Gemini_LLM_PALM.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/AryanGupta20605/-Image-Colorization-with-Deep-Convolutional-Neural-Network/blob/main/Gemini_LLM_PALM.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "installing langchain,google generative ai,pinecone-libraries"
      ],
      "metadata": {
        "id": "yi9Hlnsi37JA"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "af8Cl6ys36EU",
        "outputId": "2009c687-af2c-428e-c433-cb517b3f92cc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: langchain in /usr/local/lib/python3.10/dist-packages (0.1.8)\n",
            "Requirement already satisfied: PyYAML>=5.3 in /usr/local/lib/python3.10/dist-packages (from langchain) (6.0.1)\n",
            "Requirement already satisfied: SQLAlchemy<3,>=1.4 in /usr/local/lib/python3.10/dist-packages (from langchain) (2.0.27)\n",
            "Requirement already satisfied: aiohttp<4.0.0,>=3.8.3 in /usr/local/lib/python3.10/dist-packages (from langchain) (3.9.3)\n",
            "Requirement already satisfied: async-timeout<5.0.0,>=4.0.0 in /usr/local/lib/python3.10/dist-packages (from langchain) (4.0.3)\n",
            "Requirement already satisfied: dataclasses-json<0.7,>=0.5.7 in /usr/local/lib/python3.10/dist-packages (from langchain) (0.6.4)\n",
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            "Requirement already satisfied: tenacity<9.0.0,>=8.1.0 in /usr/local/lib/python3.10/dist-packages (from langchain) (8.2.3)\n",
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            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (23.2.0)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (1.4.1)\n",
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            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (1.9.4)\n",
            "Requirement already satisfied: marshmallow<4.0.0,>=3.18.0 in /usr/local/lib/python3.10/dist-packages (from dataclasses-json<0.7,>=0.5.7->langchain) (3.20.2)\n",
            "Requirement already satisfied: typing-inspect<1,>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from dataclasses-json<0.7,>=0.5.7->langchain) (0.9.0)\n",
            "Requirement already satisfied: jsonpointer>=1.9 in /usr/local/lib/python3.10/dist-packages (from jsonpatch<2.0,>=1.33->langchain) (2.4)\n",
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            "Requirement already satisfied: annotated-types>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1->langchain) (0.6.0)\n",
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            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain) (3.6)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain) (2024.2.2)\n",
            "Requirement already satisfied: greenlet!=0.4.17 in /usr/local/lib/python3.10/dist-packages (from SQLAlchemy<3,>=1.4->langchain) (3.0.3)\n",
            "Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3->langchain-core<0.2,>=0.1.24->langchain) (1.3.0)\n",
            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3->langchain-core<0.2,>=0.1.24->langchain) (1.2.0)\n",
            "Requirement already satisfied: mypy-extensions>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from typing-inspect<1,>=0.4.0->dataclasses-json<0.7,>=0.5.7->langchain) (1.0.0)\n"
          ]
        }
      ],
      "source": [
        "!pip install langchain"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install pinecone-client==2.2.4\n",
        "!pip install pypdf\n",
        "!pip install -q google-generativeai"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4n24qnoc4gpa",
        "outputId": "a1b3e4d3-ee7c-4ea8-c4df-9bbf25e2b7b7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: pinecone-client==2.2.4 in /usr/local/lib/python3.10/dist-packages (2.2.4)\n",
            "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages (from pinecone-client==2.2.4) (2.31.0)\n",
            "Requirement already satisfied: pyyaml>=5.4 in /usr/local/lib/python3.10/dist-packages (from pinecone-client==2.2.4) (6.0.1)\n",
            "Requirement already satisfied: loguru>=0.5.0 in /usr/local/lib/python3.10/dist-packages (from pinecone-client==2.2.4) (0.7.2)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4 in /usr/local/lib/python3.10/dist-packages (from pinecone-client==2.2.4) (4.9.0)\n",
            "Requirement already satisfied: dnspython>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from pinecone-client==2.2.4) (2.6.1)\n",
            "Requirement already satisfied: python-dateutil>=2.5.3 in /usr/local/lib/python3.10/dist-packages (from pinecone-client==2.2.4) (2.8.2)\n",
            "Requirement already satisfied: urllib3>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from pinecone-client==2.2.4) (2.0.7)\n",
