🖼️ Image Generation API

POST https://platform.beeknoee.com/v1/image/generations

Authorization: Bearer sk-bee-xxxxxx
Content-Type: application/json

curl -X POST https://platform.beeknoee.com/v1/image/generations \
  -H "Authorization: Bearer sk-bee-xxxxxx" -H "Content-Type: application/json" \
  -d '{"model": "qwen/qwen-image-3-pro", "prompt": "A cozy coffee shop, watercolor", "resolution": "2K", "aspect_ratio": "16:9"}'

curl -X POST https://platform.beeknoee.com/api/v1/image/generations \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "bee/gpt-image-2",
    "prompt": "A cinematic wide shot of a mountain lake at sunrise, mist over water",
    "size": "1792x1024",
    "resolution": "2K",
    "quality": "high"
  }'

curl -X POST https://platform.beeknoee.com/v1/image/generations \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "A cute 3D cartoon mascot bee, centered, full body",
    "background": "transparent",
    "output_format": "png"
  }'

curl -X POST https://platform.beeknoee.com/v1/image/generations \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "Professional product photo of a coffee mug on a wooden table",
    "output_format": "jpeg"
  }'

curl -X POST https://platform.beeknoee.com/v1/image/generations \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-1.5",
    "prompt": "Một con mèo đang ngồi trên mặt trăng, phong cách anime"
  }'

curl -X POST https://platform.beeknoee.com/v1/image/generations \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "dall-e-3",
    "prompt": "A cyberpunk cityscape at sunset with neon lights reflecting on wet streets",
    "size": "1792x1024",
    "quality": "hd"
  }'

curl -X POST https://platform.beeknoee.com/v1/image/generations \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-1-mini",
    "prompt": "Logo đơn giản cho quán cà phê với hình hạt cà phê",
    "quality": "low"
  }'

curl -X POST https://platform.beeknoee.com/v1/image/generations \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.1-flash-image-preview",
    "prompt": "Phong cảnh đồi chè Mộc Châu lúc bình minh, sương mù"
  }'

curl -X POST https://platform.beeknoee.com/v1/image/generations \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.1-flash-image-preview",
    "prompt": "Detailed digital painting of a Vietnamese dragon",
    "size": "2048x2048"
  }'

curl -X POST https://platform.beeknoee.com/v1/image/generations \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3-pro-image-preview",
    "prompt": "Beautiful portrait of a Vietnamese woman in ao dai, sakura background",
    "size": "3072x4096"
  }'

curl -X POST https://platform.beeknoee.com/v1/image/generations \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-2.5-flash-image",
    "prompt": "Panoramic view of Ha Long Bay at golden hour, dramatic clouds",
    "size": "2048x1152"
  }'

from openai import OpenAI

client = OpenAI(
    api_key="sk-bee-xxxxxx",
    base_url="https://platform.beeknoee.com/v1"
)

# Dùng đúng SDK OpenAI, chỉ đổi model name
response = client.images.generate(
    model="gemini-2.5-flash-image",
    prompt="Cute chibi cat astronaut floating in space with stars",
    size="1024x1024",  # 1K, giá chỉ $0.039
)

# Google models trả base64
import base64
image_data = base64.b64decode(response.data[0].b64_json)
with open("output.png", "wb") as f:
    f.write(image_data)
print("Saved output.png!")

curl https://platform.beeknoee.com/v1/models \
  -H "Authorization: Bearer sk-bee-xxxxxx"

curl "https://platform.beeknoee.com/v1/image/generations?limit=20&offset=0" \
  -H "Authorization: Bearer sk-bee-xxxxxx"

