Building a Chatbots using AWS Lex and Nodejs

Building a Chatbots using AWS Lex and Nodejs

Learn how to build a basic, but intelligent chatbot using Nodejs with AWS Lex and AWS Lambda.

Learn how to build a basic, but intelligent chatbot using Nodejs with AWS Lex and AWS Lambda.

Amazon and a lot of cloud vendors such as Microsoft and Google have services around machine learning (ML), artificial intelligence (AI), and virtual assistants.

The concept around Alexa is simple. Provide the Alexa service some audio, have that audio converted into text or some other format that can be evaluated, execute some code, and respond with something to be spoken to the user. However, what if you didn’t necessarily want to use a virtual assistant with audio, but integrate as part of a chat application in the form of a chatbot?

In this tutorial we’re going to look at using Amazon Web Services (AWS) Lex, which is a service for adding conversational interfaces to your applications. If you’re coming from an Amazon Alexa background, the concepts will be similar as AWS Lex shares the same deep learning technologies.

The assumption going into this tutorial is that you have Node.js installed and configured and have an Amazon Web Services (AWS) account. Nothing we do will have any requirement beyond Amazon’s free tier for developers.

Configuring a Custom Bot with AWS Lex

Before we write any code, we’re going to want to configure our chatbot in the AWS portal. The configuration process will accomplish the following:

  1. Define our intents to execute application logic.
  2. Supply our sample utterances to make our chatbot smarter.
  3. Define any variables that are to be determined by the end user.

If you’ve worked with Alexa before, some of the above terms might be familiar. Regardless of your Alexa experience, we’re going to explore each when working with AWS Lex.

Before we can configure our chatbot, we need to create it. From the AWS Lex landing page, choose to create a custom bot.

When creating a custom bot, give it a name, choose text only output, and a short timeout of maybe a minute. Pretty much only use the defaults for this particular example.

After the custom bot has been created, we need to create a new intent.

To start, we’re going to create something basic with the sole purpose of telling users who designed the chatbot. Let’s name this AboutIntent, even though the name isn’t too important. In the AboutIntent, we’re going to need to define some sample utterances, also known as sample phrases. These phrases are the possible sentences that your users might use when interacting with the chatbot.

My sample utterances are as follows:

give me information about this bot
who made this bot

In a perfect world, you’re going to want as many sample utterances as you can think up, so probably something more than 20. AWS Lex is smart and can actually learn from your sample utterances. This means the more you have, the more likely AWS Lex can fill in the blanks if the user provides a message that is similar, but doesn’t quite exist in the list.

Because we don’t have AWS Lambda hooked up yet, we should probably choose Return parameters to client before saving. This will essentially show us which intent was chosen, but not actually perform any logic.

If you haven’t figured it out, an intent is an outlet to performing logic. You can have many intents, each with their own sample utterances. When AWS Lex receives a phrase, it determines which intent to execute, which later gets passed to your AWS Lambda function.

Let’s see another example of an intent. Something a little more than just a basic example.

Create another intent, but this time name it FullNameIntent. Again, the name isn’t too important as long as we’re consistent when we reach the AWS Lambda step.

The goal of this intent is to show how we can use slot data which are variables to be defined by the end user.

This is just a simple example, but we’re going to allow the user to provide their full name. Of course this full name will be different on a per user basis. To make a slot, name it and then choose AMAZON.Person as the type. It doesn’t really matter the name as long as you’re consistent.

Then in your sample utterances, include the slot in your utterance. Defining a word as a slot variable versus a regular word can be handled by using curly brackets.

Now that we have two different intents, we can focus on some actual logic.

Developing the Chatbot Logic with AWS Lambda and Node.js

When it comes to defining the chatbot logic, there isn’t much to it. We’re going to be creating an AWS Lambda function that receives JSON data as input. That JSON input will contain information such as the intent that was triggered, any available slot data, etc., and as a response we’re going to provide JSON data that meets the AWS Lex specification. What happens in-between is up to us.

