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app.py

@@ -91,7 +91,7 @@ def predict_product_sale_batch():
     input_data["Store_Age"] = current_year - input_data["Store_Establishment_Year"]
     input_data.drop("Store_Establishment_Year", axis=1, inplace=True)
 
-    # Make predictions for all properties in the DataFrame
+    # Make predictions for all products in the DataFrame
     predicted_sales = model.predict(input_data).tolist()
 
     # Create a dictionary of predictions with product IDs as keys
@@ -103,4 +103,5 @@ def predict_product_sale_batch():
 
 # Run the Flask application in debug mode if this script is executed directly
 if __name__ == '__main__':
-    SK_Sales_Forecast_api.run(debug=True)
+    #SK_Sales_Forecast_api.run(debug=True)
+    SK_Sales_Forecast_api.run(host="0.0.0.0", port=7860)