{
  "jobs": [
    {
      "job_id": "a1b2c3d4-...",
      "status": "COMPLETED",
      "model": "bee/gpt-image-2",
      "model_name": "GPT Image 2",
      "supplier": "beeknoee",
      "prompt": "a cinematic sunset...",
      "size": "1024x1024",
      "quality": "high",
      "cost_vnd": 1500,
      "data": [{ "url": "/v1/image/generations/a1b2c3d4-.../download?index=0" }],
      "cache_expires_at": "2026-07-11T10:00:00.000Z",
      "created_at": "2026-07-08T10:00:00.000Z"
    }
  ],
  "total": 42,
  "limit": 20,
  "offset": 0
}

curl "https://platform.beeknoee.com/v1/image/generations?status=PROCESSING" \
  -H "Authorization: Bearer sk-bee-xxxxxx"

curl "https://platform.beeknoee.com/v1/image/generations?status=COMPLETED&limit=50" \
  -H "Authorization: Bearer sk-bee-xxxxxx"

curl "https://platform.beeknoee.com/v1/image/generations/{job_id}/download?index=0" \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -o image.png

curl -X POST https://platform.beeknoee.com/api/v1/image/generations \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3-pro-image-preview",
    "prompt": "Đổi màu chiếc áo thành xanh dương, giữ nguyên mọi thứ khác",
    "image_urls": ["https://cdn.example.com/portrait.jpg"]
  }'

curl -X POST https://platform.beeknoee.com/api/v1/image/generations \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.1-flash-image-preview",
    "prompt": "Đặt sản phẩm ở ảnh 1 vào khung cảnh của ảnh 2, ánh sáng tự nhiên",
    "image_urls": [
      "https://cdn.example.com/product.png",
      "https://cdn.example.com/scene.jpg"
    ]
  }'

import base64, requests

def to_data_uri(path: str, mime: str = "image/png") -> str:
    with open(path, "rb") as f:
        return f"data:{mime};base64,{base64.b64encode(f.read()).decode()}"

res = requests.post(
    "https://platform.beeknoee.com/api/v1/image/generations",
    headers={
        "Authorization": "Bearer sk-bee-xxxxxx",
        "Content-Type": "application/json",
    },
    json={
        "model": "gemini-2.5-flash-image",
        "prompt": "Xoá phông nền, thay bằng nền trắng studio",
        "image_urls": [to_data_uri("./anh-cua-toi.jpg", "image/jpeg")],
        # Bỏ "size" để giữ nguyên tỉ lệ ảnh gốc
    },
    timeout=300,
)

data = res.json()
print("Job:", data.get("job_id"), "| Chi phí:", data.get("cost_vnd"), "đ")

# Ảnh trả về dạng base64 trong data[0].b64_json
b64 = data["data"][0].get("b64_json")
if b64:
    with open("ket-qua.png", "wb") as f:
        f.write(base64.b64decode(b64))
    print("Đã lưu: ket-qua.png")

const res = await fetch('https://platform.beeknoee.com/api/v1/image/generations', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer sk-bee-xxxxxx',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    model: 'gemini-3-pro-image-preview',
    prompt: 'Mở rộng khung cảnh sang hai bên, giữ nguyên chủ thể ở giữa',
    image_urls: ['https://cdn.example.com/square-photo.jpg'],
    size: '1024x576',   // ép ảnh vuông → khung ngang 16:9
  }),
});

const data = await res.json();
console.log('Chi phí:', data.cost_vnd, 'đ');

User gửi image_urls: ["data:image/png;base64,..."]
  │
  ▼
Backend nhận request
  │
  ├── URL bắt đầu http(s):// → pass through (giữ nguyên)
  │
  └── URL bắt đầu data: → tự upload lên bộ nhớ tạm
       │  → nhận fileUrl công khai (tự hết hạn)
       │
       ▼
  Gửi model provider tạo ảnh với input_urls = [fileUrl]
       │
       ▼
  Poll kết quả → trả ảnh cho user

curl -s -X POST "https://platform.beeknoee.com/v1/image/generations" \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "flux-2-pro",
    "prompt": "Transform this photo into a beautiful oil painting style, keep the same composition",
    "image_urls": ["https://example.com/my-photo.jpg"],
    "quality": "medium"
  }'

curl -s -X POST "https://platform.beeknoee.com/v1/image/generations" \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "flux-2-pro",
    "prompt": "The jar in image 1 is filled with capsules exactly same as image 2 with the exact logo",
    "image_urls": [
      "https://cdn.example.com/photos/jar.png",
      "https://cdn.example.com/photos/capsules.png"
    ],
    "quality": "high"
  }'

