How to combine control flow and state updates with Command¶

Prerequisites

This guide assumes familiarity with the following:

It can be useful to combine control flow (edges) and state updates (nodes). For example, you might want to BOTH perform state updates AND decide which node to go to next in the SAME node. LangGraph provides a way to do so by returning a Command object from node functions:

def my_node(state: State) -> Command[Literal["my_other_node"]]:
    return Command(
        # state update
        update={"foo": "bar"},
        # control flow
        goto="my_other_node"
    )

This guide shows how you can do use Command to add dynamic control flow in your LangGraph app.

Setup¶

First, let's install the required packages

%%capture --no-stderr
%pip install -U langgraph

Set up LangSmith for LangGraph development

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Let's create a simple graph with 3 nodes: A, B and C. We will first execute node A, and then decide whether to go to Node B or Node C next based on the output of node A.

Define graph¶

import random
from typing_extensions import TypedDict, Literal

from langgraph.graph import StateGraph, START
from langgraph.types import Command


# Define graph state
class State(TypedDict):
    foo: str


# Define the nodes


def node_a(state: State) -> Command[Literal["node_b", "node_c"]]:
    print("Called A")
    value = random.choice(["a", "b"])
    # this is a replacement for a conditional edge function
    if value == "a":
        goto = "node_b"
    else:
        goto = "node_c"

    # note how Command allows you to BOTH update the graph state AND route to the next node
    return Command(
        # this is the state update
        update={"foo": value},
        # this is a replacement for an edge
        goto=goto,
    )


# Nodes B and C are unchanged


def node_b(state: State):
    print("Called B")
    return {"foo": state["foo"] + "b"}


def node_c(state: State):
    print("Called C")
    return {"foo": state["foo"] + "c"}

API Reference: StateGraph | START

We can now create the StateGraph with the above nodes. Notice that the graph doesn't have conditional edges for routing! This is because control flow is defined with Command inside node_a.

builder = StateGraph(State)
builder.add_edge(START, "node_a")
builder.add_node(node_a)
builder.add_node(node_b)
builder.add_node(node_c)
# NOTE: there are no edges between nodes A, B and C!

graph = builder.compile()

Important

You might have noticed that we used Command as a return type annotation, e.g. Command[Literal["node_b", "node_c"]]. This is necessary for the graph rendering and tells LangGraph that node_a can navigate to node_b and node_c.

from IPython.display import display, Image

display(Image(graph.get_graph().draw_mermaid_png()))

If we run the graph multiple times, we'd see it take different paths (A -> B or A -> C) based on the random choice in node A.

graph.invoke({"foo": ""})

Called A
Called C

{'foo': 'bc'}

How to combine control flow and state updates with Command¶

Setup¶

Define graph¶

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