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～ ✨"
],
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"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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"text": "# 🎨 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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"name": "value"
},
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],
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{
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"links": [
2274
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}
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"mode": 0,
"inputs": [
{
"localized_name": "图像",
"name": "image",
"type": "IMAGE",
"link": 2471
}
],
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{
"localized_name": "宽度",
"name": "width",
"type": "INT",
"links": [
2322,
2325
]
},
{
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"links": [
2323,
2326
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},
{
"localized_name": "批处理大小",
"name": "batch_size",
"type": "INT",
"links": []
}
],
"properties": {
"cnr_id": "comfy-core",
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"Node name for S&R": "GetImageSize",
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"tabWidth": 65,
"tabXOffset": 10,
"hasSecondTab": false,
"secondTabText": "Send Back",
"secondTabOffset": 80,
"secondTabWidth": 65,
"ue_properties": {
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},
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},
{
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"pos": [
-7910,
660
],
"size": [
350,
160
],
"flags": {},
"order": 0,
"mode": 0,
"inputs": [],
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{
"localized_name": "字符串",
"name": "STRING",
"type": "STRING",
"links": [
2307
]
}
],
"properties": {
"cnr_id": "comfy-core",
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"aaaliceControlHostId": "host_3b497b46-260c-4b4b-b43c-a17b9dd1308e"
},
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"# 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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-11060,
440
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270,
60
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{
"localized_name": "值",
"name": "value",
"type": "BOOLEAN",
"widget": {
"name": "value"
},
"link": 2047
}
],
"outputs": [
{
"localized_name": "布尔",
"name": "BOOLEAN",
"type": "BOOLEAN",
"links": [
1937,
1964,
2357
]
}
],
"title": "是否使用Krita预处理",
"properties": {
"cnr_id": "comfy-core",
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"Node name for S&R": "PrimitiveBoolean",
"aaaliceControlHostId": "host_6f302410-c0ff-4f74-84f4-5883e6509cf1"
},
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true
],
"widgets_values_named": {
"value": true
},
"color": "#2a363b",
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},
{
"id": 1456,
"type": "ConditionalSaveImage",
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-7540,
320
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360,
640
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"order": 12,
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"inputs": [
{
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{
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"type": "METADATA",
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{
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},
{
"localized_name": "文件名前缀",
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{
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{
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{
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"type": "IMAGE",
"links": [
2279
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}
],
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true,
true,
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{
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{
"localized_name": "为真时",
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},
{
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"widget": {
"name": "switch"
},
"link": 2357
}
],
"outputs": [
{
"localized_name": "输出",
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"links": [
2361
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}
],
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{
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320
],
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230,
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"flags": {},
"order": 4,
"mode": 0,
"inputs": [
{
"localized_name": "stitcher",
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"link": 1934
},
{
"localized_name": "inpainted_image",
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"type": "IMAGE",
"link": 2336
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],
"outputs": [
{
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"links": [
2280
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}
],
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{
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320,
130
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"flags": {},
"order": 26,
"mode": 0,
"inputs": [
{
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{
"localized_name": "image_ref",
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},
{
"localized_name": "method",
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"type": "COMBO",
"widget": {
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{
"localized_name": "strength",
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"type": "FLOAT",
"widget": {
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],
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{
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"links": [
2335
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}
],
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"widgets_values": [
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1,
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"widgets_values_named": {
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"multithread": true
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},
{
"id": 1468,
"type": "CLIPLoader",
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"size": [
370,
150
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"order": 16,
