GPT Image 2

curl https://api.rendergrid.io/api/public/v1/images/generate \
  -H "Authorization: Bearer $RENDERGRID_API_KEY" \
  -H "Content-Type: application/json" \
  -H "X-Idempotency-Key: 7b3e0c2a-0001" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "四格漫画：小机器人学烤面包——揉面团、守在烤箱旁等待、面团溢了出来、机器人骄傲地举着一根长面包。配简短的中文文字说明，色彩鲜艳",
    "resolution": "1K",
    "aspect_ratio": "1:1"
  }'

# 然后查询状态和结果链接
curl https://api.rendergrid.io/api/public/v1/creations/8f2c41a9-1710-4917-ae39-f3374ea1952c \
  -H "Authorization: Bearer $RENDERGRID_API_KEY"

import os, time, requests

API = "https://api.rendergrid.io/api/public/v1"
headers = {"Authorization": f"Bearer {os.environ['RENDERGRID_API_KEY']}"}

job = requests.post(f"{API}/images/generate", headers=headers, json={
    "model": "gpt-image-2",
    "prompt": "四格漫画：小机器人学烤面包——揉面团、守在烤箱旁等待、面团溢了出来、机器人骄傲地举着一根长面包。配简短的中文文字说明，色彩鲜艳",
    "resolution": "1K",
    "aspect_ratio": "1:1",
}).json()  # 202: {"id": "…", "status": "queued", "task_id": "…", "cost": 0.02}

while True:
    c = requests.get(f"{API}/creations/{job['id']}", headers=headers).json()
    if c["status"] in ("completed", "failed"):
        break
    time.sleep(5)

print(c.get("result_urls"))

const API = "https://api.rendergrid.io/api/public/v1";
const headers = {
  Authorization: `Bearer ${process.env.RENDERGRID_API_KEY}`,
  "Content-Type": "application/json",
};

const job = await fetch(`${API}/images/generate`, {
  method: "POST",
  headers,
  body: JSON.stringify({
    model: "gpt-image-2",
    prompt: "四格漫画：小机器人学烤面包——揉面团、守在烤箱旁等待、面团溢了出来、机器人骄傲地举着一根长面包。配简短的中文文字说明，色彩鲜艳",
    resolution: "1K",
    aspect_ratio: "1:1",
  }),
}).then((r) => r.json()); // 202: {"id": "…", "status": "queued", "task_id": "…", "cost": 0.02}

let c;
do {
  await new Promise((r) => setTimeout(r, 5000));
  c = await fetch(`${API}/creations/${job.id}`, { headers }).then((r) => r.json());
} while (c.status === "queued" || c.status === "processing");

console.log(c.result_urls);