remove manual counter

app.py

@@ -149,10 +149,11 @@ with gr.Blocks(css=custom_css, js=js_func, theme=gr.themes.Default(primary_hue=c
             leaderboard = gr.DataFrame(
                 value=filter_leaderboard('VerilogEval S2R', 'All', "", 700),
                 headers="first row",
+                show_row_numbers=True,
                 wrap=False,
-                datatype=["markdown", "markdown", "html",],
+                datatype=["markdown", "html",],
                 interactive=False,
-                column_widths=["4%", "5%", "28%", "10%", "14%"],)
+                column_widths=["5%", "28%", "10%", "14%"],)
         
         with gr.Tab("Interactive Bubble Plot"):
             with gr.Row():

utils.py

@@ -28,7 +28,7 @@ def filter_RTLRepo(subset: pd.DataFrame) -> pd.DataFrame:
     filtered_df['Type'] = filtered_df['Model Type'].map(lambda x: type_emoji.get(x, ""))
     filtered_df = filtered_df[['Type', 'Model', 'Params', 'Exact Matching (EM)']]
     filtered_df = filtered_df.sort_values(by='Exact Matching (EM)', ascending=False).reset_index(drop=True)
-    filtered_df.insert(0, '', range(1, len(filtered_df) + 1))
+    # filtered_df.insert(0, '', range(1, len(filtered_df) + 1))
     return filtered_df
 
 def filter_bench(subset: pd.DataFrame) -> pd.DataFrame:
@@ -42,7 +42,7 @@ def filter_bench(subset: pd.DataFrame) -> pd.DataFrame:
     columns_order = ['Type', 'Model', 'Params', 'Average ⬆️', 'STX', 'FNC', 'SYN', 'Power', 'Perf', 'Area']
     pivot_df = pivot_df[[col for col in columns_order if col in pivot_df.columns]]
     pivot_df = pivot_df.sort_values(by='Average ⬆️', ascending=False).reset_index(drop=True)
-    pivot_df.insert(0, '', range(1, len(pivot_df) + 1))
+    # pivot_df.insert(0, '', range(1, len(pivot_df) + 1))
     return pivot_df
 
 def filter_bench_all(subset: pd.DataFrame) -> pd.DataFrame:
@@ -64,5 +64,5 @@ def filter_bench_all(subset: pd.DataFrame) -> pd.DataFrame:
     columns_order = ['Type', 'Model', 'Params', '🐢 Score (Avg of all) ⬆️', 'Avg EM', 'Avg STX', 'Avg FNC', 'Avg SYN', 'Avg Power', 'Avg Perf', 'Avg Area']
     pivot_df = pivot_df[[col for col in columns_order if col in pivot_df.columns]]
     pivot_df = pivot_df.sort_values(by='🐢 Score (Avg of all) ⬆️', ascending=False).reset_index(drop=True)
-    pivot_df.insert(0, '', range(1, len(pivot_df) + 1))
+    # pivot_df.insert(0, '', range(1, len(pivot_df) + 1))
     return pivot_df