LangGraph

Learn about using Sentry for LangGraph.

This integration connects Sentry with LangGraph in Python.

Once you've installed this SDK, you can use Sentry AI Agents Monitoring, a Sentry dashboard that helps you understand what's going on with your AI requests. Sentry AI Monitoring will automatically collect information about prompts, tools, tokens, and models. Learn more about the AI Agents Dashboard.

Install sentry-sdk from PyPI with the langgraph extra:

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pip install "sentry-sdk[langgraph]"

If you have the langgraph package in your dependencies, the LangGraph integration will be enabled automatically when you initialize the Sentry SDK. For correct token accounting, you need to disable the integration for the model provider you are using (e.g. OpenAI or Anthropic).

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import sentry_sdk
from sentry_sdk.integrations.openai import OpenAIIntegration

sentry_sdk.init(
    dsn="https://examplePublicKey@o0.ingest.sentry.io/0
example-org / example-project
",
    environment="local",
    traces_sample_rate=1.0,
    send_default_pii=True,
    disabled_integrations=[OpenAIIntegration()],
)

Verify that the integration works by creating a LangGraph workflow and executing it. In these examples, we're creating a simple agent graph that can use a function tool to roll a die.

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import os
import random
from typing import Annotated, Literal, TypedDict

from langchain.chat_models import init_chat_model
from langchain_core.messages import AnyMessage, HumanMessage
from langchain_core.tools import tool
from langgraph.graph import END, StateGraph
from langgraph.graph.message import add_messages
from langgraph.prebuilt import ToolNode


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

@tool
def roll_die(sides: int = 6) -> str:
    """Roll a die with a given number of sides"""
    return f"Rolled a {random.randint(1, sides)} on a {sides}-sided die."

def chatbot(state: State):
    model = init_chat_model("gpt-4o-mini", model_provider="openai")
    return {"messages": [model.bind_tools([roll_die]).invoke(state["messages"])]}

def should_continue(state: State) -> Literal["tools", END]:
    last_message = state["messages"][-1]
    return "tools" if getattr(last_message, "tool_calls", None) else END

with sentry_sdk.start_transaction(name="langgraph-openai"):
    graph_builder = StateGraph(State)
    graph_builder.add_node("chatbot", chatbot)
    graph_builder.add_node("tools", ToolNode([roll_die]))
    graph_builder.set_entry_point("chatbot")
    graph_builder.add_conditional_edges("chatbot", should_continue)
    graph_builder.add_edge("tools", "chatbot")
    graph = graph_builder.compile()
    result = graph.invoke({
        "messages": [
            HumanMessage(content="Hello, my name is Alice! Please roll a six-sided die.")
        ]
    })
    print(result)

After running this script, the resulting data should show up in the "AI Spans" tab on the "Explore" > "Traces" page on Sentry.io, and in the AI Agents Dashboard.

It may take a couple of moments for the data to appear in sentry.io.

  • The LangGraph integration will connect Sentry with all supported LangGraph methods automatically.

  • All exceptions are reported.

By adding LangGraphIntegration to your sentry_sdk.init() call explicitly, you can set options for LangGraphIntegration to change its behavior:

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import sentry_sdk
from sentry_sdk.integrations.langgraph import LangGraphIntegration

sentry_sdk.init(
    # ...
    # Add data like inputs and responses;
    # see https://docs.sentry.io/platforms/python/data-management/data-collected/ for more info
    send_default_pii=True,
    integrations=[
        LangGraphIntegration(
            include_prompts=False,  # LLM inputs/outputs will be not sent to Sentry, despite send_default_pii=True
        ),
    ],
)

You can pass the following keyword arguments to LangGraphIntegration():

  • include_prompts

    Controls whether LLM inputs and outputs should be sent to Sentry. Sentry considers this data personal identifiable data (PII) by default. If you want to include the data, set send_default_pii=True in the sentry_sdk.init() call. To explicitly exclude prompts and outputs despite send_default_pii=True, configure the integration with include_prompts=False.

    The default is True.

  • OpenAI: 1.0+
  • Python: 3.9+
  • LangGraph: 0.6+
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