API ServersFastify
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 = await 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.
index.ts
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 = await 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.
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 = await 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 });