AI SDK UICompletion

Completion

The useCompletion hook allows you to create a user interface to handle text completions in your application. It enables the streaming of text completions from your AI provider, manages the state for chat input, and updates the UI automatically as new messages are received.

In this guide, you will learn how to use the useCompletion hook in your application to generate text completions and stream them in real-time to your users.

Example

app/page.tsx
'use client';
import { useCompletion } from 'ai/react';
export default function Page() {
const { completion, input, handleInputChange, handleSubmit } = useCompletion({
api: '/api/completion',
});
return (
<form onSubmit={handleSubmit}>
<input
name="prompt"
value={input}
onChange={handleInputChange}
id="input"
/>
<button type="submit">Submit</button>
<div>{completion}</div>
</form>
);
}
app/api/completion/route.ts
import { StreamingTextResponse, experimental_streamText } from 'ai';
import { openai } from '@ai-sdk/openai';
export async function POST(req: Request) {
const { prompt }: { prompt: string } = await req.json();
const result = await experimental_streamText({
model: openai('gpt-3.5-turbo'),
prompt,
});
return new StreamingTextResponse(result.toAIStream());
}

In the Page component, the useCompletion hook will request to your AI provider endpoint whenever the user submits a message. The completion is then streamed back in real-time and displayed in the UI.

This enables a seamless text completion experience where the user can see the AI response as soon as it is available, without having to wait for the entire response to be received.

Customized UI

useCompletion also provides ways to manage the prompt via code, show loading and error states, and update messages without being triggered by user interactions.

Loading and error states

To show a loading spinner while the chatbot is processing the user's message, you can use the isLoading state returned by the useCompletion hook:

const { isLoading, ... } = useCompletion()
return(
<>
{isLoading ? <Spinner /> : null}
</>
)

Similarly, the error state reflects the error object thrown during the fetch request. It can be used to display an error message, or show a toast notification:

const { error, ... } = useCompletion()
useEffect(() => {
if (error) {
toast.error(error.message)
}
}, [error])
// Or display the error message in the UI:
return (
<>
{error ? <div>{error.message}</div> : null}
</>
)

Controlled input

In the initial example, we have handleSubmit and handleInputChange callbacks that manage the input changes and form submissions. These are handy for common use cases, but you can also use uncontrolled APIs for more advanced scenarios such as form validation or customized components.

The following example demonstrates how to use more granular APIs like setInput with your custom input and submit button components:

const { input, setInput } = useCompletion();
return (
<>
<MyCustomInput value={input} onChange={value => setInput(value)} />
</>
);

Cancelation

It's also a common use case to abort the response message while it's still streaming back from the AI provider. You can do this by calling the stop function returned by the useCompletion hook.

const { stop, isLoading, ... } = useCompletion()
return (
<>
<button onClick={stop} disabled={!isLoading}>Stop</button>
</>
)

When the user clicks the "Stop" button, the fetch request will be aborted. This avoids consuming unnecessary resources and improves the UX of your application.

Event Callbacks

useCompletion also provides optional event callbacks that you can use to handle different stages of the chatbot lifecycle. These callbacks can be used to trigger additional actions, such as logging, analytics, or custom UI updates.

const { ... } = useCompletion({
onResponse: (response: Response) => {
console.log('Received response from server:', response)
},
onFinish: (message: Message) => {
console.log('Finished streaming message:', message)
},
onError: (error: Error) => {
console.error('An error occurred:', error)
},
})

It's worth nothing that you can abort the processing by throwing an error in the onResponse callback. This will trigger the onError callback and stop the message from being appended to the chat UI. This can be useful for handling unexpected responses from the AI provider.

Configure Request Options

By default, the useCompletion hook sends a HTTP POST request to the /api/completion endpoint with the prompt as part of the request body. You can customize the request by passing additional options to the useCompletion hook:

const { messages, input, handleInputChange, handleSubmit } = useCompletion({
api: '/api/custom-completion',
headers: {
Authorization: 'your_token',
},
body: {
user_id: '123',
},
credentials: 'same-origin',
});

In this example, the useCompletion hook sends a POST request to the /api/completion endpoint with the specified headers, additional body fields, and credentials for that fetch request. On your server side, you can handle the request with these additional information.