How to Use GPT Image 1.5 API in Python — Complete Guide 2026

pip install requests

import requests
import os

# Get your API key from RapidAPI: https://rapidapi.com/nexaquency/api/gpt-image-1-5
RAPIDAPI_KEY = os.environ.get("RAPIDAPI_KEY", "your-rapidapi-key-here")
API_HOST = "gpt-image-1-5.p.rapidapi.com"

def generate_image(prompt: str, width: int = 1024, height: int = 1024, **kwargs) -> dict:
    """
    Generate an image using GPT Image 1.5 API via NexaAPI on RapidAPI.
    
    Args:
        prompt: Text description of the image to generate
        width: Image width in pixels (default: 1024)
        height: Image height in pixels (default: 1024)
        **kwargs: Additional model-specific parameters
    
    Returns:
        dict with 'url' key containing the generated image URL
    """
    url = f"https://{API_HOST}/generate"
    
    headers = {
        "x-rapidapi-key": RAPIDAPI_KEY,
        "x-rapidapi-host": API_HOST,
        "Content-Type": "application/json"
    }
    
    payload = {
        "prompt": prompt,
        "width": width,
        "height": height,
        **kwargs
    }
    
    response = requests.post(url, json=payload, headers=headers)
    response.raise_for_status()
    return response.json()


def batch_generate(prompts: list, **kwargs) -> list:
    """
    Generate multiple images from a list of prompts.
    Returns a list of result dicts.
    """
    results = []
    for i, prompt in enumerate(prompts):
        print(f"Generating image {i+1}/{len(prompts)}: {prompt[:50]}...")
        result = generate_image(prompt, **kwargs)
        results.append(result)
    return results


if __name__ == "__main__":
    # Example 1: Single image generation
    print("Generating single image...")
    result = generate_image(
        prompt="a majestic snow-capped mountain at sunrise, photorealistic, 8K",
        width=1024,
        height=1024
    )
    image_url = result.get("url") or result.get("images", [{}])[0].get("url")
    print(f"Image URL: {image_url}")
    
    # Example 2: Batch generation
    print("
Batch generating images...")
    prompts = [
        "a futuristic cityscape at night with neon lights",
        "a peaceful Japanese zen garden in autumn",
        "an underwater coral reef with colorful fish"
    ]
    batch_results = batch_generate(prompts, width=1024, height=1024)
    for i, r in enumerate(batch_results):
        url = r.get("url") or r.get("images", [{}])[0].get("url")
        print(f"Image {i+1}: {url}")

import requests
import time
import os

RAPIDAPI_KEY = os.environ.get("RAPIDAPI_KEY")
API_HOST = "gpt-image-1-5.p.rapidapi.com"

def generate_with_retry(prompt: str, max_retries: int = 3, **kwargs) -> dict:
    """Generate image with automatic retry on failure."""
    for attempt in range(max_retries):
        try:
            response = requests.post(
                f"https://{API_HOST}/generate",
                json={"prompt": prompt, **kwargs},
                headers={
                    "x-rapidapi-key": RAPIDAPI_KEY,
                    "x-rapidapi-host": API_HOST,
                    "Content-Type": "application/json"
                },
                timeout=60
            )
            response.raise_for_status()
            return response.json()
        except requests.exceptions.HTTPError as e:
            if e.response.status_code == 429:  # Rate limited
                wait_time = 2 ** attempt  # Exponential backoff
                print(f"Rate limited. Waiting {wait_time}s before retry {attempt+1}/{max_retries}")
                time.sleep(wait_time)
            elif e.response.status_code >= 500:  # Server error
                print(f"Server error {e.response.status_code}. Retry {attempt+1}/{max_retries}")
                time.sleep(1)
            else:
                raise  # Don't retry client errors (4xx except 429)
        except requests.exceptions.Timeout:
            print(f"Request timed out. Retry {attempt+1}/{max_retries}")
            time.sleep(2)
    
    raise Exception(f"Failed after {max_retries} retries")