Upload gf using SD-Hub extension

.gitattributes

@@ -34,3 +34,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 fc/sd_webui_masactrl_orig/resources/img/xyz_grid-0010-1508457017.png filter=lfs diff=lfs merge=lfs -text
+gf/sd-webui-rich-text/assets/color.png filter=lfs diff=lfs merge=lfs -text
+gf/sd-webui-rich-text/assets/font.png filter=lfs diff=lfs merge=lfs -text
+gf/sd-webui-rich-text/assets/footnote.png filter=lfs diff=lfs merge=lfs -text
+gf/sd-webui-rich-text/assets/size.png filter=lfs diff=lfs merge=lfs -text

gf/LightDiffusionFlow/.gitignore

@@ -0,0 +1,3 @@
+.idea
+__pycache__/
+dev

gf/LightDiffusionFlow/CONTRIBUTING.md

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+### Contributing
+
+欢迎参与 LightDiffusionFlow 的贡献，你可以给我们提出意见、建议，报告 bug，或者贡献代码。在参与贡献之前，请阅读以下指引。
+
+#### 咨询问题
+
+简单的咨询，如询问如何使用或其他StableDiffision相关的技术问题，请在官方微信群中询问，效率更高。
+
+#### 关于 issue
+
+如果你对 LightDiffusionFlow 的现状有意见、建议或者发现了 bug，欢迎通过 issue 给我们提出。提 issue 之前，请阅读以下指引。
+
+- 搜索以往的 issue ，看是否已经提过，避免重复提出；
+- 请确认你遇到的问题，是否在最新版本已被修复；
+- 如果是报告 bug，请尽量提供可以复现的条件：
+    - 操作系统、浏览器版本
+    - Stable Diffusion WebUI 版本以及相关插件的版本（如果有的话）
+    - LightDiffusionFlow 插件版本
+    - Bug 表现
+    - 操作步骤
+    - 是否必现
+    - 最好可以提供截图
+- 如果你的问题已经得到解决，请关闭你的 issue。
+
+#### 贡献者名单
+
+非常感谢以下几位对LightDiffusionFlow做出的贡献：
+
+- 非常感谢 [Hali](https://github.com/ThisHaliHali) 为本项目提供的灵感、建议以及在开发期间的各种支持！
+
+- 我们的项目是以 [Ilian Iliev](https://github.com/ilian6806) 的 [stable-diffusion-webui-state](https://github.com/ilian6806/stable-diffusion-webui-state) 项目为基础进行的二次开发，这为我们提供了很大的帮助，感谢 Ilian Iliev ！

gf/LightDiffusionFlow/ChangeLog.md

@@ -0,0 +1,126 @@
+## 2.1.4
+
+### Features:
+ * 增加本地保存Flow配置功能，可直接下拉列表选择已保存的Flow文件。（导入或使用新flow之前，建议先刷新页面，目前插件暂时没有重置参数的功能）
+ * 增加记录额外LoRA模型数据，以便导入时从Civitai搜索缺失的lora模型。
+ * 模型模糊匹配优化，增加匹配子文件夹下的模型。
+ * 设置页面增加保存flow的默认路径选项，以及相同作用的命令行选项"--local-flows-path"。
+
+### Bug Fixes:
+ * 修复了部分已知的参数设置失败的问题，如ControlNet在Canny模式下的"Canny Low/Hight Threshold"等参数。
+
+
+## 2.1.3
+
+### Features:
+ * 缺失LoRA模型提示。
+ * 插件增加Core和ALL两种运行模式，Core模式仅支持WebUI的基本参数+ControlNet参数。All模式则会尽可能多的支持页面上的参数，但是缺点是有概率导致UI卡住，无限转圈。
+
+### Bug Fixes:
+ * 增加了错误参数纠正步骤，处理Controlnet tab保存序号错误的问题。
+ * 修复了一些已知的问题。
+ * 修复了一些img2img模式丢失的参数。
+
+
+## 2.1.2
+
+### Features:
+ * UI组件增加elem_id。
+ * flow文件导出时，支持自定义名称。
+ * ControlNet模型支持模糊匹配。
+ * 如本地没有ControlNet模型，会提供下载链接。
+ * 缺失插件提示。
+ * 插件增加中英文切换。
+
+### Bug Fixes:
+ * 图片组件保存功能优化，支持所有带elem_id的图片组件。  
+ 因为gradio组件bug影响，目前暂时不支持不带elem_id的组件保存功能。  
+ 目前新版本似乎已经修复，但秋叶启动器的gradio版本似乎还是旧版？待跟进。
+ issue链接: https://github.com/gradio-app/gradio/issues/5548
+ * refiner参数保存bug修复。
+ * 插件含tab的组件保存编号错误bug修复。
+ * 插件导入提示优化。
+ * 参数保存逻辑优化。
+ * 之前版本会保存多余参数，当前版本已修改，但注意缺失插件的提示，不一定是真的需要。
+
+## 2.1.1
+
+### Bug Fixes:
+ * sd webui v1.6.0 之前的版本兼容问题解决。
+
+## 2.1.0
+
+### Bug Fixes:
+ * py实现与js一样的创建组件编号，优化导入逻辑，部分dropdown组件改由py处理，降低UI面板无限转圈概率。
+ * 修复了一些已知的问题。
+
+### Features:
+ * UI面板挪到右侧，图片信息栏下方。
+
+## 2.0.4
+
+### Bug Fixes:
+ * 修复了部分插件tab面板以外的参数保存问题。
+ * 支持解析jpeg图片的png info。
+ * 修复了一些已知的问题。
+
+## 2.0.3
+
+### Bug Fixes:
+ * 修复了对比模型选项出现的bug。
+ * 修复了一些已知的问题。
+ * 确定了插件名称和文件后缀。
+
+### Features:
+ * 导入flow文件时，会自动在Civitai搜索相关模型，如果找到对应模型则提供下载链接。
+
+## 2.0.2
+
+### Bug Fixes:
+ * 修复了ControlNet max_models_num设置导致的错误。
+ * 修复了一些已知的问题。
+
+### Features:
+ * 支持到最新的WebUI v1.6.
+ * 设置模型时，支持单独匹配Hash或者文件名，满足其中一项就能设置成功。
+
+## 2.0.1
+
+### Bug Fixes:
+ * 修复了一些已知的问题。
+
+### Features:
+ * 增加HTTP调用接口，支持设置预加载文件。
+
+## 2.0.0
+
+### Bug Fixes:
+ * 现在可以更好的兼容汉化文件。
+
+### Features:
+ * 重写第三方插件支持代码，通用支持所有插件参数（不包括图片）。
+
+## 1.2.2
+
+### Features:
+ * 插件提示文字统一使用英文，插件说明文档调整并增加中文说明文档。
+ 
+## 1.2.1
+
+### Bug Fixes:
+ * png_info解析转换时，部分key值设置错误问题修复。
+
+## 1.2.0
+
+### Features:
+ * 添加支持解析图片文件，读取png info并还原到界面上
+
+### Bug Fixes:
+ * 解决了部分汉化文件读取错误的问题，现在可以更好的兼容汉化文件。
+
+## 1.1.3
+
+### Bug Fixes:
+ * 因“使用下拉菜单取代单选列表选项”导致部分选项设置不上的问题解决。
+ * 解决了一些venus平台和秋叶启动器上的兼容问题，秋叶启动器开启前需要关闭“启动云端页面汉化”选项。
+ * 页面已经设置了图片的选项再覆盖设置其他图片没有触发保存问题修复。

gf/LightDiffusionFlow/LICENSE

@@ -0,0 +1,237 @@
+Tencent is pleased to support the open source community by making LightDiffusionFlow (extension for Stable Diffusion)  available. 
+
+Copyright (C) 2023 THL A29 Limited, a Tencent company.  All rights reserved. The below software in this distribution may have been modified by THL A29 Limited ("Tencent Modifications"). All Tencent Modifications are Copyright (C) THL A29 Limited.
+
+LightDiffusionFlow (extension for Stable Diffusion)  is licensed under the GNU AFFERO GENERAL PUBLIC LICENSE v3 except for the third-party components listed below.
+
+
+Terms of the GNU AFFERO GENERAL PUBLIC LICENSE v3:
+--------------------------------------------------------------------
+GNU AFFERO GENERAL PUBLIC LICENSE
+Version 3, 19 November 2007
+
+Copyright © 2007 Free Software Foundation, Inc. <https://fsf.org/>
+Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed.
+
+Preamble
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+You may not impose any further restrictions on the exercise of the rights granted or affirmed under this License. For example, you may not impose a license fee, royalty, or other charge for exercise of rights granted under this License, and you may not initiate litigation (including a cross-claim or counterclaim in a lawsuit) alleging that any patent claim is infringed by making, using, selling, offering for sale, or importing the Program or any portion of it.
+
+11. Patents.
+A "contributor" is a copyright holder who authorizes use under this License of the Program or a work on which the Program is based. The work thus licensed is called the contributor's "contributor version".
+
+A contributor's "essential patent claims" are all patent claims owned or controlled by the contributor, whether already acquired or hereafter acquired, that would be infringed by some manner, permitted by this License, of making, using, or selling its contributor version, but do not include claims that would be infringed only as a consequence of further modification of the contributor version. For purposes of this definition, "control" includes the right to grant patent sublicenses in a manner consistent with the requirements of this License.
+
+Each contributor grants you a non-exclusive, worldwide, royalty-free patent license under the contributor's essential patent claims, to make, use, sell, offer for sale, import and otherwise run, modify and propagate the contents of its contributor version.
+
+In the following three paragraphs, a "patent license" is any express agreement or commitment, however denominated, not to enforce a patent (such as an express permission to practice a patent or covenant not to sue for patent infringement). To "grant" such a patent license to a party means to make such an agreement or commitment not to enforce a patent against the party.
+
+If you convey a covered work, knowingly relying on a patent license, and the Corresponding Source of the work is not available for anyone to copy, free of charge and under the terms of this License, through a publicly available network server or other readily accessible means, then you must either (1) cause the Corresponding Source to be so available, or (2) arrange to deprive yourself of the benefit of the patent license for this particular work, or (3) arrange, in a manner consistent with the requirements of this License, to extend the patent license to downstream recipients. "Knowingly relying" means you have actual knowledge that, but for the patent license, your conveying the covered work in a country, or your recipient's use of the covered work in a country, would infringe one or more identifiable patents in that country that you have reason to believe are valid.
+
+If, pursuant to or in connection with a single transaction or arrangement, you convey, or propagate by procuring conveyance of, a covered work, and grant a patent license to some of the parties receiving the covered work authorizing them to use, propagate, modify or convey a specific copy of the covered work, then the patent license you grant is automatically extended to all recipients of the covered work and works based on it.
+
+A patent license is "discriminatory" if it does not include within the scope of its coverage, prohibits the exercise of, or is conditioned on the non-exercise of one or more of the rights that are specifically granted under this License. You may not convey a covered work if you are a party to an arrangement with a third party that is in the business of distributing software, under which you make payment to the third party based on the extent of your activity of conveying the work, and under which the third party grants, to any of the parties who would receive the covered work from you, a discriminatory patent license (a) in connection with copies of the covered work conveyed by you (or copies made from those copies), or (b) primarily for and in connection with specific products or compilations that contain the covered work, unless you entered into that arrangement, or that patent license was granted, prior to 28 March 2007.
+
+Nothing in this License shall be construed as excluding or limiting any implied license or other defenses to infringement that may otherwise be available to you under applicable patent law.
+
+12. No Surrender of Others' Freedom.
+If conditions are imposed on you (whether by court order, agreement or otherwise) that contradict the conditions of this License, they do not excuse you from the conditions of this License. If you cannot convey a covered work so as to satisfy simultaneously your obligations under this License and any other pertinent obligations, then as a consequence you may not convey it at all. For example, if you agree to terms that obligate you to collect a royalty for further conveying from those to whom you convey the Program, the only way you could satisfy both those terms and this License would be to refrain entirely from conveying the Program.
+
+13. Remote Network Interaction; Use with the GNU General Public License.
+Notwithstanding any other provision of this License, if you modify the Program, your modified version must prominently offer all users interacting with it remotely through a computer network (if your version supports such interaction) an opportunity to receive the Corresponding Source of your version by providing access to the Corresponding Source from a network server at no charge, through some standard or customary means of facilitating copying of software. This Corresponding Source shall include the Corresponding Source for any work covered by version 3 of the GNU General Public License that is incorporated pursuant to the following paragraph.
+
+Notwithstanding any other provision of this License, you have permission to link or combine any covered work with a work licensed under version 3 of the GNU General Public License into a single combined work, and to convey the resulting work. The terms of this License will continue to apply to the part which is the covered work, but the work with which it is combined will remain governed by version 3 of the GNU General Public License.
+
+14. Revised Versions of this License.
+The Free Software Foundation may publish revised and/or new versions of the GNU Affero General Public License from time to time. Such new versions will be similar in spirit to the present version, but may differ in detail to address new problems or concerns.
+
+Each version is given a distinguishing version number. If the Program specifies that a certain numbered version of the GNU Affero General Public License "or any later version" applies to it, you have the option of following the terms and conditions either of that numbered version or of any later version published by the Free Software Foundation. If the Program does not specify a version number of the GNU Affero General Public License, you may choose any version ever published by the Free Software Foundation.
+
+If the Program specifies that a proxy can decide which future versions of the GNU Affero General Public License can be used, that proxy's public statement of acceptance of a version permanently authorizes you to choose that version for the Program.
+
+Later license versions may give you additional or different permissions. However, no additional obligations are imposed on any author or copyright holder as a result of your choosing to follow a later version.
+
+15. Disclaimer of Warranty.
+THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+16. Limitation of Liability.
+IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
+
+17. Interpretation of Sections 15 and 16.
+If the disclaimer of warranty and limitation of liability provided above cannot be given local legal effect according to their terms, reviewing courts shall apply local law that most closely approximates an absolute waiver of all civil liability in connection with the Program, unless a warranty or assumption of liability accompanies a copy of the Program in return for a fee.
+
+END OF TERMS AND CONDITIONS
+
+How to Apply These Terms to Your New Programs
+If you develop a new program, and you want it to be of the greatest possible use to the public, the best way to achieve this is to make it free software which everyone can redistribute and change under these terms.
+
+To do so, attach the following notices to the program. It is safest to attach them to the start of each source file to most effectively state the exclusion of warranty; and each file should have at least the "copyright" line and a pointer to where the full notice is found.
+
+    <one line to give the program's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU Affero General Public License as
+    published by the Free Software Foundation, either version 3 of the
+    License, or (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU Affero General Public License for more details.
+
+    You should have received a copy of the GNU Affero General Public License
+    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+Also add information on how to contact you by electronic and paper mail.
+
+If your software can interact with users remotely through a computer network, you should also make sure that it provides a way for users to get its source. For example, if your program is a web application, its interface could display a "Source" link that leads users to an archive of the code. There are many ways you could offer source, and different solutions will be better for different programs; see section 13 for the specific requirements.
+
+You should also get your employer (if you work as a programmer) or school, if any, to sign a "copyright disclaimer" for the program, if necessary. For more information on this, and how to apply and follow the GNU AGPL, see <https://www.gnu.org/licenses/>.
+
+
+
+Other dependencies and licenses:
+
+
+Open Source Software Licensed under the MIT License:
+The below software in this distribution may have been modified by THL A29 Limited ("Tencent Modifications"). All Tencent Modifications are Copyright (C) 2023 THL A29 Limited.
+--------------------------------------------------------------------
+1. stable-diffusion-webui-state
+Copyright (c) 2023 Ilian Iliev
+
+
+Terms of the MIT License:
+--------------------------------------------------------------------
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

gf/LightDiffusionFlow/LICENSES/Licenses.md

@@ -0,0 +1,24 @@
+
+## [stable-diffusion-webui-state](https://github.com/ilian6806/stable-diffusion-webui-state)
+
+MIT License
+
+Copyright (c) 2023 Ilian Iliev
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

gf/LightDiffusionFlow/README.md

@@ -0,0 +1,63 @@
+<p float="left">
+    <img alt="" src="https://img.shields.io/badge/JavaScript-323330?style=for-the-badge&logo=javascript&logoColor=F7DF1E" />
+    <img alt="" src="https://img.shields.io/badge/Python-FFD43B?style=for-the-badge&logo=python&logoColor=blue" />
+</p>
+
+# sd-webui-lightdiffusionflow
+
+[**English**](./README.md) | [**中文**](./README_CN.md)
+
+This extension is developed for AUTOMATIC1111's [Stable Diffusion web UI](https://github.com/AUTOMATIC1111/stable-diffusion-webui) that provides import/export options for parameters.  
+"Stable Diffusion Web UI" hereafter referred to as "SD Web UI"  
+* [**Plugin demonstration and other instructions**](https://fvkij7wuqx9.feishu.cn/docx/HgZndihraotmmzxFni7cFZISnvb)  
+* [**LightFlow workflow community**](https://www.lightflow.ai/)  
+* [**Discord**](https://discord.gg/CaD4mchHxW)  
+* [**Twitter: @LightFlow_AI**](https://twitter.com/LightFlow_AI)  
+
+
+### Capabilities
+
+* Export/Import web UI parameters with a single file (images, inputs, sliders, checkboxes etc.) .
+* Support parsing png info from image and restoring parameters back to the web UI.
+* Supported extensions:
+    - In theory, it can support any plugin. (Except for certain plugin images, as they require the corresponding elem_id to be provided.)
+
+![lightflow_en](https://github.com/Tencent/LightDiffusionFlow/assets/20501414/e03cc556-9962-41a3-8738-606ee9e38a04)
+
+### Install
+
+Use **Install from URL** option with this repo url. 
+
+### Requirements
+
+*None at all.*
+
+### Usage
+ * Export Parameters:  
+In the SD Web UI, configure the desired options, and click the "Export" button to export a flow file that records the current parameters.
+
+ * Import Parameters:  
+In the SD Web UI, click the "FileBox", select the corresponding flow file, and import the parameters from the file.
+You can also directly drag and drop the flow file into the "FileBox" for importing.
+
+**Currently, the plugin supports SD WebUI versions v1.5 and above, and compatibility testing for earlier versions has not been conducted.**  
+**If not due to compatibility issues with essential functionalities, it is strongly recommended to upgrade to version v1.6 or above before using this plugin!**
+
+### Examples
+
+You can find several official examples in the example/ folder. If you want to try out more possibilities, please visit [**Our open-source community**](https://www.lightflow.ai/) for more public examples. 
+
+### Contributing
+
+If you have any comments, suggestions, or encounter issues with our project, please feel free to raise them through an issue, and we also welcome pull requests at any time!  
+You are also more than welcomed to share your own LightDiffusionFlow on [**Our open-source community**](https://www.lightflow.ai/). 
+
+### Credits
+
+Licenses for borrowed code can be found in LICENSES/[**Licenses.md**](./LICENSES/Licenses.md)
+
+- stable-diffusion-webui-state - https://github.com/ilian6806/stable-diffusion-webui-state
+
+    *Our team urgently needs a solution to easily share the Stable Diffusion Web UI settings, and Ilian Iliev's stable-diffusion-webui-state project has been a great help to us. Thank you, Ilian Iliev!*
+
+- Big thanks to [Hali](https://github.com/ThisHaliHali) for the inspiration, suggestions, and various forms of support during the development of this project. Much appreciated!

gf/LightDiffusionFlow/README_CN.md

@@ -0,0 +1,62 @@
+<p float="left">
+    <img alt="" src="https://img.shields.io/badge/JavaScript-323330?style=for-the-badge&logo=javascript&logoColor=F7DF1E" />
+    <img alt="" src="https://img.shields.io/badge/Python-FFD43B?style=for-the-badge&logo=python&logoColor=blue" />
+</p>
+
+# sd-webui-lightdiffusionflow
+
+[**English**](./README.md) | [**中文**](./README_CN.md)
+
+这是为[Stable Diffusion Web UI](https://github.com/AUTOMATIC1111/stable-diffusion-webui) 开发的一款导入/导出参数选项的插件。  
+Stable Diffusion Web UI 以下简称 SD Web UI。  
+* [**插件效果演示和其他说明**](https://fvkij7wuqx9.feishu.cn/docx/HgZndihraotmmzxFni7cFZISnvb)  
+* [**Lightflow开源社区**](https://www.lightflow.ai/)
+* [**Discord**](https://discord.gg/CaD4mchHxW)  
+* [**Twitter: @LightFlow_AI**](https://twitter.com/LightFlow_AI)  
+
+### 功能
+
+* 实现单个文件导入/导出SD Web UI参数选项。
+* 支持解析图片的PNG Info，并自动将参数恢复到SD Web UI面板上，包括部分插件参数。
+* 目前支持的插件：
+    - 理论上来说，目前可以支持所有插件。  
+    部分插件的图片参数除外，因为必须要有对应的elem_id。
+
+![lightflow_CN](https://github.com/Tencent/LightDiffusionFlow/assets/20501414/492f7408-7729-4370-b0f9-c17a80211029)
+
+### 安装
+
+粘贴本项目链接到 **Install from URL** 选项里，点击安装按钮即可。
+
+### 插件依赖项
+
+无
+
+### 用法
+
+* 导出配置：
+    - 在SD Web UI上设置好合适的选项，点击Export按钮即可导出记录了当前设置的flow文件。
+* 导入配置：
+    - 在SD Web UI上，点击文件框选择对应的flow文件，即可导入文件中的设置。
+    - 也可以直接把flow文件拖入文件框内完成导入。
+
+**目前，该插件支持SD WebUI v1.5及以上版本，尚未对早期版本进行兼容性测试。**  
+**如果不是因为基本功能的兼容性问题，强烈建议在使用此插件之前升级到v1.6或更高版本。**
+### 注意事项
+
+* 每次导入新的flow文件之前，最好刷新一下SD Web UI页面，因为插件只会修改已保存的参数选项。
+* 插件当前版本不支持秋叶启动器的"云端汉化选项"，使用本插件时建议关闭。
+
+### 插件共建
+
+如果你对我们的项目有意见、建议或者使用中遇到问题，欢迎通过 issue 给我们提出，也欢迎随时发起PR!
+
+### 感谢
+
+本项目参考和引用的第三方代码开源许可放在 LICENSES/[**Licenses.md**](./LICENSES/Licenses.md)
+
+- stable-diffusion-webui-state - https://github.com/ilian6806/stable-diffusion-webui-state
+
+    *我们团队急需一个能快速分享 SD Web UI 设置的解决方案，Ilian Iliev 的 stable-diffusion-webui-state 项目为我们提供了很大的帮助，感谢 Ilian Iliev！*
+
+- 非常感谢 [Hali](https://github.com/ThisHaliHali) 为本项目提供的灵感、建议以及在开发期间的各种支持！

gf/LightDiffusionFlow/example/Product Design_线稿-工业产品.flow

@@ -0,0 +1,21 @@
+{
+    "state-ext-control-net-txt2img_0-pixel-perfect": "true",
+    "state-ext-control-net-txt2img_0-model": "control_v11p_sd15_scribble [d4ba51ff]",
+    "state-txt2img_steps": "30",
+    "state-txt2img_height": "768",
+    "state-txt2img_seed": "1405674945",
+    "state-ext-control-net-txt2img-tab": "ControlNet Unit 0 [Scribble]",
+    "state-txt2img_neg_prompt": "colorful,illustration, painting, cartoons, sketch, (worst quality:2), (low quality:2), (normal quality:2), lowres, bad anatomy, bad hands, ((monochrome)), ((grayscale)), oversaturated, extra limb, missing limbs, deformed hands, long neck, long body, imperfect, (bad hands), signature, watermark, username, artist name, conjoined fingers, deformed fingers, ugly eyes, imperfect eyes, skewed eyes, unnatural face, unnatural body",
+    "state-ext-control-net-txt2img_0-preprocessor": "scribble_pidinet",
+    "state-txt2img_sampling": "DPM++ SDE Karras",
+    "state-ext-control-net-txt2img_0-allow-preview": "true",
+    "state-ext-control-net-txt2img_0-control-type": "Scribble",
+    "state-txt2img_enable_hr": "true",
+    "state-txt2img_hr_upscaler": "R-ESRGAN 4x+",
+    "state-tab": "txt2img",
+    "state-setting_sd_model_checkpoint": "chilloutmix_NiPrunedFp32Fix.safetensors [fc2511737a]",
+    "state-ext-control-net-txt2img_0-enable": "true",
+    "state-ext-control-net-txt2img-toggled": "false",
+    "state-txt2img_prompt": "product design,white material, Apple style,modern style,minimalist style,white background,classic color matching,light red,C4d rendering,ultra-high definition,32K UHD",
+    "txt2img_controlnet_ControlNet-0_input_image": 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"
+}

gf/LightDiffusionFlow/example/lightflow艺术二维码.flow

@@ -0,0 +1,36 @@
+{
+    "state-ext-control-net-txt2img_0-pixel-perfect": "true",
+    "state-ext-control-net-txt2img_0-model": "control_v1p_sd15_qrcode_monster [a6e58995]",
+    "state-ext-control-net-txt2img_3-control-weight": "0.4",
+    "state-txt2img_seed": "2587406147",
+    "state-ext-control-net-txt2img_3-enabled": "true",
+    "state-ext-control-net-txt2img_0-ending-control-step": "0.87",
+    "state-ext-control-net-txt2img-tab": "ControlNet Unit 1 ",
+    "state-ext-control-net-txt2img_0-guidance-start-(t)": "0.21",
+    "state-setting_sd_model_checkpoint": "天空之境.safetensors [c1d961233a]",
+    "state-txt2img_sampling": "DPM++ 2M Karras",
+    "state-ext-control-net-txt2img_0-active": "true",
+    "state-ext-control-net-txt2img_3-pixel-perfect": "true",
+    "state-ext-control-net-txt2img_3-enable": "true",
+    "state-ext-control-net-txt2img_0-starting-control-step": "0.21",
+    "state-tab": "txt2img",
+    "state-ext-control-net-txt2img_0-enabled": "true",
+    "state-ext-control-net-txt2img_0-control-weight": "1.2",
+    "state-ext-control-net-txt2img_3-guidance-end-(t)": "0.75",
+    "state-txt2img_steps": "30",
+    "state-txt2img_height": "768",
+    "state-ext-control-net-txt2img_1-model": "control_v1p_sd15_brightness [5f6aa6ed]",
+    "state-ext-control-net-txt2img_3-model": "control_v1p_sd15_brightness [5f6aa6ed]",
+    "state-ext-control-net-txt2img_3-active": "true",
+    "state-ext-control-net-txt2img_0-guidance-end-(t)": "0.87",
+    "state-txt2img_prompt": "A RAW photo of a delicious plate of Rice,chocolate rice dumpling shrimp,mixed vegetables,thinly sliced chicken in a coconut milk curry sauce,hyperrealism,hyperrealistic,octane render,hyper detailed,8K,",
+    "state-txt2img_neg_prompt": "(worst quality, low quality:1.4), negative_hand Negative Embedding, verybadimagenegative_v1.3, 2girls, nsfw:1.4, bad anatomy, bad hands, cropped, missing fingers, too many fingers, missing arms, long neck, Humpbacked, deformed, disfigured, poorly drawn face, distorted face, mutation, mutated, extra limb, ugly, poorly drawn hands, missing limb, floating limbs, disconnected limbs, malformed hands, out of focus, long body, missing toes, too many toes, monochrome, symbol, text, logo, door frame, window frame, mirror frame, ",
+    "state-txt2img_width": "768",
+    "state-ext-control-net-txt2img_3-guidance-start-(t)": "0.45",
+    "state-ext-control-net-txt2img_3-ending-control-step": "0.75",
+    "state-ext-control-net-txt2img_3-starting-control-step": "0.45",
+    "state-ext-control-net-txt2img_0-enable": "true",
+    "state-ext-control-net-txt2img-toggled": "false",
+    "txt2img_controlnet_ControlNet-0_input_image": "data:image/png;base64,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",
+    "txt2img_controlnet_ControlNet-1_input_image": "data:image/png;base64,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"
+}

