Struct aws_sdk_lexruntimev2::operation::recognize_utterance::RecognizeUtteranceOutput

#[non_exhaustive]
pub struct RecognizeUtteranceOutput {
    pub input_mode: Option<String>,
    pub content_type: Option<String>,
    pub messages: Option<String>,
    pub interpretations: Option<String>,
    pub session_state: Option<String>,
    pub request_attributes: Option<String>,
    pub session_id: Option<String>,
    pub input_transcript: Option<String>,
    pub audio_stream: ByteStream,
    pub recognized_bot_member: Option<String>,
    /* private fields */
}

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

input_mode: Option<String>

Indicates whether the input mode to the operation was text or speech.

content_type: Option<String>

Content type as specified in the responseContentType in the request.

messages: Option<String>

A list of messages that were last sent to the user. The messages are ordered based on the order that you returned the messages from your Lambda function or the order that the messages are defined in the bot.

The messages field is compressed with gzip and then base64 encoded. Before you can use the contents of the field, you must decode and decompress the contents. See the example for a simple function to decode and decompress the contents.

interpretations: Option<String>

A list of intents that Amazon Lex V2 determined might satisfy the user's utterance.

Each interpretation includes the intent, a score that indicates how confident Amazon Lex V2 is that the interpretation is the correct one, and an optional sentiment response that indicates the sentiment expressed in the utterance.

The interpretations field is compressed with gzip and then base64 encoded. Before you can use the contents of the field, you must decode and decompress the contents. See the example for a simple function to decode and decompress the contents.

session_state: Option<String>

Represents the current state of the dialog between the user and the bot.

Use this to determine the progress of the conversation and what the next action might be.

The sessionState field is compressed with gzip and then base64 encoded. Before you can use the contents of the field, you must decode and decompress the contents. See the example for a simple function to decode and decompress the contents.

request_attributes: Option<String>

The attributes sent in the request.

The requestAttributes field is compressed with gzip and then base64 encoded. Before you can use the contents of the field, you must decode and decompress the contents.

session_id: Option<String>

The identifier of the session in use.

input_transcript: Option<String>

The text used to process the request.

If the input was an audio stream, the inputTranscript field contains the text extracted from the audio stream. This is the text that is actually processed to recognize intents and slot values. You can use this information to determine if Amazon Lex V2 is correctly processing the audio that you send.

The inputTranscript field is compressed with gzip and then base64 encoded. Before you can use the contents of the field, you must decode and decompress the contents. See the example for a simple function to decode and decompress the contents.

audio_stream: ByteStream

The prompt or statement to send to the user. This is based on the bot configuration and context. For example, if Amazon Lex V2 did not understand the user intent, it sends the clarificationPrompt configured for the bot. If the intent requires confirmation before taking the fulfillment action, it sends the confirmationPrompt. Another example: Suppose that the Lambda function successfully fulfilled the intent, and sent a message to convey to the user. Then Amazon Lex V2 sends that message in the response.

recognized_bot_member: Option<String>

The bot member that recognized the utterance.

Implementations

impl RecognizeUtteranceOutput

pub fn input_mode(&self) -> Option<&str>

Indicates whether the input mode to the operation was text or speech.

pub fn content_type(&self) -> Option<&str>

Content type as specified in the responseContentType in the request.

pub fn messages(&self) -> Option<&str>

A list of messages that were last sent to the user. The messages are ordered based on the order that you returned the messages from your Lambda function or the order that the messages are defined in the bot.

The messages field is compressed with gzip and then base64 encoded. Before you can use the contents of the field, you must decode and decompress the contents. See the example for a simple function to decode and decompress the contents.

pub fn interpretations(&self) -> Option<&str>

A list of intents that Amazon Lex V2 determined might satisfy the user's utterance.

Each interpretation includes the intent, a score that indicates how confident Amazon Lex V2 is that the interpretation is the correct one, and an optional sentiment response that indicates the sentiment expressed in the utterance.

The interpretations field is compressed with gzip and then base64 encoded. Before you can use the contents of the field, you must decode and decompress the contents. See the example for a simple function to decode and decompress the contents.

pub fn session_state(&self) -> Option<&str>

Represents the current state of the dialog between the user and the bot.

Use this to determine the progress of the conversation and what the next action might be.

The sessionState field is compressed with gzip and then base64 encoded. Before you can use the contents of the field, you must decode and decompress the contents. See the example for a simple function to decode and decompress the contents.

pub fn request_attributes(&self) -> Option<&str>

The attributes sent in the request.

The requestAttributes field is compressed with gzip and then base64 encoded. Before you can use the contents of the field, you must decode and decompress the contents.

pub fn session_id(&self) -> Option<&str>

The identifier of the session in use.

pub fn input_transcript(&self) -> Option<&str>

The text used to process the request.

If the input was an audio stream, the inputTranscript field contains the text extracted from the audio stream. This is the text that is actually processed to recognize intents and slot values. You can use this information to determine if Amazon Lex V2 is correctly processing the audio that you send.

The inputTranscript field is compressed with gzip and then base64 encoded. Before you can use the contents of the field, you must decode and decompress the contents. See the example for a simple function to decode and decompress the contents.

pub fn audio_stream(&self) -> &ByteStream

The prompt or statement to send to the user. This is based on the bot configuration and context. For example, if Amazon Lex V2 did not understand the user intent, it sends the clarificationPrompt configured for the bot. If the intent requires confirmation before taking the fulfillment action, it sends the confirmationPrompt. Another example: Suppose that the Lambda function successfully fulfilled the intent, and sent a message to convey to the user. Then Amazon Lex V2 sends that message in the response.

pub fn recognized_bot_member(&self) -> Option<&str>

The bot member that recognized the utterance.

impl RecognizeUtteranceOutput

pub fn builder() -> RecognizeUtteranceOutputBuilder

Creates a new builder-style object to manufacture RecognizeUtteranceOutput.

Trait Implementations

impl Debug for RecognizeUtteranceOutput

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl RequestId for RecognizeUtteranceOutput

fn request_id(&self) -> Option<&str>

Returns the request ID, or None if the service could not be reached.