From 4df7797a8e76c27bae4390a81a3b503da5f55463 Mon Sep 17 00:00:00 2001
From: Divam Gupta <divamgupta@gmail.com>
Date: Wed, 13 Dec 2023 13:03:17 -0500
Subject: [PATCH] Code for V2 added, completely new UI and lots of features

---
 README.md                                     |     3 +
 backends/model_converter/convert_model.py     |    15 +
 backends/model_converter/sd_shapes.py         |     5 +-
 backends/model_converter/tdict.py             |    21 +-
 .../__init__.py                               |     0
 backends/stable_diffusion/applets/applets.py  |    58 +
 .../stable_diffusion/applets/form_utils.py    |    75 +
 .../applets/frame_interpolator.py             |   179 +
 backends/stable_diffusion/applets/options.py  |   346 +
 .../stable_diffusion/applets/sample_applet.py |    13 +
 backends/stable_diffusion/build.sh            |     6 -
 .../stable_diffusion/diffusionbee_backend.py  |   228 +-
 backends/stable_diffusion/downloader.py       |   155 -
 backends/stable_diffusion/environment_m1.yml  |   134 -
 .../__init__.py                               |     0
 .../interface.py}                             |    12 +-
 backends/stable_diffusion/requirements.txt    |    21 +-
 backends/stable_diffusion/requirements_m1.txt |     9 -
 backends/stable_diffusion/setup.py            |    12 -
 backends/stable_diffusion/stable_diffusion.py |   711 -
 .../{utils => stable_diffusion}/__init__.py   |     0
 .../clip_tokenizer/__init__.py                |    18 +-
 .../bpe_simple_vocab_16e6.txt.gz              |   Bin
 .../clip_tokenizer/xl_text_projection_mat.npy |   Bin 0 -> 3276928 bytes
 .../control_processors/__init__.py            |     0
 .../control_processors/process_body_pose.py   |     0
 .../control_processors/process_lineart.py     |    31 +
 .../control_processors/process_midas_depth.py |     2 +-
 .../stable_diffusion/plugins/__init__.py      |     0
 .../stable_diffusion/plugins/base_plugin.py   |     6 +
 .../stable_diffusion/plugins/controlnet.py    |   117 +
 .../stable_diffusion/plugins/inpainting.py    |    83 +
 .../stable_diffusion/plugins/plugin_system.py |    38 +
 .../plugins/sd15_inpainting.py                |    36 +
 .../stable_diffusion/schedulers/__init__.py   |     0
 .../schedulers/get_scheduler.py               |    60 +
 .../schedulers/k_euler.py                     |     0
 .../schedulers/k_euler_ancestral.py           |     0
 .../schedulers/karras_scheduler.py            |   171 +
 .../schedulers/scheduler_mixin.py             |     0
 .../schedulers/scheduling_ddim.py             |     0
 .../schedulers/scheduling_lms_discrete.py     |     0
 .../schedulers/scheduling_pndm.py             |     0
 .../stable_diffusion/sd_run.py                |    63 +
 .../stable_diffusion/stable_diffusion.py      |   547 +
 .../stable_diffusion/utils/__init__.py        |     0
 .../utils/extra_model_utils.py                |    21 +
 .../utils/image_preprocess.py                 |    40 +
 .../{ => stable_diffusion}/utils/logging.py   |     0
 .../stable_diffusion/utils/model_interface.py |    65 +
 .../utils}/stdin_input.py                     |     0
 .../stable_diffusion/utils/utils.py           |    55 +
 backends/stable_diffusion/test_assets/ddd.png |   Bin 12106 -> 0 bytes
 .../test_assets/inp_command_strings.txt       |     1 -
 backends/stable_diffusion/test_assets/mmm.png |   Bin 404753 -> 0 bytes
 .../test_assets/scribble_turtle.png           |   Bin 86057 -> 0 bytes
 .../test_assets/scribble_turtle_2.png         |   Bin 72553 -> 0 bytes
 .../stable_diffusion/test_assets/yoga1.jpg    |   Bin 22166 -> 0 bytes
 .../yoga1.jpg.processed_body_pose.jpg         |   Bin 22985 -> 0 bytes
 backends/stable_diffusion/tests.py            |   564 -
 .../stable_diffusion_tf_models/interface.py   |     4 +-
 DOCUMENTATION.md => docs/DOCUMENTATION.md     |     0
 docs/Running_from_source.md                   |    47 +
 electron_app/.gitignore                       |     5 +-
 electron_app/.nvmrc                           |     1 -
 electron_app/afterSignHook.js                 |    35 -
 electron_app/package-lock.json                | 37809 +++++-----------
 electron_app/package.json                     |    35 +-
 electron_app/src/App.vue                      |   228 +-
 electron_app/src/AssetsManager.vue            |   224 +
 electron_app/src/SDManager.vue                |   302 +
 electron_app/src/StableDiffusion.vue          |    72 +-
 electron_app/src/assets/css/theme.css         |    73 +-
 electron_app/src/assets/imgs/blank_illus4.png |   Bin 0 -> 5672 bytes
 .../src/assets/imgs/blank_illus4_dark.png     |   Bin 0 -> 6030 bytes
 .../assets/imgs/page_icon_imgs/default.png    |   Bin 0 -> 114348 bytes
 .../assets/imgs/page_icon_imgs/default1.png   |   Bin 0 -> 107960 bytes
 .../assets/imgs/page_icon_imgs/deforum.gif    |   Bin 0 -> 3835575 bytes
 .../assets/imgs/page_icon_imgs/history.png    |   Bin 0 -> 106649 bytes
 .../assets/imgs/page_icon_imgs/img2img.png    |   Bin 0 -> 610215 bytes
 .../assets/imgs/page_icon_imgs/inpainting.png |   Bin 0 -> 444311 bytes
 .../imgs/page_icon_imgs/inpainting_1.png      |   Bin 0 -> 170830 bytes
 .../imgs/page_icon_imgs/interpolate.gif       |   Bin 0 -> 2595584 bytes
 .../src/assets/imgs/page_icon_imgs/models.png |   Bin 0 -> 103270 bytes
 .../assets/imgs/page_icon_imgs/models0.png    |   Bin 0 -> 211835 bytes
 .../imgs/page_icon_imgs/outpainting.png       |   Bin 0 -> 469901 bytes
 .../assets/imgs/page_icon_imgs/settings.png   |   Bin 0 -> 100346 bytes
 .../assets/imgs/page_icon_imgs/training.png   |   Bin 0 -> 822490 bytes
 .../assets/imgs/page_icon_imgs/txt2img.png    |   Bin 0 -> 314439 bytes
 .../assets/imgs/page_icon_imgs/upscale.png    |   Bin 0 -> 424630 bytes
 electron_app/src/background.js                |    15 +-
 electron_app/src/bridge.js                    |     3 +-
 electron_app/src/components/AppletPage.vue    |   128 +
 electron_app/src/components/BasicSDApplet.vue |   313 +
 electron_app/src/components/ControlNet.vue    |   319 -
 .../src/components/DownloadButton.vue         |    71 +
 .../src/components/GenerationGallery.vue      |   158 +
 electron_app/src/components/History.vue       |   220 -
 electron_app/src/components/Img2Img.vue       |   313 -
 electron_app/src/components/ImgGenerate.vue   |   364 -
 electron_app/src/components/Inpainting.vue    |   310 -
 electron_app/src/components/MainToolbar.vue   |   154 +
 electron_app/src/components/Outpainting.vue   |   570 -
 electron_app/src/components/PagesRouter.vue   |   173 +
 .../components/SDImageGenerationApplet.vue    |   163 +
 electron_app/src/components/Settings.vue      |   190 -
 electron_app/src/components/UpscaleImage.vue  |    60 -
 .../{ImageItem.vue => _REM_ImageItem.vue}     |     0
 .../src/components/image_menu_functions.js    |   113 +
 .../src/components_bare/ApplicationFrame.vue  |   409 +-
 .../src/components_bare/CircleProgress.vue    |    94 +
 electron_app/src/components_bare/Form.vue     |   236 +-
 .../src/components_bare/FormInput.vue         |   160 -
 .../components_bare/GalleryContainerBare.vue  |    96 -
 .../src/components_bare/GalleryImage.vue      |   139 +
 .../src/components_bare/GalleryItem.vue       |   423 -
 .../src/components_bare/GalleryPane.vue       |   214 +
 .../src/components_bare/ImageCanvas.vue       |    32 +-
 .../src/components_bare/LoaderModal.vue       |     2 +-
 .../src/components_bare/SDOptionsDropdown.vue |   534 -
 .../components_bare/TwoColAppletLayout.vue    |    77 +
 .../src/components_bare/empty_component.vue   |     6 +-
 .../src/components_bare/icon_library.js       |   124 +
 .../components_bare/inputform/Accordian.vue   |    51 +
 .../inputform/BetterSelector.vue              |   115 +
 .../components_bare/inputform/Checkbox.vue    |   151 +
 .../components_bare/inputform/Dropdown.vue    |    74 +
 .../inputform/FilePathTextBox.vue             |    57 +
 .../inputform/FormInputMixin.vue              |    95 +
 .../components_bare/inputform/ImageInput.vue  |   128 +
 .../inputform/InputWithDesc.vue               |    46 +
 .../components_bare/inputform/OutputImage.vue |    62 +
 .../components_bare/inputform/OutputText.vue  |    42 +
 .../inputform/ResolveInputComponent.vue       |   147 +
 .../src/components_bare/inputform/Slider.vue  |    98 +
 .../components_bare/inputform/Textarea.vue    |    49 +
 .../src/components_bare/inputform/Textbox.vue |    47 +
 electron_app/src/fake_backend.py              |    37 +-
 electron_app/src/forms/sample_ext_applet.json |    33 +
 electron_app/src/forms/sd_options_adv.json    |   433 +
 electron_app/src/init_vue_libs.js             |    27 +-
 electron_app/src/main.js                      |     4 +
 electron_app/src/native_functions.js          |   186 +-
 electron_app/src/pages/BlankPage.vue          |    31 +
 electron_app/src/pages/ContactUs.vue          |    58 +
 electron_app/src/pages/History.vue            |   302 +
 electron_app/src/pages/Homepage.vue           |   139 +
 electron_app/src/pages/Img2Img.vue            |    81 +
 electron_app/src/pages/Inpainting.vue         |   387 +
 electron_app/src/pages/Logs.vue               |    39 +
 electron_app/src/pages/ModelStore.vue         |   262 +
 electron_app/src/pages/PostProcessImage.vue   |   146 +
 electron_app/src/pages/Settings.vue           |   121 +
 electron_app/src/pages/Training.vue           |    37 +
 electron_app/src/pages/Txt2Img.vue            |    45 +
 electron_app/src/preload.js                   |    52 +-
 electron_app/src/py_vue_bridge.js             |     6 +-
 electron_app/src/utils.js                     |   162 +-
 .../src/utils/controlnet_frontend_utils.js    |   184 +
 electron_app/src/utils/in_out_paint_utils.js  |    90 +
 electron_app/vue.config.js                    |     6 +-
 package-lock.json                             |     6 +