gf/LightDiffusionFlow/install.py

@@ -0,0 +1,6 @@
+import launch
+import os,sys
+
+
+# if not launch.is_installed("js2py"):
+#   launch.run_pip("install js2py", "js2py")

gf/LightDiffusionFlow/javascript/state.app.js

@@ -0,0 +1,4 @@
+
+document.addEventListener('DOMContentLoaded', function() {
+  onUiLoaded(state.core.init);
+});

gf/LightDiffusionFlow/javascript/state.constants.js

@@ -0,0 +1,6 @@
+window.state = window.state || {};
+state = window.state;
+
+state.constants = {
+  LS_PREFIX: 'state-'
+};

gf/LightDiffusionFlow/javascript/state.core.js

@@ -0,0 +1,1006 @@
+window.state = window.state || {};
+state = window.state;
+
+
+state.core = (function () {
+
+  const TABS = ['txt2img', 'img2img'];
+
+  // settingId, element
+  const ELEMENTS = {
+    'prompt': 'prompt',
+    'negative_prompt': 'neg_prompt',
+    'sampling_steps': 'steps',
+    'restore_faces': 'restore_faces',
+    'tiling': 'tiling',
+    'hires_fix': 'enable_hr',
+    'hires_steps': 'hires_steps',
+    'hires_scale': 'hr_scale',
+    'hires_resize_x': 'hr_resize_x',
+    'hires_resize_y': 'hr_resize_y',
+    'hires_denoising_strength': 'denoising_strength',
+    'width': 'width',
+    'height': 'height',
+    'batch_count': 'batch_count',
+    'batch_size': 'batch_size',
+    'cfg_scale': 'cfg_scale',
+    'denoising_strength': 'denoising_strength',
+    'seed': 'seed',
+    'sampling': 'sampling',
+    'switch_at': 'switch_at'
+  };
+
+  const ACCORDION = {
+    "hires_fix": "hr",
+    "refiner": "enable"
+  }
+
+  const ELEMENTS_WITHOUT_PREFIX = {
+    'resize_mode': 'resize_mode',
+    'setting_inpainting_mask_weight': 'setting_inpainting_mask_weight',
+    'setting_CLIP_stop_at_last_layers': 'setting_CLIP_stop_at_last_layers',
+    'setting_eta_noise_seed_delta': 'setting_eta_noise_seed_delta',
+    'img2img_mask_blur': 'img2img_mask_blur',
+    'img2img_mask_mode': 'img2img_mask_mode',
+    'img2img_inpainting_fill': 'img2img_inpainting_fill',
+    'img2img_inpaint_full_res_padding': 'img2img_inpaint_full_res_padding',
+    'img2img_inpaint_full_res': 'img2img_inpaint_full_res',
+    'img2img_mask_alpha': 'img2img_mask_alpha'
+    //'generation_info_txt2img': 'generation_info_txt2img' // 可能因为是visible=false 所以触发不了onchange事件？
+  };
+
+  const SELECTS = {
+    'sampling': 'sampling',
+    'hires_upscaler': 'hr_upscaler',
+    'script': '#script_list',
+    'checkpoint': 'checkpoint',
+  };
+
+  const SELECTS_WITHOUT_PREFIX = {
+    'setting_sd_model_checkpoint': 'setting_sd_model_checkpoint',
+    'setting_sd_vae': 'setting_sd_vae'
+  };
+
+  const MULTI_SELECTS = {
+    'styles': 'styles'
+  };
+
+  const TOGGLE_BUTTONS = {
+    'extra_networks': 'extra_networks',
+  };
+  
+  var IMAGES_WITHOUT_PREFIX = {
+  };
+
+  const ELEMENTS_ALWAYS_SAVE = {
+    'setting_sd_model_checkpoint': 'setting_sd_model_checkpoint',
+  };
+
+  const Image_extensions = [".png", ".jpg", ".jpeg"]
+
+  let store = null;
+  let timer = null;
+  let inited = false
+  let sd_versions = "0.0.0"
+  let waiting_second_apply = false
+  let timeout_id = undefined
+  let img_elem_keys=[];
+  let ext_list=[];
+  let flow_save_mode = "Core"
+
+
+  function hasSetting(id, tab) {
+    return true // 需要默认保存全部选项 不需要判断
+    const suffix = tab ? `_${tab}` : '';
+    return this[`state${suffix}`] && this[`state${suffix}`].indexOf(id) > -1;
+  }
+
+  function fn_timer(){
+
+    // if(inited){ 
+      fetch('/lightdiffusionflow/local/need_preload')
+      .then(response => response.json())
+      .then(data => {
+        console.log(`fn_timer`)
+        if (data != ""){
+          //state.core.actions.handleLightDiffusionFlow([{"name":data}]);
+          const btn1 = gradioApp().querySelector(`button#set_lightdiffusionflow_file`);
+          state.utils.triggerMouseEvent(btn1);
+          setTimeout(() => {
+            const btn2 = gradioApp().querySelector(`button#preload_button`);
+            state.utils.triggerMouseEvent(btn2);
+          }, 1000);
+        }
+      }).catch(function(e) {
+        clearInterval(timer)
+        console.log("Oops, error");
+      });
+    // }
+    // else{
+
+    //   fetch('/lightdiffusionflow/local/get_imgs_elem_key') //初始化部分图片组件id, 后续设置onchanged事件
+    //   .then(response => response.json())
+    //   .then(data => {
+    //     if(data != ""){
+
+    //       img_elem_keys = data.split(",")
+    //       img_elem_keys.forEach(key => {
+    //         IMAGES_WITHOUT_PREFIX[key] = key
+    //       });
+          
+    //       // 等上面的组件ID同步过来后 再加载其他配置
+    //       fetch('/lightdiffusionflow/local/config.json?_=' + (+new Date()))
+    //       .then(response => response.json())
+    //       .then(config => {          
+    //         try {
+    //           store = new state.Store();
+    //           store.clearAll();
+    //           load(config);
+    //           inited = true
+    //         } catch (error) {
+    //           console.error('[state]: Error:', error);
+    //         }
+    //       })
+    //       .catch(error => console.error('[state]: Error getting JSON file:', error));
+    //     }
+    //   });
+        
+
+    // }
+      
+  }
+
+  function get_js_local_data(){
+    
+    if(state.utils.getCurSeed('txt2img') != undefined){
+      store.set(`txt2img_seed`,state.utils.getCurSeed('txt2img'))
+    }
+    if(state.utils.getCurSeed('img2img') != undefined){
+      store.set(`img2img_seed`,state.utils.getCurSeed('img2img'))
+    }
+
+    stored_config = store.getAll()
+
+    for (let key in stored_config){
+      if(key.indexOf("allow-preview") !== -1 && key.indexOf("ext-control-net") !== -1)
+      {
+        console.log("allow-preview改成false")
+        stored_config[key] = "false"
+      }
+    }
+
+    return stored_config
+  }
+
+  function get_imgs_elem_key(){
+
+    fetch('/lightdiffusionflow/local/get_imgs_elem_key') //初始化部分图片组件id, 后续设置onchanged事件
+      .then(response => response.json())
+      .then(data => {
+        console.log(data)
+        if(data == ''){
+          setTimeout(() => {
+            get_imgs_elem_key()
+          }, 500);
+        }
+        else{
+          img_elem_keys = data.split(",")
+          img_elem_keys.forEach(key => {
+            IMAGES_WITHOUT_PREFIX[key] = key
+          });
+          
+          fetch('/lightdiffusionflow/local/get_ext_list')
+          .then(response => response.json())
+          .then(data => {
+            ext_list = data.split(",")
+          });
+          
+          // 等上面的组件ID同步过来后 再加载其他配置
+          fetch('/lightdiffusionflow/local/config.json?_=' + (+new Date()))
+            .then(response => response.json())
+            .then(config => {
+              try {
+                
+                try{
+                  flow_save_mode = config['lightdiffusionflow-mode']
+                }catch (error) {
+                  flow_save_mode = "Core"
+                }
+
+                store = new state.Store();
+                store.clearAll();
+                load(config);
+                timer = window.setInterval(fn_timer,1000); // 初始化页面完成后再启动timer读取文件
+              } catch (error) {
+                console.error('[state]: Error:', error);
+              }
+            })
+            .catch(error => console.error('[state]: Error getting JSON file:', error));
+        }
+      });
+
+  }
+
+  function init() {
+    
+    //console.log(window.localization)
+    fetch('/lightdiffusionflow/local/refresh_ui') // 刷新页面触发python重置图片数据
+    .then(response => response.json())
+    .then(data => {
+      sd_versions = data
+    });
+
+    get_imgs_elem_key()
+
+  }
+  
+  // function forEachImageElement(list, action) {
+  //   for (const [settingId, element] of Object.entries(list)) {
+  //     TABS.forEach(tab => {
+  //       //if (config.hasSetting(settingId, tab)) {
+  //         action(element, tab);
+  //       //}
+  //     });
+  //   }
+  // }
+
+  function forEachElement_WithoutTabs(list, action) {
+    for (const [settingId, element] of Object.entries(list)) {
+      action(element);
+    }
+  }
+
+  function forEachElement(list, config, action) {
+    for (const [settingId, element] of Object.entries(list)) {
+      TABS.forEach(tab => {
+        if (config.hasSetting(settingId, tab)) {
+          action(element, tab);
+        }
+      });
+    }
+  }
+
+  function load(config, addEvtLsner=true) {
+    config.hasSetting = hasSetting
+
+    //loadUI(); // 往页面上添加按钮
+
+    for (let tab of TABS)
+    {
+      //console.log(`${tab}_script_container start`)
+      let script_container = getElement(`${tab}_script_container`)
+      state.utils.onFrameContentChange(script_container, function (el) {
+        clearTimeout(timeout_id);
+        timeout_id = setTimeout(() => {
+          if(waiting_second_apply)
+          {
+            waiting_second_apply = false
+            actions.applyState(false);
+            setTimeout(() => {
+              actions.preset_output_log("finished")
+            }, 3000);
+          }
+        }, 3000);
+      });
+    }
+
+    forEachElement(ACCORDION, config, (element, tab) => {
+      handleSavedAccordion(`${tab}_${element}`, addEvtLsner);
+    });
+
+    forEachElement_WithoutTabs(SELECTS_WITHOUT_PREFIX, (element) => {
+      handleSavedSelects(element, addEvtLsner);
+    });
+
+    forEachElement(ELEMENTS, config, (element, tab) => {
+      handleSavedInput(`${tab}_${element}`, addEvtLsner);
+    });
+
+    forEachElement_WithoutTabs(ELEMENTS_WITHOUT_PREFIX, (element) => {
+      handleSavedInput(element, addEvtLsner);
+    });
+
+    forEachElement(SELECTS, config, (element, tab) => {
+      handleSavedSelects(`${tab}_${element}`, addEvtLsner);
+    });
+
+    forEachElement(MULTI_SELECTS, config, (element, tab) => {
+      handleSavedMultiSelects(`${tab}_${element}`, addEvtLsner);
+    });
+
+    forEachElement(TOGGLE_BUTTONS, config, (element, tab) => {
+      handleToggleButton(`${tab}_${element}`, addEvtLsner);
+    });
+
+    forEachElement_WithoutTabs(IMAGES_WITHOUT_PREFIX, (element) => {
+      handleSavedImage(`${element}`, addEvtLsner);
+    });
+
+    handleExtensions(config, addEvtLsner);
+    //handleSettingsPage();
+
+    restoreTabs(config, addEvtLsner); // 恢复到最后点击的tab页面
+
+    forEachElement_WithoutTabs(ELEMENTS_ALWAYS_SAVE, (element) => {
+      state.utils.forceSaveSelect(getElement(element), element, store); //每次无论有没有修改都需要导出的选项
+    });
+  }
+
+  function createHeaderButton(title, text, className, style, action) {
+
+    const button = state.utils.html.create('button', {
+      title: title,
+      innerHTML: text,
+      className: className,
+    }, style);
+
+    if (action) {
+      button.addEventListener('click', action);
+    }
+
+    return button;
+  }
+
+  // function createHeaderFileInput(title, text, className) {
+
+  //   let inputId = 'state-import-file-inline';
+
+  //   let importBtn = createHeaderButton(title,text, className, {
+  //     display: 'none'
+  //   }, () => {
+  //     actions.importState(inputId);
+  //   });
+
+  //   let label = state.utils.html.create('label', {}, { cursor: 'pointer' });
+  //   label.appendChild(state.utils.html.create('input', {
+  //     type: 'file',
+  //     id: inputId,
+  //     accept: 'application/json',
+  //   }, {
+  //     display: 'none'
+  //   }));
+  //   label.appendChild(document.createTextNode(text));
+  //   label.addEventListener('change', () => {
+  //     importBtn.dispatchEvent(new Event('click'));
+  //   });
+
+  //   let button = createHeaderButton(title, '', className, {});
+  //   button.appendChild(label);
+
+  //   return {
+  //     hiddenButton: importBtn,
+  //     button: button
+  //   };
+  // }
+
+  // function loadUI() {
+  //   let quickSettings = gradioApp().getElementById("quicksettings");
+  //   let className = quickSettings.querySelector('button').className;
+  //   quickSettings.appendChild(createHeaderButton('State: Reset', "*️⃣", className, {}, actions.resetAll));
+  //   quickSettings.appendChild(createHeaderButton('State: Export',"📤", className, {}, actions.exportState));
+  //   quickSettings.appendChild(createHeaderButton('State: test',"📤", className, {}, actions.test));
+  //   let fileInput = createHeaderFileInput('State: Import',"📥", className);
+  //   quickSettings.appendChild(fileInput.hiddenButton);
+  //   quickSettings.appendChild(fileInput.button);
+  // }
+
+
+  function restoreTabs(config, addEvtLsner=true) {
+
+    if (! config.hasSetting('tabs')) {
+      return;
+    }
+
+    const tabs = gradioApp().querySelectorAll('#tabs > div:first-child button');
+    const value = store.get('tab');
+    if (value) {
+      for (var i = 0; i < tabs.length; i++) {
+        if (tabs[i].textContent === state.utils.getTranslation(value)) {
+          state.utils.triggerEvent(tabs[i], 'click');
+          break;
+        }
+      }
+    }
+
+    // Use this when onUiTabChange is fixed
+    // onUiTabChange(function () {
+    //   store.set('tab', gradioApp().querySelector('#tabs .tab-nav button.selected').textContent);
+    // });
+    if(addEvtLsner){
+      bindTabClickEvents();
+    }
+  }
+
+  function bindTabClickEvents() {
+    Array.from(gradioApp().querySelectorAll('#tabs .tab-nav button')).forEach(tab => {
+      tab.removeEventListener('click', storeTab);
+      tab.addEventListener('click', storeTab);
+    });
+  }
+
+  function storeTab() {
+    let tab_name = gradioApp().querySelector('#tabs .tab-nav button.selected').textContent;
+    store.set('tab', state.utils.reverseTranslation(tab_name)[0]);
+    bindTabClickEvents(); // dirty hack here...
+  }
+
+  function getElement(id) {
+    for (let i = 0; i < TABS.length; i++) {
+      if (id.startsWith(`${TABS[i]}_#`)) {
+        // handle elements with same ids in different tabs...
+        return gradioApp().querySelector('#tab_' + id.replace(`${TABS[i]}_#`, `${TABS[i]} #`));
+      }
+    }
+    return gradioApp().getElementById(id);
+  }
+
+  function handleSavedInput(id, addEvtLsner=true) {
+
+    const elements = gradioApp().querySelectorAll(`#${id} textarea, #${id} input, #${id} img`);
+    const events = ['change', 'input'];
+
+    if (! elements || ! elements.length) {
+      return;
+    }
+    
+    let forEach = function (action) {
+      events.forEach(function(event) {
+        elements.forEach(function (element) {
+          action.call(element, event);
+        });
+      });
+    };
+
+    if(addEvtLsner){
+      forEach(function (event) {
+        this.addEventListener(event, function () {
+          let value = this.value;
+          if (this.type && this.type === 'checkbox') {
+            value = this.checked;
+          }
+          else if (this.className === 'img') {
+            value = this.checked;
+          }
+          store.set(id, value);
+        });
+      });
+
+      TABS.forEach(tab => {
+        const seedInput = gradioApp().querySelector(`#${tab}_seed input`);
+        ['random_seed', 'reuse_seed'].forEach(id => {
+          const btn = gradioApp().querySelector(`#${tab}_${id}`);
+          btn.addEventListener('click', () => {
+            setTimeout(() => {
+              state.utils.triggerEvent(seedInput, 'change');
+            }, 100);
+          });
+        });
+      });
+    }
+
+    let value = store.get(id);
+    if (! value) {
+      return;
+    }
+    forEach(function (event) {
+      state.utils.setValue(this, value, event);
+    });
+  }
+
+  function handleSavedSelects(id, addEvtLsner=true) {
+    state.utils.handleSelect(getElement(id), id, store, force=false, addEvtLsner);
+  }
+
+  function handleSavedAccordion(id, addEvtLsner=true) {
+    state.utils.handleAccordion(getElement(id), id, store, addEvtLsner);
+  }
+
+  function handleSavedMultiSelects(id, addEvtLsner=true) {
+    const select = gradioApp().getElementById(`${id}`);
+    state.utils.handleMultipleSelect(select, id, store, addEvtLsner);
+  }
+
+  function handleSavedImage(id, addEvtLsner=true) {
+    state.utils.handleImage(getElement(id), id, store, addEvtLsner); // 图片有修改就发回到python保存
+  }
+
+  function handleToggleButton(id, addEvtLsner=true) {
+    const btn = gradioApp().querySelector(`button#${id}`);
+    if (! btn) { return; }
+    // legionfu
+    if (store.get(id) === 'true') {
+      state.utils.triggerMouseEvent(btn);
+    }
+    if(addEvtLsner){
+      btn.addEventListener('click', function () {
+        store.set(id, Array.from(this.classList).indexOf('secondary-down') === -1);
+      });
+    }
+  }
+
+  function handleExtensions(config, addEvtLsner=true) {
+    // if (config['state_extensions']) {
+    //   config['state_extensions'].forEach(function (ext) {
+    //     if (ext in state.extensions) {
+    //       state.extensions[ext].init();
+    //     }
+    //   });
+    // }
+    for (const [name, obj] of Object.entries(state.extensions)) {
+      obj.init(flow_save_mode == "Core", addEvtLsner);
+    }
+
+  }
+
+  // function handleSettingsPage() {  // settings   state 界面 绑定按钮事件等操作
+
+  //   const page = gradioApp().querySelector('#settings_state');
+  //   state.utils.html.setStyle(page.querySelectorAll('fieldset'), {
+  //     'marginTop': '20px',
+  //     'marginBottom': '10px'
+  //   });
+
+  //   let buttonsContainer = gradioApp().querySelector('#settings_state_buttons');
+  //   if (buttonsContainer) {
+  //     buttonsContainer.parentNode.removeChild(buttonsContainer);
+  //   }
+  //   buttonsContainer = document.createElement('div');
+  //   buttonsContainer.id = 'settings_state_buttons';
+
+  //   let setCheckboxes = function (value, checkFunc) {
+  //     checkFunc = checkFunc || function () { return true; };
+  //     Array.from(page.querySelectorAll('input[type="checkbox"]')).forEach(function (el) {
+  //       if (checkFunc(el)) {
+  //         if (el.checked !== value) {
+  //           el.checked = value;
+  //           state.utils.triggerEvent(el, 'change');
+  //         }
+  //       } else if (el.checked === value) {
+  //         el.checked = !value;
+  //         state.utils.triggerEvent(el, 'change');
+  //       }
+  //     });
+  //   };
+  //   buttonsContainer.appendChild(state.utils.html.createButton('Select All', function () {
+  //     setCheckboxes(true);
+  //   }));
+  //   buttonsContainer.appendChild(state.utils.html.createButton('Select All Except Seeds', function () {
+  //     setCheckboxes(true, function (el) {
+  //       return el.nextElementSibling.textContent.indexOf('seed') === -1;
+  //     });
+  //   }));
+  //   buttonsContainer.appendChild(state.utils.html.createButton('Unselect All', function () {
+  //     setCheckboxes(false);
+  //   }));
+  //   state.utils.html.setStyle(buttonsContainer, {
+  //     'marginTop': '20px',
+  //     'marginBottom': '10px'
+  //   });
+  //   buttonsContainer.appendChild(state.utils.html.create('hr'));
+  //   buttonsContainer.appendChild(state.utils.html.create('div',
+  //    { innerHTML: 'Actions' },
+  //    { marginBottom: '10px' }));
+  //   buttonsContainer.appendChild(state.utils.html.createButton('Reset All', actions.resetAll));
+  //   buttonsContainer.appendChild(state.utils.html.createButton('Export State', actions.exportState));
+  //   buttonsContainer.appendChild(state.utils.html.createButton('Import State', actions.importState));
+  //   buttonsContainer.appendChild(state.utils.html.create('input', {
+  //     id: 'state-import-file', type: 'file', accept: 'application/json'
+  //   }));
+  //   page.appendChild(buttonsContainer);
+  // }
+
+  let actions = {
+    // resetAll: function () {
+    //   let confirmed = confirm('Reset all state values?');
+    //   if (confirmed) {
+    //     store.clearAll();
+    //     alert('All state values deleted!');
+    //   }
+    // },
+    applyState: async function (addEvtLsner=true) {
+      console.log("applyState")
+      await fetch('/lightdiffusionflow/local/config.json?_=' + (+new Date()))
+        .then(response => response.json())
+        .then(config => {
+          try {
+            config.hasSetting = hasSetting
+            
+            try{
+              flow_save_mode = config['lightdiffusionflow-mode']
+            }catch (error) {
+              flow_save_mode = "Core"
+            }
+            //console.log(config)
+            //restoreTabs(config); // 恢复到最后点击的tab页面
+            load(config, addEvtLsner);
+            // forEachElement_WithoutTabs(SELECTS_WITHOUT_PREFIX, (element) => {
+            //   handleSavedSelects(element);
+            // });
+
+            // forEachElement(ELEMENTS, config, (element, tab) => {
+            //   handleSavedInput(`${tab}_${element}`);
+            // });
+
+            // forEachElement_WithoutTabs(ELEMENTS_WITHOUT_PREFIX, (element) => {
+            //   handleSavedInput(element);
+            // });
+
+            // forEachElement(SELECTS, config, (element, tab) => {
+            //   handleSavedSelects(`${tab}_${element}`);
+            // });
+
+            // forEachElement(MULTI_SELECTS, config, (element, tab) => {
+            //   handleSavedMultiSelects(`${tab}_${element}`);
+            // });
+
+            // forEachElement(TOGGLE_BUTTONS, config, (element, tab) => {
+            //   handleToggleButton(`${tab}_${element}`);
+            // });
+
+            // forEachElement_WithoutTabs(IMAGES_WITHOUT_PREFIX, (element) => {
+            //   handleSavedImage(element);
+            // });
+        
+            // handleExtensions(config);
+
+            
+            //handleSettingsPage();
+          } catch (error) {
+            console.error('[state]: Error:', error);
+          }
+        })
+        .catch(error => console.error('[state]: Error getting JSON file:', error));
+    },
+    
+    exportState: function () {
+      
+      // if(state.utils.getCurSeed('txt2img') != undefined){
+      //   store.set(`txt2img_seed`,state.utils.getCurSeed('txt2img'))
+      // }
+      // if(state.utils.getCurSeed('img2img') != undefined){
+      //   store.set(`img2img_seed`,state.utils.getCurSeed('img2img'))
+      // }
+      let stored_config = get_js_local_data()
+      
+      fetch('/lightdiffusionflow/local/lightdiffusionflow_config?data2export=true')
+      .then(response => response.json())
+      .then(config => {
+
+        config = JSON.parse(config)
+        //stored_config = store.getAll()
+        
+        let data = {
+          method: 'POST',
+          headers: { 'Content-Type': 'application/json' },
+          body: JSON.stringify({
+            "config_data":stored_config
+          })
+        }
+        fetch(`/lightdiffusionflow/local/parse_lora_info`, data)
+        .then(response => response.json())
+        .then(response_lora_info => {
+          
+        for (let key in response_lora_info){
+          stored_config[key] = response_lora_info[key]
+        }
+
+        for (let key in config){
+          if(config[key] != ""){
+            stored_config[key] = config[key]
+          }
+        }
+
+        // for (let key in stored_config){
+        //   if(key.indexOf("allow-preview") !== -1 && key.indexOf("ext-control-net") !== -1)
+        //   {
+        //     console.log("allow-preview改成false")
+        //     stored_config[key] = "false"
+        //   }
+        // }
+
+        var checkTime = function (i) {
+          if (i < 10) { i = "0" + i; }
+          return i;
+        }
+        let nowdate = new Date();
+        let year = String(nowdate.getFullYear())
+        let month = String(checkTime(nowdate.getMonth() + 1))
+        let day = String(checkTime(nowdate.getDate()))
+        let h = String(checkTime(nowdate.getHours()))
+        let m = String(checkTime(nowdate.getMinutes()))
+        let s = String(checkTime(nowdate.getSeconds()))
+        let time_str = year+month+day+h+m+s
+
+        filename = 'flow-'+time_str+'.flow'
+        filename = prompt("Export workflow as:", filename);
+        if (!filename) return;
+        if (!filename.toLowerCase().endsWith(".flow")) {
+          filename += ".flow";
+        }
+        if(filename != ".flow"){
+          // const handle = window.showDirectoryPicker();
+          // console.log(handle)
+          
+          state.utils.saveFile(filename, stored_config);
+          
+          fetch('https://api.lightflow.ai/openapi/access?action=export')
+          .then(response => response.json())
+          .then(config => {
+            console.log(config)
+          }).catch(function(e) {
+            console.log("Oops, export callback error!");
+          });
+
+        }
+
+        }).catch(error => console.error('[state]: Error getting Flow file:', error));
+
+      }).catch(error => console.error('[state]: Error getting Flow file:', error));
+
+      //config = JSON.stringify(store.getAll(), null, 4);
+      //fetch(`/lightdiffusionflow/local/ExportLightDiffusionFlow?config=${config}`)
+    },
+    saveFlowToLocal: function saveFlowToLocal(){
+      var checkTime = function (i) {
+        if (i < 10) { i = "0" + i; }
+        return i;
+      }
+      let nowdate = new Date();
+      let year = String(nowdate.getFullYear())
+      let month = String(checkTime(nowdate.getMonth() + 1))
+      let day = String(checkTime(nowdate.getDate()))
+      let h = String(checkTime(nowdate.getHours()))
+      let m = String(checkTime(nowdate.getMinutes()))
+      let s = String(checkTime(nowdate.getSeconds()))
+      let time_str = year+month+day+h+m+s
+
+      filename = 'flow-'+time_str+'.flow'
+      filename = prompt("Save workflow as:", filename);
+      if (!filename) return;
+      if (!filename.toLowerCase().endsWith(".flow")) {
+        filename += ".flow";
+      }
+      if(filename != ".flow"){
+
+        let data = {
+          method: 'POST',
+          headers: { 'Content-Type': 'application/json' },
+          body: JSON.stringify({
+            "file_path":filename
+          })
+        }
+        fetch(`/lightdiffusionflow/local/file_exist`, data)
+        .then(response => response.json())
+        .then(data => {
+          if(!data || (data && confirm("Overwrite the existing file with the same name?")))
+          {
+            let stored_config = get_js_local_data()
+            let flow_data = {
+              method: 'POST',
+              headers: {'Content-Type': 'application/json'},
+              body: JSON.stringify({
+                "file_name":filename,
+                "file_data":stored_config,
+                "overwrite":true
+              })
+            }
+            fetch("/lightdiffusionflow/local/save_flow_to_local",flow_data)
+            
+            fetch('https://api.lightflow.ai/openapi/access?action=save')
+            .then(response => response.json())
+            .then(config => {
+              console.log(config)
+            }).catch(function(e) {
+              console.log("Oops, export callback error!");
+            });
+          }
+        });
+      }
+    },
+
+    handleLightDiffusionFlow: function (fileInput){
+      actions.preset_output_log("start")
+      //actions.output_log("<hr style='margin-top:10px;margin-bottom:10px'>Start parsing settings...")
+      console.log(fileInput)
+      let temp_fileInput = undefined
+      try{temp_fileInput = fileInput[0]} catch(error){}
+      if ( !temp_fileInput ) {temp_fileInput = fileInput}
+      if ( !temp_fileInput ) {
+        //alert('Please select a JSON file!');
+        actions.preset_output_log("invalid")
+        //actions.output_log("Please select a valid lightdiffusionflow or image file!")
+        return;
+      }
+
+      let file_name = temp_fileInput.name;
+      console.log(file_name)
+      let extension = file_name.substring(file_name.lastIndexOf("."));
+      if( Image_extensions.indexOf(extension) != -1 ){
+        let data = {
+          method: 'POST',
+          headers: { 'Content-Type': 'application/json' },
+          body: JSON.stringify({
+            "img_path":file_name
+          })
+        }
+        fetch(`/lightdiffusionflow/local/png_info`, data)
+          .then(response => response.json())
+          .then(data => {
+            //console.log(data)
+            actions.importLightDiffusionFlow(data)
+          });
+      }
+      else{
+        // const file = new Blob([fileInput[0].name]);
+        const file = temp_fileInput.blob;
+        const reader = new FileReader();
+        reader.onload = function (event) {
+          actions.importLightDiffusionFlow(event.target.result)
+        };
+        try{ reader.readAsText(file); } catch (error) {
+          console.log("read from python")
+          if(temp_fileInput.name != ""){
+            let data = {
+              method: 'POST',
+              headers: { 'Content-Type': 'application/json' },
+              body: JSON.stringify({
+                "file_path":temp_fileInput.name
+              })
+            }
+            fetch(`/lightdiffusionflow/local/read_file`, data)
+              .then(response => response.json())
+              .then(data => {
+                actions.importLightDiffusionFlow(data)
+              });
+          }
+
+        }
+      }
+      return fileInput
+    },
+    importLightDiffusionFlow: function (inputData){
+
+      forEachElement_WithoutTabs(IMAGES_WITHOUT_PREFIX, (image_id) => {
+        state.utils.clearImage(getElement(image_id));
+      });
+      
+      let json_obj = {}
+      try { json_obj = JSON.parse(inputData) } catch (error) {
+        actions.preset_output_log("invalid")
+        //actions.output_log("Please select a valid lightdiffusionflow or image file!")
+        return;
+      }
+
+      // 筛选掉默认值参数
+      let data = {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({
+          "config_data":json_obj
+        })
+      }
+      fetch(`/lightdiffusionflow/local/useless_config_filter`, data)
+      .then(response => response.json())
+      .then(data => {
+        json_obj = data
+        console.log(ext_list)
+        // 缺少的插件
+        missing_ext_list = []
+        for (let key in json_obj){
+          ext_name = key.match(/ext-(\S+?)-(txt2img|img2img)/)
+          //console.log(key)
+          if(ext_name != null){
+            ext_name = ext_name[1]
+            //console.log(ext_name)
+            if(ext_list.indexOf(ext_name) === -1){
+              if(missing_ext_list.indexOf(ext_name) === -1){
+                missing_ext_list.push(ext_name)
+              }
+            }
+          }
+        }
+
+        if(missing_ext_list.length > 0){
+          actions.preset_output_log("missing_exts","",missing_ext_list.join(';'))
+        }
+
+        forEachElement_WithoutTabs(IMAGES_WITHOUT_PREFIX, (image_id) => {
+          json_obj[image_id] = ""
+        });
+        // webui主界面 没有localization相关的兼容问题 所以不用管
+        
+        waiting_second_apply = true
+        store.clearAll();
+        store.load(json_obj);
+        actions.applyState();
+      });
+      return;
+    },
+    startImportImage: function (index){
+      index = Number(index)
+
+      //console.log(`-------startImportImage--'${index}'---------------`)
+      if(index+1 < img_elem_keys.length){
+        //console.log(`---------${img_elem_keys}---------------`)
+        //console.log(`---------'${index}'-----'${img_elem_keys.length}'-----------`)
+        switch_tab_dict = {
+          "img2img_invisible_img2img_image": "switch_to_img2img()",
+          "img2img_invisible_img2img_sketch": "switch_to_sketch()",
+          "img2img_invisible_img2maskimg": "switch_to_inpaint()",
+          "img2img_invisible_inpaint_sketch": "switch_to_inpaint_sketch()",
+          "img2img_invisible_img_inpaint_base": "state.utils.switch_to_img_inpaint()",
+          "img2img_invisible_img_inpaint_mask": "state.utils.switch_to_img_inpaint()",
+          "img2img_invisible_txt2img_controlnet_ControlNet_input_image": "state.utils.switch_to_txt2img_ControlNet(0)",
+          "img2img_invisible_img2img_controlnet_ControlNet_input_image": "state.utils.switch_to_img2img_ControlNet(0)"
+        }
+        
+        for (let i = 0; i < 10; i++) {
+          switch_tab_dict[`img2img_invisible_txt2img_controlnet_ControlNet-${i}_input_image`] = `state.utils.switch_to_txt2img_ControlNet(${i})`
+          switch_tab_dict[`img2img_invisible_img2img_controlnet_ControlNet-${i}_input_image`] = `state.utils.switch_to_img2img_ControlNet(${i})`
+        }
+
+        state.utils.sleep(300).then(() => {
+          try{
+            key = "img2img_invisible_"+img_elem_keys[index+1]
+            eval( switch_tab_dict[key] ) // 跳转界面
+            const button = gradioApp().getElementById(key);
+            button.click();
+          } catch (error) {
+            console.warn('[startImportImage]: Error:', error);
+            if(index+1 < img_elem_keys.length){
+              // 图片组件设置出错了，但是需要继续后续的流程
+              index = img_elem_keys.length-1
+            }
+          }
+        });
+      }
+
+      switch(index+1 - img_elem_keys.length){
+        case 0:// 图片导入完成，开始导入Dropdown
+          state.utils.sleep(500).then(() => {
+            try{
+              const button = gradioApp().getElementById("lightdiffusionflow_set_dropdowns");
+              button.click();
+            } catch (error) {
+              console.warn('[set_dropdowns]: Error:', error);
+            }
+          });
+          break
+        // case 1:// 触发了导入Dropdown，现在导入其他参数会卡死，触发导入按钮，等下一轮正式开始导入
+        //   state.utils.sleep(500).then(() => {
+        //     const button = gradioApp().getElementById("lightdiffusionflow_set_js_params");
+        //     console.log("lightdiffusionflow_set_js_params")
+        //     button.click();
+        //   });
+        //   break
+        // case 2:// 导入其他参数
+        //   state.utils.sleep(500).then(() => {
+        //     console.log("导入其他参数")
+        //     actions.applyState();
+        //   });
+        //   break
+      }
+    },
+    preset_output_log: function (preset, key="", value=""){
+      fetch(`/lightdiffusionflow/local/preset_output_log?preset=${preset}&key=${key}&value=${value}`).then(() => {
+        gradioApp().getElementById("img2img_invisible_refresh_log").click();
+      });
+    },
+    output_log: function (msg, msg_style=""){
+      fetch(`/lightdiffusionflow/local/output_log?msg=${msg}&style=${msg_style}`).then(() => {
+        gradioApp().getElementById("img2img_invisible_refresh_log").click();
+      });
+    },
+    output_warning: function (msg, msg_style="color:Orange;"){
+      actions.output_log(msg,msg_style)
+    },
+    output_error: function (msg, msg_style="color:Red;"){
+      actions.output_log(msg,msg_style)
+    },
+    get_sd_version: function (){
+      return sd_versions
+    }
+  };
+
+  return { init, actions };
+}());

