Streaming Custom Data

It is often useful to send additional data alongside the model's response. For example, you may want to send status information, the message ids after storing them, or references to content that the language model is referring to.

The AI SDK provides several helpers that allows you to stream additional data to the client and attach it to the UIMessage parts array:

  • createUIMessageStream: creates a data stream
  • createUIMessageStreamResponse: creates a response object that streams data
  • pipeUIMessageStreamToResponse: pipes a data stream to a server response object

The data is streamed as part of the response stream using Server-Sent Events.

Setting Up Type-Safe Data Streaming

First, define your custom message type with data part schemas for type safety:

ai/types.ts
import { UIMessage } from 'ai';
// Define your custom message type with data part schemas
export type MyUIMessage = UIMessage<
never, // metadata type
{
weather: {
city: string;
weather?: string;
status: 'loading' | 'success';
};
notification: {
message: string;
level: 'info' | 'warning' | 'error';
};
} // data parts type
>;

Streaming Data from the Server

In your server-side route handler, you can create a UIMessageStream and then pass it to createUIMessageStreamResponse:

route.ts
import { openai } from '@ai-sdk/openai';
import {
createUIMessageStream,
createUIMessageStreamResponse,
streamText,
convertToModelMessages,
} from 'ai';
import { MyUIMessage } from '@/ai/types';
export async function POST(req: Request) {
const { messages } = await req.json();
const stream = createUIMessageStream<MyUIMessage>({
execute: ({ writer }) => {
// 1. Send initial status (transient - won't be added to message history)
writer.write({
type: 'data-notification',
data: { message: 'Processing your request...', level: 'info' },
transient: true, // This part won't be added to message history
});
// 2. Send sources (useful for RAG use cases)
writer.write({
type: 'source',
value: {
type: 'source',
sourceType: 'url',
id: 'source-1',
url: 'https://weather.com',
title: 'Weather Data Source',
},
});
// 3. Send data parts with loading state
writer.write({
type: 'data-weather',
id: 'weather-1',
data: { city: 'San Francisco', status: 'loading' },
});
const result = streamText({
model: openai('gpt-4.1'),
messages: convertToModelMessages(messages),
onFinish() {
// 4. Update the same data part (reconciliation)
writer.write({
type: 'data-weather',
id: 'weather-1', // Same ID = update existing part
data: {
city: 'San Francisco',
weather: 'sunny',
status: 'success',
},
});
// 5. Send completion notification (transient)
writer.write({
type: 'data-notification',
data: { message: 'Request completed', level: 'info' },
transient: true, // Won't be added to message history
});
},
});
writer.merge(result.toUIMessageStream());
},
});
return createUIMessageStreamResponse({ stream });
}

You can also send stream data from custom backends, e.g. Python / FastAPI, using the UI Message Stream Protocol.

Types of Streamable Data

Data Parts (Persistent)

Regular data parts are added to the message history and appear in message.parts:

writer.write({
type: 'data-weather',
id: 'weather-1', // Optional: enables reconciliation
data: { city: 'San Francisco', status: 'loading' },
});

Sources

Sources are useful for RAG implementations where you want to show which documents or URLs were referenced:

writer.write({
type: 'source',
value: {
type: 'source',
sourceType: 'url',
id: 'source-1',
url: 'https://example.com',
title: 'Example Source',
},
});

Transient Data Parts (Ephemeral)

Transient parts are sent to the client but not added to the message history. They are only accessible via the onData useChat handler:

// server
writer.write({
type: 'data-notification',
data: { message: 'Processing...', level: 'info' },
transient: true, // Won't be added to message history
});
// client
const [notification, setNotification] = useState();
const { messages } = useChat({
onData: ({ data, type }) => {
if (type === 'data-notification') {
setNotification({ message: data.message, level: data.level });
}
},
});

Data Part Reconciliation

When you write to a data part with the same ID, the client automatically reconciles and updates that part. This enables powerful dynamic experiences like:

  • Collaborative artifacts - Update code, documents, or designs in real-time
  • Progressive data loading - Show loading states that transform into final results
  • Live status updates - Update progress bars, counters, or status indicators
  • Interactive components - Build UI elements that evolve based on user interaction

The reconciliation happens automatically - simply use the same id when writing to the stream.

