associate_personas_to_entities ¶

def associate_personas_to_entities(
    self,
    id: "capo_kendra.types.experience_id.ExperienceId",
    index_id: "capo_kendra.types.index_id.IndexId",
    personas: "capo_kendra.types.entity_persona_configuration_list.EntityPersonaConfigurationList",
    *,
    config_overrides: Optional[kendraClientConfig] = None,
) -> "capo_kendra.types.associate_personas_to_entities_response.AssociatePersonasToEntitiesResponse":
    """<p>Defines the specific permissions of users or groups in your IAM Identity Center identity source with access to your Amazon Kendra experience. You can create an Amazon Kendra experience such as a search application. For more information on creating a search application experience, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/deploying-search-experience-no-code.html">Building a search experience with no code</a>.</p>

    Args:
        id: <p>The identifier of your Amazon Kendra experience.</p>
        index_id: <p>The identifier of the index for your Amazon Kendra experience.</p>
        personas: <p>The personas that define the specific permissions of users or groups in your IAM Identity Center identity source. The available personas or access roles are <code>Owner</code> and <code>Viewer</code>. For more information on these personas, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/deploying-search-experience-no-code.html#access-search-experience">Providing access to your search page</a>.</p>

    Raises:
        capo_kendra.errors.access_denied_exception.AccessDeniedException: <p>You don't have sufficient access to perform this action. Please ensure you have the required permission policies and user accounts and try again.</p>
        capo_kendra.errors.internal_server_exception.InternalServerException: <p>An issue occurred with the internal server used for your Amazon Kendra service. Please wait a few minutes and try again, or contact <a href="http://aws.amazon.com/contact-us/">Support</a> for help.</p>
        capo_kendra.errors.resource_already_exist_exception.ResourceAlreadyExistException: <p>The resource you want to use already exists. Please check you have provided the correct resource and try again.</p>
        capo_kendra.errors.resource_not_found_exception.ResourceNotFoundException: <p>The resource you want to use doesn’t exist. Please check you have provided the correct resource and try again.</p>
        capo_kendra.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling. Please reduce the number of requests and try again.</p>
        capo_kendra.errors.validation_exception.ValidationException: <p>The input fails to satisfy the constraints set by the Amazon Kendra service. Please provide the correct input and try again.</p>
        capo_kendra.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_kendra.types.associate_personas_to_entities_request.AssociatePersonasToEntitiesRequest]",
    ) -> OperationResponse[
        "capo_kendra.types.associate_personas_to_entities_response.AssociatePersonasToEntitiesResponse"
    ]:
        import capo_kendra._operations.aws_kendra_frontend_service.associate_personas_to_entities

        output, http_response = (
            capo_kendra._operations.aws_kendra_frontend_service.associate_personas_to_entities.associate_personas_to_entities(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("AssociatePersonasToEntities")
    )
    input_: capo_kendra.types.associate_personas_to_entities_request.AssociatePersonasToEntitiesRequest = {
        "id": id,
        "index_id": index_id,
        "personas": personas,
    }

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output