Update app.py

app.py

@@ -32,12 +32,7 @@ js = """
 """
 
 def T_on_select(evt: gr.SelectData):
-    # if evt.index[1] == 3:
-    #     html = """<blockquote id="tweet-container" class="twitter-tweet" data-dnt="true" data-theme="dark">""" + \
-    #            f"""\n<a href="https://twitter.com/anyuser/status/{evt.value}"></a></blockquote>"""
-    # else:
-    #     html = f"""<h2>{evt.value}</h2>"""
-    return evt.value #html 
+    return evt.value 
 
 def single_classification(text, event_model, threshold):
     res = classify(text, event_model, HFTOKEN, threshold)
@@ -200,22 +195,21 @@ with gr.Blocks(fill_width=True) as demo:
                     
         gr.Markdown("""Select an ID cell in dataframe to view Embedded tweet""")
         T_tweetID = gr.Textbox(visible=False)
-        
-        with gr.Row():
-            with gr.Column(scale=4):
-                with gr.Group():
+        with gr.Group():
+            with gr.Row():
+                with gr.Column(scale=3):
                     T_data_filter = gr.Dropdown(visible=False)
                     T_tweet_embed = gr.HTML("""<div id="tweet-container"></div>""")
-                
-            with gr.Column(scale=6):
-                T_data = gr.DataFrame(headers=["Texts", "event_label", "model_score", "IDs"], 
-                                      wrap=True,
-                                      show_fullscreen_button=True, 
-                                      show_copy_button=True,
-                                      show_row_numbers=True,
-                                      show_search="filter",
-                                      max_height=1000,
-                                      column_widths=["49%","17%","17%","17%"])
+                    
+                with gr.Column(scale=7):
+                    T_data = gr.DataFrame(headers=["Texts", "event_label", "model_score", "IDs"], 
+                                          wrap=True,
+                                          show_fullscreen_button=True, 
+                                          show_copy_button=True,
+                                          show_row_numbers=True,
+                                          show_search="filter",
+                                          max_height=1000,
+                                          column_widths=["49%","17%","17%","17%"])
 
     
 
@@ -247,7 +241,7 @@ with gr.Blocks(fill_width=True) as demo:
                               info="This value sets a threshold by which texts classified flood or fire are accepted, \
                                   higher values makes the classifier stricter (CAUTION: A value of 1 will set all predictions as none)", interactive=True)
         
-        with gr.Row(): # XXX confirm this is not a problem later --equal_height=True
+        with gr.Row(): 
             with gr.Column():
                 gr.Markdown("""### Flood-related""")
                 flood_checkbox_output = gr.CheckboxGroup(label="Select ONLY incorrect classifications", interactive=True)