mirror of
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Upgrade AWS SDK to the latest version
This commit is contained in:
Andrey Smirnov
+163
-3
@@ -11,6 +11,29 @@
|
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"uid":"runtime.lex-2016-11-28"
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},
|
||||
"operations":{
|
||||
"PostContent":{
|
||||
"name":"PostContent",
|
||||
"http":{
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||||
"method":"POST",
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"requestUri":"/bot/{botName}/alias/{botAlias}/user/{userId}/content"
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},
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||||
"input":{"shape":"PostContentRequest"},
|
||||
"output":{"shape":"PostContentResponse"},
|
||||
"errors":[
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{"shape":"NotFoundException"},
|
||||
{"shape":"BadRequestException"},
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||||
{"shape":"LimitExceededException"},
|
||||
{"shape":"InternalFailureException"},
|
||||
{"shape":"ConflictException"},
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||||
{"shape":"UnsupportedMediaTypeException"},
|
||||
{"shape":"NotAcceptableException"},
|
||||
{"shape":"RequestTimeoutException"},
|
||||
{"shape":"DependencyFailedException"},
|
||||
{"shape":"BadGatewayException"},
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||||
{"shape":"LoopDetectedException"}
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],
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"authtype":"v4-unsigned-body"
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},
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"PostText":{
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"name":"PostText",
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"http":{
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@@ -32,6 +55,11 @@
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}
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},
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"shapes":{
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"Accept":{"type":"string"},
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||||
"AttributesString":{
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||||
"type":"string",
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||||
"sensitive":true
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||||
},
|
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"BadGatewayException":{
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"type":"structure",
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"members":{
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@@ -48,6 +76,10 @@
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"error":{"httpStatusCode":400},
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"exception":true
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},
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"BlobStream":{
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"type":"blob",
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"streaming":true
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},
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"BotAlias":{"type":"string"},
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"BotName":{"type":"string"},
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"Button":{
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@@ -113,6 +145,7 @@
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"buttons":{"shape":"listOfButtons"}
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}
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},
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"HttpContentType":{"type":"string"},
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"IntentName":{"type":"string"},
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"InternalFailureException":{
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"type":"structure",
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@@ -144,6 +177,14 @@
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"error":{"httpStatusCode":508},
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"exception":true
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},
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"NotAcceptableException":{
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"type":"structure",
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"members":{
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"message":{"shape":"String"}
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},
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"error":{"httpStatusCode":406},
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"exception":true
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},
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"NotFoundException":{
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"type":"structure",
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"members":{
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@@ -152,6 +193,106 @@
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"error":{"httpStatusCode":404},
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"exception":true
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},
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"PostContentRequest":{
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"type":"structure",
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"required":[
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"botName",
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"botAlias",
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"userId",
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"contentType",
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"inputStream"
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],
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"members":{
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"botName":{
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"shape":"BotName",
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"location":"uri",
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"locationName":"botName"
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},
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"botAlias":{
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"shape":"BotAlias",
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"location":"uri",
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"locationName":"botAlias"
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},
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"userId":{
