pyrit.models.UnvalidatedScore

class UnvalidatedScore(raw_score_value: str, score_value_description: str, score_category: List[str] | None, score_rationale: str, score_metadata: Dict[str, str | int] | None, scorer_class_identifier: Dict[str, str], prompt_request_response_id: UUID | str, objective: str | None, id: UUID | str | None = None, timestamp: datetime | None = None)

Bases: object

Score is an object that validates all the fields. However, we need a common data class that can be used to store the raw score value before it is normalized and validated.

__init__(raw_score_value: str, score_value_description: str, score_category: List[str] | None, score_rationale: str, score_metadata: Dict[str, str | int] | None, scorer_class_identifier: Dict[str, str], prompt_request_response_id: UUID | str, objective: str | None, id: UUID | str | None = None, timestamp: datetime | None = None) → None

Methods

__init__(raw_score_value, ...[, id, timestamp])
to_score(*, score_value, score_type)

Attributes

id
timestamp
raw_score_value
score_value_description
score_category
score_rationale
score_metadata
scorer_class_identifier
prompt_request_response_id
objective

id: UUID | str | None = None

objective: str | None

prompt_request_response_id: UUID | str

raw_score_value: str

score_category: List[str] | None

score_metadata: Dict[str, str | int] | None

score_rationale: str

score_value_description: str

scorer_class_identifier: Dict[str, str]

timestamp: datetime | None = None

to_score(*, score_value: str, score_type: Literal['true_false', 'float_scale'])