import requests
import base64

# Đọc file ảnh local → base64 data URI
with open("my-photo.jpg", "rb") as f:
    data_uri = f"data:image/jpeg;base64,{base64.b64encode(f.read()).decode()}"

response = requests.post(
    "https://platform.beeknoee.com/v1/image/generations",
    headers={
        "Authorization": "Bearer sk-bee-xxxxxx",
        "Content-Type": "application/json",
    },
    json={
        "model": "flux-2-pro",
        "prompt": "Chuyển ảnh này sang phong cách quảng cáo chuyên nghiệp, nền gradient",
        "image_urls": [data_uri],  # Backend tự upload lên bộ nhớ tạm
        "quality": "medium",
        "size": "1024x1024",
    },
)
result = response.json()
print(result)

curl -s -X POST "https://platform.beeknoee.com/v1/image/generations" \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "wan-2.7-image",
    "prompt": "A cozy coffee shop interior with warm lighting and wooden furniture",
    "quality": "medium",
    "n": 1
  }'

import requests

response = requests.post(
    "https://platform.beeknoee.com/v1/image/generations",
    headers={
        "Authorization": "Bearer sk-bee-xxxxxx",
        "Content-Type": "application/json",
    },
    json={
        "model": "wan-2.7-image",
        "prompt": "Combine the style of image 1 with the subject in image 2, keep composition consistent",
        "image_urls": [
            "https://example.com/style-ref.jpg",
            "https://example.com/subject.jpg"
        ],
        "quality": "high",
    },
)
print(response.json())

curl -s -X POST "https://platform.beeknoee.com/v1/image/generations" \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "grok-imagine",
    "prompt": "A futuristic cityscape at sunset with flying cars and neon lights",
    "n": 2
  }'

import requests

response = requests.post(
    "https://platform.beeknoee.com/v1/image/generations",
    headers={
        "Authorization": "Bearer sk-bee-xxxxxx",
        "Content-Type": "application/json",
    },
    json={
        "model": "grok-imagine-quality",
        "prompt": "Professional product photography of a luxury watch on marble surface",
        "size": "1024x1024",
    },
)
print(response.json())

const response = await fetch('https://platform.beeknoee.com/v1/image/generations', {
    method: 'POST',
    headers: {
        'Authorization': 'Bearer sk-bee-xxxxxx',
        'Content-Type': 'application/json',
    },
    body: JSON.stringify({
        model: 'grok-imagine',
        prompt: 'Transform this photo into cyberpunk style with neon lighting',
        image_urls: ['https://example.com/my-photo.jpg'],
    }),
});
console.log(await response.json());

POST https://platform.beeknoee.com/v1/image/edits
Content-Type: multipart/form-data

# Chỉnh sửa ảnh (không mask — AI tự xác định vùng cần sửa)
curl -X POST https://platform.beeknoee.com/v1/image/edits \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -F "[email protected]" \
  -F "prompt=Chuyển ảnh sang phong cách tranh sơn dầu" \
  -F "model=gpt-image-1" \
  -F "quality=medium"

# Chỉnh sửa có mask (inpainting — chỉ sửa vùng được đánh dấu)
curl -X POST https://platform.beeknoee.com/v1/image/edits \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -F "[email protected]" \
  -F "[email protected]" \
  -F "prompt=Thay nền thành bãi biển hoàng hôn" \
  -F "model=gpt-image-1" \
  -F "size=1024x1024" \
  -F "quality=medium"

import requests

# ═══ Upload file từ ổ đĩa ═══
response = requests.post(
    "https://platform.beeknoee.com/v1/image/edits",
    headers={"Authorization": "Bearer sk-bee-xxxxxx"},
    files={
        "image": ("photo.png", open("photo.png", "rb"), "image/png"),
    },
    data={
        "prompt": "Thêm kính mát cho nhân vật trong ảnh",
        "model": "gpt-image-1",
        "size": "1024x1024",
        "quality": "medium",
    },
)
print(response.json())

