# Fastify

You can use the AI SDK in a [Fastify](https://fastify.dev/) 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`:

```bash
curl -X POST http://localhost:8080
```

<Note>
  The examples use the Vercel AI Gateway. Ensure that your AI Gateway API key is
  set in the `AI_GATEWAY_API_KEY` environment variable.
</Note>

**Full example**: [github.com/vercel/ai/examples/fastify](https://github.com/vercel/ai/tree/main/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.

```ts filename='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.',
  });

  // 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.

```ts filename='index.ts' highlight="8-11,18"
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.

```ts filename='index.ts' highlight="15"
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](/docs/troubleshooting/streaming-not-working-when-proxied)


## Navigation

- [Node.js HTTP Server](/v5/cookbook/api-servers/node-http-server)
- [Express](/v5/cookbook/api-servers/express)
- [Hono](/v5/cookbook/api-servers/hono)
- [Fastify](/v5/cookbook/api-servers/fastify)
- [Nest.js](/v5/cookbook/api-servers/nest)


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