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app.py

@@ -73,12 +73,12 @@ def predict_rental_price_batch():
     # Read the CSV file into a Pandas DataFrame
     input_data = pd.read_csv(file)
 
-    # Make predictions for all properties in the DataFrame (get log_prices)
+    # Make predictions for all properties in the DataFrame (get sales)
     predicted_sales = model.predict(input_data).tolist()
 
-    # Create a dictionary of predictions with property IDs as keys
-    property_ids = input_data['Product_Id'].tolist()  # Assuming 'id' is the property ID column
-    output_dict = dict(zip(property_ids, predicted_sales))  # Use actual prices
+    # Create a dictionary of predictions with product IDs as keys
+    product_ids = input_data['Product_Id'].tolist()  # Assuming 'product_id' is the product ID column
+    output_dict = dict(zip(product_ids, predicted_sales))  # Use actual sales
 
     # Return the predictions dictionary as a JSON response
     return output_dict