# ═══ Upload file + mask (inpainting) ═══
response = requests.post(
    "https://platform.beeknoee.com/v1/image/edits",
    headers={"Authorization": "Bearer sk-bee-xxxxxx"},
    files={
        "image": ("photo.png", open("photo.png", "rb"), "image/png"),
        "mask": ("mask.png", open("mask.png", "rb"), "image/png"),
    },
    data={
        "prompt": "Thay background thành phòng làm việc hiện đại",
        "model": "gpt-image-1",
        "quality": "high",
    },
)

import requests
import base64
from io import BytesIO

# ═══ Từ base64 string ═══
base64_image = "iVBORw0KGgoAAAANSUhEUg..."  # base64 string của ảnh

# Decode base64 → bytes → gửi như file
image_bytes = base64.b64decode(base64_image)

response = requests.post(
    "https://platform.beeknoee.com/v1/image/edits",
    headers={"Authorization": "Bearer sk-bee-xxxxxx"},
    files={
        "image": ("input.png", BytesIO(image_bytes), "image/png"),
    },
    data={
        "prompt": "Chuyển ảnh sang style anime Ghibli",
        "model": "gpt-image-1",
        "quality": "high",
    },
)
result = response.json()
print(result)

# ═══ Từ URL (download → gửi) ═══
import requests
from io import BytesIO

image_url = "https://example.com/my-photo.jpg"
img_response = requests.get(image_url)
image_bytes = img_response.content

response = requests.post(
    "https://platform.beeknoee.com/v1/image/edits",
    headers={"Authorization": "Bearer sk-bee-xxxxxx"},
    files={
        "image": ("downloaded.png", BytesIO(image_bytes), "image/png"),
    },
    data={
        "prompt": "Xóa tất cả text/watermark trong ảnh",
        "model": "gpt-image-1",
        "quality": "medium",
    },
)

const fs = require('fs');

// ═══ Từ file trên ổ đĩa ═══
const form = new FormData();
form.append('image', new Blob([fs.readFileSync('photo.png')], { type: 'image/png' }), 'photo.png');
form.append('prompt', 'Chuyển ảnh sang phong cách cyberpunk neon');
form.append('model', 'gpt-image-1');
form.append('quality', 'medium');

const response = await fetch('https://platform.beeknoee.com/v1/image/edits', {
  method: 'POST',
  headers: { 'Authorization': 'Bearer sk-bee-xxxxxx' },
  body: form,
});
console.log(await response.json());

// ═══ Từ base64 string ═══
const base64Image = 'iVBORw0KGgoAAAANSUhEUg...'; // base64 của ảnh
const imageBuffer = Buffer.from(base64Image, 'base64');

const form = new FormData();
form.append('image', new Blob([imageBuffer], { type: 'image/png' }), 'input.png');
form.append('prompt', 'Thêm hiệu ứng tuyết rơi vào ảnh');
form.append('model', 'gpt-image-1');
form.append('quality', 'medium');

const response = await fetch('https://platform.beeknoee.com/v1/image/edits', {
  method: 'POST',
  headers: { 'Authorization': 'Bearer sk-bee-xxxxxx' },
  body: form,
});

// ═══ Từ URL (download → gửi) ═══
const imgRes = await fetch('https://example.com/my-photo.jpg');
const imgBuffer = Buffer.from(await imgRes.arrayBuffer());

const form = new FormData();
form.append('image', new Blob([imgBuffer], { type: 'image/jpeg' }), 'photo.jpg');
form.append('prompt', 'Upscale ảnh và tăng độ sắc nét');
form.append('model', 'gpt-image-2');
form.append('quality', 'high');

const response = await fetch('https://platform.beeknoee.com/v1/image/edits', {
  method: 'POST',
  headers: { 'Authorization': 'Bearer sk-bee-xxxxxx' },
  body: form,
});

from openai import OpenAI
import base64
from pathlib import Path

client = OpenAI(
    api_key="sk-bee-xxxxxx",
    base_url="https://platform.beeknoee.com/v1"
)

