create_evaluation_form ¶

def create_evaluation_form(
    self,
    instance_id: "capo_connect.types.instance_id.InstanceId",
    title: "capo_connect.types.evaluation_form_title.EvaluationFormTitle",
    items: "capo_connect.types.evaluation_form_items_list.EvaluationFormItemsList",
    *,
    config_overrides: Optional[ConnectClientConfig] = None,
    description: Optional[
        "capo_connect.types.evaluation_form_description.EvaluationFormDescription"
    ] = None,
    scoring_strategy: Optional[
        "capo_connect.types.evaluation_form_scoring_strategy.EvaluationFormScoringStrategy"
    ] = None,
    auto_evaluation_configuration: Optional[
        "capo_connect.types.evaluation_form_auto_evaluation_configuration.EvaluationFormAutoEvaluationConfiguration"
    ] = None,
    client_token: Optional["capo_connect.types.client_token.ClientToken"] = None,
    as_draft: Optional["capo_connect.types.boxed_boolean.BoxedBoolean"] = None,
    tags: Optional["capo_connect.types.tag_map.TagMap"] = None,
    review_configuration: Optional[
        "capo_connect.types.evaluation_review_configuration.EvaluationReviewConfiguration"
    ] = None,
    target_configuration: Optional[
        "capo_connect.types.evaluation_form_target_configuration.EvaluationFormTargetConfiguration"
    ] = None,
    language_configuration: Optional[
        "capo_connect.types.evaluation_form_language_configuration.EvaluationFormLanguageConfiguration"
    ] = None,
    ai_version: Optional[
        "capo_connect.types.evaluation_form_ai_version.EvaluationFormAIVersion"
    ] = None,
) -> "capo_connect.types.create_evaluation_form_response.CreateEvaluationFormResponse":
    """<p>Creates an evaluation form in the specified Connect Customer instance. The form can be used to define questions related to agent performance, and create sections to organize such questions. Question and section identifiers cannot be duplicated within the same evaluation form.</p>

    Args:
        instance_id: <p>The identifier of the Connect Customer instance. You can <a href="https://docs.aws.amazon.com/connect/latest/adminguide/find-instance-arn.html">find the instance ID</a> in the Amazon Resource Name (ARN) of the instance.</p>
        title: <p>A title of the evaluation form.</p>
        description: <p>The description of the evaluation form.</p>
        items: <p>Items that are part of the evaluation form. The total number of sections and questions must not exceed 100 each. Questions must be contained in a section.</p>
        scoring_strategy: <p>A scoring strategy of the evaluation form.</p>
        auto_evaluation_configuration: <p>Configuration information about automated evaluations.</p>
        client_token: <p>A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. If not provided, the Amazon Web Services SDK populates this field. For more information about idempotency, see <a href="https://aws.amazon.com/builders-library/making-retries-safe-with-idempotent-APIs/">Making retries safe with idempotent APIs</a>.</p>
        as_draft: <p>A boolean flag indicating whether to create evaluation form in draft state.</p>
        tags: <p>The tags used to organize, track, or control access for this resource. For example, { "Tags": {"key1":"value1", "key2":"value2"} }.</p>
        review_configuration: <p>Configuration information about evaluation reviews.</p>
        target_configuration: <p>Configuration that specifies the target for the evaluation form.</p>
        language_configuration: <p>Configuration for language settings of the evaluation form.</p>
        ai_version: <p>The AI version to use for the evaluation form. This specifies which AI model version is used for automated evaluations.</p>

    Raises:
        capo_connect.errors.internal_service_exception.InternalServiceException: <p>Request processing failed because of an error or failure with the service.</p>
        capo_connect.errors.invalid_parameter_exception.InvalidParameterException: <p>One or more of the specified parameters are not valid.</p>
        capo_connect.errors.resource_conflict_exception.ResourceConflictException: <p>A resource already has that name.</p>
        capo_connect.errors.resource_not_found_exception.ResourceNotFoundException: <p>The specified resource was not found.</p>
        capo_connect.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>The service quota has been exceeded.</p>
        capo_connect.errors.throttling_exception.ThrottlingException: <p>The throttling limit has been exceeded.</p>
        capo_connect.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_connect.types.create_evaluation_form_request.CreateEvaluationFormRequest]",
    ) -> OperationResponse[
        "capo_connect.types.create_evaluation_form_response.CreateEvaluationFormResponse"
    ]:
        import capo_connect._operations.amazon_connect_service.create_evaluation_form

        output, http_response = (
            capo_connect._operations.amazon_connect_service.create_evaluation_form.create_evaluation_form(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("CreateEvaluationForm")
    )
    input_: capo_connect.types.create_evaluation_form_request.CreateEvaluationFormRequest = {
        "instance_id": instance_id,
        "title": title,
        "items": items,
    }
    if description is not None:
        input_["description"] = description
    if scoring_strategy is not None:
        input_["scoring_strategy"] = scoring_strategy
    if auto_evaluation_configuration is not None:
        input_["auto_evaluation_configuration"] = auto_evaluation_configuration
    if client_token is None:
        client_token = str(uuid.uuid4())
    input_["client_token"] = client_token
    if as_draft is not None:
        input_["as_draft"] = as_draft
    if tags is not None:
        input_["tags"] = tags
    if review_configuration is not None:
        input_["review_configuration"] = review_configuration
    if target_configuration is not None:
        input_["target_configuration"] = target_configuration
    if language_configuration is not None:
        input_["language_configuration"] = language_configuration
    if ai_version is not None:
        input_["ai_version"] = ai_version

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