added 35 semantic similarity

index_retriever.py

@@ -21,7 +21,7 @@ def create_query_engine(vector_index):
         
         vector_retriever = VectorIndexRetriever(
             index=vector_index, 
-            similarity_top_k=25,  # Increased
+            similarity_top_k=35,  # Increased
             similarity_cutoff=0.65  # Slightly lower for recall
         )
         
@@ -63,10 +63,8 @@ def rerank_nodes(query, nodes, reranker, top_k=20, min_score_threshold=0.5, dive
         scores = reranker.predict(pairs)
         scored_nodes = list(zip(nodes, scores))
         
-        # Sort by score descending
         scored_nodes.sort(key=lambda x: x[1], reverse=True)
         
-        # Filter by minimum threshold (more strict)
         if min_score_threshold is not None:
             scored_nodes = [(node, score) for node, score in scored_nodes 
                           if score >= min_score_threshold]