# Generative AI on Google Cloud
> The latest Gemini models are available! Try out [Gemini 4 Carbon](https://github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/getting-started/intro_gemini_4_carbon.ipynb).
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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](https://cloud.google.com/ai/generative-ai) with [Agent Platform](https://docs.cloud.google.com/gemini-enterprise-agent-platform).
## Intro Video
[](https://goo.gle/agent-platform-video)
<table>
<tr>
<th></th>
<th style="text-align: center;">Description</th>
</tr>
<tr>
<td>
<img src="https://storage.googleapis.com/github-repo/img/gemini/Spark__Gradient_Alpha_100px.gif" width="45px" alt="Gemini">
<br>
<a href="gemini/"><code>gemini/</code></a>
</td>
<td>
Discover Gemini through starter notebooks, use cases, function calling, sample apps, and more.
</td>
</tr>
<tr>
<td>
<img src="https://www.gstatic.com/images/branding/gcpiconscolors/service_discovery/v1/24px.svg" width="40px" alt="Search">
<br>
<a href="search/"><code>search/</code></a>
</td>
<td>Use this folder if you're interested in using <a href="https://cloud.google.com/enterprise-search">Agent Search</a>, 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).</td>
</tr>
<tr>
<td>
<img src="https://fonts.gstatic.com/s/i/short-term/release/googlesymbols/nature_people/default/40px.svg" alt="RAG Grounding">
<br>
<a href="rag-grounding/"><code>rag-grounding/</code></a>
</td>
<td>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.</td>
</tr>
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<td>
<img src="https://fonts.gstatic.com/s/i/short-term/release/googlesymbols/image/default/40px.svg" alt="Vision">
<br>
<a href="vision/"><code>vision/</code></a>
</td>
<td>
Use this folder if you're interested in building your own solutions from scratch using features from Imagen and Veo.
</td>
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<td>
<img src="https://fonts.gstatic.com/s/i/short-term/release/googlesymbols/mic/default/40px.svg" alt="Speech">
<br>
<a href="audio/"><code>audio/</code></a>
</td>
<td>
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).
</td>
</tr>
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<td>
<img src="https://fonts.gstatic.com/s/i/short-term/release/googlesymbols/build/default/40px.svg" alt="Setup Env">
<br>
<a href="setup-env/"><code>setup-env/</code></a>
</td>
<td>Instructions on how to set up Google Cloud, the Gen AI Python SDK, and notebook environments on Google Colab and Workbench.</td>
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<td>
<img src="https://fonts.gstatic.com/s/i/short-term/release/googlesymbols/media_link/default/40px.svg" alt="Resources">
<br>
<a href="RESOURCES.md"><code>RESOURCES.md</code></a>
</td>
<td>Learning resources (e.g. blogs, YouTube playlists) about Generative AI on Google Cloud.</td>
</tr>
</table>
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## Related Repositories
- ✨ [Agent Development Kit (ADK) Samples](https://github.com/google/adk-samples): This repository provides ready-to-use agents built on top of the Agent Development Kit, designed to accelerate your development process. These agents cover a range of common use cases and complexities, from simple conversational bots to complex multi-agent workflows.
- [🚀 Agent Starter Pack](https://github.com/GoogleCloudPlatform/agent-starter-pack)
- A collection of production-ready Generative AI Agent templates built for Google Cloud.
- It accelerates development by providing a holistic, production-ready solution, addressing common challenges (Deployment & Operations, Evaluation, Customization, Observability) in building and deploying Gen AI agents.
- [Gemini Cookbook](https://github.com/google-gemini/cookbook/)
- [genai-factory](https://github.com/googleCloudPlatform/genai-factory) - A collection of end-to-end infrastructure blueprints to deploy generative AI infrastructures in GCP, using IaC and following security best-practices.
