完整 JSON
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"## 🎨 一、文生图\n\n### 🧱 底图模式：二选一\n\n- **普通底图**：只生成底图，流程简单，推荐新手使用。\n- **双采样底图**：集成「底图生成 + 潜空间放大 + 二次采样」。首次采样完成底图，经 **SesquiLSR** 放大潜空间后，再由第二次采样补充细节，无需中途反复 VAE 解码和编码。两次采样可分别设置 CFG、采样器、调度器和 LoRA。\n\n> 例如总步数为 8、切换步数为 4：首次采样 8 步，第二次从第 4 步运行到第 8 步，共计 12 步。\n\n### 💬 模型与提示词\n\n- **Krea 2（默认）**：主要使用**自然语言**，支持中、日、英文。擅长 SFW、复杂构图与精细表现，但更吃配置、速度较慢，同人角色知识及 NSFW 表现较弱。\n- **Anima（可选）**：支持 **Tag、自然语言及混合提示词**，支持 NSFW，同人角色知识更丰富，配置要求较低、速度更快。[提示词说明](https://huggingface.co/circlestone-labs/Anima#prompting)\n\n> **Anima 系列推荐使用自带放大的「双采样底图」，不建议再开启独立的「潜空间放大」组。** 如需进一步提高清晰度或分辨率，可按需追加 **SeedVR2** 或 **N 卡放大**。\n\n### 🔎 SeedVR2：放大与修复\n\n偏向**去噪、修复与纹理重建**，适合底图有脏污、噪点或局部模糊的情况，也可能改变或抹掉部分原有细节。\n\n> 需额外下载模型，地址见工作流中的 **「必看」** 注释。\n\n### ⚡ N 卡放大：放大与光影优化\n\n按 **VSR → DLSS-NR** 顺序处理：\n\n- **VSR**：提高分辨率，默认 **2 倍放大 + ULTRA 质量**。\n- **DLSS-NR**：进行同分辨率神经渲染，调整光影与局部结构，不再增加尺寸。默认 **「电影」风格**，强度、局部光影、局部细节与输出混合均为 **1**。\n\n调整方法：\n\n- **光影变化太大**：降低「局部光影」。\n- **轮廓或细节变化太多**：降低「局部细节」。\n- **整体效果太强**：降低「输出混合」；设为 **0** 时保留 VSR 放大结果。\n\n> 当前 DLSS-NR 插件支持 **Windows + RTX 30 / 40 / 50 系列**，首次运行需联网下载对应运行文件。[插件说明](https://github.com/storyAura/DLSS5-Comfyui)\n\n### 🔗 如何搭配\n\n**需要修复选 SeedVR2，需要放大并优化光影选 N 卡放大，通常二选一即可。**\n\n> 两个底图组只开启一个。各处理阶段按顺序接力，多个放大阶段会叠加倍率；只开启需要的组，注意最终尺寸、显存占用与耗时。\n\n---\n\n## 📦 二、可选功能\n\n### 🖼️ 画廊与图像反推\n\n同时开启时，图像反推优先使用**画廊中选择的图像**。\n\n### ✍️ 反推提示词\n\n反推结果会**替换正面主提示词**，保留原有前缀与后缀。\n\n### ✨ 正面提示词优化\n\n在主提示词、前缀和后缀组合完成后，进行最终优化。\n\n> **处理顺序：**画廊图像 → 图像反推 → 替换主提示词 → 拼接前后缀 → 正面提示词优化。"
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"# ⚠️ 须知\n\n此工作流**完全免费开源**，并提供配套定制化插件。 \n如在使用过程中遇到问题，欢迎前往 Discord 反馈，或在对应插件仓库提交 Issue。\n\n## 🔌 配套插件列表\n> 以下仅列出作者本人开发的插件，不包含工作流依赖的其他第三方插件\n\n### 一、核心插件\n- 🏠 **地址**：[GitHub 仓库](https://github.com/Aaalice233/ComfyUI-Aaalice-Nodes) \n- ✨ **功能**：侧边栏控制面板、组跳转轮盘、提示词选择器、booru 画廊、分辨率预设等\n\n### 二、自动补全插件（二开增强版）\n- 🏠 **地址**：[GitHub 仓库](https://github.com/Aaalice233/ComfyUI-Autocomplete-Aaalice) \n- ✨ **功能**：基于上游仓库的增强维护版本，支持 Danbooru 标签在线拉取、Lora Manager联动、第三方汉化数据库接入及 LLM 汉化接口\n\n### 三、工作流订阅管理插件\n- 🏠 **地址**：[GitHub 仓库](https://github.com/Aaalice233/ComfyUI-Aaalice-Workflow-Hub) \n- ✨ **功能**：在 ComfyUI 内直接查看工作流列表、更新日志并快速订阅更新\n\n### 四、图像选择器插件\n- 🏠 **地址**：[GitHub 仓库](https://github.com/Aaalice233/ComfyUI-Aaalice-Image-Picker) \n- ✨ **功能**：在工作流中暂停执行并人工筛选批次图像，支持单选/多选、局部缩放对比和超时策略；底图和局部重绘组均使用它确认候选结果\n\n---\n\n# 🐱 Discord 社区与教程\n\n- 💬 [加入 Discord 服务器](https://discord.gg/R48n6GwXzD)\n- 🎓 [打开工作流安装与使用教程频道](https://discord.com/channels/1349298998988771359/1536643406787387392)\n\n> ⚠️ 如果尚未加入服务器，频道链接会无法打开。请先通过上方邀请链接加入服务器，再打开教程频道。\n\n# 📦 工作流仓库地址\n[GitHub 仓库](https://github.com/Aaalice233/Aaalice-Workflows) \n\n推荐配合订阅管理插件使用，可快速检查更新、查看列表、下载和补全依赖等： \n[订阅管理插件仓库](https://github.com/Aaalice233/ComfyUI-Aaalice-Workflow-Hub)\n\n# 💡 使用技巧\n- 🖱️ 点击侧边栏中样式为大写字母 **「A」** 的按钮，即可快速打开工作流定制控制面板（支持调参、预设管理、组跳转设置、提示词词库管理等）\n- ⌨️ 默认情况下，按下波浪号键（**~**）可快速呼出组跳转轮盘\n- 🟣 被**紫色边框**包裹的参数，表示该参数受侧边栏控制\n\n---\n\n# 📥 模型下载列表（按所选底模与功能下载）\n\n> 当前默认底模为 **SilvermoonMix Anima v2.3 2.9B Turbo**。侧边栏预设提供 **「默认-Anima-2.9B-Turbo-Silvermoon」**、**「默认-Anima-2.9B-Silvermoon」** 和 **「默认-Krea2-Turbo-Int8」**，请按所选预设下载对应模型，无需全部下载。 \n> SilvermoonMix 的 UNet 请从下方 Civitai 对应版本页面下载；CLIP、VAE 继续使用表中 Hugging Face 链接。 \n> 下载后请将文件放置到对应目录，并重启 ComfyUI。\n\n## 🎨 Krea2（可选底模）\n\n| 类型 | 模型文件名 | 下载链接 | 本地放置路径 |\n|------|------------|----------|--------------|\n| **UNet** | `krea2_turbo_int8_convrot.safetensors` | [下载](https://huggingface.co/Comfy-Org/Krea-2/resolve/main/diffusion_models/krea2_turbo_int8_convrot.safetensors) | `ComfyUI/models/diffusion_models/` |\n| **CLIP** | `qwen3vl_4b_fp8_scaled.safetensors` | [下载](https://huggingface.co/Comfy-Org/Krea-2/resolve/main/text_encoders/qwen3vl_4b_fp8_scaled.safetensors) | `ComfyUI/models/text_encoders/` |\n| **VAE** | `qwen_image_vae.safetensors` | [下载](https://huggingface.co/Comfy-Org/Krea-2/resolve/main/vae/qwen_image_vae.safetensors) | `ComfyUI/models/vae/` |\n\n## 🌸 SilvermoonMix Anima v2.3 2.9B（可选底模）\n\n| 类型 | 模型文件名 | 下载链接 | 本地放置路径 |\n|------|------------|----------|--------------|\n| **UNet** | `silvermoonmixAnima_v2329B.safetensors` | [下载（普通版）](https://civitai.red/models/2639339/silvermoonmix-anima-evolved?modelVersionId=3335123) | `ComfyUI/models/diffusion_models/` |\n| **CLIP** | `qwen_3_06b_base.safetensors` | [下载](https://huggingface.co/circlestone-labs/Anima/resolve/main/split_files/text_encoders/qwen_3_06b_base.safetensors) | `ComfyUI/models/text_encoders/` |\n| **VAE** | `qwen_image_vae.safetensors`（与 Krea2 共用） | [下载](https://huggingface.co/Comfy-Org/Krea-2/resolve/main/vae/qwen_image_vae.safetensors) | `ComfyUI/models/vae/` |\n\n## 🚀 SilvermoonMix Anima v2.3 2.9B Turbo（默认底模）\n\n| 类型 | 模型文件名 | 下载链接 | 本地放置路径 |\n|------|------------|----------|--------------|\n| **UNet** | `silvermoonmixAnima_v2329BTurbo.safetensors` | [下载（Turbo 版）](https://civitai.red/models/2639339/silvermoonmix-anima-evolved?modelVersionId=3335132) | `ComfyUI/models/diffusion_models/` |\n| **CLIP** | `qwen_3_06b_base.safetensors`（与 SilvermoonMix 普通版共用） | [下载](https://huggingface.co/circlestone-labs/Anima/resolve/main/split_files/text_encoders/qwen_3_06b_base.safetensors) | `ComfyUI/models/text_encoders/` |\n| **VAE** | `qwen_image_vae.safetensors`（与 Krea2、SilvermoonMix 普通版共用） | [下载](https://huggingface.co/Comfy-Org/Krea-2/resolve/main/vae/qwen_image_vae.safetensors) | `ComfyUI/models/vae/` |\n\n## 🩹 FLUX.2 Klein 9B FP8（局部重绘：物体移除可选专用）\n\n> 💡 **非必需，按需下载**：局部重绘日常修手、修面部、微调细节**默认直接复用当前底模管线**，无需下载此模型。 \n> 仅在开启局部重绘组内控制器中的 **「是否Flux2Klein重绘」**（用于眼镜等遮挡物移除、语义擦除）时才需要本套独立模型。\n>\n> ⚠️ FLUX.2 Klein 的 UNet 仓库需要登录 Hugging Face，并先在模型页面接受许可协议；未完成授权时，直接下载链接会返回无权限。\n\n| 类型 | 模型文件名 | 下载链接 | 本地放置路径 |\n|------|------------|----------|--------------|\n| **UNet** | `flux-2-klein-9b-fp8.safetensors` | [下载](https://huggingface.co/black-forest-labs/FLUX.2-klein-9b-fp8/resolve/main/flux-2-klein-9b-fp8.safetensors) | `ComfyUI/models/diffusion_models/` |\n| **CLIP** | `qwen_3_8b_fp8mixed.safetensors` | [下载](https://huggingface.co/Comfy-Org/flux2-klein-9B/resolve/main/split_files/text_encoders/qwen_3_8b_fp8mixed.safetensors) | `ComfyUI/models/text_encoders/` |\n| **VAE** | `full_encoder_small_decoder.safetensors` | [下载](https://huggingface.co/black-forest-labs/FLUX.2-small-decoder/resolve/main/full_encoder_small_decoder.safetensors) | `ComfyUI/models/vae/` |\n\n## 🔍 SeedVR2-7B-Int8-Sharp（放大用）\n| 类型 | 模型文件名 | 下载链接 | 本地放置路径 |\n|------|------------|----------|--------------|\n| **UNet** | `seedvr2_7b_sharp_int8_convrot.safetensors` | [下载](https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/diffusion_models/seedvr2_7b_sharp_int8_convrot.safetensors) | `ComfyUI/models/diffusion_models/` |\n| **VAE** | `seedvr2_ema_vae_fp16.safetensors` | [下载](https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/vae/seedvr2_ema_vae_fp16.safetensors) | `ComfyUI/models/vae/` |\n\n---\n\n# ⚡ 默认设置下会自动下载的模型\n\n> ⚠️ **重要提示**：使用相关功能时请确保已开启 VPN，并打开 **TUN 模式**！如果自动下载失败，请按下面给出的目录层级手动下载并放置模型，然后重启 ComfyUI。\n\n## 1. 🎭 Forbidden Vision（脸部细化模型）\n\n- 🏠 **插件地址**：[GitHub 仓库](https://github.com/luxdelux7/ComfyUI-Forbidden-Vision) \n- 📦 **模型仓库**：[Hugging Face 仓库](https://huggingface.co/luxdelux7/ForbiddenVision_Models) \n- 💡 插件首次启动时会自动下载人脸检测、脸部分割和色调校正模型；网络下载失败时，请手动下载下列文件，**不要修改文件名**。\n\n| 用途 | 模型文件名 | 下载链接 | 是否必需 |\n|------|------------|----------|----------|\n| **人脸检测（PyTorch）** | `ForbiddenVision_face_detect_v1.pt` | [下载](https://huggingface.co/luxdelux7/ForbiddenVision_Models/resolve/main/ForbiddenVision_face_detect_v1.pt) | **必需，默认回退模型** |\n| **人脸检测（ONNX）** | `ForbiddenVision_face_detect_v1.onnx` | [下载](https://huggingface.co/luxdelux7/ForbiddenVision_Models/resolve/main/ForbiddenVision_face_detect_v1.onnx) | 可选，仅在可用的 ONNX Runtime 环境中使用 |\n| **脸部分割** | `ForbiddenVision_face_segment_v1.safetensors` | [下载](https://huggingface.co/luxdelux7/ForbiddenVision_Models/resolve/main/ForbiddenVision_face_segment_v1.safetensors) | **必需** |\n| **色调与颜色校正** | `ForbiddenVision_neural_corrector_v1.safetensors` | [下载](https://huggingface.co/luxdelux7/ForbiddenVision_Models/resolve/main/ForbiddenVision_neural_corrector_v1.safetensors) | **必需** |\n\n**模型放置层级如下，四个文件均直接放在 `forbidden_vision` 文件夹内：**\n```\n📂 ComfyUI/\n└── 📂 models/\n └── 📂 forbidden_vision/\n ├── ForbiddenVision_face_detect_v1.pt\n ├── ForbiddenVision_face_detect_v1.onnx （可选）\n ├── ForbiddenVision_face_segment_v1.safetensors\n └── ForbiddenVision_neural_corrector_v1.safetensors\n```\n\n## 2. 🏷️ WD Timm Tagger（图像反推模型）\n\n- 🏠 **插件地址**：[GitHub 仓库](https://github.com/bedovyy/ComfyUI-WD-Timm-Tagger) \n- 📦 **默认模型仓库**：[Hugging Face 仓库](https://huggingface.co/Bedovyy/pixai-tagger-v0.9-timm) \n- 💡 工作流默认使用 `pixai-tagger-v0.9-timm`。第一次执行反推时，插件会自动下载模型；如果因 VPN 或 Hugging Face 连接问题下载失败，请手动下载下面三个文件，**不要修改文件名**。\n\n| 用途 | 文件名 | 下载链接 |\n|------|--------|----------|\n| **模型配置** | `config.json` | [下载](https://huggingface.co/Bedovyy/pixai-tagger-v0.9-timm/resolve/main/config.json) |\n| **反推模型** | `model.safetensors` | [下载](https://huggingface.co/Bedovyy/pixai-tagger-v0.9-timm/resolve/main/model.safetensors) |\n| **标签数据** | `selected_tags.csv` | [下载](https://huggingface.co/Bedovyy/pixai-tagger-v0.9-timm/resolve/main/selected_tags.csv) |\n\n**三个文件必须放在同一个 `pixai-tagger-v0.9-timm` 子文件夹内，不能直接放进 `wd_taggers`：**\n```\n📂 ComfyUI/\n└── 📂 models/\n └── 📂 wd_taggers/\n └── 📂 pixai-tagger-v0.9-timm/\n ├── config.json\n ├── model.safetensors\n └── selected_tags.csv\n```\n\n放置完成后重启 ComfyUI。如果节点仍然找不到模型，请检查是否出现了重复嵌套目录，例如错误的 `pixai-tagger-v0.9-timm/pixai-tagger-v0.9-timm/`。\n\n---\n\n# 那么，祝使用愉快～ ✨"
],
"widgets_values_named": {
"text": "# ⚠️ 须知\n\n此工作流**完全免费开源**，并提供配套定制化插件。 \n如在使用过程中遇到问题，欢迎前往 Discord 反馈，或在对应插件仓库提交 Issue。\n\n## 🔌 配套插件列表\n> 以下仅列出作者本人开发的插件，不包含工作流依赖的其他第三方插件\n\n### 一、核心插件\n- 🏠 **地址**：[GitHub 仓库](https://github.com/Aaalice233/ComfyUI-Aaalice-Nodes) \n- ✨ **功能**：侧边栏控制面板、组跳转轮盘、提示词选择器、booru 画廊、分辨率预设等\n\n### 二、自动补全插件（二开增强版）\n- 🏠 **地址**：[GitHub 仓库](https://github.com/Aaalice233/ComfyUI-Autocomplete-Aaalice) \n- ✨ **功能**：基于上游仓库的增强维护版本，支持 Danbooru 标签在线拉取、Lora Manager联动、第三方汉化数据库接入及 LLM 汉化接口\n\n### 三、工作流订阅管理插件\n- 🏠 **地址**：[GitHub 仓库](https://github.com/Aaalice233/ComfyUI-Aaalice-Workflow-Hub) \n- ✨ **功能**：在 ComfyUI 内直接查看工作流列表、更新日志并快速订阅更新\n\n### 四、图像选择器插件\n- 🏠 **地址**：[GitHub 仓库](https://github.com/Aaalice233/ComfyUI-Aaalice-Image-Picker) \n- ✨ **功能**：在工作流中暂停执行并人工筛选批次图像，支持单选/多选、局部缩放对比和超时策略；底图和局部重绘组均使用它确认候选结果\n\n---\n\n# 🐱 Discord 社区与教程\n\n- 💬 [加入 Discord 服务器](https://discord.gg/R48n6GwXzD)\n- 🎓 [打开工作流安装与使用教程频道](https://discord.com/channels/1349298998988771359/1536643406787387392)\n\n> ⚠️ 如果尚未加入服务器，频道链接会无法打开。请先通过上方邀请链接加入服务器，再打开教程频道。\n\n# 📦 工作流仓库地址\n[GitHub 仓库](https://github.com/Aaalice233/Aaalice-Workflows) \n\n推荐配合订阅管理插件使用，可快速检查更新、查看列表、下载和补全依赖等： \n[订阅管理插件仓库](https://github.com/Aaalice233/ComfyUI-Aaalice-Workflow-Hub)\n\n# 💡 使用技巧\n- 🖱️ 点击侧边栏中样式为大写字母 **「A」** 的按钮，即可快速打开工作流定制控制面板（支持调参、预设管理、组跳转设置、提示词词库管理等）\n- ⌨️ 默认情况下，按下波浪号键（**~**）可快速呼出组跳转轮盘\n- 🟣 被**紫色边框**包裹的参数，表示该参数受侧边栏控制\n\n---\n\n# 📥 模型下载列表（按所选底模与功能下载）\n\n> 当前默认底模为 **SilvermoonMix Anima v2.3 2.9B Turbo**。侧边栏预设提供 **「默认-Anima-2.9B-Turbo-Silvermoon」**、**「默认-Anima-2.9B-Silvermoon」** 和 **「默认-Krea2-Turbo-Int8」**，请按所选预设下载对应模型，无需全部下载。 \n> SilvermoonMix 的 UNet 请从下方 Civitai 对应版本页面下载；CLIP、VAE 继续使用表中 Hugging Face 链接。 \n> 下载后请将文件放置到对应目录，并重启 ComfyUI。\n\n## 🎨 Krea2（可选底模）\n\n| 类型 | 模型文件名 | 下载链接 | 本地放置路径 |\n|------|------------|----------|--------------|\n| **UNet** | `krea2_turbo_int8_convrot.safetensors` | [下载](https://huggingface.co/Comfy-Org/Krea-2/resolve/main/diffusion_models/krea2_turbo_int8_convrot.safetensors) | `ComfyUI/models/diffusion_models/` |\n| **CLIP** | `qwen3vl_4b_fp8_scaled.safetensors` | [下载](https://huggingface.co/Comfy-Org/Krea-2/resolve/main/text_encoders/qwen3vl_4b_fp8_scaled.safetensors) | `ComfyUI/models/text_encoders/` |\n| **VAE** | `qwen_image_vae.safetensors` | [下载](https://huggingface.co/Comfy-Org/Krea-2/resolve/main/vae/qwen_image_vae.safetensors) | `ComfyUI/models/vae/` |\n\n## 🌸 SilvermoonMix Anima v2.3 2.9B（可选底模）\n\n| 类型 | 模型文件名 | 下载链接 | 本地放置路径 |\n|------|------------|----------|--------------|\n| **UNet** | `silvermoonmixAnima_v2329B.safetensors` | [下载（普通版）](https://civitai.red/models/2639339/silvermoonmix-anima-evolved?modelVersionId=3335123) | `ComfyUI/models/diffusion_models/` |\n| **CLIP** | `qwen_3_06b_base.safetensors` | [下载](https://huggingface.co/circlestone-labs/Anima/resolve/main/split_files/text_encoders/qwen_3_06b_base.safetensors) | `ComfyUI/models/text_encoders/` |\n| **VAE** | `qwen_image_vae.safetensors`（与 Krea2 共用） | [下载](https://huggingface.co/Comfy-Org/Krea-2/resolve/main/vae/qwen_image_vae.safetensors) | `ComfyUI/models/vae/` |\n\n## 🚀 SilvermoonMix Anima v2.3 2.9B Turbo（默认底模）\n\n| 类型 | 模型文件名 | 下载链接 | 本地放置路径 |\n|------|------------|----------|--------------|\n| **UNet** | `silvermoonmixAnima_v2329BTurbo.safetensors` | [下载（Turbo 版）](https://civitai.red/models/2639339/silvermoonmix-anima-evolved?modelVersionId=3335132) | `ComfyUI/models/diffusion_models/` |\n| **CLIP** | `qwen_3_06b_base.safetensors`（与 SilvermoonMix 普通版共用） | [下载](https://huggingface.co/circlestone-labs/Anima/resolve/main/split_files/text_encoders/qwen_3_06b_base.safetensors) | `ComfyUI/models/text_encoders/` |\n| **VAE** | `qwen_image_vae.safetensors`（与 Krea2、SilvermoonMix 普通版共用） | [下载](https://huggingface.co/Comfy-Org/Krea-2/resolve/main/vae/qwen_image_vae.safetensors) | `ComfyUI/models/vae/` |\n\n## 🩹 FLUX.2 Klein 9B FP8（局部重绘：物体移除可选专用）\n\n> 💡 **非必需，按需下载**：局部重绘日常修手、修面部、微调细节**默认直接复用当前底模管线**，无需下载此模型。 \n> 仅在开启局部重绘组内控制器中的 **「是否Flux2Klein重绘」**（用于眼镜等遮挡物移除、语义擦除）时才需要本套独立模型。\n>\n> ⚠️ FLUX.2 Klein 的 UNet 仓库需要登录 Hugging Face，并先在模型页面接受许可协议；未完成授权时，直接下载链接会返回无权限。\n\n| 类型 | 模型文件名 | 下载链接 | 本地放置路径 |\n|------|------------|----------|--------------|\n| **UNet** | `flux-2-klein-9b-fp8.safetensors` | [下载](https://huggingface.co/black-forest-labs/FLUX.2-klein-9b-fp8/resolve/main/flux-2-klein-9b-fp8.safetensors) | `ComfyUI/models/diffusion_models/` |\n| **CLIP** | `qwen_3_8b_fp8mixed.safetensors` | [下载](https://huggingface.co/Comfy-Org/flux2-klein-9B/resolve/main/split_files/text_encoders/qwen_3_8b_fp8mixed.safetensors) | `ComfyUI/models/text_encoders/` |\n| **VAE** | `full_encoder_small_decoder.safetensors` | [下载](https://huggingface.co/black-forest-labs/FLUX.2-small-decoder/resolve/main/full_encoder_small_decoder.safetensors) | `ComfyUI/models/vae/` |\n\n## 🔍 SeedVR2-7B-Int8-Sharp（放大用）\n| 类型 | 模型文件名 | 下载链接 | 本地放置路径 |\n|------|------------|----------|--------------|\n| **UNet** | `seedvr2_7b_sharp_int8_convrot.safetensors` | [下载](https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/diffusion_models/seedvr2_7b_sharp_int8_convrot.safetensors) | `ComfyUI/models/diffusion_models/` |\n| **VAE** | `seedvr2_ema_vae_fp16.safetensors` | [下载](https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/vae/seedvr2_ema_vae_fp16.safetensors) | `ComfyUI/models/vae/` |\n\n---\n\n# ⚡ 默认设置下会自动下载的模型\n\n> ⚠️ **重要提示**：使用相关功能时请确保已开启 VPN，并打开 **TUN 模式**！如果自动下载失败，请按下面给出的目录层级手动下载并放置模型，然后重启 ComfyUI。\n\n## 1. 🎭 Forbidden Vision（脸部细化模型）\n\n- 🏠 **插件地址**：[GitHub 仓库](https://github.com/luxdelux7/ComfyUI-Forbidden-Vision) \n- 📦 **模型仓库**：[Hugging Face 仓库](https://huggingface.co/luxdelux7/ForbiddenVision_Models) \n- 💡 插件首次启动时会自动下载人脸检测、脸部分割和色调校正模型；网络下载失败时，请手动下载下列文件，**不要修改文件名**。\n\n| 用途 | 模型文件名 | 下载链接 | 是否必需 |\n|------|------------|----------|----------|\n| **人脸检测（PyTorch）** | `ForbiddenVision_face_detect_v1.pt` | [下载](https://huggingface.co/luxdelux7/ForbiddenVision_Models/resolve/main/ForbiddenVision_face_detect_v1.pt) | **必需，默认回退模型** |\n| **人脸检测（ONNX）** | `ForbiddenVision_face_detect_v1.onnx` | [下载](https://huggingface.co/luxdelux7/ForbiddenVision_Models/resolve/main/ForbiddenVision_face_detect_v1.onnx) | 可选，仅在可用的 ONNX Runtime 环境中使用 |\n| **脸部分割** | `ForbiddenVision_face_segment_v1.safetensors` | [下载](https://huggingface.co/luxdelux7/ForbiddenVision_Models/resolve/main/ForbiddenVision_face_segment_v1.safetensors) | **必需** |\n| **色调与颜色校正** | `ForbiddenVision_neural_corrector_v1.safetensors` | [下载](https://huggingface.co/luxdelux7/ForbiddenVision_Models/resolve/main/ForbiddenVision_neural_corrector_v1.safetensors) | **必需** |\n\n**模型放置层级如下，四个文件均直接放在 `forbidden_vision` 文件夹内：**\n```\n📂 ComfyUI/\n└── 📂 models/\n └── 📂 forbidden_vision/\n ├── ForbiddenVision_face_detect_v1.pt\n ├── ForbiddenVision_face_detect_v1.onnx （可选）\n ├── ForbiddenVision_face_segment_v1.safetensors\n └── ForbiddenVision_neural_corrector_v1.safetensors\n```\n\n## 2. 🏷️ WD Timm Tagger（图像反推模型）\n\n- 🏠 **插件地址**：[GitHub 仓库](https://github.com/bedovyy/ComfyUI-WD-Timm-Tagger) \n- 📦 **默认模型仓库**：[Hugging Face 仓库](https://huggingface.co/Bedovyy/pixai-tagger-v0.9-timm) \n- 💡 工作流默认使用 `pixai-tagger-v0.9-timm`。第一次执行反推时，插件会自动下载模型；如果因 VPN 或 Hugging Face 连接问题下载失败，请手动下载下面三个文件，**不要修改文件名**。\n\n| 用途 | 文件名 | 下载链接 |\n|------|--------|----------|\n| **模型配置** | `config.json` | [下载](https://huggingface.co/Bedovyy/pixai-tagger-v0.9-timm/resolve/main/config.json) |\n| **反推模型** | `model.safetensors` | [下载](https://huggingface.co/Bedovyy/pixai-tagger-v0.9-timm/resolve/main/model.safetensors) |\n| **标签数据** | `selected_tags.csv` | [下载](https://huggingface.co/Bedovyy/pixai-tagger-v0.9-timm/resolve/main/selected_tags.csv) |\n\n**三个文件必须放在同一个 `pixai-tagger-v0.9-timm` 子文件夹内，不能直接放进 `wd_taggers`：**\n```\n📂 ComfyUI/\n└── 📂 models/\n └── 📂 wd_taggers/\n └── 📂 pixai-tagger-v0.9-timm/\n ├── config.json\n ├── model.safetensors\n └── selected_tags.csv\n```\n\n放置完成后重启 ComfyUI。如果节点仍然找不到模型，请检查是否出现了重复嵌套目录，例如错误的 `pixai-tagger-v0.9-timm/pixai-tagger-v0.9-timm/`。\n\n---\n\n# 那么，祝使用愉快～ ✨"
