LangGraph — Stateful AI Agent Graphs by LangChain

Core Concepts

State Graph

Define your workflow as a directed graph:

graph = StateGraph(AgentState)
graph.add_node("plan", plan_step)
graph.add_node("execute", execute_step)
graph.add_node("review", review_step)

# Conditional routing
graph.add_conditional_edges("review", decide_next, {
    "revise": "execute",   # Loop back if needs revision
    "approve": END          # Finish if approved
})

Cycles (Agent Loops)

LangGraph supports loops — agents can iterate until satisfied:

plan → execute → review → execute → review → approve → END
                  ↑___________|
                  (revision loop)

Human-in-the-Loop

Pause execution for human approval:

from langgraph.checkpoint import MemorySaver

graph.add_node("human_review", interrupt_before=True)

# Agent pauses here, human reviews, then continues
app = graph.compile(checkpointer=MemorySaver())

Persistence

Checkpoint state for resuming later:

from langgraph.checkpoint.postgres import PostgresSaver

checkpointer = PostgresSaver(connection_string="...")
app = graph.compile(checkpointer=checkpointer)

# Resume from any checkpoint
result = app.invoke(None, config={"thread_id": "task-123"})

Multi-Agent Patterns

# Supervisor pattern: one agent delegates to specialists
supervisor = create_supervisor(
    agents=[researcher, coder, reviewer],
    model="claude-sonnet-4-20250514"
)

# Each agent is a subgraph node
graph.add_node("supervisor", supervisor)
graph.add_node("researcher", researcher_graph)
graph.add_node("coder", coder_graph)

Key Stats

• 8,000+ GitHub stars
• By LangChain team
• Cycles and conditional branching
• Persistent checkpointing
• Human-in-the-loop support

FAQ

Q: What is LangGraph? A: LangGraph is a framework for building stateful AI agent applications as directed graphs with support for cycles, branching, persistence, and human-in-the-loop workflows.

Q: Is LangGraph free? A: Yes, open-source under MIT license. LangGraph Platform (managed hosting) is paid.

Q: How is LangGraph different from CrewAI? A: LangGraph uses graph-based control flow with explicit state management. CrewAI uses role-based agents with implicit orchestration. LangGraph offers finer-grained control.