Image generation

curl https://apixly.ai/v1/images/generations \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "A cat astronaut floating in space, digital art",
    "size": "1024x1024"
  }'

{
  "created": 1782500000,
  "data": [{ "b64_json": "<BASE64_IMAGE_DATA>" }]
}

curl https://apixly.ai/v1/images/edits \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F model="gpt-image-2" \
  -F image="@photo.png" \
  -F prompt="Add a wizard hat and a soft magical glow" \
  -F size="1024x1024"

{
  "created": 1782500000,
  "data": [{ "b64_json": "<BASE64_IMAGE_DATA>" }]
}

curl https://apixly.ai/v1/images/generations \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "a cute robot",
    "n": 1,
    "size": "1024x1024",
    "quality": "high",
    "async": true
  }'
# => 202 Accepted
# {"id":"123","object":"image.generation.job","status":"queued","model":"gpt-image-2","created":1782500000}

curl https://apixly.ai/v1/images/edits \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F "model=gpt-image-2" \
  -F "[email protected]" \
  -F "prompt=Replace the background with white; preserve the product." \
  -F "async=true" \
  -F "callback_url=https://your-server.example.com/webhooks/image"

curl https://apixly.ai/v1/images/edits \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.1-flash-image-preview",
    "prompt": "Replace the background with white; preserve the product.",
    "images": [{"image_url": "https://your-server.example.com/photo.png"}],
    "async": true,
    "callback_url": "https://your-server.example.com/webhooks/image"
  }'

curl https://apixly.ai/v1/images/generations/JOB_ID \
  -H "Authorization: Bearer YOUR_API_KEY"
# status: queued -> in_progress -> succeeded | failed
# on success each result is a temporary URL under data[].url, valid ~10 minutes after success
# a succeeded job polled after its results aged out returns status "expired"
# succeeded with EMPTY data[] = links temporarily unavailable, retry the poll (NOT a failure)

{
  "id": "123",
  "object": "image.generation.job",
  "status": "succeeded",
  "model": "gpt-image-2",
  "data": [{ "url": "<TEMPORARY_DOWNLOAD_URL>" }]
}

curl https://apixly.ai/v1/images/generations \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "a cute robot",
    "size": "1024x1024",
    "async": true,
    "callback_url": "https://your-server.example.com/webhooks/image"
  }'

// POST to your callback_url on the terminal state. Headers we send:
//   Content-Type: application/json        User-Agent: sub2api-webhook/1.0
//   X-Webhook-Signature: t=<unix>,v1=<hex hmac>   X-Webhook-Attempt: 1..4
{
  "object": "image.generation.job",
  "task_id": "456",
  "id": "456",
  "model": "gpt-image-2",
  "status": "succeeded",             // succeeded | failed | expired
  "created_at": 1785774335,
  "completed_at": 1785774396,
  "usage": { "input_tokens": 123, "output_tokens": 4096, "total_tokens": 4219 },
  "data": [
    { "url": "https://apixly.ai/v1/images/content?ref=..." }
  ]
}
// data[].url is valid ~10 minutes AFTER THE JOB SUCCEEDED (redeliveries do not
// extend it) — download immediately. "usage" appears only when the provider
// reported token usage; it may also include "image_output_tokens".

# Optional: verify X-Webhook-Signature (recommended — reject unsigned
# requests and stale timestamps if you enable verification).
import hashlib, hmac, time

def verify(header: str, body: bytes, api_key: str, max_age: int = 300) -> bool:
    parts = dict(p.split("=", 1) for p in header.split(",") if "=" in p)
    t, v1 = parts.get("t", ""), parts.get("v1", "")
    if not t or not v1:
        return False
    if abs(time.time() - int(t)) > max_age:  # replay protection
        return False
    mac = hmac.new(api_key.encode(), f"{t}.".encode() + body, hashlib.sha256)
    return hmac.compare_digest(mac.hexdigest(), v1)

# Use case: e-commerce product shot — quality tier + exact size
curl https://apixly.ai/v1/images/generations \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "studio product photo of a matte black thermos on white marble, soft window light, subtle shadow, 45-degree angle, no text",
    "size": "1024x1536",
    "quality": "high"
  }'

import json
import time
import urllib.request
from pathlib import Path

BASE = "https://apixly.ai"
API_KEY = "YOUR_API_KEY"


def request_json(path, payload=None):
    body = json.dumps(payload).encode() if payload is not None else None
    req = urllib.request.Request(
        BASE + path, data=body,
        headers={"Authorization": "Bearer " + API_KEY,
                 "Content-Type": "application/json"},
    )
    with urllib.request.urlopen(req, timeout=20) as response:
        return json.load(response)


# Submit once. Never automatically retry a POST after a network timeout.
try:
    job = request_json("/v1/images/generations", {
        "model": "gpt-image-2", "prompt": "a cozy reading nook, warm light",
        "n": 1, "size": "1024x1024", "async": True,
    })
    job_id = job["id"]
    if not isinstance(job_id, str) or not job_id.isdigit():
        raise ValueError("invalid job id")
except Exception as error:
    raise SystemExit(f"Submission not confirmed: {error}. Do not auto-resubmit; check with support.")

print(f"Save this job id: {job_id}", flush=True)
# Editing jobs use this same GET endpoint.
deadline = time.monotonic() + 600
status, images = None, []
try:
    for attempt in range(120):
        if time.monotonic() >= deadline:
            break
        result = request_json(f"/v1/images/generations/{job_id}")
        status = result.get("status")
        print(f"{job_id}: {status}")
        if status in ("failed", "expired"):
            raise ValueError(json.dumps(result, ensure_ascii=False))
        if status not in ("queued", "in_progress", "succeeded"):
            raise ValueError("invalid status response")
        images = result.get("data") or []
        if status == "succeeded" and images:
            for index, item in enumerate(images, 1):
                with urllib.request.urlopen(item["url"], timeout=30) as response:
                    Path(f"image_{job_id}_{index}.bin").write_bytes(response.read())
            print("Downloaded. File format depends on the model; inspect before renaming.")
            break
        time.sleep(5)
    else:
        raise TimeoutError("polling limit reached")
    if not (status == "succeeded" and images):
        raise TimeoutError("local waiting limit reached")
except Exception as error:
    raise SystemExit(f"Job {job_id}: {error}. Keep this id; query GET again or contact support. Do not auto-resubmit.")