Update app.py

app.py

@@ -189,18 +189,25 @@ def optimize_query(
     # Initialize the language model
     #llm = HuggingFacePipeline(pipeline(model=llm_model))
 
+    print('---- optimize query ----')
     # Create a temporary vector store for query optimization
     temp_vector_store = get_vector_store(vector_store_type, chunks, embedding_model)
 
+    print('---- optimize query 2 ----')
+
     # Create a retriever with the temporary vector store
     temp_retriever = get_retriever(temp_vector_store, search_type, {"k": top_k})
 
+    print('---- optimize query 3 ----')
+    
     # Initialize MultiQueryRetriever with the temporary retriever and the language model
     multi_query_retriever = MultiQueryRetriever.from_llm(
         retriever=temp_retriever,
         llm=llm
     )
 
+    print('---- optimize query 4 ----')
+    #print(llm.invoke('Hello'))
     # Limit max time or set a timeout for LLM to avoid endless execution
     optimized_queries = multi_query_retriever.invoke(query, max_time=30)  # Timeout in seconds