""" LLS / Utils =========== 功能域：数据类型与逻辑工具（对应功能分类总览第 14 节） 职责：封装工作流编排所需的基础类型节点、数学运算、逻辑判断、 类型转换、分辨率辅助、曲线编辑、NOP 占位等节点。 开发规范 -------- - CATEGORY = "LLS/Utils" - 节点尽量纯 Python 实现，减少对 ComfyUI 内部模块的依赖 - 对外只暴露 NODE_CLASS_MAPPINGS 和 NODE_DISPLAY_NAME_MAPPINGS 节点列表（待实现） ------------------ - LLSStringLiteral : 字符串字面量节点 - LLSIntLiteral : 整数字面量节点 - LLSFloatLiteral : 浮点数字面量节点 - LLSBoolLiteral : 布尔字面量节点 - LLSMathOp : 数学运算（加减乘除/取模/幂/对数） - LLSLogicOp : 逻辑判断（与/或/非/比较） - LLSIfElse : If/Else 条件分支 - LLSTypeConvert : 类型转换（数字 ↔ 字符串） - LLSResolutionSelector : 常用分辨率选择器（含宽高比计算） - LLSBezierCurve : 贝塞尔曲线数值生成 - LLSStringFormat : 字符串格式化（f-string 风格） - LLSStringConcat : 字符串拼接 - LLSRegexReplace : 正则替换 - LLSNop : 透传占位节点（调试用） - LLSPreviewAny : 预览任意数据类型（String/Number/Dict） """ from __future__ import annotations from .concat_by_target import ( NODE_CLASS_MAPPINGS as CONCAT_NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS as CONCAT_NODE_DISPLAY_NAME_MAPPINGS, ) from .model_info import ( FAMILY_DEFAULT_PRESET, MODEL_FAMILY_CHOICES, SIZE_PRESET_AUTO, get_family_defaults, get_sampling_preset, info_to_json, resolve_model_family, ) # ---------- 节点类示例（基础类型，纯 Python 无外部依赖） ---------- class LLSStringLiteral: """输出一个字符串常量，可复用于多个下游节点。""" CATEGORY = "LLS/Utils" FUNCTION = "execute" RETURN_TYPES = ("STRING",) RETURN_NAMES = ("string",) DESCRIPTION = "Output a constant string value." @classmethod def INPUT_TYPES(cls): return { "required": { "value": ("STRING", {"default": "", "multiline": True}), } } def execute(self, value: str): return (value,) class LLSIntLiteral: """输出一个整数常量。""" CATEGORY = "LLS/Utils" FUNCTION = "execute" RETURN_TYPES = ("INT",) RETURN_NAMES = ("int",) DESCRIPTION = "Output a constant integer value." @classmethod def INPUT_TYPES(cls): return { "required": { "value": ("INT", {"default": 0, "min": -2**31, "max": 2**31 - 1}), } } def execute(self, value: int): return (value,) class LLSFloatLiteral: """输出一个浮点数常量。""" CATEGORY = "LLS/Utils" FUNCTION = "execute" RETURN_TYPES = ("FLOAT",) RETURN_NAMES = ("float",) DESCRIPTION = "Output a constant float value." @classmethod def INPUT_TYPES(cls): return { "required": { "value": ("FLOAT", {"default": 0.0, "step": 0.01}), } } def execute(self, value: float): return (value,) class LLSResolutionSelector: """常用分辨率选择器，返回宽和高。""" CATEGORY = "LLS/Utils" FUNCTION = "execute" RETURN_TYPES = ("INT", "INT") RETURN_NAMES = ("width", "height") DESCRIPTION = "Select from common resolutions or enter custom width/height." _PRESETS = [ "Custom", "512x512", "768x768", "1024x1024", "512x768", "768x512", "768x1024", "1024x768", "1024x576", "576x1024", "1280x720", "720x1280", "1920x1080", "1080x1920", "2048x2048", ] @classmethod def INPUT_TYPES(cls): return { "required": { "preset": (cls._PRESETS, {"default": "1024x1024"}), "custom_width": ("INT", {"default": 1024, "min": 64, "max": 8192, "step": 8}), "custom_height": ("INT", {"default": 1024, "min": 64, "max": 8192, "step": 8}), } } def execute(self, preset: str, custom_width: int, custom_height: int): if preset == "Custom": return (custom_width, custom_height) w, h = preset.split("x") return (int(w), int(h)) class LLSGenerationConfig: """按模型家族输出推荐分辨率与采样配置。""" CATEGORY = "LLS/Utils" FUNCTION = "execute" RETURN_TYPES = ("INT", "INT", "INT", "FLOAT", "FLOAT", "STRING", "STRING", "FLOAT", "STRING") RETURN_NAMES = ("width", "height", "steps", "cfg", "guidance", "sampler_name", "scheduler", "denoise", "config_info") DESCRIPTION = "Generate family-aware default width/height and sampling parameters." _QUALITY_PRESETS = [FAMILY_DEFAULT_PRESET, "Manual", "Fast", "Balanced", "High Quality"] _SIZE_PRESETS = [SIZE_PRESET_AUTO, "Custom", "512x512", "768x768", "1024x1024"] @classmethod def INPUT_TYPES(cls): return { "required": { "quality_preset": (cls._QUALITY_PRESETS, {"default": FAMILY_DEFAULT_PRESET}), "size_preset": (cls._SIZE_PRESETS, {"default": SIZE_PRESET_AUTO}), "model_family": (MODEL_FAMILY_CHOICES, {"default": "Auto"}), }, "optional": { "model": ("MODEL",), "clip": ("CLIP",), }, } def execute(self, quality_preset: str, size_preset: str, model_family: str = "Auto", model=None, clip=None): family = resolve_model_family(model_family, model=model, clip=clip) defaults = get_family_defaults(family) preset = get_sampling_preset(defaults, quality_preset) or { "steps": defaults["default_steps"], "cfg": defaults["default_cfg"], "guidance": defaults["default_guidance"], "sampler_name": defaults["default_sampler"], "scheduler": defaults["default_scheduler"], "denoise": defaults["default_denoise"], } if size_preset == SIZE_PRESET_AUTO: width = defaults["default_width"] height = defaults["default_height"] elif size_preset == "Custom": width = defaults["default_width"] height = defaults["default_height"] else: width, height = [int(part) for part in size_preset.split("x", 1)] guidance = preset.get("guidance") guidance = 0.0 if guidance is None else float(guidance) config_info = info_to_json( { "family": family, "width": width, "height": height, "steps": int(preset["steps"]), "cfg": float(preset["cfg"]), "guidance": guidance, "sampler_name": str(preset["sampler_name"]), "scheduler": str(preset["scheduler"]), "denoise": float(preset["denoise"]), "quality_preset": quality_preset, "size_preset": size_preset, } ) return ( int(width), int(height), int(preset["steps"]), float(preset["cfg"]), guidance, str(preset["sampler_name"]), str(preset["scheduler"]), float(preset["denoise"]), config_info, ) # ---------- 注册表 ---------- NODE_CLASS_MAPPINGS: dict[str, type] = { "LLSStringLiteral": LLSStringLiteral, "LLSIntLiteral": LLSIntLiteral, "LLSFloatLiteral": LLSFloatLiteral, "LLSResolutionSelector": LLSResolutionSelector, "LLSGenerationConfig": LLSGenerationConfig, } NODE_CLASS_MAPPINGS.update(CONCAT_NODE_CLASS_MAPPINGS) NODE_DISPLAY_NAME_MAPPINGS: dict[str, str] = { "LLSStringLiteral": "LLS String Literal", "LLSIntLiteral": "LLS Int Literal", "LLSFloatLiteral": "LLS Float Literal", "LLSResolutionSelector": "LLS Resolution Selector", "LLSGenerationConfig": "LLS Generation Config", } NODE_DISPLAY_NAME_MAPPINGS.update(CONCAT_NODE_DISPLAY_NAME_MAPPINGS)