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"# 🎨 局部重绘使用说明\n\n> 💬 [加入 Discord 社区](https://discord.gg/R48n6GwXzD) ｜ 📺 [查看视频教程（Discord 频道）](https://discord.com/channels/1349298998988771359/1536643406787387392) \n> *注：视频教程频道需先通过邀请链接加入服务器后方可正常访问。*\n\n---\n\n> 📌 **启动前须知**：使用前请先启用 **「【📦可选】局部重绘」** 组。 \n> 开启后，工作流会自动旁路（关闭）文生图相关组，避免重复执行并节省显存。\n\n---\n\n## ⚙️ 重绘模式选择\n\n本工作流提供两种重绘路径，分别针对不同的修图需求：\n\n### 1. 原生底模重绘（默认推荐：修手、修脸、改细节）\n- **开关设置**：保持 **「是否Flux2Klein重绘」** 为 **关闭（False）**。\n- **核心机制**：直接继承主流程当前加载的模型、CLIP、VAE 与负面条件，完全保持原图的画风、色调、笔触与 LoRA 特征。\n- **适用场景**：手指修复、面部微调、肢体修整、服装细节调整。\n- **关键参数建议**：\n - **原生重绘步数**：**修手与肢体时建议调高步数，至少不低于底图生成的步数**。若步数过低，细微结构的重绘质量将明显不足。\n - **原生重绘降噪幅度**：微调修复建议 **0.35 ~ 0.5**；较大范围改动姿势或造型建议 **0.6 ~ 0.75**。\n - **变化幅度控制（重要）**：重绘部位的变化幅度**除了直接受「降噪幅度」影响外，采样器与调度器也同样会显著影响变化幅度**。在相同的降噪幅度下，不同调度器（如 beta、karras、exponential 等）分配的起始加噪量与去噪曲线差异明显；若发现画面改动过剧烈或变化过弱，除调整降噪外，也可检查采样器与调度器的组合（默认推荐 `euler` + `beta`）。\n - **批次大小**：修手或抽卡时建议设为 **大于 1 的数值（如 2 ~ 4）**，配合选择器多中选优。\n - 内置差分扩散（Differential Diffusion）支持，确保蒙版边缘自然融合。\n\n### 2. FLUX.2 Klein 独立重绘（专精：物体移除）\n- **开关设置**：将 **「是否Flux2Klein重绘」** 打勾 **开启（True）**。\n- **核心机制**：启用独立的 FLUX.2 Klein 9B FP8 专用模型，具备极强的语义擦除与底层结构复原能力。\n- **适用场景**：**物体移除与遮挡消除**。典型如移除角色佩戴的眼镜、耳机、配饰或背景杂物，能够在抹除遮挡物的同时精准补全底层面部及背景，而不破坏原有五官特征。\n- **注意事项**：首次使用需先按工作流「👀必看」说明，下载对应的 UNet、CLIP 和 VAE 模型放置于相应目录；该模式的采样步数和 CFG 已在内部自动优化。\n\n---\n\n## 📋 标准操作流程\n\n### 步骤一：准备图像与蒙版（二选一）\n\n- **方案 A：ComfyUI 网页内涂抹（轻量快捷）**\n 1. 将「**是否使用Krita预处理**」设为 **关闭（False）**。\n 2. 在组内的「**加载图像**」节点中选择待修图像。\n 3. 右键该节点，选择 **Open in MaskEditor**，使用笔刷涂抹需要重绘的区域，点击右上角 **Save** 保存蒙版。\n\n- **方案 B：Krita 联动（推荐精细修图与高成功率修手）**\n 1. 将「**是否使用Krita预处理**」打勾 **开启（True）**。\n 2. 在 Krita 中打开待修图像，使用选区工具（套索或矩形）圈出重绘区域。\n 3. *初次连接*：在「🎨 从 Krita 获取」节点设置中点击「安装并启用 Bridge」，随后启动 Krita 即可自动建立连接。\n\n### 步骤二：编写提示词\n\n在「**重绘提示词**」输入框中使用明确的自然语言描述：\n- **修改或重绘时**：写明蒙版区域的目标结果与需保持的上下文。 \n *示例：`白皙修长的少女手部，自然的放松手势，保持二次元插画风格与原有光影`*\n- **物体移除时（配合 FLUX.2 Klein）**：明确说明移除目标并强调底层特征保持。 \n *示例：`移除脸部眼镜，清晰明亮的眼睛，白皙干净的面部皮肤，保持原有五官与面部特征`*\n- 避免使用“修复一下”、“变得更好看”等模糊主观词。\n\n### 步骤三：执行与候选图筛选\n\n1. 点击 **Queue / 执行** 开始生成。\n2. **批次挑选（AaaliceImagePicker）**：\n - 将「**批次大小**」设为大于 1（例如 2 ~ 4），一次生成多张候选图。\n - 保持「**是否保存前确认**」开启，生成完毕后会自动弹出图像选择窗口。可在交互窗口中放大检查各候选图，**仅勾选确认满意的图像提交保存**。\n3. 生成结束时将收到系统桌面通知与提示音。\n\n### 步骤四：对比与范围校验\n\n- **效果对比**：通过右侧的 **Image Comparer** 节点左右滑动滑块，直观比对原图与重绘图的接缝与细节。\n- **范围监控**：最右侧两个预览窗口直观呈现本次重绘的**局部裁切参考图**与**黑白蒙版**，便于确认模型的实际视场与边界。\n\n---\n\n## 💡 技巧与常见问题\n\n### 1. 手部修复的两种方案\n- **直接蒙版抽卡（常规流程）**：\n 直接在 ComfyUI 内涂抹手部蒙版（选区建议适当包含手腕或前臂作为结构依据），将「**批次大小**」设置为大于 1（如 2 ~ 4 张），利用生成后的选择器弹窗直接挑选形态自然的结果。\n- **Krita 涂鸦预处理（显著提高成功率）**：\n 若手部结构严重畸变或直接抽卡难以收敛，建议联动 Krita：先用拾色器吸取周围肤色，用画笔将多余、扭曲的手指简单涂色覆盖为大致的手部色块轮廓，再框选重绘。该方法能大幅降低盲抽成本，显著提高一次性出图的成功率。\n- **核心原则**：无论使用哪种方案，修手均建议使用**原生底模重绘**，且**重绘步数不低于底图生成的步数**。\n\n### 2. 为什么重绘改动幅度过大或过小？\n重绘区域的变化幅度受多个核心参数共同影响：\n- **降噪幅度**：数值越大重绘改动越彻底，数值越小越保留原图；\n- **采样器与调度器**：**调度器（Scheduler）与采样器（Sampler）同样直接决定了去噪初始值与衰减节奏**。若相同的降噪幅度下改动幅度不符合预期，请同步留意调度器类型（如 beta、karras、simple、exponential 的加噪曲线均有差异）；\n- **重绘周边区域大小（默认 1.2）**：向外扩展的上下文范围，提供肢体与透视参考，避免设过大引入无关杂物；\n- **颜色匹配方法与强度（默认 1.0）**：将重绘区域色彩与周围原图自动校准，消除边缘接缝、断层或偏色。"
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"cnr_id": "comfy-core",
"ver": "0.28.0",
"Node name for S&R": "ComfySwitchNode",
"aaaliceControlHostId": "host_c121831b-49ce-48ae-8080-cfa69bca7c81"
},
"widgets_values": [
false
],
"widgets_values_named": {
"switch": false
},
"color": "#232",
"bgcolor": "#353"
},
{
"id": 239,
"type": "VAEDecodeTiled",
"pos": [
-1740,
-1750
],
"size": [
270,
150
],
"flags": {},
"order": 7,
"mode": 0,
"inputs": [
{
"localized_name": "Latent",
"name": "samples",
"type": "LATENT",
"link": 1811
},
{
"localized_name": "vae",
"name": "vae",
"type": "VAE",
"link": 412
}
],
"outputs": [
{
"localized_name": "图像",
"name": "IMAGE",
"type": "IMAGE",
"links": [
992
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.28.0",
"Node name for S&R": "VAEDecodeTiled",
"aaaliceControlHostId": "host_817db3b2-1b2f-469a-835a-50ded872c2bf"
},
"widgets_values": [
512,
64,
64,
8
],
"widgets_values_named": {
"tile_size": 512,
"overlap": 64,
"temporal_size": 64,
"temporal_overlap": 8
}
},
{
"id": 688,
"type": "ComfySwitchNode",
"pos": [
-1160,
-1750
],
"size": [
350,
130
],
"flags": {},
"order": 9,
"mode": 0,
"inputs": [
{
"localized_name": "为假时",
"name": "on_false",
"shape": 7,
"type": "IMAGE",
"link": 993
},
{
"localized_name": "为真时",
"name": "on_true",
"shape": 7,
"type": "IMAGE",
"link": 2298
},
{
"label": "是否底图确认",
"localized_name": "切换",
"name": "switch",
"type": "BOOLEAN",
"widget": {
"name": "switch"
},
"link": 1298
}
],
"outputs": [
{
"localized_name": "输出",
"name": "output",
"type": "IMAGE",
"links": [
1591
]
}
],
"title": "是否底图确认",
"properties": {
"cnr_id": "comfy-core",
"ver": "0.28.0",
"Node name for S&R": "ComfySwitchNode",
"aaaliceControlHostId": "host_4614578e-32d4-4cd5-b032-ea2f9ffec17d"
},
"widgets_values": [
true
],
"widgets_values_named": {
"switch": true
}
},
{
"id": 1240,
"type": "KSampler",
"pos": [
-2290,
-1750
],
"size": [
530,
1140
],
"flags": {},
"order": 11,
"mode": 0,
"inputs": [
{
"localized_name": "模型",
"name": "model",
"type": "MODEL",
"link": 1799
},
{
"localized_name": "正面条件",
"name": "positive",
"type": "CONDITIONING",
"link": 1800
},
{
"localized_name": "负面条件",
"name": "negative",
"type": "CONDITIONING",
"link": 1801
},
{
"localized_name": "Latent图像",
"name": "latent_image",
"type": "LATENT",
"link": 2516
},
{
"localized_name": "种子",
"name": "seed",
"type": "INT",
"widget": {
"name": "seed"
},
"link": 1804
},
{
"localized_name": "步数",
"name": "steps",
"type": "INT",
"widget": {
"name": "steps"
},
"link": 1810
},
{
"localized_name": "cfg",
"name": "cfg",
"type": "FLOAT",
"widget": {
"name": "cfg"
},
"link": 1805
},
{
"localized_name": "采样器名称",
"name": "sampler_name",
"type": "COMBO",
"widget": {
"name": "sampler_name"
},
"link": 1807
},
{
"localized_name": "调度器",
"name": "scheduler",
"type": "COMBO",
"widget": {
"name": "scheduler"
},
"link": 1808
},
{
"localized_name": "降噪",
"name": "denoise",
"type": "FLOAT",
"widget": {
"name": "denoise"
},
"link": 1809
}
],
"outputs": [
{
"localized_name": "Latent",
"name": "LATENT",
"type": "LATENT",
"links": [
1811
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.33.1",
"Node name for S&R": "KSampler",
"aaaliceControlHostId": "host_3e0da365-09d4-476d-85fd-51064f9799e3"
},
"widgets_values": [
0,
"randomize",
20,
8,
"euler",
"simple",
1
],
"widgets_values_named": {
"seed": 0,
"control_after_generate": "randomize",
"steps": 20,
"cfg": 8,
"sampler_name": "euler",
"scheduler": "simple",
"denoise": 1
},
"color": "#432",
"bgcolor": "#653",
"shape": 1
},
{
"id": 1241,
"type": "ComfyMathExpression",
"pos": [
-3310,
-1580
],
"size": [
230,
150
],
"flags": {
"collapsed": false
},
"order": 12,
"mode": 0,
"inputs": [
{
"label": "a",
"localized_name": "a",
"name": "values.a",
"type": "FLOAT,INT,BOOLEAN",
"link": 1815
},
{
"localized_name": "b",
"name": "values.b",
"shape": 7,
"type": "FLOAT,INT,BOOLEAN",
"link": null
}
],
"outputs": [
{
"localized_name": "浮点",
"name": "FLOAT",
"type": "FLOAT",
"links": null
},
{
"localized_name": "整数",
"name": "INT",
"type": "INT",
"links": [
1816
]
},
{
"localized_name": "布尔值",
"name": "BOOL",
"type": "BOOLEAN",
"links": null
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.33.1",
"Node name for S&R": "ComfyMathExpression",
"aaaliceControlHostId": "host_a4021366-2e3f-4e8c-938e-bdfd8f030855"
},
"widgets_values": [
"a // 2"
],
"widgets_values_named": {
"expression": "a // 2"
}
},
{
"id": 1107,
"type": "ConditionalSaveImage",
"pos": [
-790,
-1750
],
"size": [
360,
640
],
"flags": {},
"order": 10,
"mode": 0,
"inputs": [
{
"localized_name": "图像",
"name": "images",
"type": "IMAGE",
"link": 1591
},
{
"localized_name": "元数据",
"name": "metadata",
"shape": 7,
"type": "METADATA",
"link": null
},
{
"localized_name": "启用",
"name": "enabled",
"type": "BOOLEAN",
"widget": {
"name": "enabled"
},
"link": 1592
},
{
"localized_name": "文件名前缀",
"name": "filename_prefix",
"type": "STRING",
"widget": {
"name": "filename_prefix"
},
"link": 1593
},
{
"localized_name": "嵌入工作流",
"name": "embed_workflow",
"type": "BOOLEAN",
"widget": {
"name": "embed_workflow"
},
"link": 1595
},
{
"localized_name": "保存元数据",
"name": "save_with_metadata",
"type": "BOOLEAN",
"widget": {
"name": "save_with_metadata"
},
"link": 1596
}
],
"outputs": [
{
"localized_name": "图像",
"name": "images",
"type": "IMAGE",
"links": [
2196
]
}
],
"properties": {
"cnr_id": "comfyui-aaalice-nodes",
"ver": "5c4d31a0892f308d0234782a23749ace1fc5fe64",
"Node name for S&R": "ConditionalSaveImage",
"aaaliceControlHostId": "host_5b5cfa06-1ff9-4859-ba76-9959fa23c0d7"
},
"widgets_values": [
true,
"ComfyUI",
"png",
false,
100,
6,
0,
false,
true,
true,
true,
false
],
"widgets_values_named": {
"enabled": true,
"filename_prefix": "ComfyUI",
"file_format": "png",
"lossless_webp": false,
"quality": 100,
"webp_method": 6,
"jpeg_subsampling": 0,
"embed_workflow": false,
"save_with_metadata": true,
"add_loras_to_prompt": true,
"add_counter_to_filename": true,
"save_as_recipe": false
},
"color": "#223",
"bgcolor": "#335"
},
{
"id": 1413,
"type": "VRAM_Debug",
"pos": [
-410,
-1750
],
"size": [
300,
190
],
"flags": {},
"order": 13,
"mode": 0,
"inputs": [
{
"localized_name": "any_input",
"name": "any_input",
"shape": 7,
"type": "*",
"link": null
},
{
"localized_name": "image_pass",
"name": "image_pass",
"shape": 7,
"type": "IMAGE",
"link": 2196
},
{
"localized_name": "model_pass",
"name": "model_pass",
"shape": 7,
"type": "MODEL",
"link": null
}
],
"outputs": [
{
"localized_name": "any_output",
"name": "any_output",
"type": "*",
"links": null
},
{
"localized_name": "image_pass",
"name": "image_pass",
"type": "IMAGE",
"links": [
2197
]
},
{
"localized_name": "model_pass",
"name": "model_pass",
"type": "MODEL",
"links": null
},
{
"label": "3,156,680,230 freemem_before",
"localized_name": "freemem_before",
"name": "freemem_before",
"type": "INT",
"links": null
},
{
"label": "3,156,680,230 freemem_after",
"localized_name": "freemem_after",
"name": "freemem_after",
"type": "INT",
"links": null
}
],
"properties": {
"cnr_id": "comfyui-kjnodes",
"ver": "3f20054214fec9f9234fd3841ae6f1e4287948f6",
"Node name for S&R": "VRAM_Debug",
"aaaliceControlHostId": "host_6bb7eaae-5f40-4d1d-8ee6-c85886db2e39"
},
"widgets_values": [
true,
true,
false
],
"widgets_values_named": {
"empty_cache": true,
"gc_collect": true,
"unload_all_models": false
},
"color": "#323",
"bgcolor": "#535"
},
{
"id": 422,
"type": "SimpleNotify",
"pos": [
-1450,
-1750
],
"size": [
270,
200
],
"flags": {},
"order": 8,
"mode": 0,
"inputs": [
{
"localized_name": "值",
"name": "value",
"type": "*",
"link": 992
},
{
"label": "消息通知内容",
"localized_name": "消息",
"name": "message",
"type": "STRING",
"widget": {
"name": "message"
},
"link": 1295
},
{
"label": "是否消息通知",
"localized_name": "桌面通知",
"name": "desktop_notification",
"type": "BOOLEAN",
"widget": {
"name": "desktop_notification"
},
"link": 1294
},
{
"label": "是否通知音效",
"localized_name": "提示音",
"name": "sound",
"type": "BOOLEAN",
"widget": {
"name": "sound"
},
"link": 1296
},
{
"label": "通知音效音量",
"localized_name": "音量",
"name": "volume",
"type": "FLOAT",
"widget": {
"name": "volume"
},
"link": 1297
}
],
"outputs": [
{
"localized_name": "值",
"name": "Value",
"type": "IMAGE",
"links": [
993,
2297
]
}
],
"properties": {
"cnr_id": "comfyui-aaalice-nodes",
"ver": "796f924765b3dc52ef5ba83e5f540ceefdf30ca8",
"Node name for S&R": "SimpleNotify",
"aaaliceControlHostId": "host_3741ce99-bb98-45c7-be5c-ab9792be42e9"
},
"widgets_values": [
"底图生成完毕喵~",
true,
true,
0.5
],
"widgets_values_named": {
"message": "底图生成完毕喵~",
"desktop_notification": true,
"sound": true,
"volume": 0.5
}
},
{
"id": 1460,
"type": "AaaliceImagePicker",
"pos": [
-1160,
-1580
],
"size": [
350,
130
],
"flags": {},
"order": 14,
"mode": 0,
"inputs": [
{
"localized_name": "图像",
"name": "images",
"type": "IMAGE",
"link": 2297
},
{
"localized_name": "说明",
"name": "instructions",
"shape": 7,
"type": "STRING",
"link": 2299
},
{
"localized_name": "超时",
"name": "timeout",
"type": "INT",
"widget": {
"name": "timeout"
},
"link": 2300
},
{
"localized_name": "超时策略",
"name": "timeout_action",
"type": "COMBO",
"widget": {
"name": "timeout_action"
},
"link": 2301
}
],
"outputs": [
{
"localized_name": "图像",
"name": "images",
"type": "IMAGE",
"links": [
2298
]
}
],
"properties": {
"cnr_id": "aaalice-image-picker",
"ver": "42df5d3bedf2155da679f078f31de1e7426a41de",
"Node name for S&R": "AaaliceImagePicker",
"aux_id": "Aaalice233/ComfyUI-Aaalice-Image-Picker",
"aaaliceControlHostId": "host_72f68a4b-b8ce-444e-a33f-a80b4c103188"
},
"widgets_values": [
"multiple",
300,
"submit_all"
],
"widgets_values_named": {
"selection_mode": "multiple",
"timeout": 300,
"timeout_action": "submit_all"
},
"color": "#223",
"bgcolor": "#335"
},
{
"id": 1461,
"type": "PrimitiveStringMultiline",
"pos": [
-1160,
-1410
],
"size": [
350,
160
],
"flags": {},
"order": 3,
"mode": 0,
"inputs": [],
"outputs": [
{
"localized_name": "字符串",
"name": "STRING",
"type": "STRING",
"links": [
2299
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.33.3",
"Node name for S&R": "PrimitiveStringMultiline",
"aaaliceControlHostId": "host_d8ba48e5-a8bf-46ba-a058-17ed9dedc526"
