Stream Text with Image Prompt

Vision models such as GPT-4 can process both text and images. In this example, we will show you how to send an image URL along with the user's message to the model.

Using Image URLs

Server

We split the user's message into two parts: the text and the image URL. We then send both parts to the model. The last message is the user's message, and we add the image URL to it.

app/api/chat/route.ts
import { openai } from '@ai-sdk/openai';
import { streamText } from 'ai';
export const maxDuration = 60;
export async function POST(req: Request) {
// 'data' contains the additional data that you have sent:
const { messages, data } = await req.json();
const initialMessages = messages.slice(0, -1);
const currentMessage = messages[messages.length - 1];
// Call the language model
const result = streamText({
model: openai('gpt-4-turbo'),
messages: [
...initialMessages,
{
role: 'user',
content: [
{ type: 'text', text: currentMessage.content },
{ type: 'image', image: new URL(data.imageUrl) },
],
},
],
});
// Respond with the stream
return result.toDataStreamResponse();
}

Client

On the client we can send the image URL along with the user's message by adding the data object to the handleSubmit function. You can replace the imageUrl with the actual URL of the image you want to send.

app/page.tsx
'use client';
import { useChat } from 'ai/react';
// Allow streaming responses up to 30 seconds
export const maxDuration = 30;
export default function Chat() {
const { messages, input, handleInputChange, handleSubmit } = useChat();
return (
<div>
{messages.map(m => (
<div key={m.id}>
{m.role === 'user' ? 'User: ' : 'AI: '}
{m.content}
</div>
))}
<form
onSubmit={e => {
handleSubmit(e, {
data: { imageUrl: 'https://somewhere.com/image.png' },
});
}}
>
<input
value={input}
placeholder="What does the image show..."
onChange={handleInputChange}
/>
</form>
</div>
);
}