pipecat-ai-whisker 0.0.10

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)
• ngrok (for connecting to the hosted UI)

Install Whisker for Python

uv pip install pipecat-ai-whisker

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

🌐 Option A: Use the hosted UI (Recommended)

1. Expose your local server with ngrok:

   ngrok http 9090
   

2. Copy the ngrok URL (e.g., your-ngrok-url.ngrok.io)

3. Open the hosted Whisker UI: https://whisker.pipecat.ai/

4. Connect to your bot:

   • In the WebSocket URL field, enter: wss://your-ngrok-url.ngrok.io
   • Click connect

🏠 Option B: Run the UI locally

If you prefer to run the UI locally:

1. Clone the repository:

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

2. Start the UI:

   cd whisker/ui
   npm install
   npm run dev
   

3. Connect to http://localhost:5173

The UI will automatically connect to ws://localhost:9090 by default.

💾 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.

📚 Next steps

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