 162 files changed, 19923 insertions(+), 33052 deletions(-)
 rename backends/stable_diffusion/{control_processors => applets}/__init__.py (100%)
 create mode 100644 backends/stable_diffusion/applets/applets.py
 create mode 100644 backends/stable_diffusion/applets/form_utils.py
 create mode 100644 backends/stable_diffusion/applets/frame_interpolator.py
 create mode 100644 backends/stable_diffusion/applets/options.py
 create mode 100644 backends/stable_diffusion/applets/sample_applet.py
 delete mode 100644 backends/stable_diffusion/build.sh
 delete mode 100644 backends/stable_diffusion/downloader.py
 delete mode 100644 backends/stable_diffusion/environment_m1.yml
 rename backends/stable_diffusion/{schedulers => fake_interface}/__init__.py (100%)
 rename backends/stable_diffusion/{fake_interface.py => fake_interface/interface.py} (59%)
 delete mode 100644 backends/stable_diffusion/requirements_m1.txt
 delete mode 100644 backends/stable_diffusion/setup.py
 delete mode 100644 backends/stable_diffusion/stable_diffusion.py
 rename backends/stable_diffusion/{utils => stable_diffusion}/__init__.py (100%)
 rename backends/stable_diffusion/{ => stable_diffusion}/clip_tokenizer/__init__.py (93%)
 rename backends/stable_diffusion/{ => stable_diffusion}/clip_tokenizer/bpe_simple_vocab_16e6.txt.gz (100%)
 create mode 100644 backends/stable_diffusion/stable_diffusion/clip_tokenizer/xl_text_projection_mat.npy
 create mode 100644 backends/stable_diffusion/stable_diffusion/control_processors/__init__.py
 rename backends/stable_diffusion/{ => stable_diffusion}/control_processors/process_body_pose.py (100%)
 create mode 100644 backends/stable_diffusion/stable_diffusion/control_processors/process_lineart.py
 rename backends/stable_diffusion/{ => stable_diffusion}/control_processors/process_midas_depth.py (89%)
 create mode 100644 backends/stable_diffusion/stable_diffusion/plugins/__init__.py
 create mode 100644 backends/stable_diffusion/stable_diffusion/plugins/base_plugin.py
 create mode 100644 backends/stable_diffusion/stable_diffusion/plugins/controlnet.py
 create mode 100644 backends/stable_diffusion/stable_diffusion/plugins/inpainting.py
 create mode 100644 backends/stable_diffusion/stable_diffusion/plugins/plugin_system.py
 create mode 100644 backends/stable_diffusion/stable_diffusion/plugins/sd15_inpainting.py
 create mode 100644 backends/stable_diffusion/stable_diffusion/schedulers/__init__.py
 create mode 100644 backends/stable_diffusion/stable_diffusion/schedulers/get_scheduler.py
 rename backends/stable_diffusion/{ => stable_diffusion}/schedulers/k_euler.py (100%)
 rename backends/stable_diffusion/{ => stable_diffusion}/schedulers/k_euler_ancestral.py (100%)
 create mode 100644 backends/stable_diffusion/stable_diffusion/schedulers/karras_scheduler.py
 rename backends/stable_diffusion/{ => stable_diffusion}/schedulers/scheduler_mixin.py (100%)
 rename backends/stable_diffusion/{ => stable_diffusion}/schedulers/scheduling_ddim.py (100%)
 rename backends/stable_diffusion/{ => stable_diffusion}/schedulers/scheduling_lms_discrete.py (100%)
 rename backends/stable_diffusion/{ => stable_diffusion}/schedulers/scheduling_pndm.py (100%)
 create mode 100644 backends/stable_diffusion/stable_diffusion/sd_run.py
 create mode 100644 backends/stable_diffusion/stable_diffusion/stable_diffusion.py
 create mode 100644 backends/stable_diffusion/stable_diffusion/utils/__init__.py
 rename backends/stable_diffusion/{ => stable_diffusion}/utils/extra_model_utils.py (68%)
 create mode 100644 backends/stable_diffusion/stable_diffusion/utils/image_preprocess.py
 rename backends/stable_diffusion/{ => stable_diffusion}/utils/logging.py (100%)
 create mode 100644 backends/stable_diffusion/stable_diffusion/utils/model_interface.py
 rename backends/stable_diffusion/{ => stable_diffusion/utils}/stdin_input.py (100%)
 create mode 100644 backends/stable_diffusion/stable_diffusion/utils/utils.py
 delete mode 100644 backends/stable_diffusion/test_assets/ddd.png
 delete mode 100644 backends/stable_diffusion/test_assets/inp_command_strings.txt
 delete mode 100644 backends/stable_diffusion/test_assets/mmm.png
 delete mode 100644 backends/stable_diffusion/test_assets/scribble_turtle.png
 delete mode 100644 backends/stable_diffusion/test_assets/scribble_turtle_2.png
 delete mode 100644 backends/stable_diffusion/test_assets/yoga1.jpg
 delete mode 100644 backends/stable_diffusion/test_assets/yoga1.jpg.processed_body_pose.jpg
 delete mode 100644 backends/stable_diffusion/tests.py
 rename DOCUMENTATION.md => docs/DOCUMENTATION.md (100%)
 create mode 100644 docs/Running_from_source.md
 delete mode 100644 electron_app/.nvmrc
 delete mode 100644 electron_app/afterSignHook.js
 create mode 100644 electron_app/src/AssetsManager.vue
 create mode 100644 electron_app/src/SDManager.vue
 create mode 100644 electron_app/src/assets/imgs/blank_illus4.png
 create mode 100644 electron_app/src/assets/imgs/blank_illus4_dark.png
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/default.png
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/default1.png
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/deforum.gif
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/history.png
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/img2img.png
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/inpainting.png
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/inpainting_1.png
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/interpolate.gif
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/models.png
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/models0.png
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/outpainting.png
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/settings.png
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/training.png
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/txt2img.png
 create mode 100644 electron_app/src/assets/imgs/page_icon_imgs/upscale.png
 create mode 100644 electron_app/src/components/AppletPage.vue
 create mode 100644 electron_app/src/components/BasicSDApplet.vue
 delete mode 100644 electron_app/src/components/ControlNet.vue
 create mode 100644 electron_app/src/components/DownloadButton.vue
 create mode 100644 electron_app/src/components/GenerationGallery.vue
 delete mode 100644 electron_app/src/components/History.vue
 delete mode 100644 electron_app/src/components/Img2Img.vue
 delete mode 100644 electron_app/src/components/ImgGenerate.vue
 delete mode 100644 electron_app/src/components/Inpainting.vue
 create mode 100644 electron_app/src/components/MainToolbar.vue
 delete mode 100644 electron_app/src/components/Outpainting.vue
 create mode 100644 electron_app/src/components/PagesRouter.vue
 create mode 100644 electron_app/src/components/SDImageGenerationApplet.vue
 delete mode 100644 electron_app/src/components/Settings.vue
 delete mode 100644 electron_app/src/components/UpscaleImage.vue
 rename electron_app/src/components/{ImageItem.vue => _REM_ImageItem.vue} (100%)
 create mode 100644 electron_app/src/components/image_menu_functions.js
 create mode 100644 electron_app/src/components_bare/CircleProgress.vue
 delete mode 100644 electron_app/src/components_bare/FormInput.vue
 delete mode 100644 electron_app/src/components_bare/GalleryContainerBare.vue
 create mode 100644 electron_app/src/components_bare/GalleryImage.vue
 delete mode 100644 electron_app/src/components_bare/GalleryItem.vue
 create mode 100644 electron_app/src/components_bare/GalleryPane.vue
 delete mode 100644 electron_app/src/components_bare/SDOptionsDropdown.vue
 create mode 100644 electron_app/src/components_bare/TwoColAppletLayout.vue
 create mode 100644 electron_app/src/components_bare/icon_library.js
 create mode 100644 electron_app/src/components_bare/inputform/Accordian.vue
 create mode 100644 electron_app/src/components_bare/inputform/BetterSelector.vue
 create mode 100644 electron_app/src/components_bare/inputform/Checkbox.vue
 create mode 100644 electron_app/src/components_bare/inputform/Dropdown.vue
 create mode 100644 electron_app/src/components_bare/inputform/FilePathTextBox.vue
 create mode 100644 electron_app/src/components_bare/inputform/FormInputMixin.vue
 create mode 100644 electron_app/src/components_bare/inputform/ImageInput.vue
 create mode 100644 electron_app/src/components_bare/inputform/InputWithDesc.vue
 create mode 100644 electron_app/src/components_bare/inputform/OutputImage.vue
 create mode 100644 electron_app/src/components_bare/inputform/OutputText.vue
 create mode 100644 electron_app/src/components_bare/inputform/ResolveInputComponent.vue
 create mode 100644 electron_app/src/components_bare/inputform/Slider.vue
 create mode 100644 electron_app/src/components_bare/inputform/Textarea.vue
 create mode 100644 electron_app/src/components_bare/inputform/Textbox.vue
 create mode 100644 electron_app/src/forms/sample_ext_applet.json
 create mode 100644 electron_app/src/forms/sd_options_adv.json
 create mode 100644 electron_app/src/pages/BlankPage.vue
 create mode 100644 electron_app/src/pages/ContactUs.vue
 create mode 100644 electron_app/src/pages/History.vue
 create mode 100644 electron_app/src/pages/Homepage.vue
 create mode 100644 electron_app/src/pages/Img2Img.vue
 create mode 100644 electron_app/src/pages/Inpainting.vue
 create mode 100644 electron_app/src/pages/Logs.vue
 create mode 100644 electron_app/src/pages/ModelStore.vue
 create mode 100644 electron_app/src/pages/PostProcessImage.vue
 create mode 100644 electron_app/src/pages/Settings.vue
 create mode 100644 electron_app/src/pages/Training.vue
 create mode 100644 electron_app/src/pages/Txt2Img.vue
 create mode 100644 electron_app/src/utils/controlnet_frontend_utils.js
 create mode 100644 electron_app/src/utils/in_out_paint_utils.js
 create mode 100644 package-lock.json

