ChatGeneration Chat Completion

Generate Chat Completion

Previously, we were able to generate text and objects using either a single message prompt, a system prompt, or a combination of both of them. However, there may be times when you want to generate text based on a series of messages.

A chat completion allows you to generate text based on a series of messages. This series of messages can be any series of interactions between any number systems, but the most popular and relatable use case has been a series of messages that represent a conversation between a user and a model.

http://localhost:3000
User: How is it going?
Assistant: All good, how may I help you?
Why is the sky blue?
Send Message

Client

Let's create a simple conversation between a user and a model, and place a button that will call continueConversation.

app/page.tsx
'use client';
import { useState } from 'react';
import { Message, continueConversation } from './actions';
// Force the page to be dynamic and allow streaming responses up to 30 seconds
export const dynamic = 'force-dynamic';
export const maxDuration = 30;
export default function Home() {
const [conversation, setConversation] = useState<Message[]>([]);
const [input, setInput] = useState<string>('');
return (
<div>
<div>
{conversation.map((message, index) => (
<div key={index}>
{message.role}: {message.content}
</div>
))}
</div>
<div>
<input
type="text"
value={input}
onChange={event => {
setInput(event.target.value);
}}
/>
<button
onClick={async () => {
const { messages } = await continueConversation([
...conversation,
{ role: 'user', content: input },
]);
setConversation(messages);
}}
>
Send Message
</button>
</div>
</div>
);
}

Server

Now, let's implement the continueConversation function that will insert the user's message into the conversation and generate a response.

app/actions.ts
'use server';
import { generateText } from 'ai';
import { openai } from '@ai-sdk/openai';
export interface Message {
role: 'user' | 'assistant';
content: string;
}
export async function continueConversation(history: Message[]) {
'use server';
const { text } = await generateText({
model: openai('gpt-3.5-turbo'),
system: 'You are a friendly assistant!',
messages: history,
});
return {
messages: [
...history,
{
role: 'assistant' as const,
content: text,
},
],
};
}