Merge pull request #1379 from easydiffusion/yaml-legacy-path

Handle the legacy yaml config path

.gitignore

@@ -3,3 +3,4 @@ installer
 installer.tar
 dist
 .idea/*
+node_modules/*

.prettierignore

@@ -0,0 +1,9 @@
+*.min.*
+*.py
+*.json
+*.html
+/*
+!/ui
+/ui/easydiffusion
+!/ui/plugins
+!/ui/media

.prettierrc.json

@@ -0,0 +1,7 @@
+{
+    "printWidth": 120,
+    "tabWidth": 4,
+    "semi": false,
+    "arrowParens": "always",
+    "trailingComma": "es5"
+}

3rd-PARTY-LICENSES

@@ -4,24 +4,711 @@ https://craftpip.github.io/jquery-confirm/
 
 jquery-confirm is licensed under the MIT license:
 
-  The MIT License (MIT)
+    The MIT License (MIT)
+  
+    Copyright (c) 2019 Boniface Pereira
+  
+    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.
 
-  Copyright (c) 2019 Boniface Pereira
 
-  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:
+jszip
+=====
+https://stuk.github.io/jszip/
 
-  The above copyright notice and this permission notice shall be included in all
-  copies or substantial portions of the Software.
+JSZip is dual licensed. At your choice you may use it under the MIT license *or* the GPLv3
+license.
 
-  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
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-  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.
+    The MIT License
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+    
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+                         END OF TERMS AND CONDITIONS
+
+FileSaver.js
+============
+https://github.com/eligrey/FileSaver.js
+
+FileSaver.js is licensed under the MIT license:
+
+    The MIT License
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+    Copyright © 2016 [Eli Grey][1].
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+    SOFTWARE.
+    
+      [1]: http://eligrey.com

CHANGES.md

@@ -1,5 +1,125 @@
 # What's new?
 
+## v2.5
+### Major Changes
+- **Nearly twice as fast** - significantly faster speed of image generation. Code contributions are welcome to make our project even faster: https://github.com/easydiffusion/sdkit/#is-it-fast
+- **Mac M1/M2 support** - Experimental support for Mac M1/M2. Thanks @michaelgallacher, @JeLuf and vishae.
+- **AMD support for Linux** - Experimental support for AMD GPUs on Linux. Thanks @DianaNites and @JeLuf.
+- **Full support for Stable Diffusion 2.1 (including CPU)** - supports loading v1.4 or v2.0 or v2.1 models seamlessly. No need to enable "Test SD2", and no need to add `sd2_` to your SD 2.0 model file names. Works on CPU as well.
+- **Memory optimized Stable Diffusion 2.1** - you can now use Stable Diffusion 2.1 models, with the same low VRAM optimizations that we've always had for SD 1.4. Please note, the SD 2.0 and 2.1 models require more GPU and System RAM, as compared to the SD 1.4 and 1.5 models.
+- **11 new samplers!** - explore the new samplers, some of which can generate great images in less than 10 inference steps! We've added the Karras and UniPC samplers. Thanks @Schorny for the UniPC samplers.
+- **Model Merging** - You can now merge two models (`.ckpt` or `.safetensors`) and output `.ckpt` or `.safetensors` models, optionally in `fp16` precision. Details: https://github.com/cmdr2/stable-diffusion-ui/wiki/Model-Merging . Thanks @JeLuf.
+- **Fast loading/unloading of VAEs** - No longer needs to reload the entire Stable Diffusion model, each time you change the VAE
+- **Database of known models** - automatically picks the right configuration for known models. E.g. we automatically detect and apply "v" parameterization (required for some SD 2.0 models), and "fp32" attention precision (required for some SD 2.1 models).
+- **Color correction for img2img** - an option to preserve the color profile (histogram) of the initial image. This is especially useful if you're getting red-tinted images after inpainting/masking.
+- **Three GPU Memory Usage Settings** - `High` (fastest, maximum VRAM usage), `Balanced` (default - almost as fast, significantly lower VRAM usage), `Low` (slowest, very low VRAM usage). The `Low` setting is applied automatically for GPUs with less than 4 GB of VRAM.
+- **Find models in sub-folders** - This allows you to organize your models into sub-folders inside `models/stable-diffusion`, instead of keeping them all in a single folder. Thanks @patriceac and @ogmaresca.
+- **Custom Modifier Categories** - Ability to create custom modifiers with thumbnails, and custom categories (and hierarchy of categories). Details: https://github.com/cmdr2/stable-diffusion-ui/wiki/Custom-Modifiers . Thanks @ogmaresca.
+- **Embed metadata, or save as TXT/JSON** - You can now embed the metadata directly into the images, or save them as text or json files (choose in the Settings tab). Thanks @patriceac.
+- **Major rewrite of the code** - Most of the codebase has been reorganized and rewritten, to make it more manageable and easier for new developers to contribute features. We've separated our core engine into a new project called `sdkit`, which allows anyone to easily integrate Stable Diffusion (and related modules like GFPGAN etc) into their programming projects (via a simple `pip install sdkit`): https://github.com/easydiffusion/sdkit/
+- **Name change** - Last, and probably the least, the UI is now called "Easy Diffusion". It indicates the focus of this project - an easy way for people to play with Stable Diffusion.
+
+Our focus continues to remain on an easy installation experience, and an easy user-interface. While still remaining pretty powerful, in terms of features and speed.
+
+### Detailed changelog
+* 2.5.41 - 24 Jun 2023 - (beta-only) Fix broken inpainting in low VRAM usage mode.
+* 2.5.41 - 24 Jun 2023 - (beta-only) Fix a recent regression where the LoRA would not get applied when changing SD models.
+* 2.5.41 - 23 Jun 2023 - Fix a regression where latent upscaler stopped working on PCs without a graphics card.
+* 2.5.41 - 20 Jun 2023 - Automatically fix black images if fp32 attention precision is required in diffusers.
+* 2.5.41 - 19 Jun 2023 - Another fix for multi-gpu rendering (in all VRAM usage modes).
+* 2.5.41 - 13 Jun 2023 - Fix multi-gpu bug with "low" VRAM usage mode while generating images.
+* 2.5.41 - 12 Jun 2023 - Fix multi-gpu bug with CodeFormer.
+* 2.5.41 - 6 Jun 2023 - Allow changing the strength of CodeFormer, and slightly improved styling of the CodeFormer options.
+* 2.5.41 - 5 Jun 2023 - Allow sharing an Easy Diffusion instance via https://try.cloudflare.com/ . You can find this option at the bottom of the Settings tab. Thanks @JeLuf.
+* 2.5.41 - 5 Jun 2023 - Show an option to download for tiled images. Shows a button on the generated image. Creates larger images by tiling them with the image generated by Easy Diffusion. Thanks @JeLuf.
+* 2.5.41 - 5 Jun 2023 - (beta-only) Allow LoRA strengths between -2 and 2. Thanks @ogmaresca.
+* 2.5.40 - 5 Jun 2023 - Reduce the VRAM usage of Latent Upscaling when using "balanced" VRAM usage mode.
+* 2.5.40 - 5 Jun 2023 - Fix the "realesrgan" key error when using CodeFormer with more than 1 image in a batch.
+* 2.5.40 - 3 Jun 2023 - Added CodeFormer as another option for fixing faces and eyes. CodeFormer tends to perform better than GFPGAN for many images. Thanks @patriceac for the implementation, and for contacting the CodeFormer team (who were supportive of it being integrated into Easy Diffusion).
+* 2.5.39 - 25 May 2023 - (beta-only) Seamless Tiling - make seamlessly tiled images, e.g. rock and grass textures. Thanks @JeLuf.
+* 2.5.38 - 24 May 2023 - Better reporting of errors, and show an explanation if the user cannot disable the "Use CPU" setting.
+* 2.5.38 - 23 May 2023 - Add Latent Upscaler as another option for upscaling images. Thanks @JeLuf for the implementation of the Latent Upscaler model.
+* 2.5.37 - 19 May 2023 - (beta-only) Two more samplers: DDPM and DEIS. Also disables the samplers that aren't working yet in the Diffusers version. Thanks @ogmaresca.
+* 2.5.37 - 19 May 2023 - (beta-only) Support CLIP-Skip. You can set this option under the models dropdown. Thanks @JeLuf.
+* 2.5.37 - 19 May 2023 - (beta-only) More VRAM optimizations for all modes in diffusers. The VRAM usage for diffusers in "low" and "balanced" should now be equal or less than the non-diffusers version. Performs softmax in half precision, like sdkit does.
+* 2.5.36 - 16 May 2023 - (beta-only) More VRAM optimizations for "balanced" VRAM usage mode.
+* 2.5.36 - 11 May 2023 - (beta-only) More VRAM optimizations for "low" VRAM usage mode.
+* 2.5.36 - 10 May 2023 - (beta-only) Bug fix for "meta" error when using a LoRA in 'low' VRAM usage mode.
+* 2.5.35 - 8 May 2023 - Allow dragging a zoomed-in image (after opening an image with the "expand" button). Thanks @ogmaresca.
+* 2.5.35 - 3 May 2023 - (beta-only) First round of VRAM Optimizations for the "Test Diffusers" version. This change significantly reduces the amount of VRAM used by the diffusers version during image generation. The VRAM usage is still not equal to the "non-diffusers" version, but more optimizations are coming soon.
+* 2.5.34 - 22 Apr 2023 - Don't start the browser in an incognito new profile (on Windows). Thanks @JeLuf.
+* 2.5.33 - 21 Apr 2023 - Install PyTorch 2.0 on new installations (on Windows and Linux).
+* 2.5.32 - 19 Apr 2023 - Automatically check for black images, and set full-precision if necessary (for attn). This means custom models based on Stable Diffusion v2.1 will just work, without needing special command-line arguments or editing of yaml config files.
+* 2.5.32 - 18 Apr 2023 - Automatic support for AMD graphics cards on Linux. Thanks @DianaNites and @JeLuf.
+* 2.5.31 - 10 Apr 2023 - Reduce VRAM usage while upscaling.
+* 2.5.31 - 6 Apr 2023 - Allow seeds upto `4,294,967,295`. Thanks @ogmaresca.
+* 2.5.31 - 6 Apr 2023 - Buttons to show the previous/next image in the image popup. Thanks @ogmaresca.
+* 2.5.30 - 5 Apr 2023 - Fix a bug where the JPEG image quality wasn't being respected when embedding the metadata into it. Thanks @JeLuf.
+* 2.5.30 - 1 Apr 2023 - (beta-only) Slider to control the strength of the LoRA model.
+* 2.5.30 - 28 Mar 2023 - Refactor task entry config to use a generating method. Added ability for plugins to easily add to this. Removed confusing sentence from `contributing.md`
+* 2.5.30 - 28 Mar 2023 - Allow the user to undo the deletion of tasks or images, instead of showing a pop-up each time. The new `Undo` button will be present at the top of the UI. Thanks @JeLuf.
+* 2.5.30 - 28 Mar 2023 - Support saving lossless WEBP images. Thanks @ogmaresca.
+* 2.5.30 - 28 Mar 2023 - Lots of bug fixes for the UI (Read LoRA flag in metadata files, new prompt weight format with scrollwheel, fix overflow with lots of tabs, clear button in image editor, shorter filenames in download). Thanks @patriceac, @JeLuf and @ogmaresca.
+* 2.5.29 - 27 Mar 2023 - (beta-only) Fix a bug where some non-square images would fail while inpainting with a `The size of tensor a must match size of tensor b` error.
+* 2.5.29 - 27 Mar 2023 - (beta-only) Fix the `incorrect number of channels` error, when given a PNG image with an alpha channel in `Test Diffusers`.
+* 2.5.29 - 27 Mar 2023 - (beta-only) Fix broken inpainting in `Test Diffusers`.
+* 2.5.28 - 24 Mar 2023 - (beta-only) Support for weighted prompts and long prompt lengths (not limited to 77 tokens). This change requires enabling the `Test Diffusers` setting in beta (in the Settings tab), and restarting the program.
+* 2.5.27 - 21 Mar 2023 - (beta-only) LoRA support, accessible by enabling the `Test Diffusers` setting (in the Settings tab in the UI). This change switches the internal engine to diffusers (if the `Test Diffusers` setting is enabled). If the `Test Diffusers` flag is disabled, it'll have no impact for the user.
+* 2.5.26 - 15 Mar 2023 - Allow styling the buttons displayed on an image. Update the API to allow multiple buttons and text labels in a single row. Thanks @ogmaresca.
+* 2.5.26 - 15 Mar 2023 - View images in full-screen, by either clicking on the image, or clicking the "Full screen" icon next to the Seed number on the image. Thanks @ogmaresca for the internal API.
+* 2.5.25 - 14 Mar 2023 - Button to download all the images, and all the metadata as a zip file. This is available at the top of the UI, as well as on each image. Thanks @JeLuf.
+* 2.5.25 - 14 Mar 2023 - Lots of UI tweaks and bug fixes. Thanks @patriceac and @JeLuf.
+* 2.5.24 - 11 Mar 2023 - Button to load an image mask from a file.
+* 2.5.24 - 10 Mar 2023 - Logo change. Image credit: @lazlo_vii.
+* 2.5.23 - 8 Mar 2023 - Experimental support for Mac M1/M2. Thanks @michaelgallacher, @JeLuf and vishae!
+* 2.5.23 - 8 Mar 2023 - Ability to create custom modifiers with thumbnails, and custom categories (and hierarchy of categories). More details - https://github.com/cmdr2/stable-diffusion-ui/wiki/Custom-Modifiers . Thanks @ogmaresca.
+* 2.5.22 - 28 Feb 2023 - Minor styling changes to UI buttons, and the models dropdown.
+* 2.5.22 - 28 Feb 2023 - Lots of UI-related bug fixes. Thanks @patriceac.
+* 2.5.21 - 22 Feb 2023 - An option to control the size of the image thumbnails. You can use the `Display options` in the top-right corner to change this. Thanks @JeLuf.
+* 2.5.20 - 20 Feb 2023 - Support saving images in WEBP format (which consumes less disk space, with similar quality). Thanks @ogmaresca.
+* 2.5.20 - 18 Feb 2023 - A setting to block NSFW images from being generated. You can enable this setting in the Settings tab.
+* 2.5.19 - 17 Feb 2023 - Initial support for server-side plugins. Currently supports overriding the `get_cond_and_uncond()` function.
+* 2.5.18 - 17 Feb 2023 - 5 new samplers! UniPC samplers, some of which produce images in less than 15 steps. Thanks @Schorny.
+* 2.5.16 - 13 Feb 2023 - Searchable dropdown for models. This is useful if you have a LOT of models. You can type part of the model name, to auto-search through your models. Thanks @patriceac for the feature, and @AssassinJN for help in UI tweaks!
+* 2.5.16 - 13 Feb 2023 - Lots of fixes and improvements to the installer. First round of changes to add Mac support. Thanks @JeLuf.
+* 2.5.16 - 13 Feb 2023 - UI bug fixes for the inpainter editor. Thanks @patriceac.
+* 2.5.16 - 13 Feb 2023 - Fix broken task reorder. Thanks @JeLuf.
+* 2.5.16 - 13 Feb 2023 - Remove a task if all the images inside it have been removed. Thanks @AssassinJN.
+* 2.5.16 - 10 Feb 2023 - Embed metadata into the JPG/PNG images, if selected in the "Settings" tab (under "Metadata format"). Thanks @patriceac.
+* 2.5.16 - 10 Feb 2023 - Sort models alphabetically in the models dropdown. Thanks @ogmaresca.
+* 2.5.16 - 10 Feb 2023 - Support multiple GFPGAN models. Download new GFPGAN models into the `models/gfpgan` folder, and refresh the UI to use it. Thanks @JeLuf.
+* 2.5.16 - 10 Feb 2023 - Allow a server to enforce a fixed directory path to save images. This is useful if the server is exposed to a lot of users. This can be set in the `config.json` file as `force_save_path: "/path/to/fixed/save/dir"`. E.g. `force_save_path: "D:/user_images"`. Thanks @JeLuf.
+* 2.5.16 - 10 Feb 2023 - The "Make Images" button now shows the correct amount of images it'll create when using operators like `{}` or `|`. For e.g. if the prompt is `Photo of a {woman, man}`, then the button will say `Make 2 Images`. Thanks @JeLuf.
+* 2.5.16 - 10 Feb 2023 - A bunch of UI-related bug fixes. Thanks @patriceac.
+* 2.5.15 - 8 Feb 2023 - Allow using 'balanced' VRAM usage mode on GPUs with 4 GB or less of VRAM. This mode used to be called 'Turbo' in the previous version.
+* 2.5.14 - 8 Feb 2023 - Fix broken auto-save settings. We renamed `sampler` to `sampler_name`, which caused old settings to fail.
+* 2.5.14 - 6 Feb 2023 - Simplify the UI for merging models, and some other minor UI tweaks. Better error reporting if a model failed to load.
+* 2.5.14 - 3 Feb 2023 - Fix the 'Make Similar Images' button, which was producing incorrect images (weren't very similar).
+* 2.5.13 - 1 Feb 2023 - Fix the remaining GPU memory leaks, including a better fix (more comprehensive) for the change in 2.5.12 (27 Jan).
+* 2.5.12 - 27 Jan 2023 - Fix a memory leak, which made the UI unresponsive after an out-of-memory error. The allocated memory is now freed-up after an error.
+* 2.5.11 - 25 Jan 2023 - UI for Merging Models. Thanks @JeLuf. More info: https://github.com/cmdr2/stable-diffusion-ui/wiki/Model-Merging
+* 2.5.10 - 24 Jan 2023 - Reduce the VRAM usage for img2img in 'balanced' mode (without reducing the rendering speed), to make it similar to v2.4 of this UI.
+* 2.5.9 - 23 Jan 2023 - Fix a bug where img2img would produce poorer-quality images for the same settings, as compared to version 2.4 of this UI.
+* 2.5.9 - 23 Jan 2023 - Reduce the VRAM usage for 'balanced' mode (without reducing the rendering speed), to make it similar to v2.4 of the UI.
+* 2.5.8 - 17 Jan 2023 - Fix a bug where 'Low' VRAM usage would consume a LOT of VRAM (on higher-end GPUs). Also fixed a bug that caused out-of-memory errors on SD 2.1-768 models, on 'high' VRAM usage setting.
+* 2.5.7 - 16 Jan 2023 - Fix a bug where VAE files ending with .vae.pt weren't getting displayed. Thanks Madrang, rbertus2000 and JeLuf.
+* 2.5.6 - 10 Jan 2023 - `Fill` tool for the Image Editor, to allow filling areas with color (or the entire image). And some bug fixes to the Image Editor. Thanks @mdiller.
+* 2.5.6 - 10 Jan 2023 - Find Stable Diffusion models in sub-folders inside `models/stable-diffusion`. This allows you to organize your models into sub-folders, instead of keeping them all in a single folder. Thanks @JeLuf.
+* 2.5.5 - 9 Jan 2023 - Lots of bug fixes. Thanks @patriceac and @JeLuf.
+* 2.5.4 - 29 Dec 2022 - Press Esc key on the keyboard to close the Image Editor. Thanks @patriceac.
+* 2.5.4 - 29 Dec 2022 - Lots of bug fixes in the UI. Thanks @patriceac.
+* 2.5.4 - 28 Dec 2022 - Full support for running tasks in parallel on multiple GPUs. Warning: 'Euler Ancestral', 'DPM2 Ancestral' and 'DPM++ 2s Ancestral' may produce slight variations in the image (if run in parallel), so we recommend using the other samplers.
+* 2.5.3 - 27 Dec 2022 - Fix broken drag-and-drop for text metadata files (as well as paste in clipboard).
+* 2.5.3 - 27 Dec 2022 - Allow upscaling by 2x as well as 4x.
+* 2.5.3 - 27 Dec 2022 - Fix broken renders on a second GPU.
+* 2.5.3 - 26 Dec 2022 - Add a `Remove` button on each image. Thanks @JeLuf.
+* 2.5.2 - 26 Dec 2022 - Fix broken inpainting if using non-square target images.
+* 2.5.2 - 26 Dec 2022 - Fix a bug where an incorrect model config would get used for some SD 2.1 models.
+* 2.5.2 - 26 Dec 2022 - Slight performance and memory improvement while rendering using SD 2.1 models.
+* 2.5.1 - 25 Dec 2022 - Allow custom config yaml files for models. You can put a config file (`.yaml`) next to the model file, with the same name as the model. For e.g. if you put `robo-diffusion-v2-base.yaml` next to `robo-diffusion-v2-base.ckpt`, it'll automatically use that config file.
+* 2.5.1 - 25 Dec 2022 - Fix broken rendering for SD 2.1-768 models. Fix broken rendering SD 2.0 safetensor models.
+* 2.5.0 - 25 Dec 2022 - Major new release! Nearly twice as fast, Full support for SD 2.1 (including low GPU RAM optimizations), 6 new samplers, Model Merging, Fast loading/unloading of VAEs, Database of known models, Color correction for img2img, Three GPU Memory Usage Settings, Save metadata as JSON, Major rewrite of the code, Name change.
+
 ## v2.4
 ### Major Changes
 - **Allow reordering the task queue** (by dragging and dropping tasks). Thanks @madrang
@@ -27,6 +147,9 @@
 - Support loading models in the safetensor format, for improved safety
 
 ### Detailed changelog
+* 2.4.24 - 9 Jan 2022 - Urgent fix for failures on old/long-term-support browsers. Thanks @JeLuf.
+* 2.4.23/22 - 29 Dec 2022 - Allow rolling back from the upcoming v2.5 change (in beta).
+* 2.4.21 - 23 Dec 2022 - Speed up image creation, by removing a delay (regression) of 4-5 seconds between clicking the `Make Image` button and calling the server.
 * 2.4.20 - 22 Dec 2022 - `Pause All` button to pause all the pending tasks. Thanks @JeLuf
 * 2.4.20 - 22 Dec 2022 - `Undo`/`Redo` buttons in the image editor. Thanks @JeLuf
 * 2.4.20 - 22 Dec 2022 - Drag handle to reorder the tasks. This fixed a bug where the metadata was no longer selectable (for copying). Thanks @JeLuf

CONTRIBUTING.md

@@ -42,8 +42,6 @@ or for Windows
 10) Congrats, now any changes you make in your repo `ui` folder are linked to this running archive of the app and can be previewed in the browser.
 11) Please update CHANGES.md in your pull requests.
 
-Check the `ui/frontend/build/README.md` for instructions on running and building the React code.
-
 ## Development environment for Installer changes
 Build the Windows installer using Windows, and the Linux installer using Linux. Don't mix the two, and don't use WSL. An Ubuntu VM is fine for building the Linux installer on a Windows host.
 

How to install and run.txt

@@ -5,10 +5,10 @@ If you haven't downloaded Stable Diffusion UI yet, please download from https://
 After downloading, to install please follow these instructions:
 
 For Windows:
-- Please double-click the "Start Stable Diffusion UI.cmd" file inside the "stable-diffusion-ui" folder.
+- Please double-click the "Easy-Diffusion-Windows.exe" file and follow the instructions.
 
 For Linux:
-- Please open a terminal, and go to the "stable-diffusion-ui" directory. Then run ./start.sh
+- Please open a terminal, unzip the Easy-Diffusion-Linux.zip file and go to the "easy-diffusion" directory. Then run ./start.sh
 
 That file will automatically install everything. After that it will start the Stable Diffusion interface in a web browser.
 
@@ -21,4 +21,4 @@ If you have any problems, please:
 3. Or, file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues
 
 Thanks
-cmdr2 (and contributors to the project)
+cmdr2 (and contributors to the project)

NSIS/.gitignore

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

NSIS/nsisconf.nsh

@@ -0,0 +1 @@
+!define EXISTING_INSTALLATION_DIR "D:\path\to\installed\easy-diffusion"

NSIS/sdui.nsi

@@ -1,20 +1,24 @@
 ; Script generated by the HM NIS Edit Script Wizard.
 
-Target x86-unicode
+Target amd64-unicode
 Unicode True
-!AddPluginDir /x86-unicode "."
+SetCompressor /FINAL lzma
+RequestExecutionLevel user
+!AddPluginDir /amd64-unicode "."
 ; HM NIS Edit Wizard helper defines
-!define PRODUCT_NAME "Stable Diffusion UI"
-!define PRODUCT_VERSION "Installer 2.35"
+!define PRODUCT_NAME "Easy Diffusion"
+!define PRODUCT_VERSION "2.5"
 !define PRODUCT_PUBLISHER "cmdr2 and contributors"
 !define PRODUCT_WEB_SITE "https://stable-diffusion-ui.github.io"
-!define PRODUCT_DIR_REGKEY "Software\Microsoft\Cmdr2\App Paths\installer.exe"
+!define PRODUCT_DIR_REGKEY "Software\Microsoft\Easy Diffusion\App Paths\installer.exe"
 
 ; MUI 1.67 compatible ------
 !include "MUI.nsh"
 !include "LogicLib.nsh"
 !include "nsDialogs.nsh"
 
+!include "nsisconf.nsh"
+
 Var Dialog
 Var Label
 Var Button
@@ -106,7 +110,7 @@ Function DirectoryLeave
    StrCpy $5 $INSTDIR 3
    System::Call 'Kernel32::GetVolumeInformation(t "$5",t,i ${NSIS_MAX_STRLEN},*i,*i,*i,t.r1,i ${NSIS_MAX_STRLEN})i.r0'
    ${If} $0 <> 0
-   ${AndIf} $1 == "NTFS"
+   ${AndIf} $1 != "NTFS"
        MessageBox mb_ok "$5 has filesystem type '$1'.$\nOnly NTFS filesystems are supported.$\nPlease choose a different drive."
        Abort
    ${EndIf}
@@ -140,7 +144,7 @@ Function MediaPackDialog
 	Abort
     ${EndIf}
 
-    ${NSD_CreateLabel} 0 0 100% 48u "The Windows Media Feature Pack is missing on this computer. It is required for the Stable Diffusion UI.$\nYou can continue the installation after installing the Windows Media Feature Pack."
+    ${NSD_CreateLabel} 0 0 100% 48u "The Windows Media Feature Pack is missing on this computer. It is required for Easy Diffusion.$\nYou can continue the installation after installing the Windows Media Feature Pack."
     Pop $Label
  	
     ${NSD_CreateButton} 10% 49u 80% 12u "Download Meda Feature Pack from Microsoft"
@@ -153,16 +157,20 @@ Function MediaPackDialog
     nsDialogs::Show
 FunctionEnd
 
+Function FinishPageAction
+CreateShortCut "$DESKTOP\Easy Diffusion.lnk" "$INSTDIR\Start Stable Diffusion UI.cmd" "" "$INSTDIR\installer_files\cyborg_flower_girl.ico"
+FunctionEnd
+
 ;---------------------------------------------------------------------------------------------------------
 ; MUI Settings
 ;---------------------------------------------------------------------------------------------------------
 !define MUI_ABORTWARNING
-!define MUI_ICON "sd.ico"
+!define MUI_ICON "cyborg_flower_girl.ico"
 
-!define MUI_WELCOMEFINISHPAGE_BITMAP "astro.bmp"
+!define MUI_WELCOMEFINISHPAGE_BITMAP "cyborg_flower_girl.bmp"
 
 ; Welcome page
-!define MUI_WELCOMEPAGE_TEXT "This installer will guide you through the installation of Stable Diffusion UI.$\n$\n\
+!define MUI_WELCOMEPAGE_TEXT "This installer will guide you through the installation of Easy Diffusion.$\n$\n\
 Click Next to continue."
 !insertmacro MUI_PAGE_WELCOME
 Page custom MediaPackDialog
@@ -178,6 +186,11 @@ Page custom MediaPackDialog
 !insertmacro MUI_PAGE_INSTFILES 
 
 ; Finish page
+!define MUI_FINISHPAGE_SHOWREADME ""
+!define MUI_FINISHPAGE_SHOWREADME_NOTCHECKED
+!define MUI_FINISHPAGE_SHOWREADME_TEXT "Create Desktop Shortcut"
+!define MUI_FINISHPAGE_SHOWREADME_FUNCTION FinishPageAction
+
 !define MUI_FINISHPAGE_RUN "$INSTDIR\Start Stable Diffusion UI.cmd"
 !insertmacro MUI_PAGE_FINISH
 
@@ -188,8 +201,8 @@ Page custom MediaPackDialog
 ;---------------------------------------------------------------------------------------------------------
 
 Name "${PRODUCT_NAME} ${PRODUCT_VERSION}"
-OutFile "Install Stable Diffusion UI.exe"
-InstallDir "C:\Stable-Diffusion-UI\"
+OutFile "Install Easy Diffusion.exe"
+InstallDir "C:\EasyDiffusion\"
 InstallDirRegKey HKLM "${PRODUCT_DIR_REGKEY}" ""
 ShowInstDetails show
 
@@ -200,15 +213,42 @@ Section "MainSection" SEC01
   File "..\CreativeML Open RAIL-M License"
   File "..\How to install and run.txt"
   File "..\LICENSE"
-  File "..\Start Stable Diffusion UI.cmd"
+  File "..\scripts\Start Stable Diffusion UI.cmd"
+  File /r "${EXISTING_INSTALLATION_DIR}\installer_files"
+  File /r "${EXISTING_INSTALLATION_DIR}\profile"
+  File /r "${EXISTING_INSTALLATION_DIR}\sd-ui-files"
+  SetOutPath "$INSTDIR\installer_files"
+  File "cyborg_flower_girl.ico"
   SetOutPath "$INSTDIR\scripts"
-  File "..\scripts\bootstrap.bat"
-  File "..\scripts\install_status.txt"
+  File "${EXISTING_INSTALLATION_DIR}\scripts\install_status.txt"
   File "..\scripts\on_env_start.bat"
   File "C:\windows\system32\curl.exe"
-  CreateDirectory "$INSTDIR\profile"
-  CreateDirectory "$SMPROGRAMS\Stable Diffusion UI"
-  CreateShortCut "$SMPROGRAMS\Stable Diffusion UI\Start Stable Diffusion UI.lnk" "$INSTDIR\Start Stable Diffusion UI.cmd"
+  CreateDirectory "$INSTDIR\models"
+  CreateDirectory "$INSTDIR\models\stable-diffusion"
+  CreateDirectory "$INSTDIR\models\gfpgan"
+  CreateDirectory "$INSTDIR\models\realesrgan"
+  CreateDirectory "$INSTDIR\models\vae"
+  CreateDirectory "$SMPROGRAMS\Easy Diffusion"
+  CreateShortCut "$SMPROGRAMS\Easy Diffusion\Easy Diffusion.lnk" "$INSTDIR\Start Stable Diffusion UI.cmd" "" "$INSTDIR\installer_files\cyborg_flower_girl.ico"
+
+  DetailPrint 'Downloading the Stable Diffusion 1.4 model...'
+  NScurl::http get "https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt" "$INSTDIR\models\stable-diffusion\sd-v1-4.ckpt" /CANCEL /INSIST /END
+
+  DetailPrint 'Downloading the GFPGAN model...'
+  NScurl::http get "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth" "$INSTDIR\models\gfpgan\GFPGANv1.4.pth" /CANCEL /INSIST /END
+
+  DetailPrint 'Downloading the RealESRGAN_x4plus model...'
+  NScurl::http get "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth" "$INSTDIR\models\realesrgan\RealESRGAN_x4plus.pth" /CANCEL /INSIST /END
+
+  DetailPrint 'Downloading the RealESRGAN_x4plus_anime model...'
+  NScurl::http get "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth" "$INSTDIR\models\realesrgan\RealESRGAN_x4plus_anime_6B.pth" /CANCEL /INSIST /END
+
+  DetailPrint 'Downloading the default VAE (sd-vae-ft-mse-original) model...'
+  NScurl::http get "https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt" "$INSTDIR\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" /CANCEL /INSIST /END
+
+  DetailPrint 'Downloading the CLIP model (clip-vit-large-patch14)...'
+  NScurl::http get "https://huggingface.co/openai/clip-vit-large-patch14/resolve/8d052a0f05efbaefbc9e8786ba291cfdf93e5bff/pytorch_model.bin" "$INSTDIR\profile\.cache\huggingface\hub\models--openai--clip-vit-large-patch14\snapshots\8d052a0f05efbaefbc9e8786ba291cfdf93e5bff\pytorch_model.bin" /CANCEL /INSIST /END
+
 SectionEnd
 
 ;---------------------------------------------------------------------------------------------------------
@@ -254,7 +294,7 @@ Function .onInit
 
    ${If} $4 < "8000"
       MessageBox MB_OK|MB_ICONEXCLAMATION "Warning!$\n$\nYour system has less than 8GB of memory (RAM).$\n$\n\
-You can still try to install Stable Diffusion UI,$\nbut it might have problems to start, or run$\nvery slowly."
+You can still try to install Easy Diffusion,$\nbut it might have problems to start, or run$\nvery slowly."
    ${EndIf}
   
 FunctionEnd

PRIVACY.md

@@ -0,0 +1,9 @@
+// placeholder until a more formal and legal-sounding privacy policy document is written. but the information below is true.
+
+This is a summary of whether Easy Diffusion uses your data or tracks you:
+* The short answer is - Easy Diffusion does *not* use your data, and does *not* track you.
+* Easy Diffusion does not send your prompts or usage or analytics to anyone. There is no tracking. We don't even know how many people use Easy Diffusion, let alone their prompts.
+* Easy Diffusion fetches updates to the code whenever it starts up. It does this by contacting GitHub directly, via SSL (secure connection). Only your computer and GitHub and [this repository](https://github.com/cmdr2/stable-diffusion-ui) are involved, and no third party is involved. Some countries intercepts SSL connections, that's not something we can do much about. GitHub does *not* share statistics (even with me) about how many people fetched code updates.
+* Easy Diffusion fetches the models from huggingface.co and github.com, if they don't exist on your PC. For e.g. if the safety checker (NSFW) model doesn't exist, it'll try to download it.
+* Easy Diffusion fetches code packages from pypi.org, which is the standard hosting service for all Python projects. That's where packages installed via `pip install` are stored.
+* Occasionally, antivirus software are known to *incorrectly* flag and delete some model files, which will result in Easy Diffusion re-downloading `pytorch_model.bin`. This *incorrect deletion* affects other Stable Diffusion UIs as well, like Invoke AI - https://itch.io/post/7509488

README.md

@@ -1,40 +1,46 @@
-# Stable Diffusion UI
-### The easiest way to install and use [Stable Diffusion](https://github.com/CompVis/stable-diffusion) on your own computer. Does not require technical knowledge, does not require pre-installed software. 1-click install, powerful features, friendly community.
+# Easy Diffusion 2.5
+### The easiest way to install and use [Stable Diffusion](https://github.com/CompVis/stable-diffusion) on your computer.
 
-[![Discord Server](https://img.shields.io/discord/1014774730907209781?label=Discord)](https://discord.com/invite/u9yhsFmEkB) (for support, and development discussion) | [Troubleshooting guide for common problems](https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting)
+Does not require technical knowledge, does not require pre-installed software. 1-click install, powerful features, friendly community.
 
-### New: 
-Experimental support for Stable Diffusion 2.0 is available in beta!
+[Installation guide](#installation) | [Troubleshooting guide](https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting) | <sub>[![Discord Server](https://img.shields.io/discord/1014774730907209781?label=Discord)](https://discord.com/invite/u9yhsFmEkB)</sub> <sup>(for support queries, and development discussions)</sup>
 
-----
+![t2i](https://raw.githubusercontent.com/Stability-AI/stablediffusion/main/assets/stable-samples/txt2img/768/merged-0006.png)
 
-# Step 1: Download and prepare the installer
+# Installation
 Click the download button for your operating system:
 
 <p float="left">
-  <a href="https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.4.13/stable-diffusion-ui-windows.zip"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-win.png" width="200" /></a>
-  <a href="https://github.com/cmdr2/stable-diffusion-ui#installation"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-linux.png" width="200" /></a>
+  <a href="https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.5.24/Easy-Diffusion-Windows.exe"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-win.png" width="200" /></a>
+  <a href="https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.5.24/Easy-Diffusion-Linux.zip"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-linux.png" width="200" /></a>
+  <a href="https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.5.24/Easy-Diffusion-Mac.zip"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-mac.png" width="200" /></a>
 </p>
 
-## On Windows:
-1. Unzip/extract the folder `stable-diffusion-ui` which should be in your downloads folder, unless you changed your default downloads destination.
-2. Move the `stable-diffusion-ui` folder to your `C:` drive (or any other drive like `D:`, at the top root level). `C:\stable-diffusion-ui` or `D:\stable-diffusion-ui` as examples. This will avoid a common problem with Windows (file path length limits).
-## On Linux:
-1. Unzip/extract the folder `stable-diffusion-ui` which should be in your downloads folder, unless you changed your default downloads destination.
-2. Open a terminal window, and navigate to the `stable-diffusion-ui` directory.
+**Hardware requirements:**
+- **Windows:** NVIDIA graphics card (minimum 2 GB RAM), or run on your CPU.
+- **Linux:** NVIDIA or AMD graphics card (minimum 2 GB RAM), or run on your CPU.
+- **Mac:** M1 or M2, or run on your CPU.
+- Minimum 8 GB of system RAM.
+- Atleast 25 GB of space on the hard disk.
 
-# Step 2: Run the program
-## On Windows: 
-Double-click `Start Stable Diffusion UI.cmd`.
-If Windows SmartScreen prevents you from running the program click `More info` and then `Run anyway`.
-## On Linux: 
-Run `./start.sh` (or `bash start.sh`) in a terminal.
 
 The installer will take care of whatever is needed. If you face any problems, you can join the friendly [Discord community](https://discord.com/invite/u9yhsFmEkB) and ask for assistance.
 
-# Step 3: There is no Step 3. It's that simple!
+## On Windows:
+1. Run the downloaded `Easy-Diffusion-Windows.exe` file.
+2. Run `Easy Diffusion` once the installation finishes. You can also start from your Start Menu, or from your desktop (if you created a shortcut).
 
-**To Uninstall:** Just delete the `stable-diffusion-ui` folder to uninstall all the downloaded packages.
+If Windows SmartScreen prevents you from running the program click `More info` and then `Run anyway`.
+
+**Tip:** On Windows 10, please install at the top level in your drive, e.g. `C:\EasyDiffusion` or `D:\EasyDiffusion`. This will avoid a common problem with Windows 10 (file path length limits).
+
+## On Linux/Mac:
+1. Unzip/extract the folder `easy-diffusion` which should be in your downloads folder, unless you changed your default downloads destination.
+2. Open a terminal window, and navigate to the `easy-diffusion` directory.
+3. Run `./start.sh` (or `bash start.sh`) in a terminal.
+
+# To remove/uninstall:
+Just delete the `EasyDiffusion` folder to uninstall all the downloaded packages.
 
 ----
 
@@ -44,9 +50,18 @@ The installer will take care of whatever is needed. If you face any problems, yo
 ### User experience
 - **Hassle-free installation**: Does not require technical knowledge, does not require pre-installed software. Just download and run!
 - **Clutter-free UI**: A friendly and simple UI, while providing a lot of powerful features.
+- **Task Queue**: Queue up all your ideas, without waiting for the current task to finish.
+- **Intelligent Model Detection**: Automatically figures out the YAML config file to use for the chosen model (via a models database).
+- **Live Preview**: See the image as the AI is drawing it.
+- **Image Modifiers**: A library of *modifier tags* like *"Realistic"*, *"Pencil Sketch"*, *"ArtStation"* etc. Experiment with various styles quickly.
+- **Multiple Prompts File**: Queue multiple prompts by entering one prompt per line, or by running a text file.
+- **Save generated images to disk**: Save your images to your PC!
+- **UI Themes**: Customize the program to your liking.
+- **Searchable models dropdown**: organize your models into sub-folders, and search through them in the UI.
 
 ### Image generation
 - **Supports**: "*Text to Image*" and "*Image to Image*".
+- **21 Samplers**: `ddim`, `plms`, `heun`, `euler`, `euler_a`, `dpm2`, `dpm2_a`, `lms`, `dpm_solver_stability`, `dpmpp_2s_a`, `dpmpp_2m`, `dpmpp_sde`, `dpm_fast`, `dpm_adaptive`, `ddpm`, `deis`, `unipc_snr`, `unipc_tu`, `unipc_tq`, `unipc_snr_2`, `unipc_tu_2`.
 - **In-Painting**: Specify areas of your image to paint into.
 - **Simple Drawing Tool**: Draw basic images to guide the AI, without needing an external drawing program.
 - **Face Correction (GFPGAN)**
@@ -56,21 +71,23 @@ The installer will take care of whatever is needed. If you face any problems, yo
 - **Attention/Emphasis**: () in the prompt increases the model's attention to enclosed words, and [] decreases it.
 - **Weighted Prompts**: Use weights for specific words in your prompt to change their importance, e.g. `red:2.4 dragon:1.2`.
 - **Prompt Matrix**: Quickly create multiple variations of your prompt, e.g. `a photograph of an astronaut riding a horse | illustration | cinematic lighting`.
-- **Lots of Samplers**: ddim, plms, heun, euler, euler_a, dpm2, dpm2_a, lms.
 - **1-click Upscale/Face Correction**: Upscale or correct an image after it has been generated.
 - **Make Similar Images**: Click to generate multiple variations of a generated image.
 - **NSFW Setting**: A setting in the UI to control *NSFW content*.
-- **JPEG/PNG output**: Multiple file formats.
+- **JPEG/PNG/WEBP output**: Multiple file formats.
 
 ### Advanced features
 - **Custom Models**: Use your own `.ckpt` or `.safetensors` file, by placing it inside the `models/stable-diffusion` folder!
-- **Stable Diffusion 2.0 support (experimental)**: available in beta channel.
+- **Stable Diffusion 2.1 support**
+- **Merge Models**
 - **Use custom VAE models**
 - **Use pre-trained Hypernetworks**
+- **Use custom GFPGAN models**
 - **UI Plugins**: Choose from a growing list of [community-generated UI plugins](https://github.com/cmdr2/stable-diffusion-ui/wiki/UI-Plugins), or write your own plugin to add features to the project!
 
 ### Performance and security
-- **Low Memory Usage**: Creates 512x512 images with less than 4GB of GPU RAM!
+- **Fast**: Creates a 512x512 image with euler_a in 5 seconds, on an NVIDIA 3060 12GB.
+- **Low Memory Usage**: Create 512x512 images with less than 2 GB of GPU RAM, and 768x768 images with less than 3 GB of GPU RAM!
 - **Use CPU setting**: If you don't have a compatible graphics card, but still want to run it on your CPU.
 - **Multi-GPU support**: Automatically spreads your tasks across multiple GPUs (if available), for faster performance!
 - **Auto scan for malicious models**: Uses picklescan to prevent malicious models.
@@ -78,23 +95,17 @@ The installer will take care of whatever is needed. If you face any problems, yo
 - **Auto-updater**: Gets you the latest improvements and bug-fixes to a rapidly evolving project.
 - **Developer Console**: A developer-mode for those who want to modify their Stable Diffusion code, and edit the conda environment.
 
-### Usability:
-- **Live Preview**: See the image as the AI is drawing it.
-- **Task Queue**: Queue up all your ideas, without waiting for the current task to finish.
-- **Image Modifiers**: A library of *modifier tags* like *"Realistic"*, *"Pencil Sketch"*, *"ArtStation"* etc. Experiment with various styles quickly.
-- **Multiple Prompts File**: Queue multiple prompts by entering one prompt per line, or by running a text file.
-- **Save generated images to disk**: Save your images to your PC!
-- **UI Themes**: Customize the program to your liking.
-
 **(and a lot more)**
 
 ----
 
 ## Easy for new users:
-![Screenshot of the initial UI](media/shot-v10-simple.jpg?raw=true)
+![Screenshot of the initial UI](https://user-images.githubusercontent.com/844287/217043152-29454d15-0387-4228-b70d-9a4b84aeb8ba.png)
+
 
 ## Powerful features for advanced users:
-![Screenshot of advanced settings](media/shot-v10.jpg?raw=true)
+![Screenshot of advanced settings](https://user-images.githubusercontent.com/844287/217042588-fc53c975-bacd-4a9c-af88-37408734ade3.png)
+
 
 ## Live Preview
 Useful for judging (and stopping) an image quickly, without waiting for it to finish rendering.
@@ -102,14 +113,8 @@ Useful for judging (and stopping) an image quickly, without waiting for it to fi
 ![live-512](https://user-images.githubusercontent.com/844287/192097249-729a0a1e-a677-485e-9ccc-16a9e848fabe.gif)
 
 ## Task Queue
-![Screenshot of task queue](media/task-queue-v1.jpg?raw=true)
+![Screenshot of task queue](https://user-images.githubusercontent.com/844287/217043984-0b35f73b-1318-47cb-9eed-a2a91b430490.png)
 
-# System Requirements
-1. Windows 10/11, or Linux. Experimental support for Mac is coming soon.
-2. An NVIDIA graphics card, preferably with 4GB or more of VRAM. If you don't have a compatible graphics card, it'll automatically run in the slower "CPU Mode".
-3. Minimum 8 GB of RAM and 25GB of disk space.
-
-You don't need to install or struggle with Python, Anaconda, Docker etc. The installer will take care of whatever is needed.
 
 ----
 

package.json

@@ -0,0 +1,9 @@
+{
+  "scripts": {
+    "prettier-fix": "npx prettier --write \"./**/*.js\"",
+    "prettier-check": "npx prettier --check \"./**/*.js\""
+  },
+  "devDependencies": {
+    "prettier": "^1.19.1"
+  }
+}

scripts/Developer Console.cmd

@@ -23,23 +23,20 @@ call conda --version
 
 echo.
 
-@rem activate the environment
-call conda activate .\stable-diffusion\env
+@rem activate the legacy environment (if present) and set PYTHONPATH
+if exist "installer_files\env" (
+    set PYTHONPATH=%cd%\installer_files\env\lib\site-packages
+)
+if exist "stable-diffusion\env" (
+    call conda activate .\stable-diffusion\env
+    set PYTHONPATH=%cd%\stable-diffusion\env\lib\site-packages
+)
 
 call where python
 call python --version
 
-@rem set the PYTHONPATH
-cd stable-diffusion
-set SD_DIR=%cd%
-
-cd env\lib\site-packages
-set PYTHONPATH=%SD_DIR%;%cd%
-cd ..\..\..
 echo PYTHONPATH=%PYTHONPATH%
 
-cd ..
-
 @rem done
 echo.
 

scripts/Start Stable Diffusion UI.cmd

@@ -1,20 +1,36 @@
 @echo off
 
 cd /d %~dp0
+echo Install dir: %~dp0
+
 set PATH=C:\Windows\System32;%PATH%
 
+if exist "on_sd_start.bat" (
+    echo ================================================================================
+    echo.
+    echo !!!! WARNING !!!!
+    echo.
+    echo It looks like you're trying to run the installation script from a source code 
+    echo download. This will not work.
+    echo.
+    echo Recommended: Please close this window and download the installer from
+    echo https://stable-diffusion-ui.github.io/docs/installation/
+    echo.
+    echo ================================================================================
+    echo.
+    pause
+    exit /b
+) 
+
 @rem set legacy installer's PATH, if it exists
 if exist "installer" set PATH=%cd%\installer;%cd%\installer\Library\bin;%cd%\installer\Scripts;%cd%\installer\Library\usr\bin;%PATH%
 
-@rem Setup the packages required for the installer
-call scripts\bootstrap.bat
-
 @rem set new installer's PATH, if it downloaded any packages
 if exist "installer_files\env" set PATH=%cd%\installer_files\env;%cd%\installer_files\env\Library\bin;%cd%\installer_files\env\Scripts;%cd%\installer_files\Library\usr\bin;%PATH%
 
 set PYTHONPATH=%cd%\installer;%cd%\installer_files\env
 
-@rem Test the bootstrap
+@rem Test the core requirements
 call where git
 call git --version
 

scripts/bootstrap.bat

@@ -1,4 +1,5 @@
 @echo off
+setlocal enabledelayedexpansion
 
 @rem This script will install git and conda (if not found on the PATH variable)
 @rem  using micromamba (an 8mb static-linked single-file binary, conda replacement).
@@ -24,14 +25,14 @@ if exist "%INSTALL_ENV_DIR%" set PATH=%INSTALL_ENV_DIR%;%INSTALL_ENV_DIR%\Librar
 set PACKAGES_TO_INSTALL=
 
 if not exist "%LEGACY_INSTALL_ENV_DIR%\etc\profile.d\conda.sh" (
-    if not exist "%INSTALL_ENV_DIR%\etc\profile.d\conda.sh" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% conda
+    if not exist "%INSTALL_ENV_DIR%\etc\profile.d\conda.sh" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% conda python=3.8.5
 )
 
 call git --version >.tmp1 2>.tmp2
-if "%ERRORLEVEL%" NEQ "0" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% git
+if "!ERRORLEVEL!" NEQ "0" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% git
 
 call "%MAMBA_ROOT_PREFIX%\micromamba.exe" --version >.tmp1 2>.tmp2
-if "%ERRORLEVEL%" EQU "0" set umamba_exists=T
+if "!ERRORLEVEL!" EQU "0" set umamba_exists=T
 
 @rem (if necessary) install git and conda into a contained environment
 if "%PACKAGES_TO_INSTALL%" NEQ "" (
@@ -42,7 +43,7 @@ if "%PACKAGES_TO_INSTALL%" NEQ "" (
         mkdir "%MAMBA_ROOT_PREFIX%"
         call curl -Lk "%MICROMAMBA_DOWNLOAD_URL%" > "%MAMBA_ROOT_PREFIX%\micromamba.exe"
 
-        if "%ERRORLEVEL%" NEQ "0" (
+        if "!ERRORLEVEL!" NEQ "0" (
             echo "There was a problem downloading micromamba. Cannot continue."
             pause
             exit /b

scripts/bootstrap.sh

@@ -21,9 +21,16 @@ OS_ARCH=$(uname -m)
 case "${OS_ARCH}" in
     x86_64*)    OS_ARCH="64";;
     arm64*)     OS_ARCH="arm64";;
+    aarch64*)     OS_ARCH="arm64";;
     *)          echo "Unknown system architecture: $OS_ARCH! This script runs only on x86_64 or arm64" && exit
 esac
 
+if ! which curl; then fail "'curl' not found. Please install curl."; fi
+if ! which tar; then fail "'tar' not found. Please install tar."; fi
+if ! which bzip2; then fail "'bzip2' not found. Please install bzip2."; fi
+
+if pwd | grep ' '; then fail "The installation directory's path contains a space character. Conda will fail to install. Please change the directory."; fi
+
 # https://mamba.readthedocs.io/en/latest/installation.html
 if [ "$OS_NAME" == "linux" ] && [ "$OS_ARCH" == "arm64" ]; then OS_ARCH="aarch64"; fi
 
@@ -39,7 +46,7 @@ if [ -e "$INSTALL_ENV_DIR" ]; then export PATH="$INSTALL_ENV_DIR/bin:$PATH"; fi
 
 PACKAGES_TO_INSTALL=""
 
-if [ ! -e "$LEGACY_INSTALL_ENV_DIR/etc/profile.d/conda.sh" ] && [ ! -e "$INSTALL_ENV_DIR/etc/profile.d/conda.sh" ]; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL conda"; fi
+if [ ! -e "$LEGACY_INSTALL_ENV_DIR/etc/profile.d/conda.sh" ] && [ ! -e "$INSTALL_ENV_DIR/etc/profile.d/conda.sh" ]; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL conda python=3.8.5"; fi
 if ! hash "git" &>/dev/null; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL git"; fi
 
 if "$MAMBA_ROOT_PREFIX/micromamba" --version &>/dev/null; then umamba_exists="T"; fi
@@ -51,7 +58,7 @@ if [ "$PACKAGES_TO_INSTALL" != "" ]; then
         echo "Downloading micromamba from $MICROMAMBA_DOWNLOAD_URL to $MAMBA_ROOT_PREFIX/micromamba"
 
         mkdir -p "$MAMBA_ROOT_PREFIX"
-        curl -L "$MICROMAMBA_DOWNLOAD_URL" | tar -xvj bin/micromamba -O > "$MAMBA_ROOT_PREFIX/micromamba"
+        curl -L "$MICROMAMBA_DOWNLOAD_URL" | tar -xvj -O bin/micromamba > "$MAMBA_ROOT_PREFIX/micromamba"
 
         if [ "$?" != "0" ]; then
             echo

scripts/check_modules.py

@@ -0,0 +1,161 @@
+"""
+This script checks and installs the required modules.
+
+This script runs inside the legacy "stable-diffusion" folder
+
+TODO - Maybe replace the bulk of this script with a call to `pip install -f requirements.txt`, with
+a custom index URL depending on the platform.
+
+"""
+
+import os
+from importlib.metadata import version as pkg_version
+import platform
+import traceback
+
+os_name = platform.system()
+
+modules_to_check = {
+    "torch": ("1.11.0", "1.13.1", "2.0.0"),
+    "torchvision": ("0.12.0", "0.14.1", "0.15.1"),
+    "sdkit": "1.0.112",
+    "stable-diffusion-sdkit": "2.1.4",
+    "rich": "12.6.0",
+    "uvicorn": "0.19.0",
+    "fastapi": "0.85.1",
+    "pycloudflared": "0.2.0",
+    # "xformers": "0.0.16",
+}
+modules_to_log = ["torch", "torchvision", "sdkit", "stable-diffusion-sdkit"]
+
+
+def version(module_name: str) -> str:
+    try:
+        return pkg_version(module_name)
+    except:
+        return None
+
+
+def install(module_name: str, module_version: str):
+    if module_name == "xformers" and (os_name == "Darwin" or is_amd_on_linux()):
+        return
+
+    index_url = None
+    if module_name in ("torch", "torchvision"):
+        module_version, index_url = apply_torch_install_overrides(module_version)
+
+    if is_amd_on_linux():  # hack until AMD works properly on torch 2.0 (avoids black images on some cards)
+        if module_name == "torch":
+            module_version = "1.13.1+rocm5.2"
+        elif module_name == "torchvision":
+            module_version = "0.14.1+rocm5.2"
+    elif os_name == "Darwin":
+        if module_name == "torch":
+            module_version = "1.13.1"
+        elif module_name == "torchvision":
+            module_version = "0.14.1"
+
+    install_cmd = f"python -m pip install --upgrade {module_name}=={module_version}"
+    if index_url:
+        install_cmd += f" --index-url {index_url}"
+    if module_name == "sdkit" and version("sdkit") is not None:
+        install_cmd += " -q"
+
+    print(">", install_cmd)
+    os.system(install_cmd)
+
+
+def init():
+    for module_name, allowed_versions in modules_to_check.items():
+        if os.path.exists(f"../src/{module_name}"):
+            print(f"Skipping {module_name} update, since it's in developer/editable mode")
+            continue
+
+        allowed_versions, latest_version = get_allowed_versions(module_name, allowed_versions)
+
+        requires_install = False
+        if module_name in ("torch", "torchvision"):
+            if version(module_name) is None:  # allow any torch version
+                requires_install = True
+            elif os_name == "Darwin" and (  # force mac to downgrade from torch 2.0
+                version("torch").startswith("2.") or version("torchvision").startswith("0.15.")
+            ):
+                requires_install = True
+        elif version(module_name) not in allowed_versions:
+            requires_install = True
+
+        if requires_install:
+            try:
+                install(module_name, latest_version)
+            except:
+                traceback.print_exc()
+                fail(module_name)
+
+        if module_name in modules_to_log:
+            print(f"{module_name}: {version(module_name)}")
+
+
+### utilities
+
+
+def get_allowed_versions(module_name: str, allowed_versions: tuple):
+    allowed_versions = (allowed_versions,) if isinstance(allowed_versions, str) else allowed_versions
+    latest_version = allowed_versions[-1]
+
+    if module_name in ("torch", "torchvision"):
+        allowed_versions = include_cuda_versions(allowed_versions)
+
+    return allowed_versions, latest_version
+
+
+def apply_torch_install_overrides(module_version: str):
+    index_url = None
+    if os_name == "Windows":
+        module_version += "+cu117"
+        index_url = "https://download.pytorch.org/whl/cu117"
+    elif is_amd_on_linux():
+        index_url = "https://download.pytorch.org/whl/rocm5.2"
+
+    return module_version, index_url
+
+
+def include_cuda_versions(module_versions: tuple) -> tuple:
+    "Adds CUDA-specific versions to the list of allowed version numbers"
+
+    allowed_versions = tuple(module_versions)
+    allowed_versions += tuple(f"{v}+cu116" for v in module_versions)
+    allowed_versions += tuple(f"{v}+cu117" for v in module_versions)
+    allowed_versions += tuple(f"{v}+rocm5.2" for v in module_versions)
+    allowed_versions += tuple(f"{v}+rocm5.4.2" for v in module_versions)
+
+    return allowed_versions
+
+
+def is_amd_on_linux():
+    if os_name == "Linux":
+        try:
+            with open("/proc/bus/pci/devices", "r") as f:
+                device_info = f.read()
+                if "amdgpu" in device_info and "nvidia" not in device_info:
+                    return True
+        except:
+            return False
+
+    return False
+
+
+def fail(module_name):
+    print(
+        f"""Error installing {module_name}. Sorry about that, please try to:
+1. Run this installer again.
+2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting
+3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB
+4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues
+Thanks!"""
+    )
+    exit(1)
+
+
+### start
+
+init()

scripts/developer_console.sh

@@ -26,21 +26,25 @@ if [ "$0" == "bash" ]; then
 
   echo ""
 
-  # activate the environment
-  CONDA_BASEPATH=$(conda info --base)
-  source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # otherwise conda complains about 'shell not initialized' (needed when running in a script)
+  # activate the legacy environment (if present) and set PYTHONPATH
+  if [ -e "installer_files/env" ]; then
+    export PYTHONPATH="$(pwd)/installer_files/env/lib/python3.8/site-packages"
+  fi
+  if [ -e "stable-diffusion/env" ]; then
+    CONDA_BASEPATH=$(conda info --base)
+    source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # otherwise conda complains about 'shell not initialized' (needed when running in a script)
 
-  conda activate ./stable-diffusion/env
+    conda activate ./stable-diffusion/env
+
+    export PYTHONPATH="$(pwd)/stable-diffusion/env/lib/python3.8/site-packages"
+  fi
+
+  export PYTHONNOUSERSITE=y
 
   which python
   python --version
 
-  # set the PYTHONPATH
-  cd stable-diffusion
-  SD_PATH=`pwd`
-  export PYTHONPATH="$SD_PATH:$SD_PATH/env/lib/python3.8/site-packages"
   echo "PYTHONPATH=$PYTHONPATH"
-  cd ..
 
   # done
 

scripts/functions.sh

@@ -28,5 +28,12 @@ EOF
 
 }
 
+filesize() {
+    case "$(uname -s)" in
+        Linux*)     stat -c "%s" $1;;
+        Darwin*)    /usr/bin/stat -f "%z" $1;;
+        *)          echo "Unknown OS: $OS_NAME! This script runs only on Linux or Mac" && exit
+    esac
+}
 
 

scripts/get_config.py

@@ -0,0 +1,47 @@
+import os
+import argparse
+import sys
+
+# The config file is in the same directory as this script
+config_directory = os.path.dirname(__file__)
+# config_yaml = os.path.join(config_directory, "config.yaml")
+config_json = os.path.join(config_directory, "config.json")
+
+parser = argparse.ArgumentParser(description='Get values from config file')
+parser.add_argument('--default', dest='default', action='store',
+                     help='default value, to be used if the setting is not defined in the config file')
+parser.add_argument('key', metavar='key', nargs='+',
+                    help='config key to return')
+
+args = parser.parse_args()
+
+
+# if os.path.isfile(config_yaml):
+#     import yaml
+#     with open(config_yaml, 'r') as configfile:
+#         try:
+#             config = yaml.safe_load(configfile)
+#         except Exception as e:
+#             print(e, file=sys.stderr)
+#             config = {}
+# el
+if os.path.isfile(config_json):
+    import json
+    with open(config_json, 'r') as configfile:
+        try:
+            config = json.load(configfile)
+        except Exception as e:
+            print(e, file=sys.stderr)
+            config = {}
+else:
+    config = {}
+
+for k in args.key:
+    if k in config:
+        config = config[k]
+    else:
+        if args.default != None:
+            print(args.default)
+            exit()
+
+print(config)

scripts/on_env_start.bat

@@ -1,6 +1,6 @@
 @echo off
 
-@echo. & echo "Stable Diffusion UI - v2" & echo.
+@echo. & echo "Easy Diffusion - v2" & echo.
 
 set PATH=C:\Windows\System32;%PATH%
 
@@ -8,6 +8,20 @@ if exist "scripts\config.bat" (
     @call scripts\config.bat
 )
 
+if exist "scripts\user_config.bat" (
+    @call scripts\user_config.bat
+)
+
+if exist "stable-diffusion\env" (
+    @set PYTHONPATH=%PYTHONPATH%;%cd%\stable-diffusion\env\lib\site-packages
+)
+
+if exist "scripts\get_config.py" (
+    @FOR /F "tokens=* USEBACKQ" %%F IN (`python scripts\get_config.py --default=main update_branch`) DO (
+        @SET update_branch=%%F
+    )
+)
+
 if "%update_branch%"=="" (
     set update_branch=main
 )
@@ -28,7 +42,7 @@ if "%update_branch%"=="" (
 
 @>nul findstr /m "sd_ui_git_cloned" scripts\install_status.txt
 @if "%ERRORLEVEL%" EQU "0" (
-    @echo "Stable Diffusion UI's git repository was already installed. Updating from %update_branch%.."
+    @echo "Easy Diffusion's git repository was already installed. Updating from %update_branch%.."
 
     @cd sd-ui-files
 
@@ -38,13 +52,13 @@ if "%update_branch%"=="" (
 
     @cd ..
 ) else (
-    @echo. & echo "Downloading Stable Diffusion UI.." & echo.
+    @echo. & echo "Downloading Easy Diffusion..." & echo.
     @echo "Using the %update_branch% channel" & echo.
 
     @call git clone -b "%update_branch%" https://github.com/cmdr2/stable-diffusion-ui.git sd-ui-files && (
         @echo sd_ui_git_cloned >> scripts\install_status.txt
     ) || (
-        @echo "Error downloading Stable Diffusion UI. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
+        @echo "Error downloading Easy Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
         pause
         @exit /b
     )
@@ -52,7 +66,8 @@ if "%update_branch%"=="" (
 
 @xcopy sd-ui-files\ui ui /s /i /Y /q
 @copy sd-ui-files\scripts\on_sd_start.bat scripts\ /Y
-@copy sd-ui-files\scripts\bootstrap.bat scripts\ /Y
+@copy sd-ui-files\scripts\check_modules.py scripts\ /Y
+@copy sd-ui-files\scripts\get_config.py scripts\ /Y
 @copy "sd-ui-files\scripts\Start Stable Diffusion UI.cmd" . /Y
 @copy "sd-ui-files\scripts\Developer Console.cmd" . /Y
 

scripts/on_env_start.sh

@@ -2,18 +2,30 @@
 
 source ./scripts/functions.sh
 
-printf "\n\nStable Diffusion UI\n\n"
+printf "\n\nEasy Diffusion\n\n"
+
+export PYTHONNOUSERSITE=y
 
 if [ -f "scripts/config.sh" ]; then
     source scripts/config.sh
 fi
 
+if [ -f "scripts/user_config.sh" ]; then
+    source scripts/user_config.sh
+fi
+
+export PYTHONPATH=$(pwd)/installer_files/env/lib/python3.8/site-packages:$(pwd)/stable-diffusion/env/lib/python3.8/site-packages
+
+if [ -f "scripts/get_config.py" ]; then
+   export update_branch="$( python scripts/get_config.py --default=main update_branch )"
+fi
+
 if [ "$update_branch" == "" ]; then
     export update_branch="main"
 fi
 
 if [ -f "scripts/install_status.txt" ] && [ `grep -c sd_ui_git_cloned scripts/install_status.txt` -gt "0" ]; then
-    echo "Stable Diffusion UI's git repository was already installed. Updating from $update_branch.."
+    echo "Easy Diffusion's git repository was already installed. Updating from $update_branch.."
 
     cd sd-ui-files
 
@@ -23,7 +35,7 @@ if [ -f "scripts/install_status.txt" ] && [ `grep -c sd_ui_git_cloned scripts/in
 
     cd ..
 else
-    printf "\n\nDownloading Stable Diffusion UI..\n\n"
+    printf "\n\nDownloading Easy Diffusion..\n\n"
     printf "Using the $update_branch channel\n\n"
 
     if git clone -b "$update_branch" https://github.com/cmdr2/stable-diffusion-ui.git sd-ui-files ; then
@@ -37,9 +49,10 @@ rm -rf ui
 cp -Rf sd-ui-files/ui .
 cp sd-ui-files/scripts/on_sd_start.sh scripts/
 cp sd-ui-files/scripts/bootstrap.sh scripts/
+cp sd-ui-files/scripts/check_modules.py scripts/
+cp sd-ui-files/scripts/get_config.py scripts/
 cp sd-ui-files/scripts/start.sh .
 cp sd-ui-files/scripts/developer_console.sh .
+cp sd-ui-files/scripts/functions.sh scripts/
 
-./scripts/on_sd_start.sh
-
-read -p "Press any key to continue"
+exec ./scripts/on_sd_start.sh

scripts/on_sd_start.bat

@@ -4,10 +4,19 @@
 @REM Note to self: Please rewrite this in Python. For the sake of your own sanity.
 
