Update app.py

app.py

@@ -135,20 +135,21 @@ Search Query: transformer architectures
 User Question: What is the history of the transformer model?
 Search Query: transformer model history
 """
+
+# remove strange char like *,/
 def clean_text(text):
     cleaned = re.sub(r'[^\x00-\x7F]+', '', text)  # Remove non-ASCII chars
     cleaned = re.sub(r'[^a-zA-Z0-9_\- ]', '', cleaned) #Then your original rule
     return cleaned
+    
 def to_query(provider,question):
-    print(f"<question> = {question}")
-    print(f"<query sytem> = {query_system}")
+
     try:
         query_agent = LlamaCppAgent(
                 provider,
                 system_prompt=f"{query_system}",
-                #system_prompt="you are kind assistant",
                 predefined_messages_formatter_type=MessagesFormatterType.GEMMA_2,
-                debug_output=True,
+                debug_output=False,
             )
 
         message="""
@@ -157,12 +158,10 @@ User Question: %s
 Search Query:
     """%question
         
-        print("<message>")
-        print(message)
+
         settings = provider.get_provider_default_settings()
         messages = BasicChatHistory()
         result = query_agent.get_chat_response(
-                #query_system+message,
                 message,
                 llm_sampling_settings=settings,
                 chat_history=messages,
@@ -202,6 +201,9 @@ def respond(
     Returns:
         str: The response to the message.
     """
+    if model is None:#
+        return
+        
     try:
         # Load the global variables
         global llm
@@ -222,17 +224,10 @@ def respond(
         provider = LlamaCppPythonProvider(llm)
 
         query = to_query(provider,message)
-        print("<query>")
-        print(f"from {message} to {query}")
         text = retriever_tool(query=f"{query}")
 
-        retriever_system="""
-        You are an AI assistant that answers questions based on documents provided by the user.  Wait for the user to send a document. Once you receive the document, carefully read its contents and then answer the following question:
-
-Question: %s
 
-Document:
-        """ % message
+        #very sensitive against prompt
         retriever_system="""
         You are an AI assistant that answers questions based on below retrievered documents.
         
@@ -243,7 +238,6 @@ Documents:
 Question: %s
 Answer:
         """ % (text,message)
-#[Wait for user's document]
         
         # Create the agent
         agent = LlamaCppAgent(
@@ -251,7 +245,7 @@ Answer:
             #system_prompt=f"{retriever_system}",
             system_prompt="you are kind assistant",
             predefined_messages_formatter_type=MessagesFormatterType.GEMMA_2,
-            debug_output=True,
+            debug_output=False,
         )
 
         # Set the settings like temperature, top-k, top-p, max tokens, etc.
@@ -261,7 +255,7 @@ Answer:
         settings.top_p = top_p
         settings.max_tokens = max_tokens
         settings.repeat_penalty = repeat_penalty
-        settings.stream = True
+        settings.stream = False
 
         messages = BasicChatHistory()