Update app.py

app.py

@@ -151,20 +151,16 @@ def filter_models(
 
     type_emoji = [t[0] for t in type_query]
     # type_emojiフィルタリングを条件付きで適用
-    if type_emoji:
-        filtered_df = filtered_df[filtered_df['Type_Symbol'].isin(type_emoji + ['?'])]
+    filtered_df = filtered_df[filtered_df['Type_Symbol'].isin(type_emoji + ['?'])]
     
     # precisionフィルタリングを条件付きで適用
-    if precision_query:
-        filtered_df = filtered_df[filtered_df[AutoEvalColumn.precision.name].isin(precision_query + ['Unknown'])]
+    filtered_df = filtered_df[filtered_df[AutoEvalColumn.precision.name].isin(precision_query + ['Unknown'])]
     
     # add_special_tokensフィルタリングを条件付きで適用
-    if add_special_tokens_query:
-        filtered_df = filtered_df[filtered_df[AutoEvalColumn.add_special_tokens.name].isin(add_special_tokens_query + ['Unknown'])]
+    filtered_df = filtered_df[filtered_df[AutoEvalColumn.add_special_tokens.name].isin(add_special_tokens_query + ['Unknown'])]
     
     # num_few_shotsフィルタリングを条件付きで適用
-    if num_few_shots_query:
-        filtered_df = filtered_df[filtered_df[AutoEvalColumn.num_few_shots.name].isin(num_few_shots_query + ['Unknown'])]
+    filtered_df = filtered_df[filtered_df[AutoEvalColumn.num_few_shots.name].isin(num_few_shots_query + ['Unknown'])]
     print(f"After num_few_shots filter: {filtered_df.shape}")
     
 
@@ -272,7 +268,7 @@ with demo:
                     [c for c in COLS if c in leaderboard_df.columns]
                 ],
                 headers=[c for c in COLS if c in leaderboard_df.columns],
-                datatype={c: str(leaderboard_df[c].dtype) for c in leaderboard_df.columns if c in COLS},
+                datatype={c: str(t) for c, t in leaderboard_df.dtypes.items() if c in COLS},
                 elem_id="leaderboard-table",
                 interactive=False,
                 visible=True,