[mob][photos] Only download models on wifi

mobile/lib/services/machine_learning/ml_computer.dart

@@ -158,8 +158,8 @@ class MLComputer {
   }
 
   Future<List<double>> runClipText(String query) async {
-    await _ensureLoadedClipTextModel();
     try {
+      await _ensureLoadedClipTextModel();
       final int clipAddress = ClipTextEncoder.instance.sessionAddress;
       final textEmbedding = await _runInIsolate(
         (
@@ -195,9 +195,10 @@ class MLComputer {
 
         // Load ClipText model
         final String modelName = ClipTextEncoder.instance.modelName;
-        final String modelRemotePath = ClipTextEncoder.instance.modelRemotePath;
-        final String modelPath =
-            await RemoteAssetsService.instance.getAssetPath(modelRemotePath);
+        final String? modelPath = await ClipTextEncoder.instance.downloadModelSafe();
+        if (modelPath == null) {
+          throw Exception("Could not download clip text model, no wifi");
+        }
         final address = await _runInIsolate(
           (
             MLComputerOperation.loadModel,

mobile/lib/services/machine_learning/ml_model.dart

@@ -5,6 +5,7 @@ import "package:onnx_dart/onnx_dart.dart";
 import "package:onnxruntime/onnxruntime.dart";
 import "package:photos/services/machine_learning/onnx_env.dart";
 import "package:photos/services/remote_assets_service.dart";
+import "package:photos/utils/network_util.dart";
 import "package:synchronized/synchronized.dart";
 
 abstract class MlModel {
@@ -32,6 +33,7 @@ abstract class MlModel {
   bool _isNativePluginInitialized = false;
   int _nativePluginSessionIndex = -1;
 
+  /// WARNING: If [downloadModel] was not first called, this method will download the model first using high bandwidth.
   Future<(String, String)> getModelNameAndPath() async {
     return _downloadModelLock.synchronized(() async {
       final path =
@@ -40,12 +42,29 @@ abstract class MlModel {
     });
   }
 
-  Future<void> downloadModel([bool forceRefresh = false]) async {
+  Future<String?> downloadModelSafe() async {
+    if (await RemoteAssetsService.instance.hasAsset(modelRemotePath)) {
+      return await RemoteAssetsService.instance.getAssetPath(modelRemotePath);
+    } else {
+      if (await canUseHighBandwidth()) {
+        return await downloadModel();
+      } else {
+        logger.warning(
+          'Cannot return model path as it is not available locally and high bandwidth is not available.',
+        );
+        return null;
+      }
+    }
+  }
+
+  Future<String> downloadModel([bool forceRefresh = false]) async {
     return _downloadModelLock.synchronized(() async {
       if (forceRefresh) {
-        await RemoteAssetsService.instance.getAssetIfUpdated(modelRemotePath);
+        final file = await RemoteAssetsService.instance
+            .getAssetIfUpdated(modelRemotePath);
+        return file!.path;
       } else {
-        await RemoteAssetsService.instance.getAsset(modelRemotePath);
+        return await RemoteAssetsService.instance.getAssetPath(modelRemotePath);
       }
     });
   }

mobile/lib/services/machine_learning/ml_service.dart

@@ -171,6 +171,8 @@ class MLService {
             'stopping indexing because user is not connected to wifi',
           );
           break;
+        } else {
+          await _ensureDownloadedModels();
         }
         final futures = <Future<bool>>[];
         for (final instruction in chunk) {
@@ -500,6 +502,11 @@ class MLService {
         _logger.finest("Models already downloaded");
         return;
       }
+      final goodInternet = await canUseHighBandwidth();
+      if (!goodInternet) {
+        _logger.info("Cannot download models because user is not connected to wifi");
+        return;
+      }
       _logger.info('Downloading models');
       await Future.wait([
         FaceDetectionService.instance.downloadModel(forceRefresh),