LangGraph
AI AgentsA stateful multi-agent system framework by the LangChain team. Define and manage complex AI agent workflows using graph structures.
What is LangGraph?
LangGraph is an open-source framework for building AI agents and multi-agent systems, developed by the LangChain team. It uses directed graph structures to define AI processing flows, enabling programmatic construction of complex workflows with state management, conditional branching, loops, and parallel processing. LangGraph's defining feature is its stateful design. The results of each step are preserved as state, which subsequent steps can reference for processing. This enables iterative agent workflows — such as decide, act, evaluate, and re-decide — that are impossible with simple chain processing. It supports Human-in-the-Loop (human review and intervention), checkpointing for pause and resume, and streaming output. LangGraph Cloud allows you to deploy built agents at scale. Available in both Python and JavaScript, it integrates easily with the LangChain ecosystem.
Pricing Plans
Key Features
Pros & Cons
Pros
- ●Graph-based structure for flexible complex agent workflow design
- ●Stateful design supporting state management, loops, and conditionals
- ●Built-in Human-in-the-Loop functionality
- ●Strong compatibility with the LangChain ecosystem
- ●Available in both Python and JavaScript
- ●Checkpointing for pause and resume capabilities
Cons
- ●Programming knowledge (Python/JS) is required
- ●Concepts like graphs and state management have a learning curve
- ●Takes longer to build compared to no-code tools
- ●Documentation is primarily in English with limited Japanese resources
Frequently Asked Questions
Q. What is the difference between LangGraph and LangChain?
A. LangChain is a general-purpose framework for LLM application development, while LangGraph is a specialized framework within the LangChain ecosystem focused on building agents and multi-agent systems. Where LangChain's chains are suited for linear processing, LangGraph handles complex workflows with loops and branching.
Q. Is LangGraph suitable for beginners?
A. It's accessible with basic Python knowledge, but requires understanding graph theory and state management concepts. The official tutorials are comprehensive, so we recommend learning step by step. For no-code agent building, Coze or Dify may be more suitable.
Q. What is LangGraph Cloud?
A. LangGraph Cloud is a managed service for deploying and scaling agents built with LangGraph. It provides automatic API endpoint generation, asynchronous execution, and a monitoring dashboard.
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