Streaming

curl -X POST https://www.draftify.site/api/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_DRAFTIFY_API_KEY" \
  -d '{
    "model": "sonnet-4.6-level",
    "stream": true,
    "messages": [
      {
        "role": "user",
        "content": "Write a long story about a robot."
      }
    ]
  }'

### Node.js Example

const response = await fetch('https://www.draftify.site/api/v1/chat/completions', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': `Bearer ${process.env.DRAFTIFY_API_KEY}`,
  },
  body: JSON.stringify({
    model: 'sonnet-4.6-level',
    stream: true,
    messages: [{ role: 'user', content: 'Write a long story about a robot.' }]
  }),
});

const reader = response.body.getReader();
const decoder = new TextDecoder();

while (true) {
  const { done, value } = await reader.read();
  if (done) break;

  const chunk = decoder.decode(value, { stream: true });
  console.log(chunk);
}
──────
## Understanding the Stream Format

When streaming is enabled, the API will respond with a continuous stream of text chunks. Each event begins with  data:   and        
contains a stringified JSON object.

A typical stream chunk looks like this:

data: {"choices": [{"index": 0, "delta": {"content": "Hello"}}]}

The very last event in the stream will always be:

data: [DONE]
──────
## Vercel AI SDK Integration

Because the Draftify API strictly follows the standard OpenAI Chat Completions format, it works out-of-the-box with popular
frameworks like the Vercel AI SDK.

You can use the  @ai-sdk/openai  provider and just override the  baseURL  to point to Draftify:

import { createOpenAI } from '@ai-sdk/openai';
import { streamText } from 'ai';

const draftify = createOpenAI({
  baseURL: 'https://www.draftify.site/api/v1',
  apiKey: process.env.DRAFTIFY_API_KEY,
});

export async function POST(req) {
  const { messages } = await req.json();

  const result = await streamText({
    model: draftify('opus-4.8-level'),
    messages,
  });

  return result.toDataStreamResponse();
}