bm = 30, semantic = 30. hybrid = 60, cutoff = 0.7, topk_reranker= 60

index_retriever.py

@@ -16,18 +16,18 @@ def create_query_engine(vector_index):
     try:
         bm25_retriever = BM25Retriever.from_defaults(
             docstore=vector_index.docstore, 
-            similarity_top_k=25 
+            similarity_top_k=30 
         )
         
         vector_retriever = VectorIndexRetriever(
             index=vector_index, 
-            similarity_top_k=25,  
+            similarity_top_k=30,  
             similarity_cutoff=0.6
         )
         
         hybrid_retriever = QueryFusionRetriever(
             [vector_retriever, bm25_retriever],
-            similarity_top_k=50,  
+            similarity_top_k=60,  
             num_queries=1
         )
         

utils.py

@@ -243,7 +243,7 @@ def answer_question(question, query_engine, reranker, current_model, chunks_df=N
             question,  
             retrieved_nodes, 
             reranker, 
-            top_k=40,
+            top_k=60,
             min_score_threshold=0.5, 
             diversity_penalty=0.3
         )