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associate_default_vocabulary

associate_default_vocabulary(
    instance_id: InstanceId,
    language_code: VocabularyLanguageCode,
    *,
    config_overrides: Optional[ConnectClientConfig] = None,
    vocabulary_id: Optional[VocabularyId] = None,
) -> AssociateDefaultVocabularyResponse

Associates an existing vocabulary as the default. Contact Lens for Connect Customer uses the vocabulary in post-call and real-time analysis sessions for the given language.

Parameters:

Raises:

Source code in docs_src/capo_connect/_services/connect.py
def associate_default_vocabulary(
    self,
    instance_id: "capo_connect.types.instance_id.InstanceId",
    language_code: "capo_connect.types.vocabulary_language_code.VocabularyLanguageCode",
    *,
    config_overrides: Optional[ConnectClientConfig] = None,
    vocabulary_id: Optional["capo_connect.types.vocabulary_id.VocabularyId"] = None,
) -> "capo_connect.types.associate_default_vocabulary_response.AssociateDefaultVocabularyResponse":
    """<p>Associates an existing vocabulary as the default. Contact Lens for Connect Customer uses the vocabulary in post-call and real-time analysis sessions for the given language.</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>
        language_code: <p>The language code of the vocabulary entries. For a list of languages and their corresponding language codes, see <a href="https://docs.aws.amazon.com/transcribe/latest/dg/transcribe-whatis.html">What is Amazon Transcribe?</a> </p>
        vocabulary_id: <p>The identifier of the custom vocabulary. If this is empty, the default is set to none.</p>

    Raises:
        capo_connect.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient permissions to perform this action.</p>
        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_request_exception.InvalidRequestException: <p>The request is not valid.</p>
        capo_connect.errors.resource_not_found_exception.ResourceNotFoundException: <p>The specified resource was not found.</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.associate_default_vocabulary_request.AssociateDefaultVocabularyRequest]",
    ) -> OperationResponse[
        "capo_connect.types.associate_default_vocabulary_response.AssociateDefaultVocabularyResponse"
    ]:
        import capo_connect._operations.amazon_connect_service.associate_default_vocabulary

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("AssociateDefaultVocabulary")
    )
    input_: capo_connect.types.associate_default_vocabulary_request.AssociateDefaultVocabularyRequest = {
        "instance_id": instance_id,
        "language_code": language_code,
    }
    if vocabulary_id is not None:
        input_["vocabulary_id"] = vocabulary_id

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