            "Requirement already satisfied: tqdm>=4.64.1 in /usr/local/lib/python3.10/dist-packages (from pinecone-client==2.2.4) (4.66.2)\n",
            "Requirement already satisfied: numpy>=1.22.0 in /usr/local/lib/python3.10/dist-packages (from pinecone-client==2.2.4) (1.25.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.5.3->pinecone-client==2.2.4) (1.16.0)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->pinecone-client==2.2.4) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->pinecone-client==2.2.4) (3.6)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->pinecone-client==2.2.4) (2024.2.2)\n",
            "Requirement already satisfied: pypdf in /usr/local/lib/python3.10/dist-packages (4.0.2)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain.llms import GooglePalm\n",
        "from langchain. vectorstores import Pinecone\n",
        "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
        "from langchain.document_loaders import PyPDFDirectoryLoader\n",
        "from langchain.embeddings import GooglePalmEmbeddings\n",
        "from langchain.chains import RetrievalQA\n",
        "from langchain.prompts import PromptTemplate\n",
        "import pinecone\n",
        "import os\n",
        "import sys"
      ],
      "metadata": {
        "id": "mqtmLvAM4y1b"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!mkdir pdfs"
      ],
      "metadata": {
        "id": "kc-JxVj-6LPA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9e33058e-02a8-4a2d-cef0-2d48dd091303"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "mkdir: cannot create directory ‘pdfs’: File exists\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "loader=PyPDFDirectoryLoader(\"pdfs\")\n",
        "data=loader.load()"
      ],
      "metadata": {
        "id": "EPUSWp2d6bKY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MJlbH6Bv6vrD",
        "outputId": "b5a98eee-157f-41a5-af6c-6223345667f6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[Document(page_content=' \\n1 | S C A N N E R  C L A S S  &  C O M M A N D  L I N E  A R G U M E N T  \\n Scanner class:- In generally we used Scanner class to read \\ncharacter data they coming from the command prompt, Scanner class \\npresent in java.util package. \\nThis class introduce in java 1.5 version. \\nTo get Scanner class object:- \\nScanner sc=new Scanner(System.in) \\nMost important method of Scanner class:- \\npublic XXX nextXXX() method \\nwhere XXX value may be Int, Byte, Short, Boolean, Float, Line... \\n1. public int nextInt() \\n2. public boolean nextBoolen() \\n3. public String next() \\n4. public String nextLine() \\nExample:-1 \\nimport java.util.*; \\npublic class ScannerDemo \\n{ \\npublic static void main(String[]args)throws Exception \\n{ \\nScanner sc=new Scanner(System.in); \\nSystem.out.println(\"Enter Name of Student\"); \\nString sname=sc.next(); \\nSystem.out.println(\"Enter Id of Student\"); \\nint sid=sc.nextInt(); \\nSystem.out.println(\"Enter Address of Student\"); \\nString saddr=sc.next(); \\nSystem.out.println(\"Student Name:\"+sname); \\nSystem.out.println(\"Student Id:\"+sid); \\nSystem.out.println(\"Student Address:\"+saddr); \\n} \\n} \\n \\nCommand Line Argument:- line arguments:  \\nThe arguments which are passing from command prompt are called \\ncommand line arguments. \\n \\nThe main objective of command line arguments is customize the \\nbehaviour of the main() method. \\n ', metadata={'source': 'pdfs/4.Scanner class & Comman Line Argument.pdf', 'page': 0}), Document(page_content=' \\n2 | S C A N N E R  C L A S S  &  C O M M A N D  L I N E  A R G U M E N T  \\n Example:- \\nclass Test \\n{ \\npublic static void main(String[] args) \\n{ \\nfor(int i=0;i<=args.length;i++) \\n{ \\nSystem.out.println(args[i]); \\n} \\n} \\n} \\njava Test A B C \\nOutput:- ArrayIndexOutOfBoundsException: 3 \\n \\nNote:-Replace i<=args.length with i<args.length then it will run \\nsuccessfully. \\n \\nWithin the main() method command line arguments are available in the \\nform of String hence  \"+\" operator acts as string concatenation but \\nnot perform arithmetic addition. \\nExample:- \\nclass Test \\n{ \\npublic static void main(String[] args) \\n{ \\nSystem.out.println(args[0]+args[1]); \\n} \\n} \\nOutput:- \\njavac Test.java \\njava Test 100 200 \\nOutput:-100200 \\n \\nSpace is the separator between 2 command line arguments and if our \\ncommand line argument itself contains space then we should enclose \\nwith in double quotes. \\n \\nExample:- \\nclass Test \\n{ \\npublic static void main(String[] args) \\n{ \\nSystem.out.println(args[0]); \\n} \\n} \\nOutput: \\njavac Test.java \\njava Test \"GLA UNIVERSITY\" \\nOutput:-GLA UNIVERSITY ', metadata={'source': 'pdfs/4.Scanner class & Comman Line Argument.pdf', 'page': 1})]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "text_splitter = RecursiveCharacterTextSplitter(\n",
