🧩 图像模型调用

curl https://nexor.nexoraivision.com/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "一个极简风格的蓝白配色支付产品宣传海报，中文标题，留白充足",
    "size": "1024x1024",
    "quality": "high",
    "background": "opaque",
    "output_format": "png",
    "moderation": "auto",
    "n": 1
  }'

from openai import OpenAI

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

resp = client.images.generate(
    model="gpt-image-2",
    prompt="一个极简风格的蓝白配色支付产品宣传海报，中文标题，留白充足",
    size="1024x1024",
    quality="high",
    background="opaque",
    output_format="png",
    n=1
)

# 写入文件
import base64
image_bytes = base64.b64decode(resp.data[0].b64_json)
with open("output.png", "wb") as f:
    f.write(image_bytes)

import OpenAI from 'openai'
import fs from 'fs'

const client = new OpenAI({
  apiKey: 'YOUR_API_KEY',
  baseURL: 'https://nexor.nexoraivision.com/v1'
})

const resp = await client.images.generate({
  model: 'gpt-image-2',
  prompt: '一个极简风格的蓝白配色支付产品宣传海报，中文标题，留白充足',
  size: '1024x1024',
  quality: 'high',
  background: 'opaque',
  output_format: 'png',
  n: 1
})

// 写入文件
const buf = Buffer.from(resp.data[0].b64_json, 'base64')
fs.writeFileSync('output.png', buf)

# Linux / macOS
curl -s https://nexor.nexoraivision.com/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "一只橘猫戴橙色围巾抱水獭，温暖插画风格",
    "size": "1024x1024",
    "quality": "high",
    "output_format": "png",
    "n": 1
  }' \
  | jq -r '.data[0].b64_json' \
  | base64 -d > output.png

echo "saved as output.png"

$response = Invoke-RestMethod -Uri 'https://nexor.nexoraivision.com/v1/images/generations' `
  -Method Post `
  -Headers @{ 'Authorization' = 'Bearer YOUR_API_KEY' } `
  -ContentType 'application/json' `
  -Body (@{
    model = 'gpt-image-2'
    prompt = '一只橘猫戴橙色围巾抱水獭，温暖插画风格'
    size = '1024x1024'
    quality = 'high'
    output_format = 'png'
    n = 1
  } | ConvertTo-Json)

[IO.File]::WriteAllBytes('output.png', [Convert]::FromBase64String($response.data[0].b64_json))

import base64, requests

resp = requests.post(
    "https://nexor.nexoraivision.com/v1/images/generations",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    json={
        "model": "gpt-image-2",
        "prompt": "一只橘猫戴橙色围巾抱水獭，温暖插画风格",
        "size": "1024x1024",
        "quality": "high",
        "output_format": "png",
        "n": 1
    }
).json()

with open("output.png", "wb") as f:
    f.write(base64.b64decode(resp["data"][0]["b64_json"]))

import fs from 'fs'

const resp = await fetch('https://nexor.nexoraivision.com/v1/images/generations', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    model: 'gpt-image-2',
    prompt: '一只橘猫戴橙色围巾抱水獭，温暖插画风格',
    size: '1024x1024',
    quality: 'high',
    output_format: 'png',
    n: 1
  })
}).then(r => r.json())

fs.writeFileSync('output.png', Buffer.from(resp.data[0].b64_json, 'base64'))

from openai import OpenAI

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

with open("source.png", "rb") as img, open("mask.png", "rb") as mask:
    resp = client.images.edit(
        model="gpt-image-2",
        image=img,
        mask=mask,
        prompt="仅替换透明区域为蓝白科技风 UI 面板",
        size="1024x1024",
        quality="high",
        output_format="png"
    )

import base64
with open("output.png", "wb") as f:
    f.write(base64.b64decode(resp.data[0].b64_json))

import OpenAI, { toFile } from 'openai'
import fs from 'fs'

const client = new OpenAI({
  apiKey: 'YOUR_API_KEY',
  baseURL: 'https://nexor.nexoraivision.com/v1'
})

const resp = await client.images.edit({
  model: 'gpt-image-2',
  image: await toFile(fs.createReadStream('source.png')),
  mask: await toFile(fs.createReadStream('mask.png')),
  prompt: '仅替换透明区域为蓝白科技风 UI 面板',
  size: '1024x1024',
  quality: 'high',
  output_format: 'png'
})

fs.writeFileSync('output.png', Buffer.from(resp.data[0].b64_json, 'base64'))