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"shape":"UserId",
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"location":"uri",
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"locationName":"userId"
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},
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"sessionAttributes":{
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"shape":"AttributesString",
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"jsonvalue":true,
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"location":"header",
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"locationName":"x-amz-lex-session-attributes"
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},
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"requestAttributes":{
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"shape":"AttributesString",
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"jsonvalue":true,
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"location":"header",
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"locationName":"x-amz-lex-request-attributes"
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},
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"contentType":{
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"shape":"HttpContentType",
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"location":"header",
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"locationName":"Content-Type"
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},
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"accept":{
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"shape":"Accept",
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"location":"header",
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"locationName":"Accept"
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},
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"inputStream":{"shape":"BlobStream"}
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},
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"payload":"inputStream"
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},
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"PostContentResponse":{
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"type":"structure",
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"members":{
|
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"contentType":{
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"shape":"HttpContentType",
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"location":"header",
|
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"locationName":"Content-Type"
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},
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"intentName":{
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"shape":"IntentName",
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"location":"header",
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"locationName":"x-amz-lex-intent-name"
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},
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"slots":{
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"shape":"String",
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"jsonvalue":true,
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"location":"header",
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"locationName":"x-amz-lex-slots"
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},
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"sessionAttributes":{
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"shape":"String",
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"jsonvalue":true,
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"location":"header",
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"locationName":"x-amz-lex-session-attributes"
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},
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"message":{
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"shape":"Text",
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"location":"header",
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"locationName":"x-amz-lex-message"
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},
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"dialogState":{
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"shape":"DialogState",
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"location":"header",
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"locationName":"x-amz-lex-dialog-state"
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},
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"slotToElicit":{
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"shape":"String",
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"location":"header",
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"locationName":"x-amz-lex-slot-to-elicit"
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},
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"inputTranscript":{
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"shape":"String",
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"location":"header",
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"locationName":"x-amz-lex-input-transcript"
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},
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"audioStream":{"shape":"BlobStream"}
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},
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"payload":"audioStream"
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},
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"PostTextRequest":{
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"type":"structure",
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"required":[
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@@ -177,6 +318,7 @@
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"locationName":"userId"
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},
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"sessionAttributes":{"shape":"StringMap"},
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"requestAttributes":{"shape":"StringMap"},
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"inputText":{"shape":"Text"}
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}
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},
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@@ -192,6 +334,14 @@
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"responseCard":{"shape":"ResponseCard"}
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}
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},
