108 lines
4.8 KiB
Python
108 lines
4.8 KiB
Python
import comfy.sd
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import comfy.samplers # For accessing lists of SAMPLERS and SCHEDULERS
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import folder_paths
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import json
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import inspect # For type verification
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# Define a custom type for "pipe" for better readability
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PIPE_TYPE_NAME = "PARAMS_PIPE"
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# --- Node 1: ModelParamsPipeNode ---
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class ModelParamsPipeNode:
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@classmethod
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def INPUT_TYPES(cls):
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samplers = comfy.samplers.KSampler.SAMPLERS
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schedulers = comfy.samplers.KSampler.SCHEDULERS
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return {
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"required": {
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"ckpt_name": (folder_paths.get_filename_list("checkpoints"),),
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"steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
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"cfg": ("FLOAT", {"default": 7.0, "min": 0.0, "max": 100.0, "step": 0.1}),
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"sampler_name": (samplers,),
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"scheduler": (schedulers,),
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"positive_tag": ("STRING", {"multiline": True, "default": ""}),
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"negative_tag": ("STRING", {"multiline": True, "default": ""}),
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"clip_skip": ("INT", {"default": -2, "min": -12, "max": 0, "step": 1}),
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},
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"optional": {
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"vae_override": ("VAE",),
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}
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}
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RETURN_TYPES = ("MODEL", "CLIP", "VAE",
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"INT", "FLOAT", "STRING", "STRING", "STRING", "STRING",
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PIPE_TYPE_NAME)
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RETURN_NAMES = ("MODEL", "CLIP", "VAE",
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"steps", "cfg", "sampler_name", "scheduler",
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"positive_tag", "negative_tag",
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"params_pipe")
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FUNCTION = "process_to_pipe"
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CATEGORY = "MultiModel"
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def process_to_pipe(self, ckpt_name, steps, cfg, sampler_name, scheduler,
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positive_tag, negative_tag, clip_skip, vae_override=None):
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ckpt_path = folder_paths.get_full_path("checkpoints", ckpt_name)
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out = comfy.sd.load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, embedding_directory=folder_paths.get_folder_paths("embeddings"))
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model = out[0]
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clip = out[1]
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vae_from_checkpoint = out[2]
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clip_skipped = clip.clone()
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clip_skipped.clip_layer(clip_skip)
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final_vae = vae_override if vae_override is not None else vae_from_checkpoint
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combined_params = {
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"ckpt_name": ckpt_name, "steps": steps, "cfg": cfg,
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"sampler_name": str(sampler_name), "scheduler": str(scheduler),
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"positive_tag": positive_tag.strip() if isinstance(positive_tag, str) else positive_tag,
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"negative_tag": negative_tag.strip() if isinstance(negative_tag, str) else negative_tag,
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"clip_skip": clip_skip
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}
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pipe_data = (model, clip_skipped, final_vae, combined_params)
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return (model, clip_skipped, final_vae, steps, cfg, str(sampler_name), str(scheduler),
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positive_tag, negative_tag, pipe_data)
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# --- Node 2: ParamsPipeUnpack ---
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class ParamsPipeUnpack:
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@classmethod
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def INPUT_TYPES(cls):
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return { "required": { "params_pipe": (PIPE_TYPE_NAME,), } }
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RETURN_TYPES = ("MODEL", "CLIP", "VAE", "INT", "FLOAT",
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comfy.samplers.KSampler.SAMPLERS, comfy.samplers.KSampler.SCHEDULERS,
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"STRING", "STRING", PIPE_TYPE_NAME)
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RETURN_NAMES = ("MODEL", "CLIP", "VAE", "steps", "cfg",
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"sampler_name", "scheduler",
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"positive_tag", "negative_tag", "params_pipe")
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FUNCTION = "unpack_pipe"
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CATEGORY = "MultiModel"
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def unpack_pipe(self, params_pipe):
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if not isinstance(params_pipe, tuple) or len(params_pipe) != 4:
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raise ValueError(f"Unpack: Expected PARAMS_PIPE tuple of length 4, but got: {type(params_pipe)}")
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model, clip, vae, params_dict = params_pipe
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if not isinstance(params_dict, dict):
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raise ValueError(f"Unpack: Expected dict as the 4th element in PARAMS_PIPE, but got: {type(params_dict)}")
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steps = params_dict.get("steps")
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cfg = params_dict.get("cfg")
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sampler_name = params_dict.get("sampler_name")
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scheduler = params_dict.get("scheduler")
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positive_tag = params_dict.get("positive_tag")
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negative_tag = params_dict.get("negative_tag")
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return (model, clip, vae, steps, cfg, sampler_name, scheduler,
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positive_tag, negative_tag, params_pipe)
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# --- Registration for only the first two nodes ---
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NODE_CLASS_MAPPINGS = {
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"ModelParamsPipeNode": ModelParamsPipeNode,
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"ParamsPipeUnpack": ParamsPipeUnpack
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}
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# --- Display names for only the first two nodes ---
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NODE_DISPLAY_NAME_MAPPINGS = {
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"ModelParamsPipeNode": "Model Parameters Pipe Hub",
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"ParamsPipeUnpack": "Unpack Parameters Pipe"
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}
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# Loading message
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print("✅ Loaded custom nodes (Reverted): ModelParamsPipeNode, ParamsPipeUnpack ▪B ▪B ▪С")
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