 @copy sd-ui-files\scripts\on_env_start.bat scripts\ /Y
-@copy sd-ui-files\scripts\bootstrap.bat scripts\ /Y
+@copy sd-ui-files\scripts\check_modules.py scripts\ /Y
+@copy sd-ui-files\scripts\get_config.py scripts\ /Y
 
 if exist "%cd%\profile" (
-    set USERPROFILE=%cd%\profile
+    set HF_HOME=%cd%\profile\.cache\huggingface
+)
+
+@rem set the correct installer path (current vs legacy)
+if exist "%cd%\installer_files\env" (
+    set INSTALL_ENV_DIR=%cd%\installer_files\env
+)
+if exist "%cd%\stable-diffusion\env" (
+    set INSTALL_ENV_DIR=%cd%\stable-diffusion\env
 )
 
 @mkdir tmp
@@ -17,7 +26,7 @@ if exist "%cd%\profile" (
 @rem activate the installer env
 call conda activate
 @if "%ERRORLEVEL%" NEQ "0" (
-       @echo. & echo "Error activating conda for Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+       @echo. & echo "Error activating conda for Easy Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
        pause
        exit /b
 )
@@ -25,143 +34,35 @@ call conda activate
 @REM remove the old version of the dev console script, if it's still present
 if exist "Open Developer Console.cmd" del "Open Developer Console.cmd"
 
-@call python -c "import os; import shutil; frm = 'sd-ui-files\\ui\\hotfix\\9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'; dst = os.path.join(os.path.expanduser('~'), '.cache', 'huggingface', 'transformers', '9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'); shutil.copyfile(frm, dst) if os.path.exists(dst) else print(''); print('Hotfixed broken JSON file from OpenAI');"
+@rem create the stable-diffusion folder, to work with legacy installations
+if not exist "stable-diffusion" mkdir stable-diffusion
+cd stable-diffusion
 
-if NOT DEFINED test_sd2 set test_sd2=N
-
-@>nul findstr /m "sd_git_cloned" scripts\install_status.txt
-@if "%ERRORLEVEL%" EQU "0" (
-    @echo "Stable Diffusion's git repository was already installed. Updating.."
-
-    @cd stable-diffusion
-
-    @call git remote set-url origin https://github.com/easydiffusion/diffusion-kit.git
-
-    @call git reset --hard
-    @call git pull
-
-    if "%test_sd2%" == "N" (
-        @call git -c advice.detachedHead=false checkout 7f32368ed1030a6e710537047bacd908adea183a
-    )
-    if "%test_sd2%" == "Y" (
-        @call git -c advice.detachedHead=false checkout 733a1f6f9cae9b9a9b83294bf3281b123378cb1f
-    )
-
-    @cd ..
-) else (
-    @echo. & echo "Downloading Stable Diffusion.." & echo.
-
-    @call git clone https://github.com/easydiffusion/diffusion-kit.git stable-diffusion && (
-        @echo sd_git_cloned >> scripts\install_status.txt
-    ) || (
-        @echo "Error downloading Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
-        pause
-        @exit /b
-    )
-
-    @cd stable-diffusion
-    @call git -c advice.detachedHead=false checkout 7f32368ed1030a6e710537047bacd908adea183a
-
-    @cd ..
+@rem activate the old stable-diffusion env, if it exists
+if exist "env" (
+    call conda activate .\env
 )
 
-@cd stable-diffusion
+@rem disable the legacy src and ldm folder (otherwise this prevents installing gfpgan and realesrgan)
+if exist src rename src src-old
+if exist ldm rename ldm ldm-old
 
-@>nul findstr /m "conda_sd_env_created" ..\scripts\install_status.txt
-@if "%ERRORLEVEL%" EQU "0" (
-    @echo "Packages necessary for Stable Diffusion were already installed"
 
-    @call conda activate .\env
-) else (
-    @echo. & echo "Downloading packages necessary for Stable Diffusion.." & echo. & echo "***** This will take some time (depending on the speed of the Internet connection) and may appear to be stuck, but please be patient ***** .." & echo.
-
-    @rmdir /s /q .\env
-
-    @REM prevent conda from using packages from the user's home directory, to avoid conflicts
-    @set PYTHONNOUSERSITE=1
-
-    set USERPROFILE=%cd%\profile
-
-    set PYTHONPATH=%cd%;%cd%\env\lib\site-packages
-
-    @call conda env create --prefix env -f environment.yaml || (
-        @echo. & echo "Error installing the packages necessary for Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-        pause
-        exit /b
-    )
-
-    @call conda activate .\env
-
-    for /f "tokens=*" %%a in ('python -c "import torch; import ldm; import transformers; import numpy; import antlr4; print(42)"') do if "%%a" NEQ "42" (
-        @echo. & echo "Dependency test failed! Error installing the packages necessary for Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-        pause
-        exit /b
-    )
-
-    @echo conda_sd_env_created >> ..\scripts\install_status.txt
-)
+if not exist "%INSTALL_ENV_DIR%\DLLs\libssl-1_1-x64.dll"    copy "%INSTALL_ENV_DIR%\Library\bin\libssl-1_1-x64.dll"    "%INSTALL_ENV_DIR%\DLLs\"
+if not exist "%INSTALL_ENV_DIR%\DLLs\libcrypto-1_1-x64.dll" copy "%INSTALL_ENV_DIR%\Library\bin\libcrypto-1_1-x64.dll" "%INSTALL_ENV_DIR%\DLLs\"
 
+@rem install or upgrade the required modules
 set PATH=C:\Windows\System32;%PATH%
 
-@>nul findstr /m "conda_sd_gfpgan_deps_installed" ..\scripts\install_status.txt
-@if "%ERRORLEVEL%" EQU "0" (
-    @echo "Packages necessary for GFPGAN (Face Correction) were already installed"
-) else (
-    @echo. & echo "Downloading packages necessary for GFPGAN (Face Correction).." & echo.
+@REM prevent from using packages from the user's home directory, to avoid conflicts
+set PYTHONNOUSERSITE=1
+set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
 
-    @set PYTHONNOUSERSITE=1
-
-    set USERPROFILE=%cd%\profile
-
-    set PYTHONPATH=%cd%;%cd%\env\lib\site-packages
-
-    for /f "tokens=*" %%a in ('python -c "from gfpgan import GFPGANer; print(42)"') do if "%%a" NEQ "42" (
-        @echo. & echo "Dependency test failed! Error installing the packages necessary for GFPGAN (Face Correction). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-        pause
-        exit /b
-    )
-
-    @echo conda_sd_gfpgan_deps_installed >> ..\scripts\install_status.txt
-)
-
-@>nul findstr /m "conda_sd_esrgan_deps_installed" ..\scripts\install_status.txt
-@if "%ERRORLEVEL%" EQU "0" (
-    @echo "Packages necessary for ESRGAN (Resolution Upscaling) were already installed"
-) else (
-    @echo. & echo "Downloading packages necessary for ESRGAN (Resolution Upscaling).." & echo.
-
-    @set PYTHONNOUSERSITE=1
-
-    set USERPROFILE=%cd%\profile
-
-    set PYTHONPATH=%cd%;%cd%\env\lib\site-packages
-
-    for /f "tokens=*" %%a in ('python -c "from basicsr.archs.rrdbnet_arch import RRDBNet; from realesrgan import RealESRGANer; print(42)"') do if "%%a" NEQ "42" (
-        @echo. & echo "Dependency test failed! Error installing the packages necessary for ESRGAN (Resolution Upscaling). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-        pause
-        exit /b
-    )
-
-    @echo conda_sd_esrgan_deps_installed >> ..\scripts\install_status.txt
-)
-
-@>nul findstr /m "conda_sd_ui_deps_installed" ..\scripts\install_status.txt
-@if "%ERRORLEVEL%" EQU "0" (
-    echo "Packages necessary for Stable Diffusion UI were already installed"
-) else (
-    @echo. & echo "Downloading packages necessary for Stable Diffusion UI.." & echo.
-
-    @set PYTHONNOUSERSITE=1
-
-    set USERPROFILE=%cd%\profile
-
-    set PYTHONPATH=%cd%;%cd%\env\lib\site-packages
-
-    @call conda install -c conda-forge -y --prefix env uvicorn fastapi || (
-        echo "Error installing the packages necessary for Stable Diffusion UI. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
-        pause
-        exit /b
-    )
+@rem Download the required packages
+call python ..\scripts\check_modules.py
+if "%ERRORLEVEL%" NEQ "0" (
+    pause
+    exit /b
 )
 
 call WHERE uvicorn > .tmp
@@ -172,233 +73,48 @@ call WHERE uvicorn > .tmp
     exit /b
 )
 
-@>nul 2>nul call python -m picklescan --help
-@if "%ERRORLEVEL%" NEQ "0" (
-    @echo. & echo Picklescan not found. Installing
-    @call pip install picklescan || (
-        echo "Error installing the picklescan package necessary for Stable Diffusion UI. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
-        pause
-        exit /b
-    )
-)
-
-@>nul 2>nul call python -c "import safetensors"
-@if "%ERRORLEVEL%" NEQ "0" (
-    @echo. & echo SafeTensors not found. Installing
-    @call pip install safetensors || (
-        echo "Error installing the safetensors package necessary for Stable Diffusion UI. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
-        pause
-        exit /b
-    )
-)
-
 @>nul findstr /m "conda_sd_ui_deps_installed" ..\scripts\install_status.txt
 @if "%ERRORLEVEL%" NEQ "0" (
     @echo conda_sd_ui_deps_installed >> ..\scripts\install_status.txt
 )
 
-
-
-if not exist "..\models\stable-diffusion" mkdir "..\models\stable-diffusion"
-if not exist "..\models\vae" mkdir "..\models\vae"
-if not exist "..\models\hypernetwork" mkdir "..\models\hypernetwork"
-echo. > "..\models\stable-diffusion\Put your custom ckpt files here.txt"
-echo. > "..\models\vae\Put your VAE files here.txt"
-echo. > "..\models\hypernetwork\Put your hypernetwork files here.txt"
-
-@if exist "sd-v1-4.ckpt" (
-    for %%I in ("sd-v1-4.ckpt") do if "%%~zI" EQU "4265380512" (
-        echo "Data files (weights) necessary for Stable Diffusion were already downloaded. Using the HuggingFace 4 GB Model."
-    ) else (
-        for %%J in ("sd-v1-4.ckpt") do if "%%~zJ" EQU "7703807346" (
-            echo "Data files (weights) necessary for Stable Diffusion were already downloaded. Using the HuggingFace 7 GB Model."
-        ) else (
-            for %%K in ("sd-v1-4.ckpt") do if "%%~zK" EQU "7703810927" (
-                echo "Data files (weights) necessary for Stable Diffusion were already downloaded. Using the Waifu Model."
-            ) else (
-                echo. & echo "The model file present at %cd%\sd-v1-4.ckpt is invalid. It is only %%~zK bytes in size. Re-downloading.." & echo.
-                del "sd-v1-4.ckpt"
-            )
-        )
-    )
-)
-
-@if not exist "sd-v1-4.ckpt" (
-    @echo. & echo "Downloading data files (weights) for Stable Diffusion.." & echo.
-
-    @call curl -L -k https://me.cmdr2.org/stable-diffusion-ui/sd-v1-4.ckpt > sd-v1-4.ckpt
-
-    @if exist "sd-v1-4.ckpt" (
-        for %%I in ("sd-v1-4.ckpt") do if "%%~zI" NEQ "4265380512" (
-            echo. & echo "Error: The downloaded model file was invalid! Bytes downloaded: %%~zI" & echo.
-            echo. & echo "Error downloading the data files (weights) for Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-            pause
-            exit /b
-        )
-    ) else (
-        @echo. & echo "Error downloading the data files (weights) for Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-        pause
-        exit /b
-    )
-)
-
-
-
-@if exist "GFPGANv1.3.pth" (
-    for %%I in ("GFPGANv1.3.pth") do if "%%~zI" EQU "348632874" (
-        echo "Data files (weights) necessary for GFPGAN (Face Correction) were already downloaded"
-    ) else (
-        echo. & echo "The GFPGAN model file present at %cd%\GFPGANv1.3.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
-        del "GFPGANv1.3.pth"
-    )
-)
-
-@if not exist "GFPGANv1.3.pth" (
-    @echo. & echo "Downloading data files (weights) for GFPGAN (Face Correction).." & echo.
-
-    @call curl -L -k https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth > GFPGANv1.3.pth
-
-    @if exist "GFPGANv1.3.pth" (
-        for %%I in ("GFPGANv1.3.pth") do if "%%~zI" NEQ "348632874" (
-            echo. & echo "Error: The downloaded GFPGAN model file was invalid! Bytes downloaded: %%~zI" & echo.
-            echo. & echo "Error downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-            pause
-            exit /b
-        )
-    ) else (
-        @echo. & echo "Error downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-        pause
-        exit /b
-    )
-)
-
-
-
-@if exist "RealESRGAN_x4plus.pth" (
-    for %%I in ("RealESRGAN_x4plus.pth") do if "%%~zI" EQU "67040989" (
-        echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus were already downloaded"
-    ) else (
-        echo. & echo "The RealESRGAN model file present at %cd%\RealESRGAN_x4plus.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
-        del "RealESRGAN_x4plus.pth"
-    )
-)
-
-@if not exist "RealESRGAN_x4plus.pth" (
-    @echo. & echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus.." & echo.
-
-    @call curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth > RealESRGAN_x4plus.pth
-
-    @if exist "RealESRGAN_x4plus.pth" (
-        for %%I in ("RealESRGAN_x4plus.pth") do if "%%~zI" NEQ "67040989" (
-            echo. & echo "Error: The downloaded ESRGAN x4plus model file was invalid! Bytes downloaded: %%~zI" & echo.
-            echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-            pause
-            exit /b
-        )
-    ) else (
-        @echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-        pause
-        exit /b
-    )
-)
-
-
-
-@if exist "RealESRGAN_x4plus_anime_6B.pth" (
-    for %%I in ("RealESRGAN_x4plus_anime_6B.pth") do if "%%~zI" EQU "17938799" (
-        echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus_anime were already downloaded"
-    ) else (
-        echo. & echo "The RealESRGAN model file present at %cd%\RealESRGAN_x4plus_anime_6B.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
-        del "RealESRGAN_x4plus_anime_6B.pth"
-    )
-)
-
-@if not exist "RealESRGAN_x4plus_anime_6B.pth" (
-    @echo. & echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime.." & echo.
-
-    @call curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth > RealESRGAN_x4plus_anime_6B.pth
-
-    @if exist "RealESRGAN_x4plus_anime_6B.pth" (
-        for %%I in ("RealESRGAN_x4plus_anime_6B.pth") do if "%%~zI" NEQ "17938799" (
-            echo. & echo "Error: The downloaded ESRGAN x4plus_anime model file was invalid! Bytes downloaded: %%~zI" & echo.
-            echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-            pause
-            exit /b
-        )
-    ) else (
-        @echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-        pause
-        exit /b
-    )
-)
-
-
-
-@if exist "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" (
-    for %%I in ("..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt") do if "%%~zI" EQU "334695179" (
-        echo "Data files (weights) necessary for the default VAE (sd-vae-ft-mse-original) were already downloaded"
-    ) else (
-        echo. & echo "The default VAE (sd-vae-ft-mse-original) file present at models\vae\vae-ft-mse-840000-ema-pruned.ckpt is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
-        del "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt"
-    )
-)
-
-@if not exist "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" (
-    @echo. & echo "Downloading data files (weights) for the default VAE (sd-vae-ft-mse-original).." & echo.
-
-    @call curl -L -k https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt > ..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt
-
-    @if exist "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" (
-        for %%I in ("..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt") do if "%%~zI" NEQ "334695179" (
-            echo. & echo "Error: The downloaded default VAE (sd-vae-ft-mse-original) file was invalid! Bytes downloaded: %%~zI" & echo.
-            echo. & echo "Error downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-            pause
-            exit /b
-        )
-    ) else (
-        @echo. & echo "Error downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-        pause
-        exit /b
-    )
-)
-
-if "%test_sd2%" == "Y" (
-    @call pip install open_clip_torch==2.0.2
-)
-
 @>nul findstr /m "sd_install_complete" ..\scripts\install_status.txt
 @if "%ERRORLEVEL%" NEQ "0" (
     @echo sd_weights_downloaded >> ..\scripts\install_status.txt
     @echo sd_install_complete >> ..\scripts\install_status.txt
 )
 
-@echo. & echo "Stable Diffusion is ready!" & echo.
+@echo. & echo "Easy Diffusion installation complete! Starting the server!" & echo.
 
 @set SD_DIR=%cd%
 
-@cd env\lib\site-packages
-@set PYTHONPATH=%SD_DIR%;%cd%
-@cd ..\..\..
-@echo PYTHONPATH=%PYTHONPATH%
+set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
+echo PYTHONPATH=%PYTHONPATH%
 
 call where python
 call python --version
 
 @cd ..
 @set SD_UI_PATH=%cd%\ui
+
+@FOR /F "tokens=* USEBACKQ" %%F IN (`python scripts\get_config.py --default=9000 net listen_port`) DO (
+    @SET ED_BIND_PORT=%%F
+)
+
+@FOR /F "tokens=* USEBACKQ" %%F IN (`python scripts\get_config.py --default=False net listen_to_network`) DO (
+    if "%%F" EQU "True" (
+        @SET ED_BIND_IP=0.0.0.0    
+    ) else (
+        @SET ED_BIND_IP=127.0.0.1
+    )
+)
+
 @cd stable-diffusion
 
-@rem
-@rem Rewrite easy-install.pth. This fixes the installation if the user has relocated the SDUI installation
-@rem
->env\Lib\site-packages\easy-install.pth echo %cd%\src\taming-transformers
->>env\Lib\site-packages\easy-install.pth echo %cd%\src\clip
->>env\Lib\site-packages\easy-install.pth echo %cd%\src\gfpgan
->>env\Lib\site-packages\easy-install.pth echo %cd%\src\realesrgan
+@rem set any overrides
+set HF_HUB_DISABLE_SYMLINKS_WARNING=true
 
-@if NOT DEFINED SD_UI_BIND_PORT set SD_UI_BIND_PORT=9000
-@if NOT DEFINED SD_UI_BIND_IP set SD_UI_BIND_IP=0.0.0.0
-@uvicorn server:app --app-dir "%SD_UI_PATH%" --port %SD_UI_BIND_PORT% --host %SD_UI_BIND_IP%
+@uvicorn main:server_api --app-dir "%SD_UI_PATH%" --port %ED_BIND_PORT% --host %ED_BIND_IP% --log-level error
 
 
 @pause

scripts/on_sd_start.sh

@@ -1,9 +1,12 @@
 #!/bin/bash
 
-source ./scripts/functions.sh
-
+cp sd-ui-files/scripts/functions.sh scripts/
 cp sd-ui-files/scripts/on_env_start.sh scripts/
 cp sd-ui-files/scripts/bootstrap.sh scripts/
+cp sd-ui-files/scripts/check_modules.py scripts/
+cp sd-ui-files/scripts/get_config.py scripts/
+
+source ./scripts/functions.sh
 
 # activate the installer env
 CONDA_BASEPATH=$(conda info --base)
@@ -16,297 +19,35 @@ if [ -e "open_dev_console.sh" ]; then
     rm "open_dev_console.sh"
 fi
 
-python -c "import os; import shutil; frm = 'sd-ui-files/ui/hotfix/9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'; dst = os.path.join(os.path.expanduser('~'), '.cache', 'huggingface', 'transformers', '9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'); shutil.copyfile(frm, dst) if os.path.exists(dst) else print(''); print('Hotfixed broken JSON file from OpenAI');" 
-
-# Caution, this file will make your eyes and brain bleed. It's such an unholy mess.
-# Note to self: Please rewrite this in Python. For the sake of your own sanity.
-
-if [ "$test_sd2" == "" ]; then
-    export test_sd2="N"
-fi
-
-if [ -e "scripts/install_status.txt" ] && [ `grep -c sd_git_cloned scripts/install_status.txt` -gt "0" ]; then
-    echo "Stable Diffusion's git repository was already installed. Updating.."
-
-    cd stable-diffusion
-
-    git remote set-url origin https://github.com/easydiffusion/diffusion-kit.git
-
-    git reset --hard
-    git pull
-
-    if [ "$test_sd2" == "N" ]; then
-        git -c advice.detachedHead=false checkout 7f32368ed1030a6e710537047bacd908adea183a
-    elif [ "$test_sd2" == "Y" ]; then
-        git -c advice.detachedHead=false checkout 733a1f6f9cae9b9a9b83294bf3281b123378cb1f
-    fi
-
-    cd ..
-else
-    printf "\n\nDownloading Stable Diffusion..\n\n"
-
-    if git clone https://github.com/easydiffusion/diffusion-kit.git stable-diffusion ; then
-        echo sd_git_cloned >> scripts/install_status.txt
-    else
-        fail "git clone of basujindal/stable-diffusion.git failed"
-    fi
-
-    cd stable-diffusion
-    git -c advice.detachedHead=false checkout 7f32368ed1030a6e710537047bacd908adea183a
-
-    cd ..
+# set the correct installer path (current vs legacy)
+if [ -e "installer_files/env" ]; then
+    export INSTALL_ENV_DIR="$(pwd)/installer_files/env"
+fi
+if [ -e "stable-diffusion/env" ]; then
+    export INSTALL_ENV_DIR="$(pwd)/stable-diffusion/env"
 fi
 
+# create the stable-diffusion folder, to work with legacy installations
+if [ ! -e "stable-diffusion" ]; then mkdir stable-diffusion; fi
 cd stable-diffusion
 
-if [ `grep -c conda_sd_env_created ../scripts/install_status.txt` -gt "0" ]; then
-    echo "Packages necessary for Stable Diffusion were already installed"
-
+# activate the old stable-diffusion env, if it exists
+if [ -e "env" ]; then
     conda activate ./env || fail "conda activate failed"
-else
-    printf "\n\nDownloading packages necessary for Stable Diffusion..\n"
-    printf "\n\n***** This will take some time (depending on the speed of the Internet connection) and may appear to be stuck, but please be patient ***** ..\n\n"
-
-    # prevent conda from using packages from the user's home directory, to avoid conflicts
-    export PYTHONNOUSERSITE=1
-    export PYTHONPATH="$(pwd):$(pwd)/env/lib/site-packages"
-
-    if conda env create --prefix env --force -f environment.yaml ; then
-        echo "Installed. Testing.."
-    else
-        fail "'conda env create' failed"
-    fi
-
-    conda activate ./env || fail "conda activate failed"
-
-    out_test=`python -c "import torch; import ldm; import transformers; import numpy; import antlr4; print(42)"`
-    if [ "$out_test" != "42" ]; then
-        fail "Dependency test failed"
-    fi
-
-    echo conda_sd_env_created >> ../scripts/install_status.txt
 fi
 
-if [ `grep -c conda_sd_gfpgan_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
-    echo "Packages necessary for GFPGAN (Face Correction) were already installed"
-else
-    printf "\n\nDownloading packages necessary for GFPGAN (Face Correction)..\n"
+# disable the legacy src and ldm folder (otherwise this prevents installing gfpgan and realesrgan)
+if [ -e "src" ]; then mv src src-old; fi
+if [ -e "ldm" ]; then mv ldm ldm-old; fi
 
-    export PYTHONNOUSERSITE=1
-    export PYTHONPATH="$(pwd):$(pwd)/env/lib/site-packages"
-
-    out_test=`python -c "from gfpgan import GFPGANer; print(42)"`
-    if [ "$out_test" != "42" ]; then
-        echo "EE The dependency check has failed. This usually means that some system libraries are missing."
-	echo "EE On Debian/Ubuntu systems, this are often these packages: libsm6 libxext6 libxrender-dev"
-	echo "EE Other Linux distributions might have different package names for these libraries."
-        fail "GFPGAN dependency test failed"
-    fi
-
-    echo conda_sd_gfpgan_deps_installed >> ../scripts/install_status.txt
+# Download the required packages
+if ! python ../scripts/check_modules.py; then
+    read -p "Press any key to continue"
+    exit 1
 fi
 
-if [ `grep -c conda_sd_esrgan_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
-    echo "Packages necessary for ESRGAN (Resolution Upscaling) were already installed"
-else
-    printf "\n\nDownloading packages necessary for ESRGAN (Resolution Upscaling)..\n"
-
-    export PYTHONNOUSERSITE=1
-    export PYTHONPATH="$(pwd):$(pwd)/env/lib/site-packages"
-
-    out_test=`python -c "from basicsr.archs.rrdbnet_arch import RRDBNet; from realesrgan import RealESRGANer; print(42)"`
-    if [ "$out_test" != "42" ]; then
-        fail "ESRGAN dependency test failed"
-    fi
-
-    echo conda_sd_esrgan_deps_installed >> ../scripts/install_status.txt
-fi
-
-if [ `grep -c conda_sd_ui_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
-    echo "Packages necessary for Stable Diffusion UI were already installed"
-else
-    printf "\n\nDownloading packages necessary for Stable Diffusion UI..\n\n"
-
-    export PYTHONNOUSERSITE=1
-    export PYTHONPATH="$(pwd):$(pwd)/env/lib/site-packages"
-
-    if conda install -c conda-forge --prefix ./env -y uvicorn fastapi ; then
-        echo "Installed. Testing.."
-    else
-        fail "'conda install uvicorn' failed" 
-    fi
-
-    if ! command -v uvicorn &> /dev/null; then
-        fail "UI packages not found!"
-    fi
-
-    echo conda_sd_ui_deps_installed >> ../scripts/install_status.txt
-fi
-
-if python -m picklescan --help >/dev/null 2>&1; then
-    echo "Picklescan is already installed."
-else
-    echo "Picklescan not found, installing."
-    pip install picklescan || fail "Picklescan installation failed."
-fi
-
-if python -c "import safetensors" --help >/dev/null 2>&1; then
-    echo "SafeTensors is already installed."
-else
-    echo "SafeTensors not found, installing."
-    pip install safetensors || fail "SafeTensors installation failed."
-fi
-
-
-
-mkdir -p "../models/stable-diffusion"
-mkdir -p "../models/vae"
-mkdir -p "../models/hypernetwork"
-echo "" > "../models/stable-diffusion/Put your custom ckpt files here.txt"
-echo "" > "../models/vae/Put your VAE files here.txt"
-echo "" > "../models/hypernetwork/Put your hypernetwork files here.txt"
-
-if [ -f "sd-v1-4.ckpt" ]; then
-    model_size=`find "sd-v1-4.ckpt" -printf "%s"`
-
-    if [ "$model_size" -eq "4265380512" ] || [ "$model_size" -eq "7703807346" ] || [ "$model_size" -eq "7703810927" ]; then
-        echo "Data files (weights) necessary for Stable Diffusion were already downloaded"
-    else
-        printf "\n\nThe model file present at $PWD/sd-v1-4.ckpt is invalid. It is only $model_size bytes in size. Re-downloading.."
-        rm sd-v1-4.ckpt
-    fi
-fi
-
-if [ ! -f "sd-v1-4.ckpt" ]; then
-    echo "Downloading data files (weights) for Stable Diffusion.."
-
-    curl -L -k https://me.cmdr2.org/stable-diffusion-ui/sd-v1-4.ckpt > sd-v1-4.ckpt
-
-    if [ -f "sd-v1-4.ckpt" ]; then
-        model_size=`find "sd-v1-4.ckpt" -printf "%s"`
-        if [ ! "$model_size" == "4265380512" ]; then
-	    fail "The downloaded model file was invalid! Bytes downloaded: $model_size"
-        fi
-    else
-        fail "Error downloading the data files (weights) for Stable Diffusion"
-    fi
-fi
-
-
-if [ -f "GFPGANv1.3.pth" ]; then
-    model_size=`find "GFPGANv1.3.pth" -printf "%s"`
-
-    if [ "$model_size" -eq "348632874" ]; then
-        echo "Data files (weights) necessary for GFPGAN (Face Correction) were already downloaded"
-    else
-        printf "\n\nThe model file present at $PWD/GFPGANv1.3.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
-        rm GFPGANv1.3.pth
-    fi
-fi
-
-if [ ! -f "GFPGANv1.3.pth" ]; then
-    echo "Downloading data files (weights) for GFPGAN (Face Correction).."
-
-    curl -L -k https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth > GFPGANv1.3.pth
-
-    if [ -f "GFPGANv1.3.pth" ]; then
-        model_size=`find "GFPGANv1.3.pth" -printf "%s"`
-        if [ ! "$model_size" -eq "348632874" ]; then
-            fail "The downloaded GFPGAN model file was invalid! Bytes downloaded: $model_size"
-        fi
-    else
-        fail "Error downloading the data files (weights) for GFPGAN (Face Correction)."
-    fi
-fi
-
-
-if [ -f "RealESRGAN_x4plus.pth" ]; then
-    model_size=`find "RealESRGAN_x4plus.pth" -printf "%s"`
-
-    if [ "$model_size" -eq "67040989" ]; then
-        echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus were already downloaded"
-    else
-        printf "\n\nThe model file present at $PWD/RealESRGAN_x4plus.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
-        rm RealESRGAN_x4plus.pth
-    fi
-fi
-
-if [ ! -f "RealESRGAN_x4plus.pth" ]; then
-    echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus.."
-
-    curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth > RealESRGAN_x4plus.pth
-
-    if [ -f "RealESRGAN_x4plus.pth" ]; then
-        model_size=`find "RealESRGAN_x4plus.pth" -printf "%s"`
-        if [ ! "$model_size" -eq "67040989" ]; then
-            fail "The downloaded ESRGAN x4plus model file was invalid! Bytes downloaded: $model_size"
-        fi
-    else
-        fail "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus"
-    fi
-fi
-
-
-if [ -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
-    model_size=`find "RealESRGAN_x4plus_anime_6B.pth" -printf "%s"`
-
-    if [ "$model_size" -eq "17938799" ]; then
-        echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus_anime were already downloaded"
-    else
-        printf "\n\nThe model file present at $PWD/RealESRGAN_x4plus_anime_6B.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
-        rm RealESRGAN_x4plus_anime_6B.pth
-    fi
-fi
-
-if [ ! -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
-    echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime.."
-
-    curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth > RealESRGAN_x4plus_anime_6B.pth
-
-    if [ -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
-        model_size=`find "RealESRGAN_x4plus_anime_6B.pth" -printf "%s"`
-        if [ ! "$model_size" -eq "17938799" ]; then
-            fail "The downloaded ESRGAN x4plus_anime model file was invalid! Bytes downloaded: $model_size"
-        fi
-    else
-        fail "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime."
-    fi
-fi
-
-
-if [ -f "../models/vae/vae-ft-mse-840000-ema-pruned.ckpt" ]; then
-    model_size=`find ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt -printf "%s"`
-
-    if [ "$model_size" -eq "334695179" ]; then
-        echo "Data files (weights) necessary for the default VAE (sd-vae-ft-mse-original) were already downloaded"
-    else
-        printf "\n\nThe model file present at models/vae/vae-ft-mse-840000-ema-pruned.ckpt is invalid. It is only $model_size bytes in size. Re-downloading.."
-        rm ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt
-    fi
-fi
-
-if [ ! -f "../models/vae/vae-ft-mse-840000-ema-pruned.ckpt" ]; then
-    echo "Downloading data files (weights) for the default VAE (sd-vae-ft-mse-original).."
-
-    curl -L -k https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt > ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt
-
-    if [ -f "../models/vae/vae-ft-mse-840000-ema-pruned.ckpt" ]; then
-        model_size=`find ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt -printf "%s"`
-        if [ ! "$model_size" -eq "334695179" ]; then
-            printf "\n\nError: The downloaded default VAE (sd-vae-ft-mse-original) file was invalid! Bytes downloaded: $model_size\n\n"
-            printf "\n\nError downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
-            read -p "Press any key to continue"
-            exit
-        fi
-    else
-        printf "\n\nError downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
-        read -p "Press any key to continue"
-        exit
-    fi
-fi
-
-if [ "$test_sd2" == "Y" ]; then
-    pip install open_clip_torch==2.0.2
+if ! command -v uvicorn &> /dev/null; then
+    fail "UI packages not found!"
 fi
 
 if [ `grep -c sd_install_complete ../scripts/install_status.txt` -gt "0" ]; then
@@ -314,10 +55,12 @@ if [ `grep -c sd_install_complete ../scripts/install_status.txt` -gt "0" ]; then
     echo sd_install_complete >> ../scripts/install_status.txt
 fi
 
-printf "\n\nStable Diffusion is ready!\n\n"
+printf "\n\nEasy Diffusion installation complete, starting the server!\n\n"
 
 SD_PATH=`pwd`
-export PYTHONPATH="$SD_PATH:$SD_PATH/env/lib/python3.8/site-packages"
+
+export PYTORCH_ENABLE_MPS_FALLBACK=1
+export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
 echo "PYTHONPATH=$PYTHONPATH"
 
 which python
@@ -325,8 +68,17 @@ python --version
 
 cd ..
 export SD_UI_PATH=`pwd`/ui
+export ED_BIND_PORT="$( python scripts/get_config.py --default=9000 net listen_port )"
+case "$( python scripts/get_config.py --default=False net listen_to_network )" in
+    "True")
+        export ED_BIND_IP=0.0.0.0
+        ;;
+    "False")
+        export ED_BIND_IP=127.0.0.1
+        ;;
+esac
 cd stable-diffusion
 
-uvicorn server:app --app-dir "$SD_UI_PATH" --port ${SD_UI_BIND_PORT:-9000} --host ${SD_UI_BIND_IP:-0.0.0.0}
+uvicorn main:server_api --app-dir "$SD_UI_PATH" --port "$ED_BIND_PORT" --host "$ED_BIND_IP" --log-level error
 
 read -p "Press any key to continue"

scripts/start.sh

@@ -2,6 +2,24 @@
 
 cd "$(dirname "${BASH_SOURCE[0]}")"
 
+if [ -f "on_sd_start.bat" ]; then
+    echo ================================================================================
+    echo
+    echo !!!! WARNING !!!!
+    echo
+    echo It looks like you\'re trying to run the installation script from a source code
+    echo download. This will not work.
+    echo
+    echo Recommended: Please close this window and download the installer from
+    echo https://stable-diffusion-ui.github.io/docs/installation/
+    echo
+    echo ================================================================================
+    echo
+    read
+    exit 1
+fi
+
+
 # set legacy installer's PATH, if it exists
 if [ -e "installer" ]; then export PATH="$(pwd)/installer/bin:$PATH"; fi
 
@@ -19,4 +37,5 @@ which conda
 conda --version || exit 1
 
 # Download the rest of the installer and UI
+chmod +x scripts/*.sh
 scripts/on_env_start.sh

ui/easydiffusion/app.py

@@ -0,0 +1,382 @@
+import json
+import logging
+import os
+import socket
+import sys
+import traceback
+import urllib
+import warnings
+
+from easydiffusion import task_manager
+from easydiffusion.utils import log
+from rich.logging import RichHandler
+from rich.console import Console
+from rich.panel import Panel
+from sdkit.utils import log as sdkit_log  # hack, so we can overwrite the log config
+
+# Remove all handlers associated with the root logger object.
+for handler in logging.root.handlers[:]:
+    logging.root.removeHandler(handler)
+
+LOG_FORMAT = "%(asctime)s.%(msecs)03d %(levelname)s %(threadName)s %(message)s"
+logging.basicConfig(
+    level=logging.INFO,
+    format=LOG_FORMAT,
+    datefmt="%X",
+    handlers=[RichHandler(markup=True, rich_tracebacks=False, show_time=False, show_level=False)],
+)
+
+SD_DIR = os.getcwd()
+
+SD_UI_DIR = os.getenv("SD_UI_PATH", None)
+
+CONFIG_DIR = os.path.abspath(os.path.join(SD_UI_DIR, "..", "scripts"))
+MODELS_DIR = os.path.abspath(os.path.join(SD_DIR, "..", "models"))
+
+USER_PLUGINS_DIR = os.path.abspath(os.path.join(SD_DIR, "..", "plugins"))
+CORE_PLUGINS_DIR = os.path.abspath(os.path.join(SD_UI_DIR, "plugins"))
+
+USER_UI_PLUGINS_DIR = os.path.join(USER_PLUGINS_DIR, "ui")
+CORE_UI_PLUGINS_DIR = os.path.join(CORE_PLUGINS_DIR, "ui")
+USER_SERVER_PLUGINS_DIR = os.path.join(USER_PLUGINS_DIR, "server")
+UI_PLUGINS_SOURCES = ((CORE_UI_PLUGINS_DIR, "core"), (USER_UI_PLUGINS_DIR, "user"))
+
+sys.path.append(os.path.dirname(SD_UI_DIR))
+sys.path.append(USER_SERVER_PLUGINS_DIR)
+
+OUTPUT_DIRNAME = "Stable Diffusion UI"  # in the user's home folder
+PRESERVE_CONFIG_VARS = ["FORCE_FULL_PRECISION"]
+TASK_TTL = 15 * 60  # Discard last session's task timeout
+APP_CONFIG_DEFAULTS = {
+    # auto: selects the cuda device with the most free memory, cuda: use the currently active cuda device.
+    "render_devices": "auto",  # valid entries: 'auto', 'cpu' or 'cuda:N' (where N is a GPU index)
+    "update_branch": "main",
+    "ui": {
+        "open_browser_on_start": True,
+    },
+}
+
+IMAGE_EXTENSIONS = [
+    ".png",
+    ".apng",
+    ".jpg",
+    ".jpeg",
+    ".jfif",
+    ".pjpeg",
+    ".pjp",
+    ".jxl",
+    ".gif",
+    ".webp",
+    ".avif",
+    ".svg",
+]
+CUSTOM_MODIFIERS_DIR = os.path.abspath(os.path.join(SD_DIR, "..", "modifiers"))
+CUSTOM_MODIFIERS_PORTRAIT_EXTENSIONS = [
+    ".portrait",
+    "_portrait",
+    " portrait",
+    "-portrait",
+]
+CUSTOM_MODIFIERS_LANDSCAPE_EXTENSIONS = [
+    ".landscape",
+    "_landscape",
+    " landscape",
+    "-landscape",
+]
+
+
+def init():
+    os.makedirs(USER_UI_PLUGINS_DIR, exist_ok=True)
+    os.makedirs(USER_SERVER_PLUGINS_DIR, exist_ok=True)
+
+    # https://pytorch.org/docs/stable/storage.html
+    warnings.filterwarnings("ignore", category=UserWarning, message="TypedStorage is deprecated")
+
+    load_server_plugins()
+
+    update_render_threads()
+
+
+def getConfig(default_val=APP_CONFIG_DEFAULTS):
+    try:
+        config_json_path = os.path.join(CONFIG_DIR, "config.json")
+
+        # compatibility with upcoming yaml changes, switching from beta to main
+        config_yaml_path = os.path.join(CONFIG_DIR, "..", "config.yaml")
+
+        # migrate the old config yaml location
+        config_legacy_yaml = os.path.join(CONFIG_DIR, "config.yaml")
+        if os.path.isfile(config_legacy_yaml):
+            shutil.move(config_legacy_yaml, config_yaml_path)
+
+        if os.path.exists(config_yaml_path):
+            try:
+                import yaml
+
+                with open(config_yaml_path, "r", encoding="utf-8") as f:
+                    config = yaml.safe_load(f)
+
+                setConfig(config)  # save to config.json
+                os.remove(config_yaml_path)  # delete the yaml file
+            except:
+                log.warn(traceback.format_exc())
+                config = default_val
+        elif not os.path.exists(config_json_path):
+            config = default_val
+        else:
+            with open(config_json_path, "r", encoding="utf-8") as f:
+                config = json.load(f)
+        if "net" not in config:
+            config["net"] = {}
+        if os.getenv("SD_UI_BIND_PORT") is not None:
+            config["net"]["listen_port"] = int(os.getenv("SD_UI_BIND_PORT"))
+        if os.getenv("SD_UI_BIND_IP") is not None:
+            config["net"]["listen_to_network"] = os.getenv("SD_UI_BIND_IP") == "0.0.0.0"
+        return config
+    except Exception:
+        log.warn(traceback.format_exc())
+        return default_val
+
+
+def setConfig(config):
+    try:  # config.json
+        config_json_path = os.path.join(CONFIG_DIR, "config.json")
+        with open(config_json_path, "w", encoding="utf-8") as f:
+            json.dump(config, f)
+    except:
+        log.error(traceback.format_exc())
+
+
+def save_to_config(ckpt_model_name, vae_model_name, hypernetwork_model_name, vram_usage_level):
+    config = getConfig()
+    if "model" not in config:
+        config["model"] = {}
+
+    config["model"]["stable-diffusion"] = ckpt_model_name
+    config["model"]["vae"] = vae_model_name
+    config["model"]["hypernetwork"] = hypernetwork_model_name
+
+    if vae_model_name is None or vae_model_name == "":
+        del config["model"]["vae"]
+    if hypernetwork_model_name is None or hypernetwork_model_name == "":
+        del config["model"]["hypernetwork"]
+
+    config["vram_usage_level"] = vram_usage_level
+
+    setConfig(config)
+
+
+def update_render_threads():
+    config = getConfig()
+    render_devices = config.get("render_devices", "auto")
+    active_devices = task_manager.get_devices()["active"].keys()
+
+    log.debug(f"requesting for render_devices: {render_devices}")
+    task_manager.update_render_threads(render_devices, active_devices)
+
+
+def getUIPlugins():
+    plugins = []
+
+    for plugins_dir, dir_prefix in UI_PLUGINS_SOURCES:
+        for file in os.listdir(plugins_dir):
+            if file.endswith(".plugin.js"):
+                plugins.append(f"/plugins/{dir_prefix}/{file}")
+
+    return plugins
+
+
+def load_server_plugins():
+    if not os.path.exists(USER_SERVER_PLUGINS_DIR):
+        return
+
+    import importlib
+
+    def load_plugin(file):
+        mod_path = file.replace(".py", "")
+        return importlib.import_module(mod_path)
+
+    def apply_plugin(file, plugin):
+        if hasattr(plugin, "get_cond_and_uncond"):
+            import sdkit.generate.image_generator
+
+            sdkit.generate.image_generator.get_cond_and_uncond = plugin.get_cond_and_uncond
+            log.info(f"Overridden get_cond_and_uncond with the one in the server plugin: {file}")
+
+    for file in os.listdir(USER_SERVER_PLUGINS_DIR):
+        file_path = os.path.join(USER_SERVER_PLUGINS_DIR, file)
+        if (not os.path.isdir(file_path) and not file_path.endswith("_plugin.py")) or (
+            os.path.isdir(file_path) and not file_path.endswith("_plugin")
+        ):
+            continue
+
+        try:
+            log.info(f"Loading server plugin: {file}")
+            mod = load_plugin(file)
+
+            log.info(f"Applying server plugin: {file}")
+            apply_plugin(file, mod)
+        except:
+            log.warn(f"Error while loading a server plugin")
+            log.warn(traceback.format_exc())
+
+
+def getIPConfig():
+    try:
+        ips = socket.gethostbyname_ex(socket.gethostname())
+        ips[2].append(ips[0])
+        return ips[2]
+    except Exception as e:
+        log.exception(e)
+        return []
+
+
+def open_browser():
+    config = getConfig()
+    ui = config.get("ui", {})
+    net = config.get("net", {})
+    port = net.get("listen_port", 9000)
+
+    if ui.get("open_browser_on_start", True):
+        import webbrowser
+
+        webbrowser.open(f"http://localhost:{port}")
+
+    Console().print(
+        Panel(
+            "\n"
+            + "[white]Easy Diffusion is ready to serve requests.\n\n"
+            + "A new browser tab should have been opened by now.\n"
+            + f"If not, please open your web browser and navigate to [bold yellow underline]http://localhost:{port}/\n",
+            title="Easy Diffusion is ready",
+            style="bold yellow on blue",
+        )
+    )
+
+
+def fail_and_die(fail_type: str, data: str):
+    suggestions = [
+        "Run this installer again.",
+        "If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB",
+        "If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues",
+    ]
+
+    if fail_type == "model_download":
+        fail_label = f"Error downloading the {data} model"
+        suggestions.insert(
+            1,
+            "If that doesn't fix it, please try to download the file manually. The address to download from, and the destination to save to are printed above this message.",
+        )
+    else:
+        fail_label = "Error while installing Easy Diffusion"
+
+    msg = [f"{fail_label}. Sorry about that, please try to:"]
+    for i, suggestion in enumerate(suggestions):
+        msg.append(f"{i+1}. {suggestion}")
+    msg.append("Thanks!")
+
+    print("\n".join(msg))
+    exit(1)
+
+
+def get_image_modifiers():
+    modifiers_json_path = os.path.join(SD_UI_DIR, "modifiers.json")
+
+    modifier_categories = {}
+    original_category_order = []
+    with open(modifiers_json_path, "r", encoding="utf-8") as f:
+        modifiers_file = json.load(f)
+
+        # The trailing slash is needed to support symlinks
+        if not os.path.isdir(f"{CUSTOM_MODIFIERS_DIR}/"):
+            return modifiers_file
+
+        # convert modifiers from a list of objects to a dict of dicts
+        for category_item in modifiers_file:
+            category_name = category_item["category"]
+            original_category_order.append(category_name)
+            category = {}
+            for modifier_item in category_item["modifiers"]:
+                modifier = {}
+                for preview_item in modifier_item["previews"]:
+                    modifier[preview_item["name"]] = preview_item["path"]
+                category[modifier_item["modifier"]] = modifier
+            modifier_categories[category_name] = category
+
+    def scan_directory(directory_path: str, category_name="Modifiers"):
+        for entry in os.scandir(directory_path):
+            if entry.is_file():
+                file_extension = list(filter(lambda e: entry.name.endswith(e), IMAGE_EXTENSIONS))
+                if len(file_extension) == 0:
+                    continue
+
+                modifier_name = entry.name[: -len(file_extension[0])]
+                modifier_path = f"custom/{entry.path[len(CUSTOM_MODIFIERS_DIR) + 1:]}"
+                # URL encode path segments
+                modifier_path = "/".join(
+                    map(
+                        lambda segment: urllib.parse.quote(segment),
+                        modifier_path.split("/"),
+                    )
+                )
+                is_portrait = True
+                is_landscape = True
+
+                portrait_extension = list(
+                    filter(
+                        lambda e: modifier_name.lower().endswith(e),
+                        CUSTOM_MODIFIERS_PORTRAIT_EXTENSIONS,
+                    )
+                )
+                landscape_extension = list(
+                    filter(
+                        lambda e: modifier_name.lower().endswith(e),
+                        CUSTOM_MODIFIERS_LANDSCAPE_EXTENSIONS,
+                    )
+                )
+
+                if len(portrait_extension) > 0:
+                    is_landscape = False
+                    modifier_name = modifier_name[: -len(portrait_extension[0])]
+                elif len(landscape_extension) > 0:
+                    is_portrait = False
+                    modifier_name = modifier_name[: -len(landscape_extension[0])]
+
+                if category_name not in modifier_categories:
+                    modifier_categories[category_name] = {}
+
+                category = modifier_categories[category_name]
+
+                if modifier_name not in category:
+                    category[modifier_name] = {}
+
+                if is_portrait or "portrait" not in category[modifier_name]:
+                    category[modifier_name]["portrait"] = modifier_path
+
+                if is_landscape or "landscape" not in category[modifier_name]:
+                    category[modifier_name]["landscape"] = modifier_path
+            elif entry.is_dir():
+                scan_directory(
+                    entry.path,
+                    entry.name if directory_path == CUSTOM_MODIFIERS_DIR else f"{category_name}/{entry.name}",
+                )
+
+    scan_directory(CUSTOM_MODIFIERS_DIR)
+
+    custom_categories = sorted(
+        [cn for cn in modifier_categories.keys() if cn not in original_category_order],
+        key=str.casefold,
+    )
+
+    # convert the modifiers back into a list of objects
+    modifier_categories_list = []
+    for category_name in [*original_category_order, *custom_categories]:
+        category = {"category": category_name, "modifiers": []}
+        for modifier_name in sorted(modifier_categories[category_name].keys(), key=str.casefold):
+            modifier = {"modifier": modifier_name, "previews": []}
+            for preview_name, preview_path in modifier_categories[category_name][modifier_name].items():
+                modifier["previews"].append({"name": preview_name, "path": preview_path})
+            category["modifiers"].append(modifier)
+        modifier_categories_list.append(category)
+
+    return modifier_categories_list

ui/easydiffusion/device_manager.py

@@ -0,0 +1,257 @@
+import os
+import platform
+import re
+import traceback
+
+import torch
+from easydiffusion.utils import log
+
+"""
+Set `FORCE_FULL_PRECISION` in the environment variables, or in `config.bat`/`config.sh` to set full precision (i.e. float32).
+Otherwise the models will load at half-precision (i.e. float16).
+
+Half-precision is fine most of the time. Full precision is only needed for working around GPU bugs (like NVIDIA 16xx GPUs).
+"""
+
+COMPARABLE_GPU_PERCENTILE = (
+    0.65  # if a GPU's free_mem is within this % of the GPU with the most free_mem, it will be picked
+)
+
+mem_free_threshold = 0
+
+
+def get_device_delta(render_devices, active_devices):
+    """
+    render_devices: 'cpu', or 'auto', or 'mps' or ['cuda:N'...]
+    active_devices: ['cpu', 'mps', 'cuda:N'...]
+    """
+
+    if render_devices in ("cpu", "auto", "mps"):
+        render_devices = [render_devices]
+    elif render_devices is not None:
+        if isinstance(render_devices, str):
+            render_devices = [render_devices]
+        if isinstance(render_devices, list) and len(render_devices) > 0:
+            render_devices = list(filter(lambda x: x.startswith("cuda:") or x == "mps", render_devices))
+            if len(render_devices) == 0:
+                raise Exception(
+                    'Invalid render_devices value in config.json. Valid: {"render_devices": ["cuda:0", "cuda:1"...]}, or {"render_devices": "cpu"} or {"render_devices": "mps"} or {"render_devices": "auto"}'
+                )
+
+            render_devices = list(filter(lambda x: is_device_compatible(x), render_devices))
+            if len(render_devices) == 0:
+                raise Exception(
+                    "Sorry, none of the render_devices configured in config.json are compatible with Stable Diffusion"
+                )
+        else:
+            raise Exception(
+                'Invalid render_devices value in config.json. Valid: {"render_devices": ["cuda:0", "cuda:1"...]}, or {"render_devices": "cpu"} or {"render_devices": "auto"}'
+            )
+    else:
+        render_devices = ["auto"]
+
+    if "auto" in render_devices:
+        render_devices = auto_pick_devices(active_devices)
+        if "cpu" in render_devices:
+            log.warn("WARNING: Could not find a compatible GPU. Using the CPU, but this will be very slow!")
+
+    active_devices = set(active_devices)
+    render_devices = set(render_devices)
+
+    devices_to_start = render_devices - active_devices
+    devices_to_stop = active_devices - render_devices
+
+    return devices_to_start, devices_to_stop
+
+
+def is_mps_available():
+    return (
+        platform.system() == "Darwin"
+        and hasattr(torch.backends, "mps")
+        and torch.backends.mps.is_available()
+        and torch.backends.mps.is_built()
+    )
+
+
+def is_cuda_available():
+    return torch.cuda.is_available()
+
+
+def auto_pick_devices(currently_active_devices):
+    global mem_free_threshold
+
+    if is_mps_available():
+        return ["mps"]
+
+    if not is_cuda_available():
+        return ["cpu"]
+
+    device_count = torch.cuda.device_count()
+    if device_count == 1:
+        return ["cuda:0"] if is_device_compatible("cuda:0") else ["cpu"]
+
+    log.debug("Autoselecting GPU. Using most free memory.")
+    devices = []
+    for device in range(device_count):
+        device = f"cuda:{device}"
+        if not is_device_compatible(device):
+            continue
+
+        mem_free, mem_total = torch.cuda.mem_get_info(device)
+        mem_free /= float(10**9)
+        mem_total /= float(10**9)
+        device_name = torch.cuda.get_device_name(device)
+        log.debug(
+            f"{device} detected: {device_name} - Memory (free/total): {round(mem_free, 2)}Gb / {round(mem_total, 2)}Gb"
+        )
+        devices.append({"device": device, "device_name": device_name, "mem_free": mem_free})
+
+    devices.sort(key=lambda x: x["mem_free"], reverse=True)
+    max_mem_free = devices[0]["mem_free"]
+    curr_mem_free_threshold = COMPARABLE_GPU_PERCENTILE * max_mem_free
+    mem_free_threshold = max(curr_mem_free_threshold, mem_free_threshold)
+
+    # Auto-pick algorithm:
+    # 1. Pick the top 75 percentile of the GPUs, sorted by free_mem.
+    # 2. Also include already-running devices (GPU-only), otherwise their free_mem will
+    #    always be very low (since their VRAM contains the model).
+    #    These already-running devices probably aren't terrible, since they were picked in the past.
+    #    Worst case, the user can restart the program and that'll get rid of them.
+    devices = list(
+        filter(
+            (lambda x: x["mem_free"] > mem_free_threshold or x["device"] in currently_active_devices),
+            devices,
+        )
+    )
+    devices = list(map(lambda x: x["device"], devices))
+    return devices
+
+
+def device_init(context, device):
+    """
+    This function assumes the 'device' has already been verified to be compatible.
+    `get_device_delta()` has already filtered out incompatible devices.
+    """
+
+    validate_device_id(device, log_prefix="device_init")
+
+    if "cuda" not in device:
+        context.device = device
+        context.device_name = get_processor_name()
+        context.half_precision = False
+        log.debug(f"Render device available as {context.device_name}")
+        return
+
+    context.device_name = torch.cuda.get_device_name(device)
+    context.device = device
+
+    # Force full precision on 1660 and 1650 NVIDIA cards to avoid creating green images
+    if needs_to_force_full_precision(context):
+        log.warn(f"forcing full precision on this GPU, to avoid green images. GPU detected: {context.device_name}")
+        # Apply force_full_precision now before models are loaded.
+        context.half_precision = False
+
+    log.info(f'Setting {device} as active, with precision: {"half" if context.half_precision else "full"}')
+    torch.cuda.device(device)
+
+
+def needs_to_force_full_precision(context):
+    if "FORCE_FULL_PRECISION" in os.environ:
+        return True
+
+    device_name = context.device_name.lower()
+    return (
+        ("nvidia" in device_name or "geforce" in device_name or "quadro" in device_name)
+        and (
+            " 1660" in device_name
+            or " 1650" in device_name
+            or " 1630" in device_name
+            or " t400" in device_name
+            or " t550" in device_name
+            or " t600" in device_name
+            or " t1000" in device_name
+            or " t1200" in device_name
+            or " t2000" in device_name
+        )
+    ) or ("tesla k40m" in device_name)
+
+
+def get_max_vram_usage_level(device):
+    if "cuda" in device:
+        _, mem_total = torch.cuda.mem_get_info(device)
+    else:
+        return "high"
+
+    mem_total /= float(10**9)
+    if mem_total < 4.5:
+        return "low"
+    elif mem_total < 6.5:
+        return "balanced"
+
+    return "high"
+
+
+def validate_device_id(device, log_prefix=""):
+    def is_valid():
+        if not isinstance(device, str):
+            return False
+        if device == "cpu" or device == "mps":
+            return True
+        if not device.startswith("cuda:") or not device[5:].isnumeric():
+            return False
+        return True
+
+    if not is_valid():
+        raise EnvironmentError(
+            f"{log_prefix}: device id should be 'cpu', 'mps', or 'cuda:N' (where N is an integer index for the GPU). Got: {device}"
+        )
+
+
+def is_device_compatible(device):
+    """
+    Returns True/False, and prints any compatibility errors
+    """
+    # static variable "history".
+    is_device_compatible.history = getattr(is_device_compatible, "history", {})
+    try:
+        validate_device_id(device, log_prefix="is_device_compatible")
+    except:
+        log.error(str(e))
+        return False
+
+    if device in ("cpu", "mps"):
+        return True
+    # Memory check
+    try:
+        _, mem_total = torch.cuda.mem_get_info(device)
+        mem_total /= float(10**9)
+        if mem_total < 1.9:
+            if is_device_compatible.history.get(device) == None:
+                log.warn(f"GPU {device} with less than 2 GB of VRAM is not compatible with Stable Diffusion")
+                is_device_compatible.history[device] = 1
+            return False
+    except RuntimeError as e:
+        log.error(str(e))
+        return False
+    return True
+
+
+def get_processor_name():
+    try:
+        import subprocess
+
+        if platform.system() == "Windows":
+            return platform.processor()
+        elif platform.system() == "Darwin":
+            os.environ["PATH"] = os.environ["PATH"] + os.pathsep + "/usr/sbin"
+            command = "sysctl -n machdep.cpu.brand_string"
+            return subprocess.check_output(command, shell=True).decode().strip()
+        elif platform.system() == "Linux":
+            command = "cat /proc/cpuinfo"
+            all_info = subprocess.check_output(command, shell=True).decode().strip()
+            for line in all_info.split("\n"):
+                if "model name" in line:
+                    return re.sub(".*model name.*:", "", line, 1).strip()
+    except:
+        log.error(traceback.format_exc())
+        return "cpu"

ui/easydiffusion/model_manager.py

@@ -0,0 +1,381 @@
+import os
+import shutil
+from glob import glob
+import traceback
+
+from easydiffusion import app
+from easydiffusion.types import TaskData
+from easydiffusion.utils import log
+from sdkit import Context
+from sdkit.models import load_model, scan_model, unload_model, download_model, get_model_info_from_db
+from sdkit.utils import hash_file_quick
+
+KNOWN_MODEL_TYPES = [
+    "stable-diffusion",
+    "vae",
+    "hypernetwork",
+    "gfpgan",
+    "realesrgan",
+    "lora",
+    "codeformer",
+]
+MODEL_EXTENSIONS = {
+    "stable-diffusion": [".ckpt", ".safetensors"],
+    "vae": [".vae.pt", ".ckpt", ".safetensors"],
+    "hypernetwork": [".pt", ".safetensors"],
+    "gfpgan": [".pth"],
+    "realesrgan": [".pth"],
+    "lora": [".ckpt", ".safetensors"],
+    "codeformer": [".pth"],
+}
+DEFAULT_MODELS = {
+    "stable-diffusion": [
+        {"file_name": "sd-v1-4.ckpt", "model_id": "1.4"},
+    ],
+    "gfpgan": [
+        {"file_name": "GFPGANv1.4.pth", "model_id": "1.4"},
+    ],
+    "realesrgan": [
+        {"file_name": "RealESRGAN_x4plus.pth", "model_id": "x4plus"},
+        {"file_name": "RealESRGAN_x4plus_anime_6B.pth", "model_id": "x4plus_anime_6"},
+    ],
+    "vae": [
+        {"file_name": "vae-ft-mse-840000-ema-pruned.ckpt", "model_id": "vae-ft-mse-840000-ema-pruned"},
+    ],
+}
+MODELS_TO_LOAD_ON_START = ["stable-diffusion", "vae", "hypernetwork", "lora"]
+
+known_models = {}
+
+
+def init():
+    make_model_folders()
+    migrate_legacy_model_location()  # if necessary
+    download_default_models_if_necessary()
+    getModels()  # run this once, to cache the picklescan results
+
+
+def load_default_models(context: Context):
+    set_vram_optimizations(context)
+
+    # init default model paths
+    for model_type in MODELS_TO_LOAD_ON_START:
+        context.model_paths[model_type] = resolve_model_to_use(model_type=model_type, fail_if_not_found=False)
+        try:
+            load_model(
+                context,
+                model_type,
+                scan_model=context.model_paths[model_type] != None
+                and not context.model_paths[model_type].endswith(".safetensors"),
+            )
+            if model_type in context.model_load_errors:
+                del context.model_load_errors[model_type]
+        except Exception as e:
+            log.error(f"[red]Error while loading {model_type} model: {context.model_paths[model_type]}[/red]")
+            if "DefaultCPUAllocator: not enough memory" in str(e):
+                log.error(
+                    f"[red]Your PC is low on system RAM. Please add some virtual memory (or swap space) by following the instructions at this link: https://www.ibm.com/docs/en/opw/8.2.0?topic=tuning-optional-increasing-paging-file-size-windows-computers[/red]"
+                )
+            else:
+                log.exception(e)
+            del context.model_paths[model_type]
+
+            context.model_load_errors[model_type] = str(e)  # storing the entire Exception can lead to memory leaks
+
+
+def unload_all(context: Context):
+    for model_type in KNOWN_MODEL_TYPES:
+        unload_model(context, model_type)
+        if model_type in context.model_load_errors:
+            del context.model_load_errors[model_type]
+
+
+def resolve_model_to_use(model_name: str = None, model_type: str = None, fail_if_not_found: bool = True):
+    model_extensions = MODEL_EXTENSIONS.get(model_type, [])
+    default_models = DEFAULT_MODELS.get(model_type, [])
+    config = app.getConfig()
+
+    model_dir = os.path.join(app.MODELS_DIR, model_type)
+    if not model_name:  # When None try user configured model.
+        # config = getConfig()
+        if "model" in config and model_type in config["model"]:
+            model_name = config["model"][model_type]
+
+    if model_name:
+        # Check models directory
+        model_path = os.path.join(model_dir, model_name)
+        if os.path.exists(model_path):
+            return model_path
+        for model_extension in model_extensions:
+            if os.path.exists(model_path + model_extension):
+                return model_path + model_extension
+            if os.path.exists(model_name + model_extension):
+                return os.path.abspath(model_name + model_extension)
+
+    # Can't find requested model, check the default paths.
+    if model_type == "stable-diffusion" and not fail_if_not_found:
+        for default_model in default_models:
+            default_model_path = os.path.join(model_dir, default_model["file_name"])
+            if os.path.exists(default_model_path):
+                if model_name is not None:
+                    log.warn(
+                        f"Could not find the configured custom model {model_name}. Using the default one: {default_model_path}"
+                    )
+                return default_model_path
+
+    if model_name and fail_if_not_found:
+        raise Exception(f"Could not find the desired model {model_name}! Is it present in the {model_dir} folder?")
+
+
+def reload_models_if_necessary(context: Context, task_data: TaskData):
+    face_fix_lower = task_data.use_face_correction.lower() if task_data.use_face_correction else ""
+    upscale_lower = task_data.use_upscale.lower() if task_data.use_upscale else ""
+
+    model_paths_in_req = {
+        "stable-diffusion": task_data.use_stable_diffusion_model,
+        "vae": task_data.use_vae_model,
+        "hypernetwork": task_data.use_hypernetwork_model,
+        "codeformer": task_data.use_face_correction if "codeformer" in face_fix_lower else None,
+        "gfpgan": task_data.use_face_correction if "gfpgan" in face_fix_lower else None,
+        "realesrgan": task_data.use_upscale if "realesrgan" in upscale_lower else None,
+        "latent_upscaler": True if "latent_upscaler" in upscale_lower else None,
+        "nsfw_checker": True if task_data.block_nsfw else None,
+        "lora": task_data.use_lora_model,
+    }
+    models_to_reload = {
+        model_type: path
+        for model_type, path in model_paths_in_req.items()
+        if context.model_paths.get(model_type) != path
+    }
+
+    if task_data.codeformer_upscale_faces:
+        if "realesrgan" not in models_to_reload and "realesrgan" not in context.models:
+            default_realesrgan = DEFAULT_MODELS["realesrgan"][0]["file_name"]
+            models_to_reload["realesrgan"] = resolve_model_to_use(default_realesrgan, "realesrgan")
+        elif "realesrgan" in models_to_reload and models_to_reload["realesrgan"] is None:
+            del models_to_reload["realesrgan"]  # don't unload realesrgan
+
+    if set_vram_optimizations(context) or set_clip_skip(context, task_data):  # reload SD
+        models_to_reload["stable-diffusion"] = model_paths_in_req["stable-diffusion"]
+
+    for model_type, model_path_in_req in models_to_reload.items():
+        context.model_paths[model_type] = model_path_in_req
+
+        action_fn = unload_model if context.model_paths[model_type] is None else load_model
+        try:
+            action_fn(context, model_type, scan_model=False)  # we've scanned them already
+            if model_type in context.model_load_errors:
+                del context.model_load_errors[model_type]
+        except Exception as e:
+            log.exception(e)
+            if action_fn == load_model:
+                context.model_load_errors[model_type] = str(e)  # storing the entire Exception can lead to memory leaks
+
+
+def resolve_model_paths(task_data: TaskData):
+    task_data.use_stable_diffusion_model = resolve_model_to_use(
+        task_data.use_stable_diffusion_model, model_type="stable-diffusion"
+    )
+    task_data.use_vae_model = resolve_model_to_use(task_data.use_vae_model, model_type="vae")
+    task_data.use_hypernetwork_model = resolve_model_to_use(task_data.use_hypernetwork_model, model_type="hypernetwork")
+    task_data.use_lora_model = resolve_model_to_use(task_data.use_lora_model, model_type="lora")
+
+    if task_data.use_face_correction:
+        if "gfpgan" in task_data.use_face_correction.lower():
+            model_type = "gfpgan"
+        elif "codeformer" in task_data.use_face_correction.lower():
+            model_type = "codeformer"
+            download_if_necessary("codeformer", "codeformer.pth", "codeformer-0.1.0")
+
+        task_data.use_face_correction = resolve_model_to_use(task_data.use_face_correction, model_type)
+    if task_data.use_upscale and "realesrgan" in task_data.use_upscale.lower():
+        task_data.use_upscale = resolve_model_to_use(task_data.use_upscale, "realesrgan")
+
+
+def fail_if_models_did_not_load(context: Context):
+    for model_type in KNOWN_MODEL_TYPES:
+        if model_type in context.model_load_errors:
+            e = context.model_load_errors[model_type]
+            raise Exception(f"Could not load the {model_type} model! Reason: " + e)
+
+
+def download_default_models_if_necessary():
+    for model_type, models in DEFAULT_MODELS.items():
+        for model in models:
+            try:
+                download_if_necessary(model_type, model["file_name"], model["model_id"])
+            except:
+                traceback.print_exc()
+                app.fail_and_die(fail_type="model_download", data=model_type)
+
+        print(model_type, "model(s) found.")
+
+
+def download_if_necessary(model_type: str, file_name: str, model_id: str):
+    model_path = os.path.join(app.MODELS_DIR, model_type, file_name)
+    expected_hash = get_model_info_from_db(model_type=model_type, model_id=model_id)["quick_hash"]
+
+    other_models_exist = any_model_exists(model_type)
+    known_model_exists = os.path.exists(model_path)
+    known_model_is_corrupt = known_model_exists and hash_file_quick(model_path) != expected_hash
+
+    if known_model_is_corrupt or (not other_models_exist and not known_model_exists):
+        print("> download", model_type, model_id)
+        download_model(model_type, model_id, download_base_dir=app.MODELS_DIR)
+
+
+def set_vram_optimizations(context: Context):
+    config = app.getConfig()
+    vram_usage_level = config.get("vram_usage_level", "balanced")
+
+    if vram_usage_level != context.vram_usage_level:
+        context.vram_usage_level = vram_usage_level
+        return True
+
+    return False
+
+
+def migrate_legacy_model_location():
+    'Move the models inside the legacy "stable-diffusion" folder, to their respective folders'
+
+    for model_type, models in DEFAULT_MODELS.items():
+        for model in models:
+            file_name = model["file_name"]
+            legacy_path = os.path.join(app.SD_DIR, file_name)
+            if os.path.exists(legacy_path):
+                shutil.move(legacy_path, os.path.join(app.MODELS_DIR, model_type, file_name))
+
+
+def any_model_exists(model_type: str) -> bool:
+    extensions = MODEL_EXTENSIONS.get(model_type, [])
+    for ext in extensions:
+        if any(glob(f"{app.MODELS_DIR}/{model_type}/**/*{ext}", recursive=True)):
+            return True
+
+    return False
+
+
+def set_clip_skip(context: Context, task_data: TaskData):
+    clip_skip = task_data.clip_skip
+
+    if clip_skip != context.clip_skip:
+        context.clip_skip = clip_skip
+        return True
+
+    return False
+
+
+def make_model_folders():
+    for model_type in KNOWN_MODEL_TYPES:
+        model_dir_path = os.path.join(app.MODELS_DIR, model_type)
+
+        os.makedirs(model_dir_path, exist_ok=True)
+
+        help_file_name = f"Place your {model_type} model files here.txt"
+        help_file_contents = f'Supported extensions: {" or ".join(MODEL_EXTENSIONS.get(model_type))}'
+
+        with open(os.path.join(model_dir_path, help_file_name), "w", encoding="utf-8") as f:
+            f.write(help_file_contents)
+
+
+def is_malicious_model(file_path):
+    try:
+        if file_path.endswith(".safetensors"):
+            return False
+        scan_result = scan_model(file_path)
+        if scan_result.issues_count > 0 or scan_result.infected_files > 0:
+            log.warn(
+                ":warning: [bold red]Scan %s: %d scanned, %d issue, %d infected.[/bold red]"
+                % (
+                    file_path,
+                    scan_result.scanned_files,
+                    scan_result.issues_count,
+                    scan_result.infected_files,
+                )
+            )
+            return True
+        else:
+            log.debug(
+                "Scan %s: [green]%d scanned, %d issue, %d infected.[/green]"
+                % (
+                    file_path,
+                    scan_result.scanned_files,
+                    scan_result.issues_count,
+                    scan_result.infected_files,
+                )
+            )
+            return False
+    except Exception as e:
+        log.error(f"error while scanning: {file_path}, error: {e}")
+    return False
+
+
+def getModels():
+    models = {
+        "options": {
+            "stable-diffusion": ["sd-v1-4"],
+            "vae": [],
+            "hypernetwork": [],
+            "lora": [],
+            "codeformer": ["codeformer"],
+        },
+    }
+
+    models_scanned = 0
+
+    class MaliciousModelException(Exception):
+        "Raised when picklescan reports a problem with a model"
+
+    def scan_directory(directory, suffixes, directoriesFirst: bool = True):
+        nonlocal models_scanned
+        tree = []
+        for entry in sorted(
+            os.scandir(directory),
+            key=lambda entry: (entry.is_file() == directoriesFirst, entry.name.lower()),
+        ):
+            if entry.is_file():
+                matching_suffix = list(filter(lambda s: entry.name.endswith(s), suffixes))
+                if len(matching_suffix) == 0:
+                    continue
+                matching_suffix = matching_suffix[0]
+
+                mtime = entry.stat().st_mtime
+                mod_time = known_models[entry.path] if entry.path in known_models else -1
+                if mod_time != mtime:
+                    models_scanned += 1
+                    if is_malicious_model(entry.path):
+                        raise MaliciousModelException(entry.path)
+                known_models[entry.path] = mtime
+                tree.append(entry.name[: -len(matching_suffix)])
+            elif entry.is_dir():
+                scan = scan_directory(entry.path, suffixes, directoriesFirst=False)
+
+                if len(scan) != 0:
+                    tree.append((entry.name, scan))
+        return tree
+
+    def listModels(model_type):
+        nonlocal models_scanned
+
+        model_extensions = MODEL_EXTENSIONS.get(model_type, [])
+        models_dir = os.path.join(app.MODELS_DIR, model_type)
+        if not os.path.exists(models_dir):
+            os.makedirs(models_dir)
+
+        try:
+            models["options"][model_type] = scan_directory(models_dir, model_extensions)
+        except MaliciousModelException as e:
+            models["scan-error"] = e
+
+    log.info(f"[green]Scanning all model folders for models...[/]")
+    # custom models
+    listModels(model_type="stable-diffusion")
+    listModels(model_type="vae")
+    listModels(model_type="hypernetwork")
+    listModels(model_type="gfpgan")
+    listModels(model_type="lora")
+
+    if models_scanned > 0:
+        log.info(f"[green]Scanned {models_scanned} models. Nothing infected[/]")
+
+    return models

