Chat completion can sometimes take a long time to finish, especially when the response is big. In such cases, it is useful to stream the chat completion to the client in real-time. This allows the client to display the new message as it is being generated by the model, rather than have users wait for it to finish.
Let's create a React component that imports the useChat
hook from the ai/react
module. The useChat
hook will call the /api/chat
endpoint when the user sends a message. The endpoint will generate the assistant's response based on the conversation history and stream it to the client.
'use client';
import { useChat } from 'ai/react';
export default function Page() { const { messages, input, setInput, append } = useChat();
return ( <div> <input value={input} onChange={event => { setInput(event.target.value); }} onKeyDown={async event => { if (event.key === 'Enter') { append({ content: input, role: 'user' }); } }} />
{messages.map((message, index) => ( <div key={index}>{message.content}</div> ))} </div> );}
Next, let's create the /api/chat
endpoint that generates the assistant's response based on the conversation history.
import { CoreMessage, streamText } from 'ai';import { openai } from '@ai-sdk/openai';
export async function POST(req: Request) { const { messages }: { messages: CoreMessage[] } = await req.json();
const result = streamText({ model: openai('gpt-4'), system: 'You are a helpful assistant.', messages, });
return result.toDataStreamResponse();}