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Langfuse Integration with Open WebUI

Langfuse (GitHub) offers open source observability and evaluations for Open WebUI. By enabling the Langfuse integration, you can trace your application data with Langfuse to develop, monitor, and improve the use of Open WebUI, including:

  • Application traces
  • Usage patterns
  • Cost data by user and model
  • Replay sessions to debug issues
  • Evaluations

How to integrate Langfuse with Open WebUI​

Langfuse Integration Langfuse integration steps

Pipelines in Open WebUI is an UI-agnostic framework for OpenAI API plugins. It enables the injection of plugins that intercept, process, and forward user prompts to the final LLM, allowing for enhanced control and customization of prompt handling.

To trace your application data with Langfuse, you can use the Langfuse pipeline, which enables real-time monitoring and analysis of message interactions.

Quick Start Guide​

Step 1: Setup Open WebUI​

Make sure to have Open WebUI running. To do so, have a look at the Open WebUI documentation.

Step 2: Set Up Pipelines​

Launch Pipelines by using Docker. Use the following command to start Pipelines:

docker run -p 9099:9099 --add-host=host.docker.internal:host-gateway -v pipelines:/app/pipelines --name pipelines --restart always ghcr.io/open-webui/pipelines:main

Step 3: Connecting Open WebUI with Pipelines​

In the Admin Settings, create and save a new connection of type OpenAI API with the following details:

Open WebUI Settings

Step 4: Adding the Langfuse Filter Pipeline​

Next, navigate to Admin Settings -> Pipelines and add the Langfuse Filter Pipeline. Specify that Pipelines is listening on http://host.docker.internal:9099 (as configured earlier) and install the Langfuse Filter Pipeline by using the Install from Github URL option with the following URL:

https://github.com/open-webui/pipelines/blob/main/examples/filters/langfuse_filter_pipeline.py

Now, add your Langfuse API keys below. If you haven't signed up to Langfuse yet, you can get your API keys by creating an account here.

Open WebUI add Langfuse Pipeline

Note: Capture usage (token counts) for OpenAi models while streaming is enabled, you have to navigate to the model settings in Open WebUI and check the "Usage" box below Capabilities.

Step 5: See your traces in Langfuse​

You can now interact with your Open WebUI application and see the traces in Langfuse.

Example trace in the Langfuse UI:

Open WebUI Example Trace in Langfuse

Learn more​

For a comprehensive guide on Open WebUI Pipelines, visit this post.