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"RequestTimeoutException":{
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||||
"type":"structure",
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||||
"members":{
|
||||
"message":{"shape":"String"}
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||||
},
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"error":{"httpStatusCode":408},
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"exception":true
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},
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"ResponseCard":{
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"type":"structure",
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"members":{
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@@ -204,7 +354,8 @@
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"StringMap":{
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"type":"map",
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||||
"key":{"shape":"String"},
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"value":{"shape":"String"}
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"value":{"shape":"String"},
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||||
"sensitive":true
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},
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"StringUrlWithLength":{
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"type":"string",
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@@ -219,11 +370,20 @@
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"Text":{
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"type":"string",
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"max":1024,
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"min":1
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"min":1,
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"sensitive":true
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||||
},
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||||
"UnsupportedMediaTypeException":{
|
||||
"type":"structure",
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||||
"members":{
|
||||
"message":{"shape":"String"}
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},
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"error":{"httpStatusCode":415},
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||||
"exception":true
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||||
},
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"UserId":{
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"type":"string",
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||||
"max":50,
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||||
"max":100,
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"min":2,
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"pattern":"[0-9a-zA-Z._:-]+"
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},
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+98
-31
@@ -1,30 +1,53 @@
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{
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"version": "2.0",
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"service": "<p>Amazon Lex provides both build and runtime endpoints. Each endpoint provides a set of operations (API). Your application uses the runtime API to understand user utterances (user input text or voice). For example, suppose user says \"I want pizza\", your application 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 application). Then Amazon Lex engages in user conversation on behalf of the application 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 application). You use the build-time API to create and manage your Amazon Lex applications. For a list of build-time operations, see the build-time API. . </p>",
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"service": "<p>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, . </p>",
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"operations": {
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"PostText": "<p>Sends user input text to Amazon Lex at runtime. Amazon Lex uses the machine learning model that the service built for the application to interpret user input. </p> <p> In response, Amazon Lex returns the next message to convey to the user (based on the context of the user interaction) and whether to expect a user response to the message (<code>dialogState</code>). For example, consider the following response messages: </p> <ul> <li> <p>\"What pizza toppings would you like?\" – In this case, the <code>dialogState</code> would be <code>ElicitSlot</code> (that is, a user response is expected). </p> </li> <li> <p>\"Your order has been placed.\" – In this case, Amazon Lex returns one of the following <code>dialogState</code> values depending on how the intent fulfillment is configured (see <code>fulfillmentActivity</code> in <code>CreateIntent</code>): </p> <ul> <li> <p> <code>FulFilled</code> – The intent fulfillment is configured through a Lambda function. </p> </li> <li> <p> <code>ReadyForFulfilment</code> – The intent's <code>fulfillmentActivity</code> is to simply return the intent data back to the client application. </p> </li> </ul> </li> </ul>"
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"PostContent": "<p> 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. </p> <p>The <code>PostContent</code> operation supports audio input at 8kHz and 16kHz. You can use 8kHz audio to achieve higher speech recognition accuracy in telephone audio applications. </p> <p> In response, Amazon Lex returns the next message to convey to the user. Consider the following example messages: </p> <ul> <li> <p> For a user input \"I would like a pizza,\" Amazon Lex might return a response with a message eliciting slot data (for example, <code>PizzaSize</code>): \"What size pizza would you like?\". </p> </li> <li> <p> 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?\". </p> </li> <li> <p> After the user replies \"Yes\" to the confirmation prompt, Amazon Lex might return a conclusion statement: \"Thank you, your cheese pizza has been ordered.\". </p> </li> </ul> <p> 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 <code>message</code>, 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: </p> <ul> <li> <p> If the message is to elicit slot data, Amazon Lex returns the following context information: </p> <ul> <li> <p> <code>x-amz-lex-dialog-state</code> header set to <code>ElicitSlot</code> </p> </li> <li> <p> <code>x-amz-lex-intent-name</code> header set to the intent name in the current context </p> </li> <li> <p> <code>x-amz-lex-slot-to-elicit</code> header set to the slot name for which the <code>message</code> is eliciting information </p> </li> <li> <p> <code>x-amz-lex-slots</code> header set to a map of slots configured for the intent with their current values </p> </li> </ul> </li> <li> <p> If the message is a confirmation prompt, the <code>x-amz-lex-dialog-state</code> header is set to <code>Confirmation</code> and the <code>x-amz-lex-slot-to-elicit</code> header is omitted. </p> </li> <li> <p> If the message is a clarification prompt configured for the intent, indicating that the user intent is not understood, the <code>x-amz-dialog-state</code> header is set to <code>ElicitIntent</code> and the <code>x-amz-slot-to-elicit</code> header is omitted. </p> </li> </ul> <p> In addition, Amazon Lex also returns your application-specific <code>sessionAttributes</code>. For more information, see <a href=\"http://docs.aws.amazon.com/lex/latest/dg/context-mgmt.html\">Managing Conversation Context</a>. </p>",