gf/LightDiffusionFlow/javascript/state.ext.general.js

@@ -0,0 +1,501 @@
+window.state = window.state || {};
+window.state.extensions = window.state.extensions || {};
+state = window.state;
+
+function general_ext(tab_name, extension_name, root_container) {
+
+  let container = root_container;
+  let store = null;
+  let cnTabs = [];
+  let root_not_tabs = null;
+  let cur_tab_name = tab_name;
+  let ext_name = extension_name
+  let LS_PREFIX = 'ext-'+ ext_name.replace(" ","-").toLowerCase() + "-"
+
+  function handleToggle(addEvtLsner=true) {
+    let value = store.get('toggled');
+    let toggleBtn = container.querySelector('div.cursor-pointer, .label-wrap');
+    //for(let toggleBtn of toggleBtns){
+    //if(!toggleBtn){continue}
+    if(toggleBtn && toggleBtn.className.split(' ').pop() != "open"){
+      if (value && value === 'true') {
+        state.utils.triggerEvent(toggleBtn, 'click');
+        //load();
+      }
+
+      if(addEvtLsner)
+      {
+        toggleBtn.addEventListener('click', function () {
+          let span = this.querySelector('.transition, .icon');
+          store.set('toggled', span.style.transform !== 'rotate(90deg)');
+          //load();
+        });
+      }
+    }
+    //}
+  }
+
+  function bindTabEvents(addEvtLsner=true) {
+    const tabs = container.querySelectorAll('.tabs > div > button');
+    if(addEvtLsner)
+    {
+      tabs.forEach(tab => { // dirty hack here
+        tab.removeEventListener('click', onTabClick);
+        tab.addEventListener('click', onTabClick);
+      });
+    }
+    return tabs;
+  }
+
+  function handleTabs(addEvtLsner=true) {
+    let tabs = bindTabEvents(addEvtLsner);
+    let value = store.get('tab');
+    if (value) {
+      for (var i = 0; i < tabs.length; i++) {
+        let translations = state.utils.reverseTranslation(tabs[i].textContent)
+        if (value in translations) {
+        //if (tabs[i].textContent === value) {
+          state.utils.triggerEvent(tabs[i], 'click');
+          break;
+        }
+      }
+    }
+  }
+
+  function onTabClick() {
+    store.set('tab', state.utils.reverseTranslation(this.textContent)[0]);
+    bindTabEvents();
+  }
+
+  function handleCheckbox(checkbox, store, addEvtLsner=true) {
+    let label = checkbox.nextElementSibling;
+    let translations = state.utils.reverseTranslation(label.textContent)
+    for (var text of translations){
+      var id = state.utils.txtToId(text);
+      var value = store.get(id);
+      if (value) {break}
+    }
+    if (value) {
+      state.utils.setValue(checkbox, value, 'change');
+    }
+
+    if(addEvtLsner){
+      checkbox.addEventListener('change', function () {
+        let label = checkbox.nextElementSibling;
+        let translations = state.utils.reverseTranslation(label.textContent)
+        for (var text of translations){
+          var id = state.utils.txtToId(text);
+          store.set(id, this.checked);
+        }
+      });
+    }
+  }
+  function handleCheckboxes(addEvtLsner=true) {
+    let root_checkboxes = root_not_tabs.container.querySelectorAll('input[type="checkbox"]');
+    root_checkboxes.forEach(function (root_checkbox) {
+      if(cnTabs.length == 0){
+        handleCheckbox(root_checkbox, root_not_tabs.store, addEvtLsner)
+      }
+      else{
+        let needsHandle = true
+        for(let tab of cnTabs){
+          if(tab.container.contains(root_checkbox)){
+            needsHandle = false
+            break
+          }
+        }
+        if(needsHandle){handleCheckbox(root_checkbox, root_not_tabs.store, addEvtLsner)}
+      } // else
+    });
+    
+    cnTabs.forEach(({ container, store }) => {
+      let checkboxes = container.querySelectorAll('input[type="checkbox"]');
+      checkboxes.forEach(function (checkbox) {
+        handleCheckbox(checkbox, store, addEvtLsner)
+      });
+    });
+
+  }
+
+  function handleTextArea(textarea, index, store, addEvtLsner=true) {
+    var id = state.utils.txtToId(`textarea_${index}`);
+    var value = store.get(id);
+    if (value) {
+      state.utils.setValue(textarea, value, 'change');
+    }
+
+    if(addEvtLsner){
+      textarea.addEventListener('change', function () {
+        let text = this.value;
+        store.set(id, text);
+        //console.log(`id = ${id}  value = ${text}`)
+      });
+    }
+  }
+  function handleTextAreas(addEvtLsner=true) {
+    let textArea_index = 0; // 因为文本框的顺序不会变，所以命名直接使用序号区分 "textarea_0"
+    
+    let root_textareas = root_not_tabs.container.querySelectorAll('textarea');
+    root_textareas.forEach(function (root_textarea) {
+    
+      if(cnTabs.length == 0){
+        handleTextArea(root_textarea, textArea_index, root_not_tabs.store, addEvtLsner)
+        textArea_index += 1
+      }
+      else{
+        let needsHandle = true
+        for(let tab of cnTabs){
+          if(tab.container.contains(root_textarea)){
+            needsHandle = false
+            break
+          }
+        }
+        if(needsHandle){
+          handleTextArea(root_textarea, textArea_index, root_not_tabs.store, addEvtLsner)
+          textArea_index += 1
+        }
+      } // else
+
+    });
+
+    cnTabs.forEach(({ container, store }) => {
+      container.querySelectorAll('textarea').forEach(textarea => {
+        handleTextArea(textarea, textArea_index, store, addEvtLsner)
+        textArea_index += 1
+      });
+    });
+
+  }
+
+  function handleSelect(select, store, addEvtLsner=true) {
+    let translations = state.utils.reverseTranslation(select.querySelector('label').firstChild.textContent)
+    for (var text of translations){
+      var id = state.utils.txtToId(text);
+      var value = store.get(id);
+      if (value) {break}
+    }
+    //id = state.utils.txtToId(translations[0]);
+    //if (value) { //前面不需要判断是否有值，因为需要执行handleSelect绑定onchange事件
+    state.utils.handleSelect(select, id, store, force=true, addEvtLsner);
+    //}
+
+    // let id = state.constants.LS_PREFIX+LS_PREFIX+"dropdown_"+index
+    // state.utils.onContentChange(select, function (el) {
+    //   console.log(`onContentChange ${id}`)
+    //   let selected = el.querySelector('span.single-select');
+    //   if (selected) {
+    //     store.setWithNoPrefix(id, selected.textContent);
+    //   } else {
+    //     // new gradio version...
+    //     let input = el.querySelector('input');
+    //     if (input) {
+    //       store.setWithNoPrefix(id, input.value);
+    //     }
+    //   }
+    // });
+
+    if (id === 'preprocessor' && value && value.toLowerCase() !== 'none') {
+      state.utils.onNextUiUpdates(handleSliders); // update new sliders if needed
+    }
+  }
+  function handleSelects(addEvtLsner=true) {
+    // let root_selects = root_not_tabs.container.querySelectorAll('.gradio-dropdown');
+    // root_selects.forEach(function (root_select) {
+    //   if(cnTabs.length == 0){
+    //     handleSelect(root_select, global_dropdown_index[ext_name], root_not_tabs.store)
+    //     global_dropdown_index[ext_name] += 1
+    //     console.log(`global_dropdown_index = ${global_dropdown_index[ext_name]}`)
+    //   }
+    //   else{
+    //     let needsHandle = true
+    //     for(let tab of cnTabs){
+    //       if(tab.container.contains(root_select)){
+    //         needsHandle = false
+    //         break
+    //       }
+    //     }
+    //     if(needsHandle){
+    //       handleSelect(root_select, global_dropdown_index[ext_name], root_not_tabs.store)
+    //       global_dropdown_index[ext_name] += 1
+    //       console.log(`global_dropdown_index = ${global_dropdown_index[ext_name]}`)
+    //     }
+    //   } // else
+    // });
+
+    // cnTabs.forEach(({ container, store }) => {
+    //   container.querySelectorAll('.gradio-dropdown').forEach(select => {
+    //     handleSelect(select, global_dropdown_index[ext_name], store)
+    //     global_dropdown_index[ext_name] += 1
+    //     console.log(`global_dropdown_index = ${global_dropdown_index[ext_name]}`)
+    //   });
+    // });
+
+    let root_selects = root_not_tabs.container.querySelectorAll('.gradio-dropdown');
+    root_selects.forEach(function (root_select) {
+      if(cnTabs.length == 0){
+        handleSelect(root_select, root_not_tabs.store, addEvtLsner)
+      }
+      else{
+        let needsHandle = true
+        for(let tab of cnTabs){
+          if(tab.container.contains(root_select)){
+            needsHandle = false
+            break
+          }
+        }
+        if(needsHandle){handleSelect(root_select, root_not_tabs.store, addEvtLsner)}
+      } // else
+    });
+
+    cnTabs.forEach(({ container, store }) => {
+      container.querySelectorAll('.gradio-dropdown').forEach(select => {
+        handleSelect(select, store, addEvtLsner)
+      });
+    });
+
+  }
+
+  function handleSlider(slider, store, addEvtLsner=true) {
+    let label = slider.previousElementSibling.querySelector('label span');
+    let translations = state.utils.reverseTranslation(label.textContent)
+    for (var text of translations){
+      var id = state.utils.txtToId(text);
+      var value = store.get(id);
+      if (value) {break}
+    }
+    if (value) {
+      state.utils.setValue(slider, value, 'change');
+    }
+    if(addEvtLsner){
+      slider.addEventListener('change', function () {
+        //store.set(id, state.utils.reverseTranslation(this.value)[0]);
+        let label = slider.previousElementSibling.querySelector('label span');
+        let translations = state.utils.reverseTranslation(label.textContent)
+        for (var text of translations){
+          var id = state.utils.txtToId(text);
+          store.set(id, state.utils.reverseTranslation(this.value)[0]);
+        }
+      });
+    }
+  }
+  function handleSliders(addEvtLsner=true) {
+
+    let root_sliders = root_not_tabs.container.querySelectorAll('input[type="range"]');
+    root_sliders.forEach(function (root_slider) {
+      if(cnTabs.length == 0){
+        handleSlider(root_slider, root_not_tabs.store, addEvtLsner)
+      }
+      else{
+        let needsHandle = true
+        for(let tab of cnTabs){
+          if(tab.container.contains(root_slider)){
+            needsHandle = false
+            break
+          }
+        }
+        if(needsHandle){handleSlider(root_slider, root_not_tabs.store, addEvtLsner)}
+      } // else
+    });
+
+    cnTabs.forEach(({ container, store }) => {
+      let sliders = container.querySelectorAll('input[type="range"]');
+      sliders.forEach(function (slider) {
+        handleSlider(slider, store, addEvtLsner)
+      });
+    });
+  }
+
+  function handleRadioButton(fieldset, store, addEvtLsner=true) {
+    let label = fieldset.firstChild.nextElementSibling;
+    let radios = fieldset.querySelectorAll('input[type="radio"]');
+    let translations = state.utils.reverseTranslation(label.textContent)
+    for (var text of translations){
+      var id = state.utils.txtToId(text);
+      var value = store.get(id);
+      if (value) {break}
+    }
+    if (value) {
+      radios.forEach(function (radio) {
+        state.utils.setValue(radio, value, 'change');
+      });
+    }
+
+    if(addEvtLsner){
+      radios.forEach(function (radio) {
+        radio.addEventListener('change', function () {
+          let label = fieldset.firstChild.nextElementSibling;
+          let translations = state.utils.reverseTranslation(label.textContent)
+          for (var text of translations){
+            var id = state.utils.txtToId(text);
+            store.set(id, state.utils.reverseTranslation(this.value)[0]);
+          }
+        });
+      });
+    }
+  }
+  function handleRadioButtons(addEvtLsner=true) {
+
+    let root_fieldsets = root_not_tabs.container.querySelectorAll('fieldset');
+    root_fieldsets.forEach(function (root_fieldset) {
+      if(cnTabs.length == 0){
+        handleRadioButton(root_fieldset, root_not_tabs.store, addEvtLsner)
+      }
+      else{
+        let needsHandle = true
+        for(let tab of cnTabs){
+          if(tab.container.contains(root_fieldset)){
+            needsHandle = false
+            break
+          }
+        }
+        if(needsHandle){handleRadioButton(root_fieldset, root_not_tabs.store, addEvtLsner)}
+      } // else
+    });
+
+    cnTabs.forEach(({ container, store }) => {
+      let fieldsets = container.querySelectorAll('fieldset');
+      fieldsets.forEach(function (fieldset) {
+        handleRadioButton(fieldset, store, addEvtLsner)
+      });
+    });
+  }
+
+
+  function load(addEvtLsner=true) {
+    setTimeout(function () {
+      handleTabs(addEvtLsner);
+      handleCheckboxes(addEvtLsner);
+      handleTextAreas(addEvtLsner);
+      if(state.utils.target_is_newer_version(state.core.actions.get_sd_version(), "v1.6.0")){
+        //console.log("-----------general handleSelects-------")
+        handleSelects(addEvtLsner);
+      }
+      handleSliders(addEvtLsner);
+      handleRadioButtons(addEvtLsner);
+    }, 500);
+  }
+
+  function init(addEvtLsner=true) {
+
+    store = new state.Store(LS_PREFIX + cur_tab_name);
+
+    if (! container) {
+      return;
+    }
+
+    let tabnav = container.getElementsByClassName('tabs');
+    let tabs = []
+    if(tabnav.length > 0 ){
+      tabs = Array.from(tabnav[0].childNodes).filter(item => item.className && item.className.indexOf("tabitem") !== -1)
+    }
+    
+    cnTabs = [];
+    if (tabs.length) {
+      tabs.forEach((tabContainer, i) => {
+        cnTabs.push({
+          container: tabContainer,
+          store: new state.Store(LS_PREFIX + cur_tab_name + "_" + i)
+        });
+      });
+    }
+    //else {
+    root_not_tabs = {
+      container: container,
+      store: new state.Store(LS_PREFIX + cur_tab_name)
+    }
+    //}
+
+    handleToggle(addEvtLsner);
+    load(addEvtLsner);
+  }
+  return { init,LS_PREFIX };
+}
+
+
+function general_ext_main(tab){
+
+  let cur_tab_name = tab
+  let general_ext_list = []
+  // 遍历第一级子节点  每个节点选出一个层级最小且innerText不为空的子节点
+  function walks_element(element, cur_gen){
+    if(element.innerText != "" && element.innerText != undefined && element.children.length == 0){
+      return [[element.innerText,cur_gen]]
+    }
+    let res = []
+    for(child of element.children){
+      res = res.concat(walks_element(child,cur_gen+1,res))
+    }
+
+    return res
+  }
+
+  function init(core_mode = true, addEvtLsner=true) {
+    console.log(`------------${cur_tab_name}----init--- addEvtLsner=${addEvtLsner} ----`)
+
+    if(addEvtLsner==false)
+    {
+      for (let obj of general_ext_list)
+      {
+        obj.init(addEvtLsner);
+      }
+      return
+    }
+
+    let container = gradioApp().getElementById(cur_tab_name+'_script_container'); // main container
+
+    let extensions_root = container.children
+    if(extensions_root.length > 0 && extensions_root[0].className.split(' ')[0] != "gr-group" && extensions_root[0].className.split(' ')[0] != "gradio-group"){
+      extensions_root = extensions_root[0].children // webui v1.6.0 版本，UI结构有变更
+    }
+    //console.log(extensions_root)
+    for (child of extensions_root){
+      let root_container = child
+      res = walks_element(child, 0)
+      let min_gen = 99
+      let title = undefined
+      for(pair of res){
+        if(pair[1] < min_gen){
+          min_gen = pair[1]
+          title = pair[0]
+        }
+      }
+      
+      if(title == undefined 
+        || title.toLowerCase() == "lightdiffusionflow" // 自己存自己就不用了
+      ){continue}
+
+      let translations = state.utils.reverseTranslation(title)
+      title = translations[0] // 标题翻译一般只会有一个？
+      if(title.toLowerCase() == 'script'){break} // script后面的面板暂时不考虑
+      console.log(title)
+      
+      reg = /(.+) v[0-9\.]+/
+      if(reg.test(title)){title = RegExp.$1} // 匹配 xxx v0.0.0 格式的标题，把后半部分的版本号去掉
+
+      if(title == "ControlNet"){title = "Control Net"} // 兼容旧命名
+      else{
+        if(core_mode){continue}
+      }
+      
+      let ext_name = title.replace(" ","-").toLowerCase()
+      console.log(ext_name)
+      
+      // if(!global_dropdown_index[ext_name]){
+      //   global_dropdown_index[ext_name] = 0
+      // }
+      general_ext_obj = general_ext(cur_tab_name, ext_name, root_container)
+      general_ext_list.push(general_ext_obj)
+      general_ext_obj.init(addEvtLsner);
+    }
+    
+  }
+  return {init}
+}
+
+//global_dropdown_index = {} // py里是不分txt2img和img2img的，但是这里是需要区分的。。
+
+const TABS = ['txt2img', 'img2img'];
+for (tab of TABS){
+  state.extensions[`${tab}-ext-general`] = general_ext_main(tab);
+}
+