diff --git a/README.md b/README.md
index 8b12d029..91b3212d 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,8 @@
 # Diffusion Bee - Stable Diffusion GUI App for MacOS
 [![Twitter](https://img.shields.io/twitter/url.svg?label=Follow%20%40divamgupta&style=social&url=https%3A%2F%2Ftwitter.com%2Fdivamgupta)](https://twitter.com/divamgupta)
 
+a
+
 
 ### Diffusion Bee is the easiest way to run Stable Diffusion locally on your Intel / M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed.
 
@@ -14,6 +16,7 @@
 Download at https://diffusionbee.com/
 
 
+
 <br>
 
 For prompt ideas visit https://arthub.ai
diff --git a/backends/model_converter/convert_model.py b/backends/model_converter/convert_model.py
index cf8ff32c..a9839a08 100644
--- a/backends/model_converter/convert_model.py
+++ b/backends/model_converter/convert_model.py
@@ -42,6 +42,12 @@ def convert_model(checkpoint_filename=None, out_filename=None,  torch_weights=No
 
 
     for k in (list(state_dict.keys())):
+
+        if ".encoder." in k or ".decoder." in k:
+            for v , s  in [('q' , 'to_q') , ('v' , 'to_v' ) , ('k' , 'to_k') , ('proj_out' , 'to_out.0')]:
+                if f'.{s}.' in k:
+                    state_dict[ k.replace(f'.{s}.' , f'.{v}.') ] = state_dict[k]
+
         if '.norm' in k and '.bias' in k:
             k2 = k.replace(".bias" , ".weight")
             k3 = k.replace(".bias" , ".bias_by_weight")
@@ -106,6 +112,15 @@ def convert_model(checkpoint_filename=None, out_filename=None,  torch_weights=No
         outfile.write_key(key=k , tensor=np_arr)
 
     outfile.finish_write()
+    sd_version = model_type.replace("_float16" , "").replace("_float32" , "") 
+    if sd_version in ["SD_1x" , "SD_2x"]:
+        sd_type = "sd_model"
+    elif sd_version in ["SD_1x_inpaint" , "SD_2x_inpaint"]:
+        sd_type = "sd_model_inpaint"
+    else:
+        raise ValueError("Invalid sd_version "+ sd_version)
+    model_metadata = {"float_type" : cur_dtype , "sd_type" :sd_version, "type" : sd_type }
+    print("__converted_model_data__" , json.dumps(model_metadata))
 
 
 def usage():
diff --git a/backends/model_converter/sd_shapes.py b/backends/model_converter/sd_shapes.py
index 528a1937..05a81e8f 100644
--- a/backends/model_converter/sd_shapes.py
+++ b/backends/model_converter/sd_shapes.py
@@ -77,7 +77,10 @@ def add_aux_shapes(d):
     "SD_1x_float16": 1012 , 
     "SD_1x_inpaint_float16": 1013 , 
     "SD_1x_just_controlnet_16" : 1014,
-    "SD_2x_float16": 1015 }
+    "SD_2x_float16": 1015 ,
+    "sdxl_base_unet_f8_rest_f16" : 3031,
+    }
+
 
 
 extra_keys = ['temb_coefficients_fp32' , 'temb_coefficients_fp16' , 'causal_mask' , 'aux_output_conv.weight' , 'aux_output_conv.bias', 'alphas_cumprod']
diff --git a/backends/model_converter/tdict.py b/backends/model_converter/tdict.py
index 425a171d..fe6e49f1 100644
--- a/backends/model_converter/tdict.py
+++ b/backends/model_converter/tdict.py
@@ -22,7 +22,7 @@ def pad_bytes(self, nb):
         self.out_file.write(b'\x00' * nb )
         self.filep += nb
 
