LangGraph
A stateful agent runtime published by LangChain Inc, usable without the LangChain components. It decides how steps run: in a line, in a loop, with state that survives from one step to the next, conditional routing and cross-turn persistence.
Strengths
- Cyclic graphs: agents can loop, re-evaluate, and change strategy mid-run
- Built-in persistence: cross-turn memory, checkpoints, state snapshots
- Native human-in-the-loop: pause agent for human validation, then resume
- Native streaming: each graph node streams its output in real-time
- LangGraph Platform: persistent agent deployment in production (hosted)
- Usable without LangChain: the official documentation says so, you plug your own model and tool calls into the runtime
Limitations
- Increased complexity vs simple chains, debugging cyclic graphs is non-trivial
- LangGraph Platform (hosted) is paid, self-hosting requires infra work
- Overkill for simple agents (question → tool call → response)
Best for
- Multi-step agents with memory, loops, and human validation
- Complex LLM workflows: iterative search, planning, self-correction
- Enterprise chatbots requiring persistent state across sessions