sample Amazon Lex Web Interface
This is a sample Amazon Lexweb interface. It provides a chatbot UI component that can be integratedin your website. The interface allows a user to interact with a Lex bot directlyfrom a browser using text or voice.
Add feature for connect live chat. Allow client to optionally interact with an agent via Connect.See Connect Live Chat Agent Readme for additional details.
The Lex Web Ui now supports configuration of multiple Lex V2 Bot Locale IDsusing a comma separated list in the parameter LexV2BotLocaleId. The default Locale IDis en_US. Other supported values are de_DE, en_AU, en_GB, es_419, es_ES, es_US, fr_CA,fr_FR, it_IT, and ja_JP. See "https://docs.aws.amazon.com/lexv2/latest/dg/lex2.0.pdf"for the current list of supported Locale IDs.
When multiple Locale IDs are specified in LexV2BotLocaleId, the Lex Web UI toolbar menuwill allow the user to select the locale to use. The user selected locale ID ispreserved across page refreshes. The locale selection menu items will be disabled ifthe user is the middle of completing an intent as the locale ID can't be changed at thistime. The selected locale ID will be displayed in the toolbar.
Lex Web Ui is now available in the Canada (Central) region - ca-central-1
For a complete list of fixes/changes in this version see CHANGELOG.md.
It can be used as a full page chatbot UI:
Or embedded into an existing site as a chatbot widget:
The easiest way to test drive the chatbot UI is to deploy it using theAWS CloudFormation templatesprovided by this project. Once you have launched the CloudFormation stack,you will get a fully working demo site hosted in your account.
Click a button to launch it in the desired region
Region | Launch |
---|---|
Northern Virginia | |
Oregon | |
Ireland | |
Sydney | |
Singapore | |
London | |
Tokyo | |
Frankfurt | |
Canada (Central) |
By default, the CloudFormation templatecreates a sample Lex bot and a Amazon Cognito IdentityPoolto get you started. It copies the chatbot UI web application to anAmazon S3 bucket including a dynamicallycreated configuration file. The CloudFormation stack outputs links tothe demo and related configuration once deployed. See the CloudFormationDeployment section for details.
You can modify the configuration of the deployed demo site to customizethe chatbot UI. It can also be further configured to be embedded it onyour web site. See the sections below for code samples and a descriptionof the configuration and deployment options.
In addition to the CloudFormation deployment mentioned above, there areother methods to integrate and deploy this project. Here is a summaryof the various methods:
# | Method | Description | Use Case |
---|---|---|---|
1 | CloudFormation Deployment using the CloudFormation templates provided by this project | Fully automated deployment of a hosted web application to an S3 bucket with an optional CI/CD pipeline. By default, it also creates a Cognito Identity Pool and a sample Lex bot | Use when you want to have a infrastructure as code approach that automatically builds and configures the chatbot UI resources |
2 | Use the pre-built libraries from the dist directory of this repo | We provide a pre-built version of the chatbot UI component and a loader library that you can use on your web site as a stand alone page or as an embeddable iframe | Use when you have an existing site and want to add the chatbot UI to it by simply copying or referencing the library files |
4 | Use npm to install and use the chatbot UI as a Vue component | Enables developers to consume this project as an npm package that provides a Vue component. See the Npm Install and Vue Component Use section for details | Use when developing front-end based web applications built using JavaScript and bundled with tools such as webpack |
See the Usage and Deployment sections below for details.
This project provides a set of JavaScript libraries used to dynamicallyinsert the chatbot UI in a web page. The chatbot UI is loaded andcustomized by including these libraries in your code and calling theirfunctions with configuration parameters.
The chatbot UI can be displayed either as a full page or embeddedin an iframe. In this section, you will find a brief overview ofthe libraries and configuration parameters. It is useful to getfamiliar with the concepts described in the Librariesand Configuration sections before jumping to the codeexamples.
The list below describes the libraries produced by this project.Pre-built versions of the libraries are found under the distdirectory of this repository.
lex-web-ui.js
file under the dist directory. Itis bundled from the source under the lex-web-uidirectory. This library is geared to be used as an import in a webpackbased web application but can also be instantiated directly in a web pageprovided that you manually load the dependencies and explicitly passthe configuration. See the component's READMEfor detailslex-web-ui-loader.js
file under thedist directory. It is bundled from the sources under thesrc/lex-web-ui-loader directory. This libraryis used by adding a few script tags to an HTML page. See the loaderREADME for detailsThe chatbot UI component requires a configuration objectpointing to an existing Lex bot and to an Amazon Cognito IdentityPoolto create credentials used to authenticate the Lex API calls from thebrowser. The configuration object is also used to customize its behaviorand UI elements of the chatbot UI component.
