export VIZLUMA_API_KEY="YOUR_API_KEY"
export VIZLUMA_BASE_URL="https://api.vizluma.online/v1"
export VIZLUMA_MODEL="gpt-image-2"
VIZLUMA_MODEL 可替换为已开通的 gpt-image-2.5-flare 或 gpt-image-2.5-sunburst。
Python
Python 3.10 或更高版本，仅使用标准库。保存为generate.py：
generate.py
import json
import os
import sys
import urllib.error
import urllib.request
from pathlib import Path
api_key = os.environ.get("VIZLUMA_API_KEY")
if not api_key or api_key == "YOUR_API_KEY":
raise SystemExit("请先配置服务端环境变量 VIZLUMA_API_KEY")
base_url = os.environ.get(
"VIZLUMA_BASE_URL", "https://api.vizluma.online/v1"
).rstrip("/")
body = {
"model": os.environ.get("VIZLUMA_MODEL", "gpt-image-2"),
"prompt": "一只小橘猫坐在纯白色背景上，简洁插画，无文字",
"size": "1024x1024",
"n": 1,
"response_format": "url",
}
request = urllib.request.Request(
f"{base_url}/images/generations",
data=json.dumps(body).encode("utf-8"),
headers={
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
},
method="POST",
)
try:
with urllib.request.urlopen(request, timeout=600) as response:
result = json.load(response)
except urllib.error.HTTPError as error:
print(f"HTTP {error.code}", file=sys.stderr)
print(error.read().decode("utf-8", errors="replace"), file=sys.stderr)
raise SystemExit(1)
except (urllib.error.URLError, TimeoutError) as error:
print(f"请求未取得可确认的结果：{error}", file=sys.stderr)
print("请核对调用记录，不要立即自动重发。", file=sys.stderr)
raise SystemExit(1)
if result.get("error") or not result.get("data"):
raise SystemExit("未收到有效图片结果，请核对调用记录")
Path("generation.json").write_text(
json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8"
)
print("响应已保存至 generation.json，请继续下载 data 中的图片。")
python3 generate.py
Node.js
Node.js 20 或更高版本，使用原生fetch。保存为 generate.mjs：
generate.mjs
import { writeFile } from "node:fs/promises";
const apiKey = process.env.VIZLUMA_API_KEY;
if (!apiKey || apiKey === "YOUR_API_KEY") {
throw new Error("请先配置服务端环境变量 VIZLUMA_API_KEY");
}
const baseUrl = (
process.env.VIZLUMA_BASE_URL ?? "https://api.vizluma.online/v1"
).replace(/\/+$/, "");
try {
const response = await fetch(`${baseUrl}/images/generations`, {
method: "POST",
headers: {
Authorization: `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
model: process.env.VIZLUMA_MODEL ?? "gpt-image-2",
prompt: "一只小橘猫坐在纯白色背景上，简洁插画，无文字",
size: "1024x1024",
n: 1,
response_format: "url",
}),
signal: AbortSignal.timeout(600_000),
});
if (!response.ok) {
console.error(`HTTP ${response.status}: ${await response.text()}`);
process.exitCode = 1;
} else {
const result = await response.json();
if (result.error || !Array.isArray(result.data) || !result.data.length) {
throw new Error("未收到有效图片结果，请核对调用记录");
}
await writeFile("generation.json", JSON.stringify(result, null, 2));
console.log("响应已保存至 generation.json，请继续下载 data 中的图片。");
}
} catch (error) {
console.error(error.message);
console.error("未取得可确认的结果时，请核对调用记录，不要立即自动重发。");
process.exitCode = 1;
}
node generate.mjs