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import json
import os
from typing import List, List, Tuple, Any, Dict
from huggingface_hub import snapshot_download
from collections import defaultdict
import requests
from src.envs import EVAL_REQUESTS_PATH, QUEUE_REPO
def webhook_bot(msg: str):
bot_url = os.environ.get("DISCORD_WEBHOOK_URL", "")
if bot_url != "":
requests.post(bot_url, json={"content": msg})
def read_all_pending_model(EVAL_REQUESTS_PATH: str) -> Dict[str, List[Tuple[Any, str]]]:
depth = 1
alls = defaultdict(list)
for root, _, files in os.walk(EVAL_REQUESTS_PATH):
current_depth = root.count(os.sep) - EVAL_REQUESTS_PATH.count(os.sep)
if current_depth == depth:
for file in files:
if not file.endswith(".json"):
continue
file_abs_path = os.path.join(root, file)
with open(file_abs_path, "r") as f:
info = json.load(f)
alls[info['model']].append((info, file_abs_path))
pendings = {}
for k in alls.keys():
is_pending = False
for stat in alls[k]:
info_dict = stat[0]
if info_dict['status'] == "PENDING":
is_pending = True
if is_pending:
pendings[k] = alls[k]
return pendings
def watch_submit_queue():
try:
snapshot_download(
repo_id=QUEUE_REPO,
local_dir=EVAL_REQUESTS_PATH,
repo_type="dataset",
tqdm_class=None,
etag_timeout=30,
)
alls = read_all_pending_model(EVAL_REQUESTS_PATH)
pending_model = []
for model_name in alls.keys():
for request_row in alls[model_name]:
info, filepath = request_row
status = info["status"]
model_name = info["model"]
if status == "PENDING":
pending_model.append(model_name)
pending_model = list(set(pending_model))
pending_model_str = '\n'.join(pending_model)
webhook_bot(f'Leaderboard model pending: {len(pending_model)}\n### Models\n{pending_model_str}')
except Exception as e:
print(f'Watch submit queue error: {e}')
pass |