googleapis/python-genai

Google Gen AI Python SDK provides an interface for developers to integrate Google's generative models into their Python applications.

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Summary Information

Updated 1 hour ago
Added to GitGenius on September 17th, 2026
Created on December 6th, 2024
Open Issues & Pull Requests: 318 (+0)
GitHub issues: Enabled
Number of forks: 1,014
Total Stargazers: 3,984 (+0)
Total Subscribers: 233 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 10.8 hours
Mean response time: 3.6 days
90th percentile: 3.7 days
Tracked items: 939

Most active contributors

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How this project is maintained

Practically every issue opened in the past year has drawn a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 55% of tracked open issues have had no activity in three months. 61% of issues opened in the past year have been closed, leaving a working backlog.

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Issue Activity (beta)

Open issues: 212
New in 7 days: 4
Closed in 7 days: 1
Avg open age: 230 days
Stale 30+ days: 166
Stale 90+ days: 120

Recent activity

Opened in 7 days: 4
Closed in 7 days: 1
Comments in 7 days: 4
Events in 7 days: 15

Top labels

  • type: bug (545)
  • priority: p2 (537)
  • status:awaiting user response (308)
  • priority: p3 (302)
  • status:stale (245)
  • type: feature request (178)
  • type: question (169)
  • api: gemini-api (92)

Detailed Description

Google Gen AI Python SDK is a Python library that provides an interface for integrating Google's generative models into applications.

The SDK addresses the need for developers to access Google's generative AI capabilities through a unified Python interface. It supports both the Gemini Developer API and the Gemini Enterprise Agent Platform APIs. The library offers methods for generating content, including text and video generation, with support for function calling through its Chats modules. Developers can work with both Pydantic types and dictionaries when interacting with the API, and the SDK handles authentication through environment variables or explicit client configuration.

Developers should adopt this SDK when building applications that integrate Google's Gemini models. It suits projects ranging from simple content generation tasks to more complex agent-based systems that require tool use and multi-turn conversations. The README indicates that the project is actively evolving, with planned breaking changes in upcoming major versions that will restructure how automatic function calling works, moving it exclusively to Chats modules rather than direct model calls. Developers should pin their dependency version if they need stability across updates.

The project maintains a substantial user base, with nearly all open issues originating from external users rather than the core team. Maintainers respond to new issues and pull requests within a day.