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app.py

@@ -78,7 +78,8 @@ def forecast_sales_batch():
     forcasted_sales = model.predict(input_data).tolist()
 
     # Calculate actual prices
-    forcasted_sales = [round(float(forcasted_sales), 2)]
+    forcasted_sales = [round(float(forcasted_sales), 2) for sales in forcasted_sales]
+    #round(float(np.exp(log_price)), 2) for log_price in predicted_log_prices
 
     # Create a dictionary of predictions with product IDs as keys
     product_ids = input_data['id'].tolist()  # Assuming 'id' is the product ID column