Update app.py

app.py

@@ -94,7 +94,7 @@ def load_and_classify_csv_dataframe(file, text_field, event_model, threshold):
     filters = list(result_df["event_label"].unique())
     extra_filters = ['Not-'+x for x in filters]+['All']
     
-    return gr.update(value=result_df), result_df, gr.update(choices=sorted(filters+extra_filters), 
+    return result_df, result_df, gr.update(choices=sorted(filters+extra_filters), 
                                                             value='All', 
                                                             label="Filter data by label", 
                                                             visible=True)
@@ -378,7 +378,7 @@ with gr.Blocks(fill_width=True) as demo:
         outputs=[T_data, T_data_ss_state, T_data_filter]
         )
     
-    T_data.select(T_on_select, None, T_tweet_embed, preprocess=False).then(fn=None, js="reloadTwitterWidgets()")
+    T_data.select(T_on_select, None, T_tweet_embed, trigger_mode="once").then(fn=None, js="reloadTwitterWidgets()")
     # T_data.select(
     #     fn=lambda: gr.update(value=""),
     #     outputs=T_tweet_embed).then(T_on_select, None, T_tweet_embed).then(fn=None, js="reloadTwitterWidgets()")
@@ -391,7 +391,7 @@ with gr.Blocks(fill_width=True) as demo:
             result_df = df[df["event_label"]!=filter.split('-')[1]].copy()
         else: 
             result_df = df[df["event_label"]==filter].copy()     
-        return gr.update(value=result_df) 
+        return result_df 
 
 
     # Button clicks ETC Eval