|
||||
"PostText": "<p>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. </p> <p> In response, Amazon Lex returns the next <code>message</code> to convey to the user an optional <code>responseCard</code> to display. Consider the following example messages: </p> <ul> <li> <p> 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?\" </p> </li> <li> <p> 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?\". </p> </li> <li> <p> 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.\". </p> </li> </ul> <p> 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 <code>message</code>, 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 <code>slotToElicit</code>, <code>dialogState</code>, <code>intentName</code>, and <code>slots</code> fields in the response. Consider the following examples: </p> <ul> <li> <p>If the message is to elicit slot data, Amazon Lex returns the following context information:</p> <ul> <li> <p> <code>dialogState</code> set to ElicitSlot </p> </li> <li> <p> <code>intentName</code> set to the intent name in the current context </p> </li> <li> <p> <code>slotToElicit</code> set to the slot name for which the <code>message</code> is eliciting information </p> </li> <li> <p> <code>slots</code> set to a map of slots, configured for the intent, with currently known values </p> </li> </ul> </li> <li> <p> If the message is a confirmation prompt, the <code>dialogState</code> is set to ConfirmIntent and <code>SlotToElicit</code> is set to null. </p> </li> <li> <p>If the message is a clarification prompt (configured for the intent) that indicates that user intent is not understood, the <code>dialogState</code> is set to ElicitIntent and <code>slotToElicit</code> is set to null. </p> </li> </ul> <p> In addition, Amazon Lex also returns your application-specific <code>sessionAttributes</code>. For more information, see <a href=\"http://docs.aws.amazon.com/lex/latest/dg/context-mgmt.html\">Managing Conversation Context</a>. </p>"
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},
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"shapes": {
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"Accept": {
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"base": null,
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"refs": {
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"PostContentRequest$accept": "<p> You pass this value as the <code>Accept</code> HTTP header. </p> <p> The message Amazon Lex returns in the response can be either text or speech based on the <code>Accept</code> HTTP header value in the request. </p> <ul> <li> <p> If the value is <code>text/plain; charset=utf-8</code>, Amazon Lex returns text in the response. </p> </li> <li> <p> If the value begins with <code>audio/</code>, Amazon Lex returns speech in the response. Amazon Lex uses Amazon Polly to generate the speech (using the configuration you specified in the <code>Accept</code> header). For example, if you specify <code>audio/mpeg</code> as the value, Amazon Lex returns speech in the MPEG format.</p> <p>The following are the accepted values:</p> <ul> <li> <p>audio/mpeg</p> </li> <li> <p>audio/ogg</p> </li> <li> <p>audio/pcm</p> </li> <li> <p>text/plain; charset=utf-8</p> </li> <li> <p>audio/* (defaults to mpeg)</p> </li> </ul> </li> </ul>"
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}
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},
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"AttributesString": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"PostContentRequest$sessionAttributes": "<p>You pass this value as the <code>x-amz-lex-session-attributes</code> HTTP header.</p> <p>Application-specific information passed between Amazon Lex and a client application. The value must be a JSON serialized and base64 encoded map with string keys and values. The total size of the <code>sessionAttributes</code> and <code>requestAttributes</code> headers is limited to 12 KB.</p> <p>For more information, see <a href=\"http://docs.aws.amazon.com/lex/latest/dg/context-mgmt.html#context-mgmt-session-attribs\">Setting Session Attributes</a>.</p>",
|
||||
"PostContentRequest$requestAttributes": "<p>You pass this value as the <code>x-amz-lex-request-attributes</code> HTTP header.</p> <p>Request-specific information passed between Amazon Lex and a client application. The value must be a JSON serialized and base64 encoded map with string keys and values. The total size of the <code>requestAttributes</code> and <code>sessionAttributes</code> headers is limited to 12 KB.</p> <p>The namespace <code>x-amz-lex:</code> is reserved for special attributes. Don't create any request attributes with the prefix <code>x-amz-lex:</code>.</p> <p>For more information, see <a href=\"http://docs.aws.amazon.com/lex/latest/dg/context-mgmt.html#context-mgmt-request-attribs\">Setting Request Attributes</a>.</p>"
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||||
}
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||||
},
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||||
"BadGatewayException": {
|
||||
"base": "<p>Either the Amazon Lex bot is still building, or one of the dependent services (Amazon Polly, AWS Lambda) failed with an internal service error.</p>",
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||||
"refs": {
|
||||
}
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||||
},
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||||
"BadRequestException": {
|
||||
"base": "<p> Request validation failed, there is no usable message in the context, or the bot build failed. </p>",
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||||
"base": "<p> Request validation failed, there is no usable message in the context, or the bot build failed, is still in progress, or contains unbuilt changes. </p>",
|
||||
"refs": {
|
||||
}
|
||||
},
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||||
"BlobStream": {
|
||||
"base": null,
|
||||
"refs": {