ui/easydiffusion/renderer.py

@@ -0,0 +1,279 @@
+import json
+import pprint
+import queue
+import time
+
+from easydiffusion import device_manager
+from easydiffusion.types import GenerateImageRequest
+from easydiffusion.types import Image as ResponseImage
+from easydiffusion.types import Response, TaskData, UserInitiatedStop
+from easydiffusion.model_manager import DEFAULT_MODELS, resolve_model_to_use
+from easydiffusion.utils import get_printable_request, log, save_images_to_disk
+from sdkit import Context
+from sdkit.filter import apply_filters
+from sdkit.generate import generate_images
+from sdkit.models import load_model
+from sdkit.utils import (
+    diffusers_latent_samples_to_images,
+    gc,
+    img_to_base64_str,
+    img_to_buffer,
+    latent_samples_to_images,
+    get_device_usage,
+)
+
+context = Context()  # thread-local
+"""
+runtime data (bound locally to this thread), for e.g. device, references to loaded models, optimization flags etc
+"""
+
+
+def init(device):
+    """
+    Initializes the fields that will be bound to this runtime's context, and sets the current torch device
+    """
+    context.stop_processing = False
+    context.temp_images = {}
+    context.partial_x_samples = None
+    context.model_load_errors = {}
+    context.enable_codeformer = True
+
+    from easydiffusion import app
+
+    app_config = app.getConfig()
+    context.test_diffusers = (
+        app_config.get("test_diffusers", False) and app_config.get("update_branch", "main") != "main"
+    )
+
+    log.info("Device usage during initialization:")
+    get_device_usage(device, log_info=True, process_usage_only=False)
+
+    device_manager.device_init(context, device)
+
+
+def make_images(
+    req: GenerateImageRequest,
+    task_data: TaskData,
+    data_queue: queue.Queue,
+    task_temp_images: list,
+    step_callback,
+):
+    context.stop_processing = False
+    print_task_info(req, task_data)
+
+    images, seeds = make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
+
+    res = Response(
+        req,
+        task_data,
+        images=construct_response(images, seeds, task_data, base_seed=req.seed),
+    )
+    res = res.json()
+    data_queue.put(json.dumps(res))
+    log.info("Task completed")
+
+    return res
+
+
+def print_task_info(req: GenerateImageRequest, task_data: TaskData):
+    req_str = pprint.pformat(get_printable_request(req, task_data)).replace("[", "\[")
+    task_str = pprint.pformat(task_data.dict()).replace("[", "\[")
+    log.info(f"request: {req_str}")
+    log.info(f"task data: {task_str}")
+
+
+def make_images_internal(
+    req: GenerateImageRequest,
+    task_data: TaskData,
+    data_queue: queue.Queue,
+    task_temp_images: list,
+    step_callback,
+):
+    images, user_stopped = generate_images_internal(
+        req,
+        task_data,
+        data_queue,
+        task_temp_images,
+        step_callback,
+        task_data.stream_image_progress,
+        task_data.stream_image_progress_interval,
+    )
+    gc(context)
+    filtered_images = filter_images(req, task_data, images, user_stopped)
+
+    if task_data.save_to_disk_path is not None:
+        save_images_to_disk(images, filtered_images, req, task_data)
+
+    seeds = [*range(req.seed, req.seed + len(images))]
+    if task_data.show_only_filtered_image or filtered_images is images:
+        return filtered_images, seeds
+    else:
+        return images + filtered_images, seeds + seeds
+
+
+def generate_images_internal(
+    req: GenerateImageRequest,
+    task_data: TaskData,
+    data_queue: queue.Queue,
+    task_temp_images: list,
+    step_callback,
+    stream_image_progress: bool,
+    stream_image_progress_interval: int,
+):
+    context.temp_images.clear()
+
+    callback = make_step_callback(
+        req,
+        task_data,
+        data_queue,
+        task_temp_images,
+        step_callback,
+        stream_image_progress,
+        stream_image_progress_interval,
+    )
+
+    try:
+        if req.init_image is not None and not context.test_diffusers:
+            req.sampler_name = "ddim"
+
+        images = generate_images(context, callback=callback, **req.dict())
+        user_stopped = False
+    except UserInitiatedStop:
+        images = []
+        user_stopped = True
+        if context.partial_x_samples is not None:
+            if context.test_diffusers:
+                images = diffusers_latent_samples_to_images(context, context.partial_x_samples)
+            else:
+                images = latent_samples_to_images(context, context.partial_x_samples)
+    finally:
+        if hasattr(context, "partial_x_samples") and context.partial_x_samples is not None:
+            if not context.test_diffusers:
+                del context.partial_x_samples
+            context.partial_x_samples = None
+
+    return images, user_stopped
+
+
+def filter_images(req: GenerateImageRequest, task_data: TaskData, images: list, user_stopped):
+    if user_stopped:
+        return images
+
+    if task_data.block_nsfw:
+        images = apply_filters(context, "nsfw_checker", images)
+
+    if task_data.use_face_correction and "codeformer" in task_data.use_face_correction.lower():
+        default_realesrgan = DEFAULT_MODELS["realesrgan"][0]["file_name"]
+        prev_realesrgan_path = None
+        if task_data.codeformer_upscale_faces and default_realesrgan not in context.model_paths["realesrgan"]:
+            prev_realesrgan_path = context.model_paths["realesrgan"]
+            context.model_paths["realesrgan"] = resolve_model_to_use(default_realesrgan, "realesrgan")
+            load_model(context, "realesrgan")
+
+        try:
+            images = apply_filters(
+                context,
+                "codeformer",
+                images,
+                upscale_faces=task_data.codeformer_upscale_faces,
+                codeformer_fidelity=task_data.codeformer_fidelity,
+            )
+        finally:
+            if prev_realesrgan_path:
+                context.model_paths["realesrgan"] = prev_realesrgan_path
+                load_model(context, "realesrgan")
+    elif task_data.use_face_correction and "gfpgan" in task_data.use_face_correction.lower():
+        images = apply_filters(context, "gfpgan", images)
+
+    if task_data.use_upscale:
+        if "realesrgan" in task_data.use_upscale.lower():
+            images = apply_filters(context, "realesrgan", images, scale=task_data.upscale_amount)
+        elif task_data.use_upscale == "latent_upscaler":
+            images = apply_filters(
+                context,
+                "latent_upscaler",
+                images,
+                scale=task_data.upscale_amount,
+                latent_upscaler_options={
+                    "prompt": req.prompt,
+                    "negative_prompt": req.negative_prompt,
+                    "seed": req.seed,
+                    "num_inference_steps": task_data.latent_upscaler_steps,
+                    "guidance_scale": 0,
+                },
+            )
+
+    return images
+
+
+def construct_response(images: list, seeds: list, task_data: TaskData, base_seed: int):
+    return [
+        ResponseImage(
+            data=img_to_base64_str(
+                img,
+                task_data.output_format,
+                task_data.output_quality,
+                task_data.output_lossless,
+            ),
+            seed=seed,
+        )
+        for img, seed in zip(images, seeds)
+    ]
+
+
+def make_step_callback(
+    req: GenerateImageRequest,
+    task_data: TaskData,
+    data_queue: queue.Queue,
+    task_temp_images: list,
+    step_callback,
+    stream_image_progress: bool,
+    stream_image_progress_interval: int,
+):
+    n_steps = req.num_inference_steps if req.init_image is None else int(req.num_inference_steps * req.prompt_strength)
+    last_callback_time = -1
+
+    def update_temp_img(x_samples, task_temp_images: list):
+        partial_images = []
+
+        if context.test_diffusers:
+            images = diffusers_latent_samples_to_images(context, x_samples)
+        else:
+            images = latent_samples_to_images(context, x_samples)
+
+        if task_data.block_nsfw:
+            images = apply_filters(context, "nsfw_checker", images)
+
+        for i, img in enumerate(images):
+            buf = img_to_buffer(img, output_format="JPEG")
+
+            context.temp_images[f"{task_data.request_id}/{i}"] = buf
+            task_temp_images[i] = buf
+            partial_images.append({"path": f"/image/tmp/{task_data.request_id}/{i}"})
+        del images
+        return partial_images
+
+    def on_image_step(x_samples, i, *args):
+        nonlocal last_callback_time
+
+        if context.test_diffusers:
+            context.partial_x_samples = (x_samples, args[0])
+        else:
+            context.partial_x_samples = x_samples
+
+        step_time = time.time() - last_callback_time if last_callback_time != -1 else -1
+        last_callback_time = time.time()
+
+        progress = {"step": i, "step_time": step_time, "total_steps": n_steps}
+
+        if stream_image_progress and stream_image_progress_interval > 0 and i % stream_image_progress_interval == 0:
+            progress["output"] = update_temp_img(context.partial_x_samples, task_temp_images)
+
+        data_queue.put(json.dumps(progress))
+
+        step_callback()
+
+        if context.stop_processing:
+            raise UserInitiatedStop("User requested that we stop processing")
+
+    return on_image_step

ui/easydiffusion/server.py

@@ -0,0 +1,379 @@
+"""server.py: FastAPI SD-UI Web Host.
+Notes:
+    async endpoints always run on the main thread. Without they run on the thread pool.
+"""
+import datetime
+import mimetypes
+import os
+import traceback
+from typing import List, Union
+
+from easydiffusion import app, model_manager, task_manager
+from easydiffusion.types import GenerateImageRequest, MergeRequest, TaskData
+from easydiffusion.utils import log
+from fastapi import FastAPI, HTTPException
+from fastapi.staticfiles import StaticFiles
+from pydantic import BaseModel, Extra
+from starlette.responses import FileResponse, JSONResponse, StreamingResponse
+from pycloudflared import try_cloudflare
+
+log.info(f"started in {app.SD_DIR}")
+log.info(f"started at {datetime.datetime.now():%x %X}")
+
+server_api = FastAPI()
+
+NOCACHE_HEADERS = {
+    "Cache-Control": "no-cache, no-store, must-revalidate",
+    "Pragma": "no-cache",
+    "Expires": "0",
+}
+
+
+class NoCacheStaticFiles(StaticFiles):
+    def __init__(self, directory: str):
+        # follow_symlink is only available on fastapi >= 0.92.0
+        if os.path.islink(directory):
+            super().__init__(directory=os.path.realpath(directory))
+        else:
+            super().__init__(directory=directory)
+
+    def is_not_modified(self, response_headers, request_headers) -> bool:
+        if "content-type" in response_headers and (
+            "javascript" in response_headers["content-type"] or "css" in response_headers["content-type"]
+        ):
+            response_headers.update(NOCACHE_HEADERS)
+            return False
+
+        return super().is_not_modified(response_headers, request_headers)
+
+
+class SetAppConfigRequest(BaseModel, extra=Extra.allow):
+    update_branch: str = None
+    render_devices: Union[List[str], List[int], str, int] = None
+    model_vae: str = None
+    ui_open_browser_on_start: bool = None
+    listen_to_network: bool = None
+    listen_port: int = None
+    test_diffusers: bool = False
+
+
+def init():
+    mimetypes.init()
+    mimetypes.add_type("text/css", ".css")
+
+    if os.path.isdir(app.CUSTOM_MODIFIERS_DIR):
+        server_api.mount(
+            "/media/modifier-thumbnails/custom",
+            NoCacheStaticFiles(directory=app.CUSTOM_MODIFIERS_DIR),
+            name="custom-thumbnails",
+        )
+
+    server_api.mount(
+        "/media",
+        NoCacheStaticFiles(directory=os.path.join(app.SD_UI_DIR, "media")),
+        name="media",
+    )
+
+    for plugins_dir, dir_prefix in app.UI_PLUGINS_SOURCES:
+        server_api.mount(
+            f"/plugins/{dir_prefix}",
+            NoCacheStaticFiles(directory=plugins_dir),
+            name=f"plugins-{dir_prefix}",
+        )
+
+    @server_api.post("/app_config")
+    async def set_app_config(req: SetAppConfigRequest):
+        return set_app_config_internal(req)
+
+    @server_api.get("/get/{key:path}")
+    def read_web_data(key: str = None):
+        return read_web_data_internal(key)
+
+    @server_api.get("/ping")  # Get server and optionally session status.
+    def ping(session_id: str = None):
+        return ping_internal(session_id)
+
+    @server_api.post("/render")
+    def render(req: dict):
+        return render_internal(req)
+
+    @server_api.post("/model/merge")
+    def model_merge(req: dict):
+        print(req)
+        return model_merge_internal(req)
+
+    @server_api.get("/image/stream/{task_id:int}")
+    def stream(task_id: int):
+        return stream_internal(task_id)
+
+    @server_api.get("/image/stop")
+    def stop(task: int):
+        return stop_internal(task)
+
+    @server_api.get("/image/tmp/{task_id:int}/{img_id:int}")
+    def get_image(task_id: int, img_id: int):
+        return get_image_internal(task_id, img_id)
+
+    @server_api.post("/tunnel/cloudflare/start")
+    def start_cloudflare_tunnel(req: dict):
+        return start_cloudflare_tunnel_internal(req)
+
+    @server_api.post("/tunnel/cloudflare/stop")
+    def stop_cloudflare_tunnel(req: dict):
+        return stop_cloudflare_tunnel_internal(req)
+
+    @server_api.get("/")
+    def read_root():
+        return FileResponse(os.path.join(app.SD_UI_DIR, "index.html"), headers=NOCACHE_HEADERS)
+
+    @server_api.on_event("shutdown")
+    def shutdown_event():  # Signal render thread to close on shutdown
+        task_manager.current_state_error = SystemExit("Application shutting down.")
+
+
+# API implementations
+def set_app_config_internal(req: SetAppConfigRequest):
+    config = app.getConfig()
+    if req.update_branch is not None:
+        config["update_branch"] = req.update_branch
+    if req.render_devices is not None:
+        update_render_devices_in_config(config, req.render_devices)
+    if req.ui_open_browser_on_start is not None:
+        if "ui" not in config:
+            config["ui"] = {}
+        config["ui"]["open_browser_on_start"] = req.ui_open_browser_on_start
+    if req.listen_to_network is not None:
+        if "net" not in config:
+            config["net"] = {}
+        config["net"]["listen_to_network"] = bool(req.listen_to_network)
+    if req.listen_port is not None:
+        if "net" not in config:
+            config["net"] = {}
+        config["net"]["listen_port"] = int(req.listen_port)
+
+    config["test_diffusers"] = req.test_diffusers
+
+    for property, property_value in req.dict().items():
+        if property_value is not None and property not in req.__fields__:
+            config[property] = property_value
+
+    try:
+        app.setConfig(config)
+
+        if req.render_devices:
+            app.update_render_threads()
+
+        return JSONResponse({"status": "OK"}, headers=NOCACHE_HEADERS)
+    except Exception as e:
+        log.error(traceback.format_exc())
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+def update_render_devices_in_config(config, render_devices):
+    if render_devices not in ("cpu", "auto") and not render_devices.startswith("cuda:"):
+        raise HTTPException(status_code=400, detail=f"Invalid render device requested: {render_devices}")
+
+    if render_devices.startswith("cuda:"):
+        render_devices = render_devices.split(",")
+
+    config["render_devices"] = render_devices
+
+
+def read_web_data_internal(key: str = None):
+    if not key:  # /get without parameters, stable-diffusion easter egg.
+        raise HTTPException(status_code=418, detail="StableDiffusion is drawing a teapot!")  # HTTP418 I'm a teapot
+    elif key == "app_config":
+        return JSONResponse(app.getConfig(), headers=NOCACHE_HEADERS)
+    elif key == "system_info":
+        config = app.getConfig()
+
+        output_dir = config.get("force_save_path", os.path.join(os.path.expanduser("~"), app.OUTPUT_DIRNAME))
+
+        system_info = {
+            "devices": task_manager.get_devices(),
+            "hosts": app.getIPConfig(),
+            "default_output_dir": output_dir,
+            "enforce_output_dir": ("force_save_path" in config),
+        }
+        system_info["devices"]["config"] = config.get("render_devices", "auto")
+        return JSONResponse(system_info, headers=NOCACHE_HEADERS)
+    elif key == "models":
+        return JSONResponse(model_manager.getModels(), headers=NOCACHE_HEADERS)
+    elif key == "modifiers":
+        return JSONResponse(app.get_image_modifiers(), headers=NOCACHE_HEADERS)
+    elif key == "ui_plugins":
+        return JSONResponse(app.getUIPlugins(), headers=NOCACHE_HEADERS)
+    else:
+        raise HTTPException(status_code=404, detail=f"Request for unknown {key}")  # HTTP404 Not Found
+
+
+def ping_internal(session_id: str = None):
+    if task_manager.is_alive() <= 0:  # Check that render threads are alive.
+        if task_manager.current_state_error:
+            raise HTTPException(status_code=500, detail=str(task_manager.current_state_error))
+        raise HTTPException(status_code=500, detail="Render thread is dead.")
+    if task_manager.current_state_error and not isinstance(task_manager.current_state_error, StopAsyncIteration):
+        raise HTTPException(status_code=500, detail=str(task_manager.current_state_error))
+    # Alive
+    response = {"status": str(task_manager.current_state)}
+    if session_id:
+        session = task_manager.get_cached_session(session_id, update_ttl=True)
+        response["tasks"] = {id(t): t.status for t in session.tasks}
+    response["devices"] = task_manager.get_devices()
+    if cloudflare.address != None:
+        response["cloudflare"] = cloudflare.address
+    return JSONResponse(response, headers=NOCACHE_HEADERS)
+
+
+def render_internal(req: dict):
+    try:
+        # separate out the request data into rendering and task-specific data
+        render_req: GenerateImageRequest = GenerateImageRequest.parse_obj(req)
+        task_data: TaskData = TaskData.parse_obj(req)
+
+        # Overwrite user specified save path
+        config = app.getConfig()
+        if "force_save_path" in config:
+            task_data.save_to_disk_path = config["force_save_path"]
+
+        render_req.init_image_mask = req.get("mask")  # hack: will rename this in the HTTP API in a future revision
+
+        app.save_to_config(
+            task_data.use_stable_diffusion_model,
+            task_data.use_vae_model,
+            task_data.use_hypernetwork_model,
+            task_data.vram_usage_level,
+        )
+
+        # enqueue the task
+        new_task = task_manager.render(render_req, task_data)
+        response = {
+            "status": str(task_manager.current_state),
+            "queue": len(task_manager.tasks_queue),
+            "stream": f"/image/stream/{id(new_task)}",
+            "task": id(new_task),
+        }
+        return JSONResponse(response, headers=NOCACHE_HEADERS)
+    except ChildProcessError as e:  # Render thread is dead
+        raise HTTPException(status_code=500, detail=f"Rendering thread has died.")  # HTTP500 Internal Server Error
+    except ConnectionRefusedError as e:  # Unstarted task pending limit reached, deny queueing too many.
+        raise HTTPException(status_code=503, detail=str(e))  # HTTP503 Service Unavailable
+    except Exception as e:
+        log.error(traceback.format_exc())
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+def model_merge_internal(req: dict):
+    try:
+        from easydiffusion.utils.save_utils import filename_regex
+        from sdkit.train import merge_models
+
+        mergeReq: MergeRequest = MergeRequest.parse_obj(req)
+
+        merge_models(
+            model_manager.resolve_model_to_use(mergeReq.model0, "stable-diffusion"),
+            model_manager.resolve_model_to_use(mergeReq.model1, "stable-diffusion"),
+            mergeReq.ratio,
+            os.path.join(
+                app.MODELS_DIR,
+                "stable-diffusion",
+                filename_regex.sub("_", mergeReq.out_path),
+            ),
+            mergeReq.use_fp16,
+        )
+        return JSONResponse({"status": "OK"}, headers=NOCACHE_HEADERS)
+    except Exception as e:
+        log.error(traceback.format_exc())
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+def stream_internal(task_id: int):
+    # TODO Move to WebSockets ??
+    task = task_manager.get_cached_task(task_id, update_ttl=True)
+    if not task:
+        raise HTTPException(status_code=404, detail=f"Request {task_id} not found.")  # HTTP404 NotFound
+    # if (id(task) != task_id): raise HTTPException(status_code=409, detail=f'Wrong task id received. Expected:{id(task)}, Received:{task_id}') # HTTP409 Conflict
+    if task.buffer_queue.empty() and not task.lock.locked():
+        if task.response:
+            # log.info(f'Session {session_id} sending cached response')
+            return JSONResponse(task.response, headers=NOCACHE_HEADERS)
+        raise HTTPException(status_code=425, detail="Too Early, task not started yet.")  # HTTP425 Too Early
+    # log.info(f'Session {session_id} opened live render stream {id(task.buffer_queue)}')
+    return StreamingResponse(task.read_buffer_generator(), media_type="application/json")
+
+
+def stop_internal(task: int):
+    if not task:
+        if (
+            task_manager.current_state == task_manager.ServerStates.Online
+            or task_manager.current_state == task_manager.ServerStates.Unavailable
+        ):
+            raise HTTPException(status_code=409, detail="Not currently running any tasks.")  # HTTP409 Conflict
+        task_manager.current_state_error = StopAsyncIteration("")
+        return {"OK"}
+    task_id = task
+    task = task_manager.get_cached_task(task_id, update_ttl=False)
+    if not task:
+        raise HTTPException(status_code=404, detail=f"Task {task_id} was not found.")  # HTTP404 Not Found
+    if isinstance(task.error, StopAsyncIteration):
+        raise HTTPException(status_code=409, detail=f"Task {task_id} is already stopped.")  # HTTP409 Conflict
+    task.error = StopAsyncIteration(f"Task {task_id} stop requested.")
+    return {"OK"}
+
+
+def get_image_internal(task_id: int, img_id: int):
+    task = task_manager.get_cached_task(task_id, update_ttl=True)
+    if not task:
+        raise HTTPException(status_code=410, detail=f"Task {task_id} could not be found.")  # HTTP404 NotFound
+    if not task.temp_images[img_id]:
+        raise HTTPException(status_code=425, detail="Too Early, task data is not available yet.")  # HTTP425 Too Early
+    try:
+        img_data = task.temp_images[img_id]
+        img_data.seek(0)
+        return StreamingResponse(img_data, media_type="image/jpeg")
+    except KeyError as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+#---- Cloudflare Tunnel ----
+class CloudflareTunnel:
+    def __init__(self):
+        config = app.getConfig()
+        self.urls = None
+        self.port = config.get("net", {}).get("listen_port")
+
+    def start(self):
+        if self.port:
+            self.urls = try_cloudflare(self.port)
+
+    def stop(self):
+        if self.urls:
+            try_cloudflare.terminate(self.port)
+            self.urls = None
+
+    @property
+    def address(self):
+        if self.urls:
+            return self.urls.tunnel
+        else:
+            return None
+
+cloudflare = CloudflareTunnel()
+
+def start_cloudflare_tunnel_internal(req: dict):
+   try:
+      cloudflare.start()
+      log.info(f"- Started cloudflare tunnel. Using address: {cloudflare.address}")
+      return JSONResponse({"address":cloudflare.address})
+   except Exception as e:
+      log.error(str(e))
+      log.error(traceback.format_exc())
+      return HTTPException(status_code=500, detail=str(e))
+
+def stop_cloudflare_tunnel_internal(req: dict):
+   try:
+      cloudflare.stop()
+   except Exception as e:
+      log.error(str(e))
+      log.error(traceback.format_exc())
+      return HTTPException(status_code=500, detail=str(e))
+

ui/easydiffusion/task_manager.py

@@ -0,0 +1,575 @@
+"""task_manager.py: manage tasks dispatching and render threads.
+Notes:
+    render_threads should be the only hard reference held by the manager to the threads.
+    Use weak_thread_data to store all other data using weak keys.
+    This will allow for garbage collection after the thread dies.
+"""
+import json
+import traceback
+
+TASK_TTL = 30 * 60  # seconds, Discard last session's task timeout
+
+import queue
+import threading
+import time
+import weakref
+from typing import Any, Hashable
+
+import torch
+from easydiffusion import device_manager
+from easydiffusion.types import GenerateImageRequest, TaskData
+from easydiffusion.utils import log
+from sdkit.utils import gc
+
+THREAD_NAME_PREFIX = ""
+ERR_LOCK_FAILED = " failed to acquire lock within timeout."
+LOCK_TIMEOUT = 15  # Maximum locking time in seconds before failing a task.
+# It's better to get an exception than a deadlock... ALWAYS use timeout in critical paths.
+
+DEVICE_START_TIMEOUT = 60  # seconds - Maximum time to wait for a render device to init.
+
+
+class SymbolClass(type):  # Print nicely formatted Symbol names.
+    def __repr__(self):
+        return self.__qualname__
+
+    def __str__(self):
+        return self.__name__
+
+
+class Symbol(metaclass=SymbolClass):
+    pass
+
+
+class ServerStates:
+    class Init(Symbol):
+        pass
+
+    class LoadingModel(Symbol):
+        pass
+
+    class Online(Symbol):
+        pass
+
+    class Rendering(Symbol):
+        pass
+
+    class Unavailable(Symbol):
+        pass
+
+
+class RenderTask:  # Task with output queue and completion lock.
+    def __init__(self, req: GenerateImageRequest, task_data: TaskData):
+        task_data.request_id = id(self)
+        self.render_request: GenerateImageRequest = req  # Initial Request
+        self.task_data: TaskData = task_data
+        self.response: Any = None  # Copy of the last reponse
+        self.render_device = None  # Select the task affinity. (Not used to change active devices).
+        self.temp_images: list = [None] * req.num_outputs * (1 if task_data.show_only_filtered_image else 2)
+        self.error: Exception = None
+        self.lock: threading.Lock = threading.Lock()  # Locks at task start and unlocks when task is completed
+        self.buffer_queue: queue.Queue = queue.Queue()  # Queue of JSON string segments
+
+    async def read_buffer_generator(self):
+        try:
+            while not self.buffer_queue.empty():
+                res = self.buffer_queue.get(block=False)
+                self.buffer_queue.task_done()
+                yield res
+        except queue.Empty as e:
+            yield
+
+    @property
+    def status(self):
+        if self.lock.locked():
+            return "running"
+        if isinstance(self.error, StopAsyncIteration):
+            return "stopped"
+        if self.error:
+            return "error"
+        if not self.buffer_queue.empty():
+            return "buffer"
+        if self.response:
+            return "completed"
+        return "pending"
+
+    @property
+    def is_pending(self):
+        return bool(not self.response and not self.error)
+
+
+# Temporary cache to allow to query tasks results for a short time after they are completed.
+class DataCache:
+    def __init__(self):
+        self._base = dict()
+        self._lock: threading.Lock = threading.Lock()
+
+    def _get_ttl_time(self, ttl: int) -> int:
+        return int(time.time()) + ttl
+
+    def _is_expired(self, timestamp: int) -> bool:
+        return int(time.time()) >= timestamp
+
+    def clean(self) -> None:
+        if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
+            raise Exception("DataCache.clean" + ERR_LOCK_FAILED)
+        try:
+            # Create a list of expired keys to delete
+            to_delete = []
+            for key in self._base:
+                ttl, _ = self._base[key]
+                if self._is_expired(ttl):
+                    to_delete.append(key)
+            # Remove Items
+            for key in to_delete:
+                (_, val) = self._base[key]
+                if isinstance(val, RenderTask):
+                    log.debug(f"RenderTask {key} expired. Data removed.")
+                elif isinstance(val, SessionState):
+                    log.debug(f"Session {key} expired. Data removed.")
+                else:
+                    log.debug(f"Key {key} expired. Data removed.")
+                del self._base[key]
+        finally:
+            self._lock.release()
+
+    def clear(self) -> None:
+        if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
+            raise Exception("DataCache.clear" + ERR_LOCK_FAILED)
+        try:
+            self._base.clear()
+        finally:
+            self._lock.release()
+
+    def delete(self, key: Hashable) -> bool:
+        if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
+            raise Exception("DataCache.delete" + ERR_LOCK_FAILED)
+        try:
+            if key not in self._base:
+                return False
+            del self._base[key]
+            return True
+        finally:
+            self._lock.release()
+
+    def keep(self, key: Hashable, ttl: int) -> bool:
+        if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
+            raise Exception("DataCache.keep" + ERR_LOCK_FAILED)
+        try:
+            if key in self._base:
+                _, value = self._base.get(key)
+                self._base[key] = (self._get_ttl_time(ttl), value)
+                return True
+            return False
+        finally:
+            self._lock.release()
+
+    def put(self, key: Hashable, value: Any, ttl: int) -> bool:
+        if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
+            raise Exception("DataCache.put" + ERR_LOCK_FAILED)
+        try:
+            self._base[key] = (self._get_ttl_time(ttl), value)
+        except Exception:
+            log.error(traceback.format_exc())
+            return False
+        else:
+            return True
+        finally:
+            self._lock.release()
+
+    def tryGet(self, key: Hashable) -> Any:
+        if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
+            raise Exception("DataCache.tryGet" + ERR_LOCK_FAILED)
+        try:
+            ttl, value = self._base.get(key, (None, None))
+            if ttl is not None and self._is_expired(ttl):
+                log.debug(f"Session {key} expired. Discarding data.")
+                del self._base[key]
+                return None
+            return value
+        finally:
+            self._lock.release()
+
+
+manager_lock = threading.RLock()
+render_threads = []
+current_state = ServerStates.Init
+current_state_error: Exception = None
+tasks_queue = []
+session_cache = DataCache()
+task_cache = DataCache()
+weak_thread_data = weakref.WeakKeyDictionary()
+idle_event: threading.Event = threading.Event()
+
+
+class SessionState:
+    def __init__(self, id: str):
+        self._id = id
+        self._tasks_ids = []
+
+    @property
+    def id(self):
+        return self._id
+
+    @property
+    def tasks(self):
+        tasks = []
+        for task_id in self._tasks_ids:
+            task = task_cache.tryGet(task_id)
+            if task:
+                tasks.append(task)
+        return tasks
+
+    def put(self, task, ttl=TASK_TTL):
+        task_id = id(task)
+        self._tasks_ids.append(task_id)
+        if not task_cache.put(task_id, task, ttl):
+            return False
+        while len(self._tasks_ids) > len(render_threads) * 2:
+            self._tasks_ids.pop(0)
+        return True
+
+
+def thread_get_next_task():
+    from easydiffusion import renderer
+
+    if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
+        log.warn(f"Render thread on device: {renderer.context.device} failed to acquire manager lock.")
+        return None
+    if len(tasks_queue) <= 0:
+        manager_lock.release()
+        return None
+    task = None
+    try:  # Select a render task.
+        for queued_task in tasks_queue:
+            if queued_task.render_device and renderer.context.device != queued_task.render_device:
+                # Is asking for a specific render device.
+                if is_alive(queued_task.render_device) > 0:
+                    continue  # requested device alive, skip current one.
+                else:
+                    # Requested device is not active, return error to UI.
+                    queued_task.error = Exception(queued_task.render_device + " is not currently active.")
+                    task = queued_task
+                    break
+            if not queued_task.render_device and renderer.context.device == "cpu" and is_alive() > 1:
+                # not asking for any specific devices, cpu want to grab task but other render devices are alive.
+                continue  # Skip Tasks, don't run on CPU unless there is nothing else or user asked for it.
+            task = queued_task
+            break
+        if task is not None:
+            del tasks_queue[tasks_queue.index(task)]
+        return task
+    finally:
+        manager_lock.release()
+
+
+def thread_render(device):
+    global current_state, current_state_error
+
+    from easydiffusion import model_manager, renderer
+
+    try:
+        renderer.init(device)
+
+        weak_thread_data[threading.current_thread()] = {
+            "device": renderer.context.device,
+            "device_name": renderer.context.device_name,
+            "alive": True,
+        }
+
+        current_state = ServerStates.LoadingModel
+        model_manager.load_default_models(renderer.context)
+
+        current_state = ServerStates.Online
+    except Exception as e:
+        log.error(traceback.format_exc())
+        weak_thread_data[threading.current_thread()] = {"error": e, "alive": False}
+        return
+
+    while True:
+        session_cache.clean()
+        task_cache.clean()
+        if not weak_thread_data[threading.current_thread()]["alive"]:
+            log.info(f"Shutting down thread for device {renderer.context.device}")
+            model_manager.unload_all(renderer.context)
+            return
+        if isinstance(current_state_error, SystemExit):
+            current_state = ServerStates.Unavailable
+            return
+        task = thread_get_next_task()
+        if task is None:
+            idle_event.clear()
+            idle_event.wait(timeout=1)
+            continue
+        if task.error is not None:
+            log.error(task.error)
+            task.response = {"status": "failed", "detail": str(task.error)}
+            task.buffer_queue.put(json.dumps(task.response))
+            continue
+        if current_state_error:
+            task.error = current_state_error
+            task.response = {"status": "failed", "detail": str(task.error)}
+            task.buffer_queue.put(json.dumps(task.response))
+            continue
+        log.info(f"Session {task.task_data.session_id} starting task {id(task)} on {renderer.context.device_name}")
+        if not task.lock.acquire(blocking=False):
+            raise Exception("Got locked task from queue.")
+        try:
+
+            def step_callback():
+                global current_state_error
+
+                task_cache.keep(id(task), TASK_TTL)
+                session_cache.keep(task.task_data.session_id, TASK_TTL)
+
+                if (
+                    isinstance(current_state_error, SystemExit)
+                    or isinstance(current_state_error, StopAsyncIteration)
+                    or isinstance(task.error, StopAsyncIteration)
+                ):
+                    renderer.context.stop_processing = True
+                    if isinstance(current_state_error, StopAsyncIteration):
+                        task.error = current_state_error
+                        current_state_error = None
+                        log.info(f"Session {task.task_data.session_id} sent cancel signal for task {id(task)}")
+
+            current_state = ServerStates.LoadingModel
+            model_manager.resolve_model_paths(task.task_data)
+            model_manager.reload_models_if_necessary(renderer.context, task.task_data)
+            model_manager.fail_if_models_did_not_load(renderer.context)
+
+            current_state = ServerStates.Rendering
+            task.response = renderer.make_images(
+                task.render_request,
+                task.task_data,
+                task.buffer_queue,
+                task.temp_images,
+                step_callback,
+            )
+            # Before looping back to the generator, mark cache as still alive.
+            task_cache.keep(id(task), TASK_TTL)
+            session_cache.keep(task.task_data.session_id, TASK_TTL)
+        except Exception as e:
+            task.error = str(e)
+            task.response = {"status": "failed", "detail": str(task.error)}
+            task.buffer_queue.put(json.dumps(task.response))
+            log.error(traceback.format_exc())
+        finally:
+            gc(renderer.context)
+            task.lock.release()
+        task_cache.keep(id(task), TASK_TTL)
+        session_cache.keep(task.task_data.session_id, TASK_TTL)
+        if isinstance(task.error, StopAsyncIteration):
+            log.info(f"Session {task.task_data.session_id} task {id(task)} cancelled!")
+        elif task.error is not None:
+            log.info(f"Session {task.task_data.session_id} task {id(task)} failed!")
+        else:
+            log.info(
+                f"Session {task.task_data.session_id} task {id(task)} completed by {renderer.context.device_name}."
+            )
+        current_state = ServerStates.Online
+
+
+def get_cached_task(task_id: str, update_ttl: bool = False):
+    # By calling keep before tryGet, wont discard if was expired.
+    if update_ttl and not task_cache.keep(task_id, TASK_TTL):
+        # Failed to keep task, already gone.
+        return None
+    return task_cache.tryGet(task_id)
+
+
+def get_cached_session(session_id: str, update_ttl: bool = False):
+    if update_ttl:
+        session_cache.keep(session_id, TASK_TTL)
+    session = session_cache.tryGet(session_id)
+    if not session:
+        session = SessionState(session_id)
+        session_cache.put(session_id, session, TASK_TTL)
+    return session
+
+
+def get_devices():
+    devices = {
+        "all": {},
+        "active": {},
+    }
+
+    def get_device_info(device):
+        if device in ("cpu", "mps"):
+            return {"name": device_manager.get_processor_name()}
+
+        mem_free, mem_total = torch.cuda.mem_get_info(device)
+        mem_free /= float(10**9)
+        mem_total /= float(10**9)
+
+        return {
+            "name": torch.cuda.get_device_name(device),
+            "mem_free": mem_free,
+            "mem_total": mem_total,
+            "max_vram_usage_level": device_manager.get_max_vram_usage_level(device),
+        }
+
+    # list the compatible devices
+    cuda_count = torch.cuda.device_count()
+    for device in range(cuda_count):
+        device = f"cuda:{device}"
+        if not device_manager.is_device_compatible(device):
+            continue
+
+        devices["all"].update({device: get_device_info(device)})
+
+    if device_manager.is_mps_available():
+        devices["all"].update({"mps": get_device_info("mps")})
+
+    devices["all"].update({"cpu": get_device_info("cpu")})
+
+    # list the activated devices
+    if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
+        raise Exception("get_devices" + ERR_LOCK_FAILED)
+    try:
+        for rthread in render_threads:
+            if not rthread.is_alive():
+                continue
+            weak_data = weak_thread_data.get(rthread)
+            if not weak_data or not "device" in weak_data or not "device_name" in weak_data:
+                continue
+            device = weak_data["device"]
+            devices["active"].update({device: get_device_info(device)})
+    finally:
+        manager_lock.release()
+
+    return devices
+
+
+def is_alive(device=None):
+    if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
+        raise Exception("is_alive" + ERR_LOCK_FAILED)
+    nbr_alive = 0
+    try:
+        for rthread in render_threads:
+            if device is not None:
+                weak_data = weak_thread_data.get(rthread)
+                if weak_data is None or not "device" in weak_data or weak_data["device"] is None:
+                    continue
+                thread_device = weak_data["device"]
+                if thread_device != device:
+                    continue
+            if rthread.is_alive():
+                nbr_alive += 1
+        return nbr_alive
+    finally:
+        manager_lock.release()
+
+
+def start_render_thread(device):
+    if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
+        raise Exception("start_render_thread" + ERR_LOCK_FAILED)
+    log.info(f"Start new Rendering Thread on device: {device}")
+    try:
+        rthread = threading.Thread(target=thread_render, kwargs={"device": device})
+        rthread.daemon = True
+        rthread.name = THREAD_NAME_PREFIX + device
+        rthread.start()
+        render_threads.append(rthread)
+    finally:
+        manager_lock.release()
+    timeout = DEVICE_START_TIMEOUT
+    while not rthread.is_alive() or not rthread in weak_thread_data or not "device" in weak_thread_data[rthread]:
+        if rthread in weak_thread_data and "error" in weak_thread_data[rthread]:
+            log.error(f"{rthread}, {device}, error: {weak_thread_data[rthread]['error']}")
+            return False
+        if timeout <= 0:
+            return False
+        timeout -= 1
+        time.sleep(1)
+    return True
+
+
+def stop_render_thread(device):
+    try:
+        device_manager.validate_device_id(device, log_prefix="stop_render_thread")
+    except:
+        log.error(traceback.format_exc())
+        return False
+
+    if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
+        raise Exception("stop_render_thread" + ERR_LOCK_FAILED)
+    log.info(f"Stopping Rendering Thread on device: {device}")
+
+    try:
+        thread_to_remove = None
+        for rthread in render_threads:
+            weak_data = weak_thread_data.get(rthread)
+            if weak_data is None or not "device" in weak_data or weak_data["device"] is None:
+                continue
+            thread_device = weak_data["device"]
+            if thread_device == device:
+                weak_data["alive"] = False
+                thread_to_remove = rthread
+                break
+        if thread_to_remove is not None:
+            render_threads.remove(rthread)
+            return True
+    finally:
+        manager_lock.release()
+
+    return False
+
+
+def update_render_threads(render_devices, active_devices):
+    devices_to_start, devices_to_stop = device_manager.get_device_delta(render_devices, active_devices)
+    log.debug(f"devices_to_start: {devices_to_start}")
+    log.debug(f"devices_to_stop: {devices_to_stop}")
+
+    for device in devices_to_stop:
+        if is_alive(device) <= 0:
+            log.debug(f"{device} is not alive")
+            continue
+        if not stop_render_thread(device):
+            log.warn(f"{device} could not stop render thread")
+
+    for device in devices_to_start:
+        if is_alive(device) >= 1:
+            log.debug(f"{device} already registered.")
+            continue
+        if not start_render_thread(device):
+            log.warn(f"{device} failed to start.")
+
+    if is_alive() <= 0:  # No running devices, probably invalid user config.
+        raise EnvironmentError(
+            'ERROR: No active render devices! Please verify the "render_devices" value in config.json'
+        )
+
+    log.debug(f"active devices: {get_devices()['active']}")
+
+
+def shutdown_event():  # Signal render thread to close on shutdown
+    global current_state_error
+    current_state_error = SystemExit("Application shutting down.")
+
+
+def render(render_req: GenerateImageRequest, task_data: TaskData):
+    current_thread_count = is_alive()
+    if current_thread_count <= 0:  # Render thread is dead
+        raise ChildProcessError("Rendering thread has died.")
+
+    # Alive, check if task in cache
+    session = get_cached_session(task_data.session_id, update_ttl=True)
+    pending_tasks = list(filter(lambda t: t.is_pending, session.tasks))
+    if current_thread_count < len(pending_tasks):
+        raise ConnectionRefusedError(
+            f"Session {task_data.session_id} already has {len(pending_tasks)} pending tasks out of {current_thread_count}."
+        )
+
+    new_task = RenderTask(render_req, task_data)
+    if session.put(new_task, TASK_TTL):
+        # Use twice the normal timeout for adding user requests.
+        # Tries to force session.put to fail before tasks_queue.put would.
+        if manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT * 2):
+            try:
+                tasks_queue.append(new_task)
+                idle_event.set()
+                return new_task
+            finally:
+                manager_lock.release()
+    raise RuntimeError("Failed to add task to cache.")

ui/easydiffusion/types.py

@@ -0,0 +1,112 @@
+from typing import Any
+
+from pydantic import BaseModel
+
+
+class GenerateImageRequest(BaseModel):
+    prompt: str = ""
+    negative_prompt: str = ""
+
+    seed: int = 42
+    width: int = 512
+    height: int = 512
+
+    num_outputs: int = 1
+    num_inference_steps: int = 50
+    guidance_scale: float = 7.5
+
+    init_image: Any = None
+    init_image_mask: Any = None
+    prompt_strength: float = 0.8
+    preserve_init_image_color_profile = False
+
+    sampler_name: str = None  # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
+    hypernetwork_strength: float = 0
+    lora_alpha: float = 0
+    tiling: str = "none"  # "none", "x", "y", "xy"
+
+
+class TaskData(BaseModel):
+    request_id: str = None
+    session_id: str = "session"
+    save_to_disk_path: str = None
+    vram_usage_level: str = "balanced"  # or "low" or "medium"
+
+    use_face_correction: str = None  # or "GFPGANv1.3"
+    use_upscale: str = None  # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B" or "latent_upscaler"
+    upscale_amount: int = 4  # or 2
+    latent_upscaler_steps: int = 10
+    use_stable_diffusion_model: str = "sd-v1-4"
+    # use_stable_diffusion_config: str = "v1-inference"
+    use_vae_model: str = None
+    use_hypernetwork_model: str = None
+    use_lora_model: str = None
+
+    show_only_filtered_image: bool = False
+    block_nsfw: bool = False
+    output_format: str = "jpeg"  # or "png" or "webp"
+    output_quality: int = 75
+    output_lossless: bool = False
+    metadata_output_format: str = "txt"  # or "json"
+    stream_image_progress: bool = False
+    stream_image_progress_interval: int = 5
+    clip_skip: bool = False
+    codeformer_upscale_faces: bool = False
+    codeformer_fidelity: float = 0.5
+
+
+class MergeRequest(BaseModel):
+    model0: str = None
+    model1: str = None
+    ratio: float = None
+    out_path: str = "mix"
+    use_fp16 = True
+
+
+class Image:
+    data: str  # base64
+    seed: int
+    is_nsfw: bool
+    path_abs: str = None
+
+    def __init__(self, data, seed):
+        self.data = data
+        self.seed = seed
+
+    def json(self):
+        return {
+            "data": self.data,
+            "seed": self.seed,
+            "path_abs": self.path_abs,
+        }
+
+
+class Response:
+    render_request: GenerateImageRequest
+    task_data: TaskData
+    images: list
+
+    def __init__(self, render_request: GenerateImageRequest, task_data: TaskData, images: list):
+        self.render_request = render_request
+        self.task_data = task_data
+        self.images = images
+
+    def json(self):
+        del self.render_request.init_image
+        del self.render_request.init_image_mask
+
+        res = {
+            "status": "succeeded",
+            "render_request": self.render_request.dict(),
+            "task_data": self.task_data.dict(),
+            "output": [],
+        }
+
+        for image in self.images:
+            res["output"].append(image.json())
+
+        return res
+
+
+class UserInitiatedStop(Exception):
+    pass

ui/easydiffusion/utils/__init__.py

@@ -0,0 +1,8 @@
+import logging
+
+log = logging.getLogger("easydiffusion")
+
+from .save_utils import (
+    save_images_to_disk,
+    get_printable_request,
+)

ui/easydiffusion/utils/save_utils.py

@@ -0,0 +1,298 @@
+import os
+import re
+import time
+from datetime import datetime
+from functools import reduce
+
+from easydiffusion import app
+from easydiffusion.types import GenerateImageRequest, TaskData
+from numpy import base_repr
+from sdkit.utils import save_dicts, save_images
+
+filename_regex = re.compile("[^a-zA-Z0-9._-]")
+img_number_regex = re.compile("([0-9]{5,})")
+
+# keep in sync with `ui/media/js/dnd.js`
+TASK_TEXT_MAPPING = {
+    "prompt": "Prompt",
+    "negative_prompt": "Negative Prompt",
+    "seed": "Seed",
+    "use_stable_diffusion_model": "Stable Diffusion model",
+    "clip_skip": "Clip Skip",
+    "use_vae_model": "VAE model",
+    "sampler_name": "Sampler",
+    "width": "Width",
+    "height": "Height",
+    "num_inference_steps": "Steps",
+    "guidance_scale": "Guidance Scale",
+    "prompt_strength": "Prompt Strength",
+    "use_lora_model": "LoRA model",
+    "lora_alpha": "LoRA Strength",
+    "use_hypernetwork_model": "Hypernetwork model",
+    "hypernetwork_strength": "Hypernetwork Strength",
+    "tiling": "Seamless Tiling",
+    "use_face_correction": "Use Face Correction",
+    "use_upscale": "Use Upscaling",
+    "upscale_amount": "Upscale By",
+    "latent_upscaler_steps": "Latent Upscaler Steps"
+}
+
+time_placeholders = {
+    "$yyyy": "%Y",
+    "$MM": "%m",
+    "$dd": "%d",
+    "$HH": "%H",
+    "$mm": "%M",
+    "$ss": "%S",
+}
+
+other_placeholders = {
+    "$id": lambda req, task_data: filename_regex.sub("_", task_data.session_id),
+    "$p": lambda req, task_data: filename_regex.sub("_", req.prompt)[:50],
+    "$s": lambda req, task_data: str(req.seed),
+}
+
+
+class ImageNumber:
+    _factory = None
+    _evaluated = False
+
+    def __init__(self, factory):
+        self._factory = factory
+        self._evaluated = None
+
+    def __call__(self) -> int:
+        if self._evaluated is None:
+            self._evaluated = self._factory()
+        return self._evaluated
+
+
+def format_placeholders(format: str, req: GenerateImageRequest, task_data: TaskData, now=None):
+    if now is None:
+        now = time.time()
+
+    for placeholder, time_format in time_placeholders.items():
+        if placeholder in format:
+            format = format.replace(placeholder, datetime.fromtimestamp(now).strftime(time_format))
+    for placeholder, replace_func in other_placeholders.items():
+        if placeholder in format:
+            format = format.replace(placeholder, replace_func(req, task_data))
+
+    return format
+
+
+def format_folder_name(format: str, req: GenerateImageRequest, task_data: TaskData):
+    format = format_placeholders(format, req, task_data)
+    return filename_regex.sub("_", format)
+
+
+def format_file_name(
+    format: str,
+    req: GenerateImageRequest,
+    task_data: TaskData,
+    now: float,
+    batch_file_number: int,
+    folder_img_number: ImageNumber,
+):
+    format = format_placeholders(format, req, task_data, now)
+
+    if "$n" in format:
+        format = format.replace("$n", f"{folder_img_number():05}")
+
+    if "$tsb64" in format:
+        img_id = base_repr(int(now * 10000), 36)[-7:] + base_repr(
+            int(batch_file_number), 36
+        )  # Base 36 conversion, 0-9, A-Z
+        format = format.replace("$tsb64", img_id)
+
+    if "$ts" in format:
+        format = format.replace("$ts", str(int(now * 1000) + batch_file_number))
+
+    return filename_regex.sub("_", format)
+
+
+def save_images_to_disk(images: list, filtered_images: list, req: GenerateImageRequest, task_data: TaskData):
+    now = time.time()
+    app_config = app.getConfig()
+    folder_format = app_config.get("folder_format", "$id")
+    save_dir_path = os.path.join(task_data.save_to_disk_path, format_folder_name(folder_format, req, task_data))
+    metadata_entries = get_metadata_entries_for_request(req, task_data)
+    file_number = calculate_img_number(save_dir_path, task_data)
+    make_filename = make_filename_callback(
+        app_config.get("filename_format", "$p_$tsb64"),
+        req,
+        task_data,
+        file_number,
+        now=now,
+    )
+
+    if task_data.show_only_filtered_image or filtered_images is images:
+        save_images(
+            filtered_images,
+            save_dir_path,
+            file_name=make_filename,
+            output_format=task_data.output_format,
+            output_quality=task_data.output_quality,
+            output_lossless=task_data.output_lossless,
+        )
+        if task_data.metadata_output_format:
+            for metadata_output_format in task_data.metadata_output_format.split(","):
+                if metadata_output_format.lower() in ["json", "txt", "embed"]:
+                    save_dicts(
+                        metadata_entries,
+                        save_dir_path,
+                        file_name=make_filename,
+                        output_format=metadata_output_format,
+                        file_format=task_data.output_format,
+                    )
+    else:
+        make_filter_filename = make_filename_callback(
+            app_config.get("filename_format", "$p_$tsb64"),
+            req,
+            task_data,
+            file_number,
+            now=now,
+            suffix="filtered",
+        )
+
+        save_images(
+            images,
+            save_dir_path,
+            file_name=make_filename,
+            output_format=task_data.output_format,
+            output_quality=task_data.output_quality,
+            output_lossless=task_data.output_lossless,
+        )
+        save_images(
+            filtered_images,
+            save_dir_path,
+            file_name=make_filter_filename,
+            output_format=task_data.output_format,
+            output_quality=task_data.output_quality,
+            output_lossless=task_data.output_lossless,
+        )
+        if task_data.metadata_output_format:
+            for metadata_output_format in task_data.metadata_output_format.split(","):
+                if metadata_output_format.lower() in ["json", "txt", "embed"]:
+                    save_dicts(
+                        metadata_entries,
+                        save_dir_path,
+                        file_name=make_filter_filename,
+                        output_format=task_data.metadata_output_format,
+                        file_format=task_data.output_format,
+                    )
+
+
+def get_metadata_entries_for_request(req: GenerateImageRequest, task_data: TaskData):
+    metadata = get_printable_request(req, task_data)
+
+    # if text, format it in the text format expected by the UI
+    is_txt_format = task_data.metadata_output_format and "txt" in task_data.metadata_output_format.lower().split(",")
+    if is_txt_format:
+        metadata = {TASK_TEXT_MAPPING[key]: val for key, val in metadata.items() if key in TASK_TEXT_MAPPING}
+
+    entries = [metadata.copy() for _ in range(req.num_outputs)]
+    for i, entry in enumerate(entries):
+        entry["Seed" if is_txt_format else "seed"] = req.seed + i
+
+    return entries
+
+
+def get_printable_request(req: GenerateImageRequest, task_data: TaskData):
+    req_metadata = req.dict()
+    task_data_metadata = task_data.dict()
+
+    # Save the metadata in the order defined in TASK_TEXT_MAPPING
+    metadata = {}
+    for key in TASK_TEXT_MAPPING.keys():
+        if key in req_metadata:
+            metadata[key] = req_metadata[key]
+        elif key in task_data_metadata:
+            metadata[key] = task_data_metadata[key]
+    
+    # Clean up the metadata
+    if req.init_image is None and "prompt_strength" in metadata:
+        del metadata["prompt_strength"]
+    if task_data.use_upscale is None and "upscale_amount" in metadata:
+        del metadata["upscale_amount"]
+    if task_data.use_hypernetwork_model is None and "hypernetwork_strength" in metadata:
+        del metadata["hypernetwork_strength"]
+    if task_data.use_lora_model is None and "lora_alpha" in metadata:
+        del metadata["lora_alpha"]
+    if task_data.use_upscale != "latent_upscaler" and "latent_upscaler_steps" in metadata:
+        del metadata["latent_upscaler_steps"]
+
+    app_config = app.getConfig()
+    if not app_config.get("test_diffusers", False):
+        for key in (x for x in ["use_lora_model", "lora_alpha", "clip_skip", "tiling", "latent_upscaler_steps"] if x in metadata):
+            del metadata[key]
+
+    return metadata
+
+
+def make_filename_callback(
+    filename_format: str,
+    req: GenerateImageRequest,
+    task_data: TaskData,
+    folder_img_number: int,
+    suffix=None,
+    now=None,
+):
+    if now is None:
+        now = time.time()
+
+    def make_filename(i):
+        name = format_file_name(filename_format, req, task_data, now, i, folder_img_number)
+        name = name if suffix is None else f"{name}_{suffix}"
+
+        return name
+
+    return make_filename
+
+
+def _calculate_img_number(save_dir_path: str, task_data: TaskData):
+    def get_highest_img_number(accumulator: int, file: os.DirEntry) -> int:
+        if not file.is_file:
+            return accumulator
+
+        if len(list(filter(lambda e: file.name.endswith(e), app.IMAGE_EXTENSIONS))) == 0:
+            return accumulator
+
+        get_highest_img_number.number_of_images = get_highest_img_number.number_of_images + 1
+
+        number_match = img_number_regex.match(file.name)
+        if not number_match:
+            return accumulator
+
+        file_number = number_match.group().lstrip("0")
+
+        # Handle 00000
+        return int(file_number) if file_number else 0
+
+    get_highest_img_number.number_of_images = 0
+
+    highest_file_number = -1
+
+    if os.path.isdir(save_dir_path):
+        existing_files = list(os.scandir(save_dir_path))
+        highest_file_number = reduce(get_highest_img_number, existing_files, -1)
+
+    calculated_img_number = max(highest_file_number, get_highest_img_number.number_of_images - 1)
+
+    if task_data.session_id in _calculate_img_number.session_img_numbers:
+        calculated_img_number = max(
+            _calculate_img_number.session_img_numbers[task_data.session_id],
+            calculated_img_number,
+        )
+
+    calculated_img_number = calculated_img_number + 1
+
+    _calculate_img_number.session_img_numbers[task_data.session_id] = calculated_img_number
+    return calculated_img_number
+
+
+_calculate_img_number.session_img_numbers = {}
+
+
+def calculate_img_number(save_dir_path: str, task_data: TaskData):
+    return ImageNumber(lambda: _calculate_img_number(save_dir_path, task_data))

ui/hotfix/9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142

@@ -1,171 +0,0 @@
-{
-  "_name_or_path": "clip-vit-large-patch14/",
-  "architectures": [
-    "CLIPModel"
-  ],
-  "initializer_factor": 1.0,
-  "logit_scale_init_value": 2.6592,
-  "model_type": "clip",
-  "projection_dim": 768,
-  "text_config": {
-    "_name_or_path": "",
-    "add_cross_attention": false,
-    "architectures": null,
-    "attention_dropout": 0.0,
-    "bad_words_ids": null,
-    "bos_token_id": 0,
-    "chunk_size_feed_forward": 0,
-    "cross_attention_hidden_size": null,
-    "decoder_start_token_id": null,
-    "diversity_penalty": 0.0,
-    "do_sample": false,
-    "dropout": 0.0,
-    "early_stopping": false,
-    "encoder_no_repeat_ngram_size": 0,
-    "eos_token_id": 2,
-    "finetuning_task": null,
-    "forced_bos_token_id": null,
-    "forced_eos_token_id": null,
-    "hidden_act": "quick_gelu",
-    "hidden_size": 768,
-    "id2label": {
-      "0": "LABEL_0",
-      "1": "LABEL_1"
-    },
-    "initializer_factor": 1.0,
-    "initializer_range": 0.02,
-    "intermediate_size": 3072,
-    "is_decoder": false,
-    "is_encoder_decoder": false,
-    "label2id": {
-      "LABEL_0": 0,
-      "LABEL_1": 1
-    },
-    "layer_norm_eps": 1e-05,
-    "length_penalty": 1.0,
-    "max_length": 20,
-    "max_position_embeddings": 77,
-    "min_length": 0,
-    "model_type": "clip_text_model",
-    "no_repeat_ngram_size": 0,
-    "num_attention_heads": 12,
-    "num_beam_groups": 1,
-    "num_beams": 1,
-    "num_hidden_layers": 12,
-    "num_return_sequences": 1,
-    "output_attentions": false,
-    "output_hidden_states": false,
-    "output_scores": false,
-    "pad_token_id": 1,
-    "prefix": null,
-    "problem_type": null,
-    "projection_dim" : 768,
-    "pruned_heads": {},
-    "remove_invalid_values": false,
-    "repetition_penalty": 1.0,
-    "return_dict": true,
-    "return_dict_in_generate": false,
-    "sep_token_id": null,
-    "task_specific_params": null,
-    "temperature": 1.0,
-    "tie_encoder_decoder": false,
-    "tie_word_embeddings": true,
-    "tokenizer_class": null,
-    "top_k": 50,
-    "top_p": 1.0,
-    "torch_dtype": null,
-    "torchscript": false,
-    "transformers_version": "4.16.0.dev0",
-    "use_bfloat16": false,
-    "vocab_size": 49408
-  },
-  "text_config_dict": {
-    "hidden_size": 768,
-    "intermediate_size": 3072,
-    "num_attention_heads": 12,
-    "num_hidden_layers": 12,
-    "projection_dim": 768
-  },
-  "torch_dtype": "float32",
-  "transformers_version": null,
-  "vision_config": {
-    "_name_or_path": "",
-    "add_cross_attention": false,
-    "architectures": null,
-    "attention_dropout": 0.0,
-    "bad_words_ids": null,
-    "bos_token_id": null,
-    "chunk_size_feed_forward": 0,
-    "cross_attention_hidden_size": null,
-    "decoder_start_token_id": null,
-    "diversity_penalty": 0.0,
-    "do_sample": false,
-    "dropout": 0.0,
-    "early_stopping": false,
-    "encoder_no_repeat_ngram_size": 0,
-    "eos_token_id": null,
-    "finetuning_task": null,
-    "forced_bos_token_id": null,
-    "forced_eos_token_id": null,
-    "hidden_act": "quick_gelu",
-    "hidden_size": 1024,
-    "id2label": {
-      "0": "LABEL_0",
-      "1": "LABEL_1"
-    },
-    "image_size": 224,
-    "initializer_factor": 1.0,
-    "initializer_range": 0.02,
-    "intermediate_size": 4096,
-    "is_decoder": false,
-    "is_encoder_decoder": false,
-    "label2id": {
-      "LABEL_0": 0,
-      "LABEL_1": 1
-    },
-    "layer_norm_eps": 1e-05,
-    "length_penalty": 1.0,
-    "max_length": 20,
-    "min_length": 0,
-    "model_type": "clip_vision_model",
-    "no_repeat_ngram_size": 0,
-    "num_attention_heads": 16,
-    "num_beam_groups": 1,
-    "num_beams": 1,
-    "num_hidden_layers": 24,
-    "num_return_sequences": 1,
-    "output_attentions": false,
-    "output_hidden_states": false,
-    "output_scores": false,
-    "pad_token_id": null,
-    "patch_size": 14,
-    "prefix": null,
-    "problem_type": null,
-    "projection_dim" : 768,
-    "pruned_heads": {},
-    "remove_invalid_values": false,
-    "repetition_penalty": 1.0,
-    "return_dict": true,
-    "return_dict_in_generate": false,
-    "sep_token_id": null,
-    "task_specific_params": null,
-    "temperature": 1.0,
-    "tie_encoder_decoder": false,
-    "tie_word_embeddings": true,
-    "tokenizer_class": null,
-    "top_k": 50,
-    "top_p": 1.0,
-    "torch_dtype": null,
-    "torchscript": false,
-    "transformers_version": "4.16.0.dev0",
-    "use_bfloat16": false
-  },
-  "vision_config_dict": {
-    "hidden_size": 1024,
-    "intermediate_size": 4096,
-    "num_attention_heads": 16,
-    "num_hidden_layers": 24,
-    "patch_size": 14,
-    "projection_dim": 768
-  }
-}

ui/index.html

@@ -1,11 +1,12 @@
 <!DOCTYPE html>
 <html>
 <head>
-    <title>Stable Diffusion UI</title>
+    <title>Easy Diffusion</title>
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
     <meta name="theme-color" content="#673AB6">
     <link rel="icon" type="image/png" href="/media/images/favicon-16x16.png" sizes="16x16">
     <link rel="icon" type="image/png" href="/media/images/favicon-32x32.png" sizes="32x32">
+    <link rel="stylesheet" href="/media/css/jquery-confirm.min.css">
     <link rel="stylesheet" href="/media/css/fonts.css">
     <link rel="stylesheet" href="/media/css/themes.css">
     <link rel="stylesheet" href="/media/css/main.css">
@@ -13,10 +14,13 @@
     <link rel="stylesheet" href="/media/css/modifier-thumbnails.css">
     <link rel="stylesheet" href="/media/css/fontawesome-all.min.css">
     <link rel="stylesheet" href="/media/css/image-editor.css">
-    <link rel="stylesheet" href="/media/css/jquery-confirm.min.css">
+    <link rel="stylesheet" href="/media/css/searchable-models.css">
+    <link rel="stylesheet" href="/media/css/image-modal.css">
     <link rel="manifest" href="/media/manifest.webmanifest">
     <script src="/media/js/jquery-3.6.1.min.js"></script>
     <script src="/media/js/jquery-confirm.min.js"></script>
+    <script src="/media/js/jszip.min.js"></script>
+    <script src="/media/js/FileSaver.min.js"></script>
     <script src="/media/js/marked.min.js"></script>
 </head>
 <body>
@@ -24,15 +28,16 @@
     <div id="top-nav">
         <div id="logo">
             <h1>
-                Stable Diffusion UI
-                <small>v2.4.20 <span id="updateBranchLabel"></span></small>
+                <img id="logo_img" src="/media/images/icon-512x512.png" >
+                Easy Diffusion
+                <small>v2.5.41 <span id="updateBranchLabel"></span></small>
             </h1>
         </div>
         <div id="server-status">
             <div id="server-status-color">●</div>
             <span id="server-status-msg">Stable Diffusion is starting..</span>
         </div>
-        <div id="tab-container">
+        <div id="tab-container" class="tab-container">
             <span id="tab-main" class="tab active">
                 <span><i class="fa fa-image icon"></i> Generate</span>
             </span>
@@ -50,12 +55,12 @@
         <div id="editor">
             <div id="editor-inputs">
                 <div id="editor-inputs-prompt" class="row">
-                    <label for="prompt"><b>Enter Prompt</b></label> <small>or</small> <button id="promptsFromFileBtn">Load from a file</button>
+                    <label for="prompt"><b>Enter Prompt</b></label> <small>or</small> <button id="promptsFromFileBtn" class="tertiaryButton">Load from a file</button>
                     <textarea id="prompt" class="col-free">a photograph of an astronaut riding a horse</textarea>
                     <input id="prompt_from_file" name="prompt_from_file" type="file" /> <!-- hidden -->
                     <label for="negative_prompt" class="collapsible" id="negative_prompt_handle">
                         Negative Prompt
-                        <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Writing-prompts#negative-prompts" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about Negative Prompts</span></i></a>
+                        <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Writing-prompts#negative-prompts" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top">Click to learn more about Negative Prompts</span></i></a>
                         <small>(optional)</small>
                     </label>
                     <div class="collapsible-content">
@@ -69,7 +74,7 @@
                     <div id="init_image_preview_container" class="image_preview_container">
                         <div id="init_image_wrapper">
                             <img id="init_image_preview" src="" />
-                            <span id="init_image_size_box"></span>
+                            <span id="init_image_size_box" class="img_bottom_label"></span>
                             <button class="init_image_clear image_clear_btn"><i class="fa-solid fa-xmark"></i></button>
                         </div>
                         <div id="init_image_buttons">
@@ -92,10 +97,12 @@
                         </div>
                     </div>
 
