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@lvrged/yt

v0.1.0

Published

YouTube research pipeline for Pi: headless yt-dlp search, audio-only download, and speech-to-text transcription with an interchangeable backend (OpenRouter, OpenAI, Groq, or local whisper.cpp). Search a topic and get transcribed research-ready text in one

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Links

Maintainers

frontier-operatorsfrontier-operators

Keywords

pi-packageyoutubeyt-dlptranscriptionwhispervoice-to-textresearch

Readme

@lvrged/yt

YouTube research pipeline for Pi: headless search, audio-only download, and speech-to-text transcription. The voice-to-text backend is interchangeable — bring OpenRouter, OpenAI, Groq, or a local whisper.cpp and flip a switch.

It's the "make YouTube into a research brief" workflow:

pick a topic → yt_scrape_topic → transcribed, source-cited text for a brief

Latest: v0.1.0

Install

pipkg install   # or
npx -y @lvrged/yt  # actually: add to pi settings.json packages

Add to your Pi settings packages:

"packages": ["npm:@lvrged/yt"]

Requires yt-dlp and ffmpeg on PATH, and at least one STT credential.

Tools

  • yt_find — headless YouTube search (no API key), returns ranked results.
  • yt_transcribe — one video → verbatim transcript.
  • yt_scrape_topic — search + filter + transcribe N videos into one research pack.
  • yt_info — which STT backends are available, and the effective default.

Interchangeable STT

Transcription uses whichever backend the host already has:

| backend id | key / prereq | endpoint | notes | |---|---|---|---| | openrouter-chat | OPENROUTER_API_KEY or ~/.pi/agent/auth.json#openrouter.key | chat-completions input_audio | default; no whisper models exist on OpenRouter | | groq-api | GROQ_API_KEY | /audio/transcriptions | whisper-large-v3-turbo; fastest $/min | | openai-api | OPENAI_API_KEY | /audio/transcriptions | whisper-1 / gpt-4o-mini-transcribe | | whisper-cpp | whisper-cli on PATH + a ggml model | local | offline, free; set YT_WHISPER_MODEL |

Switch via the transcriber tool param, or YT_TRANSCRIBER env (e.g. YT_TRANSCRIBER=groq-api). Auto-detect picks the first one present.

Development

npm install        # dev deps for typechecking
npm run check      # tsc --noEmit
npm run publish:patch  # bump + publish

The package is a standard pi package: extension/ for tools, skills/ for the skill doc. Transcription lives in extension/transcribers.ts — a provider Registry with a shared contract, so adding a backend is a ~40-line adapter.