langgraph

LangGraph Agent Builder

Quick Decision: Which API?

create_agent Quick Start

from langchain.agents import create_agent
from langchain.tools import tool
from langgraph.checkpoint.memory import InMemorySaver

@tool
def search(query: str) -> str:
    """Search for information."""
    return f"Results for: {query}"

agent = create_agent(
    model="claude-sonnet-4-5-20250929",
    tools=[search],
    system_prompt="You are a helpful assistant.",
    checkpointer=InMemorySaver(),  # Required for memory/HITL
)

# Invoke with thread_id for conversation memory
result = agent.invoke(
    {"messages": [{"role": "user", "content": "Search for LangGraph docs"}]},
    config={"configurable": {"thread_id": "user-123"}}
)

StateGraph Quick Start

from typing import Annotated
from typing_extensions import TypedDict
from langchain.messages import AnyMessage
from langchain.chat_models import init_chat_model
from langchain.tools import tool
from langgraph.graph import StateGraph, START, END
from langgraph.graph.message import add_messages
from langgraph.checkpoint.memory import InMemorySaver

# 1. Define state - MUST be TypedDict
class State(TypedDict):
    messages: Annotated[list[AnyMessage], add_messages]  # Reducer appends

# 2. Define tools
@tool
def multiply(a: int, b: int) -> int:
    """Multiply two numbers."""
    return a * b

tools = [multiply]
model = init_chat_model("claude-sonnet-4-5-20250929").bind_tools(tools)

# 3. Define nodes
def call_model(state: State):
    return {"messages": [model.invoke(state["messages"])]}

def call_tools(state: State):
    from langchain.messages import ToolMessage
    last = state["messages"][-1]
    results = []
    for tc in last.tool_calls:
        tool_fn = {t.name: t for t in tools}[tc["name"]]
        results.append(ToolMessage(content=str(tool_fn.invoke(tc["args"])), tool_call_id=tc["id"]))
    return {"messages": results}

# 4. Define routing
def should_continue(state: State):
    if state["messages"][-1].tool_calls:
        return "tools"
    return END

# 5. Build graph
graph = (
    StateGraph(State)
    .add_node("model", call_model)
    .add_node("tools", call_tools)
    .add_edge(START, "model")
    .add_conditional_edges("model", should_continue, ["tools", END])
    .add_edge("tools", "model")
    .compile(checkpointer=InMemorySaver())
)