AWS.LexRuntime (aws-elixir v0.8.0) View Source

Amazon Lex provides both build and runtime endpoints.

Each endpoint provides a set of operations (API). Your conversational bot uses the runtime API to understand user utterances (user input text or voice). For example, suppose a user says "I want pizza", your bot sends this input to Amazon Lex using the runtime API. Amazon Lex recognizes that the user request is for the OrderPizza intent (one of the intents defined in the bot). Then Amazon Lex engages in user conversation on behalf of the bot to elicit required information (slot values, such as pizza size and crust type), and then performs fulfillment activity (that you configured when you created the bot). You use the build-time API to create and manage your Amazon Lex bot. For a list of build-time operations, see the build-time API, .

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Functions

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

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

Sends user input (text or speech) to Amazon Lex.

Creates a new session or modifies an existing session with an Amazon Lex bot.

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delete_session(client, bot_alias, bot_name, user_id, input, options \\ [])

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

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get_session(client, bot_alias, bot_name, user_id, checkpoint_label_filter \\ nil, options \\ [])

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

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post_content(client, bot_alias, bot_name, user_id, input, options \\ [])

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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.

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post_text(client, bot_alias, bot_name, user_id, input, options \\ [])

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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.

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put_session(client, bot_alias, bot_name, user_id, input, options \\ [])

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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.