push

app.py

@@ -200,7 +200,7 @@ def process_query(user_input, history):
     # Step 1: Generate a search term based on the user query
     stream_search = client.chat_completion(
         model="Qwen/Qwen2.5-72B-Instruct",
-        messages=[{"role": "user", "content": f"Based on this chat history {history} the user's request '{user_input}', and this vector database {search_texts}, suggest a Google search term in a single line without specific dates; use 'this year', 'this month', etc. INCLUDE NOTHING IN YOUR RESPONSE EXCEPT THE RELEVANT SEARCH RESULT. EXAMPLE: USER: WHAT IS THE CURRENT PRICE OF COCA COLA STOCK. YOUR RESPONSE: WHAT IS THE CURRENT PRICE OF COCA COLA STOCK. here is their investor type, you can use it to specialise searches for their investor type{investor_type_value}"}],
+        messages=[{"role": "user", "content": f"Based on this chat history {history} the user's request '{user_input}', and this vector database {search_texts}, suggest a Google search term in a single line without specific dates; use 'this year', 'this month', etc. INCLUDE NOTHING IN YOUR RESPONSE EXCEPT THE RELEVANT SEARCH RESULT. EXAMPLE: USER: WHAT IS THE CURRENT PRICE OF COCA COLA STOCK. YOUR RESPONSE: WHAT IS THE CURRENT PRICE OF COCA COLA STOCK. here is their investor type."}],
         max_tokens=400,
         stream=True
     )