| from typing import Dict, List, Any |
| from setfit import SetFitModel |
|
|
| class EndpointHandler: |
| def __init__(self, path=""): |
| |
| self.model = SetFitModel.from_pretrained(path) |
|
|
| self.id2label = {0: 'Bridge', 1: 'CDP', 2: 'Cross-chain', 3: 'DEX', 4: 'Derivatives', 5: 'Insurance', 6: 'Lending', 7: 'NFT Lending', 8: 'Other', 9: 'Staking', 10: 'Synthetics'} |
|
|
| def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]: |
| """ |
| data args: |
| inputs (:obj: `str`) |
| Return: |
| A :obj:`list` | `dict`: will be serialized and returned |
| """ |
| |
| inputs = data.pop("inputs", data) |
| if isinstance(inputs, str): |
| inputs = [inputs] |
|
|
| |
| scores = self.model.predict_proba(inputs)[0] |
|
|
| return [{"label": self.id2label[i], "score": score.item()} for i, score in enumerate(scores)] |
