---
title: LangWatch
slug: /integrations-langwatch
---

[LangWatch](https://app.langwatch.ai/) is an all-in-one LLMOps platform for monitoring, observability, analytics, evaluations and alerting for getting user insights and improve your LLM workflows.

## Integrate LangWatch observability

:::note LangWatch is unavailable in the default Docker images
The official Langflow Docker images (`langflowai/langflow` and `langflowai/langflow-nightly`) run on Python 3.14, and the `langwatch` package doesn't yet support Python 3.14 (it requires Python `<3.14`). As a result, LangWatch tracing is **not available in the default Docker images** even when `LANGWATCH_API_KEY` is set. Langflow logs a warning on the first flow run and continues without LangWatch tracing.

To use LangWatch, run Langflow on Python 3.10–3.13, such as the PyPI distribution (`pip install langflow`) or the Langflow desktop app. If you need a container, build a custom image on a Python 3.10–3.13 base.
:::

To integrate with Langflow, add your LangWatch API key as a Langflow environment variable:

1. Get a LangWatch API key from your LangWatch account.

2. Add the key to your Langflow `.env` file:

    ```shell
    LANGWATCH_API_KEY="API_KEY_STRING"
    ```

    Alternatively, you can set the environment variable in your terminal session:

    ```shell
    export LANGWATCH_API_KEY="API_KEY_STRING"
    ```

3. Restart Langflow with your `.env` file, if you modified the Langflow `.env`:

    ```
    langflow run --env-file .env
    ```

4. Run a flow.

5. View the LangWatch dashboard for monitoring and observability.

![LangWatch dashboard](/img/langwatch-dashboard.png)

## Use the LangWatch Evaluator

In your flows, you can use the **LangWatch Evaluator** component to use LangWatch's evaluation endpoints to assess a model's performance.
This component is available in the **LangWatch** [bundle](/components-bundle-components).