google-gemini/cookbook resource
Examples and guides for using the Gemini API observed · 2026-08-28
Health v2 · maintenance only
70/100
- Activity 99
- Release rhythm 35
- Longevity 64
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 903
- days_rel: n/a
- days_push: 7
- n_releases_24m: 0
Adoption not part of the score
17703 stars · 2752 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
The Gemini API Cookbook is a collection of Jupyter Notebook quickstarts, tutorials, and examples for using Google's Gemini API and its models (Gemini Flash, Nano Banana, Veo, Lyria). It provides a structured hands-on learning path covering text generation, multimodal inputs, image/video generation, function calling, and building agents.
Use cases
- learn how to call the Gemini API from Python or JavaScript
- generate images with Nano Banana models
- generate videos with Veo using prompts
- build AI agents with the Gemini Agents API
- use function calling and structured output with Gemini
- get started with multimodal LLM applications
- find example notebooks for Gemini model features
When to choose
- you are learning the Gemini API and want hands-on runnable notebooks
- you need up-to-date examples for new Gemini models and features
- you want quickstart code for text, image, video, or audio generation with Gemini
When to avoid
- you need comprehensive reference documentation rather than tutorials (use ai.google.dev docs)
- you are building with a different LLM provider
- you need a production-ready application or SDK rather than example code
Facets
learning-resource · maturity active
llm-inference agent-framework prompt-engineering sdk developer-tools large-language-models artificial-intelligence tutorials developer-tools python cross-platform gemini-api cookbook jupyter-notebooks google generative-ai multimodal image-generation video-generation quickstarts ai-agents nodejs web-server
10 sources
- readme: https://github.com/google-gemini/cookbook · fetched 2026-08-28 · 842a6a37ff81
- homepage: https://ai.google.dev/gemini-api/docs · fetched 2026-08-29 · 11489b3a3b69
- site_page: https://ai.google.dev/gemini-api/docs/get-started · fetched 2026-08-29 · 0d97879d85d3
- site_page: https://ai.google.dev/gemini-api/docs/api-key · fetched 2026-08-29 · 7aacb7b0841e
- site_page: https://ai.google.dev/gemini-api/docs/pricing · fetched 2026-08-29 · 63fb7a02921f
- site_page: https://ai.google.dev/gemini-api/docs/coding-agents · fetched 2026-08-29 · 3c57684e19de
- site_page: https://ai.google.dev/gemini-api/docs/models · fetched 2026-08-29 · 6415425758d4
- site_page: https://ai.google.dev/gemini-api/docs/latest-model · fetched 2026-08-29 · f4ac326d927e
- site_page: https://ai.google.dev/gemini-api/docs/image-generation · fetched 2026-08-29 · 417b11c2f0da
- site_page: https://ai.google.dev/gemini-api/docs/veo · fetched 2026-08-29 · 20657665f2cb
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| google-gemini/cookbook | main | 70 |
For agents
markdown · JSON · MCP: product_card(name="google-gemini/cookbook")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem