update populate

src/populate.py

@@ -1,11 +1,9 @@
-# src/populate.py
-
 import os
 import pandas as pd
 import json
 
 from src.display.utils import COLUMNS, EVAL_COLS, Tasks
-from src.envs import EVAL_RESULTS_PATH  # Removed FIXED_QUESTIONS_FILE import
+from src.envs import EVAL_RESULTS_PATH
 
 def get_leaderboard_df(eval_results_path, eval_requests_path, cols, benchmark_cols):
     # Initialize an empty DataFrame
@@ -22,7 +20,6 @@ def get_leaderboard_df(eval_results_path, eval_requests_path, cols, benchmark_co
         for file in result_files:
             with open(file, 'r') as f:
                 data = json.load(f)
-                # Flatten the JSON structure if needed
                 flattened_data = {}
                 flattened_data.update(data.get('config', {}))
                 flattened_data.update(data.get('results', {}))
@@ -35,6 +32,10 @@ def get_leaderboard_df(eval_results_path, eval_requests_path, cols, benchmark_co
         if col not in df.columns:
             df[col] = None
 
+    # Convert 'average' column to float and handle errors
+    if 'average' in df.columns:
+        df['average'] = pd.to_numeric(df['average'], errors='coerce')
+
     # Sort by 'average' column if it exists
     if 'average' in df.columns:
         df = df.sort_values(by=['average'], ascending=False)
@@ -66,4 +67,4 @@ def get_evaluation_queue_df(eval_requests_path, eval_cols):
             running_df = df[df['status'] == 'running']
             pending_df = df[df['status'] == 'pending']
 
-    return finished_df, running_df, pending_df
+    return finished_df, running_df, pending_df