React Chat - Integrate with AI Service
You can integrate DevExtreme Chat with various AI services, such as OpenAI, Azure OpenAI, Google Dialogflow, and Microsoft Bot Framework.
Review this demo for Azure OpenAI integration:
OpenAI
This help topic describes how to integrate Chat with OpenAI. You can find the full example code in the following GitHub repository:
Prerequisites and Installation
First, obtain an API key. Next, install OpenAI SDK:
jQuery
<head> <!-- ... --> <script type="module"> import OpenAI from "https://esm.sh/openai@4.73.1"; </script> </hea>
Angular
npm install openai
Vue
npm install openai
React
npm install openai
AI Configuration
Create an instance of OpenAI:
jQuery
const chatService = new OpenAI({ dangerouslyAllowBrowser: true, apiKey: "OPENAI_API_KEY", // insert your OpenAI API key });
Angular
import { OpenAI } from "openai"; export class AppService { chatService: OpenAI; OpenAIConfig = { dangerouslyAllowBrowser: true, apiKey: "OPENAI_API_KEY", // insert your OpenAI API key }; constructor() { this.chatService = new OpenAI(this.OpenAIConfig); } }
Vue
import { OpenAI } from 'openai'; const OpenAIConfig = { dangerouslyAllowBrowser: true, apiKey: 'OPEN_AI_KEY', // insert your OpenAI API key }; const chatService = new OpenAI(OpenAIConfig);
React
import { OpenAI } from "openai"; class AppService { chatService: OpenAI; OpenAIConfig = { dangerouslyAllowBrowser: true, apiKey: "OPENAI_API_KEY", // insert your OpenAI API key }; constructor() { this.chatService = new OpenAI(this.OpenAIConfig); } }
dangerouslyAllowBrowser: true
enables browser-side requests. This exposes the API key. For production, route requests through your backend.Implement a getAIResponse(messages)
function to call the OpenAI API for responses. Here, the incoming argument messages
is an array of { role: "user" | "assistant" | "system"; content: string }
objects.
jQuery
async function getAIResponse(messages) { const params = { messages, model: 'gpt-4o-mini', }; const response = await chatService.chat.completions.create(params); return response.choices[0].message?.content; }
Angular
async getAIResponse(messages: Array<{ role: "user" | "assistant" | "system"; content: string }>) { const params = { messages: messages.map(msg => ({ role: msg.role, content: msg.content })), model: 'gpt-4o-mini', }; const response = await this.chatService.chat.completions.create(params); const data = { choices: response.choices }; return data.choices[0].message?.content; }
Vue
const getAIResponse = async(messages: Array<{ role: 'user' | 'assistant' | 'system'; content: string }>) => { const params = { messages: messages.map(msg => ({ role: msg.role, content: msg.content })), model: 'gpt-4o-mini' }; const response = await chatService.chat.completions.create(params); return response.choices[0].message?.content; };
React
async getAIResponse(messages: { role: 'user' | 'assistant' | 'system'; content: string }[]): Promise<any> { const params = { messages: messages.map((msg) => ({ role: msg.role, content: msg.content, })), model: 'gpt-4o-mini', }; const response = await this.chatService.chat.completions.create(params); const data = { choices: response.choices }; return data.choices[0].message?.content; }
Chat Configuration
To synchronize Chat and OpenAI, declare the processMessageSending()
function. This function configures typingUsers, pushes the assistant message to the store, and renders the message.
jQuery
async function processMessageSending() { toggleDisabledState(true); instance.option({ typingUsers: [assistant] }); try { const aiResponse = await getAIResponse(messages); setTimeout(() => { instance.option({ typingUsers: [] }); messages.push({ role: 'assistant', content: aiResponse }); renderMessage(aiResponse); }, 200); } catch { instance.option({ typingUsers: [] }); alertLimitReached(); } finally { toggleDisabledState(false); } }
Angular
async processMessageSending() { this.toggleDisabledState(true); this.typingUsersSubject.next([this.assistant]); try { const aiResponse = await this.getAIResponse(this.messages); setTimeout(() => { this.typingUsersSubject.next([]); this.messages.push({ role: "assistant", content: aiResponse ?? "" }); this.renderAssistantMessage(aiResponse ?? ""); }, 200); } catch { this.typingUsersSubject.next([]); this.alertLimitReached(); } finally { this.toggleDisabledState(false); } }
Vue
const processMessageSending = async() => { toggleDisabledState(true); typingUsers.value = [assistant]; try { const aiResponse = await getAIResponse(messages.value); setTimeout(() => { typingUsers.value = []; messages.value.push({ role: 'assistant', content: aiResponse ?? '' }); renderAssistantMessage(aiResponse ?? ''); }, 200); } catch { typingUsers.value = []; alertLimitReached(); } finally { toggleDisabledState(false); } };
React
async processMessageSending(): Promise<void> { this.toggleDisabledState(true); this.typingUsersSubject.next([this.assistant]); try { const aiResponse = await this.getAIResponse(this.messages); setTimeout(() => { this.typingUsersSubject.next([]); this.messages.push({ role: 'assistant', content: aiResponse ?? '' }); this.renderAssistantMessage(aiResponse ?? ''); }, 200); } catch { this.typingUsersSubject.next([]); this.alertLimitReached(); } finally { this.toggleDisabledState(false); } }
Call processMessageSending()
after a user message is sent in the onMessageEntered event handler:
jQuery
const instance = $('#dx-ai-chat').dxChat({ // ... dataSource: customStore, reloadOnChange: false, onMessageEntered: (e) => { const { message } = e; customStore.push([{ type: 'insert', data: { id: Date.now(), ...message } }]); messages.push({ role: 'user', content: message.text }); processMessageSending(); } }).dxChat('instance');
Angular
async onMessageEntered({ message, event }: MessageEnteredEvent) { this.dataSource ?.store() .push([{ type: "insert", data: { id: Date.now(), ...message } }]); this.messages.push({ role: "user", content: message?.text ?? "" }); this.processMessageSending(); }
Vue
const onMessageEntered = async(e: MessageEnteredEvent) => { let { message } = e; dataSource.value?.store().push([{ type: 'insert', data: { id: Date.now(), ...message } }]); messages.value.push({ role: 'user', content: message?.text ?? '' }); await processMessageSending(); };
React
onMessageEntered({ message }: MessageEnteredEvent): void { this.dataSource ?.store() .push([{ type: 'insert', data: { id: Date.now(), ...message } }]); this.messages.push({ role: 'user', content: message?.text ?? '' }); void this.processMessageSending(); }
You can also implement additional UI capabilities to further improve user experience:
- Add a Markdown converter for assistant outputs. For more information, refer to the Markdown Support help topic.
- Define a messageTemplate for the assistant’s responses and add two buttons: copy and regenerate response. See the example code in the GitHub repository:
If you have technical questions, please create a support ticket in the DevExpress Support Center.