Fastify
You can use the AI SDK in a Fastify server to generate and stream text and objects to the client.
Examples
The examples start a simple HTTP server that listens on port 8080. You can e.g. test it using curl:
curl -X POST http://localhost:8080The examples use the Vercel AI Gateway. Ensure that your AI Gateway API key is
set in the AI_GATEWAY_API_KEY environment variable.
Full example: github.com/vercel/ai/examples/fastify
UI Message Stream
You can use the toUIMessageStream method to get a UI message stream from the result and then pipe it to the response.
index.ts
import { streamText } from 'ai';import Fastify from 'fastify';
const fastify = Fastify({ logger: true });
fastify.post('/', async function (request, reply) { const result = streamText({ model: 'openai/gpt-4o', prompt: 'Invent a new holiday and describe its traditions.', });
reply.header('Content-Type', 'text/plain; charset=utf-8');
return reply.send(result.toUIMessageStream());});
fastify.listen({ port: 8080 });Sending Custom Data
createUIMessageStream can be used to send custom data to the client.
index.ts
import { createUIMessageStream, streamText } from 'ai';import Fastify from 'fastify';
const fastify = Fastify({ logger: true });
fastify.post('/stream-data', async function (request, reply) { // immediately start streaming the response const stream = createUIMessageStream({ execute: async ({ writer }) => { writer.write({ type: 'start' });
writer.write({ type: 'data-custom', data: { custom: 'initialized call', }, });
const result = streamText({ model: 'openai/gpt-4o', prompt: 'Invent a new holiday and describe its traditions.', });
writer.merge(result.toUIMessageStream({ sendStart: false })); }, onError: error => { // Error messages are masked by default for security reasons. // If you want to expose the error message to the client, you can do so here: return error instanceof Error ? error.message : String(error); }, });
reply.header('Content-Type', 'text/plain; charset=utf-8');
return reply.send(stream);});
fastify.listen({ port: 8080 });Text Stream
You can use the textStream property to get a text stream from the result and then pipe it to the response.
index.ts
import { streamText } from 'ai';import Fastify from 'fastify';
const fastify = Fastify({ logger: true });
fastify.post('/', async function (request, reply) { const result = streamText({ model: 'openai/gpt-4o', prompt: 'Invent a new holiday and describe its traditions.', });
reply.header('Content-Type', 'text/plain; charset=utf-8');
return reply.send(result.textStream);});
fastify.listen({ port: 8080 });Troubleshooting
- Streaming not working when proxied