import os

from huggingface_hub import HfApi

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

# Change to your org - don't forget to create a results and request dataset, with the correct format!
OWNER = "umdclip"

REPO_ID = f"{OWNER}/quizbowl-submission"
QUEUE_REPO = f"{OWNER}/advcal-requests"
RESULTS_REPO = f"{OWNER}/model-results"  # TODO: change to advcal-results after testing is done
LLM_CACHE_REPO = f"{OWNER}/advcal-llm-cache"

EXAMPLES_PATH = "examples"

PLAYGROUND_DATASET_NAMES = {
    "tossup": f"{OWNER}/acf-co24-tossups",
    "bonus": f"{OWNER}/acf-co24-bonuses",
}

# ----------------------------------

# If you setup a cache later, just change HF_HOME
CACHE_PATH = os.getenv("HF_HOME", ".")

# Local caches
LLM_CACHE_PATH = os.path.join(CACHE_PATH, "llm-cache")
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")


LLM_CACHE_REFRESH_INTERVAL = 600  # seconds (30 minutes)
SERVER_REFRESH_INTERVAL = 86400  # seconds (one day)
LEADERBOARD_REFRESH_INTERVAL = 600  # seconds (10 minutes)

API = HfApi(token=TOKEN)