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from src.envs import (
    API,
    EVAL_REQUESTS_PATH,
    DYNAMIC_INFO_REPO,
    DYNAMIC_INFO_FILE_PATH,
    DYNAMIC_INFO_PATH,
    EVAL_RESULTS_PATH,
    H4_TOKEN, IS_PUBLIC,
    QUEUE_REPO,
    REPO_ID,
    RESULTS_REPO,
    SHOW_INCOMPLETE_EVALS
)
from huggingface_hub import snapshot_download
import os
import glob
import json

snapshot_download(repo_id=QUEUE_REPO, local_dir=EVAL_REQUESTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30)
all_models = []
all_models.append('nvidia/Nemotron-4-340B-Instruct')
all_models.append('meta-llama/Meta-Llama-3.1-405B-Instruct')
for filepath in glob.glob(os.path.join(EVAL_REQUESTS_PATH, '**/*.json'), recursive=True):
    with open(filepath, 'r') as f:
        model_data = json.load(f)
        if model_data['status'] == 'FINISHED':
            all_models.append(model_data['model'])

all_models = sorted(list(set(all_models)))
with open('model_list.txt', 'w') as fw:
    for m in all_models:
        print(m)
        fw.write('  - '+ m + '\n')