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],
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{
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2447
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],
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{
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{
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{
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{
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270,
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],
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{
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],
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2413
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}
],
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},
{
"id": 1525,
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},
{
"localized_name": "guider",
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},
{
"localized_name": "sampler",
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},
{
"localized_name": "sigmas",
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"link": 2413
},
{
"localized_name": "latent_image",
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],
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2456
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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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},
{
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],
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],
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],
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"[\"subgraph-widget\",\"host_4ae9f10c-754c-4d6b-8edf-52c00df63fc7\",\"promoted:[\\\"1034\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_aff77634-1b75-4273-a0a6-e21ead6d242f\",\"promoted:[\\\"1222\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_e88faac8-bb94-495d-b0a4-3e2d7faf14e8\",\"promoted:[\\\"1554\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"generic-widget\",\"host_2da40a40-e509-4cce-abbd-bf1a6d194836\",\"loras\",\"lora-manager-list\"]": {
"valueType": "lora-list",
"payload": []
},
"[\"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",
"payload": "扩写-通用"
},
"[\"subgraph-widget\",\"host_47c97a7b-7904-48c0-a052-2d63cf495323\",\"promoted:[\\\"164\\\",\\\"llm_service\\\",null]\",\"comfy-native-widget\"]": {
"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"
},
"[\"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": "er_sde"
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"scheduler\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "simple"
},
"[\"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": 1081753275824763,
"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": true
},
"[\"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": false
},
"[\"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": 12,
"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": "simple"
},
"[\"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": "er_sde"
},
"[\"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": false
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1245\\\",\\\"noise_seed\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 954580310700086,
"control_after_generate": "randomize"
}
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"802\\\",\\\"value\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 6,
"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": 6
},
"[\"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": 964939506046032,
"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": 6
},
"[\"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": 795575207908045,
"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:[\\\"715\\\",\\\"vae_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "seedvr2_ema_vae_fp16.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
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"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1418\\\",\\\"resize_type.scale\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 2
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"[\"subgraph-widget\",\"host_dc761a9a-9111-4b00-b994-2d8b50383778\",\"promoted:[\\\"1446\\\",\\\"enabled\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
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"[\"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
},
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"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"
]
}
}
]
}
}
},
"[\"generic-widget\",\"host_b46f1857-6b8b-473b-9aaa-40f3bf8fbf8f\",\"image\",\"comfy-image-combo\"]": {
"valueType": "string",
"payload": "HSWZovHagAEb3tL.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": "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"
}
},
"[\"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
},
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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
},
"[\"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": "qwen_3_8b_fp8mixed.safetensors"
},
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"valueType": "string",
"payload": "full_encoder_small_decoder.safetensors"
},
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"valueType": "string",
"payload": "submit_all"
},
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"valueType": "number",
"payload": 300
},
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"valueType": "boolean",
"payload": false
},
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"valueType": "number",
"payload": 1.2
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1483\\\",\\\"strength\\\",null]\",\"comfy-native-widget\"]": {
"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
},
"[\"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
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1480\\\",\\\"batch_size\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 1
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"valueType": "number",
"payload": 1
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"valueType": "string",
"payload": "beta"
},
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"valueType": "boolean",
"payload": false
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"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": ", "
