Paws::LexRuntime - Perl Interface to AWS Amazon Lex Runtime Service
use Paws; my $obj = Paws->service('LexRuntime'); my $res = $obj->Method( Arg1 => $val1, Arg2 => [ 'V1', 'V2' ], # if Arg3 is an object, the HashRef will be used as arguments to the constructor # of the arguments type Arg3 => { Att1 => 'Val1' }, # if Arg4 is an array of objects, the HashRefs will be passed as arguments to # the constructor of the arguments type Arg4 => [ { Att1 => 'Val1' }, { Att1 => 'Val2' } ], );
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, .
For the AWS API documentation, see https://docs.aws.amazon.com/goto/WebAPI/runtime.lex-2016-11-28
Each argument is described in detail in: Paws::LexRuntime::PostContent
Returns: a Paws::LexRuntime::PostContentResponse instance
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.
PostContent
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?".
PizzaSize
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:
message
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-dialog-state
ElicitSlot
x-amz-lex-intent-name header set to the intent name in the current context
x-amz-lex-intent-name
x-amz-lex-slot-to-elicit header set to the slot name for which the message is eliciting information
x-amz-lex-slot-to-elicit
x-amz-lex-slots header set to a map of slots configured for the intent with their current values
x-amz-lex-slots
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.
Confirmation
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.
x-amz-dialog-state
ElicitIntent
x-amz-slot-to-elicit
In addition, Amazon Lex also returns your application-specific sessionAttributes. For more information, see Managing Conversation Context (http://docs.aws.amazon.com/lex/latest/dg/context-mgmt.html).
sessionAttributes
Each argument is described in detail in: Paws::LexRuntime::PostText
Returns: a Paws::LexRuntime::PostTextResponse instance
Sends user input (text-only) 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:
responseCard
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:
slotToElicit
dialogState
intentName
slots
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.
SlotToElicit
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.
Paginator methods are helpers that repetively call methods that return partial results
This service class forms part of Paws
The source code is located here: https://github.com/pplu/aws-sdk-perl
Please report bugs to: https://github.com/pplu/aws-sdk-perl/issues
To install Paws::SDK::Config, copy and paste the appropriate command in to your terminal.
cpanm
cpanm Paws::SDK::Config
CPAN shell
perl -MCPAN -e shell install Paws::SDK::Config
For more information on module installation, please visit the detailed CPAN module installation guide.