style theme

app.py

@@ -266,9 +266,9 @@ def init_leaderboard(dataframe, visible_columns=None):
     visible_columns = ['model_name'] + visible_columns
     display_df = dataframe[visible_columns].copy()
 
-    print(f"--- DataFrame inside init_leaderboard (before rounding) ---")
-    print(display_df[['model_name', 'macro_accuracy', 'macro_recall', 'total_evals_count']].head() if all(c in display_df.columns for c in ['model_name', 'macro_accuracy', 'macro_recall', 'total_evals_count']) else "Relevant columns not present")
-    print(f"-------------------------------------------------------------")
+    # print(f"--- DataFrame inside init_leaderboard (before rounding) ---")
+    # print(display_df[['model_name', 'macro_accuracy', 'macro_recall', 'total_evals_count']].head() if all(c in display_df.columns for c in ['model_name', 'macro_accuracy', 'macro_recall', 'total_evals_count']) else "Relevant columns not present")
+    # print(f"-------------------------------------------------------------")
 
     # Round numeric columns to 3 decimal places for display
     numeric_cols = display_df.select_dtypes(include=np.number).columns
@@ -338,7 +338,7 @@ def refresh_data_with_filters(version=CURRENT_VERSION, search_query="", model_ty
         # Get new data
         main_df = get_leaderboard_df(version=version)
         category_dfs = [get_category_leaderboard_df(category, version=version) for category in CATEGORIES]
-        selected_columns = [x.lower().replace(" ", "_").replace("(", "").replace(")", "").replace("_recall", "_recall_binary") for x in selected_columns]
+        selected_columns = [x.lower().replace(" ", "_").replace("(", "").replace(")", "").replace("_recall", "_recall_binary").replace("_precision", "_precision_binary") for x in selected_columns]
 
         # Log the actual columns we have
         logger.info(f"Main dataframe columns: {list(main_df.columns)}")
@@ -355,11 +355,16 @@ def refresh_data_with_filters(version=CURRENT_VERSION, search_query="", model_ty
 
         # Filter selected columns to only those available in the data
         if selected_columns:
-            valid_selected_columns = [col for col in selected_columns if col in available_columns]
+            # Convert display names to internal names first
+            internal_selected_columns = [x.lower().replace(" ", "_").replace("(", "").replace(")", "").replace("_recall", "_recall_binary").replace("_precision", "_precision_binary") for x in selected_columns]
+            valid_selected_columns = [col for col in internal_selected_columns if col in available_columns]
             if not valid_selected_columns and 'model_name' in available_columns:
-                valid_selected_columns = ['model_name'] + get_default_visible_columns()
+                # Fallback if conversion/filtering leads to empty selection
+                valid_selected_columns = ['model_name'] + [col for col in get_default_visible_columns() if col in available_columns]
         else:
-            valid_selected_columns = available_columns
+            # If no columns were selected in the dropdown, use default visible columns that exist
+             valid_selected_columns = [col for col in get_default_visible_columns() if col in available_columns]
+
 
         # Initialize dataframes for display with valid selected columns
         main_dataframe = init_leaderboard(filtered_main_df, valid_selected_columns)
@@ -675,7 +680,8 @@ with demo:
                             selected_columns = get_default_visible_columns()
                             logger.info(f"No columns selected, using defaults: {selected_columns}")
 
-                        selected_columns = [x.lower().replace(" ", "_").replace("(", "").replace(")", "").replace("_recall", "_recall_binary") for x in selected_columns]
+                        # Convert display names to internal names
+                        internal_selected_columns = [x.lower().replace(" ", "_").replace("(", "").replace(")", "").replace("_recall", "_recall_binary").replace("_precision", "_precision_binary") for x in selected_columns]
 
 
                         # Get the current data with ALL columns preserved
@@ -687,15 +693,15 @@ with demo:
 
                         # Log columns for debugging
                         logger.info(f"Main dataframe columns: {list(main_df.columns)}")
-                        logger.info(f"Selected columns: {selected_columns}")
+                        logger.info(f"Selected columns (internal): {internal_selected_columns}")
 
                         # IMPORTANT: Make sure model_name is always included
-                        if 'model_name' in main_df.columns and 'model_name' not in selected_columns:
-                            selected_columns = ['model_name'] + selected_columns
+                        if 'model_name' in main_df.columns and 'model_name' not in internal_selected_columns:
+                            internal_selected_columns = ['model_name'] + internal_selected_columns
 
                         # Initialize the main leaderboard with the selected columns
-                        # We're passing the raw selected_columns directly to preserve the selection
-                        main_leaderboard = init_leaderboard(main_df, selected_columns)
+                        # We're passing the internal_selected_columns directly to preserve the selection
+                        main_leaderboard = init_leaderboard(main_df, internal_selected_columns)
 
                         # Initialize category dataframes with the same selected columns
                         # This ensures consistency across all tabs
@@ -703,7 +709,7 @@ with demo:
                         for df in category_dfs:
                             # Use the same selected columns for each category
                             # init_leaderboard will automatically handle filtering to columns that exist
-                            category_leaderboards.append(init_leaderboard(df, selected_columns))
+                            category_leaderboards.append(init_leaderboard(df, internal_selected_columns))
 
                         return main_leaderboard, *category_leaderboards