Class TypeChatValidator

python/src/typechat/_internal/validator.py:11–45

Validates an object against a given Python type.

T = TypeVar("T", covariant=True)

class TypeChatValidator(Generic[T]):
    """
    Validates an object against a given Python type.
    """

    _adapted_type: pydantic.TypeAdapter[T]

    def __init__(self, py_type: type[T]):
        """
        Args:

            py_type: The schema type to validate against.
        """
        super().__init__()
        self._adapted_type = pydantic.TypeAdapter(py_type)

    def validate_object(self, obj: object) -> Result[T]:
        """
        Validates the given Python object according to the associated schema type.

        Returns a `Success[T]` object containing the object if validation was successful.
        Otherwise, returns a `Failure` object with a `message` property describing the error.
        """
        try:
            # TODO: Switch to `validate_python` when validation modes are exposed.
            # https://github.com/pydantic/pydantic-core/issues/712
            # We'd prefer to keep `validate_object` as the core method and
            # allow translators to concern themselves with the JSON instead.
            # However, under Pydantic's `strict` mode, a `dict` isn't considered compatible
            # with a dataclass. So for now, jump back to JSON and validate the string.
            json_str = pydantic_core.to_json(obj)
            typed_dict = self._adapted_type.validate_json(json_str, strict=True)
            return Success(typed_dict)
        except pydantic.ValidationError as validation_error:
            return _handle_error(validation_error)


def _handle_error(validation_error: pydantic.ValidationError) -> Failure: