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  • License MIT

Video intelligence distiller — extract structured notes, transcripts, and insights from any video using Gemini

Package Exports

    This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (vidistill) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

    Readme

    vidistill

    Video intelligence distiller — turn any video or audio file into structured notes, transcripts, and insights using Gemini.

    Feed it a YouTube URL, local video, or audio file. It analyzes the content through multiple AI passes (scene analysis, transcript, visuals, code extraction, people, chat, implicit signals) and synthesizes everything into organized markdown output.

    Install

    npm install -g vidistill

    Requires Node.js 22+ and ffmpeg.

    Usage

    vidistill [input] [options]

    Arguments:

    • input — YouTube URL, local video, or audio file path (prompted interactively if omitted)

    Options:

    • -c, --context — context about the video (e.g. "CS lecture", "product demo")
    • -o, --output — output directory (default: ./vidistill-output/)
    • -l, --lang <code> — output language (e.g. zh, ja, ko, es, fr, de, pt, ru, ar, hi)

    Examples:

    # Interactive mode — prompts for everything
vidistill

# YouTube video
vidistill "https://youtube.com/watch?v=dQw4w9WgXcQ"

# Local file with context
vidistill ./lecture.mp4 --context "distributed systems lecture"

# Audio file
vidistill ./podcast.mp3

# Custom output directory
vidistill ./demo.mp4 -o ./notes/

# Output in another language
vidistill ./lecture.mp4 --lang zh

    API Key

    vidistill needs a Gemini API key. It checks these sources in order:

    1. GEMINI_API_KEY environment variable
    2. ~/.vidistill/config.json
    3. Interactive prompt (with option to save for next time)

    Get a key at ai.google.dev.

    Output

    vidistill creates a folder per video with structured files:

    vidistill-output/my-video/
├── guide.md           # overview and navigation
├── transcript.md      # full timestamped transcript
├── combined.md        # transcript + visual notes merged
├── notes.md           # meeting/lecture notes
├── code/              # extracted and reconstructed source files
│   ├── *.ext          # individual source files
│   └── code-timeline.md  # code evolution timeline
├── people.md          # speakers and participants
├── chat.md            # chat messages and links
├── action-items.md    # tasks and follow-ups
├── insights.md        # implicit signals and analysis
├── links.md           # all URLs mentioned
├── prereqs.md         # prerequisite knowledge (when detected)
├── timeline.html      # interactive visual timeline
├── metadata.json      # processing metadata
├── progress.json      # resume checkpoint (during processing)
└── raw/               # raw pass outputs

    Which files are generated depends on the video content — a coding tutorial gets code/, a meeting gets people.md and action-items.md, etc.

    Speaker Naming

    When multiple speakers are detected, vidistill prompts you to assign real names after processing. Names replace generic labels (SPEAKER_00, SPEAKER_01) in all output files.

    For meetings with 6+ speakers, the top 5 by speaking time are prompted first, with remaining speakers optional.

    To rename speakers after the fact:

    vidistill rename-speakers ./vidistill-output/my-meeting/

    Resume

    If a run is interrupted (Ctrl+C), progress is saved automatically. Re-running the same command detects the incomplete run and offers to resume from where it left off.

    How It Works

    Supported video formats: MP4, MOV, WebM, MKV, AVI, MPEG, FLV, WMV, 3GPP. Supported audio formats: MP3, AAC, WAV, FLAC, OGG, M4A.

    1. Input — accepts YouTube URL directly or reads local file (video or audio), compresses if over 2GB
    2. Pass 0 — scene analysis to classify video type and determine processing strategy
    3. Pass 1 — transcript extraction with speaker identification
    4. Pass 2 — visual content extraction (screen states, diagrams, slides)
    5. Pass 3 — specialist passes based on video type:
      • 3c: chat and links (live streams) — per segment, runs 3x with consensus voting
      • 3d: implicit signals (all types) — per segment
      • 3b: people and social dynamics (meetings) — whole video
      • 3a: code reconstruction (coding videos) — whole video, runs 3x with consensus voting and validation
    6. Synthesis — cross-references all passes into unified analysis
    7. Output — generates structured markdown files

    Audio files skip visual passes and go straight to transcript, people, implicit signals, and synthesis.

    Long videos are segmented automatically. Passes that fail are skipped gracefully.

    License

    MIT