LangGraph iconLangGraph

open-source Open-core Star34k

Low-level orchestration framework for building stateful, long-running agents with human-in-the-loop controls

33.7K GitHub Stars
5.7K Forks
MIT License

Overview

LangGraph is a low-level orchestration framework from LangChain for building stateful, long-running AI agents. Unlike simple chain-based approaches, LangGraph models agent workflows as graphs with nodes (actions) and edges (transitions), enabling complex multi-step reasoning with full control over execution flow. It provides durable execution that persists through failures, comprehensive memory management, and first-class human-in-the-loop support for reviewing and modifying agent state at any point. Trusted by companies like Klarna, LinkedIn, Elastic, and ServiceNow, LangGraph is designed for production-grade agents that need reliability and observability.

The Verdict

Who Should Use LangGraph?

Best For

  • Building production-grade stateful agents
  • Complex multi-step workflows with branching
  • Teams needing human-in-the-loop controls
  • Long-running tasks requiring durability
  • Developers wanting fine-grained control

Not Ideal For

  • Simple chatbots (use LangChain directly)
  • No-code builders (try CrewAI Studio)
  • Quick prototypes (steeper learning curve)
  • Teams without Python/TS experience

What's Great

  • Durable execution persists through failures
  • First-class human-in-the-loop support
  • Graph-based control flow is highly flexible
  • Comprehensive state management and memory
  • Works with any LLM provider
  • Strong LangSmith integration for debugging
  • Active community and extensive docs

Watch Out For

  • Steeper learning curve than alternatives
  • Verbose code for simple use cases
  • Cloud platform adds cost for deployment
  • Breaking changes between versions
  • Debugging complex graphs can be challenging

Pricing

View all features & details

Core Features

  • Graph-based workflow orchestration
  • Durable execution with auto-resume
  • Human-in-the-loop interrupts
  • Short-term and long-term memory
  • State persistence and checkpointing
  • Conditional branching and cycles
  • Subgraphs for modular design
  • Streaming support

Languages & SDKs

  • Python (primary)
  • TypeScript/JavaScript
  • REST API for deployment

Integrations

  • LangSmith observability
  • LangChain components
  • Any LLM provider (OpenAI, Anthropic, etc.)
  • LangSmith Deployment platform
  • Deep Agents (higher-level package)

Enterprise Features

  • SSO/SAML authentication
  • Role-based access control
  • Dedicated infrastructure
  • Priority support
  • Custom SLAs

Real-World Usage

Community Stats

  • 5,600+ forks
  • 560+ open issues
  • Active LangChain Forum
  • Free LangChain Academy course

Production Users

  • Klarna - Financial services
  • LinkedIn - Professional networking
  • Elastic - Search & observability
  • ServiceNow - Enterprise workflows
  • Uber - Transportation platform

How It Compares

Feature LangGraph LangChain CrewAI AutoGen
GitHub Stars 33.7K 138K 52.7K 58.6K
Approach Graph-based Chain-based Role-based Conversation
State Management Built-in Limited Basic Basic
Human-in-the-Loop First-class Manual Basic Basic
Learning Curve Steeper Moderate Easy Moderate
Flexibility Highest High Medium Medium
Best For Complex agents LLM chains Multi-agent teams Chat agents
License MIT MIT MIT CC-BY-4.0

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