Update app.py

app.py

@@ -272,25 +272,31 @@ def transfer_learning_forecasting():
         time_taken = end_time - start_time
         st.success(f"Time taken for {model_choice} forecast: {time_taken:.2f} seconds")
 
-    tab_insample, tab_forecast  = st.tabs(
-                    ["Input data", "Forecast"]
-                )
-        
-    with tab_insample:
-        df_grid = df.drop(columns="unique_id")
-        st.write(df_grid)
-        # grid_table = AgGrid(
-        #                 df_grid,
-        #                 theme="alpine",
-        #             )
-
-    with tab_forecast:
-        df_grid = forecast_results[model_choice].drop(columns="unique_id")
-        st.write(df_grid)
-        # grid_table = AgGrid(
-        #                 df_grid,
-        #                 theme="alpine",
-        #             )
+        st.session_state.forecast_results = forecast_results
+
+    if 'forecast_results' in st.session_state:
+        forecast_results = st.session_state.forecast_results
+
+        st.markdwon('You can download Input and Forecast Data below')
+        tab_insample, tab_forecast  = st.tabs(
+                        ["Input data", "Forecast"]
+                    )
+            
+        with tab_insample:
+            df_grid = df.drop(columns="unique_id")
+            st.write(df_grid)
+            # grid_table = AgGrid(
+            #                 df_grid,
+            #                 theme="alpine",
+            #             )
+    
+        with tab_forecast:
+            df_grid = forecast_results[model_choice]
+            st.write(df_grid)
+            # grid_table = AgGrid(
+            #                 df_grid,
+            #                 theme="alpine",
+            #             )
 
 
 def dynamic_forecasting():