SCM — Screen Memories Deep AI search for every photo and every frame of video in any folder on macOS. Local-first — no accounts, no cloud, no uploads. Inference runs on your Mac.
What makes it different: Search like you think — describe a memory in plain language; a local vision model does the rest. Video, down to the moment — scenes are segmented and embedded, so you land on the shot, not just the file. Text and dialogue too — OCR over visible text; exact spoken-line search via Whisper, each as its own mode. Your tabs, your prompts — save any query as a tab. Screenshots and Self-maintaining library — watched folders auto-import, content hashes dedupe renames, and model switches re-embed in the background without blocking search.
Truly private — your media never leaves the machine. Weights download once; everything after that is offline. Five ways to search: Mode Finds Files Whole photos/videos by meaning — vision rank with filename and phrase boosts. Scenes Moments inside video — search a shot, jump to its timecode. OCR Text visible in images and frames, matched literally (Tesseract; eng + 35 language toggles). Dialogue Exact spoken words in videos (Whisper), tiered exactness. LLMs (opt-in) Local chat over the dialogue, OCR, and filenames your Mac already extracted — cited answers.
Requirements: macOS (packaged with electron-builder; menu-bar/tray features are macOS-only). Bun — the project uses bun as package manager and runner. Node modules installed: bun install. First use of a model downloads its weights (~435MB for the default CLIP); after that, fully offline. Download: The easiest install is via Homebrew (Apple Silicon, macOS 12+). The tap's cask clears the macOS quarantine flag automatically on every install and upgrade, so the app launches with no manual Gatekeeper steps.
出典: Hacker News · 要約：HeadlinesBriefing