langchain

什么是 langchain？

The agent engineering platform. LangChain is a framework for building agents and 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. Tip Just getting started? Check out Deep Agents — a higher-level package built on LangChain for agents that have built-in capabilites for common usage patterns such as planning, subagents, file system usage, and more. Quickstart uv add langchain from langchain . chat_models import init_chat_model model = init_chat_model "openai:gpt-5.5" result = model . invoke "Hello, world!" If you're looking for more advanced customization or agent orchestration, check out LangGraph , our framework for building controllable agent workflows. For an equivalent JS/TS library, check out LangChain.js . Tip For developing, debugging, and deploying AI agents and LLM applications, see LangSmith . LangChain ecosystem 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. Deep Agents — Build agents that can plan, use subagents, and leverage file systems for complex tasks LangGraph — Build agents that can reliably handle complex tasks with our low-level agent orchestration framework Integrations — Chat & embedding models, tools & toolkits, and more LangSmith — Agent evals, observability, and debugging for LLM apps LangSmith Deployment — Deploy and scale agents with a purpose-built platform for long-running, stateful workflows Why use LangChain? LangChain helps developers build applications powered by LLMs through a standard interface for models, embeddings, vector stores, and more. Real-time data augmentation — Easily connect LLMs to diverse data sources and external/internal systems, drawing from LangChain's vast library of integrations with model providers, tools, vector stores, retrievers, and more Model interoperability — Swap models in and out as your engineering team experiments to find the best choice for your application's needs. As the industry frontier evolves, adapt quickly — LangChain's abstractions keep you moving without losing momentum Rapid prototyping — Quickly build and iterate on LLM applications with LangChain's modular, component-based architecture. Test different approaches and workflows without rebuilding from scratch, accelerating your development cycle Production-ready features — Deploy reliable applications with built-in support for monitoring, evaluation, and debugging through integrations like LangSmith. Scale with confidence using battle-tested patterns and best practices Vibrant community and ecosystem — Leverage a rich ecosystem of integrations, templates, and community-contributed components. Benefit from continuous improvements and stay up-to-date with the latest AI developments through an active open-source community Flexible abstraction layers — Work at the level of abstraction that suits your needs — from high-level chains for quick starts to low-level components for fine-grained control. LangChain grows with your application's complexity Resources Documentation — conceptual overviews and guides LangChain ecosystem overview — how LangChain, LangGraph, and Deep Agents fit together API reference — complete reference for all public classes, functions, and types Discussions — community forum for technical questions, ideas, and feedback LangChain Academy — comprehensive, free courses on LangChain libraries and products, made by the LangChain team Contributing Guide — how to contribute and find good first issues Code of Conduct — community guidelines and standards

README 摘要

The agent engineering platform. LangChain is a framework for building agents and 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. Tip Just getting started? Check out Deep Agents — a higher-level package built on LangChain for agents that have built-in capabilites for common usage patterns such as planning, subagents, file system usage, and more. Quickstart uv add langchain from langchain . chat_models import init_chat_model model = init_chat_model ( "openai:gpt-5.5" ) result = model . invoke ( "Hello, world!" ) If you're looking for more advanced customization or agent orchestration, check out LangGraph , our framewor…