Youtube To Knowledge

youtube-to-knowledge

Turn any YouTube video into a transcript, summary, and knowledge graph — powered by Claude Code.

Paste a link. Get structured knowledge.

How it works

1. Fetches the transcript (YouTube API or local Whisper)
2. Generates a structured summary in the video's language
3. Extracts entities and relationships → builds an interactive knowledge graph

Requirements

- Python 3.10+
- Claude Code
- ffmpeg (required for Whisper mode)

Install ffmpeg

Setup

Open the folder in Claude Code.

Usage

Process multiple videos at once:

Process an entire playlist:

Already-processed videos are skipped automatically.

Additional commands:

- /video_specialist — deep-dive questions about what was said in a processed video
- /kg_navigator — explore entity connections across videos

Output

Files are saved to vault/content//:

Each file is named after the video ID, so multiple videos from the same channel are stored without overwriting each other.

Transcription modes

The /process command tries fast mode first and falls back to Whisper automatically. To force Whisper:

WhisperX mode

WhisperX provides word-level timestamps, speaker diarization, and faster transcription via faster-whisper. Install the extra dependencies:

Then use the --engine flag:

Speaker diarization requires a HuggingFace token set as HF_TOKEN in your environment. Without it, WhisperX still produces timestamped segments but without speaker labels.

Obsidian integration

Add --obsidian to export the knowledge graph directly into your Obsidian vault.

This generates one .md file per extracted entity in vault/content//obsidian/. Each file contains:

- YAML frontmatter — tags, source title, URL, channel
- Relations — outgoing links to other entities: - made_by: [[Anthropic]]
- Referenced by — incoming…