Module Awso_lex_runtime_syncSource

Sourceval post_content : ?endpoint_url:string -> ?cfg:Awso.Cfg.t -> Awso_lex_runtime.Values.PostContentRequest.t -> (Awso_lex_runtime.Values.PostContentResponse.t, Awso_lex_runtime.Values.PostContentResponse.error) Result.t
Sourceval post_text : ?endpoint_url:string -> ?cfg:Awso.Cfg.t -> Awso_lex_runtime.Values.PostTextRequest.t -> (Awso_lex_runtime.Values.PostTextResponse.t, Awso_lex_runtime.Values.PostTextResponse.error) Result.t
include module type of struct include Awso_lex_runtime.Values end
Sourceval service : Awso.Service.t
Sourceval apiVersion : string
Sourceval endpointPrefix : string
Sourceval serviceFullName : string
Sourceval signatureVersion : string
Sourceval protocol : string
Sourceval globalEndpoint : string
Sourceval simple_to_json : ('a -> Awso__Botodata.value) -> 'a -> Yojson.Safe.t
Sourceval composed_to_json : ('a -> Awso__Botodata.value) -> 'a -> Yojson.Safe.t
Sourceval to_query : ('a -> Awso.Client.Query.value) -> 'a -> Awso.Client.Query.t
Sourceval structure_to_value_aux : ('a * 'b option) list -> f:(('a * 'b) list -> 'c) -> [> `Structure of 'c ]
Sourceval structure_to_value : ('a * 'b option) list -> [> `Structure of ('a * 'b) list ]
Sourceval structure_to_wrapped_value : wrapper:'a -> response:'a -> ('b * 'c option) list -> [> `Structure of ('a * [> `Structure of ('b * 'c) list ]) list ]

Represents an option to be shown on the client platform (Facebook, Slack, etc.)

Sourcemodule Text = Awso_lex_runtime.Values.Text
Sourcemodule ActiveContextTimeToLiveInSeconds = Awso_lex_runtime.Values.ActiveContextTimeToLiveInSeconds
Sourcemodule String_ = Awso_lex_runtime.Values.String_

The length of time or number of turns that a context remains active.

Provides a score that indicates the confidence that Amazon Lex has that an intent is the one that satisfies the user's intent.

Represents an option rendered to the user when a prompt is shown. It could be an image, a button, a link, or text.

A context is a variable that contains information about the current state of the conversation between a user and Amazon Lex. Context can be set automatically by Amazon Lex when an intent is fulfilled, or it can be set at runtime using the PutContent, PutText, or PutSession operation.

Provides information about the state of an intent. You can use this information to get the current state of an intent so that you can process the intent, or so that you can return the intent to its previous state.

An intent that Amazon Lex suggests satisfies the user's intent. Includes the name of the intent, the confidence that Amazon Lex has that the user's intent is satisfied, and the slots defined for the intent.

Either the Amazon Lex bot is still building, or one of the dependent services (Amazon Polly, AWS Lambda) failed with an internal service error.

Request validation failed, there is no usable message in the context, or the bot build failed, is still in progress, or contains unbuilt changes.

Two clients are using the same AWS account, Amazon Lex bot, and user ID.

One of the dependencies, such as AWS Lambda or Amazon Polly, threw an exception. For example, If Amazon Lex does not have sufficient permissions to call a Lambda function. If a Lambda function takes longer than 30 seconds to execute. If a fulfillment Lambda function returns a Delegate dialog action without removing any slot values.

Internal service error. Retry the call.

Exceeded a limit.

The accept header in the request does not have a valid value.

The resource (such as the Amazon Lex bot or an alias) that is referred to is not found.

Describes the next action that the bot should take in its interaction with the user and provides information about the context in which the action takes place. Use the DialogAction data type to set the interaction to a specific state, or to return the interaction to a previous state.

This exception is not used.

