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convert nodes_hidream.py to V3 schema (#9946)

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Alexander Piskun 2025-09-27 09:13:05 +03:00 committed by GitHub
parent 255572188f
commit a9cf1cd249
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1 changed files with 53 additions and 35 deletions
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88
comfy_extras/nodes_hidream.py
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@ -1,55 +1,73 @@
from typing_extensions import override
import folder_paths
import comfy.sd
import comfy.model_management
from comfy_api.latest import ComfyExtension, io
class QuadrupleCLIPLoader:
class QuadrupleCLIPLoader(io.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": { "clip_name1": (folder_paths.get_filename_list("text_encoders"), ),
"clip_name2": (folder_paths.get_filename_list("text_encoders"), ),
"clip_name3": (folder_paths.get_filename_list("text_encoders"), ),
"clip_name4": (folder_paths.get_filename_list("text_encoders"), )
}}
RETURN_TYPES = ("CLIP",)
FUNCTION = "load_clip"
def define_schema(cls):
return io.Schema(
node_id="QuadrupleCLIPLoader",
category="advanced/loaders",
description="[Recipes]\n\nhidream: long clip-l, long clip-g, t5xxl, llama_8b_3.1_instruct",
inputs=[
io.Combo.Input("clip_name1", options=folder_paths.get_filename_list("text_encoders")),
io.Combo.Input("clip_name2", options=folder_paths.get_filename_list("text_encoders")),
io.Combo.Input("clip_name3", options=folder_paths.get_filename_list("text_encoders")),
io.Combo.Input("clip_name4", options=folder_paths.get_filename_list("text_encoders")),
],
outputs=[
io.Clip.Output(),
]
)
CATEGORY = "advanced/loaders"
DESCRIPTION = "[Recipes]\n\nhidream: long clip-l, long clip-g, t5xxl, llama_8b_3.1_instruct"
def load_clip(self, clip_name1, clip_name2, clip_name3, clip_name4):
@classmethod
def execute(cls, clip_name1, clip_name2, clip_name3, clip_name4):
clip_path1 = folder_paths.get_full_path_or_raise("text_encoders", clip_name1)
clip_path2 = folder_paths.get_full_path_or_raise("text_encoders", clip_name2)
clip_path3 = folder_paths.get_full_path_or_raise("text_encoders", clip_name3)
clip_path4 = folder_paths.get_full_path_or_raise("text_encoders", clip_name4)
clip = comfy.sd.load_clip(ckpt_paths=[clip_path1, clip_path2, clip_path3, clip_path4], embedding_directory=folder_paths.get_folder_paths("embeddings"))
return (clip,)
return io.NodeOutput(clip)
class CLIPTextEncodeHiDream:
class CLIPTextEncodeHiDream(io.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": {
"clip": ("CLIP", ),
"clip_l": ("STRING", {"multiline": True, "dynamicPrompts": True}),
"clip_g": ("STRING", {"multiline": True, "dynamicPrompts": True}),
"t5xxl": ("STRING", {"multiline": True, "dynamicPrompts": True}),
"llama": ("STRING", {"multiline": True, "dynamicPrompts": True})
}}
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "encode"
CATEGORY = "advanced/conditioning"
def encode(self, clip, clip_l, clip_g, t5xxl, llama):
def define_schema(cls):
return io.Schema(
node_id="CLIPTextEncodeHiDream",
category="advanced/conditioning",
inputs=[
io.Clip.Input("clip"),
io.String.Input("clip_l", multiline=True, dynamic_prompts=True),
io.String.Input("clip_g", multiline=True, dynamic_prompts=True),
io.String.Input("t5xxl", multiline=True, dynamic_prompts=True),
io.String.Input("llama", multiline=True, dynamic_prompts=True),
],
outputs=[
io.Conditioning.Output(),
]
)
@classmethod
def execute(cls, clip, clip_l, clip_g, t5xxl, llama):
tokens = clip.tokenize(clip_g)
tokens["l"] = clip.tokenize(clip_l)["l"]
tokens["t5xxl"] = clip.tokenize(t5xxl)["t5xxl"]
tokens["llama"] = clip.tokenize(llama)["llama"]
return (clip.encode_from_tokens_scheduled(tokens), )
return io.NodeOutput(clip.encode_from_tokens_scheduled(tokens))
NODE_CLASS_MAPPINGS = {
"QuadrupleCLIPLoader": QuadrupleCLIPLoader,
"CLIPTextEncodeHiDream": CLIPTextEncodeHiDream,
}
class HiDreamExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [
QuadrupleCLIPLoader,
CLIPTextEncodeHiDream,
]
async def comfy_entrypoint() -> HiDreamExtension:
return HiDreamExtension()