Images API | AI Image Generation & Editing | LaoZhang API

curl https://api.yelinai.com/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "gpt-4o-image",
    "prompt": "A serene Japanese garden with cherry blossoms",
    "n": 1,
    "size": "1024x1024"
  }'

# Sora Image 使用 Chat Completions API
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{
        "role": "user",
        "content": "画一幅美丽的日落海景【3:2】"  # 在末尾指定比例
    }]
)

# 从返回的 markdown 中提取图片 URL
import re
content = response.choices[0].message.content
image_url = re.search(r'!\[.*?\]\((.*?)\)', content).group(1)

# DALL-E 3 - 最新版本，理解能力强
response = client.images.generate(
    model="dall-e-3",
    prompt="A detailed oil painting of a robot playing chess",
    size="1024x1024",
    quality="hd",
    style="vivid"
)

# DALL-E 2 - 经典版本，性价比高
response = client.images.generate(
    model="dall-e-2",
    prompt="A minimalist logo design for a tech company",
    size="512x512"
)

# Flux Pro - 专业质量
response = client.images.generate(
    model="black-forest-labs/flux-pro-v1.1",
    prompt="Professional product photography of a luxury watch",
    extra_body={
        "aspect_ratio": "16:9",  # 灵活宽高比
        "seed": 42,  # 可重现结果
        "prompt_upsampling": True  # 自动增强提示词
    }
)

# Flux Max - 最高质量，支持编辑
response = client.images.generate(
    model="black-forest-labs/flux-kontext-max",
    prompt="Ultra detailed fantasy landscape with dragons",
    extra_body={
        "aspect_ratio": "21:9",  # 超宽屏
        "safety_tolerance": 2
    }
)

# 使用遮罩进行局部编辑
response = client.images.edit(
    image=open("original.png", "rb"),
    mask=open("mask.png", "rb"),  # 白色=编辑区域
    prompt="A sunflower in the vase",
    model="dall-e-2",
    n=1,
    size="1024x1024"
)

# Flux Max 编辑 - 支持在线图片
response = client.images.edit(
    image="https://example.com/original.jpg",  # 支持URL
    mask="https://example.com/mask.png",  # 可选
    prompt="Transform the car into a futuristic hovering vehicle",
    model="black-forest-labs/flux-kontext-max",
    extra_body={
        "aspect_ratio": "16:9"
    }
)

# 单图编辑
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "将这张图片变成水彩画风格"},
            {"type": "image_url", "image_url": {"url": "https://example.com/photo.jpg"}}
        ]
    }]
)

# 多图融合
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "将这两张图片的风格和内容融合"},
            {"type": "image_url", "image_url": {"url": "https://example.com/style.jpg"}},
            {"type": "image_url", "image_url": {"url": "https://example.com/content.jpg"}}
        ]
    }]
)

# 基础图像分析
response = client.chat.completions.create(
    model="gpt-4o",  # 或 gemini-2.5-pro、claude-3-5-sonnet
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "请详细描述这张图片的内容"},
            {"type": "image_url", "image_url": {"url": "https://example.com/image.jpg"}}
        ]
    }]
)

# OCR 文字识别
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "请提取图片中的所有文字"},
            {"type": "image_url", "image_url": {"url": "data:image/jpeg;base64,..."}}
        ]
    }]
)

# 多图对比分析
response = client.chat.completions.create(
    model="gemini-2.5-pro",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "比较这两张图片的差异"},
            {"type": "image_url", "image_url": {"url": "image1.jpg"}},
            {"type": "image_url", "image_url": {"url": "image2.jpg"}}
        ]
    }]
)

[主体描述] + [艺术风格] + [环境设置] + [光照效果] + [质量修饰词]

A majestic eagle (主体) in photorealistic style (风格) 
soaring above mountain peaks (环境) during golden hour (光照) 
highly detailed, 8K resolution (质量)

import asyncio
from openai import AsyncOpenAI

client = AsyncOpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.yelinai.com/v1"
)

async def generate_batch_images(prompts):
    tasks = []
    for prompt in prompts:
        task = client.images.generate(
            model="dall-e-3",
            prompt=prompt,
            n=1
        )
        tasks.append(task)
    
    results = await asyncio.gather(*tasks)
    return [r.data[0].url for r in results]

# 使用示例
prompts = [
    "A cute cat playing with yarn",
    "A dog running in the park",
    "A bird sitting on a branch"
]

urls = await generate_batch_images(prompts)

import requests
from datetime import datetime

def download_and_save(image_url, prefix="image"):
    response = requests.get(image_url)
    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
    filename = f"{prefix}_{timestamp}.png"
    
    with open(filename, 'wb') as f:
        f.write(response.content)
    
    return filename

# 生成并保存（标准API）
response = client.images.generate(
    model="flux-pro-v1.1",
    prompt="Beautiful sunset"
)
saved_file = download_and_save(response.data[0].url, "sunset")
print(f"Image saved as: {saved_file}")

# 生成并保存（逆向API - GPT-4o Image/Sora Image）
import re
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "生成美丽的日落图片"}]
)
content = response.choices[0].message.content
image_url = re.search(r'!\[.*?\]\((.*?)\)', content).group(1)
saved_file = download_and_save(image_url, "sunset")
print(f"Image saved as: {saved_file}")