class LumaImageModifyNode(ComfyNodeABC):
"""
Modifies images synchronously based on prompt and aspect ratio.
"""
RETURN_TYPES = (IO.IMAGE,)
DESCRIPTION = cleandoc(__doc__ or "")
FUNCTION = "api_call"
API_NODE = True
CATEGORY = "api node/image/Luma"
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"image": (IO.IMAGE,),
"prompt": (
IO.STRING,
{
"multiline": True,
"default": "",
"tooltip": "Prompt for the image generation",
},
),
"image_weight": (
IO.FLOAT,
{
"default": 1.0,
"min": 0.02,
"max": 1.0,
"step": 0.01,
"tooltip": "Weight of the image; the closer to 0.0, the less the image will be modified.",
},
),
"model": ([model.value for model in LumaImageModel],),
"seed": (
IO.INT,
{
"default": 0,
"min": 0,
"max": 0xFFFFFFFFFFFFFFFF,
"control_after_generate": True,
"tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
},
),
},
"optional": {},
"hidden": {
"auth_token": "AUTH_TOKEN_COMFY_ORG",
},
}
def api_call(
self,
prompt: str,
model: str,
image: torch.Tensor,
image_weight: float,
seed,
auth_token=None,
**kwargs,
):
download_urls = upload_images_to_comfyapi(
image, max_images=1, auth_token=auth_token
)
image_url = download_urls[0]
operation = SynchronousOperation(
endpoint=ApiEndpoint(
path="/proxy/luma/generations/image",
method=HttpMethod.POST,
request_model=LumaImageGenerationRequest,
response_model=LumaGeneration,
),
request=LumaImageGenerationRequest(
prompt=prompt,
model=model,
modify_image_ref=LumaModifyImageRef(
url=image_url, weight=round(image_weight, 2)
),
),
auth_token=auth_token,
)
response_api: LumaGeneration = operation.execute()
operation = PollingOperation(
poll_endpoint=ApiEndpoint(
path=f"/proxy/luma/generations/{response_api.id}",
method=HttpMethod.GET,
request_model=EmptyRequest,
response_model=LumaGeneration,
),
completed_statuses=[LumaState.completed],
failed_statuses=[LumaState.failed],
status_extractor=lambda x: x.state,
auth_token=auth_token,
)
response_poll = operation.execute()
img_response = requests.get(response_poll.assets.image)
img = process_image_response(img_response)
return (img,)