-    def write_block(self, block_array):
+    def write_block(self, block_array ):
 
         if self.filep  %64 != 0:
             npad = 64 - self.filep  % 64
@@ -73,7 +73,11 @@ def read_block(self, header_pos, np_shape=None, np_dtype=None):
         block  = self.in_file.read(l)
 
         if np_dtype is not None:
-            block = np.frombuffer(block, dtype=np_dtype)
+            if "cus_" in np_dtype: #custom dtype, which is not supported by numpy 
+                block = np.frombuffer(block, dtype='uint8')
+                block = decode_custom_dtype(block , np_dtype )
+            else:
+                block = np.frombuffer(block, dtype=np_dtype)
 
         if np_shape is not None:
             block = block.reshape(np_shape)
@@ -145,13 +149,24 @@ def read_key(self , key):
         assert len(ret_arr.tobytes()) == w_idx_len
         return ret_arr.copy()
 
-    def write_key(self , key , tensor):
+    def write_key(self , key , tensor, custom_dtype=None ):
         assert key not in self.keys_info
         dtype = str(tensor.dtype)
+        if custom_dtype is not None:
+            dtype = custom_dtype
+            raise not NotImplementedError("Casting not implemented.")
+
         write_info = self.write_block(tensor)
         shape = list(tensor.shape)
         self.keys_info[key] = {"start": write_info['n_start_data'] , "end" : write_info['n_end_data'] , "shape": shape , "dtype" : dtype }
 
+    def write_key_custom_dype(self, uint8_arr , key, custom_dtype , shape ):
+        assert key not in self.keys_info
+        dtype = custom_dtype
+        write_info = self.write_block(uint8_arr)
+        self.keys_info[key] = {"start": write_info['n_start_data'] , "end" : write_info['n_end_data'] , "shape": shape , "dtype" : dtype }
+
+
     def finish_write(self):
 
