Overview
This repository, maintained by Google Cloud Platform, collects notebooks, sample apps and code demonstrating generative AI workflows on Vertex AI (including Gemini). It covers agent examples, RAG grounding patterns, multimodal generation, and production-oriented deployment and evaluation practices—useful for engineering and product teams validating GenAI solutions on Google Cloud.
Key features
- Hands-on notebooks and examples organized by topic for rapid experimentation and customization.
- Agent and orchestration samples for multi-step automation and task decomposition.
- RAG grounding and retrieval examples to improve factuality and control of generated outputs.
- Production considerations such as deployment patterns, monitoring and evaluation guidance.
Use cases
- Enterprise knowledge retrieval and summarization via RAG to make internal knowledge actionable.
- Conversational assistants and automated workflows leveraging agent patterns and external integrations.
- Media generation for creative tooling: image, audio and text generation/editing pipelines.
- Developer education and experimentation for Vertex AI and Gemini capabilities.
Technical highlights
- Multimodal and multi-language notebooks (primarily Jupyter) with Python and frontend integration samples.
- Deep integration with Vertex AI APIs for model invocation, function-calling, and pipeline deployments.
- Apache-2.0 licensed, community-driven repository accepting contributions and issues.
This resource is a practical starting point for prototyping, learning, and engineering generative AI solutions on Google Cloud. Refer to the GitHub and official documentation links in the frontmatter for source code and detailed examples.