97 lines
3.1 KiB
Markdown
97 lines
3.1 KiB
Markdown
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# Documentation
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- Class name: AV_LoraListStacker
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- Category: Art Venture/Loaders
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- Output node: False
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- Repo Ref: https://github.com/comfyanonymous/ComfyUI
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AV_LoraListStacker节点旨在管理和堆叠Lora模型的配置，促进多个Lora模型动态集成并应用到处理流程中。它抽象了处理Lora模型参数的复杂性，确保模型的应用顺序尊重预期的分层和强度调整。
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# Input types
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## Required
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- data
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- 'data'输入包含了JSON格式的Lora模型列表及其配置，规定了每个Lora模型应如何应用于基础模型。
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- Comfy dtype: STRING
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- Python dtype: str
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## Optional
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- base_url
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- 'base_url'可选输入提供了一个默认的URL前缀，用于获取本地不可用的Lora模型，便于远程模型检索。
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- Comfy dtype: STRING
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- Python dtype: str
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- lora_stack
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- 'lora_stack'输入允许包含现有的Lora模型堆栈，以进行进一步处理或与新的Lora配置集成。
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- Comfy dtype: LORA_STACK
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- Python dtype: list
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# Output types
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- lora_stack
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- 返回整合了指定Lora模型调整后的更新后的Lora模型堆栈。
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- Comfy dtype: LORA_STACK
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- Python dtype: list
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## Usage tips
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- Infra type: `CPU`
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- Common nodes: unknown
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## Source code
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```python
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class AVLoraListStacker:
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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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"data": ("STRING", {"default": "", "multiline": True, "dynamicPrompts": False}),
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},
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"optional": {"base_url": ("STRING", {"default": lora_cloud_front_url}), "lora_stack": ("LORA_STACK",)},
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}
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RETURN_TYPES = ("LORA_STACK",)
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FUNCTION = "load_list_lora"
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CATEGORY = "Art Venture/Loaders"
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def parse_lora_list(self, data: str, base_url: str):
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# data is a list of lora model (lora_name, strength_model, strength_clip, url) in json format
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# trim data
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data = data.strip()
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if data == "" or data == "[]" or data is None:
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return []
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print(f"Loading lora list: {data}")
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lora_list = json.loads(data)
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if len(lora_list) == 0:
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return []
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available_loras = folder_paths.get_filename_list("loras")
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model_path = os.path.join(folder_paths.models_dir, "loras")
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lora_params = []
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for lora in lora_list:
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lora_name = lora["name"]
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strength_model = lora["strength"]
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strength_clip = lora["strength"]
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lora_url = lora.get("url", None)
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if strength_model == 0 and strength_clip == 0:
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continue
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if lora_name not in available_loras:
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lora_url = lora_url or f"{base_url}/models/loras/{lora_name}"
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load_file_from_url(lora_url, model_dir=model_path, file_name=lora_name)
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lora_params.append((lora_name, strength_model, strength_clip))
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return lora_params
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def load_list_lora(self, data, base_url=lora_cloud_front_url, lora_stack=None):
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loras = self.parse_lora_list(data, base_url=base_url)
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if lora_stack is not None:
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loras.extend([l for l in lora_stack if l[0] != "None"])
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return (loras,)
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```
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