将Salesforce Einstein聊天机器人集成到使用Dot Net和Angular构建的网站中

using System;
using System.Net.Http;
using System.Threading.Tasks;

public class SalesforceClient
{
    private readonly HttpClient _httpClient;
    private readonly string _apiKey;
    private readonly string _apiEndpoint;

    public SalesforceClient(string apiKey, string apiEndpoint)
    {
        _httpClient = new HttpClient();
        _apiKey = apiKey;
        _apiEndpoint = apiEndpoint;
    }

    public async Task<string> PostMessageAsync(string message)
    {
        var content = new StringContent($"{{\"text\": \"{message}\"}}");
        content.Headers.ContentType = System.Net.Http.Headers.MediaTypeHeaderValue.Parse("application/json");
        var response = await _httpClient.PostAsync(_apiEndpoint, content);
        response.EnsureSuccessStatusCode();
        var responseBody = await response.Content.ReadAsStringAsync();
        return responseBody;
    }
}

import { Component } from '@angular/core';
import { SalesforceService } from './salesforce.service';

@Component({
  selector: 'app-chat',
  template: `
    <div *ngFor="let message of messages">
      <span>{{ message.sender }}: {{ message.text }}</span>
    </div>
    <input [(ngModel)]="userInput" (keyup.enter)="sendMessage()" />
  `
})
export class ChatComponent {
  messages: { sender: string, text: string }[] = [];
  userInput: string;

  constructor(private salesforceService: SalesforceService) {}

  sendMessage() {
    this.messages.push({ sender: 'User', text: this.userInput });
    this.salesforceService.postMessage(this.userInput).subscribe(response => {
      const botMessage = JSON.parse(response).result.fulfillment.speech;
      this.messages.push({ sender: 'Bot', text: botMessage });
    });
  }
}