AI
streaming

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: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

Data Stream

You can use the toDataStream method to get a data stream from the result and then pipe it to the response.

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 });

Data Stream With Stream Data

toDataStream can be used with StreamData to send additional data to the client.

import { openai } from '@ai-sdk/openai';
import { StreamData, streamText } from 'ai';
import Fastify from 'fastify';


const fastify = Fastify({ logger: true });


fastify.post('/', async function (request, reply) {
  // use stream data (optional):
  const data = new StreamData();
  data.append('initialized call');


  const result = streamText({
    model: openai('gpt-4o'),
    prompt: 'Invent a new holiday and describe its traditions.',
    onFinish() {
      data.append('call completed');
      data.close();
    },
  });


  // 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 });

Text Stream

You can use the textStream property to get a text stream from the result and then pipe it to the response.

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 });