Update app/services/recommendation.py

app/services/recommendation.py

@@ -7,22 +7,26 @@ logger = logging.getLogger(__name__)
 
 class FlexibleRecipeRecommendationSystem:
     def __init__(self, csv_file_path, precomputed_dir):
-        self.feature_weights = {
+        self.default_feature_weights = {
             'ingredients': 0.15, 'category': 0.25, 'dietary': 0.20,
             'calories': 0.10, 'time': 0.10, 'keywords': 0.10, 'keywords_name': 0.10
         }
         self.image_search_service = ImageSearchService()
-        self.data = load_or_create_data(csv_file_path, precomputed_dir, self.feature_weights)
+        self.data = load_or_create_data(csv_file_path, precomputed_dir, self.default_feature_weights)
+
+    async def get_recommendations(self, category=None, dietary_preference=None, ingredients=None,
+                                  calories=None, time=None, keywords=None, keywords_name=None,
+                                  top_n=6, feature_weights=None):
+        # Use the provided feature_weights, or fall back to the default if not provided
+        weights = feature_weights or self.default_feature_weights
 
-    async def get_recommendations(self, category=None, dietary_preference=None, ingredients=None, 
-                                  calories=None, time=None, keywords=None, keywords_name=None, top_n=6):
         return await get_top_recommendations(
             self.data['df'], self.data['combined_matrix'], 
             self.data['tfidf_vectorizer_ingredients'],
             self.data['tfidf_vectorizer_keywords'], 
             self.data['tfidf_vectorizer_keywords_name'],
             self.data['category_dummies'], self.data['scaler'], 
-            self.feature_weights, self.image_search_service,
+            weights, self.image_search_service,
             category, dietary_preference, ingredients, 
             calories, time, keywords, keywords_name, top_n
         )