Images API | AI Image Generation & Editing | LaoZhang API

curl https://api.laozhang.ai/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 uses Chat Completions API
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{
        "role": "user",
        "content": "Draw a beautiful sunset seascape【3:2】"  # Specify ratio at the end
    }]
)

# Extract image URL from returned markdown
import re
content = response.choices[0].message.content
image_url = re.search(r'!\[.*?\]\((.*?)\)', content).group(1)

# Flux Pro - Professional quality
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",  # Flexible aspect ratio
        "seed": 42,  # Reproducible results
        "prompt_upsampling": True  # Automatic prompt enhancement
    }
)

# Flux Max - Highest quality, supports editing
response = client.images.generate(
    model="black-forest-labs/flux-kontext-max",
    prompt="Ultra detailed fantasy landscape with dragons",
    extra_body={
        "aspect_ratio": "21:9",  # Ultra-wide
        "safety_tolerance": 2
    }
)

# Local editing using mask
response = client.images.edit(
    image=open("original.png", "rb"),
    mask=open("mask.png", "rb"),  # White = editing area
    prompt="A sunflower in the vase",
    model="dall-e-2",
    n=1,
    size="1024x1024"
)

# Single image editing
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Turn this image into watercolor style"},
            {"type": "image_url", "image_url": {"url": "https://example.com/photo.jpg"}}
        ]
    }]
)

# Multi-image fusion
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Merge the style and content of these two images"},
            {"type": "image_url", "image_url": {"url": "https://example.com/style.jpg"}},
            {"type": "image_url", "image_url": {"url": "https://example.com/content.jpg"}}
        ]
    }]
)

# Basic image analysis
response = client.chat.completions.create(
    model="gpt-4o",  # or gemini-2.5-pro, claude-3-5-sonnet
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Please describe this image in detail"},
            {"type": "image_url", "image_url": {"url": "https://example.com/image.jpg"}}
        ]
    }]
)

# OCR text recognition
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Please extract all text from the image"},
            {"type": "image_url", "image_url": {"url": "data:image/jpeg;base64,..."}}
        ]
    }]
)

# Multi-image comparison analysis
response = client.chat.completions.create(
    model="gemini-2.5-pro",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Compare the differences between these two images"},
            {"type": "image_url", "image_url": {"url": "image1.jpg"}},
            {"type": "image_url", "image_url": {"url": "image2.jpg"}}
        ]
    }]
)

import asyncio
from openai import AsyncOpenAI

client = AsyncOpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.laozhang.ai/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]

# Usage example
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)