Update app.py

app.py

@@ -82,7 +82,10 @@ def update_table(
     print(f"Update table called with: type_query={type_query}, precision_query={precision_query}, size_query={size_query}")
     print(f"hidden_df shape before filtering: {hidden_df.shape}")
     
-    filtered_df = filter_models(hidden_df, type_query, size_query, precision_query, add_special_tokens_query, num_few_shots_query, show_deleted, show_merges, show_flagged)
+    filtered_df = filter_models(
+        hidden_df, type_query, size_query, precision_query, add_special_tokens_query, 
+        num_few_shots_query, show_deleted, show_merges, show_flagged, columns
+    )
     print(f"filtered_df shape after filter_models: {filtered_df.shape}")
     
     filtered_df = filter_queries(query, filtered_df)
@@ -92,11 +95,7 @@ def update_table(
     print("Filtered dataframe head:")
     print(filtered_df.head())
 
-    df = select_columns(filtered_df, columns)
-    print(f"Final df shape: {df.shape}")
-    print("Final dataframe head:")
-    print(df.head())
-    return df
+    return filtered_df
 
 
 
@@ -142,7 +141,9 @@ def filter_queries(query: str, filtered_df: pd.DataFrame):
 
 
 def filter_models(
-    df: pd.DataFrame, type_query: list, size_query: list, precision_query: list, add_special_tokens_query: list, num_few_shots_query: list, show_deleted: bool, show_merges: bool, show_flagged: bool
+    df: pd.DataFrame, type_query: list, size_query: list, precision_query: list, 
+    add_special_tokens_query: list, num_few_shots_query: list, show_deleted: bool, 
+    show_merges: bool, show_flagged: bool, shown_columns: list
 ) -> pd.DataFrame:
     print(f"Initial df shape: {df.shape}")
     print(f"Initial df content:\n{df}")
@@ -162,7 +163,7 @@ def filter_models(
     if 'Unknown' in size_query:
         size_mask = filtered_df['#Params (B)'].isna() | (filtered_df['#Params (B)'] == 0)
     else:
-        size_mask = filtered_df['#Params (B)'].apply(lambda x: any(x in NUMERIC_INTERVALS[s] for s in size_query if s != 'Unknown'))
+        size_mask = filtered_df['#Params (B)'].apply(lambda x: any(pd.Interval(NUMERIC_INTERVALS[s].left, NUMERIC_INTERVALS[s].right).contains(x) for s in size_query if s != 'Unknown'))
     filtered_df = filtered_df[size_mask]
     print(f"After size filter: {filtered_df.shape}")
 
@@ -179,6 +180,9 @@ def filter_models(
         filtered_df = filtered_df[filtered_df['Available on the hub'] == True]
     print(f"After show_deleted filter: {filtered_df.shape}")
 
+    # 選択された列のみを表示
+    filtered_df = filtered_df[['T', 'Model'] + [col for col in shown_columns if col in filtered_df.columns]]
+
     print("Filtered dataframe head:")
     print(filtered_df.head())
     return filtered_df
@@ -205,12 +209,12 @@ with demo:
                             choices=[
                                 c.name
                                 for c in fields(AutoEvalColumn)
-                                if not c.hidden and not c.never_hidden# and not c.dummy
+                                if not c.hidden and not c.never_hidden and c.name not in ['Type', 'Architecture', 'Precision', 'Hub License', '#Params (B)', 'Hub ❤️', 'Available on the hub', 'Model sha', 'Add Special Tokens']
                             ],
                             value=[
                                 c.name
                                 for c in fields(AutoEvalColumn)
-                                if c.displayed_by_default and not c.hidden and not c.never_hidden
+                                if c.displayed_by_default and not c.hidden and not c.never_hidden and c.name not in ['Type', 'Architecture', 'Precision', 'Hub License', '#Params (B)', 'Hub ❤️', 'Available on the hub', 'Model sha', 'Add Special Tokens']
                             ],
                             label="Select columns to show",
                             elem_id="column-select",