| """Hugging Face Inference Endpoints entry point — deploy this repo as a CPU API. |
| |
| Request body: {"inputs": {"cutoff": "1997-10-01", "horizon": 30, "index": "DAX"}} |
| (also accepted: {"inputs": "1997-10-01", "parameters": {"horizon": 30, "index": "DAX"}} |
| or {"inputs": ["1997-10-01", 30, "DAX"]}). Response: the `Predictor.predict` JSON dict. |
| """ |
| import sys |
| from pathlib import Path |
|
|
| HERE = Path(__file__).resolve().parent |
| sys.path.insert(0, str(HERE)) |
| import model as M |
|
|
|
|
| class EndpointHandler: |
| def __init__(self, path: str = ""): |
| self.predictor = M.load(path or HERE, "cuda" if M.cuda_available() else "cpu") |
|
|
| def __call__(self, data: dict): |
| inputs = data.pop("inputs", data) |
| parameters = data.pop("parameters", None) or {} |
| if isinstance(inputs, dict): |
| return self.predictor.predict(**inputs, **parameters) |
| if isinstance(inputs, (list, tuple)): |
| return self.predictor.predict(*inputs, **parameters) |
| return self.predictor.predict(inputs, **parameters) |
|
|
