Sking / banana_pro_image.py
EntropyDrop
update
627f55a
Raw
History Blame Contribute Delete
3.97 kB
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 = "nano-banana-pro"
def generate_image(images=None, prompt="", aspect_ratio="1:1", image_size="2K"):
"""
Triggers an async image generation task via the Grsai nano-banana API.
: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"
:return: task_id string
"""
url = f"{IMAGE_API_BASE_URL}/v1/api/generate"
reference_images = prepare_reference_images(images)
payload = {
"model": MODEL_NAME,
"prompt": prompt,
"aspectRatio": aspect_ratio,
"imageSize": image_size,
"replyType": "async",
}
if reference_images:
payload["images"] = reference_images
payload_body = encode_json_request(payload)
headers = get_auth_headers(api_key=API_KEY)
print(f"[*] Sending Banana Pro ({MODEL_NAME}) async generation request to: {url}")
response = requests.post(url, data=payload_body, headers=headers)
response.raise_for_status()
res_json = response.json()
task_id = res_json.get("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"):
"""
Text-to-image API for Nano Banana Pro (nano-banana-pro).
"""
task_id = generate_image(
images=None,
prompt=prompt,
aspect_ratio=aspect_ratio,
image_size=image_size,
)
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"):
"""
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,
)
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 Nano Banana Pro model via Grsai API.")
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
)