@magicul/react-chat-stream

@magicul/react-chat-stream

Introducing @magicul/react-chat-stream: A React hook designed to simplify integrating chat streams returned by your backend. Let messages appear word-by-word similar to ChatGPT.

What's this package about?

Are you building a ChatGPT-like chat interface? Then most likely you'll want to integrate a chat that has the messages appear word-by-word, similar to ChatGPT. Vercel recently released the Vercel AI SDK which adds Streaming First UI Helper, but what if you want to integrate your own backend? This package solves exactly that pain point. We've abstracted the logic into a React Hook to take care of handling everything for you.

How does it work?

If you're backend returns text/event-stream then you can use this package. This package does not "fake" this response by imitating the word-by-word appearance. It will literally take the responses from your backend as them come in through the stream. The hook provides a messages object which will change so you can display it as the result gets delivered.

Installation

Install this package with npm

npm i @magicul/react-chat-stream

Or with yarn

yarn add @magicul/react-chat-stream

Stream chat-like messages from your backend to your React app (similar to ChatGPT).

With the useChatStream hook, you can easily integrate your own API to stream chat responses (text/event-stream). Responses from your backend will appear word-by-word to give it a ChatGPT-like user experience. The following example demonstrates how to use the hook to integrate your own API that streams the results.

Please note: Your API has to return text/event-stream.

import React from 'react';
import useChatStream from '@magicul/react-chat-stream';

function App() {
  const { messages, input, handleInputChange, handleSubmit } = useChatStream({
    options: {
      url: 'https://your-api-url',
      method: 'POST',
    },
    // This means that the user input will be sent as the body of the request with the key 'prompt'.
    method: {
      type: 'body',
      key: 'prompt',
    },
  });

  return (
    <div>
      {messages.map((message, index) => (
        <div key={message.id}>
          <p>
            {message.role}: {message.content}
          </p>
        </div>
      ))}
      <form onSubmit={handleSubmit}>
        <input type="text" onChange={handleInputChange} value={input} />
        <button type="submit">Send</button>
      </form>
    </div>
  );
}

export default App;

The useChatStream hook provides a variable named messages. This messages variable comes from the internal state of the hook. It contains the chat message reply received from your API. Messages are updated in real-time as the stream continues to receive messages. The messages variable will change and will get appended with new messages received from your backend.

Important: For this to work, your API must stream back the results of the AI model as parts of the string you want to display.

Endpoint Requirements

The API endpoint you provide to the hook must be able to handle the following:

• Accept a request with a JSON body or a request with a query string for the prompt.
• Respond with a event/text-stream event stream which contains the responses you would like to display.

API Reference

Input:

The input of the hook is a configuration object with the following properties:

options

• url: string - the URL of the API endpoint.
• method: 'GET' | 'POST' - the HTTP method to use.
• query: object (optional) - the query parameters to send with the request.
• headers: object (optional) - the headers to include in the request.
• body: object (optional) - the body of the request.

method

• type: 'body' | 'query' - where to include the user's input in the request.
• key: string - the key of the input in the request.

Output:

The output of this hook is an object with the following properties:

• messages: Array<ChatMessage> - an array of chat messages. Each message is an object with an id (can be used as a key in the loop), role ('bot' or 'user') and content ( the content of the message).
• input: string - the current user input, you can use this value as the form input value.
• handleInputChange: function - a function to handle the change event of the input field. Pass it to the onChange prop of your input field.
• handleSubmit: function - a function to handle the submit event of the form. Pass it to the onSubmit prop of your form.
• isLoading: boolean - a boolean indicating whether the request is in progress.

Examples

If you want to see a working example, check out the example folder for an example on how to use this package.

Important Notes:

For those utilizing Next.js version 13 or higher as the server-side rendering framework with React, it's crucial to incorporate the useChatStream hook within a client component. The need for this is driven by the hook's use of useState, which necessitates its operation within a client component.

Transforming a regular server component into a client component is a straightforward task. Simply add the following line at the top of your component file:

'use client';