autoclip
AutoClip|一个链接,一键出片。开源 AI 视频剪辑桌面工具,将播客、访谈、课程等长视频自动剪成短视频,生成字幕、封面和发布文案,适配抖音、小红书、TikTok、Reels 与 YouTube Shorts。Open-source AI video clipping & content repurposing.
Auto-download livestreams, AI-clip the highlights, upload in realtime.
py-autovod is an open-source clipping project by 0jc1 (0jc1/py-autovod on GitHub). It has 30 GitHub stars and 17 forks, is released under the MIT license, and was last updated on GitHub on 17 September 2026.
Download the source and enter the folder.
Add the Twitch or Kick channels to watch.
Start the Docker containers.
Find AI-cut highlights uploaded automatically.
Captures livestreams as they happen.
Finds highlight moments automatically.
Clips go up while the stream runs.
Supports both major platforms.
Runs as containers with rclone uploads.
Precise clip extraction under the hood.
Download the source and move into the project folder.
git clone https://github.com/0jc1/py-autovod.git
cd py-autovodAdd the streamers to watch per the README.
# edit config with your Twitch/Kick channelsLaunch the clipping containers.
docker compose up -dIt is an open-source project at 0jc1/py-autovod with 17 forks.
Yes. It is MIT licensed.
Twitch and Kick livestreams.
AI analysis picks the clip-worthy moments from the broadcast.
They upload in realtime — rclone support covers cloud destinations.
AutoClip|一个链接,一键出片。开源 AI 视频剪辑桌面工具,将播客、访谈、课程等长视频自动剪成短视频,生成字幕、封面和发布文案,适配抖音、小红书、TikTok、Reels 与 YouTube Shorts。Open-source AI video clipping & content repurposing.
Local-first clipper: Whisper plus Ollama turn long video into captioned 9:16 clips.
Desktop highlight editor with Whisper transcription and LLM clip scoring.
Free YouTube-to-viral-clip cutter with auto transcription and 9:16 edits.
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Lightweight AI clipper that pulls highlights from streams and videos.
The most-starred other Clipping projects in the LibreAI catalogue — the realistic shortlist if py-autovod is not the right fit.
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macOS video editor built for AI
MoneyPrinter — automate YouTube Shorts from a single topic: local Ollama writes the script and metadata, stock footage and voiceover are assembled into a finished short, MIT
Free and open — grab the source, star the repo, and start creating.