Put Intent
lexmodelbuildingservice_put_intent | R Documentation |
Creates an intent or replaces an existing intent¶
Description¶
Creates an intent or replaces an existing intent.
To define the interaction between the user and your bot, you use one or
more intents. For a pizza ordering bot, for example, you would create an
OrderPizza
intent.
To create an intent or replace an existing intent, you must provide the following:
-
Intent name. For example,
OrderPizza
. -
Sample utterances. For example, "Can I order a pizza, please." and "I want to order a pizza."
-
Information to be gathered. You specify slot types for the information that your bot will request from the user. You can specify standard slot types, such as a date or a time, or custom slot types such as the size and crust of a pizza.
-
How the intent will be fulfilled. You can provide a Lambda function or configure the intent to return the intent information to the client application. If you use a Lambda function, when all of the intent information is available, Amazon Lex invokes your Lambda function. If you configure your intent to return the intent information to the client application.
You can specify other optional information in the request, such as:
-
A confirmation prompt to ask the user to confirm an intent. For example, "Shall I order your pizza?"
-
A conclusion statement to send to the user after the intent has been fulfilled. For example, "I placed your pizza order."
-
A follow-up prompt that asks the user for additional activity. For example, asking "Do you want to order a drink with your pizza?"
If you specify an existing intent name to update the intent, Amazon Lex
replaces the values in the $LATEST
version of the intent with the
values in the request. Amazon Lex removes fields that you don't provide
in the request. If you don't specify the required fields, Amazon Lex
throws an exception. When you update the $LATEST
version of an intent,
the status
field of any bot that uses the $LATEST
version of the
intent is set to NOT_BUILT
.
For more information, see how-it-works.
This operation requires permissions for the lex:PutIntent
action.
Usage¶
lexmodelbuildingservice_put_intent(name, description, slots,
sampleUtterances, confirmationPrompt, rejectionStatement,
followUpPrompt, conclusionStatement, dialogCodeHook,
fulfillmentActivity, parentIntentSignature, checksum, createVersion,
kendraConfiguration, inputContexts, outputContexts)
Arguments¶
name
[required] The name of the intent. The name is not case sensitive.
The name can't match a built-in intent name, or a built-in intent name with "AMAZON." removed. For example, because there is a built-in intent called
AMAZON.HelpIntent
, you can't create a custom intent calledHelpIntent
.For a list of built-in intents, see Standard Built-in Intents in the Alexa Skills Kit.
description
A description of the intent.
slots
An array of intent slots. At runtime, Amazon Lex elicits required slot values from the user using prompts defined in the slots. For more information, see how-it-works.
sampleUtterances
An array of utterances (strings) that a user might say to signal the intent. For example, "I want {PizzaSize} pizza", "Order {Quantity} {PizzaSize} pizzas".
In each utterance, a slot name is enclosed in curly braces.
confirmationPrompt
Prompts the user to confirm the intent. This question should have a yes or no answer.
Amazon Lex uses this prompt to ensure that the user acknowledges that the intent is ready for fulfillment. For example, with the
OrderPizza
intent, you might want to confirm that the order is correct before placing it. For other intents, such as intents that simply respond to user questions, you might not need to ask the user for confirmation before providing the information.You you must provide both the
rejectionStatement
and theconfirmationPrompt
, or neither.rejectionStatement
When the user answers "no" to the question defined in
confirmationPrompt
, Amazon Lex responds with this statement to acknowledge that the intent was canceled.You must provide both the
rejectionStatement
and theconfirmationPrompt
, or neither.followUpPrompt
Amazon Lex uses this prompt to solicit additional activity after fulfilling an intent. For example, after the
OrderPizza
intent is fulfilled, you might prompt the user to order a drink.The action that Amazon Lex takes depends on the user's response, as follows:
If the user says "Yes" it responds with the clarification prompt that is configured for the bot.
if the user says "Yes" and continues with an utterance that triggers an intent it starts a conversation for the intent.
If the user says "No" it responds with the rejection statement configured for the the follow-up prompt.
If it doesn't recognize the utterance it repeats the follow-up prompt again.
The
followUpPrompt
field and theconclusionStatement
field are mutually exclusive. You can specify only one.conclusionStatement
The statement that you want Amazon Lex to convey to the user after the intent is successfully fulfilled by the Lambda function.
This element is relevant only if you provide a Lambda function in the
fulfillmentActivity
. If you return the intent to the client application, you can't specify this element.The
followUpPrompt
andconclusionStatement
are mutually exclusive. You can specify only one.dialogCodeHook
Specifies a Lambda function to invoke for each user input. You can invoke this Lambda function to personalize user interaction.