Let’s start by creating a simple Node.js application. Create and open an index.js file on your computer:

const dispatcher = (event) => {
    let response = {
        sessionAttributes: event.sessionAttributes,
        dialogAction: {
            type: "Close",
            fulfillmentState: "",
            message: {
                "contentType": "PlainText",
                "content": ""
            }
        }
    };
    switch(event.currentIntent.name) {
        default:
            response.dialogAction.fulfillmentState = "Failed";
            response.dialogAction.message.content = "I don't know what you're asking...";
            break;
    }
    return response;
}

exports.handler = (event, context) => {
    return dispatcher(event);
}

The above code is our starting point. When the function is executed, the dispatcher function will be used. The event parameter will contain the request data that AWS Lex provides. It will look something like this:

{
    "messageVersion": "1.0",
    "invocationSource": "NicTest",
    "userId": "Nic",
    "sessionAttributes": {},
    "bot": {
        "name": "LexTest",
        "alias": "$LATEST",
        "version": "$LATEST"
    },
    "outputDialogMode": "Text",
    "currentIntent": {
        "name": "AboutIntent",
        "slots": {},
        "confirmationStatus": "None"
    }
}

Of course the above request is just an example, but the format is what matters. The JSON will include the intent name and any slot information. Inside the dispatcher function of our code, we start formatting a response. The response is completed after looking at a switch statement or some other conditional statement. We want to figure out what intent is sent before responding.

To make our code more functional, we can add the following to our dispatcher function:

const dispatcher = (event) => {
    let response = {
        sessionAttributes: event.sessionAttributes,
        dialogAction: {
            type: "Close",
            fulfillmentState: "",
            message: {
                "contentType": "PlainText",
                "content": ""
            }
        }
    };
    switch(event.currentIntent.name) {
        case "AboutIntent":
            response.dialogAction.fulfillmentState = "Fulfilled";
            response.dialogAction.message.content = "Created by Nic Raboy";
            break;
        case "FullNameIntent":
            response.dialogAction.fulfillmentState = "Fulfilled";
            response.dialogAction.message.content = "Hello " + event.currentIntent.slots.FullName + "!";
            break;
        default:
            response.dialogAction.fulfillmentState = "Failed";
            response.dialogAction.message.content = "I don't know what you're asking...";
            break;
    }
    return response;
}

Notice that now we’re checking for the AboutIntent as well as the FullNameIntent.

Now that our index.js file is complete for this particular example, it can be added to AWS Lambda. Choose to create a new AWS Lambda function with Node.js. It doesn’t really matter what you call it, but after you create the function, add the Node.js code inline.

With the code added, you can go back to AWS Lex and change the Fulfillment option of each intent to be AWS Lambda function instead. Choose the Lambda function you wish to use and you’ll be good to go.

Save each of your intents, then build the chatbot. You should be able to test each of your intents to see if they behave as expected.

Conclusion

You just saw how to build a simple chatbot using AWS Lex, AWS Lambda, and simple JavaScript. While we didn’t hook this chatbot up to any services like Slack or Twitter, we could have and it would have been awesome! Essentially what we did was define our intents for logic, our sample utterances of what users could ask, any variables for our intents, and then the logic on Lambda.

How to Use Express.js, Node.js and MongoDB.js

How to Use Express.js, Node.js and MongoDB.js

In this post, I will show you how to use Express.js, Node.js and MongoDB.js. We will be creating a very simple Node application, that will allow users to input data that they want to store in a MongoDB database. It will also show all items that have been entered into the database.

In this post, I will show you how to use Express.js, Node.js and MongoDB.js. We will be creating a very simple Node application, that will allow users to input data that they want to store in a MongoDB database. It will also show all items that have been entered into the database.

Creating a Node Application

To get started I would recommend creating a new database that will contain our application. For this demo I am creating a directory called node-demo. After creating the directory you will need to change into that directory.

mkdir node-demo
cd node-demo

Once we are in the directory we will need to create an application and we can do this by running the command
npm init

This will ask you a series of questions. Here are the answers I gave to the prompts.

The first step is to create a file that will contain our code for our Node.js server.

touch app.js

In our app.js we are going to add the following code to build a very simple Node.js Application.

var express = require("express");
var app = express();
var port = 3000;
 
app.get("/", (req, res) => {
  res.send("Hello World");
});
 
app.listen(port, () => {
  console.log("Server listening on port " + port);
});

What the code does is require the express.js application. It then creates app by calling express. We define our port to be 3000.

