Add timer-based auto-refresh for leaderboard data

When background data refresh occurs, the UI now automatically updates
within 60 seconds without requiring a page reload. This fixes the issue
where new results pushed to the GitHub repo weren't reflected on the
live site until the HF Space container was restarted.

Changes:
- Add data version tracking to detect when cache is cleared
- Add gr.Timer() that checks for data updates every 60 seconds
- Automatically refresh DataFrame and Plot components when new data is available

ui_components.py

@@ -365,6 +365,13 @@ plot_legend_html = f"""
 CACHED_VIEWERS = {}
 CACHED_TAG_MAPS = {}
 _cache_lock = __import__('threading').Lock()
+_data_version = 0  # Incremented when data is refreshed
+
+
+def get_data_version():
+    """Get the current data version number."""
+    global _data_version
+    return _data_version
 
 
 def clear_viewer_cache():
@@ -372,11 +379,12 @@ def clear_viewer_cache():
     Clear all cached viewers and tag maps.
     Called when data is refreshed from the background scheduler.
     """
-    global CACHED_VIEWERS, CACHED_TAG_MAPS
+    global CACHED_VIEWERS, CACHED_TAG_MAPS, _data_version
     with _cache_lock:
         CACHED_VIEWERS.clear()
         CACHED_TAG_MAPS.clear()
-        print("[CACHE] Viewer cache cleared after data refresh")
+        _data_version += 1
+        print(f"[CACHE] Viewer cache cleared after data refresh (version: {_data_version})")
 
 
 # Register the cache clear callback with the data refresh system
@@ -457,7 +465,13 @@ def create_leaderboard_display(
     """
     This UI factory takes pre-loaded data and renders the main DataFrame and Plot
     for a given category (e.g., "Overall" or "Literature Understanding").
+    
+    The display includes a timer that periodically checks for data updates and
+    refreshes the UI when new data is available.
     """
+    # Track the data version when this display was created
+    initial_data_version = get_data_version()
+    
     # 1. Instantiate the transformer and get the specific view for this category.
     # The function no longer loads data itself; it filters the data it receives.
     transformer = DataTransformer(full_df, tag_map)
@@ -664,6 +678,75 @@ def create_leaderboard_display(
         
         legend_markdown = create_legend_markdown(category_name)
         gr.HTML(value=legend_markdown, elem_id="legend-markdown")
+    
+    # Add a timer to periodically check for data updates and refresh the UI
+    # This runs every 60 seconds to check if new data is available
+    def check_and_refresh_data(current_checkbox_state):
+        """Check if data has been refreshed and return updated data if so."""
+        current_version = get_data_version()
+        if current_version > initial_data_version:
+            # Data has been refreshed, reload it
+            print(f"[REFRESH] Data version changed from {initial_data_version} to {current_version}, reloading...")
+            new_df, new_tag_map = get_full_leaderboard_data(split_name)
+            if not new_df.empty:
+                new_transformer = DataTransformer(new_df, new_tag_map)
+                new_df_view_full, _ = new_transformer.view(tag=category_name, use_plotly=True)
+                
+                # Prepare both complete and all entries versions
+                if 'Categories Attempted' in new_df_view_full.columns:
+                    new_df_view_complete = new_df_view_full[new_df_view_full['Categories Attempted'] == '5/5'].copy()
+                else:
+                    new_df_view_complete = new_df_view_full.copy()
+                
+                new_df_display_complete = prepare_df_for_display(new_df_view_complete)
+                new_df_display_all = prepare_df_for_display(new_df_view_full)
+                
+                # Create new scatter plots
+                new_scatter_complete = create_scatter_plot(new_df_view_complete) if len(new_df_display_complete) > 0 else go.Figure()
+                new_scatter_all = create_scatter_plot(new_df_view_full)
+                
+                # Return the appropriate data based on checkbox state
+                if current_checkbox_state:
+                    return new_df_display_all, new_scatter_all
+                else:
+                    return new_df_display_complete, new_scatter_complete
+        
+        # No change, return current values
+        if current_checkbox_state:
+            return df_display_all, scatter_plot_all
+        else:
+            return df_display_complete, scatter_plot_complete
+    
+    # Create a timer that checks for updates every 60 seconds
+    refresh_timer = gr.Timer(value=60)
+    
+    # Connect the timer to the refresh function
+    if show_incomplete_checkbox is not None:
+        refresh_timer.tick(
+            fn=check_and_refresh_data,
+            inputs=[show_incomplete_checkbox],
+            outputs=[dataframe_component, plot_component]
+        )
+    else:
+        # If no checkbox, always show all data
+        def check_and_refresh_all():
+            current_version = get_data_version()
+            if current_version > initial_data_version:
+                print(f"[REFRESH] Data version changed, reloading...")
+                new_df, new_tag_map = get_full_leaderboard_data(split_name)
+                if not new_df.empty:
+                    new_transformer = DataTransformer(new_df, new_tag_map)
+                    new_df_view_full, _ = new_transformer.view(tag=category_name, use_plotly=True)
+                    new_df_display_all = prepare_df_for_display(new_df_view_full)
+                    new_scatter_all = create_scatter_plot(new_df_view_full)
+                    return new_df_display_all, new_scatter_all
+            return df_display_all, scatter_plot_all
+        
+        refresh_timer.tick(
+            fn=check_and_refresh_all,
+            inputs=[],
+            outputs=[dataframe_component, plot_component]
+        )
 
     # Return the components so they can be referenced elsewhere.
     return plot_component, dataframe_component