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||||
"PostContentRequest$inputStream": "<p> User input in PCM or Opus audio format or text format as described in the <code>Content-Type</code> HTTP header. </p> <p>You can stream audio data to Amazon Lex or you can create a local buffer that captures all of the audio data before sending. In general, you get better performance if you stream audio data rather than buffering the data locally.</p>",
|
||||
"PostContentResponse$audioStream": "<p>The prompt (or statement) to convey to the user. This is based on the bot configuration and context. For example, if Amazon Lex did not understand the user intent, it sends the <code>clarificationPrompt</code> configured for the bot. If the intent requires confirmation before taking the fulfillment action, it sends the <code>confirmationPrompt</code>. Another example: Suppose that the Lambda function successfully fulfilled the intent, and sent a message to convey to the user. Then Amazon Lex sends that message in the response. </p>"
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||||
}
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||||
},
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||||
"BotAlias": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"PostTextRequest$botAlias": "<p>Alias of the Amazon Lex bot.</p>"
|
||||
"PostContentRequest$botAlias": "<p>Alias of the Amazon Lex bot.</p>",
|
||||
"PostTextRequest$botAlias": "<p>The alias of the Amazon Lex bot.</p>"
|
||||
}
|
||||
},
|
||||
"BotName": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"PostTextRequest$botName": "<p>Name of the Amazon Lex bot.</p>"
|
||||
"PostContentRequest$botName": "<p>Name of the Amazon Lex bot.</p>",
|
||||
"PostTextRequest$botName": "<p>The name of the Amazon Lex bot.</p>"
|
||||
}
|
||||
},
|
||||
"Button": {
|
||||
@@ -36,13 +59,13 @@
|
||||
"ButtonTextStringWithLength": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"Button$text": "<p>Text visible to the user on the button.</p>"
|
||||
"Button$text": "<p>Text that is visible to the user on the button.</p>"
|
||||
}
|
||||
},
|
||||
"ButtonValueStringWithLength": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"Button$value": "<p>Value sent to Amazon Lex when user clicks the button. For example, consider button text \"NYC\". When the user clicks the button, the value sent can be \"New York City\".</p>"
|
||||
"Button$value": "<p>The value sent to Amazon Lex when a user chooses the button. For example, consider button text \"NYC.\" When the user chooses the button, the value sent can be \"New York City.\"</p>"
|
||||
}
|
||||
},
|
||||
"ConflictException": {
|
||||
@@ -53,18 +76,19 @@
|
||||
"ContentType": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"ResponseCard$contentType": "<p>Content type of the response.</p>"
|
||||
"ResponseCard$contentType": "<p>The content type of the response.</p>"
|
||||
}
|
||||
},
|
||||
"DependencyFailedException": {
|
||||
"base": "<p> One of the downstream dependencies, such as AWS Lambda or Amazon Polly, threw an exception. For example, if Amazon Lex does not have sufficient permissions to call a Lambda function which results in AWS Lambda throwing an exception. </p>",
|
||||
"base": "<p> One of the dependencies, such as AWS Lambda or Amazon Polly, threw an exception. For example, </p> <ul> <li> <p>If Amazon Lex does not have sufficient permissions to call a Lambda function.</p> </li> <li> <p>If a Lambda function takes longer than 30 seconds to execute.</p> </li> <li> <p>If a fulfillment Lambda function returns a <code>Delegate</code> dialog action without removing any slot values.</p> </li> </ul>",
|
||||
"refs": {
|
||||
}
|
||||
},
|
||||
"DialogState": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"PostTextResponse$dialogState": "<p>Represents the message type to be conveyed to the user. For example: </p> <ul> <li> <p> <code>ElicitIntent</code> – Amazon Lex wants to elicit user intent. For example, Amazon Lex did not understand the first utterances such as \"I want to order pizza\", which indicates the OrderPizza intent. If Amazon Lex doesn't understand the intent, it returns this <code>dialogState</code>. Another example is when your intent is configured with a follow up prompt. For example, after OrderPizza intent is fulfilled, the intent might have a follow up prompt such as \" Do you want to order a drink or desert?\" In this case, Amazon Lex returns this <code>dialogState</code>. </p> </li> <li> <p> <code>ConfirmIntent</code> – Amazon Lex is expecting a yes/no response from the user indicating whether to go ahead and fulfill the intent (for example, OK to go ahead and order the pizza). In addition to a yes/no reply, the user might provide a response with additional slot information (either new slot information or changes to the existing slot values). For example, \"Yes, but change to thick crust.\" Amazon Lex understands the additional information and updates the intent slots accordingly. </p> <p> Consider another example. Before fulfilling an order, your application might prompt for confirmation such as \"Do you want to place this pizza order?\" A user might reply with \"No, I want to order a drink.\" Amazon Lex recognizes the new OrderDrink intent. </p> </li> <li> <p> <code>ElicitSlot</code> – Amazon Lex is expecting a value of a slot for the current intent. For example, suppose Amazon Lex asks, \"What size pizza would you like?\" A user might reply with \"Medium pepperoni pizza.\" Amazon Lex recognizes the size and the topping as the two separate slot values. </p> </li> <li> <p> <code>Fulfilled</code> – Conveys that the Lambda function has successfully fulfilled the intent. If Lambda function returns a statement/message to convey the fulfillment result, Amazon Lex passes this string to the client. If not, Amazon Lex looks for <code>conclusionStatement</code> that you configured for the intent. </p> <p> If both the Lambda function statement and the <code>conclusionStatement</code> are missing, Amazon Lex throws a bad request exception. </p> </li> <li> <p> <code>ReadyForFulfillment</code> – conveys that the client has to do the fulfillment work for the intent. This is the case when the current intent is configured with <code>ReturnIntent</code> as the <code>fulfillmentActivity </code>, where Amazon Lex returns this state to client. </p> </li> <li> <p> <code>Failed</code> – Conversation with the user failed. Some of the reasons for this <code>dialogState</code> are: after the configured number of attempts the user didn't provide an appropriate response, or the Lambda function failed to fulfill an intent. </p> </li> </ul>"
|
||||
