Update app.py

app.py

@@ -185,9 +185,6 @@ def compare_items():
         search_list = payload['searchList']
         print(f"\n[COMPARE] Received {len(search_list)} pre-filtered candidates for '{query_item.get('objectName')}'.")
         
-        # --- HIERARCHICAL FILTERING BLOCK HAS BEEN REMOVED ---
-        # The service now proceeds directly to scoring.
-
         # --- SCORING ---
         results = []
         for item in search_list:
@@ -204,18 +201,25 @@ def compare_items():
                 text_score = total_text_score / len(TEXT_FIELDS_TO_EMBED) if TEXT_FIELDS_TO_EMBED else 0
                 print(f"    - Text Score: {text_score:.4f}")
 
-                # 2. Calculate Image Score
+                # 2. Calculate Image Score with detailed logging
                 image_score = 0.0
                 query_img_embs = query_item.get('image_embeddings', [])
                 item_img_embs = item.get('image_embeddings', [])
                 if query_img_embs and item_img_embs:
                     all_img_scores = []
-                    for q_emb in query_img_embs:
-                        for i_emb in item_img_embs:
-                            all_img_scores.append(cosine_similarity(q_emb, i_emb))
+                    print(f"      - Image Pair Scores:") # Header for detailed scores
+                    for i, q_emb in enumerate(query_img_embs):
+                        for j, i_emb in enumerate(item_img_embs):
+                            # Calculate the score for this specific pair
+                            pair_score = cosine_similarity(q_emb, i_emb)
+                            # Print the score for this pair
+                            print(f"        - Query Img {i+1} vs Item Img {j+1}: {pair_score:.4f}")
+                            all_img_scores.append(pair_score)
                     if all_img_scores:
                         image_score = max(all_img_scores)
-                print(f"    - Image Score: {image_score:.4f}")
+                
+                # Use a clearer label for the max score
+                print(f"    - Max Image Score: {image_score:.4f}")
                 
                 # 3. Calculate Final Score
                 final_score = (SCORE_WEIGHTS['text_score'] * text_score + SCORE_WEIGHTS['image_score'] * image_score)