153 lines
5.0 KiB
Python
153 lines
5.0 KiB
Python
"""
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LLS / Conditioning
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==================
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功能域：文本编码与条件生成（对应功能分类总览第 2 节）
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CATEGORY = "LLS/Conditioning"
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"""
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from __future__ import annotations
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# ---------- 防御性导入 ----------
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# （本节点直接调用 clip 对象方法，无需额外导入 comfy.sd）
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_CLIP_SKIP_CHOICES = [None] + list(range(-1, -25, -1))
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def _encode_conditioning(clip, prompt: str):
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"""
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兼容新旧 ComfyUI 的文本编码入口。
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新版本优先使用 `encode_from_tokens_scheduled()`；
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若运行环境较旧，仅存在 `encode_from_tokens()`，则手动包装成
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ComfyUI 约定的 CONDITIONING 结构。
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"""
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tokens = clip.tokenize(prompt)
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scheduled = getattr(clip, "encode_from_tokens_scheduled", None)
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if callable(scheduled):
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return scheduled(tokens)
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plain_encode = getattr(clip, "encode_from_tokens", None)
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if not callable(plain_encode):
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raise AttributeError(
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"CLIP object does not expose encode_from_tokens_scheduled() "
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"or encode_from_tokens()."
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)
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try:
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pooled_dict = plain_encode(tokens, return_pooled=True, return_dict=True)
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except TypeError:
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encoded = plain_encode(tokens, return_pooled=True)
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if isinstance(encoded, tuple):
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cond, pooled = encoded[:2]
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pooled_dict = {"cond": cond, "pooled_output": pooled}
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else:
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pooled_dict = {"cond": encoded}
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if not isinstance(pooled_dict, dict) or "cond" not in pooled_dict:
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raise RuntimeError("[LLS] Legacy CLIP encode_from_tokens() returned an unsupported value.")
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cond = pooled_dict.pop("cond")
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return [[cond, pooled_dict]]
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def _normalize_clip_skip(value) -> int:
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"""
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兼容旧工作流中的 null / None，以及字符串形式的 clip_skip。
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"""
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if value in (None, "", "None"):
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return -1
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try:
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normalized = int(value)
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except (TypeError, ValueError) as exc:
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raise RuntimeError(f"[LLS] Invalid clip_skip value: {value!r}") from exc
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if normalized < -24 or normalized > -1:
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raise RuntimeError(f"[LLS] clip_skip out of supported range [-24, -1]: {normalized}")
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return normalized
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# ---------- 节点类 ----------
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class LLSSimplePromptEncode:
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"""
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简化版提示词编码节点。
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优先复用 ComfyUI 原生 clip.encode_from_tokens_scheduled()，
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旧版环境下自动回退到 encode_from_tokens()，
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以兼容 SD1.5 / SDXL 的常见 CLIP 编码路径。
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"""
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CATEGORY = "LLS/Conditioning"
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FUNCTION = "encode"
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RETURN_TYPES = ("CONDITIONING", "CONDITIONING", "STRING")
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RETURN_NAMES = ("positive", "negative", "prompt_info")
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DESCRIPTION = (
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"Encode positive and negative prompts into CONDITIONING tensors. "
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"Prefers ComfyUI native encode_from_tokens_scheduled and falls back to "
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"encode_from_tokens for older runtimes."
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)
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"clip": ("CLIP",),
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"positive_prompt": ("STRING", {"default": "", "multiline": True}),
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"negative_prompt": ("STRING", {"default": "", "multiline": True}),
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"clip_skip": (_CLIP_SKIP_CHOICES, {"default": -1}),
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}
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}
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def encode(self, clip, positive_prompt: str, negative_prompt: str, clip_skip):
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if clip is None:
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raise RuntimeError(
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"[LLS] CLIP is None. Make sure a checkpoint is loaded before connecting to this node."
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)
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clip_skip = _normalize_clip_skip(clip_skip)
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# 应用 clip_skip（ComfyUI CLIP 对象支持 clip_layer）
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if clip_skip != -1:
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try:
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clip = clip.clone()
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clip.clip_layer(clip_skip)
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except Exception:
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# clip_layer 不可用时静默忽略，不阻断流程
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pass
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# 编码 positive — 复用 ComfyUI 原生编码入口
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try:
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positive = _encode_conditioning(clip, positive_prompt)
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except Exception as exc:
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raise RuntimeError(
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f"[LLS] Failed to encode positive prompt: {exc}"
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) from exc
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# 编码 negative — 复用 ComfyUI 原生编码入口
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try:
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negative = _encode_conditioning(clip, negative_prompt)
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except Exception as exc:
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raise RuntimeError(
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f"[LLS] Failed to encode negative prompt: {exc}"
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) from exc
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pos_preview = positive_prompt[:60].replace("\n", " ")
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neg_preview = negative_prompt[:40].replace("\n", " ")
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prompt_info = (
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f"clip_skip={clip_skip} "
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f"| pos=\"{pos_preview}...\" | neg=\"{neg_preview}...\""
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)
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return (positive, negative, prompt_info)
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# ---------- 注册表 ----------
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NODE_CLASS_MAPPINGS: dict[str, type] = {
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"LLSSimplePromptEncode": LLSSimplePromptEncode,
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}
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NODE_DISPLAY_NAME_MAPPINGS: dict[str, str] = {
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"LLSSimplePromptEncode": "LLS Simple Prompt Encode",
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}
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