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librechat-ai/librechat

Enhanced ChatGPT Clone: Features Agents, MCP, Skills, DeepSeek, Anthropic, AWS, OpenAI, Responses API, Azure, Groq, o1, GPT-5, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching, message search, Code Interpreter, langchain, DALL-E-3, OpenAPI Actions, Functions, Secure Multi-User Auth, Presets, open-source for self-hosting. Active

TypeScriptrisingLive GitHub sample
View JSON View on GitHub

Current momentum

73capped sample

Stars

46.1K

+270 since sync

Commits

83

in period

Active contributors

5

+0%

Issues closed

1

17.5h avg. resolution

Recorded trajectory

Movement you can verify over time.

Loading daily momentum history.

Behind the number

A score you can inspect.

Each signal contributes points to the total. These are capped GitHub samples, not complete activity counts or proof of adoption.

Development activity40.0 / 40 pts

83 commits · 50 opened PRs · 1 closed issues in 7 days

24 + 22 × ln(1 + weekly weighted activity). Activity = commits + 2 × opened PRs + closed issues. Signal bounded to 0–100, then weighted 40%.

Contributor breadth17.2 / 25 pts

5 sampled contributors in 7 days · 0% contributor-growth input

24 + 25 × ln(1 + contributors × √(7 / days)) + 0.15 × growth. Growth uses the 30-day windows; capped samples use a neutral 0 input. Signal bounded to 0–100, then weighted 25%.

Issue resolution13.4 / 20 pts

17.5 hours resolution input

105 − 9 × log₂(1 + hours). Uses sampled closed issues, not first-response time. With no resolved issues, the model uses 168 hours. Signal bounded to 0–100, then weighted 20%.

Release cadence2.3 / 15 pts

18 days cadence input

105 − 5 × cadence days. With fewer than two published releases, the model uses time since the last push as a proxy. Signal bounded to 0–100, then weighted 15%.

Weighted total · rounded once73 / 100

What changed in the recorded sample?

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9.5K forks

Downstream adoption

979 open issues

Community demand

18 day cadence

Shipping consistency