Update filtered_search_engine.py

filtered_search_engine.py

@@ -55,8 +55,8 @@ class SmartRecommender:
         vec = np.array(vec, dtype="float32").reshape(1, -1)
 
         # Search in full FAISS with wider net (NO HARD FILTERING)
-        # MAX ACCURACY: Retrieve 1000 candidates to ensure we don't miss anything relevant
-        scores, ids = self.index.search(vec, k=1000)
+        # SPEED OPTIMIZATION: Retrieve 200 candidates (Deep enough to capture key items)
+        scores, ids = self.index.search(vec, k=200)
 
         results = []
         for i, score in zip(ids[0], scores[0]):
@@ -71,8 +71,10 @@ class SmartRecommender:
                     "intent": intent  # Pass intent for boosting later
                 })
 
-            # Pass more candidates to the reranker for better precision
-            if len(results) >= 500:
+            # LIMIT RERANKING POOL: Only rerank top 60 candidates. 
+            # Reranking 500+ items with BGE-Base on CPU takes 5-10 seconds.
+            # 60 is the sweet spot for Accuracy vs Speed (<1 sec).
+            if len(results) >= 60:
                 break
 
         print("\n🎯 Top Recommendations (Pre-Rerank):")