gf/LightDiffusionFlow/javascript/state.store.js

@@ -0,0 +1,60 @@
+window.state = window.state || {};
+state = window.state;
+
+state.Store = function Store (prefix) {
+  this.prefix = state.constants.LS_PREFIX + (prefix ? prefix + '-' : '');
+}
+
+state.Store.prototype.setWithNoPrefix = function (key, value) {
+    localStorage.setItem(key, value);
+};
+
+state.Store.prototype.set = function (key, value) {
+  if (key.startsWith(this.prefix)) {
+    localStorage.setItem(key, value);
+  } else {
+    localStorage.setItem(this.prefix + key, value);
+  }
+};
+
+state.Store.prototype.get = function (key) {
+  return localStorage.getItem(this.prefix + key);
+};
+
+state.Store.prototype.remove = function (key) {
+  localStorage.removeItem(this.prefix + key);
+};
+
+state.Store.prototype.clear = function () {
+  localStorage.clear();
+};
+
+state.Store.prototype.clearAll = function () {
+  let keys = Object.keys(localStorage);
+  for (let i = 0; i < keys.length; i++) {
+    if (keys[i].startsWith(state.constants.LS_PREFIX)) {
+      localStorage.removeItem(keys[i]);
+    }
+  }
+};
+
+state.Store.prototype.getAll = function () {
+  let result = {};
+  let keys = Object.keys(localStorage);
+  for (let i = 0; i < keys.length; i++) {
+    if (keys[i].startsWith(state.constants.LS_PREFIX)) {
+      result[keys[i]] = localStorage[keys[i]];
+    }
+  }
+  return result;
+};
+
+state.Store.prototype.load = function (json) {
+  this.clearAll();
+  let keys = Object.keys(json);
+  for (let i = 0; i < keys.length; i++) {
+    if (keys[i].startsWith(state.constants.LS_PREFIX)) {
+      this.set(keys[i], json[keys[i]]);
+    }
+  }
+};

gf/LightDiffusionFlow/javascript/state.utils.js

@@ -0,0 +1,684 @@
+window.state = window.state || {};
+state = window.state;
+let selectingQueue = 0; // 默认都延时一下再开始触发
+
+state.utils = {
+
+  testFunction: function testFunction() {
+    //console.log(state.extensions)
+    // const button = gradioApp().getElementById("lightdiffusionflow_set_elements");
+    // button.click();    
+    value = "新建文件夹\\anything-v5-PrtRE.safetensors"
+    value = value.replace("/","\\")
+    parts = value.split("\\")
+    console.log(parts[parts.length - 1])
+  },
+
+  target_is_newer_version: function(cur_version, target_version){
+
+    let cur = cur_version.replace("v","")
+    cur = cur.split(".")
+
+    let target = target_version.replace("v","")
+    target = target.split(".")
+    let version_len = Math.min(cur.length, target.length)
+
+    // 逐个版本号比较  v1.2.3 和 v1.2比较时，只比较前面两个数字
+    for (let i=0; i < version_len; i++){
+      if(Number(cur[i]) > Number(target[i])){
+        return false
+      }
+      else if(Number(cur[i]) < Number(target[i])){
+        return true
+      }
+    }
+
+    // 前面的版本号一样，再看谁的版本号更长
+    if(cur.length >= target.length){
+      return false
+    }
+
+    return true
+  },
+
+  searchCheckPointByHash: async function searchCheckPointByHash(hash){
+    let downloadUrl = undefined
+    hash_str = hash.replace("[","").replace("]","").replace(/^\s+|\s+$/g,"")
+    await fetch("https://civitai.com/api/v1/model-versions/by-hash/"+hash_str)
+    .then(response => response.json())
+    .then(data => {
+      //try{
+        //console.log(data["files"])
+        for (file of data["files"]){
+          for (key of Object.keys(file["hashes"])){
+            if(file["hashes"][key].toLowerCase() === hash_str.toLowerCase())
+            {
+              downloadUrl = file["downloadUrl"]
+              console.log(downloadUrl)
+              break
+            }
+          }
+        }
+        if(downloadUrl == undefined){downloadUrl = data["files"][0]["downloadUrl"]}
+      //} catch (error) {}
+    }).catch(function(e) {
+      console.log("search model error!");
+    });
+
+    return downloadUrl
+  },
+
+  getTranslation: function getTranslation(key){
+    new_key = key
+    try{
+      if(window.localization[new_key.replace(/^\s+|\s+$/g,"")] != undefined){
+        new_key = window.localization[new_key]
+      }
+    } catch (error) {
+      console.warn('getTranslation error:', error);
+    }
+    return new_key
+  },
+
+  reverseTranslation: function reverseTranslation(key){
+    new_key = []
+    try{
+      //key=key.replace(/^\s+|\s+$/g,"");
+      for (localize_key of Object.keys(window.localization)) {
+        if(key.replace(/^\s+|\s+$/g,"") === window.localization[localize_key].replace(/^\s+|\s+$/g,"")){ 
+          tmp_key = localize_key
+          new_key.push(tmp_key)
+          //break
+        }
+      }
+    } catch (error) {
+      console.warn('reverseTranslation error:', error);
+    }
+
+    if(new_key.length == 0){new_key.push(key)}
+    //console.log(`---------reverseTranslation---------${key}---------`)
+    //console.log(new_key)
+    return new_key
+  },
+
+  sleep: function sleep(time) {
+    return new Promise((resolve) => setTimeout(resolve, time));
+  },
+
+  switch_to_img_inpaint: function switch_to_img_inpaint() {
+    switch_to_img2img_tab(4);
+    return Array.from(arguments);
+  },
+  switch_to_txt2img_ControlNet: function switch_to_txt2img_ControlNet(unit) {
+
+    switch_to_txt2img()
+
+    let elem = undefined
+    elem = gradioApp().getElementById('txt2img_controlnet')
+    elem = elem.querySelector("#controlnet")
+
+    try{
+      if(elem.className.split(' ').pop() != "open"){
+        state.utils.triggerMouseEvent(elem, 'click')
+      }
+      for(e of elem.children){
+        if(e.className.split(' ').pop() != "open"){
+          state.utils.triggerMouseEvent(e, 'click')
+        }
+      }
+    } catch(error){console.log(error)}
+
+    try{
+      gradioApp().getElementById('txt2img_controlnet_tabs').querySelectorAll('button')[Number(unit)].click()
+    } catch (error) {
+      console.warn('[switch_to_txt2img_ControlNet]: Error:', error);
+    }
+  },
+  switch_to_img2img_ControlNet: function switch_to_img2img_ControlNet(unit) {
+    
+    switch_to_img2img()
+    
+    let elem = undefined //gradioApp().getElementById('txt2img_controlnet').children[0].children[1]
+    elem = gradioApp().getElementById('img2img_controlnet')
+    elem = elem.querySelector("#controlnet")
+    
+    try{
+      if(elem.className.split(' ').pop() != "open"){
+        state.utils.triggerMouseEvent(elem, 'click')
+      }
+      for(e of elem.children){
+        if(e.className.split(' ').pop() != "open"){
+          state.utils.triggerMouseEvent(e, 'click')
+        }
+      }
+    } catch(error){console.log(error)}
+
+    try{
+      gradioApp().getElementById('img2img_controlnet_tabs').querySelectorAll('button')[Number(unit)].click()
+    } catch (error) {
+      console.warn('[switch_to_img2img_ControlNet]: Error:', error);
+    }
+  },
+  triggerEvent: function triggerEvent(element, event) {
+    if (! element) {
+      return;
+    }
+    element.dispatchEvent(new Event(event.trim()));
+    return element;
+  },
+  triggerMouseEvent: function triggerMouseEvent(element, event) {
+    if (! element) {
+      return;
+    }
+    event = event || 'click';
+    element.dispatchEvent(new MouseEvent(event, {
+      view: window,
+      bubbles: true,
+      cancelable: true,
+    }));
+    return element;
+  },
+  setValue: function setValue(element, value, event) {
+    switch (element.type) {
+      case 'checkbox':
+        element.checked = value === 'true';
+        this.triggerEvent(element, event);
+        break;
+      case 'radio':
+        if (element.value === value) {
+          element.checked = true;
+          this.triggerEvent(element, event);
+        }
+        else if(element.value == "Scribble/Sketch" && value == "Scribble"){
+          element.checked = true;
+          this.triggerEvent(element, event);
+        } 
+        else {
+          element.checked = false;
+        }
+        break;
+      default:
+        element.value = value;
+        this.triggerEvent(element, event);
+    }
+  },
+  onFrameContentChange: function onFrameContentChange(targetNode, func) {
+    if(targetNode) {
+      const observer = new MutationObserver((mutationsList, observer) => {
+        for (const mutation of mutationsList) {
+          if (mutation.type === 'childList' || 
+            (mutation.type === 'attributes' && mutation.attributeName == 'src') // 图片被更改
+          ) {
+            //console.log(`onFrameContentChange ${mutation.type} `)
+            func(targetNode);
+          }
+        }
+      });
+      observer.observe(targetNode, {
+        //attributes: true,
+        childList: true,
+        //characterData: true,
+        subtree: true
+      });
+    }
+  },
+
+  onContentChange: function onContentChange(targetNode, func) {
+    if(targetNode) {
+      const observer = new MutationObserver((mutationsList, observer) => {
+        for (const mutation of mutationsList) {
+          if (mutation.type === 'childList' || 
+            (mutation.type === 'attributes' && mutation.attributeName == 'src') // 图片被更改
+          ) {
+            func(targetNode);
+          }
+        }
+      });
+      observer.observe(targetNode, {
+        attributes: true,
+        childList: true,
+        characterData: true,
+        subtree: true
+      });
+    }
+  },
+
+  onAccordionChange: function onAccordionChange(targetNode, func) {
+    if(targetNode) {
+      const observer = new MutationObserver((mutationsList, observer) => {
+        for (const mutation of mutationsList) {
+          if (mutation.type === 'attributes' ) {
+            func(targetNode);
+          }
+        }
+      });
+      observer.observe(targetNode, {
+        attributes: true,
+      });
+    }
+  },
+
+  getCurSeed: function getCurSeed(tab) {
+    const elements = gradioApp().getElementById(`html_info_${tab}`).querySelectorAll(`#html_info_${tab}`);
+    if (! elements || ! elements.length || !elements[0].innerText) {
+      return undefined;
+    }
+    seed = undefined
+    values = elements[0].innerText.split(',')
+    for (value of values){
+      pair = value.split(':')
+      if(pair[0].replace(/^\s+|\s+$/g,"") == 'Seed'){
+        seed = pair[1].replace(/^\s+|\s+$/g,"")
+      }
+    }
+    return seed
+  },
+
+  handleImage: function handleImage(select, id, store, addEvtLsner=true) {
+    if(addEvtLsner){
+      setTimeout(() => {
+        state.utils.onContentChange(select, function (el) {
+          
+          let data = {
+            method: 'POST',
+            headers: { 'Content-Type': 'application/json' },
+            body: JSON.stringify({
+              "id":id,
+              "img":""
+            })
+          }
+          
+          try {
+            // new gradio version...
+            let img = el.querySelector('img');
+            if (img) {
+              data.body = JSON.stringify({
+                "id":id,
+                "img":img.src
+              })
+            }
+          } catch (error) {
+            console.warn('[state]: Error:', error);
+          }
+          //console.log(`image changed ${id}`)
+          fetch(`/lightdiffusionflow/local/imgs_callback`, data)
+        });
+      }, 150);
+    }
+  },
+
+  clearImage: function clearImage(select) {
+    try {
+      if(select){
+        
+        let buttons = select.querySelectorAll('button');
+        buttons.forEach(button => {
+          if(button.getAttribute("aria-label") == "Clear"){
+            button.click();
+            //state.utils.triggerMouseEvent(button, 'mousedown');
+          }
+        });
+        
+      }
+    } catch (error) {
+      console.warn('[state]: Error:', error);
+    }
+  },
+  // handleSelect: function handleSelect(select, id, store) {
+  //   try {
+  //     let value = store.get(id);
+  //     if (value) {
+        
+  //       let input = select.querySelector('input');
+  //       state.utils.triggerMouseEvent(input, 'focus');
+        
+  //       setTimeout(() => {
+  //         let items = Array.from(select.querySelectorAll('ul li'));
+  //         for (li of items){
+  //           if (li.lastChild.wholeText.trim() === value) {
+  //             state.utils.triggerMouseEvent(li, 'mousedown');
+  //             //return false;
+  //             break
+  //           }
+  //         }
+  //         state.utils.triggerMouseEvent(input, 'blur');
+  //       }, 100);
+  //     }
+
+  //     setTimeout(() => {
+  //       state.utils.onContentChange(select, function (el) {
+  //         let selected = el.querySelector('span.single-select');
+  //         if (selected) {
+  //           store.set(id, selected.textContent);
+  //         } else {
+  //           // new gradio version...
+  //           let input = select.querySelector('input');
+  //           if (input) {
+  //             store.set(id, input.value);
+  //           }
+  //         }
+  //       });
+  //     }, 150);
+  //   } catch (error) {
+  //     console.warn('[state]: Error:', error);
+  //   }
+  // },
+
+  forceSaveSelect: function forceSaveSelect(select, id, store) {
+    let selected = select.querySelector('span.single-select');
+    if (selected) {
+      store.set(id, selected.textContent);
+    } else {
+      // new gradio version...
+      let input = select.querySelector('input');
+      if (input) {
+        store.set(id, input.value);
+      }
+    }
+  },
+  handleAccordion: function handleAccordion(accordion, id, store, addEvtLsner=true){
+    try{
+      let value = store.get(id);
+      let child = accordion.querySelector('div.cursor-pointer, .label-wrap');
+      if (value) {
+        //for(child of children){
+        //let span = child.querySelector('.transition, .icon');
+        //if(span.style.transform !== 'rotate(90deg)'){
+        if(child.className.split(' ').pop() != "open"){
+          state.utils.triggerMouseEvent(child, 'click')
+        }
+        //}
+      }
+
+      if(addEvtLsner){
+        setTimeout(() => {
+          state.utils.onAccordionChange(child, function (el) {
+            store.set(id, el.className.split(' ').pop() == "open");
+            //console.log(`accordion on change ${id}`)
+            //let span = el.querySelector('.transition, .icon');
+            //store.set(id, span.style.transform !== 'rotate(90deg)');
+          });
+        }, 150);
+      }
+    } catch (error) {
+      console.warn(`accordion:${accordion}, id:${id}`)
+      console.warn('[state]: Error:', error);
+    }
+  },
+  handleSelect: function handleSelect(select, id, store, force=false, addEvtLsner=true) {
+    try {
+
+      let value = store.get(id);
+      if ( value ) { //&& value != 'None'
+        value = value.replace("/","\\")
+        let parts = value.split("\\")
+        value = parts[parts.length - 1]
+
+        selectingQueue += 1;
+        setTimeout(() => {
+
+          let input = select.querySelector('input');
+          state.utils.triggerMouseEvent(input, 'focus');
+          setTimeout(() => {
+            let items = Array.from(select.querySelectorAll('ul li'));
+            let localized_value = this.getTranslation(value)
+            let successed = false
+            for (li of items){
+              // li.lastChild.wholeText.trim() === value
+              let option = li.lastChild.wholeText.trim().replace(/^\s+|\s+$/g,"")
+              option = option.replace("/","\\")
+              let parts = option.split("\\")
+              option = parts[parts.length - 1]
+              if (localized_value.replace(/^\s+|\s+$/g,"") === option) {
+                state.utils.triggerMouseEvent(li, 'mousedown');
+                successed = true
+                break
+              }
+            }
+
+            let hash_res = localized_value.match(/\[[0-9A-Fa-f]{8,10}\]/)
+            if(!successed){ // && hash_pos != -1 找不到对应选项 并且选项里有10位哈希值
+              for (li of items){
+                
+                // 去掉Hash比较
+                let text = li.lastChild.wholeText.trim()
+                text = text.replace("/","\\")
+                let parts = text.split("\\")
+                text = parts[parts.length - 1]
+                
+                let localized_value_no_hash = localized_value.replace(/\[[0-9A-Fa-f]{8,10}\]/,"").replace(/^\s+|\s+$/g,"")
+                let text_no_hash = text.replace(/\[[0-9A-Fa-f]{8,10}\]/, "").replace(/^\s+|\s+$/g,"")
+                
+                if (localized_value_no_hash === text_no_hash) {
+                  successed = true
+                }
+                
+                // 只比较Hash
+                if(!successed && hash_res != null){
+                  let hash_str = hash_res[0].replace(/^\s+|\s+$/g,"")
+                  let text_hash_res = text.match(/\[[0-9A-Fa-f]{8,10}\]/)
+                  if(text_hash_res != null){
+                    let text_hash = text_hash_res[0].replace(/^\s+|\s+$/g,"")
+                    if (hash_str === text_hash) {
+                      successed = true
+                    }
+                  }
+                }
+
+                if(successed){
+                  state.utils.triggerMouseEvent(li, 'mousedown');
+                  // state.core.actions.output_log(
+                  //   `Note: \'<b style="color:Orange;">${value}</b>\' not found. An approximate match \'<b style="color:Orange;">${li.lastChild.wholeText.trim()}</b>\' has been automatically selected as replacement.`
+                  // )
+                  state.core.actions.preset_output_log("alt_option", value, li.lastChild.wholeText.trim())
+                  break
+                }
+              }
+            }
+
+            if(!successed && items.length > 0) // 下拉框一个选项都没找到说明就没有这个下拉框，可能是界面设置把下拉框替换成了radio button
+            {
+              let option_name = store.prefix + id
+              if(option_name === "state-setting_sd_model_checkpoint"){
+                // 大模型找不到就只用warning提示，因为不影响运行
+                // state.core.actions.output_log(`Note: \'<b style="color:Orange;">${value}</b>\' not found.`)
+                state.core.actions.preset_output_log("no_option", "stable diffusion checkpoint", value)
+              }
+              else{
+                //state.core.actions.output_log(`Error: \'<b style="color:Red;">${option_name}</b>\' import failed! The option \'<b style="color:Red;">${value}</b>\' was not found!`)
+                state.core.actions.preset_output_log("no_option", option_name, value)
+              }
+              if(hash_res != null){
+                let model_name = value
+                let hash_str = hash_res[0]
+                state.utils.searchCheckPointByHash(hash_str).then( downloadUrl => {
+                  if(downloadUrl != undefined){
+                    // let warning_str = encodeURIComponent(`Click to download \
+                    // <a style ='text-decoration:underline;color:cornflowerblue;', href='${downloadUrl}'> ${model_name} </a>`)
+                    // state.core.actions.output_warning(warning_str)
+                    state.core.actions.preset_output_log("download_url", model_name, downloadUrl)
+                  }
+                });
+              }
+            }
+
+            state.utils.triggerMouseEvent(input, 'blur');
+            selectingQueue -= 1;
+            //console.log(`selectingQueue = ${selectingQueue}`)
+          }, 100);
+
+        }, selectingQueue * 200)
+      }
+
+      if(addEvtLsner)
+      {
+        setTimeout(() => {
+          state.utils.onContentChange(select, function (el) {
+            let selected = el.querySelector('span.single-select');
+            if(force){
+              let localized_id = state.utils.getTranslation(id)
+              let id_translations = state.utils.reverseTranslation(localized_id)
+              //宁可错存一千，也不漏存一个
+              for (trans_id of id_translations){
+                if (selected) {
+                  store.set(trans_id, selected.textContent);
+                } else {
+                  // new gradio version...
+                  let input = el.querySelector('input');
+                  if (input) {
+                    store.set(trans_id, input.value);
+                  }
+                }
+              }
+            }
+            else{
+              if (selected) {
+                store.set(id, selected.textContent);
+              } else {
+                // new gradio version...
+                let input = el.querySelector('input');
+                if (input) {
+                  store.set(id, input.value);
+                }
+              }
+            }
+          });
+        }, 150);
+    }
+    } catch (error) {
+      console.warn('[state]: Error:', error);
+    }
+  },
+  handleMultipleSelect: function handleMultipleSelect(select, id, store, addEvtLsner=true) {
+    try {
+      let value = store.get(id);
+
+      if (value) {
+
+        value = value.split(',').reverse();
+
+        if (value.length) {
+
+          let input = select.querySelector('input');
+
+          let selectOption = function () {
+
+            if (! value.length) {
+              state.utils.triggerMouseEvent(input, 'blur');
+              return;
+            }
+
+            let option = value.pop();
+            state.utils.triggerMouseEvent(input, 'focus');
+
+            setTimeout(() => {
+              let successed = false
+              let items = Array.from(select.querySelectorAll('ul li'));
+              items.forEach(li => {
+                if (li.lastChild.wholeText.trim() === option) {
+                  state.utils.triggerMouseEvent(li, 'mousedown');
+                  successed = true
+                  return false;
+                }
+              });
+              if(!successed){
+                state.core.actions.preset_output_log("no_option", store.prefix + id, value)
+                //state.core.actions.output_log(`Error: \'<b style="color:Red;">${store.prefix + id}</b>\' import failed! The option \'<b style="color:Red;">${value}</b>\' was not found!`)
+              }
+              setTimeout(selectOption, 100);
+            }, 100);
+          }
+          selectOption();
+        }
+      }
+
+      if(addEvtLsner){
+        state.utils.onContentChange(select, function (el) {
+          const selected = Array.from(el.querySelectorAll('.token > span')).map(item => item.textContent);
+          store.set(id, selected);
+        });
+      }
+    } catch (error) {
+      console.warn('[state]: Error:', error);
+    }
+  },
+  txtToId: function txtToId(txt) {
+    return txt.split(' ').join('-').toLowerCase();
+  },
+  callXTimes: function callXTimes(func, times) {
+    let called = 0;
+    return function() {
+      if (called < times) {
+        called++;
+        return func.apply(this);
+      }
+    }
+  },
+  saveFile: function saveJSON(fileName ,data) {
+    const json = JSON.stringify(data, null, 4);
+    const blob = new Blob([json], {type: 'application/json'});
+    const url = URL.createObjectURL(blob);
+    console.log(url)
+    const link = document.createElement('a');
+    link.href = url;
+    link.download = fileName;
+
+    document.body.appendChild(link);
+    link.click();
+    link.parentNode.removeChild(link);
+  },
+  debounce: function debounce(func, delay) {
+    let lastCallTime = 0;
+    return function() {
+      const currentCallTime = new Date().getTime();
+      if (currentCallTime - lastCallTime > delay) {
+        lastCallTime = currentCallTime;
+        func.apply(this, arguments);
+      }
+    }
+  },
+  onNextUiUpdates: function (func) {
+    // brute force this to to ensure that the method is called after next few updates
+    onUiUpdate(this.callXTimes(function () { setTimeout(func, 5); }, 150));
+  }
+};
+
+state.utils.html = {
+  setStyle: function setStyle(elements, style) {
+    if (elements instanceof NodeList) {
+      elements = Array.from(elements);
+    } else if (elements instanceof Node){
+      elements = [elements];
+    } else {
+      return;
+    }
+    elements.forEach(element => {
+      for (let key in style) {
+        if (style.hasOwnProperty(key)) {
+          element.style[key] = style[key];
+        }
+      }
+    });
+  },
+  create: function create(type, props, style) {
+    const element = document.createElement(type);
+    if (props) {
+      for (let key in props) {
+        if (props.hasOwnProperty(key)) {
+          element[key] = props[key];
+        }
+      }
+    }
+    if (style) {
+      this.setStyle(element, style);
+    }
+    return element;
+  },
+  createButton: function createButton(text, onclick) {
+    const btn = document.createElement('button');
+    btn.innerHTML = text;
+    btn.onclick = onclick || function () {};
+    btn.className = 'gr-button gr-button-lg gr-button-primary';
+    return btn;
+  }
+};

gf/LightDiffusionFlow/preload.py

@@ -0,0 +1,4 @@
+import argparse
+
+def preload(parser: argparse.ArgumentParser):
+  parser.add_argument("--local-flows-path", type=str, default="models/LightDiffusionFlow", help="Path to save flow files.")