"PostContentResponse$dialogState": "<p>Identifies the current state of the user interaction. Amazon Lex returns one of the following values as <code>dialogState</code>. The client can optionally use this information to customize the user interface. </p> <ul> <li> <p> <code>ElicitIntent</code> - Amazon Lex wants to elicit the user's intent. Consider the following examples: </p> <p> 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. </p> </li> <li> <p> <code>ConfirmIntent</code> - Amazon Lex is expecting a \"yes\" or \"no\" response. </p> <p>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). </p> </li> <li> <p> <code>ElicitSlot</code> - Amazon Lex is expecting the value of a slot for the current intent. </p> <p> 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. </p> </li> <li> <p> <code>Fulfilled</code> - Conveys that the Lambda function has successfully fulfilled the intent. </p> </li> <li> <p> <code>ReadyForFulfillment</code> - Conveys that the client has to fulfill the request. </p> </li> <li> <p> <code>Failed</code> - Conveys that the conversation with the user failed. </p> <p> 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. </p> </li> </ul>",
|
||||
"PostTextResponse$dialogState": "<p> Identifies the current state of the user interaction. Amazon Lex returns one of the following values as <code>dialogState</code>. The client can optionally use this information to customize the user interface. </p> <ul> <li> <p> <code>ElicitIntent</code> - Amazon Lex wants to elicit user intent. </p> <p>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 dialogState.</p> </li> <li> <p> <code>ConfirmIntent</code> - Amazon Lex is expecting a \"yes\" or \"no\" response. </p> <p> For example, Amazon Lex wants user confirmation before fulfilling an intent. </p> <p>Instead of a simple \"yes\" or \"no,\" a user might respond with additional information. For example, \"yes, but make it 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 value, or change intent from OrderPizza to OrderDrink).</p> </li> <li> <p> <code>ElicitSlot</code> - Amazon Lex is expecting a slot value for the current intent. </p> <p>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. </p> </li> <li> <p> <code>Fulfilled</code> - Conveys that the Lambda function configured for the intent has successfully fulfilled the intent. </p> </li> <li> <p> <code>ReadyForFulfillment</code> - Conveys that the client has to fulfill the intent. </p> </li> <li> <p> <code>Failed</code> - Conveys that the conversation with the user failed. </p> <p> This can happen for various reasons including that the user did 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 the Lambda function failed to fulfill the intent. </p> </li> </ul>"
|
||||
}
|
||||
},
|
||||
"ErrorMessage": {
|
||||
@@ -81,10 +105,18 @@
|
||||
"genericAttachmentList$member": null
|
||||
}
|
||||
},
|
||||
"HttpContentType": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"PostContentRequest$contentType": "<p> You pass this value as the <code>Content-Type</code> HTTP header. </p> <p> Indicates the audio format or text. The header value must start with one of the following prefixes: </p> <ul> <li> <p>PCM format, audio data must be in little-endian byte order.</p> <ul> <li> <p>audio/l16; rate=16000; channels=1</p> </li> <li> <p>audio/x-l16; sample-rate=16000; channel-count=1</p> </li> <li> <p>audio/lpcm; sample-rate=8000; sample-size-bits=16; channel-count=1; is-big-endian=false </p> </li> </ul> </li> <li> <p>Opus format</p> <ul> <li> <p>audio/x-cbr-opus-with-preamble; preamble-size=0; bit-rate=256000; frame-size-milliseconds=4</p> </li> </ul> </li> <li> <p>Text format</p> <ul> <li> <p>text/plain; charset=utf-8</p> </li> </ul> </li> </ul>",
|
||||
"PostContentResponse$contentType": "<p>Content type as specified in the <code>Accept</code> HTTP header in the request.</p>"
|
||||
}
|
||||
},
|
||||
"IntentName": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"PostTextResponse$intentName": "<p>Intent Amazon Lex inferred from the user input text. This is one of the intents configured for the bot. </p>"
|
||||
"PostContentResponse$intentName": "<p>Current user intent that Amazon Lex is aware of.</p>",
|
||||
"PostTextResponse$intentName": "<p>The current user intent that Amazon Lex is aware of.</p>"
|
||||
}
|
||||
},
|
||||
"InternalFailureException": {
|
||||
@@ -93,17 +125,32 @@
|
||||
}
|
||||
},
|
||||
"LimitExceededException": {
|
||||
"base": null,
|
||||
"base": "<p>Exceeded a limit.</p>",
|
||||
"refs": {
|
||||
}
|
||||
},
|
||||
"LoopDetectedException": {
|
||||
"base": "<p>Lambda fulfilment function returned <code>DelegateDialogAction</code> to Amazon Lex without changing any slot values. </p>",
|
||||
"base": "<p>This exception is not used.</p>",
|
||||
"refs": {
|
||||
}
|
||||
},
|
||||
"NotAcceptableException": {
|
||||
"base": "<p>The accept header in the request does not have a valid value.</p>",
|
||||
"refs": {
|
||||
}
|
||||
},
|
||||
"NotFoundException": {
|
||||
"base": "<p>Resource (such as the Amazon Lex bot or an alias) referred is not found.</p>",
|
||||
"base": "<p>The resource (such as the Amazon Lex bot or an alias) that is referred to is not found.</p>",
|
||||
"refs": {
|
||||
}
|
||||
},
|
||||
"PostContentRequest": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
}
|
||||
},
|
||||
"PostContentResponse": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
}
|
||||
},
|
||||
@@ -117,10 +164,15 @@
|
||||
"refs": {
|
||||
}
|
||||
},
|
||||
"ResponseCard": {
|
||||
"base": "<p>If you configure a response card when creating your bots, Amazon Lex substitutes the session attributes and slot values available, and then returns it. The response card can also come from a Lambda function ( <code>dialogCodeHook</code> and <code>fulfillmentActivity</code> on an intent).</p>",
|
||||
"RequestTimeoutException": {
|
||||
"base": "<p>The input speech is too long.</p>",
|
||||
"refs": {
|
||||
"PostTextResponse$responseCard": "<p>Represents the options that the user has to respond to the current prompt. Amazon Lex sends this in the response only if the <code>dialogState</code> value indicates that a user response is expected. </p>"
|
||||
}
|
||||
},
|
||||
"ResponseCard": {
|
||||
"base": "<p>If you configure a response card when creating your bots, Amazon Lex substitutes the session attributes and slot values that are available, and then returns it. The response card can also come from a Lambda function ( <code>dialogCodeHook</code> and <code>fulfillmentActivity</code> on an intent).</p>",
|
||||
"refs": {
|
||||
"PostTextResponse$responseCard": "<p>Represents the options that the user has to respond to the current prompt. Response Card can come from the bot configuration (in the Amazon Lex console, choose the settings button next to a slot) or from a code hook (Lambda function). </p>"
|
||||
}
|
||||
},
|
||||
"String": {
|
||||
@@ -131,46 +183,61 @@
|
||||
"InternalFailureException$message": null,
|
||||
