GPT-Image-2

import OpenAI from "openai";
import fs from "fs";
const openai = new OpenAI({
    baseURL: "https://www.vibeapi.cn/v1",
    apiKey: "YOUR_API_KEY",
});

const prompt = `
A children's book drawing of a veterinarian using a stethoscope to 
listen to the heartbeat of a baby otter.
`;

const result = await openai.images.generate({
    model: "gpt-image-2",
    prompt,
});

// 保存图片到文件
const image_base64 = result.data[0].b64_json;
const image_bytes = Buffer.from(image_base64, "base64");
fs.writeFileSync("otter.png", image_bytes);

from openai import OpenAI
import base64

client = OpenAI(
    base_url="https://www.vibeapi.cn/v1",
    api_key="YOUR_API_KEY",
)

prompt = """
A children's book drawing of a veterinarian using a stethoscope to 
listen to the heartbeat of a baby otter.
"""

result = client.images.generate(
    model="gpt-image-2",
    prompt=prompt
)

image_base64 = result.data[0].b64_json
image_bytes = base64.b64decode(image_base64)

# 保存图片到文件
with open("otter.png", "wb") as f:
    f.write(image_bytes)

curl -X POST "https://www.vibeapi.cn/v1/images/generations" \
    -H "Authorization: Bearer $OPENAI_API_KEY" \
    -H "Content-type: application/json" \
    -d '{
        "model": "gpt-image-2",
        "prompt": "A childrens book drawing of a veterinarian using a stethoscope to listen to the heartbeat of a baby otter."
    }' | jq -r '.data[0].b64_json' | base64 --decode > otter.png

import base64
from openai import OpenAI

client = OpenAI(
    base_url="https://www.vibeapi.cn/v1",
    api_key="YOUR_API_KEY",
)

prompt = """
Generate a photorealistic image of a gift basket on a white background 
labeled 'Relax & Unwind' with a ribbon and handwriting-like font, 
containing all the items in the reference pictures.
"""

result = client.images.edit(
    model="gpt-image-2",
    image=[
        open("body-lotion.png", "rb"),
        open("bath-bomb.png", "rb"),
        open("incense-kit.png", "rb"),
        open("soap.png", "rb"),
    ],
    prompt=prompt
)

image_base64 = result.data[0].b64_json
image_bytes = base64.b64decode(image_base64)

# 保存图片到文件
with open("gift-basket.png", "wb") as f:
    f.write(image_bytes)

import fs from "fs";
import OpenAI, { toFile } from "openai";

const client = new OpenAI({
    baseURL: "https://www.vibeapi.cn/v1",
    apiKey: "YOUR_API_KEY",
});

const prompt = `
Generate a photorealistic image of a gift basket on a white background 
labeled 'Relax & Unwind' with a ribbon and handwriting-like font, 
containing all the items in the reference pictures.
`;

const imageFiles = [
    "bath-bomb.png",
    "body-lotion.png",
    "incense-kit.png",
    "soap.png",
];

const images = await Promise.all(
    imageFiles.map(async (file) =>
        await toFile(fs.createReadStream(file), null, {
            type: "image/png",
        })
    ),
);

const response = await client.images.edit({
    model: "gpt-image-2",
    image: images,
    prompt,
});

// 保存图片到文件
const image_base64 = response.data[0].b64_json;
const image_bytes = Buffer.from(image_base64, "base64");
fs.writeFileSync("basket.png", image_bytes);

curl -s -D >(grep -i x-request-id >&2) \
  -o >(jq -r '.data[0].b64_json' | base64 --decode > gift-basket.png) \
  -X POST "https://www.vibeapi.cn/v1/images/edits" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -F "model=gpt-image-2" \
  -F "image[]=@body-lotion.png" \
  -F "image[]=@bath-bomb.png" \
  -F "image[]=@incense-kit.png" \
  -F "image[]=@soap.png" \
  -F 'prompt=Generate a photorealistic image of a gift basket on a white background labeled "Relax & Unwind" with a ribbon and handwriting-like font, containing all the items in the reference pictures'

from openai import OpenAI

client = OpenAI(
    base_url="https://www.vibeapi.cn/v1",
    api_key="YOUR_API_KEY",
)

result = client.images.edit(
    model="gpt-image-2",
    image=open("sunlit_lounge.png", "rb"),
    mask=open("mask.png", "rb"),
    prompt="A sunlit indoor lounge area with a pool containing a flamingo"
)

image_base64 = result.data[0].b64_json
image_bytes = base64.b64decode(image_base64)