The CloudFormation deployment method, from this project,help with building a base configuration file. When deploying with it,the base configuration is automatically pointed to the theresources created in the deployment (i.e. Lex and Cognito).
You can override the configuration at run time by passingparameters to the library functions or using various dynamicconfiguration methods provided by the loader library (e.g. JSONfile, events). For details, see the ChatBot UI ConfigurationLoading sectionof the loader library documentation and the Configuration andCustomizationsection of the chatbot UI component documentation.
The examples below are organized around the following use cases:
To render the chatbot UI as a stand-alone full page, you can use twoalternatives: 1) directly use the chatbot UI component library or 2)use the loader library. These libraries (see Libraries)provide pre-built JavaScript and CSS files that are ready to be includeddirectly into an HTML file to display a full page chatbot UI.
When you use the chatbot UI component directly, you have to manuallyload the component's dependencies and provide its configuration as aparameter. The loader library alternative provides more configurationoptions and automates the process of loading dependencies. It encapsulatesthe chatbot UI component in an automated load process.
The loader library provides the easiest way to display the chatbot UI. Theentry point to this library is the lex-web-ui-loader.js
script. Thisscript facilitates the process of loading run-time dependencies andconfiguration.
If you deploy using the CloudFormation method, you willget an S3 bucket with the loader library script and related files in away that is ready to be used. Alternatively, you can copy the files fromthe dist
directory of this repository to your web server and include theloader.
In its most simple setup, you can use the loader library like this:
<!-- include the loader library script -->
<script src="./lex-web-ui-loader.js"></script>
<script>
/*
The loader library creates a global object named ChatBotUiLoader
It includes the FullPageLoader constructor
An instance of FullPageLoader has the load function which kicks off
the load process
*/
// The following statement instantiate FullPageLoader and
// calls the load function.
// It is assumed that the configuration is present in the
// default JSON file: ./lex-web-ui-loader-config.json
new ChatBotUiLoader.FullPageLoader().load();
</script>
Similar to the iFrame loading technique described later, theFullPageComponentLoader now provides an API allowing a subset ofevents to be sent to the Lex Web UI Component. These events areping and postText. See the full page fordescription of this API.
For more details and other code examples about using the loader scriptin a full page setup, see the full pagesection of the loader documentation. You can also see the source of theindex.html page used in the demo site.
Directly loading the chatbot UI component works at a lower level thanusing the loader library as described above. This approach can be usedif you want to manually control the rendering, configuration anddependency loading process.
The entry point to the chatbot UI component is the lex-web-ui.js
JavaScript file. The UI CSS styles are contained in the lex-web-ui.css
file. The component depends on the Vue,Vuex, Vuetifyand AWS SDK libraries. Youshould either host these dependencies on your site or load them from athird-party CDN.
The HTML code below is an illustration of directly loading the chatbot UIlibrary and its dependencies.
NOTE: The versions of the links below may need to be pointedto the latest supported versions.
<html>
<head>
<!-- Font Dependencies -->
<link href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Material+Icons" rel="stylesheet" type="text/css">
<!-- Vuetify CSS Dependencies -->
<link href="https://unpkg.com/vuetify@0.16.9/dist/vuetify.min.css" rel="stylesheet" type="text/css">
<!-- LexWebUi CSS from dist directory -->
<link href="./lex-web-ui.css" rel="stylesheet" type="text/css">
<!-- page specific LexWebUi styling -->
<style type="text/css">
#lex-web-ui-app { display: flex; height: 100%; width: 100%; }
body, html { overflow-y: auto; overflow-x: hidden; }
</style>
</head>
<body>
<!-- application will be dynamically mounted here -->
<div id="lex-web-ui"></div>
<!--
Vue, Vuex, Vuetifiy and AWS SDK dependencies must be loaded before lex-web-ui.js.
