Video Subtitler

Produce a polished, timecoded .srt from a video or audio source, entirely on-device. Pipeline: get the media local → extract audio → transcribe to SRT with Whisper → clean up typos and brand names.

Prerequisites

Minimal by design — two tools cover the common case:

• ffmpeg / ffprobe — audio extraction + probing. Check which ffmpeg ffprobe; install with brew install ffmpeg.
• whisper-cli (whisper.cpp) — the transcriber. Tiny (~8 MB), MIT, pure C/C++, no Python/PyTorch, runs fast on Apple Silicon, and writes SRT directly. Check which whisper-cli; install with brew install whisper-cpp.
• yt-dlp — only when the input is a YouTube URL. brew install yt-dlp.

whisper.cpp needs a GGML model file (not bundled). See "Getting a Whisper model" below — reuse one already on disk before downloading.

Alternative transcribers exist (openai-whisper via pip, npx hyperframes transcribe) but each is a heavier dependency; see "Alternative transcribers". Default to whisper.cpp.

Workflow

Run in order. Work in the media's directory (or a temp dir for downloads) and name outputs after the source basename.