# 保存图片到文件
with open("composition.png", "wb") as f:
    f.write(image_bytes)

import fs from "fs";
import OpenAI, { toFile } from "openai";

const client = new OpenAI({
    baseURL: "https://www.vibeapi.cn/v1",
    apiKey: "YOUR_API_KEY",
});

const rsp = await client.images.edit({
    model: "gpt-image-2",
    image: await toFile(fs.createReadStream("sunlit_lounge.png"), null, {
        type: "image/png",
    }),
    mask: await toFile(fs.createReadStream("mask.png"), null, {
        type: "image/png",
    }),
    prompt: "A sunlit indoor lounge area with a pool containing a flamingo",
});

// 保存图片到文件
const image_base64 = rsp.data[0].b64_json;
const image_bytes = Buffer.from(image_base64, "base64");
fs.writeFileSync("lounge.png", image_bytes);

curl -s -D >(grep -i x-request-id >&2) \
  -o >(jq -r '.data[0].b64_json' | base64 --decode > lounge.png) \
  -X POST "https://www.vibeapi.cn/v1/images/edits" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -F "model=gpt-image-2" \
  -F "mask=@mask.png" \
  -F "image[]=@sunlit_lounge.png" \
  -F 'prompt=A sunlit indoor lounge area with a pool containing a flamingo'

from PIL import Image
from io import BytesIO

# 1. 将黑白蒙版加载为灰度图片
mask = Image.open(img_path_mask).convert("L")

# 2. 转换为 RGBA 以添加 alpha 通道
mask_rgba = mask.convert("RGBA")

# 3. 使用蒙版自身填充 alpha 通道
mask_rgba.putalpha(mask)

# 4. 将蒙版转换为字节
buf = BytesIO()
mask_rgba.save(buf, format="PNG")
mask_bytes = buf.getvalue()

# 5. 保存结果文件
img_path_mask_alpha = "mask_alpha.png"
with open(img_path_mask_alpha, "wb") as f:
    f.write(mask_bytes)

import OpenAI from "openai";
import fs from "fs";

const openai = new OpenAI({
    baseURL: "https://www.vibeapi.cn/v1",
    apiKey: "YOUR_API_KEY",
});

const stream = await openai.responses.create({
    model: "gpt-5.5",
    instructions: "You are a helpful image generation assistant.",
    input: [
        {
            role: "user",
            content: [
                {
                    type: "input_text",
                    text: "Generate an image of a cat hugging an otter with an orange scarf",
                },
            ],
        },
    ],
    stream: true,
    tools: [{ type: "image_generation" }],
});

for await (const event of stream) {
    if (event.type === "response.image_generation_call.partial_image") {
        const imageBase64 = event.partial_image_b64;
        const imageBuffer = Buffer.from(imageBase64, "base64");
        fs.writeFileSync("output.png", imageBuffer);
    }
}

from openai import OpenAI
import base64

client = OpenAI(
    base_url="https://www.vibeapi.cn/v1",
    api_key="YOUR_API_KEY",
)

stream = client.responses.create(
    model="gpt-5.5",
    instructions="You are a helpful image generation assistant.",
    input=[
        {
            "role": "user",
            "content": [
                {
                    "type": "input_text",
                    "text": "Generate an image of a cat hugging an otter with an orange scarf",
                },
            ],
        },
    ],
    stream=True,
    tools=[{"type": "image_generation"}],
)

for event in stream:
    if event.type == "response.image_generation_call.partial_image":
        image_base64 = event.partial_image_b64
        image_bytes = base64.b64decode(image_base64)
        with open("output.png", "wb") as f:
            f.write(image_bytes)

