Observability for Pipecat with Langfuse
Pipecat is an open-source Python framework for building real-time voice and multimodal conversational AI agents. Developed by Daily, it provides developers with tools to create interactive voice applications with features like noise cancellation through Krisp integration. Pipecat enables fully programmable AI voice agents and supports multimodal interactions, positioning itself as a flexible solution for developers looking to build conversational AI systems.
This page shows how to connect Pipecat with Langfuse using OpenTelemetry. Follow the steps below or check the end-to-end example in the Pipecat repository.
Obtain Langfuse API keys
Create a project in Langfuse Cloud or self-host Langfuse and copy your API keys.
Configure Pipecat for tracing
Clone the Pipecat repository and navigate to the examples/open-telemetry-tracing-langfuse folder. Copy the env.example file to .env and fill in your Langfuse credentials and service API keys.
Install the required dependencies:
pip install -r requirements.txtRun the demo
Start the example bot to generate traces:
python bot.pyYou can now interact with the bot and see your traces in Langfuse.
For more integrations, see the integration overview.