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`quak backup` and `quak backup-metadata` write each file's ML data without its CLIP embedding, and `keywords` in its place: the titles of the Discover categories of Ente's photos app that the file falls in, highest score first. A file falls in a category when the cosine similarity of its CLIP embedding and the text embedding of the category's query reaches the category's minimum score; as in Ente's app, five categories leave out videos. The 16 text embeddings ship in `src/clip-keyword-vectors.ts`, written by `bin/clip-keyword-vectors` from Ente's list and CLIP text model. quak runs no model and gains no dependency. Disclosure: the text embeddings are committed model output, against REPO_POLICIES' rule on generated files. Model: opus-5-5
