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Add dedicated video and audio corpus section to README

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Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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2026-04-10 16:22:53 +01:00
co-authored by Claude Sonnet 4.6
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@@ -255,6 +255,31 @@ Works with any mix of file types:
| Video / Audio | `.mp4 .mov .mkv .webm .avi .m4v .mp3 .wav .m4a .ogg` | Transcribed locally with faster-whisper, transcript fed into Claude extraction (requires `pip install graphifyy[video]`) |
| YouTube / URLs | any video URL | Audio downloaded via yt-dlp, then same Whisper pipeline (requires `pip install graphifyy[video]`) |
## Video and audio corpus
Drop video or audio files into your corpus folder alongside your code and docs — graphify picks them up automatically:
```bash
pip install 'graphifyy[video]' # one-time setup
/graphify ./my-corpus # transcribes any video/audio files it finds
```
Add a YouTube video (or any public video URL) directly:
```bash
/graphify add https://www.youtube.com/watch?v=...
```
yt-dlp downloads audio-only (fast, small), Whisper transcribes it locally, and the transcript is fed into the same extraction pipeline as your other docs. Transcripts are cached in `graphify-out/transcripts/` so re-runs skip already-transcribed files.
For better accuracy on technical content, use a larger model:
```bash
/graphify ./my-corpus --whisper-model medium
```
Audio never leaves your machine. All transcription runs locally.
## What you get
**God nodes** - highest-degree concepts (what everything connects through)