adding sorting

app.py

@@ -24,26 +24,33 @@ def get_leaderboard():
 
     return full_df
 
-def format_dataframe(df, show_percentage=False, selected_groups=None):
+def format_dataframe(df, show_percentage=False, selected_groups=None, compact_view=True):
     """Format the dataframe with proper column names and optional percentages."""
     if len(df) == 0:
         return df
 
-    # Build column list based on selected metric groups
+    # Build column list based on view mode
     selected_cols = ['run_name']
-    if 'n_structures' in df.columns:
-        selected_cols.append('n_structures')
 
-    # If no groups selected, show all
-    if not selected_groups:
-        selected_groups = list(METRIC_GROUPS.keys())
-
-    # Add columns from selected groups
-    for group in selected_groups:
-        if group in METRIC_GROUPS:
-            for col in METRIC_GROUPS[group]:
-                if col in df.columns and col not in selected_cols:
-                    selected_cols.append(col)
+    if compact_view:
+        # Use predefined compact columns
+        from about import COMPACT_VIEW_COLUMNS
+        selected_cols = [col for col in COMPACT_VIEW_COLUMNS if col in df.columns]
+    else:
+        # Build from selected groups
+        if 'n_structures' in df.columns:
+            selected_cols.append('n_structures')
+
+        # If no groups selected, show all
+        if not selected_groups:
+            selected_groups = list(METRIC_GROUPS.keys())
+
+        # Add columns from selected groups
+        for group in selected_groups:
+            if group in METRIC_GROUPS:
+                for col in METRIC_GROUPS[group]:
+                    if col in df.columns and col not in selected_cols:
+                        selected_cols.append(col)
 
     # Create a copy with selected columns
     display_df = df[selected_cols].copy()
@@ -93,10 +100,25 @@ def apply_color_styling(display_df, original_cols):
     # Apply the styling function
     return display_df.style.apply(style_by_group, axis=None)
 
-def update_leaderboard(show_percentage, selected_groups):
-    """Update the leaderboard based on user selections."""
-    df = get_leaderboard()
-    formatted_df = format_dataframe(df, show_percentage, selected_groups)
+def update_leaderboard(show_percentage, selected_groups, compact_view, cached_df, sort_by, sort_direction):
+    """Update the leaderboard based on user selections.
+
+    Uses cached dataframe to avoid re-downloading data on every change.
+    """
+    # Use cached dataframe instead of re-downloading
+    df_to_format = cached_df.copy()
+
+    # Convert display name back to raw column name for sorting
+    if sort_by and sort_by != "None":
+        # Create reverse mapping from display names to raw column names
+        display_to_raw = {v: k for k, v in COLUMN_DISPLAY_NAMES.items()}
+        raw_column_name = display_to_raw.get(sort_by, sort_by)
+
+        if raw_column_name in df_to_format.columns:
+            ascending = (sort_direction == "Ascending")
+            df_to_format = df_to_format.sort_values(by=raw_column_name, ascending=ascending)
+
+    formatted_df = format_dataframe(df_to_format, show_percentage, selected_groups, compact_view)
     return formatted_df
 
 def show_output_box(message):
@@ -149,28 +171,49 @@ def gradio_interface() -> gr.Blocks:
 
                 # Display options
                 with gr.Row():
-                    with gr.Column(scale=2):
-                        selected_groups = gr.CheckboxGroup(
-                            choices=list(METRIC_GROUPS.keys()),
-                            value=list(METRIC_GROUPS.keys()),
-                            label="Metric Families",
-                            info="Select which metric groups to display"
-                        )
                     with gr.Column(scale=1):
+                        compact_view = gr.Checkbox(
+                            value=True,
+                            label="Compact View",
+                            info="Show only key metrics"
+                        )
                         show_percentage = gr.Checkbox(
                             value=True,
                             label="Show as Percentages",
                             info="Display count-based metrics as percentages of total structures"
                         )
+                    with gr.Column(scale=1):
+                        # Create choices with display names, but values are the raw column names
+                        sort_choices = ["None"] + [COLUMN_DISPLAY_NAMES.get(col, col) for col in COLUMN_DISPLAY_NAMES.keys()]
+                        sort_by = gr.Dropdown(
+                            choices=sort_choices,
+                            value="None",
+                            label="Sort By",
+                            info="Select column to sort by"
+                        )
+                        sort_direction = gr.Radio(
+                            choices=["Ascending", "Descending"],
+                            value="Descending",
+                            label="Sort Direction"
+                        )
+                    with gr.Column(scale=2):
+                        selected_groups = gr.CheckboxGroup(
+                            choices=list(METRIC_GROUPS.keys()),
+                            value=list(METRIC_GROUPS.keys()),
+                            label="Metric Families (only active when Compact View is off)",
+                            info="Select which metric groups to display"
+                        )
 
                 # Metric legend with color coding
                 with gr.Accordion("Metric Groups Legend", open=False):
                     gr.HTML(generate_metric_legend_html())
 
                 try:
-                    # Initial dataframe
+                    # Initial dataframe - load once and cache
                     initial_df = get_leaderboard()
-                    formatted_df = format_dataframe(initial_df, show_percentage=True, selected_groups=list(METRIC_GROUPS.keys()))
+                    cached_df_state = gr.State(initial_df)
+
+                    formatted_df = format_dataframe(initial_df, show_percentage=True, selected_groups=list(METRIC_GROUPS.keys()), compact_view=True)
 
                     leaderboard_table = gr.Dataframe(
                         label="GenBench Leaderboard",
@@ -181,15 +224,30 @@ def gradio_interface() -> gr.Blocks:
                         show_fullscreen_button=True
                     )
 
-                    # Update dataframe when options change
+                    # Update dataframe when options change (using cached data)
                     show_percentage.change(
                         fn=update_leaderboard,
-                        inputs=[show_percentage, selected_groups],
+                        inputs=[show_percentage, selected_groups, compact_view, cached_df_state, sort_by, sort_direction],
                         outputs=leaderboard_table
                     )
                     selected_groups.change(
                         fn=update_leaderboard,
-                        inputs=[show_percentage, selected_groups],
+                        inputs=[show_percentage, selected_groups, compact_view, cached_df_state, sort_by, sort_direction],
+                        outputs=leaderboard_table
+                    )
+                    compact_view.change(
+                        fn=update_leaderboard,
+                        inputs=[show_percentage, selected_groups, compact_view, cached_df_state, sort_by, sort_direction],
+                        outputs=leaderboard_table
+                    )
+                    sort_by.change(
+                        fn=update_leaderboard,
+                        inputs=[show_percentage, selected_groups, compact_view, cached_df_state, sort_by, sort_direction],
+                        outputs=leaderboard_table
+                    )
+                    sort_direction.change(
+                        fn=update_leaderboard,
+                        inputs=[show_percentage, selected_groups, compact_view, cached_df_state, sort_by, sort_direction],
                         outputs=leaderboard_table
                     )