Can AI replace Shade?

Build me a semantic search engine for my own footage to replace Shade. Requirements:

- A Python CLI plus a small FastAPI web UI on localhost. SQLite with sqlite-vec for
  the vectors and the metadata, one file at ~/FootageIndex/index.db.
- `index <folder>` walks the tree, and for every video ffmpeg pulls a keyframe every
  5 seconds plus one at each scene cut detected by the ffmpeg scene filter.
- Each keyframe is embedded with open_clip (ViT-B/32) and stored with its timestamp.
  Stills and photos get the same treatment as a single frame.
- Audio goes through whisper.cpp for a transcript with word timestamps, chunked into
  30-second windows and embedded with sentence-transformers for text search.
- The search box takes a plain sentence and searches image and transcript vectors
  together, returning ranked results as thumbnail, filename, and timecode. Clicking
  one opens the clip at that exact frame in a player.
- Indexing is incremental and resumable, keyed on file path plus mtime plus size, and
  prints a running count so an overnight run is checkable in the morning.
- Everything runs on my machine, models included · no accounts, no cloud, no
  telemetry, no API keys. Files are read only, never moved or renamed.
- Out of scope: face recognition, sharing links, review and comments, and team sync.
  Do not build auth or a server deployment, this is a single-user local tool.
- README: installing ffmpeg and whisper.cpp, first-run model downloads, an honest
  estimate of indexing hours per TB on CPU versus GPU, and how to reset the index.