ViralMint
Local-first video pipeline: trend scouting, clipping, captioned shorts.
FunASR-powered video transcription, subtitles and LLM-assisted clipping with a local Gradio UI.
FunClip is an open-source clipping project by modelscope (modelscope/FunClip on GitHub). It has 6,379 GitHub stars and 756 forks, is released under the MIT license, and was last updated on GitHub on 8 October 2026.
Gather the videos you want to transcribe or cut, and decide whether you need subtitles, speaker-specific clips or highlight reels.
Clone the repo, create the documented Python 3.12 virtual environment and install the requirements.
Pick a model — the default Paraformer pipeline, Fun-ASR-Nano, SenseVoice or the MOSS backend — and let the weights download.
Launch the Gradio UI, upload a video, copy the transcript segments you want, and export the clip with subtitles.
Integrates Alibaba's Paraformer-Large, one of the best-performing open-source Chinese ASR models, plus Fun-ASR-Nano and SenseVoice options.
Uses SeACo-Paraformer hotwords so names and domain terms you specify are recognized more accurately.
The CAM++ speaker recognition model lets you clip the segments spoken by a specific speaker.
Select the transcript text you want and FunClip cuts those segments, returning full-video SRT and target-segment SRT subtitles.
Everything runs through a browser UI that you can host on your own server; no video leaves your machine unless you choose a cloud LLM gateway.
Optional LLM integration helps pick and refine clip segments from the transcript.
Clone FunClip and create the documented Python environment.
git clone https://github.com/modelscope/FunClip.git
cd FunClip
python3.12 -m venv .venv && . .venv/bin/activateInstall the Python requirements and verify the environment.
python -m pip install -r requirements.txt
python -m pip checkStart FunClip locally and open the interface in your browser.
python funclip/launch.pyFunClip is a modelscope project, built on Alibaba's FunASR and Paraformer model family.
The code is MIT licensed and free; the ASR model weights are downloaded separately and governed by the terms on their model pages.
Core transcription and clipping run locally with downloaded open models — no key needed. Optional LLM gateways for assisted clipping use your own provider key.
FunClip is built around Paraformer/FunASR, which is especially strong for Chinese speech, and adds hotwords and speaker-based clipping in one Gradio tool rather than a bare transcription script.
Clone the repo, create the venv, install requirements, run python funclip/launch.py and upload a video.
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