langchain-ai/langchain
The agent engineering platform.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
5 releases in the last 90 days, the latest today, with 467 contributors on GitHub.
Gained 28% fewer stars in the last 90 days than in the 90 days before.
Use Cases & Benefits
- A framework for building applications powered by large language models by chaining interoperable components and third-party integrations.
- Enables seamless model interoperability and real-time data augmentation, allowing developers to adapt quickly as AI technology evolves.
- Use for integrating diverse data sources and external systems to enhance AI application responses with real-time information.
- Use for experimenting with and swapping different LLM providers and models to optimize application performance and capabilities.
- Use for building complex, reliable agent workflows with customizable architecture and long-term memory using LangGraph integration.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
MIT
Permissive: commercial use, modification and redistribution are allowed with attribution.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
LangChain is a framework for building LLM-powered applications. It helps you chain together interoperable components and third-party integrations to simplify AI application development — all while future-proofing decisions as the underlying technology evolves.
Documentation: To learn more about LangChain, check out the docs.
If you're looking for more advanced customization or agent orchestration, check out LangGraph, our framework for building controllable agent workflows.
LangChain helps developers build applications powered by LLMs through a standard interface for models, embeddings, vector stores, and more.
While the LangChain framework can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools when building LLM applications.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
25.0K+1.1K
Open issues
705+246
Compared with peers in AI
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| D4Vinci/Scrapling | 101.1K | +6.3K | 75 | 6 days ago |
| thedotmack/claude-mem | 115.8K | +4.7K | 75 | today |
| heygen-com/hyperframes | 82.3K | +4.0K | 75 | today |
| harry0703/MoneyPrinterTurbo | 142.0K | +3.8K | 75 | 3 days ago |
| github/spec-kit | 149.2K | +2.6K | 75 | today |
| langchain-ai/langchain | 149.0K | — | 45 | today |
| Category median | 115.8K | +4.0K | 75 | — |
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