Update app.py

app.py

@@ -172,13 +172,6 @@ def create_leaderboard_component(dataframe, displayed_cols, hidden_cols=None, ca
         ) if AutoEvalColumn.still_on_hub.name in filtered_df.columns else None,
     ]
     
-    # Adicionar filtros específicos para Energy/Reasoning na aba Geral
-    if title == "Benchmark Geral":
-        if AutoEvalColumn.energy_avg.name in filtered_df.columns:
-            raw_filter_columns.append(ColumnFilter(AutoEvalColumn.energy_avg.name, type="boolean", label="Mostrar Média Energy?"))
-        if AutoEvalColumn.reasoning_avg.name in filtered_df.columns:
-            raw_filter_columns.append(ColumnFilter(AutoEvalColumn.reasoning_avg.name, type="boolean", label="Mostrar Média Reasoning?"))
-            
     # Filtrar Nones da lista de filtros
     final_filter_columns = [f for f in raw_filter_columns if f is not None]
 
@@ -273,9 +266,9 @@ with demo:
             ] 
             general_cols_to_display = [col for col in general_cols_to_display if col in LEADERBOARD_DF.columns]
             
-            # Colunas a ocultar: Tasks + TODAS Médias Individuais (inclui Energy/Reasoning) + detalhes
+            # Colunas a ocultar: Tasks + Médias Individuais PLUE + detalhes. NÃO ocultar Energy/Reasoning Avg aqui.
             general_hidden_cols = [task.name for task in Tasks] + \
-                                  list(AREA_AVG_COLUMN_MAP.values()) + \
+                                  [AREA_AVG_COLUMN_MAP[area] for area in PLUE_GROUP_AREAS if area in AREA_AVG_COLUMN_MAP] + \
                                   [
                                       AutoEvalColumn.model_type.name,
                                       AutoEvalColumn.architecture.name,