A file's JSON holds keywords in place of its CLIP embedding (closes #218)

`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

src/metadata-backup.ts

@@ -1,6 +1,7 @@
 import { mkdirSync, readFileSync, writeFileSync } from "node:fs";
 import { join } from "node:path";
 import * as jpeg from "jpeg-js";
+import { clipKeywords } from "./clip-keywords.js";
 import type { Client } from "./client.js";
 import { describeError } from "./errors.js";
 import { readExifTags } from "./exif.js";
@@ -97,7 +98,8 @@ const extractExif = async (
 
 // Dump every decrypted metadata layer the account holds into a directory tree
 // of plain JSON: account, per-collection, and per-file records including the
-// private and public magic metadata and (by default) the ML data. Collections
+// private and public magic metadata and the ML data, with the keywords of its
+// CLIP embedding in place of the embedding (see clip-keywords.ts). Collections
 // and files are enumerated from the library's cache, which the caller refreshes
 // first. Returns how many files have no ML data because their ML data request
 // failed or their ML data did not decrypt, gunzip or parse; they are still
@@ -230,8 +232,16 @@ export const runMetadataBackup = async (
         if (file.pubMagicMetadata)
             fileMeta.pubMagicMetadata = file.pubMagicMetadata;
 
+        // The ML data without the CLIP embedding, and the keywords that
+        // embedding gives.
         const ml = mlDataMap.get(file.id);
-        if (ml) fileMeta.mlData = ml;
+        if (ml) {
+            const { clip: _clip, ...mlDataWithoutClip } = ml;
+            fileMeta.mlData = mlDataWithoutClip;
+            const isVideo = file.metadata.fileType === "video";
+            const keywords = clipKeywords(ml, isVideo);
+            if (keywords) fileMeta.keywords = keywords;
+        }
         const mlError = mlDataErrors.get(file.id);
         if (mlError) fileMeta.mlDataError = mlError;