publikclip
Long video in, scored vertical clips out — and the score shows its work
publikclip
open source · on publik
How to install publikclip
Every step written out, for people who have never opened a terminal. Pick the setup you have.
README
Open in GitHubpublikclip
Long video in. Scored vertical clips out. Everything runs on your machine.
publikclip is an open-source (AGPL-3.0) desktop app that takes a YouTube URL or a horizontal video file and produces vertical 9:16 clips with:
- Smart camera — active-speaker-tracked crop paths, smoothed motion, hard cuts on speaker change, punch-ins fired by actual laughter and vocal energy
- Word-accurate captions — multiple styles, karaoke highlighting, prosodic
emphasis (loud words get loud styling),
[laughs]tags from real laughter detection - A virality score you can audit — never a bare number: every clip ships with its subscores, which detectors fired, and every adjustment applied. LLM humor scores get discounted when no actual laughter corroborates them.
- Music-type suggestions — an editable genre/mood/energy brief derived from what's being said and how it sounds
- Optional real-outcomes loop — connect your own Instagram (via your own Meta app, no middleman) and the scorer calibrates against how your clips actually perform
Every model — speech recognition, forced alignment, diarization, laughter detection, audio tagging, face detection, active-speaker detection — runs locally. The only network calls are the video download and 2–3 small LLM calls (bring your own Gemini key, or run fully local via Ollama at reduced scoring quality).
Status
Working end to end: hour-long podcast in, rendered/captioned/scored 9:16 clips out, validated on real footage. The Instagram feedback loop ships in-app (sync, clip↔Reel matching, snapshot history, automatic score calibration). Builds are currently unsigned — install from source below, or follow the guided install at publikhq.com/publikclip.
Runs on macOS (Apple silicon) and Windows 10/11 x64. The Windows path is
validated on every push by the windows workflow: env resolve, full test
suite, NSIS build, silent install, and a launch of the installed app on a
clean VM.
Layout
pipeline/ Python package — the entire processing pipeline + CLI
app/ Tauri v2 desktop shell (React UI, Python sidecar)
Development
# pipeline
cd pipeline && uv sync && uv run pytest
uv run publikclip run "https://www.youtube.com/watch?v=..."
# app
cd app && npm install && npm run tauri dev
License
AGPL-3.0-or-later. Portions adapted from other open-source projects — see
VENDORED-LICENSES.md for the full provenance list.