Update app.py

app.py

@@ -84,7 +84,7 @@ def predict_sale_price_batch():
     #predicted_prices = [round(float(np.exp(log_price)), 2) for log_price in predicted_log_prices]
 
     # Create a dictionary of predictions with property IDs as keys
-    product_id = input_data['id'].tolist()  # Assuming 'id' is the property ID column
+    product_id = input_data['Product_Id'].tolist()  # Assuming 'id' is the property ID column
     output_dict = dict(zip(product_id, predicted_prices))  # Use actual prices
 
     # Return the predictions dictionary as a JSON response