Update app.py

app.py

@@ -9,9 +9,12 @@ with open('best_arima_models.pkl', 'rb') as f:
 
 def predict_demand(mapped_code, num_months):
     try:
+        print(f"Received mapped code: {mapped_code}")
+        print(f"Number of months for prediction: {num_months}")
+        
         # Retrieve the specific model for the mapped code
         if mapped_code not in model:
-            return f"No model found for Mapped Code: {mapped_code}"
+            return None, f"No model found for Mapped Code: {mapped_code}"
         
         model_for_code = model[mapped_code]
         
@@ -21,6 +24,7 @@ def predict_demand(mapped_code, num_months):
         # Make predictions
         future_steps = len(dates)
         forecast = model_for_code.forecast(steps=future_steps)
+        print(f"Forecast: {forecast}")
 
         # Prepare a DataFrame for display
         df = pd.DataFrame({
@@ -28,11 +32,11 @@ def predict_demand(mapped_code, num_months):
             'Predicted Demand': forecast
         })
 
-        return df
+        return df, None
     
     except Exception as e:
         print(f"Error occurred: {e}")
-        return f"An error occurred: {str(e)}"
+        return None, f"An error occurred: {str(e)}"
 
 # Gradio Interface Definition
 gr.Interface(
@@ -42,8 +46,9 @@ gr.Interface(
         gr.Slider(minimum=1, maximum=12, step=1, label="Number of Months")
     ],
     outputs=[
-        gr.Dataframe(label="Predicted Demand")
+        gr.Dataframe(label="Predicted Demand"),
+        gr.Textbox(label="Error Message")
     ],
     title="Demand Forecasting",
     description="Enter the mapped code and the number of months to predict future demand."
-).launch(share=True)
+).launch()