philschmid/gemini-samples resource

Health v2 · maintenance only

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1372 stars · 208 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of Jupyter notebook samples, snippets, and guides demonstrating how to use Google DeepMind Gemini models. It covers function calling, agents, structured outputs, MCP, context caching, and other Gemini API capabilities.

Use cases

• learn how to call Gemini models from Python
• implement function calling with Gemini
• build a ReAct agent with LangGraph and Gemini
• generate structured JSON outputs with Pydantic and Gemini
• use Gemini with the OpenAI SDK
• integrate MCP with Gemini
• reduce Gemini API costs with context caching
• transcribe and analyze YouTube videos with Gemini

When to choose

• you want practical, runnable notebook examples for the Gemini API
• you are exploring agentic patterns or function calling with Gemini
• you need reference snippets for structured outputs, caching, or batch API usage

When to avoid

• you need a production-ready library or framework rather than example code
• you work with LLM providers other than Google Gemini
• you need maintained, versioned software with API stability guarantees

Facets

learning-resource · maturity active

llm-inference agent-framework prompt-engineering mcp rag large-language-models artificial-intelligence tutorials python jvm-scripting gemini google-deepmind jupyter-notebooks samples function-calling structured-outputs ai-agents nodejs

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