Video Summarizer

Intelligently fetch video transcripts → Let LLM summarize the content

Pipeline

Video Link → Check Cache → Try downloading subtitles → Has subtitles? → Extract text directly → Summarize
                                                     ↓ No subtitles
                                                      Download audio → Whisper transcribe → Summarize

Features

• Subtitles first: Prefer official/manual subtitles, fall back to Whisper transcription only when unavailable
• Multi-platform: Bilibili, YouTube, Douyin, Twitter, TikTok and 1000+ more platforms
• Auto language detection: Whisper auto-detects video language (Chinese, English, Japanese, etc.)
• Concurrency safe: Each video uses its own temp directory, supports multiple videos simultaneously
• Smart caching: Same video returns cached result on subsequent requests

Supported Platforms

Powered by yt-dlp, supports 1000+ platforms:

Dependency Installation

The script will automatically check and install missing dependencies:

• ffmpeg (audio conversion) → brew install ffmpeg
• whisper.cpp (transcription) → brew install whisper-cpp
• Python3 (isolated virtual environment) → brew install python3

Run:

scripts/install_dependency.sh

Note: First-time installation may take a while depending on your network speed.

Usage

# Process a video (first run transcribes, subsequent runs return cached result)
scripts/process.sh "video_url"

Pipeline:

1. Check cache (return immediately if exists)
2. Try downloading subtitles (prefer Chinese manual, then auto-generated)
3. Has subtitles → extract plain text; No subtitles → download audio → Whisper transcribe
4. Save to summarize_result/{title}_transcript_raw.txt

Then ask me to summarize and save the result as a markdown file!

Input Formats

• Bilibili: https://www.bilibili.com/video/BV1s8UZBZEa8
• YouTube: https://www.youtube.com/watch?v=dQw4w9WgXcQ
• Douyin: https://www.douyin.com/video/7123456789
• Twitter: https://twitter.com/user/status/123456789
• TikTok: https://www.tiktok.com/@user/video/123456789
• Any other yt-dlp supported URLs

Output

Filenames use the video title for clarity, special characters handled automatically:

cache/{title}/
└── transcript_raw.txt          # Raw transcript

summarize_result/
└── {title}.md                    # Summary

Filename sanitization:

• Chinese punctuation 《》【】：？ → _
• English symbols /\:*?"<>| → _
• Spaces → _
• Consecutive underscores merged
• Max 50 characters

Directory Structure

video-summarize/
├── cache/                   # Cache directory
│   └── {title}/             # Per-video directory
│       ├── transcript_raw.txt  # Raw transcript (preserved)
│       ├── status.json      # Processing status (cleaned up)
│       ├── subs/            # Subtitle temp dir (cleaned up)
│       ├── audio.m4a        # Audio file (cleaned up)
│       └── audio.wav        # WAV format (cleaned up)
├── summarize_result/        # Summary output directory
│   └── {title}.md           # Summary file
├── whisper-models/
│   └── ggml-base.bin
├── scripts/
│   ├── install_dependency.sh
│   ├── process.sh
│   └── safe_filename.py
└── SKILL.md
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Subtitle Support

Subtitle priority: Chinese manual > English manual > Auto-generated

Notes

• Only processes public videos (no members-only or paid content)
• Subtitles are generally better than Whisper transcription (preferred)
• Transcription quality depends on audio quality and Whisper base model
• Long videos (>30 min) take longer to transcribe
• Works well with Chinese, English, Japanese and other major languages
• Requires network connection to download video audio/subtitles