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47 行
3.3 KiB
Markdown
47 行
3.3 KiB
Markdown
# 🦜🕸️ LangGraph
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[](https://pypi.org/project/langgraph/#history)
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[](https://opensource.org/licenses/MIT)
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[](https://pypistats.org/packages/langgraph)
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[](https://github.com/langchain-ai/langgraph/issues)
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[](https://x.com/langchain_oss)
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Looking for the JS/TS version? Check out [LangGraph.js](https://github.com/langchain-ai/langgraphjs).
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To help you ship LangGraph apps to production faster, check out [LangSmith](https://www.langchain.com/langsmith).
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[LangSmith](https://www.langchain.com/langsmith) is a unified developer platform for building, testing, and monitoring LLM applications.
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## Quick Install
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```bash
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uv add langgraph
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```
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## 🤔 What is this?
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LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents. LangGraph provides the infrastructure for durable execution, streaming, human-in-the-loop, persistence, memory, and more.
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We recommend you use LangGraph when you have advanced needs that require a combination of deterministic and agentic workflows, heavy customization, and carefully controlled latency. Use [LangChain](https://docs.langchain.com/oss/python/langchain/overview) when you want to quickly build agents and applications powered by LLMs using pre-built agent architectures and model integrations.
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LangChain [agents](https://docs.langchain.com/oss/python/langchain/agents) are built on top of LangGraph in order to provide durable execution, streaming, human-in-the-loop, persistence, and more. (You do not need to know LangGraph for basic LangChain agent usage.)
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Trusted by companies shaping the future of agents – including Klarna, Replit, Elastic, and more – LangGraph is used to ship AI applications at scale.
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## 📖 Documentation
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For full documentation, see the [API reference](https://reference.langchain.com/python/langgraph/). For conceptual guides, tutorials, and examples on using LangGraph, see the [LangGraph Docs](https://docs.langchain.com/oss/python/langgraph/overview). Get started with the [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart).
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## 📕 Releases & Versioning
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See our [Releases](https://docs.langchain.com/oss/python/release-policy) and [Versioning](https://docs.langchain.com/oss/python/versioning) policies.
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## 💁 Contributing
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As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
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For detailed information on how to contribute, see the [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview).
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## Acknowledgements
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LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
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