}
},
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"valueType": "prompt-selector",
"payload": {
"version": 1,
"selections": [],
"separator": ", "
}
}
}
},
{
"id": "dashboard_preset_01e68ac7-b2b0-482b-8dec-6fb85cd7378a",
"name": "默认-Anima-2.9B-Silvermoon",
"dashboard": {
"version": 4,
"pages": [
{
"id": "page_b5a57e0d-f4c3-4f5f-975c-c9b665d2d518",
"name": "🎯组管理",
"gridColumns": 12,
"tone": null,
"items": [
{
"id": "item_010e9a67-1f5e-47be-ab89-4341b8eb277a",
"kind": "control",
"binding": {
"provider": "quick-group-manager",
"hostId": "host_3892ff51-89bf-4641-b0c1-80d431b3c41c",
"controlId": "manager",
"valueType": "quick-group-manager"
},
"label": "⚡ 快速组管理器",
"groupId": null,
"tone": "sky",
"labelSource": "⚡ 快速组管理器",
"layout": {
"row": 0,
"column": 0,
"columnSpan": 12,
"rowSpan": 52
}
},
{
"id": "item_d19ae00f-ff17-4d1f-bea7-b3924e4a4134",
"kind": "control",
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"[\"subgraph-widget\",\"host_e79a5102-004f-408a-9991-c39d2d03e32a\",\"promoted:[\\\"1002\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_49d7435c-e923-40f9-8b4b-823c60168c7a\",\"promoted:[\\\"1018\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_4ae9f10c-754c-4d6b-8edf-52c00df63fc7\",\"promoted:[\\\"1034\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_aff77634-1b75-4273-a0a6-e21ead6d242f\",\"promoted:[\\\"1222\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_e88faac8-bb94-495d-b0a4-3e2d7faf14e8\",\"promoted:[\\\"1554\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"generic-widget\",\"host_2da40a40-e509-4cce-abbd-bf1a6d194836\",\"loras\",\"lora-manager-list\"]": {
"valueType": "lora-list",
"payload": []
},
"[\"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",
"payload": "扩写-通用"
},
"[\"subgraph-widget\",\"host_47c97a7b-7904-48c0-a052-2d63cf495323\",\"promoted:[\\\"164\\\",\\\"llm_service\\\",null]\",\"comfy-native-widget\"]": {
"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"
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"steps\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 28
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"cfg\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 4
},
"[\"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": 404572692939880,
"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": true
},
"[\"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": false
},
"[\"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": 28,
"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": "normal"
},
"[\"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": 4
},
"[\"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_ancestral"
},
"[\"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": 4
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1245\\\",\\\"sampler_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "euler_ancestral"
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1245\\\",\\\"scheduler\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "normal"
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"538\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": false
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"1245\\\",\\\"noise_seed\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 75222765497786,
"control_after_generate": "randomize"
}
},
"[\"subgraph-widget\",\"host_c959b807-ee66-41bc-a041-74a85547cc20\",\"promoted:[\\\"802\\\",\\\"value\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 14,
"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": 14
},
"[\"subgraph-widget\",\"host_5ec9065d-be24-4b4b-b4fa-7417664bf535\",\"cfg\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 4
},
"[\"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": 142351079931325,
"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": 14
},
"[\"subgraph-widget\",\"host_6b308764-76c5-4359-b869-98c7c62b7758\",\"promoted:[\\\"1215\\\",\\\"cfg_scale\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 4
},
"[\"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": 590657087978397,
"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": "search",
"period": ""
},
"navigation": {
"page": 2
},
"dashboard": {
"searchOpen": false
},
"prompt": {
"categories": [
"copyright",
"character",
"general"
],
"replaceUnderscores": false,
"escapeParentheses": false
},
"selections": [
{
"source": "danbooru",
"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": [
"1girl",
"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"
]
}
}
]
}
}
},
"[\"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": "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"
}
},
"[\"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:[\\\"1468\\\",\\\"clip_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "qwen_3_8b_fp8mixed.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"
},
"[\"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": 28
},
"[\"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": 4
},
"[\"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:[\\\"1466\\\",\\\"unet_name\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "flux-2-klein-9b-fp8.safetensors"
}
}
},
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"[\"subgraph-widget\",\"host_8a5476c3-8df5-40a9-a604-f95e9d188790\",\"promoted:[\\\"1573\\\",\\\"image\\\",null]\",\"comfy-image-combo\"]": {
"valueType": "string",
"payload": "Aaalice_example.jpg"
},
"[\"generic-widget\",\"host_ecb16b92-94db-4682-826f-9af53c995c31\",\"value\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": {
"value": 1,
"control_after_generate": "fixed"
}
},
"[\"generic-widget\",\"host_1e8585fc-d8a6-44ed-a336-179dda56eba8\",\"loras\",\"lora-manager-list\"]": {
"valueType": "lora-list",
"payload": [
{
"name": "画风类/velnari_fantasy_impressions_krea2",
"strength": 0.57,
"active": false,
"expanded": false,
"clipStrength": 0.57,
"locked": false
},
{
"name": "画风类/k2-void_0_c1-st4000",
"strength": 0.39,
"active": false,
"expanded": false,
"clipStrength": 0.39,
"locked": false
},
{
"name": "画风类/starshadowmagician_style_krea2_uma_v1_krea2_3335939_epoch_10",
"strength": 0.6,
"active": false,
"expanded": false,
"clipStrength": 0.6,
"locked": false
},
{
"name": "功能类/krea2filterbypass3",
"strength": 1,
"active": false,
"expanded": false,
"clipStrength": 1,
"locked": false
},
{
"name": "画风类/m87_lora_v1",
