Show HN: A video editor where the LLM never watches the video (github.com)

A new video editing tool, created by developer Ranahaani, utilizes local language model (LLM) technologies to streamline video production without requiring the LLM to "watch" the footage. Users simply upload their raw video clips, and the tool automatically selects takes, captures critical segments, adds captions, and incorporates sound effects, yielding a polished final product. This innovative approach leverages local transcription with Whisper and employs automated scripts for editing, enhancing the efficiency of creating talking-head videos and YouTube explainers. This tool is significant for the AI/ML community as it minimizes the reliance on cloud services, thus protecting users' privacy and data. By operating entirely on local machines, it mitigates latency issues and allows for a customizable editing process, where users define preferences that improve with each video iteration. Key technical details include its integration of ffmpeg for media processing and Whisper for transcription, ensuring precise editing through real-time analysis around cut seams. Overall, this offering demonstrates a promising shift toward more autonomous and user-focused video editing solutions in the realm of machine learning.