LangGraph Tutor Skill

Expert guidance for building production AI agents with LangGraph.

Quick Start

from langgraph.graph import StateGraph, START, END from typing import Annotated from typing_extensions import TypedDict from langgraph.graph.message import add_messages

class State(TypedDict): messages: Annotated[list, add_messages]

def chatbot(state: State): return {"messages": [llm.invoke(state["messages"])]}

graph = StateGraph(State) graph.add_node("chatbot", chatbot) graph.add_edge(START, "chatbot") graph.add_edge("chatbot", END) app = graph.compile()

Core Concepts

1. State Definition

State flows through the graph. Use TypedDict with optional reducers:

class State(TypedDict): messages: Annotated[list, add_messages] # Accumulates context: str # Overwrites count: Annotated[int, operator.add] # Sums

2. Nodes

Functions that receive state and return updates:

def my_node(state: State) -> dict: # Read from state messages = state["messages"] # Return updates (don't mutate!) return {"context": "new value"}

3. Edges

Connect nodes in the graph:

graph.add_edge(START, "node_a") # Entry point graph.add_edge("node_a", "node_b") # Linear flow graph.add_edge("node_b", END) # Exit point

4. Conditional Routing

Route based on state:

def router(state: State) -> Literal["path_a", "path_b"]: if condition: return "path_a" return "path_b"

graph.add_conditional_edges("source", router)

5. Memory/Checkpointing

Persist state across invocations:

from langgraph.checkpoint.memory import InMemorySaver

memory = InMemorySaver() app = graph.compile(checkpointer=memory)

config = {"configurable": {"thread_id": "user-123"}} result = app.invoke({"messages": [msg]}, config)

6. Human-in-the-Loop

Pause for human input:

from langgraph.types import interrupt

def approval_node(state): response = interrupt({"question": "Approve?"}) return {"approved": response["answer"]}

Common Patterns

ReAct Agent (Reasoning + Acting)

See references/patterns.md for full implementation.

Supervisor Multi-Agent

See references/multi-agent.md for patterns.

Tool Calling

See references/tools.md for integration.

Validation

Run the validation script to check your graph:

python scripts/validate_graph.py your_graph.py

Examples

Working examples in examples/:

• simple_chatbot.py

• Minimal chatbot

• tool_agent.py

• Agent with tools

• multi_agent.py

• Supervisor pattern

Common Errors

Error Cause Fix

"Node has no outgoing edge" Missing edge Add edge to END or next node

"State key not found" Accessing undefined key Check State TypedDict

"Cannot serialize" Complex objects in state Use JSON-serializable types

Resources

• LangGraph Docs

• Tutorials

• API Reference