pyrit.score.HumanInTheLoopScorerGradio

class HumanInTheLoopScorerGradio(*, open_browser=False, validator: ~pyrit.score.scorer_prompt_validator.ScorerPromptValidator | None = None, score_aggregator: ~typing.Callable[[~typing.Iterable[~pyrit.models.score.Score]], ~pyrit.score.score_aggregator_result.ScoreAggregatorResult] = <function _create_aggregator.<locals>.aggregator>)

Bases: TrueFalseScorer

Create scores from manual human input using Gradio and adds them to the database.

In the future this will not be a TrueFalseScorer. However, it is all that is supported currently.

Parameters:

• open_browser (bool) – If True, the scorer will open the Gradio interface in a browser instead of opening it in PyWebview. Defaults to False.

• validator (Optional[ScorerPromptValidator]) – Custom validator. Defaults to None.

• score_aggregator (TrueFalseAggregatorFunc) – Aggregator for combining scores. Defaults to TrueFalseScoreAggregator.OR.

__init__(*, open_browser=False, validator: ~pyrit.score.scorer_prompt_validator.ScorerPromptValidator | None = None, score_aggregator: ~typing.Callable[[~typing.Iterable[~pyrit.models.score.Score]], ~pyrit.score.score_aggregator_result.ScoreAggregatorResult] = <function _create_aggregator.<locals>.aggregator>) → None

Methods

__init__(*[, open_browser, validator, ...])
get_identifier()	Returns an identifier dictionary for the scorer.
get_scorer_metrics(dataset_name[, metrics_type])	Returns evaluation statistics for the scorer using the dataset_name of the human labeled dataset that this scorer was run against.
retrieve_score(request_prompt, *[, objective])	Retrieve a score from the human evaluator through the RPC server.
scale_value_float(value, min_value, max_value)	Scales a value from 0 to 1 based on the given min and max values.
score_async(request_response, *[, ...])	Score the request_response, add the results to the database and return a list of Score objects.
score_image_async(image_path, *[, objective])	Scores the given image using the chat target.
score_image_batch_async(*, image_paths[, ...])
score_prompts_batch_async(*, request_responses)	Score multiple prompts in batches using the provided objectives.
score_response_async(*, response[, ...])	Score a response using an objective scorer and optional auxiliary scorers.
score_response_multiple_scorers_async(*, ...)	Score a response using multiple scorers in parallel.
score_text_async(text, *[, objective])	Scores the given text based on the task using the chat target.
validate_return_scores(scores)	Validates the scores returned by the scorer.

Attributes

scorer_type

retrieve_score(request_prompt: PromptRequestPiece, *, objective: str | None = None) → list[Score]

Retrieve a score from the human evaluator through the RPC server.

Parameters:

• request_prompt (PromptRequestPiece) – The prompt request piece to be scored.

• objective (Optional[str]) – The objective to evaluate against. Defaults to None.

Returns:

A list containing a single Score object from the human evaluator.

Return type:

list[Score]