| from typing import Dict, List, Any |
| from transformers import pipeline |
| import holidays |
|
|
|
|
| class EndpointHandler: |
| def __init__(self, path=""): |
| self.pipeline = pipeline("text-classification", model=path) |
| self.holidays = holidays.US() |
|
|
| def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]: |
| """ |
| data args: |
| inputs (:obj: `str`) |
| date (:obj: `str`) |
| Return: |
| A :obj:`list` | `dict`: will be serialized and returned |
| """ |
| |
| inputs = data.pop("inputs", data) |
| |
| date = data.pop("date", None) |
|
|
| |
| if date is not None and date in self.holidays: |
| return [{"label": "happy", "score": 1}] |
|
|
| |
| prediction = self.pipeline(inputs) |
| return prediction |
|
|