Test ML data with faces and no CLIP embedding, and name the norm

Each backup command's tests now have a file whose ML data holds faces and
no CLIP embedding; its JSON has the ML data and no keywords. The helper
that gives a vector's norm is called norm. The README names what a
video's JSON lacks, and the generator states its download size with the
Python packages counted.

Model: opus-5-5

test/cli/backup.test.ts

@@ -996,6 +996,33 @@ describe("ML data in each file's JSON", () => {
         await lib.close();
     });
 
+    // A file's ML data can hold faces and no CLIP embedding. Its JSON then has
+    // the ML data and no keywords.
+    it("writes no keywords for ML data without a CLIP embedding", async () => {
+        const faces = { face: { faces: [{ faceID: "101_1", score: 0.9 }] } };
+
+        // Gives file 101 ML data holding only faces.
+        class FacesClient extends MockClient {
+            async fetchMLData(args: { fileIDs: number[] }): Promise<{
+                payloads: Map<number, MLData>;
+                errors: Map<number, unknown>;
+            }> {
+                const payloads = new Map<number, MLData>();
+                if (args.fileIDs.includes(101)) payloads.set(101, faces);
+                return { payloads, errors: new Map() };
+            }
+        }
+        const lib = await openLibrary(stubSource(), new FacesClient());
+        const outDir = join(root, "backup");
+
+        const result = await lib.backup({ downloadDirectory: outDir });
+
+        expect(result.failed).toBe(0);
+        expect(fileJSON(outDir, 101).mlData).toEqual(faces);
+        expect(fileJSON(outDir, 101)).not.toHaveProperty("keywords");
+        await lib.close();
+    });
+
     // Ente's photos app keeps videos out of some Discover categories, Identity
     // among them. Here a photo and a video share one CLIP embedding, Identity's
     // own text embedding, so the photo gets the keyword Identity and the video