clipKeywords takes the CLIP embedding out of a file's ML data with
clipEmbedding, now exported from src/library/mldata.ts, and adds only its own
checks: 512 numbers, not all zero. bin/clip-keyword-vectors puts its body in
a main function called at the bottom, as the scripts under script/ do; it
writes the same files. The README lists the Discover categories as bullets
and states the score, the rule and the video rule in short sentences of their
own.
Model: opus-5-5
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, by the app's rule.
src/clip-keywords.ts applies the rule. src/clip-keyword-vectors.ts holds the
16 categories from Ente's discover.json with the text embedding Ente's CLIP
text model gives each query. bin/clip-keyword-vectors writes that file and the
test fixture in a digest-pinned Python image, with every download pinned by
sha256; it runs by hand only. quak gains no dependency.
Model: opus-5-5
clawbot