+                    <div id="apply_color_correction_setting" class="pl-5"><input id="apply_color_correction" name="apply_color_correction" type="checkbox"> <label for="apply_color_correction">Preserve color profile <small>(helps during inpainting)</small></label></div>
+
                 </div>
 
                 <div id="editor-inputs-tags-container" class="row">
-                    <label>Image Modifiers <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">click an Image Modifier to remove it, use Ctrl+Mouse Wheel to adjust its weight</span></i>:</label>
+                    <label>Image Modifiers <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip right">click an Image Modifier to remove it, right-click to temporarily disable it, use Ctrl+Mouse Wheel to adjust its weight</span></i></label>
                     <div id="editor-inputs-tags-list"></div>
                 </div>
 
@@ -123,28 +130,45 @@
                     <tr><b class="settings-subheader">Image Settings</b></tr>
                     <tr class="pl-5"><td><label for="seed">Seed:</label></td><td><input id="seed" name="seed" size="10" value="0" onkeypress="preventNonNumericalInput(event)"> <input id="random_seed" name="random_seed" type="checkbox" checked><label for="random_seed">Random</label></td></tr>
                     <tr class="pl-5"><td><label for="num_outputs_total">Number of Images:</label></td><td><input id="num_outputs_total" name="num_outputs_total" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label><small>(total)</small></label> <input id="num_outputs_parallel" name="num_outputs_parallel" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label for="num_outputs_parallel"><small>(in parallel)</small></label></td></tr>
-                    <tr class="pl-5"><td><label for="stable_diffusion_model">Model:</label></td><td>
-                        <select id="stable_diffusion_model" name="stable_diffusion_model">
-                            <!-- <option value="sd-v1-4" selected>sd-v1-4</option> -->
-                        </select>
+                    <tr class="pl-5"><td><label for="stable_diffusion_model">Model:</label></td><td class="model-input">
+                        <input id="stable_diffusion_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
+                        <button id="reload-models" class="secondaryButton reloadModels"><i class='fa-solid fa-rotate'></i></button>
                         <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Custom-Models" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about custom models</span></i></a>
                     </td></tr>
-                    <tr class="pl-5"><td><label for="vae_model">Custom VAE:</i></label></td><td>
-                        <select id="vae_model" name="vae_model">
-                            <!-- <option value="" selected>None</option> -->
-                        </select>
+                    <tr class="pl-5 displayNone" id="clip_skip_config">
+                        <td><label for="clip_skip">Clip Skip:</label></td>
+                        <td>
+                            <input id="clip_skip" name="clip_skip" type="checkbox">
+                            <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Clip-Skip" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about Clip Skip</span></i></a>
+                        </td>
+                    </tr>
+                    <tr class="pl-5"><td><label for="vae_model">Custom VAE:</label></td><td>
+                        <input id="vae_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
                         <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/VAE-Variational-Auto-Encoder" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about VAEs</span></i></a>
                     </td></tr>
-                    <tr id="samplerSelection" class="pl-5"><td><label for="sampler">Sampler:</label></td><td>
-                        <select id="sampler" name="sampler">
-                            <option value="plms">plms</option>
-                            <option value="ddim">ddim</option>
-                            <option value="heun">heun</option>
-                            <option value="euler">euler</option>
-                            <option value="euler_a" selected>euler_a</option>
-                            <option value="dpm2">dpm2</option>
-                            <option value="dpm2_a">dpm2_a</option>
-                            <option value="lms">lms</option>
+                    <tr id="samplerSelection" class="pl-5"><td><label for="sampler_name">Sampler:</label></td><td>
+                        <select id="sampler_name" name="sampler_name">
+                            <option value="plms">PLMS</option>
+                            <option value="ddim">DDIM</option>
+                            <option value="heun">Heun</option>
+                            <option value="euler">Euler</option>
+                            <option value="euler_a" selected>Euler Ancestral</option>
+                            <option value="dpm2">DPM2</option>
+                            <option value="dpm2_a">DPM2 Ancestral</option>
+                            <option value="lms">LMS</option>
+                            <option value="dpm_solver_stability">DPM Solver (Stability AI)</option>
+                            <option value="dpmpp_2s_a" class="k_diffusion-only">DPM++ 2s Ancestral (Karras)</option>
+                            <option value="dpmpp_2m">DPM++ 2m (Karras)</option>
+                            <option value="dpmpp_sde" class="k_diffusion-only">DPM++ SDE (Karras)</option>
+                            <option value="dpm_fast" class="k_diffusion-only">DPM Fast (Karras)</option>
+                            <option value="dpm_adaptive" class="k_diffusion-only">DPM Adaptive (Karras)</option>
+                            <option value="ddpm" class="diffusers-only">DDPM</option>
+                            <option value="deis" class="diffusers-only">DEIS</option>
+                            <option value="unipc_snr" class="k_diffusion-only">UniPC SNR</option>
+                            <option value="unipc_tu">UniPC TU</option>
+                            <option value="unipc_snr_2" class="k_diffusion-only">UniPC SNR 2</option>
+                            <option value="unipc_tu_2" class="k_diffusion-only">UniPC TU 2</option>
+                            <option value="unipc_tq" class="k_diffusion-only">UniPC TQ</option>
                         </select>
                         <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/How-to-Use#samplers" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about samplers</span></i></a>
                     </td></tr>
@@ -193,26 +217,48 @@
                             <option value="2048">2048</option>
                         </select>
                         <label for="height"><small>(height)</small></label>
+                        <div id="small_image_warning" class="displayNone">Small image sizes can cause bad image quality</div>
                     </td></tr>
                     <tr class="pl-5"><td><label for="num_inference_steps">Inference Steps:</label></td><td> <input id="num_inference_steps" name="num_inference_steps" size="4" value="25" onkeypress="preventNonNumericalInput(event)"></td></tr>
-                    <tr class="pl-5"><td><label for="guidance_scale_slider">Guidance Scale:</label></td><td> <input id="guidance_scale_slider" name="guidance_scale_slider" class="editor-slider" value="75" type="range" min="10" max="500"> <input id="guidance_scale" name="guidance_scale" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"></td></tr>
+                    <tr class="pl-5"><td><label for="guidance_scale_slider">Guidance Scale:</label></td><td> <input id="guidance_scale_slider" name="guidance_scale_slider" class="editor-slider" value="75" type="range" min="11" max="500"> <input id="guidance_scale" name="guidance_scale" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"></td></tr>
                     <tr id="prompt_strength_container" class="pl-5"><td><label for="prompt_strength_slider">Prompt Strength:</label></td><td> <input id="prompt_strength_slider" name="prompt_strength_slider" class="editor-slider" value="80" type="range" min="0" max="99"> <input id="prompt_strength" name="prompt_strength" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"><br/></td></tr>
-                    <tr class="pl-5"><td><label for="hypernetwork_model">Hypernetwork:</i></label></td><td>
-                        <select id="hypernetwork_model" name="hypernetwork_model">
-                            <!-- <option value="" selected>None</option> -->
-                        </select>
+                    <tr id="lora_model_container" class="pl-5"><td><label for="lora_model">LoRA:</label></td><td>
+                        <input id="lora_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
+                    </td></tr>
+                    <tr id="lora_alpha_container" class="pl-5">
+                        <td><label for="lora_alpha_slider">LoRA Strength:</label></td>
+                        <td>
+                            <small>-2</small> <input id="lora_alpha_slider" name="lora_alpha_slider" class="editor-slider" value="50" type="range" min="-200" max="200"> <small>2</small> &nbsp;
+                            <input id="lora_alpha" name="lora_alpha" size="4" pattern="^-?[0-9]*\.?[0-9]*$" onkeypress="preventNonNumericalInput(event)"><br/>
+                        </td>
+                    </tr>
+                    <tr class="pl-5"><td><label for="hypernetwork_model">Hypernetwork:</label></td><td>
+                        <input id="hypernetwork_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
                     </td></tr>
                     <tr id="hypernetwork_strength_container" class="pl-5">
                         <td><label for="hypernetwork_strength_slider">Hypernetwork Strength:</label></td>
                         <td> <input id="hypernetwork_strength_slider" name="hypernetwork_strength_slider" class="editor-slider" value="100" type="range" min="0" max="100"> <input id="hypernetwork_strength" name="hypernetwork_strength" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"><br/></td>
                     </tr>
+                    <tr id="tiling_container" class="pl-5"><td><label for="tiling">Seamless Tiling:</label></td><td>
+                        <select id="tiling" name="tiling">
+                            <option value="none" selected>None</option>
+                            <option value="x">Horizontal</option>
+                            <option value="y">Vertical</option>
+                            <option value="xy">Both</option>
+                        </select>
+                        <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Seamless-Tiling" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about Seamless Tiling</span></i></a>
+                    </td></tr>
                     <tr class="pl-5"><td><label for="output_format">Output Format:</label></td><td>
                         <select id="output_format" name="output_format">
                             <option value="jpeg" selected>jpeg</option>
                             <option value="png">png</option>
+                            <option value="webp">webp</option>
                         </select>
+                        <span id="output_lossless_container" class="displayNone">
+                            <input id="output_lossless" name="output_lossless" type="checkbox"><label for="output_lossless">Lossless</label>
+                        </span>
                     </td></tr>
-                    <tr class="pl-5" id="output_quality_row"><td><label for="output_quality">JPEG Quality:</label></td><td>
+                    <tr class="pl-5" id="output_quality_row"><td><label for="output_quality">Image Quality:</label></td><td>
                     <input id="output_quality_slider" name="output_quality" class="editor-slider" value="75" type="range" min="10" max="95"> <input id="output_quality" name="output_quality" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)">
                     </td></tr>
                     </table></div>
@@ -220,13 +266,28 @@
                     <div><ul>
                     <li><b class="settings-subheader">Render Settings</b></li>
                     <li class="pl-5"><input id="stream_image_progress" name="stream_image_progress" type="checkbox"> <label for="stream_image_progress">Show a live preview <small>(uses more VRAM, slower images)</small></label></li>
-                    <li class="pl-5"><input id="use_face_correction" name="use_face_correction" type="checkbox"> <label for="use_face_correction">Fix incorrect faces and eyes <small>(uses GFPGAN)</small></label></li>
+                    <li class="pl-5" id="use_face_correction_container">
+                        <input id="use_face_correction" name="use_face_correction" type="checkbox"> <label for="use_face_correction">Fix incorrect faces and eyes</label> <div style="display:inline-block;"><input id="gfpgan_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" /></div>
+                        <table id="codeformer_settings" class="displayNone sub-settings">
+                            <tr class="pl-5"><td><label for="codeformer_fidelity_slider">Strength:</label></td><td><input id="codeformer_fidelity_slider" name="codeformer_fidelity_slider" class="editor-slider" value="5" type="range" min="0" max="10"> <input id="codeformer_fidelity" name="codeformer_fidelity" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"></td></tr>
+                            <tr class="pl-5"><td><label for="codeformer_upscale_faces">Upscale Faces:</label></td><td><input id="codeformer_upscale_faces" name="codeformer_upscale_faces" type="checkbox" checked> <label><small>(improves the resolution of faces)</small></label></td></tr>
+                        </table>
+                    </li>
                     <li class="pl-5">
-                        <input id="use_upscale" name="use_upscale" type="checkbox"> <label for="use_upscale">Upscale image by 4x with </label>
+                        <input id="use_upscale" name="use_upscale" type="checkbox"> <label for="use_upscale">Scale up by</label> 
+                        <select id="upscale_amount" name="upscale_amount">
+                            <option id="upscale_amount_2x" value="2">2x</option>
+                            <option id="upscale_amount_4x" value="4" selected>4x</option>
+                        </select>
+                        with 
                         <select id="upscale_model" name="upscale_model">
                             <option value="RealESRGAN_x4plus" selected>RealESRGAN_x4plus</option>
                             <option value="RealESRGAN_x4plus_anime_6B">RealESRGAN_x4plus_anime_6B</option>
+                            <option value="latent_upscaler">Latent Upscaler 2x</option>
                         </select>
+                        <table id="latent_upscaler_settings" class="displayNone sub-settings">
+                            <tr class="pl-5"><td><label for="latent_upscaler_steps_slider">Upscaling Steps:</label></td><td><input id="latent_upscaler_steps_slider" name="latent_upscaler_steps_slider" class="editor-slider" value="10" type="range" min="1" max="50"> <input id="latent_upscaler_steps" name="latent_upscaler_steps" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"></td></tr>
+                        </table>
                     </li>
                     <li class="pl-5"><input id="show_only_filtered_image" name="show_only_filtered_image" type="checkbox" checked> <label for="show_only_filtered_image">Show only the corrected/upscaled image</label></li>
                     </ul></div>
@@ -258,14 +319,45 @@
         </div>
 
         <div id="preview" class="col-free">
+
             <div id="initial-text">
                 Type a prompt and press the "Make Image" button.<br/><br/>You can set an "Initial Image" if you want to guide the AI.<br/><br/>
                 You can also add modifiers like "Realistic", "Pencil Sketch", "ArtStation" etc by browsing through the "Image Modifiers" section 
                 and selecting the desired modifiers.<br/><br/>
                 Click "Image Settings" for additional settings like seed, image size, number of images to generate etc.<br/><br/>Enjoy! :)
             </div>
-            <div id="preview-tools">
-                <button id="clear-all-previews" class="secondaryButton"><i class="fa-solid fa-trash-can"></i> Clear All</button>
+            <div id="preview-content">
+                <div id="preview-tools" class="displayNone">
+                    <button id="clear-all-previews" class="secondaryButton"><i class="fa-solid fa-trash-can icon"></i> Clear All</button>
+                    <button class="tertiaryButton" id="show-download-popup"><i class="fa-solid fa-download"></i> Download images</button>
+                    <div class="display-settings">
+                        <button id="undo" class="displayNone primaryButton">
+                            Undo <i class="fa-solid fa-rotate-left icon"></i>
+                            <span class="simple-tooltip left">Undo last remove</span>
+                        </button>
+                        <span class="auto-scroll"></span> <!-- hack for Rabbit Hole update -->
+                        <button id="auto_scroll_btn" class="tertiaryButton">
+                            <i class="fa-solid fa-arrows-up-to-line icon"></i>
+                            <input id="auto_scroll" name="auto_scroll" type="checkbox" style="display: none">
+                            <span class="simple-tooltip left">
+                                Scroll to generated image (<span class="state">OFF</span>)
+                            </span>
+                        </button>
+                        <button class="dropdown tertiaryButton">
+                            <i class="fa-solid fa-magnifying-glass-plus icon dropbtn"></i>
+                            <span class="simple-tooltip left">
+                                Image Size
+                            </span>
+                        </button>
+                        <div class="dropdown-content">
+                            <div class="dropdown-item">
+                                <input id="thumbnail_size" name="thumbnail_size" class="editor-slider" type="range" value="70" min="5" max="200" oninput="sliderUpdate(event)"> 
+                                <input id="thumbnail_size-input" name="thumbnail_size-input" size="3" value="70" pattern="^[0-9.]+$" onkeypress="preventNonNumericalInput(event)" oninput="sliderUpdate(event)">&nbsp;%
+                            </div>
+                        </div>
+                    </div>
+                    <div class="clearfix" style="clear: both;"></div>
+                </div>
             </div>
         </div>
         </div>
@@ -273,10 +365,16 @@
         <div id="tab-content-settings" class="tab-content">
             <div id="system-settings" class="tab-content-inner">
                 <h1>System Settings</h1>
-                <div class="parameters-table"></div>
+                <div class="parameters-table" id="system-settings-table"></div>
                 <br/>
                 <button id="save-system-settings-btn" class="primaryButton">Save</button>
                 <br/><br/>
+                <div id="share-easy-diffusion">
+                   <h3><i class="fa fa-user-group"></i> Share Easy Diffusion</h3>
+                   <div class="parameters-table" id="system-settings-network-table">
+                   </div>
+                </div>
+                <br/><br/>
                 <div>
                     <h3><i class="fa fa-microchip icon"></i> System Info</h3>
                     <div id="system-info">
@@ -335,6 +433,31 @@
     </div>
     
 
+    <div class="popup" id="download-images-popup">
+        <div>
+            <i class="close-button fa-solid fa-xmark"></i>
+            <h1>Download all images</h1>
+            <div class="parameters-table">
+                <div>
+                    <div><i class="fa fa-file-zipper"></i></div>
+                    <div><label for="theme">Download as a ZIP file</label><small>Instead of downloading individual files, generate one zip file with all images</small></div>
+                    <div><div class="input-toggle"><input id="zip_toggle" name="zip_toggle" checked="" type="checkbox"><label for="zip_toggle"></label></div></div>
+                </div>
+                <div id="download-add-folders">
+                    <div><i class="fa fa-folder-tree"></i></div>
+                    <div><label for="theme">Add per-job folders</label><small>Place images into job folders</small></div>
+                    <div><div class="input-toggle"><input id="tree_toggle" name="tree_toggle" checked="" type="checkbox"><label for="tree_toggle"></label></div></div>
+                </div>
+                <div>
+                    <div><i class="fa fa-sliders"></i></div>
+                    <div><label for="theme">Add metadata files</label><small>For each image, also download a JSON file with all the settings used to generate the image</small></div>
+                    <div><div class="input-toggle"><input id="json_toggle" name="json_toggle" checked="" type="checkbox"><label for="json_toggle"></label></div></div>
+                </div>
+            </div>
+            <br/>
+            <button id="save-all-images" class="primaryButton"><i class="fa-solid fa-images"></i> Start download</button>
+        </div>
+    </div>
     <div id="save-settings-config" class="popup">
         <div>
             <i class="close-button fa-solid fa-xmark"></i>
@@ -345,12 +468,12 @@
         </div>
     </div>
 
-    <div id="modifier-settings-config" class="popup">
+    <div id="modifier-settings-config" class="popup" tabindex="0">
         <div>
             <i class="close-button fa-solid fa-xmark"></i>
             <h1>Modifier Settings</h1>
             <p>Set your custom modifiers (one per line)</p>
-            <textarea id="custom-modifiers-input" placeholder="Enter your custom modifiers, one-per-line"></textarea>
+            <textarea id="custom-modifiers-input" placeholder="Enter your custom modifiers, one-per-line" spellcheck="false"></textarea>
             <p><small><b>Tip:</b> You can include special characters like {} () [] and |. You can also put multiple comma-separated phrases in a single line, to make a single modifier that combines all of those.</small></p>
         </div>
     </div>
@@ -408,15 +531,16 @@
 <script src="media/js/image-modifiers.js"></script>
 <script src="media/js/auto-save.js"></script>
 
+<script src="media/js/searchable-models.js"></script>
 <script src="media/js/main.js"></script>
 <script src="media/js/themes.js"></script>
 <script src="media/js/dnd.js"></script>
 <script src="media/js/image-editor.js"></script>
+<script src="media/js/image-modal.js"></script>
 <script>
 async function init() {
     await initSettings()
     await getModels()
-    await getDiskPath()
     await getAppConfig()
     await loadUIPlugins()
     await loadModifiers()
@@ -424,12 +548,13 @@ async function init() {
 
     SD.init({
         events: {
-            statusChange: setServerStatus
-            , idle: onIdle
+            statusChange: setServerStatus,
+            idle: onIdle,
+            ping: tunnelUpdate
         }
     })
 
-    playSound()
+    // playSound()
 }
 
 init()

ui/main.py

@@ -0,0 +1,10 @@
+from easydiffusion import model_manager, app, server
+from easydiffusion.server import server_api # required for uvicorn
+
+# Init the app
+model_manager.init()
+app.init()
+server.init()
+
+# start the browser ui
+app.open_browser()

ui/media/css/auto-save.css

@@ -69,13 +69,15 @@
 }
 
 .parameters-table > div:first-child {
-    border-radius: 12px 12px 0px 0px;
+    border-top-left-radius: 12px;
+    border-top-right-radius: 12px;
 }
 
 .parameters-table > div:last-child {
-    border-radius: 0px 0px 12px 12px;
+    border-bottom-left-radius: 12px;
+    border-bottom-right-radius: 12px;
 }
 
 .parameters-table .fa-fire {
     color: #F7630C;
-}
+}

ui/media/css/fonts.css

@@ -3,7 +3,7 @@
     font-family: 'Work Sans';
     font-style: normal;
     font-weight: 400;
-    src: local(''),
+    src: local('Work Sans'),
          url('/media/fonts/work-sans-v18-latin-regular.woff2') format('woff2'), /* Chrome 26+, Opera 23+, Firefox 39+ */
          url('/media/fonts/work-sans-v18-latin-regular.woff') format('woff'); /* Chrome 6+, Firefox 3.6+, IE 9+, Safari 5.1+ */
   }
@@ -13,7 +13,7 @@
     font-family: 'Work Sans';
     font-style: normal;
     font-weight: 600;
-    src: local(''),
+    src: local('Work Sans'),
          url('/media/fonts/work-sans-v18-latin-600.woff2') format('woff2'), /* Chrome 26+, Opera 23+, Firefox 39+ */
          url('/media/fonts/work-sans-v18-latin-600.woff') format('woff'); /* Chrome 6+, Firefox 3.6+, IE 9+, Safari 5.1+ */
   }
@@ -23,7 +23,7 @@
     font-family: 'Work Sans';
     font-style: normal;
     font-weight: 700;
-    src: local(''),
+    src: local('Work Sans'),
          url('/media/fonts/work-sans-v18-latin-700.woff2') format('woff2'), /* Chrome 26+, Opera 23+, Firefox 39+ */
          url('/media/fonts/work-sans-v18-latin-700.woff') format('woff'); /* Chrome 6+, Firefox 3.6+, IE 9+, Safari 5.1+ */
   }
@@ -33,8 +33,8 @@
     font-family: 'Work Sans';
     font-style: normal;
     font-weight: 800;
-    src: local(''),
+    src: local('Work Sans'),
          url('/media/fonts/work-sans-v18-latin-800.woff2') format('woff2'), /* Chrome 26+, Opera 23+, Firefox 39+ */
          url('/media/fonts/work-sans-v18-latin-800.woff') format('woff'); /* Chrome 6+, Firefox 3.6+, IE 9+, Safari 5.1+ */
   }
-  
+  

ui/media/css/image-editor.css

@@ -2,12 +2,12 @@
 	padding-left: 32px;
 	text-align: left;
 	padding-bottom: 20px;
+	max-width: min-content;
 }
 
 .editor-options-container {
 	display: flex;
 	row-gap: 10px;
-	max-width: 210px;
 }
 
 .editor-options-container > * {
@@ -31,7 +31,7 @@
 }
 
 .editor-options-container > * > *.active {
-	border: 2px solid #3584e4;
+	border: 1px solid #3584e4;
 }
 
 .image_editor_opacity .editor-options-container > * > *:not(.active) {
@@ -96,7 +96,7 @@
 
 .editor-controls-center {
 	/* background: var(--background-color2); */
-	flex: 1;
+	flex: 0;
 	display: flex;
 	justify-content: center;
 	align-items: center;
@@ -105,6 +105,8 @@
 .editor-controls-center > div {
 	position: relative;
 	background: black;
+	margin: 20pt;
+	margin-top: 40pt;
 }
 
 .editor-controls-center canvas {
@@ -149,17 +151,25 @@
 	pointer-events: none;
 }
 
-
 .image-editor-popup {
 	--popup-margin: 16px;
 	--popup-padding: 24px;
 }
 
+@media screen and (min-width: 700px) {
+	.image-editor-popup {
+		overflow-y: auto;
+	}
+}
+
 .image-editor-popup > div {
 	margin: var(--popup-margin);
 	padding: var(--popup-padding);
-	min-height: calc(100vh - (2 * var(--popup-margin)));
-	max-width: none;
+	min-height: calc(99h - (2 * var(--popup-margin)));
+	max-width: fit-content;
+	min-width: fit-content;
+	margin-left: auto;
+	margin-right: auto;
 }
 
 .image-editor-popup h1 {
@@ -185,7 +195,7 @@
 
 
 .image-editor-popup > div > div {
-	min-height: calc(100vh - (2 * var(--popup-margin)) - (2 * var(--popup-padding)));
+	min-height: calc(99vh - (2 * var(--popup-margin)) - (2 * var(--popup-padding)));
 }
 
 .inpainter .image_editor_color {
@@ -213,3 +223,10 @@
 .image-editor-popup h4 {
 	text-align: left;
 }
+
+.image-editor-popup .load_mask {
+	display: none;
+}
+.inpainter .load_mask {
+	display: flex;
+}

ui/media/css/image-modal.css

@@ -0,0 +1,96 @@
+#viewFullSizeImgModal {
+    --popup-padding: 24px;
+    position: sticky;
+    padding: var(--popup-padding);
+    pointer-events: none;
+    width: 100vw;
+    height: 100vh;
+    box-sizing: border-box;
+    display: flex;
+    justify-content: center;
+    align-items: center;
+    overflow: hidden;
+    z-index: 1001;
+}
+
+#viewFullSizeImgModal:not(.active) {
+    display: none;
+}
+
+#viewFullSizeImgModal > * {
+    pointer-events: auto;
+    margin: 0;
+    padding: 0;
+    box-sizing: border-box;
+}
+
+#viewFullSizeImgModal .backdrop {
+    max-width: unset;
+    width: 100%;
+    max-height: unset;
+    height: 100%;
+    inset: 0;
+    position: absolute;
+    top: 0;
+    left: 0;
+    z-index: 1001;
+    opacity: .5;
+    border: none;
+    box-shadow: none;
+    overflow: hidden;
+}
+
+#viewFullSizeImgModal .content {
+    min-height: initial;
+    max-height: calc(100vh - (var(--popup-padding) * 2));
+    height: fit-content;
+    min-width: initial;
+    max-width: calc(100vw - (var(--popup-padding) * 2));
+    width: fit-content;
+    z-index: 1003;
+    overflow: visible;
+}
+
+#viewFullSizeImgModal .image-wrapper {
+    min-height: initial;
+    max-height: calc(100vh - (var(--popup-padding) * 2));
+    height: fit-content;
+    min-width: initial;
+    max-width: calc(100vw - (var(--popup-padding) * 2));
+    width: fit-content;
+    box-sizing: border-box;
+    pointer-events: auto;
+    margin: 0;
+    padding: 0;
+    overflow: auto;
+}
+
+#viewFullSizeImgModal img.natural-zoom {
+    max-width: calc(100vh - (var(--popup-padding) * 2) - 4px);
+    max-height: calc(100vh - (var(--popup-padding) * 2) - 4px);
+}
+
+#viewFullSizeImgModal img:not(.natural-zoom) {
+    cursor: grab;
+}
+
+#viewFullSizeImgModal .grabbing img:not(.natural-zoom) {
+    cursor: grabbing;
+}
+
+#viewFullSizeImgModal .content > div::-webkit-scrollbar-track, #viewFullSizeImgModal .content > div::-webkit-scrollbar-corner {
+    background: rgba(0, 0, 0, .5)
+}
+
+#viewFullSizeImgModal .menu-bar {
+    position: absolute;
+    top: 0;
+    right: 0;
+    padding-right: var(--scrollbar-width);
+}
+
+#viewFullSizeImgModal .menu-bar .tertiaryButton {
+    font-size: 1.2em;
+    margin: 12px 12px 0 0;
+    cursor: pointer;
+}

ui/media/css/main.css

@@ -27,6 +27,11 @@ code {
     padding: 2px 4px;
     border-radius: 4px;
 }
+#logo_img {
+    width: 32px;
+    height: 32px;
+    transform: translateY(4px);
+}
 #prompt {
     width: 100%;
     height: 65pt;
@@ -93,11 +98,23 @@ code {
 #footer-spacer {
     flex: 0.7
 }
-.imgSeedLabel {
+.imgInfoLabel {
     font-size: 0.8em;
     background-color: var(--background-color2);
-    border-radius: 3px;
+}
+.imgSeedLabel {
     padding: 5px;
+    border-radius: 0px 3px 3px 0px;
+}
+.imgExpandBtn {
+    border-radius: 3px 0px 0px 3px;
+    border-right: 1px solid var(--tertiary-border-color);
+    padding: 5px 5px 5px;
+    padding-left: 7px;
+    cursor: pointer;
+}
+.imgExpandBtn:hover {
+    background-color: var(--accent-color);
 }
 .imgItem {
     display: inline-block;
@@ -107,6 +124,7 @@ code {
 .imgContainer {
     display: flex;
     justify-content: flex-end;
+    position: relative;
 }
 .imgItemInfo {
     padding-bottom: 0.5em;
@@ -114,16 +132,38 @@ code {
     align-items: flex-end;
     flex-direction: column;
     position: absolute;
-    padding: 5px;
+    padding-right: 5pt;
+    padding-top: 6pt;
     opacity: 0;
     transition: 0.1s all;
 }
+.imgPreviewItemClearBtn {
+    opacity: 0;
+}
+.imgContainer .img_bottom_label {
+    opacity: 0;
+}
+.imgPreviewItemClearBtn:hover {
+    background: rgb(177, 27, 0);
+}
 .imgContainer:hover > .imgItemInfo {
     opacity: 1;
 }
-.imgItemInfo * {
+.imgContainer:hover > .imgPreviewItemClearBtn {
+    opacity: 1;
+}
+.imgContainer:hover > .img_bottom_label {
+    opacity: 60%;
+}
+.imgItemInfo > * {
     margin-bottom: 7px;
 }
+.imgItemInfo .tasksBtns {
+    margin-left: 5pt;
+}
+.imgItem .image_clear_btn {
+    transform: translate(40%, -50%);
+}
 #container {
     min-height: 100vh;
     width: 100%;
@@ -179,7 +219,7 @@ code {
     flex: 0 0 70px;
     background: var(--accent-color);
     border: var(--primary-button-border);
-    color: rgb(255, 221, 255);
+    color: var(--accent-text-color);
     width: 100%;
     height: 30pt;
 }
@@ -198,6 +238,10 @@ code {
 #stopImage:hover {
     background: rgb(177, 27, 0);
 }
+#undo {
+    float: right;
+    margin-left: 5px;
+}
 
 div#render-buttons {
     gap: 3px;
@@ -251,6 +295,12 @@ button#resume {
 img {
     box-shadow: 0 4px 8px 0 rgba(0, 0, 0, 0.15), 0 6px 20px 0 rgba(0, 0, 0, 0.15);
 }
+div.img-preview img {
+    width:100%;
+    height: 100%;
+    max-height: 70vh;
+    cursor: pointer;
+}
 .line-separator {
     background: var(--background-color3);
     height: 1pt;
@@ -263,8 +313,7 @@ img {
 #server-status {
     position: absolute;
     right: 16px;
-    top: 50%;
-    transform: translateY(-50%);
+    top: 4px;
     text-align: right;
 }
 #server-status-color {
@@ -290,6 +339,7 @@ img {
     position: relative;
     background: var(--background-color4);
     display: flex;
+    padding: 12px 0 0;
 }
 .tab .icon {
     padding-right: 4pt;
@@ -298,7 +348,7 @@ img {
 }
 #logo {
     display: inline;
-    padding: 12px;
+    padding: 0 12px 12px;
     white-space: nowrap;
 }
 #logo h1 {
@@ -383,17 +433,44 @@ img {
     display: none;
     position: absolute;
     z-index: 2;
-
-    background: var(--background-color4);
-    border: 2px solid var(--background-color2);
     border-radius: 7px;
-    padding: 5px;
+    padding: 0px;
     margin-bottom: 15px;
-    box-shadow: 0 20px 28px 0 rgba(0, 0, 0, 0.15), 0 6px 20px 0 rgba(0, 0, 0, 0.15);
+    box-shadow: 0 20px 28px 0 rgba(0, 0, 0, 0.75), 0 6px 20px 0 rgba(0, 0, 0, 0.75);
 }
 .dropdown:hover .dropdown-content {
     display: block;
 }
+.dropdown:hover + .dropdown-content {
+    display: block;
+}
+.dropdown-content:hover {
+    display: block;
+}
+
+.display-settings {
+    float: right;
+    position: relative;
+}
+
+.display-settings .dropdown-content {
+    right: 0px;
+    top: 12pt;
+}
+
+.dropdown-item {
+    padding: 4px;
+    background: var(--background-color1);
+    border: 2px solid var(--background-color4);
+}
+
+.dropdown-item:first-child {
+    border-radius: 7px 7px 0px 0px;
+}
+
+.dropdown-item:last-child {
+    border-radius: 0px 0px 7px 7px;
+}
 
 .imageTaskContainer {
     border: 1px solid var(--background-color2);
@@ -449,6 +526,7 @@ img {
     background: var(--accent-color);
     border: var(--primary-button-border);
     color: rgb(255, 221, 255);
+    padding: 3pt 6pt;
 }
 .secondaryButton {
     background: rgb(132, 8, 0);
@@ -460,30 +538,49 @@ img {
 .secondaryButton:hover {
     background: rgb(177, 27, 0);
 }
-.useSettings {
-    background: var(--accent-color);
-    border: 1px solid var(--accent-color);
-    color: rgb(255, 221, 255);
+.tertiaryButton {
+    background: var(--tertiary-background-color);
+    color: var(--tertiary-color);
+    border: 1px solid var(--tertiary-border-color);
     padding: 3pt 6pt;
+    border-radius: 5px;
+}
+.tertiaryButton:hover {
+    background: hsl(var(--accent-hue), 100%, calc(var(--accent-lightness) + 6%));
+    color: var(--accent-text-color);
+}
+.tertiaryButton.pressed {
+    border-style: inset;
+    background: hsl(var(--accent-hue), 100%, calc(var(--accent-lightness) + 6%));
+    color: var(--accent-text-color);
+}
+.useSettings {
     margin-right: 6pt;
     float: right;
 }
-.useSettings:hover {
-    background: hsl(var(--accent-hue), 100%, calc(var(--accent-lightness) + 6%));
-}
 .stopTask {
     float: right;
 }
 #preview-tools {
-    display: none;
     padding: 4pt;
 }
+#preview-tools .display-settings .dropdown-content {
+    right: -6px;
+    top: 20px;
+    box-shadow: none;
+    width: max-content;
+}
 .taskConfig {
     font-size: 10pt;
     color: #aaa;
     margin-bottom: 5pt;
     margin-top: 5pt;
 }
+
+.taskConfigContainer {
+    display: inline;
+}
+
 .img-batch {
     display: inline;
 }
@@ -558,6 +655,9 @@ img {
 } */
 
 #init_image_size_box {
+    border-radius: 6px 0px;
+}
+.img_bottom_label {
     position: absolute;
     right: 0px;
     bottom: 0px;
@@ -567,7 +667,6 @@ img {
     text-shadow: 0px 0px 4px black;
     opacity: 60%;
     font-size: 12px;
-    border-radius: 6px 0px;
 }
 
 #editor-settings {
@@ -584,7 +683,6 @@ img {
 }
 
 #editor-settings-entries ul {
-    margin: 0px;
     padding: 0px;
 }
 
@@ -731,9 +829,16 @@ input::file-selector-button {
     right: calc(var(--input-border-size) + var(--input-switch-padding));
     opacity: 1;
 }
+.model-filter {
+    width: 90%;
+    padding-right: 20px;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
 
 /* Small screens */
-@media screen and (max-width: 1265px) {
+@media screen and (max-width: 1365px) {
     #top-nav {
         flex-direction: column;
     }
@@ -768,12 +873,6 @@ input::file-selector-button {
         width: 100%;
         object-fit: contain;
     }
-    .dropdown-content {
-        width: auto !important;
-        transform: none !important;
-        left: 0px;
-        right: 0px;
-    }
     #editor {
         padding: 16px 8px;
     }
@@ -789,9 +888,6 @@ input::file-selector-button {
     .tab .icon {
         padding-right: 0px;
     }
-    #server-status {
-        top: 75%;
-    }
     .popup > div {
         padding-left: 5px !important;
         padding-right: 5px !important;
@@ -806,6 +902,12 @@ input::file-selector-button {
     .simple-tooltip {
         display: none;
     }
+    #preview-tools button {
+        font-size: 0px;
+    }
+    #preview-tools button .icon {
+        font-size: 12pt;
+    }
 }
 
 @media screen and (max-width: 500px) {
@@ -838,7 +940,7 @@ input::file-selector-button {
 #promptsFromFileBtn {
     font-size: 9pt;
     display: inline;
-    background-color: var(--accent-color);
+    padding: 2pt;
 }
 
 .section-button {
@@ -871,17 +973,19 @@ input::file-selector-button {
 
 /* SIMPLE TOOTIP */
 .simple-tooltip {
-	border-radius: 3px;
-	font-weight: bold;
-	font-size: 12px;
+    border-radius: 3px;
+    font-weight: bold;
+    font-size: 12px;
     background-color: var(--background-color3);
 
-	visibility: hidden;
-	opacity: 0;
-	position: absolute;
-	white-space: nowrap;
-	padding: 8px 12px;
-	transition: 0.3s all;
+    visibility: hidden;
+    opacity: 0;
+    position: absolute;
+    width: max-content;
+    max-width: 300px;
+    padding: 8px 12px;
+    transition: 0.3s all;
+    z-index: 1000;
 
     pointer-events: none;
 }
@@ -895,7 +999,7 @@ input::file-selector-button {
 .simple-tooltip.right {
     right: 0px;
     top: 50%;
-    transform: translate(calc(100% - 15%), -50%);
+    transform: translate(100%, -50%);
 }
 :hover > .simple-tooltip.right {
     transform: translate(100%, -50%);
@@ -1023,9 +1127,11 @@ input::file-selector-button {
 }
 
 /* TABS */
-#tab-container {
+.tab-container {
     display: flex;
     align-items: flex-end;
+    overflow-x: auto;
+    overflow-y: hidden;
 }
 
 .tab {
@@ -1099,11 +1205,11 @@ button:active {
 
 div.task-initimg > img {
     margin-right: 6px;
-    display:      block;
+    display: block;
 }
 div.task-fs-initimage {
-    display:  none;
-#    position: absolute;
+    display: none;
+    position: absolute;
 }
 div.task-initimg:hover div.task-fs-initimage {
     display: block;
@@ -1111,6 +1217,8 @@ div.task-initimg:hover div.task-fs-initimage {
     z-index: 9999;
     box-shadow: 0 0 30px #000;
     margin-top:-64px;
+    max-width: 75vw;
+    max-height: 75vh;
 }
 div.top-right {
     position: absolute;
@@ -1118,6 +1226,11 @@ div.top-right {
     right: 8px;
 }
 
+#small_image_warning {
+     font-size: smaller;
+     color: var(--status-orange);
+}
+
 button#save-system-settings-btn {
     padding: 4pt 8pt;
 }
@@ -1128,6 +1241,10 @@ button#save-system-settings-btn {
     line-height: 200%;
 }
 
+#download-images-popup .parameters-table > div {
+    background: var(--background-color1);
+}
+
 /* SCROLLBARS */
 :root {
     --scrollbar-width: 14px;
@@ -1174,3 +1291,94 @@ body.wait-pause {
     50% { border: solid 12px var(--background-color1); }
    100% { border: solid 12px var(--accent-color); }
 }
+
+.jconfirm.jconfirm-modern .jconfirm-box div.jconfirm-title-c {
+    color: var(--button-text-color);
+}
+.jconfirm.jconfirm-modern .jconfirm-box {
+    background-color: var(--background-color1);
+}
+
+.displayNone {
+    display:none !important;
+}
+
+.sub-settings {
+    padding-top: 3pt;
+    padding-bottom: 3pt;
+    padding-left: 5pt;
+}
+
+#cloudflare-address {
+    background-color: var(--background-color3);
+    padding: 6px;
+    border-radius: var(--input-border-radius);
+    border: var(--input-border-size) solid var(--input-border-color);
+    margin-top: 0.2em;
+    margin-bottom: 0.2em;
+    display: inline-block;
+}
+
+#copy-cloudflare-address {
+    padding: 4px 8px;
+    margin-left: 0.5em;
+}
+
+.expandedSettingRow {
+    background: var(--background-color1);
+    width: 95%;
+    border-radius: 4pt;
+    margin-top: 5pt;
+    margin-bottom: 3pt;
+}
+
+/* TOAST NOTIFICATIONS */
+.toast-notification {
+    position: fixed;
+    bottom: 10px;
+    right: -300px;
+    width: 300px;
+    background-color: #333;
+    color: #fff;
+    padding: 10px 20px;
+    border-radius: 5px;
+    box-shadow: 0 0 10px rgba(0, 0, 0, 0.5);
+    z-index: 9999;
+    animation: slideInRight 0.5s ease forwards;
+    transition: bottom 0.5s ease; /* Add a transition to smoothly reposition the toasts */
+}
+
+.toast-notification-error {
+    color: red;
+}
+
+@keyframes slideInRight {
+    from {
+        right: -300px;
+    }
+    to {
+        right: 10px;
+    }
+}
+
+.toast-notification.hide {
+    animation: slideOutRight 0.5s ease forwards;
+}
+
+@keyframes slideOutRight {
+    from {
+        right: 10px;
+    }
+    to {
+        right: -300px;
+    }
+}
+
+@keyframes slideDown {
+    from {
+        bottom: 10px;
+    }
+    to {
+        bottom: 0;
+    }
+}

ui/media/css/modifier-thumbnails.css

@@ -153,6 +153,10 @@
     position: absolute;
     z-index: 3;
 }
+.modifier-card-overlay:hover ~ .modifier-card-container .modifier-card-label.tooltip .tooltip-text {
+    visibility: visible;
+    opacity: 1;
+}
 .modifier-card:hover > .modifier-card-image-container .modifier-card-image-overlay {
     opacity: 1;
 }
@@ -220,4 +224,4 @@
 #modifier-settings-config textarea {
     width: 90%;
     height: 150px;
-}
+}

ui/media/css/searchable-models.css

@@ -0,0 +1,99 @@
+.model-list {
+    position: absolute;
+    margin-block-start: 2px;
+    display: none;
+    padding-inline-start: 0;
+    max-height: 200px;
+    overflow: auto;
+    background: var(--input-background-color);
+    border: var(--input-border-size) solid var(--input-border-color);
+    border-radius: var(--input-border-radius);
+    color: var(--input-text-color);
+    z-index: 1;
+    line-height: normal;
+}
+
+.model-list ul {
+    padding-right: 20px;
+    padding-inline-start: 0;
+    margin-top: 3pt;
+}
+
+.model-list li {
+    padding-top: 3px;
+    padding-bottom: 3px;
+}
+
+.model-list .icon {
+    padding-right: 3pt;
+}
+
+.model-result {
+    list-style: none;
+}
+
+.model-no-result {
+    color: var(--text-color);
+    list-style: none;
+    padding: 3px 6px 3px 6px;
+    font-size: 9pt;
+    font-style: italic;
+    display: none;
+}
+
+.model-list li.model-folder {
+    color: var(--text-color);
+    list-style: none;
+    padding: 6px 6px 6px 6px;
+    font-size: 9pt;
+    font-weight: bold;
+    border-top: 1px solid var(--background-color1);
+}
+
+.model-list li.model-file {
+    color: var(--input-text-color);
+    list-style: none;
+    padding-left: 12px;
+    padding-right:20px;
+    font-size: 10pt;
+    font-weight: normal;
+    transition: none;
+    transition-property: none;
+    cursor: default;
+}
+
+.model-list li.model-file.in-root-folder {
+    padding-left: 6px;
+}
+
+.model-list li.model-file.selected {
+    background: grey;
+}
+
+.model-selector {
+    cursor: pointer;
+}
+
+.model-selector-arrow {
+    position: absolute;
+    width: 17px;
+    margin: 5px -17px;
+    padding-top: 3px;
+    cursor: pointer;
+    font-size: 8pt;
+    transition: none;
+}
+
+.model-input {
+    white-space: nowrap;
+}
+
+.reloadModels {
+    background: var(--background-color2);
+    border: none;
+    padding: 0px 0px;
+}
+
+#reload-models.secondaryButton:hover {
+    background: var(--background-color2);
+}

ui/media/css/themes.css

@@ -27,12 +27,19 @@
     --input-border-size: 1px; 
     --accent-color: hsl(var(--accent-hue), 100%, var(--accent-lightness));
     --accent-color-hover: hsl(var(--accent-hue), 100%, var(--accent-lightness-hover));
+    --accent-text-color: rgb(255, 221, 255);
     --primary-button-border: none;
     --input-switch-padding: 1px;
     --input-height: 18px;
+	--tertiary-background-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (2 * var(--value-step))));
+    --tertiary-border-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (3 * var(--value-step))));
+    --tertiary-color: var(--input-text-color);
 
     /* Main theme color, hex color fallback. */
     --theme-color-fallback: #673AB6;
+    --status-orange: rgb(200, 139, 0);
+    --status-green: green;
+    --status-red: red;
 }
 
 .theme-light {
@@ -48,6 +55,11 @@
     --input-border-color: grey; 
 
     --theme-color-fallback: #aaaaaa;
+
+	--tertiary-background-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (16.8 * var(--value-step))));
+    --tertiary-border-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (12 * var(--value-step))));
+
+    --accent-text-color: white;
 }
 
 .theme-discord {
@@ -64,6 +76,10 @@
     --input-border-color: var(--input-background-color); 
 
     --theme-color-fallback: #202225;
+
+    --tertiary-background-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (3.5 * var(--value-step))));
+    --tertiary-border-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (4.5 * var(--value-step))));
+    --accent-text-color: white;
 }
 
 .theme-cool-blue {
@@ -81,6 +97,10 @@
     --accent-hue: 212;
 
     --theme-color-fallback: #0056b8;
+
+    --tertiary-background-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (3.5 * var(--value-step))));
+    --tertiary-border-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (4.5 * var(--value-step))));
+    --accent-text-color: #f7fbff;
 }
 
 
@@ -97,6 +117,9 @@
     --input-background-color: var(--background-color3);
 
     --theme-color-fallback: #5300b8;
+
+    --tertiary-background-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (3.5 * var(--value-step))));
+    --tertiary-border-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (4.5 * var(--value-step))));
 }
 
 .theme-super-dark {
@@ -131,6 +154,9 @@
     --input-background-color: hsl(222, var(--main-saturation), calc(var(--value-base) - (2 * var(--value-step))));
     --input-text-color: #FF0000;
     --input-border-color: #005E05;
+
+    --tertiary-color: white;
+    --accent-text-color: #f7fbff;
 }
 
 
@@ -157,4 +183,4 @@
     border: none;
     box-shadow: 0px 1px 2px rgba(0, 0, 0, 0.25);
     border-radius: 10px;
-}
+}

ui/media/images/fa-eraser.svg

@@ -0,0 +1,4 @@
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 576 576" width="24" height="24">
+<!--! Font Awesome Pro 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license (Commercial License) Copyright 2022 Fonticons, Inc.-->
+  <path style="filter: drop-shadow(0px 0px 20px white)" d="M290.7 57.4 57.4 290.7c-25 25-25 65.5 0 90.5l80 80c12 12 28.3 18.7 45.3 18.7H512c17.7 0 32-14.3 32-32s-14.3-32-32-32H387.9l130.7-130.6c25-25 25-65.5 0-90.5L381.3 57.4c-25-25-65.5-25-90.5 0zm6.7 358.6H182.6l-80-80 124.7-124.7 137.4 137.4-67.3 67.3z"/>
+</svg>

ui/media/images/fa-eye-dropper.svg

@@ -0,0 +1,4 @@
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" width="24" height="24">
+<!--! Font Awesome Pro 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license (Commercial License) Copyright 2022 Fonticons, Inc.-->
+  <path style="filter: drop-shadow(0px 0px 20px white)" d="M341.6 29.2 240.1 130.8l-9.4-9.4c-12.5-12.5-32.8-12.5-45.3 0s-12.5 32.8 0 45.3l160 160c12.5 12.5 32.8 12.5 45.3 0s12.5-32.8 0-45.3l-9.4-9.4 101.5-101.6c39-39 39-102.2 0-141.1s-102.2-39-141.1 0zM55.4 323.3c-15 15-23.4 35.4-23.4 56.6v42.4L5.4 462.2c-8.5 12.7-6.8 29.6 4 40.4s27.7 12.5 40.4 4L89.7 480h42.4c21.2 0 41.6-8.4 56.6-23.4l120.7-120.7-45.3-45.3-120.7 120.7c-3 3-7.1 4.7-11.3 4.7H96v-36.1c0-4.2 1.7-8.3 4.7-11.3l120.7-120.7-45.3-45.3L55.4 323.3z"/>
+</svg>

ui/media/images/fa-fill.svg

@@ -0,0 +1,4 @@
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 576 576" width="24" height="24">
+<!--! Font Awesome Pro 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license (Commercial License) Copyright 2022 Fonticons, Inc.-->
+  <path style="filter: drop-shadow(0px 0px 20px white)" d="M118.6 9.4c-12.5-12.5-32.7-12.5-45.2 0s-12.5 32.8 0 45.3l81.3 81.3-92.1 92.1c-37.5 37.5-37.5 98.3 0 135.8l117.5 117.5c37.5 37.5 98.3 37.5 135.8 0l190.4-190.5c28.1-28.1 28.1-73.7 0-101.8L354.9 37.7c-28.1-28.1-73.7-28.1-101.8 0l-53.1 53-81.4-81.3zM200 181.3l49.4 49.4c12.5 12.5 32.8 12.5 45.3 0s12.5-32.8 0-45.3L245.3 136l53.1-53.1c3.1-3.1 8.2-3.1 11.3 0l151.4 151.4c3.1 3.1 3.1 8.2 0 11.3L418.7 288H99.5c1.4-5.4 4.2-10.4 8.4-14.6l92.1-92.1z"/>
+</svg>

ui/media/images/fa-pencil.svg

@@ -0,0 +1,4 @@
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" width="24" height="24">
+<!--! Font Awesome Pro 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license (Commercial License) Copyright 2022 Fonticons, Inc.-->
+  <path style="filter: drop-shadow(0px 0px 20px white)" d="m410.3 231 11.3-11.3-33.9-33.9-62.1-62.1-33.9-33.9-11.3 11.3-22.6 22.6L58.6 322.9c-10.4 10.4-18 23.3-22.2 37.4L1 480.7c-2.5 8.4-.2 17.5 6.1 23.7s15.3 8.5 23.7 6.1l120.3-35.4c14.1-4.2 27-11.8 37.4-22.2l199.2-199.2 22.6-22.7zM160 399.4l-9.1 22.7c-4 3.1-8.5 5.4-13.3 6.9l-78.2 23 23-78.1c1.4-4.9 3.8-9.4 6.9-13.3l22.7-9.1v32c0 8.8 7.2 16 16 16h32zM362.7 18.7l-14.4 14.5-22.6 22.6-11.4 11.3 33.9 33.9 62.1 62.1 33.9 33.9 11.3-11.3 22.6-22.6 14.5-14.5c25-25 25-65.5 0-90.5l-39.3-39.4c-25-25-65.5-25-90.5 0zm-47.4 168-144 144c-6.2 6.2-16.4 6.2-22.6 0s-6.2-16.4 0-22.6l144-144c6.2-6.2 16.4-6.2 22.6 0s6.2 16.4 0 22.6z"/>
+</svg>

ui/media/js/FileSaver.min.js

@@ -0,0 +1,2 @@
+(function(a,b){if("function"==typeof define&&define.amd)define([],b);else if("undefined"!=typeof exports)b();else{b(),a.FileSaver={exports:{}}.exports}})(this,function(){"use strict";function b(a,b){return"undefined"==typeof b?b={autoBom:!1}:"object"!=typeof b&&(console.warn("Deprecated: Expected third argument to be a object"),b={autoBom:!b}),b.autoBom&&/^\s*(?:text\/\S*|application\/xml|\S*\/\S*\+xml)\s*;.*charset\s*=\s*utf-8/i.test(a.type)?new Blob(["\uFEFF",a],{type:a.type}):a}function c(a,b,c){var d=new XMLHttpRequest;d.open("GET",a),d.responseType="blob",d.onload=function(){g(d.response,b,c)},d.onerror=function(){console.error("could not download file")},d.send()}function d(a){var b=new XMLHttpRequest;b.open("HEAD",a,!1);try{b.send()}catch(a){}return 200<=b.status&&299>=b.status}function e(a){try{a.dispatchEvent(new MouseEvent("click"))}catch(c){var b=document.createEvent("MouseEvents");b.initMouseEvent("click",!0,!0,window,0,0,0,80,20,!1,!1,!1,!1,0,null),a.dispatchEvent(b)}}var f="object"==typeof window&&window.window===window?window:"object"==typeof self&&self.self===self?self:"object"==typeof global&&global.global===global?global:void 0,a=/Macintosh/.test(navigator.userAgent)&&/AppleWebKit/.test(navigator.userAgent)&&!/Safari/.test(navigator.userAgent),g=f.saveAs||("object"!=typeof window||window!==f?function(){}:"download"in HTMLAnchorElement.prototype&&!a?function(b,g,h){var i=f.URL||f.webkitURL,j=document.createElement("a");g=g||b.name||"download",j.download=g,j.rel="noopener","string"==typeof b?(j.href=b,j.origin===location.origin?e(j):d(j.href)?c(b,g,h):e(j,j.target="_blank")):(j.href=i.createObjectURL(b),setTimeout(function(){i.revokeObjectURL(j.href)},4E4),setTimeout(function(){e(j)},0))}:"msSaveOrOpenBlob"in navigator?function(f,g,h){if(g=g||f.name||"download","string"!=typeof f)navigator.msSaveOrOpenBlob(b(f,h),g);else if(d(f))c(f,g,h);else{var i=document.createElement("a");i.href=f,i.target="_blank",setTimeout(function(){e(i)})}}:function(b,d,e,g){if(g=g||open("","_blank"),g&&(g.document.title=g.document.body.innerText="downloading..."),"string"==typeof b)return c(b,d,e);var h="application/octet-stream"===b.type,i=/constructor/i.test(f.HTMLElement)||f.safari,j=/CriOS\/[\d]+/.test(navigator.userAgent);if((j||h&&i||a)&&"undefined"!=typeof FileReader){var k=new FileReader;k.onloadend=function(){var a=k.result;a=j?a:a.replace(/^data:[^;]*;/,"data:attachment/file;"),g?g.location.href=a:location=a,g=null},k.readAsDataURL(b)}else{var l=f.URL||f.webkitURL,m=l.createObjectURL(b);g?g.location=m:location.href=m,g=null,setTimeout(function(){l.revokeObjectURL(m)},4E4)}});f.saveAs=g.saveAs=g,"undefined"!=typeof module&&(module.exports=g)});
+

ui/media/js/auto-save.js

@@ -13,21 +13,30 @@ const SETTINGS_IDS_LIST = [
     "num_outputs_total",
     "num_outputs_parallel",
     "stable_diffusion_model",
+    "clip_skip",
     "vae_model",
     "hypernetwork_model",
-    "sampler",
+    "lora_model",
+    "sampler_name",
     "width",
     "height",
     "num_inference_steps",
     "guidance_scale",
     "prompt_strength",
     "hypernetwork_strength",
+    "lora_alpha",
+    "tiling",
     "output_format",
     "output_quality",
+    "output_lossless",
     "negative_prompt",
     "stream_image_progress",
     "use_face_correction",
+    "gfpgan_model",
     "use_upscale",
+    "upscale_amount",
+    "latent_upscaler_steps",
+    "block_nsfw",
     "show_only_filtered_image",
     "upscale_model",
     "preview-image",
@@ -36,30 +45,37 @@ const SETTINGS_IDS_LIST = [
     "save_to_disk",
     "diskPath",
     "sound_toggle",
-    "turbo",
-    "use_full_precision",
+    "vram_usage_level",
     "confirm_dangerous_actions",
-    "auto_save_settings"
+    "metadata_output_format",
+    "auto_save_settings",
+    "apply_color_correction",
+    "process_order_toggle",
+    "thumbnail_size",
+    "auto_scroll",
+    "zip_toggle",
+    "tree_toggle",
+    "json_toggle",
 ]
 
-const IGNORE_BY_DEFAULT = [
-    "prompt"
-]
+const IGNORE_BY_DEFAULT = ["prompt"]
 
-const SETTINGS_SECTIONS = [ // gets the "keys" property filled in with an ordered list of settings in this section via initSettings
-    { id: "editor-inputs",   name: "Prompt" },
+const SETTINGS_SECTIONS = [
+    // gets the "keys" property filled in with an ordered list of settings in this section via initSettings
+    { id: "editor-inputs", name: "Prompt" },
     { id: "editor-settings", name: "Image Settings" },
     { id: "system-settings", name: "System Settings" },
-    { id: "container",       name: "Other" }
+    { id: "container", name: "Other" },
 ]
 
 async function initSettings() {
-    SETTINGS_IDS_LIST.forEach(id => {
+    SETTINGS_IDS_LIST.forEach((id) => {
         var element = document.getElementById(id)
         if (!element) {
             console.error(`Missing settings element ${id}`)
         }
-        if (id in SETTINGS) { // don't create it again
+        if (id in SETTINGS) {
+            // don't create it again
             return
         }
         SETTINGS[id] = {
@@ -68,27 +84,30 @@ async function initSettings() {
             label: getSettingLabel(element),
             default: getSetting(element),
             value: getSetting(element),
-            ignore: IGNORE_BY_DEFAULT.includes(id)
+            ignore: IGNORE_BY_DEFAULT.includes(id),
         }
         element.addEventListener("input", settingChangeHandler)
         element.addEventListener("change", settingChangeHandler)
     })
     var unsorted_settings_ids = [...SETTINGS_IDS_LIST]
-    SETTINGS_SECTIONS.forEach(section => {
+    SETTINGS_SECTIONS.forEach((section) => {
         var name = section.name
         var element = document.getElementById(section.id)
-        var unsorted_ids = unsorted_settings_ids.map(id => `#${id}`).join(",")
-        var children = unsorted_ids == "" ? [] : Array.from(element.querySelectorAll(unsorted_ids));
+        var unsorted_ids = unsorted_settings_ids.map((id) => `#${id}`).join(",")
+        var children = unsorted_ids == "" ? [] : Array.from(element.querySelectorAll(unsorted_ids))
         section.keys = []
-        children.forEach(e => {
+        children.forEach((e) => {
             section.keys.push(e.id)
         })
-        unsorted_settings_ids = unsorted_settings_ids.filter(id => children.find(e => e.id == id) == undefined)
+        unsorted_settings_ids = unsorted_settings_ids.filter((id) => children.find((e) => e.id == id) == undefined)
     })
     loadSettings()
 }
 
 function getSetting(element) {
+    if (element.dataset && "path" in element.dataset) {
+        return element.dataset.path
+    }
     if (typeof element === "string" || element instanceof String) {
         element = SETTINGS[element].element
     }
@@ -98,6 +117,10 @@ function getSetting(element) {
     return element.value
 }
 function setSetting(element, value) {
+    if (element.dataset && "path" in element.dataset) {
+        element.dataset.path = value
+        return // no need to dispatch any event here because the models are not loaded yet
+    }
     if (typeof element === "string" || element instanceof String) {
         element = SETTINGS[element].element
     }
@@ -107,8 +130,7 @@ function setSetting(element, value) {
     }
     if (element.type == "checkbox") {
         element.checked = value
-    }
-    else {
+    } else {
         element.value = value
     }
     element.dispatchEvent(new Event("input"))
@@ -116,11 +138,11 @@ function setSetting(element, value) {
 }
 
 function saveSettings() {
-    var saved_settings = Object.values(SETTINGS).map(setting => {
+    var saved_settings = Object.values(SETTINGS).map((setting) => {
         return {
             key: setting.key,
             value: setting.value,
-            ignore: setting.ignore
+            ignore: setting.ignore,
         }
     })
     localStorage.setItem(SETTINGS_KEY, JSON.stringify(saved_settings))
@@ -131,16 +153,16 @@ function loadSettings() {
     var saved_settings_text = localStorage.getItem(SETTINGS_KEY)
     if (saved_settings_text) {
         var saved_settings = JSON.parse(saved_settings_text)
-        if (saved_settings.find(s => s.key == "auto_save_settings")?.value == false) {
+        if (saved_settings.find((s) => s.key == "auto_save_settings")?.value == false) {
             setSetting("auto_save_settings", false)
             return
         }
         CURRENTLY_LOADING_SETTINGS = true
-        saved_settings.forEach(saved_setting => {
+        saved_settings.forEach((saved_setting) => {
             var setting = SETTINGS[saved_setting.key]
             if (!setting) {
-                console.warn(`Attempted to load setting ${saved_setting.key}, but no setting found`);
-                return null;
+                console.warn(`Attempted to load setting ${saved_setting.key}, but no setting found`)
+                return null
             }
             setting.ignore = saved_setting.ignore
             if (!setting.ignore) {
@@ -149,10 +171,25 @@ function loadSettings() {
             }
         })
         CURRENTLY_LOADING_SETTINGS = false
-    }
-    else {
+    } else if (localStorage.length < 2) {
+        // localStorage is too short for OldSettings
+        // So this is likely the first time Easy Diffusion is running.
+        // Initialize vram_usage_level based on the available VRAM
+        function initGPUProfile(event) {
+            if (    "detail" in event 
+                && "active" in event.detail
+                && "cuda:0" in event.detail.active
+                && event.detail.active["cuda:0"].mem_total <4.5 )
+            {
+               vramUsageLevelField.value = "low"
+               vramUsageLevelField.dispatchEvent(new Event("change"))
+            }
+            document.removeEventListener("system_info_update", initGPUProfile)
+        }
+        document.addEventListener("system_info_update", initGPUProfile)
+    } else {
         CURRENTLY_LOADING_SETTINGS = true
-        tryLoadOldSettings();
+        tryLoadOldSettings()
         CURRENTLY_LOADING_SETTINGS = false
         saveSettings()
     }
@@ -160,9 +197,9 @@ function loadSettings() {
 
 function loadDefaultSettingsSection(section_id) {
     CURRENTLY_LOADING_SETTINGS = true
-    var section = SETTINGS_SECTIONS.find(s => s.id == section_id);
-    section.keys.forEach(key => {
-        var setting = SETTINGS[key];
+    var section = SETTINGS_SECTIONS.find((s) => s.id == section_id)
+    section.keys.forEach((key) => {
+        var setting = SETTINGS[key]
         setting.value = setting.default
         setSetting(setting.element, setting.value)
     })
@@ -198,10 +235,10 @@ function getSettingLabel(element) {
 
 function fillSaveSettingsConfigTable() {
     saveSettingsConfigTable.textContent = ""
-    SETTINGS_SECTIONS.forEach(section => {
+    SETTINGS_SECTIONS.forEach((section) => {
         var section_row = `<tr><th>${section.name}</th><td></td></tr>`
         saveSettingsConfigTable.insertAdjacentHTML("beforeend", section_row)
-        section.keys.forEach(key => {
+        section.keys.forEach((key) => {
             var setting = SETTINGS[key]
             var element = setting.element
             var checkbox_id = `shouldsave_${element.id}`
@@ -214,7 +251,7 @@ function fillSaveSettingsConfigTable() {
             var newrow = `<tr><td><label for="${checkbox_id}">${setting.label}</label></td><td><input id="${checkbox_id}" name="${checkbox_id}" ${is_checked} type="checkbox" ></td><td><small>(${value})</small></td></tr>`
             saveSettingsConfigTable.insertAdjacentHTML("beforeend", newrow)
             var checkbox = document.getElementById(checkbox_id)
-            checkbox.addEventListener("input", event => {
+            checkbox.addEventListener("input", (event) => {
                 setting.ignore = !checkbox.checked
                 saveSettings()
             })
@@ -225,9 +262,6 @@ function fillSaveSettingsConfigTable() {
 
