import argparse import requests from image_api_utils import ( IMAGE_API_BASE_URL, API_KEY, encode_json_request, get_auth_headers, poll_and_download_result, prepare_reference_images, ) MODEL_NAME = "gemini-3-pro-image-preview" def generate_image(images=None, prompt="", aspect_ratio="1:1", image_size="2K", notify_url=None): """ Triggers the image generation task using the Nano Banana Pro (gemini-3-pro-image-preview) model. :param images: Up to 14 local image paths, HTTP(S) URLs, or base64 data URLs. :param prompt: Text prompt describing the desired image content. :param aspect_ratio: Image aspect ratio. Allowed: "1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9" :param image_size: Image resolution/quality. Allowed: "1K", "2K", "4K" :param notify_url: Optional webhook URL for async callback. :return: task_id string/int """ url = f"{IMAGE_API_BASE_URL}/v1/media/generate" params = { "aspectRatio": aspect_ratio, "imageSize": image_size } reference_images = prepare_reference_images(images) if reference_images: params["images"] = reference_images payload = { "model": MODEL_NAME, "params": params, "prompt": prompt } if notify_url: payload["notify_url"] = notify_url payload_body = encode_json_request(payload) headers = get_auth_headers(api_key=API_KEY) print(f"[*] Sending Banana Pro ({MODEL_NAME}) generation request to: {url}") response = requests.post(url, data=payload_body, headers=headers) response.raise_for_status() res_json = response.json() # Try parsing task_id from root or nested "data" dictionary task_id = res_json.get("task_id") if not task_id and "data" in res_json and isinstance(res_json["data"], dict): task_id = res_json["data"].get("task_id") if not task_id: raise ValueError(f"Failed to obtain task_id from response: {res_json}") print(f"[+] Task created successfully. Task ID: {task_id}") return task_id def generate_txt2img(prompt, output_path=None, aspect_ratio="1:1", image_size="2K", notify_url=None): """ Text-to-image API for Nano Banana Pro (gemini-3-pro-image-preview). """ task_id = generate_image( images=None, prompt=prompt, aspect_ratio=aspect_ratio, image_size=image_size, notify_url=notify_url, ) return poll_and_download_result( task_id=task_id, output_path=output_path, default_prefix="banana_pro_result", ) def generate_img2img(local_image_paths, prompt, output_path=None, aspect_ratio="1:1", image_size="2K", notify_url=None): """ Image-to-image API accepting local paths, HTTP(S) URLs, or base64 data URLs. """ task_id = generate_image( images=local_image_paths, prompt=prompt, aspect_ratio=aspect_ratio, image_size=image_size, notify_url=notify_url, ) return poll_and_download_result( task_id=task_id, output_path=output_path, default_prefix="banana_pro_result", ) if __name__ == '__main__': parser = argparse.ArgumentParser(description="Generate image using Gemini 3 Pro (Nano Banana Pro) model.") parser.add_argument("prompt", help="Text prompt for image generation.") parser.add_argument( "-i", "--images", nargs="+", help="Reference image path(s), HTTP(S) URL(s), or base64 data URL(s), up to 14.", ) parser.add_argument("-o", "--output", help="Output path for the generated image.") parser.add_argument("-a", "--aspect-ratio", default="1:1", choices=["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9"], help="Aspect ratio (default: 1:1).") parser.add_argument("-s", "--image-size", default="2K", choices=["1K", "2K", "4K"], help="Resolution size (default: 2K).") args = parser.parse_args() if args.images: generate_img2img( local_image_paths=args.images, prompt=args.prompt, output_path=args.output, aspect_ratio=args.aspect_ratio, image_size=args.image_size ) else: generate_txt2img( prompt=args.prompt, output_path=args.output, aspect_ratio=args.aspect_ratio, image_size=args.image_size )