Update app.py

app.py

@@ -67,14 +67,23 @@ similarity_model = SentenceTransformer('all-MiniLM-L6-v2')
 
 
 def determine_query_type(query: str, chat_history: str, llm_client) -> str:
-    system_prompt = """You are an intelligent agent tasked with determining whether a user query requires a web search or can be answered using the AI's existing knowledge base. Your task is to analyze the query and decide on the appropriate action.
+    system_prompt = """You are Sentinel, an intelligent AI agent tasked with determining whether a user query requires a web search or can be answered using your existing knowledge base. Your task is to analyze the query and decide on the appropriate action.
 
-    Instructions:
+    Instructions for Sentinel:
     1. If the query is a general conversation starter, greeting, or can be answered without real-time information, classify it as "knowledge_base".
     2. If the query requires up-to-date information, news, or specific data that might change over time, classify it as "web_search".
     3. Consider the chat history when making your decision.
     4. Respond with ONLY "knowledge_base" or "web_search".
 
+    Instructions for users (include this in your first interaction):
+    "Hello! I'm Sentinel, your AI assistant. I can help you with various tasks and answer your questions. Here's how to get the best results:
+    - For general knowledge questions or conversational topics, just ask normally.
+    - For recent news, current events, or real-time data, mention that you need up-to-date information.
+    - If you're unsure, you can ask 'Do you need to search the web for this?'
+    - Feel free to ask follow-up questions or request clarification on any topic.
+
+    How can I assist you today?"
+
     Examples:
     - "Hi, how are you?" -> "knowledge_base"
     - "What's the latest news in the US?" -> "web_search"
@@ -106,7 +115,7 @@ def determine_query_type(query: str, chat_history: str, llm_client) -> str:
         return "web_search" if decision == "web_search" else "knowledge_base"
     except Exception as e:
         logger.error(f"Error determining query type: {e}")
-        return "web_search"  # Default to web search if there's an error
+        return "web_search"  # Default to web search if there's an error  # Default to web search if there's an error
 
 def generate_ai_response(query: str, chat_history: str, llm_client, model: str) -> str:
     system_prompt = """You are a helpful AI assistant. Provide a concise and informative response to the user's query based on your existing knowledge. Do not make up information or claim to have real-time data."""