},
"widgets_values": [
"# 选择你满意的图像👉\n\n- 通过调整“批次大小”参数，可以一次生成多张图像\n- 批次大小越大，越吃配置\n- 图像确认阶段可以通过参数关闭"
],
"widgets_values_named": {
"value": "# 选择你满意的图像👉\n\n- 通过调整“批次大小”参数，可以一次生成多张图像\n- 批次大小越大，越吃配置\n- 图像确认阶段可以通过参数关闭"
}
},
{
"id": 53,
"type": "EmptyLatentImage",
"pos": [
-2960,
-1240
],
"size": [
320,
170
],
"flags": {},
"order": 4,
"mode": 0,
"inputs": [
{
"localized_name": "宽度",
"name": "width",
"type": "INT",
"widget": {
"name": "width"
},
"link": 297
},
{
"localized_name": "高度",
"name": "height",
"type": "INT",
"widget": {
"name": "height"
},
"link": 298
},
{
"localized_name": "批量大小",
"name": "batch_size",
"type": "INT",
"widget": {
"name": "batch_size"
},
"link": 299
}
],
"outputs": [
{
"localized_name": "Latent",
"name": "LATENT",
"type": "LATENT",
"slot_index": 0,
"links": [
2512
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.25.0",
"Node name for S&R": "EmptyLatentImage",
"aaaliceControlHostId": "host_3c1554c9-98db-4374-9b77-60525b39cf76"
},
"widgets_values": [
1024,
1024,
1
],
"widgets_values_named": {
"width": 1024,
"height": 1024,
"batch_size": 1
},
"color": "#323",
"bgcolor": "#535"
},
{
"id": 1578,
"type": "VAEEncode",
"pos": [
-2630,
-1120
],
"size": [
280,
50
],
"flags": {},
"order": 16,
"mode": 0,
"inputs": [
{
"localized_name": "像素",
"name": "pixels",
"type": "IMAGE",
"link": 2514
},
{
"localized_name": "vae",
"name": "vae",
"type": "VAE",
"link": 2513
}
],
"outputs": [
{
"localized_name": "Latent",
"name": "LATENT",
"type": "LATENT",
"links": [
2515
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.36.0",
"Node name for S&R": "VAEEncode",
"aaaliceControlHostId": "host_c39049ae-02ca-410e-b0b9-8828541d066e"
}
},
{
"id": 1577,
"type": "ComfySwitchNode",
"pos": [
-2630,
-1240
],
"size": [
280,
80
],
"flags": {},
"order": 15,
"mode": 0,
"inputs": [
{
"localized_name": "为假时",
"name": "on_false",
"shape": 7,
"type": "LATENT",
"link": 2512
},
{
"localized_name": "为真时",
"name": "on_true",
"shape": 7,
"type": "LATENT",
"link": 2515
},
{
"localized_name": "切换",
"name": "switch",
"type": "BOOLEAN",
"widget": {
"name": "switch"
},
"link": 2519
}
],
"outputs": [
{
"localized_name": "输出",
"name": "output",
"type": "LATENT",
"links": [
2516
]
}
],
"title": "是否图生图",
"properties": {
"cnr_id": "comfy-core",
"ver": "0.36.0",
"Node name for S&R": "ComfySwitchNode",
"aaaliceControlHostId": "host_19900e92-94ef-4e45-92a8-5567187c970c"
},
"widgets_values": [
false
],
"widgets_values_named": {
"switch": false
}
}
],
"groups": [],
"links": [
{
"id": 297,
"origin_id": 206,
"origin_slot": 0,
"target_id": 53,
"target_slot": 0,
"type": "INT"
},
{
"id": 298,
"origin_id": 209,
"origin_slot": 0,
"target_id": 53,
"target_slot": 1,
"type": "INT"
},
{
"id": 299,
"origin_id": 210,
"origin_slot": 0,
"target_id": 53,
"target_slot": 2,
"type": "INT"
},
{
"id": 308,
"origin_id": 158,
"origin_slot": 0,
"target_id": 213,
"target_slot": 1,
"type": "CONDITIONING"
},
{
"id": 412,
"origin_id": -10,
"origin_slot": 22,
"target_id": 239,
"target_slot": 1,
"type": "VAE"
},
{
"id": 985,
"origin_id": -10,
"origin_slot": 20,
"target_id": 158,
"target_slot": 0,
"type": "CONDITIONING"
},
{
"id": 986,
"origin_id": -10,
"origin_slot": 20,
"target_id": 213,
"target_slot": 0,
"type": "CONDITIONING"
},
{
"id": 992,
"origin_id": 239,
"origin_slot": 0,
"target_id": 422,
"target_slot": 0,
"type": "IMAGE"
},
{
"id": 993,
"origin_id": 422,
"origin_slot": 0,
"target_id": 688,
"target_slot": 0,
"type": "IMAGE"
},
{
"id": 1289,
"origin_id": -10,
"origin_slot": 6,
"target_id": 213,
"target_slot": 2,
"type": "BOOLEAN"
},
{
"id": 1294,
"origin_id": -10,
"origin_slot": 12,
"target_id": 422,
"target_slot": 2,
"type": "BOOLEAN"
},
{
"id": 1295,
"origin_id": -10,
"origin_slot": 13,
"target_id": 422,
"target_slot": 1,
"type": "STRING"
},
{
"id": 1296,
"origin_id": -10,
"origin_slot": 14,
"target_id": 422,
"target_slot": 3,
"type": "BOOLEAN"
},
{
"id": 1297,
"origin_id": -10,
"origin_slot": 15,
"target_id": 422,
"target_slot": 4,
"type": "FLOAT"
},
{
"id": 1298,
"origin_id": -10,
"origin_slot": 16,
"target_id": 688,
"target_slot": 2,
"type": "BOOLEAN"
},
{
"id": 1591,
"origin_id": 688,
"origin_slot": 0,
"target_id": 1107,
"target_slot": 0,
"type": "IMAGE"
},
{
"id": 1592,
"origin_id": -10,
"origin_slot": 8,
"target_id": 1107,
"target_slot": 2,
"type": "BOOLEAN"
},
{
"id": 1593,
"origin_id": -10,
"origin_slot": 9,
"target_id": 1107,
"target_slot": 3,
"type": "STRING"
},
{
"id": 1595,
"origin_id": -10,
"origin_slot": 10,
"target_id": 1107,
"target_slot": 4,
"type": "BOOLEAN"
},
{
"id": 1596,
"origin_id": -10,
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"name": "images",
"type": "IMAGE",
"links": [
2198
]
}
],
"properties": {
"cnr_id": "comfyui-aaalice-nodes",
"ver": "5c4d31a0892f308d0234782a23749ace1fc5fe64",
"Node name for S&R": "ConditionalSaveImage",
"aaaliceControlHostId": "host_f55ea63b-5613-4ff3-a2f6-32cfcba370d3"
},
"widgets_values": [
true,
"ComfyUI",
"png",
false,
100,
6,
0,
false,
true,
true,
true,
false
],
"widgets_values_named": {
"enabled": true,
"filename_prefix": "ComfyUI",
"file_format": "png",
"lossless_webp": false,
"quality": 100,
"webp_method": 6,
"jpeg_subsampling": 0,
"embed_workflow": false,
"save_with_metadata": true,
"add_loras_to_prompt": true,
"add_counter_to_filename": true,
"save_as_recipe": false
},
"color": "#223",
"bgcolor": "#335"
},
{
"id": 1414,
"type": "VRAM_Debug",
"pos": [
-2080,
-180
],
"size": [
300,
190
],
"flags": {},
"order": 16,
"mode": 0,
"inputs": [
{
"localized_name": "any_input",
"name": "any_input",
"shape": 7,
"type": "*",
"link": null
},
{
"localized_name": "image_pass",
"name": "image_pass",
"shape": 7,
"type": "IMAGE",
"link": 2198
},
{
"localized_name": "model_pass",
"name": "model_pass",
"shape": 7,
"type": "MODEL",
"link": null
}
],
"outputs": [
{
"localized_name": "any_output",
"name": "any_output",
"type": "*",
"links": null
},
{
"localized_name": "image_pass",
"name": "image_pass",
"type": "IMAGE",
"links": [
2199
]
},
{
"localized_name": "model_pass",
"name": "model_pass",
"type": "MODEL",
"links": null
},
{
"label": "3,072,902,834 freemem_before",
"localized_name": "freemem_before",
"name": "freemem_before",
"type": "INT",
"links": null
},
{
"label": "3,072,902,834 freemem_after",
"localized_name": "freemem_after",
"name": "freemem_after",
"type": "INT",
"links": null
}
],
"properties": {
"cnr_id": "comfyui-kjnodes",
"ver": "3f20054214fec9f9234fd3841ae6f1e4287948f6",
"Node name for S&R": "VRAM_Debug",
"aaaliceControlHostId": "host_ce1c70e9-b708-4391-afa2-1a1507d4c267"
},
"widgets_values": [
true,
true,
false
],
"widgets_values_named": {
"empty_cache": true,
"gc_collect": true,
"unload_all_models": false
},
"color": "#323",
"bgcolor": "#535"
},
{
"id": 496,
"type": "EmptyLatentImage",
"pos": [
-5340,
490
],
"size": [
320,
170
],
"flags": {},
"order": 4,
"mode": 0,
"inputs": [
{
"localized_name": "宽度",
"name": "width",
"type": "INT",
"widget": {
"name": "width"
},
"link": 715
},
{
"localized_name": "高度",
"name": "height",
"type": "INT",
"widget": {
"name": "height"
},
"link": 716
},
{
"localized_name": "批量大小",
"name": "batch_size",
"type": "INT",
"widget": {
"name": "batch_size"
},
"link": 717
}
],
"outputs": [
{
"localized_name": "Latent",
"name": "LATENT",
"type": "LATENT",
"slot_index": 0,
"links": [
1826
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.25.0",
"Node name for S&R": "EmptyLatentImage",
"aaaliceControlHostId": "host_d57789f9-8f6e-4009-baa3-0b8316a39336"
},
"widgets_values": [
1024,
1024,
1
],
"widgets_values_named": {
"width": 1024,
"height": 1024,
"batch_size": 1
},
"color": "#323",
"bgcolor": "#535"
},
{
"id": 497,
"type": "GetNode",
"pos": [
-5530,
520
],
"size": [
230,
40
],
"flags": {
"collapsed": true
},
"order": 2,
"mode": 0,
"inputs": [],
"outputs": [
{
"name": "INT",
"type": "INT",
"links": [
715
]
}
],
"title": "Get_底图宽度",
"properties": {
"Node name for S&R": "GetNode",
"aux_id": "kijai/ComfyUI-KJNodes",
"aaaliceControlHostId": "host_6efd56c5-c9cf-4f30-8352-3e423c1cc875"
},
"widgets_values": [
"底图宽度"
],
"widgets_values_named": {
"Constant": "底图宽度"
},
"color": "#1b4669",
"bgcolor": "#29699c"
},
{
"id": 697,
"type": "ComfySwitchNode",
"pos": [
-2830,
-180
],
"size": [
350,
130
],
"flags": {},
"order": 9,
"mode": 0,
"inputs": [
{
"localized_name": "为假时",
"name": "on_false",
"shape": 7,
"type": "IMAGE",
"link": 1007
},
{
"localized_name": "为真时",
"name": "on_true",
"shape": 7,
"type": "IMAGE",
"link": 2304
},
{
"label": "是否底图确认",
"localized_name": "切换",
"name": "switch",
"type": "BOOLEAN",
"widget": {
"name": "switch"
},
"link": 1319
}
],
"outputs": [
{
"localized_name": "输出",
"name": "output",
"type": "IMAGE",
"links": [
1607
]
}
],
"title": "是否底图确认",
"properties": {
"cnr_id": "comfy-core",
"ver": "0.28.0",
"Node name for S&R": "ComfySwitchNode",
"aaaliceControlHostId": "host_102b732e-8d38-4dc6-befb-a5294b520213"
},
"widgets_values": [
true
],
"widgets_values_named": {
"switch": true
}
},
{
"id": 1450,
"type": "SesquiLatentUpscale",
"pos": [
-4340,
-180
],
"size": [
290,
110
],
"flags": {},
"order": 17,
"mode": 0,
"inputs": [
{
"localized_name": "latent",
"name": "latent",
"type": "LATENT",
"link": 2245
},
{
"localized_name": "model_format",
"name": "model_format",
"type": "COMBO",
"widget": {
"name": "model_format"
},
"link": 2255
},
{
"localized_name": "scale",
"name": "scale",
"type": "FLOAT",
"widget": {
"name": "scale"
},
"link": 2254
}
],
"outputs": [
{
"localized_name": "Latent",
"name": "LATENT",
"type": "LATENT",
"links": [
2253
]
}
],
"properties": {
"aux_id": "LoganBooker/SesquiLSR",
"ver": "befae004248c403f38b76b9f65fd43b901ea3eaa",
"Node name for S&R": "SesquiLatentUpscale",
"aaaliceControlHostId": "host_1943f2f3-a576-4eb6-8266-39cb5ad5d937"
},
"widgets_values": [
"Wan 2.1",
1,
true
],
"widgets_values_named": {
"model_format": "Wan 2.1",
"scale": 1,
"half_precision": true
},
"color": "#323",
"bgcolor": "#535"
},
{
"id": 1245,
"type": "KSamplerAdvanced",
"pos": [
-4880,
-180
],
"size": [
530,
1140
],
"flags": {},
"order": 14,
"mode": 0,
"showAdvanced": true,
"inputs": [
{
"localized_name": "模型",
"name": "model",
"type": "MODEL",
"link": 1824
},
{
"localized_name": "正面条件",
"name": "positive",
"type": "CONDITIONING",
"link": 1820
},
{
"localized_name": "负面条件",
"name": "negative",
"type": "CONDITIONING",
"link": 1825
},
{
"localized_name": "Latent图像",
"name": "latent_image",
"type": "LATENT",
"link": 1826
},
{
"localized_name": "随机种",
"name": "noise_seed",
"type": "INT",
"widget": {
"name": "noise_seed"
},
"link": 1833
},
{
"localized_name": "步数",
"name": "steps",
"type": "INT",
"widget": {
"name": "steps"
},
"link": 2270
},
{
"localized_name": "cfg",
"name": "cfg",
"type": "FLOAT",
"widget": {
"name": "cfg"
},
"link": 1834
},
{
"localized_name": "采样器名称",
"name": "sampler_name",
"type": "COMBO",
"widget": {
"name": "sampler_name"
},
"link": 1835
},
{
"localized_name": "调度器",
"name": "scheduler",
"type": "COMBO",
"widget": {
"name": "scheduler"
},
"link": 1836
},
{
"localized_name": "结束步数",
"name": "end_at_step",
"type": "INT",
"widget": {
"name": "end_at_step"
},
"link": 2271
}
],
"outputs": [
{
"localized_name": "Latent",
"name": "LATENT",
"type": "LATENT",
"links": [
2245
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.33.1",
"Node name for S&R": "KSamplerAdvanced",
"aaaliceControlHostId": "host_00eac501-ccf6-47a7-85d6-49489d533a53"
},
"widgets_values": [
"enable",
0,
"randomize",
20,
8,
"euler",
"simple",
0,
10000,
"enable"
],
"widgets_values_named": {
"add_noise": "enable",
"noise_seed": 0,
"control_after_generate": "randomize",
"steps": 20,
"cfg": 8,
"sampler_name": "euler",
"scheduler": "simple",
"start_at_step": 0,
"end_at_step": 10000,
"return_with_leftover_noise": "enable"
},
"color": "#432",
"bgcolor": "#653",
"shape": 1
},
{
"id": 1246,
"type": "KSamplerAdvanced",
"pos": [
-4040,
-180
],
"size": [
530,
1140
],
"flags": {},
"order": 15,
"mode": 0,
"showAdvanced": true,
"inputs": [
{
"localized_name": "模型",
"name": "model",
"type": "MODEL",
"link": 1823
},
{
"localized_name": "正面条件",
"name": "positive",
"type": "CONDITIONING",
"link": 1821
},
{
"localized_name": "负面条件",
"name": "negative",
"type": "CONDITIONING",
"link": 1822
},
{
"localized_name": "Latent图像",
"name": "latent_image",
"type": "LATENT",
"link": 2253
},
{
"localized_name": "随机种",
"name": "noise_seed",
"type": "INT",
"widget": {
"name": "noise_seed"
},
"link": 2195
},
{
"localized_name": "步数",
"name": "steps",
"type": "INT",
"widget": {
"name": "steps"
},
"link": 2272
},
{
"localized_name": "cfg",
"name": "cfg",
"type": "FLOAT",
"widget": {
"name": "cfg"
},
"link": 1837
},
{
"localized_name": "采样器名称",
"name": "sampler_name",
"type": "COMBO",
"widget": {
"name": "sampler_name"
},
"link": 1839
},
{
"localized_name": "调度器",
"name": "scheduler",
"type": "COMBO",
"widget": {
"name": "scheduler"
},
"link": 1840
},
{
"localized_name": "开始步数",
"name": "start_at_step",
"type": "INT",
"widget": {
"name": "start_at_step"
},
"link": 2274
},
{
"localized_name": "结束步数",
"name": "end_at_step",
"type": "INT",
"widget": {
"name": "end_at_step"
},
"link": 2273
}
],
"outputs": [
{
"localized_name": "Latent",
"name": "LATENT",
"type": "LATENT",
"links": [
1828
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.33.1",
"Node name for S&R": "KSamplerAdvanced",
"aaaliceControlHostId": "host_47ef67ed-e860-4676-9976-be08fd49fae3"
},
"widgets_values": [
"enable",
0,
"randomize",
20,
8,
"euler",
"simple",
0,
10000,
"disable"
],
"widgets_values_named": {
"add_noise": "enable",
"noise_seed": 0,
"control_after_generate": "randomize",
"steps": 20,
"cfg": 8,
"sampler_name": "euler",
"scheduler": "simple",
"start_at_step": 0,
"end_at_step": 10000,
"return_with_leftover_noise": "disable"
},
"color": "#432",
"bgcolor": "#653",
"shape": 1
},
{
"id": 801,
"type": "PrimitiveInt",
"pos": [
-5340,
710
],
"size": [
270,
90
],
"flags": {},
"order": 10,
"mode": 0,
"inputs": [
{
"label": "总步数",
"localized_name": "数值",
"name": "value",
"type": "INT",
"widget": {
"name": "value"
},
"link": 1302
}
],
"outputs": [
{
"localized_name": "整数",
"name": "INT",
"type": "INT",
"links": [
2270,
2271,
2272,
2273
]
}
],
"title": "总步数",
"properties": {
"cnr_id": "comfy-core",
"ver": "0.28.0",
"Node name for S&R": "PrimitiveInt",
"aaaliceControlHostId": "host_d0c4b918-3111-41aa-b6e1-aa292f891183"
},
"widgets_values": [
30,
"fixed"
],
"widgets_values_named": {
"value": 30,
"fixed": "fixed"
}
},
{
"id": 802,
"type": "PrimitiveInt",
"pos": [
-5340,
850
],
"size": [
270,
90
],
"flags": {},
"order": 11,
"mode": 0,
"inputs": [
{
"label": "采样器切换步数",
"localized_name": "数值",
"name": "value",
"type": "INT",
"widget": {
"name": "value"
},
"link": 1303
}
],
"outputs": [
{
"localized_name": "整数",
"name": "INT",
"type": "INT",
"links": [
2274
]
}
],
"title": "采样器切换步数",
"properties": {
"cnr_id": "comfy-core",
"ver": "0.28.0",
"Node name for S&R": "PrimitiveInt",
"aaaliceControlHostId": "host_db4ee170-5a1e-4559-96aa-396c2d5413d1"
},
"widgets_values": [
15,
"fixed"
],
"widgets_values_named": {
"value": 15,
"fixed": "fixed"
}
},
{
"id": 543,
"type": "SimpleNotify",
"pos": [
-3160,
-180
],
"size": [
310,
200
],
"flags": {},
"order": 8,
"mode": 0,
"inputs": [
{
"localized_name": "值",
"name": "value",
"type": "*",
"link": 1005
},
{
"label": "消息通知内容",
"localized_name": "消息",
"name": "message",
"type": "STRING",
"widget": {
"name": "message"
},