gf/LightDiffusionFlow/scripts/lightdiffusionflow_config.py

@@ -0,0 +1,320 @@
+import json,os
+from modules.paths_internal import data_path
+
+PNGINFO_2_LIGHTDIFFUSIONFLOW = {}
+PNGINFO_CN_2_LIGHTDIFFUSIONFLOW = {}
+Image_Components_Key = {}
+LoRAs_In_Use = "loras_in_use"
+Flow_Save_mode = "All"
+Auto_Fix_Params = True
+Local_Flows_Path = "models/LightDiffusionFlow"
+
+class OutputPrompt_English:
+
+  def startimport():
+    return "<hr style='margin-top:10px;margin-bottom:10px'></hr><b style='color:LimeGreen;'>Start parsing settings...</b>"
+
+  def invalid_file():
+    return "<b style='color:Red;'>Please select a valid lightdiffusionflow or image file!</b>"
+
+  def importing_image(image_name):
+    return f"<b style='color:LimeGreen;'>Importing image: '{image_name}'.</b>"
+
+  def import_completed():
+    return "<b style='color:LimeGreen;'>Import Completed!</b>"
+
+  def import_completed_info():
+    return "Import Completed!"
+  
+  def save_completed():
+    return "<b style='color:LimeGreen;'>Save Completed!</b>"
+
+  def save_failed():
+    return "<b style='color:Red;'>Save Failed!</b>"
+
+  def alternative_option(target_value, new_value):
+    return f'''Note: '<b style='color:Orange;'>{target_value}</b>' not found,<br>\
+      An approximate match '<b style='color:Orange;'>{new_value}</b>' has been automatically selected as replacement.'''
+
+  def no_option(option_name, value):
+    return f'''Error: '<b style='color:Red;'>{option_name}</b>' import failed!<br>\
+    The option '<b style='color:Red;'>{value}</b>' was not found!'''
+
+  def missing_extensions(ext_list:[]):
+    if(Flow_Save_mode == "Core"):
+      error_str = "Note:  <b style='color:Orange;'>The current flow file contains parameters for other plugins:</b></p>"
+      for ext in ext_list:
+        error_str+="<p>- <b style='color:Orange;'>"+ext+"</b></p> "
+      error_str+="<b style='color:Orange;'>You can switch to 'ALL' mode to load more parameters. (This prompt is for reference only, please choose the plugin mode according to the actual situation.)</b></p> "
+    else:
+      error_str = "Note: <b style='color:Orange;'>Found missing extensions.</b></p>"
+      for ext in ext_list:
+        error_str+="<p>- <b style='color:Orange;'>"+ext+"</b></p> "
+      error_str+="<b style='color:Orange;'>The above Extension Missing Reminder is for reference only. Please determine the necessary plugins based on your actual needs and specific conditions.</b></p> "
+    return error_str
+
+  def missing_loras(loras_list:[]):
+    error_str = "Note: <b style='color:Orange;'>Found missing LoRAs.</b></p>"
+    for lora in loras_list:
+      error_str+="<p>- <b style='color:Orange;'>"+lora+"</b></p> "
+    return error_str
+
+  def click_to_download(file_name, file_url):
+    return f'''<p style="color:Orange;">Click to download \
+    <a style ='text-decoration:underline;color:cornflowerblue;', target="_blank", href='{file_url}'> {file_name} </a>
+    '''
+
+  def download_link(file_name, file_url):
+    return f'''<a style ='text-decoration:underline;color:cornflowerblue;', target="_blank", href='{file_url}'> {file_name} </a>'''
+
+  def note_for_save_mode():
+    return "Core mode only supports basic parameters for Text-to-Image and Image-to-Image, along with ControlNet parameters. \
+The All mode, on the other hand, aims to support as many parameters as possible on the page, \
+but the downside is that it may occasionally cause the UI to freeze with an infinite loading circle."
+
+class OutputPrompt_Chinese:
+
+  def startimport():
+    return "<hr style='margin-top:10px;margin-bottom:10px'></hr><b style='color:LimeGreen;'>开始解析设置...</b>"
+
+  def invalid_file():
+    return "<b style='color:Red;'>请选择一个有效的flow文件，或者含png_info数据的图片!</b>"
+
+  def importing_image(image_name):
+    return f"<b style='color:LimeGreen;'>导入图片'{image_name}'...</b>"
+
+  def import_completed():
+    return "<b style='color:LimeGreen;'>导入完成!</b>"
+    
+  def import_completed_info():
+    return "导入完成！"
+
+  def save_completed():
+    return "<b style='color:LimeGreen;'>保存完毕！</b>"
+
+  def save_failed():
+    return "<b style='color:Red;'>保存失败！</b>"
+
+  def alternative_option(target_value, new_value):
+    return f'''注意: 未找到选项'<b style='color:Orange;'>{target_value}</b>',<br>\
+      已使用近似选项'<b style='color:Orange;'>{new_value}</b>'代替.'''
+
+  def no_option(option_name, value):
+    if(option_name == "stable diffusion checkpoint"):
+      return f'''未找到大模型'<b style='color:Orange;'>{value}</b>'!'''
+    clear_option_name = option_name.replace("state-ext-","")
+    return f'''错误: '<b style='color:Red;'>{clear_option_name}</b>'导入失败!<br>\
+    未找到选项'<b style='color:Red;'>{value}</b>'!'''
+
+  def missing_extensions(ext_list:[]):
+    global Flow_Save_mode
+    if(Flow_Save_mode == "Core"):
+      error_str = "注意, <b style='color:Orange;'>当前flow文件含有其他插件参数:</b></p>"
+      for ext in ext_list:
+        error_str+="<p>- <b style='color:Orange;'>"+ext+"</b></p> "
+      error_str+="<b style='color:Orange;'>可切换至'ALL'模式加载更多参数。（提示仅供参考，请根据实际情况选择插件模式。）</b></p> "
+    else:
+      error_str = "注意, <b style='color:Orange;'>发现缺失的插件:</b></p>"
+      for ext in ext_list:
+        error_str+="<p>- <b style='color:Orange;'>"+ext+"</b></p> "
+      error_str+="<b style='color:Orange;'>以上插件缺失提示仅供参考，请注意辨别实际情况下您所需要安装的插件。</b></p> "
+    return error_str
+
+  def missing_loras(loras_list:[]):
+    error_str = "注意, <b style='color:Orange;'>发现缺失的LoRA模型:</b></p>"
+    for lora in loras_list:
+      error_str+="<p>- <b style='color:Orange;'>"+lora+"</b></p> "
+    return error_str
+
+  def click_to_download(file_name, file_url):
+    name = file_name
+    if(name == "ControlNet Models"):
+      name = "常用ControlNet模型"
+      return f'''<p style="color:Orange;">点击下载 \
+      <a style ='text-decoration:underline;color:cornflowerblue;', target="_blank", href='https://pan.quark.cn/s/eafa2a9df949'> 常用ControlNet模型 </a>
+      '''
+
+    return f'''<p style="color:Orange;">点击下载 \
+    <a style ='text-decoration:underline;color:cornflowerblue;', target="_blank", href='{file_url}'> {name} </a>
+    '''
+
+  def download_link(file_name, file_url):
+    return f'''<a style ='text-decoration:underline;color:cornflowerblue;', target="_blank", href='{file_url}'> {file_name} </a>'''
+
+  def note_for_save_mode():
+    return "Core模式仅支持文生图和图生图的基本参数+ControlNet参数。All模式则会尽可能多的支持页面上的参数，但是缺点是有概率导致UI卡住，无限转圈。"
+
+
+OutputPrompt = OutputPrompt_English
+
+def create_local_flow_path():
+  global Local_Flows_Path
+  
+  if os.path.isabs(Local_Flows_Path):
+    flows_path = Local_Flows_Path
+  else:
+    flows_path = os.path.join(data_path, Local_Flows_Path) 
+  flows_path = flows_path.replace("\\","/") # linux下反斜杠有问题
+  #print(flows_path)
+  try:
+    if(not os.path.exists(flows_path)):
+      os.makedirs(flows_path)
+      if(os.path.exists(flows_path)):
+        print(f"本地文件夹'{flows_path}'创建成功！")
+      else:
+        print(f"本地文件夹'{flows_path}'创建失败！")
+  except BaseException as e:
+    pass
+  if(not os.path.exists(flows_path)):
+    print(f"The creation of the folder '{Local_Flows_Path}' has failed! Please create this folder manually to ensure the proper functioning of the extension.")
+    print(f"创建文件夹'{Local_Flows_Path}'失败！请手动创建该文件夹，以保证插件功能正常运行。")
+
+  Local_Flows_Path = flows_path
+
+
+# 改成函数调用，修改配置之后能及时刷新
+def init():
+  global PNGINFO_2_LIGHTDIFFUSIONFLOW,PNGINFO_CN_2_LIGHTDIFFUSIONFLOW
+  global OutputPrompt,Flow_Save_mode,Auto_Fix_Params,Local_Flows_Path,Image_Components_Key
+  # PNG Info的功能除了主要的选项以外其他的都靠第三方插件的主动支持，后续再考虑能否有优化的办法
+  #print(parameters_copypaste.paste_fields) 
+  PNGINFO_2_LIGHTDIFFUSIONFLOW = {
+    "Prompt": "state-txt2img_prompt",
+    "Negative prompt": "state-txt2img_neg_prompt",
+    "Steps": "state-txt2img_steps",
+    "Sampler": "state-txt2img_sampling",
+    "CFG scale": "state-txt2img_cfg_scale",
+    "Seed": "state-txt2img_seed",
+    "Face restoration": "state-txt2img_restore_faces",
+    "Size-1": "state-txt2img_width",
+    "Size-2": "state-txt2img_height",
+    "Model hash": "state-setting_sd_model_checkpoint",
+    "Denoising strength": "state-txt2img_denoising_strength",
+    "Hires upscale": "state-txt2img_hr_scale",
+    "Hires steps": "state-txt2img_hires_steps",
+    "Hires upscaler": "state-txt2img_hr_upscaler",
+    "Hires resize-1": "state-txt2img_hr_resize_x",
+    "Hires resize-2": "state-txt2img_hr_resize_y",
+    "Clip skip": "setting_CLIP_stop_at_last_layers",
+    "ENSD": "setting_eta_noise_seed_delta"
+  }
+
+  PNGINFO_CN_2_LIGHTDIFFUSIONFLOW = {
+    "Module": "state-ext-control-net-txt2img_0-preprocessor",
+    "preprocessor": "state-ext-control-net-txt2img_0-preprocessor",
+    "model": "state-ext-control-net-txt2img_0-model",
+    "weight": "state-ext-control-net-txt2img_0-control-weight",
+    "starting": "state-ext-control-net-txt2img_0-starting-control-step",
+    "ending": "state-ext-control-net-txt2img_0-guidance-end-(t)",
+    "guidance start": "state-ext-control-net-txt2img_0-starting-control-step",
+    "guidance end": "state-ext-control-net-txt2img_0-ending-control-step",
+    "resize mode": "state-ext-control-net-txt2img_0-resize-mode",
+    "pixel perfect": "state-ext-control-net-txt2img_0-pixel-perfect",
+    "control mode": "state-ext-control-net-txt2img_0-control-mode",
+    "preprocessor params": ""
+  }
+
+  try:
+    import modules.shared as shared
+    webui_settings = {}
+    with open(shared.cmd_opts.ui_settings_file, mode='r') as f:
+      json_str = f.read()
+      webui_settings = json.loads(json_str)
+
+      # ���存模式
+      try:
+        Flow_Save_mode = webui_settings["lightdiffusionflow-mode"]
+      except:
+        pass
+
+      # 自动纠正错误的参数
+      try:
+        Auto_Fix_Params = webui_settings["lightdiffusionflow-auto-fix-params"]
+      except:
+        pass
+
+      # 本地flow保存位置，先读本地设置，再读命令行设置
+      try:
+        Local_Flows_Path = webui_settings["lightdiffusionflow-local-flows-path"]
+      except:
+        pass
+      if shared.cmd_opts.local_flows_path:
+        Local_Flows_Path = shared.cmd_opts.local_flows_path
+      create_local_flow_path()
+
+
+      language_successed = False
+      auto_language = False
+      try:
+        # 优先读取自己的设置
+        if(webui_settings['lightdiffusionflow-language'] == "default"):
+          auto_language = True
+        elif(webui_settings['lightdiffusionflow-language'] == "english"):
+          OutputPrompt = OutputPrompt_English
+          language_successed = True
+        else:
+          OutputPrompt = OutputPrompt_Chinese
+          language_successed = True
+      except:
+        OutputPrompt = OutputPrompt_English
+      
+      # 如果是default就读取其他设置配合
+      if(auto_language and not language_successed):
+        # 自带的本地化文件
+        localization_files = ["zh_CN", "zh-Hans (Stable) [vladmandic]", "zh-Hans (Stable)",
+          "zh-Hans (Testing) [vladmandic]", "zh-Hans (Testing)","chinese-all-1024","chinese-english-1024"]
+        try:
+          # 如果用户使用了中文汉化文件，插件也默认显示中文
+          localization_files.index(webui_settings["localization"])
+          OutputPrompt = OutputPrompt_Chinese
+          language_successed = True
+        except:
+          pass
+        
+        # 第三方翻译插件bilingual-localization
+        if(not language_successed):
+          try:
+            if(webui_settings["bilingual_localization_enabled"] and webui_settings["bilingual_localization_file"] != "None"):
+              OutputPrompt = OutputPrompt_Chinese
+              language_successed = True
+          except:
+            OutputPrompt = OutputPrompt_English
+  except:
+    pass
+
+  Image_Components_Key = [
+    # 第一个组件是用来预计算第一张有效图的索引 防止出现有没用的页面跳转
+    "useless_Textbox", 
+    # 每个图片组件的elem_id
+    "img2img_image","img2img_sketch","img2maskimg","inpaint_sketch","img_inpaint_base","img_inpaint_mask", 
+    ] # 只保存图片组件id，其他参数js里搞定
+
+
+  # # init number of controlnet
+  # try:
+  #   webui_settings = {}
+  #   with open(shared.cmd_opts.ui_settings_file, mode='r') as f:
+  #     json_str = f.read()
+  #     webui_settings = json.loads(json_str)
+    
+  #   Multi_ControlNet = webui_settings.get("control_net_unit_count", None) # controlnet数量，新版名字
+  #   if(Multi_ControlNet == None):
+  #     Multi_ControlNet = webui_settings.get("control_net_max_models_num", 0)
+  #   print(f"Multi_ControlNet = {Multi_ControlNet}")
+  #   if(Multi_ControlNet == 1):
+  #     Image_Components_Key.append(f"txt2img_controlnet_ControlNet_input_image")
+  #     Image_Components_Key.append(f"img2img_controlnet_ControlNet_input_image")
+  #   else:
+  #     for i in range(Multi_ControlNet):
+  #       Image_Components_Key.append(f"txt2img_controlnet_ControlNet-{i}_input_image")
+  #       Image_Components_Key.append(f"img2img_controlnet_ControlNet-{i}_input_image")
+        
+  # except:
+  #   pass
+
+  # # Segment Anything images
+  # Image_Components_Key.extend(["txt2img_sam_input_image","img2img_sam_input_image"])
+
+
+
+init()

gf/LightDiffusionFlow/scripts/lightdiffusionflow_version.py

@@ -0,0 +1 @@
+lightdiffusionflow_version = "v2.1.4"

