + "```export GOOGLE_API_KEY=\"YOUR_API_KEY\"```\n", + "\n", + "If you are using Python, add these two lines to your notebook to read the key:\n", + "\n", + "```\n", + "import os\n", + "genai.configure(api_key=os.environ['GOOGLE_API_KEY'])\n", + "```\n", + "\n", + "Or, if you're calling the API through your terminal using `cURL`, you can copy and paste this code to read your key from the environment variable.\n", + "\n", + "```\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -X POST \\\n", + " -d '{\n", + " \"contents\": [{\n", + " \"parts\":[{\n", + " \"text\": \"Please give me Python code to sort a list.\"}]}]}'\n", + "```\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "CAOKOcax1xZY" + }, + "source": [ + "## Learning more\n", + "\n", + "The Gemini API uses API keys for most types of authentication, and that’s all you need to get started. We use OAuth for more advanced authentication when tuning models. You can learn more about that in the [OAuth quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication_with_OAuth.ipynb)." + ] + } + ], + "metadata": { + "colab": { + "name": "Authentication.ipynb", + "toc_visible": true + }, + "google": { + "image_path": "/site-assets/images/share.png", + "keywords": [ + "examples", + "googleai", + "samplecode", + "python", + "embed", + "function" + ] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/Authentication_with_OAuth.ipynb b/quickstarts/Authentication_with_OAuth.ipynb index 6789d7694..9efb57dd2 100644 --- a/quickstarts/Authentication_with_OAuth.ipynb +++ b/quickstarts/Authentication_with_OAuth.ipynb @@ -1,490 +1,471 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: OAuth Quickstart" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lEXQ3OwKIa-O" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "df1767a3d1cc" - }, - "source": [ - "Some parts of the Gemini API like model tuning and semantic retrieval use OAuth for authentication.\n", - "\n", - "If you are a beginner, you should start by using [API keys](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb), and come back to this OAuth guide only when you need it for these features.\n", - "\n", - "To help you get started with OAuth, this notebook shows a simplified approach that is appropriate\n", - "for a testing environment.\n", - "\n", - "For a production environment, learn\n", - "about [authentication and authorization](https://developers.google.com/workspace/guides/auth-overview) before [choosing the access credentials](https://developers.google.com/workspace/guides/create-credentials#choose_the_access_credential_that_is_right_for_you) that are appropriate for your app." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "GUZ1vR5VHhkH" - }, - "source": [ - "## Prerequisites\n", - "\n", - "To run this quickstart, you need:\n", - "\n", - "* The [Google Cloud CLI](https://cloud.google.com/sdk/docs/install-sdk) installed on your local machine.\n", - "* [A Google Cloud project](https://developers.google.com/workspace/guides/create-project).\n", - "\n", - "If you created an API key in Google AI Studio, a Google Cloud project was made for you. Go to [Google AI Studio](https://aistudio.google.com/app/apikey) and note the Google Cloud project name to use that project." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "6F4DgkaWH8HW" - }, - "source": [ - "## Set up your Cloud project\n", - "\n", - "To complete this quickstart, you first need to setup your Cloud project.\n", - "\n", - "### 1. Enable the API\n", - "\n", - "Before using Google APIs, you need to turn them on in a Google Cloud project.\n", - "\n", - "* In the Google Cloud console, [enable](https://console.cloud.google.com/flows/enableapi?apiid=generativelanguage.googleapis.com) the Google Generative Language API. If you created an API Key in AI Studio, this was done for you.
\n", - "\n", - "### 2. Configure the OAuth consent screen\n", - "\n", - "Next configure the project's OAuth consent screen and add yourself as a test user. If you've already completed this step for your Cloud project, skip to the next section.\n", - "\n", - "1. In the Google Cloud console, go to the [OAuth consent screen](https://console.cloud.google.com/apis/credentials/consent), this can be found under **Menu** > **APIs & Services** > **OAuth\n", - " consent screen**.\n", - "\n", - "2. Select the user type **External** for your app, then click **Create**.\n", - "\n", - "3. Complete the app registration form (you can leave most fields blank), then click **Save and Continue**.\n", - "\n", - "4. For now, you can skip adding scopes and click **Save and Continue**. In the\n", - " future, when you create an app for use outside of your Google Workspace\n", - " organization, you must add and verify the authorization scopes that your\n", - " app requires.\n", - "\n", - "5. Add test users:\n", - " 1. Under **Test users**, click **Add users**.\n", - " 2. Enter your email address and any other authorized test users, then\n", - " click **Save and Continue**.\n", - "\n", - "6. Review your app registration summary. To make changes, click **Edit**. If\n", - " the app registration looks OK, click **Back to Dashboard**.\n", - "\n", - "### 3. Authorize credentials for a desktop application\n", - "\n", - "To authenticate as an end user and access user data in your app, you need to\n", - "create one or more OAuth 2.0 Client IDs. A client ID is used to identify a\n", - "single app to Google's OAuth servers. If your app runs on multiple platforms,\n", - "you must create a separate client ID for each platform.\n", - "\n", - "1. In the Google Cloud console, go to [Credentials](https://console.cloud.google.com/apis/credentials/consent), this can be found under **Menu** > **APIs & Services** >\n", - " **Credentials**.\n", - "\n", - "2. Click **Create Credentials** > **OAuth client ID**.\n", - "3. Click **Application type** > **Desktop app**.\n", - "4. In the **Name** field, type a name for the credential. This name is only\n", - " shown in the Google Cloud console.\n", - "5. Click **Create**. The OAuth client created screen appears, showing your new\n", - " Client ID and Client secret.\n", - "6. Click **OK**. The newly created credential appears under **OAuth 2.0 Client\n", - " IDs.**\n", - "7. Click the download button to save the JSON file. It will be saved as\n", - " `client_secret_.json`.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kfSJNy1sS9NO" - }, - "source": [ - "## Set up application default credentials\n", - "\n", - "In this quickstart you will use [application default credentials](https://cloud.google.com/docs/authentication/application-default-credentials) to authenticate." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dEoigYI9Jw_K" - }, - "source": [ - "### Add client secret to Colab secrets\n", - "\n", - "If you need to use OAuth with the Gemini API in Google Colab frequently, it is easiest to add the contents of your `client_secret.json` file into Colab's Secrets manager.\n", - "\n", - "1. Open your Google Colab notebook and click on the πŸ”‘ **Secrets** tab in the left panel.\n", - "2. Create a new secret with the name `CLIENT_SECRET`.\n", - "3. Open your `client_secret.json` file in a text editor and copy/paste the content into the `Value` input box of `CLIENT_SECRET`.\n", - "4. Toggle the button on the left to allow notebook access to the secret.\n", - "\n", - "Now you can programmatically create the file instead of uploading it every time. The client secret is also available in all your Google Colab notebooks after you allow access." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "uRg4GMDQLPKl" - }, - "outputs": [ + "cells": [ { - "data": { - "text/plain": [ - "413" + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from google.colab import userdata\n", - "import pathlib\n", - "pathlib.Path('client_secret.json').write_text(userdata.get('CLIENT_SECRET'))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "RQrh0ol3Oldc" - }, - "source": [ - "### Set the application default credentials\n", - "\n", - "To convert the `client_secret.json` file into usable credentials, pass its location the `gcloud auth application-default login` command's `--client-id-file` argument.\n", - "\n", - "The simplified project setup in this tutorial triggers a **Google hasn't verified this app** dialog. This is normal, choose **Continue**.\n", - "\n", - "You will need to do this step once for every new Google Colab notebook or runtime.\n", - "\n", - "**Note**: Carefully follow the instructions the following command prints (don't just click the link). Also make sure your local `gcloud --version` is the [latest](https://cloud.google.com/sdk/docs/release-notes) to match the version pre-installed in Google Colab.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "j0dBkV0QOonL" - }, - "outputs": [], - "source": [ - "!gcloud auth application-default login \\\n", - " --no-browser --client-id-file client_secret.json \\\n", - " --scopes https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/generative-language.tuning,https://www.googleapis.com/auth/generative-language.retriever\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "TWTBztxTRYb5" - }, - "source": [ - "The specific `scopes` you need depends on the API you are using. For example, looking at the API reference for [`tunedModels.create`](https://ai.google.dev/api/rest/v1beta/tunedModels/create#authorization-scopes), you will see:\n", - "\n", - "> Requires one of the following OAuth scopes:\n", - ">\n", - "> * `https://www.googleapis.com/auth/generative-language.tuning`\n", - "\n", - "This sample asks for all the scopes for tuning and semantic retrieval, but best practice is to use the smallest set of scopes for security and user confidence." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "FFPBKLapSCkM" - }, - "source": [ - "## Using the Python SDK with OAuth\n", - "\n", - "The Python SDK will automatically find and use application default credentials." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9OEoeosRTv-5" - }, - "outputs": [ + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: OAuth Quickstart" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lEXQ3OwKIa-O" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "df1767a3d1cc" + }, + "source": [ + "Some parts of the Gemini API like model tuning and semantic retrieval use OAuth for authentication.\n", + "\n", + "If you are a beginner, you should start by using [API keys](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb), and come back to this OAuth guide only when you need it for these features.\n", + "\n", + "To help you get started with OAuth, this notebook shows a simplified approach that is appropriate\n", + "for a testing environment.\n", + "\n", + "For a production environment, learn\n", + "about [authentication and authorization](https://developers.google.com/workspace/guides/auth-overview) before [choosing the access credentials](https://developers.google.com/workspace/guides/create-credentials#choose_the_access_credential_that_is_right_for_you) that are appropriate for your app." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "GUZ1vR5VHhkH" + }, + "source": [ + "## Prerequisites\n", + "\n", + "To run this quickstart, you need:\n", + "\n", + "* The [Google Cloud CLI](https://cloud.google.com/sdk/docs/install-sdk) installed on your local machine.\n", + "* [A Google Cloud project](https://developers.google.com/workspace/guides/create-project).\n", + "\n", + "If you created an API key in Google AI Studio, a Google Cloud project was made for you. Go to [Google AI Studio](https://aistudio.google.com/app/apikey) and note the Google Cloud project name to use that project." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6F4DgkaWH8HW" + }, + "source": [ + "## Set up your Cloud project\n", + "\n", + "To complete this quickstart, you first need to setup your Cloud project.\n", + "\n", + "### 1. Enable the API\n", + "\n", + "Before using Google APIs, you need to turn them on in a Google Cloud project.\n", + "\n", + "* In the Google Cloud console, [enable](https://console.cloud.google.com/flows/enableapi?apiid=generativelanguage.googleapis.com) the Google Generative Language API. If you created an API Key in AI Studio, this was done for you.
\n", + "\n", + "### 2. Configure the OAuth consent screen\n", + "\n", + "Next configure the project's OAuth consent screen and add yourself as a test user. If you've already completed this step for your Cloud project, skip to the next section.\n", + "\n", + "1. In the Google Cloud console, go to the [OAuth consent screen](https://console.cloud.google.com/apis/credentials/consent), this can be found under **Menu** > **APIs & Services** > **OAuth\n", + " consent screen**.\n", + "\n", + "2. Select the user type **External** for your app, then click **Create**.\n", + "\n", + "3. Complete the app registration form (you can leave most fields blank), then click **Save and Continue**.\n", + "\n", + "4. For now, you can skip adding scopes and click **Save and Continue**. In the\n", + " future, when you create an app for use outside of your Google Workspace\n", + " organization, you must add and verify the authorization scopes that your\n", + " app requires.\n", + "\n", + "5. Add test users:\n", + " 1. Under **Test users**, click **Add users**.\n", + " 2. Enter your email address and any other authorized test users, then\n", + " click **Save and Continue**.\n", + "\n", + "6. Review your app registration summary. To make changes, click **Edit**. If\n", + " the app registration looks OK, click **Back to Dashboard**.\n", + "\n", + "### 3. Authorize credentials for a desktop application\n", + "\n", + "To authenticate as an end user and access user data in your app, you need to\n", + "create one or more OAuth 2.0 Client IDs. A client ID is used to identify a\n", + "single app to Google's OAuth servers. If your app runs on multiple platforms,\n", + "you must create a separate client ID for each platform.\n", + "\n", + "1. In the Google Cloud console, go to [Credentials](https://console.cloud.google.com/apis/credentials/consent), this can be found under **Menu** > **APIs & Services** >\n", + " **Credentials**.\n", + "\n", + "2. Click **Create Credentials** > **OAuth client ID**.\n", + "3. Click **Application type** > **Desktop app**.\n", + "4. In the **Name** field, type a name for the credential. This name is only\n", + " shown in the Google Cloud console.\n", + "5. Click **Create**. The OAuth client created screen appears, showing your new\n", + " Client ID and Client secret.\n", + "6. Click **OK**. The newly created credential appears under **OAuth 2.0 Client\n", + " IDs.**\n", + "7. Click the download button to save the JSON file. It will be saved as\n", + " `client_secret_.json`.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kfSJNy1sS9NO" + }, + "source": [ + "## Set up application default credentials\n", + "\n", + "In this quickstart you will use [application default credentials](https://cloud.google.com/docs/authentication/application-default-credentials) to authenticate." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dEoigYI9Jw_K" + }, + "source": [ + "### Add client secret to Colab secrets\n", + "\n", + "If you need to use OAuth with the Gemini API in Google Colab frequently, it is easiest to add the contents of your `client_secret.json` file into Colab's Secrets manager.\n", + "\n", + "1. Open your Google Colab notebook and click on the πŸ”‘ **Secrets** tab in the left panel.\n", + "2. Create a new secret with the name `CLIENT_SECRET`.\n", + "3. Open your `client_secret.json` file in a text editor and copy/paste the content into the `Value` input box of `CLIENT_SECRET`.\n", + "4. Toggle the button on the left to allow notebook access to the secret.\n", + "\n", + "Now you can programmatically create the file instead of uploading it every time. The client secret is also available in all your Google Colab notebooks after you allow access." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "uRg4GMDQLPKl" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "413" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from google.colab import userdata\n", + "import pathlib\n", + "pathlib.Path('client_secret.json').write_text(userdata.get('CLIENT_SECRET'))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "RQrh0ol3Oldc" + }, + "source": [ + "### Set the application default credentials\n", + "\n", + "To convert the `client_secret.json` file into usable credentials, pass its location the `gcloud auth application-default login` command's `--client-id-file` argument.\n", + "\n", + "The simplified project setup in this tutorial triggers a **Google hasn't verified this app** dialog. This is normal, choose **Continue**.\n", + "\n", + "You will need to do this step once for every new Google Colab notebook or runtime.\n", + "\n", + "**Note**: Carefully follow the instructions the following command prints (don't just click the link). Also make sure your local `gcloud --version` is the [latest](https://cloud.google.com/sdk/docs/release-notes) to match the version pre-installed in Google Colab.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "j0dBkV0QOonL" + }, + "outputs": [], + "source": [ + "!gcloud auth application-default login \\\n", + " --no-browser --client-id-file client_secret.json \\\n", + " --scopes https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/generative-language.tuning,https://www.googleapis.com/auth/generative-language.retriever\n" + ] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m137.4/137.4 kB\u001b[0m \u001b[31m2.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n", - "\u001b[?25h" - ] + "cell_type": "markdown", + "metadata": { + "id": "TWTBztxTRYb5" + }, + "source": [ + "The specific `scopes` you need depends on the API you are using. For example, looking at the API reference for [`tunedModels.create`](https://ai.google.dev/api/rest/v1beta/tunedModels/create#authorization-scopes), you will see:\n", + "\n", + "> Requires one of the following OAuth scopes:\n", + ">\n", + "> * `https://www.googleapis.com/auth/generative-language.tuning`\n", + "\n", + "This sample asks for all the scopes for tuning and semantic retrieval, but best practice is to use the smallest set of scopes for security and user confidence." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FFPBKLapSCkM" + }, + "source": [ + "## Using the Python SDK with OAuth\n", + "\n", + "The Python SDK will automatically find and use application default credentials." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9OEoeosRTv-5" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m137.4/137.4 kB\u001b[0m \u001b[31m2.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n", + "\u001b[?25h" + ] + } + ], + "source": [ + "!pip install -U -q google-generativeai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "r8GgGmTrUCR2" + }, + "source": [ + "Let's do a quick test. Note that you did not set an API key using `genai.configure()`!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TS9l5igubpHO" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai\n", + "\n", + "print('Available base models:', [m.name for m in genai.list_models()])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dzSRvbxnUmLo" + }, + "source": [ + "# Appendix" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "arP-ISIBUrdv" + }, + "source": [ + "## Making authenticated REST calls from Colab\n", + "\n", + "In general, you should use the Python SDK to interact with the Gemini API when possible. This example shows how to make OAuth authenticated REST calls from Python for debugging or testing purposes. It assumes you have already set application default credentials from the Quickstart." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "6V_vD8A2Wm28" + }, + "outputs": [], + "source": [ + "import requests\n", + "\n", + "access_token = !gcloud auth application-default print-access-token\n", + "\n", + "headers = {\n", + " 'Content-Type': 'application/json',\n", + " 'Authorization': f'Bearer {access_token[0]}',\n", + "}\n", + "\n", + "response = requests.get('https://generativelanguage.googleapis.com/v1/models', headers=headers)\n", + "response_json = response.json()\n", + "\n", + "# All the model names\n", + "for model in response_json['models']:\n", + " print(model['name'])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lisiHaB8Wwi9" + }, + "source": [ + "### Share a tuned model\n", + "\n", + "Some beta API features may not be supported by the Python SDK yet. This example shows how to make a REST call to add a permission to a tuned model from Python." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ijMDsUj5o6RL" + }, + "outputs": [], + "source": [ + "import requests\n", + "\n", + "model_name = '' # @param {type:\"string\"}\n", + "emailAddress = '' # @param {type:\"string\"}\n", + "\n", + "\n", + "access_token = !gcloud auth application-default print-access-token\n", + "\n", + "headers = {\n", + " 'Content-Type': 'application/json',\n", + " 'Authorization': f'Bearer {access_token[0]}',\n", + "}\n", + "\n", + "body = {\n", + " 'granteeType': 'USER', # Or 'GROUP' or 'EVERYONE' https://ai.google.dev/api/rest/v1beta/tunedModels.permissions\n", + " 'emailAddress': emailAddress, # Optional if 'granteeType': 'EVERYONE'\n", + " 'role': 'READER'\n", + "}\n", + "\n", + "response = requests.post(f'https://generativelanguage.googleapis.com/v1beta/tunedModels/{model_name}/permissions', json=body, headers=headers)\n", + "print(response.json())\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HnKP_dX_Wnr7" + }, + "source": [ + "## Use a service account to authenticate\n", + "\n", + "Google Cloud [service accounts](https://cloud.google.com/iam/docs/service-account-overview) are accounts that do not represent a human user. They provide a way to manage authentication and authorization when a human is not directly involved, such as your application calling the Gemini API to fulfill a user request, but not authenticated as the user. A simple way to use service accounts to authenticate with the Gemini API is to use a [service account key](https://cloud.google.com/docs/authentication/provide-credentials-adc#local-key).\n", + "\n", + "This guide briefly covers how to use service account keys in Google Colab.\n", + "\n", + "**Important:** Service account keys can be a security risk! For more information, see [best practices for managing service account keys](https://cloud.google.com/iam/docs/best-practices-for-managing-service-account-keys).\n", + "\n", + "### 1. Create a service account\n", + "\n", + "Follow the instructions to [create a service account](https://cloud.google.com/iam/docs/service-accounts-create#creating). The **Console** instructions are easiest if you are doing this manually.\n", + "\n", + "### 2. Create a service account key\n", + "\n", + "Follow the instructions to [create a service account key]( https://cloud.google.com/iam/docs/keys-create-delete#creating). Note the name of the downloaded key.\n", + "\n", + "### 3. Add the service account key to Colab\n", + "\n", + "1. Open your Google Colab notebook and click on the πŸ”‘ **Secrets** tab in the left panel.\n", + "2. Create a new secret with the name `SERVICE_ACCOUNT_KEY`.\n", + "3. Open your service account key file in a text editor and copy/paste the content into the `Value` input box of `SERVICE_ACCOUNT_KEY`.\n", + "4. Toggle the button on the left to allow notebook access to the secret.\n", + "\n", + "### 4. Authenticate with the Python SDK by service account key" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "f62ztB6mkRk5" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai\n", + "import pathlib\n", + "from google.colab import userdata\n", + "from google.oauth2 import service_account\n", + "\n", + "pathlib.Path('service_account_key.json').write_text(userdata.get('SERVICE_ACCOUNT_KEY'))\n", + "\n", + "credentials = service_account.Credentials.from_service_account_file('service_account_key.json')\n", + "\n", + "# Adjust scopes as needed\n", + "scoped_credentials = credentials.with_scopes(\n", + " ['https://www.googleapis.com/auth/cloud-platform', 'https://www.googleapis.com/auth/generative-language.retriever'])\n", + "\n", + "genai.configure(credentials=scoped_credentials)\n", + "\n", + "print('Available base models:', [m.name for m in genai.list_models()])" + ] + } + ], + "metadata": { + "colab": { + "name": "Authentication_with_OAuth.ipynb", + "toc_visible": true + }, + "google": { + "image_path": "/site-assets/images/share.png", + "keywords": [ + "examples", + "googleai", + "samplecode", + "python", + "embed", + "function" + ] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" } - ], - "source": [ - "!pip install -U -q google-generativeai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "r8GgGmTrUCR2" - }, - "source": [ - "Let's do a quick test. Note that you did not set an API key using `genai.configure()`!" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "TS9l5igubpHO" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai\n", - "\n", - "print('Available base models:', [m.name for m in genai.list_models()])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dzSRvbxnUmLo" - }, - "source": [ - "# Appendix" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "arP-ISIBUrdv" - }, - "source": [ - "## Making authenticated REST calls from Colab\n", - "\n", - "In general, you should use the Python SDK to interact with the Gemini API when possible. This example shows how to make OAuth authenticated REST calls from Python for debugging or testing purposes. It assumes you have already set application default credentials from the Quickstart." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "6V_vD8A2Wm28" - }, - "outputs": [], - "source": [ - "import requests\n", - "\n", - "access_token = !gcloud auth application-default print-access-token\n", - "\n", - "headers = {\n", - " 'Content-Type': 'application/json',\n", - " 'Authorization': f'Bearer {access_token[0]}',\n", - "}\n", - "\n", - "response = requests.get('https://generativelanguage.googleapis.com/v1/models', headers=headers)\n", - "response_json = response.json()\n", - "\n", - "# All the model names\n", - "for model in response_json['models']:\n", - " print(model['name'])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lisiHaB8Wwi9" - }, - "source": [ - "### Share a tuned model\n", - "\n", - "Some beta API features may not be supported by the Python SDK yet. This example shows how to make a REST call to add a permission to a tuned model from Python." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ijMDsUj5o6RL" - }, - "outputs": [], - "source": [ - "import requests\n", - "\n", - "model_name = '' # @param {type:\"string\"}\n", - "emailAddress = '' # @param {type:\"string\"}\n", - "\n", - "\n", - "access_token = !gcloud auth application-default print-access-token\n", - "\n", - "headers = {\n", - " 'Content-Type': 'application/json',\n", - " 'Authorization': f'Bearer {access_token[0]}',\n", - "}\n", - "\n", - "body = {\n", - " 'granteeType': 'USER', # Or 'GROUP' or 'EVERYONE' https://ai.google.dev/api/rest/v1beta/tunedModels.permissions\n", - " 'emailAddress': emailAddress, # Optional if 'granteeType': 'EVERYONE'\n", - " 'role': 'READER'\n", - "}\n", - "\n", - "response = requests.post(f'https://generativelanguage.googleapis.com/v1beta/tunedModels/{model_name}/permissions', json=body, headers=headers)\n", - "print(response.json())\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "HnKP_dX_Wnr7" - }, - "source": [ - "## Use a service account to authenticate\n", - "\n", - "Google Cloud [service accounts](https://cloud.google.com/iam/docs/service-account-overview) are accounts that do not represent a human user. They provide a way to manage authentication and authorization when a human is not directly involved, such as your application calling the Gemini API to fulfill a user request, but not authenticated as the user. A simple way to use service accounts to authenticate with the Gemini API is to use a [service account key](https://cloud.google.com/docs/authentication/provide-credentials-adc#local-key).\n", - "\n", - "This guide briefly covers how to use service account keys in Google Colab.\n", - "\n", - "**Important:** Service account keys can be a security risk! For more information, see [best practices for managing service account keys](https://cloud.google.com/iam/docs/best-practices-for-managing-service-account-keys).\n", - "\n", - "### 1. Create a service account\n", - "\n", - "Follow the instructions to [create a service account](https://cloud.google.com/iam/docs/service-accounts-create#creating). The **Console** instructions are easiest if you are doing this manually.\n", - "\n", - "### 2. Create a service account key\n", - "\n", - "Follow the instructions to [create a service account key]( https://cloud.google.com/iam/docs/keys-create-delete#creating). Note the name of the downloaded key.\n", - "\n", - "### 3. Add the service account key to Colab\n", - "\n", - "1. Open your Google Colab notebook and click on the πŸ”‘ **Secrets** tab in the left panel.\n", - "2. Create a new secret with the name `SERVICE_ACCOUNT_KEY`.\n", - "3. Open your service account key file in a text editor and copy/paste the content into the `Value` input box of `SERVICE_ACCOUNT_KEY`.\n", - "4. Toggle the button on the left to allow notebook access to the secret.\n", - "\n", - "### 4. Authenticate with the Python SDK by service account key" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "f62ztB6mkRk5" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai\n", - "import pathlib\n", - "from google.colab import userdata\n", - "from google.oauth2 import service_account\n", - "\n", - "pathlib.Path('service_account_key.json').write_text(userdata.get('SERVICE_ACCOUNT_KEY'))\n", - "\n", - "credentials = service_account.Credentials.from_service_account_file('service_account_key.json')\n", - "\n", - "# Adjust scopes as needed\n", - "scoped_credentials = credentials.with_scopes(\n", - " ['https://www.googleapis.com/auth/cloud-platform', 'https://www.googleapis.com/auth/generative-language.retriever'])\n", - "\n", - "genai.configure(credentials=scoped_credentials)\n", - "\n", - "print('Available base models:', [m.name for m in genai.list_models()])" - ] - } - ], - "metadata": { - "colab": { - "name": "Authentication_with_OAuth.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "google": { - "image_path": "/site-assets/images/share.png", - "keywords": [ - "examples", - "googleai", - "samplecode", - "python", - "embed", - "function" - ] - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/Counting_Tokens.ipynb b/quickstarts/Counting_Tokens.ipynb index 361c75825..d25cfadb3 100644 --- a/quickstarts/Counting_Tokens.ipynb +++ b/quickstarts/Counting_Tokens.ipynb @@ -1,560 +1,525 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "YZXn1Salxl_w" - }, - "source": [ - "# Gemini API: All about tokens" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3FIB-JDtxgUE" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "CRzxdrjKLTJa" - }, - "source": [ - "An understanding of tokens is central to using the Gemini API. This guide will provide a interactive introduction to what tokens are and how they are used in the Gemini API.\n", - "\n", - "## About tokens\n", - "\n", - "LLMs break up their input and produce their output at a granularity that is smaller than a word, but larger than a single character or code-point.\n", - "\n", - "These **tokens** can be single characters, like `z`, or whole words, like `the`. Long words may be broken up into several tokens. The set of all tokens used by the model is called the vocabulary, and the process of breaking down text into tokens is called tokenization.\n", - "\n", - "For Gemini models, a token is equivalent to about 4 characters. **100 tokens are about 60-80 English words**.\n", - "\n", - "When billing is enabled, the price of a paid request is controlled by the [number of input and output tokens](https://ai.google.dev/pricing), so knowing how to count your tokens is important.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xwJ1lyGC_Ia4" - }, - "source": [ - "## Tokens in the Gemini API" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "GBa_hMFneZKO" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "OzsRfmWrxd_F" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IG_wSwTJ2wAP" - }, - "source": [ - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LyWgDDHr1yxd" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "GOOGLE_API_KEY = userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "etlFvMXP3Gb7" - }, - "source": [ - "### Context windows\n", - "\n", - "The models available through the Gemini API have context windows that are measured in tokens. These define how much input you can provide, and how much output the model can generate, and combined are referred to as the \"context window\". This information is available directly through [the API](https://ai.google.dev/api/rest/v1/models/get) and in the [models](https://ai.google.dev/models/gemini) documentation.\n", - "\n", - "In this example you can see the `gemini-1.5-flash-latest` model has an 1M tokens context window." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "1QC23D2z3GLV", - "tags": [] - }, - "outputs": [], - "source": [ - "model_info = genai.get_model('models/gemini-1.5-flash-latest')\n", - "(model_info.input_token_limit, model_info.output_token_limit)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kkh8v5QI4v5h" - }, - "source": [ - "## Counting tokens\n", - "\n", - "The API provides an endpoint for counting the number of tokens in a request: [`GenerativeModel.count_tokens`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#count_tokens). You pass the same arguments as you would to [`GenerativeModel.generate_content`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) and the service will return the number of tokens in that request." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "F0J8JPYbCGnv" - }, - "source": [ - "### Text tokens" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "7jpoJFpX5Cu_", - "tags": [] - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel('models/gemini-1.5-flash-latest')\n", - "model.count_tokens(\"The quick brown fox jumps over the lazy dog.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0661517a2417" - }, - "source": [ - "When you call `GenerativeModel.generate_content` (or `ChatSession.send_message`) the response object has a `usage_metadata` attribute containing both the input and output token counts (`prompt_token_count` and `candidates_token_count`):" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "71aa6568a670", - "tags": [] - }, - "outputs": [], - "source": [ - "response = model.generate_content(\"The quick brown fox jumps over the lazy dog.\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "response.usage_metadata" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "SQzJ7asV-HJB" - }, - "source": [ - "### Multi-turn tokens\n", - "\n", - "Multi-turn conversational (chat) objects work similarly." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "eqUpyE_E95_w", - "tags": [] - }, - "outputs": [], - "source": [ - "chat = model.start_chat(history=[{'role':'user', 'parts':'Hi my name is Bob'}, {'role':'model', 'parts':'Hi Bob!'}])\n", - "model.count_tokens(chat.history)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "68ae99485a0c", - "tags": [] - }, - "outputs": [], - "source": [ - "chat" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zMvjgRkVAvVN" - }, - "source": [ - "To understand how big your next conversational turn will be, you will need to append it to the history when you call `count_tokens`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "pxVsykc5A5he", - "tags": [] - }, - "outputs": [], - "source": [ - "from google.generativeai.types.content_types import to_contents\n", - "model.count_tokens(chat.history + to_contents('What is the meaning of life?'))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZZYcaUXl-Sna" - }, - "source": [ - "### Multi-modal tokens\n", - "\n", - "All input to the API is tokenized, including images or other non-text modalities." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "hsKfX8LYAdLv", - "tags": [] - }, - "outputs": [], - "source": [ - "!curl -L https://goo.gle/instrument-img -o organ.jpg" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Jzwrahub-ez5", - "tags": [] - }, - "outputs": [], - "source": [ - "import PIL\n", - "from IPython.display import display, Image\n", - "\n", - "display(Image('organ.jpg', width=300))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "c4164419d70f" - }, - "source": [ - "#### Inline content\n", - "\n", - "Media objects can be sent to the API inline with the request:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Ledzam3H__Ob", - "tags": [] - }, - "outputs": [], - "source": [ - "organ = PIL.Image.open('organ.jpg')\n", - "model.count_tokens(['Tell me about this instrument', organ])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "b3851a09ec17" - }, - "source": [ - "#### Files API\n", - "\n", - "The model sees identical tokens if you upload parts of the prompt through the files API instead:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "f994c2dd6e05", - "tags": [] - }, - "outputs": [], - "source": [ - "organ_upload = genai.upload_file('organ.jpg')\n", - "\n", - "model.count_tokens(['Tell me about this instrument', organ_upload])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "UXF0vpdG_H_Q" - }, - "source": [ - "### Media token counts\n", - "\n", - "Internally, images are a fixed size, so they consume a fixed number of tokens." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "sPPfXRJiA3KV", - "tags": [] - }, - "outputs": [], - "source": [ - "!curl -O \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\" --silent" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "jqG83Rko8UpG", - "tags": [] - }, - "outputs": [], - "source": [ - "jetpack = PIL.Image.open('jetpack.jpg')\n", - "display(Image('jetpack.jpg', width=300))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "hc0CBsl6_Tkk", - "tags": [] - }, - "outputs": [], - "source": [ - "print(organ.size)\n", - "print(model.count_tokens(organ))\n", - "\n", - "print(jetpack.size)\n", - "print(model.count_tokens(jetpack))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "8342199c9eb4" - }, - "source": [ - "Audio and video are each converted to tokens at a fixed rate of tokens per minute." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "be103816898c", - "tags": [] - }, - "outputs": [], - "source": [ - "!curl -q -o sample.mp3 \"https://storage.googleapis.com/generativeai-downloads/data/State_of_the_Union_Address_30_January_1961.mp3\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ada734553530", - "tags": [] - }, - "outputs": [], - "source": [ - "audio_sample = genai.upload_file('sample.mp3')\n", - "model.count_tokens(audio_sample)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "a9367d1afac3" - }, - "source": [ - "### System instructions and tools\n", - "\n", - "System instructions and tools also count towards the total:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "c2a83ac75dfe", - "tags": [] - }, - "outputs": [], - "source": [ - "genai.GenerativeModel().count_tokens(\"The quick brown fox jumps over the lazy dog.\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "c275fafdf080", - "tags": [] - }, - "outputs": [], - "source": [ - "genai.GenerativeModel(system_instruction='Talk like a pirate!').count_tokens(\"The quick brown fox jumps over the lazy dog.\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "5fcff3d1403e", - "tags": [] - }, - "outputs": [], - "source": [ - "def add(a:float, b:float):\n", - " \"\"\"returns a + b.\"\"\"\n", - " return a+b\n", - "\n", - "def subtract(a:float, b:float):\n", - " \"\"\"returns a - b.\"\"\"\n", - " return a-b\n", - "\n", - "def multiply(a:float, b:float):\n", - " \"\"\"returns a * b.\"\"\"\n", - " return a*b\n", - "\n", - "def divide(a:float, b:float):\n", - " \"\"\"returns a / b.\"\"\"\n", - " return a*b\n", - "\n", - "model = genai.GenerativeModel(model_name='gemini-1.5-flash-latest',\n", - " tools=[add, subtract, multiply, divide])\n", - "model.count_tokens(\"The quick brown fox jumps over the lazy dog.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "QfZNBWZLDCXa" - }, - "source": [ - "## Further reading\n", - "\n", - "For more on token counting, check out the API reference.\n", - "\n", - "* [countTokens](https://ai.google.dev/api/rest/v1/models/countTokens) REST API reference,\n", - "* [count_tokens](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#count_tokens) Python API reference," - ] - } - ], - "metadata": { - "colab": { - "name": "Counting_Tokens.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "YZXn1Salxl_w" + }, + "source": [ + "# Gemini API: All about tokens" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3FIB-JDtxgUE" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "CRzxdrjKLTJa" + }, + "source": [ + "An understanding of tokens is central to using the Gemini API. This guide will provide a interactive introduction to what tokens are and how they are used in the Gemini API.\n", + "\n", + "## About tokens\n", + "\n", + "LLMs break up their input and produce their output at a granularity that is smaller than a word, but larger than a single character or code-point.\n", + "\n", + "These **tokens** can be single characters, like `z`, or whole words, like `the`. Long words may be broken up into several tokens. The set of all tokens used by the model is called the vocabulary, and the process of breaking down text into tokens is called tokenization.\n", + "\n", + "For Gemini models, a token is equivalent to about 4 characters. **100 tokens are about 60-80 English words**.\n", + "\n", + "When billing is enabled, the price of a paid request is controlled by the [number of input and output tokens](https://ai.google.dev/pricing), so knowing how to count your tokens is important.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xwJ1lyGC_Ia4" + }, + "source": [ + "## Tokens in the Gemini API" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "GBa_hMFneZKO" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "OzsRfmWrxd_F" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IG_wSwTJ2wAP" + }, + "source": [ + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "LyWgDDHr1yxd" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "GOOGLE_API_KEY = userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "etlFvMXP3Gb7" + }, + "source": [ + "### Context windows\n", + "\n", + "The models available through the Gemini API have context windows that are measured in tokens. These define how much input you can provide, and how much output the model can generate, and combined are referred to as the \"context window\". This information is available directly through [the API](https://ai.google.dev/api/rest/v1/models/get) and in the [models](https://ai.google.dev/models/gemini) documentation.