GoogleCloudPlatform/generative-ai resource

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17630 stars · 4425 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A collection of Jupyter notebooks, code samples, and sample apps demonstrating how to use generative AI on Google Cloud, including Gemini models, Vertex AI, RAG grounding, and the Gemini Enterprise Agent Platform. It serves as official example documentation for building LLM, search, vision, and audio workflows on GCP.

Use cases

• learn how to call Gemini models from Python
• build a RAG pipeline on Vertex AI
• examples of function calling with Gemini
• generate images with Imagen or video with Veo
• build AI agents on Google Cloud
• get started with Vertex AI notebooks
• enterprise search with generative AI on GCP

When to choose

• you are developing on Google Cloud / Vertex AI and want official working examples
• you want to learn Gemini API patterns like function calling, grounding, and RAG
• you need starter notebooks for multimodal generation (image, video, audio)

When to avoid

• you need a production-ready library or framework rather than sample code
• you are not using Google Cloud or its AI services
• you want model-agnostic examples that run outside GCP

Facets

learning-resource · maturity active

machine-learning llm-inference rag agent-framework prompt-engineering speech-recognition image-processing artificial-intelligence large-language-models cloud-computing tutorials python cloud gemini vertex-ai google-cloud jupyter-notebooks sample-code langchain generative-ai imagen veo retrieval-augmented-generation ai-agents gpu

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For agents

markdown · JSON · MCP: product_card(name="GoogleCloudPlatform/generative-ai")