| import os | |
| from huggingface_hub import HfApi | |
| # Org/username where things are read/written | |
| OWNER = "meg" | |
| # Read/write token | |
| TOKEN = os.environ.get("HF_TOKEN") | |
| API = HfApi(token=TOKEN) | |
| # Key for Perspective API | |
| PERSPECTIVE_API_KEY = os.environ.get("PERSPECTIVE_API_KEY") | |
| # Number of lines to read in the eval file, or None for all. | |
| EVAL_CUTOFF = 120 # !!!! For testing, should be None for actual evaluations!!! | |
| # How often to try to run eval. | |
| REFRESH_RATE = 5 * 60 # 5 min | |
| # How many lines to display in the log visualizer | |
| NUM_LINES_VISUALIZE = 300 | |
| # Where results are displayed | |
| REPO_ID = f"{OWNER}/leaderboard" | |
| # Dataset directory where the requests are created | |
| REQUESTS_REPO = f"{OWNER}/requests" | |
| # Dataset directory where the results are written to | |
| RESULTS_REPO = f"{OWNER}/results" | |
| # If you set up a cache later, set HF_HOME to where it is | |
| CACHE_PATH = os.getenv("HF_HOME", ".") | |
| # Local caches | |
| EVAL_REQUESTS_PATH = os.path.join(CACHE_PATH, "eval-requests") | |
| 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") | |