gf/LightDiffusionFlow/scripts/state_api.py

@@ -0,0 +1,1419 @@
+from fastapi import FastAPI, Body, HTTPException, Request, Response
+from fastapi.responses import FileResponse
+from pydantic import BaseModel
+import gradio as gr
+
+import os, io, sys
+import json
+from PIL import Image
+import re,base64,copy
+import time,requests
+import shutil
+from urllib.parse import urlparse
+import tempfile
+
+from modules import localization, images
+import modules.shared as shared
+import modules.scripts as scripts
+import modules.script_callbacks as script_callbacks
+import modules.generation_parameters_copypaste as parameters_copypaste
+from modules.generation_parameters_copypaste import paste_fields, registered_param_bindings, parse_generation_parameters
+from modules.sd_models import checkpoints_list
+from modules import ui_components
+from modules.paths_internal import data_path
+import launch
+
+from scripts import lightdiffusionflow_version, lightdiffusionflow_config
+import scripts.lightdiffusionflow_config as lf_config
+# from scripts.lightdiffusionflow_config import OutputPrompt, Flow_Save_mode, Auto_Fix_Params, LoRAs_In_Use # 
+
+Flow_Save_mode = lf_config.Flow_Save_mode
+Auto_Fix_Params = lf_config.Auto_Fix_Params
+LoRAs_In_Use = lf_config.LoRAs_In_Use
+OutputPrompt = lf_config.OutputPrompt
+Local_Flows_Path = lf_config.Local_Flows_Path #"models/LightDiffusionFlow"
+
+# current_path = os.path.abspath(os.path.dirname(__file__))
+# sys.path.append(os.path.join(current_path,"lib"))
+api = None
+workflow_json = {}
+State_Comps = {} # 当前页面的按钮组件
+invisible_buttons = {}
+Webui_Comps = {} # webui上需要操作的图片组件
+Webui_Comps_Cur_Val = [] # 顺序与Image_Components_Key一致
+Output_Log = ""
+g_msg_info = ""
+
+conponents_originlist = []
+extensions_conponents = {}
+extensions_id_conponents = {}
+extensions_id_conponents_value = {}
+txt2img_script_container = None
+img2img_script_container = None
+
+local_flow_list = []
+Need_Preload = False
+Preload_File = r""
+File_extension = ".flow"
+
+paste_symbol = '\u2199\ufe0f'  # ↙
+refresh_symbol = '\U0001f504'  # 🔄
+save_style_symbol = '\U0001f4be'  # 💾
+clear_prompt_symbol = '\U0001f5d1\ufe0f'  # 🗑️
+apply_style_symbol = '\U0001f4cb'  # 📋
+
+
+def test_func():
+  gr.Warning("hello")
+  # global extensions_conponents, extensions_id_conponents
+  # global Output_Log
+  # print("test_func")
+  #print(Output_Log)
+  #print(networks.available_networks)
+  #print(preprocessor_filters)
+
+  #print(extensions_id_conponents["dropdown"]["state-ext-control-net-txt2img_0-model"].get_config())
+
+  # print(parameters_copypaste.paste_fields)
+
+
+# fastapi触发不了弹窗
+def custom_msg_box():
+  global g_msg_info
+  if(g_msg_info != ""):
+    print(f"gr.Info({g_msg_info})")
+    gr.Info(g_msg_info)
+    g_msg_info = ""
+
+def clear_markup(html_str):
+    clearly_str = html_str
+    results = re.findall("(<.+?>)",clearly_str)
+    for res in results:
+      clearly_str = clearly_str.replace(res,"")
+    return clearly_str
+
+def add_output_log(msg:str="", style:str=""):
+  global Output_Log
+  if(msg != ""):
+    clear_msg = clear_markup(msg)
+    print(clear_msg)
+    Output_Log += f"<p style='color:rgb(192,192,192);{style}'>{msg}</p>"
+
+  #custom_msg_box()
+  return Output_Log, Output_Log
+
+def add_output_warning(msg:str=""):
+    add_output_log(msg, style="color:Orange;")
+
+def add_output_error(msg:str=""):
+    add_output_log(msg, style="color:Red;")
+
+def add_preset_output_log(preset, key, value):
+  global g_msg_info
+  g_msg_info = ""
+  if(preset == "start"):
+    add_output_log(OutputPrompt.startimport())
+  elif(preset == "finished"):
+    g_msg_info = OutputPrompt.import_completed_info()
+    add_output_log(OutputPrompt.import_completed())
+  elif(preset == "invalid"):
+    add_output_log(OutputPrompt.invalid_file())
+  elif(preset == "importing_img"):
+    add_output_log(OutputPrompt.importing_image(key))
+  elif(preset == "alt_option"):
+    add_output_log(OutputPrompt.alternative_option(key,value))
+  elif(preset == "no_option"):
+    add_output_log(OutputPrompt.no_option(key,value))
+  elif(preset == "missing_exts"):
+    ext_list = value.split(";")
+    add_output_log(OutputPrompt.missing_extensions(ext_list))
+  elif(preset == "missing_loras"):
+    lora_list = value.split(";")
+    add_output_log(OutputPrompt.missing_loras(lora_list))
+  elif(preset == "download_url"):
+    add_output_log(OutputPrompt.click_to_download(key, value))
+
+
+def read_chunks(file, size=io.DEFAULT_BUFFER_SIZE):
+  """Yield pieces of data from a file-like object until EOF."""
+  while True:
+      chunk = file.read(size)
+      if not chunk:
+          break
+      yield chunk
+def gen_file_sha256(filname):
+  import hashlib
+  """ pip-style sha256 hash generation"""
+  print("Use Memory Optimized SHA256")
+  blocksize=1 << 20
+  sha256_hash = hashlib.sha256()
+  length = 0
+  with open(os.path.realpath(filname), 'rb') as read_file:
+      for block in read_chunks(read_file, size=blocksize):
+          length += len(block)
+          sha256_hash.update(block)
+
+  hash_value =  sha256_hash.hexdigest()
+  print(f"sha256: {hash_value}")
+  print(f"length: {length}")
+  return hash_value
+
+def find_checkpoint_from_name(name:str):
+
+  for checkpoint in checkpoints_list.keys():
+    res = re.search(r"(.+)\.(.+)", checkpoint)
+    try:
+      if(res.group(1) == name):
+        return checkpoint
+    except:
+      pass
+  return name
+
+def find_checkpoint_from_hash(hash:str):
+
+  for checkpoint in checkpoints_list.keys():
+    res = re.search(r"\[([0-9a-fA-F]{8,10})\]", checkpoint)
+    try:
+      if(res.group(1) == hash):
+        return checkpoint
+    except:
+      pass
+  return hash
+
+def SearchingCheckPointByHashFromCivitai(hash:str):
+  hash_str = hash.replace("[","").replace("]","").strip()
+  try:
+    response = requests.get("https://civitai.com/api/v1/model-versions/by-hash/"+hash_str)
+    if(response.status_code == 200):
+      #print(response.content)
+      return response.json()
+  except:
+    pass
+  return {}
+
+def refresh_local_flows(*inputs):
+  print("refresh_local_flows")
+  global local_flow_list,Local_Flows_Path
+  try:
+    #flows_path = os.path.join(data_path, Local_Flows_Path) 
+    local_flow_list = [f for f in os.listdir(Local_Flows_Path) if os.path.isfile(
+        os.path.join(Local_Flows_Path, f)) and os.path.splitext(f)[-1] == '.flow']
+  except:
+    local_flow_list = []
+  # print(inputs)
+  # print(local_flow_list)
+  ret = []
+  for dd in inputs:
+    if dd in local_flow_list:
+      selected = dd
+    else:
+      selected = None
+    ret.append(gr.Dropdown.update(choices=local_flow_list, value=selected))
+  #ret = [gr.Dropdown.update(choices=local_flow_list, value=selected) for i in inputs]
+  return ret
+
+def apply_local_flow(selected):
+  global local_flow_list,Local_Flows_Path
+  global Need_Preload,Preload_File
+
+  if(selected != "" and selected != None):
+    flow_path = os.path.join(Local_Flows_Path, selected) 
+    if(os.path.exists(flow_path)):
+      print("OK,Local File!")
+      print(flow_path)
+      Preload_File = flow_path
+      Need_Preload = True
+      gr.Info(clear_markup(OutputPrompt.startimport()))
+
+def delete_local_flow(selected):
+  global local_flow_list,Local_Flows_Path
+  if(selected != "" and selected != None):
+    flow_path = os.path.join(Local_Flows_Path, selected) 
+    if(os.path.exists(flow_path)):
+      os.remove(flow_path)
+      print("Local File Deleted!")
+
+def set_lightdiffusionflow_file():
+  global Preload_File
+  return Preload_File
+
+def on_dropdown_changed(*component):
+  global extensions_id_conponents, extensions_id_conponents_value
+
+  extensions_id_conponents_value["dropdown"] = {}
+  i = 0
+  for id in extensions_id_conponents["dropdown"].keys():
+    extensions_id_conponents_value["dropdown"][id] = component[i]
+    i+=1
+
+def cn_get_model_type(cn_model_name):
+
+  cn_type_list = ['canny','depth','normalmap','openpose','mlsd','lineart_anime','lineart','softedge','scribble',
+    'seg','shuffle','tile','inpaint','ip2p','brightness','illumination','qrcode_monster','qrcode','normalbae']
+
+  type_pattern = "("+"|".join(cn_type_list)+")"
+  res = re.search(type_pattern,cn_model_name)
+  if(res != None):
+    return res.group()
+
+  return None
+
+def set_dropdowns():
+  global extensions_id_conponents, workflow_json
+  global temp_index,next_index
+  global Webui_Comps_Cur_Val, Output_Log
+
+  temp_index = len(Webui_Comps_Cur_Val)
+  next_index = temp_index
+  
+  return_vals = []
+  for comp_id in extensions_id_conponents["dropdown"].keys():
+    value = None
+    new_value = None
+    try:
+      value = workflow_json.get(comp_id, None)
+      if(value == None):
+        new_value = extensions_id_conponents["dropdown"][comp_id].get_config()["value"]
+      else:
+        new_value = value
+        matching_successed = False
+        options = extensions_id_conponents["dropdown"][comp_id].get_config()["choices"]
+
+        for option in options:
+          if(option == new_value):
+            matching_successed = True
+            break
+          else:
+            #print(f"去掉多余文件夹路径---{temp_option}----{temp_new_value}----")
+            temp_option = os.path.split(option)[-1]
+            temp_new_value = os.path.split(new_value)[-1]
+            if(temp_option == temp_new_value):
+              matching_successed = True
+              break
+
+          # 去掉模型的多余路径？
+          # if(os.path.split(option)[-1] == os.path.split(new_value)[-1]):
+          #   matching_successed = True
+          #   break
+        
+        # 没有完全匹配
+        if(not matching_successed):
+          
+          # controlnet模型
+          res = re.search(r"state-ext-control-net-txt2img_[0-9]-model", comp_id)
+          if(res != None):
+            cn_model = cn_get_model_type(new_value)
+            if(cn_model != None):
+              if(len(options) <= 1):
+                add_preset_output_log("download_url", "ControlNet Models", "https://huggingface.co/lllyasviel/ControlNet-v1-1/tree/main")
+              for option in options:
+                if(cn_model == cn_get_model_type(option)):
+                  new_value = option
+                  matching_successed = True
+                  break
+
+          # 哈希值匹配
+          if(not matching_successed):
+
+            # 寻找哈希值
+            value_hash_val = None
+            value_no_hash = None
+            res = re.search(r"(\[[0-9A-Fa-f]{8,10}\])", new_value)
+            if(res != None):
+              value_hash_val = res.group(1)
+              value_no_hash = new_value.replace(value_hash_val,"").rstrip()
+                
+            for option in options:
+
+              option_hash_val = None
+              option_no_hash = None
+              res = re.search(r"(\[[0-9A-Fa-f]{8,10}\])", option)
+              if(res != None): # 选项有哈希
+                option_hash_val = res.group(1)
+                option_no_hash = option.replace(option_hash_val,"").rstrip()
+                if(value_hash_val == None): # 值没有哈希
+                  if(new_value.rstrip() == option_no_hash):
+                    new_value = option
+                    matching_successed = True
+                    break
+                else: # 值有哈希
+                  if(value_hash_val == option_hash_val or option_no_hash == value_no_hash):
+                    new_value = option
+                    matching_successed = True
+                    break
+              else: # 选项没有哈希
+                if(value_hash_val == None): # 值没有哈希
+                  if(new_value.rstrip() == option.rstrip()):
+                    new_value = option
+                    matching_successed = True
+                    break
+                else: # 值有哈希
+                  if(value_no_hash == option.rstrip()):
+                    new_value = option
+                    matching_successed = True
+                    break
+
+          if(matching_successed):
+            add_output_log(OutputPrompt.alternative_option(value,new_value))
+            #add_output_log(f"Note: '<b style='color:Orange;'>{value}</b>' not found. An approximate match '<b style='color:Orange;'>{new_value}</b>' has been automatically selected as replacement.")
+            #print(f"Note: '{value}' not found. An approximate match '{new_value}' has been automatically selected as replacement.")
+          else:
+            add_output_log(OutputPrompt.no_option(comp_id,value))
+            #add_output_log(f"Error: '<b style='color:Red;'>{comp_id}</b>' import failed! The option '<b style='color:Red;'>{value}</b>' was not found!")
+            #print(f"'{comp_id}' import failed! The option '{value}' was not found!")
+            new_value = extensions_id_conponents["dropdown"][comp_id].get_config()["value"]
+
+    except KeyError as e:
+      print(e)
+    return_vals.append(new_value)
+
+  return_vals.append(temp_index) # 给json2js
+  return_vals.append(Output_Log)
+  return_vals.append(Output_Log)
+  #print(return_vals)
+  return tuple(return_vals)
+
+def set_js_params():
+  global temp_index,next_index
+  temp_index = next_index+1
+  next_index = temp_index
+  print("set_js_params")
+  return temp_index
+
+# use_elem_id 是为了兼容旧版的图片组件直接使用elem_id作为组件名称的情况
+def comp_create_id(component, tab_name, ext_name, sub_tab, use_elem_id = False): 
+  comp_id = None
+  if(use_elem_id):
+    try:
+      comp_id = component.elem_id
+    except:
+      pass
+  
+  if(comp_id == None):
+    #try:
+    comp_name = component.get_config()['label'].replace(" ", "-").lower()
+    temp_sub_tab = ("_"+sub_tab) if sub_tab != "base" else ""
+    comp_id = 'state-ext-'+ ext_name.replace(" ","-").lower() + "-" + tab_name + temp_sub_tab + "-" + comp_name
+    #except:
+    #  pass
+
+  return comp_id
+
+def params_create_ids():
+  global extensions_id_conponents, extensions_conponents
+  extensions_id_conponents = {"dropdown":{}, "image":{}}
+
+  for key in lf_config.Image_Components_Key:
+    if(key == "useless_Textbox"):
+      extensions_id_conponents["image"]["useless_Textbox"] = State_Comps["useless_Textbox"]
+    else:
+      extensions_id_conponents["image"][key] = Webui_Comps[key]
+
+  for tab_name in extensions_conponents.keys(): # tab name
+    for ext_name in extensions_conponents[tab_name].keys(): # plugin name
+      comp_index = 0
+      for sub_tab in extensions_conponents[tab_name][ext_name].keys(): # sub_tab 如果没有默认就是base
+        for comp in extensions_conponents[tab_name][ext_name][sub_tab]: # component
+          try:
+            # 先只考虑有label的组件
+            if(isinstance(comp, gr.Dropdown)):
+              # try:
+              #   comp_name = comp.get_config()['label'].replace(" ", "-").lower()
+              #   temp_sub_tab = ("_"+sub_tab) if sub_tab != "base" else ""
+              #   comp_id = 'state-ext-'+ ext_name.replace(" ","-").lower() + "-" + tab_name + temp_sub_tab + "-" + comp_name
+              # except:
+              #   pass
+              comp_id = comp_create_id(comp, tab_name, ext_name, sub_tab)
+              # comp_name = comp.get_config()['name'] + "_" + str(comp_index)
+              # comp_index += 1
+              # comp_id = 'state-ext-'+ ext_name.replace(" ","-").lower() + "-" + comp_name
+              extensions_id_conponents["dropdown"][comp_id] = comp
+            elif(isinstance(comp, gr.Image)):
+              comp_id = comp_create_id(comp, tab_name, ext_name, sub_tab, True)
+              if("generated_image" in comp_id):
+                pass
+                #print(f"skip component: {comp_id}")
+              else:
+                extensions_id_conponents["image"][comp_id] = comp
+              
+          except BaseException as e:
+            pass
+  #print(extensions_id_conponents)
+
+def get_lora_info(using_loras:list):
+  import networks
+  print(f"using_loras = {using_loras}")
+  loras_info = {}
+  for lora_name in using_loras:
+    for network in networks.available_networks.keys():
+      if( (lora_name == networks.available_networks[network].name or lora_name == networks.available_networks[network].alias) and networks.available_networks[network].shorthash != ""):
+        print(networks.available_networks[network].filename)
+        sha256 = gen_file_sha256(networks.available_networks[network].filename)
+        loras_info[sha256] = {
+          'name':networks.available_networks[network].name,
+          'alias':networks.available_networks[network].alias
+        }
+  print(f"loras_info = {loras_info}")
+  return loras_info
+
+def get_lora_from_prompt(prompt):
+  import networks
+
+  available_loras = []
+  for network in networks.available_networks.keys():
+    available_loras.append((networks.available_networks[network].name,networks.available_networks[network].alias))
+  #print(available_loras)
+  
+  used_loras = []
+  re_lora_prompt = re.compile("<lora:([\w_\s.]+):([ \d.]+)>", re.IGNORECASE)
+  results = re.findall(re_lora_prompt, prompt)
+  # print("使用到的lora:")
+  # print(results)
+  for res in results:
+    lora_name = res[0]
+    for lora in available_loras:
+      if(lora_name == lora[0] or lora_name == lora[1]):
+        used_loras.append(lora_name)
+  return used_loras
+
+def get_missing_lora(workflow_json):
+  import networks
+
+  data_str = json.dumps(workflow_json)
+  # re_parens = re.compile(r"[\\/\[\](){}]+")
+  # prompt = re.sub(
+  #   re_parens, "", prompt.replace("，", ",")#.replace("-", " ").replace("_", " ")
+  # )
+
+  available_loras = []
+  for network in networks.available_networks.keys():
+    available_loras.append((networks.available_networks[network].name,networks.available_networks[network].alias))
+  #print(available_loras)
+  
+  missing_loras = []
+  loras_info = workflow_json[LoRAs_In_Use]
+  re_lora_prompt = re.compile("<lora:([\w_\s.]+):([ \d.]+)>", re.IGNORECASE)
+  results = re.findall(re_lora_prompt, data_str)
+  # print("使用到的lora:")
+  # print(results)
+  for res in results:
+    lora_name = res[0]
+    for lora in available_loras:
+      if(lora_name == lora[0] or lora_name == lora[1]):
+        break
+    else:
+      # SD默认计算的lora的hash值无法用来在C站搜索，下载链接需要的Hash需单独计算导出才能支持。
+      # name,alias,hash,downloadUrl
+      for sha256 in loras_info.keys():
+        if(loras_info[sha256]["name"] == lora_name or loras_info[sha256]["alias"] == lora_name):
+          try:
+            model_info = SearchingCheckPointByHashFromCivitai(sha256)
+            if(model_info != {}):
+              lora_link = OutputPrompt.download_link(lora_name, model_info["downloadUrl"])
+              missing_loras.append(lora_link)
+              break
+          except:
+           pass
+      else:
+        missing_loras.append(lora_name)
+  # print("丢失的lora:")
+  # print(missing_loras)
+  return missing_loras
+
+def get_extname_from_label(label):
+  ext_name = label
+  res = re.search(r"(.+) v[0-9\.]+", ext_name)
+  if(res != None):
+    ext_name = res.group(1)
+  #兼容旧命名
+  if(ext_name == "ControlNet"):
+    ext_name = "Control-Net"
+  return ext_name
+
+
+def get_script_container(component):
+  global txt2img_script_container, img2img_script_container
+  if(txt2img_script_container == None):
+    temp = component
+    #i = 10
+    while temp:
+      if(temp.elem_id == "txt2img_script_container"):
+        txt2img_script_container = temp
+        break
+      else:
+        temp = temp.parent
+        #i-=1
+  
+  if(img2img_script_container == None):
+    temp = component
+    i = 10
+    while temp and i>0:
+      if(temp.elem_id == "img2img_script_container"):
+        img2img_script_container = temp
+        break
+      else:
+        temp = temp.parent
+        i-=1
+
+def searching_extensions_title():
+  global txt2img_script_container, img2img_script_container, extensions_conponents, Flow_Save_mode
+
+  if(Flow_Save_mode == "Core"):
+    extensions_conponents["txt2img"] = {}
+    extensions_conponents["img2img"] = {}
+    extensions_conponents["txt2img"]["Control-Net"] = {"base":[]}
+    extensions_conponents["img2img"]["Control-Net"] = {"base":[]}     
+
+  else:
+    for group in txt2img_script_container.children: # 遍历读取所��的插件名称
+
+      label = ""
+      try:
+        label = get_extname_from_label(group.children[0].label)
+      except BaseException as e:
+        pass
+      
+      if(label == ""):
+        try:
+          label = get_extname_from_label(group.children[0].children[0].label)
+        except BaseException as e:
+          pass
+
+      if(label != ""):
+        try:
+          extensions_conponents["txt2img"]
+        except:
+          extensions_conponents["txt2img"] = {}
+          extensions_conponents["img2img"] = {}
+        extensions_conponents["txt2img"][label] = {"base":[]}
+        extensions_conponents["img2img"][label] = {"base":[]}     
+        #extensions_conponents[label] = []
+    #print(extensions_conponents)
+
+def on_img_changed(*component):
+  global extensions_id_conponents, extensions_id_conponents_value
+
+  #test_vals = []
+  extensions_id_conponents_value["image"] = {}
+  i = 0
+  for id in extensions_id_conponents["image"].keys():
+    extensions_id_conponents_value["image"][id] = component[i]
+    # if(component[i] == None):
+    #   test_vals.append("0")
+    # else:
+    #   test_vals.append("1")
+    i+=1
+
+  #print(test_vals)
+
+temp_index = -1
+next_index = -1
+def func_for_invisiblebutton():
+  global temp_index,next_index
+  global extensions_id_conponents, Webui_Comps_Cur_Val, Output_Log
+
+  temp_index = next_index+1
+  next_index = temp_index
+
+  try:
+    while( next_index < len(Webui_Comps_Cur_Val) and Webui_Comps_Cur_Val[next_index+1] == None ):
+      next_index += 1
+  except:
+    pass
+  
+  # try:
+  #   print(f"func_for_invisiblebutton {temp_index} {next_index} {len(Webui_Comps_Cur_Val)}")
+  #   print(f"func_for_invisiblebutton {lf_config.Image_Components_Key[temp_index]} {Webui_Comps_Cur_Val[temp_index]} ")
+  # except:
+  #   pass
+  
+  
+  # 第一个组件是用来预计算第一张图的索引 防止出现有没用的页面跳转 所以不用输出日志信息
+  if(temp_index > 0):
+    add_output_log(OutputPrompt.importing_image(list(extensions_id_conponents['image'].keys())[temp_index]))
+    #add_output_log(f"importing image: \'{list(extensions_id_conponents['image'].keys())[temp_index]}\' ") 
+    
+  #if(next_index+1 == len(Webui_Comps_Cur_Val)):
+    #add_output_log(OutputPrompt.import_completed())
+    #add_output_log(f"import completed!")
+  
+  # 因为显示日志的窗口分txt2img和img2img两个位置 所以两个位置同步导出
+  return Webui_Comps_Cur_Val[temp_index], next_index, Output_Log, Output_Log 
+
+
+def config_filter(config):
+  global extensions_id_conponents
+  new_config = config
+  for comp_type in extensions_id_conponents.keys():
+    for comp_id in extensions_id_conponents[comp_type].keys():
+      try:
+        # 筛掉python相关组件的默认值选项
+        default_val = extensions_id_conponents[comp_type][comp_id].get_config()["value"]
+        if(default_val == new_config[comp_id]):
+          del new_config[comp_id]
+      except KeyError as e:
+        pass
+
+  if(Auto_Fix_Params == False):
+    return new_config
+    
+  # 处理旧版插件保存的错误参数问题
+  print("-------错误参数纠正-------")
+  found_tabs = []
+  fixed_config = {}
+  for param in new_config.keys():
+    res = re.match("state-ext-control-net-(txt2img|img2img)_([0-9]+)-(.+)",param)
+    if(res != None):
+      if(res.group(3) not in ["presets","preprocessor","model"]):
+        try:
+          found_tabs.index(res.group(2))
+        except ValueError:
+          found_tabs.append(res.group(2))
+
+  for param in new_config.keys():
+
+    # 缝缝补补。。。 js保存的参数因为是汉语反推回英文，所以就会有 model->模型->models 的情况。
+    res = re.search("[-_](model|models|checkpoint|checkpoints)$",param)
+    if(res != None):
+      for key in ["model","models","checkpoint","checkpoints"]:
+        target_word = str(res.group()).replace(res.group(1),key)
+        new_param = re.sub("[-_](model|models|checkpoint|checkpoints)$", target_word, param)
+        fixed_config[new_param] = new_config[param]
+        #print(f"根据{param}，补充{new_param}")
+    
+    # 纠正编号
+    res = re.match("state-ext-control-net-(txt2img|img2img)_([0-9]+)-(.+)",param)
+    if(res != None):
+      tab_num = int(res.group(2))
+      if(res.group(2) != "0" and tab_num%3 == 0 ):
+        try:
+          found_tabs.index(str(tab_num/3))
+          # 如果是9 如果发现3的位置有参数，就还需要检查一下1
+          if(tab_num == 9):
+            found_tabs.index("1")
+        except ValueError:
+          new_key = f"state-ext-control-net-{res.group(1)}_{int(tab_num/3)}-{res.group(3)}"
+          # 这三个选项，旧版是js控制会有序号问题，新版本py控制没有序号问题，所以这里判断纠正之后的位置有没有值，有的话就不动。
+          if(res.group(3) in ["presets","preprocessor","model"]):
+              #print(param)
+              if(new_config.get(new_key,None) == None):
+                fixed_config[new_key] = new_config[param]
+                print(f" {param} 改为 {new_key}")
+                continue
+          else:
+            fixed_config[new_key] = new_config[param]
+            print(f" {param} 改为 {new_key}")
+            continue
+
+    # 其余参数照搬
+    fixed_config[param] = new_config[param]
+
+  #print(fixed_config)
+  #print("-------处理错误-------")
+
+  new_config = fixed_config
+  return new_config
+
+
+def fn_import_workflow(workflow_file):
+  global workflow_json, Output_Log
+  global extensions_id_conponents, Webui_Comps_Cur_Val, temp_index, next_index
+  temp_index = -1 # 重置索引
+  next_index = -1
+  
+  workflow_json = {}
+  workflow_json_str = ""
+  if(workflow_file):
+    try:
+      config_file = workflow_file[0].name
+    except:
+      config_file = workflow_file.name
+
+    print("fn_import_workflow "+str(config_file))
+    if (os.path.splitext(config_file)[-1] in  [File_extension, ".lightflow", ".json"]): # 兼容部分旧版本文件
+      with open(config_file, mode='r', encoding='UTF-8') as f:
+        workflow_json_str = f.read()
+        workflow_json = json.loads(workflow_json_str)
+
+      try:
+        response = requests.get("https://api.lightflow.ai/openapi/access?action=import")
+        if(response.status_code == 200):
+          pass
+      except:
+        pass
+
+    else:
+      print("invalid file!")
+
+
+  workflow_json = config_filter(workflow_json)
+
+  Webui_Comps_Cur_Val = []
+  for key in extensions_id_conponents["image"].keys():
+  #for key in lf_config.Image_Components_Key:
+    image = None
+    successed = 2
+    tempkey = key
+    while successed > 0:
+      try:
+        image_data = workflow_json[key]
+        matchObj = re.match("data:image/[a-zA-Z0-9]+;base64,",image_data)
+        if matchObj != None:
+          image_data = image_data[len(matchObj.group()):]
+        image_data = base64.decodebytes(image_data.encode('utf-8'))
+        image = Image.open(io.BytesIO(image_data))
+        successed = 0
+      except:
+        # 如果是controlnet 第一张图 就修改一下key值重试一遍
+        if(key == "txt2img_controlnet_ControlNet_input_image"):
+          key = "txt2img_controlnet_ControlNet-0_input_image"
+        elif(key == "img2img_controlnet_ControlNet_input_image"):
+          key = "img2img_controlnet_ControlNet-0_input_image"
+
+        elif(key == "txt2img_controlnet_ControlNet-0_input_image"):
+          key = "txt2img_controlnet_ControlNet_input_image"
+        elif(key == "img2img_controlnet_ControlNet-0_input_image"):
+          key = "img2img_controlnet_ControlNet_input_image"
+        else:
+          successed = 0
+      successed-=1
+    
+    Webui_Comps_Cur_Val.append(image)
+
+  # 检查lora
+  missing_loras = []
+  try:
+    missing_loras = get_missing_lora(workflow_json)
+    if(len(missing_loras) > 0):
+      add_output_log(OutputPrompt.missing_loras(missing_loras))
+    
+    # # SD默认计算的lora的hash值无法用来在C站搜索，下载链接需要的Hash需单独计算导出才能支持。
+    # # name,alias,hash,downloadUrl
+    # loras_info = workflow_json[LoRAs_In_Use]
+    # for lora_name in missing_loras:
+    #   for sha256 in loras_info.keys():
+    #     if(loras_info[sha256]["name"] == lora_name or loras_info[sha256]["alias"] == lora_name):
+    #       try:
+    #         model_info = SearchingCheckPointByHashFromCivitai(sha256)
+    #         if(model_info != {}):
+    #           add_preset_output_log("download_url", lora_name, model_info["downloadUrl"])
+    #       except:
+    #         pass
+  except KeyError as e:
+    pass
+    #print(f"except missing loras error: {e}")
+
+  #print(Webui_Comps_Cur_Val)
+  #set_elements()
+  # return_vals.append(str(time.time())) # 用来触发json2js事件，python设置完图片 js继续设置其他参数  弃用
+  # return tuple(return_vals)
+  return str(temp_index)#, Output_Log, Output_Log
+
+class config_params(BaseModel):
+  config_data:dict
+
+class imgs_callback_params(BaseModel):
+  id:str
+  img:str
+
+class png_info_params(BaseModel):
+  img_path:str
+
+class file_params(BaseModel):
+  file_path:str
+
+class savefile_params(BaseModel):
+  file_name:str
+  file_data:dict
+  overwrite:bool
+
+class StateApi():
+
+  BASE_PATH = '/lightdiffusionflow'
+
+  def get_path(self, path):
+    return f"{self.BASE_PATH}{path}"
+
+  def add_api_route(self, path: str, endpoint, **kwargs):
+    return self.app.add_api_route(self.get_path(path), endpoint, **kwargs)
+
+  def start(self, _: gr.Blocks, app: FastAPI):
+    print("----------------- light_diffusion_flow api start------------------")
+
+    self.app = app 
+    # 读取本地的config.json
+    self.add_api_route('/local/config.json', self.get_config, methods=['GET']) 
+    # python已经加载好的配置workflow_json  发送给 js
+    self.add_api_route('/local/lightdiffusionflow_config', self.get_lightdiffusionflow_config, methods=['GET']) 
+    self.add_api_route('/local/parse_lora_info', self.parse_lora_info, methods=['POST']) 
+    # 获取图片的组件id 由js来设置onchange事件
+    self.add_api_route('/local/get_imgs_elem_key', self.get_img_elem_key, methods=['GET']) 
+    # 获取当前已安装的插件列表
+    self.add_api_route('/local/get_ext_list', self.get_ext_list, methods=['GET']) 
+    # 用户设置了新图片 触发回调保存到 workflow_json
+    self.add_api_route('/local/imgs_callback', self.imgs_callback, methods=['POST']) 
+    self.add_api_route('/local/useless_config_filter', self.useless_config_filter, methods=['POST'])
+    # 刷新页面之后触发
+    self.add_api_route('/local/refresh_ui', self.refresh_ui, methods=['GET']) 
+    self.add_api_route('/local/output_log', add_output_log, methods=['GET']) 
+    self.add_api_route('/local/preset_output_log', add_preset_output_log, methods=['GET']) 
+    self.add_api_route('/local/png_info', self.png_info, methods=['POST']) # 
+    # 传入一个文件路径，返回文件内容
+    self.add_api_route('/local/read_file', self.read_file, methods=['POST']) 
+    self.add_api_route('/local/file_exist', self.file_exist, methods=['POST']) 
+    self.add_api_route('/local/need_preload', self.need_preload, methods=['GET'])
+    # 保存当前配置到本地文件夹
+    self.add_api_route('/local/save_flow_to_local', self.saveFlowToLocal, methods=['POST'])
+    
+    self.add_api_route('/set_preload', self.set_preload, methods=['POST'])
+
+  def get_config(self):
+    return FileResponse(shared.cmd_opts.ui_settings_file)
+  
+  def get_ext_list(self):
+    global extensions_conponents
+    ext_str = ""
+    try:
+      ext_str = ",".join(list(extensions_conponents["txt2img"].keys())).lower().replace(" ", "-")
+    except:
+      pass
+    return ext_str
+
+  def useless_config_filter(self, config:config_params):
+    return config_filter(config.config_data)
+
+  def get_lightdiffusionflow_config(self, data2export:bool = False):
+    global workflow_json, extensions_id_conponents, extensions_id_conponents_value
+    temp_json = {}
+    if(data2export):
+
+      for key in extensions_id_conponents["image"].keys():
+      # for key in lf_config.Image_Components_Key:
+        try:
+          temp_json[key] = workflow_json[key]
+        except:
+          pass
+
+      # using_loras = get_lora_from_prompt(json.dumps(temp_json))
+      # temp_json[LoRAs_In_Use] = get_lora_info(using_loras)
+          
+      # 导出时调用，这里把py负责的其他组件一起读进来
+      for comp_type in extensions_id_conponents_value.keys():
+        for comp_id in extensions_id_conponents_value[comp_type].keys():
+          try:
+            # 默认值的选项不导出
+            default_val = extensions_id_conponents[comp_type][comp_id].get_config()["value"]
+            if(default_val != extensions_id_conponents_value[comp_type][comp_id]):
+              temp_json[comp_id] = extensions_id_conponents_value[comp_type][comp_id]
+          except KeyError as e:
+            pass
+    else:
+      temp_json = copy.deepcopy(workflow_json)
+      for key in extensions_id_conponents["image"].keys():
+      #for key in lf_config.Image_Components_Key:
+        temp_json[key] = ""
+
+    return json.dumps(temp_json)
+
+  def parse_lora_info(self, config:config_params):
+    temp_json = {}
+    json_str = json.dumps(config.config_data)
+    using_loras = get_lora_from_prompt(json_str)
+    temp_json[LoRAs_In_Use] = get_lora_info(using_loras)
+    return temp_json
+
+  def str_2_json(self, str_data:str):
+    out_json = {}
+    res = re.findall(r"([^:]+:[^:]{1,})(,|$)",str_data)
+    for field in res:
+      data = field[0].split(":")
+      try:
+        out_json[data[0].strip()] = data[1].strip()
+      except IndexError as e:
+        print(f"str_2_json [key error]: {e}")
+    return out_json
+
+  def png_info(self, img_data:png_info_params):
+
+    geninfo, items = images.read_info_from_image(Image.open(img_data.img_path))
+    geninfo = parse_generation_parameters(geninfo)
+    temp_json = {}
+    for key in geninfo.keys():
+      
+      matchObj = re.match("ControlNet ([0-9])", key)
+      if(matchObj != None): # controlnet
+        cn_info = self.str_2_json(geninfo[key])
+        if(len(cn_info.keys()) > 0):
+          temp_json["state-ext-control-net-txt2img_0-enable".replace("0",matchObj.group(1))] = True
+
+        for cn_key in cn_info.keys():
+          if(cn_key == "starting/ending"):
+            cn_key_split = cn_key.split("/")
+            data = cn_info[cn_key].replace("(","").replace(")","").split(",")
+            temp_json[lf_config.PNGINFO_CN_2_LIGHTDIFFUSIONFLOW[cn_key_split[0]].replace("0",matchObj.group(1))]\
+               = data[0].strip()
+            temp_json[lf_config.PNGINFO_CN_2_LIGHTDIFFUSIONFLOW[cn_key_split[1]].replace("0",matchObj.group(1))]\
+               = data[1].strip()
+          elif(cn_key == "pixel perfect"):
+            temp_json[lf_config.PNGINFO_CN_2_LIGHTDIFFUSIONFLOW[cn_key].replace("0",matchObj.group(1))]\
+               = (cn_info[cn_key].lower() == "true")
+          else:
+            try:
+              temp_json[lf_config.PNGINFO_CN_2_LIGHTDIFFUSIONFLOW[cn_key.lower()].replace("0",matchObj.group(1))] = cn_info[cn_key]
+            except KeyError as e:
+              print(f"ControlNet option '{cn_key}' parsing failed.")
+
+      elif(key == "Model hash"):
+        target_model = find_checkpoint_from_hash(geninfo[key])
+        if(target_model == geninfo[key]):#说明没有找到相同hash值的模型，改用名称查找
+          try:
+            target_model = find_checkpoint_from_name(geninfo["Model"])
+          except:
+            pass
+        temp_json[lf_config.PNGINFO_2_LIGHTDIFFUSIONFLOW[key]] = target_model
+
+      elif(key == "Face restoration"):
+        temp_json[lf_config.PNGINFO_2_LIGHTDIFFUSIONFLOW[key]] = True
+      else:
+        try:
+          temp_json[lf_config.PNGINFO_2_LIGHTDIFFUSIONFLOW[key]] = geninfo[key]
+        except KeyError as e:
+          pass
+          #print(e)
+      
+      if(key in ["Hires upscale","Hires steps","Hires upscaler","Hires resize-1","Hires resize-2"]):
+        temp_json["state-txt2img_enable_hr"] = True
+
+    return json.dumps(temp_json)
+
+  def read_file(self, params:file_params):
+    print("read_file")
+    file_content = ""
+    with open(params.file_path, mode='r', encoding='UTF-8') as f:
+      file_content = f.read()
+    return file_content
+
+  def file_exist(self, params:file_params):
+    print("file_exist")
+    if(not os.path.exists(params.file_path)):
+      flow_path = os.path.join(Local_Flows_Path, params.file_path) 
+      if(os.path.exists(flow_path)):
+        return True
+      else:
+        return False
+    return False
+
+  def get_img_elem_key(self):
+    global extensions_id_conponents
+    keys_str = ""
+    #keys_str = ",".join(lf_config.Image_Components_Key)
+    try:
+      keys_str = ",".join(list(extensions_id_conponents["image"].keys()))
+    except:
+      pass
+    return keys_str
+
+  def imgs_callback(self, img_data:imgs_callback_params):
+    global workflow_json
+    workflow_json[img_data.id] = img_data.img
+
+  def refresh_ui(self):
+    global workflow_json, Output_Log
+    workflow_json = {}
+    Output_Log = ""
+    print("refresh_ui")  
+    tag = launch.git_tag()
+    return tag
+
+  def set_preload(self, params:file_params):
+    global Need_Preload,Preload_File
+    print(params.file_path)
+    res = "OK"
+    if(params.file_path):
+      if(os.path.exists(params.file_path)):
+        Preload_File = params.file_path
+        Need_Preload = True
+        res = "OK,Local File!"
+      else:
+        response = requests.get(params.file_path)
+        if(response.status_code == 200):
+          parsed_url = urlparse(params.file_path)
+          file_name = os.path.basename(parsed_url.path)
+          tempdir = os.path.join(tempfile.gettempdir(),"lightdiffusionflow_temp")
+          if(os.path.exists(tempdir)):
+            shutil.rmtree(tempdir)
+          if(not os.path.exists(tempdir)):
+            os.mkdir(tempdir)
+          temp_file = os.path.join(tempdir,file_name)
+          
+          with open(temp_file,"wb") as f:
+            f.write(response.content)
+          
+          print(temp_file)
+          Preload_File = temp_file
+          Need_Preload = True
+          res = "OK,Network File!"
+        else:
+          res = "Invalid File!"
+
+    return res
+
+  def need_preload(self):
+    global Need_Preload,Preload_File
+    if(Need_Preload):
+      Need_Preload = False
+      return Preload_File
+    return ""
+
+  def saveFlowToLocal(self, data_to_save:savefile_params):
+    global Local_Flows_Path
+    global add_output_log
+
+    overall_data = {}
+    print(data_to_save.file_name)
+    print(data_to_save.file_data)
+    filedata = data_to_save.file_data
+
+    # python处理的图片和dropdown信息
+    overall_data = json.loads(self.get_lightdiffusionflow_config(True))
+    for key in filedata.keys():
+      if(filedata[key] != ""):
+        overall_data[key] = filedata[key]
+
+    # Lora信息
+    params = config_params(config_data=overall_data)
+    lora_info = self.parse_lora_info(params)
+    for key in lora_info.keys():
+      overall_data[key] = lora_info[key]
+
+    # 过滤掉一些没用的默认值的信息
+    overall_data = config_filter(overall_data)
+
+    flow_path = os.path.join(Local_Flows_Path, data_to_save.file_name) 
+    print(flow_path)
+    if(not os.path.exists(flow_path) or (data_to_save.overwrite)):
+      with open(flow_path,"w") as f:
+        #json.dump(overall_data,f)
+        f.write(json.dumps(overall_data, ensure_ascii=False, indent=4))
+      add_output_log(OutputPrompt.save_completed())
+    else:
+      add_output_log(OutputPrompt.save_failed())
+
+    return flow_path
+
+class Script(scripts.Script):  
+
+  def __init__(self) -> None:
+    super().__init__()
+    #记录无id元素的id
+    self.new_ids={}
+
+  def title(self):
+    return "lightdiffusionflow plugin"
+
+  def show(self, is_img2img):
+    return scripts.AlwaysVisible
+
+  def after_component(self, component, **kwargs):
+    '''
+    python触发导入事件，按正常触发逻辑先执行js代码，把除图片以外的参数全部设置好，
+    然后回到python代码，读取图片保存到Webui_Comps_Cur_Val，
+    再用json2js的onchange事件触发js来点击隐藏按钮开始触发设置图片的事件队列。
+    代码从on_after_component 移到script里的after_component:
+      txt2img和img2img面板以外的组件回调不再有效
+      但是可以读取self.is_img2img确定当前组件存在的面板
+    '''
+    # #当前模式
+    # teb_mode="img2img" if self.is_img2img else "txt2img"
+    # #空id补全方法
+    # def in_zone(dom,id=""):
+    #   if dom:
+    #     if dom.elem_id:
+    #       id+="-"+dom.elem_id
+    #       return in_zone(dom.parent,id)
+    #     elif dom.elem_classes and dom.elem_classes[0]!='gradio-blocks':
+    #       if dom.elem_classes[0]=='gradio-accordion':
+    #         id+='-'+dom.label+"?"
+    #       return in_zone(dom.parent,id)
+    #   if re.search('2img_(textual|hypernetworks|checkpoints|lora)_',id):
+    #     return False
+    #   else:
+    #     id=re.sub(r'\?[^\?]+$|[ \?]','',id)
+    #     if id in self.new_ids:
+    #       self.new_ids[id]+=1
+    #     else:
+    #       self.new_ids[id]=1
+    #     return id+'-'+str(self.new_ids[id])
+  
+    # #记录组件
+    # try:
+    #   #拉取id
+    #   id=component.elem_id
+    #   #若没有就重构
+    #   if id==None:
+    #     id=component.elem_id==in_zone(component.parent,teb_mode)
+    #   Webui_Comps[id] = component
+    # except BaseException as e:
+    #   pass
+
+    global txt2img_script_container, img2img_script_container, extensions_id_conponents, extensions_conponents
+    
+    conponents_originlist.append((component, 'img2img' if self.is_img2img else 'txt2img'))
+    #print(f"after_component {component} {kwargs.get('elem_id', None)} {'img2img' if self.is_img2img else 'txt2img'} ")
+    try:
+
+      if kwargs["elem_id"] == "txt2img_generation_info_button": # or kwargs["elem_id"] == "img2img_generation_info_button":
+        self.custom_ui()
+
+      if(Webui_Comps.get(kwargs["elem_id"], None) == None):
+        Webui_Comps[kwargs["elem_id"]] = component
+        #print(kwargs["elem_id"])
+
+    except BaseException as e:
+      pass
+
+    get_script_container(component)
+
+    if (isinstance(component, gr.Button) and kwargs["elem_id"] == "img2img_generation_info_button"): # 加载到最后一个组件了。   兼容旧版，暂时不使用“img2img_preview_filename”
+
+      searching_extensions_title()
+      #print(extensions_conponents)
+
+      for comp_tuple in conponents_originlist:
+        comp = comp_tuple[0]
+        temp_parent  = comp.parent
+        mode_tab = comp_tuple[1]
+        tab = None
+        tabs = None
+        ext_name = ""
+
+        # --------------------------------------组件分类--------------------------------------------------
+        while temp_parent:
+          try:
+            # tab 如果有多层只存最上层
+            if(isinstance(temp_parent,gr.Tab)):
+              tab = temp_parent
+            if(isinstance(temp_parent,gr.Tabs)):
+              tabs = temp_parent
+
+            temp_ext_name = get_extname_from_label(temp_parent.label)
+            if(extensions_conponents[mode_tab].get(temp_ext_name, None) != None):
+              ext_name = temp_ext_name
+              break
+          except BaseException as e:
+            pass
+          temp_parent = temp_parent.parent
+
+        try:
+          if(tabs):
+            tab_index = 0
+            for temp_tab in tabs.children:
+              if (tab == temp_tab):
+                break
+              tab_index+=1
+            if(extensions_conponents[mode_tab][ext_name].get(str(tab_index), None) != None):
+              extensions_conponents[mode_tab][ext_name][str(tab_index)].append(comp)
+            else:
+              extensions_conponents[mode_tab][ext_name][str(tab_index)] = [comp]
+          else:
+            extensions_conponents[mode_tab][ext_name]["base"].append(comp)
+        except KeyError as e:
+          pass
+
+      # print(extensions_conponents) # 整理好的第三方插件用到的组件
+      # --------------------------------------组件分类--------------------------------------------------
+      
+      if(self.is_img2img):
+          State_Comps["useless_Textbox"] = \
+            gr.Textbox(value='useless_Textbox', elem_id='useless_Textbox', visible=False)
+
+      params_create_ids()
+      
+      # img2img下的面板
+      self.custom_ui()
+
+      target_comps = []
+      target_comps.append(State_Comps["json2js"]) # 触发事件传递json给js
+      #target_comps.append(State_Comps["outlog"][0])
+      #target_comps.append(State_Comps["outlog"][1]) # 因为显示日志的窗口分txt2img和img2img两个位置 所以两个位置同步导出
+      
+      for i in range(len(State_Comps["local_flows"])):
+        #State_Comps["local_flows"]
+        State_Comps["refresh"][i].click(refresh_local_flows, inputs=State_Comps["local_flows"],outputs=State_Comps["local_flows"])
+        State_Comps["apply"][i].click(apply_local_flow, inputs=[State_Comps["local_flows"][i]],outputs=[])
+        State_Comps["save"][i].click(fn=None,_js="state.core.actions.saveFlowToLocal", inputs=[],outputs=[])
+        #State_Comps["delete"][i].click(delete_local_flow, inputs=[State_Comps["local_flows"][i]],outputs=State_Comps["local_flows"])
+        
+
+      for btn in State_Comps["export"]:
+        btn.click(None,_js="state.core.actions.exportState") #, inputs=[],outputs=[] 
+
+      for btn in State_Comps["import"]:
+        # js里加载除图片以外的参数 python加载图片
+        btn.upload(fn_import_workflow, _js=f"state.core.actions.handleLightDiffusionFlow",
+          inputs=[btn],outputs=target_comps, show_progress=False)
+
+      State_Comps["json2js"].change(fn=None,_js="state.core.actions.startImportImage",
+        inputs=[State_Comps["json2js"]])
+      
+      State_Comps["test_button"].click(test_func,_js="state.utils.testFunction",inputs=[])
+
+      State_Comps["refresh_log"].click(add_output_log,inputs=[],outputs=[State_Comps["outlog"][0], State_Comps["outlog"][1]])
+
+      on_dropdown_change_inputs = list(extensions_id_conponents["dropdown"].values())
+      for comp_to_bind in extensions_id_conponents["dropdown"].keys():
+        extensions_id_conponents["dropdown"][comp_to_bind].change(on_dropdown_changed,inputs=on_dropdown_change_inputs,outputs=[])
+
+      # change事件，每次上传一张图会触发change时间几十次
+      # clear事件，删除图片的时候不触发，官方bug好像新版本有解决。
+      # edit事件，每次编辑都能触发一次，上传图片的时候也能触发。
+      # 没有合适的清除图片的事件，无法使用python监控图片组件
+      # on_img_change_inputs = list(extensions_id_conponents["image"].values())
+      # for comp_to_bind in extensions_id_conponents["image"].keys():
+      #   extensions_id_conponents["image"][comp_to_bind].edit(on_img_changed,inputs=on_img_change_inputs,outputs=[])
+      #   extensions_id_conponents["image"][comp_to_bind].clear(on_img_changed,inputs=on_img_change_inputs,outputs=[])
+
+      temp_dropdown_outputs = list(extensions_id_conponents["dropdown"].values())
+      temp_dropdown_outputs.append(State_Comps["json2js"]) # json2js触发完成事件
+      temp_dropdown_outputs.append(State_Comps["outlog"][0]) # 输出日志
+      temp_dropdown_outputs.append(State_Comps["outlog"][1]) # 输出日志
+      State_Comps["set_dropdowns"].click(set_dropdowns,inputs=[],outputs=temp_dropdown_outputs,show_progress=False)
+
+      State_Comps["set_js_params"].click(set_js_params,inputs=[],outputs=State_Comps["json2js"])
+
+      input_component = State_Comps["background_import"] #State_Comps["import"][0]
+      State_Comps["set_file_button"].click(set_lightdiffusionflow_file,inputs=[],outputs=[input_component])
+      State_Comps["preload_button"].click(fn_import_workflow, _js=f"state.core.actions.handleLightDiffusionFlow", 
+        inputs=[input_component],outputs=target_comps)
+
+      for key in invisible_buttons.keys():
+        segs = key.split("_")
+        comp_name = "_".join(segs[2:])
+        #print(comp_name)
+        try:
+          invisible_buttons[key].click(func_for_invisiblebutton,
+            inputs=[], 
+            outputs=[
+              #Webui_Comps[comp_name], 
+              extensions_id_conponents["image"][comp_name],
+              State_Comps["json2js"], 
+              State_Comps["outlog"][0], 
+              State_Comps["outlog"][1]
+            ])
+        except KeyError:
+          print(f"No such component: {comp_name}")
+      
+      print("LightDiffusionFlow 绑定完成")
+
+  def ui(self, is_img2img):
+    pass
+
+  def custom_ui(self):
+    global File_extension, extensions_id_conponents
+    try:
+      State_Comps["import"]
+      State_Comps["export"]
+      State_Comps["outlog"]
+      State_Comps["local_flows"]
+      State_Comps["apply"]
+      State_Comps["delete"]
+      State_Comps["save"]
+      State_Comps["refresh"]
+    except:
+      State_Comps["import"] = []
+      State_Comps["export"] = []
+      State_Comps["outlog"] = []
+      State_Comps["local_flows"] = []
+      State_Comps["apply"] = []
+      State_Comps["delete"] = []
+      State_Comps["save"] = []
+      State_Comps["refresh"] = []
+
+
+    cur_mode = "img2img" if self.is_img2img else "txt2img"
+    save_mode = " (for all extensions)"
+    if(Flow_Save_mode == "Core"):
+      save_mode = " (only ControlNet)"
+
+    global local_flow_list,Local_Flows_Path
+    try:
+      #flows_path = os.path.join(data_path, Local_Flows_Path) 
+      local_flow_list = [f for f in os.listdir(Local_Flows_Path) if os.path.isfile(
+          os.path.join(Local_Flows_Path, f)) and os.path.splitext(f)[-1] == '.flow']
+    except:
+      local_flow_list = []
+
+    with gr.Accordion('LightDiffusionFlow '+lightdiffusionflow_version.lightdiffusionflow_version + save_mode, open=True, visible=True, elem_id=cur_mode+'_lightdiffusionflow'):
+
+      with gr.Row():
+        State_Comps["local_flows"].append(gr.Dropdown(label="", show_label=False , multiselect=False, choices=local_flow_list,value='',elem_id=cur_mode+'_ldf_local_flows'))
+        State_Comps["apply"].append(ui_components.ToolButton(value=paste_symbol,elem_id=cur_mode+'_ldf_apply'))
+        #State_Comps["delete"].append(ui_components.ToolButton(value=clear_prompt_symbol,elem_id=cur_mode+'_ldf_delete'))
+        State_Comps["save"].append(ui_components.ToolButton(value=save_style_symbol,elem_id=cur_mode+'_ldf_save'))
+        State_Comps["refresh"].append(ui_components.ToolButton(value=refresh_symbol,elem_id=cur_mode+'_ldf_refresh'))
+
+      with gr.Row():
+        gr.HTML(label="",value="<hr style='margin-top:10px;margin-bottom:10px'></hr>")
+
+      with gr.Row():
+        lightdiffusionflow_file = gr.File(label="LightDiffusionFlow File",file_count="single", file_types=[File_extension], elem_id=cur_mode+'_ldf_import')
+        State_Comps["import"].append(lightdiffusionflow_file)
+        
+        with gr.Column(scale=1):
+          gr.HTML(label="",value='''
+          <a style ="text-decoration:underline;color:cornflowerblue;",
+          href="https://www.lightflow.ai/">开源社区/open-source community</a>''')
+          State_Comps["outlog"].append(gr.HTML(label="Output Log",elem_id=cur_mode+'_ldf_outlog',value='''
+          <p style=color:Red;>Welcome to LightDiffusionFlow!  \(^o^)/~</p>
+          <p style=color:MediumSeaGreen;>Welcome to LightDiffusionFlow!  \(^o^)/~</p>
+          <p style=color:DodgerBlue;>Welcome to LightDiffusionFlow!  \(^o^)/~</p>'''))
+
+      with gr.Row():
+        export_config = gr.Button(value='导出/Export',elem_id=cur_mode+'_ldf_export')
+        State_Comps["export"].append(export_config)
+
+      if(self.is_img2img):
+        State_Comps["background_import"] = gr.File(label="LightDiffusionFlow File",file_count="single",
+           file_types=[File_extension],visible=False)
+        State_Comps["json2js"] = gr.Textbox(label="json2js",visible=False)
+        State_Comps["test_button"] = gr.Button(value='测试',elem_id='test_button',visible=True)
+        State_Comps["refresh_log"] = gr.Button(value='刷新日志',elem_id='img2img_invisible_refresh_log',visible=False)
+        State_Comps["set_dropdowns"] = gr.Button(value='设置部分参数',elem_id='lightdiffusionflow_set_dropdowns',visible=False)
+        State_Comps["set_js_params"] = gr.Button(value='设置剩下的js参数',elem_id='lightdiffusionflow_set_js_params',visible=False)
+        State_Comps["set_file_button"] = gr.Button(value='设置文件',elem_id='set_lightdiffusionflow_file',visible=False)
+        State_Comps["preload_button"] = gr.Button(value='预加载',elem_id='preload_button',visible=False)
+
+        with gr.Row():
+          #State_Comps["useless_Textbox"] = \
+          #  gr.Textbox(value='useless_Textbox', elem_id='useless_Textbox', visible=False)
+          
+          #for key in lf_config.Image_Components_Key:
+          for key in extensions_id_conponents["image"].keys():
+            #print(key)
+            elem_id = ("img2img_" if self.is_img2img else "txt2img_") + "invisible_" + key
+            invisible_buttons[elem_id] = gr.Button(value=elem_id, elem_id=elem_id, visible=False)
+
+
+
+def on_after_component(component, **kwargs):
+  global Webui_Comps
+
+  # img2img和txt2img面板以外的组件信息只能在这里获取
+  # 如果希望python里控制这些组件，还需要把部分代码移到这里实现
+  try:
+    if(Webui_Comps.get(kwargs["elem_id"], None) == None):
+      Webui_Comps[kwargs["elem_id"]] = component
+      #if( kwargs["elem_id"] == "setting_sd_model_checkpoint"):
+      #  print("--------------setting_sd_model_checkpoint---------------")
+  except KeyError:
+    pass
+
+
+def on_before_reload():
+  lightdiffusionflow_config.init()
+
+# add callbacks
+api = StateApi()
+script_callbacks.on_app_started(api.start)
+script_callbacks.on_after_component(on_after_component)
+script_callbacks.on_before_reload(on_before_reload)