"link": 1316
},
{
"label": "是否消息通知",
"localized_name": "桌面通知",
"name": "desktop_notification",
"type": "BOOLEAN",
"widget": {
"name": "desktop_notification"
},
"link": 1315
},
{
"label": "是否通知音效",
"localized_name": "提示音",
"name": "sound",
"type": "BOOLEAN",
"widget": {
"name": "sound"
},
"link": 1317
},
{
"label": "通知音效音量",
"localized_name": "音量",
"name": "volume",
"type": "FLOAT",
"widget": {
"name": "volume"
},
"link": 1318
}
],
"outputs": [
{
"localized_name": "值",
"name": "Value",
"type": "IMAGE",
"links": [
1007,
2303
]
}
],
"properties": {
"cnr_id": "comfyui-aaalice-nodes",
"ver": "796f924765b3dc52ef5ba83e5f540ceefdf30ca8",
"Node name for S&R": "SimpleNotify",
"aaaliceControlHostId": "host_1fa2c96e-4760-4331-a83d-4e1985951553"
},
"widgets_values": [
"底图（双采样）生成完毕喵~",
true,
true,
0.5
],
"widgets_values_named": {
"message": "底图（双采样）生成完毕喵~",
"desktop_notification": true,
"sound": true,
"volume": 0.5
},
"color": "#223",
"bgcolor": "#335"
},
{
"id": 1463,
"type": "AaaliceImagePicker",
"pos": [
-2830,
-10
],
"size": [
350,
130
],
"flags": {},
"order": 18,
"mode": 0,
"inputs": [
{
"localized_name": "图像",
"name": "images",
"type": "IMAGE",
"link": 2303
},
{
"localized_name": "说明",
"name": "instructions",
"shape": 7,
"type": "STRING",
"link": 2302
},
{
"localized_name": "超时",
"name": "timeout",
"type": "INT",
"widget": {
"name": "timeout"
},
"link": 2305
},
{
"localized_name": "超时策略",
"name": "timeout_action",
"type": "COMBO",
"widget": {
"name": "timeout_action"
},
"link": 2306
}
],
"outputs": [
{
"localized_name": "图像",
"name": "images",
"type": "IMAGE",
"links": [
2304
]
}
],
"properties": {
"cnr_id": "aaalice-image-picker",
"ver": "42df5d3bedf2155da679f078f31de1e7426a41de",
"Node name for S&R": "AaaliceImagePicker",
"aux_id": "Aaalice233/ComfyUI-Aaalice-Image-Picker",
"aaaliceControlHostId": "host_87a94942-ceb9-463b-bad0-473887261d80"
},
"widgets_values": [
"multiple",
300,
"submit_all"
],
"widgets_values_named": {
"selection_mode": "multiple",
"timeout": 300,
"timeout_action": "submit_all"
},
"color": "#223",
"bgcolor": "#335"
},
{
"id": 1462,
"type": "PrimitiveStringMultiline",
"pos": [
-2830,
160
],
"size": [
350,
160
],
"flags": {},
"order": 3,
"mode": 0,
"inputs": [],
"outputs": [
{
"localized_name": "字符串",
"name": "STRING",
"type": "STRING",
"links": [
2302
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.33.3",
"Node name for S&R": "PrimitiveStringMultiline",
"aaaliceControlHostId": "host_74861290-b39c-4152-802b-87662ac1d8ef"
},
"widgets_values": [
"# 选择你满意的图像👉\n\n- 通过调整“批次大小”参数，可以一次生成多张图像\n- 批次大小越大，越吃配置\n- 图像确认阶段可以通过参数关闭"
],
"widgets_values_named": {
"value": "# 选择你满意的图像👉\n\n- 通过调整“批次大小”参数，可以一次生成多张图像\n- 批次大小越大，越吃配置\n- 图像确认阶段可以通过参数关闭"
}
}
],
"groups": [],
"links": [
{
"id": 715,
"origin_id": 497,
"origin_slot": 0,
"target_id": 496,
"target_slot": 0,
"type": "INT"
},
{
"id": 716,
"origin_id": 498,
"origin_slot": 0,
"target_id": 496,
"target_slot": 1,
"type": "INT"
},
{
"id": 717,
"origin_id": 499,
"origin_slot": 0,
"target_id": 496,
"target_slot": 2,
"type": "INT"
},
{
"id": 751,
"origin_id": 537,
"origin_slot": 0,
"target_id": 538,
"target_slot": 1,
"type": "CONDITIONING"
},
{
"id": 1005,
"origin_id": 539,
"origin_slot": 0,
"target_id": 543,
"target_slot": 0,
"type": "IMAGE"
},
{
"id": 1007,
"origin_id": 543,
"origin_slot": 0,
"target_id": 697,
"target_slot": 0,
"type": "IMAGE"
},
{
"id": 1024,
"origin_id": -10,
"origin_slot": 24,
"target_id": 537,
"target_slot": 0,
"type": "CONDITIONING"
},
{
"id": 1025,
"origin_id": -10,
"origin_slot": 24,
"target_id": 538,
"target_slot": 0,
"type": "CONDITIONING"
},
{
"id": 1030,
"origin_id": -10,
"origin_slot": 29,
"target_id": 539,
"target_slot": 1,
"type": "VAE"
},
{
"id": 1302,
"origin_id": -10,
"origin_slot": 0,
"target_id": 801,
"target_slot": 0,
"type": "INT"
},
{
"id": 1303,
"origin_id": -10,
"origin_slot": 1,
"target_id": 802,
"target_slot": 0,
"type": "INT"
},
{
"id": 1310,
"origin_id": -10,
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{
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{
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{
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{
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{
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{
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{
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350,
130
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{
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{
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],
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],
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{
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"widget": {
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},
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},
{
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},
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},
{
"label": "是否通知音效",
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},
{
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],
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2276,
2308
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true,
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{
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{
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2309
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}
],
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300,
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"timeout_action": "submit_all"
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{
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"type": "GetImageSize",
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2322,
2325
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{
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{
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],
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"tabXOffset": 10,
"hasSecondTab": false,
"secondTabText": "Send Back",
"secondTabOffset": 80,
"secondTabWidth": 65,
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{
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660
],
"size": [
350,
160
],
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"mode": 0,
"inputs": [],
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"links": [
2307
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}
],
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"aaaliceControlHostId": "host_3b497b46-260c-4b4b-b43c-a17b9dd1308e"
},
"widgets_values": [
"# 选择你满意的图像👉\n\n- 通过调整“批次大小”参数，可以一次生成多张图像\n- 批次大小越大，越吃配置\n- 图像确认阶段可以通过参数关闭"
],
"widgets_values_named": {
"value": "# 选择你满意的图像👉\n\n- 通过调整“批次大小”参数，可以一次生成多张图像\n- 批次大小越大，越吃配置\n- 图像确认阶段可以通过参数关闭"
}
},
{
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440
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"name": "value",
"type": "BOOLEAN",
"widget": {
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},
"link": 2047
}
],
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{
"localized_name": "布尔",
"name": "BOOLEAN",
"type": "BOOLEAN",
"links": [
1937,
1964,
2357
]
}
],
"title": "是否使用Krita预处理",
"properties": {
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"Node name for S&R": "PrimitiveBoolean",
"aaaliceControlHostId": "host_6f302410-c0ff-4f74-84f4-5883e6509cf1"
},
"widgets_values": [
true
],
"widgets_values_named": {
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},
"color": "#2a363b",
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},
{
"id": 1456,
"type": "ConditionalSaveImage",
"pos": [
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320
],
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360,
640
],
"flags": {},
"order": 12,
"mode": 0,
"inputs": [
{
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"name": "images",
"type": "IMAGE",
"link": 2278
},
{
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"name": "metadata",
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"type": "METADATA",
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},
{
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"name": "enabled",
"type": "BOOLEAN",
"widget": {
"name": "enabled"
},
"link": 2282
},
{
"localized_name": "文件名前缀",
"name": "filename_prefix",
"type": "STRING",
"widget": {
"name": "filename_prefix"
},
"link": 2283
},
{
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"name": "embed_workflow",
"type": "BOOLEAN",
"widget": {
"name": "embed_workflow"
},
"link": 2284
},
{
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"name": "save_with_metadata",
"type": "BOOLEAN",
"widget": {
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},
"link": 2285
}
],
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"name": "images",
"type": "IMAGE",
"links": [
2279
]
}
],
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100,
6,
0,
false,
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true,
true,
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"quality": 100,
"webp_method": 6,
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"embed_workflow": false,
"save_with_metadata": true,
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"add_counter_to_filename": true,
"save_as_recipe": false
},
"color": "#223",
"bgcolor": "#335"
},
{
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"type": "ComfySwitchNode",
"pos": [
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530
],
"size": [
270,
80
],
"flags": {},
"order": 28,
"mode": 0,
"inputs": [
{
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"name": "on_false",
"shape": 7,
"type": "METADATA",
"link": 2358
},
{
"localized_name": "为真时",
"name": "on_true",
"shape": 7,
"type": "METADATA",
"link": 2362
},
{
"localized_name": "切换",
"name": "switch",
"type": "BOOLEAN",
"widget": {
"name": "switch"
},
"link": 2357
}
],
"outputs": [
{
"localized_name": "输出",
"name": "output",
"type": "METADATA",
"links": [
2361
]
}
],
"properties": {
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"ver": "0.33.1",
"Node name for S&R": "ComfySwitchNode",
"aaaliceControlHostId": "host_62512518-21a3-4c76-bc2c-da45c95a39c6"
},
"widgets_values": [
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],
"widgets_values_named": {
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}
},
{
"id": 1282,
"type": "InpaintStitchImproved",
"pos": [
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320
],
"size": [
230,
80
],
"flags": {},
"order": 4,
"mode": 0,
"inputs": [
{
"localized_name": "stitcher",
"name": "stitcher",
"type": "STITCHER",
"link": 1934
},
{
"localized_name": "inpainted_image",
"name": "inpainted_image",
"type": "IMAGE",
"link": 2336
}
],
"outputs": [
{
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"name": "image",
"type": "IMAGE",
"links": [
2280
]
}
],
"properties": {
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"shape": 7,
"type": "*",
"link": 2642
},
{
"localized_name": "为真时",
"name": "on_true",
"shape": 7,
"type": "IMAGE",
"link": 2643
},
{
"localized_name": "切换",
"name": "switch",
"type": "BOOLEAN",
"widget": {
"name": "switch"
},
"link": 2644
}
],
"outputs": [
{
"localized_name": "输出",
"name": "output",
"type": "IMAGE",
"links": [
2645
]
}
],
"properties": {
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"ver": "0.28.0",
"Node name for S&R": "ComfySwitchNode",
"aaaliceControlHostId": "host_ef5134eb-64a6-428d-b35e-817aa12d3b61"
},
"widgets_values": [
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"widgets_values_named": {
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}
},
{
"id": 1340,
"type": "LoadImage",
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],
"size": [
270,
340
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"flags": {},
"order": 3,
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"localized_name": "图像",
"name": "image",
"type": "COMBO",
"widget": {
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},
"link": 2646
},
{
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"name": "upload",
"type": "IMAGEUPLOAD",
"widget": {
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},
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}
],
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"name": "IMAGE",
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2642
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},
{
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},
{
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},
{
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},
{
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},
{
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}
],
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}
],
"title": "Get_【图像】底图",
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"aaaliceControlHostId": "host_1c4b1a7a-213f-4d6e-82c1-cea00b890443"
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{
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"outputs": [
{
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"links": [
2210
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}
],
"title": "Get_【图像】底图_双采样",
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"aux_id": "kijai/ComfyUI-KJNodes",
"aaaliceControlHostId": "host_131772ef-fc37-474c-b1c7-b652b8f7789d"
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{
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"type": "GetNode",
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{
"name": "IMAGE",
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}
],
"title": "Get_【图像】脸部细化",
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},
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},
{
"id": 1419,
"type": "Any Switch (rgthree)",
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"flags": {},
"order": 5,
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"inputs": [
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"link": 2207
},
{
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"name": "any_02",
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"link": 2208
},
{
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"name": "any_03",
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"link": 2209
},
{
"dir": 3,
"name": "any_04",
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"link": 2210
},
{
"dir": 3,
"name": "any_05",
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},
{
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"name": "any_06",
"type": "*",
"link": 2214
},
{
"name": "any_07",
"type": "*",
"link": null
}
],
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{
"dir": 4,
"label": "*",
"name": "*",
"shape": 3,
"type": "*",
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2648
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}
],
"properties": {
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"localized_name": "图像",
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"widget": {
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},
"link": 2649
}
],
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"name": "IMAGE",
"type": "IMAGE",
"links": [
2214
]
},
{
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},
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2207
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}