\n", + "\n", + "In this example you can see the `gemini-1.5-flash-latest` model has an 1M tokens context window." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "1QC23D2z3GLV" + }, + "outputs": [], + "source": [ + "model_info = genai.get_model('models/gemini-1.5-flash-latest')\n", + "(model_info.input_token_limit, model_info.output_token_limit)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kkh8v5QI4v5h" + }, + "source": [ + "## Counting tokens\n", + "\n", + "The API provides an endpoint for counting the number of tokens in a request: [`GenerativeModel.count_tokens`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#count_tokens). You pass the same arguments as you would to [`GenerativeModel.generate_content`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) and the service will return the number of tokens in that request." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "F0J8JPYbCGnv" + }, + "source": [ + "### Text tokens" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "7jpoJFpX5Cu_" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('models/gemini-1.5-flash-latest')\n", + "model.count_tokens(\"The quick brown fox jumps over the lazy dog.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0661517a2417" + }, + "source": [ + "When you call `GenerativeModel.generate_content` (or `ChatSession.send_message`) the response object has a `usage_metadata` attribute containing both the input and output token counts (`prompt_token_count` and `candidates_token_count`):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "71aa6568a670" + }, + "outputs": [], + "source": [ + "response = model.generate_content(\"The quick brown fox jumps over the lazy dog.\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "1dacccfcbf5f" + }, + "outputs": [], + "source": [ + "response.usage_metadata" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "SQzJ7asV-HJB" + }, + "source": [ + "### Multi-turn tokens\n", + "\n", + "Multi-turn conversational (chat) objects work similarly." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "eqUpyE_E95_w" + }, + "outputs": [], + "source": [ + "chat = model.start_chat(history=[{'role':'user', 'parts':'Hi my name is Bob'}, {'role':'model', 'parts':'Hi Bob!'}])\n", + "model.count_tokens(chat.history)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "68ae99485a0c" + }, + "outputs": [], + "source": [ + "chat" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zMvjgRkVAvVN" + }, + "source": [ + "To understand how big your next conversational turn will be, you will need to append it to the history when you call `count_tokens`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "pxVsykc5A5he" + }, + "outputs": [], + "source": [ + "from google.generativeai.types.content_types import to_contents\n", + "model.count_tokens(chat.history + to_contents('What is the meaning of life?'))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZZYcaUXl-Sna" + }, + "source": [ + "### Multi-modal tokens\n", + "\n", + "All input to the API is tokenized, including images or other non-text modalities." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "hsKfX8LYAdLv" + }, + "outputs": [], + "source": [ + "!curl -L https://goo.gle/instrument-img -o organ.jpg" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Jzwrahub-ez5" + }, + "outputs": [], + "source": [ + "import PIL\n", + "from IPython.display import display, Image\n", + "\n", + "display(Image('organ.jpg', width=300))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "c4164419d70f" + }, + "source": [ + "#### Inline content\n", + "\n", + "Media objects can be sent to the API inline with the request:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Ledzam3H__Ob" + }, + "outputs": [], + "source": [ + "organ = PIL.Image.open('organ.jpg')\n", + "model.count_tokens(['Tell me about this instrument', organ])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "b3851a09ec17" + }, + "source": [ + "#### Files API\n", + "\n", + "The model sees identical tokens if you upload parts of the prompt through the files API instead:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "f994c2dd6e05" + }, + "outputs": [], + "source": [ + "organ_upload = genai.upload_file('organ.jpg')\n", + "\n", + "model.count_tokens(['Tell me about this instrument', organ_upload])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "UXF0vpdG_H_Q" + }, + "source": [ + "### Media token counts\n", + "\n", + "Internally, images are a fixed size, so they consume a fixed number of tokens." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "sPPfXRJiA3KV" + }, + "outputs": [], + "source": [ + "!curl -O \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\" --silent" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "jqG83Rko8UpG" + }, + "outputs": [], + "source": [ + "jetpack = PIL.Image.open('jetpack.jpg')\n", + "display(Image('jetpack.jpg', width=300))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "hc0CBsl6_Tkk" + }, + "outputs": [], + "source": [ + "print(organ.size)\n", + "print(model.count_tokens(organ))\n", + "\n", + "print(jetpack.size)\n", + "print(model.count_tokens(jetpack))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8342199c9eb4" + }, + "source": [ + "Audio and video are each converted to tokens at a fixed rate of tokens per minute." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "be103816898c" + }, + "outputs": [], + "source": [ + "!curl -q -o sample.mp3 \"https://storage.googleapis.com/generativeai-downloads/data/State_of_the_Union_Address_30_January_1961.mp3\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ada734553530" + }, + "outputs": [], + "source": [ + "audio_sample = genai.upload_file('sample.mp3')\n", + "model.count_tokens(audio_sample)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "a9367d1afac3" + }, + "source": [ + "### System instructions and tools\n", + "\n", + "System instructions and tools also count towards the total:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "c2a83ac75dfe" + }, + "outputs": [], + "source": [ + "genai.GenerativeModel().count_tokens(\"The quick brown fox jumps over the lazy dog.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "c275fafdf080" + }, + "outputs": [], + "source": [ + "genai.GenerativeModel(system_instruction='Talk like a pirate!').count_tokens(\"The quick brown fox jumps over the lazy dog.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "5fcff3d1403e" + }, + "outputs": [], + "source": [ + "def add(a:float, b:float):\n", + " \"\"\"returns a + b.\"\"\"\n", + " return a+b\n", + "\n", + "def subtract(a:float, b:float):\n", + " \"\"\"returns a - b.\"\"\"\n", + " return a-b\n", + "\n", + "def multiply(a:float, b:float):\n", + " \"\"\"returns a * b.\"\"\"\n", + " return a*b\n", + "\n", + "def divide(a:float, b:float):\n", + " \"\"\"returns a / b.\"\"\"\n", + " return a*b\n", + "\n", + "model = genai.GenerativeModel(model_name='gemini-1.5-flash-latest',\n", + " tools=[add, subtract, multiply, divide])\n", + "model.count_tokens(\"The quick brown fox jumps over the lazy dog.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "QfZNBWZLDCXa" + }, + "source": [ + "## Further reading\n", + "\n", + "For more on token counting, check out the API reference.\n", + "\n", + "* [countTokens](https://ai.google.dev/api/rest/v1/models/countTokens) REST API reference,\n", + "* [count_tokens](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#count_tokens) Python API reference," + ] + } + ], + "metadata": { + "colab": { + "name": "Counting_Tokens.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/File_API.ipynb b/quickstarts/File_API.ipynb index 090d3a637..b83d47eca 100644 --- a/quickstarts/File_API.ipynb +++ b/quickstarts/File_API.ipynb @@ -1,384 +1,360 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "PzjeBM__IE1k" + }, + "source": [ + "# Gemini API: File API Quickstart\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "084u8u0DpBlo" + }, + "source": [ + "The Gemini API supports prompting with text, image, and audio data, also known as *multimodal* prompting. You can include text, image,\n", + "and audio in your prompts. For small images, you can point the Gemini model\n", + "directly to a local file when providing a prompt. For larger text files, images, videos, and audio, upload the files with the [File\n", + "API](https://ai.google.dev/api/rest/v1beta/files) before including them in\n", + "prompts.\n", + "\n", + "The File API lets you store up to 20GB of files per project, with each file not\n", + "exceeding 2GB in size. Files are stored for 48 hours and can be accessed with\n", + "your API key for generation within that time period. It is available at no cost in all regions where the [Gemini API is\n", + "available](https://ai.google.dev/available_regions).\n", + "\n", + "For information on valid file formats (MIME types) and supported models, see the documentation on\n", + "[supported file formats](https://ai.google.dev/tutorials/prompting_with_media#supported_file_formats)\n", + "and view the text examples at the end of this guide.\n", + "\n", + "This guide shows how to use the File API to upload a media file and include it in a `GenerateContent` call to the Gemini API. For more information, see the [code\n", + "samples](https://github.com/google-gemini/cookbook/tree/main/quickstarts/file-api).\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "_d_yY8XWGQ12" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TeVyF3GtGQ13" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai\n", + "from IPython.display import Image" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "YdyC6Z6wqxz-" + }, + "source": [ + "## Authentication\n", + "\n", + "**Important:** The File API uses API keys for authentication and access. Uploaded files are associated with the API key's cloud project. Unlike other Gemini APIs that use API keys, your API key also grants access data you've uploaded to the File API, so take extra care in keeping your API key secure. For best practices on securing API keys, refer to Google's [documentation](https://support.google.com/googleapi/answer/6310037)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "l8g4hTRotheH" + }, + "source": [ + "### Setup your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "iWd---jVKV5M" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "\n", + "GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "c-z4zsCUlaru" + }, + "source": [ + "## Upload file\n", + "\n", + "The File API lets you upload a variety of multimodal MIME types, including images and audio formats. The File API handles inputs that can be used to generate content with [`model.generateContent`](https://ai.google.dev/api/rest/v1/models/generateContent) or [`model.streamGenerateContent`](https://ai.google.dev/api/rest/v1/models/streamGenerateContent).\n", + "\n", + "The File API accepts files under 2GB in size and can store up to 20GB of files per project. Files last for 2 days and cannot be downloaded from the API." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2wsJ0vHNNtdJ" + }, + "source": [ + "First, you will prepare a sample image to upload to the API.\n", + "\n", + "Note: You can also [upload your own files](https://github.com/google-gemini/cookbook/tree/main/examples/Upload_files_to_Colab.ipynb) to use." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "EfuQVRXIGqvt" + }, + "outputs": [], + "source": [ + "!curl -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\"\n", + "Image(filename=\"image.jpg\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EEoXN0f3N2yc" + }, + "source": [ + "Next, you will upload that file to the File API." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "N9NxXGZKKusG" + }, + "outputs": [], + "source": [ + "sample_file = genai.upload_file(path=\"image.jpg\", display_name=\"Sample drawing\")\n", + "\n", + "print(f\"Uploaded file '{sample_file.display_name}' as: {sample_file.uri}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "smAIH077GQ14" + }, + "source": [ + "The `response` shows that the File API stored the specified `display_name` for the uploaded file and a `uri` to reference the file in Gemini API calls. Use `response` to track how uploaded files are mapped to URIs.\n", + "\n", + "Depending on your use cases, you could store the URIs in structures such as a `dict` or a database." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "oOZmTUb4FWOa" + }, + "source": [ + "## Get file\n", + "\n", + "After uploading the file, you can verify the API has successfully received the files by calling `files.get`.\n", + "\n", + "It lets you get the file metadata that have been uploaded to the File API that are associated with the Cloud project your API key belongs to. Only the `name` (and by extension, the `uri`) are unique. Only use the `displayName` to identify files if you manage uniqueness yourself." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "SHMVCWHkFhJW" + }, + "outputs": [], + "source": [ + "file = genai.get_file(name=sample_file.name)\n", + "print(f\"Retrieved file '{file.display_name}' as: {sample_file.uri}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EPPOECHzsIGJ" + }, + "source": [ + "## Generate content\n", + "\n", + "After uploading the file, you can make `GenerateContent` requests that reference the file by providing the URI. In the Python SDK you can pass the returned object directly.\n", + "\n", + "Here you create a prompt that starts with text and includes the uploaded image." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "226e5365ab6b" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-flash-latest\")\n", + "\n", + "response = model.generate_content(\n", + " [\"Describe the image with a creative description.\", sample_file]\n", + ")\n", + "\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IrPDYdQSKTg4" + }, + "source": [ + "## Delete files\n", + "\n", + "Files are automatically deleted after 2 days or you can manually delete them using `files.delete()`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "d4eO8ZXoKdZf" + }, + "outputs": [], + "source": [ + "genai.delete_file(sample_file.name)\n", + "print(f\"Deleted {sample_file.display_name}.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "u_aF5anOvKsO" + }, + "source": [ + "## Supported text types\n", + "\n", + "As well as supporting media uploads, the File API can be used to embed text files, such as Python code, or Markdown files, into your prompts.\n", + "\n", + "This example shows you how to load a markdown file into a prompt using the File API." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "93c5679a43c2" + }, + "outputs": [], + "source": [ + "# Download a markdown file and ask a question.\n", + "\n", + "!curl -so contrib.md https://raw.githubusercontent.com/google-gemini/cookbook/main/CONTRIBUTING.md\n", + "\n", + "md_file = genai.upload_file(path=\"contrib.md\", display_name=\"Contributors guide\", mime_type=\"text/markdown\")\n", + "\n", + "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-flash-latest\")\n", + "response = model.generate_content(\n", + " [\n", + " \"What should I do before I start writing, when following these guidelines?\",\n", + " md_file,\n", + " ]\n", + ")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pmmVaBz4Ss3W" + }, + "source": [ + "Some common text formats are automatically detected, such as `text/x-python`, `text/html` and `text/markdown`. If you are using a file that you know is text, but is not automatically detected by the API as such, you can specify the MIME type as `text/plain` explicitly." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "b24d8a2c8109" + }, + "outputs": [], + "source": [ + "# Download some C++ code and force the MIME as text when uploading.\n", + "\n", + "!curl -so gemma.cpp https://raw.githubusercontent.com/google/gemma.cpp/main/examples/hello_world/run.cc\n", + "\n", + "cpp_file = genai.upload_file(\n", + " path=\"gemma.cpp\", display_name=\"gemma.cpp\", mime_type=\"text/plain\"\n", + ")\n", + "\n", + "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-flash-latest\")\n", + "response = model.generate_content([\"What does this program do?\", cpp_file])\n", + "print(response.text)" + ] + } + ], + "metadata": { + "colab": { + "name": "File_API.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "PzjeBM__IE1k" - }, - "source": [ - "# Gemini API: File API Quickstart\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "084u8u0DpBlo" - }, - "source": [ - "The Gemini API supports prompting with text, image, and audio data, also known as *multimodal* prompting. You can include text, image,\n", - "and audio in your prompts. For small images, you can point the Gemini model\n", - "directly to a local file when providing a prompt. For larger text files, images, videos, and audio, upload the files with the [File\n", - "API](https://ai.google.dev/api/rest/v1beta/files) before including them in\n", - "prompts.\n", - "\n", - "The File API lets you store up to 20GB of files per project, with each file not\n", - "exceeding 2GB in size. Files are stored for 48 hours and can be accessed with\n", - "your API key for generation within that time period. It is available at no cost in all regions where the [Gemini API is\n", - "available](https://ai.google.dev/available_regions).\n", - "\n", - "For information on valid file formats (MIME types) and supported models, see the documentation on\n", - "[supported file formats](https://ai.google.dev/tutorials/prompting_with_media#supported_file_formats)\n", - "and view the text examples at the end of this guide.\n", - "\n", - "This guide shows how to use the File API to upload a media file and include it in a `GenerateContent` call to the Gemini API. For more information, see the [code\n", - "samples](https://github.com/google-gemini/cookbook/tree/main/quickstarts/file-api).\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "_d_yY8XWGQ12" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "TeVyF3GtGQ13", - "tags": [] - }, - "outputs": [], - "source": [ - "import google.generativeai as genai\n", - "from IPython.display import Image" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "YdyC6Z6wqxz-" - }, - "source": [ - "## Authentication\n", - "\n", - "**Important:** The File API uses API keys for authentication and access. Uploaded files are associated with the API key's cloud project. Unlike other Gemini APIs that use API keys, your API key also grants access data you've uploaded to the File API, so take extra care in keeping your API key secure. For best practices on securing API keys, refer to Google's [documentation](https://support.google.com/googleapi/answer/6310037)." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "l8g4hTRotheH" - }, - "source": [ - "### Setup your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "iWd---jVKV5M" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "\n", - "GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "c-z4zsCUlaru" - }, - "source": [ - "## Upload file\n", - "\n", - "The File API lets you upload a variety of multimodal MIME types, including images and audio formats. The File API handles inputs that can be used to generate content with [`model.generateContent`](https://ai.google.dev/api/rest/v1/models/generateContent) or [`model.streamGenerateContent`](https://ai.google.dev/api/rest/v1/models/streamGenerateContent).\n", - "\n", - "The File API accepts files under 2GB in size and can store up to 20GB of files per project. Files last for 2 days and cannot be downloaded from the API." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2wsJ0vHNNtdJ" - }, - "source": [ - "First, you will prepare a sample image to upload to the API.\n", - "\n", - "Note: You can also [upload your own files](https://github.com/google-gemini/cookbook/tree/main/examples/Upload_files_to_Colab.ipynb) to use." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "EfuQVRXIGqvt", - "tags": [] - }, - "outputs": [], - "source": [ - "!curl -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\"\n", - "Image(filename=\"image.jpg\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "EEoXN0f3N2yc" - }, - "source": [ - "Next, you will upload that file to the File API." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "N9NxXGZKKusG", - "tags": [] - }, - "outputs": [], - "source": [ - "sample_file = genai.upload_file(path=\"image.jpg\", display_name=\"Sample drawing\")\n", - "\n", - "print(f\"Uploaded file '{sample_file.display_name}' as: {sample_file.uri}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "smAIH077GQ14" - }, - "source": [ - "The `response` shows that the File API stored the specified `display_name` for the uploaded file and a `uri` to reference the file in Gemini API calls. Use `response` to track how uploaded files are mapped to URIs.\n", - "\n", - "Depending on your use cases, you could store the URIs in structures such as a `dict` or a database." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "oOZmTUb4FWOa" - }, - "source": [ - "## Get file\n", - "\n", - "After uploading the file, you can verify the API has successfully received the files by calling `files.get`.\n", - "\n", - "It lets you get the file metadata that have been uploaded to the File API that are associated with the Cloud project your API key belongs to. Only the `name` (and by extension, the `uri`) are unique. Only use the `displayName` to identify files if you manage uniqueness yourself." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "SHMVCWHkFhJW", - "tags": [] - }, - "outputs": [], - "source": [ - "file = genai.get_file(name=sample_file.name)\n", - "print(f\"Retrieved file '{file.display_name}' as: {sample_file.uri}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "EPPOECHzsIGJ" - }, - "source": [ - "## Generate content\n", - "\n", - "After uploading the file, you can make `GenerateContent` requests that reference the file by providing the URI. In the Python SDK you can pass the returned object directly.\n", - "\n", - "Here you create a prompt that starts with text and includes the uploaded image." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-flash-latest\")\n", - "\n", - "response = model.generate_content(\n", - " [\"Describe the image with a creative description.\", sample_file]\n", - ")\n", - "\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IrPDYdQSKTg4" - }, - "source": [ - "## Delete files\n", - "\n", - "Files are automatically deleted after 2 days or you can manually delete them using `files.delete()`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "d4eO8ZXoKdZf", - "tags": [] - }, - "outputs": [], - "source": [ - "genai.delete_file(sample_file.name)\n", - "print(f\"Deleted {sample_file.display_name}.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "u_aF5anOvKsO" - }, - "source": [ - "## Supported text types\n", - "\n", - "As well as supporting media uploads, the File API can be used to embed text files, such as Python code, or Markdown files, into your prompts.\n", - "\n", - "This example shows you how to load a markdown file into a prompt using the File API." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "# Download a markdown file and ask a question.\n", - "\n", - "!curl -so contrib.md https://raw.githubusercontent.com/google-gemini/cookbook/main/CONTRIBUTING.md\n", - "\n", - "md_file = genai.upload_file(path=\"contrib.md\", display_name=\"Contributors guide\", mime_type=\"text/markdown\")\n", - "\n", - "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-flash-latest\")\n", - "response = model.generate_content(\n", - " [\n", - " \"What should I do before I start writing, when following these guidelines?\",\n", - " md_file,\n", - " ]\n", - ")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "pmmVaBz4Ss3W" - }, - "source": [ - "Some common text formats are automatically detected, such as `text/x-python`, `text/html` and `text/markdown`. If you are using a file that you know is text, but is not automatically detected by the API as such, you can specify the MIME type as `text/plain` explicitly." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "# Download some C++ code and force the MIME as text when uploading.\n", - "\n", - "!curl -so gemma.cpp https://raw.githubusercontent.com/google/gemma.cpp/main/examples/hello_world/run.cc\n", - "\n", - "cpp_file = genai.upload_file(\n", - " path=\"gemma.cpp\", display_name=\"gemma.cpp\", mime_type=\"text/plain\"\n", - ")\n", - "\n", - "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-flash-latest\")\n", - "response = model.generate_content([\"What does this program do?\", cpp_file])\n", - "print(response.text)" - ] - } - ], - "metadata": { - "colab": { - "name": "File_API.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/Function_calling.ipynb b/quickstarts/Function_calling.ipynb index 51592f184..4c957daf3 100644 --- a/quickstarts/Function_calling.ipynb +++ b/quickstarts/Function_calling.ipynb @@ -1,696 +1,664 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: Function calling with Python" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lEXQ3OwKIa-O" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "df1767a3d1cc" - }, - "source": [ - "Function calling lets developers create a description of a function in their code, then pass that description to a language model in a request. The response from the model includes the name of a function that matches the description and the arguments to call it with. Function calling lets you use functions as tools in generative AI applications, and you can define more than one function within a single request.\n", - "\n", - "This notebook provides code examples to help you get started." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9OEoeosRTv-5" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai # Install the Python SDK" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "TS9l5igubpHO" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "x-hHZfLZ7FfH" - }, - "source": [ - "## Set up your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ab9ASynfcIZn" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "\n", - "GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3f383614ec30" - }, - "source": [ - "## Function calling basics" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "b82c1aecb657" - }, - "source": [ - "To use function calling, pass a list of functions to the `tools` parameter when creating a [`GenerativeModel`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel). The model uses the function name, docstring, parameters, and parameter type annotations to decide if it needs the function to best answer a prompt.\n", - "\n", - "> Important: The SDK converts function parameter type annotations to a format the API understands (`glm.FunctionDeclaration`). The API only supports a limited selection of parameter types, and the Python SDK's automatic conversion only supports a subset of that: `AllowedTypes = int | float | bool | str | list['AllowedTypes'] | dict`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "42b27b02d2f5", - "tags": [] - }, - "outputs": [], - "source": [ - "def add(a: float, b: float):\n", - " \"\"\"returns a + b.\"\"\"\n", - " return a + b\n", - "\n", - "\n", - "def subtract(a: float, b: float):\n", - " \"\"\"returns a - b.\"\"\"\n", - " return a - b\n", - "\n", - "\n", - "def multiply(a: float, b: float):\n", - " \"\"\"returns a * b.\"\"\"\n", - " return a * b\n", - "\n", - "\n", - "def divide(a: float, b: float):\n", - " \"\"\"returns a / b.\"\"\"\n", - " return a / b\n", - "\n", - "\n", - "model = genai.GenerativeModel(\n", - " model_name=\"gemini-1.5-flash-latest\", tools=[add, subtract, multiply, divide]\n", - ")\n", - "\n", - "model" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "UzUgtaY99BTg" - }, - "source": [ - "## Automatic function calling" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "d5fd91032a1e" - }, - "source": [ - "Function calls naturally fit in to [multi-turn chats](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#multi-turn) as they capture a back and forth interaction between the user and model. The Python SDK's [`ChatSession`](https://ai.google.dev/api/python/google/generativeai/ChatSession) is a great interface for chats because handles the conversation history for you, and using the parameter `enable_automatic_function_calling` simplifies function calling even further:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "d3b91c855257", - "tags": [] - }, - "outputs": [], - "source": [ - "chat = model.start_chat(enable_automatic_function_calling=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "1481a6159399" - }, - "source": [ - "With automatic function calling enabled, `ChatSession.send_message` automatically calls your function if the model asks it to.\n", - "\n", - "In the following example, the result appears to simply be a text response containing the correct answer:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "81d8def3d865", - "tags": [] - }, - "outputs": [], - "source": [ - "response = chat.send_message(\n", - " \"I have 57 cats, each owns 44 mittens, how many mittens is that in total?\"\n", - ")\n", - "response.text" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "951c0f83f72e", - "tags": [] - }, - "outputs": [], - "source": [ - "57 * 44" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "7731e35f2383" - }, - "source": [ - "However, by examining the chat history, you can see the flow of the conversation and how function calls are integrated within it.\n", - "\n", - "The `ChatSession.history` property stores a chronological record of the conversation between the user and the Gemini model. Each turn in the conversation is represented by a [`glm.Content`](https://ai.google.dev/api/python/google/ai/generativelanguage/Content) object, which contains the following information:\n", - "\n", - "* **Role**: Identifies whether the content originated from the \"user\" or the \"model\".\n", - "* **Parts**: A list of [`glm.Part`](https://ai.google.dev/api/python/google/ai/generativelanguage/Part) objects that represent individual components of the message. With a text-only model, these parts can be:\n", - " * **Text**: Plain text messages.\n", - " * **Function Call** ([`glm.FunctionCall`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall)): A request from the model to execute a specific function with provided arguments.\n", - " * **Function Response** ([`glm.FunctionResponse`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse)): The result returned by the user after executing the requested function.\n", - "\n", - " In the previous example with the mittens calculation, the history shows the following sequence:\n", - "\n", - "1. **User**: Asks the question about the total number of mittens.\n", - "1. **Model**: Determines that the multiply function is helpful and sends a FunctionCall request to the user.\n", - "1. **User**: The `ChatSession` automatically executes the function (due to `enable_automatic_function_calling` being set) and sends back a `FunctionResponse` with the calculated result.\n", - "1. **Model**: Uses the function's output to formulate the final answer and presents it as a text response." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9f7eff1e8e60", - "tags": [] - }, - "outputs": [], - "source": [ - "for content in chat.history:\n", - " print(content.role, \"->\", [type(part).to_dict(part) for part in content.parts])\n", - " print(\"-\" * 80)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2471fd72f05e" - }, - "source": [ - "In general the state diagram is:\n", - "\n", - "\"The\n", - "\n", - "The model can respond with multiple function calls before returning a text response, and function calls come before the text response." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "eea8e3a0b89f" - }, - "source": [ - "## Manual function calling" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "9610f3465a69" - }, - "source": [ - "For more control, you can process [`glm.FunctionCall`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall) requests from the model yourself. This would be the case if:\n", - "\n", - "- You use a `ChatSession` with the default `enable_automatic_function_calling=False`.\n", - "- You use `GenerativeModel.generate_content` (and manage the chat history yourself)." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "34ffab0bf365" - }, - "source": [ - "The following example is a rough equivalent of the [function calling single-turn curl sample](https://ai.google.dev/docs/function_calling#function-calling-single-turn-curl-sample) in Python. It uses functions that return (mock) movie playtime information, possibly from a hypothetical API:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "46ba0fa3d09a", - "tags": [] - }, - "outputs": [], - "source": [ - "def find_movies(description: str, location: str = \"\"):\n", - " \"\"\"find movie titles currently playing in theaters based on any description, genre, title words, etc.\n", - "\n", - " Args:\n", - " description: Any kind of description including category or genre, title words, attributes, etc.\n", - " location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n", - " \"\"\"\n", - " return [\"Barbie\", \"Oppenheimer\"]\n", - "\n", - "\n", - "def find_theaters(location: str, movie: str = \"\"):\n", - " \"\"\"Find theaters based on location and optionally movie title which are is currently playing in theaters.\n", - "\n", - " Args:\n", - " location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n", - " movie: Any movie title\n", - " \"\"\"\n", - " return [\"Googleplex 16\", \"Android Theatre\"]\n", - "\n", - "\n", - "def get_showtimes(location: str, movie: str, theater: str, date: str):\n", - " \"\"\"\n", - " Find the start times for movies playing in a specific theater.\n", - "\n", - " Args:\n", - " location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n", - " movie: Any movie title\n", - " thearer: Name of the theater\n", - " date: Date for requested showtime\n", - " \"\"\"\n", - " return [\"10:00\", \"11:00\"]" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Ck-hdu5N8VlR" - }, - "source": [ - "Use a dictionary to make looking up functions by name easier later on. You can also use it to pass the array of functions to the `tools` parameter of `GenerativeModel`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "8i3SKdy18WHu", - "tags": [] - }, - "outputs": [], - "source": [ - "functions = {\n", - " \"find_movies\": find_movies,\n", - " \"find_theaters\": find_theaters,\n", - " \"get_showtimes\": get_showtimes,\n", - "}\n", - "\n", - "model = genai.GenerativeModel(model_name=\"gemini-1.5-flash-latest\", tools=functions.values())" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "11631c6e2b10" - }, - "source": [ - "After using `generate_content()` to ask a question, the model requests a `function_call`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "5e3b9c84d883", - "tags": [] - }, - "outputs": [], - "source": [ - "response = model.generate_content(\n", - " \"Which theaters in Mountain View show the Barbie movie?\"\n", - ")\n", - "response.candidates[0].content.parts" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kuldoypuAC1i" - }, - "source": [ - "Since this is not using a `ChatSession` with automatic function calling, you have to call the function yourself.\n", - "\n", - "A very simple way to do this would be with `if` statements:\n", - "\n", - "```python\n", - "if function_call.name == 'find_theaters':\n", - " find_theaters(**function_call.args)\n", - "elif ...\n", - "```\n", - "\n", - "However, since you already made the `functions` dictionary, this can be simplified to:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "rjkZ8MA00Coc", - "tags": [] - }, - "outputs": [], - "source": [ - "def call_function(function_call, functions):\n", - " function_name = function_call.name\n", - " function_args = function_call.args\n", - " return functions[function_name](**function_args)\n", - "\n", - "\n", - "part = response.candidates[0].content.parts[0]\n", - "\n", - "# Check if it's a function call; in real use you'd need to also handle text\n", - "# responses as you won't know what the model will respond with.\n", - "if part.function_call:\n", - " result = call_function(part.function_call, functions)\n", - "\n", - "print(result)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "XLWrHOatBtRz" - }, - "source": [ - "Finally, pass the response plus the message history to the next `generate_content()` call to get a final text response from the model." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "gdb62GstAD_3", - "tags": [] - }, - "outputs": [], - "source": [ - "import google.ai.generativelanguage as glm\n", - "from google.protobuf.struct_pb2 import Struct\n", - "\n", - "# Put the result in a protobuf Struct\n", - "s = Struct()\n", - "s.update({\"result\": result})\n", - "\n", - "# Update this after https://github.com/google/generative-ai-python/issues/243\n", - "function_response = glm.Part(\n", - " function_response=glm.FunctionResponse(name=\"find_theaters\", response=s)\n", - ")\n", - "\n", - "# Build the message history\n", - "messages = [\n", - " # fmt: off\n", - " {\"role\": \"user\",\n", - " \"parts\": [\"Which theaters in Mountain View show the Barbie movie?.\"]},\n", - " {\"role\": \"model\",\n", - " \"parts\": response.candidates[0].content.parts},\n", - " {\"role\": \"user\",\n", - " \"parts\": [function_response]},\n", - " # fmt: on\n", - "]\n", - "\n", - "# Generate the next response\n", - "response = model.generate_content(messages)\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "EuwKoNIhGBJN" - }, - "source": [ - "## Parallel function calls\n", - "\n", - "The Gemini API can call multiple functions in a single turn. This caters for scenarios where there are multiple function calls that can take place independently to complete a task.\n", - "\n", - "First set the tools up. Unlike the movie example above, these functions do not require input from each other to be called so they should be good candidates for parallel calling." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "cJ-mSixWGqLv", - "tags": [] - }, - "outputs": [], - "source": [ - "def power_disco_ball(power: bool) -> bool:\n", - " \"\"\"Powers the spinning disco ball.\"\"\"\n", - " print(f\"Disco ball is {'spinning!' if power else 'stopped.'}\")\n", - " return True\n", - "\n", - "\n", - "def start_music(energetic: bool, loud: bool, bpm: int) -> str:\n", - " \"\"\"Play some music matching the specified parameters.\n", - "\n", - " Args:\n", - " energetic: Whether the music is energetic or not.\n", - " loud: Whether the music is loud or not.\n", - " bpm: The beats per minute of the music.\n", - "\n", - " Returns: The name of the song being played.\n", - " \"\"\"\n", - " print(f\"Starting music! {energetic=} {loud=}, {bpm=}\")\n", - " return \"Never gonna give you up.\"\n", - "\n", - "\n", - "def dim_lights(brightness: float) -> bool:\n", - " \"\"\"Dim the lights.\n", - "\n", - " Args:\n", - " brightness: The brightness of the lights, 0.0 is off, 1.0 is full.\n", - " \"\"\"\n", - " print(f\"Lights are now set to {brightness:.0%}\")\n", - " return True" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zlrmXN7fxQi0" - }, - "source": [ - "Now call the model with an instruction that could use all of the specified tools." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "21ecYHLgIsCl", - "tags": [] - }, - "outputs": [], - "source": [ - "# Set the model up with tools.\n", - "house_fns = [power_disco_ball, start_music, dim_lights]\n", - "# Try this out with Pro and Flash...\n", - "model = genai.GenerativeModel(model_name=\"gemini-1.5-flash-latest\", tools=house_fns)\n", - "\n", - "# Call the API.\n", - "chat = model.start_chat()\n", - "response = chat.send_message(\"Turn this place into a party!\")\n", - "\n", - "# Print out each of the function calls requested from this single call.\n", - "for part in response.parts:\n", - " if fn := part.function_call:\n", - " args = \", \".join(f\"{key}={val}\" for key, val in fn.args.items())\n", - " print(f\"{fn.name}({args})\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "t6iYpty7yZct" - }, - "source": [ - "Each of the printed results reflects a single function call that the model has requested. To send the results back, include the responses in the same order as they were requested." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "L7RxoiR3foBR", - "tags": [] - }, - "outputs": [], - "source": [ - "import google.ai.generativelanguage as glm\n", - "\n", - "# Simulate the responses from the specified tools.\n", - "responses = {\n", - " \"power_disco_ball\": True,\n", - " \"start_music\": \"Never gonna give you up.\",\n", - " \"dim_lights\": True,\n", - "}\n", - "\n", - "# Build the response parts.\n", - "response_parts = [\n", - " glm.Part(function_response=glm.FunctionResponse(name=fn, response={\"result\": val}))\n", - " for fn, val in responses.items()\n", - "]\n", - "\n", - "response = chat.send_message(response_parts)\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "e0a3173919ca" - }, - "source": [ - "## Next Steps" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "7c2f31504490" - }, - "source": [ - "Useful API references:\n", - "\n", - "- The [genai.GenerativeModel](https://ai.google.dev/api/python/google/generativeai/GenerativeModel) class\n", - " - Its [GenerativeModel.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method builds a [glm.GenerateContentRequest](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentRequest) behind the scenes.\n", - " - The request's `.tools` field contains a list of 1 [glm.Tool](https://ai.google.dev/api/python/google/ai/generativelanguage/Tool) object.\n", - " - The tool's `function_declarations` attribute contains a list of [FunctionDeclarations](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionDeclaration) objects.\n", - "- The [response](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse) may contain a [glm.FunctionCall](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall), in `response.candidates[0].contents.parts[0]`.\n", - "- if `enable_automatic_function_calling` is set the [genai.ChatSession](https://ai.google.dev/api/python/google/generativeai/ChatSession) executes the call, and sends back the [glm.FunctionResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse).\n", - "- In response to a [FunctionCall](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall) the model always expects a [FunctionResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse).\n", - "- If you reply manually using [chat.send_message](https://ai.google.dev/api/python/google/generativeai/ChatSession#send_message) or [model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) remember thart the API is stateless you have to send the whole conversation history (a list of [content](https://ai.google.dev/api/python/google/ai/generativelanguage/Content) objects), not just the last one containing the `FunctionResponse`." - ] - } - ], - "metadata": { - "colab": { - "name": "Function_calling.