class OpenAIDalle2(ComfyNodeABC):
"""
Generates images synchronously via OpenAI's DALL·E 2 endpoint.
Uses the proxy at /proxy/openai/images/generations. Returned URLs are short‑lived,
so download or cache results if you need to keep them.
"""
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls) -> InputTypeDict:
return {
"required": {
"prompt": (
IO.STRING,
{
"multiline": True,
"default": "",
"tooltip": "Text prompt for DALL·E",
},
),
},
"optional": {
"seed": (
IO.INT,
{
"default": 0,
"min": 0,
"max": 2**31 - 1,
"step": 1,
"display": "number",
"control_after_generate": True,
"tooltip": "not implemented yet in backend",
},
),
"size": (
IO.COMBO,
{
"options": ["256x256", "512x512", "1024x1024"],
"default": "1024x1024",
"tooltip": "Image size",
},
),
"n": (
IO.INT,
{
"default": 1,
"min": 1,
"max": 8,
"step": 1,
"display": "number",
"tooltip": "How many images to generate",
},
),
"image": (
IO.IMAGE,
{
"default": None,
"tooltip": "Optional reference image for image editing.",
},
),
"mask": (
IO.MASK,
{
"default": None,
"tooltip": "Optional mask for inpainting (white areas will be replaced)",
},
),
},
"hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
}
RETURN_TYPES = (IO.IMAGE,)
FUNCTION = "api_call"
CATEGORY = "api node/image/openai"
DESCRIPTION = cleandoc(__doc__ or "")
API_NODE = True
def api_call(
self,
prompt,
seed=0,
image=None,
mask=None,
n=1,
size="1024x1024",
auth_token=None,
):
model = "dall-e-2"
path = "/proxy/openai/images/generations"
content_type = "application/json"
request_class = OpenAIImageGenerationRequest
img_binary = None
if image is not None and mask is not None:
path = "/proxy/openai/images/edits"
content_type = "multipart/form-data"
request_class = OpenAIImageEditRequest
input_tensor = image.squeeze().cpu()
height, width, channels = input_tensor.shape
rgba_tensor = torch.ones(height, width, 4, device="cpu")
rgba_tensor[:, :, :channels] = input_tensor
if mask.shape[1:] != image.shape[1:-1]:
raise Exception("Mask and Image must be the same size")
rgba_tensor[:, :, 3] = 1 - mask.squeeze().cpu()
rgba_tensor = downscale_image_tensor(rgba_tensor.unsqueeze(0)).squeeze()
image_np = (rgba_tensor.numpy() * 255).astype(np.uint8)
img = Image.fromarray(image_np)
img_byte_arr = io.BytesIO()
img.save(img_byte_arr, format="PNG")
img_byte_arr.seek(0)
img_binary = img_byte_arr # .getvalue()
img_binary.name = "image.png"
elif image is not None or mask is not None:
raise Exception("Dall-E 2 image editing requires an image AND a mask")
# Build the operation
operation = SynchronousOperation(
endpoint=ApiEndpoint(
path=path,
method=HttpMethod.POST,
request_model=request_class,
response_model=OpenAIImageGenerationResponse,
),
request=request_class(
model=model,
prompt=prompt,
n=n,
size=size,
seed=seed,
),
files=(
{
"image": img_binary,
}
if img_binary
else None
),
content_type=content_type,
auth_token=auth_token,
)
response = operation.execute()
img_tensor = validate_and_cast_response(response)
return (img_tensor,)
