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app.py

@@ -112,7 +112,7 @@ def predict_product_sales_batch():
     file = request.files['file']
 
     # Read the CSV file into a Pandas DataFrame
-    input_data = pd.read_csv(file)
+    df = pd.read_csv(file)
 
     #Creating df with numeric features. 
     numeric_features = df[['Product_Weight', 'Product_Allocated_Area', 'Product_MRP', 'Store_Age']]
@@ -152,7 +152,7 @@ def predict_product_sales_batch():
 
     # Make predictions for all properties in the DataFrame (get log_prices)
     predicted_sales = model.predict(input_df).tolist()
-    prod_id_list = input_df['Product_Id'].tolist()
+    prod_id_list = df['Product_Id'].tolist()
 
     # Create a dictionary of predictions with property IDs as keys
     output_dict = dict(zip(prod_id_list, predicted_sales))