import os

from huggingface_hub import HfApi

# Info to change for your repository
# ----------------------------------
TOKEN = os.environ.get("TOKEN") # A read/write token for your org

OWNER = "speakleash" # Change to your org - don't forget to create a results and request file
DEVICE = "cpu" # "cuda:0" if you add compute
LIMIT = 20 # !!!! Should be None for actual evaluations!!!
# ----------------------------------

REPO_ID = f"{OWNER}/open_pl_llm_leaderboard"
QUEUE_REPO = f"{OWNER}/open_pl_llm_leaderboard_requests"
RESULTS_REPO = f"{OWNER}/open_pl_llm_leaderboard_results"

# If you setup a cache later, just change HF_HOME
CACHE_PATH=os.getenv("HF_HOME", ".")
print('CACHE_PATH', CACHE_PATH)
# Local caches
EVAL_REQUESTS_PATH = os.path.join(CACHE_PATH, "eval-queue")
EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval-results")
EVAL_REQUESTS_PATH_BACKEND = os.path.join(CACHE_PATH, "eval-queue-bk")
EVAL_RESULTS_PATH_BACKEND = os.path.join(CACHE_PATH, "eval-results-bk")

print('EVAL_RESULTS_PATH', EVAL_RESULTS_PATH)
print('EVAL_RESULTS_PATH absolute path:', os.path.abspath(EVAL_RESULTS_PATH))

try:
    print('Content of EVAL_RESULTS_PATH:')
    print("Files:", os.listdir(EVAL_RESULTS_PATH))
except Exception as e:
    print(f"Error accessing EVAL_RESULTS_PATH: {e}")




API = HfApi(token=TOKEN)