LangWatch

LangWatch 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:

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   LANGWATCH_API_KEY="API_KEY_STRING"
   

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

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   export LANGWATCH_API_KEY="API_KEY_STRING"
   

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

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   langflow run --env-file .env
   

4. Run a flow.

5. View the LangWatch dashboard for monitoring and observability.

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.