gf/LightDiffusionFlow/scripts/state_settings.py

@@ -0,0 +1,52 @@
+import gradio as gr
+import modules.shared as shared
+from modules import scripts
+from scripts import lightdiffusionflow_config
+#from scripts.lightdiffusionflow_config import OutputPrompt
+OutputPrompt = lightdiffusionflow_config.OutputPrompt
+
+def on_ui_settings():
+
+  section = ("lightdiffusionflow", "Light Diffusion Flow")
+
+    # "sd_lora": shared.OptionInfo("None", "Add network to prompt", gr.Dropdown,
+    # lambda: {"choices": ["None", *networks.available_networks]}, refresh=networks.list_available_networks),
+  shared.opts.add_option("lightdiffusionflow-language",
+    shared.OptionInfo(
+      "default",
+      "显示语言/Language", 
+      gr.Dropdown, 
+      lambda: {
+        "choices": ["default","中文","english"]
+      }, section=section)
+  )
+
+  shared.opts.add_option("lightdiffusionflow-mode",
+    shared.OptionInfo(
+      "All",
+      f"模式/Mode: ({OutputPrompt.note_for_save_mode()})",
+      gr.Dropdown, 
+      lambda: {
+        "choices": ["Core","All"]
+      }, section=section)
+  )
+
+  shared.opts.add_option("lightdiffusionflow-local-flows-path",
+    shared.OptionInfo(
+      default="models/LightDiffusionFlow",
+      label=f"本地保存的flow文件路径/Local path to save flow files",
+      #component=gr.TextBox,
+      section=section)
+  )
+
+  shared.opts.add_option("lightdiffusionflow-auto-fix-params",
+    shared.OptionInfo(
+      True,
+      f"自动纠正错误的参数/Automatically fix incorrect parameters",
+      gr.Checkbox, 
+      {"interactive": True}, 
+      section=section)
+  )
+
+
+scripts.script_callbacks.on_ui_settings(on_ui_settings)

gf/LightDiffusionFlow/style.css

@@ -0,0 +1,20 @@
+#settings_state_buttons button,
+#settings_state_buttons input[type="file"] {
+    color: white;
+    background: rgb(249, 115, 22);
+    border-radius: 8px;
+    padding: 5px 15px;
+    font-weight: bold;
+    font-size: 16px;
+    margin-left: 5px;
+    margin-right: 5px;
+}
+
+#settings_state_buttons input[type="file"] {
+    padding: 3px 5px;
+}
+
+#settings_state hr {
+    margin-top: 32px;
+    margin-bottom: 32px;
+}

gf/a1111-stable-diffusion-webui-vram-estimator/.gitignore

@@ -0,0 +1,6 @@
+.DS_Store
+.idea
+*.log
+tmp/
+
+stats.json

gf/a1111-stable-diffusion-webui-vram-estimator/LICENSE

@@ -0,0 +1,9 @@
+MIT License
+
+Copyright 2023 space-nuko
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

gf/a1111-stable-diffusion-webui-vram-estimator/README.md

@@ -0,0 +1,13 @@
+# VRAM Estimator for stable-diffusion-webui
+
+When using stable-diffusion-webui, if you find yourself frequently running out of VRAM or worried that pushing your settings too far will break your webui, this extension might be of use. It gathers a set of statistics based on running `txt2img` and `img2img` with various different settings and uses extrapolation to estimate the amount of VRAM your settings will use.
+
+![Preview](./static/preview.png)
+
+## Usage
+
+First you will need to gather some data from running a bunch of image generations for the extension to use (you'll only have to do this step once). Go to the `VRAM Estimator` tab and set the `Max Image Size` and `Max Batch Count` parameters to the maximum that your system can handle when generating with `txt2img` and Hires Fix enabled (Hires Fix uses more VRAM than plain `txt2img` even when the target resolution is the same). The default settings of size 960 and 8 batch count are appropriate for an RTX 3090. Make sure you've closed any other programs that can take up VRAM, then click `Run Benchmark` and watch the console for progress. The benchmark will generate several images at different resolutions with `txt2img` and `img2img` and save the VRAM used by each run.
+
+After the benchmark has finished, you can go to the `txt2img` or `img2img` tab and adjust the sliders for Width/Height/Hires Fix to see the estimated VRAM usage. Note that the estimate is based on the amount of used VRAM on your system at the time you change the slider. As a rule of thumb you should expect about 1 GB more of VRAM to actually be used by the generating operation you choose.
+
+Also note that this extension does not take into account VRAM allocated by other extensions like ControlNet; it only looks at the width, height and batch count of the vanilla generation config. If you update webui, it's worth running the benchmark again if you find the estimates are no longer accurate.

