bm25 full corpuse + COMPACT + NodePostprocessor

index_retriever.py

@@ -14,33 +14,36 @@ def create_vector_index(documents):
 
 def create_query_engine(vector_index):
     try:
+        # ✅ Get all nodes from docstore instead of vector_index.get_nodes()
+        all_nodes = list(vector_index.docstore.get_all_nodes().values())
+
         bm25_retriever = BM25Retriever.from_defaults(
             docstore=vector_index.docstore,
-            nodes=vector_index.get_nodes(),  # <-- add this line
-            similarity_top_k=20
+            nodes=all_nodes,
+            similarity_top_k=20,
         )
         
         vector_retriever = VectorIndexRetriever(
             index=vector_index, 
             similarity_top_k=30,
-            similarity_cutoff=0.7
+            similarity_cutoff=0.7,
         )
         
         hybrid_retriever = QueryFusionRetriever(
             [vector_retriever, bm25_retriever],
             similarity_top_k=40,
-            num_queries=1
+            num_queries=1,
         )
         
         custom_prompt_template = PromptTemplate(PROMPT_SIMPLE_POISK)
         response_synthesizer = get_response_synthesizer(
             response_mode=ResponseMode.COMPACT,
-            text_qa_template=custom_prompt_template
+            text_qa_template=custom_prompt_template,
         )
         
         query_engine = RetrieverQueryEngine(
             retriever=hybrid_retriever,
-            response_synthesizer=response_synthesizer
+            response_synthesizer=response_synthesizer,
         )
         
         log_message("Query engine успешно создан")