Major version update with enhanced functionality
Added environment-based configuration to streamline deployments Improved data validation logic for more robust CRUD operations Refined folder structure to optimize code organization
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import torch
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from nodes import SaveImage
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import folder_paths
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class ExcuteCryptoNode:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"crypto_file_path": (
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"STRING",
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{"default": folder_paths.output_directory},
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)
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},
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"optional": {"input_anything": ("*",)},
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"hidden": {
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"unique_id": "UNIQUE_ID",
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"prompt": "PROMPT",
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"extra_pnginfo": "EXTRA_PNGINFO",
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},
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}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "excute"
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CATEGORY = "__hidden__"
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def excute(self, **kwargs):
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batch_size = 1
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height = 1024
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width = 1024
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color = 16711680
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r = torch.full([batch_size, height, width, 1], (color >> 16 & 255) / 255)
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g = torch.full([batch_size, height, width, 1], (color >> 8 & 255) / 255)
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b = torch.full([batch_size, height, width, 1], (color & 255) / 255)
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return (torch.cat((r, g, b), dim=-1),)
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class CryptoCatImage(SaveImage):
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def __init__(self):
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super().__init__()
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"images": ("IMAGE", {"tooltip": "The images to save."}),
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"filename_prefix": (
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"STRING",
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{
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"default": "ComfyUI",
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"tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes.",
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},
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),
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},
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"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
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}
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RETURN_TYPES = ()
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FUNCTION = "save_images"
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OUTPUT_NODE = True
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CATEGORY = "__hidden__"
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DESCRIPTION = "Saves the input images to your ComfyUI output directory."
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def save_images(
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self, images, filename_prefix="ComfyUI", prompt=None, extra_pnginfo=None
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):
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return super().save_images(images, filename_prefix, None, None)
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