Skip to main content

A real-time debugger for Pipecat

Project description

whisker

PyPI Discord

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.

Think of Whisker as trace logging with batteries.

Whisker

🧭 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

🚀 Running the debugger UI

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pipecat_ai_whisker-0.0.1.tar.gz (136.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pipecat_ai_whisker-0.0.1-py3-none-any.whl (7.4 kB view details)

Uploaded Python 3

File details

Details for the file pipecat_ai_whisker-0.0.1.tar.gz.

File metadata

  • Download URL: pipecat_ai_whisker-0.0.1.tar.gz
  • Upload date:
  • Size: 136.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for pipecat_ai_whisker-0.0.1.tar.gz
Algorithm Hash digest
SHA256 7e8551b76f6a6b5cbd48ac3d1d009b0aa25763951bfaad73e0aaceff6a6e0465
MD5 12349750ae7798a599f29ddb2d841aba
BLAKE2b-256 1fd1ed5cf279dc16b039afa68171b1c31b3933ca3a0639489bdcd4c4be0a8922

See more details on using hashes here.

Provenance

The following attestation bundles were made for pipecat_ai_whisker-0.0.1.tar.gz:

Publisher: publish.yaml on pipecat-ai/whisker

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file pipecat_ai_whisker-0.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for pipecat_ai_whisker-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 39b9d97714508238ed4969dc4637005769767333cde9be30fbd3734c3c68a0ce
MD5 a2c937593d28a6c9a785a05cbeffe7f2
BLAKE2b-256 45d49a1d6451528abec6fc8247f42744a33a2213f575a9f22eae5aa3d323615b

See more details on using hashes here.

Provenance

The following attestation bundles were made for pipecat_ai_whisker-0.0.1-py3-none-any.whl:

Publisher: publish.yaml on pipecat-ai/whisker

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page