PostContentOutputBuilder

aws_sdk_lexruntime::operation::post_content::builders

Struct PostContentOutputBuilder 

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#[non_exhaustive]
pub struct PostContentOutputBuilder { /* private fields */ }
Expand description

A builder for PostContentOutput.

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impl PostContentOutputBuilder

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pub fn content_type(self, input: impl Into<String>) -> Self

Content type as specified in the Accept HTTP header in the request.

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pub fn set_content_type(self, input: Option<String>) -> Self

Content type as specified in the Accept HTTP header in the request.

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pub fn get_content_type(&self) -> &Option<String>

Content type as specified in the Accept HTTP header in the request.

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pub fn intent_name(self, input: impl Into<String>) -> Self

Current user intent that Amazon Lex is aware of.

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pub fn set_intent_name(self, input: Option<String>) -> Self

Current user intent that Amazon Lex is aware of.

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pub fn get_intent_name(&self) -> &Option<String>

Current user intent that Amazon Lex is aware of.

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pub fn nlu_intent_confidence(self, input: impl Into<String>) -> Self

Provides a score that indicates how confident Amazon Lex is that the returned intent is the one that matches the user's intent. The score is between 0.0 and 1.0.

The score is a relative score, not an absolute score. The score may change based on improvements to Amazon Lex.

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pub fn set_nlu_intent_confidence(self, input: Option<String>) -> Self

Provides a score that indicates how confident Amazon Lex is that the returned intent is the one that matches the user's intent. The score is between 0.0 and 1.0.

The score is a relative score, not an absolute score. The score may change based on improvements to Amazon Lex.

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pub fn get_nlu_intent_confidence(&self) -> &Option<String>

Provides a score that indicates how confident Amazon Lex is that the returned intent is the one that matches the user's intent. The score is between 0.0 and 1.0.

The score is a relative score, not an absolute score. The score may change based on improvements to Amazon Lex.

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pub fn alternative_intents(self, input: impl Into<String>) -> Self

One to four alternative intents that may be applicable to the user's intent.

Each alternative includes a score that indicates how confident Amazon Lex is that the intent matches the user's intent. The intents are sorted by the confidence score.

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pub fn set_alternative_intents(self, input: Option<String>) -> Self

One to four alternative intents that may be applicable to the user's intent.

Each alternative includes a score that indicates how confident Amazon Lex is that the intent matches the user's intent. The intents are sorted by the confidence score.

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pub fn get_alternative_intents(&self) -> &Option<String>

One to four alternative intents that may be applicable to the user's intent.

Each alternative includes a score that indicates how confident Amazon Lex is that the intent matches the user's intent. The intents are sorted by the confidence score.

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pub fn slots(self, input: impl Into<String>) -> Self

Map of zero or more intent slots (name/value pairs) Amazon Lex detected from the user input during the conversation. The field is base-64 encoded.

Amazon Lex creates a resolution list containing likely values for a slot. The value that it returns is determined by the valueSelectionStrategy selected when the slot type was created or updated. If valueSelectionStrategy is set to ORIGINAL_VALUE, the value provided by the user is returned, if the user value is similar to the slot values. If valueSelectionStrategy is set to TOP_RESOLUTION Amazon Lex returns the first value in the resolution list or, if there is no resolution list, null. If you don't specify a valueSelectionStrategy, the default is ORIGINAL_VALUE.

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pub fn set_slots(self, input: Option<String>) -> Self

Map of zero or more intent slots (name/value pairs) Amazon Lex detected from the user input during the conversation. The field is base-64 encoded.

Amazon Lex creates a resolution list containing likely values for a slot. The value that it returns is determined by the valueSelectionStrategy selected when the slot type was created or updated. If valueSelectionStrategy is set to ORIGINAL_VALUE, the value provided by the user is returned, if the user value is similar to the slot values. If valueSelectionStrategy is set to TOP_RESOLUTION Amazon Lex returns the first value in the resolution list or, if there is no resolution list, null. If you don't specify a valueSelectionStrategy, the default is ORIGINAL_VALUE.

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pub fn get_slots(&self) -> &Option<String>

Map of zero or more intent slots (name/value pairs) Amazon Lex detected from the user input during the conversation. The field is base-64 encoded.

Amazon Lex creates a resolution list containing likely values for a slot. The value that it returns is determined by the valueSelectionStrategy selected when the slot type was created or updated. If valueSelectionStrategy is set to ORIGINAL_VALUE, the value provided by the user is returned, if the user value is similar to the slot values. If valueSelectionStrategy is set to TOP_RESOLUTION Amazon Lex returns the first value in the resolution list or, if there is no resolution list, null. If you don't specify a valueSelectionStrategy, the default is ORIGINAL_VALUE.