For example, suppose your bot determines that the user is John. Your Lambda function might retrieve John's information from a backend database and prepopulate some of the values. For example, if you find that John is gluten intolerant, you might set the corresponding intent slot,
GlutenIntolerant
, to true. You might find John's phone number and set the corresponding session attribute.fulfillmentActivity
Required. Describes how the intent is fulfilled. For example, after a user provides all of the information for a pizza order,
fulfillmentActivity
defines how the bot places an order with a local pizza store.You might configure Amazon Lex to return all of the intent information to the client application, or direct it to invoke a Lambda function that can process the intent (for example, place an order with a pizzeria).
parentIntentSignature
A unique identifier for the built-in intent to base this intent on. To find the signature for an intent, see Standard Built-in Intents in the Alexa Skills Kit.
checksum
Identifies a specific revision of the
$LATEST
version.When you create a new intent, leave the
checksum
field blank. If you specify a checksum you get aBadRequestException
exception.When you want to update a intent, set the
checksum
field to the checksum of the most recent revision of the$LATEST
version. If you don't specify thechecksum
field, or if the checksum does not match the$LATEST
version, you get aPreconditionFailedException
exception.createVersion
When set to
true
a new numbered version of the intent is created. This is the same as calling thecreate_intent_version
operation. If you do not specifycreateVersion
, the default isfalse
.kendraConfiguration
Configuration information required to use the
AMAZON.KendraSearchIntent
intent to connect to an Amazon Kendra index. For more information, see AMAZON.KendraSearchIntent.inputContexts
An array of
InputContext
objects that lists the contexts that must be active for Amazon Lex to choose the intent in a conversation with the user.outputContexts
An array of
OutputContext
objects that lists the contexts that the intent activates when the intent is fulfilled.
Value¶
A list with the following syntax:
list(
name = "string",
description = "string",
slots = list(
list(
name = "string",
description = "string",
slotConstraint = "Required"|"Optional",
slotType = "string",
slotTypeVersion = "string",
valueElicitationPrompt = list(
messages = list(
list(
contentType = "PlainText"|"SSML"|"CustomPayload",
content = "string",
groupNumber = 123
)
),
maxAttempts = 123,
responseCard = "string"
),
priority = 123,
sampleUtterances = list(
"string"
),
responseCard = "string",
obfuscationSetting = "NONE"|"DEFAULT_OBFUSCATION",
defaultValueSpec = list(
defaultValueList = list(
list(
defaultValue = "string"
)
)
)
)
),
sampleUtterances = list(
"string"
),
confirmationPrompt = list(
messages = list(
list(
contentType = "PlainText"|"SSML"|"CustomPayload",
content = "string",
groupNumber = 123
)
),
maxAttempts = 123,
responseCard = "string"
),
rejectionStatement = list(
messages = list(
list(
contentType = "PlainText"|"SSML"|"CustomPayload",
content = "string",
groupNumber = 123
)
),
responseCard = "string"
),
followUpPrompt = list(
prompt = list(
messages = list(
list(
contentType = "PlainText"|"SSML"|"CustomPayload",
content = "string",
groupNumber = 123
)
),
maxAttempts = 123,
responseCard = "string"
),
rejectionStatement = list(
messages = list(
list(
contentType = "PlainText"|"SSML"|"CustomPayload",
content = "string",
groupNumber = 123
)
),
responseCard = "string"
)
),
conclusionStatement = list(
messages = list(
list(
contentType = "PlainText"|"SSML"|"CustomPayload",
content = "string",
groupNumber = 123
)
),
responseCard = "string"
),
dialogCodeHook = list(
uri = "string",
messageVersion = "string"
),
fulfillmentActivity = list(
type = "ReturnIntent"|"CodeHook",
codeHook = list(
uri = "string",
messageVersion = "string"
)
),
parentIntentSignature = "string",
lastUpdatedDate = as.POSIXct(
"2015-01-01"
),
createdDate = as.POSIXct(
"2015-01-01"
),
version = "string",
checksum = "string",
createVersion = TRUE|FALSE,
kendraConfiguration = list(
kendraIndex = "string",
queryFilterString = "string",
role = "string"
),
inputContexts = list(
list(
name = "string"
)
),
outputContexts = list(
list(
name = "string",
timeToLiveInSeconds = 123,
turnsToLive = 123
)
)
)
Request syntax¶
svc$put_intent(
name = "string",
description = "string",
slots = list(
list(
name = "string",
description = "string",
slotConstraint = "Required"|"Optional",
slotType = "string",
