Update app.py

app.py

@@ -171,7 +171,7 @@ def interact_with_salesforce(mode, entry_type, quantity, attributes):
             query_conditions = [f"{product_field_name} = '{attributes['Product name']}'"]
             if "Model Name" in attributes and attributes["Model Name"]:
                 query_conditions.append(f"{model_field_name} = '{attributes['Model Name']}'")
-            if "Stage" in attributes and attributes["Stage"]:
+            if "Stage" in attributes and attributes["Stage"] != "":
                 query_conditions.append(f"{stage_field_name} = '{attributes['Stage']}'")
             if "H.P." in attributes and attributes["H.P."]:
                 query_conditions.append(f"{hp_field_name} = '{attributes['H.P.']}'")
@@ -220,10 +220,49 @@ def export_to_salesforce(mode, entry_type, quantity, edited_df):
     try:
         # Convert edited DataFrame back to dictionary
         edited_attributes = dict(zip(edited_df["Attribute"], edited_df["Value"]))
-       
+
         # Export to Salesforce
         message = interact_with_salesforce(mode, entry_type, quantity, edited_attributes)
-        return message
+
+        # Fetch the price from Inventory_Management__c based on attributes
+        try:
+            sf = Salesforce(
+                username=SALESFORCE_USERNAME,
+                password=SALESFORCE_PASSWORD,
+                security_token=SALESFORCE_SECURITY_TOKEN
+            )
+            product_name = edited_attributes.get("Product name", "")
+            model_name = edited_attributes.get("Model Name", "")
+            stage = edited_attributes.get("Stage", "")
+
+            # Build the query
+            query_conditions = []
+            if product_name:
+                query_conditions.append(f"Productname__c = '{product_name}'")
+            if model_name:
+                query_conditions.append(f"Model__c = '{model_name}'")
+            if stage:
+                query_conditions.append(f"Stage__c = '{stage}'")
+
+            if query_conditions:
+                query = f"SELECT Price__c FROM Inventory_Management__c WHERE {' AND '.join(query_conditions)} LIMIT 1"
+                response = sf.query(query)
+
+                if response["records"]:
+                    price = response["records"][0].get("Price__c", None)
+                    if price:
+                        price_message = f"The estimated price for the {product_name} with {model_name} at {stage} is ₹{price:,}."
+                        return f"{message}\n\n{price_message}"
+                    else:
+                        return f"{message}\n\nPrice information not available for the specified product."
+                else:
+                    return f"{message}\n\nNo matching record found for the specified product."
+            else:
+                return f"{message}\n\nInsufficient data to fetch price information."
+
+        except Exception as e:
+            return f"{message}\n\nError fetching price information: {str(e)}"
+
     except Exception as e:
         return f"❌ Error exporting to Salesforce: {str(e)}"
 
@@ -239,9 +278,9 @@ def pull_data_from_salesforce(data_type):
         )
        
         if data_type == "Inventory":
-            query = "SELECT Productname__c, Model__c, H_p__c, Stage__c, Current_Stocks__c, soldstock__c, Price__c FROM Inventory_Management__c LIMIT 100"
+            query = "SELECT Productname__c, Model__c, H_p__c, Stage__c, Current_Stocks__c, soldstock__c,Last_Modified_Date__c FROM Inventory_Management__c LIMIT 100"
         else:
-            query = "SELECT Productname__c, Model__c, H_p__c, Stage__c, Current_Stock__c, soldstock__c, Price__c FROM Un_Billable__c LIMIT 100"
+            query = "SELECT Productname__c, Model__c, H_p__c, Stage__c, Current_Stock__c, soldstock__c, Last_Modified_Date__c FROM Un_Billable__c LIMIT 100"
        
         response = sf.query_all(query)
         records = response.get("records", [])
@@ -251,6 +290,11 @@ def pull_data_from_salesforce(data_type):
        
         df = pd.DataFrame(records)
         df = df.drop(columns=['attributes'], errors='ignore')
+
+        # Format the Last_Modified_Date__c field to show only the date
+        if "Last_Modified_Date__c" in df.columns:
+            df["Last_Modified_Date__c"] = pd.to_datetime(df["Last_Modified_Date__c"]).dt.date
+
        
         # Rename columns for better readability
         df.rename(columns={
@@ -261,7 +305,7 @@ def pull_data_from_salesforce(data_type):
             "Current_Stocks__c": "Current Stocks",
             "Current_Stock__c": "Current Stocks",
             "soldstock__c": "Sold Stock",
-            "Price__c": "Price"
+            "Last_Modified_Date__c": "Last Modified Date"
         }, inplace=True)
        
         excel_path = "salesforce_data.xlsx"