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pub fn session_attributes(self, input: impl Into<String>) -> Self

Map of key/value pairs representing the session-specific context information.

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pub fn set_session_attributes(self, input: Option<String>) -> Self

Map of key/value pairs representing the session-specific context information.

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pub fn get_session_attributes(&self) -> &Option<String>

Map of key/value pairs representing the session-specific context information.

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pub fn sentiment_response(self, input: impl Into<String>) -> Self

The sentiment expressed in an utterance.

When the bot is configured to send utterances to Amazon Comprehend for sentiment analysis, this field contains the result of the analysis.

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pub fn set_sentiment_response(self, input: Option<String>) -> Self

The sentiment expressed in an utterance.

When the bot is configured to send utterances to Amazon Comprehend for sentiment analysis, this field contains the result of the analysis.

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pub fn get_sentiment_response(&self) -> &Option<String>

The sentiment expressed in an utterance.

When the bot is configured to send utterances to Amazon Comprehend for sentiment analysis, this field contains the result of the analysis.

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pub fn message(self, input: impl Into<String>) -> Self

👎Deprecated: The message field is deprecated, use the encodedMessage field instead. The message field is available only in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR and it-IT locales.

You can only use this field in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR, and it-IT locales. In all other locales, the message field is null. You should use the encodedMessage field instead.

The message to convey to the user. The message can come from the bot's configuration or from a Lambda function.

If the intent is not configured with a Lambda function, or if the Lambda function returned Delegate as the dialogAction.type in its response, Amazon Lex decides on the next course of action and selects an appropriate message from the bot's configuration based on the current interaction context. For example, if Amazon Lex isn't able to understand user input, it uses a clarification prompt message.

When you create an intent you can assign messages to groups. When messages are assigned to groups Amazon Lex returns one message from each group in the response. The message field is an escaped JSON string containing the messages. For more information about the structure of the JSON string returned, see msg-prompts-formats.

If the Lambda function returns a message, Amazon Lex passes it to the client in its response.

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pub fn set_message(self, input: Option<String>) -> Self

👎Deprecated: The message field is deprecated, use the encodedMessage field instead. The message field is available only in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR and it-IT locales.

You can only use this field in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR, and it-IT locales. In all other locales, the message field is null. You should use the encodedMessage field instead.

The message to convey to the user. The message can come from the bot's configuration or from a Lambda function.

If the intent is not configured with a Lambda function, or if the Lambda function returned Delegate as the dialogAction.type in its response, Amazon Lex decides on the next course of action and selects an appropriate message from the bot's configuration based on the current interaction context. For example, if Amazon Lex isn't able to understand user input, it uses a clarification prompt message.

When you create an intent you can assign messages to groups. When messages are assigned to groups Amazon Lex returns one message from each group in the response. The message field is an escaped JSON string containing the messages. For more information about the structure of the JSON string returned, see msg-prompts-formats.

If the Lambda function returns a message, Amazon Lex passes it to the client in its response.

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pub fn get_message(&self) -> &Option<String>

👎Deprecated: The message field is deprecated, use the encodedMessage field instead. The message field is available only in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR and it-IT locales.

You can only use this field in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR, and it-IT locales. In all other locales, the message field is null. You should use the encodedMessage field instead.

The message to convey to the user. The message can come from the bot's configuration or from a Lambda function.

If the intent is not configured with a Lambda function, or if the Lambda function returned Delegate as the dialogAction.type in its response, Amazon Lex decides on the next course of action and selects an appropriate message from the bot's configuration based on the current interaction context. For example, if Amazon Lex isn't able to understand user input, it uses a clarification prompt message.

When you create an intent you can assign messages to groups. When messages are assigned to groups Amazon Lex returns one message from each group in the response. The message field is an escaped JSON string containing the messages. For more information about the structure of the JSON string returned, see msg-prompts-formats.

If the Lambda function returns a message, Amazon Lex passes it to the client in its response.

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pub fn encoded_message(self, input: impl Into<String>) -> Self

The message to convey to the user. The message can come from the bot's configuration or from a Lambda function.

If the intent is not configured with a Lambda function, or if the Lambda function returned Delegate as the dialogAction.type in its response, Amazon Lex decides on the next course of action and selects an appropriate message from the bot's configuration based on the current interaction context. For example, if Amazon Lex isn't able to understand user input, it uses a clarification prompt message.