If you configure a response card when creating your bots, Amazon Lex substitutes the session attributes and slot values that are available, and then returns it. The response card can also come from a Lambda function ( dialogCodeHook and fulfillmentActivity on an intent).

The sentiment expressed in an utterance. When the bot is configured to send utterances to Amazon Comprehend for sentiment analysis, this field structure contains the result of the analysis.

The input speech is too long.

The Content-Type header (PostContent API) has an invalid value.

Creates a new session or modifies an existing session with an Amazon Lex bot. Use this operation to enable your application to set the state of the bot. For more information, see Managing Sessions.

Creates a new session or modifies an existing session with an Amazon Lex bot. Use this operation to enable your application to set the state of the bot. For more information, see Managing Sessions.

Sends user input to Amazon Lex. Client applications can use this API to send requests to Amazon Lex at runtime. Amazon Lex then interprets the user input using the machine learning model it built for the bot. In response, Amazon Lex returns the next message to convey to the user an optional responseCard to display. Consider the following example messages: For a user input "I would like a pizza", Amazon Lex might return a response with a message eliciting slot data (for example, PizzaSize): "What size pizza would you like?" After the user provides all of the pizza order information, Amazon Lex might return a response with a message to obtain user confirmation "Proceed with the pizza order?". After the user replies to a confirmation prompt with a "yes", Amazon Lex might return a conclusion statement: "Thank you, your cheese pizza has been ordered.". Not all Amazon Lex messages require a user response. For example, a conclusion statement does not require a response. Some messages require only a "yes" or "no" user response. In addition to the message, Amazon Lex provides additional context about the message in the response that you might use to enhance client behavior, for example, to display the appropriate client user interface. These are the slotToElicit, dialogState, intentName, and slots fields in the response. Consider the following examples: If the message is to elicit slot data, Amazon Lex returns the following context information: dialogState set to ElicitSlot intentName set to the intent name in the current context slotToElicit set to the slot name for which the message is eliciting information slots set to a map of slots, configured for the intent, with currently known values If the message is a confirmation prompt, the dialogState is set to ConfirmIntent and SlotToElicit is set to null. If the message is a clarification prompt (configured for the intent) that indicates that user intent is not understood, the dialogState is set to ElicitIntent and slotToElicit is set to null. In addition, Amazon Lex also returns your application-specific sessionAttributes. For more information, see Managing Conversation Context.

Sends user input to Amazon Lex. Client applications can use this API to send requests to Amazon Lex at runtime. Amazon Lex then interprets the user input using the machine learning model it built for the bot. In response, Amazon Lex returns the next message to convey to the user an optional responseCard to display. Consider the following example messages: For a user input "I would like a pizza", Amazon Lex might return a response with a message eliciting slot data (for example, PizzaSize): "What size pizza would you like?" After the user provides all of the pizza order information, Amazon Lex might return a response with a message to obtain user confirmation "Proceed with the pizza order?". After the user replies to a confirmation prompt with a "yes", Amazon Lex might return a conclusion statement: "Thank you, your cheese pizza has been ordered.". Not all Amazon Lex messages require a user response. For example, a conclusion statement does not require a response. Some messages require only a "yes" or "no" user response. In addition to the message, Amazon Lex provides additional context about the message in the response that you might use to enhance client behavior, for example, to display the appropriate client user interface. These are the slotToElicit, dialogState, intentName, and slots fields in the response. Consider the following examples: If the message is to elicit slot data, Amazon Lex returns the following context information: dialogState set to ElicitSlot intentName set to the intent name in the current context slotToElicit set to the slot name for which the message is eliciting information slots set to a map of slots, configured for the intent, with currently known values If the message is a confirmation prompt, the dialogState is set to ConfirmIntent and SlotToElicit is set to null. If the message is a clarification prompt (configured for the intent) that indicates that user intent is not understood, the dialogState is set to ElicitIntent and slotToElicit is set to null. In addition, Amazon Lex also returns your application-specific sessionAttributes. For more information, see Managing Conversation Context.

