Update app.py

app.py

@@ -236,8 +236,6 @@ def transfer_learning_forecasting():
             grid_table = AgGrid(
                             df_grid,
                             theme="alpine",
-                            fit_columns_on_grid_load=True,
-                            height=360,
                         )
 
         with tab_forecast:
@@ -245,8 +243,6 @@ def transfer_learning_forecasting():
             grid_table = AgGrid(
                             df_grid,
                             theme="alpine",
-                            fit_columns_on_grid_load=True,
-                            height=360,
                         )
             
     with col2:
@@ -263,9 +259,10 @@ def transfer_learning_forecasting():
             forecast_results['LSTM'] = generate_forecast(lstm_model, df)
         elif model_choice == "TFT":
             forecast_results['TFT'] = generate_forecast(tft_model, df)
-    
-        for model_name, forecast_df in forecast_results.items():
-            plot_forecasts(forecast_df, df, f'{model_name} Forecast for {y_col}')
+
+        if st.sidebar.button("Submit"):
+            for model_name, forecast_df in forecast_results.items():
+                plot_forecasts(forecast_df, df, f'{model_name} Forecast for {y_col}')
     
         end_time = time.time()  # End timing
         time_taken = end_time - start_time
@@ -304,8 +301,8 @@ def dynamic_forecasting():
     dynamic_horizon = st.sidebar.number_input("Forecast horizon", value=18)
     dynamic_max_steps = st.sidebar.number_input('Max steps', value=200)
 
-    
-    forecast_time_series(df, dynamic_model_choice, dynamic_horizon, dynamic_max_steps,y_col)
+    if st.sidebar.button("Submit"):
+        forecast_time_series(df, dynamic_model_choice, dynamic_horizon, dynamic_max_steps,y_col)
 
 pg = st.navigation({
     "Overview": [