Update model.py

model.py

@@ -1121,8 +1121,10 @@ def query_document_info(query_word, alternative_query_word, metadata, master_str
     if run_rag:
         print("try run rag")
         # Determine the phrase for LLM query
-        rag_query_phrase = f"'{query_word}'"
-        if alternative_query_word_cleaned and alternative_query_word_cleaned != query_word:
+        rag_query_phrase = ""
+        if query_word.lower() != "unknown":
+            rag_query_phrase += f"'{query_word}'"
+        if alternative_query_word_cleaned and alternative_query_word_cleaned != query_word and alternative_query_word_cleaned.lower() != "unknown":
             rag_query_phrase += f" or its alternative word '{alternative_query_word_cleaned}'"
 
         # Construct a more specific semantic query phrase for embedding if structured info is available
@@ -1301,7 +1303,7 @@ def query_document_info(query_word, alternative_query_word, metadata, master_str
     f"The text explicitly states BRU18 in the context of brunei (borneo), indicating the country and a broader geographic region within that country."
     f"The study is published in a journal, implying research on living individuals, hence modern."
 )
-
+        print("this is prompt: ", prompt_for_llm)
         if model_ai:
           print("back up to ", model_ai)
           llm_response_text, model_instance = call_llm_api(prompt_for_llm, model=model_ai)