         if self.filep  %64 != 0:
diff --git a/backends/stable_diffusion/control_processors/__init__.py b/backends/stable_diffusion/applets/__init__.py
similarity index 100%
rename from backends/stable_diffusion/control_processors/__init__.py
rename to backends/stable_diffusion/applets/__init__.py
diff --git a/backends/stable_diffusion/applets/applets.py b/backends/stable_diffusion/applets/applets.py
new file mode 100644
index 00000000..5fe976d8
--- /dev/null
+++ b/backends/stable_diffusion/applets/applets.py
@@ -0,0 +1,58 @@
+import json
+
+def update_state_raw(key , val ):
+    print( "utds " +  key + "___U_P_D_A_T_E___" + json.dumps(val))
+
+
+registered_applets = {}
+
+def register_applet(model_container, applet_cls):
+    applet_name = applet_cls.applet_name
+    applet = applet_cls()
+    applet.init_applet(model_container)
+    registered_applets[applet_name] = applet
+
+def run_applet(applet_name , params_dict):
+    registered_applets[applet_name].run(params_dict)
+
+
+class AppletBase:
+
+    applet_name = None
+    applet_title = None
+    is_stop_avail = False
+    applet_description = ""
+    applet_icon = "file"
+    applet_icon_fname = None
+    
+    def run(self, params):
+        raise NotImplementedError("base cls")
+
+    def get_input_form(self):
+        return []
+    
+    def update_output( self, key , val ):
+        self.update_state( "outputs." + key , val)
+
+    def update_state(self , key  , val ):
+        key = "registered_ext_applets." + self.applet_name + "." +  key
+        update_state_raw(key , val)
+
+    def init_applet(self, model_container):
+
+        self.model_container = model_container
+
+        update_state_raw( "registered_ext_applets." + self.applet_name , {})
+        update_state_raw( "registered_ext_applets." + self.applet_name + ".id" ,  self.applet_name)
+        update_state_raw( "registered_ext_applets." + self.applet_name + ".title" ,  self.applet_title)
+        update_state_raw( "registered_ext_applets." + self.applet_name + ".description" ,  self.applet_description)
+        update_state_raw( "registered_ext_applets." + self.applet_name + ".icon" ,  self.applet_icon )
+        if self.applet_icon_fname is not None:
+            update_state_raw( "registered_ext_applets." + self.applet_name + ".img_icon" ,  self.applet_icon_fname )        
+        update_state_raw( "registered_ext_applets." + self.applet_name + ".home_category" ,  "misc")
+        update_state_raw( "registered_ext_applets." + self.applet_name + ".inputs" ,   self.get_input_form() )
+        update_state_raw( "registered_ext_applets." + self.applet_name + ".outputs" ,   [] )
+        update_state_raw( "registered_ext_applets." + self.applet_name + ".is_stop_avail" ,   self.is_stop_avail )
+
+
+        
diff --git a/backends/stable_diffusion/applets/form_utils.py b/backends/stable_diffusion/applets/form_utils.py
new file mode 100644
index 00000000..1993b3ee
--- /dev/null
+++ b/backends/stable_diffusion/applets/form_utils.py
@@ -0,0 +1,75 @@
+import random
+
+def get_textbox(id, type="str" , default="" ,  title="" , description=""):
+
+    types = {"str" : "text" , "int" : "number" , "float" : "number"}
+
+    return {
+                "id": str(random.randint(0,19989999)),
+                "component": "InputWithDesc",
+                "title": title,
+                "description":description ,
+                "children": [
+                    {
+                        "id": id,
+                        "component": "Textbox",
+                        "placeholder" : "",
+                        "default_value" : default ,
+                        "type" : types[type],
+                        "output_type" :type ,
+                        "is_persistant" : False
+                    }
+                ]
+            }
+
+def get_output_text(text):
+    return {
+        "id":  str(random.randint(0,19989999)),
+        "component": "OutputText",
+        "text" : text
+    }
+def get_output_img(img_path, save_ext='.png' , is_save=False):
+    return {
+        "id":  str(random.randint(0,19989999)),
+        "component": "OutputImage",
+        "img_path" : img_path,
+        "is_save" : is_save , 
+        "save_ext" : save_ext 
+    }
+
+def get_file_textbox(id , path_type="",  title="" , description="" ):
+    return {
+                "id":  str(random.randint(0,19989999)),
+                "component": "InputWithDesc",
+                "full_width": True,
+                "title": title,
+                "description": description,
+                "children": [
+                    {
+                        "id": id ,
+                        "component": "FilePathTextBox",
+                        "placeholder" : "",
+                        "is_persistant" : False,
+                        "path_type" : path_type
+                    },
+                ]
+            }
+
+def get_textarea(id ,   title="" , description="" ):
+    return {
+                "id":  str(random.randint(0,19989999)),
+                "component": "InputWithDesc",
+                "full_width": True,
+                "title": title,
+                "description": description,
+                "children": [
+                    {
+                        "id": id ,
+                        "component": "Textarea",
+                        "placeholder" : title ,
+                        "is_small" : True,
+                        "is_persistant" : False,
+                    },
+                ]
+            }
+
diff --git a/backends/stable_diffusion/applets/frame_interpolator.py b/backends/stable_diffusion/applets/frame_interpolator.py
new file mode 100644
index 00000000..c1f7db74
--- /dev/null
+++ b/backends/stable_diffusion/applets/frame_interpolator.py
@@ -0,0 +1,179 @@
+from .applets import AppletBase
+import json
+from .form_utils import get_textbox , get_file_textbox , get_output_text , get_textarea, get_output_img
+from stable_diffusion.stable_diffusion import StableDiffusion
+from interface import ModelInterface
+import copy
+import numpy as np
+import math
+from stable_diffusion.plugins.base_plugin import BasePlugin
+from stable_diffusion.utils.utils import get_sd_run_from_dict, sd_bee_stop_callback
+import os 
+from PIL import Image
+from stable_diffusion.sd_run import SDRun 
+from dataclasses import fields
+import random
+from .options import options
+
+class InterpolatorHelperPlugin(BasePlugin):
+    def hook_post_prepare_init_latent(self, sd_run):
+        if self.parent.do_interpolate:
+            sd_run.init_latent = self.parent.latent_a * self.parent.frac_a_latent + self.parent.latent_b * self.parent.frac_b_latent
+            sd_run.latent = sd_run.init_latent
+        elif self.parent.save_a:
+            self.parent.latent_a = np.copy(sd_run.init_latent)
+        elif self.parent.save_b:
+            self.parent.latent_b = np.copy(sd_run.init_latent)
+        else:
+            raise ValueError("Err in hook_post_prepare_init_latent for interpolate")
+    
+    def hook_post_generate_text_emb(self, sd_run):
+        if self.parent.do_interpolate:
+            sd_run.context = self.parent.context_a *  self.parent.frac_a_context  +  self.parent.context_b * self.parent.frac_b_context
+        elif self.parent.save_a:
+            self.parent.context_a = np.copy(sd_run.context)
+        elif self.parent.save_b:
+            self.parent.context_b = np.copy(sd_run.context)
+
+
+
+class FrameInterpolator(AppletBase):
+
+    applet_name = "frame_interpolate"
+    applet_title = "Interpolator"
+    applet_description = "Generate videos by interpolating prompts and seeds"
+    is_stop_avail = True
+    applet_icon_fname = "interpolate.gif"
+
+    def get_input_form(self):
+
+        my_el = [
+            get_textbox("num_frames", type="int" ,  default=40,  title="Number of frames" , description="The number of frames you want in the video."),
+
+            get_textbox("seed1", type="int" ,    title="Start Seed" , description="The seed from which it will start the video."), 
+            get_textarea("prompt1", title="Start Prompt" , description="The prompt from which it will start the video."),
+            
+            get_textbox("seed2", type="int" ,    title="End Seed" , description="The seed to which it will end the video. Keep it same as start seed if you dont want to change the seed in the video."), 
+            get_textarea("prompt2", title="End Prompt" , description="The prompt to which it will end the video. Keep it same as start prompt if you dont want to change the prompt in the video."),
+
+            get_output_text("The following options will remain constant in the whole video:")
+        ]
+
+        form =  json.loads(options)
+        form = [f for f in form if not f['id'] in [ 'controlnet_acc' , 'seed_acc' , 'seed_desc' , 'prompt',  'num_imgs_desc']]
+        return my_el +  form
+    
+    def update_progress(self , n_img_done, n_total, cur_img=None):
+        oo = [get_output_text(f"Rendering... \n\n Rendered {n_img_done} out of {n_total} images.")] 
+        if cur_img is not None:
+            if type(cur_img) is not str:
+                fn = "/tmp/" + str(random.randint(0,10000)) + ".jpg"
+                cur_img = cur_img.resize( [ s//2 for s in cur_img.size] )
+                cur_img = cur_img.save(fn)
+            oo.append(get_output_text("Current frame:"))
+            oo.append(get_output_img(fn))
+        self.update_state("outputs" , oo )
+    
+    def stopped(self):
+        oo = [get_output_text(f"Stopped")] 
+        self.update_state("outputs" , oo )
+
+    def run(self , params ):
+
+        if "num_frames" not in params or params['num_frames'] < 3:
+            raise ValueError("Enter a valid number of frames")
+        n_total = int(params['num_frames'])
+        
+        if "seed1" not in params or params['seed1'] < 1:
+            raise ValueError("Enter a valid start seed")
+        seed1 = int(params['seed1'])
+        
+        if "seed2" not in params or params['seed2'] < 1:
+            raise ValueError("Enter a valid end seed")
+        seed2 = int(params['seed2'])
+        
+        if "prompt1" not in params or len(params['prompt1']) < 5:
+            raise ValueError("Enter a valid start prompt")
+        prompt1 = str(params['prompt1'])
+
+        if "prompt2" not in params or len(params['prompt2']) < 5:
+            raise ValueError("Enter a valid end prompt")
+        prompt2 = str(params['prompt2'])
+        
+
+        # params = json.dumps(params)
+        params = copy.deepcopy(params)
+
+        generator = StableDiffusion( self.model_container , ModelInterface , None , model_name=None, callback=sd_bee_stop_callback )
+        generator.add_plugin(InterpolatorHelperPlugin)
+
+        rendered_imgs = []
+        
+        generator.do_interpolate = False
+        generator.save_a = True
+        generator.save_b = False
+        params['seed'] = seed1
+        params['prompt'] = prompt1
+        sd_run = get_sd_run_from_dict(params)
+
+        self.update_progress(0 , n_total)
+        img = generator.generate(sd_run)
+        if img is None:
+            return self.stopped()
+        img = Image.fromarray(img['img'][0]) 
+        rendered_imgs.append(img)
+        self.update_progress(1 , n_total, rendered_imgs[-1])
+
+        generator.do_interpolate = False
+        generator.save_b = True
+        generator.save_a = False
+        params['seed'] = seed2
+        params['prompt'] = prompt2
+        sd_run = get_sd_run_from_dict(params)
+        
+        img = generator.generate(sd_run)
+        if img is None:
+            return self.stopped()
+        im_end = Image.fromarray(img['img'][0]) 
+        self.update_progress(2 , n_total, rendered_imgs[-1])
+
+        N = n_total - 1
+
+        for i in range(1 , N):
+            frac = float(i) / N
+            generator.do_interpolate = True 
+            generator.interpolate_frac = frac
+            # generator.frac_a = np.cos( generator.interpolate_frac * np.pi / 2 )
+            # generator.frac_b = np.sin( generator.interpolate_frac * np.pi / 2 )
+            if seed1 != seed2:
+                generator.frac_a_latent = np.sqrt(1 - frac )
+                generator.frac_b_latent  = np.sqrt( frac )
+            else:
+                generator.frac_a_latent = 0.5
+                generator.frac_b_latent = 0.5
+
+            generator.frac_a_context = (1 - frac )
+            generator.frac_b_context  =  ( frac )
+
+            sd_run = get_sd_run_from_dict(params)
+            img = generator.generate(sd_run)
+            if img is None:
+                return self.stopped()
+            img = Image.fromarray(img['img'][0]) 
+            rendered_imgs.append(img)
+            self.update_progress(2+i , n_total, rendered_imgs[-1])
+
+        rendered_imgs.append(im_end)    
+
+        fn = "/tmp/" + str(random.randint(0,10000)) + ".gif"
+        rendered_imgs[0].save(fn, format='GIF', append_images=rendered_imgs[1:] , save_all=True , loop=0)
+        self.update_state("outputs" , [get_output_img(fn , save_ext='.gif' , is_save=True)] )
+
+    
+        
+
+        
+
+
+
+
diff --git a/backends/stable_diffusion/applets/options.py b/backends/stable_diffusion/applets/options.py
new file mode 100644
index 00000000..033b49f1
--- /dev/null