Loading from third party CDN for quick testing
-->
<script src="https://unpkg.com/vue@2.5.3"></script>
<script src="https://unpkg.com/vuex@3.0.1"></script>
<script src="https://unpkg.com/vuetify@0.16.9"></script>
<script src="https://sdk.amazonaws.com/js/aws-sdk-2.149.0.min.js"></script>
<!-- LexWebUi Library from dist directory -->
<script src="./lex-web-ui.js"></script>
<!-- instantiate the web ui with a basic config -->
<script>
// LexWebUi supports numerous configuration options. Here
// is an example using just a couple of the required options.
var config = {
cognito: {
// Your Cognito Pool Id - this is required to provide AWS credentials
poolId: '<your cognito pool id>'
},
lex: {
// Lex Bot Name in your account
botName: '<your lex bot name>'
}
};
// load the LexWebUi component
var lexWebUi = new LexWebUi.Loader(config);
// instantiate Vue
new Vue({
el: '#lex-web-ui',
store: lexWebUi.store,
template: '<div id="lex-web-ui-app"><lex-web-ui/></div>',
});
</script>
</body>
</html>
You can embed the chatbot UI into an existing page using an iframe.This approach provides a self-contained widget that can interact withthe parent page hosting the iframe. The lex-web-ui-loader.js
loaderlibrary provides the functionality to add it as an iframe in a page.
This loader script dynamically creates the iframe tag and supportspassing asynchronous configuration using events and JSON files. It alsoprovides an API between the iframe and the parent page which can be usedto pass Lex state and other events. These features are detailed in theIframe Embedding section of the library.
The HTML code below is a basic example of a parent page that adds thechatbot UI as an iframe. In this scenario, the libraries and relatedfiles from the dist
directory of this repo are hosted in the samedirectory as the parent page.
Please note that the loaderOptions
variable has an iframeSrcPath
field which defines the path to the full page chatbot UI. This variablecan be pointed to a page like the one described in the stand-alonepage section.
<html>
<head>
<title>My Parent Page</title>
</head>
<body>
<h1>Welcome to my parent page</h1>
<!-- loader script -->
<script src="./lex-web-ui-loader.js"></script>
<script>
/*
The loader library creates a global object named ChatBotUiLoader
It includes the IframeLoader constructor
An instance of IframeLoader has the load function which kicks off
the load process
*/
// options for the loader constructor
var loaderOptions = {
// you can put the chatbot UI config in a JSON file
configUrl: './chatbot-ui-loader-config.json',
// the full page chatbot UI that will be iframed
iframeSrcPath: './chatbot-index.html#/?lexWebUiEmbed=true'
};
// The following statement instantiates the IframeLoader
var iframeLoader = new ChatBotUiLoader.IframeLoader(loaderOptions);
// chatbot UI config
// The loader can also obtain these values from other sources such
// as a JSON file or events. The configUrl variable in the
// loaderOptions above can be used to put these config values in a file
// instead of explicitly passing it as an argument.
var chatbotUiConfig = {
ui: {
// origin of the parent site where you are including the chatbot UI
// set to window.location.origin since hosting on same site
parentOrigin: window.location.origin,
},
iframe: {
// origin hosting the HTML file that will be embedded in the iframe
// set to window.location.origin since hosting on same site
iframeOrigin: window.location.origin,
},
cognito: {
// Your Cognito Pool Id - this is required to provide AWS credentials
poolId: '<your cognito pool id>'
},
connect: {
contactFlowId : '<your contact flow id>',
instanceId : '<your instance id>',
apiGatewayEndpoint : '<your api gateway endpoint>',
},
lex: {
// Lex Bot Name in your account
botName: '<your lex bot name>'
}
};
// Call the load function which returns a promise that is resolved
// once the component is loaded or is rejected if there is an error
iframeLoader.load(chatbotUiConfig)
.then(function () {
console.log('iframe loaded');
})
.catch(function (err) {
console.error(err);
});
</script>
</body>
</html>
For more examples showing how to include the chatbot UI as an iframe,see the source of the parent.html page and theIframe Embedding documentation of theloader library.
You can use the npm package manager toinstall this project. The npm installation provides a library that youcan import as a module into your JavaScript code. The component is builtas a reusable Vue plugin. This approach is gearedto be used in a webpack based project.
Package installation using npm
:
# install npm package from github repo
npm install --save awslabs/aws-lex-web-ui
# you may need to install co-dependencies:
npm install --save vue vuex vuetify material-design-icons roboto-fontface
This is a quick example showing how to import the library in your project:
// assumes that a bundler like webpack will handle import/require
// using es6 module
import LexWebUi from 'aws-lex-web-ui';
// or using require
var LexWebUi = require('aws-lex-web-ui');
// import the debug non-minimized version
import LexWebUi from 'aws-lex-web-ui/dist/lex-web-ui';
The source of the chatbot UI component resides under thelex-web-ui directory. For further details about the chatbotUI component see its README file.
