update_rescore_execution_plan ¶

def update_rescore_execution_plan(
    self,
    id: "capo_kendra_ranking.types.rescore_execution_plan_id.RescoreExecutionPlanId",
    *,
    config_overrides: Optional[KendraRankingClientConfig] = None,
    name: Optional[
        "capo_kendra_ranking.types.rescore_execution_plan_name.RescoreExecutionPlanName"
    ] = None,
    description: Optional[
        "capo_kendra_ranking.types.description.Description"
    ] = None,
    capacity_units: Optional[
        "capo_kendra_ranking.types.capacity_units_configuration.CapacityUnitsConfiguration"
    ] = None,
) -> None:
    """<p>Updates a rescore execution plan. A rescore execution plan is an Amazon Kendra Intelligent Ranking resource used for provisioning the <code>Rescore</code> API. You can update the number of capacity units you require for Amazon Kendra Intelligent Ranking to rescore or re-rank a search service's results.</p>

    Args:
        id: <p>The identifier of the rescore execution plan that you want to update.</p>
        name: <p>A new name for the rescore execution plan.</p>
        description: <p>A new description for the rescore execution plan.</p>
        capacity_units: <p>You can set additional capacity units to meet the needs of your rescore execution plan. You are given a single capacity unit by default. If you want to use the default capacity, you don't set additional capacity units. For more information on the default capacity and additional capacity units, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/adjusting-capacity.html">Adjusting capacity</a>.</p>

    Raises:
        capo_kendra_ranking.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_ranking.errors.conflict_exception.ConflictException: <p>A conflict occurred with the request. Please fix any inconsistencies with your resources and try again.</p>
        capo_kendra_ranking.errors.internal_server_exception.InternalServerException: <p>An issue occurred with the internal server used for your Amazon Kendra Intelligent Ranking 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_ranking.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_ranking.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>You have exceeded the set limits for your Amazon Kendra Intelligent Ranking service. Please see <a href="https://docs.aws.amazon.com/kendra/latest/dg/quotas.html">Quotas</a> for more information, or contact <a href="http://aws.amazon.com/contact-us/">Support</a> to inquire about an increase of limits.</p>
        capo_kendra_ranking.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_ranking.errors.validation_exception.ValidationException: <p>The input fails to satisfy the constraints set by the Amazon Kendra Intelligent Ranking service. Please provide the correct input and try again.</p>
        capo_kendra_ranking.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_kendra_ranking.types.update_rescore_execution_plan_request.UpdateRescoreExecutionPlanRequest]",
    ) -> OperationResponse[None]:
        import capo_kendra_ranking._operations.aws_kendra_reranking_frontend_service.update_rescore_execution_plan

        output, http_response = (
            capo_kendra_ranking._operations.aws_kendra_reranking_frontend_service.update_rescore_execution_plan.update_rescore_execution_plan(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("UpdateRescoreExecutionPlan")
    )
    input_: capo_kendra_ranking.types.update_rescore_execution_plan_request.UpdateRescoreExecutionPlanRequest = {
        "id": id
    }
    if name is not None:
        input_["name"] = name
    if description is not None:
        input_["description"] = description
    if capacity_units is not None:
        input_["capacity_units"] = capacity_units

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