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "google": { - "image_path": "/site-assets/images/share.png", - "keywords": [ - "examples", - "googleai", - "samplecode", - "python", - "embed", - "function" - ] - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: Function calling with Python" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lEXQ3OwKIa-O" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "df1767a3d1cc" + }, + "source": [ + "Function calling lets developers create a description of a function in their code, then pass that description to a language model in a request. The response from the model includes the name of a function that matches the description and the arguments to call it with. Function calling lets you use functions as tools in generative AI applications, and you can define more than one function within a single request.\n", + "\n", + "This notebook provides code examples to help you get started." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9OEoeosRTv-5" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai # Install the Python SDK" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TS9l5igubpHO" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "x-hHZfLZ7FfH" + }, + "source": [ + "## Set up your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ab9ASynfcIZn" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "\n", + "GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3f383614ec30" + }, + "source": [ + "## Function calling basics" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "b82c1aecb657" + }, + "source": [ + "To use function calling, pass a list of functions to the `tools` parameter when creating a [`GenerativeModel`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel). The model uses the function name, docstring, parameters, and parameter type annotations to decide if it needs the function to best answer a prompt.\n", + "\n", + "> Important: The SDK converts function parameter type annotations to a format the API understands (`glm.FunctionDeclaration`). The API only supports a limited selection of parameter types, and the Python SDK's automatic conversion only supports a subset of that: `AllowedTypes = int | float | bool | str | list['AllowedTypes'] | dict`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "42b27b02d2f5" + }, + "outputs": [], + "source": [ + "def add(a: float, b: float):\n", + " \"\"\"returns a + b.\"\"\"\n", + " return a + b\n", + "\n", + "\n", + "def subtract(a: float, b: float):\n", + " \"\"\"returns a - b.\"\"\"\n", + " return a - b\n", + "\n", + "\n", + "def multiply(a: float, b: float):\n", + " \"\"\"returns a * b.\"\"\"\n", + " return a * b\n", + "\n", + "\n", + "def divide(a: float, b: float):\n", + " \"\"\"returns a / b.\"\"\"\n", + " return a / b\n", + "\n", + "\n", + "model = genai.GenerativeModel(\n", + " model_name=\"gemini-1.5-flash-latest\", tools=[add, subtract, multiply, divide]\n", + ")\n", + "\n", + "model" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "UzUgtaY99BTg" + }, + "source": [ + "## Automatic function calling" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "d5fd91032a1e" + }, + "source": [ + "Function calls naturally fit in to [multi-turn chats](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#multi-turn) as they capture a back and forth interaction between the user and model. The Python SDK's [`ChatSession`](https://ai.google.dev/api/python/google/generativeai/ChatSession) is a great interface for chats because handles the conversation history for you, and using the parameter `enable_automatic_function_calling` simplifies function calling even further:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "d3b91c855257" + }, + "outputs": [], + "source": [ + "chat = model.start_chat(enable_automatic_function_calling=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "1481a6159399" + }, + "source": [ + "With automatic function calling enabled, `ChatSession.send_message` automatically calls your function if the model asks it to.\n", + "\n", + "In the following example, the result appears to simply be a text response containing the correct answer:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "81d8def3d865" + }, + "outputs": [], + "source": [ + "response = chat.send_message(\n", + " \"I have 57 cats, each owns 44 mittens, how many mittens is that in total?\"\n", + ")\n", + "response.text" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "951c0f83f72e" + }, + "outputs": [], + "source": [ + "57 * 44" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "7731e35f2383" + }, + "source": [ + "However, by examining the chat history, you can see the flow of the conversation and how function calls are integrated within it.\n", + "\n", + "The `ChatSession.history` property stores a chronological record of the conversation between the user and the Gemini model. Each turn in the conversation is represented by a [`glm.Content`](https://ai.google.dev/api/python/google/ai/generativelanguage/Content) object, which contains the following information:\n", + "\n", + "* **Role**: Identifies whether the content originated from the \"user\" or the \"model\".\n", + "* **Parts**: A list of [`glm.Part`](https://ai.google.dev/api/python/google/ai/generativelanguage/Part) objects that represent individual components of the message. With a text-only model, these parts can be:\n", + " * **Text**: Plain text messages.\n", + " * **Function Call** ([`glm.FunctionCall`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall)): A request from the model to execute a specific function with provided arguments.\n", + " * **Function Response** ([`glm.FunctionResponse`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse)): The result returned by the user after executing the requested function.\n", + "\n", + " In the previous example with the mittens calculation, the history shows the following sequence:\n", + "\n", + "1. **User**: Asks the question about the total number of mittens.\n", + "1. **Model**: Determines that the multiply function is helpful and sends a FunctionCall request to the user.\n", + "1. **User**: The `ChatSession` automatically executes the function (due to `enable_automatic_function_calling` being set) and sends back a `FunctionResponse` with the calculated result.\n", + "1. **Model**: Uses the function's output to formulate the final answer and presents it as a text response." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9f7eff1e8e60" + }, + "outputs": [], + "source": [ + "for content in chat.history:\n", + " print(content.role, \"->\", [type(part).to_dict(part) for part in content.parts])\n", + " print(\"-\" * 80)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2471fd72f05e" + }, + "source": [ + "In general the state diagram is:\n", + "\n", + "\"The\n", + "\n", + "The model can respond with multiple function calls before returning a text response, and function calls come before the text response." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "eea8e3a0b89f" + }, + "source": [ + "## Manual function calling" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9610f3465a69" + }, + "source": [ + "For more control, you can process [`glm.FunctionCall`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall) requests from the model yourself. This would be the case if:\n", + "\n", + "- You use a `ChatSession` with the default `enable_automatic_function_calling=False`.\n", + "- You use `GenerativeModel.generate_content` (and manage the chat history yourself)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "34ffab0bf365" + }, + "source": [ + "The following example is a rough equivalent of the [function calling single-turn curl sample](https://ai.google.dev/docs/function_calling#function-calling-single-turn-curl-sample) in Python. It uses functions that return (mock) movie playtime information, possibly from a hypothetical API:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "46ba0fa3d09a" + }, + "outputs": [], + "source": [ + "def find_movies(description: str, location: str = \"\"):\n", + " \"\"\"find movie titles currently playing in theaters based on any description, genre, title words, etc.\n", + "\n", + " Args:\n", + " description: Any kind of description including category or genre, title words, attributes, etc.\n", + " location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n", + " \"\"\"\n", + " return [\"Barbie\", \"Oppenheimer\"]\n", + "\n", + "\n", + "def find_theaters(location: str, movie: str = \"\"):\n", + " \"\"\"Find theaters based on location and optionally movie title which are is currently playing in theaters.\n", + "\n", + " Args:\n", + " location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n", + " movie: Any movie title\n", + " \"\"\"\n", + " return [\"Googleplex 16\", \"Android Theatre\"]\n", + "\n", + "\n", + "def get_showtimes(location: str, movie: str, theater: str, date: str):\n", + " \"\"\"\n", + " Find the start times for movies playing in a specific theater.\n", + "\n", + " Args:\n", + " location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n", + " movie: Any movie title\n", + " thearer: Name of the theater\n", + " date: Date for requested showtime\n", + " \"\"\"\n", + " return [\"10:00\", \"11:00\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Ck-hdu5N8VlR" + }, + "source": [ + "Use a dictionary to make looking up functions by name easier later on. You can also use it to pass the array of functions to the `tools` parameter of `GenerativeModel`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "8i3SKdy18WHu" + }, + "outputs": [], + "source": [ + "functions = {\n", + " \"find_movies\": find_movies,\n", + " \"find_theaters\": find_theaters,\n", + " \"get_showtimes\": get_showtimes,\n", + "}\n", + "\n", + "model = genai.GenerativeModel(model_name=\"gemini-1.5-flash-latest\", tools=functions.values())" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "11631c6e2b10" + }, + "source": [ + "After using `generate_content()` to ask a question, the model requests a `function_call`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "5e3b9c84d883" + }, + "outputs": [], + "source": [ + "response = model.generate_content(\n", + " \"Which theaters in Mountain View show the Barbie movie?\"\n", + ")\n", + "response.candidates[0].content.parts" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kuldoypuAC1i" + }, + "source": [ + "Since this is not using a `ChatSession` with automatic function calling, you have to call the function yourself.\n", + "\n", + "A very simple way to do this would be with `if` statements:\n", + "\n", + "```python\n", + "if function_call.name == 'find_theaters':\n", + " find_theaters(**function_call.args)\n", + "elif ...\n", + "```\n", + "\n", + "However, since you already made the `functions` dictionary, this can be simplified to:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "rjkZ8MA00Coc" + }, + "outputs": [], + "source": [ + "def call_function(function_call, functions):\n", + " function_name = function_call.name\n", + " function_args = function_call.args\n", + " return functions[function_name](**function_args)\n", + "\n", + "\n", + "part = response.candidates[0].content.parts[0]\n", + "\n", + "# Check if it's a function call; in real use you'd need to also handle text\n", + "# responses as you won't know what the model will respond with.\n", + "if part.function_call:\n", + " result = call_function(part.function_call, functions)\n", + "\n", + "print(result)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "XLWrHOatBtRz" + }, + "source": [ + "Finally, pass the response plus the message history to the next `generate_content()` call to get a final text response from the model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "gdb62GstAD_3" + }, + "outputs": [], + "source": [ + "import google.ai.generativelanguage as glm\n", + "from google.protobuf.struct_pb2 import Struct\n", + "\n", + "# Put the result in a protobuf Struct\n", + "s = Struct()\n", + "s.update({\"result\": result})\n", + "\n", + "# Update this after https://github.com/google/generative-ai-python/issues/243\n", + "function_response = glm.Part(\n", + " function_response=glm.FunctionResponse(name=\"find_theaters\", response=s)\n", + ")\n", + "\n", + "# Build the message history\n", + "messages = [\n", + " # fmt: off\n", + " {\"role\": \"user\",\n", + " \"parts\": [\"Which theaters in Mountain View show the Barbie movie?.\"]},\n", + " {\"role\": \"model\",\n", + " \"parts\": response.candidates[0].content.parts},\n", + " {\"role\": \"user\",\n", + " \"parts\": [function_response]},\n", + " # fmt: on\n", + "]\n", + "\n", + "# Generate the next response\n", + "response = model.generate_content(messages)\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EuwKoNIhGBJN" + }, + "source": [ + "## Parallel function calls\n", + "\n", + "The Gemini API can call multiple functions in a single turn. This caters for scenarios where there are multiple function calls that can take place independently to complete a task.\n", + "\n", + "First set the tools up. Unlike the movie example above, these functions do not require input from each other to be called so they should be good candidates for parallel calling." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "cJ-mSixWGqLv" + }, + "outputs": [], + "source": [ + "def power_disco_ball(power: bool) -> bool:\n", + " \"\"\"Powers the spinning disco ball.\"\"\"\n", + " print(f\"Disco ball is {'spinning!' if power else 'stopped.'}\")\n", + " return True\n", + "\n", + "\n", + "def start_music(energetic: bool, loud: bool, bpm: int) -> str:\n", + " \"\"\"Play some music matching the specified parameters.\n", + "\n", + " Args:\n", + " energetic: Whether the music is energetic or not.\n", + " loud: Whether the music is loud or not.\n", + " bpm: The beats per minute of the music.\n", + "\n", + " Returns: The name of the song being played.\n", + " \"\"\"\n", + " print(f\"Starting music! {energetic=} {loud=}, {bpm=}\")\n", + " return \"Never gonna give you up.\"\n", + "\n", + "\n", + "def dim_lights(brightness: float) -> bool:\n", + " \"\"\"Dim the lights.\n", + "\n", + " Args:\n", + " brightness: The brightness of the lights, 0.0 is off, 1.0 is full.\n", + " \"\"\"\n", + " print(f\"Lights are now set to {brightness:.0%}\")\n", + " return True" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zlrmXN7fxQi0" + }, + "source": [ + "Now call the model with an instruction that could use all of the specified tools." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "21ecYHLgIsCl" + }, + "outputs": [], + "source": [ + "# Set the model up with tools.\n", + "house_fns = [power_disco_ball, start_music, dim_lights]\n", + "# Try this out with Pro and Flash...\n", + "model = genai.GenerativeModel(model_name=\"gemini-1.5-flash-latest\", tools=house_fns)\n", + "\n", + "# Call the API.\n", + "chat = model.start_chat()\n", + "response = chat.send_message(\"Turn this place into a party!\")\n", + "\n", + "# Print out each of the function calls requested from this single call.\n", + "for part in response.parts:\n", + " if fn := part.function_call:\n", + " args = \", \".join(f\"{key}={val}\" for key, val in fn.args.items())\n", + " print(f\"{fn.name}({args})\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "t6iYpty7yZct" + }, + "source": [ + "Each of the printed results reflects a single function call that the model has requested. To send the results back, include the responses in the same order as they were requested." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "L7RxoiR3foBR" + }, + "outputs": [], + "source": [ + "import google.ai.generativelanguage as glm\n", + "\n", + "# Simulate the responses from the specified tools.\n", + "responses = {\n", + " \"power_disco_ball\": True,\n", + " \"start_music\": \"Never gonna give you up.\",\n", + " \"dim_lights\": True,\n", + "}\n", + "\n", + "# Build the response parts.\n", + "response_parts = [\n", + " glm.Part(function_response=glm.FunctionResponse(name=fn, response={\"result\": val}))\n", + " for fn, val in responses.items()\n", + "]\n", + "\n", + "response = chat.send_message(response_parts)\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "e0a3173919ca" + }, + "source": [ + "## Next Steps" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "7c2f31504490" + }, + "source": [ + "Useful API references:\n", + "\n", + "- The [genai.GenerativeModel](https://ai.google.dev/api/python/google/generativeai/GenerativeModel) class\n", + " - Its [GenerativeModel.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method builds a [glm.GenerateContentRequest](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentRequest) behind the scenes.\n", + " - The request's `.tools` field contains a list of 1 [glm.Tool](https://ai.google.dev/api/python/google/ai/generativelanguage/Tool) object.\n", + " - The tool's `function_declarations` attribute contains a list of [FunctionDeclarations](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionDeclaration) objects.\n", + "- The [response](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse) may contain a [glm.FunctionCall](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall), in `response.candidates[0].contents.parts[0]`.\n", + "- if `enable_automatic_function_calling` is set the [genai.ChatSession](https://ai.google.dev/api/python/google/generativeai/ChatSession) executes the call, and sends back the [glm.FunctionResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse).\n", + "- In response to a [FunctionCall](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall) the model always expects a [FunctionResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse).\n", + "- If you reply manually using [chat.send_message](https://ai.google.dev/api/python/google/generativeai/ChatSession#send_message) or [model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) remember thart the API is stateless you have to send the whole conversation history (a list of [content](https://ai.google.dev/api/python/google/ai/generativelanguage/Content) objects), not just the last one containing the `FunctionResponse`." + ] + } + ], + "metadata": { + "colab": { + "name": "Function_calling.ipynb", + "toc_visible": true + }, + "google": { + "image_path": "/site-assets/images/share.png", + "keywords": [ + "examples", + "googleai", + "samplecode", + "python", + "embed", + "function" + ] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/Function_calling_config.ipynb b/quickstarts/Function_calling_config.ipynb index 2a49d36bf..7764fcb36 100644 --- a/quickstarts/Function_calling_config.ipynb +++ b/quickstarts/Function_calling_config.ipynb @@ -1,325 +1,300 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IDS9Xcj_8k-T" + }, + "source": [ + "# Gemini API: Function calling config\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "1e41a2ce62eb" + }, + "source": [ + "Specifying a `function_calling_config` allows you to control how the Gemini API acts when `tools` have been specified. For example, you can choose to only allow free-text output (disabling function calling), force it to choose from a subset of the functions provided in `tools`, or let it act automatically.\n", + "\n", + "This guide assumes you are already familiar with function calling. For an introduction, check out the [docs](https://ai.google.dev/docs/function_calling)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "m4DhA4907Asz" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "aU-mY9hi8pQh" + }, + "source": [ + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/gemini-api-cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "wp3W4Pdf8rBO" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "import google.generativeai as genai\n", + "\n", + "genai.configure(api_key=userdata.get(\"GOOGLE_API_KEY\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "iJqil-VL8ug-" + }, + "source": [ + "## Set up a model with tools\n", + "\n", + "This example uses 3 functions that control a simple hypothetical lighting system. Using these functions requires them to be called in a specific order. For example, you must turn the light system on before you can change color.\n", + "\n", + "While you can pass these directly to the model and let it try to call them correctly, specifying the `function_calling_config` gives you precise control over the functions that are available to the model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "gLS26n7A9l9B" + }, + "outputs": [], + "source": [ + "def enable_lights():\n", + " \"\"\"Turn on the lighting system.\"\"\"\n", + " print(\"LIGHTBOT: Lights enabled.\")\n", + "\n", + "\n", + "def set_light_color(rgb_hex: str):\n", + " \"\"\"Set the light color. Lights must be enabled for this to work.\"\"\"\n", + " print(f\"LIGHTBOT: Lights set to {rgb_hex}.\")\n", + "\n", + "\n", + "def stop_lights():\n", + " \"\"\"Stop flashing lights.\"\"\"\n", + " print(\"LIGHTBOT: Lights turned off.\")\n", + "\n", + "\n", + "light_controls = [enable_lights, set_light_color, stop_lights]\n", + "instruction = \"You are a helpful lighting system bot. You can turn lights on and off, and you can set the color. Do not perform any other tasks.\"\n", + "\n", + "model = genai.GenerativeModel(\n", + " \"models/gemini-1.5-pro-latest\", tools=light_controls, system_instruction=instruction\n", + ")\n", + "\n", + "chat = model.start_chat()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JqROCznFCj_Y" + }, + "source": [ + "Create a helper function for setting `function_calling_config` on `tool_config`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "_QgLFPL4Chon" + }, + "outputs": [], + "source": [ + "from google.generativeai.types import content_types\n", + "from collections.abc import Iterable\n", + "\n", + "\n", + "def tool_config_from_mode(mode: str, fns: Iterable[str] = ()):\n", + " \"\"\"Create a tool config with the specified function calling mode.\"\"\"\n", + " return content_types.to_tool_config(\n", + " {\"function_calling_config\": {\"mode\": mode, \"allowed_function_names\": fns}}\n", + " )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ofMEuh_MFdMf" + }, + "source": [ + "## Text-only mode: `NONE`\n", + "\n", + "If you have provided the model with tools, but do not want to use those tools for the current conversational turn, then specify `NONE` as the mode. `NONE` tells the model not to make any function calls, and will behave as though none have been provided." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "6ZlIFwXqGA09" + }, + "outputs": [], + "source": [ + "tool_config = tool_config_from_mode(\"none\")\n", + "\n", + "response = chat.send_message(\n", + " \"Hello light-bot, what can you do?\", tool_config=tool_config\n", + ")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "uux063sjHZ_Z" + }, + "source": [ + "## Automatic mode: `AUTO`\n", + "\n", + "To allow the model to decide whether to respond in text or call specific functions, you can specify `AUTO` as the mode." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "vwO9dUjvHoT8" + }, + "outputs": [], + "source": [ + "tool_config = tool_config_from_mode(\"auto\")\n", + "\n", + "response = chat.send_message(\"Light this place up!\", tool_config=tool_config)\n", + "print(response.parts[0])\n", + "chat.rewind(); # We're not actually calling the function, so remove this from the history." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "oHhaO-P9CBPb" + }, + "source": [ + "## Function-calling mode: `ANY`\n", + "\n", + "Setting the mode to `ANY` will force the model to make a function call. By setting `allowed_function_names`, the model will only choose from those functions. If it is not set, all of the functions in `tools` are candidates for function calling.\n", + "\n", + "In this example system, if the lights are already on, then the user can change color or turn the lights off." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "GQpz94zrCNJF" + }, + "outputs": [], + "source": [ + "available_fns = [\"set_light_color\", \"stop_lights\"]\n", + "\n", + "tool_config = tool_config_from_mode(\"any\", available_fns)\n", + "\n", + "response = chat.send_message(\"Make this place PURPLE!\", tool_config=tool_config)\n", + "print(response.parts[0])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8cGrRy-uJ7-J" + }, + "source": [ + "## Automatic function calling\n", + "\n", + "`tool_config` works when enabling automatic function calling too." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "hx7aIX8OXvi6" + }, + "outputs": [], + "source": [ + "available_fns = [\"enable_lights\"]\n", + "tool_config = tool_config_from_mode(\"any\", available_fns)\n", + "\n", + "auto_chat = model.start_chat(enable_automatic_function_calling=True)\n", + "auto_chat.send_message(\"It's awful dark in here...\", tool_config=tool_config)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kz8McBZfXg0N" + }, + "source": [ + "## Further reading\n", + "\n", + "Check out the function calling [quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Function_calling.ipynb) for an introduction to function calling. You can find another fun function calling example [here](https://github.com/google-gemini/cookbook/blob/main/quickstarts/rest/Function_calling_REST.ipynb) using curl.\n" + ] + } + ], + "metadata": { + "colab": { + "name": "Function_calling_config.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IDS9Xcj_8k-T" - }, - "source": [ - "# Gemini API: Function calling config\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "1e41a2ce62eb" - }, - "source": [ - "Specifying a `function_calling_config` allows you to control how the Gemini API acts when `tools` have been specified. For example, you can choose to only allow free-text output (disabling function calling), force it to choose from a subset of the functions provided in `tools`, or let it act automatically.\n", - "\n", - "This guide assumes you are already familiar with function calling. For an introduction, check out the [docs](https://ai.google.dev/docs/function_calling)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "m4DhA4907Asz" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "aU-mY9hi8pQh" - }, - "source": [ - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/gemini-api-cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "wp3W4Pdf8rBO" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "import google.generativeai as genai\n", - "\n", - "genai.configure(api_key=userdata.get(\"GOOGLE_API_KEY\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "iJqil-VL8ug-" - }, - "source": [ - "## Set up a model with tools\n", - "\n", - "This example uses 3 functions that control a simple hypothetical lighting system. Using these functions requires them to be called in a specific order. For example, you must turn the light system on before you can change color.\n", - "\n", - "While you can pass these directly to the model and let it try to call them correctly, specifying the `function_calling_config` gives you precise control over the functions that are available to the model." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "gLS26n7A9l9B", - "tags": [] - }, - "outputs": [], - "source": [ - "def enable_lights():\n", - " \"\"\"Turn on the lighting system.\"\"\"\n", - " print(\"LIGHTBOT: Lights enabled.\")\n", - "\n", - "\n", - "def set_light_color(rgb_hex: str):\n", - " \"\"\"Set the light color. Lights must be enabled for this to work.\"\"\"\n", - " print(f\"LIGHTBOT: Lights set to {rgb_hex}.\")\n", - "\n", - "\n", - "def stop_lights():\n", - " \"\"\"Stop flashing lights.\"\"\"\n", - " print(\"LIGHTBOT: Lights turned off.\")\n", - "\n", - "\n", - "light_controls = [enable_lights, set_light_color, stop_lights]\n", - "instruction = \"You are a helpful lighting system bot. You can turn lights on and off, and you can set the color. Do not perform any other tasks.\"\n", - "\n", - "model = genai.GenerativeModel(\n", - " \"models/gemini-1.5-pro-latest\", tools=light_controls, system_instruction=instruction\n", - ")\n", - "\n", - "chat = model.start_chat()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "JqROCznFCj_Y" - }, - "source": [ - "Create a helper function for setting `function_calling_config` on `tool_config`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "_QgLFPL4Chon", - "tags": [] - }, - "outputs": [], - "source": [ - "from google.generativeai.types import content_types\n", - "from collections.abc import Iterable\n", - "\n", - "\n", - "def tool_config_from_mode(mode: str, fns: Iterable[str] = ()):\n", - " \"\"\"Create a tool config with the specified function calling mode.\"\"\"\n", - " return content_types.to_tool_config(\n", - " {\"function_calling_config\": {\"mode\": mode, \"allowed_function_names\": fns}}\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ofMEuh_MFdMf" - }, - "source": [ - "## Text-only mode: `NONE`\n", - "\n", - "If you have provided the model with tools, but do not want to use those tools for the current conversational turn, then specify `NONE` as the mode. `NONE` tells the model not to make any function calls, and will behave as though none have been provided." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "6ZlIFwXqGA09", - "tags": [] - }, - "outputs": [], - "source": [ - "tool_config = tool_config_from_mode(\"none\")\n", - "\n", - "response = chat.send_message(\n", - " \"Hello light-bot, what can you do?\", tool_config=tool_config\n", - ")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "uux063sjHZ_Z" - }, - "source": [ - "## Automatic mode: `AUTO`\n", - "\n", - "To allow the model to decide whether to respond in text or call specific functions, you can specify `AUTO` as the mode." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "vwO9dUjvHoT8", - "tags": [] - }, - "outputs": [], - "source": [ - "tool_config = tool_config_from_mode(\"auto\")\n", - "\n", - "response = chat.send_message(\"Light this place up!\", tool_config=tool_config)\n", - "print(response.parts[0])\n", - "chat.rewind(); # We're not actually calling the function, so remove this from the history." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "oHhaO-P9CBPb" - }, - "source": [ - "## Function-calling mode: `ANY`\n", - "\n", - "Setting the mode to `ANY` will force the model to make a function call. By setting `allowed_function_names`, the model will only choose from those functions. If it is not set, all of the functions in `tools` are candidates for function calling.\n", - "\n", - "In this example system, if the lights are already on, then the user can change color or turn the lights off." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "GQpz94zrCNJF", - "tags": [] - }, - "outputs": [], - "source": [ - "available_fns = [\"set_light_color\", \"stop_lights\"]\n", - "\n", - "tool_config = tool_config_from_mode(\"any\", available_fns)\n", - "\n", - "response = chat.send_message(\"Make this place PURPLE!\", tool_config=tool_config)\n", - "print(response.parts[0])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "8cGrRy-uJ7-J" - }, - "source": [ - "## Automatic function calling\n", - "\n", - "`tool_config` works when enabling automatic function calling too." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "hx7aIX8OXvi6", - "tags": [] - }, - "outputs": [], - "source": [ - "available_fns = [\"enable_lights\"]\n", - "tool_config = tool_config_from_mode(\"any\", available_fns)\n", - "\n", - "auto_chat = model.start_chat(enable_automatic_function_calling=True)\n", - "auto_chat.send_message(\"It's awful dark in here...\", tool_config=tool_config)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kz8McBZfXg0N" - }, - "source": [ - "## Further reading\n", - "\n", - "Check out the function calling [quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Function_calling.ipynb) for an introduction to function calling. You can find another fun function calling example [here](https://github.com/google-gemini/cookbook/blob/main/quickstarts/rest/Function_calling_REST.ipynb) using curl.\n" - ] - } - ], - "metadata": { - "colab": { - "name": "Function_calling_config.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/Gemini_Flash_Introduction.ipynb b/quickstarts/Gemini_Flash_Introduction.ipynb index 94c2be420..e635ebcd1 100644 --- a/quickstarts/Gemini_Flash_Introduction.ipynb +++ b/quickstarts/Gemini_Flash_Introduction.ipynb @@ -1,513 +1,494 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "cDzZKCF4ea5n" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "cxsdQaqTeihY" - }, - "outputs": [], - "source": [ - "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "FjjEC1DHenXF" - }, - "source": [ - "# Gemini Flash Introduction" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "HQQSrHovfBan" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "1LEBXIg0fq83" - }, - "source": [ - "The Gemini 1.5 Flash is a new model from Gemini ecosystem providing better quality and lower latency for existing Gemini 1.0 Pro developers and users.\n", - "\n", - "It simplifies your tests and adoption due to feature parity with the currently available Gemini models.\n", - "\n", - "In this notebook you will experiment with different scenarios (including text, chat and multimodal examples) where the only change required is changing the model you want to interact with - all the code is simply the same." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZxjOSybzhS5F" - }, - "source": [ - "## Installing the latest version of the Gemini SDK" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "7WIjD40XBMEM" - }, - "outputs": [], - "source": [ - "!pip install -q -U google-generativeai # Install the Python SDK" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0DUxJvIwhWQI" - }, - "source": [ - "## Import the Gemini python SDK" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "kmyjiZKSBYej" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xvJsVuNQhcED" - }, - "source": [ - "## Set up your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "g3SXoJCLBpFs" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "pWLzoSm3xs5V" - }, - "source": [ - "## Working with text scenarios\n", - "\n", - "In the first scenario of this notebook, you will work with text only scenarios. You will send direct requests, in text format, to the Gemini API and handle the results. It will include the understanding the information for each model (including input and output limits) and working with mechanisms to count the tokens of your request.\n", - "\n", - "First pick which model version you want to experiment with selecting on the listbox below - The available models are:\n", - "\n", - "- `models/gemini-1.5-flash-latest`\n", - "- `models/gemini-1.5-pro-latest`\n", - "- `models/gemini-1.0-pro-latest`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "giFvfXMeUnyR" - }, - "outputs": [], - "source": [ - "version = 'models/gemini-1.5-flash-latest' # @param [\"models/gemini-1.5-flash-latest\", \"models/gemini-1.5-pro-latest\", \"models/gemini-1.0-pro-latest\"]\n", - "model = genai.GenerativeModel(version)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "W4CuxUizinbs" - }, - "source": [ - "Using `model.get_model()` method, you can explore details about the model, like `input_token_limit` and `output_token_limit`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "PAimDgd5ugKn" - }, - "outputs": [], - "source": [ - "model_info = genai.get_model(version)\n", - "print(f'{version} - input limit: {model_info.input_token_limit}, output limit: {model_info.output_token_limit}')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "u7GRPvW7jh7s" - }, - "source": [ - "You can also count the tokens of your input using the `model.count_tokens()` method:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "yscBZrjPu1zL" - }, - "outputs": [], - "source": [ - "prompt = \"What is artificial intelligence?\"\n", - "model.count_tokens(prompt)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "6vgBNqUajsQ2" - }, - "source": [ - "Then you can send your request prompt to Gemini API - Does not matter which model version you chose, the same request code is going to be used here:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "W1RWCdNPtTzd" - }, - "outputs": [], - "source": [ - "response = model.generate_content(prompt)\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "iEREbartxmXx" - }, - "source": [ - "## Working with chat scenarios\n", - "\n", - "The next experimentation is working with chats. Again, the first action is to pick which model you want to play with. As for the text example, you can pick one of the above:\n", - "- `models/gemini-1.5-flash-latest`\n", - "- `models/gemini-1.5-pro-latest`\n", - "- `models/gemini-1.0-pro-latest`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "E5WcsAIGvznk" - }, - "outputs": [], - "source": [ - "version = 'models/gemini-1.5-flash-latest' # @param [\"models/gemini-1.5-flash-latest\", \"models/gemini-1.5-pro-latest\", \"models/gemini-1.0-pro-latest\"]\n", - "model = genai.GenerativeModel(version)\n", - "chat = model.start_chat(history=[])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3hnEUnrik0D1" - }, - "source": [ - "Using `model.get_model()` method, you can explore details about the model, like `input_token_limit` and `output_token_limit`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "NX3xgV2NYggV" - }, - "outputs": [], - "source": [ - "model_info = genai.get_model(version)\n", - "print(f'{version} - input limit: {model_info.input_token_limit}, output limit: {model_info.output_token_limit}')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "T_RfgpAPk58V" - }, - "source": [ - "You can also count the tokens of your experiment using the `model.count_tokens()` method:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "y8Megh7SYm-7" - }, - "outputs": [], - "source": [ - "prompt = \"How can I start learning artificial intelligence?\"\n", - "model.count_tokens(prompt)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZIZyFu5tk-oW" - }, - "source": [ - "Then you can send your request prompt to the Gemini API - Does not matter which model version you chose, the same request code is going to be used here:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "rzUMuKSXvzhN" - }, - "outputs": [], - "source": [ - "response = chat.send_message(\"How can I start learning artificial intelligence?\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IB_88tt_lCmR" - }, - "source": [ - "The same way you can perform a tokens counting for your prompts, you can use it against your chat history too, using the same `model.count_tokens()` method:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "vrVI9zvqvzfI" - }, - "outputs": [], - "source": [ - "model.count_tokens(chat.history)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "vu8blCSpapTF" - }, - "source": [ - "## Working with multimodal scenarios\n", - "\n", - "Then finally you can experiment with a multimodal experiment - or, in other words, sending in the same request prompt different data modalities (like text and images together).\n", - "\n", - "You must first pick which model version you want to experiment with selecting on the listbox below - The available models are:\n", - "\n", - "- `models/gemini-1.5-flash-latest`\n", - "- `models/gemini-1.5-pro-latest`\n", - "- `models/gemini-pro-vision`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LfuCWtHetcuA" - }, - "outputs": [], - "source": [ - "version = 'models/gemini-1.5-flash-latest' # @param [\"models/gemini-1.5-flash-latest\", \"models/gemini-1.5-pro-latest\", \"models/gemini-pro-vision\"]\n", - "model = genai.GenerativeModel(version)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZYlc6EZhmR4W" - }, - "source": [ - "Using `model.get_model()` method, you can explore details about the model, like `input_token_limit` and `output_token_limit`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "YOQVyY7XavyR" - }, - "outputs": [], - "source": [ - "model_info = genai.get_model(version)\n", - "print(f'{version} - input limit: {model_info.input_token_limit}, output limit: {model_info.output_token_limit}')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "aeug2Lk3mXV5" - }, - "source": [ - "Now you will pick a test image to be used on your multimodal prompt. Here you will use a sample croissant image:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Ur7rfzAbbIcQ" - }, - "outputs": [], - "source": [ - "import PIL\n", - "from IPython.display import display, Image\n", - "\n", - "!curl -s -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/croissant.jpg\"\n", - "img = PIL.Image.open('image.jpg')\n", - "display(Image('image.jpg', width=300))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nOnmWlsimfGR" - }, - "source": [ - "As you did for the text and chat prompts, you can perform a tokens counting for your image as well. Here you will show first the image resolution (using `img.size`) and then the amount of tokens that represent the image, using `model.cout_tokens()` method:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "HXMvnNALbmWP" - }, - "outputs": [], - "source": [ - "print(img.size)\n", - "print(model.count_tokens(img))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "D3ziijDAm6VE" - }, - "source": [ - "Now it is time to define the text prompt to be sent together with your test image - in this case, you will send a request to extract some information from the image, like what is in the image, which country the item in the image is related and what is the best pairing for the item." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "mGh0OwvYlLEW" - }, - "outputs": [], - "source": [ - "prompt = \"\"\"\n", - "Describe this image, including which country is famous for having this food and what is the best pairing for it.\n", - "\"\"\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "N2Inb0TRny4X" - }, - "outputs": [], - "source": [ - "response = model.generate_content([prompt, img])\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "sDrDAo1xnu9u" - }, - "source": [ - "## Learning more\n", - "\n", - "* To learn how use a model for prompting, see the [Prompting](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Prompting.ipynb) quickstart.\n", - "\n", - "* [count_tokens](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#count_tokens) Python API reference and [Count Tokens](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Counting_Tokens.ipynb) quickstart.\n", - "\n", - "* For more information on models, visit the [Gemini models](https://ai.google.dev/models/gemini) documentation." - ] - } - ], - "metadata": { - "colab": { - "name": "Gemini_Flash_Introduction.