# ═══ Từ file ═══
result = client.images.edit(
    model="gpt-image-1",
    image=open("photo.png", "rb"),
    prompt="Chuyển ảnh sang watercolor painting style",
    size="1024x1024",
)
# Download kết quả
image_url = result.data[0].url
print(f"Edited image: {image_url}")

# ═══ Từ base64 (decode → BytesIO → gửi như file) ═══
from io import BytesIO
base64_str = "iVBORw0KGgoAAAANSUhEUg..."
image_bytes = base64.b64decode(base64_str)

result = client.images.edit(
    model="gpt-image-1",
    image=BytesIO(image_bytes),
    prompt="Thêm mũ Giáng sinh cho nhân vật",
    quality="medium",
)

# Tạo mask bằng Python (PIL)
from PIL import Image, ImageDraw

# Tạo mask cho vùng hình chữ nhật ở giữa ảnh
img = Image.open("photo.png")
mask = Image.new("RGBA", img.size, (0, 0, 0, 255))  # Toàn bộ opaque
draw = ImageDraw.Draw(mask)

# Vẽ vùng cần sửa (transparent)
draw.rectangle([200, 200, 800, 800], fill=(0, 0, 0, 0))
mask.save("mask.png")

# Gửi ảnh sản phẩm → AI tạo ảnh quảng cáo mới dựa trên sản phẩm đó
curl -X POST https://platform.beeknoee.com/v1/image/edits \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -F "[email protected]" \
  -F "prompt=Tạo ảnh quảng cáo chuyên nghiệp cho sản phẩm này trên nền gradient tím-hồng, có ánh sáng studio" \
  -F "model=gpt-image-1" \
  -F "quality=high"

import requests

# Gửi ảnh mẫu phong cách → AI tạo ảnh mới theo style đó
response = requests.post(
    "https://platform.beeknoee.com/v1/image/edits",
    headers={"Authorization": "Bearer sk-bee-xxxxxx"},
    files={
        "image": ("style-ref.png", open("style-ref.png", "rb"), "image/png"),
    },
    data={
        "prompt": "Giữ nguyên phong cách nghệ thuật của ảnh này, vẽ một cảnh hoàng hôn trên biển với thuyền buồm",
        "model": "gpt-image-1",
        "quality": "high",
        "size": "1536x1024",
    },
)
result = response.json()
print(result)

import requests
import base64
from io import BytesIO

# Ảnh mẫu dạng base64 (VD: từ database hoặc API khác)
base64_reference = "iVBORw0KGgoAAAANSUhEUg..."  # base64 của ảnh mẫu
image_bytes = base64.b64decode(base64_reference)

response = requests.post(
    "https://platform.beeknoee.com/v1/image/edits",
    headers={"Authorization": "Bearer sk-bee-xxxxxx"},
    files={
        "image": ("reference.png", BytesIO(image_bytes), "image/png"),
    },
    data={
        "prompt": "Dựa trên ảnh mẫu này, tạo phiên bản 3D render chất lượng cao",
        "model": "gpt-image-2",
        "quality": "high",
    },
)

// Download ảnh mẫu từ URL → gửi kèm prompt
const refRes = await fetch('https://example.com/style-reference.jpg');
const refBuffer = Buffer.from(await refRes.arrayBuffer());

const form = new FormData();
form.append('image', new Blob([refBuffer], { type: 'image/jpeg' }), 'reference.jpg');
form.append('prompt', 'Lấy phong cách màu sắc và bố cục của ảnh này, tạo một poster phim sci-fi');
form.append('model', 'gpt-image-1');
form.append('quality', 'high');
form.append('size', '1024x1536');

const response = await fetch('https://platform.beeknoee.com/v1/image/edits', {
  method: 'POST',
  headers: { 'Authorization': 'Bearer sk-bee-xxxxxx' },
  body: form,
});
console.log(await response.json());

from openai import OpenAI

client = OpenAI(
    api_key="sk-bee-xxxxxx",
    base_url="https://platform.beeknoee.com/v1"
)

