Update app.py

app.py

@@ -149,18 +149,17 @@ async def predict(query):
     
         # Perform hybrid search for each query
         # this will result in a dictionary of re-ranked search results for each query
-        results = {}
         process_time = time.time()
-        for query in normalized_query_list:
-            product_list = copy.deepcopy(request_json)
-            keyword_scores = await check_validity(query, keyword_search)
-            semantic_scores = await semantic_search(query, doc_embeddings)
-            hybrid_scores = hybrid_search(keyword_scores, semantic_scores)
-            product_list = is_cheapest(query=query, request_json=product_list)
-            # for product in product_list:
-            #     del product['categoryName'], product['providerName'], product['brandName'], product['productId'], product['key'], product['productOldPrice'], product['imageUrl'], product['currency'], product['providerLogo'], product['productUrl'], product['productRatingCount'], product['productRating'], product['productType']
-            results[query] = rerank_results(
-                request_json=product_list, hybrid_scores=hybrid_scores
+    
+        product_list = copy.deepcopy(request_json)
+        keyword_scores = await check_validity(query, keyword_search)
+        semantic_scores = await semantic_search(query, doc_embeddings)
+        hybrid_scores = hybrid_search(keyword_scores, semantic_scores)
+        product_list = is_cheapest(query=query, request_json=product_list)
+        for product in product_list:
+            del product['categoryName'], product['providerName'], product['brandName'], product['productId'], product['key'], product['productOldPrice'], product['imageUrl'], product['currency'], product['providerLogo'], product['productUrl'], product['productRatingCount'], product['productRating'], product['productType']
+        results = rerank_results(
+            request_json=product_list, hybrid_scores=hybrid_scores
             )
     
         process_end_time = time.time()
@@ -174,8 +173,8 @@ async def predict(query):
         #         "calculate_interrelations_time": calculate_interrelations_time,
         #         "process_time": process_time_taken}
 
-        return results
-        # return print_results(results)
+        # return results
+        return print_results(results)
     
     except Exception as e:
         error_message = f"An error occurred during processing: {e}"