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.

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 });

Sending Custom Data

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 });

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 { 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 });