Craft AI-driven interfaces effortlessly.
Changelog Β· Report Bug Β· Request Feature Β· English Β· δΈζ
- π Derived from Best Practices of Enterprise-Level AI Products: Built on the RICH interaction paradigm, delivering an exceptional AI interaction experience.
- 𧩠Flexible and Diverse Atomic Components: Covers most AI dialogue scenarios, empowering you to quickly build personalized AI interaction interfaces.
- β‘ Out-of-the-Box Model Integration: Easily connect with inference services compatible with OpenAI standards.
- π Efficient Management of Conversation Data Flows: Provides powerful tools for managing data flows, enhancing development efficiency.
- π¦ Rich Template Support: Offers multiple templates for quickly starting LUI application development.
- π‘ Complete TypeScript Support: Developed with TypeScript, ensuring robust type coverage to improve the development experience and reliability.
- π¨ Advanced Theme Customization: Supports fine-grained style adjustments to meet diverse use cases and personalization needs.
npm install @ant-design/x --save
yarn add @ant-design/x
pnpm add @ant-design/x
Add script
and link
tags in your browser and use the global variable antd
.
We provide antdx.js
, antdx.min.js
, and antdx.min.js.map
in the dist directory of the npm package.
Based on the RICH interaction paradigm, we provide numerous atomic components for various stages of interaction to help you flexibly build your AI dialogue applications:
- General:
Bubble
- Message bubble,Conversations
- Conversation management - Wake-Up:
Welcome
- Welcome messages,Prompts
- Prompt sets - Expression:
Sender
- Input box,Attachment
- Attachments,Suggestion
- Quick commands - Confirmation:
ThoughtChain
- Thought chains
Below is an example of using atomic components to create a simple chatbot interface:
import React from 'react';
import {
// Message bubble
Bubble,
// Input box
Sender,
} from '@ant-design/x';
const messages = [
{
content: 'Hello, Ant Design X!',
role: 'user',
},
];
const App = () => (
<div>
<Bubble.List items={messages} />
<Sender />
</div>
);
export default App;
With the useXAgent
runtime tool, we make it easy to connect with model inference services that adhere to OpenAI standards.
Hereβs an example of using useXAgent
:
import React from 'react';
import { useXAgent, Sender } from '@ant-design/x';
const App = () => {
const [agent] = useXAgent({
// Model inference service URL
baseURL: 'https://your.api.host',
// Model name
model: 'gpt-3.5',
});
function chatRequest(text: string) {
agent.request({
// Message
messages: [
{
content: text,
role: 'user',
},
],
// Enable streaming
stream: true,
});
}
return <Sender onSubmit={chatRequest} />;
};
export default App;
Using the useXChat
runtime tool, you can easily manage data flows in AI dialogue applications:
import React from 'react';
import { useXChat, useXAgent } from '@ant-design/x';
const App = () => {
const [agent] = useXAgent({
// Model inference service URL
baseURL: 'https://your.api.host',
// Model name
model: 'gpt-3.5',
});
const {
// Initiate a chat request
onRequest,
// Message list
messages,
} = useXChat({ agent });
return (
<div>
<Bubble.List items={messages} />
<Sender onSubmit={onRequest} />
</div>
);
};
export default App;
@ant-design/x
supports ES modules tree shaking by default.
@ant-design/x
provides a built-in ts definition.
Welcome to contribute!
Ant Design X is widely used in AI-driven user interfaces within Ant Group. If your company and products use Ant Design X, feel free to leave a comment here.
Please read our CONTRIBUTING.md first.
If you'd like to help us improve antd, just create a Pull Request. Feel free to report bugs and issues here.
If you're new to posting issues, we ask that you read How To Ask Questions The Smart Way and How to Ask a Question in Open Source Community and How to Report Bugs Effectively prior to posting. Well written bug reports help us help you!
If you encounter any issues while using Ant Design X, you can seek help through the following channels. We also encourage experienced users to assist newcomers via these platforms.
When asking questions on GitHub Discussions, it's recommended to use the Q&A
tag.