curl -sN "https://www.vibeapi.cn/v1/responses" \
    -H "Authorization: Bearer $API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
        "model": "gpt-5.5",
        "instructions": "You are a helpful image generation assistant.",
        "input": [{"role": "user", "content": [{"type": "input_text", "text": "Generate an image of a cat hugging an otter"}]}],
        "stream": true,
        "tools": [{"type": "image_generation"}]
    }'

response.created                              # 请求创建
response.in_progress                          # 开始处理
response.output_item.added                    # image_generation_call 开始
response.image_generation_call.in_progress    # 图片生成中
response.image_generation_call.generating     # 正在生成
keepalive                                     # 心跳（长时间生成时出现）
response.image_generation_call.partial_image  # ★ 图片数据在这里（partial_image_b64）
response.output_item.done                     # ★ revised_prompt 在这里
response.completed                            # 完成

{
    "tools": [{
        "type": "image_generation",
        "quality": "low",
        "size": "1536x1024",
        "output_format": "webp",
        "output_compression": 50,
        "moderation": "low"
    }]
}

const stream = await openai.responses.create({
    model: "gpt-5.5",
    instructions: "You are a helpful image generation assistant.",
    input: [
        {
            role: "user",
            content: [
                { type: "input_text", text: "Make this image look like a watercolor painting" },
                { type: "input_image", image_url: "data:image/png;base64,..." },
            ],
        },
    ],
    stream: true,
    tools: [{ type: "image_generation" }],
});

stream = client.responses.create(
    model="gpt-5.5",
    instructions="You are a helpful image generation assistant.",
    input=[
        {
            "role": "user",
            "content": [
                {"type": "input_text", "text": "Make this image look like a watercolor painting"},
                {"type": "input_image", "image_url": "data:image/png;base64,..."},
            ],
        },
    ],
    stream=True,
    tools=[{"type": "image_generation"}],
)

{
    "tools": [{ "type": "image_generation", "action": "generate" }]
}

from openai import OpenAI
import base64

client = OpenAI(
    base_url="https://www.vibeapi.cn/v1",
    api_key="YOUR_API_KEY",
)

stream = client.responses.create(
    model="gpt-5.5",
    instructions="You are a helpful image generation assistant. Generate ALL images the user requests.",
    input=[
        {
            "role": "user",
            "content": [
                {
                    "type": "input_text",
                    "text": "Generate 3 different images: 1) a red circle 2) a blue square 3) a green triangle",
                },
            ],
        },
    ],
    stream=True,
    tools=[{"type": "image_generation", "quality": "low", "size": "1024x1024"}],
)

img_index = 0
for event in stream:
    if event.type == "response.image_generation_call.partial_image":
        image_bytes = base64.b64decode(event.partial_image_b64)
        with open(f"output_{img_index}.png", "wb") as f:
            f.write(image_bytes)
        img_index += 1

print(f"共生成 {img_index} 张图片")

import OpenAI from "openai";
import fs from "fs";

const openai = new OpenAI({
    baseURL: "https://www.vibeapi.cn/v1",
    apiKey: "YOUR_API_KEY",
});

const stream = await openai.responses.create({
    model: "gpt-5.5",
    instructions: "You are a helpful image generation assistant. Generate ALL images the user requests.",
    input: [
        {
            role: "user",
            content: [
                {
                    type: "input_text",
                    text: "Generate 3 different images: 1) a red circle 2) a blue square 3) a green triangle",
                },
            ],
        },
    ],
    stream: true,
    tools: [{ type: "image_generation", quality: "low", size: "1024x1024" }],
});

let imgIndex = 0;
for await (const event of stream) {
    if (event.type === "response.image_generation_call.partial_image") {
        const imageBuffer = Buffer.from(event.partial_image_b64, "base64");
        fs.writeFileSync(`output_${imgIndex}.png`, imageBuffer);
        imgIndex++;
    }
}

console.log(`共生成 ${imgIndex} 张图片`);