| from typing import Optional | |
| from pydantic import BaseModel | |
| class ProcessGrcInput(BaseModel): | |
| garbled: str | |
| gt: str | |
| def __hash__(self) -> int: | |
| return hash(self.garbled + self.gt) | |
| class TokenConfidence(BaseModel): | |
| token: str | |
| confidence: float | |
| rank: Optional[int] = None | |
| class GrcResult(BaseModel): | |
| prediction_map: list[TokenConfidence] | |
| gt_map: list[TokenConfidence] | |
| topk: list[list[TokenConfidence]] | |