start_contact_conversational_analytics_job ¶

def start_contact_conversational_analytics_job(
    self,
    instance_id: "capo_connect.types.instance_id.InstanceId",
    contact_id: "capo_connect.types.contact_id.ContactId",
    analytics_modes: "capo_connect.types.analytics_modes.AnalyticsModes",
    analytics_configuration: "capo_connect.types.analytics_configuration.AnalyticsConfiguration",
    *,
    config_overrides: Optional[ConnectClientConfig] = None,
    client_token: Optional["capo_connect.types.client_token.ClientToken"] = None,
) -> "capo_connect.types.start_contact_conversational_analytics_job_response.StartContactConversationalAnalyticsJobResponse":
    """<p>Starts a Contact Lens post-call analytics job for the specified contact. This API runs Conversational Analytics post-contact analysis on a voice recording that is already attached to the contact, generating transcription, sentiment analysis, redaction, and summarization results based on the provided configuration.</p> <important> <p>A voice recording must already be attached to the contact before calling this API. Use <code>CreateAttachedFile</code> to attach a recording from an S3 source URI.</p> </important> <note> <p>For example, you can call <code>CreateContact</code>, then <code>CreateAttachedFile</code>, then <code>StartContactConversationalAnalyticsJob</code> to create a contact, attach a recording, and run post-call analytics.</p> </note>

    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>
        contact_id: <p>The identifier of the contact in this instance of Connect Customer. </p>
        analytics_modes: <p>The analytics modes to run for the contact. Valid values: <code>PostContact</code>.</p>
        analytics_configuration: <p>The configuration for the conversational analytics job.</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>

    Raises:
        capo_connect.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient permissions to perform this action.</p>
        capo_connect.errors.idempotency_exception.IdempotencyException: <p>An entity with the same name already exists.</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.start_contact_conversational_analytics_job_request.StartContactConversationalAnalyticsJobRequest]",
    ) -> OperationResponse[
        "capo_connect.types.start_contact_conversational_analytics_job_response.StartContactConversationalAnalyticsJobResponse"
    ]:
        import capo_connect._operations.amazon_connect_service.start_contact_conversational_analytics_job

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("StartContactConversationalAnalyticsJob")
    )
    input_: capo_connect.types.start_contact_conversational_analytics_job_request.StartContactConversationalAnalyticsJobRequest = {
        "instance_id": instance_id,
        "contact_id": contact_id,
        "analytics_modes": analytics_modes,
        "analytics_configuration": analytics_configuration,
    }
    if client_token is not None:
        input_["client_token"] = client_token

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