 // configureSettingsSaveBtn
 
-
-
-
 var autoSaveSettings = document.getElementById("auto_save_settings")
 var configSettingsButton = document.createElement("button")
 configSettingsButton.textContent = "Configure"
@@ -236,72 +270,75 @@ autoSaveSettings.insertAdjacentElement("beforebegin", configSettingsButton)
 autoSaveSettings.addEventListener("change", () => {
     configSettingsButton.style.display = autoSaveSettings.checked ? "block" : "none"
 })
-configSettingsButton.addEventListener('click', () => {
+configSettingsButton.addEventListener("click", () => {
     fillSaveSettingsConfigTable()
     saveSettingsConfigOverlay.classList.add("active")
 })
-resetImageSettingsButton.addEventListener('click', event => {
-    loadDefaultSettingsSection("editor-settings");
+resetImageSettingsButton.addEventListener("click", (event) => {
+    loadDefaultSettingsSection("editor-settings")
     event.stopPropagation()
 })
 
-
 function tryLoadOldSettings() {
     console.log("Loading old user settings")
     // load v1 auto-save.js settings
     var old_map = {
-        "guidance_scale_slider": "guidance_scale",
-        "prompt_strength_slider": "prompt_strength"
+        guidance_scale_slider: "guidance_scale",
+        prompt_strength_slider: "prompt_strength",
     }
     var settings_key_v1 = "user_settings"
     var saved_settings_text = localStorage.getItem(settings_key_v1)
     if (saved_settings_text) {
         var saved_settings = JSON.parse(saved_settings_text)
-        Object.keys(saved_settings.should_save).forEach(key => {
+        Object.keys(saved_settings.should_save).forEach((key) => {
             key = key in old_map ? old_map[key] : key
+            if (!(key in SETTINGS)) return
             SETTINGS[key].ignore = !saved_settings.should_save[key]
-        });
-        Object.keys(saved_settings.values).forEach(key => {
+        })
+        Object.keys(saved_settings.values).forEach((key) => {
             key = key in old_map ? old_map[key] : key
+            if (!(key in SETTINGS)) return
             var setting = SETTINGS[key]
             if (!setting.ignore) {
                 setting.value = saved_settings.values[key]
                 setSetting(setting.element, setting.value)
             }
-        });
+        })
         localStorage.removeItem(settings_key_v1)
     }
 
     // load old individually stored items
-    var individual_settings_map = { // maps old localStorage-key to new SETTINGS-key
-        "soundEnabled": "sound_toggle",
-        "saveToDisk": "save_to_disk",
-        "useCPU": "use_cpu",
-        "useFullPrecision": "use_full_precision",
-        "useTurboMode": "turbo",
-        "diskPath": "diskPath",
-        "useFaceCorrection": "use_face_correction",
-        "useUpscaling": "use_upscale",
-        "showOnlyFilteredImage": "show_only_filtered_image",
-        "streamImageProgress": "stream_image_progress",
-        "outputFormat": "output_format",
-        "autoSaveSettings": "auto_save_settings",
-    };
-    Object.keys(individual_settings_map).forEach(localStorageKey => {
-        var localStorageValue = localStorage.getItem(localStorageKey);
+    var individual_settings_map = {
+        // maps old localStorage-key to new SETTINGS-key
+        soundEnabled: "sound_toggle",
+        saveToDisk: "save_to_disk",
+        useCPU: "use_cpu",
+        diskPath: "diskPath",
+        useFaceCorrection: "use_face_correction",
+        useUpscaling: "use_upscale",
+        showOnlyFilteredImage: "show_only_filtered_image",
+        streamImageProgress: "stream_image_progress",
+        outputFormat: "output_format",
+        autoSaveSettings: "auto_save_settings",
+    }
+    Object.keys(individual_settings_map).forEach((localStorageKey) => {
+        var localStorageValue = localStorage.getItem(localStorageKey)
         if (localStorageValue !== null) {
             let key = individual_settings_map[localStorageKey]
             var setting = SETTINGS[key]
             if (!setting) {
-                console.warn(`Attempted to map old setting ${key}, but no setting found`);
-                return null;
+                console.warn(`Attempted to map old setting ${key}, but no setting found`)
+                return null
             }
-            if (setting.element.type == "checkbox" && (typeof localStorageValue === "string" || localStorageValue instanceof String)) {
+            if (
+                setting.element.type == "checkbox" &&
+                (typeof localStorageValue === "string" || localStorageValue instanceof String)
+            ) {
                 localStorageValue = localStorageValue == "true"
             }
             setting.value = localStorageValue
             setSetting(setting.element, setting.value)
-            localStorage.removeItem(localStorageKey);
+            localStorage.removeItem(localStorageKey)
         }
     })
 }

ui/media/js/dnd.js

@@ -1,86 +1,104 @@
 "use strict" // Opt in to a restricted variant of JavaScript
 
 const EXT_REGEX = /(?:\.([^.]+))?$/
-const TEXT_EXTENSIONS = ['txt', 'json']
-const IMAGE_EXTENSIONS = ['jpg', 'jpeg', 'png', 'bmp', 'tiff', 'tif', 'tga']
+const TEXT_EXTENSIONS = ["txt", "json"]
+const IMAGE_EXTENSIONS = ["jpg", "jpeg", "png", "bmp", "tiff", "tif", "tga", "webp"]
 
 function parseBoolean(stringValue) {
-    if (typeof stringValue === 'boolean') {
+    if (typeof stringValue === "boolean") {
         return stringValue
     }
-    if (typeof stringValue === 'number') {
+    if (typeof stringValue === "number") {
         return stringValue !== 0
     }
-    if (typeof stringValue !== 'string') {
+    if (typeof stringValue !== "string") {
         return false
     }
-    switch(stringValue?.toLowerCase()?.trim()) {
+    switch (stringValue?.toLowerCase()?.trim()) {
         case "true":
         case "yes":
         case "on":
         case "1":
-          return true;
+            return true
 
         case "false":
         case "no":
         case "off":
         case "0":
+        case "none":
         case null:
         case undefined:
-          return false;
+            return false
     }
     try {
-        return Boolean(JSON.parse(stringValue));
+        return Boolean(JSON.parse(stringValue))
     } catch {
         return Boolean(stringValue)
     }
 }
 
+// keep in sync with `ui/easydiffusion/utils/save_utils.py`
 const TASK_MAPPING = {
-    prompt: { name: 'Prompt',
+    prompt: {
+        name: "Prompt",
         setUI: (prompt) => {
             promptField.value = prompt
         },
         readUI: () => promptField.value,
-        parse: (val) => val
+        parse: (val) => val,
     },
-    negative_prompt: { name: 'Negative Prompt',
+    negative_prompt: {
+        name: "Negative Prompt",
         setUI: (negative_prompt) => {
             negativePromptField.value = negative_prompt
         },
         readUI: () => negativePromptField.value,
-        parse: (val) => val
+        parse: (val) => val,
     },
-    active_tags: { name: "Image Modifiers",
+    active_tags: {
+        name: "Image Modifiers",
         setUI: (active_tags) => {
             refreshModifiersState(active_tags)
         },
-        readUI: () => activeTags.map(x => x.name),
-        parse: (val) => val
+        readUI: () => activeTags.map((x) => x.name),
+        parse: (val) => val,
     },
-    width: { name: 'Width',
+    inactive_tags: {
+        name: "Inactive Image Modifiers",
+        setUI: (inactive_tags) => {
+            refreshInactiveTags(inactive_tags)
+        },
+        readUI: () => activeTags.filter((tag) => tag.inactive === true).map((x) => x.name),
+        parse: (val) => val,
+    },
+    width: {
+        name: "Width",
         setUI: (width) => {
             const oldVal = widthField.value
             widthField.value = width
             if (!widthField.value) {
                 widthField.value = oldVal
             }
+            widthField.dispatchEvent(new Event("change"))
         },
         readUI: () => parseInt(widthField.value),
-        parse: (val) => parseInt(val)
+        parse: (val) => parseInt(val),
     },
-    height: { name: 'Height',
+    height: {
+        name: "Height",
         setUI: (height) => {
             const oldVal = heightField.value
             heightField.value = height
             if (!heightField.value) {
                 heightField.value = oldVal
             }
+            heightField.dispatchEvent(new Event("change"))
         },
         readUI: () => parseInt(heightField.value),
-        parse: (val) => parseInt(val)
+        parse: (val) => parseInt(val),
     },
-    seed: { name: 'Seed',
+    seed: {
+        name: "Seed",
         setUI: (seed) => {
             if (!seed) {
                 randomSeedField.checked = true
@@ -89,89 +107,147 @@ const TASK_MAPPING = {
                 return
             }
             randomSeedField.checked = false
+            randomSeedField.dispatchEvent(new Event("change")) // let plugins know that the state of the random seed toggle changed
             seedField.disabled = false
             seedField.value = seed
         },
         readUI: () => parseInt(seedField.value), // just return the value the user is seeing in the UI
-        parse: (val) => parseInt(val)
+        parse: (val) => parseInt(val),
     },
-    num_inference_steps: { name: 'Steps',
+    num_inference_steps: {
+        name: "Steps",
         setUI: (num_inference_steps) => {
             numInferenceStepsField.value = num_inference_steps
         },
         readUI: () => parseInt(numInferenceStepsField.value),
-        parse: (val) => parseInt(val)
+        parse: (val) => parseInt(val),
     },
-    guidance_scale: { name: 'Guidance Scale',
+    guidance_scale: {
+        name: "Guidance Scale",
         setUI: (guidance_scale) => {
             guidanceScaleField.value = guidance_scale
             updateGuidanceScaleSlider()
         },
         readUI: () => parseFloat(guidanceScaleField.value),
-        parse: (val) => parseFloat(val)
+        parse: (val) => parseFloat(val),
     },
-    prompt_strength: { name: 'Prompt Strength',
+    prompt_strength: {
+        name: "Prompt Strength",
         setUI: (prompt_strength) => {
             promptStrengthField.value = prompt_strength
             updatePromptStrengthSlider()
         },
         readUI: () => parseFloat(promptStrengthField.value),
-        parse: (val) => parseFloat(val)
+        parse: (val) => parseFloat(val),
     },
 
-    init_image:  { name: 'Initial Image',
+    init_image: {
+        name: "Initial Image",
         setUI: (init_image) => {
             initImagePreview.src = init_image
         },
         readUI: () => initImagePreview.src,
-        parse: (val) => val
+        parse: (val) => val,
     },
-    mask:  { name: 'Mask',
+    mask: {
+        name: "Mask",
         setUI: (mask) => {
-            setTimeout(() => { // add a delay to insure this happens AFTER the main image loads (which reloads the inpainter)
+            setTimeout(() => {
+                // add a delay to insure this happens AFTER the main image loads (which reloads the inpainter)
                 imageInpainter.setImg(mask)
             }, 250)
             maskSetting.checked = Boolean(mask)
         },
         readUI: () => (maskSetting.checked ? imageInpainter.getImg() : undefined),
-        parse: (val) => val
+        parse: (val) => val,
+    },
+    preserve_init_image_color_profile: {
+        name: "Preserve Color Profile",
+        setUI: (preserve_init_image_color_profile) => {
+            applyColorCorrectionField.checked = parseBoolean(preserve_init_image_color_profile)
+        },
+        readUI: () => applyColorCorrectionField.checked,
+        parse: (val) => parseBoolean(val),
     },
 
-    use_face_correction: { name: 'Use Face Correction',
+    use_face_correction: {
+        name: "Use Face Correction",
         setUI: (use_face_correction) => {
-            useFaceCorrectionField.checked = parseBoolean(use_face_correction)
+            const oldVal = gfpganModelField.value
+            console.log("use face correction", use_face_correction)
+            if (use_face_correction == null || use_face_correction == "None") {
+                gfpganModelField.disabled = true
+                useFaceCorrectionField.checked = false
+            } else {
+                gfpganModelField.value = getModelPath(use_face_correction, [".pth"])
+                if (gfpganModelField.value) {
+                    // Is a valid value for the field.
+                    useFaceCorrectionField.checked = true
+                    gfpganModelField.disabled = false
+                } else {
+                    // Not a valid value, restore the old value and disable the filter.
+                    gfpganModelField.disabled = true
+                    gfpganModelField.value = oldVal
+                    useFaceCorrectionField.checked = false
+                }
+            }
+
+            //useFaceCorrectionField.checked = parseBoolean(use_face_correction)
         },
-        readUI: () => useFaceCorrectionField.checked,
-        parse: (val) => parseBoolean(val)
+        readUI: () => (useFaceCorrectionField.checked ? gfpganModelField.value : undefined),
+        parse: (val) => val,
     },
-    use_upscale: { name: 'Use Upscaling',
+    use_upscale: {
+        name: "Use Upscaling",
         setUI: (use_upscale) => {
             const oldVal = upscaleModelField.value
-            upscaleModelField.value = use_upscale
-            if (upscaleModelField.value) { // Is a valid value for the field.
+            upscaleModelField.value = getModelPath(use_upscale, [".pth"])
+            if (upscaleModelField.value) {
+                // Is a valid value for the field.
                 useUpscalingField.checked = true
                 upscaleModelField.disabled = false
-            } else { // Not a valid value, restore the old value and disable the filter.
+                upscaleAmountField.disabled = false
+            } else {
+                // Not a valid value, restore the old value and disable the filter.
                 upscaleModelField.disabled = true
+                upscaleAmountField.disabled = true
                 upscaleModelField.value = oldVal
                 useUpscalingField.checked = false
             }
         },
         readUI: () => (useUpscalingField.checked ? upscaleModelField.value : undefined),
-        parse: (val) => val
+        parse: (val) => val,
     },
-    sampler: { name: 'Sampler',
-        setUI: (sampler) => {
-            samplerField.value = sampler
+    upscale_amount: {
+        name: "Upscale By",
+        setUI: (upscale_amount) => {
+            upscaleAmountField.value = upscale_amount
+        },
+        readUI: () => upscaleAmountField.value,
+        parse: (val) => val,
+    },
+    latent_upscaler_steps: {
+        name: "Latent Upscaler Steps",
+        setUI: (latent_upscaler_steps) => {
+            latentUpscalerStepsField.value = latent_upscaler_steps
+        },
+        readUI: () => latentUpscalerStepsField.value,
+        parse: (val) => val,
+    },
+    sampler_name: {
+        name: "Sampler",
+        setUI: (sampler_name) => {
+            samplerField.value = sampler_name
         },
         readUI: () => samplerField.value,
-        parse: (val) => val
+        parse: (val) => val,
     },
-    use_stable_diffusion_model: { name: 'Stable Diffusion model',
+    use_stable_diffusion_model: {
+        name: "Stable Diffusion model",
         setUI: (use_stable_diffusion_model) => {
             const oldVal = stableDiffusionModelField.value
 
-            use_stable_diffusion_model = getModelPath(use_stable_diffusion_model, ['.ckpt'])
+            use_stable_diffusion_model = getModelPath(use_stable_diffusion_model, [".ckpt", ".safetensors"])
             stableDiffusionModelField.value = use_stable_diffusion_model
 
             if (!stableDiffusionModelField.value) {
@@ -179,115 +255,162 @@ const TASK_MAPPING = {
             }
         },
         readUI: () => stableDiffusionModelField.value,
-        parse: (val) => val
+        parse: (val) => val,
     },
-    use_vae_model: { name: 'VAE model',
+    clip_skip: {
+        name: "Clip Skip",
+        setUI: (value) => {
+            clip_skip.checked = value
+        },
+        readUI: () => clip_skip.checked,
+        parse: (val) => Boolean(val),
+    },
+    tiling: {
+        name: "Tiling",
+        setUI: (val) => {
+            tilingField.value = val
+        },
+        readUI: () => tilingField.value,
+        parse: (val) => val,
+    },
+    use_vae_model: {
+        name: "VAE model",
         setUI: (use_vae_model) => {
             const oldVal = vaeModelField.value
+            use_vae_model =
+                use_vae_model === undefined || use_vae_model === null || use_vae_model === "None" ? "" : use_vae_model
 
-            if (use_vae_model !== '') {
-                use_vae_model = getModelPath(use_vae_model, ['.vae.pt', '.ckpt'])
-                use_vae_model = use_vae_model !== '' ? use_vae_model : oldVal
+            if (use_vae_model !== "") {
+                use_vae_model = getModelPath(use_vae_model, [".vae.pt", ".ckpt"])
+                use_vae_model = use_vae_model !== "" ? use_vae_model : oldVal
             }
             vaeModelField.value = use_vae_model
         },
         readUI: () => vaeModelField.value,
-        parse: (val) => val
+        parse: (val) => val,
     },
-    use_hypernetwork_model: { name: 'Hypernetwork model',
+    use_lora_model: {
+        name: "LoRA model",
+        setUI: (use_lora_model) => {
+            const oldVal = loraModelField.value
+            use_lora_model =
+                use_lora_model === undefined || use_lora_model === null || use_lora_model === "None"
+                    ? ""
+                    : use_lora_model
+
+            if (use_lora_model !== "") {
+                use_lora_model = getModelPath(use_lora_model, [".ckpt", ".safetensors"])
+                use_lora_model = use_lora_model !== "" ? use_lora_model : oldVal
+            }
+            loraModelField.value = use_lora_model
+        },
+        readUI: () => loraModelField.value,
+        parse: (val) => val,
+    },
+    lora_alpha: {
+        name: "LoRA Strength",
+        setUI: (lora_alpha) => {
+            loraAlphaField.value = lora_alpha
+            updateLoraAlphaSlider()
+        },
+        readUI: () => parseFloat(loraAlphaField.value),
+        parse: (val) => parseFloat(val),
+    },
+    use_hypernetwork_model: {
+        name: "Hypernetwork model",
         setUI: (use_hypernetwork_model) => {
             const oldVal = hypernetworkModelField.value
+            use_hypernetwork_model =
+                use_hypernetwork_model === undefined ||
+                use_hypernetwork_model === null ||
+                use_hypernetwork_model === "None"
+                    ? ""
+                    : use_hypernetwork_model
 
-            if (use_hypernetwork_model !== '') {
-                use_hypernetwork_model = getModelPath(use_hypernetwork_model, ['.pt'])
-                use_hypernetwork_model = use_hypernetwork_model !== '' ? use_hypernetwork_model : oldVal
+            if (use_hypernetwork_model !== "") {
+                use_hypernetwork_model = getModelPath(use_hypernetwork_model, [".pt"])
+                use_hypernetwork_model = use_hypernetwork_model !== "" ? use_hypernetwork_model : oldVal
             }
             hypernetworkModelField.value = use_hypernetwork_model
-            hypernetworkModelField.dispatchEvent(new Event('change'))
+            hypernetworkModelField.dispatchEvent(new Event("change"))
         },
         readUI: () => hypernetworkModelField.value,
-        parse: (val) => val
+        parse: (val) => val,
     },
-    hypernetwork_strength: { name: 'Hypernetwork Strength',
+    hypernetwork_strength: {
+        name: "Hypernetwork Strength",
         setUI: (hypernetwork_strength) => {
             hypernetworkStrengthField.value = hypernetwork_strength
             updateHypernetworkStrengthSlider()
         },
         readUI: () => parseFloat(hypernetworkStrengthField.value),
-        parse: (val) => parseFloat(val)
+        parse: (val) => parseFloat(val),
     },
 
-    num_outputs: { name: 'Parallel Images',
+    num_outputs: {
+        name: "Parallel Images",
         setUI: (num_outputs) => {
             numOutputsParallelField.value = num_outputs
         },
         readUI: () => parseInt(numOutputsParallelField.value),
-        parse: (val) => val
+        parse: (val) => val,
     },
 
-    use_cpu: { name: 'Use CPU',
+    use_cpu: {
+        name: "Use CPU",
         setUI: (use_cpu) => {
             useCPUField.checked = use_cpu
         },
         readUI: () => useCPUField.checked,
-        parse: (val) => val
-    },
-    turbo: { name: 'Turbo',
-        setUI: (turbo) => {
-            turboField.checked = turbo
-        },
-        readUI: () => turboField.checked,
-        parse: (val) => Boolean(val)
-    },
-    use_full_precision: { name: 'Use Full Precision',
-        setUI: (use_full_precision) => {
-            useFullPrecisionField.checked = use_full_precision
-        },
-        readUI: () => useFullPrecisionField.checked,
-        parse: (val) => Boolean(val)
+        parse: (val) => val,
     },
 
-    stream_image_progress: { name: 'Stream Image Progress',
+    stream_image_progress: {
+        name: "Stream Image Progress",
         setUI: (stream_image_progress) => {
-            streamImageProgressField.checked = (parseInt(numOutputsTotalField.value) > 50 ? false : stream_image_progress)
+            streamImageProgressField.checked = parseInt(numOutputsTotalField.value) > 50 ? false : stream_image_progress
         },
         readUI: () => streamImageProgressField.checked,
-        parse: (val) => Boolean(val)
+        parse: (val) => Boolean(val),
     },
-    show_only_filtered_image: { name: 'Show only the corrected/upscaled image',
+    show_only_filtered_image: {
+        name: "Show only the corrected/upscaled image",
         setUI: (show_only_filtered_image) => {
             showOnlyFilteredImageField.checked = show_only_filtered_image
         },
         readUI: () => showOnlyFilteredImageField.checked,
-        parse: (val) => Boolean(val)
+        parse: (val) => Boolean(val),
     },
-    output_format: { name: 'Output Format',
+    output_format: {
+        name: "Output Format",
         setUI: (output_format) => {
             outputFormatField.value = output_format
         },
         readUI: () => outputFormatField.value,
-        parse: (val) => val
+        parse: (val) => val,
     },
-    save_to_disk_path: { name: 'Save to disk path',
+    save_to_disk_path: {
+        name: "Save to disk path",
         setUI: (save_to_disk_path) => {
             saveToDiskField.checked = Boolean(save_to_disk_path)
             diskPathField.value = save_to_disk_path
         },
         readUI: () => diskPathField.value,
-        parse: (val) => val
-    }
+        parse: (val) => val,
+    },
 }
+
 function restoreTaskToUI(task, fieldsToSkip) {
     fieldsToSkip = fieldsToSkip || []
 
-    if ('numOutputsTotal' in task) {
+    if ("numOutputsTotal" in task) {
         numOutputsTotalField.value = task.numOutputsTotal
     }
-    if ('seed' in task) {
+    if ("seed" in task) {
         randomSeedField.checked = false
         seedField.value = task.seed
     }
-    if (!('reqBody' in task)) {
+    if (!("reqBody" in task)) {
         return
     }
     for (const key in TASK_MAPPING) {
@@ -296,29 +419,56 @@ function restoreTaskToUI(task, fieldsToSkip) {
         }
     }
 
-    // restore the original tag
-    promptField.value = task.reqBody.original_prompt || task.reqBody.prompt
+    // properly reset fields not present in the task
+    if (!("use_hypernetwork_model" in task.reqBody)) {
+        hypernetworkModelField.value = ""
+        hypernetworkModelField.dispatchEvent(new Event("change"))
+    }
+
+    if (!("use_lora_model" in task.reqBody)) {
+        loraModelField.value = ""
+        loraModelField.dispatchEvent(new Event("change"))
+    }
+
+    // restore the original prompt if provided (e.g. use settings), fallback to prompt as needed (e.g. copy/paste or d&d)
+    promptField.value = task.reqBody.original_prompt
+    if (!("original_prompt" in task.reqBody)) {
+        promptField.value = task.reqBody.prompt
+    }
+    promptField.dispatchEvent(new Event("input"))
 
     // properly reset checkboxes
-    if (!('use_face_correction' in task.reqBody)) {
+    if (!("use_face_correction" in task.reqBody)) {
         useFaceCorrectionField.checked = false
+        gfpganModelField.disabled = true
     }
-    if (!('use_upscale' in task.reqBody)) {
+    if (!("use_upscale" in task.reqBody)) {
         useUpscalingField.checked = false
     }
-    if (!('mask' in task.reqBody)) {
+    if (!("mask" in task.reqBody) && maskSetting.checked) {
         maskSetting.checked = false
+        maskSetting.dispatchEvent(new Event("click"))
     }
     upscaleModelField.disabled = !useUpscalingField.checked
+    upscaleAmountField.disabled = !useUpscalingField.checked
 
-    // Show the source picture if present
-    initImagePreview.src = (task.reqBody.init_image == undefined ? '' : task.reqBody.init_image)
-    if (IMAGE_REGEX.test(initImagePreview.src)) {
-        if (Boolean(task.reqBody.mask)) {
-            setTimeout(() => { // add a delay to insure this happens AFTER the main image loads (which reloads the inpainter)
-                imageInpainter.setImg(task.reqBody.mask)
-            }, 250)
-        }
+    // hide/show source picture as needed
+    if (IMAGE_REGEX.test(initImagePreview.src) && task.reqBody.init_image == undefined) {
+        // hide source image
+        initImageClearBtn.dispatchEvent(new Event("click"))
+    } else if (task.reqBody.init_image !== undefined) {
+        // listen for inpainter loading event, which happens AFTER the main image loads (which reloads the inpainter)
+        initImagePreview.addEventListener(
+            "load",
+            function() {
+                if (Boolean(task.reqBody.mask)) {
+                    imageInpainter.setImg(task.reqBody.mask)
+                    maskSetting.checked = true
+                }
+            },
+            { once: true }
+        )
+        initImagePreview.src = task.reqBody.init_image
     }
 }
 function readUI() {
@@ -327,21 +477,26 @@ function readUI() {
         reqBody[key] = TASK_MAPPING[key].readUI()
     }
     return {
-        'numOutputsTotal': parseInt(numOutputsTotalField.value),
-        'seed': TASK_MAPPING['seed'].readUI(),
-        'reqBody': reqBody
+        numOutputsTotal: parseInt(numOutputsTotalField.value),
+        seed: TASK_MAPPING["seed"].readUI(),
+        reqBody: reqBody,
     }
 }
-function getModelPath(filename, extensions)
-{
-    let pathIdx = filename.lastIndexOf('/') // Linux, Mac paths
-    if (pathIdx < 0) {
-        pathIdx = filename.lastIndexOf('\\') // Windows paths.
+function getModelPath(filename, extensions) {
+    if (typeof filename !== "string") {
+        return
+    }
+
+    let pathIdx
+    if (filename.includes("/models/stable-diffusion/")) {
+        pathIdx = filename.indexOf("/models/stable-diffusion/") + 25 // Linux, Mac paths
+    } else if (filename.includes("\\models\\stable-diffusion\\")) {
+        pathIdx = filename.indexOf("\\models\\stable-diffusion\\") + 25 // Linux, Mac paths
     }
     if (pathIdx >= 0) {
-        filename = filename.slice(pathIdx + 1)
+        filename = filename.slice(pathIdx)
     }
-    extensions.forEach(ext => {
+    extensions.forEach((ext) => {
         if (filename.endsWith(ext)) {
             filename = filename.slice(0, filename.length - ext.length)
         }
@@ -350,46 +505,60 @@ function getModelPath(filename, extensions)
 }
 
 const TASK_TEXT_MAPPING = {
-    width: 'Width',
-    height: 'Height',
-    seed: 'Seed',
-    num_inference_steps: 'Steps',
-    guidance_scale: 'Guidance Scale',
-    prompt_strength: 'Prompt Strength',
-    use_face_correction: 'Use Face Correction',
-    use_upscale: 'Use Upscaling',
-    sampler: 'Sampler',
-    negative_prompt: 'Negative Prompt',
-    use_stable_diffusion_model: 'Stable Diffusion model',
-    use_hypernetwork_model: 'Hypernetwork model',
-    hypernetwork_strength: 'Hypernetwork Strength'
+    prompt: "Prompt",
+    width: "Width",
+    height: "Height",
+    seed: "Seed",
+    num_inference_steps: "Steps",
+    guidance_scale: "Guidance Scale",
+    prompt_strength: "Prompt Strength",
+    use_face_correction: "Use Face Correction",
+    use_upscale: "Use Upscaling",
+    upscale_amount: "Upscale By",
+    sampler_name: "Sampler",
+    negative_prompt: "Negative Prompt",
+    use_stable_diffusion_model: "Stable Diffusion model",
+    use_hypernetwork_model: "Hypernetwork model",
+    hypernetwork_strength: "Hypernetwork Strength",
 }
-const afterPromptRe = /^\s*Width\s*:\s*\d+\s*(?:\r\n|\r|\n)+\s*Height\s*:\s*\d+\s*(\r\n|\r|\n)+Seed\s*:\s*\d+\s*$/igm
 function parseTaskFromText(str) {
     const taskReqBody = {}
 
-    // Prompt
-    afterPromptRe.lastIndex = 0
-    const match = afterPromptRe.exec(str)
-    if (match) {
-        let prompt = str.slice(0, match.index)
-        str = str.slice(prompt.length)
-        taskReqBody.prompt = prompt.trim()
-        console.log('Prompt:', taskReqBody.prompt)
+    const lines = str.split("\n")
+    if (lines.length === 0) {
+        return
     }
+
+    // Prompt
+    let knownKeyOnFirstLine = false
+    for (let key in TASK_TEXT_MAPPING) {
+        if (lines[0].startsWith(TASK_TEXT_MAPPING[key] + ":")) {
+            knownKeyOnFirstLine = true
+            break
+        }
+    }
+    if (!knownKeyOnFirstLine) {
+        taskReqBody.prompt = lines[0]
+        console.log("Prompt:", taskReqBody.prompt)
+    }
+
     for (const key in TASK_TEXT_MAPPING) {
-        const name = TASK_TEXT_MAPPING[key];
+        if (key in taskReqBody) {
+            continue
+        }
+
+        const name = TASK_TEXT_MAPPING[key]
         let val = undefined
 
-        const reName = new RegExp(`${name}\\ *:\\ *(.*)(?:\\r\\n|\\r|\\n)*`, 'igm')
-        const match = reName.exec(str);
+        const reName = new RegExp(`${name}\\ *:\\ *(.*)(?:\\r\\n|\\r|\\n)*`, "igm")
+        const match = reName.exec(str)
         if (match) {
             str = str.slice(0, match.index) + str.slice(match.index + match[0].length)
             val = match[1]
         }
         if (val !== undefined) {
             taskReqBody[key] = TASK_MAPPING[key].parse(val.trim())
-            console.log(TASK_MAPPING[key].name + ':', taskReqBody[key])
+            console.log(TASK_MAPPING[key].name + ":", taskReqBody[key])
             if (!str) {
                 break
             }
@@ -399,17 +568,21 @@ function parseTaskFromText(str) {
         return undefined
     }
     const task = { reqBody: taskReqBody }
-    if ('seed' in taskReqBody) {
+    if ("seed" in taskReqBody) {
         task.seed = taskReqBody.seed
     }
     return task
 }
 
 async function parseContent(text) {
-    text = text.trim();
-    if (text.startsWith('{') && text.endsWith('}')) {
+    text = text.trim()
+    if (text.startsWith("{") && text.endsWith("}")) {
         try {
             const task = JSON.parse(text)
+            if (!("reqBody" in task)) {
+                // support the format saved to the disk, by the UI
+                task.reqBody = Object.assign({}, task)
+            }
             restoreTaskToUI(task)
             return true
         } catch (e) {
@@ -419,11 +592,13 @@ async function parseContent(text) {
     }
     // Normal txt file.
     const task = parseTaskFromText(text)
-    if (task) {
+    if (text.toLowerCase().includes("seed:") && task) {
+        // only parse valid task content
         restoreTaskToUI(task)
         return true
     } else {
         console.warn(`Raw text content couldn't be parsed.`)
+        promptField.value = text
         return false
     }
 }
@@ -435,21 +610,25 @@ async function readFile(file, i) {
 }
 
 function dropHandler(ev) {
-    console.log('Content dropped...')
+    console.log("Content dropped...")
     let items = []
 
-    if (ev?.dataTransfer?.items) { // Use DataTransferItemList interface
+    if (ev?.dataTransfer?.items) {
+        // Use DataTransferItemList interface
         items = Array.from(ev.dataTransfer.items)
-        items = items.filter(item => item.kind === 'file')
-        items = items.map(item => item.getAsFile())
-    } else if (ev?.dataTransfer?.files) { // Use DataTransfer interface
+        items = items.filter((item) => item.kind === "file")
+        items = items.map((item) => item.getAsFile())
+    } else if (ev?.dataTransfer?.files) {
+        // Use DataTransfer interface
         items = Array.from(ev.dataTransfer.files)
     }
 
-    items.forEach(item => {item.file_ext = EXT_REGEX.exec(item.name.toLowerCase())[1]})
+    items.forEach((item) => {
+        item.file_ext = EXT_REGEX.exec(item.name.toLowerCase())[1]
+    })
 
-    let text_items = items.filter(item => TEXT_EXTENSIONS.includes(item.file_ext))
-    let image_items = items.filter(item => IMAGE_EXTENSIONS.includes(item.file_ext))
+    let text_items = items.filter((item) => TEXT_EXTENSIONS.includes(item.file_ext))
+    let image_items = items.filter((item) => IMAGE_EXTENSIONS.includes(item.file_ext))
 
     if (image_items.length > 0 && ev.target == initImageSelector) {
         return // let the event bubble up, so that the Init Image filepicker can receive this
@@ -459,7 +638,7 @@ function dropHandler(ev) {
     text_items.forEach(readFile)
 }
 function dragOverHandler(ev) {
-    console.log('Content in drop zone')
+    console.log("Content in drop zone")
 
     // Prevent default behavior (Prevent file/content from being opened)
     ev.preventDefault()
@@ -467,75 +646,72 @@ function dragOverHandler(ev) {
     ev.dataTransfer.dropEffect = "copy"
 
     let img = new Image()
-    img.src = location.host + '/media/images/favicon-32x32.png'
+    img.src = "//" + location.host + "/media/images/favicon-32x32.png"
     ev.dataTransfer.setDragImage(img, 16, 16)
 }
 
 document.addEventListener("drop", dropHandler)
 document.addEventListener("dragover", dragOverHandler)
 
-const TASK_REQ_NO_EXPORT = [
-    "use_cpu",
-    "turbo",
-    "use_full_precision",
-    "save_to_disk_path"
-]
-const resetSettings = document.getElementById('reset-image-settings')
+const TASK_REQ_NO_EXPORT = ["use_cpu", "save_to_disk_path"]
+const resetSettings = document.getElementById("reset-image-settings")
 
-function checkReadTextClipboardPermission (result) {
+function checkReadTextClipboardPermission(result) {
     if (result.state != "granted" && result.state != "prompt") {
         return
     }
     // PASTE ICON
-    const pasteIcon = document.createElement('i')
-    pasteIcon.className = 'fa-solid fa-paste section-button'
+    const pasteIcon = document.createElement("i")
+    pasteIcon.className = "fa-solid fa-paste section-button"
     pasteIcon.innerHTML = `<span class="simple-tooltip top-left">Paste Image Settings</span>`
-    pasteIcon.addEventListener('click', async (event) => {
+    pasteIcon.addEventListener("click", async (event) => {
         event.stopPropagation()
         // Add css class 'active'
-        pasteIcon.classList.add('active')
+        pasteIcon.classList.add("active")
         // In 350 ms remove the 'active' class
-        asyncDelay(350).then(() => pasteIcon.classList.remove('active'))
+        asyncDelay(350).then(() => pasteIcon.classList.remove("active"))
 
         // Retrieve clipboard content and try to parse it
-        const text = await navigator.clipboard.readText();
+        const text = await navigator.clipboard.readText()
         await parseContent(text)
     })
     resetSettings.parentNode.insertBefore(pasteIcon, resetSettings)
 }
-navigator.permissions.query({ name: "clipboard-read" }).then(checkReadTextClipboardPermission, (reason) => console.log('clipboard-read is not available. %o', reason))
+navigator.permissions
+    .query({ name: "clipboard-read" })
+    .then(checkReadTextClipboardPermission, (reason) => console.log("clipboard-read is not available. %o", reason))
 
-document.addEventListener('paste', async (event) => {
+document.addEventListener("paste", async (event) => {
     if (event.target) {
         const targetTag = event.target.tagName.toLowerCase()
         // Disable when targeting input elements.
-        if (targetTag === 'input' || targetTag === 'textarea') {
+        if (targetTag === "input" || targetTag === "textarea") {
             return
         }
     }
-    const paste = (event.clipboardData || window.clipboardData).getData('text')
+    const paste = (event.clipboardData || window.clipboardData).getData("text")
     const selection = window.getSelection()
-    if (selection.toString().trim().length <= 0 && await parseContent(paste)) {
+    if (paste != "" && selection.toString().trim().length <= 0 && (await parseContent(paste))) {
         event.preventDefault()
         return
     }
 })
 
 // Adds a copy and a paste icon if the browser grants permission to write to clipboard.
-function checkWriteToClipboardPermission (result) {
+function checkWriteToClipboardPermission(result) {
     if (result.state != "granted" && result.state != "prompt") {
         return
     }
     // COPY ICON
-    const copyIcon = document.createElement('i')
-    copyIcon.className = 'fa-solid fa-clipboard section-button'
+    const copyIcon = document.createElement("i")
+    copyIcon.className = "fa-solid fa-clipboard section-button"
     copyIcon.innerHTML = `<span class="simple-tooltip top-left">Copy Image Settings</span>`
-    copyIcon.addEventListener('click', (event) => {
+    copyIcon.addEventListener("click", (event) => {
         event.stopPropagation()
         // Add css class 'active'
-        copyIcon.classList.add('active')
+        copyIcon.classList.add("active")
         // In 350 ms remove the 'active' class
-        asyncDelay(350).then(() => copyIcon.classList.remove('active'))
+        asyncDelay(350).then(() => copyIcon.classList.remove("active"))
         const uiState = readUI()
         TASK_REQ_NO_EXPORT.forEach((key) => delete uiState.reqBody[key])
         if (uiState.reqBody.init_image && !IMAGE_REGEX.test(uiState.reqBody.init_image)) {
@@ -548,8 +724,8 @@ function checkWriteToClipboardPermission (result) {
 }
 // Determine which access we have to the clipboard. Clipboard access is only available on localhost or via TLS.
 navigator.permissions.query({ name: "clipboard-write" }).then(checkWriteToClipboardPermission, (e) => {
-    if (e instanceof TypeError && typeof navigator?.clipboard?.writeText === 'function') {
+    if (e instanceof TypeError && typeof navigator?.clipboard?.writeText === "function") {
         // Fix for firefox https://bugzilla.mozilla.org/show_bug.cgi?id=1560373
-        checkWriteToClipboardPermission({state:"granted"})
+        checkWriteToClipboardPermission({ state: "granted" })
     }
 })

ui/media/js/image-modal.js

@@ -0,0 +1,228 @@
+"use strict"
+
+/**
+ * @typedef {object} ImageModalRequest
+ * @property {string} src
+ * @property {ImageModalRequest | () => ImageModalRequest | undefined} previous
+ * @property {ImageModalRequest | () => ImageModalRequest | undefined} next
+ */
+
+/**
+ * @type {(() => (string | ImageModalRequest) | string | ImageModalRequest) => {}}
+ */
+const imageModal = (function() {
+    const backElem = createElement("i", undefined, ["fa-solid", "fa-arrow-left", "tertiaryButton"])
+
+    const forwardElem = createElement("i", undefined, ["fa-solid", "fa-arrow-right", "tertiaryButton"])
+
+    const zoomElem = createElement("i", undefined, ["fa-solid", "tertiaryButton"])
+
+    const closeElem = createElement("i", undefined, ["fa-solid", "fa-xmark", "tertiaryButton"])
+
+    const menuBarElem = createElement("div", undefined, "menu-bar", [backElem, forwardElem, zoomElem, closeElem])
+
+    const imageContainer = createElement("div", undefined, "image-wrapper")
+
+    const backdrop = createElement("div", undefined, "backdrop")
+
+    const modalContainer = createElement("div", undefined, "content", [menuBarElem, imageContainer])
+
+    const modalElem = createElement("div", { id: "viewFullSizeImgModal" }, ["popup"], [backdrop, modalContainer])
+    document.body.appendChild(modalElem)
+
+    const setZoomLevel = (value) => {
+        const img = imageContainer.querySelector("img")
+
+        if (value) {
+            zoomElem.classList.remove("fa-magnifying-glass-plus")
+            zoomElem.classList.add("fa-magnifying-glass-minus")
+            if (img) {
+                img.classList.remove("natural-zoom")
+
+                let zoomLevel = typeof value === "number" ? value : img.dataset.zoomLevel
+                if (!zoomLevel) {
+                    zoomLevel = 100
+                }
+
+                img.dataset.zoomLevel = zoomLevel
+                img.width = img.naturalWidth * (+zoomLevel / 100)
+                img.height = img.naturalHeight * (+zoomLevel / 100)
+            }
+        } else {
+            zoomElem.classList.remove("fa-magnifying-glass-minus")
+            zoomElem.classList.add("fa-magnifying-glass-plus")
+            if (img) {
+                img.classList.add("natural-zoom")
+                img.removeAttribute("width")
+                img.removeAttribute("height")
+            }
+        }
+    }
+
+    zoomElem.addEventListener("click", () =>
+        setZoomLevel(imageContainer.querySelector("img")?.classList?.contains("natural-zoom"))
+    )
+
+    const initialState = () => ({
+        previous: undefined,
+        next: undefined,
+
+        start: {
+            x: 0,
+            y: 0,
+        },
+
+        scroll: {
+            x: 0,
+            y: 0,
+        },
+    })
+
+    const state = initialState()
+
+    // Allow grabbing the image to scroll
+    const stopGrabbing = (e) => {
+        if(imageContainer.classList.contains("grabbing")) {
+            imageContainer.classList.remove("grabbing")
+            e?.preventDefault()
+            console.log(`stopGrabbing()`, e)
+        }
+    }
+
+    const addImageGrabbing = (image) => {
+        image?.addEventListener('mousedown', (e) => {
+            if (!image.classList.contains("natural-zoom")) {
+                e.stopPropagation()
+                e.stopImmediatePropagation()
+                e.preventDefault()
+
+                imageContainer.classList.add("grabbing")
+                state.start.x = e.pageX - imageContainer.offsetLeft
+                state.scroll.x = imageContainer.scrollLeft
+                state.start.y = e.pageY - imageContainer.offsetTop
+                state.scroll.y = imageContainer.scrollTop
+            }
+        })
+
+        image?.addEventListener('mouseup', stopGrabbing)
+        image?.addEventListener('mouseleave', stopGrabbing)
+        image?.addEventListener('mousemove', (e) => {
+            if(imageContainer.classList.contains("grabbing")) {
+                e.stopPropagation()
+                e.stopImmediatePropagation()
+                e.preventDefault()
+
+                // Might need to increase this multiplier based on the image size to window size ratio
+                // The default 1:1 is pretty slow
+                const multiplier = 1.0
+
+                const deltaX = e.pageX - imageContainer.offsetLeft - state.start.x
+                imageContainer.scrollLeft = state.scroll.x - (deltaX * multiplier)
+                const deltaY = e.pageY - imageContainer.offsetTop - state.start.y
+                imageContainer.scrollTop = state.scroll.y - (deltaY * multiplier)
+            }
+        })
+    }
+
+    const clear = () => {
+        imageContainer.innerHTML = ""
+
+        Object.entries(initialState()).forEach(([key, value]) => state[key] = value)
+
+        stopGrabbing()
+    }
+
+    const close = () => {
+        clear()
+        modalElem.classList.remove("active")
+        document.body.style.overflow = "initial"
+    }
+
+    /**
+     * @param {() => (string | ImageModalRequest) | string | ImageModalRequest} optionsFactory
+     */
+    function init(optionsFactory) {
+        if (!optionsFactory) {
+            close()
+            return
+        }
+
+        clear()
+
+        const options = typeof optionsFactory === "function" ? optionsFactory() : optionsFactory
+        const src = typeof options === "string" ? options : options.src
+
+        const imgElem = createElement("img", { src }, "natural-zoom")
+        addImageGrabbing(imgElem)
+        imageContainer.appendChild(imgElem)
+        modalElem.classList.add("active")
+        document.body.style.overflow = "hidden"
+        setZoomLevel(false)
+
+        if (typeof options === "object" && options.previous) {
+            state.previous = options.previous
+            backElem.style.display = "unset"
+        } else {
+            backElem.style.display = "none"
+        }
+
+        if (typeof options === "object" && options.next) {
+            state.next = options.next
+            forwardElem.style.display = "unset"
+        } else {
+            forwardElem.style.display = "none"
+        }
+    }
+
+    const back = () => {
+        if (state.previous) {
+            init(state.previous)
+        } else {
+            backElem.style.display = "none"
+        }
+    }
+
+    const forward = () => {
+        if (state.next) {
+            init(state.next)
+        } else {
+            forwardElem.style.display = "none"
+        }
+    }
+
+    window.addEventListener("keydown", (e) => {
+        if (modalElem.classList.contains("active")) {
+            switch (e.key) {
+                case "Escape":
+                    close()
+                    break
+                case "ArrowLeft":
+                    back()
+                    break
+                case "ArrowRight":
+                    forward()
+                    break
+            }
+        }
+    })
+    window.addEventListener("click", (e) => {
+        if (modalElem.classList.contains("active")) {
+            if (e.target === backdrop || e.target === closeElem) {
+                close()
+            }
+
+            e.stopPropagation()
+            e.stopImmediatePropagation()
+            e.preventDefault()
+        }
+    })
+
+    backElem.addEventListener("click", back)
+
+    forwardElem.addEventListener("click", forward)
+
+    /**
+     * @param {() => (string | ImageModalRequest) | string | ImageModalRequest} optionsFactory
+     */
+    return (optionsFactory) => init(optionsFactory)
+})()

ui/media/js/image-modifiers.js

@@ -1,24 +1,28 @@
 let activeTags = []
 let modifiers = []
 let customModifiersGroupElement = undefined
+let customModifiersInitialContent
 
-let editorModifierEntries = document.querySelector('#editor-modifiers-entries')
-let editorModifierTagsList = document.querySelector('#editor-inputs-tags-list')
-let editorTagsContainer = document.querySelector('#editor-inputs-tags-container')
-let modifierCardSizeSlider = document.querySelector('#modifier-card-size-slider')
-let previewImageField = document.querySelector('#preview-image')
-let modifierSettingsBtn = document.querySelector('#modifier-settings-btn')
-let modifierSettingsOverlay = document.querySelector('#modifier-settings-config')
-let customModifiersTextBox = document.querySelector('#custom-modifiers-input')
-let customModifierEntriesToolbar = document.querySelector('#editor-modifiers-entries-toolbar')
+let editorModifierEntries = document.querySelector("#editor-modifiers-entries")
+let editorModifierTagsList = document.querySelector("#editor-inputs-tags-list")
+let editorTagsContainer = document.querySelector("#editor-inputs-tags-container")
+let modifierCardSizeSlider = document.querySelector("#modifier-card-size-slider")
+let previewImageField = document.querySelector("#preview-image")
+let modifierSettingsBtn = document.querySelector("#modifier-settings-btn")
+let modifierSettingsOverlay = document.querySelector("#modifier-settings-config")
+let customModifiersTextBox = document.querySelector("#custom-modifiers-input")
+let customModifierEntriesToolbar = document.querySelector("#editor-modifiers-entries-toolbar")
 
-const modifierThumbnailPath = 'media/modifier-thumbnails'
-const activeCardClass = 'modifier-card-active'
+const modifierThumbnailPath = "media/modifier-thumbnails"
+const activeCardClass = "modifier-card-active"
 const CUSTOM_MODIFIERS_KEY = "customModifiers"
 
-function createModifierCard(name, previews) {
-    const modifierCard = document.createElement('div')
-    modifierCard.className = 'modifier-card'
+function createModifierCard(name, previews, removeBy) {
+    const modifierCard = document.createElement("div")
+    let style = previewImageField.value
+    let styleIndex = style == "portrait" ? 0 : 1
+
+    modifierCard.className = "modifier-card"
     modifierCard.innerHTML = `
     <div class="modifier-card-overlay"></div>
     <div class="modifier-card-image-container">
@@ -30,89 +34,95 @@ function createModifierCard(name, previews) {
         <div class="modifier-card-label"><p></p></div>
     </div>`
 
-    const image = modifierCard.querySelector('.modifier-card-image')
-    const errorText =  modifierCard.querySelector('.modifier-card-error-label')
-    const label = modifierCard.querySelector('.modifier-card-label')
+    const image = modifierCard.querySelector(".modifier-card-image")
+    const errorText = modifierCard.querySelector(".modifier-card-error-label")
+    const label = modifierCard.querySelector(".modifier-card-label")
 
-    errorText.innerText = 'No Image'
+    errorText.innerText = "No Image"
 
-    if (typeof previews == 'object') {
-        image.src = previews[0]; // portrait
-        image.setAttribute('preview-type', 'portrait')
+    if (typeof previews == "object") {
+        image.src = previews[styleIndex] // portrait
+        image.setAttribute("preview-type", style)
     } else {
         image.remove()
     }
 
     const maxLabelLength = 30
-    const nameWithoutBy = name.replace('by ', '')
+    const cardLabel = removeBy ? name.replace("by ", "") : name
 
-    if(nameWithoutBy.length <= maxLabelLength) {
-        label.querySelector('p').innerText = nameWithoutBy
+    if (cardLabel.length <= maxLabelLength) {
+        label.querySelector("p").innerText = cardLabel
     } else {
-        const tooltipText = document.createElement('span')
-        tooltipText.className = 'tooltip-text'
+        const tooltipText = document.createElement("span")
+        tooltipText.className = "tooltip-text"
         tooltipText.innerText = name
 
-        label.classList.add('tooltip')
+        label.classList.add("tooltip")
         label.appendChild(tooltipText)
 
-        label.querySelector('p').innerText = nameWithoutBy.substring(0, maxLabelLength) + '...'
+        label.querySelector("p").innerText = cardLabel.substring(0, maxLabelLength) + "..."
     }
+    label.querySelector("p").dataset.fullName = name // preserve the full name
 
     return modifierCard
 }
 
-function createModifierGroup(modifierGroup, initiallyExpanded) {
+function createModifierGroup(modifierGroup, initiallyExpanded, removeBy) {
     const title = modifierGroup.category
     const modifiers = modifierGroup.modifiers
 
-    const titleEl = document.createElement('h5')
-    titleEl.className = 'collapsible'
+    const titleEl = document.createElement("h5")
+    titleEl.className = "collapsible"
     titleEl.innerText = title
 
-    const modifiersEl = document.createElement('div')
-    modifiersEl.classList.add('collapsible-content', 'editor-modifiers-leaf')
+    const modifiersEl = document.createElement("div")
+    modifiersEl.classList.add("collapsible-content", "editor-modifiers-leaf")
 
     if (initiallyExpanded === true) {
-        titleEl.className += ' active'
+        titleEl.className += " active"
     }
 
-    modifiers.forEach(modObj => {
+    modifiers.forEach((modObj) => {
         const modifierName = modObj.modifier
-        const modifierPreviews = modObj?.previews?.map(preview => `${modifierThumbnailPath}/${preview.path}`)
+        const modifierPreviews = modObj?.previews?.map(
+            (preview) =>
+                `${IMAGE_REGEX.test(preview.image) ? preview.image : modifierThumbnailPath + "/" + preview.path}`
+        )
 
-        const modifierCard = createModifierCard(modifierName, modifierPreviews)
+        const modifierCard = createModifierCard(modifierName, modifierPreviews, removeBy)
 
-        if(typeof modifierCard == 'object') {
+        if (typeof modifierCard == "object") {
             modifiersEl.appendChild(modifierCard)
             const trimmedName = trimModifiers(modifierName)
 
-            modifierCard.addEventListener('click', () => {
-                if (activeTags.map(x => trimModifiers(x.name)).includes(trimmedName)) {
+            modifierCard.addEventListener("click", () => {
+                if (activeTags.map((x) => trimModifiers(x.name)).includes(trimmedName)) {
                     // remove modifier from active array
-                    activeTags = activeTags.filter(x => trimModifiers(x.name) != trimmedName)
+                    activeTags = activeTags.filter((x) => trimModifiers(x.name) != trimmedName)
                     toggleCardState(trimmedName, false)
                 } else {
                     // add modifier to active array
                     activeTags.push({
-                        'name': modifierName,
-                        'element': modifierCard.cloneNode(true),
-                        'originElement': modifierCard,
-                        'previews': modifierPreviews
+                        name: modifierName,
+                        element: modifierCard.cloneNode(true),
+                        originElement: modifierCard,
+                        previews: modifierPreviews,
                     })
                     toggleCardState(trimmedName, true)
                 }
 
                 refreshTagsList()
+                document.dispatchEvent(new Event("refreshImageModifiers"))
             })
         }
     })
 
-    let brk = document.createElement('br')
-    brk.style.clear = 'both'
+    let brk = document.createElement("br")
+    brk.style.clear = "both"
     modifiersEl.appendChild(brk)
 
-    let e = document.createElement('div')
+    let e = document.createElement("div")
+    e.className = "modifier-category"
     e.appendChild(titleEl)
     e.appendChild(modifiersEl)
 
@@ -122,104 +132,146 @@ function createModifierGroup(modifierGroup, initiallyExpanded) {
 }
 
 function trimModifiers(tag) {
-    return tag.replace(/^\(+|\)+$/g, '').replace(/^\[+|\]+$/g, '')
+    // Remove trailing '-' and/or '+'
+    tag = tag.replace(/[-+]+$/, "")
+    // Remove parentheses at beginning and end
+    return tag.replace(/^[(]+|[\s)]+$/g, "")
 }
 
 async function loadModifiers() {
     try {
-        let res = await fetch('/get/modifiers')
+        let res = await fetch("/get/modifiers")
         if (res.status === 200) {
             res = await res.json()
 
-            modifiers = res; // update global variable
+            modifiers = res // update global variable
 
             res.reverse()
 
             res.forEach((modifierGroup, idx) => {
-                createModifierGroup(modifierGroup, idx === res.length - 1)
+                createModifierGroup(modifierGroup, idx === res.length - 1, modifierGroup === "Artist" ? true : false) // only remove "By " for artists
             })
 
             createCollapsibles(editorModifierEntries)
         }
     } catch (e) {
-        console.log('error fetching modifiers', e)
+        console.error("error fetching modifiers", e)
     }
 
     loadCustomModifiers()
+    resizeModifierCards(modifierCardSizeSlider.value)
+    document.dispatchEvent(new Event("loadImageModifiers"))
 }
 
-function refreshModifiersState(newTags) {
+function refreshModifiersState(newTags, inactiveTags) {
     // clear existing modifiers
-    document.querySelector('#editor-modifiers').querySelectorAll('.modifier-card').forEach(modifierCard => {
-        const modifierName = modifierCard.querySelector('.modifier-card-label').innerText
-        if (activeTags.map(x => x.name).includes(modifierName)) {
-            modifierCard.classList.remove(activeCardClass)
-            modifierCard.querySelector('.modifier-card-image-overlay').innerText = '+'
-        }
-    })
+    document
+        .querySelector("#editor-modifiers")
+        .querySelectorAll(".modifier-card")
+        .forEach((modifierCard) => {
+            const modifierName = modifierCard.querySelector(".modifier-card-label p").dataset.fullName // pick the full modifier name
+            if (activeTags.map((x) => x.name).includes(modifierName)) {
+                modifierCard.classList.remove(activeCardClass)
+                modifierCard.querySelector(".modifier-card-image-overlay").innerText = "+"
+            }
+        })
     activeTags = []
 
     // set new modifiers
-    newTags.forEach(tag => {
+    newTags.forEach((tag) => {
         let found = false
-        document.querySelector('#editor-modifiers').querySelectorAll('.modifier-card').forEach(modifierCard => {
-            const modifierName = modifierCard.querySelector('.modifier-card-label').innerText
-            if (tag == modifierName) {
-                // add modifier to active array
-                if (!activeTags.map(x => x.name).includes(tag)) { // only add each tag once even if several custom modifier cards share the same tag
-                    activeTags.push({
-                        'name': modifierName,
-                        'element': modifierCard.cloneNode(true),
-                        'originElement': modifierCard
-                    })
+        document
+            .querySelector("#editor-modifiers")
+            .querySelectorAll(".modifier-card")
+            .forEach((modifierCard) => {
+                const modifierName = modifierCard.querySelector(".modifier-card-label p").dataset.fullName
+                const shortModifierName = modifierCard.querySelector(".modifier-card-label p").innerText
+                if (trimModifiers(tag) == trimModifiers(modifierName)) {
+                    // add modifier to active array
+                    if (!activeTags.map((x) => x.name).includes(tag)) {
+                        // only add each tag once even if several custom modifier cards share the same tag
+                        const imageModifierCard = modifierCard.cloneNode(true)
+                        imageModifierCard.querySelector(".modifier-card-label p").innerText = tag.replace(
+                            modifierName,
+                            shortModifierName
+                        )
+                        activeTags.push({
+                            name: tag,
+                            element: imageModifierCard,
+                            originElement: modifierCard,
+                        })
+                    }
+                    modifierCard.classList.add(activeCardClass)
+                    modifierCard.querySelector(".modifier-card-image-overlay").innerText = "-"
+                    found = true
                 }
-                modifierCard.classList.add(activeCardClass)
-                modifierCard.querySelector('.modifier-card-image-overlay').innerText = '-'
-                found = true
-            }
-        })
-        if (found == false) { // custom tag went missing, create one here
-            let modifierCard = createModifierCard(tag, undefined) // create a modifier card for the missing tag, no image
-            
-            modifierCard.addEventListener('click', () => {
-                if (activeTags.map(x => x.name).includes(tag)) {
+            })
+        if (found == false) {
+            // custom tag went missing, create one here
+            let modifierCard = createModifierCard(tag, undefined, false) // create a modifier card for the missing tag, no image
+
+            modifierCard.addEventListener("click", () => {
+                if (activeTags.map((x) => x.name).includes(tag)) {
                     // remove modifier from active array
-                    activeTags = activeTags.filter(x => x.name != tag)
+                    activeTags = activeTags.filter((x) => x.name != tag)
                     modifierCard.classList.remove(activeCardClass)
 
-                    modifierCard.querySelector('.modifier-card-image-overlay').innerText = '+'
+                    modifierCard.querySelector(".modifier-card-image-overlay").innerText = "+"
                 }
                 refreshTagsList()
             })
 
             activeTags.push({
-                'name': tag,
-                'element': modifierCard,
-                'originElement': undefined  // no origin element for missing tags
+                name: tag,
+                element: modifierCard,
+                originElement: undefined, // no origin element for missing tags
             })
         }
     })
-    refreshTagsList()
+    refreshTagsList(inactiveTags)
 }
 
-function refreshTagsList() {
-    editorModifierTagsList.innerHTML = ''
+function refreshInactiveTags(inactiveTags) {
+    // update inactive tags
+    if (inactiveTags !== undefined && inactiveTags.length > 0) {
+        activeTags.forEach((tag) => {
+            if (inactiveTags.find((element) => element === tag.name) !== undefined) {
+                tag.inactive = true
+            }
+        })
+    }
+
+    // update cards
+    let overlays = document.querySelector("#editor-inputs-tags-list").querySelectorAll(".modifier-card-overlay")
+    overlays.forEach((i) => {
+        let modifierName = i.parentElement.getElementsByClassName("modifier-card-label")[0].getElementsByTagName("p")[0]
+            .dataset.fullName
+        if (inactiveTags?.find((element) => trimModifiers(element) === modifierName) !== undefined) {
+            i.parentElement.classList.add("modifier-toggle-inactive")
+        }
+    })
+}
+
+function refreshTagsList(inactiveTags) {
+    editorModifierTagsList.innerHTML = ""
 
     if (activeTags.length == 0) {
-        editorTagsContainer.style.display = 'none'
+        editorTagsContainer.style.display = "none"
         return
     } else {
-        editorTagsContainer.style.display = 'block'
+        editorTagsContainer.style.display = "block"
     }
 
     activeTags.forEach((tag, index) => {
-        tag.element.querySelector('.modifier-card-image-overlay').innerText = '-'
-        tag.element.classList.add('modifier-card-tiny')
+        tag.element.querySelector(".modifier-card-image-overlay").innerText = "-"
+        tag.element.classList.add("modifier-card-tiny")
 
         editorModifierTagsList.appendChild(tag.element)
 
-        tag.element.addEventListener('click', () => {
-            let idx = activeTags.findIndex(o => { return o.name === tag.name })            
+        tag.element.addEventListener("click", () => {
+            let idx = activeTags.findIndex((o) => {
+                return o.name === tag.name
+            })
 
             if (idx !== -1) {
                 toggleCardState(activeTags[idx].name, false)
@@ -227,85 +279,91 @@ function refreshTagsList() {
                 activeTags.splice(idx, 1)
                 refreshTagsList()
             }
+            document.dispatchEvent(new Event("refreshImageModifiers"))
         })
     })
 
-    let brk = document.createElement('br')
-    brk.style.clear = 'both'
+    let brk = document.createElement("br")
+    brk.style.clear = "both"
     editorModifierTagsList.appendChild(brk)
+    refreshInactiveTags(inactiveTags)
+    document.dispatchEvent(new Event("refreshImageModifiers")) // notify plugins that the image tags have been refreshed
 }
 
 function toggleCardState(modifierName, makeActive) {
-    document.querySelector('#editor-modifiers').querySelectorAll('.modifier-card').forEach(card => {
-        const name = card.querySelector('.modifier-card-label').innerText
-        if (   trimModifiers(modifierName) == trimModifiers(name)
-            || trimModifiers(modifierName) == 'by ' + trimModifiers(name)) {
-            if(makeActive) {
-                card.classList.add(activeCardClass)
-                card.querySelector('.modifier-card-image-overlay').innerText = '-'
+    document
+        .querySelector("#editor-modifiers")
+        .querySelectorAll(".modifier-card")
+        .forEach((card) => {
+            const name = card.querySelector(".modifier-card-label").innerText
+            if (
+                trimModifiers(modifierName) == trimModifiers(name) ||
+                trimModifiers(modifierName) == "by " + trimModifiers(name)
+            ) {
+                if (makeActive) {
+                    card.classList.add(activeCardClass)
+                    card.querySelector(".modifier-card-image-overlay").innerText = "-"
+                } else {
+                    card.classList.remove(activeCardClass)
+                    card.querySelector(".modifier-card-image-overlay").innerText = "+"
+                }
             }
-            else{
-                card.classList.remove(activeCardClass)
-                card.querySelector('.modifier-card-image-overlay').innerText = '+'
-            }
-        }
-    })
+        })
 }
 
 function changePreviewImages(val) {
-    const previewImages = document.querySelectorAll('.modifier-card-image-container img')
+    const previewImages = document.querySelectorAll(".modifier-card-image-container img")
 
     let previewArr = []
 
-    modifiers.map(x => x.modifiers).forEach(x => previewArr.push(...x.map(m => m.previews)))
-    
-    previewArr = previewArr.map(x => {
+    modifiers.map((x) => x.modifiers).forEach((x) => previewArr.push(...x.map((m) => m.previews)))
+
+    previewArr = previewArr.map((x) => {
         let obj = {}
 
-        x.forEach(preview => {
+        x.forEach((preview) => {
             obj[preview.name] = preview.path
         })
-        
+
         return obj
     })
 
-    previewImages.forEach(previewImage => {
-        const currentPreviewType = previewImage.getAttribute('preview-type')
-        const relativePreviewPath = previewImage.src.split(modifierThumbnailPath + '/').pop()
+    previewImages.forEach((previewImage) => {
+        const currentPreviewType = previewImage.getAttribute("preview-type")
+        const relativePreviewPath = previewImage.src.split(modifierThumbnailPath + "/").pop()
 
-        const previews = previewArr.find(preview => relativePreviewPath == preview[currentPreviewType])
+        const previews = previewArr.find((preview) => relativePreviewPath == preview[currentPreviewType])
 
-        if(typeof previews == 'object') {
+        if (typeof previews == "object") {
             let preview = null
 