The app.use line will listen to requests from the browser and will return the text “Hello World” back to the browser.

The last line actually starts the server and tells it to listen on port 3000.

Installing Express

Our app.js required the Express.js module. We need to install express in order for this to work properly. Go to your terminal and enter this command.

npm install express --save

This command will install the express module into our package.json. The module is installed as a dependency in our package.json as shown below.

To test our application you can go to the terminal and enter the command

node app.js

Open up a browser and navigate to the url http://localhost:3000

You will see the following in your browser

Creating Website to Save Data to MongoDB Database

Instead of showing the text “Hello World” when people view your application, what we want to do is to show a place for user to save data to the database.

We are going to allow users to enter a first name and a last name that we will be saving in the database.

To do this we will need to create a basic HTML file. In your terminal enter the following command to create an index.html file.

touch index.html

In our index.html file we will be creating an input filed where users can input data that they want to have stored in the database. We will also need a button for users to click on that will add the data to the database.

Here is what our index.html file looks like.

<!DOCTYPE html>
<html>
  <head>
    <title>Intro to Node and MongoDB<title>
  <head>

  <body>
    <h1>Into to Node and MongoDB<&#47;h1>
    <form method="post" action="/addname">
      <label>Enter Your Name<&#47;label><br>
      <input type="text" name="firstName" placeholder="Enter first name..." required>
      <input type="text" name="lastName" placeholder="Enter last name..." required>
      <input type="submit" value="Add Name">
    </form>
  <body>
<html>

If you are familiar with HTML, you will not find anything unusual in our code for our index.html file. We are creating a form where users can input their first name and last name and then click an “Add Name” button.

The form will do a post call to the /addname endpoint. We will be talking about endpoints and post later in this tutorial.

Displaying our Website to Users

We were previously displaying the text “Hello World” to users when they visited our website. Now we want to display our html file that we created. To do this we will need to change the app.use line our our app.js file.

We will be using the sendFile command to show the index.html file. We will need to tell the server exactly where to find the index.html file. We can do that by using a node global call __dirname. The __dirname will provide the current directly where the command was run. We will then append the path to our index.html file.

The app.use lines will need to be changed to
app.use("/", (req, res) => {   res.sendFile(__dirname + "/index.html"); });

Once you have saved your app.js file, we can test it by going to terminal and running node app.js

Open your browser and navigate to “http://localhost:3000”. You will see the following

Connecting to the Database

Now we need to add our database to the application. We will be connecting to a MongoDB database. I am assuming that you already have MongoDB installed and running on your computer.

To connect to the MongoDB database we are going to use a module called Mongoose. We will need to install mongoose module just like we did with express. Go to your terminal and enter the following command.
npm install mongoose --save

This will install the mongoose model and add it as a dependency in our package.json.

Connecting to the Database

Now that we have the mongoose module installed, we need to connect to the database in our app.js file. MongoDB, by default, runs on port 27017. You connect to the database by telling it the location of the database and the name of the database.

In our app.js file after the line for the port and before the app.use line, enter the following two lines to get access to mongoose and to connect to the database. For the database, I am going to use “node-demo”.

var mongoose = require("mongoose"); mongoose.Promise = global.Promise; mongoose.connect("mongodb://localhost:27017/node-demo");

Creating a Database Schema

Once the user enters data in the input field and clicks the add button, we want the contents of the input field to be stored in the database. In order to know the format of the data in the database, we need to have a Schema.

For this tutorial, we will need a very simple Schema that has only two fields. I am going to call the field firstName and lastName. The data stored in both fields will be a String.

After connecting to the database in our app.js we need to define our Schema. Here are the lines you need to add to the app.js.
var nameSchema = new mongoose.Schema({   firstName: String,   lastNameName: String });

Once we have built our Schema, we need to create a model from it. I am going to call my model “DataInput”. Here is the line you will add next to create our mode.
var User = mongoose.model("User", nameSchema);

Creating RESTful API

Now that we have a connection to our database, we need to create the mechanism by which data will be added to the database. This is done through our REST API. We will need to create an endpoint that will be used to send data to our server. Once the server receives this data then it will store the data in the database.

An endpoint is a route that our server will be listening to to get data from the browser. We already have one route that we have created already in the application and that is the route that is listening at the endpoint “/” which is the homepage of our application.

