SDK e librerie client

pip install openai

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["ATLASCLOUD_API_KEY"],
    base_url="https://api.atlascloud.ai/v1",
)

response = client.chat.completions.create(
    model="deepseek-ai/deepseek-v3.2",
    messages=[{"role": "user", "content": "Explain HTTP vs HTTPS"}],
)
print(response.choices[0].message.content)

import os
import time
import requests

API_KEY = os.environ["ATLASCLOUD_API_KEY"]
BASE = "https://api.atlascloud.ai/api/v1"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}

# L'endpoint è scelto in base al tipo di output: il 3D usa image; voce, musica e trascrizione usano tutti audio
ENDPOINTS = {
    "image": f"{BASE}/model/generateImage",
    "video": f"{BASE}/model/generateVideo",
    "audio": f"{BASE}/model/generateAudio",
}
TERMINAL = {"completed", "succeeded", "failed", "timeout"}


def submit(kind: str, model: str, **params) -> str:
    """Invia un'attività e restituisce il suo ID di predizione. I parametri vanno al primo livello, non dentro un oggetto `input`."""
    response = requests.post(
        ENDPOINTS[kind],
        headers=HEADERS,
        json={"model": model, **params},
        timeout=60,
    )
    response.raise_for_status()
    return response.json()["data"]["id"]


def wait(prediction_id: str, timeout: int = 600) -> dict:
    """Fa polling finché l'attività non raggiunge uno stato terminale, applicando un backoff progressivo."""
    deadline = time.time() + timeout
    delay = 2.0

    while time.time() < deadline:
        response = requests.get(
            f"{BASE}/model/prediction/{prediction_id}",
            headers=HEADERS,
            timeout=30,
        )
        response.raise_for_status()
        data = response.json()["data"]

        if data.get("status") in TERMINAL:
            if data["status"] in ("failed", "timeout"):
                raise RuntimeError(f"Generation failed: {data.get('error') or data['status']}")
            return data

        time.sleep(delay)
        delay = min(delay * 1.5, 10.0)

    raise TimeoutError(f"Job {prediction_id} did not finish within {timeout}s")


def upload(path: str) -> str:
    """Carica un file locale e restituisce un URL utilizzabile in una richiesta di generazione."""
    with open(path, "rb") as f:
        response = requests.post(
            f"{BASE}/model/uploadMedia", headers=HEADERS, files={"file": f}, timeout=600
        )
    response.raise_for_status()
    data = response.json()["data"]
    return data.get("download_url") or data.get("url")


if __name__ == "__main__":
    pid = submit("image", "MODEL_ID", prompt="a ceramic mug on a linen backdrop")
    result = wait(pid)
    print(result["outputs"][0])