-            if (val == 'portrait') {
+            if (val == "portrait") {
                 preview = previews.portrait
-            }
-            else if (val == 'landscape') {
+            } else if (val == "landscape") {
                 preview = previews.landscape
             }
 
-            if(preview != null) {
+            if (preview != null) {
                 previewImage.src = `${modifierThumbnailPath}/${preview}`
-                previewImage.setAttribute('preview-type', val)
+                previewImage.setAttribute("preview-type", val)
             }
         }
     })
 }
 
 function resizeModifierCards(val) {
-    const cardSizePrefix = 'modifier-card-size_'
-    const modifierCardClass = 'modifier-card'
+    const cardSizePrefix = "modifier-card-size_"
+    const modifierCardClass = "modifier-card"
 
     const modifierCards = document.querySelectorAll(`.${modifierCardClass}`)
-    const cardSize = n => `${cardSizePrefix}${n}`
+    const cardSize = (n) => `${cardSizePrefix}${n}`
 
-    modifierCards.forEach(card => {
+    modifierCards.forEach((card) => {
         // remove existing size classes
-        const classes = card.className.split(' ').filter(c => !c.startsWith(cardSizePrefix))
-        card.className = classes.join(' ').trim()
+        const classes = card.className.split(" ").filter((c) => !c.startsWith(cardSizePrefix))
+        card.className = classes.join(" ").trim()
 
-        if(val != 0) {
+        if (val != 0) {
             card.classList.add(cardSize(val))
         }
     })
@@ -314,11 +372,31 @@ function resizeModifierCards(val) {
 modifierCardSizeSlider.onchange = () => resizeModifierCards(modifierCardSizeSlider.value)
 previewImageField.onchange = () => changePreviewImages(previewImageField.value)
 
-modifierSettingsBtn.addEventListener('click', function(e) {
+modifierSettingsBtn.addEventListener("click", function(e) {
     modifierSettingsOverlay.classList.add("active")
+    customModifiersTextBox.setSelectionRange(0, 0)
+    customModifiersTextBox.focus()
+    customModifiersInitialContent = customModifiersTextBox.value // preserve the initial content
     e.stopPropagation()
 })
 
+modifierSettingsOverlay.addEventListener("keydown", function(e) {
+    switch (e.key) {
+        case "Escape": // Escape to cancel
+            customModifiersTextBox.value = customModifiersInitialContent // undo the changes
+            modifierSettingsOverlay.classList.remove("active")
+            e.stopPropagation()
+            break
+        case "Enter":
+            if (e.ctrlKey) {
+                // Ctrl+Enter to confirm
+                modifierSettingsOverlay.classList.remove("active")
+                e.stopPropagation()
+                break
+            }
+    }
+})
+
 function saveCustomModifiers() {
     localStorage.setItem(CUSTOM_MODIFIERS_KEY, customModifiersTextBox.value.trim())
 
@@ -326,7 +404,7 @@ function saveCustomModifiers() {
 }
 
 function loadCustomModifiers() {
-    PLUGINS['MODIFIERS_LOAD'].forEach(fn=>fn.loader.call())
+    PLUGINS["MODIFIERS_LOAD"].forEach((fn) => fn.loader.call())
 }
 
-customModifiersTextBox.addEventListener('change', saveCustomModifiers)
+customModifiersTextBox.addEventListener("change", saveCustomModifiers)

ui/media/js/parameters.js

@@ -3,24 +3,33 @@
  * @readonly
  * @enum {string}
  */
- var ParameterType = {
+var ParameterType = {
     checkbox: "checkbox",
     select: "select",
     select_multiple: "select_multiple",
+    slider: "slider",
     custom: "custom",
-};
+}
+
+/**
+ * Element shortcuts
+ */
+let parametersTable = document.querySelector("#system-settings-table")
+let networkParametersTable = document.querySelector("#system-settings-network-table")
 
 /**
  * JSDoc style
  * @typedef {object} Parameter
  * @property {string} id
- * @property {ParameterType} type
- * @property {string} label
- * @property {?string} note
+ * @property {keyof ParameterType} type
+ * @property {string | (parameter: Parameter) => (HTMLElement | string)} label
+ * @property {string | (parameter: Parameter) => (HTMLElement | string) | undefined} note
+ * @property {(parameter: Parameter) => (HTMLElement | string) | undefined} render
+ * @property {string | undefined} icon
  * @property {number|boolean|string} default
+ * @property {boolean?} saveInAppConfig
  */
 
-
 /** @type {Array.<Parameter>} */
 var PARAMETERS = [
     {
@@ -29,13 +38,14 @@ var PARAMETERS = [
         label: "Theme",
         default: "theme-default",
         note: "customize the look and feel of the ui",
-        options: [ // Note: options expanded dynamically
+        options: [
+            // Note: options expanded dynamically
             {
                 value: "theme-default",
-                label: "Default"
-            }
+                label: "Default",
+            },
         ],
-        icon: "fa-palette"
+        icon: "fa-palette",
     },
     {
         id: "save_to_disk",
@@ -51,7 +61,48 @@ var PARAMETERS = [
         label: "Save Location",
         render: (parameter) => {
             return `<input id="${parameter.id}" name="${parameter.id}" size="30" disabled>`
-        }
+        },
+    },
+    {
+        id: "metadata_output_format",
+        type: ParameterType.select,
+        label: "Metadata format",
+        note: "will be saved to disk in this format",
+        default: "txt",
+        options: [
+            {
+                value: "none",
+                label: "none",
+            },
+            {
+                value: "txt",
+                label: "txt",
+            },
+            {
+                value: "json",
+                label: "json",
+            },
+            {
+                value: "embed",
+                label: "embed",
+            },
+            {
+                value: "embed,txt",
+                label: "embed & txt",
+            },
+            {
+                value: "embed,json",
+                label: "embed & json",
+            },
+        ],
+    },
+    {
+        id: "block_nsfw",
+        type: ParameterType.checkbox,
+        label: "Block NSFW images",
+        note: "blurs out NSFW images",
+        icon: "fa-land-mine-on",
+        default: false,
     },
     {
         id: "sound_toggle",
@@ -66,6 +117,7 @@ var PARAMETERS = [
         type: ParameterType.checkbox,
         label: "Process newest jobs first",
         note: "reverse the normal processing order",
+        icon: "fa-arrow-down-short-wide",
         default: false,
     },
     {
@@ -75,14 +127,24 @@ var PARAMETERS = [
         note: "starts the default browser on startup",
         icon: "fa-window-restore",
         default: true,
+        saveInAppConfig: true,
     },
     {
-        id: "turbo",
-        type: ParameterType.checkbox,
-        label: "Turbo Mode",
-        note: "generates images faster, but uses an additional 1 GB of GPU memory",
+        id: "vram_usage_level",
+        type: ParameterType.select,
+        label: "GPU Memory Usage",
+        note:
+            "Faster performance requires more GPU memory (VRAM)<br/><br/>" +
+            "<b>Balanced:</b> nearly as fast as High, much lower VRAM usage<br/>" +
+            "<b>High:</b> fastest, maximum GPU memory usage</br>" +
+            "<b>Low:</b> slowest, recommended for GPUs with 3 to 4 GB memory",
         icon: "fa-forward",
-        default: true,
+        default: "balanced",
+        options: [
+            { value: "balanced", label: "Balanced" },
+            { value: "high", label: "High" },
+            { value: "low", label: "Low" },
+        ],
     },
     {
         id: "use_cpu",
@@ -105,14 +167,6 @@ var PARAMETERS = [
         note: "to process in parallel",
         default: false,
     },
-    {
-        id: "use_full_precision",
-        type: ParameterType.checkbox,
-        label: "Use Full Precision",
-        note: "for GPU-only. warning: this will consume more VRAM",
-        icon: "fa-crosshairs",
-        default: false,
-    },
     {
         id: "auto_save_settings",
         type: ParameterType.checkbox,
@@ -125,7 +179,8 @@ var PARAMETERS = [
         id: "confirm_dangerous_actions",
         type: ParameterType.checkbox,
         label: "Confirm dangerous actions",
-        note: "Actions that might lead to data loss must either be clicked with the shift key pressed, or confirmed in an 'Are you sure?' dialog",
+        note:
+            "Actions that might lead to data loss must either be clicked with the shift key pressed, or confirmed in an 'Are you sure?' dialog",
         icon: "fa-check-double",
         default: true,
     },
@@ -133,135 +188,232 @@ var PARAMETERS = [
         id: "listen_to_network",
         type: ParameterType.checkbox,
         label: "Make Stable Diffusion available on your network",
-        note: "Other devices on your network can access this web page",
+        note: "Other devices on your network can access this web page. Please restart the program after changing this.",
         icon: "fa-network-wired",
         default: true,
+        saveInAppConfig: true,
+        table: networkParametersTable,
     },
     {
         id: "listen_port",
         type: ParameterType.custom,
         label: "Network port",
-        note: "Port that this server listens to. The '9000' part in 'http://localhost:9000'",
+        note:
+            "Port that this server listens to. The '9000' part in 'http://localhost:9000'. Please restart the program after changing this.",
         icon: "fa-anchor",
         render: (parameter) => {
             return `<input id="${parameter.id}" name="${parameter.id}" size="6" value="9000" onkeypress="preventNonNumericalInput(event)">`
-        }
-    },
-    {
-        id: "test_sd2",
-        type: ParameterType.checkbox,
-        label: "Test SD 2.0",
-        note: "Experimental! High memory usage! GPU-only! Not the final version! Please restart the program after changing this.",
-        icon: "fa-fire",
-        default: false,
+        },
+        saveInAppConfig: true,
+        table: networkParametersTable,
     },
     {
         id: "use_beta_channel",
         type: ParameterType.checkbox,
         label: "Beta channel",
-        note: "Get the latest features immediately (but could be less stable). Please restart the program after changing this.",
+        note:
+            "Get the latest features immediately (but could be less stable). Please restart the program after changing this.",
         icon: "fa-fire",
         default: false,
     },
-];
+    {
+        id: "test_diffusers",
+        type: ParameterType.checkbox,
+        label: "Test Diffusers",
+        note:
+            "<b>Experimental! Can have bugs!</b> Use upcoming features (like LoRA) in our new engine. Please press Save, then restart the program after changing this.",
+        icon: "fa-bolt",
+        default: false,
+        saveInAppConfig: true,
+    },
+    {
+        id: "cloudflare",
+        type: ParameterType.custom,
+        label: "Cloudflare tunnel",
+        note: `<span id="cloudflare-off">Create a VPN tunnel to share your Easy Diffusion instance with your friends. This will
+               generate a web server address on the public Internet for your Easy Diffusion instance. </span>
+               <div id="cloudflare-on" class="displayNone"><div>This Easy Diffusion server is available on the Internet using the
+               address:</div><div><div id="cloudflare-address"></div><button id="copy-cloudflare-address">Copy</button></div></div>
+               <b>Anyone knowing this address can access your server.</b> The address of your server will change each time
+               you share a session.<br>
+               Uses <a href="https://try.cloudflare.com/" target="_blank">Cloudflare services</a>.`,
+        icon: ["fa-brands", "fa-cloudflare"],
+        render: () => '<button id="toggle-cloudflare-tunnel" class="primaryButton">Start</button>',
+        table: networkParametersTable,
+    }
+]
 
 function getParameterSettingsEntry(id) {
-    let parameter = PARAMETERS.filter(p => p.id === id)
+    let parameter = PARAMETERS.filter((p) => p.id === id)
     if (parameter.length === 0) {
         return
     }
     return parameter[0].settingsEntry
 }
 
+function sliderUpdate(event) {
+    if (event.srcElement.id.endsWith("-input")) {
+        let slider = document.getElementById(event.srcElement.id.slice(0, -6))
+        slider.value = event.srcElement.value
+        slider.dispatchEvent(new Event("change"))
+    } else {
+        let field = document.getElementById(event.srcElement.id + "-input")
+        field.value = event.srcElement.value
+        field.dispatchEvent(new Event("change"))
+    }
+}
+
+/**
+ * @param {Parameter} parameter
+ * @returns {string | HTMLElement}
+ */
 function getParameterElement(parameter) {
     switch (parameter.type) {
         case ParameterType.checkbox:
-            var is_checked = parameter.default ? " checked" : "";
+            var is_checked = parameter.default ? " checked" : ""
             return `<input id="${parameter.id}" name="${parameter.id}"${is_checked} type="checkbox">`
         case ParameterType.select:
         case ParameterType.select_multiple:
-            var options = (parameter.options || []).map(option => `<option value="${option.value}">${option.label}</option>`).join("")
-            var multiple = (parameter.type == ParameterType.select_multiple ? 'multiple' : '')
+            var options = (parameter.options || [])
+                .map((option) => `<option value="${option.value}">${option.label}</option>`)
+                .join("")
+            var multiple = parameter.type == ParameterType.select_multiple ? "multiple" : ""
             return `<select id="${parameter.id}" name="${parameter.id}" ${multiple}>${options}</select>`
+        case ParameterType.slider:
+            return `<input id="${parameter.id}" name="${parameter.id}" class="editor-slider" type="range" value="${parameter.default}" min="${parameter.slider_min}" max="${parameter.slider_max}" oninput="sliderUpdate(event)"> <input id="${parameter.id}-input" name="${parameter.id}-input" size="4" value="${parameter.default}" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)" oninput="sliderUpdate(event)">&nbsp;${parameter.slider_unit}`
         case ParameterType.custom:
             return parameter.render(parameter)
         default:
-            console.error(`Invalid type for parameter ${parameter.id}`);
+            console.error(`Invalid type ${parameter.type} for parameter ${parameter.id}`)
             return "ERROR: Invalid Type"
     }
 }
 
-let parametersTable = document.querySelector("#system-settings .parameters-table")
-/* fill in the system settings popup table */
-function initParameters() {
-    PARAMETERS.forEach(parameter => {
-        var element = getParameterElement(parameter)
-        var note = parameter.note ? `<small>${parameter.note}</small>` : "";
-        var icon = parameter.icon ? `<i class="fa ${parameter.icon}"></i>` : "";
-        var newrow = document.createElement('div')
-        newrow.innerHTML = `
-            <div>${icon}</div>
-            <div><label for="${parameter.id}">${parameter.label}</label>${note}</div>
-            <div>${element}</div>`
-        parametersTable.appendChild(newrow)
+/**
+ * fill in the system settings popup table
+ * @param {Array<Parameter> | undefined} parameters
+ * */
+function initParameters(parameters) {
+    parameters.forEach((parameter) => {
+        const element = getParameterElement(parameter)
+        const elementWrapper = createElement("div")
+        if (element instanceof Node) {
+            elementWrapper.appendChild(element)
+        } else {
+            elementWrapper.innerHTML = element
+        }
+
+        const note = typeof parameter.note === "function" ? parameter.note(parameter) : parameter.note
+        const noteElements = []
+        if (note) {
+            const noteElement = createElement("small")
+            if (note instanceof Node) {
+                noteElement.appendChild(note)
+            } else {
+                noteElement.innerHTML = note || ""
+            }
+            noteElements.push(noteElement)
+        }
+
+        if (typeof(parameter.icon) == "string") {
+            parameter.icon = [parameter.icon]
+        }
+        const icon = parameter.icon ? [createElement("i", undefined, ["fa", ...parameter.icon])] : []
+
+        const label = typeof parameter.label === "function" ? parameter.label(parameter) : parameter.label
+        const labelElement = createElement("label", { for: parameter.id })
+        if (label instanceof Node) {
+            labelElement.appendChild(label)
+        } else {
+            labelElement.innerHTML = label
+        }
+
+        const newrow = createElement(
+            "div",
+            { "data-setting-id": parameter.id, "data-save-in-app-config": parameter.saveInAppConfig },
+            undefined,
+            [
+                createElement("div", undefined, undefined, icon),
+                createElement("div", undefined, undefined, [labelElement, ...noteElements]),
+                elementWrapper,
+            ]
+        )
+
+        let p = parametersTable
+        if (parameter.table) {
+            p = parameter.table
+        } 
+        p.appendChild(newrow)
+
         parameter.settingsEntry = newrow
     })
 }
 
-initParameters()
+initParameters(PARAMETERS)
 
-let turboField = document.querySelector('#turbo')
-let useCPUField = document.querySelector('#use_cpu')
-let autoPickGPUsField = document.querySelector('#auto_pick_gpus')
-let useGPUsField = document.querySelector('#use_gpus')
-let useFullPrecisionField = document.querySelector('#use_full_precision')
-let saveToDiskField = document.querySelector('#save_to_disk')
-let diskPathField = document.querySelector('#diskPath')
+// listen to parameters from plugins
+PARAMETERS.addEventListener("push", (...items) => {
+    initParameters(items)
+
+    if (items.find((item) => item.saveInAppConfig)) {
+        console.log(
+            "Reloading app config for new parameters",
+            items.map((p) => p.id)
+        )
+        getAppConfig()
+    }
+})
+
+let vramUsageLevelField = document.querySelector("#vram_usage_level")
+let useCPUField = document.querySelector("#use_cpu")
+let autoPickGPUsField = document.querySelector("#auto_pick_gpus")
+let useGPUsField = document.querySelector("#use_gpus")
+let saveToDiskField = document.querySelector("#save_to_disk")
+let diskPathField = document.querySelector("#diskPath")
+let metadataOutputFormatField = document.querySelector("#metadata_output_format")
 let listenToNetworkField = document.querySelector("#listen_to_network")
 let listenPortField = document.querySelector("#listen_port")
-let testSD2Field = document.querySelector("#test_sd2")
 let useBetaChannelField = document.querySelector("#use_beta_channel")
 let uiOpenBrowserOnStartField = document.querySelector("#ui_open_browser_on_start")
 let confirmDangerousActionsField = document.querySelector("#confirm_dangerous_actions")
+let testDiffusers = document.querySelector("#test_diffusers")
 
-let saveSettingsBtn = document.querySelector('#save-system-settings-btn')
-
+let saveSettingsBtn = document.querySelector("#save-system-settings-btn")
 
 async function changeAppConfig(configDelta) {
     try {
-        let res = await fetch('/app_config', {
-            method: 'POST',
+        let res = await fetch("/app_config", {
+            method: "POST",
             headers: {
-                'Content-Type': 'application/json'
+                "Content-Type": "application/json",
             },
-            body: JSON.stringify(configDelta)
+            body: JSON.stringify(configDelta),
         })
         res = await res.json()
 
-        console.log('set config status response', res)
+        console.log("set config status response", res)
     } catch (e) {
-        console.log('set config status error', e)
+        console.log("set config status error", e)
     }
 }
 
 async function getAppConfig() {
     try {
-        let res = await fetch('/get/app_config')
+        let res = await fetch("/get/app_config")
         const config = await res.json()
 
-        if (config.update_branch === 'beta') {
+        applySettingsFromConfig(config)
+
+        // custom overrides
+        if (config.update_branch === "beta") {
             useBetaChannelField.checked = true
             document.querySelector("#updateBranchLabel").innerText = "(beta)"
+        } else {
+            getParameterSettingsEntry("test_diffusers").style.display = "none"
         }
         if (config.ui && config.ui.open_browser_on_start === false) {
             uiOpenBrowserOnStartField.checked = false
         }
-        if ('test_sd2' in config) {
-            testSD2Field.checked = config['test_sd2']
-        }
-
-        let testSD2SettingEntry = getParameterSettingsEntry('test_sd2')
-        testSD2SettingEntry.style.display = (config.update_branch === 'beta' ? '' : 'none')
         if (config.net && config.net.listen_to_network === false) {
             listenToNetworkField.checked = false
         }
@@ -269,90 +421,145 @@ async function getAppConfig() {
             listenPortField.value = config.net.listen_port
         }
 
-        console.log('get config status response', config)
+        const testDiffusersEnabled = config.test_diffusers && config.update_branch !== "main"
+        testDiffusers.checked = testDiffusersEnabled
+
+        if (!testDiffusersEnabled) {
+            document.querySelector("#lora_model_container").style.display = "none"
+            document.querySelector("#lora_alpha_container").style.display = "none"
+            document.querySelector("#tiling_container").style.display = "none"
+
+            document.querySelectorAll("#sampler_name option.diffusers-only").forEach((option) => {
+                option.style.display = "none"
+            })
+        } else {
+            document.querySelector("#lora_model_container").style.display = ""
+            document.querySelector("#lora_alpha_container").style.display = loraModelField.value ? "" : "none"
+            document.querySelector("#tiling_container").style.display = ""
+
+            document.querySelectorAll("#sampler_name option.k_diffusion-only").forEach((option) => {
+                option.disabled = true
+            })
+            document.querySelector("#clip_skip_config").classList.remove("displayNone")
+        }
+
+        console.log("get config status response", config)
+
+        return config
     } catch (e) {
-        console.log('get config status error', e)
+        console.log("get config status error", e)
+
+        return {}
     }
 }
 
-saveToDiskField.addEventListener('change', function(e) {
+function applySettingsFromConfig(config) {
+    Array.from(parametersTable.children).forEach((parameterRow) => {
+        if (parameterRow.dataset.settingId in config && parameterRow.dataset.saveInAppConfig === "true") {
+            const configValue = config[parameterRow.dataset.settingId]
+            const parameterElement =
+                document.getElementById(parameterRow.dataset.settingId) ||
+                parameterRow.querySelector("input") ||
+                parameterRow.querySelector("select")
+
+            switch (parameterElement?.tagName) {
+                case "INPUT":
+                    if (parameterElement.type === "checkbox") {
+                        parameterElement.checked = configValue
+                    } else {
+                        parameterElement.value = configValue
+                    }
+                    parameterElement.dispatchEvent(new Event("change"))
+                    break
+                case "SELECT":
+                    if (Array.isArray(configValue)) {
+                        Array.from(parameterElement.options).forEach((option) => {
+                            if (configValue.includes(option.value || option.text)) {
+                                option.selected = true
+                            }
+                        })
+                    } else {
+                        parameterElement.value = configValue
+                    }
+                    parameterElement.dispatchEvent(new Event("change"))
+                    break
+            }
+        }
+    })
+}
+
+saveToDiskField.addEventListener("change", function(e) {
     diskPathField.disabled = !this.checked
+    metadataOutputFormatField.disabled = !this.checked
 })
 
 function getCurrentRenderDeviceSelection() {
-    let selectedGPUs = $('#use_gpus').val()
+    let selectedGPUs = $("#use_gpus").val()
 
     if (useCPUField.checked && !autoPickGPUsField.checked) {
-        return 'cpu'
+        return "cpu"
     }
     if (autoPickGPUsField.checked || selectedGPUs.length == 0) {
-        return 'auto'
+        return "auto"
     }
 
-    return selectedGPUs.join(',')
+    return selectedGPUs.join(",")
 }
 
-useCPUField.addEventListener('click', function() {
-    let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
-    let autoPickGPUSettingEntry = getParameterSettingsEntry('auto_pick_gpus')
+useCPUField.addEventListener("click", function() {
+    let gpuSettingEntry = getParameterSettingsEntry("use_gpus")
+    let autoPickGPUSettingEntry = getParameterSettingsEntry("auto_pick_gpus")
     if (this.checked) {
-        gpuSettingEntry.style.display = 'none'
-        autoPickGPUSettingEntry.style.display = 'none'
-        autoPickGPUsField.setAttribute('data-old-value', autoPickGPUsField.checked)
+        gpuSettingEntry.style.display = "none"
+        autoPickGPUSettingEntry.style.display = "none"
+        autoPickGPUsField.setAttribute("data-old-value", autoPickGPUsField.checked)
         autoPickGPUsField.checked = false
     } else if (useGPUsField.options.length >= MIN_GPUS_TO_SHOW_SELECTION) {
-        gpuSettingEntry.style.display = ''
-        autoPickGPUSettingEntry.style.display = ''
-        let oldVal = autoPickGPUsField.getAttribute('data-old-value')
-        if (oldVal === null || oldVal === undefined) { // the UI started with CPU selected by default
+        gpuSettingEntry.style.display = ""
+        autoPickGPUSettingEntry.style.display = ""
+        let oldVal = autoPickGPUsField.getAttribute("data-old-value")
+        if (oldVal === null || oldVal === undefined) {
+            // the UI started with CPU selected by default
             autoPickGPUsField.checked = true
         } else {
-            autoPickGPUsField.checked = (oldVal === 'true')
+            autoPickGPUsField.checked = oldVal === "true"
         }
-        gpuSettingEntry.style.display = (autoPickGPUsField.checked ? 'none' : '')
+        gpuSettingEntry.style.display = autoPickGPUsField.checked ? "none" : ""
     }
 })
 
-useGPUsField.addEventListener('click', function() {
-    let selectedGPUs = $('#use_gpus').val()
-    autoPickGPUsField.checked = (selectedGPUs.length === 0)
+useGPUsField.addEventListener("click", function() {
+    let selectedGPUs = $("#use_gpus").val()
+    autoPickGPUsField.checked = selectedGPUs.length === 0
 })
 
-autoPickGPUsField.addEventListener('click', function() {
+autoPickGPUsField.addEventListener("click", function() {
     if (this.checked) {
-        $('#use_gpus').val([])
+        $("#use_gpus").val([])
     }
 
-    let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
-    gpuSettingEntry.style.display = (this.checked ? 'none' : '')
+    let gpuSettingEntry = getParameterSettingsEntry("use_gpus")
+    gpuSettingEntry.style.display = this.checked ? "none" : ""
 })
 
-async function getDiskPath() {
-    try {
-        var diskPath = getSetting("diskPath")
-        if (diskPath == '' || diskPath == undefined || diskPath == "undefined") {
-            let res = await fetch('/get/output_dir')
-            if (res.status === 200) {
-                res = await res.json()
-                res = res.output_dir
-
-                setSetting("diskPath", res)
-            }
-        }
-    } catch (e) {
-        console.log('error fetching output dir path', e)
+async function setDiskPath(defaultDiskPath, force = false) {
+    var diskPath = getSetting("diskPath")
+    if (force || diskPath == "" || diskPath == undefined || diskPath == "undefined") {
+        setSetting("diskPath", defaultDiskPath)
     }
 }
 
 function setDeviceInfo(devices) {
     let cpu = devices.all.cpu.name
-    let allGPUs = Object.keys(devices.all).filter(d => d != 'cpu')
+    let allGPUs = Object.keys(devices.all).filter((d) => d != "cpu")
     let activeGPUs = Object.keys(devices.active)
 
     function ID_TO_TEXT(d) {
         let info = devices.all[d]
         if ("mem_free" in info && "mem_total" in info) {
-            return `${info.name} <small>(${d}) (${info.mem_free.toFixed(1)}Gb free / ${info.mem_total.toFixed(1)} Gb total)</small>`
+            return `${info.name} <small>(${d}) (${info.mem_free.toFixed(1)}Gb free / ${info.mem_total.toFixed(
+                1
+            )} Gb total)</small>`
         } else {
             return `${info.name} <small>(${d}) (no memory info)</small>`
         }
@@ -361,83 +568,155 @@ function setDeviceInfo(devices) {
     allGPUs = allGPUs.map(ID_TO_TEXT)
     activeGPUs = activeGPUs.map(ID_TO_TEXT)
 
-    let systemInfoEl = document.querySelector('#system-info')
-    systemInfoEl.querySelector('#system-info-cpu').innerText = cpu
-    systemInfoEl.querySelector('#system-info-gpus-all').innerHTML = allGPUs.join('</br>')
-    systemInfoEl.querySelector('#system-info-rendering-devices').innerHTML = activeGPUs.join('</br>')
+    let systemInfoEl = document.querySelector("#system-info")
+    systemInfoEl.querySelector("#system-info-cpu").innerText = cpu
+    systemInfoEl.querySelector("#system-info-gpus-all").innerHTML = allGPUs.join("</br>")
+    systemInfoEl.querySelector("#system-info-rendering-devices").innerHTML = activeGPUs.join("</br>")
 }
 
 function setHostInfo(hosts) {
     let port = listenPortField.value
-    hosts = hosts.map(addr => `http://${addr}:${port}/`).map(url => `<div><a href="${url}">${url}</a></div>`)
-    document.querySelector('#system-info-server-hosts').innerHTML = hosts.join('')
+    hosts = hosts.map((addr) => `http://${addr}:${port}/`).map((url) => `<div><a href="${url}">${url}</a></div>`)
+    document.querySelector("#system-info-server-hosts").innerHTML = hosts.join("")
 }
 
 async function getSystemInfo() {
     try {
         const res = await SD.getSystemInfo()
-        let devices = res['devices']
+        let devices = res["devices"]
 
-        let allDeviceIds = Object.keys(devices['all']).filter(d => d !== 'cpu')
-        let activeDeviceIds = Object.keys(devices['active']).filter(d => d !== 'cpu')
+        let allDeviceIds = Object.keys(devices["all"]).filter((d) => d !== "cpu")
+        let activeDeviceIds = Object.keys(devices["active"]).filter((d) => d !== "cpu")
 
         if (activeDeviceIds.length === 0) {
             useCPUField.checked = true
         }
 
         if (allDeviceIds.length < MIN_GPUS_TO_SHOW_SELECTION || useCPUField.checked) {
-            let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
-            gpuSettingEntry.style.display = 'none'
-            let autoPickGPUSettingEntry = getParameterSettingsEntry('auto_pick_gpus')
-            autoPickGPUSettingEntry.style.display = 'none'
+            let gpuSettingEntry = getParameterSettingsEntry("use_gpus")
+            gpuSettingEntry.style.display = "none"
+            let autoPickGPUSettingEntry = getParameterSettingsEntry("auto_pick_gpus")
+            autoPickGPUSettingEntry.style.display = "none"
         }
 
         if (allDeviceIds.length === 0) {
             useCPUField.checked = true
             useCPUField.disabled = true // no compatible GPUs, so make the CPU mandatory
+
+            getParameterSettingsEntry("use_cpu").addEventListener("click", function() {
+                alert(
+                    "Sorry, we could not find a compatible graphics card! Easy Diffusion supports graphics cards with minimum 2 GB of RAM. " +
+                        "Only NVIDIA cards are supported on Windows. NVIDIA and AMD cards are supported on Linux.<br/><br/>" +
+                        "If you have a compatible graphics card, please try updating to the latest drivers.<br/><br/>" +
+                        "Only the CPU can be used for generating images, without a compatible graphics card.",
+                    "No compatible graphics card found!"
+                )
+            })
         }
 
-        autoPickGPUsField.checked = (devices['config'] === 'auto')
+        autoPickGPUsField.checked = devices["config"] === "auto"
 
-        useGPUsField.innerHTML = ''
-        allDeviceIds.forEach(device => {
-            let deviceName = devices['all'][device]['name']
+        useGPUsField.innerHTML = ""
+        allDeviceIds.forEach((device) => {
+            let deviceName = devices["all"][device]["name"]
             let deviceOption = `<option value="${device}">${deviceName} (${device})</option>`
-            useGPUsField.insertAdjacentHTML('beforeend', deviceOption)
+            useGPUsField.insertAdjacentHTML("beforeend", deviceOption)
         })
 
         if (autoPickGPUsField.checked) {
-            let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
-            gpuSettingEntry.style.display = 'none'
+            let gpuSettingEntry = getParameterSettingsEntry("use_gpus")
+            gpuSettingEntry.style.display = "none"
         } else {
-            $('#use_gpus').val(activeDeviceIds)
+            $("#use_gpus").val(activeDeviceIds)
         }
 
-        setDeviceInfo(devices)
-        setHostInfo(res['hosts'])
+        document.dispatchEvent(new CustomEvent("system_info_update", { detail: devices }))
+        setHostInfo(res["hosts"])
+        let force = false
+        if (res["enforce_output_dir"] !== undefined) {
+            force = res["enforce_output_dir"]
+            if (force == true) {
+                saveToDiskField.checked = true
+                metadataOutputFormatField.disabled = false
+            }
+            saveToDiskField.disabled = force
+            diskPathField.disabled = force
+        }
+        setDiskPath(res["default_output_dir"], force)
     } catch (e) {
-        console.log('error fetching devices', e)
+        console.log("error fetching devices", e)
     }
 }
 
-saveSettingsBtn.addEventListener('click', function() {
-    if (listenPortField.value == '') {
-        alert('The network port field must not be empty.')
+saveSettingsBtn.addEventListener("click", function() {
+    if (listenPortField.value == "") {
+        alert("The network port field must not be empty.")
         return
     }
     if (listenPortField.value < 1 || listenPortField.value > 65535) {
-        alert('The network port must be a number from 1 to 65535')
+        alert("The network port must be a number from 1 to 65535")
         return
     }
-    let updateBranch = (useBetaChannelField.checked ? 'beta' : 'main')
-    changeAppConfig({
-        'render_devices': getCurrentRenderDeviceSelection(),
-        'update_branch': updateBranch,
-        'ui_open_browser_on_start': uiOpenBrowserOnStartField.checked,
-        'listen_to_network': listenToNetworkField.checked,
-        'listen_port': listenPortField.value,
-        'test_sd2': testSD2Field.checked
+    const updateBranch = useBetaChannelField.checked ? "beta" : "main"
+
+    const updateAppConfigRequest = {
+        render_devices: getCurrentRenderDeviceSelection(),
+        update_branch: updateBranch,
+    }
+
+    document.querySelectorAll('#system-settings [data-setting-id]').forEach((parameterRow) => {
+        if (parameterRow.dataset.saveInAppConfig === "true") {
+            const parameterElement =
+                document.getElementById(parameterRow.dataset.settingId) ||
+                parameterRow.querySelector("input") ||
+                parameterRow.querySelector("select")
+
+            switch (parameterElement?.tagName) {
+                case "INPUT":
+                    if (parameterElement.type === "checkbox") {
+                        updateAppConfigRequest[parameterRow.dataset.settingId] = parameterElement.checked
+                    } else {
+                        updateAppConfigRequest[parameterRow.dataset.settingId] = parameterElement.value
+                    }
+                    break
+                case "SELECT":
+                    if (parameterElement.multiple) {
+                        updateAppConfigRequest[parameterRow.dataset.settingId] = Array.from(parameterElement.options)
+                            .filter((option) => option.selected)
+                            .map((option) => option.value || option.text)
+                    } else {
+                        updateAppConfigRequest[parameterRow.dataset.settingId] = parameterElement.value
+                    }
+                    break
+                default:
+                    console.error(
+                        `Setting parameter ${parameterRow.dataset.settingId} couldn't be saved to app.config - element #${parameter.id} is a <${parameterElement?.tagName} /> instead of a <input /> or a <select />!`
+                    )
+                    break
+            }
+        }
     })
-    saveSettingsBtn.classList.add('active')
-    asyncDelay(300).then(() => saveSettingsBtn.classList.remove('active'))
+
+    const savePromise = changeAppConfig(updateAppConfigRequest)
+    showToast("Settings saved")
+    saveSettingsBtn.classList.add("active")
+    Promise.all([savePromise, asyncDelay(300)]).then(() => saveSettingsBtn.classList.remove("active"))
 })
+
+listenToNetworkField.addEventListener("change", debounce( ()=>{
+    saveSettingsBtn.click()
+}, 1000))
+
+listenPortField.addEventListener("change", debounce( ()=>{
+    saveSettingsBtn.click()
+}, 1000))
+
+let copyCloudflareAddressBtn = document.querySelector("#copy-cloudflare-address")
+let cloudflareAddressField = document.getElementById("cloudflare-address")
+
+copyCloudflareAddressBtn.addEventListener("click", (e) => {
+    navigator.clipboard.writeText(cloudflareAddressField.innerHTML)
+    showToast("Copied server address to clipboard")
+})
+
+document.addEventListener("system_info_update", (e) => setDeviceInfo(e.detail))

ui/media/js/plugins.js

@@ -3,7 +3,7 @@ const PLUGIN_API_VERSION = "1.0"
 const PLUGINS = {
     /**
      * Register new buttons to show on each output image.
-     * 
+     *
      * Example:
      * PLUGINS['IMAGE_INFO_BUTTONS'].push({
      *   text: 'Make a Similar Image',
@@ -25,16 +25,24 @@ const PLUGINS = {
      * })
      */
     IMAGE_INFO_BUTTONS: [],
+    GET_PROMPTS_HOOK: [],
     MODIFIERS_LOAD: [],
     TASK_CREATE: [],
     OUTPUTS_FORMATS: new ServiceContainer(
-        function png() { return (reqBody) => new SD.RenderTask(reqBody) }
-        , function jpeg() { return (reqBody) => new SD.RenderTask(reqBody) }
+        function png() {
+            return (reqBody) => new SD.RenderTask(reqBody)
+        },
+        function jpeg() {
+            return (reqBody) => new SD.RenderTask(reqBody)
+        },
+        function webp() {
+            return (reqBody) => new SD.RenderTask(reqBody)
+        }
     ),
 }
 PLUGINS.OUTPUTS_FORMATS.register = function(...args) {
     const service = ServiceContainer.prototype.register.apply(this, args)
-    if (typeof outputFormatField !== 'undefined') {
+    if (typeof outputFormatField !== "undefined") {
         const newOption = document.createElement("option")
         newOption.setAttribute("value", service.name)
         newOption.innerText = service.name
@@ -44,13 +52,13 @@ PLUGINS.OUTPUTS_FORMATS.register = function(...args) {
 }
 
 function loadScript(url) {
-    const script = document.createElement('script')
+    const script = document.createElement("script")
     const promiseSrc = new PromiseSource()
-    script.addEventListener('error', () => promiseSrc.reject(new Error(`Script "${url}" couldn't be loaded.`)))
-    script.addEventListener('load', () => promiseSrc.resolve(url))
-    script.src = url + '?t=' + Date.now()
+    script.addEventListener("error", () => promiseSrc.reject(new Error(`Script "${url}" couldn't be loaded.`)))
+    script.addEventListener("load", () => promiseSrc.resolve(url))
+    script.src = url + "?t=" + Date.now()
 
-    console.log('loading script', url)
+    console.log("loading script", url)
     document.head.appendChild(script)
 
     return promiseSrc.promise
@@ -58,7 +66,7 @@ function loadScript(url) {
 
 async function loadUIPlugins() {
     try {
-        const res = await fetch('/get/ui_plugins')
+        const res = await fetch("/get/ui_plugins")
         if (!res.ok) {
             console.error(`Error HTTP${res.status} while loading plugins list. - ${res.statusText}`)
             return
@@ -67,6 +75,6 @@ async function loadUIPlugins() {
         const loadingPromises = plugins.map(loadScript)
         return await Promise.allSettled(loadingPromises)
     } catch (e) {
-        console.log('error fetching plugin paths', e)
+        console.log("error fetching plugin paths", e)
     }
 }

ui/media/js/searchable-models.js

@@ -0,0 +1,670 @@
+"use strict"
+
+let modelsCache
+let modelsOptions
+
+/*
+*** SEARCHABLE MODELS ***
+Creates searchable dropdowns for SD, VAE, or HN models.
+Also adds a reload models button (placed next to SD models, reloads everything including VAE and HN models).
+More reload buttons may be added at strategic UI locations as needed.
+Merely calling getModels() makes all the magic happen behind the scene to refresh the dropdowns.
+
+HOW TO CREATE A MODEL DROPDOWN:
+1) Create an input element. Make sure to add a data-path property, as this is how model dropdowns are identified in auto-save.js.
+<input id="stable_diffusion_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
+
+2) Just declare one of these for your own dropdown (remember to change the element id, e.g. #stable_diffusion_models to your own input's id).
+let stableDiffusionModelField = new ModelDropdown(document.querySelector('#stable_diffusion_model'), 'stable-diffusion')
+let vaeModelField = new ModelDropdown(document.querySelector('#vae_model'), 'vae', 'None')
+let hypernetworkModelField = new ModelDropdown(document.querySelector('#hypernetwork_model'), 'hypernetwork', 'None')
+
+3) Model dropdowns will be refreshed automatically when the reload models button is invoked.
+*/
+class ModelDropdown {
+    modelFilter //= document.querySelector("#model-filter")
+    modelFilterArrow //= document.querySelector("#model-filter-arrow")
+    modelList //= document.querySelector("#model-list")
+    modelResult //= document.querySelector("#model-result")
+    modelNoResult //= document.querySelector("#model-no-result")
+
+    currentSelection //= { elem: undefined, value: '', path: ''}
+    highlightedModelEntry //= undefined
+    activeModel //= undefined
+
+    inputModels //= undefined
+    modelKey //= undefined
+    flatModelList //= []
+    noneEntry //= ''
+    modelFilterInitialized //= undefined
+
+    sorted //= true
+
+    /* MIMIC A REGULAR INPUT FIELD */
+    get parentElement() {
+        return this.modelFilter.parentElement
+    }
+    get parentNode() {
+        return this.modelFilter.parentNode
+    }
+    get value() {
+        return this.modelFilter.dataset.path
+    }
+    set value(path) {
+        this.modelFilter.dataset.path = path
+        this.selectEntry(path)
+    }
+    get disabled() {
+        return this.modelFilter.disabled
+    }
+    set disabled(state) {
+        this.modelFilter.disabled = state
+        if (this.modelFilterArrow) {
+            this.modelFilterArrow.style.color = state ? "dimgray" : ""
+        }
+    }
+    get modelElements() {
+        return this.modelList.querySelectorAll(".model-file")
+    }
+    addEventListener(type, listener, options) {
+        return this.modelFilter.addEventListener(type, listener, options)
+    }
+    dispatchEvent(event) {
+        return this.modelFilter.dispatchEvent(event)
+    }
+    appendChild(option) {
+        // do nothing
+    }
+
+    // remember 'this' - http://blog.niftysnippets.org/2008/04/you-must-remember-this.html
+    bind(f, obj) {
+        return function() {
+            return f.apply(obj, arguments)
+        }
+    }
+
+    /* SEARCHABLE INPUT */
+
+    constructor(input, modelKey, noneEntry = "", sorted = true) {
+        this.modelFilter = input
+        this.noneEntry = noneEntry
+        this.modelKey = modelKey
+        this.sorted = sorted
+
+        if (modelsOptions !== undefined) {
+            // reuse models from cache (only useful for plugins, which are loaded after models)
+            this.inputModels = []
+            let modelKeys = Array.isArray(this.modelKey) ? this.modelKey : [this.modelKey]
+            for (let i = 0; i < modelKeys.length; i++) {
+                let key = modelKeys[i]
+                let k = Array.isArray(modelsOptions[key]) ? modelsOptions[key] : [modelsOptions[key]]
+                this.inputModels.push(...k)
+            }
+            this.populateModels()
+        }
+        document.addEventListener(
+            "refreshModels",
+            this.bind(function(e) {
+                // reload the models
+                this.inputModels = []
+                let modelKeys = Array.isArray(this.modelKey) ? this.modelKey : [this.modelKey]
+                for (let i = 0; i < modelKeys.length; i++) {
+                    let key = modelKeys[i]
+                    let k = Array.isArray(modelsOptions[key]) ? modelsOptions[key] : [modelsOptions[key]]
+                    this.inputModels.push(...k)
+                }
+                this.populateModels()
+            }, this)
+        )
+    }
+
+    saveCurrentSelection(elem, value, path) {
+        this.currentSelection.elem = elem
+        this.currentSelection.value = value
+        this.currentSelection.path = path
+        this.modelFilter.dataset.path = path
+        this.modelFilter.value = value
+        this.modelFilter.dispatchEvent(new Event("change"))
+    }
+
+    processClick(e) {
+        e.preventDefault()
+        if (e.srcElement.classList.contains("model-file") || e.srcElement.classList.contains("fa-file")) {
+            const elem = e.srcElement.classList.contains("model-file") ? e.srcElement : e.srcElement.parentElement
+            this.saveCurrentSelection(elem, elem.innerText, elem.dataset.path)
+            this.hideModelList()
+            this.modelFilter.focus()
+            this.modelFilter.select()
+        }
+    }
+
+    getPreviousVisibleSibling(elem) {
+        const modelElements = Array.from(this.modelElements)
+        const index = modelElements.indexOf(elem)
+        if (index <= 0) {
+            return undefined
+        }
+
+        return modelElements
+            .slice(0, index)
+            .reverse()
+            .find((e) => e.style.display === "list-item")
+    }
+
+    getLastVisibleChild(elem) {
+        let lastElementChild = elem.lastElementChild
+        if (lastElementChild.style.display == "list-item") return lastElementChild
+        return this.getPreviousVisibleSibling(lastElementChild)
+    }
+
+    getNextVisibleSibling(elem) {
+        const modelElements = Array.from(this.modelElements)
+        const index = modelElements.indexOf(elem)
+        return modelElements.slice(index + 1).find((e) => e.style.display === "list-item")
+    }
+
+    getFirstVisibleChild(elem) {
+        let firstElementChild = elem.firstElementChild
+        if (firstElementChild.style.display == "list-item") return firstElementChild
+        return this.getNextVisibleSibling(firstElementChild)
+    }
+
+    selectModelEntry(elem) {
+        if (elem) {
+            if (this.highlightedModelEntry !== undefined) {
+                this.highlightedModelEntry.classList.remove("selected")
+            }
+            this.saveCurrentSelection(elem, elem.innerText, elem.dataset.path)
+            elem.classList.add("selected")
+            elem.scrollIntoView({ block: "nearest" })
+            this.highlightedModelEntry = elem
+        }
+    }
+
+    selectPreviousFile() {
+        const elem = this.getPreviousVisibleSibling(this.highlightedModelEntry)
+        if (elem) {
+            this.selectModelEntry(elem)
+        } else {
+            //this.highlightedModelEntry.parentElement.parentElement.scrollIntoView({block: 'nearest'})
+            this.highlightedModelEntry.closest(".model-list").scrollTop = 0
+        }
+        this.modelFilter.select()
+    }
+
+    selectNextFile() {
+        this.selectModelEntry(this.getNextVisibleSibling(this.highlightedModelEntry))
+        this.modelFilter.select()
+    }
+
+    selectFirstFile() {
+        this.selectModelEntry(this.modelList.querySelector(".model-file"))
+        this.highlightedModelEntry.scrollIntoView({ block: "nearest" })
+        this.modelFilter.select()
+    }
+
+    selectLastFile() {
+        const elems = this.modelList.querySelectorAll(".model-file:last-child")
+        this.selectModelEntry(elems[elems.length - 1])
+        this.modelFilter.select()
+    }
+
+    resetSelection() {
+        this.hideModelList()
+        this.showAllEntries()
+        this.modelFilter.value = this.currentSelection.value
+        this.modelFilter.focus()
+        this.modelFilter.select()
+    }
+
+    validEntrySelected() {
+        return this.modelNoResult.style.display === "none"
+    }
+
+    processKey(e) {
+        switch (e.key) {
+            case "Escape":
+                e.preventDefault()
+                this.resetSelection()
+                break
+            case "Enter":
+                e.preventDefault()
+                if (this.validEntrySelected()) {
+                    if (this.modelList.style.display != "block") {
+                        this.showModelList()
+                    } else {
+                        this.saveCurrentSelection(
+                            this.highlightedModelEntry,
+                            this.highlightedModelEntry.innerText,
+                            this.highlightedModelEntry.dataset.path
+                        )
+                        this.hideModelList()
+                        this.showAllEntries()
+                    }
+                    this.modelFilter.focus()
+                } else {
+                    this.resetSelection()
+                }
+                break
+            case "ArrowUp":
+                e.preventDefault()
+                if (this.validEntrySelected()) {
+                    this.selectPreviousFile()
+                }
+                break
+            case "ArrowDown":
+                e.preventDefault()
+                if (this.validEntrySelected()) {
+                    this.selectNextFile()
+                }
+                break
+            case "ArrowLeft":
+                if (this.modelList.style.display != "block") {
+                    e.preventDefault()
+                }
+                break
+            case "ArrowRight":
+                if (this.modelList.style.display != "block") {
+                    e.preventDefault()
+                }
+                break
+            case "PageUp":
+                e.preventDefault()
+                if (this.validEntrySelected()) {
+                    this.selectPreviousFile()
+                    this.selectPreviousFile()
+                    this.selectPreviousFile()
+                    this.selectPreviousFile()
+                    this.selectPreviousFile()
+                    this.selectPreviousFile()
+                    this.selectPreviousFile()
+                    this.selectPreviousFile()
+                }
+                break
+            case "PageDown":
+                e.preventDefault()
+                if (this.validEntrySelected()) {
+                    this.selectNextFile()
+                    this.selectNextFile()
+                    this.selectNextFile()
+                    this.selectNextFile()
+                    this.selectNextFile()
+                    this.selectNextFile()
+                    this.selectNextFile()
+                    this.selectNextFile()
+                }
+                break
+            case "Home":
+                //if (this.modelList.style.display != 'block') {
+                e.preventDefault()
+                if (this.validEntrySelected()) {
+                    this.selectFirstFile()
+                }
+                //}
+                break
+            case "End":
+                //if (this.modelList.style.display != 'block') {
+                e.preventDefault()
+                if (this.validEntrySelected()) {
+                    this.selectLastFile()
+                }
+                //}
+                break
+            default:
+            //console.log(e.key)
+        }
+    }
+
+    modelListFocus() {
+        this.selectEntry()
+        this.showAllEntries()
+    }
+
+    showModelList() {
+        this.modelList.style.display = "block"
+        this.selectEntry()
+        this.showAllEntries()
+        //this.modelFilter.value = ''
+        this.modelFilter.select() // preselect the entire string so user can just start typing.
+        this.modelFilter.focus()
+        this.modelFilter.style.cursor = "auto"
+    }
+
+    hideModelList() {
+        this.modelList.style.display = "none"
+        this.modelFilter.value = this.currentSelection.value
+        this.modelFilter.style.cursor = ""
+    }
+
+    toggleModelList(e) {
+        e.preventDefault()
+        if (!this.modelFilter.disabled) {
+            if (this.modelList.style.display != "block") {
+                this.showModelList()
+            } else {
+                this.hideModelList()
+                this.modelFilter.select()
+            }
+        }
+    }
+
+    selectEntry(path) {
+        if (path !== undefined) {
+            const entries = this.modelElements
+
+            for (const elem of entries) {
+                if (elem.dataset.path == path) {
+                    this.saveCurrentSelection(elem, elem.innerText, elem.dataset.path)
+                    this.highlightedModelEntry = elem
+                    elem.scrollIntoView({ block: "nearest" })
+                    break
+                }
+            }
+        }
+
+        if (this.currentSelection.elem !== undefined) {
+            // select the previous element
+            if (this.highlightedModelEntry !== undefined && this.highlightedModelEntry != this.currentSelection.elem) {
+                this.highlightedModelEntry.classList.remove("selected")
+            }
+            this.currentSelection.elem.classList.add("selected")
+            this.highlightedModelEntry = this.currentSelection.elem
+            this.currentSelection.elem.scrollIntoView({ block: "nearest" })
+        } else {
+            this.selectFirstFile()
+        }
+    }
+
+    highlightModelAtPosition(e) {
+        let elem = document.elementFromPoint(e.clientX, e.clientY)
+
+        if (elem.classList.contains("model-file")) {
+            this.highlightModel(elem)
+        }
+    }
+
+    highlightModel(elem) {
+        if (elem.classList.contains("model-file")) {
+            if (this.highlightedModelEntry !== undefined && this.highlightedModelEntry != elem) {
+                this.highlightedModelEntry.classList.remove("selected")
+            }
+            elem.classList.add("selected")
+            this.highlightedModelEntry = elem
+        }
+    }
+
+    showAllEntries() {
+        this.modelList.querySelectorAll("li").forEach(function(li) {
+            if (li.id !== "model-no-result") {
+                li.style.display = "list-item"
+            }
+        })
+        this.modelNoResult.style.display = "none"
+    }
+
+    filterList(e) {
+        const filter = this.modelFilter.value.toLowerCase()
+        let found = false
+        let showAllChildren = false
+
+        this.modelList.querySelectorAll("li").forEach(function(li) {
+            if (li.classList.contains("model-folder")) {
+                showAllChildren = false
+            }
+            if (filter == "") {
+                li.style.display = "list-item"
+                found = true
+            } else if (showAllChildren || li.textContent.toLowerCase().match(filter)) {
+                li.style.display = "list-item"
+                if (li.classList.contains("model-folder") && li.firstChild.textContent.toLowerCase().match(filter)) {
+                    showAllChildren = true
+                }
+                found = true
+            } else {
+                li.style.display = "none"
+            }
+        })
+
+        if (found) {
+            this.modelResult.style.display = "list-item"
+            this.modelNoResult.style.display = "none"
+            const elem = this.getNextVisibleSibling(this.modelList.querySelector(".model-file"))
+            this.highlightModel(elem)
+            elem.scrollIntoView({ block: "nearest" })
+        } else {
+            this.modelResult.style.display = "none"
+            this.modelNoResult.style.display = "list-item"
+        }
+        this.modelList.style.display = "block"
+    }
+
+    /* MODEL LOADER */
+    getElementDimensions(element) {
+        // Clone the element
+        const clone = element.cloneNode(true)
+
+        // Copy the styles of the original element to the cloned element
+        const originalStyles = window.getComputedStyle(element)
+        for (let i = 0; i < originalStyles.length; i++) {
+            const property = originalStyles[i]
+            clone.style[property] = originalStyles.getPropertyValue(property)
+        }
+
+        // Set its visibility to hidden and display to inline-block
+        clone.style.visibility = "hidden"
+        clone.style.display = "inline-block"
+
+        // Put the cloned element next to the original element
+        element.parentNode.insertBefore(clone, element.nextSibling)
+
+        // Get its width and height
+        const width = clone.offsetWidth
+        const height = clone.offsetHeight
+
+        // Remove it from the DOM
+        clone.remove()
+
+        // Return its width and height
+        return { width, height }
+    }
+
+    /**
+     * @param {Array<string>} models
+     */
+    sortStringArray(models) {
+        models.sort((a, b) => a.localeCompare(b, undefined, { sensitivity: "base" }))
+    }
+
+    populateModels() {
+        this.activeModel = this.modelFilter.dataset.path
+
+        this.currentSelection = { elem: undefined, value: "", path: "" }
+        this.highlightedModelEntry = undefined
+        this.flatModelList = []
+
+        if (this.modelList !== undefined) {
+            this.modelList.remove()
+            this.modelFilterArrow.remove()
+        }
+        this.createDropdown()
+    }
+
+    createDropdown() {
+        // create dropdown entries
+        let rootModelList = this.createRootModelList(this.inputModels)
+        this.modelFilter.insertAdjacentElement("afterend", rootModelList)
+        this.modelFilter.insertAdjacentElement(
+            "afterend",
+            createElement("i", { id: `${this.modelFilter.id}-model-filter-arrow` }, [
+                "model-selector-arrow",
+                "fa-solid",
+                "fa-angle-down",
+            ])
+        )
+        this.modelFilter.classList.add("model-selector")
+        this.modelFilterArrow = document.querySelector(`#${this.modelFilter.id}-model-filter-arrow`)
+        if (this.modelFilterArrow) {
+            this.modelFilterArrow.style.color = this.modelFilter.disabled ? "dimgray" : ""
+        }
+        this.modelList = document.querySelector(`#${this.modelFilter.id}-model-list`)
+        this.modelResult = document.querySelector(`#${this.modelFilter.id}-model-result`)
+        this.modelNoResult = document.querySelector(`#${this.modelFilter.id}-model-no-result`)
+
+        if (this.modelFilterInitialized !== true) {
+            this.modelFilter.addEventListener("input", this.bind(this.filterList, this))
+            this.modelFilter.addEventListener("focus", this.bind(this.modelListFocus, this))
+            this.modelFilter.addEventListener("blur", this.bind(this.hideModelList, this))
+            this.modelFilter.addEventListener("click", this.bind(this.showModelList, this))
+            this.modelFilter.addEventListener("keydown", this.bind(this.processKey, this))
+
+            this.modelFilterInitialized = true
+        }
+        this.modelFilterArrow.addEventListener("mousedown", this.bind(this.toggleModelList, this))
+        this.modelList.addEventListener("mousemove", this.bind(this.highlightModelAtPosition, this))
+        this.modelList.addEventListener("mousedown", this.bind(this.processClick, this))
+
+        let mf = this.modelFilter
+        this.modelFilter.addEventListener("focus", function() {
+            let modelFilterStyle = window.getComputedStyle(mf)
+            rootModelList.style.minWidth = modelFilterStyle.width
+        })
+
+        this.selectEntry(this.activeModel)
+    }
+
+    /**
+     * @param {Array<string | object} modelTree
+     * @param {string} folderName
+     * @param {boolean} isRootFolder
+     * @returns {HTMLElement}
+     */
+    createModelNodeList(folderName, modelTree, isRootFolder) {
+        const listElement = createElement("ul")
+
+        const foldersMap = new Map()
+        const modelsMap = new Map()
+
+        modelTree.forEach((model) => {
+            if (Array.isArray(model)) {
+                const [childFolderName, childModels] = model
+                foldersMap.set(
+                    childFolderName,
+                    this.createModelNodeList(`${folderName || ""}/${childFolderName}`, childModels, false)
+                )
+            } else {
+                const classes = ["model-file"]
+                if (isRootFolder) {
+                    classes.push("in-root-folder")
+                }
+                // Remove the leading slash from the model path
+                const fullPath = folderName ? `${folderName.substring(1)}/${model}` : model
+                modelsMap.set(
+                    model,
+                    createElement("li", { "data-path": fullPath }, classes, [
+                        createElement("i", undefined, ["fa-regular", "fa-file", "icon"]),
+                        model,
+                    ])
+                )
+            }
+        })
+
+        const childFolderNames = Array.from(foldersMap.keys())
+        if (this.sorted) {
+            this.sortStringArray(childFolderNames)
+        }
+        const folderElements = childFolderNames.map((name) => foldersMap.get(name))
+
+        const modelNames = Array.from(modelsMap.keys())
+        if (this.sorted) {
+            this.sortStringArray(modelNames)
+        }
+        const modelElements = modelNames.map((name) => modelsMap.get(name))
+
+        if (modelElements.length && folderName) {
+            listElement.appendChild(
+                createElement(
+                    "li",
+                    undefined,
+                    ["model-folder"],
+                    [createElement("i", undefined, ["fa-regular", "fa-folder-open", "icon"]), folderName.substring(1)]
+                )
+            )
+        }
+
+        // const allModelElements = isRootFolder ? [...folderElements, ...modelElements] : [...modelElements, ...folderElements]
+        const allModelElements = [...modelElements, ...folderElements]
+        allModelElements.forEach((e) => listElement.appendChild(e))
+        return listElement
+    }
+
+    /**
+     * @param {object} modelTree
+     * @returns {HTMLElement}
+     */
+    createRootModelList(modelTree) {
+        const rootList = createElement("ul", { id: `${this.modelFilter.id}-model-list` }, ["model-list"])
+        rootList.appendChild(
+            createElement("li", { id: `${this.modelFilter.id}-model-no-result` }, ["model-no-result"], "No result")
+        )
+
+        if (this.noneEntry) {
+            rootList.appendChild(
+                createElement("li", { "data-path": "" }, ["model-file", "in-root-folder"], this.noneEntry)
+            )
+        }
+
+        if (modelTree.length > 0) {
+            const containerListItem = createElement("li", { id: `${this.modelFilter.id}-model-result` }, [
+                "model-result",
+            ])
+            //console.log(containerListItem)
+            containerListItem.appendChild(this.createModelNodeList(undefined, modelTree, true))
+            rootList.appendChild(containerListItem)
+        }
+
+        return rootList
+    }
+}
+
+/* (RE)LOAD THE MODELS */
+async function getModels() {
+    try {
+        modelsCache = await SD.getModels()
+        modelsOptions = modelsCache["options"]
+        if ("scan-error" in modelsCache) {
+            // let previewPane = document.getElementById('tab-content-wrapper')
+            let previewPane = document.getElementById("preview")
+            previewPane.style.background = "red"
+            previewPane.style.textAlign = "center"
+            previewPane.innerHTML =
+                "<H1>🔥Malware alert!🔥</H1><h2>The file <i>" +
+                modelsCache["scan-error"] +
+                '</i> in your <tt>models/stable-diffusion</tt> folder is probably malware infected.</h2><h2>Please delete this file from the folder before proceeding!</h2>After deleting the file, reload this page.<br><br><button onClick="window.location.reload();">Reload Page</button>'
+            makeImageBtn.disabled = true
+        }
+
+        /* This code should no longer be needed. Commenting out for now, will cleanup later.
+        const sd_model_setting_key = "stable_diffusion_model"
+        const vae_model_setting_key = "vae_model"
+        const hypernetwork_model_key = "hypernetwork_model"
+
+        const stableDiffusionOptions = modelsOptions['stable-diffusion']
+        const vaeOptions = modelsOptions['vae']
+        const hypernetworkOptions = modelsOptions['hypernetwork']
+
+        // TODO: set default for model here too
+        SETTINGS[sd_model_setting_key].default = stableDiffusionOptions[0]
+        if (getSetting(sd_model_setting_key) == '' || SETTINGS[sd_model_setting_key].value == '') {
+            setSetting(sd_model_setting_key, stableDiffusionOptions[0])
+        }
+        */
+
+        // notify ModelDropdown objects to refresh
+        document.dispatchEvent(new Event("refreshModels"))
+    } catch (e) {
+        console.log("get models error", e)
+    }
+}
+
+// reload models button
+document.querySelector("#reload-models").addEventListener("click", getModels)

ui/media/js/themes.js

@@ -1,81 +1,85 @@
-const themeField = document.getElementById("theme");
-var DEFAULT_THEME = {};
-var THEMES = []; // initialized in initTheme from data in css
+const themeField = document.getElementById("theme")
+var DEFAULT_THEME = {}
+var THEMES = [] // initialized in initTheme from data in css
 
 function getThemeName(theme) {
-    theme = theme.replace("theme-", "");
-    theme = theme.split("-").map(word => word.charAt(0).toUpperCase() + word.slice(1)).join(" ");
-    return theme;
+    theme = theme.replace("theme-", "")
+    theme = theme
+        .split("-")
+        .map((word) => word.charAt(0).toUpperCase() + word.slice(1))
+        .join(" ")
+    return theme
 }
 // init themefield
 function initTheme() {
     Array.from(document.styleSheets)
-        .filter(sheet => sheet.href?.startsWith(window.location.origin))
-        .flatMap(sheet => Array.from(sheet.cssRules))
-        .forEach(rule => {
-            var selector = rule.selectorText; // TODO: also do selector == ":root", re-run un-set props
+        .filter((sheet) => sheet.href?.startsWith(window.location.origin))
+        .flatMap((sheet) => Array.from(sheet.cssRules))
+        .forEach((rule) => {
+            var selector = rule.selectorText
             if (selector && selector.startsWith(".theme-") && !selector.includes(" ")) {
-                var theme_key = selector.substring(1);
+                if (DEFAULT_THEME) {
+                    // re-add props that dont change (css needs this so they update correctly)
+                    Array.from(DEFAULT_THEME.rule.style)
+                        .filter((cssVariable) => !Array.from(rule.style).includes(cssVariable))
+                        .forEach((cssVariable) => {
+                            rule.style.setProperty(cssVariable, DEFAULT_THEME.rule.style.getPropertyValue(cssVariable))
+                        })
+                }
+                var theme_key = selector.substring(1)
                 THEMES.push({
                     key: theme_key,
                     name: getThemeName(theme_key),
-                    rule: rule
+                    rule: rule,
                 })
             }
             if (selector && selector == ":root") {
                 DEFAULT_THEME = {
                     key: "theme-default",
                     name: "Default",
-                    rule: rule
-                };
+                    rule: rule,
+                }
             }
-    });
-    
-    THEMES.forEach(theme => {
-        var new_option = document.createElement("option");
-        new_option.setAttribute("value", theme.key);
-        new_option.innerText = theme.name;
-        themeField.appendChild(new_option);
-    });
+        })
+
+    THEMES.forEach((theme) => {
+        var new_option = document.createElement("option")
+        new_option.setAttribute("value", theme.key)
+        new_option.innerText = theme.name
+        themeField.appendChild(new_option)
+    })
 
-    
     // setup the style transitions a second after app initializes, so initial style is instant
     setTimeout(() => {
-        var body = document.querySelector("body");
-        var style = document.createElement('style');
-        style.innerHTML = "* { transition: background 0.5s, color 0.5s, background-color 0.5s; }";
-        body.appendChild(style);
-    }, 1000);
+        var body = document.querySelector("body")
+        var style = document.createElement("style")
+        style.innerHTML = "* { transition: background 0.5s, color 0.5s, background-color 0.5s; }"
+        body.appendChild(style)
+    }, 1000)
 }
-initTheme();
+initTheme()
 
 function themeFieldChanged() {
-    var theme_key = themeField.value;
+    var theme_key = themeField.value
 
-    var body = document.querySelector("body");
-    body.classList.remove(...THEMES.map(theme => theme.key));
-    body.classList.add(theme_key);
-    
-    // 
+    var body = document.querySelector("body")
+    body.classList.remove(...THEMES.map((theme) => theme.key))
+    body.classList.add(theme_key)
 
-    body.style = "";
-    var theme = THEMES.find(t => t.key == theme_key);
+    //
+
+    body.style = ""
+    var theme = THEMES.find((t) => t.key == theme_key)
     let borderColor = undefined
     if (theme) {
-        // refresh variables incase they are back referencing
-        Array.from(DEFAULT_THEME.rule.style)
-            .filter(cssVariable => !Array.from(theme.rule.style).includes(cssVariable))
-            .forEach(cssVariable => {
-            body.style.setProperty(cssVariable, DEFAULT_THEME.rule.style.getPropertyValue(cssVariable));
-        });
-        borderColor = theme.rule.style.getPropertyValue('--input-border-color').trim()
-        if (!borderColor.startsWith('#')) {
-            borderColor = theme.rule.style.getPropertyValue('--theme-color-fallback')
+        borderColor = theme.rule.style.getPropertyValue("--input-border-color").trim()
+        if (!borderColor.startsWith("#")) {
+            borderColor = theme.rule.style.getPropertyValue("--theme-color-fallback")
         }
     } else {
-        borderColor = DEFAULT_THEME.rule.style.getPropertyValue('--theme-color-fallback')
+        borderColor = DEFAULT_THEME.rule.style.getPropertyValue("--theme-color-fallback")
     }
     document.querySelector('meta[name="theme-color"]').setAttribute("content", borderColor)
 }
 