HTTP Verbs in a REST API

The communication between the client(the browser) and the server is done through an HTTP verb. The most common HTTP verbs are
GET, PUT, POST, and DELETE.

The following table explains what each HTTP verb does.

HTTP Verb Operation
GET Read
POST Create
PUT Update
DELETE Delete

As you can see from these verbs, they form the basis of CRUD operations that I talked about previously.

Building a CRUD endpoint

If you remember, the form in our index.html file used a post method to call this endpoint. We will now create this endpoint.

In our previous endpoint we used a “GET” http verb to display the index.html file. We are going to do something very similar but instead of using “GET”, we are going to use “POST”. To get started this is what the framework of our endpoint will look like.

app.post("/addname", (req, res) => {
 
});
Express Middleware

To fill out the contents of our endpoint, we want to store the firstName and lastName entered by the user into the database. The values for firstName and lastName are in the body of the request that we send to the server. We want to capture that data, convert it to JSON and store it into the database.

Express.js version 4 removed all middleware. To parse the data in the body we will need to add middleware into our application to provide this functionality. We will be using the body-parser module. We need to install it, so in your terminal window enter the following command.

npm install body-parser --save

Once it is installed, we will need to require this module and configure it. The configuration will allow us to pass the data for firstName and lastName in the body to the server. It can also convert that data into JSON format. This will be handy because we can take this formatted data and save it directly into our database.

To add the body-parser middleware to our application and configure it, we can add the following lines directly after the line that sets our port.

var bodyParser = require('body-parser');
app.use(bodyParser.json());
app.use(bodyParser.urlencoded({ extended: true }));
Saving data to database

Mongoose provides a save function that will take a JSON object and store it in the database. Our body-parser middleware, will convert the user’s input into the JSON format for us.

To save the data into the database, we need to create a new instance of our model that we created early. We will pass into this instance the user’s input. Once we have it then we just need to enter the command “save”.

Mongoose will return a promise on a save to the database. A promise is what is returned when the save to the database completes. This save will either finish successfully or it will fail. A promise provides two methods that will handle both of these scenarios.

If this save to the database was successful it will return to the .then segment of the promise. In this case we want to send text back the user to let them know the data was saved to the database.

If it fails it will return to the .catch segment of the promise. In this case, we want to send text back to the user telling them the data was not saved to the database. It is best practice to also change the statusCode that is returned from the default 200 to a 400. A 400 statusCode signifies that the operation failed.

Now putting all of this together here is what our final endpoint will look like.

app.post("/addname", (req, res) => {
  var myData = new User(req.body);
  myData.save()
    .then(item => {
      res.send("item saved to database");
    })
    .catch(err => {
      res.status(400).send("unable to save to database");
    });
});
Testing our code

Save your code. Go to your terminal and enter the command node app.js to start our server. Open up your browser and navigate to the URL “http://localhost:3000”. You will see our index.html file displayed to you.

Make sure you have mongo running.

Enter your first name and last name in the input fields and then click the “Add Name” button. You should get back text that says the name has been saved to the database like below.

Access to Code

The final version of the code is available in my Github repo. To access the code click here. Thank you for reading !

Node.js for Beginners - Learn Node.js from Scratch (Step by Step)

Node.js for Beginners - Learn Node.js from Scratch (Step by Step)

Node.js for Beginners - Learn Node.js from Scratch (Step by Step) - Learn the basics of Node.js. This Node.js tutorial will guide you step by step so that you will learn basics and theory of every part. Learn to use Node.js like a professional. You’ll learn: Basic Of Node, Modules, NPM In Node, Event, Email, Uploading File, Advance Of Node.

Node.js for Beginners

Learn Node.js from Scratch (Step by Step)

Welcome to my course "Node.js for Beginners - Learn Node.js from Scratch". This course will guide you step by step so that you will learn basics and theory of every part. This course contain hands on example so that you can understand coding in Node.js better. If you have no previous knowledge or experience in Node.js, you will like that the course begins with Node.js basics. otherwise if you have few experience in programming in Node.js, this course can help you learn some new information . This course contain hands on practical examples without neglecting theory and basics. Learn to use Node.js like a professional. This comprehensive course will allow to work on the real world as an expert!
What you’ll learn:

  • Basic Of Node
  • Modules
  • NPM In Node
  • Event
  • Email
  • Uploading File
  • Advance Of Node

Top 7 Most Popular Node.js Frameworks You Should Know

Top 7 Most Popular Node.js Frameworks You Should Know

Node.js is an open-source, cross-platform, runtime environment that allows developers to run JavaScript outside of a browser. In this post, you'll see top 7 of the most popular Node frameworks at this point in time (ranked from high to low by GitHub stars).

