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import json
import os
import time
from openai import OpenAI
BATCH_IDS_FILE = "data/putnam_eval/submitted_batch_ids.json"
def check_status():
api_key = os.getenv("OPENAI_API_KEY")
if not api_key:
print("Error: OPENAI_API_KEY not set.")
return
client = OpenAI(api_key=api_key)
if not os.path.exists(BATCH_IDS_FILE):
print(f"Error: {BATCH_IDS_FILE} not found. Did you submit batches?")
return
with open(BATCH_IDS_FILE, "r") as f:
batch_ids = json.load(f)
print(f"Checking status for {len(batch_ids)} batches...\n")
all_completed = True
completed_count = 0
print(f"{'BATCH ID':<35} | {'STATUS':<15} | {'REQ COUNT':<10} | {'COMPLETED':<10} | {'FAILED':<10}")
print("-" * 95)
for b_id in batch_ids:
try:
batch = client.batches.retrieve(b_id)
status = batch.status
counts = batch.request_counts
total = counts.total if counts else 0
comp = counts.completed if counts else 0
fail = counts.failed if counts else 0
print(f"{b_id:<35} | {status:<15} | {total:<10} | {comp:<10} | {fail:<10}")
if status != "completed":
all_completed = False
else:
completed_count += 1
except Exception as e:
print(f"{b_id:<35} | {'ERROR':<15} | {str(e)}")
all_completed = False
print("-" * 95)
print(f"\nProgress: {completed_count}/{len(batch_ids)} batches completed.")
if all_completed:
print("\nSUCCESS: All batches finished! You can now run scripts/retrieve_results.py")
else:
print("\nSome batches are still processing. Check again later.")
if __name__ == "__main__":
check_status()
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