hybrid format + llm + keywoard, + 4000, 30

config.py

@@ -51,7 +51,7 @@ DEFAULT_MODEL = "Gemini 2.5 Flash"
 CHUNK_SIZE = 1500
 CHUNK_OVERLAP = 128
 
-MAX_CHARS_TABLE = 3000
+MAX_CHARS_TABLE = 4000
 MAX_ROWS_TABLE = 30
 
 

utils.py

@@ -197,7 +197,7 @@ def debug_search_tables(vector_index, search_term="С-25"):
 
 GENERIC_STEEL_CONTEXT = "стандарт ГОСТ технические условия марка материал применение сварка"
 
-
+from config import QUERY_EXPANSION_PROMPT
 from documents_prep import normalize_text, normalize_steel_designations
 
 STEEL_PRODUCT_EXPANSIONS = {
@@ -264,9 +264,23 @@ def answer_question(question, query_engine, reranker, current_model, chunks_df=N
     normalized_question = normalize_text(question)
     normalized_question_2, query_changes, change_list = normalize_steel_designations(question)
     
-    # FIX: Add query enhancement for steel grades
+    # Step 1: Keyword-based enhancement (existing)
     enhanced_question = enhance_query_for_steel_grades(normalized_question_2)
     
+    # Step 2: LLM-based query expansion (NEW)
+    try:
+        llm = get_llm_model(current_model)
+        expansion_prompt = QUERY_EXPANSION_PROMPT.format(original_query=enhanced_question)
+        expanded_queries = llm.complete(expansion_prompt).text.strip()
+        
+        # Combine original + expanded queries
+        enhanced_question = f"{enhanced_question} {expanded_queries}"
+        log_message(f"LLM expanded query: {expanded_queries[:200]}...")
+    except Exception as e:
+        log_message(f"Query expansion failed: {e}, using keyword-only enhancement")
+    
+    if change_list:
+        log_message(f"Query changes: {', '.join(change_list)}")
     if change_list:
         log_message(f"Query changes: {', '.join(change_list)}")    
     if query_engine is None:
@@ -274,12 +288,11 @@ def answer_question(question, query_engine, reranker, current_model, chunks_df=N
     
     try:
         start_time = time.time()
-        # FIX: Use enhanced_question instead of normalized_question_2
         retrieved_nodes = query_engine.retriever.retrieve(enhanced_question)
         log_message(f"user query: {question}")
         log_message(f"normalized query: {normalized_question}")
         log_message(f"after steel normalization: {normalized_question_2}")
-        log_message(f"enhanced query: {enhanced_question}")  # ADD THIS LOG
+        log_message(f"enhanced query: {enhanced_question}") 
         log_message(f"Steel grades normalized in query: {query_changes}")
         
         log_message(f"RETRIEVED: {len(retrieved_nodes)} nodes")