---
title: "LangChain"
description: "Learn about using Sentry for LangChain."
url: https://docs.sentry.io/platforms/python/integrations/langchain/
---

# LangChain | Sentry for Python

This integration connects Sentry with [LangChain](https://github.com/langchain-ai/langchain) 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](https://docs.sentry.io/ai/monitoring/agents.md).

## [Install](https://docs.sentry.io/platforms/python/integrations/langchain.md#install)

Install `sentry-sdk` from PyPI:

```bash
pip install sentry-sdk
```

## [Configure](https://docs.sentry.io/platforms/python/integrations/langchain.md#configure)

If you have the `langchain` package in your dependencies, the LangChain integration will be enabled automatically when you initialize the Sentry SDK.

```python
import sentry_sdk
from sentry_sdk.integrations.langchain import LangchainIntegration
from sentry_sdk.integrations.openai import OpenAIIntegration

sentry_sdk.init(
    dsn="___PUBLIC_DSN___",
    environment="local",
    traces_sample_rate=1.0,
    send_default_pii=True,
    debug=True,
    integrations=[
        LangchainIntegration(),
    ]
)
```

## [Verify](https://docs.sentry.io/platforms/python/integrations/langchain.md#verify)

Verify that the integration works by initializing a transaction and invoking an agent. In these examples, we're providing a function tool to roll a die.

```python
import random

from langchain.agents import AgentExecutor, create_openai_functions_agent
from langchain.chat_models import init_chat_model
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain_core.tools import tool

@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."


with sentry_sdk.start_transaction(name="langchain-openai"):
    model = init_chat_model(
        "gpt-4o-mini",
        model_provider="openai",
        model_kwargs={"stream_options": {"include_usage": True}},
    )
    tools = [roll_die]
    prompt = ChatPromptTemplate.from_messages(
        [
            SystemMessage(
                content="Greet the user and use the die roll tool. Do not terminate before using the tool."
            ),
            HumanMessage(content="{input}"),
            MessagesPlaceholder("agent_scratchpad"),
        ]
    )

    agent = create_openai_functions_agent(model, tools, prompt)
    agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)

    result = agent_executor.invoke(
        {
            "input": "Hello, my name is Alice! Please roll a six-sided die.",
            "chat_history": [],
        }
    )
    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](https://docs.sentry.io/ai/monitoring/agents.md).

It may take a couple of moments for the data to appear in [sentry.io](https://sentry.io).

## [Behavior](https://docs.sentry.io/platforms/python/integrations/langchain.md#behavior)

* The LangChain integration will connect Sentry with all supported LangChain methods automatically.

* All exceptions are reported.

* Sentry considers LLM and tokenizer inputs/outputs as PII (Personally identifiable information) and doesn't include PII data 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` as shown in the [Options section](https://docs.sentry.io/platforms/python/integrations/langchain.md#options) below.

## [Options](https://docs.sentry.io/platforms/python/integrations/langchain.md#options)

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

```python
import sentry_sdk
from sentry_sdk.integrations.langchain import LangchainIntegration

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=[
        LangchainIntegration(
            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 `LangchainIntegration()`:

* `include_prompts`

  Whether LLM and tokenizer 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`.

## [Supported Versions](https://docs.sentry.io/platforms/python/integrations/langchain.md#supported-versions)

* OpenAI: 1.0+
* Python: 3.9+
* langchain: 0.1.0+