File: fastify.md | Updated: 11/15/2025
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You can use the AI SDK in a Fastify server to generate and stream text and objects to the client.
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:8080
The examples use the OpenAI gpt-4o model. Ensure that the OpenAI API key is set in the OPENAI_API_KEY environment variable.
Full example: github.com/vercel/ai/examples/fastify
You can use the toDataStream method to get a data stream from the result and then pipe it to the response.
index.ts
import { openai } from '@ai-sdk/openai';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.', });
// Mark the response as a v1 data stream: reply.header('X-Vercel-AI-Data-Stream', 'v1'); reply.header('Content-Type', 'text/plain; charset=utf-8');
return reply.send(result.toDataStream({ data }));});
fastify.listen({ port: 8080 });
createDataStream can be used to send custom data to the client.
index.ts
import { openai } from '@ai-sdk/openai';import { createDataStream, 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 dataStream = createDataStream({ execute: async dataStreamWriter => { dataStreamWriter.writeData('initialized call');
const result = streamText({ model: openai('gpt-4o'), prompt: 'Invent a new holiday and describe its traditions.', });
result.mergeIntoDataStream(dataStreamWriter); }, 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); }, });
// Mark the response as a v1 data stream: reply.header('X-Vercel-AI-Data-Stream', 'v1'); reply.header('Content-Type', 'text/plain; charset=utf-8');
return reply.send(dataStream);});
fastify.listen({ port: 8080 });
You can use the textStream property to get a text stream from the result and then pipe it to the response.
index.ts
import { openai } from '@ai-sdk/openai';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 });
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