Update utility.py

utility.py

@@ -82,13 +82,13 @@ def generateResponse(prompt,model='Meta-Llama-3.1-70B-Instruct'):
           Details: as a sublist of the key details like name of item, quantity, cost price, currency, unit for the quantity, description, among other details you are able to extract. 
       """
     sample_single_transaction_template = """
-      The information provided indicates that you want to **create/record** a new transaction.
-      **Extracted Information**:
+      The information provided indicates that you want to *create/record* a new transaction.
+      *Extracted Information*:
 
-      **Intent**: Create
+      *Intent*: Create
 
-      **Transaction Type**: Purchase
-      **Details**: 
+      *Transaction Type*: Purchase
+      *Details*: 
               - Item: Car
               - Purpose: Business
               - Quantity: 1
@@ -102,14 +102,14 @@ def generateResponse(prompt,model='Meta-Llama-3.1-70B-Instruct'):
     sample_multi_transaction_template = """
       The information provided indicates that you want to **create/record** a new transaction.
 
-      **Extracted Information**:
+      *Extracted Information*:
 
-      **Intent**: Create
+      *Intent*: Create
 
       Transaction 1: 
 
-      **Transaction Type**: Purchase
-      **Details**: 
+      *Transaction Type*: Purchase
+      *Details*: 
               - Item: Car
               - Purpose: Business
               - Quantity: 1
@@ -121,8 +121,8 @@ def generateResponse(prompt,model='Meta-Llama-3.1-70B-Instruct'):
 
       Transaction 2:
 
-      **Transaction Type**: Expense  
-      **Details**:  
+      *Transaction Type*: Expense  
+      *Details*:  
             - Item: Office Chair  
             - Quantity: 2
             - Unit: None
@@ -277,10 +277,10 @@ def read_datalake(user_phone, user_question):
 
     inventory_list = [doc.to_dict() for doc in inventory_ref.stream()]
     sales_list = [doc.to_dict() for doc in sales_ref.stream()]
-
+    
     inventory_df = pd.DataFrame(inventory_list)
     sales_df = pd.DataFrame(sales_list)
-    
+    return f"{inventory_df} \n\n {sales_df}"
 
     lake = SmartDatalake([inventory_df, sales_df], config={"llm": llm, "response_parser": FlaskResponse, "enable_cache": False, "save_logs": False})
     response = lake.chat(user_question)