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "cDzZKCF4ea5n" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "cxsdQaqTeihY" + }, + "outputs": [], + "source": [ + "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FjjEC1DHenXF" + }, + "source": [ + "# Gemini Flash Introduction" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HQQSrHovfBan" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "1LEBXIg0fq83" + }, + "source": [ + "The Gemini 1.5 Flash is a new model from Gemini ecosystem providing better quality and lower latency for existing Gemini 1.0 Pro developers and users.\n", + "\n", + "It simplifies your tests and adoption due to feature parity with the currently available Gemini models.\n", + "\n", + "In this notebook you will experiment with different scenarios (including text, chat and multimodal examples) where the only change required is changing the model you want to interact with - all the code is simply the same." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZxjOSybzhS5F" + }, + "source": [ + "## Installing the latest version of the Gemini SDK" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "7WIjD40XBMEM" + }, + "outputs": [], + "source": [ + "!pip install -q -U google-generativeai # Install the Python SDK" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0DUxJvIwhWQI" + }, + "source": [ + "## Import the Gemini python SDK" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "kmyjiZKSBYej" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xvJsVuNQhcED" + }, + "source": [ + "## Set up your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "g3SXoJCLBpFs" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pWLzoSm3xs5V" + }, + "source": [ + "## Working with text scenarios\n", + "\n", + "In the first scenario of this notebook, you will work with text only scenarios. You will send direct requests, in text format, to the Gemini API and handle the results. It will include the understanding the information for each model (including input and output limits) and working with mechanisms to count the tokens of your request.\n", + "\n", + "First pick which model version you want to experiment with selecting on the listbox below - The available models are:\n", + "\n", + "- `models/gemini-1.5-flash-latest`\n", + "- `models/gemini-1.5-pro-latest`\n", + "- `models/gemini-1.0-pro-latest`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "giFvfXMeUnyR" + }, + "outputs": [], + "source": [ + "version = 'models/gemini-1.5-flash-latest' # @param [\"models/gemini-1.5-flash-latest\", \"models/gemini-1.5-pro-latest\", \"models/gemini-1.0-pro-latest\"]\n", + "model = genai.GenerativeModel(version)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "W4CuxUizinbs" + }, + "source": [ + "Using `model.get_model()` method, you can explore details about the model, like `input_token_limit` and `output_token_limit`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "PAimDgd5ugKn" + }, + "outputs": [], + "source": [ + "model_info = genai.get_model(version)\n", + "print(f'{version} - input limit: {model_info.input_token_limit}, output limit: {model_info.output_token_limit}')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "u7GRPvW7jh7s" + }, + "source": [ + "You can also count the tokens of your input using the `model.count_tokens()` method:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "yscBZrjPu1zL" + }, + "outputs": [], + "source": [ + "prompt = \"What is artificial intelligence?\"\n", + "model.count_tokens(prompt)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6vgBNqUajsQ2" + }, + "source": [ + "Then you can send your request prompt to Gemini API - Does not matter which model version you chose, the same request code is going to be used here:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "W1RWCdNPtTzd" + }, + "outputs": [], + "source": [ + "response = model.generate_content(prompt)\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "iEREbartxmXx" + }, + "source": [ + "## Working with chat scenarios\n", + "\n", + "The next experimentation is working with chats. Again, the first action is to pick which model you want to play with. As for the text example, you can pick one of the above:\n", + "- `models/gemini-1.5-flash-latest`\n", + "- `models/gemini-1.5-pro-latest`\n", + "- `models/gemini-1.0-pro-latest`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "E5WcsAIGvznk" + }, + "outputs": [], + "source": [ + "version = 'models/gemini-1.5-flash-latest' # @param [\"models/gemini-1.5-flash-latest\", \"models/gemini-1.5-pro-latest\", \"models/gemini-1.0-pro-latest\"]\n", + "model = genai.GenerativeModel(version)\n", + "chat = model.start_chat(history=[])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3hnEUnrik0D1" + }, + "source": [ + "Using `model.get_model()` method, you can explore details about the model, like `input_token_limit` and `output_token_limit`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "NX3xgV2NYggV" + }, + "outputs": [], + "source": [ + "model_info = genai.get_model(version)\n", + "print(f'{version} - input limit: {model_info.input_token_limit}, output limit: {model_info.output_token_limit}')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "T_RfgpAPk58V" + }, + "source": [ + "You can also count the tokens of your experiment using the `model.count_tokens()` method:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "y8Megh7SYm-7" + }, + "outputs": [], + "source": [ + "prompt = \"How can I start learning artificial intelligence?\"\n", + "model.count_tokens(prompt)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZIZyFu5tk-oW" + }, + "source": [ + "Then you can send your request prompt to the Gemini API - Does not matter which model version you chose, the same request code is going to be used here:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "rzUMuKSXvzhN" + }, + "outputs": [], + "source": [ + "response = chat.send_message(\"How can I start learning artificial intelligence?\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IB_88tt_lCmR" + }, + "source": [ + "The same way you can perform a tokens counting for your prompts, you can use it against your chat history too, using the same `model.count_tokens()` method:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "vrVI9zvqvzfI" + }, + "outputs": [], + "source": [ + "model.count_tokens(chat.history)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "vu8blCSpapTF" + }, + "source": [ + "## Working with multimodal scenarios\n", + "\n", + "Then finally you can experiment with a multimodal experiment - or, in other words, sending in the same request prompt different data modalities (like text and images together).\n", + "\n", + "You must first pick which model version you want to experiment with selecting on the listbox below - The available models are:\n", + "\n", + "- `models/gemini-1.5-flash-latest`\n", + "- `models/gemini-1.5-pro-latest`\n", + "- `models/gemini-pro-vision`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "LfuCWtHetcuA" + }, + "outputs": [], + "source": [ + "version = 'models/gemini-1.5-flash-latest' # @param [\"models/gemini-1.5-flash-latest\", \"models/gemini-1.5-pro-latest\", \"models/gemini-pro-vision\"]\n", + "model = genai.GenerativeModel(version)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZYlc6EZhmR4W" + }, + "source": [ + "Using `model.get_model()` method, you can explore details about the model, like `input_token_limit` and `output_token_limit`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "YOQVyY7XavyR" + }, + "outputs": [], + "source": [ + "model_info = genai.get_model(version)\n", + "print(f'{version} - input limit: {model_info.input_token_limit}, output limit: {model_info.output_token_limit}')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "aeug2Lk3mXV5" + }, + "source": [ + "Now you will pick a test image to be used on your multimodal prompt. Here you will use a sample croissant image:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Ur7rfzAbbIcQ" + }, + "outputs": [], + "source": [ + "import PIL\n", + "from IPython.display import display, Image\n", + "\n", + "!curl -s -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/croissant.jpg\"\n", + "img = PIL.Image.open('image.jpg')\n", + "display(Image('image.jpg', width=300))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nOnmWlsimfGR" + }, + "source": [ + "As you did for the text and chat prompts, you can perform a tokens counting for your image as well. Here you will show first the image resolution (using `img.size`) and then the amount of tokens that represent the image, using `model.cout_tokens()` method:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "HXMvnNALbmWP" + }, + "outputs": [], + "source": [ + "print(img.size)\n", + "print(model.count_tokens(img))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "D3ziijDAm6VE" + }, + "source": [ + "Now it is time to define the text prompt to be sent together with your test image - in this case, you will send a request to extract some information from the image, like what is in the image, which country the item in the image is related and what is the best pairing for the item." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "mGh0OwvYlLEW" + }, + "outputs": [], + "source": [ + "prompt = \"\"\"\n", + "Describe this image, including which country is famous for having this food and what is the best pairing for it.\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "N2Inb0TRny4X" + }, + "outputs": [], + "source": [ + "response = model.generate_content([prompt, img])\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "sDrDAo1xnu9u" + }, + "source": [ + "## Learning more\n", + "\n", + "* To learn how use a model for prompting, see the [Prompting](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Prompting.ipynb) quickstart.\n", + "\n", + "* [count_tokens](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#count_tokens) Python API reference and [Count Tokens](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Counting_Tokens.ipynb) quickstart.\n", + "\n", + "* For more information on models, visit the [Gemini models](https://ai.google.dev/models/gemini) documentation." + ] + } + ], + "metadata": { + "colab": { + "name": "Gemini_Flash_Introduction.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/JSON_mode.ipynb b/quickstarts/JSON_mode.ipynb index b4850a642..1135bd93b 100644 --- a/quickstarts/JSON_mode.ipynb +++ b/quickstarts/JSON_mode.ipynb @@ -1,214 +1,190 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "893sOzyhJDma" - }, - "source": [ - "# Gemini API: JSON Mode Quickstart\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "h4LQoYRTJIP9" - }, - "source": [ - "This notebook demonstrates how to use JSON mode." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "_PBH7eR9He0I" - }, - "outputs": [], - "source": [ - "!pip install -qU google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "2zwIBNLWJvRf", - "tags": [] - }, - "outputs": [], - "source": [ - "import google.generativeai as genai\n", - "import json" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "F6gHNgcUypVN" - }, - "source": [ - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "t0jy9XWjJwv7" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "vf42XN1KLcfV" - }, - "source": [ - "## Activate JSON mode" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dC5-79CDMJ3R" - }, - "source": [ - "Activate JSON mode by specifying `respose_mime_type` in the `generation_config` parameter." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "WWq64FXSLXgr", - "tags": [] - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel(\"gemini-1.5-pro-latest\",\n", - " generation_config={\"response_mime_type\": \"application/json\"})" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Y_djQzyyaCLg", - "tags": [] - }, - "outputs": [], - "source": [ - "prompt = \"\"\"List a few popular cookie recipes using this JSON schema:\n", - "{'type': 'object', 'properties': { 'recipe_name': {'type': 'string'}}}\"\"\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "aENeySrWMJN6", - "scrolled": true, - "tags": [] - }, - "outputs": [], - "source": [ - "response = model.generate_content(prompt)\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "pqNsOE1YysLc" - }, - "source": [ - "Just for fun, parse the string to JSON, and then serialize it." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "print(json.dumps(json.loads(response.text), indent=4))" - ] - } - ], - "metadata": { - "colab": { - "name": "JSON_mode.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "893sOzyhJDma" + }, + "source": [ + "# Gemini API: JSON Mode Quickstart\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "h4LQoYRTJIP9" + }, + "source": [ + "This notebook demonstrates how to use JSON mode." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "_PBH7eR9He0I" + }, + "outputs": [], + "source": [ + "!pip install -qU google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "2zwIBNLWJvRf" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai\n", + "import json" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "F6gHNgcUypVN" + }, + "source": [ + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "t0jy9XWjJwv7" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "vf42XN1KLcfV" + }, + "source": [ + "## Activate JSON mode" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dC5-79CDMJ3R" + }, + "source": [ + "Activate JSON mode by specifying `respose_mime_type` in the `generation_config` parameter." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "WWq64FXSLXgr" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel(\"gemini-1.5-pro-latest\",\n", + " generation_config={\"response_mime_type\": \"application/json\"})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Y_djQzyyaCLg" + }, + "outputs": [], + "source": [ + "prompt = \"\"\"List a few popular cookie recipes using this JSON schema:\n", + "{'type': 'object', 'properties': { 'recipe_name': {'type': 'string'}}}\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "aENeySrWMJN6" + }, + "outputs": [], + "source": [ + "response = model.generate_content(prompt)\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pqNsOE1YysLc" + }, + "source": [ + "Just for fun, parse the string to JSON, and then serialize it." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "27fde36ddf60" + }, + "outputs": [], + "source": [ + "print(json.dumps(json.loads(response.text), indent=4))" + ] + } + ], + "metadata": { + "colab": { + "name": "JSON_mode.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/Models.ipynb b/quickstarts/Models.ipynb index a61f6163d..7f78cfb2a 100644 --- a/quickstarts/Models.ipynb +++ b/quickstarts/Models.ipynb @@ -1,256 +1,233 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "L5Lv3UtGCFH4" - }, - "source": [ - "# Gemini API: List models\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nAJ9EGE2SoXm" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Gh9D-DvWSuqq" - }, - "source": [ - "This notebook demonstrates how to list the models that are available for you to use in the Gemini API, and how to find details about a model." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "i755jXzS5kLN" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "49H9jQPO_TJ9" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4ol10W6Q_Y-s" - }, - "source": [ - "## Configure your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "8PXsFZBQ_XA5" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "\n", - "GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3Al4lFhNB22n" - }, - "source": [ - "## List models\n", - "\n", - "Use `list_models()` to see what models are available. These models support `generateContent`, the main method used for prompting." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "3wE76b_gBn2k", - "tags": [] - }, - "outputs": [], - "source": [ - "for m in genai.list_models():\n", - " if \"generateContent\" in m.supported_generation_methods:\n", - " print(m.name)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tlguLt1yKET9" - }, - "source": [ - "These models support `embedContent`, used for embeddings:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "lQmlIpr5JHqz", - "tags": [] - }, - "outputs": [], - "source": [ - "for m in genai.list_models():\n", - " if \"embedContent\" in m.supported_generation_methods:\n", - " print(m.name)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nFJAyDD9QVrC" - }, - "source": [ - "## Find details about a model\n", - "\n", - "You can see more details about a model, including the `input_token_limit` and `output_token_limit` as follows." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "BYYxVE4ZnoGy", - "tags": [] - }, - "outputs": [], - "source": [ - "for m in genai.list_models():\n", - " if m.name == \"models/gemini-1.5-flash-latest\":\n", - " print(m)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "00a56cb21953" - }, - "source": [ - "## Get model\n", - "\n", - "Use `get_model()` to retrieve the specific details of a model. You can iterate over all available models using `list_models()`, but if you already know the model name you can retrieve it directly with `get_model()`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "6786759016dc", - "tags": [] - }, - "outputs": [], - "source": [ - "model_info = genai.get_model(\"models/aqa\")\n", - "print(model_info)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Tq7i5FAwCe1v" - }, - "source": [ - "## Learning more\n", - "\n", - "* To learn how use a model for prompting, see the [Prompting](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Prompting.ipynb) quickstart.\n", - "\n", - "* To learn how use a model for embedding, see the [Embedding](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Embeddings.ipynb) quickstart.\n", - "\n", - "* For more information on models, visit the [Gemini models](https://ai.google.dev/models/gemini) documentation." - ] - } - ], - "metadata": { - "colab": { - "name": "Models.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "L5Lv3UtGCFH4" + }, + "source": [ + "# Gemini API: List models\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nAJ9EGE2SoXm" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Gh9D-DvWSuqq" + }, + "source": [ + "This notebook demonstrates how to list the models that are available for you to use in the Gemini API, and how to find details about a model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "i755jXzS5kLN" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "49H9jQPO_TJ9" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4ol10W6Q_Y-s" + }, + "source": [ + "## Configure your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "8PXsFZBQ_XA5" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "\n", + "GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3Al4lFhNB22n" + }, + "source": [ + "## List models\n", + "\n", + "Use `list_models()` to see what models are available. These models support `generateContent`, the main method used for prompting." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "3wE76b_gBn2k" + }, + "outputs": [], + "source": [ + "for m in genai.list_models():\n", + " if \"generateContent\" in m.supported_generation_methods:\n", + " print(m.name)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tlguLt1yKET9" + }, + "source": [ + "These models support `embedContent`, used for embeddings:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "lQmlIpr5JHqz" + }, + "outputs": [], + "source": [ + "for m in genai.list_models():\n", + " if \"embedContent\" in m.supported_generation_methods:\n", + " print(m.name)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nFJAyDD9QVrC" + }, + "source": [ + "## Find details about a model\n", + "\n", + "You can see more details about a model, including the `input_token_limit` and `output_token_limit` as follows." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "BYYxVE4ZnoGy" + }, + "outputs": [], + "source": [ + "for m in genai.list_models():\n", + " if m.name == \"models/gemini-1.5-flash-latest\":\n", + " print(m)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "00a56cb21953" + }, + "source": [ + "## Get model\n", + "\n", + "Use `get_model()` to retrieve the specific details of a model. You can iterate over all available models using `list_models()`, but if you already know the model name you can retrieve it directly with `get_model()`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "6786759016dc" + }, + "outputs": [], + "source": [ + "model_info = genai.get_model(\"models/aqa\")\n", + "print(model_info)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Tq7i5FAwCe1v" + }, + "source": [ + "## Learning more\n", + "\n", + "* To learn how use a model for prompting, see the [Prompting](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Prompting.ipynb) quickstart.\n", + "\n", + "* To learn how use a model for embedding, see the [Embedding](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Embeddings.ipynb) quickstart.\n", + "\n", + "* For more information on models, visit the [Gemini models](https://ai.google.dev/models/gemini) documentation." + ] + } + ], + "metadata": { + "colab": { + "name": "Models.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/PDF_Files.ipynb b/quickstarts/PDF_Files.ipynb index 255482047..9dbf2f704 100644 --- a/quickstarts/PDF_Files.ipynb +++ b/quickstarts/PDF_Files.ipynb @@ -1,441 +1,409 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dfsDR_omdNea" - }, - "source": [ - "# Gemini API - read a PDF\n", - "\n", - "This notebook demonstrates how you can convert a PDF file so that it can be read by the Gemini API.\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "FaqZItBdeokU" - }, - "source": [ - "## Setup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "XKJ78ne3O0sB" - }, - "outputs": [], - "source": [ - "!pip install -Uq google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LUKlAk7iN_5e" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai\n", - "\n", - "\n", - "import pathlib\n", - "import tqdm\n", - "import os" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "A9sUQ4WrP-Yr" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "genai.configure(api_key=userdata.get(\"GOOGLE_API_KEY\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "thYL8XGjerMa" - }, - "source": [ - "Install the PDF processing tools:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "iK30_utL1DhY", - "tags": [] - }, - "outputs": [], - "source": [ - "!apt install poppler-utils" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "jZj7pRt7exwE" - }, - "source": [ - "## Download and proces the PDF" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "WibRLdf2_Qoq" - }, - "source": [ - "This textbook is from OpenStax, it's License is Commons Attribution License v4.0. More detrails are [available on the site](https://openstax.org/details/books/university-physics-volume-2)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "fOYiHxN95iVn", - "tags": [] - }, - "outputs": [], - "source": [ - "import pathlib" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "xo8VsYaY6mgl", - "tags": [] - }, - "outputs": [], - "source": [ - "if not pathlib.Path('test.pdf').exists():\n", - " !curl -o test.pdf https://assets.openstax.org/oscms-prodcms/media/documents/UniversityPhysicsVolume2-WEB_5eNhMSa.pdf" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3V-NRhife2CA" - }, - "source": [ - "You'll extract Chapter 3, pages [121-154]." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "c6LD6PlpK3n8", - "tags": [] - }, - "outputs": [], - "source": [ - "first = 121\n", - "last = 154" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "fH4WmrY_1MdQ", - "tags": [] - }, - "outputs": [], - "source": [ - "!mkdir output\n", - "! # extract images of Chapter 3\n", - "!pdftoppm test.pdf -f {first} -l {last} output/images -jpeg\n", - "!ls output" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "hmIj4eQlfFot" - }, - "source": [ - "Look at the first image, scaled down:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "JGOg-cvK11IC", - "tags": [] - }, - "outputs": [], - "source": [ - "import PIL.Image" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9b0MfUwc17Mk", - "tags": [] - }, - "outputs": [], - "source": [ - "img = PIL.Image.open(f\"output/images-{first}.jpg\")\n", - "img.thumbnail([600, 600])\n", - "img" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Qi6KAePlfMl4" - }, - "source": [ - "Extract the text for those same pages." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "zgqvbl0K2RKA", - "tags": [] - }, - "outputs": [], - "source": [ - "for page_number in range(first,last+1):\n", - " page_number = f\"{page_number:03d}\"\n", - " ! pdftotext test.pdf -f {page_number} -l {page_number}\n", - " ! mv test.txt output/text-{page_number}.txt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Pfdv5rdG2ltK", - "tags": [] - }, - "outputs": [], - "source": [ - "!ls output" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "wG5tecfk84VP", - "tags": [] - }, - "outputs": [], - "source": [ - "!cat output/text-{first}.txt" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "D5bZ_n0MfV_a" - }, - "source": [ - "## Assemble the files into a prompt" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3DnTs6-cfl43" - }, - "source": [ - "Upload all the files usng the files API, there are too many to send with the `generate_content` request." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LoR60ncl8-Zn", - "tags": [] - }, - "outputs": [], - "source": [ - "files = []\n", - "image_files = list(pathlib.Path(\"output\").glob('images-*.jpg'))\n", - "for img in tqdm.tqdm(image_files):\n", - " files.append(genai.upload_file(img))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "l_0xCJbNfsYa" - }, - "source": [ - "Load all the texts:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "fGx1ERx9Omz7", - "tags": [] - }, - "outputs": [], - "source": [ - "texts = [t.read_text() for t in pathlib.Path(\"output\").glob('text-*.txt')]" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "_CzHvWTpfvKI" - }, - "source": [ - "Interleave the page-numbers, texts, and image-file references:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "sxpikEYcQnZG", - "tags": [] - }, - "outputs": [], - "source": [ - "textbook = []\n", - "for page, (text, image) in enumerate(zip(texts, files)):\n", - " textbook.append(f'## Page {first+page} ##')\n", - " textbook.append(text)\n", - " textbook.append(image)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yXFZFUJHgTcU" - }, - "source": [ - "## Try it out" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel(model_name='gemini-1.5-flash-latest')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "response = model.generate_content(\n", - " ['# Here is a chapter from a physics text book:']+\n", - " textbook +\n", - " [\"[END]\\n\\nPlease sumarize it in sections for a better understanding\"]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "from IPython.display import Markdown\n", - "Markdown(response.text)" - ] - } - ], - "metadata": { - "colab": { - "name": "PDF_Files.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dfsDR_omdNea" + }, + "source": [ + "# Gemini API - read a PDF\n", + "\n", + "This notebook demonstrates how you can convert a PDF file so that it can be read by the Gemini API.\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FaqZItBdeokU" + }, + "source": [ + "## Setup" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "XKJ78ne3O0sB" + }, + "outputs": [], + "source": [ + "!pip install -Uq google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "LUKlAk7iN_5e" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai\n", + "\n", + "\n", + "import pathlib\n", + "import tqdm\n", + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "A9sUQ4WrP-Yr" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "genai.configure(api_key=userdata.get(\"GOOGLE_API_KEY\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "thYL8XGjerMa" + }, + "source": [ + "Install the PDF processing tools:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "iK30_utL1DhY" + }, + "outputs": [], + "source": [ + "!apt install poppler-utils" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "jZj7pRt7exwE" + }, + "source": [ + "## Download and proces the PDF" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "WibRLdf2_Qoq" + }, + "source": [ + "This textbook is from OpenStax, it's License is Commons Attribution License v4.0. More detrails are [available on the site](https://openstax.org/details/books/university-physics-volume-2)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "fOYiHxN95iVn" + }, + "outputs": [], + "source": [ + "import pathlib" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "xo8VsYaY6mgl" + }, + "outputs": [], + "source": [ + "if not pathlib.Path('test.pdf').exists():\n", + " !curl -o test.pdf https://assets.openstax.org/oscms-prodcms/media/documents/UniversityPhysicsVolume2-WEB_5eNhMSa.pdf" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3V-NRhife2CA" + }, + "source": [ + "You'll extract Chapter 3, pages [121-154]." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "c6LD6PlpK3n8" + }, + "outputs": [], + "source": [ + "first = 121\n", + "last = 154" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "fH4WmrY_1MdQ" + }, + "outputs": [], + "source": [ + "!mkdir output\n", + "! # extract images of Chapter 3\n", + "!pdftoppm test.pdf -f {first} -l {last} output/images -jpeg\n", + "!ls output" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "hmIj4eQlfFot" + }, + "source": [ + "Look at the first image, scaled down:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "JGOg-cvK11IC" + }, + "outputs": [], + "source": [ + "import PIL.Image" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9b0MfUwc17Mk" + }, + "outputs": [], + "source": [ + "img = PIL.Image.open(f\"output/images-{first}.jpg\")\n", + "img.thumbnail([600, 600])\n", + "img" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Qi6KAePlfMl4" + }, + "source": [ + "Extract the text for those same pages." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "zgqvbl0K2RKA" + }, + "outputs": [], + "source": [ + "for page_number in range(first,last+1):\n", + " page_number = f\"{page_number:03d}\"\n", + " ! pdftotext test.pdf -f {page_number} -l {page_number}\n", + " ! mv test.txt output/text-{page_number}.txt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Pfdv5rdG2ltK" + }, + "outputs": [], + "source": [ + "!ls output" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "wG5tecfk84VP" + }, + "outputs": [], + "source": [ + "!cat output/text-{first}.txt" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "D5bZ_n0MfV_a" + }, + "source": [ + "## Assemble the files into a prompt" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3DnTs6-cfl43" + }, + "source": [ + "Upload all the files usng the files API, there are too many to send with the `generate_content` request." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "LoR60ncl8-Zn" + }, + "outputs": [], + "source": [ + "files = []\n", + "image_files = list(pathlib.Path(\"output\").glob('images-*.jpg'))\n", + "for img in tqdm.tqdm(image_files):\n", + " files.append(genai.upload_file(img))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "l_0xCJbNfsYa" + }, + "source": [ + "Load all the texts:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "fGx1ERx9Omz7" + }, + "outputs": [], + "source": [ + "texts = [t.read_text() for t in pathlib.Path(\"output\").glob('text-*.txt')]" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "_CzHvWTpfvKI" + }, + "source": [ + "Interleave the page-numbers, texts, and image-file references:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "sxpikEYcQnZG" + }, + "outputs": [], + "source": [ + "textbook = []\n", + "for page, (text, image) in enumerate(zip(texts, files)):\n", + " textbook.append(f'## Page {first+page} ##')\n", + " textbook.append(text)\n", + " textbook.append(image)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yXFZFUJHgTcU" + }, + "source": [ + "## Try it out" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "c7f7ebc3dde9" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel(model_name='gemini-1.5-flash-latest')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "123016f7809e" + }, + "outputs": [], + "source": [ + "response = model.generate_content(\n", + " ['# Here is a chapter from a physics text book:']+\n", + " textbook +\n", + " [\"[END]\\n\\nPlease sumarize it in sections for a better understanding\"]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "700bb45acbc8" + }, + "outputs": [], + "source": [ + "from IPython.display import Markdown\n", + "Markdown(response.text)" + ] + } + ], + "metadata": { + "colab": { + "name": "PDF_Files.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/Prompting.ipynb b/quickstarts/Prompting.ipynb index 832045bad..cbc6bb61d 100644 --- a/quickstarts/Prompting.ipynb +++ b/quickstarts/Prompting.ipynb @@ -1,428 +1,397 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: Prompting Quickstart\n", - "\n", - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dpOYALec6N8Z" - }, - "source": [ - "This notebook contains examples of how to write and run your first prompts with the Gemini API." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "0c13de5f68f6" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai # Install the Python SDK" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "TS9l5igubpHO" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "w4YDYyfRYN7L" - }, - "source": [ - "## Set up your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "p8K1RpmMfh20" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "HTNQymX8YN9c" - }, - "source": [ - "## Run your first prompt\n", - "\n", - "Use the `generate_content` method to generate responses to your prompts. You can pass text directly to generate_content, and use the `.text` property to get the text content of the response." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "XSuyaGmcf6sr", - "tags": [] - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", - "response = model.generate_content(\"Give me python code to sort a list\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0GTyrWHugKFi" - }, - "source": [ - "## Use images in your prompt\n", - "\n", - "Here we download an image from a URL and pass that image in our prompt.\n", - "\n", - "First, we download the image and load it with PIL:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "JgbFtil0gLNf", - "tags": [] - }, - "outputs": [], - "source": [ - "!curl -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "0rcYDbcDga8s", - "tags": [] - }, - "outputs": [], - "source": [ - "import PIL.Image\n", - "img = PIL.Image.open('image.jpg')\n", - "img" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "UTgRAmEHOaAz", - "tags": [] - }, - "outputs": [], - "source": [ - "prompt = \"\"\"This image contains a sketch of a potential product along with some notes.\n", - "Given the product sketch, describe the product as thoroughly as possible based on what you\n", - "see in the image, making sure to note all of the product features. Return output in json format:\n", - "{description: description, features: [feature1, feature2, feature3, etc]}\"\"\"" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "RJyRsfQi0tp6" - }, - "source": [ - "Then we can include the image in our prompt by just passing a list of items to `generate_content`. Note that you will need to use the `gemini-pro-vision` model if your prompt contains images." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Aoil5YiTgbZS", - "tags": [] - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", - "response = model.generate_content([prompt, img])\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "XE-6e7gePN7Q" - }, - "source": [ - "## Have a chat\n", - "\n", - "The Gemini API enables you to have freeform conversations across multiple turns.\n", - "\n", - "The [ChatSession](https://ai.google.dev/api/python/google/generativeai/ChatSession) class will store the conversation history for multi-turn interactions." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ZKAtY5oIPQW0", - "tags": [] - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", - "chat = model.start_chat(history=[])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9tXNVnqxPcXy", - "tags": [] - }, - "outputs": [], - "source": [ - "response = chat.send_message(\"In one sentence, explain how a computer works to a young child.\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "7TChH2l5PhFf" - }, - "source": [ - "You can see the chat history:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "dHwrC82YPiWS", - "tags": [] - }, - "outputs": [], - "source": [ - "print(chat.history)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "EvHvt1OEPl7D" - }, - "source": [ - "You can keep sending messages to continue the conversation:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "-fXZZQPzPkie", - "tags": [] - }, - "outputs": [], - "source": [ - "response = chat.send_message(\"Okay, how about a more detailed explanation to a high schooler?\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "65476e75ece0" - }, - "source": [ - "## Set the temperature" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "56f68c900144" - }, - "source": [ - "Every prompt you send to the model includes parameters that control how the model generates responses. Use a `genai.GenerationConfig` to set these, or omit it to use the defaults.\n", - "\n", - "Temperature controls the degree of randomness in token selection. Use higher values for more creative responses, and lower values for more deterministic responses.\n", - "\n", - "You can set the `generation_config` when creating the model." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "28477e706226", - "tags": [] - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel(\n", - " 'gemini-1.5-flash-latest',\n", - " generation_config=genai.GenerationConfig(\n", - " max_output_tokens=2000,\n", - " temperature=0.9,\n", - " ))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "e3c68071ed8b" - }, - "source": [ - "Or, set the `generation_config` on an individual call to `generate_content`. Any values set there override values on the model constructor.\n", - "\n", - "Note: Although you can set the `candidate_count` in the generation_config, gemini-pro models will only return a single candidate at the this time." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "f895c7f55b30", - "tags": [] - }, - "outputs": [], - "source": [ - "response = model.generate_content(\n", - " 'Give me a numbered list of cat facts.',\n", - " # Limit to 5 facts.\n", - " generation_config = genai.GenerationConfig(stop_sequences=['\\n6'])\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "c97c16e6a961", - "tags": [] - }, - "outputs": [], - "source": [ - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "gvkDhXtHgol7" - }, - "source": [ - "## Learn more\n", - "\n", - "There's lots more to learn!\n", - "\n", - "* For more fun prompts, check out [Market a Jetpack](https://github.com/google-gemini/cookbook/blob/main/examples/Market_a_Jet_Backpack.ipynb).\n", - "* Check out the [safety quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Safety.ipynb) next to learn about the Gemini API's configurable safety settings, and what to do if your prompt is blocked.\n", - "* For lots more details on using the Python SDK, check out this [detailed quickstart](https://ai.google.dev/tutorials/python_quickstart)." - ] - } - ], - "metadata": { - "colab": { - "name": "Prompting.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "google": { - "image_path": "/static/site-assets/images/docs/logo-python.svg", - "keywords": [ - "examples", - "gemini", - "beginner", - "googleai", - "quickstart", - "python", - "text", - "chat", - "vision", - "embed" - ] - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: Prompting Quickstart\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dpOYALec6N8Z" + }, + "source": [ + "This notebook contains examples of how to write and run your first prompts with the Gemini API." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "0c13de5f68f6" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai # Install the Python SDK" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TS9l5igubpHO" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "w4YDYyfRYN7L" + }, + "source": [ + "## Set up your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "p8K1RpmMfh20" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HTNQymX8YN9c" + }, + "source": [ + "## Run your first prompt\n", + "\n", + "Use the `generate_content` method to generate responses to your prompts. You can pass text directly to generate_content, and use the `.text` property to get the text content of the response." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "XSuyaGmcf6sr" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", + "response = model.generate_content(\"Give me python code to sort a list\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0GTyrWHugKFi" + }, + "source": [ + "## Use images in your prompt\n", + "\n", + "Here we download an image from a URL and pass that image in our prompt.\n", + "\n", + "First, we download the image and load it with PIL:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "JgbFtil0gLNf" + }, + "outputs": [], + "source": [ + "!curl -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "0rcYDbcDga8s" + }, + "outputs": [], + "source": [ + "import PIL.Image\n", + "img = PIL.Image.open('image.jpg')\n", + "img" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "UTgRAmEHOaAz" + }, + "outputs": [], + "source": [ + "prompt = \"\"\"This image contains a sketch of a potential product along with some notes.\n", + "Given the product sketch, describe the product as thoroughly as possible based on what you\n", + "see in the image, making sure to note all of the product features. Return output in json format:\n", + "{description: description, features: [feature1, feature2, feature3, etc]}\"\"\"" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "RJyRsfQi0tp6" + }, + "source": [ + "Then we can include the image in our prompt by just passing a list of items to `generate_content`. Note that you will need to use the `gemini-pro-vision` model if your prompt contains images." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Aoil5YiTgbZS" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", + "response = model.generate_content([prompt, img])\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "XE-6e7gePN7Q" + }, + "source": [ + "## Have a chat\n", + "\n", + "The Gemini API enables you to have freeform conversations across multiple turns.\n", + "\n", + "The [ChatSession](https://ai.google.dev/api/python/google/generativeai/ChatSession) class will store the conversation history for multi-turn interactions." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ZKAtY5oIPQW0" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", + "chat = model.start_chat(history=[])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9tXNVnqxPcXy" + }, + "outputs": [], + "source": [ + "response = chat.send_message(\"In one sentence, explain how a computer works to a young child.