Turn livestream VOD moments into shortform clips — batch crop, faster-whisper auto-captions, ASS/SRT export. A six-hour stream becomes a tray of ready-to-post shorts.

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What it does

• Create multi-clip VOD projects for stream sessions.
• Pull recent Twitch VODs, Twitch markers, and Twitch clips via shared auth.deutschmark.online Twitch login.
• Import manual timestamps from any hotkey or marker workflow.
• Surface all those moments in a Session Inbox.
• Prep moments as shorts with streamer-specific presets:
  • Gameplay Focus
  • Facecam Top
  • Baked Text Punch
• Batch-prep a whole inbox and batch-queue prepared shorts for longform.
• Stitch clips into a preview sequence, transcribe captions, and export.
• Build a horizontal longform derivative from queued prepared shorts.
• Use a saved facecam guide instead of auto-detection for recurring stream layouts.

Captions

• 1-click caption dependency install for faster-whisper + torch.
• Managed captioning virtualenv owned by the app.
• Optional pyannote.audio install for diarization.
• Editable captions with speaker colors, ASS/SRT export, and burn-in control.

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Getting started

Run from source

git clone https://github.com/thedeutschmark/clipline.git
cd clipline
pip install -r requirements.txt
python desktop.py

Browser-only mode:

python app.py

The local app runs on http://localhost:3000 by default.

Build the EXE

build.bat

Outputs dist\clipline.exe.

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Configuration

State location

Clipline stores its settings, runtime tools, and captioning virtualenv in:

• Windows: %LOCALAPPDATA%\clipline\

Environment overrides

Variable	Default	Description
CLIPLINE_HOST	localhost	Bind host
CLIPLINE_PORT	3000	Bind port
CLIPLINE_SHARED_AUTH_URL	https://auth.deutschmark.online	Shared Twitch auth origin

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_{All projects → github.com/thedeutschmark}

License

AGPL-3.0 — see LICENSE.