[mob] Zip embeddings

mobile/lib/services/machine_learning/face_ml/face_recognition_service.dart

@@ -89,7 +89,7 @@ class FaceRecognitionService {
   }
 
   Future<void> _syncFaceEmbeddings({int retryFetchCount = 10}) async {
-    final filesToIndex = await getFilesForMlIndexing();
+    final List<FileMLInstruction> filesToIndex = await getFilesForMlIndexing();
     final List<List<FileMLInstruction>> chunks =
         filesToIndex.chunks(_embeddingFetchLimit); // Chunks of 200
     int fetchedCount = 0;

mobile/lib/services/machine_learning/file_ml/file_ml.dart

@@ -1,45 +1,58 @@
 import "package:photos/face/model/face.dart";
 
+const _faceKey = 'face';
+const _clipKey = 'clip';
+
 class RemoteFileML {
   final int fileID;
   final Map<String, dynamic> remoteRawData;
-  final RemoteFaceEmbedding? faceEmbedding;
-  final RemoteClipEmbedding? clipEmbedding;
 
   RemoteFileML(
     this.fileID,
-    this.remoteRawData, {
-    required this.faceEmbedding,
-    this.clipEmbedding,
-  });
+    this.remoteRawData,
+  );
 
-  // toJson
-  Map<String, dynamic> toJson() {
-    throw UnimplementedError();
-  }
-
-  // fromRemote
   factory RemoteFileML.fromRemote(int fileID, Map<String, dynamic> json) {
     return RemoteFileML(
       fileID,
       json,
-      faceEmbedding: json['face'] != null
-          ? RemoteFaceEmbedding.fromJson(
-              json['face'] as Map<String, dynamic>,
-            )
-          : null,
-      clipEmbedding: json['clip'] == null
-          ? null
-          : RemoteClipEmbedding.fromJson(
-              json['clip'] as Map<String, dynamic>,
-            ),
     );
   }
+
+  static RemoteFileML empty(int i) {
+    final Map<String, dynamic> json = {};
+    return RemoteFileML(i, json);
+  }
+
+  void putFaceIfNotNull(RemoteFaceEmbedding? faceEmbedding) {
+    if (faceEmbedding != null) {
+      remoteRawData[_faceKey] = faceEmbedding.toJson();
+    }
+  }
+
+  void putClipIfNotNull(RemoteClipEmbedding? clipEmbedding) {
+    if (clipEmbedding != null) {
+      remoteRawData[_clipKey] = clipEmbedding.toJson();
+    }
+  }
+
+  RemoteFaceEmbedding? get faceEmbedding => remoteRawData[_faceKey] != null
+      ? RemoteFaceEmbedding.fromJson(
+          remoteRawData[_faceKey] as Map<String, dynamic>,
+        )
+      : null;
+
+  RemoteClipEmbedding? get clipEmbedding => remoteRawData[_clipKey] != null
+      ? RemoteClipEmbedding.fromJson(
+          remoteRawData[_clipKey] as Map<String, dynamic>,
+        )
+      : null;
 }
 
 class RemoteFaceEmbedding {
   final List<Face> faces;
   final int version;
+
   // packageName/version
   final String client;
   final int height;

mobile/lib/services/machine_learning/file_ml/remote_fileml_service.dart

@@ -3,7 +3,7 @@ import "dart:convert";
 import "dart:io";
 
 import "package:computer/computer.dart";
-import "package:flutter/foundation.dart" show Uint8List, debugPrint;
+import "package:flutter/foundation.dart" show Uint8List;
 import "package:logging/logging.dart";
 import "package:photos/core/network/network.dart";
 import "package:photos/db/files_db.dart";
@@ -28,14 +28,19 @@ class RemoteFileMLService {
 
