Chatbot_AWS_LEX

A Basic chatbot using AWS Lex Service. This demo bot provides address for a given pincode that is provided by the user on the chat.

Terminologies

Intent – An intent represents an action that the user wants to perform. You create a bot to support one or more related intents. For example, you might create a bot that orders pizza. We have to provice a descriptive name for the intent called Intent name. For example, OrderPizza. Intent names must be unique within your account.
Sample utterances – How a user might convey the intent. For example, a user might say "Can I order a pizza please" or "I want to order a pizza".
Fulfillment – How you want to fulfill the intent after the user provides the necessary information (for example, place order with a local pizza shop). We recommend that you create a Lambda function to fulfill the intent.
Slot – An intent can require zero or more slots or parameters. For example, the OrderPizza intent requires slots such as pizza size, crust type, and number of pizzas. For example, you might create and use the following slot types for the OrderPizza intent:

Size – With enumeration values Small, Medium, and Large.
Crust – With enumeration values Thick and Thin.
Count - Amazon Lex also provides built-in slot types. For example, AMAZON.NUMBER is a built-in slot type that you can use for the number of pizzas ordered.

Setting up AWS in Windows system

Go to Servces -> IAM , Create an IAM user and attach policy AdministratorAccess. Go to Security Credentials Tab and create Access key
Create profile in our Windows System. Go to Users root directory (type %USERPROFILE%). Create folder .aws.. Add file credentials

[default]
aws_access_key_id = XXXXXXXXXXXXXXXXXXXXXX
aws_secret_access_key = YYYYYYYYYYYYYYYYYY

The project has 3 steps :

Step 1 (a): Create AWS Lex Chatbot

Step 1 (a)

Go to Services -> Amazon Lex
Select Version 1, Go to Bots -> Create Bot -> Choose Custom Bot
Add a Bot name ( eg: GetAddress), Language, Output voice as None -Text, Session timeout, IAM role etc.
Create Intent -> Add a name (eg: Address)
Add Sample Utterances (eg: Tell me the address, What is the address for the pincode {Pincode})
Add slots - Name(eg: Pincode) , Slot type (eg: AMAZON.NUMBER), Prompt (eg: Sure, what is the Pincode)
Add Fulfillment - Select Return parameters to client for now. We will create a lambda function and add it to this in Step 1 (b)

Step 1 (b): Update Lex Fulfillment to use the Lambda function we create in Step 2

Go to the Lex Bot created
Choose Fulfillment as AWS Lambda function, Add Lambda function as the created one in Step 2 (here PostalAddress)
Save the Intent, Build and Test the Bot
Publish the bot, give an alias name (eg: AddressBotVone)

Step 2: Create Lambda function

This function is used to fetch postal addresses baed on a Pincode. I have used a public postalpincode API.

This is a AWS Lambda (Serverless Functions). AWS Lambda can be plugged into Amzon Lex Intent to act on it.

To create Lamda project, AWS Toolkit for Visual Studio is and Lambda Project (.NET Core) is created . AWS Nuget Packages Amazon.Lambda.Core, Amazon.Lambda.LexEvents and Amazon.Lambda.Serialization.Json have been used for Lambda functionality.

    public async Task<LexResponse> FunctionHandler(LexEvent lexEvent, ILambdaContext context)
    {
        string pincode = lexEvent.CurrentIntent.Slots["Pincode"];
        var responseContent = "";
        var lexResponse = new LexResponse();
        lexResponse.DialogAction = new LexResponse.LexDialogAction
        {
            Type = "Close",
            FulfillmentState = "Fulfilled",
            Message = new LexResponse.LexMessage
            {
                ContentType = "PlainText",
                Content = ""
            }
        };

        var client = new HttpClient();
        var request = new HttpRequestMessage
        {
            Method = HttpMethod.Get,
            RequestUri = new Uri("https://api.postalpincode.in/pincode/" + pincode),
        };
        using (var response = await client.SendAsync(request))
        {
            response.EnsureSuccessStatusCode();
            var body = await response.Content.ReadAsStringAsync();
            var result = JsonSerializer.Deserialize<List<PostalAddress>>(body);
            var postoffices = result.FirstOrDefault().PostOffice.ToList();
            if (postoffices.Count > 0)
            {
                var postalInfo = postoffices[0];
                responseContent = "Post Offices : " + string.Join(", ", postoffices.Select(x => x.Name).ToList())
                    + ", " + "District : " + postalInfo.District
                    + ", " + "State : " + postalInfo.State
                    + ", " + "Country : " + postalInfo.Country
                    + ", " + "Pincode : " + postalInfo.Pincode;
            }
            else
            {
                responseContent = "No records found.";
            }
        }

        lexResponse.DialogAction.Message.Content = responseContent;
        return lexResponse;
    }

Uploading Lambda Function

Right-Click on Project node and then choosing Publish to AWS Lambda.
In the Upload Lambda Function window, enter a name for the function, or select a previously published function to republish.
Set Handler as "Assembly::Namespace.Class::Function"
Set other details like IAM Role, Memory etc. and upload
Test the Lambda function in AWS Console

Step 3: Create an Angular UI for the chat functionality

Initialisation

Install AWS-SDK that gives type definitions for node.

npm install aws-sdk

Use the type definitions in tsconfig.app.json file

"types": ["node"]

Global needs to be defined in the polyfill.ts file

(window as any).global = window;

Adding Credentials

Add IAM accessKeyId and secretAccessKey in environment.ts

export const environment = {
  accessKeyId: "XXXXXXXXXXXXXXXXXXXXXX",
  secretAccessKey: "YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY",
  region: "us-xxxx-1",
  botAlias: 'AddressBotVone', 
  botName: 'GetAddress'
};

Generate the Component