Update src/populate.py

src/populate.py

@@ -1 +1,70 @@
-d
+import os
+import pandas as pd
+import json
+
+from src.display.utils import COLUMNS, EVAL_COLS, Tasks
+from src.envs import EVAL_RESULTS_PATH
+
+def get_leaderboard_df(eval_results_path, eval_requests_path, cols, benchmark_cols):
+    # Initialize an empty DataFrame
+    df = pd.DataFrame(columns=cols)
+
+    # Load evaluation results from JSON files
+    if os.path.exists(eval_results_path):
+        result_files = [
+            os.path.join(eval_results_path, f) 
+            for f in os.listdir(eval_results_path) 
+            if f.endswith('.json')
+        ]
+        data_list = []
+        for file in result_files:
+            with open(file, 'r') as f:
+                data = json.load(f)
+                flattened_data = {}
+                flattened_data.update(data.get('config', {}))
+                flattened_data.update(data.get('results', {}))
+                data_list.append(flattened_data)
+        if data_list:
+            df = pd.DataFrame(data_list)
+
+    # Ensure DataFrame has all columns
+    for col in cols:
+        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)
+
+    return df
+
+def get_evaluation_queue_df(eval_requests_path, eval_cols):
+    # Initialize empty DataFrames
+    finished_df = pd.DataFrame(columns=eval_cols)
+    running_df = pd.DataFrame(columns=eval_cols)
+    pending_df = pd.DataFrame(columns=eval_cols)
+
+    # Load evaluation requests from JSON files
+    if os.path.exists(eval_requests_path):
+        request_files = [
+            os.path.join(eval_requests_path, f) 
+            for f in os.listdir(eval_requests_path) 
+            if f.endswith('.json')
+        ]
+        data_list = []
+        for file in request_files:
+            with open(file, 'r') as f:
+                data = json.load(f)
+                data_list.append(data)
+        if data_list:
+            df = pd.DataFrame(data_list)
+            # Split DataFrame based on status
+            finished_df = df[df['status'] == 'finished']
+            running_df = df[df['status'] == 'running']
+            pending_df = df[df['status'] == 'pending']
+
+    return finished_df, running_df, pending_df