        "    chunk_size = 1000,\n",
        "    chunk_overlap = 200\n",
        ")"
      ],
      "metadata": {
        "id": "rILHKUbO7tI2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "text_chunks = text_splitter.split_documents(data)\n",
        "len(text_chunks)\n",
        "print(text_chunks[2])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qd5BreSq8xOL",
        "outputId": "3cda9ac5-c6a1-4cf8-ba81-caff2fbc19a4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "page_content='2 | S C A N N E R  C L A S S  &  C O M M A N D  L I N E  A R G U M E N T  \\n Example:- \\nclass Test \\n{ \\npublic static void main(String[] args) \\n{ \\nfor(int i=0;i<=args.length;i++) \\n{ \\nSystem.out.println(args[i]); \\n} \\n} \\n} \\njava Test A B C \\nOutput:- ArrayIndexOutOfBoundsException: 3 \\n \\nNote:-Replace i<=args.length with i<args.length then it will run \\nsuccessfully. \\n \\nWithin the main() method command line arguments are available in the \\nform of String hence  \"+\" operator acts as string concatenation but \\nnot perform arithmetic addition. \\nExample:- \\nclass Test \\n{ \\npublic static void main(String[] args) \\n{ \\nSystem.out.println(args[0]+args[1]); \\n} \\n} \\nOutput:- \\njavac Test.java \\njava Test 100 200 \\nOutput:-100200 \\n \\nSpace is the separator between 2 command line arguments and if our \\ncommand line argument itself contains space then we should enclose \\nwith in double quotes. \\n \\nExample:- \\nclass Test \\n{ \\npublic static void main(String[] args) \\n{ \\nSystem.out.println(args[0]); \\n} \\n} \\nOutput:' metadata={'source': 'pdfs/4.Scanner class & Comman Line Argument.pdf', 'page': 1}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(text_chunks)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "phnkitDy8ynD",
        "outputId": "38ac0608-7c70-4b3b-a32d-47727e3a1e82"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "GEMINI API,PINECONE API,LANGCHAIN GOOGLEPALM"
      ],
      "metadata": {
        "id": "tMOwFQEP9JB0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "os.environ[\"GOOGLE_API_KEY\"]=\"AIzaSyCYNZ8WPIeP6c2F2NJResGaT48vbv5jt0Y\""
      ],
      "metadata": {
        "id": "78WTP50I80jg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "embedding=GooglePalmEmbeddings()"
      ],
      "metadata": {
        "id": "S4t7k8Og9rMv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "query_result=embedding.embed_query(\"Hello World\")\n",
        "print(len(query_result))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "id": "thNcicoV-Bp2",
        "outputId": "c49c1a26-b1e9-419c-f5bc-2cb0d32f22bb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "768\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "PINECONE_API_KEY=os.environ.get('PINECONE_API_KEY','efc1940d-5aaa-4d34-87cf-b8ba0d726f7a')\n",
        "PINECONE_API_ENV=os.environ.get('PINECONE_API_KEY','gcp-starter')"
      ],
      "metadata": {
        "id": "9M7s1_Rj-dcb"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pinecone.init(\n",
        "    api_key=PINECONE_API_KEY,\n",
        "    environment=PINECONE_API_ENV\n",
        ")\n",
        "index_name=\"langchainbot\""
      ],
      "metadata": {
        "id": "oNnfa-tiqSk4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "docsearch = Pinecone.from_texts([t.page_content for t in text_chunks],embedding=embedding,index_name=index_name)"
      ],
      "metadata": {
        "id": "s7ERSSZxqsTL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "query = \"What is budget?\""
      ],
      "metadata": {
        "id": "W158HR9gr__C"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "docs = docsearch.similarity_search(query,k=4)"
      ],
      "metadata": {
        "id": "vVSuCGE3s-ea"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "docs"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a3QVnDkLtBRH",
        "outputId": "9ce255a1-bc01-4f9c-f279-285b3e71c709"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Document(page_content='String sname=sc.next(); \\nSystem.out.println(\"Enter Id of Student\"); \\nint sid=sc.nextInt(); \\nSystem.out.println(\"Enter Address of Student\"); \\nString saddr=sc.next(); \\nSystem.out.println(\"Student Name:\"+sname); \\nSystem.out.println(\"Student Id:\"+sid); \\nSystem.out.println(\"Student Address:\"+saddr); \\n} \\n} \\n \\nCommand Line Argument:- line arguments:  \\nThe arguments which are passing from command prompt are called \\ncommand line arguments. \\n \\nThe main objective of command line arguments is customize the \\nbehaviour of the main() method.'),\n",