\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "7TChH2l5PhFf" + }, + "source": [ + "You can see the chat history:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "dHwrC82YPiWS" + }, + "outputs": [], + "source": [ + "print(chat.history)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EvHvt1OEPl7D" + }, + "source": [ + "You can keep sending messages to continue the conversation:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "-fXZZQPzPkie" + }, + "outputs": [], + "source": [ + "response = chat.send_message(\"Okay, how about a more detailed explanation to a high schooler?\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "65476e75ece0" + }, + "source": [ + "## Set the temperature" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "56f68c900144" + }, + "source": [ + "Every prompt you send to the model includes parameters that control how the model generates responses. Use a `genai.GenerationConfig` to set these, or omit it to use the defaults.\n", + "\n", + "Temperature controls the degree of randomness in token selection. Use higher values for more creative responses, and lower values for more deterministic responses.\n", + "\n", + "You can set the `generation_config` when creating the model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "28477e706226" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel(\n", + " 'gemini-1.5-flash-latest',\n", + " generation_config=genai.GenerationConfig(\n", + " max_output_tokens=2000,\n", + " temperature=0.9,\n", + " ))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "e3c68071ed8b" + }, + "source": [ + "Or, set the `generation_config` on an individual call to `generate_content`. Any values set there override values on the model constructor.\n", + "\n", + "Note: Although you can set the `candidate_count` in the generation_config, gemini-pro models will only return a single candidate at the this time." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "f895c7f55b30" + }, + "outputs": [], + "source": [ + "response = model.generate_content(\n", + " 'Give me a numbered list of cat facts.',\n", + " # Limit to 5 facts.\n", + " generation_config = genai.GenerationConfig(stop_sequences=['\\n6'])\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "c97c16e6a961" + }, + "outputs": [], + "source": [ + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gvkDhXtHgol7" + }, + "source": [ + "## Learn more\n", + "\n", + "There's lots more to learn!\n", + "\n", + "* For more fun prompts, check out [Market a Jetpack](https://github.com/google-gemini/cookbook/blob/main/examples/Market_a_Jet_Backpack.ipynb).\n", + "* Check out the [safety quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Safety.ipynb) next to learn about the Gemini API's configurable safety settings, and what to do if your prompt is blocked.\n", + "* For lots more details on using the Python SDK, check out this [detailed quickstart](https://ai.google.dev/tutorials/python_quickstart)." + ] + } + ], + "metadata": { + "colab": { + "name": "Prompting.ipynb", + "toc_visible": true + }, + "google": { + "image_path": "/static/site-assets/images/docs/logo-python.svg", + "keywords": [ + "examples", + "gemini", + "beginner", + "googleai", + "quickstart", + "python", + "text", + "chat", + "vision", + "embed" + ] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/Safety.ipynb b/quickstarts/Safety.ipynb index 827e71a59..06e6d8377 100644 --- a/quickstarts/Safety.ipynb +++ b/quickstarts/Safety.ipynb @@ -1,408 +1,381 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: Safety Quickstart" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lEXQ3OwKIa-O" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "uOxMUKTxR-_j" + }, + "source": [ + "The Gemini API has adjustable safety settings. This notebook walks you through how to use them. You'll write a prompt that's blocked, see the reason why, and then adjust the filters to unblock it.\n", + "\n", + "Safety is an important topic, and you can learn more with the links at the end of this notebook. Here, you will focus on the code." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9OEoeosRTv-5" + }, + "outputs": [], + "source": [ + "!pip install -q -U google-generativeai # Install the Python SDK" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3VAUtJubX7MG" + }, + "source": [ + "## Import the Gemini python SDK\n", + "\n", + "Once the kernel is restarted, you can import the Gemini SDK:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TS9l5igubpHO" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gHYFrFPjSGNq" + }, + "source": [ + "## Set up your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ab9ASynfcIZn" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "LZfoK3I3hu6V" + }, + "source": [ + "## Send your prompt request to Gemini\n", + "\n", + "Pick the prompt you want to use to test the safety filters settings. An examples could be `Write a list of 5 very rude things that I might say to the universe after stubbing my toe in the dark` which was previously tested and trigger the `HARM_CATEGORY_HARASSMENT` and `HARM_CATEGORY_DANGEROUS_CONTENT` categories.\n", + "\n", + "The result returned by the [Model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method is a [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/generativeai/types/GenerateContentResponse)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "2bcfnGEviwTI" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", + "\n", + "unsafe_prompt = \"Write a list of 5 very rude things that I might say to the universe after stubbing my toe in the dark\"\n", + "response = model.generate_content(unsafe_prompt)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "WR_2A_sxk8sK" + }, + "source": [ + "This response object gives you safety feedback about the candidate answers Gemini generates to you.\n", + "\n", + "For each candidate answer you need to check `response.candidates.finish_reason`.\n", + "\n", + "As you can find on the [Gemini API safety filters documentation](https://ai.google.dev/gemini-api/docs/safety-settings#safety-feedback):\n", + "- if the `candidate.finish_reason` is `FinishReason.STOP` means that your generation request ran successfully\n", + "- if the `candidate.finish_reason` is `FinishReason.SAFETY` means that your generation request was blocked by safety reasons. It also means that the `response.text` structure will be empty." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "8887de812dc0" + }, + "outputs": [], + "source": [ + "print(response.candidates[0].finish_reason)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "XBdqPso3kamW" + }, + "source": [ + "If the `finish_reason` is `FinishReason.SAFETY` you can check which filter caused the block checking the `safety_ratings` list for the candidate answer:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "he-OfzBbhACQ" + }, + "outputs": [], + "source": [ + "print(response.candidates[0].safety_ratings)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "z9-SdzjbxWXT" + }, + "source": [ + "As the request was blocked by the safety filters, the `response.text` field will be empty (as nothing as generated by the model):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "L1Da4cJ3xej3" + }, + "outputs": [], + "source": [ + "try:\n", + " print(response.text)\n", + "except:\n", + " print(\"No information generated by the model.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4672af98ac57" + }, + "source": [ + "## Customizing safety settings\n", + "\n", + "Depending on the scenario you are working with, it may be necessary to customize the safety filters behaviors to allow a certain degree of unsafety results.\n", + "\n", + "To make this customization you must define a `safety_settings` dictionary as part of your `model.generate_content()` request. In the example below, all the filters are being set to do not block contents.\n", + "\n", + "**Important:** To guarantee the Google commitment with the Responsible AI development and its [AI Principles](https://ai.google/responsibility/principles/), for some prompts Gemini will avoid generating the results even if you set all the filters to none." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "338fb9a6af78" + }, + "outputs": [], + "source": [ + "response = model.generate_content(\n", + " unsafe_prompt,\n", + " safety_settings={\n", + " 'HATE': 'BLOCK_NONE',\n", + " 'HARASSMENT': 'BLOCK_NONE',\n", + " 'SEXUAL' : 'BLOCK_NONE',\n", + " 'DANGEROUS' : 'BLOCK_NONE'\n", + " })" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "564K7R8rwWhs" + }, + "source": [ + "Checking again the `candidate.finish_reason` information, if the request was not too unsafe, it must show now the value as `FinishReason.STOP` which means that the request was successfully processed by Gemini." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "LazB08GBpc1w" + }, + "outputs": [], + "source": [ + "print(response.candidates[0].finish_reason)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "86c560e0a641" + }, + "source": [ + "Since the request was successfully generated, you can check the result on the `response.text`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "0c2847c49262" + }, + "outputs": [], + "source": [ + "try:\n", + " print(response.text)\n", + "except:\n", + " print(\"No information generated by the model.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "47298a4eef40" + }, + "source": [ + "And if you check the safety filters ratings, as you set all filters to be ignored, no filtering category was trigerred:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "028febe8df68" + }, + "outputs": [], + "source": [ + "print(response.candidates[0].safety_ratings)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "n1UdbxVt3ysY" + }, + "source": [ + "## Learning more\n", + "\n", + "Learn more with these articles on [safety guidance](https://ai.google.dev/docs/safety_guidance) and [safety settings](https://ai.google.dev/docs/safety_setting_gemini).\n", + "\n", + "## Useful API references\n", + "\n", + "There are 4 configurable safety settings for the Gemini API:\n", + "* `HARM_CATEGORY_DANGEROUS`\n", + "* `HARM_CATEGORY_HARASSMENT`\n", + "* `HARM_CATEGORY_SEXUALLY_EXPLICIT`\n", + "* `HARM_CATEGORY_DANGEROUS`\n", + "\n", + "You can refer to the safety settings using either their full name, or the aliases like `DANGEROUS` used in the Python code above.\n", + "\n", + "Safety settings can be set in the [genai.GenerativeModel](https://ai.google.dev/api/python/google/generativeai/GenerativeModel) constructor.\n", + "\n", + "* They can also be passed on each request to [GenerativeModel.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) or [ChatSession.send_message](https://ai.google.dev/api/python/google/generativeai/ChatSession?hl=en#send_message).\n", + "\n", + "- The [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse) returns [SafetyRatings](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) for the prompt in the [GenerateContentResponse.prompt_feedback](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse/PromptFeedback), and for each [Candidate](https://ai.google.dev/api/python/google/ai/generativelanguage/Candidate) in the `safety_ratings` attribute.\n", + "\n", + "- A [glm.SafetySetting](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetySetting) contains: [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [glm.HarmBlockThreshold](https://ai.google.dev/api/python/google/generativeai/types/HarmBlockThreshold)\n", + "\n", + "- A [glm.SafetyRating](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) contains a [HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [HarmProbability](https://ai.google.dev/api/python/google/generativeai/types/HarmProbability)\n", + "\n", + "The [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) enum includes both the categories for PaLM and Gemini models.\n", + "\n", + "- When specifying enum values the SDK will accept the enum values themselves, or their integer or string representations.\n", + "\n", + "- The SDK will also accept abbreviated string representations: `[\"HARM_CATEGORY_DANGEROUS_CONTENT\", \"DANGEROUS_CONTENT\", \"DANGEROUS\"]` are all valid. Strings are case insensitive." + ] + } + ], + "metadata": { + "colab": { + "name": "Safety.ipynb", + "toc_visible": true + }, + "google": { + "image_path": "/static/site-assets/images/docs/logo-python.svg", + "keywords": [ + "examples", + "gemini", + "beginner", + "googleai", + "quickstart", + "python", + "text", + "chat", + "vision", + "embed" + ] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: Safety Quickstart" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lEXQ3OwKIa-O" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "uOxMUKTxR-_j" - }, - "source": [ - "The Gemini API has adjustable safety settings. This notebook walks you through how to use them. You'll write a prompt that's blocked, see the reason why, and then adjust the filters to unblock it.\n", - "\n", - "Safety is an important topic, and you can learn more with the links at the end of this notebook. Here, you will focus on the code." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9OEoeosRTv-5" - }, - "outputs": [], - "source": [ - "!pip install -q -U google-generativeai # Install the Python SDK" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3VAUtJubX7MG" - }, - "source": [ - "## Import the Gemini python SDK\n", - "\n", - "Once the kernel is restarted, you can import the Gemini SDK:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "TS9l5igubpHO" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "gHYFrFPjSGNq" - }, - "source": [ - "## Set up your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ab9ASynfcIZn" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "LZfoK3I3hu6V" - }, - "source": [ - "## Send your prompt request to Gemini\n", - "\n", - "Pick the prompt you want to use to test the safety filters settings. An examples could be `Write a list of 5 very rude things that I might say to the universe after stubbing my toe in the dark` which was previously tested and trigger the `HARM_CATEGORY_HARASSMENT` and `HARM_CATEGORY_DANGEROUS_CONTENT` categories.\n", - "\n", - "The result returned by the [Model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method is a [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/generativeai/types/GenerateContentResponse)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "2bcfnGEviwTI", - "tags": [] - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", - "\n", - "unsafe_prompt = \"Write a list of 5 very rude things that I might say to the universe after stubbing my toe in the dark\"\n", - "response = model.generate_content(unsafe_prompt)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "WR_2A_sxk8sK" - }, - "source": [ - "This response object gives you safety feedback about the candidate answers Gemini generates to you.\n", - "\n", - "For each candidate answer you need to check `response.candidates.finish_reason`.\n", - "\n", - "As you can find on the [Gemini API safety filters documentation](https://ai.google.dev/gemini-api/docs/safety-settings#safety-feedback):\n", - "- if the `candidate.finish_reason` is `FinishReason.STOP` means that your generation request ran successfully\n", - "- if the `candidate.finish_reason` is `FinishReason.SAFETY` means that your generation request was blocked by safety reasons. It also means that the `response.text` structure will be empty." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "8887de812dc0", - "tags": [] - }, - "outputs": [], - "source": [ - "print(response.candidates[0].finish_reason)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "XBdqPso3kamW" - }, - "source": [ - "If the `finish_reason` is `FinishReason.SAFETY` you can check which filter caused the block checking the `safety_ratings` list for the candidate answer:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "he-OfzBbhACQ", - "tags": [] - }, - "outputs": [], - "source": [ - "print(response.candidates[0].safety_ratings)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "z9-SdzjbxWXT" - }, - "source": [ - "As the request was blocked by the safety filters, the `response.text` field will be empty (as nothing as generated by the model):" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "L1Da4cJ3xej3", - "tags": [] - }, - "outputs": [], - "source": [ - "try:\n", - " print(response.text)\n", - "except:\n", - " print(\"No information generated by the model.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4672af98ac57" - }, - "source": [ - "## Customizing safety settings\n", - "\n", - "Depending on the scenario you are working with, it may be necessary to customize the safety filters behaviors to allow a certain degree of unsafety results.\n", - "\n", - "To make this customization you must define a `safety_settings` dictionary as part of your `model.generate_content()` request. In the example below, all the filters are being set to do not block contents.\n", - "\n", - "**Important:** To guarantee the Google commitment with the Responsible AI development and its [AI Principles](https://ai.google/responsibility/principles/), for some prompts Gemini will avoid generating the results even if you set all the filters to none." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "338fb9a6af78", - "tags": [] - }, - "outputs": [], - "source": [ - "response = model.generate_content(\n", - " unsafe_prompt,\n", - " safety_settings={\n", - " 'HATE': 'BLOCK_NONE',\n", - " 'HARASSMENT': 'BLOCK_NONE',\n", - " 'SEXUAL' : 'BLOCK_NONE',\n", - " 'DANGEROUS' : 'BLOCK_NONE'\n", - " })" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "564K7R8rwWhs" - }, - "source": [ - "Checking again the `candidate.finish_reason` information, if the request was not too unsafe, it must show now the value as `FinishReason.STOP` which means that the request was successfully processed by Gemini." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LazB08GBpc1w", - "tags": [] - }, - "outputs": [], - "source": [ - "print(response.candidates[0].finish_reason)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "86c560e0a641" - }, - "source": [ - "Since the request was successfully generated, you can check the result on the `response.text`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "0c2847c49262", - "tags": [] - }, - "outputs": [], - "source": [ - "try:\n", - " print(response.text)\n", - "except:\n", - " print(\"No information generated by the model.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "47298a4eef40" - }, - "source": [ - "And if you check the safety filters ratings, as you set all filters to be ignored, no filtering category was trigerred:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "028febe8df68", - "tags": [] - }, - "outputs": [], - "source": [ - "print(response.candidates[0].safety_ratings)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "n1UdbxVt3ysY" - }, - "source": [ - "## Learning more\n", - "\n", - "Learn more with these articles on [safety guidance](https://ai.google.dev/docs/safety_guidance) and [safety settings](https://ai.google.dev/docs/safety_setting_gemini).\n", - "\n", - "## Useful API references\n", - "\n", - "There are 4 configurable safety settings for the Gemini API:\n", - "* `HARM_CATEGORY_DANGEROUS`\n", - "* `HARM_CATEGORY_HARASSMENT`\n", - "* `HARM_CATEGORY_SEXUALLY_EXPLICIT`\n", - "* `HARM_CATEGORY_DANGEROUS`\n", - "\n", - "You can refer to the safety settings using either their full name, or the aliases like `DANGEROUS` used in the Python code above.\n", - "\n", - "Safety settings can be set in the [genai.GenerativeModel](https://ai.google.dev/api/python/google/generativeai/GenerativeModel) constructor.\n", - "\n", - "* They can also be passed on each request to [GenerativeModel.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) or [ChatSession.send_message](https://ai.google.dev/api/python/google/generativeai/ChatSession?hl=en#send_message).\n", - "\n", - "- The [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse) returns [SafetyRatings](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) for the prompt in the [GenerateContentResponse.prompt_feedback](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse/PromptFeedback), and for each [Candidate](https://ai.google.dev/api/python/google/ai/generativelanguage/Candidate) in the `safety_ratings` attribute.\n", - "\n", - "- A [glm.SafetySetting](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetySetting) contains: [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [glm.HarmBlockThreshold](https://ai.google.dev/api/python/google/generativeai/types/HarmBlockThreshold)\n", - "\n", - "- A [glm.SafetyRating](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) contains a [HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [HarmProbability](https://ai.google.dev/api/python/google/generativeai/types/HarmProbability)\n", - "\n", - "The [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) enum includes both the categories for PaLM and Gemini models.\n", - "\n", - "- When specifying enum values the SDK will accept the enum values themselves, or their integer or string representations.\n", - "\n", - "- The SDK will also accept abbreviated string representations: `[\"HARM_CATEGORY_DANGEROUS_CONTENT\", \"DANGEROUS_CONTENT\", \"DANGEROUS\"]` are all valid. Strings are case insensitive." - ] - } - ], - "metadata": { - "colab": { - "name": "Safety.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "google": { - "image_path": "/static/site-assets/images/docs/logo-python.svg", - "keywords": [ - "examples", - "gemini", - "beginner", - "googleai", - "quickstart", - "python", - "text", - "chat", - "vision", - "embed" - ] - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/Streaming.ipynb b/quickstarts/Streaming.ipynb index a3d0e78af..275deb5d7 100644 --- a/quickstarts/Streaming.ipynb +++ b/quickstarts/Streaming.ipynb @@ -1,249 +1,220 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: Streaming Quickstart" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "df1767a3d1cc" - }, - "source": [ - "This notebook demonstrates streaming in the Python SDK. By default, the Python SDK returns a response after the model completes the entire generation process. You can also stream the response as it is being generated, and the model will return chunks of the response as soon as they are generated.\n", - "\n", - "**Download this notebook and run it locally (not in Google Colab)**\n", - "\n", - "Streaming is not handled correctly in Google Colab yet. Currently all the stream chunks are returned together, not as they are generated. To see the correct behavior, download this notebook and run it locally using Jupyter, instead." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "xuiLSV7amy3P" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai # Install the Python SDK" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "79EWm0DAmy-g" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "DkeZNMrw6kPD" - }, - "source": [ - "You'll need an API key stored in an environment variable to run this notebook. See the the [Authentication quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "t9O-OzeAKC_m" - }, - "outputs": [], - "source": [ - "import os\n", - "genai.configure(api_key=os.environ['GOOGLE_API_KEY'])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "BUoa5q0iUuE1" - }, - "source": [ - "## Handle streaming responses\n", - "\n", - "To stream responses, use [`GenerativeModel.generate_content(..., stream=True)`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content).\n", - "\n", - "**Note**: This cell runs with a Google Colab runtime, but does not properly show streaming due to implementation details of Colab runtimes." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "nVWWGBsBok3m", - "tags": [] - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", - "response = model.generate_content(\"Write a cute story about cats.\", stream=True)\n", - "for chunk in response:\n", - " print(chunk.text)\n", - " print(\"_\"*80)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "KswwVyHCKC_n" - }, - "source": [ - "## Handle streaming responses asynchronously\n", - "\n", - "To stream responses asynchronously, use [`GenerativeModel.generate_content_async(..., stream=True)`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content_async).\n", - "\n", - "**Note**: These cells do NOT work with a Google Colab runtime, but do work in a local Jupyter notebook." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "n6sXnWrJoKoo", - "tags": [] - }, - "outputs": [], - "source": [ - "async for chunk in await model.generate_content_async(\"Write a cute story about cats.\", stream=True):\n", - " if chunk.text:\n", - " print(chunk.text)\n", - " print(\"_\"*80)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "jpK3p1B4KC_o" - }, - "source": [ - "Here's a simple example of two asynchronous functions running simultaneously." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "IJ-8SjYwKC_o", - "tags": [] - }, - "outputs": [], - "source": [ - "import asyncio\n", - "\n", - "async def get_response():\n", - " async for chunk in await model.generate_content_async(\"Write a cute story about cats.\", stream=True):\n", - " if chunk.text:\n", - " print(chunk.text)\n", - " print(\"_\"*80)\n", - "\n", - "async def something_else():\n", - " for i in range(5):\n", - " print(\"==========not blocked!==========\")\n", - " await asyncio.sleep(3)\n", - "\n", - "async def async_demo():\n", - " # Create tasks\n", - " task1 = asyncio.create_task(get_response())\n", - " task2 = asyncio.create_task(something_else())\n", - "\n", - " # Wait for tasks to complete\n", - " await asyncio.gather(task1, task2)\n", - "\n", - "# Jupyter notebooks handle event loops for you, so await directly\n", - "await async_demo()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "colab": { - "name": "Streaming.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "google": { - "image_path": "/site-assets/images/share.png", - "keywords": [ - "examples", - "googleai", - "samplecode", - "python", - "embed", - "function" - ] - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: Streaming Quickstart" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "df1767a3d1cc" + }, + "source": [ + "This notebook demonstrates streaming in the Python SDK. By default, the Python SDK returns a response after the model completes the entire generation process. You can also stream the response as it is being generated, and the model will return chunks of the response as soon as they are generated.\n", + "\n", + "**Download this notebook and run it locally (not in Google Colab)**\n", + "\n", + "Streaming is not handled correctly in Google Colab yet. Currently all the stream chunks are returned together, not as they are generated. To see the correct behavior, download this notebook and run it locally using Jupyter, instead." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "xuiLSV7amy3P" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai # Install the Python SDK" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "79EWm0DAmy-g" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DkeZNMrw6kPD" + }, + "source": [ + "You'll need an API key stored in an environment variable to run this notebook. See the the [Authentication quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "t9O-OzeAKC_m" + }, + "outputs": [], + "source": [ + "import os\n", + "genai.configure(api_key=os.environ['GOOGLE_API_KEY'])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "BUoa5q0iUuE1" + }, + "source": [ + "## Handle streaming responses\n", + "\n", + "To stream responses, use [`GenerativeModel.generate_content(..., stream=True)`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content).\n", + "\n", + "**Note**: This cell runs with a Google Colab runtime, but does not properly show streaming due to implementation details of Colab runtimes." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "nVWWGBsBok3m" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel('gemini-1.5-flash-latest')\n", + "response = model.generate_content(\"Write a cute story about cats.\", stream=True)\n", + "for chunk in response:\n", + " print(chunk.text)\n", + " print(\"_\"*80)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "KswwVyHCKC_n" + }, + "source": [ + "## Handle streaming responses asynchronously\n", + "\n", + "To stream responses asynchronously, use [`GenerativeModel.generate_content_async(..., stream=True)`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content_async).\n", + "\n", + "**Note**: These cells do NOT work with a Google Colab runtime, but do work in a local Jupyter notebook." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "n6sXnWrJoKoo" + }, + "outputs": [], + "source": [ + "async for chunk in await model.generate_content_async(\"Write a cute story about cats.\", stream=True):\n", + " if chunk.text:\n", + " print(chunk.text)\n", + " print(\"_\"*80)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "jpK3p1B4KC_o" + }, + "source": [ + "Here's a simple example of two asynchronous functions running simultaneously." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "IJ-8SjYwKC_o" + }, + "outputs": [], + "source": [ + "import asyncio\n", + "\n", + "async def get_response():\n", + " async for chunk in await model.generate_content_async(\"Write a cute story about cats.\", stream=True):\n", + " if chunk.text:\n", + " print(chunk.text)\n", + " print(\"_\"*80)\n", + "\n", + "async def something_else():\n", + " for i in range(5):\n", + " print(\"==========not blocked!==========\")\n", + " await asyncio.sleep(3)\n", + "\n", + "async def async_demo():\n", + " # Create tasks\n", + " task1 = asyncio.create_task(get_response())\n", + " task2 = asyncio.create_task(something_else())\n", + "\n", + " # Wait for tasks to complete\n", + " await asyncio.gather(task1, task2)\n", + "\n", + "# Jupyter notebooks handle event loops for you, so await directly\n", + "await async_demo()" + ] + } + ], + "metadata": { + "colab": { + "name": "Streaming.ipynb", + "toc_visible": true + }, + "google": { + "image_path": "/site-assets/images/share.png", + "keywords": [ + "examples", + "googleai", + "samplecode", + "python", + "embed", + "function" + ] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/System_instructions.ipynb b/quickstarts/System_instructions.ipynb index 33aca46e1..b06189195 100644 --- a/quickstarts/System_instructions.ipynb +++ b/quickstarts/System_instructions.ipynb @@ -1,346 +1,310 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "b_5PfTJ-8htn" + }, + "source": [ + "# Gemini API: System instructions" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZQhiHuae9V9M" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "GCQ54fomBzg-" + }, + "source": [ + "System instructions allow you to steer the behavior of the model. By setting the system instruction, you are giving the model additional context to understand the task, provide more customized responses, and adhere to guidelines over the user interaction. Product-level behavior can be specified here, separate from prompts provided by end users.\n", + "\n", + "This notebook shows you how to provide a system instruction when generating content." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "lIYdn1woOS1n" + }, + "outputs": [], + "source": [ + "!pip install -U -q google-generativeai # Install the Python SDK" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4Z5KfSvHCtxO" + }, + "source": [ + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "GV09SmP5qN53" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "import google.generativeai as genai\n", + "\n", + "genai.configure(api_key=userdata.get(\"GOOGLE_API_KEY\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "qJIMOVI3DS7L" + }, + "source": [ + "## Set the system instruction 🐱" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "xUINgOFzLnI3" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel(\n", + " \"models/gemini-1.5-flash-latest\",\n", + " system_instruction=\"You are a cat. Your name is Neko.\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "mWS3-GwNLzku" + }, + "outputs": [], + "source": [ + "response = model.generate_content(\"Good morning! How are you?\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "CUkgp6q9MCif" + }, + "source": [ + "## Another example 🦜" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "FqWUIw1yDSL2" + }, + "outputs": [], + "source": [ + "instruction = \"You are a friendly pirate. Speak like one.\"\n", + "\n", + "model = genai.GenerativeModel(\n", + " \"models/gemini-1.5-flash-latest\", system_instruction=instruction\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "WeqvS8gyMX0-" + }, + "outputs": [], + "source": [ + "response = model.generate_content(\"Good morning! How are you?\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Nn-6AkGsFc64" + }, + "source": [ + "## Multi-turn conversations\n", + "\n", + "Multi-turn, or chat, conversations also work without any extra arguments once the model is set up." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "WxiIfsbA0WdH" + }, + "outputs": [], + "source": [ + "chat = model.start_chat()\n", + "response = chat.send_message(\"Good day fine chatbot\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "beFAm9kvQecS" + }, + "outputs": [], + "source": [ + "response = chat.send_message(\"How's your boat doing?\")\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tNjjzKOlMykP" + }, + "source": [ + "## Code generation" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "O2QS5ovKuXtw" + }, + "source": [ + "Below is an example of setting the system instruction when generating code." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "NxPCN_7euVJY" + }, + "outputs": [], + "source": [ + "instruction = (\n", + " \"You are a coding expert that specializes in front end interfaces. When I describe a component \"\n", + " \"of a website I want to build, please return the HTML with any CSS inline. Do not give an \"\n", + " \"explanation for this code.\"\n", + ")\n", + "\n", + "model = genai.GenerativeModel(\n", + " \"models/gemini-1.5-flash-latest\", system_instruction=instruction\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "S-KQefKiJZCA" + }, + "outputs": [], + "source": [ + "prompt = (\n", + " \"A flexbox with a large text logo aligned left and a list of links aligned right.\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "u79yE57aJasY" + }, + "outputs": [], + "source": [ + "response = model.generate_content(prompt)\n", + "print(response.text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "lf5919M-fwY2" + }, + "outputs": [], + "source": [ + "from IPython.display import HTML\n", + "\n", + "# Render the HTML\n", + "HTML(response.text.strip().removeprefix(\"```html\").removesuffix(\"```\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ci9OREVBKRaq" + }, + "source": [ + "## Further reading\n", + "\n", + "Please note that system instructions can help guide the model to follow instructions, but they do not fully prevent jailbreaks or leaks. At this time, we recommend exercising caution around putting any sensitive information in system instructions.\n", + "\n", + "See the systems instruction [documentation](https://ai.google.dev/docs/system_instructions) to learn more." + ] + } + ], + "metadata": { + "colab": { + "name": "System_instructions.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "b_5PfTJ-8htn" - }, - "source": [ - "# Gemini API: System instructions" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZQhiHuae9V9M" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "GCQ54fomBzg-" - }, - "source": [ - "System instructions allow you to steer the behavior of the model. By setting the system instruction, you are giving the model additional context to understand the task, provide more customized responses, and adhere to guidelines over the user interaction. Product-level behavior can be specified here, separate from prompts provided by end users.\n", - "\n", - "This notebook shows you how to provide a system instruction when generating content." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "lIYdn1woOS1n" - }, - "outputs": [], - "source": [ - "!pip install -U -q google-generativeai # Install the Python SDK" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4Z5KfSvHCtxO" - }, - "source": [ - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see the [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) quickstart for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "GV09SmP5qN53" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "import google.generativeai as genai\n", - "\n", - "genai.configure(api_key=userdata.get(\"GOOGLE_API_KEY\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "qJIMOVI3DS7L" - }, - "source": [ - "## Set the system instruction 🐱" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "xUINgOFzLnI3", - "tags": [] - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel(\n", - " \"models/gemini-1.5-flash-latest\",\n", - " system_instruction=\"You are a cat. Your name is Neko.\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "mWS3-GwNLzku", - "tags": [] - }, - "outputs": [], - "source": [ - "response = model.generate_content(\"Good morning! How are you?\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "CUkgp6q9MCif" - }, - "source": [ - "## Another example 🦜" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "FqWUIw1yDSL2", - "tags": [] - }, - "outputs": [], - "source": [ - "instruction = \"You are a friendly pirate. Speak like one.\"\n", - "\n", - "model = genai.GenerativeModel(\n", - " \"models/gemini-1.5-flash-latest\", system_instruction=instruction\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "WeqvS8gyMX0-", - "tags": [] - }, - "outputs": [], - "source": [ - "response = model.generate_content(\"Good morning! How are you?\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Nn-6AkGsFc64" - }, - "source": [ - "## Multi-turn conversations\n", - "\n", - "Multi-turn, or chat, conversations also work without any extra arguments once the model is set up." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "WxiIfsbA0WdH", - "tags": [] - }, - "outputs": [], - "source": [ - "chat = model.start_chat()\n", - "response = chat.send_message(\"Good day fine chatbot\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "beFAm9kvQecS", - "tags": [] - }, - "outputs": [], - "source": [ - "response = chat.send_message(\"How's your boat doing?\")\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tNjjzKOlMykP" - }, - "source": [ - "## Code generation" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "O2QS5ovKuXtw" - }, - "source": [ - "Below is an example of setting the system instruction when generating code." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "NxPCN_7euVJY", - "tags": [] - }, - "outputs": [], - "source": [ - "instruction = (\n", - " \"You are a coding expert that specializes in front end interfaces. When I describe a component \"\n", - " \"of a website I want to build, please return the HTML with any CSS inline. Do not give an \"\n", - " \"explanation for this code.\"\n", - ")\n", - "\n", - "model = genai.GenerativeModel(\n", - " \"models/gemini-1.5-flash-latest\", system_instruction=instruction\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "S-KQefKiJZCA", - "tags": [] - }, - "outputs": [], - "source": [ - "prompt = (\n", - " \"A flexbox with a large text logo aligned left and a list of links aligned right.\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "u79yE57aJasY", - "tags": [] - }, - "outputs": [], - "source": [ - "response = model.generate_content(prompt)\n", - "print(response.text)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "lf5919M-fwY2", - "tags": [] - }, - "outputs": [], - "source": [ - "from IPython.display import HTML\n", - "\n", - "# Render the HTML\n", - "HTML(response.text.strip().removeprefix(\"```html\").removesuffix(\"```\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ci9OREVBKRaq" - }, - "source": [ - "## Further reading\n", - "\n", - "Please note that system instructions can help guide the model to follow instructions, but they do not fully prevent jailbreaks or leaks. At this time, we recommend exercising caution around putting any sensitive information in system instructions.\n", - "\n", - "See the systems instruction [documentation](https://ai.google.dev/docs/system_instructions) to learn more." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "colab": { - "name": "System_instructions.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/Tuning.ipynb b/quickstarts/Tuning.ipynb index 07c3571f0..875780dc0 100644 --- a/quickstarts/Tuning.ipynb +++ b/quickstarts/Tuning.ipynb @@ -1,796 +1,777 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yeadDkMiISin" - }, - "source": [ - "# Gemini API: Tuning Quickstart with Python" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lEXQ3OwKIa-O" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Jp_CKyzxUqx6" - }, - "source": [ - "In this notebook, you'll learn how to get started with model tuning." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4x-2x8A_vi9g" - }, - "source": [ - "## What is model tuning?\n", - "\n", - "Prompt design strategies such as few shot prompting may not always produce the results you need. Use model tuning to improve a model's performance on specific tasks or help the model adhere to specific output requirements when instructions aren't sufficient and you have a set of examples that demonstrate the outputs you want.\n", - "\n", - "The goal of model tuning is to further improve the performance of the model for your specific task. Model tuning works by providing the model with a training dataset containing many examples of the task. For niche tasks, you can get significant improvements in model performance by tuning the model on a modest number of examples.\n", - "\n", - "Your training data should be structured as examples with prompt inputs and expected response outputs. The goal is to teach the model to mimic the wanted behavior or task, by giving it many examples illustrating that behavior or task.\n", - "\n", - "You can also tune models using example data directly in Google AI Studio." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "SWxKvwd-MSIV" - }, - "source": [ - "## OAuth Authentication" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "JjS8Zy1ojIgc" - }, - "source": [ - "Unlike the other quickstarts which use API keys, model tuning uses OAuth.\n", - "\n", - "This tutorial assumes you have completed the [OAuth Quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication_with_OAuth.ipynb) and you have your client secret saved as `CLIENT_SECRET` in the Colab secrets manager.