-themeField.addEventListener('change', themeFieldChanged);
+themeField.addEventListener("change", themeFieldChanged)

ui/modifiers.json

@@ -2428,6 +2428,19 @@
             "path": "artist/by_yoshitaka_amano/landscape-0.jpg"
           }
         ]
+      },
+      {
+        "modifier": "by Zdzislaw Beksinski",
+        "previews": [
+          {
+            "name": "portrait",
+            "path": "artist/by_zdzislaw_beksinski/portrait-0.jpg"
+          },
+          {
+            "name": "landscape",
+            "path": "artist/by_zdzislaw_beksinski/landscape-0.jpg"
+          }
+        ]
       }
     ]
   },

ui/plugins/ui/Autoscroll.plugin.js

@@ -1,45 +1,32 @@
-(function () {
+;(function() {
     "use strict"
 
-    var styleSheet = document.createElement("style");
-    styleSheet.textContent = `
-        .auto-scroll {
-            float: right;
-        }
-    `;
-    document.head.appendChild(styleSheet);
-    
-    const autoScrollControl = document.createElement('div');
-    autoScrollControl.innerHTML = `<input id="auto_scroll" name="auto_scroll" type="checkbox">
-                            <label for="auto_scroll">Scroll to generated image</label>`
-    autoScrollControl.className = "auto-scroll"
-    clearAllPreviewsBtn.parentNode.insertBefore(autoScrollControl, clearAllPreviewsBtn.nextSibling)
-    prettifyInputs(document);
     let autoScroll = document.querySelector("#auto_scroll")
-    
-    // save/restore the toggle state
-    autoScroll.addEventListener('click', (e) => {
-        localStorage.setItem('auto_scroll', autoScroll.checked)
-    })
-    autoScroll.checked = localStorage.getItem('auto_scroll') == "true"
 
     // observe for changes in the preview pane
-    var observer = new MutationObserver(function (mutations) {
-        mutations.forEach(function (mutation) {
-            if (mutation.target.className == 'img-batch') {
+    var observer = new MutationObserver(function(mutations) {
+        mutations.forEach(function(mutation) {
+            if (mutation.target.className == "img-batch") {
                 Autoscroll(mutation.target)
             }
         })
     })
-    
-    observer.observe(document.getElementById('preview'), {
-            childList: true,
-            subtree: true
+
+    observer.observe(document.getElementById("preview"), {
+        childList: true,
+        subtree: true,
     })
 
     function Autoscroll(target) {
         if (autoScroll.checked && target !== null) {
-            target.parentElement.parentElement.parentElement.scrollIntoView();
+            const img = target.querySelector("img")
+            img.addEventListener(
+                "load",
+                function() {
+                    img?.closest(".imageTaskContainer").scrollIntoView()
+                },
+                { once: true }
+            )
         }
     }
 })()

ui/plugins/ui/Modifiers-dnd.plugin.js

@@ -1,92 +1,116 @@
-(function () { "use strict"
-    if (typeof editorModifierTagsList !== 'object') {
-        console.error('editorModifierTagsList missing...')
+;(function() {
+    "use strict"
+    if (typeof editorModifierTagsList !== "object") {
+        console.error("editorModifierTagsList missing...")
         return
     }
 
-    const styleSheet = document.createElement("style");
+    const styleSheet = document.createElement("style")
     styleSheet.textContent = `
         .modifier-card-tiny.drag-sort-active {
             background: transparent;
             border: 2px dashed white;
             opacity:0.2;
         }
-    `;
-    document.head.appendChild(styleSheet);
+    `
+    document.head.appendChild(styleSheet)
 
     // observe for changes in tag list
-    const observer = new MutationObserver(function (mutations) {
-    //    mutations.forEach(function (mutation) {
-            if (editorModifierTagsList.childNodes.length > 0) {
-                ModifierDragAndDrop(editorModifierTagsList)
-            }
-    //    })
+    const observer = new MutationObserver(function(mutations) {
+        //    mutations.forEach(function (mutation) {
+        if (editorModifierTagsList.childNodes.length > 0) {
+            ModifierDragAndDrop(editorModifierTagsList)
+        }
+        //    })
     })
-    
+
     observer.observe(editorModifierTagsList, {
-            childList: true
+        childList: true,
     })
 
     let current
     function ModifierDragAndDrop(target) {
-        let overlays = document.querySelector('#editor-inputs-tags-list').querySelectorAll('.modifier-card-overlay')
-        overlays.forEach (i => {
-            i.parentElement.draggable = true;
-            
+        let overlays = document.querySelector("#editor-inputs-tags-list").querySelectorAll(".modifier-card-overlay")
+        overlays.forEach((i) => {
+            i.parentElement.draggable = true
+
             i.parentElement.ondragstart = (e) => {
                 current = i
-                i.parentElement.getElementsByClassName('modifier-card-image-overlay')[0].innerText = ''
+                i.parentElement.getElementsByClassName("modifier-card-image-overlay")[0].innerText = ""
                 i.parentElement.draggable = true
-                i.parentElement.classList.add('drag-sort-active')
-                for(let item of document.querySelector('#editor-inputs-tags-list').getElementsByClassName('modifier-card-image-overlay')) {
-                    if (item.parentElement.parentElement.getElementsByClassName('modifier-card-overlay')[0] != current) {
-                        item.parentElement.parentElement.getElementsByClassName('modifier-card-image-overlay')[0].style.opacity = 0
-                        if(item.parentElement.getElementsByClassName('modifier-card-image').length > 0) {
-                            item.parentElement.getElementsByClassName('modifier-card-image')[0].style.filter = 'none'
+                i.parentElement.classList.add("drag-sort-active")
+                for (let item of document
+                    .querySelector("#editor-inputs-tags-list")
+                    .getElementsByClassName("modifier-card-image-overlay")) {
+                    if (
+                        item.parentElement.parentElement.getElementsByClassName("modifier-card-overlay")[0] != current
+                    ) {
+                        item.parentElement.parentElement.getElementsByClassName(
+                            "modifier-card-image-overlay"
+                        )[0].style.opacity = 0
+                        if (item.parentElement.getElementsByClassName("modifier-card-image").length > 0) {
+                            item.parentElement.getElementsByClassName("modifier-card-image")[0].style.filter = "none"
                         }
-                        item.parentElement.parentElement.style.transform = 'none'
-                        item.parentElement.parentElement.style.boxShadow = 'none'
+                        item.parentElement.parentElement.style.transform = "none"
+                        item.parentElement.parentElement.style.boxShadow = "none"
                     }
-                    item.innerText = ''
+                    item.innerText = ""
                 }
             }
-            
+
             i.ondragenter = (e) => {
                 e.preventDefault()
                 if (i != current) {
-                    let currentPos = 0, droppedPos = 0;
+                    let currentPos = 0,
+                        droppedPos = 0
                     for (let it = 0; it < overlays.length; it++) {
-                        if (current == overlays[it]) { currentPos = it; }
-                        if (i == overlays[it]) { droppedPos = it; }
+                        if (current == overlays[it]) {
+                            currentPos = it
+                        }
+                        if (i == overlays[it]) {
+                            droppedPos = it
+                        }
                     }
 
                     if (i.parentElement != current.parentElement) {
-                        let currentPos = 0, droppedPos = 0
+                        let currentPos = 0,
+                            droppedPos = 0
                         for (let it = 0; it < overlays.length; it++) {
-                            if (current == overlays[it]) { currentPos = it }
-                            if (i == overlays[it]) { droppedPos = it }
+                            if (current == overlays[it]) {
+                                currentPos = it
+                            }
+                            if (i == overlays[it]) {
+                                droppedPos = it
+                            }
                         }
                         if (currentPos < droppedPos) {
-                            current = i.parentElement.parentNode.insertBefore(current.parentElement, i.parentElement.nextSibling).getElementsByClassName('modifier-card-overlay')[0]
+                            current = i.parentElement.parentNode
+                                .insertBefore(current.parentElement, i.parentElement.nextSibling)
+                                .getElementsByClassName("modifier-card-overlay")[0]
                         } else {
-                            current = i.parentElement.parentNode.insertBefore(current.parentElement, i.parentElement).getElementsByClassName('modifier-card-overlay')[0]
+                            current = i.parentElement.parentNode
+                                .insertBefore(current.parentElement, i.parentElement)
+                                .getElementsByClassName("modifier-card-overlay")[0]
                         }
                         // update activeTags
                         const tag = activeTags.splice(currentPos, 1)
                         activeTags.splice(droppedPos, 0, tag[0])
+                        document.dispatchEvent(new Event("refreshImageModifiers"))
                     }
                 }
-            };
+            }
 
             i.ondragover = (e) => {
                 e.preventDefault()
             }
-            
+
             i.parentElement.ondragend = (e) => {
-                i.parentElement.classList.remove('drag-sort-active')
-                for(let item of document.querySelector('#editor-inputs-tags-list').getElementsByClassName('modifier-card-image-overlay')) {
-                    item.style.opacity = ''
-                    item.innerText = '-'
+                i.parentElement.classList.remove("drag-sort-active")
+                for (let item of document
+                    .querySelector("#editor-inputs-tags-list")
+                    .getElementsByClassName("modifier-card-image-overlay")) {
+                    item.style.opacity = ""
+                    item.innerText = "-"
                 }
             }
         })

ui/plugins/ui/Modifiers-wheel.plugin.js

@@ -1,63 +1,87 @@
-(function () { "use strict"
-    if (typeof editorModifierTagsList !== 'object') {
-        console.error('editorModifierTagsList missing...')
+;(function() {
+    "use strict"
+
+    const MAX_WEIGHT = 5
+
+    if (typeof editorModifierTagsList !== "object") {
+        console.error("editorModifierTagsList missing...")
         return
     }
 
     // observe for changes in tag list
-    const observer = new MutationObserver(function (mutations) {
-    //    mutations.forEach(function (mutation) {
-            if (editorModifierTagsList.childNodes.length > 0) {
-                ModifierMouseWheel(editorModifierTagsList)
-            }
-    //    })
+    const observer = new MutationObserver(function(mutations) {
+        //    mutations.forEach(function (mutation) {
+        if (editorModifierTagsList.childNodes.length > 0) {
+            ModifierMouseWheel(editorModifierTagsList)
+        }
+        //    })
     })
-    
+
     observer.observe(editorModifierTagsList, {
-            childList: true
+        childList: true,
     })
 
     function ModifierMouseWheel(target) {
-        let overlays = document.querySelector('#editor-inputs-tags-list').querySelectorAll('.modifier-card-overlay')
-        overlays.forEach (i => {
+        let overlays = document.querySelector("#editor-inputs-tags-list").querySelectorAll(".modifier-card-overlay")
+        overlays.forEach((i) => {
             i.onwheel = (e) => {
                 if (e.ctrlKey == true) {
                     e.preventDefault()
-    
+
                     const delta = Math.sign(event.deltaY)
-                    let s = i.parentElement.getElementsByClassName('modifier-card-label')[0].getElementsByTagName("p")[0].innerText
-                    if (delta < 0) {
-                        // wheel scrolling up
-                        if (s.substring(0, 1) == '[' && s.substring(s.length-1) == ']') {
-                            s = s.substring(1, s.length - 1)
-                        }
-                        else
-                        {
-                            if (s.substring(0, 10) !== '('.repeat(10) && s.substring(s.length-10) !== ')'.repeat(10)) {
-                                s = '(' + s + ')'
-                            }
-                        }
-                    }
-                    else{
-                        // wheel scrolling down
-                        if (s.substring(0, 1) == '(' && s.substring(s.length-1) == ')') {
-                            s = s.substring(1, s.length - 1)
-                        }
-                        else
-                        {
-                            if (s.substring(0, 10) !== '['.repeat(10) && s.substring(s.length-10) !== ']'.repeat(10)) {
-                                s = '[' + s + ']'
-                            }
-                        }
-                    }
-                    i.parentElement.getElementsByClassName('modifier-card-label')[0].getElementsByTagName("p")[0].innerText = s
-                    // update activeTags
+                    let s = i.parentElement
+                        .getElementsByClassName("modifier-card-label")[0]
+                        .getElementsByTagName("p")[0].innerText
+                    let t
+                    // find the corresponding tag
                     for (let it = 0; it < overlays.length; it++) {
                         if (i == overlays[it]) {
-                            activeTags[it].name = s
+                            t = activeTags[it].name
                             break
                         }
                     }
+                    if (s.charAt(0) !== "(" && s.charAt(s.length - 1) !== ")" && s.trim().includes(" ")) {
+                        s = "(" + s + ")"
+                        t = "(" + t + ")"
+                    }
+                    if (delta < 0) {
+                        // wheel scrolling up
+                        if (s.substring(s.length - 1) == "-") {
+                            s = s.substring(0, s.length - 1)
+                            t = t.substring(0, t.length - 1)
+                        } else {
+                            if (s.substring(s.length - MAX_WEIGHT) !== "+".repeat(MAX_WEIGHT)) {
+                                s = s + "+"
+                                t = t + "+"
+                            }
+                        }
+                    } else {
+                        // wheel scrolling down
+                        if (s.substring(s.length - 1) == "+") {
+                            s = s.substring(0, s.length - 1)
+                            t = t.substring(0, t.length - 1)
+                        } else {
+                            if (s.substring(s.length - MAX_WEIGHT) !== "-".repeat(MAX_WEIGHT)) {
+                                s = s + "-"
+                                t = t + "-"
+                            }
+                        }
+                    }
+                    if (s.charAt(0) === "(" && s.charAt(s.length - 1) === ")") {
+                        s = s.substring(1, s.length - 1)
+                        t = t.substring(1, t.length - 1)
+                    }
+                    i.parentElement
+                        .getElementsByClassName("modifier-card-label")[0]
+                        .getElementsByTagName("p")[0].innerText = s
+                    // update activeTags
+                    for (let it = 0; it < overlays.length; it++) {
+                        if (i == overlays[it]) {
+                            activeTags[it].name = t
+                            break
+                        }
+                    }
+                    document.dispatchEvent(new Event("refreshImageModifiers"))
                 }
             }
         })

ui/plugins/ui/custom-modifiers.plugin.js

@@ -1,31 +1,31 @@
-(function() {
-    PLUGINS['MODIFIERS_LOAD'].push({
+;(function() {
+    PLUGINS["MODIFIERS_LOAD"].push({
         loader: function() {
-            let customModifiers = localStorage.getItem(CUSTOM_MODIFIERS_KEY, '')
+            let customModifiers = localStorage.getItem(CUSTOM_MODIFIERS_KEY, "")
             customModifiersTextBox.value = customModifiers
 
             if (customModifiersGroupElement !== undefined) {
                 customModifiersGroupElement.remove()
             }
 
-            if (customModifiers && customModifiers.trim() !== '') {
-                customModifiers = customModifiers.split('\n')
-                customModifiers = customModifiers.filter(m => m.trim() !== '')
+            if (customModifiers && customModifiers.trim() !== "") {
+                customModifiers = customModifiers.split("\n")
+                customModifiers = customModifiers.filter((m) => m.trim() !== "")
                 customModifiers = customModifiers.map(function(m) {
                     return {
-                        "modifier": m
+                        modifier: m,
                     }
                 })
 
                 let customGroup = {
-                    'category': 'Custom Modifiers',
-                    'modifiers': customModifiers
+                    category: "Custom Modifiers",
+                    modifiers: customModifiers,
                 }
 
                 customModifiersGroupElement = createModifierGroup(customGroup, true)
 
                 createCollapsibles(customModifiersGroupElement)
             }
-        }
+        },
     })
 })()

ui/plugins/ui/jasmine/boot0.js

@@ -26,39 +26,39 @@ WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
  after `jasmine.js` and `jasmine_html.js`, but before `boot1.js` or any project
  source files or spec files are loaded.
  */
-(function() {
-  const jasmineRequire = window.jasmineRequire || require('./jasmine.js');
+;(function() {
+    const jasmineRequire = window.jasmineRequire || require("./jasmine.js")
 
-  /**
-   * ## Require & Instantiate
-   *
-   * Require Jasmine's core files. Specifically, this requires and attaches all of Jasmine's code to the `jasmine` reference.
-   */
-  const jasmine = jasmineRequire.core(jasmineRequire),
-    global = jasmine.getGlobal();
-  global.jasmine = jasmine;
+    /**
+     * ## Require & Instantiate
+     *
+     * Require Jasmine's core files. Specifically, this requires and attaches all of Jasmine's code to the `jasmine` reference.
+     */
+    const jasmine = jasmineRequire.core(jasmineRequire),
+        global = jasmine.getGlobal()
+    global.jasmine = jasmine
 
-  /**
-   * Since this is being run in a browser and the results should populate to an HTML page, require the HTML-specific Jasmine code, injecting the same reference.
-   */
-  jasmineRequire.html(jasmine);
+    /**
+     * Since this is being run in a browser and the results should populate to an HTML page, require the HTML-specific Jasmine code, injecting the same reference.
+     */
+    jasmineRequire.html(jasmine)
 
-  /**
-   * Create the Jasmine environment. This is used to run all specs in a project.
-   */
-  const env = jasmine.getEnv();
+    /**
+     * Create the Jasmine environment. This is used to run all specs in a project.
+     */
+    const env = jasmine.getEnv()
 
-  /**
-   * ## The Global Interface
-   *
-   * Build up the functions that will be exposed as the Jasmine public interface. A project can customize, rename or alias any of these functions as desired, provided the implementation remains unchanged.
-   */
-  const jasmineInterface = jasmineRequire.interface(jasmine, env);
+    /**
+     * ## The Global Interface
+     *
+     * Build up the functions that will be exposed as the Jasmine public interface. A project can customize, rename or alias any of these functions as desired, provided the implementation remains unchanged.
+     */
+    const jasmineInterface = jasmineRequire.interface(jasmine, env)
 
-  /**
-   * Add all of the Jasmine global/public interface to the global scope, so a project can use the public interface directly. For example, calling `describe` in specs instead of `jasmine.getEnv().describe`.
-   */
-  for (const property in jasmineInterface) {
-    global[property] = jasmineInterface[property];
-  }
-})();
+    /**
+     * Add all of the Jasmine global/public interface to the global scope, so a project can use the public interface directly. For example, calling `describe` in specs instead of `jasmine.getEnv().describe`.
+     */
+    for (const property in jasmineInterface) {
+        global[property] = jasmineInterface[property]
+    }
+})()

ui/plugins/ui/jasmine/boot1.js

@@ -33,100 +33,98 @@ WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
  after `boot0.js` is loaded and before this file is loaded.
  */
 
-(function() {
-  const env = jasmine.getEnv();
+;(function() {
+    const env = jasmine.getEnv()
 
-  /**
-   * ## Runner Parameters
-   *
-   * More browser specific code - wrap the query string in an object and to allow for getting/setting parameters from the runner user interface.
-   */
+    /**
+     * ## Runner Parameters
+     *
+     * More browser specific code - wrap the query string in an object and to allow for getting/setting parameters from the runner user interface.
+     */
 
-  const queryString = new jasmine.QueryString({
-    getWindowLocation: function() {
-      return window.location;
+    const queryString = new jasmine.QueryString({
+        getWindowLocation: function() {
+            return window.location
+        },
+    })
+
+    const filterSpecs = !!queryString.getParam("spec")
+
+    const config = {
+        stopOnSpecFailure: queryString.getParam("stopOnSpecFailure"),
+        stopSpecOnExpectationFailure: queryString.getParam("stopSpecOnExpectationFailure"),
+        hideDisabled: queryString.getParam("hideDisabled"),
     }
-  });
 
-  const filterSpecs = !!queryString.getParam('spec');
+    const random = queryString.getParam("random")
 
-  const config = {
-    stopOnSpecFailure: queryString.getParam('stopOnSpecFailure'),
-    stopSpecOnExpectationFailure: queryString.getParam(
-      'stopSpecOnExpectationFailure'
-    ),
-    hideDisabled: queryString.getParam('hideDisabled')
-  };
-
-  const random = queryString.getParam('random');
-
-  if (random !== undefined && random !== '') {
-    config.random = random;
-  }
-
-  const seed = queryString.getParam('seed');
-  if (seed) {
-    config.seed = seed;
-  }
-
-  /**
-   * ## Reporters
-   * The `HtmlReporter` builds all of the HTML UI for the runner page. This reporter paints the dots, stars, and x's for specs, as well as all spec names and all failures (if any).
-   */
-  const htmlReporter = new jasmine.HtmlReporter({
-    env: env,
-    navigateWithNewParam: function(key, value) {
-      return queryString.navigateWithNewParam(key, value);
-    },
-    addToExistingQueryString: function(key, value) {
-      return queryString.fullStringWithNewParam(key, value);
-    },
-    getContainer: function() {
-      return document.body;
-    },
-    createElement: function() {
-      return document.createElement.apply(document, arguments);
-    },
-    createTextNode: function() {
-      return document.createTextNode.apply(document, arguments);
-    },
-    timer: new jasmine.Timer(),
-    filterSpecs: filterSpecs
-  });
-
-  /**
-   * The `jsApiReporter` also receives spec results, and is used by any environment that needs to extract the results  from JavaScript.
-   */
-  env.addReporter(jsApiReporter);
-  env.addReporter(htmlReporter);
-
-  /**
-   * Filter which specs will be run by matching the start of the full name against the `spec` query param.
-   */
-  const specFilter = new jasmine.HtmlSpecFilter({
-    filterString: function() {
-      return queryString.getParam('spec');
+    if (random !== undefined && random !== "") {
+        config.random = random
     }
-  });
 
-  config.specFilter = function(spec) {
-    return specFilter.matches(spec.getFullName());
-  };
-
-  env.configure(config);
-
-  /**
-   * ## Execution
-   *
-   * Replace the browser window's `onload`, ensure it's called, and then run all of the loaded specs. This includes initializing the `HtmlReporter` instance and then executing the loaded Jasmine environment. All of this will happen after all of the specs are loaded.
-   */
-  const currentWindowOnload = window.onload;
-
-  window.onload = function() {
-    if (currentWindowOnload) {
-      currentWindowOnload();
+    const seed = queryString.getParam("seed")
+    if (seed) {
+        config.seed = seed
     }
-    htmlReporter.initialize();
-    env.execute();
-  };
-})();
+
+    /**
+     * ## Reporters
+     * The `HtmlReporter` builds all of the HTML UI for the runner page. This reporter paints the dots, stars, and x's for specs, as well as all spec names and all failures (if any).
+     */
+    const htmlReporter = new jasmine.HtmlReporter({
+        env: env,
+        navigateWithNewParam: function(key, value) {
+            return queryString.navigateWithNewParam(key, value)
+        },
+        addToExistingQueryString: function(key, value) {
+            return queryString.fullStringWithNewParam(key, value)
+        },
+        getContainer: function() {
+            return document.body
+        },
+        createElement: function() {
+            return document.createElement.apply(document, arguments)
+        },
+        createTextNode: function() {
+            return document.createTextNode.apply(document, arguments)
+        },
+        timer: new jasmine.Timer(),
+        filterSpecs: filterSpecs,
+    })
+
+    /**
+     * The `jsApiReporter` also receives spec results, and is used by any environment that needs to extract the results  from JavaScript.
+     */
+    env.addReporter(jsApiReporter)
+    env.addReporter(htmlReporter)
+
+    /**
+     * Filter which specs will be run by matching the start of the full name against the `spec` query param.
+     */
+    const specFilter = new jasmine.HtmlSpecFilter({
+        filterString: function() {
+            return queryString.getParam("spec")
+        },
+    })
+
+    config.specFilter = function(spec) {
+        return specFilter.matches(spec.getFullName())
+    }
+
+    env.configure(config)
+
+    /**
+     * ## Execution
+     *
+     * Replace the browser window's `onload`, ensure it's called, and then run all of the loaded specs. This includes initializing the `HtmlReporter` instance and then executing the loaded Jasmine environment. All of this will happen after all of the specs are loaded.
+     */
+    const currentWindowOnload = window.onload
+
+    window.onload = function() {
+        if (currentWindowOnload) {
+            currentWindowOnload()
+        }
+        htmlReporter.initialize()
+        env.execute()
+    }
+})()

ui/plugins/ui/jasmineSpec.js

@@ -2,34 +2,34 @@
 
 const JASMINE_SESSION_ID = `jasmine-${String(Date.now()).slice(8)}`
 
-beforeEach(function () {
+beforeEach(function() {
     jasmine.DEFAULT_TIMEOUT_INTERVAL = 15 * 60 * 1000 // Test timeout after 15 minutes
     jasmine.addMatchers({
-        toBeOneOf: function () {
+        toBeOneOf: function() {
             return {
-                compare: function (actual, expected) {
+                compare: function(actual, expected) {
                     return {
-                        pass: expected.includes(actual)
+                        pass: expected.includes(actual),
                     }
-                }
+                },
             }
-        }
+        },
     })
 })
-describe('stable-diffusion-ui', function() {
+describe("stable-diffusion-ui", function() {
     beforeEach(function() {
-        expect(typeof SD).toBe('object')
-        expect(typeof SD.serverState).toBe('object')
-        expect(typeof SD.serverState.status).toBe('string')
+        expect(typeof SD).toBe("object")
+        expect(typeof SD.serverState).toBe("object")
+        expect(typeof SD.serverState.status).toBe("string")
     })
-    it('should be able to reach the backend', async function() {
+    it("should be able to reach the backend", async function() {
         expect(SD.serverState.status).toBe(SD.ServerStates.unavailable)
         SD.sessionId = JASMINE_SESSION_ID
         await SD.init()
         expect(SD.isServerAvailable()).toBeTrue()
     })
 
-    it('enfore the current task state', function() {
+    it("enfore the current task state", function() {
         const task = new SD.Task()
         expect(task.status).toBe(SD.TaskStatus.init)
         expect(task.isPending).toBeTrue()
@@ -65,149 +65,161 @@ describe('stable-diffusion-ui', function() {
             task._setStatus(SD.TaskStatus.completed)
         }).toThrowError()
     })
-    it('should be able to run tasks', async function() {
-        expect(typeof SD.Task.run).toBe('function')
+    it("should be able to run tasks", async function() {
+        expect(typeof SD.Task.run).toBe("function")
         const promiseGenerator = (function*(val) {
-            expect(val).toBe('start')
+            expect(val).toBe("start")
             expect(yield 1 + 1).toBe(4)
             expect(yield 2 + 2).toBe(8)
             yield asyncDelay(500)
             expect(yield 3 + 3).toBe(12)
             expect(yield 4 + 4).toBe(16)
             return 8 + 8
-        })('start')
-        const callback = function({value, done}) {
-            return {value: 2 * value, done}
+        })("start")
+        const callback = function({ value, done }) {
+            return { value: 2 * value, done }
         }
-        expect(await SD.Task.run(promiseGenerator, {callback})).toBe(32)
+        expect(await SD.Task.run(promiseGenerator, { callback })).toBe(32)
     })
-    it('should be able to queue tasks', async function() {
-        expect(typeof SD.Task.enqueue).toBe('function')
+    it("should be able to queue tasks", async function() {
+        expect(typeof SD.Task.enqueue).toBe("function")
         const promiseGenerator = (function*(val) {
-            expect(val).toBe('start')
+            expect(val).toBe("start")
             expect(yield 1 + 1).toBe(4)
             expect(yield 2 + 2).toBe(8)
             yield asyncDelay(500)
             expect(yield 3 + 3).toBe(12)
             expect(yield 4 + 4).toBe(16)
             return 8 + 8
-        })('start')
-        const callback = function({value, done}) {
-            return {value: 2 * value, done}
+        })("start")
+        const callback = function({ value, done }) {
+            return { value: 2 * value, done }
         }
-        const gen = SD.Task.asGenerator({generator: promiseGenerator, callback})
+        const gen = SD.Task.asGenerator({ generator: promiseGenerator, callback })
         expect(await SD.Task.enqueue(gen)).toBe(32)
     })
-    it('should be able to chain handlers', async function() {
-        expect(typeof SD.Task.enqueue).toBe('function')
+    it("should be able to chain handlers", async function() {
+        expect(typeof SD.Task.enqueue).toBe("function")
         const promiseGenerator = (function*(val) {
-            expect(val).toBe('start')
-            expect(yield {test: '1'}).toEqual({test: '1', foo: 'bar'})
+            expect(val).toBe("start")
+            expect(yield { test: "1" }).toEqual({ test: "1", foo: "bar" })
             expect(yield 2 + 2).toEqual(8)
             yield asyncDelay(500)
             expect(yield 3 + 3).toEqual(12)
-            expect(yield {test: 4}).toEqual({test: 8, foo: 'bar'})
-            return {test: 8}
-        })('start')
-        const gen1 = SD.Task.asGenerator({generator: promiseGenerator, callback: function({value, done}) {
-            if (typeof value === "object") {
-                value['foo'] = 'bar'
-            }
-            return {value, done}
-        }})
-        const gen2 = SD.Task.asGenerator({generator: gen1, callback: function({value, done}) {
-            if (typeof value === 'number') {
-                value = 2 * value
-            }
-            if (typeof value === 'object' && typeof value.test === 'number') {
-                value.test = 2 * value.test
-            }
-            return {value, done}
-        }})
-        expect(await SD.Task.enqueue(gen2)).toEqual({test:32, foo: 'bar'})
+            expect(yield { test: 4 }).toEqual({ test: 8, foo: "bar" })
+            return { test: 8 }
+        })("start")
+        const gen1 = SD.Task.asGenerator({
+            generator: promiseGenerator,
+            callback: function({ value, done }) {
+                if (typeof value === "object") {
+                    value["foo"] = "bar"
+                }
+                return { value, done }
+            },
+        })
+        const gen2 = SD.Task.asGenerator({
+            generator: gen1,
+            callback: function({ value, done }) {
+                if (typeof value === "number") {
+                    value = 2 * value
+                }
+                if (typeof value === "object" && typeof value.test === "number") {
+                    value.test = 2 * value.test
+                }
+                return { value, done }
+            },
+        })
+        expect(await SD.Task.enqueue(gen2)).toEqual({ test: 32, foo: "bar" })
     })
-    describe('ServiceContainer', function() {
-        it('should be able to register providers', function() {
+    describe("ServiceContainer", function() {
+        it("should be able to register providers", function() {
             const cont = new ServiceContainer(
                 function foo() {
-                    this.bar = ''
+                    this.bar = ""
                 },
                 function bar() {
                     return () => 0
                 },
-                { name: 'zero', definition: 0 },
-                { name: 'ctx', definition: () => Object.create(null), singleton: true },
-                { name: 'test',
+                { name: "zero", definition: 0 },
+                { name: "ctx", definition: () => Object.create(null), singleton: true },
+                {
+                    name: "test",
                     definition: (ctx, missing, one, foo) => {
-                        expect(ctx).toEqual({ran: true})
+                        expect(ctx).toEqual({ ran: true })
                         expect(one).toBe(1)
-                        expect(typeof foo).toBe('object')
+                        expect(typeof foo).toBe("object")
                         expect(foo.bar).toBeDefined()
-                        expect(typeof missing).toBe('undefined')
-                        return {foo: 'bar'}
-                    }, dependencies: ['ctx', 'missing', 'one', 'foo']
+                        expect(typeof missing).toBe("undefined")
+                        return { foo: "bar" }
+                    },
+                    dependencies: ["ctx", "missing", "one", "foo"],
                 }
             )
-            const fooObj = cont.get('foo')
-            expect(typeof fooObj).toBe('object')
+            const fooObj = cont.get("foo")
+            expect(typeof fooObj).toBe("object")
             fooObj.ran = true
 
-            const ctx = cont.get('ctx')
+            const ctx = cont.get("ctx")
             expect(ctx).toEqual({})
             ctx.ran = true
 
-            const bar = cont.get('bar')
-            expect(typeof bar).toBe('function')
+            const bar = cont.get("bar")
+            expect(typeof bar).toBe("function")
             expect(bar()).toBe(0)
 
-            cont.register({name: 'one', definition: 1})
-            const test = cont.get('test')
-            expect(typeof test).toBe('object')
-            expect(test.foo).toBe('bar')
+            cont.register({ name: "one", definition: 1 })
+            const test = cont.get("test")
+            expect(typeof test).toBe("object")
+            expect(test.foo).toBe("bar")
         })
     })
-    it('should be able to stream data in chunks', async function() {
+    it("should be able to stream data in chunks", async function() {
         expect(SD.isServerAvailable()).toBeTrue()
         const nbr_steps = 15
-        let res = await fetch('/render', {
-            method: 'POST',
+        let res = await fetch("/render", {
+            method: "POST",
             headers: {
-                'Content-Type': 'application/json'
+                "Content-Type": "application/json",
             },
             body: JSON.stringify({
-                "prompt": "a photograph of an astronaut riding a horse",
-                "negative_prompt": "",
-                "width": 128,
-                "height": 128,
-                "seed": Math.floor(Math.random() * 10000000),
+                prompt: "a photograph of an astronaut riding a horse",
+                negative_prompt: "",
+                width: 128,
+                height: 128,
+                seed: Math.floor(Math.random() * 10000000),
 
-                "sampler": "plms",
-                "use_stable_diffusion_model": "sd-v1-4",
-                "num_inference_steps": nbr_steps,
-                "guidance_scale": 7.5,
+                sampler: "plms",
+                use_stable_diffusion_model: "sd-v1-4",
+                num_inference_steps: nbr_steps,
+                guidance_scale: 7.5,
 
-                "numOutputsParallel": 1,
-                "stream_image_progress": true,
-                "show_only_filtered_image": true,
-                "output_format": "jpeg",
+                numOutputsParallel: 1,
+                stream_image_progress: true,
+                show_only_filtered_image: true,
+                output_format: "jpeg",
 
-                "session_id": JASMINE_SESSION_ID,
+                session_id: JASMINE_SESSION_ID,
             }),
         })
         expect(res.ok).toBeTruthy()
         const renderRequest = await res.json()
-        expect(typeof renderRequest.stream).toBe('string')
+        expect(typeof renderRequest.stream).toBe("string")
         expect(renderRequest.task).toBeDefined()
 
         // Wait for server status to update.
-        await SD.waitUntil(() => {
-            console.log('Waiting for %s to be received...', renderRequest.task)
-            return (!SD.serverState.tasks || SD.serverState.tasks[String(renderRequest.task)])
-        }, 250, 10 * 60 * 1000)
+        await SD.waitUntil(
+            () => {
+                console.log("Waiting for %s to be received...", renderRequest.task)
+                return !SD.serverState.tasks || SD.serverState.tasks[String(renderRequest.task)]
+            },
+            250,
+            10 * 60 * 1000
+        )
         // Wait for task to start on server.
         await SD.waitUntil(() => {
-            console.log('Waiting for %s to start...', renderRequest.task)
-            return !SD.serverState.tasks || SD.serverState.tasks[String(renderRequest.task)] !== 'pending'
+            console.log("Waiting for %s to start...", renderRequest.task)
+            return !SD.serverState.tasks || SD.serverState.tasks[String(renderRequest.task)] !== "pending"
         }, 250)
 
         const reader = new SD.ChunkedStreamReader(renderRequest.stream)
@@ -217,24 +229,24 @@ describe('stable-diffusion-ui', function() {
             if (!value || value.length <= 0) {
                 return
             }
-            return reader.readStreamAsJSON(value.join(''))
+            return reader.readStreamAsJSON(value.join(""))
         }
-        reader.onNext = function({done, value}) {
+        reader.onNext = function({ done, value }) {
             console.log(value)
-            if (typeof value === 'object' && 'status' in value) {
+            if (typeof value === "object" && "status" in value) {
                 done = true
             }
-            return {done, value}
+            return { done, value }
         }
         let lastUpdate = undefined
         let stepCount = 0
         let complete = false
         //for await (const stepUpdate of reader) {
         for await (const stepUpdate of reader.open()) {
-            console.log('ChunkedStreamReader received ', stepUpdate)
+            console.log("ChunkedStreamReader received ", stepUpdate)
             lastUpdate = stepUpdate
             if (complete) {
-                expect(stepUpdate.status).toBe('succeeded')
+                expect(stepUpdate.status).toBe("succeeded")
                 expect(stepUpdate.output).toHaveSize(1)
             } else {
                 expect(stepUpdate.total_steps).toBe(nbr_steps)
@@ -246,70 +258,76 @@ describe('stable-diffusion-ui', function() {
                 }
             }
         }
-        for(let i=1; i <= 5; ++i) {
+        for (let i = 1; i <= 5; ++i) {
             res = await fetch(renderRequest.stream)
             expect(res.ok).toBeTruthy()
             const cachedResponse = await res.json()
-            console.log('Cache test %s received %o', i, cachedResponse)
+            console.log("Cache test %s received %o", i, cachedResponse)
             expect(lastUpdate).toEqual(cachedResponse)
         }
     })
 
-    describe('should be able to make renders', function() {
+    describe("should be able to make renders", function() {
         beforeEach(function() {
             expect(SD.isServerAvailable()).toBeTrue()
         })
-        it('basic inline request', async function() {
+        it("basic inline request", async function() {
             let stepCount = 0
             let complete = false
-            const result = await SD.render({
-                "prompt": "a photograph of an astronaut riding a horse",
-                "width": 128,
-                "height": 128,
-                "num_inference_steps": 10,
-                "show_only_filtered_image": false,
-                //"use_face_correction": 'GFPGANv1.3',
-                "use_upscale": "RealESRGAN_x4plus",
-                "session_id": JASMINE_SESSION_ID,
-            }, function(event) {
-                console.log(this, event)
-                if ('update' in event) {
-                    const stepUpdate = event.update
-                    if (complete || (stepUpdate.status && stepUpdate.step === stepUpdate.total_steps)) {
-                        expect(stepUpdate.status).toBe('succeeded')
-                        expect(stepUpdate.output).toHaveSize(2)
-                    } else {
-                        expect(stepUpdate.step).toBe(stepCount)
-                        if (stepUpdate.step === stepUpdate.total_steps) {
-                            complete = true
+            const result = await SD.render(
+                {
+                    prompt: "a photograph of an astronaut riding a horse",
+                    width: 128,
+                    height: 128,
+                    num_inference_steps: 10,
+                    show_only_filtered_image: false,
+                    //"use_face_correction": 'GFPGANv1.3',
+                    use_upscale: "RealESRGAN_x4plus",
+                    session_id: JASMINE_SESSION_ID,
+                },
+                function(event) {
+                    console.log(this, event)
+                    if ("update" in event) {
+                        const stepUpdate = event.update
+                        if (complete || (stepUpdate.status && stepUpdate.step === stepUpdate.total_steps)) {
+                            expect(stepUpdate.status).toBe("succeeded")
+                            expect(stepUpdate.output).toHaveSize(2)
                         } else {
-                            stepCount++
+                            expect(stepUpdate.step).toBe(stepCount)
+                            if (stepUpdate.step === stepUpdate.total_steps) {
+                                complete = true
+                            } else {
+                                stepCount++
+                            }
                         }
                     }
                 }
-            })
+            )
             console.log(result)
-            expect(result.status).toBe('succeeded')
+            expect(result.status).toBe("succeeded")
             expect(result.output).toHaveSize(2)
         })
-        it('post and reader request', async function() {
+        it("post and reader request", async function() {
             const renderTask = new SD.RenderTask({
-                "prompt": "a photograph of an astronaut riding a horse",
-                "width": 128,
-                "height": 128,
-                "seed": SD.MAX_SEED_VALUE,
-                "num_inference_steps": 10,
-                "session_id": JASMINE_SESSION_ID,
+                prompt: "a photograph of an astronaut riding a horse",
+                width: 128,
+                height: 128,
+                seed: SD.MAX_SEED_VALUE,
+                num_inference_steps: 10,
+                session_id: JASMINE_SESSION_ID,
             })
             expect(renderTask.status).toBe(SD.TaskStatus.init)
 
             const timeout = -1
             const renderRequest = await renderTask.post(timeout)
-            expect(typeof renderRequest.stream).toBe('string')
+            expect(typeof renderRequest.stream).toBe("string")
             expect(renderTask.status).toBe(SD.TaskStatus.waiting)
             expect(renderTask.streamUrl).toBe(renderRequest.stream)
 
-            await renderTask.waitUntil({state: SD.TaskStatus.processing, callback: () => console.log('Waiting for render task to start...') })
+            await renderTask.waitUntil({
+                state: SD.TaskStatus.processing,
+                callback: () => console.log("Waiting for render task to start..."),
+            })
             expect(renderTask.status).toBe(SD.TaskStatus.processing)
 
             let stepCount = 0
@@ -318,7 +336,7 @@ describe('stable-diffusion-ui', function() {
             for await (const stepUpdate of renderTask.reader.open()) {
                 console.log(stepUpdate)
                 if (complete || (stepUpdate.status && stepUpdate.step === stepUpdate.total_steps)) {
-                    expect(stepUpdate.status).toBe('succeeded')
+                    expect(stepUpdate.status).toBe("succeeded")
                     expect(stepUpdate.output).toHaveSize(1)
                 } else {
                     expect(stepUpdate.step).toBe(stepCount)
@@ -330,28 +348,28 @@ describe('stable-diffusion-ui', function() {
                 }
             }
             expect(renderTask.status).toBe(SD.TaskStatus.completed)
-            expect(renderTask.result.status).toBe('succeeded')
+            expect(renderTask.result.status).toBe("succeeded")
             expect(renderTask.result.output).toHaveSize(1)
         })
-        it('queued request', async function() {
+        it("queued request", async function() {
             let stepCount = 0
             let complete = false
             const renderTask = new SD.RenderTask({
-                "prompt": "a photograph of an astronaut riding a horse",
-                "width": 128,
-                "height": 128,
-                "num_inference_steps": 10,
-                "show_only_filtered_image": false,
+                prompt: "a photograph of an astronaut riding a horse",
+                width: 128,
+                height: 128,
+                num_inference_steps: 10,
+                show_only_filtered_image: false,
                 //"use_face_correction": 'GFPGANv1.3',
-                "use_upscale": "RealESRGAN_x4plus",
-                "session_id": JASMINE_SESSION_ID,
+                use_upscale: "RealESRGAN_x4plus",
+                session_id: JASMINE_SESSION_ID,
             })
             await renderTask.enqueue(function(event) {
                 console.log(this, event)
-                if ('update' in event) {
+                if ("update" in event) {
                     const stepUpdate = event.update
                     if (complete || (stepUpdate.status && stepUpdate.step === stepUpdate.total_steps)) {
-                        expect(stepUpdate.status).toBe('succeeded')
+                        expect(stepUpdate.status).toBe("succeeded")
                         expect(stepUpdate.output).toHaveSize(2)
                     } else {
                         expect(stepUpdate.step).toBe(stepCount)
@@ -364,12 +382,12 @@ describe('stable-diffusion-ui', function() {
                 }
             })
             console.log(renderTask.result)
-            expect(renderTask.result.status).toBe('succeeded')
+            expect(renderTask.result.status).toBe("succeeded")
             expect(renderTask.result.output).toHaveSize(2)
         })
     })
-    describe('# Special cases', function() {
-        it('should throw an exception on set for invalid sessionId', function() {
+    describe("# Special cases", function() {
+        it("should throw an exception on set for invalid sessionId", function() {
             expect(function() {
                 SD.sessionId = undefined
             }).toThrowError("Can't set sessionId to undefined.")
@@ -386,16 +404,17 @@ if (!PLUGINS.SELFTEST) {
     PLUGINS.SELFTEST = {}
 }
 loadUIPlugins().then(function() {
-    console.log('loadCompleted', loadEvent)
-    describe('@Plugins', function() {
-        it('exposes hooks to overide', function() {
-            expect(typeof PLUGINS.IMAGE_INFO_BUTTONS).toBe('object')
-            expect(typeof PLUGINS.TASK_CREATE).toBe('object')
+    console.log("loadCompleted", loadEvent)
+    describe("@Plugins", function() {
+        it("exposes hooks to overide", function() {
+            expect(typeof PLUGINS.IMAGE_INFO_BUTTONS).toBe("object")
+            expect(typeof PLUGINS.TASK_CREATE).toBe("object")
         })
-        describe('supports selftests', function() { // Hook to allow plugins to define tests.
+        describe("supports selftests", function() {
+            // Hook to allow plugins to define tests.
             const pluginsTests = Object.keys(PLUGINS.SELFTEST).filter((key) => PLUGINS.SELFTEST.hasOwnProperty(key))
             if (!pluginsTests || pluginsTests.length <= 0) {
-                it('but nothing loaded...', function() {
+                it("but nothing loaded...", function() {
                     expect(true).toBeTruthy()
                 })
                 return

ui/plugins/ui/merge.plugin.js

@@ -0,0 +1,454 @@
+;(function() {
+    "use strict"
+
+    ///////////////////// Function section
+    function smoothstep(x) {
+        return x * x * (3 - 2 * x)
+    }
+
+    function smootherstep(x) {
+        return x * x * x * (x * (x * 6 - 15) + 10)
+    }
+
+    function smootheststep(x) {
+        let y = -20 * Math.pow(x, 7)
+        y += 70 * Math.pow(x, 6)
+        y -= 84 * Math.pow(x, 5)
+        y += 35 * Math.pow(x, 4)
+        return y
+    }
+    function getCurrentTime() {
+        const now = new Date()
+        let hours = now.getHours()
+        let minutes = now.getMinutes()
+        let seconds = now.getSeconds()
+
+        hours = hours < 10 ? `0${hours}` : hours
+        minutes = minutes < 10 ? `0${minutes}` : minutes
+        seconds = seconds < 10 ? `0${seconds}` : seconds
+
+        return `${hours}:${minutes}:${seconds}`
+    }
+
+    function addLogMessage(message) {
+        const logContainer = document.getElementById("merge-log")
+        logContainer.innerHTML += `<i>${getCurrentTime()}</i> ${message}<br>`
+
+        // Scroll to the bottom of the log
+        logContainer.scrollTop = logContainer.scrollHeight
+
+        document.querySelector("#merge-log-container").style.display = "block"
+    }
+
+    function addLogSeparator() {
+        const logContainer = document.getElementById("merge-log")
+        logContainer.innerHTML += "<hr>"
+
+        logContainer.scrollTop = logContainer.scrollHeight
+    }
+
+    function drawDiagram(fn) {
+        const SIZE = 300
+        const canvas = document.getElementById("merge-canvas")
+        canvas.height = canvas.width = SIZE
+        const ctx = canvas.getContext("2d")
+
+        // Draw coordinate system
+        ctx.scale(1, -1)
+        ctx.translate(0, -canvas.height)
+        ctx.lineWidth = 1
+        ctx.beginPath()
+
+        ctx.strokeStyle = "white"
+        ctx.moveTo(0, 0)
+        ctx.lineTo(0, SIZE)
+        ctx.lineTo(SIZE, SIZE)
+        ctx.lineTo(SIZE, 0)
+        ctx.lineTo(0, 0)
+        ctx.lineTo(SIZE, SIZE)
+        ctx.stroke()
+        ctx.beginPath()
+        ctx.setLineDash([1, 2])
+        const n = SIZE / 10
+        for (let i = n; i < SIZE; i += n) {
+            ctx.moveTo(0, i)
+            ctx.lineTo(SIZE, i)
+            ctx.moveTo(i, 0)
+            ctx.lineTo(i, SIZE)
+        }
+        ctx.stroke()
+        ctx.beginPath()
+        ctx.setLineDash([])
+        ctx.beginPath()
+        ctx.strokeStyle = "black"
+        ctx.lineWidth = 3
+        // Plot function
+        const numSamples = 20
+        for (let i = 0; i <= numSamples; i++) {
+            const x = i / numSamples
+            const y = fn(x)
+
+            const canvasX = x * SIZE
+            const canvasY = y * SIZE
+
+            if (i === 0) {
+                ctx.moveTo(canvasX, canvasY)
+            } else {
+                ctx.lineTo(canvasX, canvasY)
+            }
+        }
+        ctx.stroke()
+        // Plot alpha values (yellow boxes)
+        let start = parseFloat(document.querySelector("#merge-start").value)
+        let step = parseFloat(document.querySelector("#merge-step").value)
+        let iterations = document.querySelector("#merge-count").value >> 0
+        ctx.beginPath()
+        ctx.fillStyle = "yellow"
+        for (let i = 0; i < iterations; i++) {
+            const alpha = (start + i * step) / 100
+            const x = alpha * SIZE
+            const y = fn(alpha) * SIZE
+            if (x <= SIZE) {
+                ctx.rect(x - 3, y - 3, 6, 6)
+                ctx.fill()
+            } else {
+                ctx.strokeStyle = "red"
+                ctx.moveTo(0, 0)
+                ctx.lineTo(0, SIZE)
+                ctx.lineTo(SIZE, SIZE)
+                ctx.lineTo(SIZE, 0)
+                ctx.lineTo(0, 0)
+                ctx.lineTo(SIZE, SIZE)
+                ctx.stroke()
+                addLogMessage("<i>Warning: maximum ratio is &#8805; 100%</i>")
+            }
+        }
+    }
+
+    function updateChart() {
+        let fn = (x) => x
+        switch (document.querySelector("#merge-interpolation").value) {
+            case "SmoothStep":
+                fn = smoothstep
+                break
+            case "SmootherStep":
+                fn = smootherstep
+                break
+            case "SmoothestStep":
+                fn = smootheststep
+                break
+        }
+        drawDiagram(fn)
+    }
+    createTab({
+        id: "merge",
+        icon: "fa-code-merge",
+        label: "Merge models",
+        css: `
+        #tab-content-merge .tab-content-inner {
+            max-width: 100%;
+            padding: 10pt;
+        }
+        .merge-container {  
+            margin-left: 15%;
+            margin-right: 15%;
+            text-align: left;
+            display: inline-grid;
+            grid-template-columns: 1fr 1fr;
+            grid-template-rows: auto auto auto;
+            gap: 0px 0px;
+            grid-auto-flow: row;
+            grid-template-areas:
+              "merge-input merge-config"
+              "merge-buttons merge-buttons";
+        }
+        .merge-container p {
+            margin-top: 3pt;
+            margin-bottom: 3pt;
+        }
+        .merge-config .tab-content {
+            background: var(--background-color1);
+            border-radius: 3pt;
+        }
+        .merge-config .tab-content-inner {
+            text-align: left;
+        }
+
+        .merge-input { 
+            grid-area: merge-input; 
+            padding-left:1em;
+        }
+        .merge-config { 
+            grid-area: merge-config; 
+            padding:1em;
+        }
+        .merge-config input { 
+            margin-bottom: 3px; 
+        }
+        .merge-config select { 
+            margin-bottom: 3px; 
+        }
+        .merge-buttons { 
+            grid-area: merge-buttons; 
+            padding:1em; 
+            text-align: center;
+        }
+        #merge-button  { 
+            padding: 8px; 
+            width:20em; 
+        }
+        div#merge-log {
+            height:150px; 
+            overflow-x:hidden;
+            overflow-y:scroll;
+            background:var(--background-color1);
+            border-radius: 3pt;
+        }
+        div#merge-log i {
+            color: hsl(var(--accent-hue), 100%, calc(2*var(--accent-lightness))); 
+            font-family: monospace;
+        }
+        .disabled { 
+            background: var(--background-color4); 
+            color: var(--text-color); 
+        }
+        #merge-type-tabs {
+            border-bottom: 1px solid black;
+        }
+        #merge-log-container {
+            display: none;
+        }
+        .merge-container #merge-warning {
+            color: rgb(153, 153, 153);
+        }`,
+        content: `
+        <div class="merge-container panel-box">
+          <div class="merge-input">
+             <p><label for="#mergeModelA">Select Model A:</label></p>
+             <input id="mergeModelA" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
+             <p><label for="#mergeModelB">Select Model B:</label></p>
+             <input id="mergeModelB" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
+             <br/><br/>
+             <p id="merge-warning"><small><b>Important:</b> Please merge models of similar type.<br/>For e.g. <code>SD 1.4</code> models with only <code>SD 1.4/1.5</code> models,<br/><code>SD 2.0</code> with <code>SD 2.0</code>-type, and <code>SD 2.1</code> with <code>SD 2.1</code>-type models.</small></p>
+             <br/>
+             <table>
+                <tr>
+                    <td><label for="#merge-filename">Output file name:</label></td>
+                    <td><input id="merge-filename" size=24> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Base name of the output file.<br>Mix ratio and file suffix will be appended to this.</span></i></td>
+                </tr>
+                <tr>
+                    <td><label for="#merge-fp">Output precision:</label></td>
+                    <td><select id="merge-fp">
+                        <option value="fp16">fp16 (smaller file size)</option>
+                        <option value="fp32">fp32 (larger file size)</option>
+                    </select>
+                    <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Image generation uses fp16, so it's a good choice.<br>Use fp32 if you want to use the result models for more mixes</span></i>
+                    </td>
+                </tr>
+                <tr>
+                    <td><label for="#merge-format">Output file format:</label></td>
+                    <td><select id="merge-format">
+                        <option value="safetensors">Safetensors (recommended)</option>
+                        <option value="ckpt">CKPT/Pickle (legacy format)</option>
+                    </select>
+                    </td>
+                </tr>
+             </table>
+             <br/>
+             <div id="merge-log-container">
+                <p><label for="#merge-log">Log messages:</label></p>
+                <div id="merge-log"></div>
+             </div>
+          </div>
+          <div class="merge-config">
+             <div class="tab-container">
+                <span id="tab-merge-opts-single" class="tab active">
+                    <span>Make a single file</small></span>
+                </span>
+                <span id="tab-merge-opts-batch" class="tab">
+                    <span>Make multiple variations</small></span>
+                </span>
+             </div>
+             <div>
+                <div id="tab-content-merge-opts-single" class="tab-content active">
+                    <div class="tab-content-inner">
+                        <small>Saves a single merged model file, at the specified merge ratio.</small><br/><br/>
+                        <label for="#single-merge-ratio-slider">Merge ratio:</label>
+                        <input id="single-merge-ratio-slider" name="single-merge-ratio-slider" class="editor-slider" value="50" type="range" min="1" max="1000">
+                        <input id="single-merge-ratio" size=2 value="5">%
+                        <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Model A's contribution to the mix. The rest will be from Model B.</span></i>
+                    </div>
+                </div>
+                <div id="tab-content-merge-opts-batch" class="tab-content">
+                    <div class="tab-content-inner">
+                        <small>Saves multiple variations of the model, at different merge ratios.<br/>Each variation will be saved as a separate file.</small><br/><br/>
+                        <table>
+                            <tr><td><label for="#merge-count">Number of variations:</label></td>
+                                <td> <input id="merge-count" size=2 value="5"></td>
+                                <td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Number of models to create</span></i></td></tr>
+                            <tr><td><label for="#merge-start">Starting merge ratio:</label></td>
+                                <td> <input id="merge-start" size=2 value="5">%</td>
+                                <td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Smallest share of model A in the mix</span></i></td></tr>
+                            <tr><td><label for="#merge-step">Increment each step:</label></td>
+                                <td> <input id="merge-step" size=2 value="10">%</td>
+                                <td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Share of model A added into the mix per step</span></i></td></tr>
+                            <tr><td><label for="#merge-interpolation">Interpolation model:</label></td>
+                                <td> <select id="merge-interpolation">
+                                    <option>Exact</option>
+                                    <option>SmoothStep</option>
+                                    <option>SmootherStep</option>
+                                    <option>SmoothestStep</option>
+                                </select></td>
+                                <td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Sigmoid function to be applied to the model share before mixing</span></i></td></tr>
+                        </table>
+                        <br/>
+                        <small>Preview of variation ratios:</small><br/>
+                        <canvas id="merge-canvas" width="400" height="400"></canvas>
+                    </div>
+                </div>
+             </div>
+          </div>
+          <div class="merge-buttons">
+             <button id="merge-button" class="primaryButton">Merge models</button>
+          </div>
+        </div>`,
+        onOpen: ({ firstOpen }) => {
+            if (!firstOpen) {
+                return
+            }
+
+            const tabSettingsSingle = document.querySelector("#tab-merge-opts-single")
+            const tabSettingsBatch = document.querySelector("#tab-merge-opts-batch")
+            linkTabContents(tabSettingsSingle)
+            linkTabContents(tabSettingsBatch)
+
+            console.log("Activate")
+            let mergeModelAField = new ModelDropdown(document.querySelector("#mergeModelA"), "stable-diffusion")
+            let mergeModelBField = new ModelDropdown(document.querySelector("#mergeModelB"), "stable-diffusion")
+            updateChart()
+
+            // slider
+            const singleMergeRatioField = document.querySelector("#single-merge-ratio")
+            const singleMergeRatioSlider = document.querySelector("#single-merge-ratio-slider")
+
+            function updateSingleMergeRatio() {
+                singleMergeRatioField.value = singleMergeRatioSlider.value / 10
+                singleMergeRatioField.dispatchEvent(new Event("change"))
+            }
+
+            function updateSingleMergeRatioSlider() {
+                if (singleMergeRatioField.value < 0) {
+                    singleMergeRatioField.value = 0
+                } else if (singleMergeRatioField.value > 100) {
+                    singleMergeRatioField.value = 100
+                }
+
+                singleMergeRatioSlider.value = singleMergeRatioField.value * 10
+                singleMergeRatioSlider.dispatchEvent(new Event("change"))
+            }
+
+            singleMergeRatioSlider.addEventListener("input", updateSingleMergeRatio)
+            singleMergeRatioField.addEventListener("input", updateSingleMergeRatioSlider)
+            updateSingleMergeRatio()
+
+            document.querySelector(".merge-config").addEventListener("change", updateChart)
+
+            document.querySelector("#merge-button").addEventListener("click", async function(e) {
+                // Build request template
+                let model0 = mergeModelAField.value
+                let model1 = mergeModelBField.value
+                let request = { model0: model0, model1: model1 }
+                request["use_fp16"] = document.querySelector("#merge-fp").value == "fp16"
+                let iterations = document.querySelector("#merge-count").value >> 0
+                let start = parseFloat(document.querySelector("#merge-start").value)
+                let step = parseFloat(document.querySelector("#merge-step").value)
+
+                if (isTabActive(tabSettingsSingle)) {
+                    start = parseFloat(singleMergeRatioField.value)
+                    step = 0
+                    iterations = 1
+                    addLogMessage(`merge ratio = ${start}%`)
+                } else {
+                    addLogMessage(`start = ${start}%`)
+                    addLogMessage(`step  = ${step}%`)
+                }
+
+                if (start + (iterations - 1) * step >= 100) {
+                    addLogMessage("<i>Aborting: maximum ratio is &#8805; 100%</i>")
+                    addLogMessage("Reduce the number of variations or the step size")
+                    addLogSeparator()
+                    document.querySelector("#merge-count").focus()
+                    return
+                }
+
+                if (document.querySelector("#merge-filename").value == "") {
+                    addLogMessage("<i>Aborting: No output file name specified</i>")
+                    addLogSeparator()
+                    document.querySelector("#merge-filename").focus()
+                    return
+                }
+
+                // Disable merge button
+                e.target.disabled = true
+                e.target.classList.add("disabled")
+                let cursor = $("body").css("cursor")
+                let label = document.querySelector("#merge-button").innerHTML
+                $("body").css("cursor", "progress")
+                document.querySelector("#merge-button").innerHTML = "Merging models ..."
+
+                addLogMessage("Merging models")
+                addLogMessage("Model A: " + model0)
+                addLogMessage("Model B: " + model1)
+
+                // Batch main loop
+                for (let i = 0; i < iterations; i++) {
+                    let alpha = (start + i * step) / 100
+
+                    if (isTabActive(tabSettingsBatch)) {
+                        switch (document.querySelector("#merge-interpolation").value) {
+                            case "SmoothStep":
+                                alpha = smoothstep(alpha)
+                                break
+                            case "SmootherStep":
+                                alpha = smootherstep(alpha)
+                                break
+                            case "SmoothestStep":
+                                alpha = smootheststep(alpha)
+                                break
+                        }
+                    }
+                    addLogMessage(`merging batch job ${i + 1}/${iterations}, alpha = ${alpha.toFixed(5)}...`)
+
+                    request["out_path"] = document.querySelector("#merge-filename").value
+                    request["out_path"] += "-" + alpha.toFixed(5) + "." + document.querySelector("#merge-format").value
+                    addLogMessage(`&nbsp;&nbsp;filename: ${request["out_path"]}`)
+
+                    // sdkit documentation: "ratio - the ratio of the second model. 1 means only the second model will be used."
+                    request["ratio"] = 1-alpha 
+                    let res = await fetch("/model/merge", {
+                        method: "POST",
+                        headers: { "Content-Type": "application/json" },
+                        body: JSON.stringify(request),
+                    })
+                    const data = await res.json()
+                    addLogMessage(JSON.stringify(data))
+                }
+                addLogMessage(
+                    "<b>Done.</b> The models have been saved to your <tt>models/stable-diffusion</tt> folder."
+                )
+                addLogSeparator()
+                // Re-enable merge button
+                $("body").css("cursor", cursor)
+                document.querySelector("#merge-button").innerHTML = label
+                e.target.disabled = false
+                e.target.classList.remove("disabled")
+
+                // Update model list
+                stableDiffusionModelField.innerHTML = ""
+                vaeModelField.innerHTML = ""
+                hypernetworkModelField.innerHTML = ""
+                await getModels()
+            })
+        },
+    })
+})()

ui/plugins/ui/modifiers-toggle.plugin.js

@@ -1,52 +1,52 @@
-(function () {
+;(function() {
     "use strict"
 
-    var styleSheet = document.createElement("style");
+    var styleSheet = document.createElement("style")
     styleSheet.textContent = `
         .modifier-card-tiny.modifier-toggle-inactive {
             background: transparent;
             border: 2px dashed red;
             opacity:0.2;
         }
-    `;
-    document.head.appendChild(styleSheet);
+    `
+    document.head.appendChild(styleSheet)
 
     // observe for changes in tag list
-    var observer = new MutationObserver(function (mutations) {
-    //    mutations.forEach(function (mutation) {
-            if (editorModifierTagsList.childNodes.length > 0) {
-                ModifierToggle()
-            }
-    //    })
+    var observer = new MutationObserver(function(mutations) {
+        //    mutations.forEach(function (mutation) {
+        if (editorModifierTagsList.childNodes.length > 0) {
+            ModifierToggle()
+        }
+        //    })
     })
 
     observer.observe(editorModifierTagsList, {
-            childList: true
+        childList: true,
     })
 
     function ModifierToggle() {
-        let overlays = document.querySelector('#editor-inputs-tags-list').querySelectorAll('.modifier-card-overlay')
-        overlays.forEach (i => {
+        let overlays = document.querySelector("#editor-inputs-tags-list").querySelectorAll(".modifier-card-overlay")
+        overlays.forEach((i) => {
             i.oncontextmenu = (e) => {
                 e.preventDefault()
 
-                if (i.parentElement.classList.contains('modifier-toggle-inactive')) {
-                    i.parentElement.classList.remove('modifier-toggle-inactive')
-                }
-                else
-                {
-                    i.parentElement.classList.add('modifier-toggle-inactive')
+                if (i.parentElement.classList.contains("modifier-toggle-inactive")) {
+                    i.parentElement.classList.remove("modifier-toggle-inactive")
+                } else {
+                    i.parentElement.classList.add("modifier-toggle-inactive")
                 }
                 // refresh activeTags
-                let modifierName = i.parentElement.getElementsByClassName('modifier-card-label')[0].getElementsByTagName("p")[0].innerText
-                activeTags = activeTags.map(obj => {
-                    if (obj.name === modifierName) {
-                        return {...obj, inactive: (obj.element.classList.contains('modifier-toggle-inactive'))};
+                let modifierName = i.parentElement
+                    .getElementsByClassName("modifier-card-label")[0]
+                    .getElementsByTagName("p")[0].dataset.fullName
+                activeTags = activeTags.map((obj) => {
+                    if (trimModifiers(obj.name) === trimModifiers(modifierName)) {
+                        return { ...obj, inactive: obj.element.classList.contains("modifier-toggle-inactive") }
                     }
-                    
-                    return obj;
-                });
-                console.log(activeTags)
+
+                    return obj
+                })
+                document.dispatchEvent(new Event("refreshImageModifiers"))
             }
         })
     }

ui/plugins/ui/release-notes.plugin.js

@@ -1,64 +1,53 @@
-(function() {
+;(function() {
     // Register selftests when loaded by jasmine.
-    if (typeof PLUGINS?.SELFTEST === 'object') {
+    if (typeof PLUGINS?.SELFTEST === "object") {
         PLUGINS.SELFTEST["release-notes"] = function() {
-            it('should be able to fetch CHANGES.md', async function() {
-                let releaseNotes = await fetch(`https://raw.githubusercontent.com/cmdr2/stable-diffusion-ui/main/CHANGES.md`)
+            it("should be able to fetch CHANGES.md", async function() {
+                let releaseNotes = await fetch(
+                    `https://raw.githubusercontent.com/cmdr2/stable-diffusion-ui/main/CHANGES.md`
+                )
                 expect(releaseNotes.status).toBe(200)
             })
         }
     }
 
-    document.querySelector('#tab-container')?.insertAdjacentHTML('beforeend', `
-        <span id="tab-news" class="tab">
-            <span><i class="fa fa-bolt icon"></i> What's new?</span>
-        </span>
-    `)
-
-    document.querySelector('#tab-content-wrapper')?.insertAdjacentHTML('beforeend', `
-        <div id="tab-content-news" class="tab-content">
-            <div id="news" class="tab-content-inner">
-                Loading..
-            </div>
-        </div>
-    `)
-
-    const tabNews = document.querySelector('#tab-news')
-    if (tabNews) {
-        linkTabContents(tabNews)
-    }
-    const news = document.querySelector('#news')
-    if (!news) {
-        // news tab not found, dont exec plugin code.
-        return
-    }
-
-    document.querySelector('body').insertAdjacentHTML('beforeend', `
-        <style>
+    createTab({
+        id: "news",
+        icon: "fa-bolt",
+        label: "What's new",
+        css: `
         #tab-content-news .tab-content-inner {
             max-width: 100%;
             text-align: left;
             padding: 10pt;
         }
-        </style>
-    `)
+        `,
+        onOpen: async ({ firstOpen }) => {
+            if (firstOpen) {
+                const loadMarkedScriptPromise = loadScript("/media/js/marked.min.js")
 
