langchain-ai/langgraph

Project overview

A framework that provides low-level infrastructure for building long-running, stateful agents. It offers durable execution, human-in-the-loop interactions, and comprehensive memory for managing persistent workflows.

Project type

Workflow

Use cases

Automation

Deployment

Library integration

License

MIT

Best for

• Developers and enterprise teams who need low-level infrastructure for long-running, stateful agents.

Key capabilities

• Enables the creation of stateful agents featuring short-term working memory for ongoing reasoning alongside long-term persistent memory across sessions.

Limitations and risks

• Requires coding to build and manage agents, functioning as a developer library.
• Telemetry, GPU requirements, and minimum hardware specifications are not documented.

Getting started

• The framework is easy to install quickly via pip, with a first success path of pip install -U langgraph.

Evidence and sources

• GitHub project description: Build resilient agents.
• README: LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents.
• README: While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents.
• README: Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off.
• README: Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution.

Reviewed at: 2026-07-17T08:50:16Z