pipecat-ai-whisker 0.0.8

A real-time debugger for Pipecat

ᓚᘏᗢ Whisker: A Pipecat Debugger

Whisker is a live graphical debugger for the Pipecat voice and multimodal conversational AI framework.

It lets you visualize pipelines and debug frames in real time — so you can see exactly what your bot is thinking and doing.

With Whisker you can:

• 🗺️ View a live graph of your pipeline
• ⚡ Watch frame processors flash in real time as frames pass through them
• 📌 Select a processor to inspect the frames it has handled (both pushed and processed)
• 🔍 Filter frames by name to quickly find the ones you care about
• 🧵 Select a frame to trace its full path through the pipeline
• 💾 Save and load previous sessions for review, collaboration, or troubleshooting

Think of Whisker as trace logging with batteries.

🧭 Getting started

Requirements:

• Python 3.10+
• Pipecat installed
• Node.js 20+ (for the UI)

1. Install Whisker for Python

uv pip install pipecat-ai-whisker

2. Add Whisker to your Pipecat pipeline

from pipecat_whisker import WhiskerObserver

pipeline = Pipeline(...)

whisker = WhiskerObserver(pipeline)

task = PipelineTask(..., observers=[whisker])

This starts the Whisker server that the graphical UI will connect to. By default, the Whisker server runs at:

ws://localhost:9090

💾 Saving sessions

You can also save your sessions to a file, which is helpful for debugging later or sharing with someone for assistance:

whisker = WhiskerObserver(pipeline, file_name="whisker.bin")

Load the file using the Whisker client.

🚀 Running the client

Clone the repository:

git clone https://github.com/pipecat-ai/whisker.git

Then, start Whisker with:

cd ui
npm install
npm run dev

and connect to http://localhost:5173.

📚 Next steps

• View some examples in the examples folder
• See the Pipecat documentation for more about building bots