"LimitExceededException$retryAfterSeconds": null,
|
||||
"LimitExceededException$message": null,
|
||||
"NotAcceptableException$message": null,
|
||||
"NotFoundException$message": null,
|
||||
"PostTextResponse$slotToElicit": "<p>If <code>dialogState</code> value is <code>ElicitSlot</code>, returns the name of the slot for which Amazon Lex is eliciting a value. </p>",
|
||||
"ResponseCard$version": "<p>Version of response card format.</p>",
|
||||
"PostContentResponse$slots": "<p>Map of zero or more intent slots (name/value pairs) Amazon Lex detected from the user input during the conversation.</p> <p>Amazon Lex creates a resolution list containing likely values for a slot. The value that it returns is determined by the <code>valueSelectionStrategy</code> selected when the slot type was created or updated. If <code>valueSelectionStrategy</code> is set to <code>ORIGINAL_VALUE</code>, the value provided by the user is returned, if the user value is similar to the slot values. If <code>valueSelectionStrategy</code> is set to <code>TOP_RESOLUTION</code> Amazon Lex returns the first value in the resolution list or, if there is no resolution list, null. If you don't specify a <code>valueSelectionStrategy</code>, the default is <code>ORIGINAL_VALUE</code>.</p>",
|
||||
"PostContentResponse$sessionAttributes": "<p> Map of key/value pairs representing the session-specific context information. </p>",
|
||||
"PostContentResponse$slotToElicit": "<p> If the <code>dialogState</code> value is <code>ElicitSlot</code>, returns the name of the slot for which Amazon Lex is eliciting a value. </p>",
|
||||
"PostContentResponse$inputTranscript": "<p>The text used to process the request.</p> <p>If the input was an audio stream, the <code>inputTranscript</code> field contains the text extracted from the audio stream. This is the text that is actually processed to recognize intents and slot values. You can use this information to determine if Amazon Lex is correctly processing the audio that you send.</p>",
|
||||
"PostTextResponse$slotToElicit": "<p>If the <code>dialogState</code> value is <code>ElicitSlot</code>, returns the name of the slot for which Amazon Lex is eliciting a value. </p>",
|
||||
"RequestTimeoutException$message": null,
|
||||
"ResponseCard$version": "<p>The version of the response card format.</p>",
|
||||
"StringMap$key": null,
|
||||
"StringMap$value": null
|
||||
"StringMap$value": null,
|
||||
"UnsupportedMediaTypeException$message": null
|
||||
}
|
||||
},
|
||||
"StringMap": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"PostTextRequest$sessionAttributes": "<p> A session represents the dialog between a user and Amazon Lex. At runtime, a client application can pass contextual information (session attributes) in the request. For example, <code>\"FirstName\" : \"Joe\"</code>. Amazon Lex passes these session attributes to the AWS Lambda functions configured for the intent (see <code>dialogCodeHook</code> and <code>fulfillmentActivity.codeHook</code> in <code>CreateIntent</code>). </p> <p>In your Lambda function, you can use the session attributes for customization. Some examples are:</p> <ul> <li> <p> In a pizza ordering application, if you can pass user location as a session attribute (for example, <code>\"Location\" : \"111 Maple street\"</code>), your Lambda function might use this information to determine the closest pizzeria to place the order. </p> </li> <li> <p> Use session attributes to personalize prompts. For example, you pass in user name as a session attribute (<code>\"FirstName\" : \"Joe\"</code>), you might configure subsequent prompts to refer to this attribute, as <code>$session.FirstName\"</code>. At runtime, Amazon Lex substitutes a real value when it generates a prompt, such as \"Hello Joe, what would you like to order?\" </p> </li> </ul> <note> <p> Amazon Lex does not persist session attributes. </p> <p> If the intent is configured without a Lambda function to process the intent (that is, the client application to process the intent), Amazon Lex simply returns the session attributes back to the client application. </p> <p> If the intent is configured with a Lambda function to process the intent, Amazon Lex passes the incoming session attributes to the Lambda function. The Lambda function must return these session attributes if you want Amazon Lex to return them back to the client. </p> </note>",
|
||||
"PostTextResponse$slots": "<p> Intent slots (name/value pairs) Amazon Lex detected so far from the user input in the conversation. </p>",
|
||||
"PostTextResponse$sessionAttributes": "<p>Map of key value pairs representing the session specific context information.</p>"
|
||||
"PostTextRequest$sessionAttributes": "<p>Application-specific information passed between Amazon Lex and a client application.</p> <p>For more information, see <a href=\"http://docs.aws.amazon.com/lex/latest/dg/context-mgmt.html#context-mgmt-session-attribs\">Setting Session Attributes</a>.</p>",
|
||||
"PostTextRequest$requestAttributes": "<p>Request-specific information passed between Amazon Lex and a client application.</p> <p>The namespace <code>x-amz-lex:</code> is reserved for special attributes. Don't create any request attributes with the prefix <code>x-amz-lex:</code>.</p> <p>For more information, see <a href=\"http://docs.aws.amazon.com/lex/latest/dg/context-mgmt.html#context-mgmt-request-attribs\">Setting Request Attributes</a>.</p>",
|
||||
"PostTextResponse$slots": "<p> The intent slots that Amazon Lex detected from the user input in the conversation. </p> <p>Amazon Lex creates a resolution list containing likely values for a slot. The value that it returns is determined by the <code>valueSelectionStrategy</code> selected when the slot type was created or updated. If <code>valueSelectionStrategy</code> is set to <code>ORIGINAL_VALUE</code>, the value provided by the user is returned, if the user value is similar to the slot values. If <code>valueSelectionStrategy</code> is set to <code>TOP_RESOLUTION</code> Amazon Lex returns the first value in the resolution list or, if there is no resolution list, null. If you don't specify a <code>valueSelectionStrategy</code>, the default is <code>ORIGINAL_VALUE</code>.</p>",
|
||||
"PostTextResponse$sessionAttributes": "<p>A map of key-value pairs representing the session-specific context information.</p>"
|
||||
}
|
||||
},
|
||||
"StringUrlWithLength": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"GenericAttachment$attachmentLinkUrl": null,
|
||||
"GenericAttachment$imageUrl": "<p>URL of an image that is displayed to the user.</p>"
|
||||
"GenericAttachment$attachmentLinkUrl": "<p>The URL of an attachment to the response card.</p>",
|
||||
"GenericAttachment$imageUrl": "<p>The URL of an image that is displayed to the user.</p>"
|
||||
}
|
||||
},
|
||||
