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app.py

@@ -276,32 +276,53 @@ def handle_cancellation(user_query: str, raw_orders: str, order_status: str) ->
 
     else:
         return "Your order cannot be canceled. We hope to serve you again!"
-
-# Order chatbot tool
+#________________________________________________________________________________________________________________________
+# --- TOOL 1: Order Query Tool ---
 def order_chatbot(input_string: str) -> str:
-    """Fetch order details from database"""
+    """
+    Accepts a stringified dict input like:
+    "{'cust_id': 'C1016', 'user_message': 'Where is my order?'}"
+    Parses it, authenticates, fetches data, and returns structured info.
+    """
     try:
+        # Safely parse the input string into a Python dictionary
         data = ast.literal_eval(input_string)
+
+        # Extract customer ID and user message from the parsed data
         cust_id = data.get("cust_id")
         user_message = data.get("user_message")
     except Exception:
+        # If parsing fails, return a formatted error message
         return "⚠️ Invalid input format for OrderQueryTool."
 
+    # Step 1: Fetch order details from the database
     try:
+        # Query the database for all orders related to the given customer ID
         order_result = db_agent.invoke(f"SELECT * FROM orders WHERE cust_id = '{cust_id}';")
+
+        # Extract the output (raw order data) from the query result
         raw_orders = order_result.get("output") if order_result else None
     except Exception:
+        # Handle any database or query execution errors gracefully
         return "🚫 Sorry, we cannot fetch your order details right now. Please try again later."
 
+    # ✅ Return structured dictionary string for next tool
+    # Print raw orders for debugging/logging
+    #print(raw_orders)
+
+    # Return a stringified dictionary containing customer ID, query, and order data
     return str({
         "cust_id": cust_id,
         "user_query": user_message,
         "raw_orders": raw_orders
     })
 
-# Format customer response
+#---------------------------------------------------------------------------------------------------------------------------
 def format_customer_response(input_string: str) -> str:
-    """Generate final friendly message for customer"""
+    """
+    Receives the output from OrderQueryTool as stringified dict,
+    parses it, and generates the final friendly message.
+    """
     try:
         data = ast.literal_eval(input_string)
         cust_id = data.get("cust_id", "Unknown")
@@ -311,28 +332,35 @@ def format_customer_response(input_string: str) -> str:
         return "⚠️ Error: Could not parse order data properly."
 
     order_status = None
+    item_in_order = None
+    preparing_eta = None
+    delivery_time = None
 
+    # 🔹 Parse the raw order details line by line
     for line in raw_orders.splitlines():
         if "Order Status" in line:
             order_status = line.split(":", 1)[1].strip()
-        elif "order_status" in line.lower():
-            try:
-                order_status = line.split(":", 1)[1].strip().rstrip(",")
-            except:
-                pass
+        elif "Preparing ETA" in line:
+            preparing_eta = line.split(":", 1)[1].strip()
+        elif "Delivery Time" in line:
+            delivery_time = line.split(":", 1)[1].strip()
 
+    # 🔹 Check if user query needs escalation (e.g., delayed order or major issue)
     escalation_var = detect_escalation(user_query)
     if escalation_var == "Escalated":
         return (
-            f"Present status of your order is : {order_status.lower() if order_status else 'processing'}. "
-            "⚠️ Your issue requires immediate attention. "
+            f"Present status of your order is : {order_status.lower()}." +
+            "⚠️ Your issue requires immediate attention. " +
             "We have escalated your query to a human agent who will contact you shortly."
         )
 
-    cancel_response = handle_cancellation(user_query, raw_orders, order_status if order_status else "")
-    if cancel_response:
+    # 🔹 Handle cancellation requests (calls the function)
+    cancel_response = handle_cancellation(user_query, raw_orders, order_status)
+    if cancel_response:  # If function returns a valid message
         return cancel_response
 
+
+    # 🔹 Format normal order response using LLM
     system_prompt = f"""
     You are a friendly customer support assistant for FoodHub.
 
@@ -340,34 +368,51 @@ def format_customer_response(input_string: str) -> str:
     Here is the customer's order data from the database:
     {raw_orders}
 
+    Sample of raw_orders :
+    order_id: O12501,
+    cust_id: C1026,
+    order_time: 12:59,
+    order_status: preparing food,
+    payment_status: COD,
+    item_in_order: Burger, Fries, Soda,
+    preparing_eta: 13:14,
+    prepared_time: None,
+    delivery_eta: None,
+    delivery_time: None
+
     Instructions:
     1. Respond naturally and conversationally in a very short response.
-    2. Use only raw_orders data to answer the user's query.
-    3. Interpret the raw_orders into polite, concise, and customer-friendly responses.
-    4. If order_status = 'preparing food', include ETA from 'preparing_eta' and also include ETA from 'delivery_eta'.
+    2. Use only raw_oreders data to answer the user's query.
+    2. Interpret the raw_orders into polite, concise, and customer-friendly responses.
+    3. If order_status = 'preparing food', include ETA from 'preparing_eta' and also include ETA from 'delivery_eta'.
        - If 'delivery_eta' is missing or None, say: "Your order is being prepared, and Delivery ETA will be available soon."
-    5. If order_status = 'delivered', mention 'delivery_time'.
-    6. If order_status = 'canceled', explain politely.
-    7. If order_status = 'picked up', include ETA from 'delivery_eta'.
+    4. If order_status = 'delivered', mention 'delivery_time'.
+    5. If order_status = 'canceled', explain politely.
+    6. If order_status = 'picked up', include ETA from 'delivery_eta'.
        - If 'delivery_eta' is missing or None, say: "Your order has been picked up, delivery ETA will be available soon."
-    8. If user_query contains 'Where is my order' then provide the order_status from the raw_orders.
-    9. If user_query contains 'How many items' then provide the 'Items in Order' from the raw_orders and return only that number in a friendly way.
+    7. If user_query contains 'Where is my order' then provide the order_status from the raw_orders.
+    8. If user_query contains 'How many items' then provide the 'Items in Order' from the raw_orders and return only that number in a friendly way (e.g., “Your order contains 3 items.”).
+
     """
 
+    # Build user-specific prompt
     user_prompt = f"User Query: {user_query}"
 
+    # 🔹 Generate response using LLM (system + user messages)
     response_msg = llm.predict_messages([
         SystemMessage(content=system_prompt),
         HumanMessage(content=user_prompt)
     ])
 
+    # Clean and return the final LLM response
     response = response_msg.content.strip()
 
+    # Return fallback message if no response is generated
     if not response:
         return "Sorry, we could not retrieve your order details at this time."
-
     return response
 
+#------------------------------------------------------------------------------------------------------------------------------
 # Register Tools
 Order_Query_Tool = Tool(
     name="OrderQueryTool",
@@ -390,9 +435,11 @@ agent = initialize_agent(
     verbose=False
 )
 
-# Agent tool response
+# --- AGENT CONTROLLER ---
 def agent_tool_response(cust_id: str, user_query: str) -> str:
-    """Execute tools in correct sequence"""
+    """
+    Executes tools in correct sequence: OrderQueryTool → AnswerTool.
+    """
     agent_prompt = f"""
     You are FoodHub's Order Assistant.