],
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{
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{
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{
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},
{
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"label": "是否消息通知",
"pos": [
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},
{
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"pos": [
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},
{
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"name": "sound",
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},
{
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},
{
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"type": "IMAGE",
"linkIds": [
2231
],
"localized_name": "images",
"pos": [
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}
],
"outputs": [
{
"id": "96ded87f-b2ae-44b0-8ed8-51d47f37aa6f",
"name": "upscaled_images",
"type": "IMAGE",
"linkIds": [
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"localized_name": "upscaled_images",
"pos": [
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}
],
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"inputs": [
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{
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"widget": {
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},
"link": 2234
},
{
"label": "是否消息通知",
"localized_name": "桌面通知",
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"type": "BOOLEAN",
"widget": {
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},
"link": 2235
},
{
"label": "是否通知音效",
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"name": "sound",
"type": "BOOLEAN",
"widget": {
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},
"link": 2236
},
{
"label": "通知音效音量",
"localized_name": "音量",
"name": "volume",
"type": "FLOAT",
"widget": {
"name": "volume"
},
"link": 2237
}
],
"outputs": [
{
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"name": "Value",
"type": "IMAGE",
"links": [
2228
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}
],
"properties": {
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"aaaliceControlHostId": "host_c305f74b-a345-45da-ac6c-00aa945a1494"
},
"widgets_values": [
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true,
true,
0.5
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"desktop_notification": true,
"sound": true,
"volume": 0.5
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},
{
"id": 1446,
"type": "ConditionalSaveImage",
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{
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{
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"type": "BOOLEAN",
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},
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{
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},
{
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"type": "BOOLEAN",
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},
{
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"widget": {
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},
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}
],
"outputs": [
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}
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"shape": 7,
"type": "*",
"link": 2660
},
{
"localized_name": "为真时",
"name": "on_true",
"shape": 7,
"type": "IMAGE",
"link": 2661
},
{
"localized_name": "切换",
"name": "switch",
"type": "BOOLEAN",
"widget": {
"name": "switch"
},
"link": 2662
}
],
"outputs": [
{
"localized_name": "输出",
"name": "output",
"type": "IMAGE",
"links": [
2663
]
}
],
"properties": {
"cnr_id": "comfy-core",
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"aaaliceControlHostId": "host_6a7e89f2-cef8-451c-9206-006035ce26fb"
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{
"id": 1440,
"type": "LoadImage",
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510
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"size": [
270,
340
],
"flags": {},
"order": 3,
"mode": 0,
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"type": "COMBO",
"widget": {
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"link": 2664
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{
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"name": "upload",
"type": "IMAGEUPLOAD",
"widget": {
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},
"link": 2665
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],
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{
"localized_name": "图像",
"name": "IMAGE",
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2660
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},
{
"localized_name": "遮罩",
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}
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{
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}
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}
],
"title": "Get_【提示词】最终正面提示词",
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}
],
"title": "Get_【管线】Clip_Lora_1",
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}
],
"title": "Get_【管线】Clip_Lora_2",
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"aaaliceControlHostId": "host_05ca514a-34c9-4ed7-a219-aa97b3118abd"
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{
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"flags": {
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}
],
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{
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}
],
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{
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],
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},
"[\"subgraph-widget\",\"host_35c97c46-4202-41d0-bb23-1d568207ed9c\",\"promoted:[\\\"57\\\",\\\"clip_name\\\",null]\",\"comfy-native-widget\"]": {
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"payload": "qwen3vl_4b_bf16-krea2.safetensors"
},
"[\"subgraph-widget\",\"host_35c97c46-4202-41d0-bb23-1d568207ed9c\",\"promoted:[\\\"58\\\",\\\"vae_name\\\",null]\",\"comfy-native-widget\"]": {
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"payload": "qwen_image_vae-krea2.safetensors"
},
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},
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"payload": "worst quality, low quality, score_1, score_2, score_3, blurry, jpeg artifacts, sepia"
},
"[\"subgraph-widget\",\"host_5bd5e77c-0ac9-4d16-bcf6-443fbe692d65\",\"promoted:[\\\"835\\\",\\\"image\\\",null]\",\"comfy-image-combo\"]": {
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},
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},
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},
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"payload": "Aaalice_example.jpg"
},
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},
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},
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},
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},
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},
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},
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},
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"payload": "Aaalice_example.jpg"
},
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},
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},
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"valueType": "boolean",
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"[\"subgraph-widget\",\"host_47c97a7b-7904-48c0-a052-2d63cf495323\",\"promoted:[\\\"271\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_47c97a7b-7904-48c0-a052-2d63cf495323\",\"promoted:[\\\"164\\\",\\\"rule\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
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},
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"valueType": "string",
"payload": "智谱/glm-4.5-flash"
},
"[\"subgraph-widget\",\"host_47c97a7b-7904-48c0-a052-2d63cf495323\",\"promoted:[\\\"164\\\",\\\"seed\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 1717233,
"control_after_generate": "fixed"
}
},
"[\"subgraph-widget\",\"host_47c97a7b-7904-48c0-a052-2d63cf495323\",\"promoted:[\\\"1195\\\",\\\"llm_service\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "智谱/glm-4.5-flash"
},
"[\"subgraph-widget\",\"host_47c97a7b-7904-48c0-a052-2d63cf495323\",\"promoted:[\\\"1198\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_47c97a7b-7904-48c0-a052-2d63cf495323\",\"promoted:[\\\"1195\\\",\\\"seed\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 1717233,
"control_after_generate": "fixed"
}
},
"[\"subgraph-widget\",\"host_47c97a7b-7904-48c0-a052-2d63cf495323\",\"promoted:[\\\"1197\\\",\\\"value\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "发色、发型、发长、眼睛颜色、瞳孔、皮肤、脸型、身高、体型、胸部、服装、配饰、特殊特征（角/尾巴/耳朵等）、气质"
},
"[\"subgraph-widget\",\"host_47c97a7b-7904-48c0-a052-2d63cf495323\",\"promoted:[\\\"1195\\\",\\\"custom_rule_content\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "你是一位专业的 AI 绘图提示词角色替换专家，专门负责把别人的角色提示词一键替换成用户的 OC。\n\n### 你的任务\n用户会给你一段文本，里面包含三部分信息：\n1. 原始绘图提示词（别人的串串）\n2. 用户的 OC 设定（完整人物描述）\n3. 需要替换的内容（例如：眼睛、发型发色、身高、体型、衣服、配饰等）\n\n你需要精准地把原始提示词里的人物特征，替换成用户 OC 对应的特征，同时保留原始提示词中的构图、姿势、表情、场景、光影、画风、质量词等所有非人物本体的部分。\n\n### 执行规则（必须严格遵守）\n1. **只替换人物本体相关描述**，包括但不限于：\n - 外貌（脸型、眼睛、瞳色、发型、发色、发长、皮肤、身高、体型、胸部、腿部等）\n - 服装与配饰\n - 标志性特征（疤痕、纹身、角、耳朵、尾巴等）\n - 年龄感、气质相关描述（如果用户指定了要替换）\n\n2. **绝对保留**以下内容，不要改动：\n - 姿势、动作、表情\n - 构图、视角、镜头\n - 场景、背景、环境\n - 光影、氛围、色调\n - 画风、画师、质量标签（masterpiece, best quality, highly detailed 等）\n - 其他与人物本体无关的修饰词\n\n3. 替换时要自然融合，使新提示词读起来流畅，不要生硬堆砌。优先使用 OC 设定里更精确、更完整的描述覆盖原描述。\n\n4. 如果用户指定了“要替换的内容”，则只替换这些部分；如果用户没有明确指定，则默认替换所有人物外貌与服装相关描述。\n\n5. **输出格式强制要求（最高优先级）**：\n - 只输出最终替换后的完整提示词\n - 必须是纯英文\n - 禁止输出任何中文\n - 禁止添加任何解释、备注、前后缀、标题、思考过程或额外文字\n - 直接输出一行或多行纯英文提示词即可，不要用代码块包裹\n\n### 输入示例结构（用户可能这样给你）\n原始提示词：\n1girl, long blonde hair, blue eyes, white dress, standing in forest, looking at viewer, masterpiece, best quality\n\nOC设定：\n黑长直，红色眼睛，冷白皮，高挑身材，穿着黑色高领毛衣和百褶裙，左耳有银色耳钉\n\n要替换的内容：\n发型发色、眼睛、衣服"
},
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"valueType": "number",
"payload": 12
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"cfg\\\",null]\",\"comfy-native-widget\"]": {
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"payload": 1
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"sampler_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "er_sde"
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"scheduler\\\",null]\",\"comfy-native-widget\"]": {
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"valueType": "string",
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"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_底图"
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"valueType": "string",
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},
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"payload": "%date:yyyy-MM-dd%/%seed%_脸部细化"
},
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"payload": "脸部细化完毕喵~"
},
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"payload": "seedvr2_7b_sharp_int8_convrot.safetensors"
},
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"payload": "%date:yyyy-MM-dd%/%seed%_SeedVR2放大"
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"payload": "%date:yyyy-MM-dd%/%seed%_N卡放大"
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"valueType": "string",
"payload": "N卡放大完毕喵~"
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1444\\\",\\\"sound\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1444\\\",\\\"volume\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.5
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"style\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "电影"
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"intensity\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"local_tone\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"local_struct\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
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"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"output_mix\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"generic-widget\",\"host_20402d60-96a6-4477-9e05-4bc93dde5e6b\",\"aaalice_booru_gallery\",\"aaalice-booru-gallery\"]": {
"valueType": "booru-gallery",
"payload": {
"version": 1,
"state": {
"version": 1,
"source": "danbooru",
"query": "",
"view": "browse",
"selectionMode": "single",
"randomMode": false,
"filters": {
"ratings": [
"general"
],
"sort": "score",
"feed": "search",
"period": ""
},
"navigation": {
"page": 1
},
"dashboard": {
"searchOpen": false
},
"prompt": {
"categories": [
"copyright",
"character",
"general"
],
"replaceUnderscores": false,
"escapeParentheses": false
},
"selections": [
{
"source": "danbooru",
"postId": "7000000",
"postUrl": "https://danbooru.donmai.us/posts/7000000",
"mediaUrl": "https://cdn.donmai.us/original/8d/81/8d819da4871c3ca39f428999df8220ce.jpg",
"previewUrl": "https://cdn.donmai.us/180x180/8d/81/8d819da4871c3ca39f428999df8220ce.jpg",
"fileExt": "jpg",
"width": 2000,
"height": 3000,
"rating": "g",
"originalTags": {
"artist": [
"beishang_yutou"
],
"copyright": [
"reverse:1999"
],
"character": [
"sonetto_(reverse:1999)"
],
"general": [
"4girls",
"aged_down",
"arch",
"armor",
"bow",
"bowtie",
"braid",
"closed_mouth",
"dress",
"green_eyes",
"hair_intakes",
"hair_ornament",
"hairband",
"indoors",
"long_hair",
"looking_ahead",
"looking_at_viewer",
"multiple_girls",
"orange_hair",
"portrait",
"profile",
"sidelighting",
"single_braid",
"statue",
"upper_body",
"watermark",
"white_dress",
"white_hairband",
"window"
],
"meta": [
"absurdres",
"chinese_commentary",
"commentary",
"highres"
]
}
}
]
}
}
},
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"valueType": "string",
"payload": "HSWZovHagAEb3tL.jpg"
},
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"valueType": "string",
"payload": "pixai-tagger-v0.9-timm"
},
"[\"subgraph-widget\",\"host_68623cbe-89e1-4841-a842-bc7d619be8fd\",\"promoted:[\\\"986\\\",\\\"character_threshold\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.8
},
"[\"subgraph-widget\",\"host_68623cbe-89e1-4841-a842-bc7d619be8fd\",\"promoted:[\\\"985\\\",\\\"vlm_service\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "智谱/glm-4.6V-Flash"
},
"[\"subgraph-widget\",\"host_68623cbe-89e1-4841-a842-bc7d619be8fd\",\"promoted:[\\\"985\\\",\\\"rule\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "像素级描述（by:阿丹）"
},
"[\"subgraph-widget\",\"host_68623cbe-89e1-4841-a842-bc7d619be8fd\",\"promoted:[\\\"985\\\",\\\"seed\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 1717233,
"control_after_generate": "fixed"
}
},
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"valueType": "number",
"payload": 0.2
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"valueType": "boolean",
"payload": false
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"valueType": "string",
"payload": "watermark, sample watermark, too many watermarks, text, signature, logo, username, artist name, web address, copyright, stamp, sample, trademark, url, patreon logo, twitter username, weibo watermark, character name, title, barcode, UI, lower text, bad quality, low quality, blurry"
