src/envs.py

import os
from huggingface_hub import HfApi

TOKEN = os.environ.get("HF_TOKEN")
OWNER = os.environ.get("HF_ORGANIZATION", "BetaPrecision")

REPO_ID = f"{OWNER}/llm-xray-leaderboard"
QUEUE_REPO = f"{OWNER}/requests"
RESULTS_REPO = f"{OWNER}/results"

CACHE_PATH = os.getenv("HF_HOME", "/data" if os.path.exists("/data") else "./data")

EVAL_REQUESTS_PATH = os.path.join(CACHE_PATH, "eval-queue")
EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval-results")

os.makedirs(EVAL_REQUESTS_PATH, exist_ok=True)
os.makedirs(EVAL_RESULTS_PATH, exist_ok=True)

API = HfApi(token=TOKEN)

# Model size limit raised to 10.0B parameters
MAX_AUDIT_PARAMS_BILLION = float(os.environ.get("MAX_AUDIT_PARAMS_BILLION", "10.0"))
AUDIT_DEVICE = os.environ.get("AUDIT_DEVICE", "cuda" if os.environ.get("SPACES_ZERO_GPU") else "cpu")

DEMO_SEED_MODELS = [
    ("Qwen/Qwen2.5-0.5B-Instruct", "main"),
]