When you create an intent you can assign messages to groups. When messages are assigned to groups Amazon Lex returns one message from each group in the response. The message field is an escaped JSON string containing the messages. For more information about the structure of the JSON string returned, see msg-prompts-formats.

If the Lambda function returns a message, Amazon Lex passes it to the client in its response.

The encodedMessage field is base-64 encoded. You must decode the field before you can use the value.

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pub fn set_encoded_message(self, input: Option<String>) -> Self

The message to convey to the user. The message can come from the bot's configuration or from a Lambda function.

If the intent is not configured with a Lambda function, or if the Lambda function returned Delegate as the dialogAction.type in its response, Amazon Lex decides on the next course of action and selects an appropriate message from the bot's configuration based on the current interaction context. For example, if Amazon Lex isn't able to understand user input, it uses a clarification prompt message.

When you create an intent you can assign messages to groups. When messages are assigned to groups Amazon Lex returns one message from each group in the response. The message field is an escaped JSON string containing the messages. For more information about the structure of the JSON string returned, see msg-prompts-formats.

If the Lambda function returns a message, Amazon Lex passes it to the client in its response.

The encodedMessage field is base-64 encoded. You must decode the field before you can use the value.

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pub fn get_encoded_message(&self) -> &Option<String>

The message to convey to the user. The message can come from the bot's configuration or from a Lambda function.

If the intent is not configured with a Lambda function, or if the Lambda function returned Delegate as the dialogAction.type in its response, Amazon Lex decides on the next course of action and selects an appropriate message from the bot's configuration based on the current interaction context. For example, if Amazon Lex isn't able to understand user input, it uses a clarification prompt message.

When you create an intent you can assign messages to groups. When messages are assigned to groups Amazon Lex returns one message from each group in the response. The message field is an escaped JSON string containing the messages. For more information about the structure of the JSON string returned, see msg-prompts-formats.

If the Lambda function returns a message, Amazon Lex passes it to the client in its response.

The encodedMessage field is base-64 encoded. You must decode the field before you can use the value.

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pub fn message_format(self, input: MessageFormatType) -> Self

The format of the response message. One of the following values:

  • PlainText - The message contains plain UTF-8 text.

  • CustomPayload - The message is a custom format for the client.

  • SSML - The message contains text formatted for voice output.

  • Composite - The message contains an escaped JSON object containing one or more messages from the groups that messages were assigned to when the intent was created.

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pub fn set_message_format(self, input: Option<MessageFormatType>) -> Self

The format of the response message. One of the following values:

  • PlainText - The message contains plain UTF-8 text.

  • CustomPayload - The message is a custom format for the client.

  • SSML - The message contains text formatted for voice output.

  • Composite - The message contains an escaped JSON object containing one or more messages from the groups that messages were assigned to when the intent was created.

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pub fn get_message_format(&self) -> &Option<MessageFormatType>

The format of the response message. One of the following values:

  • PlainText - The message contains plain UTF-8 text.

  • CustomPayload - The message is a custom format for the client.

  • SSML - The message contains text formatted for voice output.

  • Composite - The message contains an escaped JSON object containing one or more messages from the groups that messages were assigned to when the intent was created.

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pub fn dialog_state(self, input: DialogState) -> Self

Identifies the current state of the user interaction. Amazon Lex returns one of the following values as dialogState. The client can optionally use this information to customize the user interface.

  • ElicitIntent - Amazon Lex wants to elicit the user's intent. Consider the following examples:

    For example, a user might utter an intent ("I want to order a pizza"). If Amazon Lex cannot infer the user intent from this utterance, it will return this dialog state.

  • ConfirmIntent - Amazon Lex is expecting a "yes" or "no" response.

    For example, Amazon Lex wants user confirmation before fulfilling an intent. Instead of a simple "yes" or "no" response, a user might respond with additional information. For example, "yes, but make it a thick crust pizza" or "no, I want to order a drink." Amazon Lex can process such additional information (in these examples, update the crust type slot or change the intent from OrderPizza to OrderDrink).

  • ElicitSlot - Amazon Lex is expecting the value of a slot for the current intent.

    For example, suppose that in the response Amazon Lex sends this message: "What size pizza would you like?". A user might reply with the slot value (e.g., "medium"). The user might also provide additional information in the response (e.g., "medium thick crust pizza"). Amazon Lex can process such additional information appropriately.

