Update app.py

app.py

@@ -41,9 +41,9 @@ def add_new_eval(
 
     return 0
 
-# Function to update leaderboard dynamically based on user selection
-def update_leaderboard(selected_methods, selected_metrics):
-    return get_baseline_df(selected_methods, selected_metrics)
+def refresh_data():
+    df = get_baseline_df(method_names, metric_names)
+    return df
 
 block = gr.Blocks()
 
@@ -56,7 +56,7 @@ with block:
             leaderboard = get_baseline_df(None, None) #get baseline leaderboard without filtering
     
             method_names = leaderboard['Method'].unique().tolist()
-            metric_names = leaderboard(CSV_RESULT_PATH).columns.tolist()
+            metric_names = leaderboard.columns.tolist()
             metrics_with_method = metric_names.copy()
             metric_names.remove('Method')  # Remove method_name from the metric options
             
@@ -85,12 +85,12 @@ with block:
 
             # Update leaderboard when method/metric selection changes
             leaderboard_method_selector.change(
-                update_leaderboard, 
+                get_baseline_df, 
                 inputs=[leaderboard_method_selector, leaderboard_metric_selector], 
                 outputs=data_component
             )
             leaderboard_metric_selector.change(
-                update_leaderboard, 
+                get_baseline_df, 
                 inputs=[leaderboard_method_selector, leaderboard_metric_selector], 
                 outputs=data_component
             )
@@ -214,10 +214,6 @@ with block:
                 ],
             )
 
-    def refresh_data():
-        value = get_baseline_df(method_names, metric_names)
-        return value
-
     with gr.Row():
         data_run = gr.Button("Refresh")
         data_run.click(refresh_data, outputs=[data_component])