              " Document(page_content='1 | S C A N N E R  C L A S S  &  C O M M A N D  L I N E  A R G U M E N T  \\n Scanner class:- In generally we used Scanner class to read \\ncharacter data they coming from the command prompt, Scanner class \\npresent in java.util package. \\nThis class introduce in java 1.5 version. \\nTo get Scanner class object:- \\nScanner sc=new Scanner(System.in) \\nMost important method of Scanner class:- \\npublic XXX nextXXX() method \\nwhere XXX value may be Int, Byte, Short, Boolean, Float, Line... \\n1. public int nextInt() \\n2. public boolean nextBoolen() \\n3. public String next() \\n4. public String nextLine() \\nExample:-1 \\nimport java.util.*; \\npublic class ScannerDemo \\n{ \\npublic static void main(String[]args)throws Exception \\n{ \\nScanner sc=new Scanner(System.in); \\nSystem.out.println(\"Enter Name of Student\"); \\nString sname=sc.next(); \\nSystem.out.println(\"Enter Id of Student\"); \\nint sid=sc.nextInt(); \\nSystem.out.println(\"Enter Address of Student\"); \\nString saddr=sc.next();'),\n",
              " Document(page_content='2 | S C A N N E R  C L A S S  &  C O M M A N D  L I N E  A R G U M E N T  \\n Example:- \\nclass Test \\n{ \\npublic static void main(String[] args) \\n{ \\nfor(int i=0;i<=args.length;i++) \\n{ \\nSystem.out.println(args[i]); \\n} \\n} \\n} \\njava Test A B C \\nOutput:- ArrayIndexOutOfBoundsException: 3 \\n \\nNote:-Replace i<=args.length with i<args.length then it will run \\nsuccessfully. \\n \\nWithin the main() method command line arguments are available in the \\nform of String hence  \"+\" operator acts as string concatenation but \\nnot perform arithmetic addition. \\nExample:- \\nclass Test \\n{ \\npublic static void main(String[] args) \\n{ \\nSystem.out.println(args[0]+args[1]); \\n} \\n} \\nOutput:- \\njavac Test.java \\njava Test 100 200 \\nOutput:-100200 \\n \\nSpace is the separator between 2 command line arguments and if our \\ncommand line argument itself contains space then we should enclose \\nwith in double quotes. \\n \\nExample:- \\nclass Test \\n{ \\npublic static void main(String[] args) \\n{ \\nSystem.out.println(args[0]); \\n} \\n} \\nOutput:'),\n",
              " Document(page_content='with in double quotes. \\n \\nExample:- \\nclass Test \\n{ \\npublic static void main(String[] args) \\n{ \\nSystem.out.println(args[0]); \\n} \\n} \\nOutput: \\njavac Test.java \\njava Test \"GLA UNIVERSITY\" \\nOutput:-GLA UNIVERSITY')]"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain.llms import GooglePalm\n",
        "api_key = \"AIzaSyCYNZ8WPIeP6c2F2NJResGaT48vbv5jt0Y\""
      ],
      "metadata": {
        "id": "zQtTX-mItDS6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "llm = GooglePalm(google_api_key=api_key,temperature=0.7)"
      ],
      "metadata": {
        "id": "sJUhsCMptjGZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "QA = RetrievalQA.from_chain_type(llm=llm,chain_type=\"stuff\",retriever=docsearch.as_retriever())"
      ],
      "metadata": {
        "id": "i2KQlFc2tnit"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "QA.run(query)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 90
        },
        "id": "7i-9joJXtqHA",
        "outputId": "f8f1847a-e0f0-4153-e9de-12c4b54d4555"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/langchain_core/_api/deprecation.py:117: LangChainDeprecationWarning: The function `run` was deprecated in LangChain 0.1.0 and will be removed in 0.2.0. Use invoke instead.\n",
            "  warn_deprecated(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'budget is the number of command line arguments passed to the program'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "query1 = \"what is green energy?\"\n"
      ],
      "metadata": {
        "id": "OlMv6rh7tsbO"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "QA.run(query1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "-zZIQB3ltui1",
        "outputId": "3abc6d2d-8b0b-4e14-a938-6b84da1f56eb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Renewable energy is called green energy'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "while True:\n",
        "  user_input = input(\"Input Prompt:\")\n",
        "  if user_input=='exit':\n",
        "    print(\"Exit...\")\n",
        "    sys.exit()\n",
        "  if user_input=='':\n",
        "    continue\n",
        "\n",
        "  result = QA({'query':user_input})\n",
        "  print(\"Answer : \",{result['result']})"
      ],
      "metadata": {
        "id": "WPP7w8pjtxc2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "MbSprkqPxubi"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}