   void init(SharedPreferences prefs) {}
 
-  Future<void> putFileEmbedding(EnteFile file, RemoteFileML fileML) async {
-    throw Exception("need to update implementation");
+  Future<void> putFileEmbedding(
+    EnteFile file,
+    RemoteFileML fileML, {
+    RemoteClipEmbedding? clipEmbedding,
+    RemoteFaceEmbedding? faceEmbedding,
+  }) async {
+    fileML.putClipIfNotNull(clipEmbedding);
+    fileML.putFaceIfNotNull(faceEmbedding);
     final encryptionKey = getFileKey(file);
-    final embeddingJSON = jsonEncode(fileML.toJson());
-    final encryptedEmbedding = await CryptoUtil.encryptChaCha(
-      utf8.encode(embeddingJSON),
-      encryptionKey,
-    );
+    final embeddingJSON = jsonEncode(fileML.remoteRawData);
+    final compressedData = gzipUInt8List(utf8.encode(embeddingJSON));
+    final encryptedEmbedding =
+        await CryptoUtil.encryptChaCha(compressedData, encryptionKey);
     final encryptedData =
         CryptoUtil.bin2base64(encryptedEmbedding.encryptedData!);
     final header = CryptoUtil.bin2base64(encryptedEmbedding.header!);
@@ -44,12 +49,11 @@ class RemoteFileMLService {
         "/embeddings",
         data: {
           "fileID": file.uploadedFileID!,
-          "model": 'file-ml-clip-face',
+          "model": 'ggml-clip',
           "encryptedEmbedding": encryptedData,
           "decryptionHeader": header,
         },
       );
-      // final updationTime = response.data["updatedAt"];
     } catch (e, s) {
       _logger.severe("Failed to put embedding", e, s);
       rethrow;
@@ -127,6 +131,13 @@ Uint8List ungzipUint8List(Uint8List compressedData) {
   return Uint8List.fromList(decompressedList);
 }
 
+// gzipUInt8List
+Uint8List gzipUInt8List(Uint8List data) {
+  final codec = GZipCodec();
+  final compressedData = codec.encode(data);
+  return Uint8List.fromList(compressedData);
+}
+
 Future<Map<int, RemoteFileML>> _decryptFileMLComputer(
   Map<String, dynamic> args,
 ) async {
@@ -140,7 +151,6 @@ Future<Map<int, RemoteFileML>> _decryptFileMLComputer(
     decryptArgs["header"] =
         CryptoUtil.base642bin(input.embedding.decryptionHeader);
     final embeddingData = chachaDecryptData(decryptArgs);
-    // unzip the gzip data
     final unzippedData = ungzipUint8List(embeddingData);
     final decodedJson = jsonDecode(utf8.decode(unzippedData));
     final RemoteFileML decodedEmbedding = RemoteFileML.fromRemote(

mobile/lib/services/machine_learning/ml_service.dart

@@ -469,24 +469,26 @@ class MLService {
         if (!result.errorOccured) {
           await RemoteFileMLService.instance.putFileEmbedding(
             instruction.enteFile,
-            RemoteFileML(
-              instruction.enteFile.uploadedFileID!,
-              {},
-              faceEmbedding: RemoteFaceEmbedding(
-                faces,
-                result.mlVersion,
-                client: client,
-                height: result.decodedImageSize.height,
-                width: result.decodedImageSize.width,
-              ),
-              clipEmbedding: result.clipRan
-                  ? RemoteClipEmbedding(
-                      result.clip!.embedding,
-                      version: result.mlVersion,
-                      client: client,
-                    )
-                  : null,
-            ),
+            instruction.existingRemoteFileML ??
+                RemoteFileML.empty(
+                  instruction.enteFile.uploadedFileID!,
+                ),
+            faceEmbedding: result.facesRan
+                ? RemoteFaceEmbedding(
+                    faces,
+                    result.mlVersion,
+                    client: client,
+                    height: result.decodedImageSize.height,
+                    width: result.decodedImageSize.width,
+                  )
+                : null,
+            clipEmbedding: result.clipRan
+                ? RemoteClipEmbedding(
+                    result.clip!.embedding,
+                    version: result.mlVersion,
+                    client: client,
+                  )
+                : null,
           );
         } else {
           _logger.warning(

mobile/lib/utils/ml_util.dart

@@ -32,12 +32,14 @@ class FileMLInstruction {
 
   final bool shouldRunFaces;
   final bool shouldRunClip;
+  RemoteFileML? existingRemoteFileML;
 
   FileMLInstruction({
     required this.enteFile,
     required this.shouldRunFaces,
     required this.shouldRunClip,
   });
+
 }
 
 Future<IndexStatus> getIndexStatus() async {