+++ b/backends/stable_diffusion/applets/options.py
@@ -0,0 +1,346 @@
+options = """
+
+
+[
+    {
+            "id" : "input_img",
+            "component" : "ImageInput",
+            "include_in" : ["img2img"] , 
+            "get_img_size" : true,
+            "draw_mask": true,
+            "store_masked_image" : true
+
+    },
+    {
+        "id" : "prompt",
+        "component": "Textarea",
+        "placeholder" : "Enter your prompt here",
+        "default_value" : ""
+    },
+    {
+        "id" : "negative_prompt",
+        "component": "Textarea",
+        "placeholder" : "Enter your negative prompt here",
+        "is_small" : true,
+        "include_in" : ["advanced"]
+    },
+    
+    {
+        "id": "is_adv_mode_desc",
+        "component": "InputWithDesc",
+        "title": "Advanced Options",
+        "description": "",
+        "children": [
+            {
+                "id": "is_adv_mode",
+                "component": "Checkbox",
+                "default_value" : false,
+                "is_persistant" : true
+            }
+        ]
+    },
+
+    {
+        "id": "selected_sd_model_desc",
+        "component": "InputWithDesc",
+        "title": "Model",
+        "description": "The Stable Diffusion model used to generate images.",
+        "children": [
+            {
+                "id": "selected_sd_model",
+                "component": "Dropdown",
+                "options": ["Default_SD1.5" ],
+                "icon": "photo",
+                "output_type" : "str",
+                "default_value" : "Default_SD1.5",
+                "is_persistant" : true
+            }
+        ]
+    },
+
+    {
+        "id": "input_image_strength_desc",
+        "component": "InputWithDesc",
+        "title": "Input Strength",
+        "full_width": true,
+        "include_in" : ["img2img"],
+        "description": "How  closely to stick to the input image.  (lower numbers makes the AI do more change)",
+        "children": [
+            {
+                "id": "input_image_strength",
+                "component": "Slider",
+                "is_persistant" : true,
+                "max_val" : 100,
+                "min_val" : 2, 
+                "output_type" : "float",
+                "default_value" : 30
+            }
+        ]
+    },
+    {
+        "id": "resolution_desc",
+        "component": "InputWithDesc",
+        "title": "Resolution",
+        "exclude_in" : [ "outpainting" , "img2img" ],
+        "description": "",
+        "children": [
+            {
+                "id": "img_width",
+                "component": "Dropdown",
+                "options": [256, 320, 384, 448, 512, 576, 640, 704, 768],
+                "icon": "img_width",
+                "output_type" : "int",
+                "default_value" : 512,
+                "is_persistant" : true
+            },
+            {
+                "id": "img_height",
+                "component": "Dropdown",
+                "options": [256, 320, 384, 448, 512, 576, 640, 704, 768],
+                "default_value" : 512,
+                "icon": "img_height",
+                "output_type" : "int",
+                "is_persistant" : true
+            }
+        ]
+    },
+
+    {
+        "id": "num_imgs_desc",
+        "component": "InputWithDesc",
+        "title": "Number of images",
+        "exclude_in" : [ "outpainting"],
+        "description": "How many images are generated in total.",
+        "children": [
+            {
+                "id": "num_imgs",
+                "component": "Dropdown",
+                "options": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 30, 50, 100 , 500 , 2000],
+                "icon": "photo",
+                "default_value" : 1,
+                "output_type" : "int",
+                "type" : "number",
+                "is_persistant" : true
+            }
+        ]
+    },
+
+    {
+        "id": "seed_desc",
+        "component": "InputWithDesc",
+        "title": "Seed",
+        "description": "",
+        "children": [
+            {
+                "id": "seed",
+                "component": "Textbox",
+                "icon": "seed",
+                "placeholder" : "-1",
+                "output_type" : "int",
+                "type" : "number",
+                "is_persistant" : false
+            }
+        ]
+    },
+
+    {
+        "id": "num_steps_desc",
+        "component": "InputWithDesc",
+        "title": "Sampling Steps",
+        "description": "",
+        "children": [
+            {
+                "id": "num_steps",
+                "component": "Dropdown",
+                "options": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75],
+                "icon": "steps",
+                "type" : "number",
+                "output_type" : "int",
+                "default_value" : 25,
+                "is_persistant" : true
+            }
+        ]
+    },
+
+    {
+        "id": "diffusion_acc",
+        "component": "Accordian",
+        "title": "Diffusion",
+        "include_in" : ["advanced"],
+        "children": [
+            {
+                "id": "43545455",
+                "component": "InputWithDesc",
+                "title": "Sampler",
+                "description": "The sampling algorithm used by DiffusionBee.",
+                "children": [
+                    {
+                        "id": "scheduler",
+                        "component": "Dropdown",
+                        "options": ["ddim" , "lmsd" , "pndm" , "k_euler_ancestral", "k_euler"  ],
+                        "icon": "photo",
+                        "output_type" : "str",
+                        "default_value" : "ddim",
+                        "is_persistant" : true
+                    }
+                ]
+            },
+            {
+                "id": "53454543",
+                "component": "InputWithDesc",
+                "title": "Steps",
+                "description": "Iterations of the image (more steps means more detail & more processing time - best to start around 10)",
+                "children": [
+                    {
+                        "id": "num_steps",
+                        "component": "Dropdown",
+                        "options": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75],
+                        "icon": "steps",
+                        "type" : "number",
+                        "output_type" : "int",
+                        "default_value" : 25,
+                        "is_persistant" : true
+                    }
+                ]
+            },
+            {
+                "id": "32e43434",
+                "component": "InputWithDesc",
+                "title": "Guidance Scale",
+                "full_width": true,
+                "description": "How closely to follow your prompt (lower numbers give the AI more creativity)",
+                "children": [
+                    {
+                        "id": "guidance_scale",
+                        "component": "Slider",
+                        "is_persistant" : true,
+                        "max_val" : 20,
+                        "output_type" : "float",
+                        "min_val" : 1, 
+                        "default_value" : 7.5
+                    }
+                ]
+            }
+        ]
+    },
+    {
+        "id": "seed_acc",
+        "component": "Accordian",
+        "title": "Seed",
+        "include_in" : ["advanced"],
+        "children": [
+            {
+                "id": "765655",
+                "component": "InputWithDesc",
+                "title": "Seed",
+                "description": "Starting point for iterations (any random number will do; DB will pick one if left blank).",
+                "children": [
+                    {
+                        "id": "seed",
+                        "component": "Textbox",
+                        "icon": "seed",
+                        "placeholder" : "-1",
+                        "type" : "number",
+                        "output_type" : "int",
+                        "is_persistant" : false
+                    }
+                ]
+            } , 
+            {
+                "id": "76565345",
+                "component": "InputWithDesc",
+                "title": "Small Modification Seed",
+                "description": "If you want to do small variations in the images.",
+                "children": [
+                    {
+                        "id": "small_mod_seed",
+                        "component": "Textbox",
+                        "icon": "seed",
+                        "placeholder" : "-1",
+                        "type" : "number",
+                        "output_type" : "int",
+                        "is_persistant" : false
+                    }
+                ]
+            } 
+        ]
+    }, 
+    {
+        "id": "controlnet_acc",
+        "component": "Accordian",
+        "title": "ControlNet",
+        "include_in" : ["advanced"],
+        "exclude_in" : [ "outpainting" ],
+        "children": [
+            
+            {
+                "id": "344345435",
+                "component": "InputWithDesc",
+                "title": "ControlNet Model",
+                "description": "",
+                "children": [
+                    {
+                        "id": "controlnet_model",
+                        "component": "Dropdown",
+                        "options": ["None" , "Depth" , "BodyPose" , "Scribble" ],
+                        "default_value" : "None",
+                        "icon": "photo",
+                        "is_persistant" : false
+                    }
+                ]
+            } , 
+            {
+                "id" : "controlnet_input_image_path",
+                "component" : "ImageInput"
+            } , 
+            {
+                "id": "678545",
+                "component": "InputWithDesc",
+                "title": "Automatically generate control?",
+                "description": "If you select No, you have to input raw control image.",
+                "children": [
+                    {
+                        "id": "do_controlnet_preprocess",
+                        "component": "Dropdown",
+                        "options": ["Yes" , "No"   ],
+                        "output_type" : "bool",
+                        "default_value" : "Yes",
+                        "icon": "photo",
+                        "is_persistant" : true
+                    }
+                ]
+            } 
+
+        ]
+    } , 
+
+    {
+        "id": "misc_acc",
+        "component": "Accordian",
+        "title": "Misc",
+        "include_in" : ["advanced"],
+        "children": [
+            {
+                "id": "678545",
+                "component": "InputWithDesc",
+                "title": "V-Prediction",
+                "description": "If it should use V-Prediction. Mostly used in SD2.X 768 models. ",
+                "children": [
+                    {
+                        "id": "do_v_prediction",
+                        "component": "Checkbox",
+                        "output_type" : "bool",
+                        "default_value" : false,
+                        "is_persistant" : false
+                    }
+                ]
+            } 
+        ]
+    } 
+
+
+]
+
+
+
+"""
\ No newline at end of file
diff --git a/backends/stable_diffusion/applets/sample_applet.py b/backends/stable_diffusion/applets/sample_applet.py
new file mode 100644
index 00000000..a4edbfcb
--- /dev/null
+++ b/backends/stable_diffusion/applets/sample_applet.py
@@ -0,0 +1,13 @@
+from .applets import AppletBase
+import json
+
+class MergeLora(AppletBase):
+
+    applet_name = "prompt_seed_interpolate"
+    applet_title = "Interpolate Prompts and Seeds"
+
+    def get_input_form(self):
+        return []
+    
+    def run(self , params ):
+        self.update_state("outputs" , [] )
\ No newline at end of file
diff --git a/backends/stable_diffusion/build.sh b/backends/stable_diffusion/build.sh
deleted file mode 100644
index 2982dcb3..00000000
--- a/backends/stable_diffusion/build.sh
+++ /dev/null
@@ -1,6 +0,0 @@
-pyinstaller   diffusionbee_backend.py  --collect-all tensorflow --collect-all tensorflow-plugins  --noconfirm --clean
-cp stable_diffusion_tf/clip_tokenizer/bpe_simple_vocab_16e6.txt.gz ./dist/diffusionbee_backend
-
-cp -r ../realesrgan_ncnn/models  ./dist/diffusionbee_backend/models 
-cp  ../realesrgan_ncnn/realesrgan_ncnn_macos  ./dist/diffusionbee_backend/realesrgan_ncnn_macos 
-cp -r ../model_converter/convert_sd_model_bin/m1  ./dist/diffusionbee_backend/convert_model
diff --git a/backends/stable_diffusion/diffusionbee_backend.py b/backends/stable_diffusion/diffusionbee_backend.py
index a3290d0b..8bc6f379 100644
--- a/backends/stable_diffusion/diffusionbee_backend.py
+++ b/backends/stable_diffusion/diffusionbee_backend.py
@@ -1,12 +1,10 @@
 print("starting backend")
-
-from  stdin_input import is_avail, get_input
+import numpy as np
 import argparse
 from PIL import Image
 import json
 import random
 import multiprocessing
-from downloader import ProgressBarDownloader
 import sys
 import copy
 import math
@@ -14,11 +12,9 @@
 import traceback
 import os
 from pathlib import Path
-import importlib
-
 
