Move to generator

web/apps/photos/src/services/face/f-index.ts

@@ -46,10 +46,14 @@ import type { Face, FaceDetection, MlFileData } from "./types-old";
  * @param file The contents of {@link enteFile} as a web {@link File}, if
  * available. These are used when they are provided, otherwise the file is
  * downloaded and decrypted from remote.
+ *
+ * @param userAgent The UA of the current client (the client that is generating
+ * the embedding).
  */
 export const indexFaces = async (
     enteFile: EnteFile,
     file: File | undefined,
+    userAgent: string,
 ) => {
     const startTime = Date.now();
 
@@ -58,7 +62,7 @@ export const indexFaces = async (
     );
     let mlFile: MlFileData;
     try {
-        mlFile = await indexFaces_(enteFile, imageBitmap);
+        mlFile = await indexFaces_(enteFile, imageBitmap, userAgent);
     } finally {
         imageBitmap.close();
     }
@@ -98,7 +102,11 @@ const fetchRenderableBlob = async (enteFile: EnteFile) => {
     }
 };
 
-const indexFaces_ = async (enteFile: EnteFile, imageBitmap: ImageBitmap) => {
+const indexFaces_ = async (
+    enteFile: EnteFile,
+    imageBitmap: ImageBitmap,
+    userAgent: string,
+) => {
     const fileID = enteFile.id;
     const { width, height } = imageBitmap;
     const imageDimensions = { width, height };
@@ -108,6 +116,7 @@ const indexFaces_ = async (enteFile: EnteFile, imageBitmap: ImageBitmap) => {
         height,
         faceEmbedding: {
             version: 1,
+            client: userAgent,
         },
         mlVersion: defaultMLVersion,
         errorCount: 0,

web/apps/photos/src/services/face/indexer.worker.ts

@@ -33,7 +33,7 @@ export class FaceIndexerWorker {
 
         let faceIndex: MlFileData;
         try {
-            faceIndex = await indexFaces(enteFile, file);
+            faceIndex = await indexFaces(enteFile, file, userAgent);
             log.debug(() => ({ f, faceIndex }));
         } catch (e) {
             // Mark indexing as having failed only if the indexing itself
@@ -44,7 +44,7 @@ export class FaceIndexerWorker {
             throw e;
         }
 
-        await putFaceEmbedding(enteFile, faceIndex, userAgent);
+        await putFaceEmbedding(enteFile, faceIndex);
         return faceIndex;
     }
 

web/apps/photos/src/services/face/remote.ts

@@ -8,9 +8,8 @@ import type { Face, FaceDetection, MlFileData } from "./types-old";
 export const putFaceEmbedding = async (
     enteFile: EnteFile,
     mlFileData: MlFileData,
-    userAgent: string,
 ) => {
-    const serverMl = LocalFileMlDataToServerFileMl(mlFileData, userAgent);
+    const serverMl = LocalFileMlDataToServerFileMl(mlFileData);
     log.debug(() => ({ t: "Local ML file data", mlFileData }));
     log.debug(() => ({
         t: "Uploaded ML file data",
@@ -111,7 +110,6 @@ class ServerFaceBox {
 
 function LocalFileMlDataToServerFileMl(
     localFileMlData: MlFileData,
-    userAgent: string,
 ): ServerFileMl {
     if (localFileMlData.errorCount > 0) {
         return null;
@@ -138,7 +136,11 @@ function LocalFileMlDataToServerFileMl(
         );
         faces.push(newFaceObject);
     }
-    const faceEmbedding = new ServerFaceEmbedding(faces, userAgent, 1);
+    const faceEmbedding = new ServerFaceEmbedding(
+        faces,
+        localFileMlData.faceEmbedding.client,
+        localFileMlData.faceEmbedding.version,
+    );
     return new ServerFileMl(
         localFileMlData.fileID,
         faceEmbedding,

web/apps/photos/src/services/face/types-old.ts

@@ -23,6 +23,7 @@ export interface MlFileData {
     height: number;
     faceEmbedding: {
         version: number;
+        client: string;
     };
     mlVersion: number;
     errorCount: number;