tes

app.py

@@ -58,6 +58,16 @@ LEADERBOARD_DF = get_leaderboard_df(EVAL_RESULTS_PATH, EVAL_REQUESTS_PATH, COLS,
     pending_eval_queue_df,
 ) = get_evaluation_queue_df(EVAL_REQUESTS_PATH, EVAL_COLS)
 
+
+pd.set_option('display.max_rows', None)  # 显示所有行
+pd.set_option('display.max_columns', None)  # 显示所有列
+pd.set_option('display.max_colwidth', None)  # 不省略列内容
+pd.set_option('display.width', 1000)  # 控制输出宽度
+print(LEADERBOARD_DF)
+print(finished_eval_queue_df)
+print(running_eval_queue_df)
+print(pending_eval_queue_df)
+assert 0
 def init_leaderboard(dataframe):
     if dataframe is None or dataframe.empty:
         raise ValueError("Leaderboard DataFrame is empty or None.")

src/populate.py

@@ -12,7 +12,6 @@ def get_leaderboard_df(results_path: str, requests_path: str, cols: list, benchm
     """Creates a dataframe from all the individual experiment results"""
     raw_data = get_raw_eval_results(results_path, requests_path)
     print(raw_data)
-    assert 0
     all_data_json = [v.to_dict() for v in raw_data]
 
     df = pd.DataFrame.from_records(all_data_json)