🦜🔗 Build context-aware reasoning applications

https://github.com/langchain-ai/langchain

🤔 What is LangChain?

LangChain is a framework for developing applications powered by large language models (LLMs).

For these applications, LangChain simplifies the entire application lifecycle:

• Open-source libraries: Build your applications using LangChain's open-source components and third-party integrations. Use LangGraph to build stateful agents with first-class streaming and human-in-the-loop support.
• Productionization: Inspect, monitor, and evaluate your apps with LangSmith so that you can constantly optimize and deploy with confidence.
• Deployment: Turn your LangGraph applications into production-ready APIs and Assistants with LangGraph Platform.

Open-source libraries

• langchain-core: Base abstractions.
• Integration packages (e.g. langchain-openai, langchain-anthropic, etc.): Important integrations have been split into lightweight packages that are co-maintained by the LangChain team and the integration developers.
• langchain: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
• langchain-community: Third-party integrations that are community maintained.
• LangGraph: LangGraph powers production-grade agents, trusted by Linkedin, Uber, Klarna, GitLab, and many more. Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it. To learn more about LangGraph, check out our first LangChain Academy course, Introduction to LangGraph, available here.

Productionization:

• LangSmith: A developer platform that lets you debug, test, evaluate, and monitor chains built on any LLM framework and seamlessly integrates with LangChain.

Deployment:

• LangGraph Platform: Turn your LangGraph applications into production-ready APIs and Assistants.