From 84d7b0703179847e6855981f8be8ef0dd2530075 Mon Sep 17 00:00:00 2001 From: Mason Daugherty Date: Mon, 16 Mar 2026 00:06:51 -0400 Subject: [PATCH] docs: further `README.md` refinements (#7188) --- README.md | 57 +++++++++++++++++++++++++++++-------------------------- 1 file changed, 30 insertions(+), 27 deletions(-) diff --git a/README.md b/README.md index f6fcb3ada..64a89b3d7 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,8 @@
- + LangGraph Logo @@ -13,13 +13,14 @@
- Version - PyPI - Downloads - Open Issues PyPI - License + PyPI - Downloads + Version Twitter / X
+
+ Trusted by companies shaping the future of agents – including Klarna, Replit, Elastic, and more – LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents. ```bash @@ -28,28 +29,21 @@ pip install -U langgraph If you're looking to quickly build agents with LangChain's `create_agent` (built on LangGraph), check out the [LangChain Agents documentation](https://docs.langchain.com/oss/python/langchain/agents). ---- - -**Documentation**: - -- [docs.langchain.com](https://docs.langchain.com/oss/python/langgraph/overview) – Comprehensive documentation, including conceptual overviews and guides -- [reference.langchain.com/python/langgraph](https://reference.langchain.com/python/langgraph) – API reference docs for LangGraph packages -- [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart) – Get started building with LangGraph - -**Discussions**: Visit the [LangChain Forum](https://forum.langchain.com) to connect with the community and share all of your technical questions, ideas, and feedback. - > [!NOTE] > Looking for the JS/TS library? Check out [LangGraph.js](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://docs.langchain.com/oss/javascript/langgraph/overview). ## Why use LangGraph? -LangGraph provides low-level supporting infrastructure for *any* long-running, stateful workflow or agent. LangGraph does not abstract prompts or architecture, and provides the following central benefits: +LangGraph provides low-level supporting infrastructure for *any* long-running, stateful workflow or agent: -- **[Durable execution](https://docs.langchain.com/oss/python/langgraph/durable-execution)**. Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off. -- **[Human-in-the-loop](https://docs.langchain.com/oss/python/langgraph/interrupts)**. Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution. -- **[Comprehensive memory](https://docs.langchain.com/oss/python/langgraph/memory)**. Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions. -- **[Debugging with LangSmith](https://www.langchain.com/langsmith)**. Gain deep visibility into complex agent behavior with visualization tools that trace execution paths, capture state transitions, and provide detailed runtime metrics. -- **[Production-ready deployment](https://docs.langchain.com/langsmith/deployments)**. Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows. +- **[Durable execution](https://docs.langchain.com/oss/python/langgraph/durable-execution)** — Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off. +- **[Human-in-the-loop](https://docs.langchain.com/oss/python/langgraph/interrupts)** — Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution. +- **[Comprehensive memory](https://docs.langchain.com/oss/python/langgraph/memory)** — Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions. +- **[Debugging with LangSmith](https://www.langchain.com/langsmith)** — Gain deep visibility into complex agent behavior with visualization tools that trace execution paths, capture state transitions, and provide detailed runtime metrics. +- **[Production-ready deployment](https://docs.langchain.com/langsmith/deployments)** — Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows. + +> [!TIP] +> For developing, debugging, and deploying AI agents and LLM applications, see [LangSmith](https://docs.langchain.com/langsmith/home). ## LangGraph ecosystem @@ -62,17 +56,26 @@ To improve your LLM application development, pair LangGraph with: - [LangSmith](https://www.langchain.com/langsmith) – Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time. - [LangSmith Deployment](https://docs.langchain.com/langsmith/deployments) – Deploy and scale agents effortlessly with a purpose-built deployment platform for long-running, stateful workflows. Discover, reuse, configure, and share agents across teams – and iterate quickly with visual prototyping in [LangSmith Studio](https://docs.langchain.com/langsmith/studio). -> [!TIP] -> For developing, debugging, and deploying AI agents and LLM applications, see [LangSmith](https://docs.langchain.com/langsmith/home). +--- + +## Documentation + +- [docs.langchain.com](https://docs.langchain.com/oss/python/langgraph/overview) – Comprehensive documentation, including conceptual overviews and guides +- [reference.langchain.com/python/langgraph](https://reference.langchain.com/python/langgraph) – API reference docs for LangGraph packages +- [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart) – Get started building with LangGraph +- [Chat LangChain](https://chat.langchain.com/) – Chat with the LangChain documentation and get answers to your questions + +**Discussions**: Visit the [LangChain Forum](https://forum.langchain.com) to connect with the community and share all of your technical questions, ideas, and feedback. ## Additional resources -- [Guides](https://docs.langchain.com/oss/python/learn) – Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.). -- [API Reference](https://reference.langchain.com/python/langgraph) – Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components. -- [Examples](https://docs.langchain.com/oss/python/langgraph/agentic-rag) – Guided examples on getting started with LangGraph. -- [LangChain Academy](https://academy.langchain.com/courses/intro-to-langgraph) – Learn the basics of LangGraph in our free, structured course. -- [Case studies](https://www.langchain.com/built-with-langgraph) – Hear how industry leaders use LangGraph to ship AI applications at scale. +- **[Guides](https://docs.langchain.com/oss/python/learn)** – Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.). +- **[LangChain Academy](https://academy.langchain.com/courses/intro-to-langgraph)** – Learn the basics of LangGraph in our free, structured course. +- **[Case studies](https://www.langchain.com/built-with-langgraph)** – Hear how industry leaders use LangGraph to ship AI applications at scale. - [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview) – Learn how to contribute to LangChain projects and find good first issues. +- [Code of Conduct](https://github.com/langchain-ai/langchain/?tab=coc-ov-file) – Our community guidelines and standards for participation. + +--- ## Acknowledgements