# google-gemini/cookbook

Examples and guides for using the Gemini API

Repository: https://github.com/google-gemini/cookbook
Canonical: https://ross.abutalabs.com/products/cookbook
Homepage: https://ai.google.dev/gemini-api/docs
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Topics: gemini, gemini-api
Last push: 2026-08-26T19:01:18+00:00

## Health v2 (maintenance only)
Score: 70/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 35, longevity 64
- inputs: {"age_days": 903, "days_push": 7, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 17703, forks 2752 (observed 2026-08-28T04:11:20.189978+00:00)

## What it is
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
- artifact type: learning-resource
- maturity: active
- function: llm-inference, agent-framework, prompt-engineering, sdk, developer-tools
- domain: large-language-models, artificial-intelligence, tutorials, developer-tools
- platform: python, cross-platform
- tags: gemini-api, cookbook, jupyter-notebooks, google, generative-ai, multimodal, image-generation, video-generation, quickstarts, ai-agents, nodejs, web-server

## Member repositories
- google-gemini/cookbook (main) score 70

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:20.189978+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:02:29.479167+00:00, confidence not recorded.
  - readme: https://github.com/google-gemini/cookbook (fetched 2026-08-28T04:11:20.189978+00:00, sha 842a6a37ff81)
  - homepage: https://ai.google.dev/gemini-api/docs (fetched 2026-08-29T08:00:50.708673+00:00, sha 11489b3a3b69)
  - site_page: https://ai.google.dev/gemini-api/docs/get-started (fetched 2026-08-29T08:00:50.718285+00:00, sha 0d97879d85d3)
  - site_page: https://ai.google.dev/gemini-api/docs/api-key (fetched 2026-08-29T08:00:50.721390+00:00, sha 7aacb7b0841e)
  - site_page: https://ai.google.dev/gemini-api/docs/pricing (fetched 2026-08-29T08:00:50.723664+00:00, sha 63fb7a02921f)
  - site_page: https://ai.google.dev/gemini-api/docs/coding-agents (fetched 2026-08-29T08:00:50.727114+00:00, sha 3c57684e19de)
  - site_page: https://ai.google.dev/gemini-api/docs/models (fetched 2026-08-29T08:00:50.729757+00:00, sha 6415425758d4)
  - site_page: https://ai.google.dev/gemini-api/docs/latest-model (fetched 2026-08-29T08:00:50.732385+00:00, sha f4ac326d927e)
  - site_page: https://ai.google.dev/gemini-api/docs/image-generation (fetched 2026-08-29T08:00:50.744934+00:00, sha 417b11c2f0da)
  - site_page: https://ai.google.dev/gemini-api/docs/veo (fetched 2026-08-29T08:00:50.768836+00:00, sha 20657665f2cb)
- Data as of 2026-08-30T08:39:29.467469+00:00.