"strength": 0.5,
"active": false,
"expanded": false,
"clipStrength": 0.5,
"locked": false
},
{
"name": "画风类/Krea_2_in_real_krea2_3320272_epoch_20",
"strength": 1,
"active": false,
"expanded": false,
"clipStrength": 1,
"locked": false
},
{
"name": "kzmynon-krea2-v2",
"strength": 0.5,
"active": false,
"expanded": false,
"clipStrength": 0.5,
"locked": false
},
{
"name": "Niji_Sweet_Spot_Krea2_v2A",
"strength": "0.80",
"active": true,
"expanded": false,
"clipStrength": "0.80",
"locked": false
},
{
"name": "krea2_koukouya_sytle_c1-st3000",
"strength": "0.90",
"active": true,
"expanded": false,
"clipStrength": "0.90",
"locked": false
},
{
"name": "Krea2_TextFusion_Refusal_Reduction",
"strength": 1,
"active": false,
"expanded": false,
"clipStrength": 1,
"locked": false
},
{
"name": "ErenARIK_v1",
"strength": 1,
"active": false,
"expanded": false,
"clipStrength": 1,
"locked": false
},
{
"name": "grainscape_krea2",
"strength": 1,
"active": false,
"expanded": false,
"clipStrength": 1,
"locked": false
},
{
"name": "vhs_krea2",
"strength": 1,
"active": false,
"expanded": false,
"clipStrength": 1,
"locked": false
},
{
"name": "nicegirls_krea2",
"strength": 1,
"active": false,
"expanded": false,
"clipStrength": 1,
"locked": false
},
{
"name": "Krea_2_in_real_krea2_3320272_epoch_20",
"strength": 1,
"active": false,
"expanded": false,
"clipStrength": 1,
"locked": false
}
]
},
"[\"subgraph-widget\",\"host_59e2aae9-2094-4e5c-9026-169f9a7a914d\",\"promoted:[\\\"293\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_e79a5102-004f-408a-9991-c39d2d03e32a\",\"promoted:[\\\"1002\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_49d7435c-e923-40f9-8b4b-823c60168c7a\",\"promoted:[\\\"1018\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_4ae9f10c-754c-4d6b-8edf-52c00df63fc7\",\"promoted:[\\\"1034\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_aff77634-1b75-4273-a0a6-e21ead6d242f\",\"promoted:[\\\"1222\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"subgraph-widget\",\"host_e88faac8-bb94-495d-b0a4-3e2d7faf14e8\",\"promoted:[\\\"1554\\\",\\\"switch\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "boolean",
"payload": true
},
"[\"generic-widget\",\"host_2da40a40-e509-4cce-abbd-bf1a6d194836\",\"loras\",\"lora-manager-list\"]": {
"valueType": "lora-list",
"payload": []
},
"[\"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",
"payload": "扩写-通用"
},
"[\"subgraph-widget\",\"host_47c97a7b-7904-48c0-a052-2d63cf495323\",\"promoted:[\\\"164\\\",\\\"llm_service\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "硅基流动/deepseek-ai/DeepSeek-V3.2"
},
"[\"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": "硅基流动/deepseek-ai/DeepSeek-V3.2"
},
"[\"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"
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"steps\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "number",
"payload": 8
},
"[\"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"
},
"[\"subgraph-widget\",\"host_900694cd-5348-4e82-b0da-ee5ea4a6e403\",\"promoted:[\\\"54\\\",\\\"scheduler\\\",null]\",\"comfy-native-widget\"]": {
"valueType": "string",
"payload": "simple"
},
"[\"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": 615593805201689,
"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": 924872977590198,
"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": 558450295180928,
"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": 23402407798739,
"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"
},
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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": 8
},
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},
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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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"separator": ", "
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},
"[\"generic-widget\",\"host_1c81204d-7e3d-48ab-a1f1-31b9e260864d\",\"aaalice_prompt_selector\",\"aaalice-prompt-selector\"]": {
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}
},
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"valueType": "string",
"payload": "ema_vae_fp16.safetensors"
},
"[\"subgraph-widget\",\"host_102be07e-193e-40ce-9be6-7967cdc50dd0\",\"promoted:[\\\"1470\\\",\\\"vae_name\\\",null]\",\"comfy-native-widget\"]": {
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}
}
],
"baselinePresetId": "dashboard_preset_4859ff28-6ebb-4503-a90d-10451d41cfa3"
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"promptSource": {
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"nodeId": "279",
"label": "最终正面提示词（不含Lora触发词）"
}
},
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"wheelShortcut": "Backquote",
"entries": [
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"label": "组控制",
"offset": {
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"y": 0
},
"zoom": 0.82
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{
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"label": "基础设置",
"offset": {
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"label": "提示词",
"offset": {
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{
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"offset": {
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},
{
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"label": "底图预览",
"offset": {
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},
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},
{
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{
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},
{
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"label": "脸部细化对比",
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{
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{
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"offset": {
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{
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"label": "【📦可选】画廊",
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"y": 0
},
"zoom": 1
},
{
"groupId": "5",
"label": "【📦可选】图像反推",
"offset": {
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},
{
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"label": "【📦可选】局部重绘",
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}
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[
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}