Sends user input (text or speech) to Amazon Lex. Clients use this API to send text and audio requests to Amazon Lex at runtime. Amazon Lex interprets the user input using the machine learning model that it built for the bot. The PostContent operation supports audio input at 8kHz and 16kHz. You can use 8kHz audio to achieve higher speech recognition accuracy in telephone audio applications. In response, Amazon Lex returns the next message to convey to the user. Consider the following example messages: For a user input "I would like a pizza," Amazon Lex might return a response with a message eliciting slot data (for example, PizzaSize): "What size pizza would you like?". After the user provides all of the pizza order information, Amazon Lex might return a response with a message to get user confirmation: "Order the pizza?". After the user replies "Yes" to the confirmation prompt, Amazon Lex might return a conclusion statement: "Thank you, your cheese pizza has been ordered.". Not all Amazon Lex messages require a response from the user. For example, conclusion statements do not require a response. Some messages require only a yes or no response. In addition to the message, Amazon Lex provides additional context about the message in the response that you can use to enhance client behavior, such as displaying the appropriate client user interface. Consider the following examples: If the message is to elicit slot data, Amazon Lex returns the following context information: x-amz-lex-dialog-state header set to ElicitSlot x-amz-lex-intent-name header set to the intent name in the current context x-amz-lex-slot-to-elicit header set to the slot name for which the message is eliciting information x-amz-lex-slots header set to a map of slots configured for the intent with their current values If the message is a confirmation prompt, the x-amz-lex-dialog-state header is set to Confirmation and the x-amz-lex-slot-to-elicit header is omitted. If the message is a clarification prompt configured for the intent, indicating that the user intent is not understood, the x-amz-dialog-state header is set to ElicitIntent and the x-amz-slot-to-elicit header is omitted. In addition, Amazon Lex also returns your application-specific sessionAttributes. For more information, see Managing Conversation Context.

Sends user input (text or speech) to Amazon Lex. Clients use this API to send text and audio requests to Amazon Lex at runtime. Amazon Lex interprets the user input using the machine learning model that it built for the bot. The PostContent operation supports audio input at 8kHz and 16kHz. You can use 8kHz audio to achieve higher speech recognition accuracy in telephone audio applications. In response, Amazon Lex returns the next message to convey to the user. Consider the following example messages: For a user input "I would like a pizza," Amazon Lex might return a response with a message eliciting slot data (for example, PizzaSize): "What size pizza would you like?". After the user provides all of the pizza order information, Amazon Lex might return a response with a message to get user confirmation: "Order the pizza?". After the user replies "Yes" to the confirmation prompt, Amazon Lex might return a conclusion statement: "Thank you, your cheese pizza has been ordered.". Not all Amazon Lex messages require a response from the user. For example, conclusion statements do not require a response. Some messages require only a yes or no response. In addition to the message, Amazon Lex provides additional context about the message in the response that you can use to enhance client behavior, such as displaying the appropriate client user interface. Consider the following examples: If the message is to elicit slot data, Amazon Lex returns the following context information: x-amz-lex-dialog-state header set to ElicitSlot x-amz-lex-intent-name header set to the intent name in the current context x-amz-lex-slot-to-elicit header set to the slot name for which the message is eliciting information x-amz-lex-slots header set to a map of slots configured for the intent with their current values If the message is a confirmation prompt, the x-amz-lex-dialog-state header is set to Confirmation and the x-amz-lex-slot-to-elicit header is omitted. If the message is a clarification prompt configured for the intent, indicating that the user intent is not understood, the x-amz-dialog-state header is set to ElicitIntent and the x-amz-slot-to-elicit header is omitted. In addition, Amazon Lex also returns your application-specific sessionAttributes. For more information, see Managing Conversation Context.

Returns session information for a specified bot, alias, and user ID.

Returns session information for a specified bot, alias, and user ID.

Removes session information for a specified bot, alias, and user ID.

Removes session information for a specified bot, alias, and user ID.