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 This is a collection of fun examples for the Gemini API. 
 
-* [Agents and Automatic Function Calling](https://github.com/google-gemini/cookbook/blob/main/examples/Agents_Function_Calling_Barista_Bot.ipynb): Create an agent (Barrista-bot) to take your coffee order. 
-* [Classify and Analyze a Video](https://github.com/google-gemini/cookbook/blob/main/examples/Analyze_a_Video_Classification.ipynb): This notebook uses multimodal capabilities of the Gemini model to classify the species of animals shown in a video.
-* [Anomaly Detection](https://github.com/google-gemini/cookbook/blob/main/examples/Anomaly_detection_with_embeddings.ipynb): Use embeddings to detect anomalies in your datasets.
-* [Analyze a Video with Summarization](https://github.com/google-gemini/cookbook/blob/main/examples/Analyze_a_Video_Summarization.ipynb): This notebook shows how you can use Gemini API's multimodal capabilities for video summarization.
-* [Apollo 11 - long context example](https://github.com/google-gemini/cookbook/blob/main/examples/Apollo_11.ipynb): Search a 400 page transcript from Apollo 11.
-* [Clasify text with emeddings](https://github.com/google-gemini/cookbook/blob/main/examples/Classify_text_with_embeddings.ipynb): Use embeddings from the Gemini API with Keras.
-* [Guess the shape](https://github.com/google-gemini/cookbook/blob/main/examples/Guess_the_shape.ipynb): A simple example of using images in prompts.
-* [Market a Jet Backpack](https://github.com/google-gemini/cookbook/blob/main/examples/Market_a_Jet_Backpack.ipynb): Create a marketing campaign from a product sketch.
-* [Object detection](https://github.com/google-gemini/cookbook/blob/main/examples/Object_detection.ipynb): Extensive examples with object detection, including with multiple classes, OCR, visual question answering, and even an interactive demo.  
-* [Opossum search](https://github.com/google-gemini/cookbook/blob/main/examples/Opossum_search.ipynb): Code generation with the Gemini API. Just for fun, you'll prompt the model to create a web app called "Opossum Search" that searches Google with "opossum" appended to the query.
-* [Search Wikipedia with ReAct](https://github.com/google-gemini/cookbook/blob/main/examples/Search_Wikipedia_using_ReAct.ipynb): Use ReAct prompting with Gemini 1.5 Flash to search Wikipedia interactively.
-* [Search Re-ranking with Embeddings](https://github.com/google-gemini/cookbook/blob/main/examples/Search_reranking_using_embeddings.ipynb): Use embeddings to re-rank search results.
-* [Story writing with prompt chaining.ipynb](https://github.com/google-gemini/cookbook/blob/main/examples/Story_Writing_with_Prompt_Chaining.ipynb): Write a story using two powerful tools: prompt chaining and iterative generation.
-* [Talk to documents](https://github.com/google-gemini/cookbook/blob/main/examples/Talk_to_documents_with_embeddings.ipynb): This is a basic intro to Retrieval Augmented Generation (RAG). Use embeddings to search through a custom database.
-* [Upload files to Colab](https://github.com/google-gemini/cookbook/blob/main/examples/Upload_files_to_Colab.ipynb): This is a helper notebook that shows how to upload files from your local computer to Colab. Note: to upload files to the Gemini API (text, code, images, audio, video), check out the [Files quickstart](https://github.com/google-gemini/cookbook/blob/main/quickstarts/File_API.ipynb).
-* [Voice Memos](https://github.com/google-gemini/cookbook/blob/main/examples/Voice_memos.ipynb): You'll use the Gemini API to help you generate ideas for your next blog post, based on voice memos you recorded on your phone, and previous articles you've written.
-* [Translate a public domain](https://github.com/google-gemini/cookbook/blob/main/examples/Translate_a_Public_Domain_Book.ipynb): In this notebook, you will explore Gemini model as a translation tool, demonstrating how to prepare data, create effective prompts, and save results into a `.txt` file.
-* [Working with Charts, Graphs, and Slide Decks](https://github.com/google-gemini/cookbook/blob/main/examples/Working_with_Charts_Graphs_and_Slide_Decks.ipynb): Gemini models are powerful multimodal LLMs that can process both text and image inputs. This notebook shows how Gemini 1.5 Flash model is capable of extracting data from various images.
-* [Entity extraction](https://github.com/google-gemini/cookbook/blob/main/examples/Entity_Extraction.ipynb): Use Gemini API to speed up some of your tasks, such as searching through text to extract needed information. Entity extraction with a Gemini model is a simple query, and you can ask it to retrieve its answer in the form that you prefer.
-* [Generate a company research report using search grounding](https://github.com/google-gemini/cookbook/blob/main/examples/search_grounding_for_research_report.ipynb): Use search grounding to write a company research report with Gemini 1.5 Flash.
 * [Agents and Automatic Function Calling](./Agents_Function_Calling_Barista_Bot.ipynb): Create an agent (Barrista-bot) to take your coffee order. 
 * Video Analysis: Three notebooks using multimodal capabilities of the Gemini model to [classify the species of animals](./Analyze_a_Video_Classification.ipynb) for a video, [summarize one](./Analyze_a_Video_Summarization.ipynb) or [recognizing when it happened](./Analyze_a_Video_Historic_Event_Recognition.ipynb), 
 * [Anomaly Detection](./Anomaly_detection_with_embeddings.ipynb): Use embeddings to detect anomalies in your datasets.