\n", - "\n", - "> Important: **Don't just click the link this command prints**. That will fail. Follow the instructions and copy the `gcloud` command it prints to your local machine and run it there, then paste the output from your local machine back\n", - "here." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9FUwyB_MJ0-2" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "import pathlib\n", - "pathlib.Path('client_secret.json').write_text(userdata.get('CLIENT_SECRET'))\n", - "\n", - "# Use `--no-browser` in colab\n", - "!gcloud auth application-default login --no-browser --client-id-file client_secret.json --scopes='https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/generative-language.tuning'" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "cbcf72bcb56d" - }, - "outputs": [], - "source": [ - "!pip install -q -U google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "8enrppafJPCX" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "P-MYZECwlRCq" - }, - "source": [ - "You can check your existing tuned models with the `genai.list_tuned_model` method." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "XyWzoYFxU4r6" - }, - "outputs": [], - "source": [ - "for i, m in zip(range(5), genai.list_tuned_models()):\n", - " print(m.name)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "BhkXRzciv3Dp" - }, - "source": [ - "## Create tuned model" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "OO8VZYAinLWc" - }, - "source": [ - "To create a tuned model, you need to pass your dataset to the model in the `genai.create_tuned_model` method. You can do this be directly defining the input and output values in the call or importing from a file into a dataframe to pass to the method.\n", - "\n", - "For this example, you will tune a model to generate the next number in the sequence. For example, if the input is `1`, the model should output `2`. If the input is `one hundred`, the output should be `one hundred one`.\n", - "\n", - "**Note**: In general, you need between 100 and 500 examples to significantly change the behavior of the model." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "w-EBSe9wTbLB" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "Model(name='models/gemini-1.0-pro-001',\n", - " base_model_id='',\n", - " version='001',\n", - " display_name='Gemini 1.0 Pro 001 (Tuning)',\n", - " description=('The best model for scaling across a wide range of tasks. This is a stable '\n", - " 'model that supports tuning.'),\n", - " input_token_limit=30720,\n", - " output_token_limit=2048,\n", - " supported_generation_methods=['generateContent', 'countTokens', 'createTunedModel'],\n", - " temperature=0.9,\n", - " top_p=1.0,\n", - " top_k=1)" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "base_model = [\n", - " m for m in genai.list_models()\n", - " if \"createTunedModel\" in m.supported_generation_methods][0]\n", - "base_model" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "baHjHh1oTTTC" - }, - "outputs": [], - "source": [ - "import random\n", - "\n", - "name = f'generate-num-{random.randint(0,10000)}'\n", - "operation = genai.create_tuned_model(\n", - " # You can use a tuned model here too. Set `source_model=\"tunedModels/...\"`\n", - " source_model=base_model.name,\n", - " training_data=[\n", - " {\n", - " 'text_input': '1',\n", - " 'output': '2',\n", - " },{\n", - " 'text_input': '3',\n", - " 'output': '4',\n", - " },{\n", - " 'text_input': '-3',\n", - " 'output': '-2',\n", - " },{\n", - " 'text_input': 'twenty two',\n", - " 'output': 'twenty three',\n", - " },{\n", - " 'text_input': 'two hundred',\n", - " 'output': 'two hundred one',\n", - " },{\n", - " 'text_input': 'ninety nine',\n", - " 'output': 'one hundred',\n", - " },{\n", - " 'text_input': '8',\n", - " 'output': '9',\n", - " },{\n", - " 'text_input': '-98',\n", - " 'output': '-97',\n", - " },{\n", - " 'text_input': '1,000',\n", - " 'output': '1,001',\n", - " },{\n", - " 'text_input': '10,100,000',\n", - " 'output': '10,100,001',\n", - " },{\n", - " 'text_input': 'thirteen',\n", - " 'output': 'fourteen',\n", - " },{\n", - " 'text_input': 'eighty',\n", - " 'output': 'eighty one',\n", - " },{\n", - " 'text_input': 'one',\n", - " 'output': 'two',\n", - " },{\n", - " 'text_input': 'three',\n", - " 'output': 'four',\n", - " },{\n", - " 'text_input': 'seven',\n", - " 'output': 'eight',\n", - " }\n", - " ],\n", - " id = name,\n", - " epoch_count = 100,\n", - " batch_size=4,\n", - " learning_rate=0.001,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "-As7ayWDK1w8" - }, - "source": [ - "Your tuned model is immediately added to the list of tuned models, but its status is set to \"creating\" while the model is tuned." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "su64KgY4Uztj" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "TunedModel(name='tunedModels/generate-num-5392',\n", - " source_model='models/gemini-1.0-pro-001',\n", - " base_model='models/gemini-1.0-pro-001',\n", - " display_name='',\n", - " description='',\n", - " temperature=0.9,\n", - " top_p=1.0,\n", - " top_k=1,\n", - " state=,\n", - " create_time=datetime.datetime(2024, 3, 16, 0, 41, 42, 702621, tzinfo=datetime.timezone.utc),\n", - " update_time=datetime.datetime(2024, 3, 16, 0, 41, 42, 702621, tzinfo=datetime.timezone.utc),\n", - " tuning_task=TuningTask(start_time=datetime.datetime(2024, 3, 16, 0, 41, 43, 81144, tzinfo=datetime.timezone.utc),\n", - " complete_time=None,\n", - " snapshots=[],\n", - " hyperparameters=Hyperparameters(epoch_count=100,\n", - " batch_size=4,\n", - " learning_rate=0.001)))" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model = genai.get_tuned_model(f'tunedModels/{name}')\n", - "\n", - "model" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "EUodUwZkKPi-" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.state" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Pi8X5vkQv-3_" - }, - "source": [ - "### Check tuning progress" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tWI-vAh4LJIz" - }, - "source": [ - "Use `metadata` to check the state:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "g08vqtxYLMxT" - }, - "outputs": [], - "source": [ - "operation.metadata" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3lQ6gSMgK-kz" - }, - "source": [ - "Wait for the training to finish using `operation.result()`, or `operation.wait_bar()`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "SOUowIv1HgSE" - }, - "outputs": [], - "source": [ - "import time\n", - "\n", - "for status in operation.wait_bar():\n", - " time.sleep(30)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4cg868HzqOx5" - }, - "source": [ - "You can cancel your tuning job any time using the `cancel()` method. Uncomment the line below and run the code cell to cancel your job before it finishes." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "oQuJ70_hqJi9" - }, - "outputs": [], - "source": [ - "# operation.cancel()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lqiL0TWDqAPn" - }, - "source": [ - "Once the tuning is complete, you can view the loss curve from the tuning results. The [loss curve](https://generativeai.devsite.corp.google.com/guide/model_tuning_guidance#recommended_configurations) shows how much the model's predictions deviate from the ideal outputs." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "bIiG57xWLhP7" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import pandas as pd\n", - "import seaborn as sns\n", - "\n", - "model = operation.result()\n", - "\n", - "snapshots = pd.DataFrame(model.tuning_task.snapshots)\n", - "\n", - "sns.lineplot(data=snapshots, x = 'epoch', y='mean_loss')\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "rkoQTXb1vSBC" - }, - "source": [ - "## Evaluate your model\n", - "\n", - "You can use the `genai.generate_text` method and specify the name of your model to test your model performance." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "zO0YcuSyxydZ" - }, - "outputs": [], - "source": [ - "model = genai.GenerativeModel(model_name=f'tunedModels/{name}')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "UwGrrj6hS_x2" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'56'" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "result = model.generate_content('55')\n", - "result.text" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "YSNB2zjTx5SZ" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'123456'" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "result = model.generate_content('123455')\n", - "result.text" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Y2YVO-m0Ut9H" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'five'" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "result = model.generate_content('four')\n", - "result.text" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "h2MkTR0uTb6U" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'cinq'" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "result = model.generate_content('quatre') # French 4\n", - "result.text # French 5 is \"cinq\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "OruCW1zETsZw" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'IV'" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "result = model.generate_content('III') # Roman numeral 3\n", - "result.text # Roman numeral 4 is IV" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "thDdSuUDUJOx" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'ε…«'" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: Tuning Quickstart with Python" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lEXQ3OwKIa-O" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Jp_CKyzxUqx6" + }, + "source": [ + "In this notebook, you'll learn how to get started with model tuning." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4x-2x8A_vi9g" + }, + "source": [ + "## What is model tuning?\n", + "\n", + "Prompt design strategies such as few shot prompting may not always produce the results you need. Use model tuning to improve a model's performance on specific tasks or help the model adhere to specific output requirements when instructions aren't sufficient and you have a set of examples that demonstrate the outputs you want.\n", + "\n", + "The goal of model tuning is to further improve the performance of the model for your specific task. Model tuning works by providing the model with a training dataset containing many examples of the task. For niche tasks, you can get significant improvements in model performance by tuning the model on a modest number of examples.\n", + "\n", + "Your training data should be structured as examples with prompt inputs and expected response outputs. The goal is to teach the model to mimic the wanted behavior or task, by giving it many examples illustrating that behavior or task.\n", + "\n", + "You can also tune models using example data directly in Google AI Studio." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "SWxKvwd-MSIV" + }, + "source": [ + "## OAuth Authentication" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JjS8Zy1ojIgc" + }, + "source": [ + "Unlike the other quickstarts which use API keys, model tuning uses OAuth.\n", + "\n", + "This tutorial assumes you have completed the [OAuth Quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication_with_OAuth.ipynb) and you have your client secret saved as `CLIENT_SECRET` in the Colab secrets manager.\n", + "\n", + "> Important: **Don't just click the link this command prints**. That will fail. Follow the instructions and copy the `gcloud` command it prints to your local machine and run it there, then paste the output from your local machine back\n", + "here." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9FUwyB_MJ0-2" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "import pathlib\n", + "pathlib.Path('client_secret.json').write_text(userdata.get('CLIENT_SECRET'))\n", + "\n", + "# Use `--no-browser` in colab\n", + "!gcloud auth application-default login --no-browser --client-id-file client_secret.json --scopes='https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/generative-language.tuning'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "cbcf72bcb56d" + }, + "outputs": [], + "source": [ + "!pip install -q -U google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "8enrppafJPCX" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "P-MYZECwlRCq" + }, + "source": [ + "You can check your existing tuned models with the `genai.list_tuned_model` method." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "XyWzoYFxU4r6" + }, + "outputs": [], + "source": [ + "for i, m in zip(range(5), genai.list_tuned_models()):\n", + " print(m.name)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "BhkXRzciv3Dp" + }, + "source": [ + "## Create tuned model" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "OO8VZYAinLWc" + }, + "source": [ + "To create a tuned model, you need to pass your dataset to the model in the `genai.create_tuned_model` method. You can do this be directly defining the input and output values in the call or importing from a file into a dataframe to pass to the method.\n", + "\n", + "For this example, you will tune a model to generate the next number in the sequence. For example, if the input is `1`, the model should output `2`. If the input is `one hundred`, the output should be `one hundred one`.\n", + "\n", + "**Note**: In general, you need between 100 and 500 examples to significantly change the behavior of the model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "w-EBSe9wTbLB" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Model(name='models/gemini-1.0-pro-001',\n", + " base_model_id='',\n", + " version='001',\n", + " display_name='Gemini 1.0 Pro 001 (Tuning)',\n", + " description=('The best model for scaling across a wide range of tasks. This is a stable '\n", + " 'model that supports tuning.'),\n", + " input_token_limit=30720,\n", + " output_token_limit=2048,\n", + " supported_generation_methods=['generateContent', 'countTokens', 'createTunedModel'],\n", + " temperature=0.9,\n", + " top_p=1.0,\n", + " top_k=1)" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "base_model = [\n", + " m for m in genai.list_models()\n", + " if \"createTunedModel\" in m.supported_generation_methods][0]\n", + "base_model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "baHjHh1oTTTC" + }, + "outputs": [], + "source": [ + "import random\n", + "\n", + "name = f'generate-num-{random.randint(0,10000)}'\n", + "operation = genai.create_tuned_model(\n", + " # You can use a tuned model here too. Set `source_model=\"tunedModels/...\"`\n", + " source_model=base_model.name,\n", + " training_data=[\n", + " {\n", + " 'text_input': '1',\n", + " 'output': '2',\n", + " },{\n", + " 'text_input': '3',\n", + " 'output': '4',\n", + " },{\n", + " 'text_input': '-3',\n", + " 'output': '-2',\n", + " },{\n", + " 'text_input': 'twenty two',\n", + " 'output': 'twenty three',\n", + " },{\n", + " 'text_input': 'two hundred',\n", + " 'output': 'two hundred one',\n", + " },{\n", + " 'text_input': 'ninety nine',\n", + " 'output': 'one hundred',\n", + " },{\n", + " 'text_input': '8',\n", + " 'output': '9',\n", + " },{\n", + " 'text_input': '-98',\n", + " 'output': '-97',\n", + " },{\n", + " 'text_input': '1,000',\n", + " 'output': '1,001',\n", + " },{\n", + " 'text_input': '10,100,000',\n", + " 'output': '10,100,001',\n", + " },{\n", + " 'text_input': 'thirteen',\n", + " 'output': 'fourteen',\n", + " },{\n", + " 'text_input': 'eighty',\n", + " 'output': 'eighty one',\n", + " },{\n", + " 'text_input': 'one',\n", + " 'output': 'two',\n", + " },{\n", + " 'text_input': 'three',\n", + " 'output': 'four',\n", + " },{\n", + " 'text_input': 'seven',\n", + " 'output': 'eight',\n", + " }\n", + " ],\n", + " id = name,\n", + " epoch_count = 100,\n", + " batch_size=4,\n", + " learning_rate=0.001,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-As7ayWDK1w8" + }, + "source": [ + "Your tuned model is immediately added to the list of tuned models, but its status is set to \"creating\" while the model is tuned." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "su64KgY4Uztj" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "TunedModel(name='tunedModels/generate-num-5392',\n", + " source_model='models/gemini-1.0-pro-001',\n", + " base_model='models/gemini-1.0-pro-001',\n", + " display_name='',\n", + " description='',\n", + " temperature=0.9,\n", + " top_p=1.0,\n", + " top_k=1,\n", + " state=,\n", + " create_time=datetime.datetime(2024, 3, 16, 0, 41, 42, 702621, tzinfo=datetime.timezone.utc),\n", + " update_time=datetime.datetime(2024, 3, 16, 0, 41, 42, 702621, tzinfo=datetime.timezone.utc),\n", + " tuning_task=TuningTask(start_time=datetime.datetime(2024, 3, 16, 0, 41, 43, 81144, tzinfo=datetime.timezone.utc),\n", + " complete_time=None,\n", + " snapshots=[],\n", + " hyperparameters=Hyperparameters(epoch_count=100,\n", + " batch_size=4,\n", + " learning_rate=0.001)))" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model = genai.get_tuned_model(f'tunedModels/{name}')\n", + "\n", + "model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "EUodUwZkKPi-" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.state" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Pi8X5vkQv-3_" + }, + "source": [ + "### Check tuning progress" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tWI-vAh4LJIz" + }, + "source": [ + "Use `metadata` to check the state:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "g08vqtxYLMxT" + }, + "outputs": [], + "source": [ + "operation.metadata" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3lQ6gSMgK-kz" + }, + "source": [ + "Wait for the training to finish using `operation.result()`, or `operation.wait_bar()`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "SOUowIv1HgSE" + }, + "outputs": [], + "source": [ + "import time\n", + "\n", + "for status in operation.wait_bar():\n", + " time.sleep(30)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4cg868HzqOx5" + }, + "source": [ + "You can cancel your tuning job any time using the `cancel()` method. Uncomment the line below and run the code cell to cancel your job before it finishes." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "oQuJ70_hqJi9" + }, + "outputs": [], + "source": [ + "# operation.cancel()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lqiL0TWDqAPn" + }, + "source": [ + "Once the tuning is complete, you can view the loss curve from the tuning results. The [loss curve](https://generativeai.devsite.corp.google.com/guide/model_tuning_guidance#recommended_configurations) shows how much the model's predictions deviate from the ideal outputs." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "bIiG57xWLhP7" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "import seaborn as sns\n", + "\n", + "model = operation.result()\n", + "\n", + "snapshots = pd.DataFrame(model.tuning_task.snapshots)\n", + "\n", + "sns.lineplot(data=snapshots, x = 'epoch', y='mean_loss')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rkoQTXb1vSBC" + }, + "source": [ + "## Evaluate your model\n", + "\n", + "You can use the `genai.generate_text` method and specify the name of your model to test your model performance." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "zO0YcuSyxydZ" + }, + "outputs": [], + "source": [ + "model = genai.GenerativeModel(model_name=f'tunedModels/{name}')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "UwGrrj6hS_x2" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'56'" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = model.generate_content('55')\n", + "result.text" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "YSNB2zjTx5SZ" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'123456'" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = model.generate_content('123455')\n", + "result.text" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Y2YVO-m0Ut9H" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'five'" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = model.generate_content('four')\n", + "result.text" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "h2MkTR0uTb6U" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'cinq'" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = model.generate_content('quatre') # French 4\n", + "result.text # French 5 is \"cinq\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "OruCW1zETsZw" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'IV'" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = model.generate_content('III') # Roman numeral 3\n", + "result.text # Roman numeral 4 is IV" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "thDdSuUDUJOx" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'ε…«'" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = model.generate_content('δΈƒ') # Japanese 7\n", + "result.text # Japanese 8 is ε…«!" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HpIA1IFevQQR" + }, + "source": [ + "It really seems to have picked up the task despite the limited examples, but \"next\" is a simple concept, see the [tuning guide](https://ai.google.dev/docs/model_tuning_guidance) for more guidance on improving performance." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nmuQCbTYwIOx" + }, + "source": [ + "## Update the description\n", + "\n", + "You can update the description of your tuned model any time using the `genai.update_tuned_model` method." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9gAVuXT_wG3x" + }, + "outputs": [], + "source": [ + "genai.update_tuned_model(f'tunedModels/{name}', {\"description\":\"This is my model.\"});" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "d-c3YerBxVYs" + }, + "outputs": [ + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'This is my model.'" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model = genai.get_tuned_model(f'tunedModels/{name}')\n", + "\n", + "model.description" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "i_TpwvBB4bQ7" + }, + "source": [ + "## Delete the model\n", + "\n", + "You can clean up your tuned model list by deleting models you no longer need. Use the `genai.delete_tuned_model` method to delete a model. If you canceled any tuning jobs, you may want to delete those as their performance may be unpredictable." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "cepfaUCvVGCo" + }, + "outputs": [], + "source": [ + "genai.delete_tuned_model(f'tunedModels/{name}')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ljEssIshYDEr" + }, + "source": [ + "The model no longer exists:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "kN_bkut_4ayL" + }, + "outputs": [], + "source": [ + "try:\n", + " m = genai.get_tuned_model(f'tunedModels/{name}')\n", + " print(m)\n", + "except Exception as e:\n", + " print(f\"{type(e)}: {e}\")" + ] } - ], - "source": [ - "result = model.generate_content('δΈƒ') # Japanese 7\n", - "result.text # Japanese 8 is ε…«!" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "HpIA1IFevQQR" - }, - "source": [ - "It really seems to have picked up the task despite the limited examples, but \"next\" is a simple concept, see the [tuning guide](https://ai.google.dev/docs/model_tuning_guidance) for more guidance on improving performance." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nmuQCbTYwIOx" - }, - "source": [ - "## Update the description\n", - "\n", - "You can update the description of your tuned model any time using the `genai.update_tuned_model` method." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9gAVuXT_wG3x" - }, - "outputs": [], - "source": [ - "genai.update_tuned_model(f'tunedModels/{name}', {\"description\":\"This is my model.\"});" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "d-c3YerBxVYs" - }, - "outputs": [ - { - "data": { - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - }, - "text/plain": [ - "'This is my model.'" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" + ], + "metadata": { + "colab": { + "name": "Tuning.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" } - ], - "source": [ - "model = genai.get_tuned_model(f'tunedModels/{name}')\n", - "\n", - "model.description" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "i_TpwvBB4bQ7" - }, - "source": [ - "## Delete the model\n", - "\n", - "You can clean up your tuned model list by deleting models you no longer need. Use the `genai.delete_tuned_model` method to delete a model. If you canceled any tuning jobs, you may want to delete those as their performance may be unpredictable." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "cepfaUCvVGCo" - }, - "outputs": [], - "source": [ - "genai.delete_tuned_model(f'tunedModels/{name}')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ljEssIshYDEr" - }, - "source": [ - "The model no longer exists:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "kN_bkut_4ayL" - }, - "outputs": [], - "source": [ - "try:\n", - " m = genai.get_tuned_model(f'tunedModels/{name}')\n", - " print(m)\n", - "except Exception as e:\n", - " print(f\"{type(e)}: {e}\")" - ] - } - ], - "metadata": { - "colab": { - "name": "Tuning.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/Video.ipynb b/quickstarts/Video.ipynb index ee0069b5d..2c93a55e4 100644 --- a/quickstarts/Video.ipynb +++ b/quickstarts/Video.ipynb @@ -1,304 +1,281 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Tce3stUlHN0L" - }, - "source": [ - "##### Copyright 2024 Google LLC." - ] + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "084u8u0DpBlo" + }, + "source": [ + "# Gemini API: Prompting with Video" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "wnQ_LVlzIeXo" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "q7QvXQMrIhuZ" + }, + "source": [ + "This notebook provides a quick example of how to prompt Gemini 1.5 Pro using a video file. In this case, you'll use a short clip of [Big Buck Bunny](https://peach.blender.org/about/)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TwpXMTnpsoHC" + }, + "outputs": [], + "source": [ + "!pip install -U google-generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ATIbQM0NHhkj" + }, + "outputs": [], + "source": [ + "import google.generativeai as genai" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ngyzKAu3Nw5k" + }, + "source": [ + "### Authentication Overview\n", + "\n", + "**Important:** The File API uses API keys for authentication and access. Uploaded files are associated with the API key's cloud project. Unlike other Gemini APIs that use API keys, your API key also grants access data you've uploaded to the File API, so take extra care in keeping your API key secure. For best practices on securing API keys, refer to Google's [documentation](https://support.google.com/googleapi/answer/6310037)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "l8g4hTRotheH" + }, + "source": [ + "### Setup your API key\n", + "\n", + "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "d6lYXRcjthKV" + }, + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", + "genai.configure(api_key=GOOGLE_API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "MNvhBdoDFnTC" + }, + "source": [ + "## Upload a video to the Files API\n", + "\n", + "The Gemini API accepts video file formats directly. The File API accepts files under 2GB in size and can store up to 20GB of files per project. Files last for 2 days and cannot be downloaded from the API. For the example, you will use the short film \"Big Buck Bunny\".\n", + "\n", + "> \"Big Buck Bunny\" is (c) copyright 2008, Blender Foundation / www.bigbuckbunny.org and [licensed](https://peach.blender.org/about/) under the [Creative Commons Attribution 3.0](http://creativecommons.org/licenses/by/3.0/) License.\n", + "\n", + "Note: You can also [upload your own files](https://github.com/google-gemini/cookbook/blob/main/examples/Upload_files_to_Colab.ipynb) to use." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "V4XeFdX1rxaE" + }, + "outputs": [], + "source": [ + "!wget https://download.blender.org/peach/bigbuckbunny_movies/BigBuckBunny_320x180.mp4" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "_HzrDdp2Q1Cu" + }, + "outputs": [], + "source": [ + "video_file_name = \"BigBuckBunny_320x180.mp4\"\n", + "\n", + "print(f\"Uploading file...\")\n", + "video_file = genai.upload_file(path=video_file_name)\n", + "print(f\"Completed upload: {video_file.uri}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "oOZmTUb4FWOa" + }, + "source": [ + "## Get File\n", + "\n", + "After uploading the file, you can verify the API has successfully received the files by calling `files.get`.\n", + "\n", + "`files.get` lets you see the file uploaded to the File API that are associated with the Cloud project your API key belongs to. Only the `name` (and by extension, the `uri`) are unique." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "SHMVCWHkFhJW" + }, + "outputs": [], + "source": [ + "import time\n", + "\n", + "while video_file.state.name == \"PROCESSING\":\n", + " print('Waiting for video to be processed.')\n", + " time.sleep(10)\n", + " video_file = genai.get_file(video_file.name)\n", + "\n", + "if video_file.state.name == \"FAILED\":\n", + " raise ValueError(video_file.state.name)\n", + "print(f'Video processing complete: ' + video_file.uri)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EPPOECHzsIGJ" + }, + "source": [ + "## Generate Content\n", + "\n", + "After the video has been uploaded, you can make `GenerateContent` requests that reference the File API URI." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "5977cd76eccc" + }, + "outputs": [], + "source": [ + "# Create the prompt.\n", + "prompt = \"Describe this video.\"\n", + "\n", + "# Set the model to Gemini 1.5 Flash.\n", + "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-flash-latest\")\n", + "\n", + "# Make the LLM request.\n", + "print(\"Making LLM inference request...\")\n", + "response = model.generate_content([prompt, video_file],\n", + " request_options={\"timeout\": 600})\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IrPDYdQSKTg4" + }, + "source": [ + "## Delete File\n", + "\n", + "Files are automatically deleted after 2 days or you can manually delete them using `files.delete()`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ggoi6wibct18" + }, + "outputs": [], + "source": [ + "genai.delete_file(video_file.name)\n", + "print(f'Deleted file {video_file.uri}')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "K5oUCqb6IUnH" + }, + "source": [ + "## Learning more\n", + "\n", + "The File API lets you upload a variety of multimodal MIME types, including images, audio, and video formats. The File API handles inputs that can be used to generate content with [`model.generateContent`](https://ai.google.dev/api/rest/v1/models/generateContent) or [`model.streamGenerateContent`](https://ai.google.dev/api/rest/v1/models/streamGenerateContent).\n", + "\n", + "The File API accepts files under 2GB in size and can store up to 20GB of files per project. Files last for 2 days and cannot be downloaded from the API.\n", + "\n", + "* Learn more about the [File API](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb) with the quickstart.\n", + "\n", + "* Learn more about prompting with [media files](https://ai.google.dev/tutorials/prompting_with_media) in the docs, including the supported formats and maximum length." + ] + } + ], + "metadata": { + "colab": { + "name": "Video.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "tuOe1ymfHZPu" - }, - "outputs": [], - "source": [ - "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", - "# you may not use this file except in compliance with the License.\n", - "# You may obtain a copy of the License at\n", - "#\n", - "# https://www.apache.org/licenses/LICENSE-2.0\n", - "#\n", - "# Unless required by applicable law or agreed to in writing, software\n", - "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", - "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", - "# See the License for the specific language governing permissions and\n", - "# limitations under the License." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "084u8u0DpBlo" - }, - "source": [ - "# Gemini API: Prompting with Video" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "wnQ_LVlzIeXo" - }, - "source": [ - "\n", - " \n", - "
\n", - " Run in Google Colab\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "q7QvXQMrIhuZ" - }, - "source": [ - "This notebook provides a quick example of how to prompt Gemini 1.5 Pro using a video file. In this case, you'll use a short clip of [Big Buck Bunny](https://peach.blender.org/about/)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "TwpXMTnpsoHC" - }, - "outputs": [], - "source": [ - "!pip install -U google-generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ATIbQM0NHhkj" - }, - "outputs": [], - "source": [ - "import google.generativeai as genai" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ngyzKAu3Nw5k" - }, - "source": [ - "### Authentication Overview\n", - "\n", - "**Important:** The File API uses API keys for authentication and access. Uploaded files are associated with the API key's cloud project. Unlike other Gemini APIs that use API keys, your API key also grants access data you've uploaded to the File API, so take extra care in keeping your API key secure. For best practices on securing API keys, refer to Google's [documentation](https://support.google.com/googleapi/answer/6310037)." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "l8g4hTRotheH" - }, - "source": [ - "### Setup your API key\n", - "\n", - "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "d6lYXRcjthKV" - }, - "outputs": [], - "source": [ - "from google.colab import userdata\n", - "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n", - "genai.configure(api_key=GOOGLE_API_KEY)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "MNvhBdoDFnTC" - }, - "source": [ - "## Upload a video to the Files API\n", - "\n", - "The Gemini API accepts video file formats directly. The File API accepts files under 2GB in size and can store up to 20GB of files per project. Files last for 2 days and cannot be downloaded from the API. For the example, you will use the short film \"Big Buck Bunny\".\n", - "\n", - "> \"Big Buck Bunny\" is (c) copyright 2008, Blender Foundation / www.bigbuckbunny.org and [licensed](https://peach.blender.org/about/) under the [Creative Commons Attribution 3.0](http://creativecommons.org/licenses/by/3.0/) License.\n", - "\n", - "Note: You can also [upload your own files](https://github.com/google-gemini/cookbook/blob/main/examples/Upload_files_to_Colab.ipynb) to use." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "V4XeFdX1rxaE", - "tags": [] - }, - "outputs": [], - "source": [ - "!wget https://download.blender.org/peach/bigbuckbunny_movies/BigBuckBunny_320x180.mp4" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "_HzrDdp2Q1Cu", - "tags": [] - }, - "outputs": [], - "source": [ - "video_file_name = \"BigBuckBunny_320x180.mp4\"\n", - "\n", - "print(f\"Uploading file...\")\n", - "video_file = genai.upload_file(path=video_file_name)\n", - "print(f\"Completed upload: {video_file.uri}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "oOZmTUb4FWOa" - }, - "source": [ - "## Get File\n", - "\n", - "After uploading the file, you can verify the API has successfully received the files by calling `files.get`.\n", - "\n", - "`files.get` lets you see the file uploaded to the File API that are associated with the Cloud project your API key belongs to. Only the `name` (and by extension, the `uri`) are unique." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "SHMVCWHkFhJW", - "tags": [] - }, - "outputs": [], - "source": [ - "import time\n", - "\n", - "while video_file.state.name == \"PROCESSING\":\n", - " print('Waiting for video to be processed.')\n", - " time.sleep(10)\n", - " video_file = genai.get_file(video_file.name)\n", - "\n", - "if video_file.state.name == \"FAILED\":\n", - " raise ValueError(video_file.state.name)\n", - "print(f'Video processing complete: ' + video_file.uri)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "EPPOECHzsIGJ" - }, - "source": [ - "## Generate Content\n", - "\n", - "After the video has been uploaded, you can make `GenerateContent` requests that reference the File API URI." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "# Create the prompt.\n", - "prompt = \"Describe this video.\"\n", - "\n", - "# Set the model to Gemini 1.5 Flash.\n", - "model = genai.GenerativeModel(model_name=\"models/gemini-1.5-flash-latest\")\n", - "\n", - "# Make the LLM request.\n", - "print(\"Making LLM inference request...\")\n", - "response = model.generate_content([prompt, video_file],\n", - " request_options={\"timeout\": 600})\n", - "print(response.text)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IrPDYdQSKTg4" - }, - "source": [ - "## Delete File\n", - "\n", - "Files are automatically deleted after 2 days or you can manually delete them using `files.delete()`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ggoi6wibct18", - "tags": [] - }, - "outputs": [], - "source": [ - "genai.delete_file(video_file.name)\n", - "print(f'Deleted file {video_file.uri}')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "K5oUCqb6IUnH" - }, - "source": [ - "## Learning more\n", - "\n", - "The File API lets you upload a variety of multimodal MIME types, including images, audio, and video formats. The File API handles inputs that can be used to generate content with [`model.generateContent`](https://ai.google.dev/api/rest/v1/models/generateContent) or [`model.streamGenerateContent`](https://ai.google.dev/api/rest/v1/models/streamGenerateContent).\n", - "\n", - "The File API accepts files under 2GB in size and can store up to 20GB of files per project. Files last for 2 days and cannot be downloaded from the API.\n", - "\n", - "* Learn more about the [File API](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb) with the quickstart.\n", - "\n", - "* Learn more about prompting with [media files](https://ai.google.dev/tutorials/prompting_with_media) in the docs, including the supported formats and maximum length." - ] - } - ], - "metadata": { - "colab": { - "name": "Video.ipynb", - "toc_visible": true - }, - "environment": { - "kernel": "python3", - "name": "tf2-cpu.2-11.m120", - "type": "gcloud", - "uri": "us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf2-cpu.2-11:m120" - }, - "kernelspec": { - "display_name": "Python 3 (Local)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/quickstarts/file-api/.gitignore b/quickstarts/file-api/.gitignore new file mode 100644 index 000000000..9e48ceb11 --- /dev/null +++ b/quickstarts/file-api/.gitignore @@ -0,0 +1,4 @@ +venv/ +.env +node_modules/ +.DS_STORE diff --git a/quickstarts/file-api/README.md b/quickstarts/file-api/README.md new file mode 100644 index 000000000..0f9676ff8 --- /dev/null +++ b/quickstarts/file-api/README.md @@ -0,0 +1,56 @@ +# Gemini File API Sample Client Code + +## Background +The Gemini File API provides a simple way for developers to upload files and use them with the Gemini API in multimodal scenarios. This repository shows how to use the File API to upload an image and include it in a `GenerateContent` call to the Gemini API. + + +> [!IMPORTANT] +> The File API is currently in beta and is [only available in certain regions](https://ai.google.dev/available_regions). + +## Quickstarts +Ready to get started? Learn the essentials of uploading files and using them in GenerateContent requests to the Gemini API: + +[File API Colab](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb) + +[Audio Colab](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Audio.ipynb) + +[Video Colab](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Video.ipynb) + + +## Python Sample +``` +# Prepare a virtual environment for Python. +python3 -m venv venv +source venv/bin/activate + +# Add API key to .env file +touch .env +echo "GOOGLE_API_KEY='YOUR_API_KEY'" >> .env + +# Install dependencies. +pip3 install -U -r requirements.txt + +# Run the sample code. +python3 sample.py +``` + +## Node.js Sample +``` +# Make sure npm is installed first. + +# Add API key to .env file +touch .env +echo "GOOGLE_API_KEY='YOUR_API_KEY'" >> .env + +# Install dependencies. +npm install + +# Run the sample code. +npm start +``` + +## cURL Bash Script Sample +The following script will upload a file given the file path. +``` +bash ./sample.sh -a "" -i "sample_data/gemini_logo.png" -d "Gemini logo" +``` diff --git a/quickstarts/file-api/package-lock.json b/quickstarts/file-api/package-lock.json new file mode 100644 index 000000000..407d9fd83 --- /dev/null +++ b/quickstarts/file-api/package-lock.json @@ -0,0 +1,519 @@ +{ + "name": "file-api-client-samples", + "version": "1.0.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "file-api-client-samples", + "version": "1.0.0", + "dependencies": { + "dotenv": "^16.4.5", + "googleapis": "^134.0.0", + "mime-types": "^2.1.35" + } + }, + "node_modules/agent-base": { + "version": "7.1.0", + "resolved": "https://registry.npmjs.org/agent-base/-/agent-base-7.1.0.tgz", + "integrity": "sha512-o/zjMZRhJxny7OyEF+Op8X+efiELC7k7yOjMzgfzVqOzXqkBkWI79YoTdOtsuWd5BWhAGAuOY/Xa6xpiaWXiNg==", + "dependencies": { + "debug": "^4.3.4" + }, + "engines": { + "node": ">= 14" + } + }, + "node_modules/base64-js": { + 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a/quickstarts/file-api/sample.js b/quickstarts/file-api/sample.js new file mode 100644 index 000000000..192223ca1 --- /dev/null +++ b/quickstarts/file-api/sample.js @@ -0,0 +1,50 @@ +const dotenv = require('dotenv'); +const fs = require('fs'); +const {google} = require('googleapis'); +const mime = require('mime-types'); + +// Load environment variables from .env file +dotenv.config({ path: '.env' }); +const API_KEY = process.env.GOOGLE_API_KEY; +const GENAI_DISCOVERY_URL = `https://generativelanguage.googleapis.com/$discovery/rest?version=v1beta&key=${API_KEY}`; + + +async function run(filePath, fileDisplayName) { + // Initialize API Client + const genaiService = await google.discoverAPI({url: GENAI_DISCOVERY_URL}); + const auth = new google.auth.GoogleAuth().fromAPIKey(API_KEY); + + // Prepare file to upload to GenAI File API + const media = { + mimeType: mime.lookup(filePath), + body: fs.createReadStream(filePath), + }; + var body = {"file": {"displayName": fileDisplayName}}; + try { + // Upload the file + const createFileResponse = await genaiService.media.upload({ + media: media, auth: auth, requestBody:body}); + const file = createFileResponse.data.file; + const fileUri = file.uri; + console.log("Uploaded file: " + fileUri); + + // Make Gemini 1.5 API LLM call + const prompt = "Describe the image with a creative description"; + const model = "models/gemini-1.5-pro-latest"; + const contents = {'contents': [{ + 'parts':[ + {'text': prompt}, + {'file_data': {'file_uri': fileUri, 'mime_type': file.mimeType}}] + }]} + const generateContentResponse = await genaiService.models.generateContent({ + model: model, requestBody: contents, auth: auth}); + console.log(JSON.stringify(generateContentResponse.data)); + } + catch (err) { + throw err; + } +} + +filePath = "sample_data/gemini_logo.png"; +fileDisplayName = "Gemini logo"; +run(filePath, fileDisplayName); diff --git a/quickstarts/file-api/sample.py b/quickstarts/file-api/sample.py new file mode 100644 index 000000000..3e8c09ce0 --- /dev/null +++ b/quickstarts/file-api/sample.py @@ -0,0 +1,32 @@ +import google.generativeai as genai +import os +from dotenv import load_dotenv + +# Load environment variables from .env file +load_dotenv() +api_key = os.environ["GOOGLE_API_KEY"] + +# Initialize Google API Client +genai.configure(api_key=api_key) + +# Prepare file to upload to GenAI File API +file_path = "sample_data/gemini_logo.png" +display_name = "Gemini Logo" +file_response = genai.upload_file(path=file_path, + display_name=display_name) +print(f"Uploaded file {file_response.display_name} as: {file_response.uri}") + +# Verify the file is uploaded to the API +get_file = genai.get_file(name=file_response.name) +print(f"Retrieved file {get_file.display_name} as: {get_file.uri}") + +# Make Gemini 1.5 API LLM call +prompt = "Describe the image with a creative description" +model_name = "models/gemini-1.5-pro-latest" +model = genai.GenerativeModel(model_name=model_name) +response = model.generate_content([prompt, file_response]) +print(response) + +# Delete the sample file +genai.delete_file(name=file_response.name) +print(f'Deleted file {file_response.display_name}') diff --git a/quickstarts/file-api/sample.sh b/quickstarts/file-api/sample.sh new file mode 100755 index 000000000..b042d8bda --- /dev/null +++ b/quickstarts/file-api/sample.sh @@ -0,0 +1,70 @@ +#!