Aws Lex Free Text Slots
| 'use strict'; |
| exports.handler=(event,context,callback)=>{ |
| // Currently all possible fields |
| // { |
| // 'sessionAttributes': { |
| // 'key1': 'value1', |
| // 'key2': 'value2' |
| // ... |
| // }, |
| // 'dialogAction': { |
| // 'type': 'ElicitIntent, ElicitSlot, ConfirmIntent, Delegate, or Close', |
| // 'fulfillmentState': 'Fulfilled or Failed', |
| // 'message': { |
| // 'contentType': 'PlainText or SSML', |
| // 'content': 'message to convey to the user' |
| // }, |
| // 'intentName': 'intent-name', |
| // 'slots': { |
| // 'slot-name': 'value', |
| // 'slot-name': 'value', |
| // 'slot-name': 'value' |
| // }, |
| // 'slotToElicit' : 'slot-name', |
| // 'responseCard': { |
| // 'version': integer-value, |
| // 'contentType': 'application/vnd.amazonaws.card.generic', |
| // 'genericAttachments': [ |
| // { |
| // 'title':'card-title', |
| // 'subTitle':'card-sub-title', |
| // 'imageUrl':'URL of the image to be shown', |
| // 'attachmentLinkUrl':'URL of the attachment to be associated with the card', |
| // 'buttons':[ |
| // { |
| // 'text':'button-text', |
| // 'value':'value sent to server on button click' |
| // } |
| // ] |
| // } |
| // ] |
| // } |
| // } |
| // } |
| // This is all that is required for a valid ElicitSlot response |
| vardummy={ |
| 'sessionAttributes': {}, |
| 'dialogAction': { |
| 'type': 'ElicitSlot', |
| 'intentName': 'ScheduleRequest', |
| 'slots': { |
| 'MusicGroup': 'null' |
| }, |
| 'slotToElicit': 'MusicGroup' |
| } |
| } |
| // Respond to Lex by passing a proper JSON response to callback |
| callback(null,dummy) |
| }; |
commented Apr 21, 2017
Aws Lex Api
Here |
Aws Lex Tutorial
Aws Lex Languages
Docker or a virtual machine software. Because we’ll be using Amazon products such as Lex and Lambda, an AWS account must be available. Both products are pay as you go, so a free tier will likely be more than enough. Since we’ll be using Amazon. Python AWS Lex Object (pylexo) to ease the pain in navigating AWS Lex lambda events and in constructing lambda response - wavycloud/pylexo. If you don’t have one, you can set one up here and click “Create a Free Account”. Once you have your account set up, we can set up the chatbot. On the AWS Management Console, search for “Lex” or click on the Services drop down menu on the top left of the page and you’ll find it under the “Machine Learning” category.