# Gửi ảnh mẫu làm tham chiếu
result = client.images.edit(
    model="gpt-image-1",
    image=open("my-sketch.png", "rb"),
    prompt="Biến bức sketch này thành ảnh thực tế chất lượng cao, giữ nguyên bố cục",
    size="1024x1024",
    quality="high",
)
print(result.data[0].url)

# Gửi 3 ảnh sản phẩm → AI tạo 1 ảnh quảng cáo kết hợp
curl -X POST https://platform.beeknoee.com/v1/image/edits \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -F "[email protected]" \
  -F "[email protected]" \
  -F "[email protected]" \
  -F "prompt=Dựa trên 3 ảnh sản phẩm này, tạo 1 banner quảng cáo chuyên nghiệp trên nền gradient tím-hồng" \
  -F "model=gpt-image-1" \
  -F "quality=high" \
  -F "size=1536x1024"

import requests

# Gửi 3 ảnh mẫu phong cách → AI kết hợp và tạo ảnh mới
response = requests.post(
    "https://platform.beeknoee.com/v1/image/edits",
    headers={"Authorization": "Bearer sk-bee-xxxxxx"},
    files=[
        ("image", ("style1.png", open("style1.png", "rb"), "image/png")),
        ("image", ("style2.png", open("style2.png", "rb"), "image/png")),
        ("image", ("style3.png", open("style3.png", "rb"), "image/png")),
    ],
    data={
        "prompt": "Kết hợp phong cách nghệ thuật của 3 ảnh mẫu này, tạo 1 bức tranh phong cảnh Hà Nội mùa thu",
        "model": "gpt-image-2",
        "quality": "high",
        "size": "1024x1024",
    },
)
result = response.json()
print(result)

import requests
import base64
from io import BytesIO

# Ảnh từ database hoặc API khác (base64)
images_b64 = [
    "iVBORw0KGgoAAAANSUhEUg...",  # ảnh 1
    "iVBORw0KGgoAAAANSUhEUg...",  # ảnh 2
    "iVBORw0KGgoAAAANSUhEUg...",  # ảnh 3
]

files = [
    ("image", (f"ref{i+1}.png", BytesIO(base64.b64decode(b64)), "image/png"))
    for i, b64 in enumerate(images_b64)
]

response = requests.post(
    "https://platform.beeknoee.com/v1/image/edits",
    headers={"Authorization": "Bearer sk-bee-xxxxxx"},
    files=files,
    data={
        "prompt": "Phân tích 3 ảnh mẫu và tạo 1 ảnh mới kết hợp tất cả yếu tố nổi bật",
        "model": "gpt-image-1",
        "quality": "high",
    },
)

const fs = require('fs');

const form = new FormData();

// Append nhiều ảnh cùng field name "image"
const imageFiles = ['photo1.png', 'photo2.png', 'photo3.png'];
for (const file of imageFiles) {
    form.append('image', new Blob([fs.readFileSync(file)], { type: 'image/png' }), file);
}

form.append('prompt', 'Tổng hợp 3 ảnh sản phẩm này thành 1 ảnh catalog chuyên nghiệp');
form.append('model', 'gpt-image-1');
form.append('quality', 'high');
form.append('size', '1536x1024');

const response = await fetch('https://platform.beeknoee.com/v1/image/edits', {
    method: 'POST',
    headers: { 'Authorization': 'Bearer sk-bee-xxxxxx' },
    body: form,
});
console.log(await response.json());

# ⚠️ OpenAI SDK chỉ hỗ trợ 1 file trong client.images.edit()
# Để gửi nhiều ảnh, dùng requests trực tiếp (xem Ví dụ 2, 3 ở trên)

{
  "job_id": "abc-123",
  "status": "PROCESSING",
  "data": [],
  "cost_vnd": 1500,
  "message": "Image is being generated. Check the status at GET /v1/image/generations/abc-123",
  "estimated_time_seconds": 150
}

curl https://platform.beeknoee.com/v1/image/generations/abc-123 \
  -H "Authorization: Bearer sk-bee-xxxxxx"