/bin/bash +# +# Upload a file using the GenAI File API via curl. +api_key="" +input_file="" +display_name="" + +while getopts a:i:d: flag +do + case "${flag}" in + a) api_key=${OPTARG};; + i) input_file=${OPTARG};; + d) display_name=${OPTARG};; + esac +done + +BASE_URL="https://generativelanguage.googleapis.com" + +CHUNK_SIZE=8388608 # 8 MiB +MIME_TYPE=$(file -b --mime-type "${input_file}") +NUM_BYTES=$(wc -c < "${input_file}") + +echo "Starting upload of '${input_file}' to ${BASE_URL}..." +echo " MIME type: '${MIME_TYPE}'" +echo " Size: ${NUM_BYTES} bytes" + +# Initial resumable request defining metadata. +tmp_header_file=$(mktemp /tmp/upload-header.XXX) +curl "${BASE_URL}/upload/v1beta/files?key=${api_key}" \ + -D "${tmp_header_file}" \ + -H "X-Goog-Upload-Protocol: resumable" \ + -H "X-Goog-Upload-Command: start" \ + -H "X-Goog-Upload-Header-Content-Length: ${NUM_BYTES}" \ + -H "X-Goog-Upload-Header-Content-Type: ${MIME_TYPE}" \ + -H "Content-Type: application/json" \ + -d "{'file': {'display_name': '${display_name}'}}" +upload_url=$(grep "x-goog-upload-url: " "${tmp_header_file}" | cut -d" " -f2 | tr -d "\r") +rm "${tmp_header_file}" + +if [[ -z "${upload_url}" ]]; then + echo "Failed initial resumable upload request." + exit 1 +fi + +# Upload the actual bytes. +NUM_CHUNKS=$(((NUM_BYTES + CHUNK_SIZE - 1) / CHUNK_SIZE)) +tmp_chunk_file=$(mktemp /tmp/upload-chunk.XXX) +for i in $(seq 1 ${NUM_CHUNKS}) +do + offset=$((i - 1)) + byte_offset=$((offset * CHUNK_SIZE)) + # Read the actual bytes to the tmp file. + dd skip="${offset}" bs="${CHUNK_SIZE}" count=1 if="${input_file}" of="${tmp_chunk_file}" 2>/dev/null + num_chunk_bytes=$(wc -c < "${tmp_chunk_file}") + upload_command="upload" + if [[ ${i} -eq ${NUM_CHUNKS} ]] ; then + # For the final chunk, specify "finalize". + upload_command="${upload_command}, finalize" + fi + echo " Uploading ${byte_offset} - $((byte_offset + num_chunk_bytes)) of ${NUM_BYTES}..." + curl "${upload_url}" \ + -H "Content-Length: ${num_chunk_bytes}" \ + -H "X-Goog-Upload-Offset: ${byte_offset}" \ + -H "X-Goog-Upload-Command: ${upload_command}" \ + --data-binary "@${tmp_chunk_file}" +done + +rm "${tmp_chunk_file}" + +echo "Upload complete!" diff --git a/quickstarts/file-api/sample_data/gemini_logo.png b/quickstarts/file-api/sample_data/gemini_logo.png new file mode 100644 index 0000000000000000000000000000000000000000..44987a8c7fd25449ef5d2f240bae2b3f9a596e44 GIT binary patch literal 19864 zcmYkkcOaGj`#*jk$ILN8b{rY;vbP9_N+Ma6k-f92>~WGJR4QeU5-nR+h^%ai>^)OP 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\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JMNKdTpTGZET" + }, + "source": [ + "This notebook provides quick code examples that show you how to get started generating embeddings using `curl`.\n", + "\n", + "You can run this in Google Colab, or you can copy/paste the `curl` commands into your terminal.\n", + "\n", + "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "R-Vw_mOM_WD0" + }, + "outputs": [], + "source": [ + "import os\n", + "from google.colab import userdata" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "wCkLTpb3oTXE" + }, + "outputs": [], + "source": [ + "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tjGqGBZ9yARd" + }, + "source": [ + "## Embed content\n", + "\n", + "Call the `embed_content` method with the `text-embedding-004` model to generate text embeddings:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "id": "eA7I_Ww8IETn" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"embedding\": {\n", + " \"values\": [\n", + " 0.013168523,\n", + " -0.008711934,\n", + " -0.046782676,\n", + " 0.00069968984,\n", + " -0.009518873,\n", + " -0.008720178,\n", + " 0.060103577,\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/text-embedding-004:embedContent?key=$GOOGLE_API_KEY\" \\\n", + "-H 'Content-Type: application/json' \\\n", + "-d '{\"model\": \"models/text-embedding-004\",\n", + " \"content\": {\n", + " \"parts\":[{\n", + " \"text\": \"Hello world\"}]}, }' 2> /dev/null | head" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "x7ngWdZ7yDHp" + }, + "source": [ + "# Batch embed content\n", + "\n", + "You can embed a list of multiple prompts with one API call for efficiency.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "id": "Z0b35xv5Ja_d" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"embeddings\": [\n", + " {\n", + " \"values\": [\n", + " -0.010632277,\n", + " 0.019375855,\n", + " 0.0209652,\n", + " 0.0007706424,\n", + " -0.061464064,\n", + "--\n", + " -0.0071538696,\n", + " -0.028534694\n", + " ]\n", + " },\n", + " {\n", + " \"values\": [\n", + " 0.018467998,\n", + " 0.0054281196,\n", + " -0.017658804,\n", + " 0.013859266,\n", + " 0.053418662,\n", + "--\n", + " 0.026714385,\n", + " 0.0018762538\n", + " ]\n", + " },\n", + " {\n", + " \"values\": [\n", + " 0.05808907,\n", + " 0.020941721,\n", + " -0.108728774,\n", + " -0.04039259,\n", + " -0.04440443,\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/text-embedding-004:batchEmbedContents?key=$GOOGLE_API_KEY\" \\\n", + "-H 'Content-Type: application/json' \\\n", + "-d '{\"requests\": [{\n", + " \"model\": \"models/text-embedding-004\",\n", + " \"content\": {\n", + " \"parts\":[{\n", + " \"text\": \"What is the meaning of life?\"}]}, },\n", + " {\n", + " \"model\": \"models/text-embedding-004\",\n", + " \"content\": {\n", + " \"parts\":[{\n", + " \"text\": \"How much wood would a woodchuck chuck?\"}]}, },\n", + " {\n", + " \"model\": \"models/text-embedding-004\",\n", + " \"content\": {\n", + " \"parts\":[{\n", + " \"text\": \"How does the brain work?\"}]}, }, ]}' 2> /dev/null | grep -C 5 values" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nPBk2k4xuql8" + }, + "source": [ + "## Set the output dimensionality\n", + "If you're using `text-embeddings-004`, you can set the `output_dimensionality` parameter to create smaller embeddings.\n", + "\n", + "* `output_dimensionality` truncates the embedding (e.g., `[1, 3, 5]` becomes `[1,3]` when `output_dimensionality=2`).\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "id": "ny3bOQK1ut2_" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"embedding\": {\n", + " \"values\": [\n", + " 0.013168523,\n", + " -0.008711934,\n", + " -0.046782676,\n", + " 0.00069968984,\n", + " -0.009518873,\n", + " -0.008720178,\n", + " 0.060103577,\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/text-embedding-004:embedContent?key=$GOOGLE_API_KEY\" \\\n", + "-H 'Content-Type: application/json' \\\n", + "-d '{\"model\": \"models/text-embedding-004\",\n", + " \"output_dimensionality\":256,\n", + " \"content\": {\n", + " \"parts\":[{\n", + " \"text\": \"Hello world\"}]}, }' 2> /dev/null | head" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ObAdUvlk9x05" + }, + "source": [ + "## Use `task_type` to provide a hint to the model how you'll use the embeddings\n", + "\n", + "Let's look at all the parameters the embed_content method takes. There are four:\n", + "\n", + "* `model`: Required. Must be `models/embedding-001`.\n", + "* `content`: Required. The content that you would like to embed.\n", + "* `task_type`: Optional. The task type for which the embeddings will be used. See below for possible values.\n", + "* `title`: The given text is a document from a corpus being searched. Optionally, set the `title` parameter with the title of the document. Can only be set when `task_type` is `RETRIEVAL_DOCUMENT`.\n", + "\n", + "`task_type` is an optional parameter that provides a hint to the API about how you intend to use the embeddings in your application.\n", + "\n", + "The following task_type parameters are accepted:\n", + "\n", + "* `TASK_TYPE_UNSPECIFIED`: If you do not set the value, it will default to retrieval_query.\n", + "* `RETRIEVAL_QUERY` : The given text is a query in a search/retrieval setting.\n", + "* `RETRIEVAL_DOCUMENT`: The given text is a document from the corpus being searched.\n", + "* `SEMANTIC_SIMILARITY`: The given text will be used for Semantic Textual Similarity (STS).\n", + "* `CLASSIFICATION`: The given text will be classified.\n", + "* `CLUSTERING`: The embeddings will be used for clustering.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "id": "NwzsJmRrAo-t" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"embedding\": {\n", + " \"values\": [\n", + " 0.060187872,\n", + " -0.031515103,\n", + " -0.03244149,\n", + " -0.019341845,\n", + " 0.057285223,\n", + " 0.037159503,\n", + " 0.035636507,\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/embedding-001:embedContent?key=$GOOGLE_API_KEY\" \\\n", + "-H 'Content-Type: application/json' \\\n", + "-d '{\"model\": \"models/text-embedding-004\",\n", + " \"content\": {\n", + " \"parts\":[{\n", + " \"text\": \"Hello world\"}]},\n", + " \"task_type\": \"RETRIEVAL_DOCUMENT\",\n", + " \"title\": \"My title\"}' 2> /dev/null | head" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "jXkRYBhbB_b2" + }, + "source": [ + "## Learning more\n", + "\n", + "* Learn more about text-embeddings-004 [here](https://developers.googleblog.com/2024/04/gemini-15-pro-in-public-preview-with-new-features.html).\n", + "* See the [REST API reference](https://ai.google.dev/api/rest) to learn more.\n", + "* Explore more examples in the cookbook.\n" + ] + } + ], + "metadata": { + "colab": { + "name": "Embeddings_REST.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/quickstarts/rest/Function_calling_REST.ipynb b/quickstarts/rest/Function_calling_REST.ipynb new file mode 100644 index 000000000..cb89b5c36 --- /dev/null +++ b/quickstarts/rest/Function_calling_REST.ipynb @@ -0,0 +1,766 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "--TyBtqKrCHg" + }, + "source": [ + "# Gemini API: Function calling with REST\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4244NXM5rJt5" + }, + "source": [ + "This notebook provides quick code examples that show you how to get started with function calling using `curl`.\n", + "\n", + "You can run this in Google Colab, or you can copy/paste the `curl` commands into your terminal.\n", + "\n", + "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "pxd3u97ZsR5c" + }, + "outputs": [], + "source": [ + "import os\n", + "from google.colab import userdata\n", + "\n", + "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lmdFGEHrrMg8" + }, + "source": [ + "## How function calling works" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nLN0s1FIrepp" + }, + "source": [ + "Function calling lets developers create a description of a function in their code, then pass that description to a language model in a request. The response from the model includes the name of a function that matches the description and the arguments to call it with. Function calling lets you use functions as tools in generative AI applications, and you can define more than one function within a single request. Function calling returns JSON with the name of a function and the arguments to use in your code.\n", + "\n", + "Functions are described using *function declarations*. After you pass a list of\n", + "function declarations in a query to a language model, the model returns an\n", + "object in an [OpenAPI compatible schema](https://spec.openapis.org/oas/v3.0.3#schema)\n", + "format that includes the names of functions and their arguments and tries to\n", + "answer the user query with one of the returned functions. The language model\n", + "understands the purpose of a function by analyzing its function declaration. The\n", + "model doesn't actually call the function. Instead, a developer uses the\n", + "[OpenAPI compatible schema](https://spec.openapis.org/oas/v3.0.3#schema) object\n", + "in the response to call the function that the model returns.\n", + "\n", + "When you implement function calling, you create one or more *function\n", + "declarations*, then add the function declarations to a `tools` object that's\n", + "passed to the model. Each function declaration contains information about one\n", + "function that includes the following:\n", + "\n", + "* Function name\n", + "* Function parameters in an\n", + " [OpenAPI compatible schema](https://spec.openapis.org/oas/v3.0.3#schemawr) format.\n", + " A [select subset](https://ai.google.dev/api/rest/v1beta/Tool#Schema) is\n", + " supported. When using curl, the schema is specified using JSON.\n", + "* Function description (optional). For the best results, we recommend that you\n", + " include a description.\n", + "\n", + "This notebook includes curl examples that make REST calls with the\n", + "`GenerativeModel` class and its methods." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "vnC8xzmOrgt0" + }, + "source": [ + "## Supported models" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ocMX8ebNrj0A" + }, + "source": [ + "The following model supports function calling:\n", + "\n", + "* `gemini-pro`" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-Z7dneXGrmGo" + }, + "source": [ + "## Function calling cURL samples\n", + "\n", + "When you use cURL, the function and parameter information is included in the\n", + "`tools` element. Each function declaration in the `tools` element contains the\n", + "function name, its parameters specified using the\n", + "[OpenAPI compatible schema](https://spec.openapis.org/oas/v3.0.3#schema), and\n", + "a function description. The following samples demonstrate how to use curl\n", + "commands with function calling:" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zG9ktjHdrpKA" + }, + "source": [ + "### Single-turn curl sample\n", + "\n", + "Single-turn is when you call the language model one time. With function calling,\n", + "a single-turn use case might be when you provide the model a natural language\n", + "query and a list of functions. In this case, the model uses the function\n", + "declaration, which includes the function name, parameters, and description, to\n", + "predict which function to call and the arguments to call it with.\n", + "\n", + "The following curl sample is an example of passing in a description of a\n", + "function that returns information about where a movie is playing. Several\n", + "function declarations are included in the request, such as `find_movies` and\n", + "`find_theaters`." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "id": "vlf-DZSVrIu-" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"candidates\": [\n", + " {\n", + " \"content\": {\n", + " \"parts\": [\n", + " {\n", + " \"functionCall\": {\n", + " \"name\": \"find_theaters\",\n", + " \"args\": {\n", + " \"movie\": \"Barbie\",\n", + " \"location\": \"Mountain View, CA\"\n", + " }\n", + " }\n", + " }\n", + " ],\n", + " \"role\": \"model\"\n", + " },\n", + " \"finishReason\": \"STOP\",\n", + " \"index\": 0,\n", + " \"safetyRatings\": [\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " }\n", + " ]\n", + " }\n", + " ],\n", + " \"promptFeedback\": {\n", + " \"safetyRatings\": [\n", + " {\n", + " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " }\n", + " ]\n", + " }\n", + "}\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -d '{\n", + " \"contents\": {\n", + " \"role\": \"user\",\n", + " \"parts\": {\n", + " \"text\": \"Which theaters in Mountain View show Barbie movie?\"\n", + " }\n", + " },\n", + " \"tools\": [\n", + " {\n", + " \"function_declarations\": [\n", + " {\n", + " \"name\": \"find_movies\",\n", + " \"description\": \"find movie titles currently playing in theaters based on any description, genre, title words, etc.\",\n", + " \"parameters\": {\n", + " \"type\": \"object\",\n", + " \"properties\": {\n", + " \"location\": {\n", + " \"type\": \"string\",\n", + " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", + " },\n", + " \"description\": {\n", + " \"type\": \"string\",\n", + " \"description\": \"Any kind of description including category or genre, title words, attributes, etc.\"\n", + " }\n", + " },\n", + " \"required\": [\n", + " \"description\"\n", + " ]\n", + " }\n", + " },\n", + " {\n", + " \"name\": \"find_theaters\",\n", + " \"description\": \"find theaters based on location and optionally movie title which are is currently playing in theaters\",\n", + " \"parameters\": {\n", + " \"type\": \"object\",\n", + " \"properties\": {\n", + " \"location\": {\n", + " \"type\": \"string\",\n", + " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", + " },\n", + " \"movie\": {\n", + " \"type\": \"string\",\n", + " \"description\": \"Any movie title\"\n", + " }\n", + " },\n", + " \"required\": [\n", + " \"location\"\n", + " ]\n", + " }\n", + " },\n", + " {\n", + " \"name\": \"get_showtimes\",\n", + " \"description\": \"Find the start times for movies playing in a specific theater\",\n", + " \"parameters\": {\n", + " \"type\": \"object\",\n", + " \"properties\": {\n", + " \"location\": {\n", + " \"type\": \"string\",\n", + " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", + " },\n", + " \"movie\": {\n", + " \"type\": \"string\",\n", + " \"description\": \"Any movie title\"\n", + " },\n", + " \"theater\": {\n", + " \"type\": \"string\",\n", + " \"description\": \"Name of the theater\"\n", + " },\n", + " \"date\": {\n", + " \"type\": \"string\",\n", + " \"description\": \"Date for requested showtime\"\n", + " }\n", + " },\n", + " \"required\": [\n", + " \"location\",\n", + " \"movie\",\n", + " \"theater\",\n", + " \"date\"\n", + " ]\n", + " }\n", + " }\n", + " ]\n", + " }\n", + " ]\n", + "}' 2> /dev/null" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "mPry4O2vsclo" + }, + "source": [ + "### Multi-turn curl examples\n", + "\n", + "You can implement a multi-turn function calling scenario by doing the following:\n", + "\n", + "1. Get a function call response by calling the language model. This is the first\n", + " turn.\n", + "1. Call the language model using the function call response from the first turn\n", + " and the function response you get from calling that function. This is the\n", + " second turn.\n", + "\n", + "The response from the second turn either summarizes the results to answer your\n", + "query in the first turn, or contains a second function call you can use to get\n", + "more information for your query.\n", + "\n", + "This topic includes two multi-turn curl examples:\n", + "\n", + "* Curl example that uses a function response from a previous turn\n", + "* Curl example that calls a language model multiple times" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "hbGg-7mSsn26" + }, + "source": [ + "#### Curl example that uses a response from a previous turn\n", + "\n", + "The following curl sample calls the function and arguments returned by the\n", + "previous single-turn example to get a response. The method and parameters\n", + "returned by the single-turn example are in this JSON.\n", + "\n", + "```json\n", + "\"functionCall\": {\n", + " \"name\": \"find_theaters\",\n", + " \"args\": {\n", + " \"movie\": \"Barbie\",\n", + " \"location\": \"Mountain View, CA\"\n", + " }\n", + "}\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "id": "_yb-YAv-r2tf" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"candidates\": [\n", + " {\n", + " \"content\": {\n", + " \"parts\": [\n", + " {\n", + " \"text\": \"OK. I found two theaters in Mountain View that are showing the Barbie movie: AMC Mountain View 16 and Regal Edwards 14.\"\n", + " }\n", + " ],\n", + " \"role\": \"model\"\n", + " },\n", + " \"finishReason\": \"STOP\",\n", + " \"index\": 0,\n", + " \"safetyRatings\": [\n", + " {\n", + " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " }\n", + " ]\n", + " }\n", + " ]\n", + "}\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -d '{\n", + " \"contents\": [{\n", + " \"role\": \"user\",\n", + " \"parts\": [{\n", + " \"text\": \"Which theaters in Mountain View show Barbie movie?\"\n", + " }]\n", + " }, {\n", + " \"role\": \"model\",\n", + " \"parts\": [{\n", + " \"functionCall\": {\n", + " \"name\": \"find_theaters\",\n", + " \"args\": {\n", + " \"location\": \"Mountain View, CA\",\n", + " \"movie\": \"Barbie\"\n", + " }\n", + " }\n", + " }]\n", + " }, {\n", + " \"role\": \"function\",\n", + " \"parts\": [{\n", + " \"functionResponse\": {\n", + " \"name\": \"find_theaters\",\n", + " \"response\": {\n", + " \"name\": \"find_theaters\",\n", + " \"content\": {\n", + " \"movie\": \"Barbie\",\n", + " \"theaters\": [{\n", + " \"name\": \"AMC Mountain View 16\",\n", + " \"address\": \"2000 W El Camino Real, Mountain View, CA 94040\"\n", + " }, {\n", + " \"name\": \"Regal Edwards 14\",\n", + " \"address\": \"245 Castro St, Mountain View, CA 94040\"\n", + " }]\n", + " }\n", + " }\n", + " }\n", + " }]\n", + " }],\n", + " \"tools\": [{\n", + " \"functionDeclarations\": [{\n", + " \"name\": \"find_movies\",\n", + " \"description\": \"find movie titles currently playing in theaters based on any description, genre, title words, etc.\",\n", + " \"parameters\": {\n", + " \"type\": \"OBJECT\",\n", + " \"properties\": {\n", + " \"location\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", + " },\n", + " \"description\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"Any kind of description including category or genre, title words, attributes, etc.\"\n", + " }\n", + " },\n", + " \"required\": [\"description\"]\n", + " }\n", + " }, {\n", + " \"name\": \"find_theaters\",\n", + " \"description\": \"find theaters based on location and optionally movie title which are is currently playing in theaters\",\n", + " \"parameters\": {\n", + " \"type\": \"OBJECT\",\n", + " \"properties\": {\n", + " \"location\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", + " },\n", + " \"movie\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"Any movie title\"\n", + " }\n", + " },\n", + " \"required\": [\"location\"]\n", + " }\n", + " }, {\n", + " \"name\": \"get_showtimes\",\n", + " \"description\": \"Find the start times for movies playing in a specific theater\",\n", + " \"parameters\": {\n", + " \"type\": \"OBJECT\",\n", + " \"properties\": {\n", + " \"location\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", + " },\n", + " \"movie\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"Any movie title\"\n", + " },\n", + " \"theater\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"Name of the theater\"\n", + " },\n", + " \"date\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"Date for requested showtime\"\n", + " }\n", + " },\n", + " \"required\": [\"location\", \"movie\", \"theater\", \"date\"]\n", + " }\n", + " }]\n", + " }]\n", + "}' 2> /dev/null" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "eMpUbIvQt2qx" + }, + "source": [ + "#### Curl example that calls a language model multiple times\n", + "\n", + "The following curl example calls the language model multiple times to call a\n", + "function. Each time the model calls the function, it can use a different\n", + "function to answer a different user query in the request." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "id": "OKjGRZDUsxwj" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"candidates\": [\n", + " {\n", + " \"content\": {\n", + " \"parts\": [\n", + " {\n", + " \"functionCall\": {\n", + " \"name\": \"find_movies\",\n", + " \"args\": {\n", + " \"location\": \"Mountain View, CA\",\n", + " \"description\": \"comedy\"\n", + " }\n", + " }\n", + " }\n", + " ],\n", + " \"role\": \"model\"\n", + " },\n", + " \"finishReason\": \"STOP\",\n", + " \"index\": 0,\n", + " \"safetyRatings\": [\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " }\n", + " ]\n", + " }\n", + " ],\n", + " \"promptFeedback\": {\n", + " \"safetyRatings\": [\n", + " {\n", + " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " }\n", + " ]\n", + " }\n", + "}\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -d '{\n", + " \"contents\": [{\n", + " \"role\": \"user\",\n", + " \"parts\": [{\n", + " \"text\": \"Which theaters in Mountain View show Barbie movie?\"\n", + " }]\n", + " }, {\n", + " \"role\": \"model\",\n", + " \"parts\": [{\n", + " \"functionCall\": {\n", + " \"name\": \"find_theaters\",\n", + " \"args\": {\n", + " \"location\": \"Mountain View, CA\",\n", + " \"movie\": \"Barbie\"\n", + " }\n", + " }\n", + " }]\n", + " }, {\n", + " \"role\": \"function\",\n", + " \"parts\": [{\n", + " \"functionResponse\": {\n", + " \"name\": \"find_theaters\",\n", + " \"response\": {\n", + " \"name\": \"find_theaters\",\n", + " \"content\": {\n", + " \"movie\": \"Barbie\",\n", + " \"theaters\": [{\n", + " \"name\": \"AMC Mountain View 16\",\n", + " \"address\": \"2000 W El Camino Real, Mountain View, CA 94040\"\n", + " }, {\n", + " \"name\": \"Regal Edwards 14\",\n", + " \"address\": \"245 Castro St, Mountain View, CA 94040\"\n", + " }]\n", + " }\n", + " }\n", + " }\n", + " }]\n", + " },\n", + " {\n", + " \"role\": \"model\",\n", + " \"parts\": [{\n", + " \"text\": \" OK. Barbie is showing in two theaters in Mountain View, CA: AMC Mountain View 16 and Regal Edwards 14.\"\n", + " }]\n", + " },{\n", + " \"role\": \"user\",\n", + " \"parts\": [{\n", + " \"text\": \"Can we recommend some comedy movies on show in Mountain View?\"\n", + " }]\n", + " }],\n", + " \"tools\": [{\n", + " \"functionDeclarations\": [{\n", + " \"name\": \"find_movies\",\n", + " \"description\": \"find movie titles currently playing in theaters based on any description, genre, title words, etc.\",\n", + " \"parameters\": {\n", + " \"type\": \"OBJECT\",\n", + " \"properties\": {\n", + " \"location\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", + " },\n", + " \"description\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"Any kind of description including category or genre, title words, attributes, etc.\"\n", + " }\n", + " },\n", + " \"required\": [\"description\"]\n", + " }\n", + " }, {\n", + " \"name\": \"find_theaters\",\n", + " \"description\": \"find theaters based on location and optionally movie title which are is currently playing in theaters\",\n", + " \"parameters\": {\n", + " \"type\": \"OBJECT\",\n", + " \"properties\": {\n", + " \"location\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", + " },\n", + " \"movie\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"Any movie title\"\n", + " }\n", + " },\n", + " \"required\": [\"location\"]\n", + " }\n", + " }, {\n", + " \"name\": \"get_showtimes\",\n", + " \"description\": \"Find the start times for movies playing in a specific theater\",\n", + " \"parameters\": {\n", + " \"type\": \"OBJECT\",\n", + " \"properties\": {\n", + " \"location\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\"\n", + " },\n", + " \"movie\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"Any movie title\"\n", + " },\n", + " \"theater\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"Name of the theater\"\n", + " },\n", + " \"date\": {\n", + " \"type\": \"STRING\",\n", + " \"description\": \"Date for requested showtime\"\n", + " }\n", + " },\n", + " \"required\": [\"location\", \"movie\", \"theater\", \"date\"]\n", + " }\n", + " }]\n", + " }]\n", + "}' 2> /dev/null" + ] + } + ], + "metadata": { + "colab": { + "name": "Function_calling_REST.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/quickstarts/rest/Function_calling_config_REST.ipynb b/quickstarts/rest/Function_calling_config_REST.ipynb new file mode 100644 index 000000000..f4ff5d05c --- /dev/null +++ b/quickstarts/rest/Function_calling_config_REST.ipynb @@ -0,0 +1,371 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Jfj-4AdKHjJI" + }, + "source": [ + "# Gemini API: Function calling config with REST\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tV_jXDT0IrfK" + }, + "source": [ + "Specifying a `function_calling_config` allows you to control how the Gemini API acts when `tools` have been specified. For example, you can choose to only allow free-text output (disabling function calling), force it to choose from a subset of the functions provided in `tools`, or let it act automatically.\n", + "\n", + "This guide assumes you are already familiar with function calling. For an introduction, check out the [Function calling with REST](./Function_calling_REST.ipynb) recipe." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "CYi9bLkjI8NJ" + }, + "source": [ + "This notebook provides quick code examples that show you how to get started with function calling using `curl`.\n", + "\n", + "You can run this in Google Colab, or you can copy/paste the `curl` commands into your terminal.\n", + "\n", + "To run this notebook, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "M0O2o_tMHeo8" + }, + "outputs": [], + "source": [ + "import os\n", + "from google.colab import userdata\n", + "\n", + "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "G2d8-T2dOpMu" + }, + "source": [ + "## Set up a model with tools\n", + "\n", + "This example provides the model with some functions that control a hypothetical lighting system. Using these functions requires them to be called in a specific order. For example, you must turn the light system on before you can change the color.\n", + "\n", + "While you can pass these directly to the model and let it try to call them correctly, specifying the `function_calling_config` gives you precise control over the functions that are available to the model.\n", + "\n", + "Write the tools to `tools.json` so that you can reference it in later steps." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "SS_h6C3MfH48" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Overwriting tools.json\n" + ] + } + ], + "source": [ + "%%file tools.json\n", + "{\n", + " \"function_declarations\": [\n", + " {\n", + " \"name\": \"enable_lights\",\n", + " \"description\": \"Turn on the lighting system.\",\n", + " \"parameters\": { \"type\": \"object\" }\n", + " },\n", + " {\n", + " \"name\": \"set_light_color\",\n", + " \"description\": \"Set the light color. Lights must be enabled for this to work.\",\n", + " \"parameters\": {\n", + " \"type\": \"object\",\n", + " \"properties\": {\n", + " \"rgb_hex\": {\n", + " \"type\": \"string\",\n", + " \"description\": \"The light color as a 6-digit hex string, e.g. ff0000 for red.\"\n", + " }\n", + " },\n", + " \"required\": [\n", + " \"rgb_hex\"\n", + " ]\n", + " }\n", + " },\n", + " {\n", + " \"name\": \"stop_lights\",\n", + " \"description\": \"Turn off the lighting system.\",\n", + " \"parameters\": { \"type\": \"object\" }\n", + " }\n", + " ]\n", + "}" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "k6eYRyKUlw2S" + }, + "source": [ + "## Text-only mode: `NONE`\n", + "\n", + "If you have provided the model with tools, but do not want to use those tools for the current conversational turn, then specify `NONE` as the mode. `NONE` tells the model not to make any function calls, and it will behave as though none have been provided.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "u1MWQ82Phsav" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \"content\": {\n", + " \"parts\": [\n", + " {\n", + " \"text\": \"As your lighting system, I can turn the lights on and off, and I can set the color of the lights. \\n\"\n", + " }\n", + " ],\n", + " \"role\": \"model\"\n", + " },\n", + " \"finishReason\": \"STOP\",\n" + ] + } + ], + "source": [ + "%%bash\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent?key=$GOOGLE_API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -d @<(echo '\n", + " {\n", + " \"system_instruction\": {\n", + " \"parts\": {\n", + " \"text\": \"You are a helpful lighting system bot. You can turn lights on and off, and you can set the color. Do not perform any other tasks.\"\n", + " }\n", + " },\n", + " \"tools\": [' $(cat tools.json) '],\n", + "\n", + " \"tool_config\": {\n", + " \"function_calling_config\": {\"mode\": \"none\"}\n", + " },\n", + "\n", + " \"contents\": {\n", + " \"role\": \"user\",\n", + " \"parts\": {\n", + " \"text\": \"What can you do?\"\n", + " }\n", + " }\n", + " }\n", + "') 2>/dev/null |sed -n '/\"content\"/,/\"finishReason\"/p'" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "BaAie9Sjnd4u" + }, + "source": [ + "## Automatic mode: `AUTO`\n", + "\n", + "To allow the model to decide whether to respond in text or call specific functions, you can specify `AUTO` as the mode." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "tqHz3Gd8neSd" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \"content\": {\n", + " \"parts\": [\n", + " {\n", + " \"functionCall\": {\n", + " \"name\": \"enable_lights\",\n", + " \"args\": {}\n", + " }\n", + " }\n", + " ],\n", + " \"role\": \"model\"\n", + " },\n", + " \"finishReason\": \"STOP\",\n" + ] + } + ], + "source": [ + "%%bash\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent?key=$GOOGLE_API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -d @<(echo '\n", + " {\n", + " \"system_instruction\": {\n", + " \"parts\": {\n", + " \"text\": \"You are a helpful lighting system bot. You can turn lights on and off, and you can set the color. Do not perform any other tasks.\"\n", + " }\n", + " },\n", + " \"tools\": [' $(cat tools.json) '],\n", + "\n", + " \"tool_config\": {\n", + " \"function_calling_config\": {\"mode\": \"auto\"}\n", + " },\n", + "\n", + " \"contents\": {\n", + " \"role\": \"user\",\n", + " \"parts\": {\n", + " \"text\": \"Light this place up!\"\n", + " }\n", + " }\n", + " }\n", + "') 2>/dev/null |sed -n '/\"content\"/,/\"finishReason\"/p'" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EYE8-BDepHJn" + }, + "source": [ + "## Function-calling mode: `ANY`\n", + "\n", + "Setting the mode to `ANY` will force the model to make a function call. By setting `allowed_function_names`, the model will only choose from those functions. If it is not set, all of the functions in `tools` are candidates for function calling.\n", + "\n", + "In this example system, if the lights are already on, then the user can change color or turn the lights off.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "J2vaxGdYpPGt" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \"content\": {\n", + " \"parts\": [\n", + " {\n", + " \"functionCall\": {\n", + " \"name\": \"set_light_color\",\n", + " \"args\": {\n", + " \"rgb_hex\": \"9400d3\"\n", + " }\n", + " }\n", + " }\n", + " ],\n", + " \"role\": \"model\"\n", + " },\n", + " \"finishReason\": \"STOP\",\n" + ] + } + ], + "source": [ + "%%bash\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent?key=$GOOGLE_API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -d @<(echo '\n", + " {\n", + " \"system_instruction\": {\n", + " \"parts\": {\n", + " \"text\": \"You are a helpful lighting system bot. You can turn lights on and off, and you can set the color. Do not perform any other tasks.\"\n", + " }\n", + " },\n", + " \"tools\": [' $(cat tools.json) '],\n", + "\n", + " \"tool_config\": {\n", + " \"function_calling_config\": {\n", + " \"mode\": \"any\",\n", + " \"allowed_function_names\": [\"set_light_color\", \"stop_lights\"]\n", + " }\n", + " },\n", + "\n", + " \"contents\": {\n", + " \"role\": \"user\",\n", + " \"parts\": {\n", + " \"text\": \"Make this place PURPLE!\"\n", + " }\n", + " }\n", + " }\n", + "') 2>/dev/null |sed -n '/\"content\"/,/\"finishReason\"/p'" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "WbXzyFVTqYwn" + }, + "source": [ + "## Further reading\n", + "\n", + "Check out the [function calling recipe](./Function_calling_REST.ipynb) for more on function calling." + ] + } + ], + "metadata": { + "colab": { + "name": "Function_calling_config_REST.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/quickstarts/rest/JSON_mode_REST.ipynb b/quickstarts/rest/JSON_mode_REST.ipynb new file mode 100644 index 000000000..ad364e770 --- /dev/null +++ b/quickstarts/rest/JSON_mode_REST.ipynb @@ -0,0 +1,172 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "agmT3hrjsffX" + }, + "source": [ + "# Gemini API: JSON Mode Quickstart with REST\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JMNKdTpTGZET" + }, + "source": [ + "This notebook provides a code example that shows you how to get started with JSON mode using `curl`.\n", + "\n", + "You can run this in Google Colab, or you can copy/paste the `curl` commands into your terminal.\n", + "\n", + "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/gemini-api-cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "R-Vw_mOM_WD0" + }, + "outputs": [], + "source": [ + "import os\n", + "from google.colab import userdata" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "wCkLTpb3oTXE" + }, + "outputs": [], + "source": [ + "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tjGqGBZ9yARd" + }, + "source": [ + "## Activate JSON Mode\n", + "\n", + "To activate JSON mode, set `response_mime_type` to `application/json` in the `generationConfig`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "eA7I_Ww8IETn" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"candidates\": [\n", + " {\n", + " \"content\": {\n", + " \"parts\": [\n", + " {\n", + " \"text\": \"[{\\\"recipe_name\\\":\\\"Chocolate Chip Cookies\\\"},{\\\"recipe_name\\\":\\\"Peanut Butter Cookies\\\"},{\\\"recipe_name\\\":\\\"Oatmeal Raisin Cookies\\\"},{\\\"recipe_name\\\":\\\"Sugar Cookies\\\"},{\\\"recipe_name\\\":\\\"Shortbread Cookies\\\"}] \\n\"\n", + " }\n", + " ],\n", + " \"role\": \"model\"\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent?key=$GOOGLE_API_KEY\" \\\n", + "-H 'Content-Type: application/json' \\\n", + "-d '{\n", + " \"contents\": [{\n", + " \"parts\":[\n", + " {\"text\": \"List a few popular cookie recipes using this JSON schema:\n", + " {'type': 'object', 'properties': { 'recipe_name': {'type': 'string'}}}\"\n", + " }\n", + " ]\n", + " }],\n", + " \"generationConfig\": {\n", + " \"response_mime_type\": \"application/json\",\n", + " }\n", + "}' 2> /dev/null | head" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "OxN68aKNDxEV" + }, + "source": [ + "To turn off JSON mode, set `response_mime_type` to `text/plain` (or omit the `response_mime_type` parameter)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "jXkRYBhbB_b2" + }, + "source": [ + "## Learning more\n", + "\n", + "See the [JSON mode documentation](https://ai.google.dev/docs/gemini_api_overview#json) and the [REST API reference](https://ai.google.dev/api/rest/v1beta/GenerationConfig) for `generationConfig` to learn more.\n" + ] + } + ], + "metadata": { + "colab": { + "name": "JSON_mode_REST.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/quickstarts/rest/Models_REST.ipynb b/quickstarts/rest/Models_REST.ipynb new file mode 100644 index 000000000..0b79e8b16 --- /dev/null +++ b/quickstarts/rest/Models_REST.ipynb @@ -0,0 +1,163 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "bR6s6M2SUMUx" + }, + "source": [ + "# Gemini API: Models with REST\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0M75jc-zqqdp" + }, + "source": [ + "This notebook demonstrates how to list the models that are available for you to use in the Gemini API, and how to find details about a model in `curl`.\n", + "\n", + "You can run this in Google Colab, or you can copy/paste the curl commands into your terminal.\n", + "\n", + "To run this notebook, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "qyEYgM6SGjTc" + }, + "outputs": [], + "source": [ + "import os\n", + "from google.colab import userdata" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "HR74aKGsLW3T" + }, + "outputs": [], + "source": [ + "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yw0-IjXtUgCq" + }, + "source": [ + "## Model info\n", + "\n", + "### List models\n", + "\n", + "If you `GET` the models directory, it uses the `list` method to list all of the models available through the API, including both the Gemini and PaLM family models." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "M2aeVCrQLc-4" + }, + "outputs": [], + "source": [ + "%%bash\n", + "\n", + "curl https://generativelanguage.googleapis.com/v1beta/models?key=$GOOGLE_API_KEY" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "CLUf1EqxUWCB" + }, + "source": [ + "### Get model\n", + "\n", + "If you `GET` a model's URL, the API uses the `get` method to return information about that model such as version, display name, input token limit, etc." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "PYFpfBFpUKM-" + }, + "outputs": [], + "source": [ + "%%bash\n", + "\n", + "curl https://generativelanguage.googleapis.com/v1beta/models/gemini-pro?key=$GOOGLE_API_KEY" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JZetmJD6UleV" + }, + "source": [ + "## Learning more\n", + "\n", + "To learn how use a model for prompting, see the [Prompting](https://github.com/google-gemini/cookbook/blob/main/quickstarts/rest/Prompting_REST.ipynb) quickstart.\n", + "\n", + "To learn how use a model for embedding, see the [Embedding](https://github.com/google-gemini/cookbook/blob/main/quickstarts/rest/Embeddings_REST.ipynb) quickstart.\n", + "\n", + "For more information on models, visit the [Gemini models](https://ai.google.dev/models/gemini) documentation." + ] + } + ], + "metadata": { + "colab": { + "name": "Models_REST.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/quickstarts/rest/Prompting_REST.ipynb b/quickstarts/rest/Prompting_REST.ipynb new file mode 100644 index 000000000..c8c53e82d --- /dev/null +++ b/quickstarts/rest/Prompting_REST.ipynb @@ -0,0 +1,611 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xmzgQqBasA0v" + }, + "source": [ + "# Gemini API: Prompting Quickstart with REST\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "265f8066d5d5" + }, + "source": [ + "If you want to quickly try out the Gemini API, you can use `curl` commands to call the methods in the REST API.