Processing Data on the Client

Using the onData Callback

The onData callback is essential for handling streaming data, especially transient parts:

page.tsx
import { useChat } from '@ai-sdk/react';
import { MyUIMessage } from '@/ai/types';
const { messages } = useChat<MyUIMessage>({
api: '/api/chat',
onData: dataPart => {
// Handle all data parts as they arrive (including transient parts)
console.log('Received data part:', dataPart);
// Handle different data part types
if (dataPart.type === 'data-weather') {
console.log('Weather update:', dataPart.data);
}
// Handle transient notifications (ONLY available here, not in message.parts)
if (dataPart.type === 'data-notification') {
showToast(dataPart.data.message, dataPart.data.level);
}
},
});

Important: Transient data parts are only available through the onData callback. They will not appear in the message.parts array since they're not added to message history.

Rendering Persistent Data Parts

You can filter and render data parts from the message parts array:

page.tsx
const result = (
<>
{messages?.map(message => (
<div key={message.id}>
{/* Render weather data parts */}
{message.parts
.filter(part => part.type === 'data-weather')
.map((part, index) => (
<div key={index} className="weather-widget">
{part.data.status === 'loading' ? (
<>Getting weather for {part.data.city}...</>
) : (
<>
Weather in {part.data.city}: {part.data.weather}
</>
)}
</div>
))}
{/* Render text content */}
{message.parts
.filter(part => part.type === 'text')
.map((part, index) => (
<div key={index}>{part.text}</div>
))}
{/* Render sources */}
{message.parts
.filter(part => part.type === 'source')
.map((part, index) => (
<div key={index} className="source">
Source: <a href={part.url}>{part.title}</a>
</div>
))}
</div>
))}
</>
);

Complete Example

page.tsx
'use client';
import { useChat } from '@ai-sdk/react';
import { useState } from 'react';
import { MyUIMessage } from '@/ai/types';
export default function Chat() {
const [input, setInput] = useState('');
const { messages, sendMessage } = useChat<MyUIMessage>({
api: '/api/chat',
onData: dataPart => {
// Handle transient notifications
if (dataPart.type === 'data-notification') {
console.log('Notification:', dataPart.data.message);
}
},
});
const handleSubmit = (e: React.FormEvent) => {
e.preventDefault();
sendMessage({ text: input });
setInput('');
};
return (
<>
{messages?.map(message => (
<div key={message.id}>
{message.role === 'user' ? 'User: ' : 'AI: '}
{/* Render weather data */}
{message.parts
.filter(part => part.type === 'data-weather')
.map((part, index) => (
<span key={index} className="weather-update">
{part.data.status === 'loading' ? (
<>Getting weather for {part.data.city}...</>
) : (
<>
Weather in {part.data.city}: {part.data.weather}
</>
)}
</span>
))}
{/* Render text content */}
{message.parts
.filter(part => part.type === 'text')
.map((part, index) => (
<div key={index}>{part.text}</div>
))}
</div>
))}
<form onSubmit={handleSubmit}>
<input
value={input}
onChange={e => setInput(e.target.value)}
placeholder="Ask about the weather..."
/>
<button type="submit">Send</button>
</form>
</>
);
}

Use Cases

  • RAG Applications - Stream sources and retrieved documents
  • Real-time Status - Show loading states and progress updates
  • Collaborative Tools - Stream live updates to shared artifacts
  • Analytics - Send usage data without cluttering message history
  • Notifications - Display temporary alerts and status messages

Message Metadata vs Data Parts

Both message metadata and data parts allow you to send additional information alongside messages, but they serve different purposes:

Message Metadata

Message metadata is best for message-level information that describes the message as a whole:

  • Attached at the message level via message.metadata
  • Sent using the messageMetadata callback in toUIMessageStreamResponse
  • Ideal for: timestamps, model info, token usage, user context
  • Type-safe with custom metadata types
// Server: Send metadata about the message
return result.toUIMessageStreamResponse({
messageMetadata: ({ part }) => {
if (part.type === 'finish') {
return {
model: part.response.modelId,
totalTokens: part.totalUsage.totalTokens,
createdAt: Date.now(),
};
}
},
});

Data Parts

Data parts are best for streaming dynamic arbitrary data:

  • Added to the message parts array via message.parts
  • Streamed using createUIMessageStream and writer.write()
  • Can be reconciled/updated using the same ID
  • Support transient parts that don't persist
  • Ideal for: dynamic content, loading states, interactive components
// Server: Stream data as part of message content
writer.write({
type: 'data-weather',
id: 'weather-1',
data: { city: 'San Francisco', status: 'loading' },
});

For more details on message metadata, see the Message Metadata documentation.