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,
@@ -93,8 +125,13 @@ def update_table(
     print(f"Final df shape: {df.shape}")
     print("Final dataframe head:")
     print(df.head())
-    return df
-
+    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
+    )
 
 def load_query(request: gr.Request):  # triggered only once at startup => read query parameter if it exists
     query = request.query_params.get("query") or ""
@@ -272,7 +309,8 @@ 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,
@@ -282,9 +320,9 @@ with demo:
             #     visible=True,
             # )
             leaderboard_table = gr.components.Dataframe(
-                value=leaderboard_df_filtered,
+                value=leaderboard_df_filtered.to_dict(orient="records"),
                 headers=list(leaderboard_df_filtered.columns),
-                datatype={col: TYPES[COLS.index(col)] if col in COLS else "str" for col in leaderboard_df_filtered.columns},
+                datatype=column_dtypes,
                 elem_id="leaderboard-table",
                 interactive=False,
                 visible=True,