Update app.py

app.py

@@ -63,6 +63,38 @@ leaderboard_df = original_df.copy()
 ) = get_evaluation_queue_df(EVAL_REQUESTS_PATH, EVAL_COLS)
 
 # Searching and filtering
+# def update_table(
+#     hidden_df: pd.DataFrame,
+#     columns: list,
+#     type_query: list,
+#     precision_query: str,
+#     size_query: list,
+#     add_special_tokens_query: list,
+#     num_few_shots_query: list,
+#     show_deleted: bool,
+#     show_merges: bool,
+#     show_flagged: bool,
+#     query: str,
+# ):
+#     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)
+#     print(f"filtered_df shape after filter_models: {filtered_df.shape}")
+    
+#     filtered_df = filter_queries(query, filtered_df)
+#     print(f"filtered_df shape after filter_queries: {filtered_df.shape}")
+    
+#     print(f"Filter applied: query={query}, columns={columns}, type_query={type_query}, precision_query={precision_query}")
+#     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
+
 def update_table(
     hidden_df: pd.DataFrame,
     columns: list,
@@ -76,23 +108,9 @@ def update_table(
     show_flagged: bool,
     query: str,
 ):
-    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)
-    print(f"filtered_df shape after filter_models: {filtered_df.shape}")
-    
     filtered_df = filter_queries(query, filtered_df)
-    print(f"filtered_df shape after filter_queries: {filtered_df.shape}")
-    
-    print(f"Filter applied: query={query}, columns={columns}, type_query={type_query}, precision_query={precision_query}")
-    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
 
 
@@ -105,16 +123,25 @@ 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
-    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
+
+    selected_cols = always_here_cols + [c for c in columns if c in df.columns]
+    return df[selected_cols]
 
 
 def filter_queries(query: str, filtered_df: pd.DataFrame):
@@ -264,10 +291,18 @@ with demo:
             initial_columns = [c.name for c in fields(AutoEvalColumn) if c.never_hidden or c.displayed_by_default]
             leaderboard_df_filtered = select_columns(leaderboard_df_filtered, initial_columns)
 
+            # leaderboard_table = gr.components.Dataframe(
+            #     value=leaderboard_df_filtered,
+            #     headers=[c.name for c in fields(AutoEvalColumn) if c.never_hidden] + shown_columns.value,
+            #     datatype=TYPES,
+            #     elem_id="leaderboard-table",
+            #     interactive=False,
+            #     visible=True,
+            # )
             leaderboard_table = gr.components.Dataframe(
-                value=leaderboard_df_filtered,
+                value=select_columns(leaderboard_df_filtered, shown_columns.value),
                 headers=[c.name for c in fields(AutoEvalColumn) if c.never_hidden] + shown_columns.value,
-                datatype=TYPES,
+                datatype={col: TYPES[COLS.index(col)] if col in COLS else "str" for col in shown_columns.value},
                 elem_id="leaderboard-table",
                 interactive=False,
                 visible=True,