LangGraph
Low-level graph-based agent orchestration from the LangChain team — explicit state, loops, and human-in-the-loop control.
Pros
- Explicit control over agent flow — nodes, edges, and shared state instead of a hidden agent loop
- Graph state model handles cycles, branching, and human-in-the-loop pauses cleanly
- Built-in checkpointing and persistence for long-running, resumable agents
- Model-agnostic — works with OpenAI, Anthropic, open, and local models via adapters
- MIT licensed and self-hostable; runs as a Python or TypeScript library
Cons
- Code-first with a real learning curve — non-developers should not start here
- Lower-level than most frameworks; you assemble more of the plumbing yourself
- Naming overlap with LangChain confuses newcomers about which to use when
- Smaller ready-made connector catalog than the LangChain framework it sits under
- Overkill for a single LLM call or a simple linear chain
Best for
- Engineering teams who need fine control over agent control flow and state
- Long-running agents with loops, branching, and human-in-the-loop steps
- Teams already in the LangChain ecosystem wanting low-level orchestration primitives
What it is
LangGraph is a low-level orchestration framework from the LangChain team for building stateful, controllable agents. It models an agent as a graph of nodes and edges over a shared, persisted state, giving explicit control over loops, branching, human-in-the-loop pauses, and checkpointing — the control-flow primitives higher-level frameworks tend to hide.
Who it’s for
Choose LangGraph when you think in graphs and want to own every step of the agent’s control flow: backend and platform teams building long-running, resumable agents, and teams already on LangChain that have outgrown the default agent loop. If you want a visual canvas or a one-line agent, start elsewhere.
FAQ
- Is LangGraph free?
- LangGraph has a free tier or open-source edition. See pricing details on the official site for paid features and usage limits.
- What is LangGraph best for?
- Engineering teams who need fine control over agent control flow and state Long-running agents with loops, branching, and human-in-the-loop steps Teams already in the LangChain ecosystem wanting low-level orchestration primitives
- What are the main downsides of LangGraph?
- Code-first with a real learning curve — non-developers should not start here Lower-level than most frameworks; you assemble more of the plumbing yourself Naming overlap with LangChain confuses newcomers about which to use when
- Who should use LangGraph?
- Low-level graph-based agent orchestration from the LangChain team — explicit state, loops, and human-in-the-loop control. See our review for the full pros and cons.