TheSmallHanCat/flow2api

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TheSmallHanCat/flow2api has 3k+ stars and 700+ forks on GitHub, is written in Python, and was last pushed on Oct 16, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 42 minutes ago
Added to GitGenius on October 5th, 2026
Created on November 24th, 2025
Open Issues & Pull Requests: 5 (+0)
GitHub issues: Enabled
Number of forks: 703
Total Stargazers: 3,055 (+0)
Total Subscribers: 16 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 26.2 hours
Mean response time: 13.0 days
90th percentile: 39.3 days
Tracked items: 131

How this project is maintained

Practically every issue opened in the past year has drawn a reply. 98% of issues opened in the past year have since been closed. Three people close 86% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 3
New in 7 days: 1
Closed in 7 days: 2
Avg open age: 3 days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 1
Closed in 7 days: 2
Comments in 7 days: 2
Events in 7 days: 7

Top labels

  • bug (2)
  • enhancement (1)

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Detailed Description

Flow2API is an OpenAI-compatible API service that provides a unified interface for Google Flow.

The tool solves the problem of accessing Google Flow capabilities through a standardized API contract. It works by implementing OpenAI API compatibility, allowing developers to use familiar OpenAI client libraries and patterns while routing requests to Flow backends. The service includes account pooling with load balancing, automatic token refresh, caching strategies, and proxy support to handle multiple accounts and distribute traffic efficiently.

Developers should choose this tool if they want to integrate Google Flow into applications built around OpenAI API conventions, avoiding the need to learn a separate API surface. It suits projects that require reliable access to Flow models and benefit from load distribution across multiple accounts. The tool is particularly relevant for applications that already depend on OpenAI client integrations and want to switch to or supplement with Flow without rewriting client code.

The project shows active development with ongoing feature additions and maintenance. The codebase demonstrates attention to production concerns like caching and load balancing rather than basic functionality alone. Community engagement is present through a dedicated discussion channel, indicating the maintainers support user questions and feedback.