- [Google Cloud Applied AI Engineering](https://github.com/GoogleCloudPlatform/applied-ai-engineering-samples)
- [Vertex AI GenMedia Creative Studio](https://github.com/GoogleCloudPlatform/vertex-ai-creative-studio) - Experience Google's generative media foundational models + custom workflows.
- [MCP Servers for GenMedia](https://goo.gle/vertex-genmedia-mcp) - Empower your agents with generative media tools.
- [Generative AI for Marketing using Google Cloud](https://github.com/GoogleCloudPlatform/genai-for-marketing)
- [Generative AI for Developer Productivity](https://github.com/GoogleCloudPlatform/genai-for-developers)
- Vertex AI Core
- [Vertex AI Samples](https://github.com/GoogleCloudPlatform/vertex-ai-samples)
- [MLOps with Vertex AI](https://github.com/GoogleCloudPlatform/mlops-with-vertex-ai)
- [Developing NLP solutions with T5X and Vertex AI](https://github.com/GoogleCloudPlatform/t5x-on-vertex-ai)
- [AlphaFold batch inference with Vertex AI Pipelines](https://github.com/GoogleCloudPlatform/vertex-ai-alphafold-inference-pipeline)
- [Serving Spark ML models using Vertex AI](https://github.com/GoogleCloudPlatform/vertex-ai-spark-ml-serving)
- [Sensitive Data Protection (Cloud DLP) for Vertex AI Generative Models (PaLM2)](https://github.com/GoogleCloudPlatform/Sensitive-Data-Protection-for-Vertex-AI-PaLM2)
- Conversational AI
- [Contact Center AI Samples](https://github.com/GoogleCloudPlatform/contact-center-ai-samples)
- [Reimagining Customer Experience 360](https://github.com/GoogleCloudPlatform/dialogflow-ccai-omnichannel)
- Document AI
- [Document AI Samples](https://github.com/GoogleCloudPlatform/document-ai-samples)
- Gemini in Google Cloud
- [Cymbal Superstore](https://github.com/GoogleCloudPlatform/cymbal-superstore)
- Cloud Databases
- [Gen AI Databases Retrieval App](https://github.com/GoogleCloudPlatform/genai-databases-retrieval-app)
- Other
- [ai-on-gke](https://github.com/GoogleCloudPlatform/ai-on-gke)
- [ai-infra-cluster-provisioning](https://github.com/GoogleCloudPlatform/ai-infra-cluster-provisioning)
- [solutions-genai-llm-workshop](https://github.com/GoogleCloudPlatform/solutions-genai-llm-workshop)
- [terraform-genai-doc-summarization](https://github.com/GoogleCloudPlatform/terraform-genai-doc-summarization)
- [terraform-genai-knowledge-base](https://github.com/GoogleCloudPlatform/terraform-genai-knowledge-base)
- [genai-product-catalog](https://github.com/GoogleCloudPlatform/genai-product-catalog)
- [solutionbuilder-terraform-genai-doc-summarization](https://github.com/GoogleCloudPlatform/solutionbuilder-terraform-genai-doc-summarization)
- [solutions-viai-edge-provisioning-configuration](https://github.com/GoogleCloudPlatform/solutions-viai-edge-provisioning-configuration)
- [mis-ai-accelerator](https://github.com/GoogleCloudPlatform/mis-ai-accelerator)
- [dataflow-opinion-analysis](https://github.com/GoogleCloudPlatform/dataflow-opinion-analysis)
- [genai-beyond-basics](https://github.com/meteatamel/genai-beyond-basics)
- [Gemini by Example](https://geminibyexample.com)
## Contributing
Contributions welcome! See the [Contributing Guide](https://github.com/GoogleCloudPlatform/generative-ai/blob/main/CONTRIBUTING.md).
## Getting help
Please use the [issues page](https://github.com/GoogleCloudPlatform/generative-ai/issues) to provide suggestions, feedback or submit a bug report.
## Disclaimer
This repository itself is not an officially supported Google product. The code in this repository is for demonstrative purposes only.