recognize_text ¶

def recognize_text(
    self,
    bot_id: "capo_lex_runtime_v2.types.bot_identifier.BotIdentifier",
    bot_alias_id: "capo_lex_runtime_v2.types.bot_alias_identifier.BotAliasIdentifier",
    locale_id: "capo_lex_runtime_v2.types.locale_id.LocaleId",
    session_id: "capo_lex_runtime_v2.types.session_id.SessionId",
    text: "capo_lex_runtime_v2.types.text.Text",
    *,
    config_overrides: Optional[LexRuntimeV2ClientConfig] = None,
    session_state: Optional[
        "capo_lex_runtime_v2.types.session_state.SessionState"
    ] = None,
    request_attributes: Optional[
        "capo_lex_runtime_v2.types.string_map.StringMap"
    ] = None,
) -> "capo_lex_runtime_v2.types.recognize_text_response.RecognizeTextResponse":
    """<p>Sends user input to Amazon Lex V2. Client applications use this API to send requests to Amazon Lex V2 at runtime. Amazon Lex V2 then interprets the user input using the machine learning model that it build for the bot.</p> <p>In response, Amazon Lex V2 returns the next message to convey to the user and an optional response card to display.</p> <p>If the optional post-fulfillment response is specified, the messages are returned as follows. For more information, see <a href="https://docs.aws.amazon.com/lexv2/latest/dg/API_PostFulfillmentStatusSpecification.html">PostFulfillmentStatusSpecification</a>.</p> <ul> <li> <p> <b>Success message</b> - Returned if the Lambda function completes successfully and the intent state is fulfilled or ready fulfillment if the message is present.</p> </li> <li> <p> <b>Failed message</b> - The failed message is returned if the Lambda function throws an exception or if the Lambda function returns a failed intent state without a message.</p> </li> <li> <p> <b>Timeout message</b> - If you don't configure a timeout message and a timeout, and the Lambda function doesn't return within 30 seconds, the timeout message is returned. If you configure a timeout, the timeout message is returned when the period times out. </p> </li> </ul> <p>For more information, see <a href="https://docs.aws.amazon.com/lexv2/latest/dg/streaming-progress.html#progress-complete.html">Completion message</a>.</p>

    Args:
        bot_id: <p>The identifier of the bot that processes the request.</p>
        bot_alias_id: <p>The alias identifier in use for the bot that processes the request.</p>
        locale_id: <p>The locale where the session is in use.</p>
        session_id: <p>The identifier of the user session that is having the conversation.</p>
        text: <p>The text that the user entered. Amazon Lex V2 interprets this text.</p>
        session_state: <p>The current state of the dialog between the user and the bot.</p>
        request_attributes: <p>Request-specific information passed between the client application and Amazon Lex V2 </p> <p>The namespace <code>x-amz-lex:</code> is reserved for special attributes. Don't create any request attributes with the prefix <code>x-amz-lex:</code>.</p>

    Raises:
        capo_lex_runtime_v2.errors.access_denied_exception.AccessDeniedException: <p></p>
        capo_lex_runtime_v2.errors.bad_gateway_exception.BadGatewayException: <p></p>
        capo_lex_runtime_v2.errors.conflict_exception.ConflictException: <p></p>
        capo_lex_runtime_v2.errors.dependency_failed_exception.DependencyFailedException: <p></p>
        capo_lex_runtime_v2.errors.internal_server_exception.InternalServerException: <p></p>
        capo_lex_runtime_v2.errors.resource_not_found_exception.ResourceNotFoundException: <p></p>
        capo_lex_runtime_v2.errors.throttling_exception.ThrottlingException: <p></p>
        capo_lex_runtime_v2.errors.validation_exception.ValidationException: <p></p>
        capo_lex_runtime_v2.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_lex_runtime_v2.types.recognize_text_request.RecognizeTextRequest]",
    ) -> OperationResponse[
        "capo_lex_runtime_v2.types.recognize_text_response.RecognizeTextResponse"
    ]:
        import capo_lex_runtime_v2._operations.aws_deep_sense_run_time_service_api2_0.recognize_text

        output, http_response = (
            capo_lex_runtime_v2._operations.aws_deep_sense_run_time_service_api2_0.recognize_text.recognize_text(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    def _redact_input(
        input_: "capo_lex_runtime_v2.types.recognize_text_request.RecognizeTextRequest",
    ) -> dict[str, Any]:
        import capo_lex_runtime_v2.types.recognize_text_request

        return capo_lex_runtime_v2.types.recognize_text_request.redact_sensitive(
            input_
        )

    def _redact_output(
        output: "capo_lex_runtime_v2.types.recognize_text_response.RecognizeTextResponse",
    ) -> dict[str, Any]:
        import capo_lex_runtime_v2.types.recognize_text_response

        return capo_lex_runtime_v2.types.recognize_text_response.redact_sensitive(
            output
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging(
            "RecognizeText",
            redact_input=_redact_input,
            redact_output=_redact_output,
        ),
    )
    input_: capo_lex_runtime_v2.types.recognize_text_request.RecognizeTextRequest = {
        "bot_id": bot_id,
        "bot_alias_id": bot_alias_id,
        "locale_id": locale_id,
        "session_id": session_id,
        "text": text,
    }
    if session_state is not None:
        input_["session_state"] = session_state
    if request_attributes is not None:
        input_["request_attributes"] = request_attributes

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