  • Fulfilled - Conveys that the Lambda function has successfully fulfilled the intent.

  • ReadyForFulfillment - Conveys that the client has to fulfill the request.

  • Failed - Conveys that the conversation with the user failed.

    This can happen for various reasons, including that the user does not provide an appropriate response to prompts from the service (you can configure how many times Amazon Lex can prompt a user for specific information), or if the Lambda function fails to fulfill the intent.

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pub fn set_dialog_state(self, input: Option<DialogState>) -> Self

Identifies the current state of the user interaction. Amazon Lex returns one of the following values as dialogState. The client can optionally use this information to customize the user interface.

  • ElicitIntent - Amazon Lex wants to elicit the user's intent. Consider the following examples:

    For example, a user might utter an intent ("I want to order a pizza"). If Amazon Lex cannot infer the user intent from this utterance, it will return this dialog state.

  • ConfirmIntent - Amazon Lex is expecting a "yes" or "no" response.

    For example, Amazon Lex wants user confirmation before fulfilling an intent. Instead of a simple "yes" or "no" response, a user might respond with additional information. For example, "yes, but make it a thick crust pizza" or "no, I want to order a drink." Amazon Lex can process such additional information (in these examples, update the crust type slot or change the intent from OrderPizza to OrderDrink).

  • ElicitSlot - Amazon Lex is expecting the value of a slot for the current intent.

    For example, suppose that in the response Amazon Lex sends this message: "What size pizza would you like?". A user might reply with the slot value (e.g., "medium"). The user might also provide additional information in the response (e.g., "medium thick crust pizza"). Amazon Lex can process such additional information appropriately.

  • Fulfilled - Conveys that the Lambda function has successfully fulfilled the intent.

  • ReadyForFulfillment - Conveys that the client has to fulfill the request.

  • Failed - Conveys that the conversation with the user failed.

    This can happen for various reasons, including that the user does not provide an appropriate response to prompts from the service (you can configure how many times Amazon Lex can prompt a user for specific information), or if the Lambda function fails to fulfill the intent.

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pub fn get_dialog_state(&self) -> &Option<DialogState>

Identifies the current state of the user interaction. Amazon Lex returns one of the following values as dialogState. The client can optionally use this information to customize the user interface.

  • ElicitIntent - Amazon Lex wants to elicit the user's intent. Consider the following examples:

    For example, a user might utter an intent ("I want to order a pizza"). If Amazon Lex cannot infer the user intent from this utterance, it will return this dialog state.

  • ConfirmIntent - Amazon Lex is expecting a "yes" or "no" response.

    For example, Amazon Lex wants user confirmation before fulfilling an intent. Instead of a simple "yes" or "no" response, a user might respond with additional information. For example, "yes, but make it a thick crust pizza" or "no, I want to order a drink." Amazon Lex can process such additional information (in these examples, update the crust type slot or change the intent from OrderPizza to OrderDrink).

  • ElicitSlot - Amazon Lex is expecting the value of a slot for the current intent.

    For example, suppose that in the response Amazon Lex sends this message: "What size pizza would you like?". A user might reply with the slot value (e.g., "medium"). The user might also provide additional information in the response (e.g., "medium thick crust pizza"). Amazon Lex can process such additional information appropriately.

  • Fulfilled - Conveys that the Lambda function has successfully fulfilled the intent.

  • ReadyForFulfillment - Conveys that the client has to fulfill the request.

  • Failed - Conveys that the conversation with the user failed.

    This can happen for various reasons, including that the user does not provide an appropriate response to prompts from the service (you can configure how many times Amazon Lex can prompt a user for specific information), or if the Lambda function fails to fulfill the intent.

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pub fn slot_to_elicit(self, input: impl Into<String>) -> Self

If the dialogState value is ElicitSlot, returns the name of the slot for which Amazon Lex is eliciting a value.

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pub fn set_slot_to_elicit(self, input: Option<String>) -> Self

If the dialogState value is ElicitSlot, returns the name of the slot for which Amazon Lex is eliciting a value.

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pub fn get_slot_to_elicit(&self) -> &Option<String>

If the dialogState value is ElicitSlot, returns the name of the slot for which Amazon Lex is eliciting a value.

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pub fn input_transcript(self, input: impl Into<String>) -> Self

👎Deprecated: The inputTranscript field is deprecated, use the encodedInputTranscript field instead. The inputTranscript field is available only in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR and it-IT locales.

The text used to process the request.