"StringWithLength": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"GenericAttachment$title": "<p>Title of the option.</p>",
|
||||
"GenericAttachment$subTitle": "<p>Subtitle shown below the title.</p>"
|
||||
"GenericAttachment$title": "<p>The title of the option.</p>",
|
||||
"GenericAttachment$subTitle": "<p>The subtitle shown below the title.</p>"
|
||||
}
|
||||
},
|
||||
"Text": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"PostTextRequest$inputText": "<p>Text user entered (Amazon Lex interprets this text).</p>",
|
||||
"PostTextResponse$message": "<p> Prompt (or statement) to convey to the user. This is based on the application configuration and context. For example, if Amazon Lex did not understand the user intent, it sends the <code>clarificationPrompt</code> configured for the application. In another example, if the intent requires confirmation before taking the fulfillment action, it sends the <code>confirmationPrompt</code>. Suppose the Lambda function successfully fulfilled the intent, and sent a message to convey to the user. In that situation, Amazon Lex sends that message in the response. </p>"
|
||||
"PostContentResponse$message": "<p> Message to convey to the user. It can come from the bot's configuration or a code hook (Lambda function). If the current intent is not configured with a code hook or if the code hook returned <code>Delegate</code> as the <code>dialogAction.type</code> in its response, then Amazon Lex decides the next course of action and selects an appropriate message from the bot configuration based on the current user interaction context. For example, if Amazon Lex is not able to understand the user input, it uses a clarification prompt message (For more information, see the Error Handling section in the Amazon Lex console). Another example: if the intent requires confirmation before fulfillment, then Amazon Lex uses the confirmation prompt message in the intent configuration. If the code hook returns a message, Amazon Lex passes it as-is in its response to the client. </p>",
|
||||
"PostTextRequest$inputText": "<p>The text that the user entered (Amazon Lex interprets this text).</p>",
|
||||
"PostTextResponse$message": "<p> A message to convey to the user. It can come from the bot's configuration or a code hook (Lambda function). If the current intent is not configured with a code hook or the code hook returned <code>Delegate</code> as the <code>dialogAction.type</code> in its response, then Amazon Lex decides the next course of action and selects an appropriate message from the bot configuration based on the current user interaction context. For example, if Amazon Lex is not able to understand the user input, it uses a clarification prompt message (for more information, see the Error Handling section in the Amazon Lex console). Another example: if the intent requires confirmation before fulfillment, then Amazon Lex uses the confirmation prompt message in the intent configuration. If the code hook returns a message, Amazon Lex passes it as-is in its response to the client. </p>"
|
||||
}
|
||||
},
|
||||
"UnsupportedMediaTypeException": {
|
||||
"base": "<p>The Content-Type header (<code>PostContent</code> API) has an invalid value. </p>",
|
||||
"refs": {
|
||||
}
|
||||
},
|
||||
"UserId": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"PostTextRequest$userId": "<p>User ID of your client application. Typically, each of your application users should have a unique ID. Note the following considerations: </p> <ul> <li> <p> If you want a user to start a conversation on one mobile device and continue the conversation on another device, you might choose a user-specific identifier, such as a login or Amazon Cognito user ID (assuming your application is using Amazon Cognito). </p> </li> <li> <p> If you want the same user to be able to have two independent conversations on two different devices, you might choose a device-specific identifier, such as device ID, or some globally unique identifier. </p> </li> </ul>"
|
||||
"PostContentRequest$userId": "<p>The ID of the client application user. Amazon Lex uses this to identify a user's conversation with your bot. At runtime, each request must contain the <code>userID</code> field.</p> <p>To decide the user ID to use for your application, consider the following factors.</p> <ul> <li> <p>The <code>userID</code> field must not contain any personally identifiable information of the user, for example, name, personal identification numbers, or other end user personal information.</p> </li> <li> <p>If you want a user to start a conversation on one device and continue on another device, use a user-specific identifier.</p> </li> <li> <p>If you want the same user to be able to have two independent conversations on two different devices, choose a device-specific identifier.</p> </li> <li> <p>A user can't have two independent conversations with two different versions of the same bot. For example, a user can't have a conversation with the PROD and BETA versions of the same bot. If you anticipate that a user will need to have conversation with two different versions, for example, while testing, include the bot alias in the user ID to separate the two conversations.</p> </li> </ul>",
|
||||
"PostTextRequest$userId": "<p>The ID of the client application user. Amazon Lex uses this to identify a user's conversation with your bot. At runtime, each request must contain the <code>userID</code> field.</p> <p>To decide the user ID to use for your application, consider the following factors.</p> <ul> <li> <p>The <code>userID</code> field must not contain any personally identifiable information of the user, for example, name, personal identification numbers, or other end user personal information.</p> </li> <li> <p>If you want a user to start a conversation on one device and continue on another device, use a user-specific identifier.</p> </li> <li> <p>If you want the same user to be able to have two independent conversations on two different devices, choose a device-specific identifier.</p> </li> <li> <p>A user can't have two independent conversations with two different versions of the same bot. For example, a user can't have a conversation with the PROD and BETA versions of the same bot. If you anticipate that a user will need to have conversation with two different versions, for example, while testing, include the bot alias in the user ID to separate the two conversations.</p> </li> </ul>"
|
||||
}
|
||||
},
|
||||
"genericAttachmentList": {
|
||||
@@ -182,7 +249,7 @@
|
||||
"listOfButtons": {
|
||||
"base": null,
|
||||
"refs": {
|
||||
"GenericAttachment$buttons": "<p>List of options to show to the user.</p>"
|
||||
"GenericAttachment$buttons": "<p>The list of options to show to the user.</p>"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user