list_ai_guardrail_versions ¶

def list_ai_guardrail_versions(
    self,
    assistant_id: "capo_qconnect.types.uuid_or_arn.UuidOrArn",
    ai_guardrail_id: "capo_qconnect.types.uuid_or_arn_or_either_with_qualifier.UuidOrArnOrEitherWithQualifier",
    *,
    config_overrides: Optional[QConnectClientConfig] = None,
    next_token: Optional["capo_qconnect.types.next_token.NextToken"] = None,
    max_results: Optional["capo_qconnect.types.max_results.MaxResults"] = None,
) -> "capo_qconnect.types.list_ai_guardrail_versions_response.ListAIGuardrailVersionsResponse":
    """<p>Lists AI Guardrail versions.</p>

    Args:
        assistant_id: <p>The identifier of the Amazon Q in Connect assistant. Can be either the ID or the ARN. URLs cannot contain the ARN.</p>
        ai_guardrail_id: <p>The identifier of the Amazon Q in Connect AI Guardrail for which versions are to be listed.</p>
        next_token: <p>The token for the next set of results. Use the value returned in the previous response in the next request to retrieve the next set of results.</p>
        max_results: <p>The maximum number of results to return per page.</p>

    Raises:
        capo_qconnect.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</p>
        capo_qconnect.errors.resource_not_found_exception.ResourceNotFoundException: <p>The specified resource does not exist.</p>
        capo_qconnect.errors.throttling_exception.ThrottlingException: <p>The throttling limit has been exceeded.</p>
        capo_qconnect.errors.unauthorized_exception.UnauthorizedException: <p>You do not have permission to perform this action.</p>
        capo_qconnect.errors.validation_exception.ValidationException: <p>The input fails to satisfy the constraints specified by a service.</p>
        capo_qconnect.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_qconnect.types.list_ai_guardrail_versions_request.ListAIGuardrailVersionsRequest]",
    ) -> OperationResponse[
        "capo_qconnect.types.list_ai_guardrail_versions_response.ListAIGuardrailVersionsResponse"
    ]:
        import capo_qconnect._operations.wisdom_service.list_ai_guardrail_versions

        output, http_response = (
            capo_qconnect._operations.wisdom_service.list_ai_guardrail_versions.list_ai_guardrail_versions(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    def _redact_output(
        output: "capo_qconnect.types.list_ai_guardrail_versions_response.ListAIGuardrailVersionsResponse",
    ) -> dict[str, Any]:
        import capo_qconnect.types.list_ai_guardrail_versions_response

        return capo_qconnect.types.list_ai_guardrail_versions_response.redact_sensitive(
            output
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("ListAIGuardrailVersions", redact_output=_redact_output),
    )
    input_: capo_qconnect.types.list_ai_guardrail_versions_request.ListAIGuardrailVersionsRequest = {
        "assistant_id": assistant_id,
        "ai_guardrail_id": ai_guardrail_id,
    }
    if next_token is not None:
        input_["next_token"] = next_token
    if max_results is not None:
        input_["max_results"] = max_results

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