Find the moment, not the filename.
Tern brings speech, on-screen text, and visual search into one interface for audio, video, and photo archives. A query returns timestamped moments that can be previewed, trimmed, and exported.
Three ways into the same archive.
Whisper transcribes speech, Apple Vision extracts text, and SigLIP-2 embeds video keyframes. SQLite FTS5 and ChromaDB power the text and visual retrieval; the results are combined into a single ranked list.
Media and search indexes stay on the Mac. A FastAPI service connects the indexing and search pipeline to a vanilla JavaScript interface inside a Tauri desktop shell.
Making retrieval useful.
Matching results are grouped into time windows, with a ranking bonus when multiple search channels agree. The visual channel uses relevance thresholds to avoid returning confident-looking results for queries with no useful match.
A built-in trim editor turns search results into clips. Export options include MP4, MP3, subtitles, CSV, and FCPXML timelines for Final Cut Pro.
Where it stands.
Tern is an unreleased v0.1 project. The public repository documents the implementation, tests, and remaining work. Its source is available for review under an all-rights-reserved license.