How to inference an AI model

The Sunrise Model Service exposes an OpenAI-compatible API for every Active Model. To send an inference request you need three pieces of information: a Base URL, a Model Name, and an API Key.

Make your first call

1. Get the Base API URL

All inference requests are sent to the Sunrise Model Service endpoint.

Environment	Base API URL
Production	`https://maas.phoeniqs.com/`

2. Pick a Model Name

Choose a model from the Active Models table. The value in the Model Name column is what you pass as "model" in your request body.

Examples:

inference-llama4-maverick
inference-bge-m3

3. Get your API Key

Your API Key authenticates every request. Pass it in the Authorization HTTP header:

Authorization: Bearer YOUR_API_KEY

Keep your API Key secret

Never commit an API Key to source control or expose it in client-side code. Rotate the key immediately if you suspect it has been leaked.

4. Send the request

With the three pieces above you can call any of the OpenAI-compatible endpoints. The minimal chat completion call looks like this:

curl --location 'https://maas.phoeniqs.com/v1/chat/completions' \
  --header 'Authorization: Bearer YOUR_API_KEY' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "inference-llama4-maverick",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from openai import OpenAI

client = OpenAI(
    base_url="https://maas.phoeniqs.com/v1",
    api_key="YOUR_API_KEY",
)

response = client.chat.completions.create(
    model="inference-llama4-maverick",
    messages=[{"role": "user", "content": "Hello!"}],
)

print(response.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://maas.phoeniqs.com/v1",
  apiKey: "YOUR_API_KEY",
});

const response = await client.chat.completions.create({
  model: "inference-llama4-maverick",
  messages: [{ role: "user", content: "Hello!" }],
});

console.log(response.choices[0].message.content);