LangGraph
by LangChain, Inc.
Low-level framework for stateful, durable, graph-based LLM agents
Last reviewed 2026-06-18
LangGraph is an open-source (MIT-licensed) framework from LangChain for building stateful, multi-actor applications with LLMs as graphs. It is a low-level orchestration layer for long-running, controllable agents: you model an agent as a graph of nodes (steps) and edges (transitions) with shared state, which makes loops, branching, and multi-agent routing explicit and inspectable. Its differentiators are durable execution (agents persist through failures and resume from where they left off), checkpointing that records every state transition as a navigable history you can rewind and fork like Git commits, and first-class human-in-the-loop interrupts that pause the graph so a person can inspect, edit state, and resume. As a framework, LangGraph supplies the runtime and primitives; the autonomy of any agent is determined by the developer's design and where they place human checkpoints. The core library is free and model-agnostic; LangChain Inc. sells the hosted LangGraph Platform for deploying and scaling agents, with observability via LangSmith.
What it can do
Build agents as stateful graphs
SupervisedModel an agent as nodes and edges over shared state, making loops, branching, and multi-actor flows explicit and controllable; the resulting autonomy is developer-defined.
sourceRun durable, resumable execution
SupervisedAgents persist through failures and can run for extended periods, automatically resuming from exactly where they left off.
sourceCheckpoint and time-travel state
SupervisedMaintain a complete history of every state transition that can be navigated like Git commits to inspect, rewind to, and fork from any prior state.
sourceAdd human-in-the-loop interrupts
SupervisedBuilt-in interrupt points pause the graph so a human can inspect and modify agent state, then resume from the exact same spot.
source
Strengths
- +Explicit graph model makes complex agent control flow (loops, branching, multi-agent routing) inspectable and controllable
- +Production-grade primitives: durable execution, checkpointing/time-travel, and first-class human-in-the-loop interrupts
- +Open source and model-agnostic, with a hosted LangGraph Platform and LangSmith observability for deployment
Limitations
- −Lower-level and more verbose than higher-level agent libraries; a steeper learning curve
- −Framework, not a product: autonomy and quality depend entirely on what the developer builds
- −Most production value (hosted deployment, observability) lives in the paid LangSmith/LangGraph Platform tiers
Overview
LangGraph is LangChain's open-source, low-level framework for building stateful, durable LLM agents as graphs. It is developer infrastructure, not an end-user product.
What it does
Developers model an agent as a graph of nodes (steps) and edges (transitions) over shared state, making loops, branching, and multi-agent routing explicit and inspectable. Its standout primitives are durable execution (resume after failures), checkpointing with time-travel (navigate, rewind, and fork state like Git commits), and first-class human-in-the-loop interrupts that pause the graph for inspection and editing. The autonomy of any agent is determined by the developer's design and checkpoint placement.
Integrations & setup
Model-agnostic (OpenAI, Anthropic, Google, and others), with function calling and MCP for tools, and LangSmith for tracing and evaluation. The library runs anywhere; the LangGraph Platform is the managed deployment service.
Pricing
The framework is free and MIT-licensed. The hosted LangGraph Platform is accessed through LangSmith, which is freemium: a free Developer tier with a trace allowance, and paid Plus and Enterprise tiers (Plus reportedly around $39/user/month).
Best for / not for
Best for developers building long-running, stateful, controllable agents that need durability and human checkpoints. Less suited to those wanting a quick high-level agent or a no-code product.
Alternatives
LangChain is the broader framework it underpins; CrewAI offers role-based multi-agent crews; AutoGen centers on multi-agent conversation.
What people are saying
We aggregate real LinkedIn discussion into sentiment for the agents people search most. LangGraph isn't tracked yet, want it added? Request tracking.
FAQ
What is the difference between LangGraph and LangChain?+
LangChain is the broader framework with quick-start agents and integrations; LangGraph is the lower-level, durable runtime for controllable, stateful agent workflows. LangChain's agents are built on LangGraph primitives.
Is a LangGraph agent autonomous?+
LangGraph is a framework, not an agent. Autonomy is determined by the developer's graph design and where they place human-in-the-loop interrupts. Its primitives are built to support controlled, supervised, and human-gated execution as well as more autonomous loops.
Sources
- LangGraph (official) · accessed 2026-06-18
- langchain-ai/langgraph on GitHub · accessed 2026-06-18
- Human-in-the-loop (LangChain docs) · accessed 2026-06-18
- LangSmith plans and pricing (official) · accessed 2026-06-18
Last reviewed 2026-06-18