slotTypeVersion = "string",
valueElicitationPrompt = list(
messages = list(
list(
contentType = "PlainText"|"SSML"|"CustomPayload",
content = "string",
groupNumber = 123
)
),
maxAttempts = 123,
responseCard = "string"
),
priority = 123,
sampleUtterances = list(
"string"
),
responseCard = "string",
obfuscationSetting = "NONE"|"DEFAULT_OBFUSCATION",
defaultValueSpec = list(
defaultValueList = list(
list(
defaultValue = "string"
)
)
)
)
),
sampleUtterances = list(
"string"
),
confirmationPrompt = list(
messages = list(
list(
contentType = "PlainText"|"SSML"|"CustomPayload",
content = "string",
groupNumber = 123
)
),
maxAttempts = 123,
responseCard = "string"
),
rejectionStatement = list(
messages = list(
list(
contentType = "PlainText"|"SSML"|"CustomPayload",
content = "string",
groupNumber = 123
)
),
responseCard = "string"
),
followUpPrompt = list(
prompt = list(
messages = list(
list(
contentType = "PlainText"|"SSML"|"CustomPayload",
content = "string",
groupNumber = 123
)
),
maxAttempts = 123,
responseCard = "string"
),
rejectionStatement = list(
messages = list(
list(
contentType = "PlainText"|"SSML"|"CustomPayload",
content = "string",
groupNumber = 123
)
),
responseCard = "string"
)
),
conclusionStatement = list(
messages = list(
list(
contentType = "PlainText"|"SSML"|"CustomPayload",
content = "string",
groupNumber = 123
)
),
responseCard = "string"
),
dialogCodeHook = list(
uri = "string",
messageVersion = "string"
),
fulfillmentActivity = list(
type = "ReturnIntent"|"CodeHook",
codeHook = list(
uri = "string",
messageVersion = "string"
)
),
parentIntentSignature = "string",
checksum = "string",
createVersion = TRUE|FALSE,
kendraConfiguration = list(
kendraIndex = "string",
queryFilterString = "string",
role = "string"
),
inputContexts = list(
list(
name = "string"
)
),
outputContexts = list(
list(
name = "string",
timeToLiveInSeconds = 123,
turnsToLive = 123
)
)
)
Examples¶
## Not run:
# This example shows how to create an intent for ordering pizzas.
svc$put_intent(
name = "DocOrderPizza",
conclusionStatement = list(
messages = list(
list(
content = "All right, I ordered you a {Crust} crust {Type} pizza with {Sauce} sauce.",
contentType = "PlainText"
),
list(
content = "OK, your {Crust} crust {Type} pizza with {Sauce} sauce is on the way.",
contentType = "PlainText"
)
),
responseCard = "foo"
),
confirmationPrompt = list(
maxAttempts = 1L,
messages = list(
list(
content = "Should I order your {Crust} crust {Type} pizza with {Sauce} sauce?",
contentType = "PlainText"
)
)
),
description = "Order a pizza from a local pizzeria.",
fulfillmentActivity = list(
type = "ReturnIntent"
),
rejectionStatement = list(
messages = list(
list(
content = "Ok, I'll cancel your order.",
contentType = "PlainText"
),
list(
content = "I cancelled your order.",
contentType = "PlainText"
)
)
),
sampleUtterances = list(
"Order me a pizza.",
"Order me a {Type} pizza.",
"I want a {Crust} crust {Type} pizza",
"I want a {Crust} crust {Type} pizza with {Sauce} sauce."
),
slots = list(
list(
name = "Type",
description = "The type of pizza to order.",
priority = 1L,
sampleUtterances = list(
"Get me a {Type} pizza.",
"A {Type} pizza please.",
"I'd like a {Type} pizza."
),
slotConstraint = "Required",
slotType = "DocPizzaType",
slotTypeVersion = "$LATEST",
valueElicitationPrompt = list(
maxAttempts = 1L,
messages = list(
list(
content = "What type of pizza would you like?",
contentType = "PlainText"
),
list(
content = "Vegie or cheese pizza?",
contentType = "PlainText"
),
list(
content = "I can get you a vegie or a cheese pizza.",
contentType = "PlainText"
)
)
)
),
list(
name = "Crust",
description = "The type of pizza crust to order.",
priority = 2L,
sampleUtterances = list(
"Make it a {Crust} crust.",
"I'd like a {Crust} crust."
),
slotConstraint = "Required",
slotType = "DocPizzaCrustType",
slotTypeVersion = "$LATEST",
valueElicitationPrompt = list(
maxAttempts = 1L,
messages = list(
list(
content = "What type of crust would you like?",
contentType = "PlainText"
),
list(
content = "Thick or thin crust?",
contentType = "PlainText"
)
)
)
),
list(
name = "Sauce",
description = "The type of sauce to use on the pizza.",
priority = 3L,
sampleUtterances = list(
"Make it {Sauce} sauce.",
"I'd like {Sauce} sauce."
),
slotConstraint = "Required",
slotType = "DocPizzaSauceType",
slotTypeVersion = "$LATEST",
valueElicitationPrompt = list(
maxAttempts = 1L,
messages = list(
list(
content = "White or red sauce?",
contentType = "PlainText"
),
list(
content = "Garlic or tomato sauce?",
contentType = "PlainText"
)
)
)
)
)
)
## End(Not run)