gf/a1111-stable-diffusion-webui-vram-estimator/scripts/vram_estimator.py

@@ -0,0 +1,405 @@
+import time
+import logging
+import socket
+import json
+import math
+import os.path
+import torch.cuda
+import numpy as np
+import scipy.linalg
+import scipy.optimize
+from collections import defaultdict
+from hashlib import sha256
+from PIL import Image
+from logging.handlers import SysLogHandler
+from modules import shared, script_callbacks, devices, scripts
+from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, Processed, process_images
+import gradio as gr
+import pandas as pd
+
+
+curves = {}
+stats_file = os.path.join(scripts.basedir(), "stats.json")
+
+
+class VRAMCurve():
+    """3d plane where x=pixels, y=batch_size, z=reserved_peak"""
+    def __init__(self, data):
+        arr = []
+        batch_sizes_x = defaultdict(list)
+        batch_sizes_y = defaultdict(list)
+        for entry in data:
+            size = math.sqrt(entry["pixels"])
+            batch_size = entry["batch_size"]
+            reserved = entry["reserved_peak"]
+
+            arr.append([size, batch_size, reserved])
+            batch_sizes_x[batch_size].append(size)
+            batch_sizes_y[batch_size].append(reserved)
+
+        data = np.array(arr)
+
+        # VRAM usage seems to scale linearly within one batch size, but the rate
+        # of increase differs between batch sizes with no real pattern
+        self.batch_sizes = {}
+        for k in batch_sizes_x.keys():
+            z = np.polyfit(batch_sizes_x[k], batch_sizes_y[k], 3)
+            f = np.poly1d(z)
+            self.batch_sizes[k] = f
+
+        # best-fit cubic curve
+        # M = [ones(size(x)), x, y, x.^2, x.*y, y.^2, x.^3, x.^2.*y, x.*y.^2, y.^3]
+        A = np.c_[np.ones(data.shape[0]), data[:,:2], data[:,0]**2, np.prod(data[:,:2], axis=1), \
+                data[:,1]**2, data[:,0]**3, np.prod(np.c_[data[:,0]**2,data[:,1]],axis=1), \
+                np.prod(np.c_[data[:,0],data[:,1]**2],axis=1), data[:,1]**3]
+        self.C,_,_,_ = scipy.linalg.lstsq(A, data[:,2])
+
+    def estimate(self, pixels, batch_size):
+        x = math.sqrt(pixels)
+        y = batch_size
+
+        if batch_size in self.batch_sizes:
+            return self.batch_sizes[batch_size](x)
+
+        return np.dot([1, x, y,
+                       x ** 2, x * y, y ** 2,
+                       x ** 3, x ** 2 * y, x * y ** 2, y ** 3], self.C)
+
+
+def load_curve():
+    global curves
+    if not os.path.isfile(stats_file):
+        print("[VRAMEstimator] No stats available, run benchmark first")
+        return None, None
+
+    with open(stats_file, "r", encoding="utf-8") as f:
+        data = json.load(f)
+
+    if "txt2img" not in data or "txt2img_hr" not in data or "txt2img_hr_latent" not in data or "img2img" not in data:
+        print("[VRAMEstimator] No stats available, run benchmark first")
+        return None, None
+
+    curves = {}
+    for k, v in data.items():
+        curves[k] = VRAMCurve(v)
+
+    print("[VRAMEstimator] Loaded benchmark data.")
+    return make_plots(data)
+
+
+def get_memory_stats():
+    devices.torch_gc()
+    torch.cuda.reset_peak_memory_stats()
+    shared.mem_mon.monitor()
+    return {k: -(v//-(1024*1024)) for k, v in shared.mem_mon.stop().items()}
+
+
+def run_benchmark(max_width, max_batch_count):
+    global curves
+    DEFAULT_ARGS = {
+        'sd_model': shared.sd_model,
+        'prompt': 'postapocalyptic steampunk city, exploration, cinematic, realistic, hyper detailed, photorealistic maximum detail, volumetric light, (((focus))), wide-angle, (((brightly lit))), (((vegetation))), lightning, vines, destruction, devastation, wartorn, ruins',
+        'sampler_name': 'Euler a',
+        'batch_size': 1,
+        'n_iter': 1,
+        'steps': 1,
+        'cfg_scale': 15.0,
+        'width': 512,
+        'height': 512,
+        'restore_faces': False,
+        'tiling': False,
+        'do_not_save_samples': True,
+        'do_not_save_grid': True,
+        'negative_prompt': '(((blurry))), ((foggy)), (((dark))), ((monochrome)), sun, (((depth of field)))',
+        'do_not_reload_embeddings': True
+    }
+    results = {}
+
+    print("[VRAMEstimator] Starting benchmark...")
+    mem_stats = get_memory_stats()
+    base_active = mem_stats["active_peak"]
+    base_reserved = mem_stats["reserved_peak"]
+    base_used = mem_stats["total"] - mem_stats["free"]
+
+    shared.state.begin()
+    shared.state.job = "VRAM Estimator Benchmark"
+    shared.state.job_count = max_batch_count * int((max_width - 256) / 64)
+
+    for op in ["txt2img", "txt2img_hr", "txt2img_hr_latent", "img2img"]:
+        results[op] = []
+        for b in range(1, max_batch_count+1):
+            for i in range(256, max_width+64, 64):
+                #More verbose and informative progress strings
+                print(f"run benchmark:\nOperation: {op} \nBatch Count: {b}\nWidth: {i}")
+                devices.torch_gc()
+                torch.cuda.reset_peak_memory_stats()
+                shared.mem_mon.monitor()
+                shared.state.begin()
+
+                args = DEFAULT_ARGS.copy()
+                args["batch_size"] = b
+
+                if op == "txt2img":
+                    args["width"] = i
+                    args["height"] = i
+                    p = StableDiffusionProcessingTxt2Img(**args)
+                elif op.startswith("txt2img_hr"):
+                    args["width"] = int(i / 2)
+                    args["height"] = int(i / 2)
+                    args["enable_hr"] = True
+                    args["hr_second_pass_steps"] = 1
+                    args["hr_resize_x"] = i
+                    args["hr_resize_y"] = i
+                    if op == "txt2img_hr_latent":
+                        args["hr_upscaler"] = "Latent"
+                    else:
+                        args["hr_upscaler"] = "Lanczos"
+                    p = StableDiffusionProcessingTxt2Img(**args)
+                elif op == "img2img":
+                    args["width"] = i
+                    args["height"] = i
+                    args["init_images"] = [Image.new("RGB", (512, 512))]
+                    p = StableDiffusionProcessingImg2Img(**args)
+                else:
+                    print(f'unknown operation: {op}')
+                    return 'error'
+
+                t0 = time.time()
+                try:
+                    process_images(p)
+                except Exception as e:
+                    print(f'benchmark error: {e}')
+                    shared.state.end()
+                    break
+
+                t1 = time.time()
+                shared.state.end()
+
+                its = args["steps"] * args["batch_size"] / (t1 - t0)
+
+                mem_stats = {k: -(v//-(1024*1024)) for k, v in shared.mem_mon.stop().items()}
+                results[op].append({
+                    "width": i,
+                    "pixels": i * i,
+                    "batch_size": args["batch_size"],
+                    "active_peak": mem_stats["active_peak"] - base_active,
+                    "reserved_peak": mem_stats["reserved_peak"] - base_reserved,
+                    "sys_peak": mem_stats["system_peak"],
+                    "sys_total": mem_stats["total"],
+                    "its": round(its, 2)
+                })
+
+                with open(stats_file, "w", encoding="utf-8") as f:
+                    json.dump(results, f)
+
+                del p
+                del args
+
+    curves = {}
+    for k, v in results.items():
+        curves[k] = VRAMCurve(v)
+
+    shared.state.end()
+    print("[VRAMEstimator] Benchmark finished.")
+
+    results = make_plots(results)
+    results.append("<span>Benchmark finished.</span>")
+    return results
+
+
+def make_plots(results):
+    dfs = []
+
+    for op in ["txt2img", "txt2img_hr", "txt2img_hr_latent", "img2img"]:
+        x = []
+        y = []
+        z = []
+
+        for result in results[op]:
+            x.append(result["pixels"])
+            y.append(result["reserved_peak"])
+            z.append(result["batch_size"])
+
+        df = pd.DataFrame({"pixels": x, "reserved_peak": y, "batch_size": z})
+        dfs.append(df)
+
+    return dfs
+
+
+def on_ui_tabs():
+    load_curve()
+
+    with gr.Blocks(analytics_enabled=False) as vram_estimator_tab:
+        with gr.Row():
+            plot = gr.LinePlot(title="txt2img Reserved VRAM", x="pixels", y="reserved_peak", color="batch_size", width=400, height=400, tooltip=["pixels", "reserved_peak", "batch_size"])
+            plot2 = gr.LinePlot(title="txt2img Highres Fix Reserved VRAM", x="pixels", y="reserved_peak", color="batch_size", width=400, height=400, tooltip=["pixels", "reserved_peak", "batch_size"])
+        with gr.Row():
+            plot3 = gr.LinePlot(title="txt2img Highres Fix (Latent) Reserved VRAM", x="pixels", y="reserved_peak", color="batch_size", width=400, height=400, tooltip=["pixels", "reserved_peak", "batch_size"])
+            plot4 = gr.LinePlot(title="img2img Reserved VRAM", x="pixels", y="reserved_peak", color="batch_size", width=400, height=400, tooltip=["pixels", "reserved_peak", "batch_size"])
+        with gr.Row():
+            width = gr.Slider(minimum=256, maximum=2048, step=64, label="Max Image Size", value=1024)
+            batch_count = gr.Slider(minimum=1, maximum=16, step=1, label="Max Batch Count", value=8)
+            with gr.Column():
+                bench_run_btn = gr.Button("Run benchmark", variant="primary").style(full_width=False)
+                load_results_button = gr.Button("Load results").style(full_width=False)
+                with gr.Row():
+                    status = gr.HTML("")
+
+        bench_run_btn.click(run_benchmark, inputs=[width, batch_count], outputs=[plot, plot2, plot3, plot4, status])
+        load_results_button.click(load_curve, inputs=[], outputs=[plot, plot2, plot3, plot4])
+
+    return [(vram_estimator_tab, "VRAM Estimator", "vram_estimator_tab")]
+
+
+heatmap = [
+    [-1.0, (0.2, 0.2, 1.0)],
+    [ 0.0, (0.2, 0.2, 1.0)],
+    [ 0.2, (0.0, 1.0, 1.0)],
+    [ 0.4, (0.0, 1.0, 0.0)],
+    [ 0.6, (1.0, 1.0, 0.0)],
+    [ 0.8, (1.0, 0.0, 0.0)],
+    [ 1.0, (1.0, 0.0, 0.8)],
+    [ 2.0, (1.0, 0.0, 0.8)],
+]
+
+
+def gaussian(x, a, b, c, d=0):
+    return a * math.exp(-(x - b)**2 / (2 * c**2)) + d
+
+def get_color(x, map=[], spread=1):
+    x = min(1.0, max(0, x))
+    r = min(1.0, sum([gaussian(x, p[1][0], p[0], 1.0 / (spread * len(map))) for p in map]))
+    g = min(1.0, sum([gaussian(x, p[1][1], p[0], 1.0 / (spread * len(map))) for p in map]))
+    b = min(1.0, sum([gaussian(x, p[1][2], p[0], 1.0 / (spread * len(map))) for p in map]))
+    return 'rgb(%.2f, %.2f, %.2f)' % (r * 255, g * 255, b * 255)
+
+
+def make_span(reserved_vram_estimate):
+    if shared.state.job_count != 0:
+        return '<div style="padding: 10px"><span>(Currently generating...)</span></div>'
+
+    mem_stats = get_memory_stats()
+
+    # VRAM estimate is taken after used system VRAM is subtracted
+    base_rest = mem_stats["total"] - mem_stats["free"]
+    estimate_total = base_rest + reserved_vram_estimate * 1.1 # buffer
+
+    formatted_est = f"{round(estimate_total, 2):.2f} MB"
+    formatted_total = f"{mem_stats['total']} MB"
+    percent_usage = estimate_total / mem_stats['total']
+    color = get_color(percent_usage, map=heatmap, spread=1.5)
+
+    return f'''
+    <div style="padding: 10px">
+      <div>Estimated VRAM usage: <span style="color: {color}">{formatted_est} / {formatted_total} ({percent_usage * 100:.2f}%)</span></div>
+      <div>({base_rest} MB system + {reserved_vram_estimate:.2f} MB used)</div>
+    </div>
+    '''
+
+
+def estimate_vram_txt2img(width, height, batch_size, enable_hr, hr_upscaler, hr_scale, hr_resize_x, hr_resize_y):
+    global curves
+    if "txt2img" not in curves or "txt2img_hr" not in curves:
+        return "<span>(No stats yet, run benchmark in VRAM Estimator tab)</span>"
+
+    final_width = width
+    final_height = height
+
+    if enable_hr:
+        if hr_resize_x == 0 and hr_resize_y == 0:
+            final_width = width * hr_scale
+            final_height = height * hr_scale
+        else:
+            if hr_resize_y == 0:
+                final_width = hr_resize_x
+                final_height = hr_resize_x * height // width
+            elif hr_resize_x == 0:
+                final_width = hr_resize_y * width // height
+                final_height = hr_resize_y
+            else:
+                src_ratio = width / height
+                dst_ratio = hr_resize_x / hr_resize_y
+
+                if src_ratio < dst_ratio:
+                    final_width = hr_resize_x
+                    final_height = hr_resize_x * height // width
+                else:
+                    final_width = hr_resize_y * width // height
+                    final_height = hr_resize_y
+
+        if hr_upscaler in shared.latent_upscale_modes:
+            upscaler_curve = "txt2img_hr_latent"
+        else:
+            upscaler_curve = "txt2img_hr"
+        print(hr_upscaler)
+        print(upscaler_curve)
+
+        vram_estimate_normal = curves["txt2img"].estimate(final_width * final_height, batch_size)
+        vram_estimate_hr = curves[upscaler_curve].estimate(final_width * final_height, batch_size)
+        vram_estimate = max(vram_estimate_normal, vram_estimate_hr)
+    else:
+        vram_estimate = curves["txt2img"].estimate(final_width * final_height, batch_size)
+
+    return make_span(vram_estimate)
+
+
+def estimate_vram_img2img(width, height, batch_size):
+    global curves
+    if "img2img" not in curves:
+        return "<span>(No stats yet, run benchmark in VRAM Estimator tab)</span>"
+
+    vram_estimate = curves["img2img"].estimate(width * height, batch_size)
+    return make_span(vram_estimate)
+
+
+class Script(scripts.Script):
+    def title(self):
+        return "VRAM Usage Estimator"
+
+    def show(self, is_img2img):
+        return scripts.AlwaysVisible
+
+    def ui(self, is_img2img):
+        with gr.Group():
+            with gr.Row():
+                vram_status = gr.HTML()
+
+        #Some extensions co-exist with vram estimator by throwing an error on load but nothing is wrong
+        try:
+            if is_img2img:
+                inputs = [self.i2i_width, self.i2i_height, self.i2i_batch_size]
+                fn = estimate_vram_img2img
+            else:
+                inputs = [self.t2i_width, self.t2i_height, self.t2i_batch_size, self.t2i_enable_hr, self.t2i_hr_upscaler, self.t2i_hr_scale, self.t2i_hr_resize_x, self.t2i_hr_resize_y]
+                fn = estimate_vram_txt2img
+        
+
+            for input in inputs:
+                input.change(
+                    fn=fn,
+                    inputs=inputs,
+                    outputs=[vram_status],
+                    show_progress=False,
+                )
+        #So if it thinks something is wrong, we'll just tell it to carry on        
+        except Exception as e:
+            return [vram_status]
+        return [vram_status]
+
+    def after_component(self, component, **kwargs):
+        elem_id = kwargs.get("elem_id")
+
+        if   elem_id == "txt2img_width":        self.t2i_width = component
+        elif elem_id == "txt2img_height":       self.t2i_height = component
+        elif elem_id == "txt2img_batch_size":   self.t2i_batch_size = component
+        elif elem_id == "txt2img_enable_hr":    self.t2i_enable_hr = component
+        elif elem_id == "txt2img_hr_upscaler":  self.t2i_hr_upscaler = component
+        elif elem_id == "txt2img_hr_scale":     self.t2i_hr_scale = component
+        elif elem_id == "txt2img_hr_resize_x":  self.t2i_hr_resize_x = component
+        elif elem_id == "txt2img_hr_resize_y":  self.t2i_hr_resize_y = component
+        elif elem_id == "img2img_width":        self.i2i_width = component
+        elif elem_id == "img2img_height":       self.i2i_height = component
+        elif elem_id == "img2img_batch_size":   self.i2i_batch_size = component
+
+
+script_callbacks.on_ui_tabs(on_ui_tabs)

gf/asymmetric-tiling-sd-webui/.gitignore

@@ -0,0 +1 @@
+*.pyc

gf/asymmetric-tiling-sd-webui/LICENSE

@@ -0,0 +1,121 @@
+Creative Commons Legal Code
+
+CC0 1.0 Universal
+
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+    LEGAL SERVICES. DISTRIBUTION OF THIS DOCUMENT DOES NOT CREATE AN
+    ATTORNEY-CLIENT RELATIONSHIP. CREATIVE COMMONS PROVIDES THIS
+    INFORMATION ON AN "AS-IS" BASIS. CREATIVE COMMONS MAKES NO WARRANTIES
+    REGARDING THE USE OF THIS DOCUMENT OR THE INFORMATION OR WORKS
+    PROVIDED HEREUNDER, AND DISCLAIMS LIABILITY FOR DAMAGES RESULTING FROM
+    THE USE OF THIS DOCUMENT OR THE INFORMATION OR WORKS PROVIDED
+    HEREUNDER.
+
+Statement of Purpose
+
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+will not (i) exercise any of his or her remaining Copyright and Related
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+express Statement of Purpose.
+
+4. Limitations and Disclaimers.
+
+ a. No trademark or patent rights held by Affirmer are waived, abandoned,
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+ b. Affirmer offers the Work as-is and makes no representations or
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gf/asymmetric-tiling-sd-webui/README.md

@@ -0,0 +1,22 @@
+# Asymmetric Tiling for stable-diffusion-webui
+
+An always visible script extension for [stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui/) to configure seamless image tiling independently for the X and Y axes.
+
+To use, install this repository from the "Extensions" tab in stable-diffusion-webui, restart your server, open the `Asymmetric tiling` foldout on txt2img or img2img, and make it active, and check `Tile X` or `Tile Y` as desired. While this script is active, the `Tiling` checkbox in the main UI will be ignored.
+
+Like existing tiling options this won't guarantee seamless tiling 100% of the time, but it should manage it for most prompts. You can check that images tile seamlessly using online tools like [Seamless Texture Check](https://www.pycheung.com/checker/).
+
+For the old, non-extension version of this script, use the "classic_script" branch.
+
+## X axis tiling examples
+
+![00817-3274117678-midnight cityscape, stunning environment, wide-angle, massive scale, landscape, panoramic, lush vegetation, idyllic](https://user-images.githubusercontent.com/19196175/195132862-8c050327-92f3-44a4-9c02-0f11cce0b609.png)
+![01064-1316547214-(((domino run))), domino toppling, line of standing dominoes, domino cascade, domino effect, black dominos](https://user-images.githubusercontent.com/19196175/195137782-e72fc69a-14f1-4ae7-bac2-219734509aea.png)
+
+## Y Axis tiling examples
+
+![00840-2320166501-man climbing ladder, safety diagram](https://user-images.githubusercontent.com/19196175/195132867-1b36848e-135d-4103-8e10-1d760b3a0a4e.png)![01095-949590403-tree, thick branches, photograph, 80mm Sigma f1 4, studio quality, nature photography](https://user-images.githubusercontent.com/19196175/195140638-49b0a4be-fbca-45bc-8e52-6c985202ce29.png)
+
+## Update 2024/04/05
+
+Support Forge (https://github.com/lllyasviel/stable-diffusion-webui-forge)

gf/asymmetric-tiling-sd-webui/scripts/asymmetric_tiling.py

@@ -0,0 +1,116 @@
+import typing as tg
+
+import gradio as gr
+from torch import Tensor
+from torch.nn import Conv2d
+from torch.nn import functional as F
+from torch.nn.modules.utils import _pair
+
+import modules.scripts
+import modules.sd_hijack
+import modules.shared
+
+try:
+    from modules_forge.unet_patcher import UnetPatcher  # type: ignore
+
+    IS_FORGE = True
+except ImportError:
+    IS_FORGE = False
+
+
+# Asymmetric tiling script for stable-diffusion-webui
+#
+# This script allows seamless tiling to be enabled separately for the X and Y axes.
+# When this script is in use, the "Tiling" option in the regular UI is ignored.
+class Script(modules.scripts.Script):
+    # Override from modules.scripts.Script
+    def title(self):
+        return "Asymmetric tiling"
+
+    # Override from modules.scripts.Script
+    def show(self, is_img2img):
+        return modules.scripts.AlwaysVisible
+
+    # Override from modules.scripts.Script
+    def ui(self, is_img2img):
+        with gr.Accordion("Asymmetric tiling", open=False):
+            active = gr.Checkbox(False, label="Active")
+            tileX = gr.Checkbox(True, label="Tile X")
+            tileY = gr.Checkbox(False, label="Tile Y")
+            startStep = gr.Number(0, label="Start tiling from step N", precision=0)
+            stopStep = gr.Number(-1, label="Stop tiling after step N (-1: Don't stop)", precision=0)
+
+        return [active, tileX, tileY, startStep, stopStep]
+
+    # Override from modules.scripts.Script
+    def process(self, p, active, tileX, tileY, startStep, stopStep):
+        if (active):
+            # Record tiling options chosen for each axis.
+            p.extra_generation_params = {
+                "Tile X": tileX,
+                "Tile Y": tileY,
+                "Start Tiling From Step": startStep,
+                "Stop Tiling After Step": stopStep,
+            }
+
+            # Modify the model's Conv2D layers to perform our chosen tiling.
+            if IS_FORGE:
+                unet_patcher = tg.cast(UnetPatcher, p.sd_model.forge_objects.unet).clone()
+                layers = [layer for layer in unet_patcher.model.modules() if isinstance(layer, Conv2d)]
+                self.__hijackConv2DMethods(layers, tileX, tileY, startStep, stopStep)
+                p.sd_model.forge_objects.unet = unet_patcher
+            else:
+                layers = [layer for layer in tg.cast(list, modules.sd_hijack.model_hijack.layers) if isinstance(layer, Conv2d)]
+                self.__hijackConv2DMethods(layers, tileX, tileY, startStep, stopStep)
+        else:
+            # Restore model behaviour to normal.
+            if IS_FORGE:
+                unet_patcher = tg.cast(UnetPatcher, p.sd_model.forge_objects.unet).clone()
+                layers = [layer for layer in unet_patcher.model.modules() if isinstance(layer, Conv2d)]
+                self.__restoreConv2DMethods(layers)
+                p.sd_model.forge_objects.unet = unet_patcher
+            else:
+                layers = [layer for layer in tg.cast(list, modules.sd_hijack.model_hijack.layers) if layer if isinstance(layer, Conv2d)]
+                self.__restoreConv2DMethods(layers)
+
+    def postprocess(self, *args):
+        # Restore model behaviour to normal.
+        if not IS_FORGE:
+            layers = [layer for layer in tg.cast(list, modules.sd_hijack.model_hijack.layers) if isinstance(layer, Conv2d)]
+            self.__restoreConv2DMethods(layers)
+
+    # [Private]
+    # Go through all the "Conv2D" layers in the model and patch them to use the requested asymmetric tiling mode.
+    def __hijackConv2DMethods(self, layers: list, tileX: bool, tileY: bool,  startStep: int, stopStep: int):
+        for layer in layers:
+            layer.padding_modeX = 'circular' if tileX else 'constant'
+            layer.padding_modeY = 'circular' if tileY else 'constant'
+            layer.paddingX = (layer._reversed_padding_repeated_twice[0], layer._reversed_padding_repeated_twice[1], 0, 0)
+            layer.paddingY = (0, 0, layer._reversed_padding_repeated_twice[2], layer._reversed_padding_repeated_twice[3])
+            layer.paddingStartStep = startStep
+            layer.paddingStopStep = stopStep
+            layer._conv_forward = TilingConv2d.replacementConv2DConvForward.__get__(layer, Conv2d)
+
+    # [Private]
+    # Go through all the "Conv2D" layers in the model and restore them to their origanal behaviour.
+    def __restoreConv2DMethods(self, layers: list):
+        for layer in layers:
+            layer._conv_forward = Conv2d._conv_forward.__get__(layer, Conv2d)
+
+
+class TilingConv2d(Conv2d):
+    # A replacement for the Conv2d._conv_forward method that pads axes asymmetrically.
+    # This replacement method performs the same operation (as of torch v1.12.1+cu113), but it pads the X and Y axes separately based on the members
+    #   padding_modeX (string, either 'circular' or 'constant')
+    #   padding_modeY (string, either 'circular' or 'constant')
+    #   paddingX (tuple, cached copy of _reversed_padding_repeated_twice with the last two values zeroed)
+    #   paddingY (tuple, cached copy of _reversed_padding_repeated_twice with the first two values zeroed)
+    def replacementConv2DConvForward(self, input: Tensor, weight: Tensor, bias: Tensor | None):
+        step = modules.shared.state.sampling_step
+        if ((self.paddingStartStep < 0 or step >= self.paddingStartStep) and (self.paddingStopStep < 0 or step <= self.paddingStopStep)):
+            working = F.pad(input, self.paddingX, mode=self.padding_modeX)
+            working = F.pad(working, self.paddingY, mode=self.padding_modeY)
+        else:
+            working = F.pad(input, self.paddingX, mode='constant')
+            working = F.pad(working, self.paddingY, mode='constant')
+        return F.conv2d(working, weight, bias, self.stride, _pair(0), self.dilation, self.groups)

gf/sd-webui-crop-extension/.gitignore

@@ -0,0 +1,2 @@
+
+*.pyc

gf/sd-webui-crop-extension/install.py

@@ -0,0 +1,6 @@
+import launch
+# launch is imported in context of webui
+if not launch.is_installed("dghs-imgutils") and not launch.is_installed("dghs-imgutils[gpu]"):
+    import torch.cuda as cuda
+    print("Installing dghs-imgutils")
+    launch.run_pip("install dghs-imgutils[gpu]" if cuda.is_available() else "install dghs-imgutils")

gf/sd-webui-crop-extension/scripts/ui.py

@@ -0,0 +1,32 @@
+from modules import script_callbacks
+import gradio as gr
+from PIL import Image
+import numpy as np
+from imgutils.detect import detect_halfbody, detect_heads
+
+
+def on_ui_tab_called():
+    with gr.Blocks() as transparent_interface:
+        with gr.Row():
+            with gr.Tabs():
+                with gr.TabItem("CropHead"):
+                    image_upload_input = gr.Image(label="Upload Image", source="upload",type="pil")
+                    button = gr.Button(label="Convert")
+                    image_upload_output = gr.Image(label="Output Image",type="numpy")
+                    
+                    def convert_image(image:Image.Image):
+                        # first convert to RGB
+                        if image.mode == "RGBA":
+                            # convert transparent pixels to white
+                            white_image = Image.new("RGB", image.size, (255, 255, 255))
+                            white_image.paste(image, mask=image.split()[3])
+                            image = white_image
+                        else:
+                            image = image.convert("RGB")
+                        result = detect_heads(image)
+                        new_image = image.crop(result[0][0])
+                        return new_image # return the new image
+                    button.click(convert_image, inputs=[image_upload_input], outputs=[image_upload_output])
+    return (transparent_interface, "CropHead", "script_crophead_interface"),
+
+script_callbacks.on_ui_tabs(on_ui_tab_called)

gf/sd-webui-lua/.github/FUNDING.yml

@@ -0,0 +1 @@
+ko_fi: Yownas

gf/sd-webui-lua/.gitignore

@@ -0,0 +1 @@
+__pycache__

gf/sd-webui-lua/LICENSE

@@ -0,0 +1,674 @@
+                    GNU GENERAL PUBLIC LICENSE
+                       Version 3, 29 June 2007
+
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gf/sd-webui-lua/README.md

@@ -0,0 +1,38 @@
+# sd-webui-lua
+Generate images with Lua scripts in Stable Diffusion webui.
+
+This is an extension for [Vlad's SD.next](https://github.com/vladmandic/automatic/) and [automatic1111's stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) to let you run Lua code to generate images (and more?).
+
+# Installation
+
+Under `Extensions` go to `Manual install` and paste the link to this repository. Click `Install`.
+
+# Usage
+
+It too early to try writing some sort of proper guide. But all functions should be listed if you open up the "Lua Extras..." at the bottom, but the best way to get started is probably by looking in the `examples` folder and tinker with those. There are also some information in the wiki.
+
+![sd-webui-lua](https://github.com/yownas/sd-webui-lua/assets/13150150/f5bbd9f0-1519-4219-8ff0-a296c4ec1172)
+
+# Why?
+
+This project started as a joke, but quickly turned into a fun way to dig into and learn more about the code behind the webui. It also turned out
+to be a fun tool to generate images in weird ways that normally isn't really possible through the webui. So, is this an amazing tool to help you
+generate beautiful images? No. But it will probably be fun to play with if you know a little about how Stable Diffusion works, but not enough
+to be comfortable to write your own code from scratch.
+
+With this extension you can let the webui do the heavy lifting but still have access to poke at things on a fairly low level.
+
+# Issues & todo
+
+* Better css for the poor Code-box.
+
+* Needs a lot more functions to manipulate/access things. (and a save button/function)
+
+* Split sd.sample() into more parts.
+
+* Maybe import the diffusers-library, but I'm not sure how to use that with ckpt/safetensors.
+
+* More examples to show how things work. (Or actual documentation)
+
+* More ideas. I'd rather have a PR than a vague Issue. But I'm happy for any input. :)
+

gf/sd-webui-lua/examples/basics/README_example.lua

@@ -0,0 +1,9 @@
+-- This is the example in the README - Yownas
+
+for i = 1, 12, 1 do
+  ui.status("Generating " .. input .. " #" .. i)
+  img = sd.process('a cute ' .. input)
+  ui.gallery.add(img)
+end
+
+return("Done...")

gf/sd-webui-lua/examples/basics/show_samplers.lua

@@ -0,0 +1,10 @@
+-- Simple example on how to list available samplers - Yownas
+ 
+-- To iterate over the list from python we'll use python.iter()
+
+samplers = sd.getsamplers()
+
+ui.out("Samplers:")
+for name in python.iter(samplers) do
+  ui.out(name)
+end

gf/sd-webui-lua/examples/basics/simple_output.lua

@@ -0,0 +1,21 @@
+-- Simple output examples - Yownas
+
+-- Clear Output box
+ui.clear()
+
+-- Add text to Output
+ui.out("Adding text to Output with ui.out()")
+
+-- These two have basically the same functionality
+print("Using print()")
+ui.console("Using ui.consol()")
+
+-- Log 
+ui.log.info("Some information.")
+ui.log.warning("A warning!")
+ui.log.error("An error! Help!")
+
+-- An optional return() will write to the Output box
+a = 1
+b = 2
+return(a + b)