Streaming

For long-lived responses — AI chat tokens, live feeds, progress updates — Mock Config gives you two dedicated factories: rest.sse for GET and rest.stream for POST. Both open a persistent connection and hand your resolver a client you push messages to over time, instead of returning a single response.

The required event-stream headers are set for you, so you only deal with sending data.

Server-Sent Events

Use rest.sse to stream over a GET request. The resolver receives a client with send and close.

rest.sse('/chat', ({ client }) => {
  client.send('Hello');
  client.send('world');
  client.close();
});

Each send pushes one message to the client. Call close when the stream is done.

Streaming Over POST

Use rest.stream when the client opens the stream with a POST request — for example, an AI chat that sends a prompt in the body and streams the answer back.

rest.stream<{ body: { prompt: string } }>('/chat', ({ request, client }) => {
  const words = ['Hello', 'from', 'the', 'mock'];

  words.forEach((word) => client.send(word));
  client.close();
});

The request body is available on request, so the streamed output can depend on the incoming prompt.

Streaming With Latency

To imitate tokens arriving over time, space out the send calls with setDelay. It returns a promise, so await it between messages.

rest.stream('/chat', async ({ client, setDelay }) => {
  const tokens = ['Hello', ' ', 'world'];

  for (const token of tokens) {
    client.send(token);
    await setDelay(200);
  }

  client.close();
});

Here each token is sent 200ms apart, similar to how an AI model streams its answer.

Event Metadata

send accepts an optional second argument to set the SSE event, id, and retry fields.

rest.sse('/notifications', ({ client }) => {
  client.send('New message', {
    event: 'message',
    id: '1',
    retry: 3000
  });

  client.close();
});

Use event to name the event type the client listens for, id to label the message, and retry to suggest a reconnection delay in milliseconds.