Update app.py

app.py

@@ -63,38 +63,6 @@ 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,
@@ -125,13 +93,8 @@ def update_table(
     print(f"Final df shape: {df.shape}")
     print("Final dataframe head:")
     print(df.head())
-    column_dtypes = {col: TYPES[COLS.index(col)] if col in COLS else "str" for col in df.columns}
-    
-    return gr.Dataframe.update(
-        value=df.to_dict(orient="records"),
-        headers=list(df.columns),
-        datatype=column_dtypes
-    )
+    return df
+
 
 def load_query(request: gr.Request):  # triggered only once at startup => read query parameter if it exists
     query = request.query_params.get("query") or ""
@@ -142,25 +105,16 @@ 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,
     ]
-    
-    selected_cols = list(dict.fromkeys(always_here_cols + [c for c in columns if c in df.columns]))
-    return df[selected_cols]
+    # 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 filter_queries(query: str, filtered_df: pd.DataFrame):
@@ -309,20 +263,11 @@ with demo:
             leaderboard_df_filtered = filter_models(leaderboard_df, [t.to_str(" : ") for t in ModelType], list(NUMERIC_INTERVALS.keys()), [i.value.name for i in Precision], [i.value.name for i in AddSpecialTokens], [i.value.name for i in NumFewShots], False, False, False)
             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)
-            column_dtypes = {col: TYPES[COLS.index(col)] if col in COLS else "str" for col in leaderboard_df_filtered.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.to_dict(orient="records"),
-                headers=list(leaderboard_df_filtered.columns),
-                datatype=column_dtypes,
+                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,