{"repo":"langchain-ai/langgraph","free":true,"listed":false,"github":"https://github.com/langchain-ai/langgraph","clone":"git clone https://github.com/langchain-ai/langgraph.git","description":"Build resilient agents.","language":"Python","stars":39804,"topics":["agents","ai","ai-agents","chatgpt","deepagents","enterprise","framework","gemini","generative-ai","langchain","langgraph","llm","multiagent","open-source","openai","pydantic","python","rag"],"license":"MIT","category":"llm_orchestration","readme_excerpt":"<div align=\"center\">\n  <a href=\"https://www.langchain.com/langgraph\">\n    <picture>\n      <source media=\"(prefers-color-scheme: dark)\" srcset=\".github/images/logo-dark.svg\">\n      <source media=\"(prefers-color-scheme: light)\" srcset=\".github/images/logo-light.svg\">\n      <img alt=\"LangGraph Logo\" src=\".github/images/logo-dark.svg\" width=\"50%\">\n    </picture>\n  </a>\n</div>\n\n<div align=\"center\">\n  <h3>Low-level orchestration framework for building stateful agents.</h3>\n</div>\n\n<div align=\"center\">\n  <a href=\"https://opensource.org/licenses/MIT\" target=\"_blank\"><img src=\"https://img.shields.io/pypi/l/langgraph\" alt=\"PyPI - License\"></a>\n  <a href=\"https://pypistats.org/packages/langgraph\" target=\"_blank\"><img src=\"https://img.shields.io/pepy/dt/langgraph\" alt=\"PyPI - Downloads\"></a>\n  <a href=\"https://pypi.org/project/langgraph/\" target=\"_blank\"><img src=\"https://img.shields.io/pypi/v/langgraph.svg?label=%20\" alt=\"Version\"></a>\n  <a href=\"https://x.com/langchain_oss\" target=\"_blank\"><img src=\"https://img.shields.io/twitter/url/https/twitter.com/langchain_oss.svg?style=social&label=Follow%20%40LangChain\" alt=\"Twitter / X\"></a>\n</div>\n\n<br>\n\nTrusted 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.\n\n```bash\npip install -U langgraph\n```\n\n> [!TIP]\n> If you're looking to quickly build agents, check out **[Deep Agents](https://docs.langchain.com/oss/python/deepagents/overview)** — a higher-level package built on LangGraph for agents that can plan, use subagents, and leverage file systems for complex tasks.\n\nFor an equivalent 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).\n\n## Why use LangGraph?\n\nLangGraph provides low-level supporting infrastructure for *any* long-running, stateful workflow or agent:\n\n- **[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.\n- **[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.\n- **[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.\n- **[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.\n- **[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.\n\n> [!TIP]\n> For developing, debugging, and deploying AI agents and LLM applications, see [LangSmith](https://docs.langchain.com/langsmith/home).\n\n## LangGraph ecosystem\n\nWhile LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents.\n\nTo improve your LLM application development, pair LangGraph with:\n\n- [Deep Agents](https://docs.langchain.com/oss/python/deepagents/overview) – Build agents that can plan, use subagents, and leverage file systems for complex tasks.\n- [LangChain](https://docs.langchain.com/oss/python/langchain/overview) – Provides integrations and composable components to streamline LLM application development.\n- [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.\n- [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).\n\n---\n\n## Documentation\n\n- [docs.langchain.com](https://docs.langchain.com/oss/python/langgraph/overview) – Comprehensive documentation, including conceptual overviews and guides\n- [reference.langchain.com/python/langgraph](https://reference.langchain.com/python/langgraph) – API reference docs for LangGraph packages\n- [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart) – Get started building with LangGraph\n- [Chat LangChain](https://chat.langchain.com/) – Chat with the LangChain documentation and get answers to your questions\n\n**Discussions**: Visit the [LangChain Forum](https://forum.langchain.com) to connect with the community and share all of your technical questions, ideas, and feedback.\n\n## Additional resources\n\n- **[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.).\n- **[LangChain Academy](https://academy.langchain.com/courses/intro-to-langgraph)** – Learn the basics of LangGraph in our free, structured course.\n- **[Case studies](https://www.langchain.com/built-with-langgraph)** – Hear how industry leaders use LangGraph to ship AI applications at scale.\n- [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview) – Learn how to contribute to LangChain projects and find good first issues.\n- [Code of Conduct](https://github.com/langchain-ai/langchain/?tab=coc-ov-file) – Our community guidelines and standards for participation.