Documentation

Quick Start Guide

Learn how to make your first API request to MX4 Atlas using the standard OpenAI SDK.

Last updated on February 2, 2026

MX4 Atlas is designed to be a drop-in replacement for OpenAI. This means you can use the libraries and tools you already know, just by changing the configuration.

Get your API Key

You'll need an API key to authenticate your requests. If you don't have one yet, contact sales to request access to the Private Beta.

Note: Your API key (`mx4-sk-...`) carries full privileges for your account. Keep it secure and never commit it to public repositories.

Install the OpenAI SDK

Since MX4 Atlas is API-compatible with OpenAI, you don't need a special "MX4" library. Just install the standard OpenAI Python package.

bash

1pip install openai

Configure the Client

Initialize the client by pointing it to the MX4 Atlas API endpoint.

main.pypython

1import openai
2import os
3
4client = openai.OpenAI(
5    # Set the base URL to MX4 Atlas
6    base_url="https://api.mx4.ai/v1",
7    # Use your MX4 API Key
8    api_key="mx4-sk-1234567890abcdef" 
9)

Make your first request

Now you can call the Chat Completions API just like you're used to. We recommend starting with the `mx4-atlas-core` model for the best balance of Arabic reasoning and performance.

main.pypython

1response = client.chat.completions.create(
2    model="mx4-atlas-core",
3    messages=[
4        {"role": "system", "content": "You are a helpful assistant."},
5        {"role": "user", "content": "Hello, who are you?"}
6    ]
7)
8
9print(response.choices[0].message.content)

You should see a response identifying the model as MX4 Atlas, running on sovereign infrastructure.

Other Languages & Methods

JavaScript/Node.js

quickstart.jsjavascript

1const OpenAI = require('openai');
2
3const client = new OpenAI({
4  apiKey: process.env.MX4_API_KEY,
5  baseURL: 'https://api.mx4.ai/v1'
6});
7
8async function main() {
9  const message = await client.chat.completions.create({
10    model: 'mx4-atlas-core',
11    messages: [{ role: 'user', content: 'Hello' }]
12  });
13  console.log(message.choices[0].message.content);
14}
15
16main();

cURL

bash

1curl https://api.mx4.ai/v1/chat/completions \
2  -H "Content-Type: application/json" \
3  -H "Authorization: Bearer $MX4_API_KEY" \
4  -d '{
5    "model": "mx4-atlas-core",
6    "messages": [
7      {"role": "user", "content": "Hello"}
8    ]
9  }'

Error Handling

Always handle errors gracefully in production. Here's a best-practice example:

error_handling.pypython

1import openai
2from openai import APIError, AuthenticationError, RateLimitError
3
4client = openai.OpenAI(
5    api_key="mx4-sk-...",
6    base_url="https://api.mx4.ai/v1"
7)
8
9try:
10    response = client.chat.completions.create(
11        model="mx4-atlas-core",
12        messages=[{"role": "user", "content": "Hello"}],
13        timeout=30
14    )
15    print(response.choices[0].message.content)
16    
17except AuthenticationError:
18    print("Invalid API key. Check your credentials.")
19except RateLimitError:
20    print("Rate limit exceeded. Wait before retrying.")
21except APIError as e:
22    print(f"API error: {e.status_code} {e.message}")

Common Issues & Solutions

❌ ModuleNotFoundError: No module named 'openai'

Run pip install --upgrade openai (requires version 1.0+)

❌ 401 Unauthorized

Your API key is missing or incorrect. Check that it starts with mx4-sk-

❌ Model not found

Your account may not have access to that model. Check the Model Garden for available models in your region.