-    loadScript('/media/js/marked.min.js').then(async function() {
-        let appConfig = await fetch('/get/app_config')
-        if (!appConfig.ok) {
-            console.error('[release-notes] Failed to get app_config.')
-            return
-        }
-        appConfig = await appConfig.json()
+                let appConfig = await fetch("/get/app_config")
+                if (!appConfig.ok) {
+                    console.error("[release-notes] Failed to get app_config.")
+                    return
+                }
+                appConfig = await appConfig.json()
 
-        const updateBranch = appConfig.update_branch || 'main'
+                const updateBranch = appConfig.update_branch || "main"
 
-        let releaseNotes = await fetch(`https://raw.githubusercontent.com/cmdr2/stable-diffusion-ui/${updateBranch}/CHANGES.md`)
-        if (!releaseNotes.ok) {
-            console.error('[release-notes] Failed to get CHANGES.md.')
-            return
-        }
-        releaseNotes = await releaseNotes.text()
-        news.innerHTML = marked.parse(releaseNotes)
+                let releaseNotes = await fetch(
+                    `https://raw.githubusercontent.com/cmdr2/stable-diffusion-ui/${updateBranch}/CHANGES.md`
+                )
+                if (!releaseNotes.ok) {
+                    console.error("[release-notes] Failed to get CHANGES.md.")
+                    return
+                }
+                releaseNotes = await releaseNotes.text()
+
+                await loadMarkedScriptPromise
+
+                return marked.parse(releaseNotes)
+            }
+        },
     })
-})()
+})()

ui/plugins/ui/selftest.plugin_.js

@@ -1,6 +1,7 @@
 /* SD-UI Selftest Plugin.js
  */
-(function() { "use strict"
+;(function() {
+    "use strict"
     const ID_PREFIX = "selftest-plugin"
 
     const links = document.getElementById("community-links")
@@ -10,16 +11,18 @@
     }
 
     // Add link to Jasmine SpecRunner
-    const pluginLink = document.createElement('li')
+    const pluginLink = document.createElement("li")
     const options = {
-        'stopSpecOnExpectationFailure': "true",
-        'stopOnSpecFailure': 'false',
-        'random': 'false',
-        'hideDisabled': 'false'
+        stopSpecOnExpectationFailure: "true",
+        stopOnSpecFailure: "false",
+        random: "false",
+        hideDisabled: "false",
     }
-    const optStr = Object.entries(options).map(([key, val]) => `${key}=${val}`).join('&')
+    const optStr = Object.entries(options)
+        .map(([key, val]) => `${key}=${val}`)
+        .join("&")
     pluginLink.innerHTML = `<a id="${ID_PREFIX}-starttest" href="${location.protocol}/plugins/core/SpecRunner.html?${optStr}" target="_blank"><i class="fa-solid fa-vial-circle-check"></i> Start SelfTest</a>`
     links.appendChild(pluginLink)
 
-    console.log('%s loaded!', ID_PREFIX)
+    console.log("%s loaded!", ID_PREFIX)
 })()

ui/plugins/ui/tiled-image-download.plugin.js

@@ -0,0 +1,326 @@
+;(function(){
+    "use strict";
+    const PAPERSIZE = [
+        {id: "a3p",  width: 297, height: 420, unit: "mm"},
+        {id: "a3l",  width: 420, height: 297, unit: "mm"},
+        {id: "a4p",  width: 210, height: 297, unit: "mm"},
+        {id: "a4l",  width: 297, height: 210, unit: "mm"},
+        {id: "ll", width: 279, height: 216, unit: "mm"},
+        {id: "lp",  width: 216, height: 279, unit: "mm"},
+        {id: "hd", width: 1920, height: 1080, unit: "pixels"},
+        {id: "4k", width: 3840, height: 2160, unit: "pixels"},
+    ]
+
+    // ---- Register plugin
+    PLUGINS['IMAGE_INFO_BUTTONS'].push({ 
+        html: '<i class="fa-solid fa-table-cells-large"></i> Download tiled image',
+        on_click: onDownloadTiledImage,
+        filter: (req, img) => req.tiling != "none",
+    })
+
+    var thisImage
+
+    function onDownloadTiledImage(req, img) {
+        document.getElementById("download-tiled-image-dialog").showModal()
+        thisImage = new Image()
+        thisImage.src = img.src
+        thisImage.dataset["prompt"] = img.dataset["prompt"]
+    }
+
+    // ---- Add HTML
+    document.getElementById('container').lastElementChild.insertAdjacentHTML("afterend",
+        `<dialog id="download-tiled-image-dialog">
+            <h1>Download tiled image</h1>
+            <div class="download-tiled-image dtim-container">
+                <div class="download-tiled-image-top">
+                    <div class="tab-container">
+                       <span id="tab-image-tiles" class="tab active">
+                           <span>Number of tiles</small></span>
+                       </span>
+                       <span id="tab-image-size" class="tab">
+                           <span>Image dimensions</span>
+                       </span>
+                    </div>
+                    <div>
+                        <div id="tab-content-image-tiles" class="tab-content active">
+                            <div class="tab-content-inner">
+                                <label for="dtim1-width">Width:</label> <input id="dtim1-width" min="1" max="99" type="number" value="2">
+                                <label for="dtim1-height">Height:</label> <input id="dtim1-height" min="1" max="99" type="number" value="2">
+                            </div>
+                        </div>
+                        <div id="tab-content-image-size" class="tab-content">
+                            <div class="tab-content-inner">
+                                <div class="method-2-options">
+                                    <label for="dtim2-width">Width:</label> <input id="dtim2-width" size="3" value="1920">
+                                    <label for="dtim2-height">Height:</label> <input id="dtim2-height" size="3" value="1080">
+                                    <select id="dtim2-unit">
+                                        <option>pixels</option>
+                                        <option>mm</option>
+                                        <option>inches</option>
+                                    </select>
+                                </div>
+                                <div class="method-2-dpi">
+                                    <label for="dtim2-dpi">DPI:</label> <input id="dtim2-dpi" size="3" value="72">
+                                </div>
+                                <div class="method-2-paper">
+                                    <i>Some standard sizes:</i><br>
+                                    <button id="dtim2-a3p">A3 portrait</button><button id="dtim2-a3l">A3 landscape</button><br>
+                                    <button id="dtim2-a4p">A4 portrait</button><button id="dtim2-a4l">A4 landscape</button><br>
+                                    <button id="dtim2-lp">Letter portrait</button><button id="dtim2-ll">Letter landscape</button><br>
+                                    <button id="dtim2-hd">Full HD</button><button id="dtim2-4k">4K</button>
+                                </div>
+                            </div>
+                        </div>
+                    </div>
+                </div>
+                <div class="download-tiled-image-placement">
+                    <div class="tab-container">
+                        <span id="tab-image-placement" class="tab active">
+                            <span>Tile placement</span>
+                        </span>
+                    </div>
+                    <div>
+                        <div id="tab-content-image-placement" class="tab-content active">
+                            <div class="tab-content-inner">
+                                <img id="dtim-1tl" class="active" src="data:image/png;base64,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" />
+                                <img id="dtim-1tr" src="data:image/png;base64,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" /><br>
+                                <img id="dtim-1bl" src="data:image/png;base64,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" />
+                                <img id="dtim-1br" src="data:image/png;base64,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" /> <br>
+                                <img id="dtim-1center" src="data:image/png;base64,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" />
+                                <img id="dtim-4center" src="data:image/png;base64,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" /> <br>
+                            </div>
+                        </div>
+                    </div>
+                </div>
+                <div class="dtim-ok">
+                    <button class="primaryButton" id="dti-ok">Download</button>
+                </div>
+                <div class="dtim-newtab">
+                    <button class="primaryButton" id="dti-newtab">Open in new tab</button>
+                </div>
+                <div class="dtim-cancel">
+                    <button class="primaryButton" id="dti-cancel">Cancel</button>
+                </div>
+            </div>
+         </dialog>`)
+
+    let downloadTiledImageDialog = document.getElementById("download-tiled-image-dialog")
+    let dtim1_width = document.getElementById("dtim1-width")
+    let dtim1_height = document.getElementById("dtim1-height")
+    let dtim2_width = document.getElementById("dtim2-width")
+    let dtim2_height = document.getElementById("dtim2-height")
+    let dtim2_unit = document.getElementById("dtim2-unit")
+    let dtim2_dpi = document.getElementById("dtim2-dpi")
+    let tabTiledTilesOptions = document.getElementById("tab-image-tiles")
+    let tabTiledSizeOptions = document.getElementById("tab-image-size")
+
+    linkTabContents(tabTiledTilesOptions)
+    linkTabContents(tabTiledSizeOptions)
+
+    prettifyInputs(downloadTiledImageDialog)
+
+    // ---- Predefined image dimensions
+    PAPERSIZE.forEach( function(p) {
+        document.getElementById("dtim2-" + p.id).addEventListener("click", (e) => {
+            dtim2_unit.value = p.unit
+            dtim2_width.value = p.width
+            dtim2_height.value = p.height
+        })
+    })
+
+    // ---- Close popup
+    document.getElementById("dti-cancel").addEventListener("click", (e) => downloadTiledImageDialog.close())
+    downloadTiledImageDialog.addEventListener('click', function (event) {
+        var rect = downloadTiledImageDialog.getBoundingClientRect();
+        var isInDialog=(rect.top <= event.clientY && event.clientY <= rect.top + rect.height
+          && rect.left <= event.clientX && event.clientX <= rect.left + rect.width);
+        if (!isInDialog) {
+            downloadTiledImageDialog.close();
+        }
+    });
+
+    // ---- Stylesheet
+    const styleSheet = document.createElement("style")
+    styleSheet.textContent = `
+        dialog {
+          background: var(--background-color2);
+          color: var(--text-color);
+          border-radius: 7px;
+          border: 1px solid var(--background-color3);
+        }
+
+        dialog::backdrop {
+          background: rgba(0, 0, 0, 0.5);
+        }
+
+
+        button[disabled] {
+          opacity: 0.5;
+        }
+
+        .method-2-dpi {
+          margin-top: 1em;
+          margin-bottom: 1em;
+        }
+
+        .method-2-paper button {
+          width: 10em;
+          padding: 4px;
+          margin: 4px;
+        }
+        
+        .download-tiled-image .tab-content {
+          background: var(--background-color1);
+          border-radius: 3pt;
+        }
+
+        .dtim-container {  display: grid;
+          grid-template-columns: auto auto;
+          grid-template-rows: auto auto;
+          gap: 1em 0px;
+          grid-auto-flow: row;
+          grid-template-areas:
+            "dtim-tab dtim-tab dtim-plc"
+            "dtim-ok dtim-newtab dtim-cancel";
+        }
+
+        .download-tiled-image-top {
+          justify-self: center;
+          grid-area: dtim-tab;
+        }
+
+        .download-tiled-image-placement {
+          justify-self: center;
+          grid-area: dtim-plc;
+          margin-left: 1em;
+        }
+
+        .dtim-ok {
+          justify-self: center;
+          align-self: start;
+          grid-area: dtim-ok;
+        }
+
+        .dtim-newtab {
+          justify-self: center;
+          align-self: start;
+          grid-area: dtim-newtab;
+        }
+
+        .dtim-cancel {
+          justify-self: center;
+          align-self: start;
+          grid-area: dtim-cancel;
+        }
+
+        #tab-content-image-placement img {
+          margin: 4px;
+          opacity: 0.3;
+          border: solid 2px var(--background-color1);
+        }
+
+        #tab-content-image-placement img:hover {
+          margin: 4px;
+          opacity: 1;
+          border: solid 2px var(--accent-color);
+          filter: brightness(2);
+        }
+
+        #tab-content-image-placement img.active {
+          margin: 4px;
+          opacity: 1;
+          border: solid 2px var(--background-color1);
+        }
+
+    `
+    document.head.appendChild(styleSheet)
+
+    // ---- Placement widget
+
+    function updatePlacementWidget(event) {
+        document.querySelector("#tab-content-image-placement img.active").classList.remove("active")
+        event.target.classList.add("active")
+    }
+
+    document.querySelectorAll("#tab-content-image-placement img").forEach(
+        (i) => i.addEventListener("click", updatePlacementWidget)
+    )
+
+    function getPlacement() {
+        return document.querySelector("#tab-content-image-placement img.active").id.substr(5)
+    }
+        
+    // ---- Make the image
+    function downloadTiledImage(image, width, height, offsetX=0, offsetY=0, new_tab=false) {
+
+        const canvas = document.createElement('canvas')
+        canvas.width = width
+        canvas.height = height
+        const context = canvas.getContext('2d')
+
+        const w = image.width
+        const h = image.height
+
+        for (var x = offsetX; x < width; x += w) {
+            for (var y = offsetY; y < height; y += h) {
+                context.drawImage(image, x, y, w, h)
+            }
+        }
+        if (new_tab) {
+            var newTab = window.open("")
+            newTab.document.write(`<html><head><title>${width}×${height}, "${image.dataset["prompt"]}"</title></head><body><img src="${canvas.toDataURL()}"></body></html>`)
+        } else {
+            const link = document.createElement('a')
+            link.href = canvas.toDataURL()
+            link.download = image.dataset["prompt"].replace(/[^a-zA-Z0-9]+/g, "-").substr(0,22)+crypto.randomUUID()+".png"
+            link.click()
+        }
+    }
+
+    function onDownloadTiledImageClick(e, newtab=false) {
+        var width, height, offsetX, offsetY
+
+        if (isTabActive(tabTiledTilesOptions)) {
+            width = thisImage.width * dtim1_width.value
+            height = thisImage.height * dtim1_height.value
+        } else {
+            if ( dtim2_unit.value == "pixels" ) {
+                width = dtim2_width.value
+                height= dtim2_height.value
+            } else if ( dtim2_unit.value == "mm" ) {
+                width = Math.floor( dtim2_width.value * dtim2_dpi.value / 25.4 )
+                height = Math.floor( dtim2_height.value * dtim2_dpi.value / 25.4 )
+            } else { // inch
+                width = Math.floor( dtim2_width.value * dtim2_dpi.value )
+                height = Math.floor( dtim2_height.value * dtim2_dpi.value )
+            }
+        }
+
+        var placement = getPlacement()
+        if (placement == "1tl") {
+            offsetX = 0
+            offsetY = 0
+        } else if (placement == "1tr") {
+            offsetX = width - thisImage.width * Math.ceil( width / thisImage.width )
+            offsetY = 0
+        } else if (placement == "1bl") {
+            offsetX = 0
+            offsetY = height - thisImage.height * Math.ceil( height / thisImage.height )
+        } else if (placement == "1br") {
+            offsetX = width - thisImage.width * Math.ceil( width / thisImage.width )
+            offsetY = height - thisImage.height * Math.ceil( height / thisImage.height )
+        } else if (placement == "4center") {
+            offsetX = width/2 - thisImage.width * Math.ceil( width/2 / thisImage.width )
+            offsetY = height/2 - thisImage.height * Math.ceil( height/2 / thisImage.height )
+        } else if (placement == "1center") {
+            offsetX = width/2 - thisImage.width/2 - thisImage.width * Math.ceil( (width/2 - thisImage.width/2) / thisImage.width )
+            offsetY = height/2 - thisImage.height/2 - thisImage.height * Math.ceil( (height/2 - thisImage.height/2) / thisImage.height )
+        }
+        downloadTiledImage(thisImage, width, height, offsetX, offsetY, newtab)
+        downloadTiledImageDialog.close()
+    }
+
+    document.getElementById("dti-ok").addEventListener("click", onDownloadTiledImageClick)
+    document.getElementById("dti-newtab").addEventListener("click", (e) => onDownloadTiledImageClick(e,true))
+
+})()

ui/sd_internal/__init__.py

@@ -1,119 +0,0 @@
-import json
-
-class Request:
-    request_id: str = None
-    session_id: str = "session"
-    prompt: str = ""
-    negative_prompt: str = ""
-    init_image: str = None # base64
-    mask: str = None # base64
-    num_outputs: int = 1
-    num_inference_steps: int = 50
-    guidance_scale: float = 7.5
-    width: int = 512
-    height: int = 512
-    seed: int = 42
-    prompt_strength: float = 0.8
-    sampler: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
-    # allow_nsfw: bool = False
-    precision: str = "autocast" # or "full"
-    save_to_disk_path: str = None
-    turbo: bool = True
-    use_full_precision: bool = False
-    use_face_correction: str = None # or "GFPGANv1.3"
-    use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
-    use_stable_diffusion_model: str = "sd-v1-4"
-    use_vae_model: str = None
-    use_hypernetwork_model: str = None
-    hypernetwork_strength: float = 1
-    show_only_filtered_image: bool = False
-    output_format: str = "jpeg" # or "png"
-    output_quality: int = 75
-
-    stream_progress_updates: bool = False
-    stream_image_progress: bool = False
-
-    def json(self):
-        return {
-            "session_id": self.session_id,
-            "prompt": self.prompt,
-            "negative_prompt": self.negative_prompt,
-            "num_outputs": self.num_outputs,
-            "num_inference_steps": self.num_inference_steps,
-            "guidance_scale": self.guidance_scale,
-            "hypernetwork_strengtgh": self.guidance_scale,
-            "width": self.width,
-            "height": self.height,
-            "seed": self.seed,
-            "prompt_strength": self.prompt_strength,
-            "sampler": self.sampler,
-            "use_face_correction": self.use_face_correction,
-            "use_upscale": self.use_upscale,
-            "use_stable_diffusion_model": self.use_stable_diffusion_model,
-            "use_vae_model": self.use_vae_model,
-            "use_hypernetwork_model": self.use_hypernetwork_model,
-            "hypernetwork_strength": self.hypernetwork_strength,
-            "output_format": self.output_format,
-            "output_quality": self.output_quality,
-        }
-
-    def __str__(self):
-        return f'''
-    session_id: {self.session_id}
-    prompt: {self.prompt}
-    negative_prompt: {self.negative_prompt}
-    seed: {self.seed}
-    num_inference_steps: {self.num_inference_steps}
-    sampler: {self.sampler}
-    guidance_scale: {self.guidance_scale}
-    w: {self.width}
-    h: {self.height}
-    precision: {self.precision}
-    save_to_disk_path: {self.save_to_disk_path}
-    turbo: {self.turbo}
-    use_full_precision: {self.use_full_precision}
-    use_face_correction: {self.use_face_correction}
-    use_upscale: {self.use_upscale}
-    use_stable_diffusion_model: {self.use_stable_diffusion_model}
-    use_vae_model: {self.use_vae_model}
-    use_hypernetwork_model: {self.use_hypernetwork_model}
-    hypernetwork_strength: {self.hypernetwork_strength}
-    show_only_filtered_image: {self.show_only_filtered_image}
-    output_format: {self.output_format}
-    output_quality: {self.output_quality}
-
-    stream_progress_updates: {self.stream_progress_updates}
-    stream_image_progress: {self.stream_image_progress}'''
-
-class Image:
-    data: str # base64
-    seed: int
-    is_nsfw: bool
-    path_abs: str = None
-
-    def __init__(self, data, seed):
-        self.data = data
-        self.seed = seed
-
-    def json(self):
-        return {
-            "data": self.data,
-            "seed": self.seed,
-            "path_abs": self.path_abs,
-        }
-
-class Response:
-    request: Request
-    images: list
-
-    def json(self):
-        res = {
-            "status": 'succeeded',
-            "request": self.request.json(),
-            "output": [],
-        }
-
-        for image in self.images:
-            res["output"].append(image.json())
-
-        return res

ui/sd_internal/ddim_callback.patch

@@ -1,162 +0,0 @@
-diff --git a/optimizedSD/ddpm.py b/optimizedSD/ddpm.py
-index 79058bc..a473411 100644
---- a/optimizedSD/ddpm.py
-+++ b/optimizedSD/ddpm.py
-@@ -564,12 +564,12 @@ class UNet(DDPM):
-                                         unconditional_guidance_scale=unconditional_guidance_scale,
-                                         callback=callback, img_callback=img_callback)
- 
-+        yield from samples
-+
-         if(self.turbo):
-             self.model1.to("cpu")
-             self.model2.to("cpu")
- 
--        return samples
--
-     @torch.no_grad()
-     def plms_sampling(self, cond,b, img,
-                       ddim_use_original_steps=False,
-@@ -608,10 +608,10 @@ class UNet(DDPM):
-             old_eps.append(e_t)
-             if len(old_eps) >= 4:
-                 old_eps.pop(0)
--            if callback: callback(i)
--            if img_callback: img_callback(pred_x0, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(pred_x0, i)
- 
--        return img
-+        yield from img_callback(img, len(iterator)-1)
- 
-     @torch.no_grad()
-     def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,
-@@ -740,13 +740,13 @@ class UNet(DDPM):
-                                           unconditional_guidance_scale=unconditional_guidance_scale,
-                                           unconditional_conditioning=unconditional_conditioning)
- 
--            if callback: callback(i)
--            if img_callback: img_callback(x_dec, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x_dec, i)
-         
-         if mask is not None:
--            return x0 * mask + (1. - mask) * x_dec
-+            x_dec = x0 * mask + (1. - mask) * x_dec
- 
--        return x_dec
-+        yield from img_callback(x_dec, len(iterator)-1)
- 
- 
-     @torch.no_grad()
-@@ -820,12 +820,12 @@ class UNet(DDPM):
- 
- 
-             d = to_d(x, sigma_hat, denoised)
--            if callback: callback(i)
--            if img_callback: img_callback(x, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x, i)
-             dt = sigmas[i + 1] - sigma_hat
-             # Euler method
-             x = x + d * dt
--        return x
-+        yield from img_callback(x, len(sigmas)-1)
- 
-     @torch.no_grad()
-     def euler_ancestral_sampling(self,ac,x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1,extra_args=None, callback=None, disable=None, img_callback=None):
-@@ -852,14 +852,14 @@ class UNet(DDPM):
-             denoised = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
- 
-             sigma_down, sigma_up = get_ancestral_step(sigmas[i], sigmas[i + 1])
--            if callback: callback(i)
--            if img_callback: img_callback(x, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x, i)
-             d = to_d(x, sigmas[i], denoised)
-             # Euler method
-             dt = sigma_down - sigmas[i]
-             x = x + d * dt
-             x = x + torch.randn_like(x) * sigma_up
--        return x
-+        yield from img_callback(x, len(sigmas)-1)
- 
- 
- 
-@@ -892,8 +892,8 @@ class UNet(DDPM):
-             denoised = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
- 
-             d = to_d(x, sigma_hat, denoised)
--            if callback: callback(i)
--            if img_callback: img_callback(x, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x, i)
-             dt = sigmas[i + 1] - sigma_hat
-             if sigmas[i + 1] == 0:
-                 # Euler method
-@@ -913,7 +913,7 @@ class UNet(DDPM):
-                 d_2 = to_d(x_2, sigmas[i + 1], denoised_2)
-                 d_prime = (d + d_2) / 2
-                 x = x + d_prime * dt
--        return x
-+        yield from img_callback(x, len(sigmas)-1)
- 
- 
-     @torch.no_grad()
-@@ -944,8 +944,8 @@ class UNet(DDPM):
-             e_t_uncond, e_t = (x_in  + eps * c_out).chunk(2)
-             denoised = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
- 
--            if callback: callback(i)
--            if img_callback: img_callback(x, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x, i)
-             
-             d = to_d(x, sigma_hat, denoised)
-             # Midpoint method, where the midpoint is chosen according to a rho=3 Karras schedule
-@@ -966,7 +966,7 @@ class UNet(DDPM):
- 
-             d_2 = to_d(x_2, sigma_mid, denoised_2)
-             x = x + d_2 * dt_2
--        return x
-+        yield from img_callback(x, len(sigmas)-1)
- 
- 
-     @torch.no_grad()
-@@ -994,8 +994,8 @@ class UNet(DDPM):
- 
- 
-             sigma_down, sigma_up = get_ancestral_step(sigmas[i], sigmas[i + 1])
--            if callback: callback(i)
--            if img_callback: img_callback(x, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x, i)
-             d = to_d(x, sigmas[i], denoised)
-             # Midpoint method, where the midpoint is chosen according to a rho=3 Karras schedule
-             sigma_mid = ((sigmas[i] ** (1 / 3) + sigma_down ** (1 / 3)) / 2) ** 3
-@@ -1016,7 +1016,7 @@ class UNet(DDPM):
-             d_2 = to_d(x_2, sigma_mid, denoised_2)
-             x = x + d_2 * dt_2
-             x = x + torch.randn_like(x) * sigma_up
--        return x
-+        yield from img_callback(x, len(sigmas)-1)
- 
- 
-     @torch.no_grad()
-@@ -1042,8 +1042,8 @@ class UNet(DDPM):
-             e_t_uncond, e_t = (x_in  + eps * c_out).chunk(2)
-             denoised = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
- 
--            if callback: callback(i)
--            if img_callback: img_callback(x, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x, i)
- 
-             d = to_d(x, sigmas[i], denoised)
-             ds.append(d)
-@@ -1054,4 +1054,4 @@ class UNet(DDPM):
-             cur_order = min(i + 1, order)
-             coeffs = [linear_multistep_coeff(cur_order, sigmas.cpu(), i, j) for j in range(cur_order)]
-             x = x + sum(coeff * d for coeff, d in zip(coeffs, reversed(ds)))
--        return x
-+        yield from img_callback(x, len(sigmas)-1)

ui/sd_internal/ddim_callback_sd2.patch

@@ -1,84 +0,0 @@
-diff --git a/ldm/models/diffusion/ddim.py b/ldm/models/diffusion/ddim.py
-index 27ead0e..6215939 100644
---- a/ldm/models/diffusion/ddim.py
-+++ b/ldm/models/diffusion/ddim.py
-@@ -100,7 +100,7 @@ class DDIMSampler(object):
-         size = (batch_size, C, H, W)
-         print(f'Data shape for DDIM sampling is {size}, eta {eta}')
- 
--        samples, intermediates = self.ddim_sampling(conditioning, size,
-+        samples = self.ddim_sampling(conditioning, size,
-                                                     callback=callback,
-                                                     img_callback=img_callback,
-                                                     quantize_denoised=quantize_x0,
-@@ -117,7 +117,8 @@ class DDIMSampler(object):
-                                                     dynamic_threshold=dynamic_threshold,
-                                                     ucg_schedule=ucg_schedule
-                                                     )
--        return samples, intermediates
-+        # return samples, intermediates
-+        yield from samples
- 
-     @torch.no_grad()
-     def ddim_sampling(self, cond, shape,
-@@ -168,14 +169,15 @@ class DDIMSampler(object):
-                                       unconditional_conditioning=unconditional_conditioning,
-                                       dynamic_threshold=dynamic_threshold)
-             img, pred_x0 = outs
--            if callback: callback(i)
--            if img_callback: img_callback(pred_x0, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(pred_x0, i)
- 
-             if index % log_every_t == 0 or index == total_steps - 1:
-                 intermediates['x_inter'].append(img)
-                 intermediates['pred_x0'].append(pred_x0)
- 
--        return img, intermediates
-+        # return img, intermediates
-+        yield from img_callback(pred_x0, len(iterator)-1)
- 
-     @torch.no_grad()
-     def p_sample_ddim(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,
-diff --git a/ldm/models/diffusion/plms.py b/ldm/models/diffusion/plms.py
-index 7002a36..0951f39 100644
---- a/ldm/models/diffusion/plms.py
-+++ b/ldm/models/diffusion/plms.py
-@@ -96,7 +96,7 @@ class PLMSSampler(object):
-         size = (batch_size, C, H, W)
-         print(f'Data shape for PLMS sampling is {size}')
- 
--        samples, intermediates = self.plms_sampling(conditioning, size,
-+        samples = self.plms_sampling(conditioning, size,
-                                                     callback=callback,
-                                                     img_callback=img_callback,
-                                                     quantize_denoised=quantize_x0,
-@@ -112,7 +112,8 @@ class PLMSSampler(object):
-                                                     unconditional_conditioning=unconditional_conditioning,
-                                                     dynamic_threshold=dynamic_threshold,
-                                                     )
--        return samples, intermediates
-+        #return samples, intermediates
-+        yield from samples
- 
-     @torch.no_grad()
-     def plms_sampling(self, cond, shape,
-@@ -165,14 +166,15 @@ class PLMSSampler(object):
-             old_eps.append(e_t)
-             if len(old_eps) >= 4:
-                 old_eps.pop(0)
--            if callback: callback(i)
--            if img_callback: img_callback(pred_x0, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(pred_x0, i)
- 
-             if index % log_every_t == 0 or index == total_steps - 1:
-                 intermediates['x_inter'].append(img)
-                 intermediates['pred_x0'].append(pred_x0)
- 
--        return img, intermediates
-+        # return img, intermediates
-+        yield from img_callback(pred_x0, len(iterator)-1)
- 
-     @torch.no_grad()
-     def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,

ui/sd_internal/device_manager.py

@@ -1,168 +0,0 @@
-import os
-import torch
-import traceback
-import re
-
-COMPARABLE_GPU_PERCENTILE = 0.65 # if a GPU's free_mem is within this % of the GPU with the most free_mem, it will be picked
-
-mem_free_threshold = 0
-
-def get_device_delta(render_devices, active_devices):
-    '''
-    render_devices: 'cpu', or 'auto' or ['cuda:N'...]
-    active_devices: ['cpu', 'cuda:N'...]
-    '''
-
-    if render_devices in ('cpu', 'auto'):
-        render_devices = [render_devices]
-    elif render_devices is not None:
-        if isinstance(render_devices, str):
-            render_devices = [render_devices]
-        if isinstance(render_devices, list) and len(render_devices) > 0:
-            render_devices = list(filter(lambda x: x.startswith('cuda:'), render_devices))
-            if len(render_devices) == 0:
-                raise Exception('Invalid render_devices value in config.json. Valid: {"render_devices": ["cuda:0", "cuda:1"...]}, or {"render_devices": "cpu"} or {"render_devices": "auto"}')
-
-            render_devices = list(filter(lambda x: is_device_compatible(x), render_devices))
-            if len(render_devices) == 0:
-                raise Exception('Sorry, none of the render_devices configured in config.json are compatible with Stable Diffusion')
-        else:
-            raise Exception('Invalid render_devices value in config.json. Valid: {"render_devices": ["cuda:0", "cuda:1"...]}, or {"render_devices": "cpu"} or {"render_devices": "auto"}')
-    else:
-        render_devices = ['auto']
-
-    if 'auto' in render_devices:
-        render_devices = auto_pick_devices(active_devices)
-        if 'cpu' in render_devices:
-            print('WARNING: Could not find a compatible GPU. Using the CPU, but this will be very slow!')
-
-    active_devices = set(active_devices)
-    render_devices = set(render_devices)
-
-    devices_to_start = render_devices - active_devices
-    devices_to_stop = active_devices - render_devices
-
-    return devices_to_start, devices_to_stop
-
-def auto_pick_devices(currently_active_devices):
-    global mem_free_threshold
-
-    if not torch.cuda.is_available(): return ['cpu']
-
-    device_count = torch.cuda.device_count()
-    if device_count == 1:
-        return ['cuda:0'] if is_device_compatible('cuda:0') else ['cpu']
-
-    print('Autoselecting GPU. Using most free memory.')
-    devices = []
-    for device in range(device_count):
-        device = f'cuda:{device}'
-        if not is_device_compatible(device):
-            continue
-
-        mem_free, mem_total = torch.cuda.mem_get_info(device)
-        mem_free /= float(10**9)
-        mem_total /= float(10**9)
-        device_name = torch.cuda.get_device_name(device)
-        print(f'{device} detected: {device_name} - Memory (free/total): {round(mem_free, 2)}Gb / {round(mem_total, 2)}Gb')
-        devices.append({'device': device, 'device_name': device_name, 'mem_free': mem_free})
-
-    devices.sort(key=lambda x:x['mem_free'], reverse=True)
-    max_mem_free = devices[0]['mem_free']
-    curr_mem_free_threshold = COMPARABLE_GPU_PERCENTILE * max_mem_free
-    mem_free_threshold = max(curr_mem_free_threshold, mem_free_threshold)
-
-    # Auto-pick algorithm:
-    # 1. Pick the top 75 percentile of the GPUs, sorted by free_mem.
-    # 2. Also include already-running devices (GPU-only), otherwise their free_mem will
-    #    always be very low (since their VRAM contains the model).
-    #    These already-running devices probably aren't terrible, since they were picked in the past.
-    #    Worst case, the user can restart the program and that'll get rid of them.
-    devices = list(filter((lambda x: x['mem_free'] > mem_free_threshold or x['device'] in currently_active_devices), devices))
-    devices = list(map(lambda x: x['device'], devices))
-    return devices
-
-def device_init(thread_data, device):
-    '''
-    This function assumes the 'device' has already been verified to be compatible.
-    `get_device_delta()` has already filtered out incompatible devices.
-    '''
-
-    validate_device_id(device, log_prefix='device_init')
-
-    if device == 'cpu':
-        thread_data.device = 'cpu'
-        thread_data.device_name = get_processor_name()
-        print('Render device CPU available as', thread_data.device_name)
-        return
-
-    thread_data.device_name = torch.cuda.get_device_name(device)
-    thread_data.device = device
-
-    # Force full precision on 1660 and 1650 NVIDIA cards to avoid creating green images
-    device_name = thread_data.device_name.lower()
-    thread_data.force_full_precision = (('nvidia' in device_name or 'geforce' in device_name) and (' 1660' in device_name or ' 1650' in device_name)) or ('Quadro T2000' in device_name)
-    if thread_data.force_full_precision:
-        print('forcing full precision on NVIDIA 16xx cards, to avoid green images. GPU detected: ', thread_data.device_name)
-        # Apply force_full_precision now before models are loaded.
-        thread_data.precision = 'full'
-
-    print(f'Setting {device} as active')
-    torch.cuda.device(device)
-
-    return
-
-def validate_device_id(device, log_prefix=''):
-    def is_valid():
-        if not isinstance(device, str):
-            return False
-        if device == 'cpu':
-            return True
-        if not device.startswith('cuda:') or not device[5:].isnumeric():
-            return False
-        return True
-
-    if not is_valid():
-        raise EnvironmentError(f"{log_prefix}: device id should be 'cpu', or 'cuda:N' (where N is an integer index for the GPU). Got: {device}")
-
-def is_device_compatible(device):
-    '''
-    Returns True/False, and prints any compatibility errors
-    '''
-    try:
-        validate_device_id(device, log_prefix='is_device_compatible')
-    except:
-        print(str(e))
-        return False
-
-    if device == 'cpu': return True
-    # Memory check
-    try:
-        _, mem_total = torch.cuda.mem_get_info(device)
-        mem_total /= float(10**9)
-        if mem_total < 3.0:
-            print(f'GPU {device} with less than 3 GB of VRAM is not compatible with Stable Diffusion')
-            return False
-    except RuntimeError as e:
-        print(str(e))
-        return False
-    return True
-
-def get_processor_name():
-    try:
-        import platform, subprocess
-        if platform.system() == "Windows":
-            return platform.processor()
-        elif platform.system() == "Darwin":
-            os.environ['PATH'] = os.environ['PATH'] + os.pathsep + '/usr/sbin'
-            command = "sysctl -n machdep.cpu.brand_string"
-            return subprocess.check_output(command).strip()
-        elif platform.system() == "Linux":
-            command = "cat /proc/cpuinfo"
-            all_info = subprocess.check_output(command, shell=True).decode().strip()
-            for line in all_info.split("\n"):
-                if "model name" in line:
-                    return re.sub(".*model name.*:", "", line, 1).strip()
-    except:
-        print(traceback.format_exc())
-        return "cpu"

ui/sd_internal/hypernetwork.py

@@ -1,198 +0,0 @@
-# this is basically a cut down version of https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob/c9a2cfdf2a53d37c2de1908423e4f548088667ef/modules/hypernetworks/hypernetwork.py, mostly for feature parity
-# I, c0bra5, don't really understand how deep learning works. I just know how to port stuff.
-
-import inspect
-import torch
-import optimizedSD.splitAttention
-from . import runtime
-from einops import rearrange
-
-optimizer_dict = {optim_name : cls_obj for optim_name, cls_obj in inspect.getmembers(torch.optim, inspect.isclass) if optim_name != "Optimizer"}
-
-loaded_hypernetwork = None
-
-class HypernetworkModule(torch.nn.Module):
-    multiplier = 0.5
-    activation_dict = {
-        "linear": torch.nn.Identity,
-        "relu": torch.nn.ReLU,
-        "leakyrelu": torch.nn.LeakyReLU,
-        "elu": torch.nn.ELU,
-        "swish": torch.nn.Hardswish,
-        "tanh": torch.nn.Tanh,
-        "sigmoid": torch.nn.Sigmoid,
-    }
-    activation_dict.update({cls_name.lower(): cls_obj for cls_name, cls_obj in inspect.getmembers(torch.nn.modules.activation) if inspect.isclass(cls_obj) and cls_obj.__module__ == 'torch.nn.modules.activation'})
-
-    def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, weight_init='Normal',
-                 add_layer_norm=False, use_dropout=False, activate_output=False, last_layer_dropout=False):
-        super().__init__()
-
-        assert layer_structure is not None, "layer_structure must not be None"
-        assert layer_structure[0] == 1, "Multiplier Sequence should start with size 1!"
-        assert layer_structure[-1] == 1, "Multiplier Sequence should end with size 1!"
-
-        linears = []
-        for i in range(len(layer_structure) - 1):
-
-            # Add a fully-connected layer
-            linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1])))
-
-            # Add an activation func except last layer
-            if activation_func == "linear" or activation_func is None or (i >= len(layer_structure) - 2 and not activate_output):
-                pass
-            elif activation_func in self.activation_dict:
-                linears.append(self.activation_dict[activation_func]())
-            else:
-                raise RuntimeError(f'hypernetwork uses an unsupported activation function: {activation_func}')
-
-            # Add layer normalization
-            if add_layer_norm:
-                linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1])))
-
-            # Add dropout except last layer
-            if use_dropout and (i < len(layer_structure) - 3 or last_layer_dropout and i < len(layer_structure) - 2):
-                linears.append(torch.nn.Dropout(p=0.3))
-
-        self.linear = torch.nn.Sequential(*linears)
-
-        self.fix_old_state_dict(state_dict)
-        self.load_state_dict(state_dict)
-
-        self.to(runtime.thread_data.device)
-
-    def fix_old_state_dict(self, state_dict):
-        changes = {
-            'linear1.bias': 'linear.0.bias',
-            'linear1.weight': 'linear.0.weight',
-            'linear2.bias': 'linear.1.bias',
-            'linear2.weight': 'linear.1.weight',
-        }
-
-        for fr, to in changes.items():
-            x = state_dict.get(fr, None)
-            if x is None:
-                continue
-
-            del state_dict[fr]
-            state_dict[to] = x
-
-    def forward(self, x: torch.Tensor):
-        return x + self.linear(x) * runtime.thread_data.hypernetwork_strength
-
-def apply_hypernetwork(hypernetwork, context, layer=None):
-    hypernetwork_layers = hypernetwork.get(context.shape[2], None)
-
-    if hypernetwork_layers is None:
-        return context, context
-
-    if layer is not None:
-        layer.hyper_k = hypernetwork_layers[0]
-        layer.hyper_v = hypernetwork_layers[1]
-
-    context_k = hypernetwork_layers[0](context)
-    context_v = hypernetwork_layers[1](context)
-    return context_k, context_v
-
-def get_kv(context, hypernetwork):
-    if hypernetwork is None:
-        return context, context
-    else:
-        return apply_hypernetwork(runtime.thread_data.hypernetwork, context)
-
-# This might need updating as the optimisedSD code changes
-# I think yall have a system for this (patch files in sd_internal) but idk how it works and no amount of searching gave me any clue
-# just in case for attribution https://github.com/easydiffusion/diffusion-kit/blob/e8ea0cadd543056059cd951e76d4744de76327d2/optimizedSD/splitAttention.py#L171
-def new_cross_attention_forward(self, x, context=None, mask=None):
-    h = self.heads
-
-    q = self.to_q(x)
-    # default context
-    context = context if context is not None else x() if inspect.isfunction(x) else x
-    # hypernetwork!
-    context_k, context_v =  get_kv(context, runtime.thread_data.hypernetwork)
-    k = self.to_k(context_k)
-    v = self.to_v(context_v)
-    del context, x
-
-    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
-
-
-    limit = k.shape[0]
-    att_step = self.att_step
-    q_chunks = list(torch.tensor_split(q, limit//att_step, dim=0))
-    k_chunks = list(torch.tensor_split(k, limit//att_step, dim=0))
-    v_chunks = list(torch.tensor_split(v, limit//att_step, dim=0))
-
-    q_chunks.reverse()
-    k_chunks.reverse()
-    v_chunks.reverse()
-    sim = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device)
-    del k, q, v
-    for i in range (0, limit, att_step):
-
-        q_buffer = q_chunks.pop()
-        k_buffer = k_chunks.pop()
-        v_buffer = v_chunks.pop()
-        sim_buffer = torch.einsum('b i d, b j d -> b i j', q_buffer, k_buffer) * self.scale
-
-        del k_buffer, q_buffer
-        # attention, what we cannot get enough of, by chunks
-
-        sim_buffer = sim_buffer.softmax(dim=-1)
-
-        sim_buffer = torch.einsum('b i j, b j d -> b i d', sim_buffer, v_buffer)
-        del v_buffer
-        sim[i:i+att_step,:,:] = sim_buffer
-
-        del sim_buffer
-    sim = rearrange(sim, '(b h) n d -> b n (h d)', h=h)
-    return self.to_out(sim)
-
-
-def load_hypernetwork(path: str):
-
-    state_dict = torch.load(path, map_location='cpu')
-
-    layer_structure = state_dict.get('layer_structure', [1, 2, 1])
-    activation_func = state_dict.get('activation_func', None)
-    weight_init = state_dict.get('weight_initialization', 'Normal')
-    add_layer_norm = state_dict.get('is_layer_norm', False)
-    use_dropout = state_dict.get('use_dropout', False)
-    activate_output = state_dict.get('activate_output', True)
-    last_layer_dropout = state_dict.get('last_layer_dropout', False)
-    # this is a bit verbose so leaving it commented out for the poor soul who ever has to debug this
-    # print(f"layer_structure: {layer_structure}")
-    # print(f"activation_func: {activation_func}")
-    # print(f"weight_init: {weight_init}")
-    # print(f"add_layer_norm: {add_layer_norm}")
-    # print(f"use_dropout: {use_dropout}")
-    # print(f"activate_output: {activate_output}")
-    # print(f"last_layer_dropout: {last_layer_dropout}")
-
-    layers = {}
-    for size, sd in state_dict.items():
-        if type(size) == int:
-            layers[size] = (
-                HypernetworkModule(size, sd[0], layer_structure, activation_func, weight_init, add_layer_norm,
-                                   use_dropout, activate_output, last_layer_dropout=last_layer_dropout),
-                HypernetworkModule(size, sd[1], layer_structure, activation_func, weight_init, add_layer_norm,
-                                   use_dropout, activate_output, last_layer_dropout=last_layer_dropout),
-            )
-    print(f"hypernetwork loaded")
-    return layers
-
-
-
-# overriding of original function
-old_cross_attention_forward = optimizedSD.splitAttention.CrossAttention.forward
-# hijacks the cross attention forward function to add hyper network support
-def hijack_cross_attention():
-    print("hypernetwork functionality added to cross attention")
-    optimizedSD.splitAttention.CrossAttention.forward = new_cross_attention_forward
-# there was a cop on board
-def unhijack_cross_attention_forward():
-    print("hypernetwork functionality removed from cross attention")
-    optimizedSD.splitAttention.CrossAttention.forward = old_cross_attention_forward
-
-hijack_cross_attention()

ui/sd_internal/task_manager.py

@@ -1,609 +0,0 @@
-"""task_manager.py: manage tasks dispatching and render threads.
-Notes:
-    render_threads should be the only hard reference held by the manager to the threads.
-    Use weak_thread_data to store all other data using weak keys.
-    This will allow for garbage collection after the thread dies.
-"""
-import json
-import traceback
-
-TASK_TTL = 15 * 60 # seconds, Discard last session's task timeout
-
-import torch
-import queue, threading, time, weakref
-from typing import Any, Generator, Hashable, Optional, Union
-
-from pydantic import BaseModel
-from sd_internal import Request, Response, runtime, device_manager
-
-THREAD_NAME_PREFIX = 'Runtime-Render/'
-ERR_LOCK_FAILED = ' failed to acquire lock within timeout.'
-LOCK_TIMEOUT = 15 # Maximum locking time in seconds before failing a task.
-# It's better to get an exception than a deadlock... ALWAYS use timeout in critical paths.
-
-DEVICE_START_TIMEOUT = 60 # seconds - Maximum time to wait for a render device to init.
-
-class SymbolClass(type): # Print nicely formatted Symbol names.
-    def __repr__(self): return self.__qualname__
-    def __str__(self): return self.__name__
-class Symbol(metaclass=SymbolClass): pass
-
-class ServerStates:
-    class Init(Symbol): pass
-    class LoadingModel(Symbol): pass
-    class Online(Symbol): pass
-    class Rendering(Symbol): pass
-    class Unavailable(Symbol): pass
-
-class RenderTask(): # Task with output queue and completion lock.
-    def __init__(self, req: Request):
-        req.request_id = id(self)
-        self.request: Request = req  # Initial Request
-        self.response: Any = None # Copy of the last reponse
-        self.render_device = None # Select the task affinity. (Not used to change active devices).
-        self.temp_images:list = [None] * req.num_outputs * (1 if req.show_only_filtered_image else 2)
-        self.error: Exception = None
-        self.lock: threading.Lock = threading.Lock() # Locks at task start and unlocks when task is completed
-        self.buffer_queue: queue.Queue = queue.Queue() # Queue of JSON string segments
-    async def read_buffer_generator(self):
-        try:
-            while not self.buffer_queue.empty():
-                res = self.buffer_queue.get(block=False)
-                self.buffer_queue.task_done()
-                yield res
-        except queue.Empty as e: yield
-    @property
-    def status(self):
-        if self.lock.locked():
-            return 'running'
-        if isinstance(self.error, StopAsyncIteration):
-            return 'stopped'
-        if self.error:
-            return 'error'
-        if not self.buffer_queue.empty():
-            return 'buffer'
-        if self.response:
-            return 'completed'
-        return 'pending'
-    @property
-    def is_pending(self):
-        return bool(not self.response and not self.error)
-
-# defaults from https://huggingface.co/blog/stable_diffusion
-class ImageRequest(BaseModel):
-    session_id: str = "session"
-    prompt: str = ""
-    negative_prompt: str = ""
-    init_image: str = None # base64
-    mask: str = None # base64
-    num_outputs: int = 1
-    num_inference_steps: int = 50
-    guidance_scale: float = 7.5
-    width: int = 512
-    height: int = 512
-    seed: int = 42
-    prompt_strength: float = 0.8
-    sampler: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
-    # allow_nsfw: bool = False
-    save_to_disk_path: str = None
-    turbo: bool = True
-    use_cpu: bool = False ##TODO Remove after UI and plugins transition.
-    render_device: str = None # Select the task affinity. (Not used to change active devices).
-    use_full_precision: bool = False
-    use_face_correction: str = None # or "GFPGANv1.3"
-    use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
-    use_stable_diffusion_model: str = "sd-v1-4"
-    use_vae_model: str = None
-    use_hypernetwork_model: str = None
-    hypernetwork_strength: float = None
-    show_only_filtered_image: bool = False
-    output_format: str = "jpeg" # or "png"
-    output_quality: int = 75
-
-    stream_progress_updates: bool = False
-    stream_image_progress: bool = False
-
-class FilterRequest(BaseModel):
-    session_id: str = "session"
-    model: str = None
-    name: str = ""
-    init_image: str = None # base64
-    width: int = 512
-    height: int = 512
-    save_to_disk_path: str = None
-    turbo: bool = True
-    render_device: str = None
-    use_full_precision: bool = False
-    output_format: str = "jpeg" # or "png"
-    output_quality: int = 75
-
-# Temporary cache to allow to query tasks results for a short time after they are completed.
-class DataCache():
-    def __init__(self):
-        self._base = dict()
-        self._lock: threading.Lock = threading.Lock()
-    def _get_ttl_time(self, ttl: int) -> int:
-        return int(time.time()) + ttl
-    def _is_expired(self, timestamp: int) -> bool:
-        return int(time.time()) >= timestamp
-    def clean(self) -> None:
-        if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.clean' + ERR_LOCK_FAILED)
-        try:
-            # Create a list of expired keys to delete
-            to_delete = []
-            for key in self._base:
-                ttl, _ = self._base[key]
-                if self._is_expired(ttl):
-                    to_delete.append(key)
-            # Remove Items
-            for key in to_delete:
-                (_, val) = self._base[key]
-                if isinstance(val, RenderTask):
-                    print(f'RenderTask {key} expired. Data removed.')
-                elif isinstance(val, SessionState):
-                    print(f'Session {key} expired. Data removed.')
-                else:
-                    print(f'Key {key} expired. Data removed.')
-                del self._base[key]
-        finally:
-            self._lock.release()
-    def clear(self) -> None:
-        if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.clear' + ERR_LOCK_FAILED)
-        try: self._base.clear()
-        finally: self._lock.release()
-    def delete(self, key: Hashable) -> bool:
-        if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.delete' + ERR_LOCK_FAILED)
-        try:
-            if key not in self._base:
-                return False
-            del self._base[key]
-            return True
-        finally:
-            self._lock.release()
-    def keep(self, key: Hashable, ttl: int) -> bool:
-        if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.keep' + ERR_LOCK_FAILED)
-        try:
-            if key in self._base:
-                _, value = self._base.get(key)
-                self._base[key] = (self._get_ttl_time(ttl), value)
-                return True
-            return False
-        finally:
-            self._lock.release()
-    def put(self, key: Hashable, value: Any, ttl: int) -> bool:
-        if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.put' + ERR_LOCK_FAILED)
-        try:
-            self._base[key] = (
-                self._get_ttl_time(ttl), value
-            )
-        except Exception as e:
-            print(str(e))
-            print(traceback.format_exc())
-            return False
-        else:
-            return True
-        finally:
-            self._lock.release()
-    def tryGet(self, key: Hashable) -> Any:
-        if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.tryGet' + ERR_LOCK_FAILED)
-        try:
-            ttl, value = self._base.get(key, (None, None))
-            if ttl is not None and self._is_expired(ttl):
-                print(f'Session {key} expired. Discarding data.')
-                del self._base[key]
-                return None
-            return value
-        finally:
-            self._lock.release()
-
-manager_lock = threading.RLock()
-render_threads = []
-current_state = ServerStates.Init
-current_state_error:Exception = None
-current_model_path = None
-current_vae_path = None
-current_hypernetwork_path = None
-tasks_queue = []
-session_cache = DataCache()
-task_cache = DataCache()
-default_model_to_load = None
-default_vae_to_load = None
-default_hypernetwork_to_load = None
-weak_thread_data = weakref.WeakKeyDictionary()
-idle_event: threading.Event = threading.Event()
-
-class SessionState():
-    def __init__(self, id: str):
-        self._id = id
-        self._tasks_ids = []
-    @property
-    def id(self):
-        return self._id
-    @property
-    def tasks(self):
-        tasks = []
-        for task_id in self._tasks_ids:
-            task = task_cache.tryGet(task_id)
-            if task:
-                tasks.append(task)
-        return tasks
-    def put(self, task, ttl=TASK_TTL):
-        task_id = id(task)
-        self._tasks_ids.append(task_id)
-        if not task_cache.put(task_id, task, ttl):
-            return False
-        while len(self._tasks_ids) > len(render_threads) * 2:
-            self._tasks_ids.pop(0)
-        return True
-
-def preload_model(ckpt_file_path=None, vae_file_path=None, hypernetwork_file_path=None):
-    global current_state, current_state_error, current_model_path, current_vae_path, current_hypernetwork_path
-    if ckpt_file_path == None:
-        ckpt_file_path = default_model_to_load
-    if vae_file_path == None:
-        vae_file_path = default_vae_to_load
-    if hypernetwork_file_path == None:
-        hypernetwork_file_path = default_hypernetwork_to_load
-    if ckpt_file_path == current_model_path and vae_file_path == current_vae_path:
-        return
-    current_state = ServerStates.LoadingModel
-    try:
-        from . import runtime
-        runtime.thread_data.hypernetwork_file = hypernetwork_file_path
-        runtime.thread_data.ckpt_file = ckpt_file_path
-        runtime.thread_data.vae_file = vae_file_path
-        runtime.load_model_ckpt()
-        runtime.load_hypernetwork()
-        current_model_path = ckpt_file_path
-        current_vae_path = vae_file_path
-        current_hypernetwork_path = hypernetwork_file_path
-        current_state_error = None
-        current_state = ServerStates.Online
-    except Exception as e:
-        current_model_path = None
-        current_vae_path = None
-        current_state_error = e
-        current_state = ServerStates.Unavailable
-        print(traceback.format_exc())
-
-def thread_get_next_task():
-    from . import runtime
-    if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
-        print('Render thread on device', runtime.thread_data.device, 'failed to acquire manager lock.')
-        return None
-    if len(tasks_queue) <= 0:
-        manager_lock.release()
-        return None
-    task = None
-    try:  # Select a render task.
-        for queued_task in tasks_queue:
-            if queued_task.render_device and runtime.thread_data.device != queued_task.render_device:
-                # Is asking for a specific render device.
-                if is_alive(queued_task.render_device) > 0:
-                    continue  # requested device alive, skip current one.
-                else:
-                    # Requested device is not active, return error to UI.
-                    queued_task.error = Exception(queued_task.render_device + ' is not currently active.')
-                    task = queued_task
-                    break
-            if not queued_task.render_device and runtime.thread_data.device == 'cpu' and is_alive() > 1:
-                # not asking for any specific devices, cpu want to grab task but other render devices are alive.
-                continue  # Skip Tasks, don't run on CPU unless there is nothing else or user asked for it.
-            task = queued_task
-            break
-        if task is not None:
-            del tasks_queue[tasks_queue.index(task)]
-        return task
-    finally:
-        manager_lock.release()
-
-def thread_render(device):
-    global current_state, current_state_error, current_model_path, current_vae_path, current_hypernetwork_path
-    from . import runtime
-    try:
-        runtime.thread_init(device)
-    except Exception as e:
-        print(traceback.format_exc())
-        weak_thread_data[threading.current_thread()] = {
-            'error': e
-        }
-        return
-    weak_thread_data[threading.current_thread()] = {
-        'device': runtime.thread_data.device,
-        'device_name': runtime.thread_data.device_name,
-        'alive': True
-    }
-    if runtime.thread_data.device != 'cpu' or is_alive() == 1:
-        preload_model()
-        current_state = ServerStates.Online
-    while True:
-        session_cache.clean()
-        task_cache.clean()
-        if not weak_thread_data[threading.current_thread()]['alive']:
-            print(f'Shutting down thread for device {runtime.thread_data.device}')
-            runtime.unload_models()
-            runtime.unload_filters()
-            return
-        if isinstance(current_state_error, SystemExit):
-            current_state = ServerStates.Unavailable
-            return
-        task = thread_get_next_task()
-        if task is None:
-            idle_event.clear()
-            idle_event.wait(timeout=1)
-            continue
-        if task.error is not None:
-            print(task.error)
-            task.response = {"status": 'failed', "detail": str(task.error)}
-            task.buffer_queue.put(json.dumps(task.response))
-            continue
-        if current_state_error:
-            task.error = current_state_error
-            task.response = {"status": 'failed', "detail": str(task.error)}
-            task.buffer_queue.put(json.dumps(task.response))
-            continue
-        print(f'Session {task.request.session_id} starting task {id(task)} on {runtime.thread_data.device_name}')
-        if not task.lock.acquire(blocking=False): raise Exception('Got locked task from queue.')
-        try:
-            if runtime.is_hypernetwork_reload_necessary(task.request):
-                runtime.reload_hypernetwork()
-                current_hypernetwork_path = task.request.use_hypernetwork_model
-                
-            if runtime.is_model_reload_necessary(task.request):
-                current_state = ServerStates.LoadingModel
-                runtime.reload_model()
-                current_model_path = task.request.use_stable_diffusion_model
-                current_vae_path = task.request.use_vae_model
-
-            def step_callback():
-                global current_state_error
-
-                if isinstance(current_state_error, SystemExit) or isinstance(current_state_error, StopAsyncIteration) or isinstance(task.error, StopAsyncIteration):
-                    runtime.thread_data.stop_processing = True
-                    if isinstance(current_state_error, StopAsyncIteration):
-                        task.error = current_state_error
-                        current_state_error = None
-                        print(f'Session {task.request.session_id} sent cancel signal for task {id(task)}')
-
-            current_state = ServerStates.Rendering
-            task.response = runtime.mk_img(task.request, task.buffer_queue, task.temp_images, step_callback)
-            # Before looping back to the generator, mark cache as still alive.
-            task_cache.keep(id(task), TASK_TTL)
-            session_cache.keep(task.request.session_id, TASK_TTL)
-        except Exception as e:
-            task.error = e
-            task.response = {"status": 'failed', "detail": str(task.error)}
-            task.buffer_queue.put(json.dumps(task.response))
-            print(traceback.format_exc())
-            continue
-        finally:
-            # Task completed
-            task.lock.release()
-        task_cache.keep(id(task), TASK_TTL)
-        session_cache.keep(task.request.session_id, TASK_TTL)
-        if isinstance(task.error, StopAsyncIteration):
-            print(f'Session {task.request.session_id} task {id(task)} cancelled!')
-        elif task.error is not None:
-            print(f'Session {task.request.session_id} task {id(task)} failed!')
-        else:
-            print(f'Session {task.request.session_id} task {id(task)} completed by {runtime.thread_data.device_name}.')
-        current_state = ServerStates.Online
-
-def get_cached_task(task_id:str, update_ttl:bool=False):
-    # By calling keep before tryGet, wont discard if was expired.
-    if update_ttl and not task_cache.keep(task_id, TASK_TTL):
-        # Failed to keep task, already gone.
-        return None
-    return task_cache.tryGet(task_id)
-
-def get_cached_session(session_id:str, update_ttl:bool=False):
-    if update_ttl:
-        session_cache.keep(session_id, TASK_TTL)
-    session = session_cache.tryGet(session_id)
-    if not session:
-        session = SessionState(session_id)
-        session_cache.put(session_id, session, TASK_TTL)
-    return session
-
-def get_devices():
-    devices = {
-        'all': {},
-        'active': {},
-    }
-
-    def get_device_info(device):
-        if device == 'cpu':
-            return {'name': device_manager.get_processor_name()}
-            
-        mem_free, mem_total = torch.cuda.mem_get_info(device)
-        mem_free /= float(10**9)
-        mem_total /= float(10**9)
-
-        return {
-            'name': torch.cuda.get_device_name(device),
-            'mem_free': mem_free,
-            'mem_total': mem_total,
-        }
-
-    # list the compatible devices
-    gpu_count = torch.cuda.device_count()
-    for device in range(gpu_count):
-        device = f'cuda:{device}'
-        if not device_manager.is_device_compatible(device):
-            continue
-
-        devices['all'].update({device: get_device_info(device)})
-
-    devices['all'].update({'cpu': get_device_info('cpu')})
-
-    # list the activated devices
-    if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('get_devices' + ERR_LOCK_FAILED)
-    try:
-        for rthread in render_threads:
-            if not rthread.is_alive():
-                continue
-            weak_data = weak_thread_data.get(rthread)
-            if not weak_data or not 'device' in weak_data or not 'device_name' in weak_data:
-                continue
-            device = weak_data['device']
-            devices['active'].update({device: get_device_info(device)})
-    finally:
-        manager_lock.release()
-
-    return devices
-
-def is_alive(device=None):
-    if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('is_alive' + ERR_LOCK_FAILED)
-    nbr_alive = 0
-    try:
-        for rthread in render_threads:
-            if device is not None:
-                weak_data = weak_thread_data.get(rthread)
-                if weak_data is None or not 'device' in weak_data or weak_data['device'] is None:
-                    continue
-                thread_device = weak_data['device']
-                if thread_device != device:
-                    continue
-            if rthread.is_alive():
-                nbr_alive += 1
-        return nbr_alive
-    finally:
-        manager_lock.release()
-
-def start_render_thread(device):
-    if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('start_render_thread' + ERR_LOCK_FAILED)
-    print('Start new Rendering Thread on device', device)
-    try:
-        rthread = threading.Thread(target=thread_render, kwargs={'device': device})
-        rthread.daemon = True
-        rthread.name = THREAD_NAME_PREFIX + device
-        rthread.start()
-        render_threads.append(rthread)
-    finally:
-        manager_lock.release()
-    timeout = DEVICE_START_TIMEOUT
-    while not rthread.is_alive() or not rthread in weak_thread_data or not 'device' in weak_thread_data[rthread]:
-        if rthread in weak_thread_data and 'error' in weak_thread_data[rthread]:
-            print(rthread, device, 'error:', weak_thread_data[rthread]['error'])
-            return False
-        if timeout <= 0:
-            return False
-        timeout -= 1
-        time.sleep(1)
-    return True
-
-def stop_render_thread(device):
-    try:
-        device_manager.validate_device_id(device, log_prefix='stop_render_thread')
-    except:
-        print(traceback.format_exc())
-        return False
-
-    if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('stop_render_thread' + ERR_LOCK_FAILED)
-    print('Stopping Rendering Thread on device', device)
-
-    try:
-        thread_to_remove = None
-        for rthread in render_threads:
-            weak_data = weak_thread_data.get(rthread)
-            if weak_data is None or not 'device' in weak_data or weak_data['device'] is None:
-                continue
-            thread_device = weak_data['device']
-            if thread_device == device:
-                weak_data['alive'] = False
-                thread_to_remove = rthread
-                break
-        if thread_to_remove is not None:
-            render_threads.remove(rthread)
-            return True
-    finally:
-        manager_lock.release()
-
-    return False
-
-def update_render_threads(render_devices, active_devices):
-    devices_to_start, devices_to_stop = device_manager.get_device_delta(render_devices, active_devices)
-    print('devices_to_start', devices_to_start)
-    print('devices_to_stop', devices_to_stop)
-
-    for device in devices_to_stop:
-        if is_alive(device) <= 0:
-            print(device, 'is not alive')
-            continue
-        if not stop_render_thread(device):
-            print(device, 'could not stop render thread')
-
-    for device in devices_to_start:
-        if is_alive(device) >= 1:
-            print(device, 'already registered.')
-            continue
-        if not start_render_thread(device):
-            print(device, 'failed to start.')
-
-    if is_alive() <= 0: # No running devices, probably invalid user config.
-        raise EnvironmentError('ERROR: No active render devices! Please verify the "render_devices" value in config.json')
-
-    print('active devices', get_devices()['active'])
-
-def shutdown_event(): # Signal render thread to close on shutdown
-    global current_state_error
-    current_state_error = SystemExit('Application shutting down.')
-
-def render(req : ImageRequest):
-    current_thread_count = is_alive()
-    if current_thread_count <= 0:  # Render thread is dead
-        raise ChildProcessError('Rendering thread has died.')
-
-    # Alive, check if task in cache
-    session = get_cached_session(req.session_id, update_ttl=True)
-    pending_tasks = list(filter(lambda t: t.is_pending, session.tasks))
-    if current_thread_count < len(pending_tasks):
-        raise ConnectionRefusedError(f'Session {req.session_id} already has {len(pending_tasks)} pending tasks out of {current_thread_count}.')
-
-    from . import runtime
-    r = Request()
-    r.session_id = req.session_id
-    r.prompt = req.prompt
-    r.negative_prompt = req.negative_prompt
-    r.init_image = req.init_image
-    r.mask = req.mask
-    r.num_outputs = req.num_outputs
-    r.num_inference_steps = req.num_inference_steps
-    r.guidance_scale = req.guidance_scale
-    r.width = req.width
-    r.height = req.height
-    r.seed = req.seed
-    r.prompt_strength = req.prompt_strength
-    r.sampler = req.sampler
-    # r.allow_nsfw = req.allow_nsfw
-    r.turbo = req.turbo
-    r.use_full_precision = req.use_full_precision
-    r.save_to_disk_path = req.save_to_disk_path
-    r.use_upscale: str = req.use_upscale
-    r.use_face_correction = req.use_face_correction
-    r.use_stable_diffusion_model = req.use_stable_diffusion_model
-    r.use_vae_model = req.use_vae_model
-    r.use_hypernetwork_model = req.use_hypernetwork_model
-    r.hypernetwork_strength = req.hypernetwork_strength
-    r.show_only_filtered_image = req.show_only_filtered_image
-    r.output_format = req.output_format
-    r.output_quality = req.output_quality
-
-    r.stream_progress_updates = True # the underlying implementation only supports streaming
-    r.stream_image_progress = req.stream_image_progress
-
-    if not req.stream_progress_updates:
-        r.stream_image_progress = False
-
-    new_task = RenderTask(r)
-    if session.put(new_task, TASK_TTL):
-        # Use twice the normal timeout for adding user requests.
-        # Tries to force session.put to fail before tasks_queue.put would.
-        if manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT * 2):
-            try:
-                tasks_queue.append(new_task)
-                idle_event.set()
-                return new_task
-            finally:
-                manager_lock.release()
-    raise RuntimeError('Failed to add task to cache.')