VidkNot

VidkNot is a general research platform framework (v0.4.2) that extracts knowledge from 11+ self-media platforms (YouTube, Bilibili, Douyin, Xiaohongshu, Kuaishou, TikTok, Twitter/X, Instagram, WeChat Channels, Weibo, Vimeo). It downloads audio, transcribes speech via dual-ASR cross-validation, generates Markdown notes, and saves them to Obsidian, Feishu, Notion, or Yuque. v0.4.0 added pluggable storage backends, an async periodic scheduler, a batch runner, and a credential-leak-proof subscription source loader; v0.4.2 adds Standard Agent Skill compliance (SKILL.md + --demo mode + scripts/install.sh).

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Use Cases

• Convert courses, interviews, podcasts, and industry videos into searchable notes
• Save useful short-video content into a personal knowledge base
• Expose video-to-note capability to agents through MCP
• Reduce transcription mistakes with dual-ASR cross-validation

Supported Platforms

See COOKIE_GUIDE.md for the full capability matrix.

Capabilities

Installation

The current GitHub release is v0.4.2. Install from GitHub:

pip install "vidknot @ git+https://github.com/suonian/vidknot.git@v0.4.2"

For development:

git clone https://github.com/suonian/vidknot.git
cd vidknot
pip install -e ".[all]"

FFmpeg must be available locally:

ffmpeg -version

Configuration

Copy .env.example to .env and configure the keys you need:

SILICONFLOW_API_KEY=your_siliconflow_api_key
OPENAI_API_KEY=your_openai_compatible_api_key

# Optional: Feishu
FEISHU_APP_ID=your_feishu_app_id
FEISHU_APP_SECRET=your_feishu_app_secret
FEISHU_FOLDER_TOKEN=your_feishu_folder_token

# Optional: Obsidian
OBSIDIAN_VAULT_PATH=/path/to/obsidian/vault

# Optional: Notion
NOTION_TOKEN=your_notion_token
NOTION_PAGE_ID=your_notion_page_id

# Optional: Yuque
YUQUE_TOKEN=your_yuque_token
YUQUE_LOGIN=your_yuque_login

# Optional: Douyin cookie file
VIDKNOT_DOUYIN_COOKIE_FILE=/path/to/douyin-cookies.txt

Default settings live in config.yaml. Dual-ASR correction is enabled by default:

settings:
  enable_correction: true
  correction_version: v4
faster_whisper:
  model: small
  device: cpu
  compute_type: int8

v4 is the conservative default. v3 makes broader corrections and carries a higher risk of changing valid text.

Usage

CLI:

# Generate a note and save to the default destination, Obsidian
python -m vidknot "https://v.douyin.com/example/"

# Print output only
python -m vidknot "https://v.douyin.com/example/" --destination none

# Save to Feishu
python -m vidknot "https://v.douyin.com/example/" --destination feishu

# Disable dual-ASR correction
python -m vidknot "https://v.douyin.com/example/" --no-correct

# Check local requirements
python -m vidknot --check-env

MCP:

python -m vidknot --mcp

FastAPI:

uvicorn vidknot.api:app --reload

Python API:

from vidknot import VideoKnowledgePipeline

pipeline = VideoKnowledgePipeline(destination="none")
result = pipeline.run("https://v.douyin.com/example/")

print(result["markdown"])

Output

VidkNot writes Markdown notes with:

• Video title, source URL, and processing metadata
• Topic and summary
• Structured key points and details
• Important quotes
• Terms and explanations
• Timestamped transcript

Documentation

Security And Compliance

• Do not commit .env, cookie files, or API keys
• Only process video content you are allowed to access and use
• Follow the terms of video platforms, cloud services, and note platforms
• Third-party service availability, pricing, and permissions are controlled by their providers

License

MIT