update

pages/leaderboard.py

@@ -24,6 +24,10 @@ df = pd.DataFrame(data)
 def update_leaderboard(sort_by):
     # In a real implementation, this would filter the data based on the category
     sorted_df = df.sort_values(by=sort_by, ascending=False)
+    
+    sorted_df.iloc[0]['Authors'] = sorted_df.iloc[0]['Authors'] + '🏅'
+    sorted_df.iloc[0]['Authors'] = sorted_df.iloc[0]['Authors'] + '🥈'
+    sorted_df.iloc[0]['Authors'] = sorted_df.iloc[0]['Authors'] + '🥉'
 
     # Update ranks based on new sorting
     sorted_df['Rank'] = range(1, len(sorted_df) + 1)
@@ -39,7 +43,7 @@ def update_leaderboard(sort_by):
     return html
 
 def create_leaderboard():
-    with gr.Blocks(theme=gr.themes.Soft(spacing_size="sm",text_size="sm"), css=custom_css) as demo:
+    with gr.Blocks(css=custom_css) as demo:
         gr.Markdown("# 🏆 Summarization Arena Leaderboard")
 
         with gr.Row():
@@ -47,11 +51,11 @@ def create_leaderboard():
 
         gr.Markdown("Welcome to our open platform for evaluating LLM summarization capabilities. We use the DATASET_NAME_PLACEHOLDER dataset to generate summaries with MODEL_NAME_PLACEHOLDER. These summaries are then evaluated by STRONGER_MODEL_NAME_PLACEHOLDER using the METRIC1_PLACEHOLDER and METRIC2_PLACEHOLDER metrics")
 
-        sort_by = gr.Dropdown(list(df.columns), label="Sort by", value="Rank")
+        sort_by = gr.Dropdown(list(df.columns), label="Sort by", value="Rouge Score")
 
         gr.Markdown("**Performance**\n\n**methods**: 5,   **questions**: 15")
 
-        leaderboard = gr.HTML(update_leaderboard("Rank"), elem_id="leaderboard")
+        leaderboard = gr.HTML(update_leaderboard("Rouge Score"), elem_id="leaderboard")
 
         sort_by.change(update_leaderboard, inputs=[sort_by], outputs=[leaderboard])