chatbot using angular

Part 2:

Sample code snippet  :

import { Component } from '@angular/core';
import { HttpClient } from '@angular/common/http';

@Component({
  selector: 'app-chatbot',
  templateUrl: './chatbot.component.html',
  styleUrls: ['./chatbot.component.css']
})
export class ChatbotComponent {
  message: string;
  options = ['Option 1', 'Option 2', 'Option 3'];
  selectedOption: string;

  constructor(private http: HttpClient) {}

  ngOnInit() {
    this.message = 'What can I help you with today?';
  }

  sendMessage() {
    if (this.selectedOption) {
      // User selected an option
      this.http.post('http://my-api.com/chatbot', {
        option: this.selectedOption
      }).subscribe(response => {
        // Display response in chat window
        this.message = response.message;
      });
    } else {
      // User entered a message
      this.http.post('http://my-api.com/chatbot', {
        message: this.message
      }).subscribe(response => {
        // Display response in chat window and provide options
        this.message = response.message;
        this.options = response.options;
      });
    }
  }

  selectOption(option: string) {
    this.selectedOption = option;
  }
}

This component uses the Angular HttpClient module to make HTTP requests to a backend API, which can handle the chatbot logic and return responses based on the user's input. The `options` array provides a list of options for the user to choose from, which can be displayed as buttons or other UI elements in the chat window.

Part1:

To create a chatbot with default questions and options using Angular:

1. Create a new Angular project using the Angular CLI command: `ng new my-chatbot-project`.

2. Install the necessary dependencies, such as the Angular Material library, which provides UI components for building a chatbot interface: `ng add @angular/material`.

3. Define the chatbot interface using HTML and CSS, which can include a chat window, input box, and buttons for selecting options.

4. Create a component to handle the chatbot logic, which can include default questions and options. The component can use the Angular HttpClient module to make HTTP requests to a backend API or a third-party chatbot service.

5. Implement the chatbot logic using the component, which can include:

   - Displaying the default question when the chatbot is opened.
   - Detecting the user's input and sending it to the backend API or third-party service.
   - Receiving the response from the API or service and displaying it in the chat window.
   - Providing buttons or other UI elements for the user to select options, and sending those selections to the backend API or service.
   - Handling errors and displaying error messages if there are issues with the API or service.

6. Deploy the Angular application to a hosting service, such as Firebase or Heroku, so that users can access the chatbot through a URL.

1. Install the necessary packages:

   npm install botframework-webchat

2. Add the BotFrameworkWebChat module to your Angular app

3. import { BotFrameworkWebChatModule } from 'botframework-webchat';
   
   @NgModule({
     imports: [BotFrameworkWebChatModule],
     // ...
   })
   export class AppModule { }
   

    

4. Add the bot component to your app component

5. import { Component } from '@angular/core';
   
   @Component({
     selector: 'app-root',
     template: `
       
     `,
   })
   export class AppComponent {
     directLineToken = 'YOUR_DIRECT_LINE_TOKEN';
     userID = 'YOUR_USER_ID';
     username = 'YOUR_USERNAME';
   }
   

    

1. Customize the bot's default questions and options using the Bot Framework SDK.

Here is an example of how to create a simple bot with a default question and options:

 

const { ActivityHandler } = require('botbuilder');

class MyBot extends ActivityHandler {
    async onMessage(context) {
        const reply = { type: 'message' };
        switch (context.activity.text.toLowerCase()) {
            case 'hi':
                reply.text = 'Hello there! How can I assist you today?';
                reply.suggestedActions = {
                    actions: [
                        { type: 'imBack', title: 'Check account balance', value: 'Check account balance' },
                        { type: 'imBack', title: 'Make a transfer', value: 'Make a transfer' },
                        { type: 'imBack', title: 'Cancel transaction', value: 'Cancel transaction' }
                    ]
                };
                break;
            default:
                reply.text = 'I didn\'t understand. Could you please rephrase your request?';
                break;
        }
        await context.sendActivity(reply);
    }
}

module.exports.MyBot = MyBot;

In this example, the bot responds with a default question "Hello there! How can I assist you today?" and offers the user three options: "Check account balance", "Make a transfer", and "Cancel transaction". If the user types anything else, the bot responds with "I didn't understand. Could you please rephrase your request?".

You can then deploy your bot to a hosting service or integrate it with your own web application using the BotFrameworkWebChat component.

Note: This is just a simple example. Machine learning can be used to create more advanced chatbots that can learn from user interactions and provide more personalized responses.