still trying to make the leaderboard

app.py

@@ -29,7 +29,10 @@ def evaluate_boundary(filename):
 def get_leaderboard():
     ds = load_dataset(results_repo, split='train')
     df = pd.DataFrame(ds)
-    
+
+    df.rename(columns={'submission_time': 'submission time', 'problem_type': 'problem type'}, inplace=True)
+    df['user'] = df['user'].apply(lambda x: f'<a href="https://huggingface.co/{x}">{x}</a>')
+
     score_field = "score" if "score" in df.columns else "objective"  # fallback
 
     df = df.sort_values(by=score_field, ascending=True)
@@ -46,10 +49,10 @@ def gradio_interface() -> gr.Blocks:
 
                 Leaderboard(
                     value=get_leaderboard(),
-                    select_columns=["submission_time", "feasibility", "score", "objective", "user"],
-                    search_columns=["submission_time", "score", "user"],
+                    select_columns=["submission time", "feasibility", "score", "problem type", "objective", "user"],
+                    search_columns=["submission time", "score", "user"],
                     hide_columns=["result_filename", "submission_filename", "minimize_objective", "boundary_json", "evaluated"],
-                    filter_columns=["problem_type"],
+                    filter_columns=["problem type"],
                     every=60,
                 )
 
@@ -100,11 +103,6 @@ def gradio_interface() -> gr.Blocks:
                     inputs=[filename],
                     outputs=[eval_state]
                 )
-                '''.then(
-                    fn=update_leaderboard,
-                    inputs=[problem_type],
-                    outputs=[leaderboard_df]
-                )'''
  
     return demo