Node.js is an open-source, cross-platform, runtime environment that allows developers to run JavaScript outside of a browser.

One of the main advantages of Node is that it enables developers to use JavaScript on both the front-end and the back-end of an application. This not only makes the source code of any app cleaner and more consistent, but it significantly speeds up app development too, as developers only need to use one language.

Node is fast, scalable, and easy to get started with. Its default package manager is npm, which means it also sports the largest ecosystem of open-source libraries. Node is used by companies such as NASA, Uber, Netflix, and Walmart.

But Node doesn't come alone. It comes with a plethora of frameworks. A Node framework can be pictured as the external scaffolding that you can build your app in. These frameworks are built on top of Node and extend the technology's functionality, mostly by making apps easier to prototype and develop, while also making them faster and more scalable.

Below are 7of the most popular Node frameworks at this point in time (ranked from high to low by GitHub stars).

Express

With over 43,000 GitHub stars, Express is the most popular Node framework. It brands itself as a fast, unopinionated, and minimalist framework. Express acts as middleware: it helps set up and configure routes to send and receive requests between the front-end and the database of an app.

Express provides lightweight, powerful tools for HTTP servers. It's a great framework for single-page apps, websites, hybrids, or public HTTP APIs. It supports over fourteen different template engines, so developers aren't forced into any specific ORM.

Meteor

Meteor is a full-stack JavaScript platform. It allows developers to build real-time web apps, i.e. apps where code changes are pushed to all browsers and devices in real-time. Additionally, servers send data over the wire, instead of HTML. The client renders the data.

The project has over 41,000 GitHub stars and is built to power large projects. Meteor is used by companies such as Mazda, Honeywell, Qualcomm, and IKEA. It has excellent documentation and a strong community behind it.

Koa

Koa is built by the same team that built Express. It uses ES6 methods that allow developers to work without callbacks. Developers also have more control over error-handling. Koa has no middleware within its core, which means that developers have more control over configuration, but which means that traditional Node middleware (e.g. req, res, next) won't work with Koa.

Koa already has over 26,000 GitHub stars. The Express developers built Koa because they wanted a lighter framework that was more expressive and more robust than Express. You can find out more about the differences between Koa and Express here.

Sails

Sails is a real-time, MVC framework for Node that's built on Express. It supports auto-generated REST APIs and comes with an easy WebSocket integration.

The project has over 20,000 stars on GitHub and is compatible with almost all databases (MySQL, MongoDB, PostgreSQL, Redis). It's also compatible with most front-end technologies (Angular, iOS, Android, React, and even Windows Phone).

Nest

Nest has over 15,000 GitHub stars. It uses progressive JavaScript and is built with TypeScript, which means it comes with strong typing. It combines elements of object-oriented programming, functional programming, and functional reactive programming.

Nest is packaged in such a way it serves as a complete development kit for writing enterprise-level apps. The framework uses Express, but is compatible with a wide range of other libraries.

LoopBack

LoopBack is a framework that allows developers to quickly create REST APIs. It has an easy-to-use CLI wizard and allows developers to create models either on their schema or dynamically. It also has a built-in API explorer.

LoopBack has over 12,000 GitHub stars and is used by companies such as GoDaddy, Symantec, and the Bank of America. It's compatible with many REST services and a wide variety of databases (MongoDB, Oracle, MySQL, PostgreSQL).

Hapi

Similar to Express, hapi serves data by intermediating between server-side and client-side. As such, it's can serve as a substitute for Express. Hapi allows developers to focus on writing reusable app logic in a modular and prescriptive fashion.

The project has over 11,000 GitHub stars. It has built-in support for input validation, caching, authentication, and more. Hapi was originally developed to handle all of Walmart's mobile traffic during Black Friday.