Quickstart - Draftify Documentation

Start using the Draftify API in seconds and integrate our powerful reasoning AI models into your applications.

The Draftify API allows you to easily integrate the smartest AI models available on our
platform (such as opus-4.8-level, opus 4.6-level, opus 4.7-level fable-5-level, or sonnet-4.6-level) directly into
your own software. This quickstart guide will walk you through the initial setup and show you how to make
your very first API request.

Prerequisites

Before you begin, you must have:

An active Draftify account (From Free plan) - A Draftify API Key (you can generate this in your Dashboard under Settings > API
Keys). - Node.js (v18+) or Python (v3.8+) installed, depending on your preferred development
environment. Note: Your subscription plan (Free, Pro, or Scale) does not restrict API access, but it does determine your maximum context limit (e.g., up to 10,000,000 characters for Scale
users).

Get started

Get your API Key

Log into your Draftify account, navigate to the Dashboard, and create a new API key.
You will need to include this key in the headers of your HTTP requests (Authorization: Bearer <TOKEN>).Tip: Never share your API key publicly and always keep it secure in environment
variables (e.g., in a .env file)!

Your first request (cURL)

The fastest way to test the API is by making a request from your terminal. Send a
simple message to the sonnet-4.6-level model:

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",
    "messages": [
      {
        "role": "user",
        "content": "Hello! Are you capable of reasoning?"
      }
    ]
  }'

Use it in Python

If you are working with Python, you can use the built-in requests library to send
your prompts.

Python

import requests
import os

api_key = os.getenv("DRAFTIFY_API_KEY")
url = "https://www.draftify.site/api/v1/chat/completions"

headers = {
    "Authorization": f"Bearer {api_key}",
    "Content-Type": "application/json"
}

data = {
    "model": "fable-5-level",
    "messages": [{"role": "user", "content": "Write a short poem about programming.    
"}]
}

response = requests.post(url, headers=headers, json=data)
print(response.json()["choices"][0]["message"]["content"])

Use it in Next.js / Node.js

In a modern web application (like a Next.js API Route), here is how you can securely
call the Draftify API from your backend using the native fetch API.

Next.js (App Router)

// app/api/chat/route.js
import { NextResponse } from 'next/server';

export async function POST(request) {
  const body = await request.json();

  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: 'opus-4.8-level',
      messages: [{ role: 'user', content: body.prompt }]
    }),
  });

  const data = await response.json();
  return NextResponse.json({ result: data.choices[0].message.content });
}

Next steps

Now that you have successfully integrated the API, you can explore more advanced features: - Read the Models documentation to find out which model is best suited
for your specific use case. - Learn about Streaming to display AI responses to your users in real-
time.

Need help or got stuck? Join our developer community on Discord, or reach out to us
directly at support@draftify.com.

​Start using the Draftify API in seconds and integrate our powerful reasoning AI models into your applications.

​Prerequisites

​Get started

​Next steps

Start using the Draftify API in seconds and integrate our powerful reasoning AI models into your applications.

Prerequisites

Get started

Next steps