\n\n---\n\n## Acknowledgements\n\nLangGraph 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.\n","default_branch":"main","files":671,"tree":[".github/ISSUE_TEMPLATE/bug-report.yml",".github/ISSUE_TEMPLATE/config.yml",".github/ISSUE_TEMPLATE/privileged.yml",".github/PULL_REQUEST_TEMPLATE.md",".github/THREAT_MODEL.md",".github/actions/uv_setup/action.yml",".github/dependabot.yml",".github/images/logo-dark.svg",".github/images/logo-light.svg",".github/scripts/check_sdk_methods.py",".github/scripts/run_langgraph_cli_test.py",".github/workflows/_integration_test.yml",".github/workflows/_lint.yml",".github/workflows/_sdk_integration_test.yml",".github/workflows/_test.yml",".github/workflows/_test_langgraph.yml",".github/workflows/_test_release.yml",".github/workflows/baseline.yml",".github/workflows/bench.yml",".github/workflows/ci.yml",".github/workflows/deploy-redirects.yml",".github/workflows/pr_lint.yml",".github/workflows/release.yml",".github/workflows/reopen_on_assignment.yml",".github/workflows/require_issue_link.yml",".github/workflows/tag-external-issues.yml",".github/workflows/tag-external-prs.yml",".github/workflows/uv_lock_ugprade.yml",".gitignore",".markdownlint.json","AGENTS.md","CLAUDE.md","LICENSE","Makefile","README.md","docs/.gitignore","docs/generate_redirects.py","docs/llms.txt","docs/redirects.json","examples/README.md","examples/chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb","examples/chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation.ipynb","examples/chatbot-simulation-evaluation/simulation_utils.py","examples/chatbots/information-gather-prompting.ipynb","examples/code_assistant/langgraph_code_assistant.ipynb","examples/code_assistant/langgraph_code_assistant_mistral.ipynb","examples/customer-support/customer-support.ipynb","examples/delta-channel-dump/README.md","examples/delta-channel-dump/dump.py","examples/extraction/retries.ipynb","examples/human_in_the_loop/wait-user-input.ipynb","examples/lats/lats.ipynb","examples/llm-compiler/LLMCompiler.ipynb","examples/multi_agent/hierarchical_agent_teams.ipynb","examples/multi_agent/multi-agent-collaboration.ipynb","examples/plan-and-execute/plan-and-execute.ipynb","examples/rag/langgraph_adaptive_rag.ipynb","examples/rag/langgraph_adaptive_rag_cohere.ipynb","examples/rag/langgraph_adaptive_rag_local.ipynb","examples/rag/langgraph_agentic_rag.ipynb","examples/rag/langgraph_crag.ipynb","examples/rag/langgraph_crag_local.ipynb","examples/rag/langgraph_self_rag.ipynb","examples/rag/langgraph_self_rag_local.ipynb","examples/rag/langgraph_self_rag_pinecone_movies.ipynb","examples/react-agent-from-scratch.ipynb","examples/react-agent-structured-output.ipynb","examples/reflection/reflection.ipynb","examples/reflexion/reflexion.ipynb","examples/rewoo/rewoo.ipynb","examples/run-id-langsmith.ipynb","examples/self-discover/self-discover.ipynb","examples/subgraph.ipynb","examples/tool-calling.ipynb","examples/tutorials/sql-agent.ipynb","examples/tutorials/tnt-llm/tnt-llm.ipynb","examples/usaco/usaco.ipynb","examples/web-navigation/web_voyager.ipynb","libs/checkpoint-conformance/Makefile","libs/checkpoint-conformance/README.md","libs/checkpoint-conformance/langgraph/checkpoint/conformance/__init__.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/capabilities.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/initializer.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/report.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/__init__.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/_delta_fixtures.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_copy_thread.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_delete_for_runs.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_delete_thread.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_delta_channel_history.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_get_tuple.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_list.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_prune.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_put.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_put_writes.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/test_utils.py","libs/checkpoint-conformance/langgraph/checkpoint/conformance/validate.py","libs/checkpoint-conformance/pyproject.toml","libs/checkpoint-conformance/tests/test_validate_memory.py","libs/checkpoint-conformance/uv.lock","libs/checkpoint-postgres/LICENSE","libs/checkpoint-postgres/Makefile","libs/checkpoint-postgres/README.md","libs/checkpoint-postgres/langgraph/checkpoint/postgres/__init__.py","libs/checkpoint-postgres/langgraph/checkpoint/postgres/_ainternal.py","libs/checkpoint-postgres/langgraph/checkpoint/postgres/_internal.py","libs/checkpoint-postgres/langgraph/checkpoi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