{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/9"},{"label":"Sound/Audio","url":"https://skillfed.io/packages/category/multimedia-sound-audio"},{"label":"Video","url":"https://skillfed.io/packages/category/multimedia-video"},{"label":"Conferencing","url":"https://skillfed.io/packages/category/communications-conferencing"}],"enrichment":{"capability":"Whisker is a real-time debugger for Pipecat voice and multimodal AI applications that lets you inspect workers, pipelines, jobs, and message flow across a multi-agent system through a graphical UI.","skillfed_tags":["pipecat-ecosystem","debugging-ui","multi-agent-systems"],"use_cases":["Debug message flow and frame routing through complex multi-worker Pipecat pipelines during development","Inspect job queues and worker state to diagnose deadlocks or unexpected behavior in live systems","Record and replay Pipecat sessions for post-mortem analysis or sharing debugging context with teammates","Monitor frame processing in real-time to identify bottlenecks or processors consuming unexpected input","Capture headless Pipecat runs in CI/testing environments by writing events to disk without UI overhead"],"what_it_does":"Whisker is a low-level debugger built specifically for the Pipecat framework, which orchestrates multi-agent voice and multimodal AI systems. It attaches observers to your Pipecat workers to capture and stream frame events, job flows, and bus messages to a graphical interface where you can browse the entire system topology, inspect individual pipelines, filter and trace frames through processors, and save sessions for later replay. The debugger runs as a WebSocket server (default localhost:9090) that the UI connects to\u2014either a hosted version via ngrok tunneling or a local Node.js development server.\n\nYou integrate Whisker by adding a WhiskerServer instance and per-worker WhiskerObserver objects to your Pipecat runner, or by using environment-variable-driven setup files to avoid modifying application code. For CI and headless recording, you can use WhiskerFile instead to write events directly to disk without opening a port. The package is designed as a trace-logging tool with a UI layer, letting you see exactly what every part of a distributed Pipecat system is doing at any moment.","worth_installing":"Yes, if you are actively developing or debugging Pipecat applications. The package is actively maintained, has no known vulnerabilities, installs with low friction, and provides a purpose-built debugging interface for a framework that otherwise lacks built-in introspection. The permissive BSD-2-Clause license poses no restrictions. Install it as a development dependency; the overhead of observers is negligible for debugging but can be disabled in production."},"id":"pipecat-ai-whisker","links":{"html":"https://skillfed.io/packages/pipecat-ai-whisker","md":"https://skillfed.io/packages/pipecat-ai-whisker.md","pypi":"https://pypi.org/project/pipecat-ai-whisker/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-05-29","license_spdx":"BSD-2-Clause","license_treatment":"permissive","name":"pipecat-ai-whisker","python_support":"supports_current","summary":"A real-time debugger for Pipecat"},"popularity":{"monthly_downloads":112004,"position":12386,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.0.0"}