# Streaming responses from LLMs

**Author:** DX Team

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AI providers can be slow when producing responses, but many make their responses available in chunks as they're processed. Streaming enables you to show users those chunks of data as they arrive rather than waiting for the full response, improving the perceived speed of AI-powered apps.

**You can use** [**Vercel's AI SDK**](https://sdk.vercel.ai/docs) **to stream responses from LLMs and AI APIs**. It reduces the boilerplate necessary for streaming responses from AI providers and allows you to change AI providers with a few lines of code, rather than rewriting your entire application.

This example demonstrates a function that sends a message to one of OpenAI's GPT models and streams the response:

## Recipe

Before you begin, ensure you're using Node.js 18 or later.

1. Install the `ai` and `@ai-sdk/openai` packages:
   

`pnpm install ai @ai-sdk/openai`

1. Copy an OpenAI API key in the `.env.local` file with name `OPENAI_API_KEY`. See the [AI SDK docs](https://sdk.vercel.ai/docs/getting-started#configure-openai-api-key) for more information on how to do this
   
2. Add the following code to your example
   

`import { streamText } from 'ai'; import { openai } from '@ai-sdk/openai'; // This method must be named GET export async function GET() { // Make a request to OpenAI's API based on // a placeholder prompt const response = streamText({ model: openai('gpt-4o-mini'), messages: [{ role: 'user', content: 'Say this is a test.' }], }); // Respond with the stream return response.toTextStreamResponse({ headers: { 'Content-Type': 'text/event-stream', }, }); }` `import { streamText } from 'ai'; import { openai } from '@ai-sdk/openai'; // This method must be named GET export async function GET() { // Make a request to OpenAI's API based on // a placeholder prompt const response = streamText({ model: openai('gpt-4o-mini'), messages: [{ role: 'user', content: 'Say this is a test.' }], }); // Respond with the stream return response.toTextStreamResponse({ headers: { 'Content-Type': 'text/event-stream', }, }); }` `// Streaming Functions must be defined in an // app directory, even if the rest of your app // is in the pages directory. import { streamText } from 'ai'; import { openai } from '@ai-sdk/openai'; // This method must be named GET export async function GET() { // Make a request to OpenAI's API based on // a placeholder prompt const response = streamText({ model: openai('gpt-4o-mini'), messages: [{ role: 'user', content: 'Say this is a test.' }], }); // Respond with the stream return response.toTextStreamResponse({ headers: { 'Content-Type': 'text/event-stream', }, }); }` `// Streaming Functions must be defined in an // app directory, even if the rest of your app // is in the pages directory. import { streamText } from 'ai'; import { openai } from '@ai-sdk/openai'; // This method must be named GET export async function GET() { // Make a request to OpenAI's API based on // a placeholder prompt const response = streamText({ model: openai('gpt-4o-mini'), messages: [{ role: 'user', content: 'Say this is a test.' }], }); // Respond with the stream return response.toTextStreamResponse({ headers: { 'Content-Type': 'text/event-stream', }, }); }` `import { streamText } from 'ai'; import { openai } from '@ai-sdk/openai'; // This method must be named GET export async function GET() { // Make a request to OpenAI's API based on // a placeholder prompt const response = streamText({ model: openai('gpt-4o-mini'), messages: [{ role: 'user', content: 'Say this is a test.' }], }); // Respond with the stream return response.toTextStreamResponse({ headers: { 'Content-Type': 'text/event-stream', }, }); }` `import { streamText } from 'ai'; import { openai } from '@ai-sdk/openai'; // This method must be named GET export async function GET() { // Make a request to OpenAI's API based on // a placeholder prompt const response = streamText({ model: openai('gpt-4o-mini'), messages: [{ role: 'user', content: 'Say this is a test.' }], }); // Respond with the stream return response.toTextStreamResponse({ headers: { 'Content-Type': 'text/event-stream', }, }); }` 1. Build your app and visit `localhost:3000/api/chat-example`. You should see the text `"This is a test."` in the browser.     ## More resources - [Streaming on Vercel](/docs/fundamentals/what-is-streaming)
  
- [Vercel AI SDK](https://sdk.vercel.ai/docs)

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