分发

分发设置用于定义工具自动管理数据集记录的标准，具体取决于每个记录的预期提交响应数。

使用示例

每个记录的默认最小提交响应数为 1。如果您希望增加此值，您可以通过 TaskDistribution 类定义它，并将其传递给 Settings 类。

settings = rg.Settings(
    guidelines="These are some guidelines.",
    fields=[
        rg.TextField(
            name="text",
        ),
    ],
    questions=[
        rg.LabelQuestion(
            name="label",
            labels=["label_1", "label_2", "label_3"]
        ),
    ],
    distribution=rg.TaskDistribution(min_submitted=3)
)

dataset = rg.Dataset(
    name="my_dataset",
    settings=settings
)

---

OverlapTaskDistribution

任务分发设置类。

此任务分发定义了完成记录所需的提交响应数。

参数

名称	类型	描述	默认
min_submitted	int	完成记录所需的最小提交响应数	required

源代码位于 src/argilla/settings/_task_distribution.py

class OverlapTaskDistribution:
    """The task distribution settings class.

    This task distribution defines a number of submitted responses required to complete a record.

    Parameters:
        min_submitted (int): The number of min. submitted responses to complete the record
    """

    strategy: Literal["overlap"] = "overlap"

    def __init__(self, min_submitted: int):
        self._model = OverlapTaskDistributionModel(min_submitted=min_submitted, strategy=self.strategy)

    def __repr__(self) -> str:
        return f"OverlapTaskDistribution(min_submitted={self.min_submitted})"

    def __eq__(self, other) -> bool:
        if not isinstance(other, self.__class__):
            return False

        return self._model == other._model

    @classmethod
    def default(cls) -> "OverlapTaskDistribution":
        return cls(min_submitted=1)

    @property
    def min_submitted(self):
        return self._model.min_submitted

    @min_submitted.setter
    def min_submitted(self, value: int):
        self._model.min_submitted = value

    @classmethod
    def from_model(cls, model: OverlapTaskDistributionModel) -> "OverlapTaskDistribution":
        return cls(min_submitted=model.min_submitted)

    @classmethod
    def from_dict(cls, dict: Dict[str, Any]) -> "OverlapTaskDistribution":
        return cls.from_model(OverlapTaskDistributionModel.model_validate(dict))

    def to_dict(self):
        return self._model.model_dump()

    def _api_model(self) -> OverlapTaskDistributionModel:
        return self._model