 
-# b2py t2im {"prompt": "sun glasses" , "W":640 , "H" : 640 , "num_imgs" : 10 , "input_image":"/Users/divamgupta/Downloads/inn.png" , "mask_image" : "/Users/divamgupta/Downloads/maa.png" , "is_inpaint":true  }
+# b2py t2im {"prompt": "sun glasses" , "img_width":640 , "img_height" : 640 , "num_imgs" : 10 , "input_image":"/Users/divamgupta/Downloads/inn.png" , "mask_image" : "/Users/divamgupta/Downloads/maa.png" , "is_inpaint":true  }
 
 if not ( getattr(sys, 'frozen', False) and hasattr(sys, '_MEIPASS')):
     print("Adding sys paths")
@@ -32,8 +28,11 @@
 
 
 from convert_model import convert_model
-from stable_diffusion import StableDiffusion , image_preprocess_model_paths
+from stable_diffusion.stable_diffusion import StableDiffusion , ModelContainer
+from stable_diffusion.utils.utils import get_sd_run_from_dict
 
+from applets.applets import register_applet , run_applet
+from applets.frame_interpolator import FrameInterpolator
 # get the model interface form the environ
 USE_DUMMY_INTERFACE = False
 if  USE_DUMMY_INTERFACE :
@@ -41,6 +40,7 @@
 else:
     from interface import ModelInterface
 
+model_container = ModelContainer()
 
 
 
@@ -92,161 +92,28 @@ def __getattr__(self, attr):
 sys.stdout = Unbuffered(sys.stdout)
 
 
-def download_weights():
-    global p_15 , p_15_np
-
-    print("sdbk mltl Loading Model")
-
-    is_downloaded = False
-    for _ in range(10):
-        try:
-
-            p_15 = ProgressBarDownloader(title="Downloading Model 1/2").download(
-                        url="https://huggingface.co/divamgupta/stable_diffusion_mps/resolve/main/sd-v1-5_fp16.tdict",
-                        md5_checksum="a36c79b8edb4b21b75e50d5834d1f4ae",
-                        verify_ssl=False,
-                        extract_zip=False,
-                    )
-
-            p_15_np = ProgressBarDownloader(title="Downloading Model 2/2").download(
-                        url="https://huggingface.co/divamgupta/stable_diffusion_mps/resolve/main/sd-v1-5-inpainting_fp16.tdict",
-                        md5_checksum="68303f49cca00968c39abddc20b622a6",
-                        verify_ssl=False,
-                        extract_zip=False,
-                    )
-
-            is_downloaded = True
-            break
-        except Exception as e:
-            pass
-
-        time.sleep(10)
-
-    if not is_downloaded:
-        raise ValueError("Unable to download the model weights. Please try again and make sure you have free space and a working internet connection.")
-
-            
 
 
 
 def process_opt(d, generator):
 
-    batch_size = int(d['batch_size'])
+    batch_size = 1# int(d['batch_size'])
     n_imgs = math.ceil(d['num_imgs'] / batch_size)
+    sd_run = get_sd_run_from_dict(d)
 
-    second_tdict_path = None
-    inp_img_preprocesser = None
+    for i in range(n_imgs):
+        
+        sd_run.img_id = i
 
-    if d['model_id'] == 1:
-        model_mode = "inpaint_15"
-        tdict_path = p_15_np
-        print("sdbk mdvr 1.5_inp")
-    else:
-        tdict_path = p_15
-        print("sdbk mdvr 1.5")
-
-        if d['do_controlnet'] == True:
-
-            if "sd_1x_controlnet" not in generator.model.avail_models:
-                raise ValueError("ControlNet is not supported. Please upgrade to macOS13.0+")
-
-            if d['control_name'] == "body_pose":
-                second_tdict_path = ProgressBarDownloader(title="Downloading ControlNet Body Model 1/2").download(
-                        url="https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/just_control_sd15_openpose_fp16.tdict",
-                        md5_checksum="81077e9fe3472ed2242a7a3d8035b6eb",
-                        verify_ssl=False,
-                        extract_zip=False,
-                    )
-                if d['do_controlnet_preprocess']:
-                    image_preprocess_model_paths['body_pose'] = ProgressBarDownloader(title="Downloading ControlNet Body Model 2/2").download(
-                        url="https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/body_pose_model.onnx",
-                        md5_checksum="51499a50aff296971a99605f32c7e8e7",
-                        verify_ssl=False,
-                        extract_zip=False,
-                    )
-
-                    inp_img_preprocesser = "body_pose"
-            elif d['control_name'] == "scribble":
-                second_tdict_path = ProgressBarDownloader(title="Downloading ControlNet Scribble Model 1/1").download(
-                        url="https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/just_control_sd15_scribble_fp16.tdict",
-                        md5_checksum="2d29e2d006035919180e2f8b6decc40a",
-                        verify_ssl=False,
-                        extract_zip=False,
-                    )
-            elif d['control_name'] == "depth":
-                second_tdict_path = ProgressBarDownloader(title="Downloading ControlNet Depth Model 1/2").download(
-                        url="https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/just_control_sd15_depth_fp16.tdict",
-                        md5_checksum="652bb2d467e37ba8253b7361973c82b6",
-                        verify_ssl=False,
-                        extract_zip=False,
-                    )
-                if d['do_controlnet_preprocess']:
-                    inp_img_preprocesser = "midas_depth"
-                    image_preprocess_model_paths['midas_depth'] = ProgressBarDownloader(title="Downloading ControlNet Depth Model 2/2").download(
-                        url="https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/midas_monodepth.onnx",
-                        md5_checksum="3ad9d8a9d820214d2bfe65c0d37683a7",
-                        verify_ssl=False,
-                        extract_zip=False,
-                    )
-            else:
-                raise ValueError("invalid control name " +d['control_name'] )
-            model_mode = "controlnet"
-
-
-        elif "input_image" in d and  d['input_image' ] is not None and d['input_image'] != "" :
-            model_mode = "img2img"
-        else:
-            model_mode = "txt2img"
-
-    if d['model_id'] == -1:
-        cust_model_path = d['custom_model_path']
-        tdict_path = cust_model_path
-        print("sdbk mdvr custom_" + cust_model_path.split(os.sep)[-1].split(".")[0])
-
-    aux_imgs = []
+        print("got" , d )
 