This repository provides a sample site that you can use as a basefor development. The site is a couple of HTML pages can be foundin the src/website directory. The pages includes theindex.html file which loads the chatbot UIin a stand-alone page and the parent.htmlwhich page loads the chatbot UI in an iframe.
These pages are the same ones that are deployed by the CloudFormationdeployment method in this project. It uses thelex-web-ui-loader.js
loader library to display and configure the chatbotUI. You can run a development version of this sample site on your machine.
This project provides a simple HTTP server to serve the sample site.You can run the server using Node.js on your localmachine or a test server.
The chatbot UI requires proper configuration values in the files locatedunder the src/config directory. Modify the values in thelex-web-ui-loader-config.json
file under the src/config
directory.If you deployed the demo site using the CloudFormation templates providedby this project, you can copy the automatically generated config filesfrom the S3 buckets to your development host.
As a minimum,you would need to pass an existing Cognito Pool Idand Lex Bot name. For example, set the appropriate values in thesrc/config/lex-web-ui-loader-config.json
file:
...
cognito: {
"poolId": "us-east-1:deadbeef-fade-babe-cafe-0123456789ab"
},
lex: {
"botName": "myHelpBot"
}
...
Before you run the local development server, you need to install thedevelopment dependencies with the command:
npm install
To start the HTTP server web on port 8000
, issue the command:
# serves http://localhost:8000/index.html
# and http://localhost:8000/parent.html
npm start
If you want to hack the libraries under the src/lex-web-ui-loader
directory, the project provides a hot reloadable webpack devserver setup with thefollowing command:
# runs on port 8000
npm run dev
For a more advanced local host development and test environment, see theDependencies and Build Setupdocumentation of the chatbot UI component.
This project provides AWS CloudFormationtemplates that can be used to launch a fully configured working demo site andrelated resources (e.g. Lex bot and Cognito Identity Pool).
The CloudFormation deployment is the preferred method as it allows toautomatically build, configure and deploy the application (including anoptional CI/CD pipeline) and it provides a higher degree of flexibilitywhen integrating with an existing environment.
The CloudFormation stack creates a web app in an S3 bucket which youcan link from your site. The S3 bucket also hosts the configuration,JavaScript and CSS files which can be loaded by your existing webpages. The CloudFormation deployment is documented in theREADME file under the templatesdirectory.
本人所整理的劳动成果,转载请务必注明出处,谢谢! 有问题欢迎评论区讨论交流,大家一起学习~ [Module 2 - Introducing Machine Learning] 1.机器学习是有关算法和统计模型的科学研究,依靠推理而不是指令来执行任务 2.强化学习通过与环境交互并学习采取能够获得最大奖励的行动 3.为呼叫中心创建机器学习解决方案,系统模板是将客户转接到适当部门(共有八个可能的部门)
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Lex是Lexical Analyzer Generator的缩写,是Unix环境下非常著名的工具,主要功能是生成一个词法分析器(scanner)的C源码,描述规则采用正则表达式(regular expression)。 描述词法分析器的文件*.l,经过lex编译后,生成一个lex.yy.c 的文件,然后由C编译器编译生成一个词法分析器。词法分析器,简单来说,其任务就是将输入的各种符号,转化成相应
lex.py是用来将输入字符串标记化。例如,假设你正在设计一个编程语言,用户的输入字符串如下: x = 3 + 42 * (s - t) 标记器将字符串分割成独立的标记: 'x','=', '3', '+', '42', '*', '(', 's', '-', 't', ')' 标记通常用一组名字来命名和表示: 'ID','EQUALS','NUMBER','PLUS','NUMBER','TIM
谢谢, 哈利
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如果你从事编译器或解析器的开发工作,你可能对 lex 和 yacc 不会陌生,PLY 是 David Beazley 实现的基于 Python 的 lex 和 yacc。作者最著名的成就可能是其撰写的 Python Cookbook, 3rd Edition。
我们在使用Twilio,Twilio应该流媒体音频。 据我所知,我有两个选择,Android Lex和Transcripbe,当Lex是机器人的,而Transcripbe只是翻译演讲,不能参与对话。 所以问题是: [机器人]:好的(就像电话会议中的第三个人..)。