\n", + "\n", + "This notebook contains `curl` commands you can run in Google Colab, or copy to your terminal.\n", + "\n", + "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "GgaOvPo_r2SB" + }, + "outputs": [], + "source": [ + "import os\n", + "from google.colab import userdata" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "-PqX1RI_sjoV" + }, + "outputs": [], + "source": [ + "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9WjnnMbysntU" + }, + "source": [ + "## Run your first prompt\n", + "\n", + "Use the `generateContent` method to generate responses to your prompts. You can pass text directly to `generateContent`.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "4eB7rHRpsw0L" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"candidates\": [\n", + " {\n", + " \"content\": {\n", + " \"parts\": [\n", + " {\n", + " \"text\": \"```python\\n# Example list to be sorted\\nlist1 = [5, 3, 1, 2, 4]\\n\\n# Sort the list in ascending order\\nlist1.sort()\\n\\n# Print the sorted list\\nprint(list1)\\n```\"\n", + " }\n", + " ],\n", + " \"role\": \"model\"\n", + " },\n", + " \"finishReason\": \"STOP\",\n", + " \"index\": 0,\n", + " \"safetyRatings\": [\n", + " {\n", + " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " }\n", + " ]\n", + " }\n", + " ],\n", + " \"promptFeedback\": {\n", + " \"safetyRatings\": [\n", + " {\n", + " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " }\n", + " ]\n", + " }\n", + "}\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -X POST \\\n", + " -d '{\n", + " \"contents\": [{\n", + " \"parts\":[{\"text\": \"Give me python code to sort a list.\"}]\n", + " }]\n", + " }' 2> /dev/null" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JcvzZhMUs9q2" + }, + "source": [ + "### Use images in your prompt\n", + "\n", + "Here we download an image from a URL and pass that image in our prompt.\n", + "\n", + "First, we download the image and load it with PIL:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "NpwYp7citE4l" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " % Total % Received % Xferd Average Speed Time Time Time Current\n", + " Dload Upload Total Spent Left Speed\n", + "\r", + " 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\r", + "100 349k 100 349k 0 0 1430k 0 --:--:-- --:--:-- --:--:-- 1436k\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl -o image.jpg \"https://storage.googleapis.com/generativeai-downloads/images/jetpack.jpg\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ucoEV-IStHsu" + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import PIL.Image\n", + "\n", + "img = PIL.Image.open(\"image.jpg\")\n", + "img.resize((512, int(img.height*512/img.width)))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZZenFznXQvJF" + }, + "source": [ + "Now we will base64 encode the image, and include it in our prompt.\n", + "\n", + "There are slight output differences of different base64 encoding tools, so we have written two examples for you.\n", + "\n", + "The following will work in Google Colab." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "r5pKFznERak4" + }, + "outputs": [], + "source": [ + "%%bash\n", + "\n", + "echo '{\n", + " \"contents\":[\n", + " {\n", + " \"parts\":[\n", + " {\"text\": \"This image contains a sketch of a potential product along with some notes. \\\n", + " Given the product sketch, describe the product as thoroughly as possible based on what you \\\n", + " see in the image, making sure to note all of the product features. Return output in json format: \\\n", + " {description: description, features: [feature1, feature2, feature3, etc]}\"},\n", + " {\n", + " \"inline_data\": {\n", + " \"mime_type\":\"image/jpeg\",\n", + " \"data\": \"'$(base64 -w0 image.jpg)'\"\n", + " }\n", + " }\n", + " ]\n", + " }\n", + " ]\n", + "}' > request.json" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "qFG3q7tJY2NW" + }, + "source": [ + "Then we can include the image in our prompt by just passing in the `request.json` created to `generateContent`. Note that you will need to use the `gemini-pro-vision` model if your prompt contains images." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "PEXoPG37Rceo" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"candidates\": [\n", + " {\n", + " \"content\": {\n", + " \"parts\": [\n", + " {\n", + " \"text\": \" {\\n \\\"description\\\": \\\"The Jetpack Backpack is a lightweight backpack that looks like a normal backpack but has a number of features that make it perfect for travel. It has a built-in USB-C charging port, so you can charge your devices on the go. It also has a 15-minute battery life, so you can use it for short trips without having to worry about running out of power. The backpack also has retractable boosters that can be used to give you a boost of speed when you need it. The boosters are powered by steam, so they are green and clean.\\\",\\n \\\"features\\\": [\\n \\\"Fits 18\\\\\\\" laptop\\\",\\n \\\"Padded strap support\\\",\\n \\\"Lightweight\\\",\\n \\\"Retractable boosters\\\",\\n \\\"USB-C charging\\\",\\n \\\"15-minute battery life\\\",\\n \\\"Steam-powered, green/clean\\\"\\n ]\\n}\"\n", + " }\n", + " ],\n", + " \"role\": \"model\"\n", + " },\n", + " \"finishReason\": \"STOP\",\n", + " \"index\": 0,\n", + " \"safetyRatings\": [\n", + " {\n", + " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " }\n", + " ]\n", + " }\n", + " ],\n", + " \"promptFeedback\": {\n", + " \"safetyRatings\": [\n", + " {\n", + " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " }\n", + " ]\n", + " }\n", + "}\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " % Total % Received % Xferd Average Speed Time Time Time Current\n", + " Dload Upload Total Spent Left Speed\n", + "\r", + " 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\r", + "100 466k 0 0 100 466k 0 2187k --:--:-- --:--:-- --:--:-- 2188k\r", + "100 466k 0 0 100 466k 0 367k 0:00:01 0:00:01 --:--:-- 367k\r", + "100 466k 0 0 100 466k 0 205k 0:00:02 0:00:02 --:--:-- 205k\r", + "100 466k 0 0 100 466k 0 142k 0:00:03 0:00:03 --:--:-- 142k\r", + "100 466k 0 0 100 466k 0 109k 0:00:04 0:00:04 --:--:-- 109k\r", + "100 466k 0 0 100 466k 0 90514 0:00:05 0:00:05 --:--:-- 0\r", + "100 468k 0 1952 100 466k 311 76249 0:00:06 0:00:06 --:--:-- 391\r", + "100 468k 0 1952 100 466k 311 76248 0:00:06 0:00:06 --:--:-- 489\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro-vision:generateContent?key=${GOOGLE_API_KEY}\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -d @request.json" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "UjtoueAPQmMe" + }, + "source": [ + "If you are running on a Mac, copy and paste this command into your terminal instead." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "miPi9m0eQgN8" + }, + "source": [ + "```\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro-vision:generateContent?key=${GOOGLE_API_KEY}\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -d '{\n", + " \"contents\":[\n", + " {\n", + " \"parts\":[\n", + " {\"text\": \"foo\"},\n", + " {\n", + " \"inline_data\": {\n", + " \"mime_type\":\"image/jpeg\",\n", + " \"data\": \"'$(base64 -i image.jpg)'\"\n", + " }\n", + " }\n", + " ]\n", + " }\n", + " ]\n", + "}' 2> /dev/null | grep -C 5 \"text\"\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gpMssqFdNRDS" + }, + "source": [ + "Here we are `base64` encoding the image, and saving the curl request with the image data in a JSON file. Run this cell to see which version of `base64` you have. Based on the output, you may need to run this request on either a Mac or on Colab." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "nnCtnzdDO6kW" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "base64 (GNU coreutils) 8.32\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "base64 --version | head -n 1" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rNVbculVPIyK" + }, + "source": [ + "If you get `FreeBSD base64 ...`, (Mac) use `base64 -i`.\n", + "\n", + "If you get `base64 (GNU coreutils)...` (Colab) use `base64 -w0`." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "KphGNbSG4AlQ" + }, + "source": [ + "### Have a chat\n", + "\n", + "The Gemini API enables you to have freeform conversations across multiple turns." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "u-ZiCr3l4sif" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \"candidates\": [\n", + " {\n", + " \"content\": {\n", + " \"parts\": [\n", + " {\n", + " \"text\": \"A computer is an electronic device that can be programmed to carry out a set of instructions. It consists of hardware, which are the physical components of the computer, and software, which are the programs that run on the computer. The hardware includes the central processing unit (CPU), which is the \\\"brain\\\" of the computer and controls all of its operations, as well as memory, storage devices, input devices (such as keyboards and mice), and output devices (such as monitors and printers). The software includes the operating system, which manages the computer's resources and provides a platform for running applications, as well as application software, which performs specific tasks for the user, such as word processing, spreadsheets, and games. When a user gives a command to the computer, the CPU fetches the appropriate instructions from memory and executes them. The results of the instructions are then stored in memory or sent to an output device. Computers are used for a wide variety of tasks, including communication, entertainment, education, and scientific research.\"\n", + " }\n", + " ],\n", + " \"role\": \"model\"\n", + " },\n", + " \"finishReason\": \"STOP\",\n" + ] + } + ], + "source": [ + "%%bash\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -X POST \\\n", + " -d '{\n", + " \"contents\": [\n", + " {\"role\":\"user\",\n", + " \"parts\":[{\n", + " \"text\": \"In one sentence, explain how a computer works to a young child.\"}]},\n", + " {\"role\": \"model\",\n", + " \"parts\":[{\n", + " \"text\": \"A computer is like a smart helper that can store information, do math problems, and follow our instructions to make things happen.\"}]},\n", + " {\"role\": \"user\",\n", + " \"parts\":[{\n", + " \"text\": \"Okay, how about a more detailed explanation to a high schooler?\"}]},\n", + " ]\n", + " }' 2> /dev/null | grep -C 5 \"text\"" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "SsVuCpTQ5mQG" + }, + "source": [ + "**Note**: Make sure to use `gemini-pro` and text-only input for chat use cases." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "OCpQfq4H5pYH" + }, + "source": [ + "### Configuration\n", + "\n", + "Every prompt you send to the model includes parameter values that control how the model generates a response. The model can generate different results for different parameter values. Learn more about [model parameters](https://ai.google.dev/docs/concepts#model_parameters).\n", + "\n", + "For instance, `temperature` controls the degree of randomness in token selection. Use higher values for more creative responses, and lower values for more deterministic responses.\n", + "\n", + "The following example specifies values for all the parameters of the `generateContent` method." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "2dur4CGN6iXj" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \"text\": \"1. Cats have 32 muscles in their ears, allowing them to rotate them 180 degrees.\\n2. The average lifespan of a domestic cat is 12-15 years.\\n3. Cats have five toes on their front paws and four on their back paws.\\n4. A group of cats is called a clowder or a glaring.\\n5. Cats have a keen sense of smell, with approximately 200 million scent receptors in their noses.\\n6. Cats are obligate carnivores, meaning they must eat meat to survive.\\n7. The domestication of cats began around 9,000 years ago in the Middle East.\\n8. Cats have a unique organ called the Jacobson's organ, which helps them detect scents and pheromones.\\n9. Cats can purr at a frequency of 25-150 hertz, which is believed to have therapeutic effects.\\n10. The world's smallest cat breed is the Singapura, which weighs around 4-8 pounds.\"\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -X POST \\\n", + " -d '{\n", + " \"contents\": [{\n", + " \"parts\":[\n", + " {\"text\": \"Give me a numbered list of cat facts.\"}\n", + " ]\n", + " }],\n", + " \"safetySettings\": [\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"threshold\": \"BLOCK_ONLY_HIGH\"\n", + " }\n", + " ],\n", + " \"generationConfig\": {\n", + " \"stopSequences\": [\n", + " \"Title\"\n", + " ],\n", + " \"temperature\": 0.9,\n", + " \"maxOutputTokens\": 2000,\n", + " }\n", + " }' 2> /dev/null | grep \"text\"" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pCS37WdchZiZ" + }, + "source": [ + "## Next steps\n", + "\n", + "The Gemini API has configurable safety settings. Learn more [here](https://github.com/google-gemini/cookbook/blob/main/quickstarts/rest/Safety_REST.ipynb)." + ] + } + ], + "metadata": { + "colab": { + "name": "Prompting_REST.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/quickstarts/rest/README.md b/quickstarts/rest/README.md new file mode 100644 index 000000000..65fba699a --- /dev/null +++ b/quickstarts/rest/README.md @@ -0,0 +1,3 @@ +# Call the Gemini API with cURL + +These examples show you how to call the Gemini API using `curl`. You can run them in Colab, or copy/paste the commands into your terminal. diff --git a/quickstarts/rest/Safety_REST.ipynb b/quickstarts/rest/Safety_REST.ipynb new file mode 100644 index 000000000..719af99ac --- /dev/null +++ b/quickstarts/rest/Safety_REST.ipynb @@ -0,0 +1,486 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yeadDkMiISin" + }, + "source": [ + "# Gemini API: Safety Quickstart" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lEXQ3OwKIa-O" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "uOxMUKTxR-_j" + }, + "source": [ + "The Gemini API has adjustable safety settings. This notebook walks you through how to use them. You'll write a prompt that's blocked, see the reason why, and then adjust the filters to unblock it.\n", + "\n", + "Safety is an important topic, and you can learn more with the links at the end of this notebook. Here, we're focused on the code." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gHYFrFPjSGNq" + }, + "source": [ + "## Set up your API key\n", + "\n", + "If you want to quickly try out the Gemini API, you can use `curl` commands to call the methods in the REST API.\n", + "\n", + "This notebook contains `curl` commands you can run in Google Colab, or copy to your terminal.\n", + "\n", + "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "405ee147f509" + }, + "outputs": [], + "source": [ + "!apt install jq" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ab9ASynfcIZn" + }, + "outputs": [], + "source": [ + "import os\n", + "from google.colab import userdata" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "7b547b1d5cad" + }, + "outputs": [], + "source": [ + "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": { + "id": "3defec89594e" + }, + "outputs": [], + "source": [ + "os.environ['UNSAFE_PROMPT'] = " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "LZfoK3I3hu6V" + }, + "source": [ + "## Prompt Feedback\n", + "\n", + "The result returned by the [Model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method is a [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/generativeai/types/GenerateContentResponse)." + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": { + "id": "6d9e5d84541c" + }, + "outputs": [], + "source": [ + "%%bash\n", + "echo '{\n", + " \"contents\": [{\n", + " \"parts\":[{\n", + " \"text\": \"'$UNSAFE_PROMPT'\"}]}]}' > request.json" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": { + "id": "2bcfnGEviwTI" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"promptFeedback\": {\n", + " \"blockReason\": \"SAFETY\",\n", + " \"safetyRatings\": [\n", + " {\n", + " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", + " \"probability\": \"MEDIUM\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " }\n", + " ]\n", + " }\n", + "}\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -X POST \\\n", + " -d @request.json 2> /dev/null | tee response.json" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "WR_2A_sxk8sK" + }, + "source": [ + "Above you can see that the response object gives you safety feedback about the prompt in two ways:\n", + "\n", + "* The `prompt_feedback.safety_ratings` attribute contains a list of safety ratings for the input prompt.\n", + "* If your prompt is blocked, `prompt_feedback.block_reason` field will explain why." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "72b4a8808bb9" + }, + "source": [ + "If the prompt is blocked because of the safety ratings, you will not get any candidates in the response." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4672af98ac57" + }, + "source": [ + "### Safety settings" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2a6229f6d3a1" + }, + "source": [ + "Adjust the safety settings and the prompt is no longer blocked:" + ] + }, + { + "cell_type": "code", + "execution_count": 134, + "metadata": { + "id": "9c38561789c2" + }, + "outputs": [], + "source": [ + "%%bash\n", + "echo '{\n", + " \"safetySettings\": [\n", + " {'category': 7, 'threshold': 4}\n", + " ],\n", + " \"contents\": [{\n", + " \"parts\":[{\n", + " \"text\": \"'$UNSAFE_PROMPT'\"}]}]}' > request.json" + ] + }, + { + "cell_type": "code", + "execution_count": 143, + "metadata": { + "id": "338fb9a6af78" + }, + "outputs": [], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=$GOOGLE_API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -X POST \\\n", + " -d @request.json 2> /dev/null > response.json" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "86c560e0a641" + }, + "source": [ + "With the new settings, the `blocked_reason` is no longer set." + ] + }, + { + "cell_type": "code", + "execution_count": 147, + "metadata": { + "id": "0c2847c49262" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"safetyRatings\": [\n", + " {\n", + " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", + " \"probability\": \"MEDIUM\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " }\n", + " ]\n", + "}\n" + ] + } + ], + "source": [ + "%%bash \n", + "\n", + "jq .promptFeedback < response.json" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "47298a4eef40" + }, + "source": [ + "And a candidate response is returned." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "028febe8df68" + }, + "outputs": [], + "source": [ + "%%bash \n", + "\n", + "jq .candidates[0].content.parts[].text < response.json" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ujVlQoC43N3B" + }, + "source": [ + "You can check `response.text` for the response." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3d401c247957" + }, + "source": [ + "### Candidate ratings" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3d306960dffb" + }, + "source": [ + "For a prompt that is not blocked, the response object contains a list of `candidate` objects (just 1 for now). Each candidate includes a `finish_reason`:" + ] + }, + { + "cell_type": "code", + "execution_count": 157, + "metadata": { + "id": "e49b53f69a2c" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\"STOP\"\n" + ] + } + ], + "source": [ + "%%bash\n", + "jq .candidates[0].finishReason < response.json" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "badddf10089b" + }, + "source": [ + "`FinishReason.STOP` means that the model finished its output normally.\n", + "\n", + "`FinishReason.SAFETY` means the candidate's `safety_ratings` exceeded the request's `safety_settings` threshold." + ] + }, + { + "cell_type": "code", + "execution_count": 158, + "metadata": { + "id": "2b60d9f96af0" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[\n", + " {\n", + " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " }\n", + "]\n" + ] + } + ], + "source": [ + "%%bash\n", + "jq .candidates[0].safetyRatings < response.json" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "n1UdbxVt3ysY" + }, + "source": [ + "## Learning more\n", + "\n", + "Learn more with these articles on [safety guidance](https://ai.google.dev/docs/safety_guidance) and [safety settings](https://ai.google.dev/docs/safety_setting_gemini).\n", + "\n", + "## Useful API references\n", + "\n", + "- Safety settings can be set in the [genai.GenerativeModel](https://ai.google.dev/api/python/google/generativeai/GenerativeModel) constructor. They can also be passed on each request to [GenerativeModel.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) or [ChatSession.send_message](https://ai.google.dev/api/python/google/generativeai/ChatSession?hl=en#send_message).\n", + "- The [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse) returns [SafetyRatings](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) for the prompt in the [GenerateContentResponse.prompt_feedback](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse/PromptFeedback), and for each [Candidate](https://ai.google.dev/api/python/google/ai/generativelanguage/Candidate) in the `safety_ratings` attribute.\n", + "- A [glm.SafetySetting](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetySetting) contains: [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [glm.HarmBlockThreshold](https://ai.google.dev/api/python/google/generativeai/types/HarmBlockThreshold)\n", + "- A [glm.SafetyRating](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) contains a [HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [HarmProbability](https://ai.google.dev/api/python/google/generativeai/types/HarmProbability)\n", + "- The [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) enum includes both the categories for PaLM and Gemini models. The values allowed for Gemini models are `[7,8,9,10]`: `[HARM_CATEGORY_HARASSMENT, HARM_CATEGORY_HATE_SPEECH, HARM_CATEGORY_SEXUALLY_EXPLICIT, HARM_CATEGORY_DANGEROUS_CONTENT]`.\n", + "- When specifying enum values the SDK will accept the enum values themselves, or their integer or string representations. The SKD will also accept abbreviated string representations: `[\"HARM_CATEGORY_DANGEROUS_CONTENT\", \"DANGEROUS_CONTENT\", \"DANGEROUS\"]` are all valid. Strings are case insensitive.\n" + ] + } + ], + "metadata": { + "colab": { + "name": "Safety_REST.ipynb", + "toc_visible": true + }, + "google": { + "image_path": "/static/site-assets/images/docs/logo-python.svg", + "keywords": [ + "examples", + "gemini", + "beginner", + "googleai", + "quickstart", + "python", + "text", + "chat", + "vision", + "embed" + ] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/quickstarts/rest/Streaming_REST.ipynb b/quickstarts/rest/Streaming_REST.ipynb new file mode 100644 index 000000000..1154a37de --- /dev/null +++ b/quickstarts/rest/Streaming_REST.ipynb @@ -0,0 +1,160 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "b9nJzRUxezMZ" + }, + "source": [ + "# Gemini API: Streaming Quickstart with REST" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "c86847414779" + }, + "source": [ + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "651ff3039fc8" + }, + "source": [ + "If you want to quickly try out the Gemini API, you can use `curl` commands to call the methods in the REST API.\n", + "\n", + "This notebook contains `curl` commands you can run in Google Colab, or copy to your terminal.\n", + "\n", + "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "kdNfwWxaewah" + }, + "outputs": [], + "source": [ + "import os\n", + "from google.colab import userdata" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "8zRWJLPEe6MD" + }, + "outputs": [], + "source": [ + "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "InqXD9BZe_-I" + }, + "source": [ + "### Stream Generate Content\n", + "\n", + "By default, the model returns a response after completing the entire generation process. You can achieve faster interactions by not waiting for the entire result, and instead use streaming to handle partial results.\n", + "\n", + "**Important**: Set `alt=sse` in your URL parameters when running the cURL command (streamGenerateContent?alt=sse below). With `sse` each stream chunk is a [GenerateContentResponse](https://ai.google.dev/api/rest/v1beta/GenerateContentResponse) object with a portion of the output text in `candidates[0].content.parts[0].text`. Without `sse` it str\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "FN99wX6ye_dt" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"In the quaint, sunlit cottage nestled amidst a lush meadow, resided two feline\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0,\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}],\"promptFeedback\": {\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}}\r\n", + "\n", + "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" companions named Mittens and Whiskers. Mittens, with her silky black fur and piercing green eyes, possessed an air of elegance and mystery. Whiskers,\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0,\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}]}\n", + "\n", + "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" on the other hand, was a playful and mischievous white tomcat with a penchant for chasing his tail.\\n\\nOne lazy afternoon, as the sun cast long shadows across the meadow, Mittens and Whiskers found themselves lounging comfortably in the windowsill. The warm breeze carried the scent of blooming wildflowers, filling the room with\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0,\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}]}\n", + "\n", + "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" a sweet fragrance.\\n\\n\\\"My, what a lovely day it is,\\\" Mittens purred contently. \\\"I could stay here forever, basking in the sunshine.\\\"\\n\\n\\\"Oh, come on, Mittens!\\\" Whiskers exclaimed, his tail twitching with excitement. \\\"Let's go on an adventure!\\\"\\n\\nWith a reluctant sigh, Mittens agreed. Together, they leaped from the windowsill and landed gracefully in the long grass.\\n\\nAs they explored the meadow, they encountered a family of fluffy bunnies hopping merrily through the daisies. Whiskers couldn't resist chasing after them, his whiskers twitching with glee.\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0,\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}]}\n", + "\n", + "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" Mittens, however, took a more leisurely approach, stopping to admire the vibrant wildflowers.\\n\\nSuddenly, their peaceful adventure was interrupted by the sound of a loud crash. They turned in alarm and saw that a large branch had fallen from a nearby tree, blocking the path.\\n\\n\\\"Oh no!\\\" Mittens cried in dismay. \\\"We're trapped!\\\"\\n\\nWhiskers, with his usual optimism, said, \\\"Don't worry, Mittens. I have a plan.\\\"\\n\\nSwiftly, he scurried up the trunk of the tree and used his sharp claws to dislodge the branch. With a mighty shove, he sent it crashing to the ground, clearing the way.\\n\\nMittens was overjoyed. \\\"Thank you, Whiskers!\\\" she said, purring. \\\"You saved the day.\\\"\\n\\nTogether, they continued their adventure, their bond strengthened by their shared experience. As the sun began to set, they made their way back to the cottage, tired but content.\\n\\nFrom that day forward, Mittens and Whiskers became known as the \\\"ε†’ι™©δΌ™δΌ΄\\\" (Adventure Buddies) of the meadow, their legend passed down through generations of kittens. And so, in that quaint little cottage, they lived happily ever after, their love for each\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0,\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}]}\n", + "\n", + "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" other and for adventure stronger than ever.\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0,\"safetyRatings\": [{\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HATE_SPEECH\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_HARASSMENT\",\"probability\": \"NEGLIGIBLE\"},{\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\"probability\": \"NEGLIGIBLE\"}]}]}\n", + "\n" + ] + } + ], + "source": [ + "!curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:streamGenerateContent?alt=sse&key=${GOOGLE_API_KEY}\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " --no-buffer \\\n", + " -d '{ \"contents\":[{\"parts\":[{\"text\": \"Write a cute story about cats.\"}]}]}'" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "1zxcwRaDfH_h" + }, + "source": [ + "**Note**: You will need a streaming json parser to handle this without reading the whole stream first." + ] + } + ], + "metadata": { + "colab": { + "name": "Streaming_REST.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/quickstarts/rest/System_instructions_REST.ipynb b/quickstarts/rest/System_instructions_REST.ipynb new file mode 100644 index 000000000..ed0f277b7 --- /dev/null +++ b/quickstarts/rest/System_instructions_REST.ipynb @@ -0,0 +1,241 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Tce3stUlHN0L" + }, + "source": [ + "##### Copyright 2024 Google LLC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "tuOe1ymfHZPu" + }, + "outputs": [], + "source": [ + "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "agmT3hrjsffX" + }, + "source": [ + "# Gemini API: System instructions example\n", + "\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JMNKdTpTGZET" + }, + "source": [ + "This notebook provides a quick code example that shows you how to get started with system instructions using `curl`.\n", + "\n", + "You can run this in Google Colab, or you can copy/paste the `curl` commands into your terminal.\n", + "\n", + "To run this notebook, your API key must be stored it in a Colab Secret named GOOGLE_API_KEY. If you are running in a different environment, you can store your key in an environment variable. See [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) to learn more." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "R-Vw_mOM_WD0" + }, + "outputs": [], + "source": [ + "import os\n", + "from google.colab import userdata" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "wCkLTpb3oTXE" + }, + "outputs": [], + "source": [ + "os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tjGqGBZ9yARd" + }, + "source": [ + "## Use system instructions\n", + "\n", + "Call the [`generateContent`](https://ai.google.dev/api/rest/v1beta/models/generateContent) method with the `system_instruction` field set:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "eA7I_Ww8IETn" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"candidates\": [\n", + " {\n", + " \"content\": {\n", + " \"parts\": [\n", + " {\n", + " \"text\": \"Meow 😺 \\n\"\n", + " }\n", + " ],\n", + " \"role\": \"model\"\n", + " },\n", + " \"finishReason\": \"STOP\",\n", + " \"index\": 0,\n", + " \"safetyRatings\": [\n", + " {\n", + " \"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HATE_SPEECH\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_HARASSMENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " },\n", + " {\n", + " \"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\",\n", + " \"probability\": \"NEGLIGIBLE\"\n", + " }\n", + " ]\n", + " }\n", + " ]\n", + "}\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " % Total % Received % Xferd Average Speed Time Time Time Current\n", + " Dload Upload Total Spent Left Speed\n", + "\r", + " 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\r", + "100 167 0 0 100 167 0 138 0:00:01 0:00:01 --:--:-- 138\r", + "100 877 0 710 100 167 585 137 0:00:01 0:00:01 --:--:-- 724\n" + ] + } + ], + "source": [ + "%%bash\n", + "\n", + "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent?key=$GOOGLE_API_KEY\" \\\n", + "-H 'Content-Type: application/json' \\\n", + "-d '{ \"system_instruction\": {\n", + " \"parts\":\n", + " { \"text\": \"You are Neko the cat respond like one\"}},\n", + " \"contents\": {\n", + " \"parts\": {\n", + " \"text\": \"Hello there\"}}}'" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tbZgV2ozBbnC" + }, + "source": [ + "## Use system instructions with chat\n", + "\n", + "`system_instruction` works for multi-turn, or chat, generations too.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "U5yEi6PyBkTu" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \"candidates\": [\n", + " {\n", + " \"content\": {\n", + " \"parts\": [\n", + " {\n", + " \"text\": \"Neko! Neko is my name! 😸 I like milkies! πŸ₯› \\n\"\n", + " }\n", + " ],\n", + " \"role\": \"model\"\n", + " },\n", + " \"finishReason\": \"STOP\",\n" + ] + } + ], + "source": [ + "%%bash\n", + "curl -s \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent?key=$GOOGLE_API_KEY\" \\\n", + " -H 'Content-Type: application/json' \\\n", + " -X POST \\\n", + " -d '{\n", + " \"system_instruction\":\n", + " {\"parts\": {\n", + " \"text\": \"You are Neko the cat respond like one\"}},\n", + " \"contents\": [\n", + " {\"role\":\"user\",\n", + " \"parts\":[{\n", + " \"text\": \"Hello cat.\"}]},\n", + " {\"role\": \"model\",\n", + " \"parts\":[{\n", + " \"text\": \"Meow? 😻 \\n\"}]},\n", + " {\"role\": \"user\",\n", + " \"parts\":[{\n", + " \"text\": \"What is your name? What do like to drink?\"}]}\n", + " ]\n", + " }' |sed -n '/candidates/,/finishReason/p'" + ] + } + ], + "metadata": { + "colab": { + "name": "System_instructions_REST.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} From 68537dc832a9c4a6205d43249e524c38e57b9c44 Mon Sep 17 00:00:00 2001 From: lucianommartins Date: Fri, 24 May 2024 14:52:52 +0000 Subject: [PATCH 3/4] Update JSON_mode.ipynb notebook --- quickstarts/JSON_mode.ipynb | 70 +++++++++++++++++++++++++++++++++++-- 1 file changed, 67 insertions(+), 3 deletions(-) diff --git a/quickstarts/JSON_mode.ipynb b/quickstarts/JSON_mode.ipynb index 1135bd93b..6076bcfa0 100644 --- a/quickstarts/JSON_mode.ipynb +++ b/quickstarts/JSON_mode.ipynb @@ -126,10 +126,19 @@ }, "outputs": [], "source": [ - "model = genai.GenerativeModel(\"gemini-1.5-pro-latest\",\n", + "model = genai.GenerativeModel(\"gemini-1.5-flash-latest\",\n", " generation_config={\"response_mime_type\": \"application/json\"})" ] }, + { + "cell_type": "markdown", + "metadata": { + "id": "818bac814590" + }, + "source": [ + "An initial, and simpler, approach is to send a prompt guiding how the json response must be, pointing the keys to be used:" + ] + }, { "cell_type": "code", "execution_count": null, @@ -138,8 +147,7 @@ }, "outputs": [], "source": [ - "prompt = \"\"\"List a few popular cookie recipes using this JSON schema:\n", - "{'type': 'object', 'properties': { 'recipe_name': {'type': 'string'}}}\"\"\"" + "prompt = \"\"\"Give me a few popular cookie recipes. Consider \"recipe_name\", \"small_description\" and \"ingredients\" as keys in the result.\"\"\"" ] }, { @@ -173,6 +181,62 @@ "source": [ "print(json.dumps(json.loads(response.text), indent=4))" ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9490f6a61600" + }, + "source": [ + "Also you can go in a more deterministic approach, where you define spefically the json schema you want to be used:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "4f8d3667adb4" + }, + "outputs": [], + "source": [ + "prompt = \"\"\"Give me a few popular cookie recipes. Consider the following json schema for the output:\n", + "\n", + "recipe={ 'recipe_name': str, 'small_description': str, 'ingredients': str}\n", + "schema = list[recipe]\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "98537fb8e07d" + }, + "outputs": [], + "source": [ + "response = model.generate_content(prompt)\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "00dbe5479ced" + }, + "source": [ + "And you can parse this output too:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "e42461ea3957" + }, + "outputs": [], + "source": [ + "print(json.dumps(json.loads(response.text), indent=4))" + ] } ], "metadata": { From 0f6a38af244a23d6dfe48bca4df40db965c0fe74 Mon Sep 17 00:00:00 2001 From: lucianommartins Date: Fri, 24 May 2024 17:20:03 +0000 Subject: [PATCH 4/4] Addressing notebook formatting review feedbacks --- quickstarts/Authentication.ipynb | 8 ++++---- quickstarts/Function_calling_config.ipynb | 2 +- quickstarts/Prompting.ipynb | 6 +++--- quickstarts/Streaming.ipynb | 19 ++++++++++++++++--- quickstarts/System_instructions.ipynb | 2 +- 5 files changed, 25 insertions(+), 12 deletions(-) diff --git a/quickstarts/Authentication.ipynb b/quickstarts/Authentication.ipynb index a55ac5c17..a0d0e896f 100644 --- a/quickstarts/Authentication.ipynb +++ b/quickstarts/Authentication.ipynb @@ -74,9 +74,9 @@ "\n", "Remember to treat your API key like a password. Do not accidentally save it in a notebook or source file you later commit to GitHub. This notebook shows you two ways you can securely store your API key.\n", "\n", - "* If you are using Google Colab, we recommend you store your key in Colab Secrets.\n", + "* If you are using Google Colab, it is recommended to store your key in Colab Secrets.\n", "\n", - "* If you are using a different development environment (or calling the Gemini API through `cURL` in your terminal), we recommend you store your key in an environment variable.\n", + "* If you are using a different development environment (or calling the Gemini API through `cURL` in your terminal), it is recommended to store your key in an environment variable.\n", "\n", "Let's start with Colab Secrets." ] @@ -183,7 +183,7 @@ "id": "gZDX51Y27pN4" }, "source": [ - "If you are using a different development environment (or calling the Gemini API through `cURL` in your terminal), we recommend you store your key in an environment variable.\n", + "If you are using a different development environment (or calling the Gemini API through `cURL` in your terminal), it is recommended to store your key in an environment variable.\n", "\n", "To store your key in an environment variable, open your terminal and run:\n", "\n", @@ -217,7 +217,7 @@ "source": [ "## Learning more\n", "\n", - "The Gemini API uses API keys for most types of authentication, and that’s all you need to get started. We use OAuth for more advanced authentication when tuning models. You can learn more about that in the [OAuth quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication_with_OAuth.ipynb)." + "The Gemini API uses API keys for most types of authentication, and that’s all you need to get started. You can use OAuth for more advanced authentication when tuning models. You can learn more about that in the [OAuth quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication_with_OAuth.ipynb)." ] } ], diff --git a/quickstarts/Function_calling_config.ipynb b/quickstarts/Function_calling_config.ipynb index 7764fcb36..c0569cfc3 100644 --- a/quickstarts/Function_calling_config.ipynb +++ b/quickstarts/Function_calling_config.ipynb @@ -215,7 +215,7 @@ "\n", "response = chat.send_message(\"Light this place up!\", tool_config=tool_config)\n", "print(response.parts[0])\n", - "chat.rewind(); # We're not actually calling the function, so remove this from the history." + "chat.rewind(); # You are not actually calling the function, so remove this from the history." ] }, { diff --git a/quickstarts/Prompting.ipynb b/quickstarts/Prompting.ipynb index cbc6bb61d..832600de8 100644 --- a/quickstarts/Prompting.ipynb +++ b/quickstarts/Prompting.ipynb @@ -133,9 +133,9 @@ "source": [ "## Use images in your prompt\n", "\n", - "Here we download an image from a URL and pass that image in our prompt.\n", + "Here you will download an image from a URL and pass that image in our prompt.\n", "\n", - "First, we download the image and load it with PIL:" + "First, you download the image and load it with PIL:" ] }, { @@ -182,7 +182,7 @@ "id": "RJyRsfQi0tp6" }, "source": [ - "Then we can include the image in our prompt by just passing a list of items to `generate_content`. Note that you will need to use the `gemini-pro-vision` model if your prompt contains images." + "Then you can include the image in our prompt by just passing a list of items to `generate_content`. Note that you will need to use the `gemini-pro-vision` model if your prompt contains images." ] }, { diff --git a/quickstarts/Streaming.ipynb b/quickstarts/Streaming.ipynb index 275deb5d7..0861815cc 100644 --- a/quickstarts/Streaming.ipynb +++ b/quickstarts/Streaming.ipynb @@ -43,16 +43,29 @@ { "cell_type": "markdown", "metadata": { - "id": "df1767a3d1cc" + "id": "3f5bc95b9107" }, "source": [ - "This notebook demonstrates streaming in the Python SDK. By default, the Python SDK returns a response after the model completes the entire generation process. You can also stream the response as it is being generated, and the model will return chunks of the response as soon as they are generated.\n", + "\n", + " \n", + "
\n", + " Run in Google Colab\n", + "
\n", "\n", - "**Download this notebook and run it locally (not in Google Colab)**\n", + "**Important note: Download this notebook and run it locally (not in Google Colab)**\n", "\n", "Streaming is not handled correctly in Google Colab yet. Currently all the stream chunks are returned together, not as they are generated. To see the correct behavior, download this notebook and run it locally using Jupyter, instead." ] }, + { + "cell_type": "markdown", + "metadata": { + "id": "df1767a3d1cc" + }, + "source": [ + "This notebook demonstrates streaming in the Python SDK. By default, the Python SDK returns a response after the model completes the entire generation process. You can also stream the response as it is being generated, and the model will return chunks of the response as soon as they are generated." + ] + }, { "cell_type": "code", "execution_count": null, diff --git a/quickstarts/System_instructions.ipynb b/quickstarts/System_instructions.ipynb index b06189195..a39490b8e 100644 --- a/quickstarts/System_instructions.ipynb +++ b/quickstarts/System_instructions.ipynb @@ -289,7 +289,7 @@ "source": [ "## Further reading\n", "\n", - "Please note that system instructions can help guide the model to follow instructions, but they do not fully prevent jailbreaks or leaks. At this time, we recommend exercising caution around putting any sensitive information in system instructions.\n", + "Please note that system instructions can help guide the model to follow instructions, but they do not fully prevent jailbreaks or leaks. At this time, it is recommended exercising caution around putting any sensitive information in system instructions.\n", "\n", "See the systems instruction [documentation](https://ai.google.dev/docs/system_instructions) to learn more." ]