Sample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform
17,689
stars
2,144
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Jupyter Notebook
primary language
Sep 9, 2026
updated
The latest Gemini models are available! Try out Gemini 3.7 Flash.
Gemini Enterprise Agent Platform, the latest evolution of Vertex AI, has been released!
Check out the
Google-Cloud-AI/agent-platformrepository for a curated list of assets for agent building on Google Cloud.
This repository contains notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage generative AI workflows using Generative AI with Agent Platform.
| Description | |
|---|---|
gemini/
| Discover Gemini through starter notebooks, use cases, function calling, sample apps, and more. |
search/
| Use this folder if you're interested in using Agent Search, a Google-managed solution to help you rapidly build search engines for websites and across enterprise data. (Formerly known as Enterprise Search on Generative AI App Builder). |
rag-grounding/
| Use this folder for information on Retrieval Augmented Generation (RAG) and Grounding. This is an index of notebooks and samples across other directories focused on this topic. |
vision/
| Use this folder if you're interested in building your own solutions from scratch using features from Imagen and Veo. |
audio/
| Use this folder if you're interested in building your own solutions from scratch using features from Chirp, a version of Google's Universal Speech Model (USM). |
setup-env/
| Instructions on how to set up Google Cloud, the Gen AI Python SDK, and notebook environments on Google Colab and Workbench. |
RESOURCES.md
| Learning resources (e.g. blogs, YouTube playlists) about Generative AI on Google Cloud. |
Contributions welcome! See the Contributing Guide.
Please use the issues page to provide suggestions, feedback or submit a bug report.
This repository itself is not an officially supported Google product. The code in this repository is for demonstrative purposes only.
(top 30 of 301)
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Sample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform
17,689
stars
2,144
commits
Jupyter Notebook
primary language
Sep 9, 2026
updated
The latest Gemini models are available! Try out Gemini 3.7 Flash.
Gemini Enterprise Agent Platform, the latest evolution of Vertex AI, has been released!
Check out the
Google-Cloud-AI/agent-platformrepository for a curated list of assets for agent building on Google Cloud.
This repository contains notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage generative AI workflows using Generative AI with Agent Platform.
| Description | |
|---|---|
gemini/
| Discover Gemini through starter notebooks, use cases, function calling, sample apps, and more. |
search/
| Use this folder if you're interested in using Agent Search, a Google-managed solution to help you rapidly build search engines for websites and across enterprise data. (Formerly known as Enterprise Search on Generative AI App Builder). |
rag-grounding/
| Use this folder for information on Retrieval Augmented Generation (RAG) and Grounding. This is an index of notebooks and samples across other directories focused on this topic. |
vision/
| Use this folder if you're interested in building your own solutions from scratch using features from Imagen and Veo. |
audio/
| Use this folder if you're interested in building your own solutions from scratch using features from Chirp, a version of Google's Universal Speech Model (USM). |
setup-env/
| Instructions on how to set up Google Cloud, the Gen AI Python SDK, and notebook environments on Google Colab and Workbench. |
RESOURCES.md
| Learning resources (e.g. blogs, YouTube playlists) about Generative AI on Google Cloud. |
Contributions welcome! See the Contributing Guide.
Please use the issues page to provide suggestions, feedback or submit a bug report.
This repository itself is not an officially supported Google product. The code in this repository is for demonstrative purposes only.
(top 30 of 301)
Jupyter Notebook
83.1%
Python
7.3%
HTML
2.8%
JavaScript
2.7%
TypeScript
1.4%
SCSS
1.3%