},
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"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1453\\\",\\\"sound\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1453\\\",\\\"desktop_notification\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1453\\\",\\\"volume\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.47601886794847814
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1453\\\",\\\"message\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "局部重绘完毕喵~"
},
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"valueType": "boolean",
"payload": true
},
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"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_局部重绘"
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1456\\\",\\\"save_with_metadata\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
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"valueType": "boolean",
"payload": true
},
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"valueType": "string",
"payload": "flux-2-klein-9b-fp8_2.safetensors"
},
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"valueType": "string",
"payload": "qwen_3_8b_fp8mixed.safetensors"
},
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"payload": "full_encoder_small_decoder.safetensors"
},
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"valueType": "string",
"payload": "submit_all"
},
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"payload": 300
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"valueType": "boolean",
"payload": false
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"valueType": "number",
"payload": 1.2
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"valueType": "number",
"payload": 1
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"valueType": "string",
"payload": "reinhard_lab_gpu"
},
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"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1543\\\",\\\"steps\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 12
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"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1543\\\",\\\"sampler_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "euler"
},
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"valueType": "number",
"payload": 0.4
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"valueType": "number",
"payload": 1
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"payload": 1
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"payload": "beta"
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"payload": false
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"valueType": "resolution",
"payload": {
"version": 1,
"width": 1024,
"height": 1536,
"alignment": 8,
"canvasMax": 2048,
"presetId": "builtin:portrait-1024x1536"
}
},
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"valueType": "prompt-selector",
"payload": {
"version": 1,
"selections": [],
"separator": ", "
}
},
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"valueType": "prompt-selector",
"payload": {
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"selections": [],
"separator": ", "
}
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"separator": ", "
}
}
}
},
{
"id": "dashboard_preset_01e68ac7-b2b0-482b-8dec-6fb85cd7378a",
"name": "默认-Anima-2.9B-Silvermoon",
"dashboard": {
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"hostId": "host_3892ff51-89bf-4641-b0c1-80d431b3c41c",
"controlId": "manager",
"valueType": "quick-group-manager"
},
"label": "⚡ 快速组管理器",
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"controlId": "manager",
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"label": "⚡ 快速组管理器-可选",
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}
],
"groups": []
},
{
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},
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},
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},
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},
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},
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},
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},
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}
},
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"payload": "发色、发型、发长、眼睛颜色、瞳孔、皮肤、脸型、身高、体型、胸部、服装、配饰、特殊特征（角/尾巴/耳朵等）、气质"
},
"[\"subgraph-widget\",\"host_47c97a7b-7904-48c0-a052-2d63cf495323\",\"promoted:[\\\"1195\\\",\\\"custom_rule_content\\\",null]\",\"comfy-native-widget\"]": {
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"payload": "你是一位专业的 AI 绘图提示词角色替换专家，专门负责把别人的角色提示词一键替换成用户的 OC。\n\n### 你的任务\n用户会给你一段文本，里面包含三部分信息：\n1. 原始绘图提示词（别人的串串）\n2. 用户的 OC 设定（完整人物描述）\n3. 需要替换的内容（例如：眼睛、发型发色、身高、体型、衣服、配饰等）\n\n你需要精准地把原始提示词里的人物特征，替换成用户 OC 对应的特征，同时保留原始提示词中的构图、姿势、表情、场景、光影、画风、质量词等所有非人物本体的部分。\n\n### 执行规则（必须严格遵守）\n1. **只替换人物本体相关描述**，包括但不限于：\n - 外貌（脸型、眼睛、瞳色、发型、发色、发长、皮肤、身高、体型、胸部、腿部等）\n - 服装与配饰\n - 标志性特征（疤痕、纹身、角、耳朵、尾巴等）\n - 年龄感、气质相关描述（如果用户指定了要替换）\n\n2. **绝对保留**以下内容，不要改动：\n - 姿势、动作、表情\n - 构图、视角、镜头\n - 场景、背景、环境\n - 光影、氛围、色调\n - 画风、画师、质量标签（masterpiece, best quality, highly detailed 等）\n - 其他与人物本体无关的修饰词\n\n3. 替换时要自然融合，使新提示词读起来流畅，不要生硬堆砌。优先使用 OC 设定里更精确、更完整的描述覆盖原描述。\n\n4. 如果用户指定了“要替换的内容”，则只替换这些部分；如果用户没有明确指定，则默认替换所有人物外貌与服装相关描述。\n\n5. **输出格式强制要求（最高优先级）**：\n - 只输出最终替换后的完整提示词\n - 必须是纯英文\n - 禁止输出任何中文\n - 禁止添加任何解释、备注、前后缀、标题、思考过程或额外文字\n - 直接输出一行或多行纯英文提示词即可，不要用代码块包裹\n\n### 输入示例结构（用户可能这样给你）\n原始提示词：\n1girl, long blonde hair, blue eyes, white dress, standing in forest, looking at viewer, masterpiece, best quality\n\nOC设定：\n黑长直，红色眼睛，冷白皮，高挑身材，穿着黑色高领毛衣和百褶裙，左耳有银色耳钉\n\n要替换的内容：\n发型发色、眼睛、衣服"
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},
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"payload": "euler_ancestral"
},
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"valueType": "string",
"payload": "normal"
},
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"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"seed\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 404572692939880,
"control_after_generate": "randomize"
}
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"valueType": "number",
"payload": 300
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"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"1460\\\",\\\"timeout_action\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "submit_all"
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"1107\\\",\\\"enabled\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"241\\\",\\\"embed_workflow\\\",null]\",\"comfy-native-widget\"]": {
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},
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"valueType": "boolean",
"payload": true
},
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"valueType": "boolean",
"payload": true
},
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"valueType": "boolean",
"payload": true
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"payload": true
},
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"valueType": "boolean",
"payload": false
},
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"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_底图"
},
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"valueType": "string",
"payload": "底图生成完毕喵~"
},
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"valueType": "boolean",
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},
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"valueType": "number",
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"value": 28,
"control_after_generate": "fixed"
}
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"valueType": "boolean",
"payload": true
},
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"valueType": "number",
"payload": 300
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},
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"valueType": "boolean",
"payload": true
},
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},
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"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_底图（双采样器）"
},
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"payload": true
},
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"valueType": "string",
"payload": "底图（双采样）生成完毕喵~"
},
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"payload": true
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"payload": true
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"valueType": "boolean",
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"payload": false
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},
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"value": 75222765497786,
"control_after_generate": "randomize"
}
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"payload": {
"value": 14,
"control_after_generate": "fixed"
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"valueType": "string",
"payload": "Wan 2.1"
},
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"valueType": "string",
"payload": "Wan 2.1"
},
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"valueType": "number",
"payload": 14
},
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"payload": 4
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"valueType": "string",
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"value": 142351079931325,
"control_after_generate": "randomize"
}
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"payload": false
},
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"payload": true
},
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"payload": "%date:yyyy-MM-dd%/%seed%_潜空间放大"
},
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"valueType": "string",
"payload": "潜空间放大完毕喵~"
},
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},
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"payload": 0.5
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"valueType": "number",
"payload": 14
},
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"payload": 4
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"payload": "simple"
},
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"valueType": "number",
"payload": {
"value": 590657087978397,
"control_after_generate": "randomize"
}
},
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"valueType": "boolean",
"payload": true
},
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"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_脸部细化"
},
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"valueType": "boolean",
"payload": true
},
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"valueType": "boolean",
"payload": true
},
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"valueType": "boolean",
"payload": true
},
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"valueType": "string",
"payload": "脸部细化完毕喵~"
},
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"valueType": "boolean",
"payload": true
},
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"valueType": "number",
"payload": 0.5
},
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"valueType": "boolean",
"payload": false
},
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"valueType": "boolean",
"payload": false
},
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"valueType": "number",
"payload": 0.25
},
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"payload": "seedvr2_7b_sharp_int8_convrot.safetensors"
},
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"valueType": "string",
"payload": "wavelet"
},
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"payload": true
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"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_SeedVR2放大"
},
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"valueType": "boolean",
"payload": true
},
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"valueType": "boolean",
"payload": true
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"payload": true
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"valueType": "string",
"payload": "SeedVR2放大完毕喵~"
},
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},
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"valueType": "number",
"payload": 0.5
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"valueType": "number",
"payload": 1.5
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"valueType": "number",
"payload": 2
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"payload": true
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"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_N卡放大"
},
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"valueType": "boolean",
"payload": true
},
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"valueType": "boolean",
"payload": true
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"valueType": "boolean",
"payload": true
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"valueType": "string",
"payload": "N卡放大完毕喵~"
},
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"valueType": "boolean",
"payload": true
},
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"valueType": "number",
"payload": 0.5
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"style\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "电影"
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"intensity\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
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"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"local_tone\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
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"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"local_struct\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
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"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"output_mix\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"generic-widget\",\"host_20402d60-96a6-4477-9e05-4bc93dde5e6b\",\"aaalice_booru_gallery\",\"aaalice-booru-gallery\"]": {
"valueType": "booru-gallery",
"payload": {
"version": 1,
"state": {
"version": 1,
"source": "danbooru",
"query": "",
"view": "browse",
"selectionMode": "single",
"randomMode": false,
"filters": {
"ratings": [
"general"
],
"sort": "latest",
"feed": "search",
"period": ""
},
"navigation": {
"page": 2
},
"dashboard": {
"searchOpen": false
},
"prompt": {
"categories": [
"copyright",
"character",
"general"
],
"replaceUnderscores": false,
"escapeParentheses": false
},
"selections": [
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"postId": "12207428",
"postUrl": "https://danbooru.donmai.us/posts/12207428",
"mediaUrl": "https://cdn.donmai.us/original/ba/61/ba612419bf4278aaa84d617278bf01fe.jpg",
"previewUrl": "https://cdn.donmai.us/180x180/ba/61/ba612419bf4278aaa84d617278bf01fe.jpg",
"fileExt": "jpg",
"width": 1152,
"height": 2048,
"rating": "g",
"originalTags": {
"artist": [
"isomnya_(sxu7cid3)"
],
"copyright": [
"blue_archive"
],
"character": [
"suzumi_(blue_archive)"
],
"general": [
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"arius_branch_school_logo",
"battle_rifle",
"black_shoes",
"black_shorts",
"breasts",
"brown_pantyhose",
