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app.py

@@ -81,9 +81,13 @@ def predict_product_sale_price_batch():
     predicted_prices = [round(float(np.exp(total_sale_price)), 2) for total_sale_price in predicted_Product_Store_Sales_Total]
 
     # Create a dictionary of predictions with product IDs as keys
-    product_ids = input_data['id'].tolist()  # Assuming 'id' is the product ID column
+    product_ids = input_data['Product_Id'].tolist()  # Assuming 'id' is the product ID column
     output_dict = dict(zip(product_ids, predicted_prices))  # Use actual prices
 
+    # Create a dictionary of predictions with Store IDs as keys
+    store_ids = input_data['Store_Id'].tolist()
+    output_dict = dict(zip(store_ids, predicted_prices))  # Use actual prices
+
     # Return the predictions dictionary as a JSON response
     return output_dict