{
  "job_id": "abc-123",
  "status": "PROCESSING",
  "model": "bee/gpt-image-2",
  "model_name": "GPT Image 2",
  "supplier": "beeknoee",
  "started_at": "2026-08-05T10:00:00.000Z",
  "completed_at": null,
  "elapsed_seconds": 45,
  "estimated_time_seconds": 152,
  "timeout_at": "2026-08-05T11:00:00.000Z",
  "data": [],
  "error_message": null
}

{
  "job_id": "abc-123",
  "status": "COMPLETED",
  "model": "bee/gpt-image-2",
  "model_name": "GPT Image 2",
  "supplier": "beeknoee",
  "prompt": "a cinematic sunset over Ha Long Bay",
  "revised_prompt": null,
  "size": "1024x1024",
  "quality": "high",
  "style": null,
  "n": 1,
  "cost_vnd": 1500,
  "started_at": "2026-08-05T10:00:00.000Z",
  "completed_at": "2026-08-05T10:02:32.000Z",
  "elapsed_seconds": 152,
  "data": [
    { "url": "/v1/image/generations/abc-123/download?index=0" }
  ],
  "error_message": null,
  "cache_expires_at": "2026-08-08T10:00:00.000Z",
  "created_at": "2026-08-05T10:00:00.000Z"
}

curl "https://platform.beeknoee.com/v1/image/generations/abc-123/download?index=0" \
  -H "Authorization: Bearer sk-bee-xxxxxx" \
  -o result.png

import requests, time

BASE = "https://platform.beeknoee.com"
KEY  = "sk-bee-xxxxxx"
H    = {"Authorization": f"Bearer {KEY}"}

# 1. Yêu cầu tạo ảnh
r = requests.post(f"{BASE}/v1/image/generations", headers=H, json={
    "model":  "bee/gpt-image-2",
    "prompt": "a cinematic sunset over Ha Long Bay",
    "size":   "1024x1024",
    "quality": "high",
})
r.raise_for_status()
job = r.json()

# 2. Nếu chưa xong thì hỏi lại cho tới khi có kết quả
if job["status"] == "PROCESSING":
    job_id = job["job_id"]
    print(f"Đang tạo… job {job_id}")
    deadline = time.time() + 3600          # cửa sổ tối đa 60 phút
    while time.time() < deadline:
        time.sleep(10)                     # 10 giây một lần là đủ, đừng hỏi dồn
        job = requests.get(f"{BASE}/v1/image/generations/{job_id}", headers=H).json()
        if job["status"] != "PROCESSING":
            break
        print("  … vẫn đang tạo")

# 3. Xử lý kết quả
if job["status"] == "FAILED":
    raise SystemExit(f"Tạo ảnh hỏng: {job.get('error_message')}")

for i, _ in enumerate(job["data"]):
    img = requests.get(f"{BASE}/v1/image/generations/{job['job_id']}/download?index={i}", headers=H)
    open(f"anh-{i}.png", "wb").write(img.content)
    print(f"Đã lưu anh-{i}.png")

print("Chi phí:", job["cost_vnd"], "đ")

const BASE = 'https://platform.beeknoee.com';
const H = { Authorization: 'Bearer sk-bee-xxxxxx', 'Content-Type': 'application/json' };
const sleep = ms => new Promise(r => setTimeout(r, ms));

let job = await (await fetch(`${BASE}/v1/image/generations`, {
    method: 'POST', headers: H,
    body: JSON.stringify({ model: 'bee/gpt-image-2', prompt: 'a cinematic sunset', size: '1024x1024' }),
})).json();

const deadline = Date.now() + 3600_000;          // 60 phút
while (job.status === 'PROCESSING' && Date.now() < deadline) {
    await sleep(10_000);
    job = await (await fetch(`${BASE}/v1/image/generations/${job.job_id}`, { headers: H })).json();
}

if (job.status === 'FAILED') throw new Error(job.error_message);

for (let i = 0; i < job.data.length; i++) {
    const res = await fetch(`${BASE}/v1/image/generations/${job.job_id}/download?index=${i}`, { headers: H });
    await require('fs').promises.writeFile(`anh-${i}.png`, Buffer.from(await res.arrayBuffer()));
}