"cleavage",
"coat",
"elbow_gloves",
"gloves",
"gun",
"hair_between_eyes",
"halo",
"handgun",
"head_wings",
"holding",
"holding_gun",
"holding_weapon",
"holster",
"holstered",
"knee_sleeve",
"large_breasts",
"load-bearing_equipment",
"long_hair",
"looking_at_viewer",
"m84_stun_grenade",
"open_mouth",
"pantyhose",
"pantyhose_under_shorts",
"pouch",
"purple_halo",
"raised_eyebrows",
"red_eyes",
"rifle",
"shadow",
"shoes",
"shorts",
"sig_mcx",
"sig_sauer",
"simple_background",
"single_head_wing",
"smile",
"smug",
"sneakers",
"solo",
"tactical_clothes",
"thigh_holster",
"thigh_pouch",
"very_long_hair",
"weapon",
"white_background",
"white_coat",
"white_hair",
"wings"
],
"meta": [
"highres"
]
}
}
]
}
}
},
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"valueType": "string",
"payload": "Aaalice_example.jpg"
},
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"valueType": "string",
"payload": "pixai-tagger-v0.9-timm"
},
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"valueType": "number",
"payload": 0.8
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"[\"subgraph-widget\",\"host_68623cbe-89e1-4841-a842-bc7d619be8fd\",\"promoted:[\\\"985\\\",\\\"vlm_service\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "智谱/glm-4.6V-Flash"
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"valueType": "string",
"payload": "像素级描述（by:阿丹）"
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"valueType": "number",
"payload": {
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"control_after_generate": "fixed"
}
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"payload": "watermark, sample watermark, too many watermarks, text, signature, logo, username, artist name, web address, copyright, stamp, sample, trademark, url, patreon logo, twitter username, weibo watermark, character name, title, barcode, UI, lower text, bad quality, low quality, blurry"
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"payload": true
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"valueType": "boolean",
"payload": true
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"payload": 0.47601886794847814
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"payload": "qwen_3_8b_fp8mixed.safetensors"
},
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"payload": "full_encoder_small_decoder.safetensors"
},
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"payload": "submit_all"
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"payload": 300
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"payload": false
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"valueType": "number",
"payload": 1.2
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"payload": 1
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"valueType": "string",
"payload": "reinhard_lab_gpu"
},
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"valueType": "boolean",
"payload": false
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"valueType": "number",
"payload": 28
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"valueType": "string",
"payload": "euler"
},
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"valueType": "number",
"payload": 0.4
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1480\\\",\\\"batch_size\\\",null]\",\"comfy-native-widget\"]": {
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"payload": 1
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"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1543\\\",\\\"cfg\\\",null]\",\"comfy-native-widget\"]": {
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"payload": 4
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"valueType": "string",
"payload": "beta"
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"payload": false
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"payload": {
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"width": 1024,
"height": 1536,
"alignment": 8,
"canvasMax": 2048,
"presetId": "builtin:portrait-1024x1536"
}
},
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"separator": ", "
}
},
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"valueType": "prompt-selector",
"payload": {
"version": 1,
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"separator": ", "
}
},
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"payload": {
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"separator": ", "
}
},
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"valueType": "string",
"payload": "ema_vae_fp16.safetensors"
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1466\\\",\\\"unet_name\\\",null]\",\"comfy-native-widget\"]": {
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"payload": "flux-2-klein-9b-fp8.safetensors"
}
}
},
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"payload": "发色、发型、发长、眼睛颜色、瞳孔、皮肤、脸型、身高、体型、胸部、服装、配饰、特殊特征（角/尾巴/耳朵等）、气质"
},
"[\"subgraph-widget\",\"host_47c97a7b-7904-48c0-a052-2d63cf495323\",\"promoted:[\\\"1195\\\",\\\"custom_rule_content\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "你是一位专业的 AI 绘图提示词角色替换专家，专门负责把别人的角色提示词一键替换成用户的 OC。\n\n### 你的任务\n用户会给你一段文本，里面包含三部分信息：\n1. 原始绘图提示词（别人的串串）\n2. 用户的 OC 设定（完整人物描述）\n3. 需要替换的内容（例如：眼睛、发型发色、身高、体型、衣服、配饰等）\n\n你需要精准地把原始提示词里的人物特征，替换成用户 OC 对应的特征，同时保留原始提示词中的构图、姿势、表情、场景、光影、画风、质量词等所有非人物本体的部分。\n\n### 执行规则（必须严格遵守）\n1. **只替换人物本体相关描述**，包括但不限于：\n - 外貌（脸型、眼睛、瞳色、发型、发色、发长、皮肤、身高、体型、胸部、腿部等）\n - 服装与配饰\n - 标志性特征（疤痕、纹身、角、耳朵、尾巴等）\n - 年龄感、气质相关描述（如果用户指定了要替换）\n\n2. **绝对保留**以下内容，不要改动：\n - 姿势、动作、表情\n - 构图、视角、镜头\n - 场景、背景、环境\n - 光影、氛围、色调\n - 画风、画师、质量标签（masterpiece, best quality, highly detailed 等）\n - 其他与人物本体无关的修饰词\n\n3. 替换时要自然融合，使新提示词读起来流畅，不要生硬堆砌。优先使用 OC 设定里更精确、更完整的描述覆盖原描述。\n\n4. 如果用户指定了“要替换的内容”，则只替换这些部分；如果用户没有明确指定，则默认替换所有人物外貌与服装相关描述。\n\n5. **输出格式强制要求（最高优先级）**：\n - 只输出最终替换后的完整提示词\n - 必须是纯英文\n - 禁止输出任何中文\n - 禁止添加任何解释、备注、前后缀、标题、思考过程或额外文字\n - 直接输出一行或多行纯英文提示词即可，不要用代码块包裹\n\n### 输入示例结构（用户可能这样给你）\n原始提示词：\n1girl, long blonde hair, blue eyes, white dress, standing in forest, looking at viewer, masterpiece, best quality\n\nOC设定：\n黑长直，红色眼睛，冷白皮，高挑身材，穿着黑色高领毛衣和百褶裙，左耳有银色耳钉\n\n要替换的内容：\n发型发色、眼睛、衣服"
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"steps\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 12
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"cfg\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"sampler_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "euler_ancestral"
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"scheduler\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "normal"
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"denoise\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"seed\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 974845072890353,
"control_after_generate": "randomize"
}
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"685\\\",\\\"timeout\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 300
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"1460\\\",\\\"timeout_action\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "submit_all"
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"1107\\\",\\\"enabled\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"241\\\",\\\"embed_workflow\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"241\\\",\\\"save_with_metadata\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"422\\\",\\\"desktop_notification\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"422\\\",\\\"volume\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.5
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"422\\\",\\\"sound\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"688\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_59e2aae9-2094-4e5c-9026-169f9a7a914d\",\"promoted:[\\\"750\\\",\\\"value\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"241\\\",\\\"filename_prefix\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_底图"
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"422\\\",\\\"message\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "底图生成完毕喵~"
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"213\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"1577\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"801\\\",\\\"value\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 16,
"control_after_generate": "fixed"
}
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"543\\\",\\\"desktop_notification\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"543\\\",\\\"volume\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.5
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"696\\\",\\\"timeout\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 300
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1463\\\",\\\"timeout_action\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "submit_all"
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1246\\\",\\\"scheduler\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "beta"
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1108\\\",\\\"enabled\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"540\\\",\\\"save_with_metadata\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"540\\\",\\\"filename_prefix\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_底图（双采样器）"
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"540\\\",\\\"embed_workflow\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"543\\\",\\\"message\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "底图（双采样）生成完毕喵~"
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"543\\\",\\\"sound\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"697\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1246\\\",\\\"cfg\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_49d7435c-e923-40f9-8b4b-823c60168c7a\",\"promoted:[\\\"1023\\\",\\\"value\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1246\\\",\\\"sampler_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "euler"
},
"[\"subgraph-widget\",\"host_e79a5102-004f-408a-9991-c39d2d03e32a\",\"promoted:[\\\"1007\\\",\\\"value\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1245\\\",\\\"cfg\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1245\\\",\\\"sampler_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "er_sde"
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1245\\\",\\\"scheduler\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "simple"
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"538\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1245\\\",\\\"noise_seed\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 88567117561095,
"control_after_generate": "randomize"
}
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"802\\\",\\\"value\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 4,
"control_after_generate": "fixed"
}
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1450\\\",\\\"scale\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1.35
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1450\\\",\\\"model_format\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "Wan 2.1"
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"scale_by\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1.5
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"upscale_method\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "Wan 2.1"
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"steps\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 4
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"cfg\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"sampler_name\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "euler"
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"scheduler\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "simple"
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"denoise\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.35
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"seed\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 279042858470865,
"control_after_generate": "randomize"
}
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"switch\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_4ae9f10c-754c-4d6b-8edf-52c00df63fc7\",\"promoted:[\\\"1039\\\",\\\"value\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"save_with_metadata\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"embed_workflow\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"filename_prefix\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_潜空间放大"
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"desktop_notification\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"message\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "潜空间放大完毕喵~"
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"sound\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"volume\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.5
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1215\\\",\\\"steps\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 4
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1215\\\",\\\"cfg_scale\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1215\\\",\\\"sampler\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "euler"
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1215\\\",\\\"scheduler\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "simple"
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1215\\\",\\\"seed\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 807707146567366,
"control_after_generate": "randomize"
}
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1262\\\",\\\"enabled\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1262\\\",\\\"filename_prefix\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_脸部细化"
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1262\\\",\\\"embed_workflow\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1262\\\",\\\"save_with_metadata\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1261\\\",\\\"desktop_notification\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1261\\\",\\\"message\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "脸部细化完毕喵~"
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1261\\\",\\\"sound\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1261\\\",\\\"volume\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.5
},
"[\"subgraph-widget\",\"host_aff77634-1b75-4273-a0a6-e21ead6d242f\",\"promoted:[\\\"1227\\\",\\\"value\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1355\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1215\\\",\\\"denoise_strength\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.25
},
"[\"subgraph-widget\",\"host_9b25233b-ba58-48f1-90e5-9151bb2af6a6\",\"promoted:[\\\"716\\\",\\\"unet_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "seedvr2_7b_sharp_int8_convrot.safetensors"
},
"[\"subgraph-widget\",\"host_9b25233b-ba58-48f1-90e5-9151bb2af6a6\",\"promoted:[\\\"721\\\",\\\"color_correction_method\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "wavelet"
},
"[\"subgraph-widget\",\"host_9b25233b-ba58-48f1-90e5-9151bb2af6a6\",\"promoted:[\\\"1112\\\",\\\"enabled\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_9b25233b-ba58-48f1-90e5-9151bb2af6a6\",\"promoted:[\\\"400\\\",\\\"filename_prefix\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_SeedVR2放大"
