FunClip

FunClip is a speech (TTS/STT) tool - FunASR-powered video transcription, subtitle generation, and LLM-assisted clipping tool with a local Gradio UI.

Overview

FunClip is a fully open-source, locally deployed automated video clipping tool. It leverages Alibaba TONGYI speech lab's open-source FunASR Paraformer series models to perform speech recognition on videos. Then, users can freely choose text segments or speakers from the recognition results and click the clip button to obtain the video clip corresponding to the selected segments (Quick Experience Modelscope⭐ HuggingFace🤗).

• 🔥Try AI clipping using LLM in FunClip now. - FunClip integrates Alibaba's open-source industrial-grade model Paraformer-Large, which is one of the best-performing open-source Chinese ASR models available, with over 13 million downloads on Modelscope. It can also accurately predict timestamps in an integrated manner. - FunClip incorporates the hotword customization feature of SeACo-Paraformer, allowing users to specify certain entity words, names, etc., as hotwords during the ASR process to enhance recognition results. - FunClip integrates the CAM++ speaker recognition model, enabling users to use the auto-recognized speaker ID as the target for trimming, to clip segments from a specific speaker. - The functionalities are realized through Gradio interaction, offering simple installation and ease of use. It can also be deployed on a server and accessed via a browser. - FunClip supports multi-segment free clipping and automatically returns full video SRT subtitles and target segment SRT subtitles, offering a simple and convenient user experience.

FunClip is open-source, written primarily in Python, with 5,877 GitHub stars under the MIT license. It was last updated on 2026-06-29.

Key capabilities

From the project's documentation:

• 🔥Try AI clipping using LLM in FunClip now.
• 2024/06/12 FunClip supports recognize and clip English audio files now. Run python funclip/launch.py -l en to try.
• 2024/05/09 FunClip updated to v1.1.0, including the following updates and fixes:
• Support configuration of output file directory, saving ASR intermediate results and video clipping intermediate files;
• Fixed a bug introduced due to FunASR interface upgrade, which has caused some serious clipping errors;
• Support configuring different start and end time offsets for each paragraph;

Install

A quick way to get started (always check the official docs for the latest):

pip install -r ./requirements.txt

How it fits a local-AI stack

FunClip runs on your own hardware, so pair it with a model and a GPU sized to your needs. Use the VRAM calculator to pick a model that fits your card, and see what you can run for hardware guidance. Related speech (TTS/STT) tools in the directory:

• "cactus"
• "claude-code-local"
• "dograh"
• "DreamServer"

Sources

• Source code & docs: modelscope/FunClip
• Official website: https://www.funasr.com

Stats from GitHub, 2026-07-02.