langchain-ai/langgraphjs
Framework to build resilient language agents as graphs.
What it solves
LangGraphjs provides a low-level orchestration framework for building controllable, stateful AI agents. It addresses the need for customizable agent architectures that can handle complex, long-running tasks which require persistence, memory, and human oversight—capabilities that go beyond simple linear LLM chains.
How it works
It acts as an infrastructure layer for stateful workflows, allowing developers to define agent logic as a graph. It supports durable execution to resume tasks after failures, implements comprehensive memory (both short-term working memory and long-term persistent memory), and allows for human-in-the-loop interactions where users can inspect or modify the agent's state during execution.
Who it’s for
It is designed for developers building sophisticated AI agents and long-running LLM applications that require high levels of control, reliability, and the ability to maintain state across sessions.
Highlights
- Durable Execution: Agents can persist through failures and automatically resume from the exact point of interruption.
- Human-in-the-Loop: Enables human oversight by allowing the inspection and modification of agent state during runtime.
- Comprehensive Memory: Supports both short-term reasoning memory and long-term persistence across different sessions.
- LangSmith Integration: Provides deep visibility into agent behavior through execution tracing and state transition capture.
- Flexible Architecture: Can be used as a standalone library or integrated with the broader LangChain ecosystem.