infer_rx_norm ¶

def infer_rx_norm(
    self,
    text: "capo_comprehendmedical.types.ontology_linking_bounded_length_string.OntologyLinkingBoundedLengthString",
    *,
    config_overrides: Optional[ComprehendMedicalClientConfig] = None,
) -> "capo_comprehendmedical.types.infer_rx_norm_response.InferRxNormResponse":
    """<p>InferRxNorm detects medications as entities listed in a patient record and links to the normalized concept identifiers in the RxNorm database from the National Library of Medicine. Amazon Comprehend Medical only detects medical entities in English language texts. </p>

    Args:
        text: <p>The input text used for analysis.</p>

    Raises:
        capo_comprehendmedical.errors.internal_server_exception.InternalServerException: <p> An internal server error occurred. Retry your request. </p>
        capo_comprehendmedical.errors.invalid_encoding_exception.InvalidEncodingException: <p> The input text was not in valid UTF-8 character encoding. Check your text then retry your request.</p>
        capo_comprehendmedical.errors.invalid_request_exception.InvalidRequestException: <p> The request that you made is invalid. Check your request to determine why it's invalid and then retry the request.</p>
        capo_comprehendmedical.errors.service_unavailable_exception.ServiceUnavailableException: <p> The Amazon Comprehend Medical service is temporarily unavailable. Please wait and then retry your request. </p>
        capo_comprehendmedical.errors.text_size_limit_exceeded_exception.TextSizeLimitExceededException: <p> The size of the text you submitted exceeds the size limit. Reduce the size of the text or use a smaller document and then retry your request. </p>
        capo_comprehendmedical.errors.too_many_requests_exception.TooManyRequestsException: <p> You have made too many requests within a short period of time. Wait for a short time and then try your request again. Contact customer support for more information about a service limit increase. </p>
        capo_comprehendmedical.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_comprehendmedical.types.infer_rx_norm_request.InferRxNormRequest]",
    ) -> OperationResponse[
        "capo_comprehendmedical.types.infer_rx_norm_response.InferRxNormResponse"
    ]:
        import capo_comprehendmedical._operations.comprehend_medical_20181030.infer_rx_norm

        output, http_response = (
            capo_comprehendmedical._operations.comprehend_medical_20181030.infer_rx_norm.infer_rx_norm(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("InferRxNorm")
    )
    input_: capo_comprehendmedical.types.infer_rx_norm_request.InferRxNormRequest = {
        "text": text
    }

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