You can use this field only in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR, and it-IT locales. In all other locales, the inputTranscript field is null. You should use the encodedInputTranscript field instead.

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 is correctly processing the audio that you send.

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pub fn set_input_transcript(self, input: Option<String>) -> Self

👎Deprecated: The inputTranscript field is deprecated, use the encodedInputTranscript field instead. The inputTranscript field is available only in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR and it-IT locales.

The text used to process the request.

You can use this field only in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR, and it-IT locales. In all other locales, the inputTranscript field is null. You should use the encodedInputTranscript field instead.

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 is correctly processing the audio that you send.

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pub fn get_input_transcript(&self) -> &Option<String>

👎Deprecated: The inputTranscript field is deprecated, use the encodedInputTranscript field instead. The inputTranscript field is available only in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR and it-IT locales.

The text used to process the request.

You can use this field only in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR, and it-IT locales. In all other locales, the inputTranscript field is null. You should use the encodedInputTranscript field instead.

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 is correctly processing the audio that you send.

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pub fn encoded_input_transcript(self, input: impl Into<String>) -> Self

The text used to process the request.

If the input was an audio stream, the encodedInputTranscript 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 is correctly processing the audio that you send.

The encodedInputTranscript field is base-64 encoded. You must decode the field before you can use the value.

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pub fn set_encoded_input_transcript(self, input: Option<String>) -> Self

The text used to process the request.

If the input was an audio stream, the encodedInputTranscript 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 is correctly processing the audio that you send.

The encodedInputTranscript field is base-64 encoded. You must decode the field before you can use the value.

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pub fn get_encoded_input_transcript(&self) -> &Option<String>

The text used to process the request.

If the input was an audio stream, the encodedInputTranscript 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 is correctly processing the audio that you send.

The encodedInputTranscript field is base-64 encoded. You must decode the field before you can use the value.

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pub fn audio_stream(self, input: ByteStream) -> Self

The prompt (or statement) to convey to the user. This is based on the bot configuration and context. For example, if Amazon Lex 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 sends that message in the response.

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pub fn set_audio_stream(self, input: Option<ByteStream>) -> Self

The prompt (or statement) to convey to the user. This is based on the bot configuration and context. For example, if Amazon Lex 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 sends that message in the response.

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pub fn get_audio_stream(&self) -> &Option<ByteStream>

The prompt (or statement) to convey to the user. This is based on the bot configuration and context. For example, if Amazon Lex 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 sends that message in the response.

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pub fn bot_version(self, input: impl Into<String>) -> Self

The version of the bot that responded to the conversation. You can use this information to help determine if one version of a bot is performing better than another version.

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pub fn set_bot_version(self, input: Option<String>) -> Self

The version of the bot that responded to the conversation. You can use this information to help determine if one version of a bot is performing better than another version.

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pub fn get_bot_version(&self) -> &Option<String>

The version of the bot that responded to the conversation. You can use this information to help determine if one version of a bot is performing better than another version.

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pub fn session_id(self, input: impl Into<String>) -> Self

The unique identifier for the session.

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pub fn set_session_id(self, input: Option<String>) -> Self

The unique identifier for the session.

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pub fn get_session_id(&self) -> &Option<String>

The unique identifier for the session.

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pub fn active_contexts(self, input: impl Into<String>) -> Self

A list of active contexts for the session. A context can be set when an intent is fulfilled or by calling the PostContent, PostText, or PutSession operation.

You can use a context to control the intents that can follow up an intent, or to modify the operation of your application.

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pub fn set_active_contexts(self, input: Option<String>) -> Self

A list of active contexts for the session. A context can be set when an intent is fulfilled or by calling the PostContent, PostText, or PutSession operation.

You can use a context to control the intents that can follow up an intent, or to modify the operation of your application.

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pub fn get_active_contexts(&self) -> &Option<String>

A list of active contexts for the session. A context can be set when an intent is fulfilled or by calling the PostContent, PostText, or PutSession operation.

You can use a context to control the intents that can follow up an intent, or to modify the operation of your application.

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pub fn build(self) -> PostContentOutput

Consumes the builder and constructs a PostContentOutput.

Trait Implementations§

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impl Debug for PostContentOutputBuilder

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

Formats the value using the given formatter. Read more
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impl Default for PostContentOutputBuilder

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fn default() -> PostContentOutputBuilder

Returns the “default value” for a type. Read more

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👎Deprecated since 1.0.1: renamed to resetting() due to conflicts with Vec::clear(). The clear() method will be removed in a future release.

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