},
"[\"subgraph-widget\",\"host_9b25233b-ba58-48f1-90e5-9151bb2af6a6\",\"promoted:[\\\"400\\\",\\\"embed_workflow\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_9b25233b-ba58-48f1-90e5-9151bb2af6a6\",\"promoted:[\\\"400\\\",\\\"save_with_metadata\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_9b25233b-ba58-48f1-90e5-9151bb2af6a6\",\"promoted:[\\\"434\\\",\\\"desktop_notification\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_9b25233b-ba58-48f1-90e5-9151bb2af6a6\",\"promoted:[\\\"434\\\",\\\"message\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "SeedVR2放大完毕喵~"
},
"[\"subgraph-widget\",\"host_9b25233b-ba58-48f1-90e5-9151bb2af6a6\",\"promoted:[\\\"434\\\",\\\"sound\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_9b25233b-ba58-48f1-90e5-9151bb2af6a6\",\"promoted:[\\\"434\\\",\\\"volume\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.5
},
"[\"subgraph-widget\",\"host_9b25233b-ba58-48f1-90e5-9151bb2af6a6\",\"promoted:[\\\"907\\\",\\\"value\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1.5
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1418\\\",\\\"resize_type.scale\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 2
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1446\\\",\\\"enabled\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1446\\\",\\\"filename_prefix\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_N卡放大"
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1446\\\",\\\"embed_workflow\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1446\\\",\\\"save_with_metadata\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1444\\\",\\\"desktop_notification\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1444\\\",\\\"message\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "N卡放大完毕喵~"
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1444\\\",\\\"sound\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1444\\\",\\\"volume\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.5
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"style\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "电影"
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"intensity\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"local_tone\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"local_struct\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1492\\\",\\\"output_mix\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"generic-widget\",\"host_20402d60-96a6-4477-9e05-4bc93dde5e6b\",\"aaalice_booru_gallery\",\"aaalice-booru-gallery\"]": {
"valueType": "booru-gallery",
"payload": {
"version": 1,
"state": {
"version": 1,
"source": "danbooru",
"query": "",
"view": "browse",
"selectionMode": "single",
"randomMode": false,
"filters": {
"ratings": [
"general"
],
"sort": "latest",
"feed": "ranking",
"period": "month"
},
"navigation": {
"page": 19
},
"dashboard": {
"searchOpen": false
},
"prompt": {
"categories": [
"copyright",
"character",
"general"
],
"replaceUnderscores": false,
"escapeParentheses": false
},
"selections": [
{
"source": "danbooru",
"postId": "12130484",
"postUrl": "https://danbooru.donmai.us/posts/12130484",
"mediaUrl": "https://cdn.donmai.us/original/9f/b0/9fb00976926ace0a6d3049d8f5a8ce13.png",
"previewUrl": "https://cdn.donmai.us/180x180/9f/b0/9fb00976926ace0a6d3049d8f5a8ce13.jpg",
"fileExt": "png",
"width": 1024,
"height": 2042,
"rating": "g",
"originalTags": {
"artist": [],
"copyright": [
"brown_dust_(series)",
"brown_dust_2",
"mato_seihei_no_slave"
],
"character": [
"yamashiro_ren"
],
"general": [
"1girl",
"anti-demon_corps_uniform",
"belt",
"black_hair",
"black_pantyhose",
"blunt_bangs",
"boots",
"breasts",
"choker",
"company_name",
"copyright_notice",
"full_body",
"hair_ornament",
"large_breasts",
"long_hair",
"looking_at_viewer",
"official_alternate_costume",
"pantyhose",
"purple_eyes",
"purple_hair",
"shoes",
"simple_background",
"solo",
"thighband_pantyhose",
"white_background",
"white_boots"
],
"meta": [
"highres",
"official_art"
]
}
}
]
}
}
},
"[\"generic-widget\",\"host_b46f1857-6b8b-473b-9aaa-40f3bf8fbf8f\",\"image\",\"comfy-image-combo\"]": {
"valueType": "string",
"payload": "Aaalice_example.jpg"
},
"[\"subgraph-widget\",\"host_68623cbe-89e1-4841-a842-bc7d619be8fd\",\"promoted:[\\\"986\\\",\\\"model_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "pixai-tagger-v0.9-timm"
},
"[\"subgraph-widget\",\"host_68623cbe-89e1-4841-a842-bc7d619be8fd\",\"promoted:[\\\"986\\\",\\\"character_threshold\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.8
},
"[\"subgraph-widget\",\"host_68623cbe-89e1-4841-a842-bc7d619be8fd\",\"promoted:[\\\"985\\\",\\\"vlm_service\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "硅基流动/zai-org/GLM-4.5V"
},
"[\"subgraph-widget\",\"host_68623cbe-89e1-4841-a842-bc7d619be8fd\",\"promoted:[\\\"985\\\",\\\"rule\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "像素级描述（by:阿丹）"
},
"[\"subgraph-widget\",\"host_68623cbe-89e1-4841-a842-bc7d619be8fd\",\"promoted:[\\\"985\\\",\\\"seed\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 1717233,
"control_after_generate": "fixed"
}
},
"[\"subgraph-widget\",\"host_68623cbe-89e1-4841-a842-bc7d619be8fd\",\"promoted:[\\\"986\\\",\\\"general_threshold\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.2
},
"[\"subgraph-widget\",\"host_68623cbe-89e1-4841-a842-bc7d619be8fd\",\"promoted:[\\\"987\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_68623cbe-89e1-4841-a842-bc7d619be8fd\",\"promoted:[\\\"986\\\",\\\"exclude_tags\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "watermark, sample watermark, too many watermarks, text, signature, logo, username, artist name, web address, copyright, stamp, sample, trademark, url, patreon logo, twitter username, weibo watermark, character name, title, barcode, UI, lower text, bad quality, low quality, blurry"
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1456\\\",\\\"embed_workflow\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1453\\\",\\\"sound\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1453\\\",\\\"desktop_notification\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1453\\\",\\\"volume\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.47601886794847814
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1453\\\",\\\"message\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "局部重绘完毕喵~"
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1456\\\",\\\"enabled\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1456\\\",\\\"filename_prefix\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "%date:yyyy-MM-dd%/%seed%_局部重绘"
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1456\\\",\\\"save_with_metadata\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1455\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1466\\\",\\\"unet_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "flux-2-klein-9b-fp8_2.safetensors"
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1468\\\",\\\"clip_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "qwen3vl_8b_int8_convrot.safetensors"
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1465\\\",\\\"timeout_action\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "submit_all"
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1465\\\",\\\"timeout\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 300
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1290\\\",\\\"value\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1277\\\",\\\"context_from_mask_extend_factor\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1.2
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1483\\\",\\\"strength\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1483\\\",\\\"method\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "reinhard_lab_gpu"
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1546\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1543\\\",\\\"steps\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 8
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1543\\\",\\\"sampler_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "euler"
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1543\\\",\\\"denoise\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 0.4
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1480\\\",\\\"batch_size\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1543\\\",\\\"cfg\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1543\\\",\\\"scheduler\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "beta"
},
"[\"subgraph-widget\",\"host_e88faac8-bb94-495d-b0a4-3e2d7faf14e8\",\"promoted:[\\\"1559\\\",\\\"value\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"generic-widget\",\"host_2bbc3763-e108-4a02-b473-a95c1367658f\",\"aaalice_resolution_preset\",\"aaalice-resolution-preset\"]": {
"valueType": "resolution",
"payload": {
"version": 1,
"width": 1024,
"height": 1536,
"alignment": 8,
"canvasMax": 2048,
"presetId": "builtin:portrait-1024x1536"
}
},
"[\"generic-widget\",\"host_0ec76858-3d5f-416a-9f37-2fcf636053c8\",\"aaalice_prompt_selector\",\"aaalice-prompt-selector\"]": {
"valueType": "prompt-selector",
"payload": {
"version": 1,
"selections": [],
"separator": ", "
}
},
"[\"generic-widget\",\"host_5d91626c-638b-4290-b83e-a2f6f5f7ea6c\",\"aaalice_prompt_selector\",\"aaalice-prompt-selector\"]": {
"valueType": "prompt-selector",
"payload": {
"version": 1,
"selections": [],
"separator": ", "
}
},
"[\"generic-widget\",\"host_1c81204d-7e3d-48ab-a1f1-31b9e260864d\",\"aaalice_prompt_selector\",\"aaalice-prompt-selector\"]": {
"valueType": "prompt-selector",
"payload": {
"version": 1,
"selections": [],
"separator": ", "
}
},
"[\"subgraph-widget\",\"host_9b25233b-ba58-48f1-90e5-9151bb2af6a6\",\"promoted:[\\\"715\\\",\\\"vae_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "ema_vae_fp16.safetensors"
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1470\\\",\\\"vae_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "full_encoder_small_decoder.safetensors"
}
}
}
],
"baselinePresetId": "dashboard_preset_4859ff28-6ebb-4503-a90d-10451d41cfa3"
},
"aaaliceDiscordShare": {
"version": 1,
"promptSource": {
"graphId": "42e812b9-cc0f-48bf-b2ad-912f831a0e29",
"nodeId": "279",
"label": "最终正面提示词（不含Lora触发词）"
}
},
"aaaliceGroupNavigation": {
"version": 3,
"wheelShortcut": "Backquote",
"entries": [
{
"groupId": "15",
"label": "组控制",
"offset": {
"x": 0,
"y": 0
},
"zoom": 0.82
},
{
"groupId": "6",
"label": "基础设置",
"offset": {
"x": 0,
"y": 0
},
"zoom": 0.82
},
{
"groupId": "9",
"label": "提示词",
"offset": {
"x": 0,
"y": 0
},
"zoom": 0.82
},
{
"groupId": "10",
"label": "【勿动】提示词后处理",
"offset": {
"x": 0,
"y": 0
},
"zoom": 0.82
},
{
"groupId": "23",
"label": "底图预览",
"offset": {
"x": 0,
"y": -100
},
"zoom": 1.2
},
{
"groupId": "24",
"label": "底图（双采样）预览",
"offset": {
"x": 0,
"y": -100
},
"zoom": 1.2
},
{
"groupId": "25",
"label": "潜空间放大对比",
"offset": {
"x": 0,
"y": -100
},
"zoom": 1.2
},
{
"groupId": "33",
"label": "脸部细化对比",
"offset": {
"x": 0,
"y": -100
},
"zoom": 1.2
},
{
"groupId": "27",
"label": "SeedVR2放大对比",
"offset": {
"x": 0,
"y": -100
},
"zoom": 1.2
},
{
"groupId": "40",
"label": "VSR放大对比",
"offset": {
"x": 0,
"y": -100
},
"zoom": 1.2
},
{
"groupId": "4",
"label": "【📦可选】画廊",
"offset": {
"x": -150,
"y": 0
},
"zoom": 1
},
{
"groupId": "5",
"label": "【📦可选】图像反推",
"offset": {
"x": 0,
"y": 0
},
"zoom": 0.82
},
{
"groupId": "35",
"label": "【📦可选】局部重绘",
"offset": {
"x": 0,
"y": 0
},
"zoom": 0.82
}
]
},
"ds": {
"scale": 0.8612347873369836,
"offset": [
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},
"linearData": {
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],
[
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"clip_name"
],
[
"42e812b9-cc0f-48bf-b2ad-912f831a0e29:167:vae_name",
"vae_name"
],
[
"42e812b9-cc0f-48bf-b2ad-912f831a0e29:167:type",
"type"
],
[
"42e812b9-cc0f-48bf-b2ad-912f831a0e29:72:text",
"text"
],
[
"42e812b9-cc0f-48bf-b2ad-912f831a0e29:72:loras",
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],
[
"42e812b9-cc0f-48bf-b2ad-912f831a0e29:168:value",
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],
[
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],
[
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],
[
"42e812b9-cc0f-48bf-b2ad-912f831a0e29:691:sampler_name",
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[
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[
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[
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[
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"parameters": "@NJSW33T, , (cardboard box:-1.2), (paper bag:-1.0), (shipping carton:-1.0), a cinematic film still of an adult woman standing by a seaside railing on an overcast day, captured in a wide full-body shot from a distance, showing her entire figure from head to toe. she wears an open brown trench coat over a crisp white shirt and a short fitted gray pencil skirt that ends high on her thighs. long blonde hair falls loosely past her shoulders. dark sunglasses cover her eyes, and a thin cigarette rests between her lips. she is leaning back against the metal railing with her upper back, her body facing the camera but her head tilted downward, gaze directed at the ground. her left hand rests naturally on the top rail of the metal railing behind her, fingers relaxed and draping over the edge, while her right arm hangs naturally straight down at her side, gripping the top handle of a rigid black leather briefcase that rests against her leg, the case is rectangular with a hard structured shell, polished metal clasps, and a clean unmarked surface. she stands in a relaxed triangular stance, one foot planted forward and one foot back, weight settled on her heels.\n\nbehind her, the railing frames a vast, grey sea stretching to a low horizon beneath a heavy, overcast sky. the background is open and empty, with no other figures or clutter. soft diffused daylight from above with no direct sun, casting gentle shadows across the folds of her coat and the angles of her face. cool desaturated tones of grey water and pale sky, contrasted by the warm brown of her coat and the gold of her hair. deep focus so both the woman and the sea remain clearly readable, fine film grain, \n<lora:kzmynon-krea2-v2:0.5> <lora:Niji_Sweet_Spot_Krea2_v2A:0.8> <lora:krea2_koukouya_sytle_c1-st3000:0.9>\nNegative prompt: worst quality, low quality, score_1, score_2, score_3, blurry, jpeg artifacts, sepia\nSteps: 12, Sampler: Euler a Normal, CFG scale: 1.0, Seed: 974845072890353, Size: 1024x768, Clip skip: 1, Model hash: 78BBF8F416, Model: krea2_turbo_bf16, Hashes: {\"model\":\"78BBF8F416\",\"LORA:kzmynon-krea2-v2\":\"09AE9C8D1D\",\"LORA:Niji_Sweet_Spot_Krea2_v2A\":\"1AA1E5A2BD\",\"LORA:krea2_koukouya_sytle_c1-st3000\":\"8CF2068C65\"}, Version: ComfyUI, Civitai resources: [{\"air\":\"urn:air:krea2:checkpoint:civitai:2726029@3064584\",\"versionName\":\"krea2_turbo_bf16\"},{\"weight\":0.5,\"air\":\"urn:air:krea2:lora:civitai:2878242@3377920\",\"versionName\":\"krea2-v2\"},{\"weight\":0.8,\"air\":\"urn:air:krea2:lora:civitai:2554999@3210573\",\"versionName\":\"Krea2_v2_A\"},{\"weight\":0.9,\"air\":\"urn:air:krea2:lora:civitai:2844656@3211621\",\"versionName\":\"v1.0\"}]"
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