Update app.py

app.py

@@ -105,14 +105,27 @@ def search_table(df: pd.DataFrame, query: str) -> pd.DataFrame:
     return df[(df[AutoEvalColumn.dummy.name].str.contains(query, case=False))]
 
 
+# def select_columns(df: pd.DataFrame, columns: list) -> pd.DataFrame:
+#     always_here_cols = [
+#         AutoEvalColumn.model_type_symbol.name,
+#         AutoEvalColumn.model.name,
+#     ]
+#     # We use COLS to maintain sorting
+#     filtered_df = df[
+#         always_here_cols + [c for c in COLS if c in df.columns and c in columns]# + [AutoEvalColumn.dummy.name]
+#     ]
+#     return filtered_df
+
 def select_columns(df: pd.DataFrame, columns: list) -> pd.DataFrame:
     always_here_cols = [
         AutoEvalColumn.model_type_symbol.name,
         AutoEvalColumn.model.name,
     ]
-    # We use COLS to maintain sorting
+    # always_here_cols が既に columns に含まれている場合は除外
+    columns = [c for c in columns if c not in always_here_cols]
+    # COLS の順序を維持しつつ、重複を避けてカラムを選択
     filtered_df = df[
-        always_here_cols + [c for c in COLS if c in df.columns and c in columns]# + [AutoEvalColumn.dummy.name]
+        always_here_cols + [c for c in COLS if c in df.columns and c in columns]
     ]
     return filtered_df
 
@@ -277,16 +290,6 @@ with demo:
             
             print("Columns in leaderboard_df_filtered:", leaderboard_df_filtered.columns)
             
-            # datatypeを準備
-            datatype_dict = {}
-            for col in leaderboard_df_filtered.columns:
-                if col == AutoEvalColumn.model.name:
-                    datatype_dict[col] = "markdown"
-                elif col in TYPES:
-                    datatype_dict[col] = TYPES[col]
-                else:
-                    datatype_dict[col] = "str"
-            
             # leaderboard_tableの初期化
             leaderboard_table = gr.components.Dataframe(
                 value=leaderboard_df_filtered.to_dict('records'),