topk query = 70 + 0.55 sim cut off + table chunk size= 4000

index_retriever.py

@@ -12,7 +12,7 @@ def create_vector_index(documents):
     log_message("Строю векторный индекс")
     return VectorStoreIndex.from_documents(documents)
 
-def rerank_nodes(query, nodes, reranker, top_k=20, min_score_threshold=0.5):
+def rerank_nodes(query, nodes, reranker, top_k=25, min_score_threshold=0.5):
     if not nodes or not reranker:
         return nodes[:top_k]
     
@@ -46,12 +46,12 @@ def create_query_engine(vector_index):
         
         bm25_retriever = BM25Retriever.from_defaults(
             docstore=vector_index.docstore, 
-            similarity_top_k=50 
+            similarity_top_k=70 
         )
         
         vector_retriever = VectorIndexRetriever(
             index=vector_index, 
-            similarity_top_k=50,
+            similarity_top_k=70,
             similarity_cutoff=0.55
         )