-    for i in range(n_imgs):
-        if 'seed' in d:
-            seed = d['seed']
-        else:
-            seed = None
-        if 'soft_seed' in d:
-            soft_seed = d['soft_seed']
-        else:
-            soft_seed = None
-
-        outs  = generator.generate(
-            d['prompt'],
-            img_height=d["H"], img_width=d["W"],
-            num_steps=d['ddim_steps'],
-            guidance_scale=d['scale'],
-            temperature=1,
-            batch_size=batch_size,
-            seed=seed,
-            soft_seed=soft_seed,
-            img_id=i,
-            negative_prompt=d['negative_prompt'],
-            input_image=d['input_image'],
-            tdict_path=tdict_path,
-            second_tdict_path=second_tdict_path, 
-            inp_img_preprocesser=inp_img_preprocesser,
-            mode=model_mode,
-            scheduler=d['scheduler'],
-            mask_image=d['mask_image'],
-            input_image_strength=(float(d['img_strength'])),
-        )
+        outs  = generator.generate(sd_run)
 
         if outs is None:
             return
 
         img = outs['img']
 
-        if 'aux_img' in outs:
-            aux_img = outs['aux_img']
-            if aux_img not in aux_imgs:
-                aux_imgs.append(aux_img)
-                print("sdbk nwim %s"%(aux_img) )
-
         if img is None:
             return
         
@@ -255,19 +122,23 @@ def process_opt(d, generator):
             fpath = os.path.join(defualt_data_root , "%s_%d.png"%(s ,  random.randint(0 ,100000000)) )
 
             Image.fromarray(img[i]).save(fpath)
-            print("sdbk nwim %s"%(fpath) )
+            ret_dict = {"generated_img_path" : fpath}
+
+            if 'aux_img' in outs:
+                ret_dict['aux_output_image_path'] = outs['aux_img']
+
+            print("sdbk nwim %s"%(json.dumps(ret_dict)) )
 
 
 
 
 def diffusion_bee_main():
 
-    global p_15 , p_15_np
-    download_weights()
+    time.sleep(2)
+    register_applet(model_container , FrameInterpolator)
 
     print("sdbk mltl Loading Model")
 
-
     def callback(state="" , progress=-1):
         print("sdbk dnpr "+str(progress) )
         if state != "Generating":
@@ -277,14 +148,7 @@ def callback(state="" , progress=-1):
             if "__stop__" in get_input():
                 return "stop"
 
-    generator = StableDiffusion( ModelInterface , p_15 , model_name="sd_1x", callback=callback, debug_output_path=debug_output_path )
-    
-
-    default_d = { "W" : 512 , "H" : 512, "num_imgs":1 , "ddim_steps" : 25 ,
-     "scale" : 7.5, "batch_size":1 , "input_image" : None, "img_strength": 0.5
-     , "scheduler":"ddim" 
-     , "do_controlnet" : False , "control_name" : None , "do_controlnet_preprocess" : False
-     , "negative_prompt" : "" ,  "mask_image" : None, "model_id": 0 , "custom_model_path":None}
+    generator = StableDiffusion( model_container , ModelInterface , None , model_name=None, callback=callback, debug_output_path=debug_output_path )    
 
 
     print("sdbk mdld")
@@ -294,26 +158,42 @@ def callback(state="" , progress=-1):
 
         inp_str = get_input()
 
+        print("got" , inp_str)
+
         if inp_str.strip() == "":
             continue
 
-        if not "b2py t2im" in inp_str or "__stop__" in inp_str:
+        if  ((not "b2py t2im" in inp_str ) and (not "b2py rapp" in inp_str) ) or "__stop__" in inp_str:
             continue
-        inp_str = inp_str.replace("b2py t2im" , "").strip()
-        try:
-            d_ = json.loads(inp_str)
-            d = copy.deepcopy(default_d)
-            d.update(d_)
-            print("sdbk inwk") # working on the input
-     
-            process_opt(d, generator)
-            
-        except Exception as e:
-            traceback.print_exc()
-            print("sdbk errr %s"%(str(e)))
-            print("py2b eror " + str(e))
-
 
+        if "b2py t2im" in inp_str:
+            inp_str = inp_str.replace("b2py t2im" , "").strip()
+            try:
+                d = json.loads(inp_str)
+                print("sdbk inwk") # working on the input
+        
+                process_opt(d, generator)
+                
+            except Exception as e:
+                traceback.print_exc()
+                print("sdbk errr %s"%(str(e)))
+                print("py2b eror " + str(e))
+
+        elif "b2py rapp" in inp_str:
+            inp_str = inp_str.replace("b2py rapp" , "").strip()
+            applet_name = inp_str.split(" ")[0]
+            inp_str = inp_str.replace(applet_name , "").strip()
+
+            try:
+                d = json.loads(inp_str)
+                print("sdbk inwk") # working on the input
+                run_applet(applet_name , d )
+            except Exception as e:
+                traceback.print_exc()
+                print("sdbk errr %s"%(str(e)))
+
+
+from  stable_diffusion.utils.stdin_input import is_avail, get_input
 
 
 if __name__ == "__main__":
diff --git a/backends/stable_diffusion/downloader.py b/backends/stable_diffusion/downloader.py
deleted file mode 100644
index ad2d541f..00000000
--- a/backends/stable_diffusion/downloader.py
+++ /dev/null
@@ -1,155 +0,0 @@
-
-
-from pathlib import Path
-import os
-
-home_path = Path.home()
-
-projects_root_path = os.path.join(home_path, ".diffusionbee")
-
-if not os.path.isdir(projects_root_path):
-    os.mkdir(projects_root_path)
-
-import requests
-import os
-import hashlib
-import zipfile
-import random
-import shutil
-import time
-
-def get_md5_file(fpath):
-
-    if os.path.exists(fpath + ".done"):
-        cached = open(fpath + ".done").read()
-        if "_" in cached:
-            md_str = cached.split("_")[0]
-            n_b = int(cached.split("_")[1])
-            if n_b == os.path.getsize(fpath):
-                return md_str
-
-    md_str =  str(hashlib.md5(open(fpath, 'rb').read()).hexdigest())
-    n_b = os.path.getsize(fpath)
-    open(fpath + ".done" , "w").write(md_str + "_" + str(n_b))
-    return md_str
-
-
-defualt_downloads_root = os.path.join(projects_root_path, "downloads")
-
-
-if not os.path.isdir(defualt_downloads_root):
-    os.mkdir(defualt_downloads_root)
-
-
-class ProgressBarDownloader(object):
-    """Downloads a file and optionally shows a progressbar in the front-end. Also does not download if its already downloaded. Also supports checksum checking.
-    Attributes:
-        app_instance (AppInstance): The frontend app instance
-        downloads_root (str): The root path where the downloaded file is stored. Defualt is the path for all projects.
-        title (str): The title which will be shown in the progress bar modal in frontend.
-    """
-
-    def __init__(self, downloads_root=defualt_downloads_root,
-                  title="Downloading"):
-        super(ProgressBarDownloader, self).__init__()
-         
-        self.title = title
-        self.downloads_root = downloads_root
-
-    def is_already_downloaded(self, out_fname=None, md5_checksum=None):
-        """Check if file is already downloaded, and matches the checksum
-        Args:
-            out_fname (str, optional): The output file name
-            md5_checksum (str, optional): The md5 checksum
-        Returns:
-            bool: If the file is already downloaded
-        """
-        out_abs_path = os.path.join(self.downloads_root, out_fname)
-        if not os.path.exists(out_abs_path):
-            return False
-        if md5_checksum is not None and get_md5_file(
-                out_abs_path) != md5_checksum:
-            return False
-        return True
-
-    def download(self, url, out_fname=None, md5_checksum=None,
-                 verify_ssl=True, extract_zip=False, dont_use_cache=False):
-        """Download the file
-        Args:
-            url (str): The url of the file from which to download
-            out_fname (str, optional): The output file name
-            md5_checksum (str, optional): The md5 checksum
-            verify_ssl (bool, optional): If it should verify the ssl certificate or not.
-            extract_zip (bool, optional): Extract the zip file as well.
-            dont_use_cache (bool, optional): If set to true, then it will download from the beginning even if its already downloaded.
-        Returns:
-            str: the path of the downloaded file
-        No Longer Raises:
-            ValueError: Description
-        """
-        if out_fname is None:
-            out_fname = url.split("/")[-1]
-
-        out_abs_path = os.path.join(self.downloads_root, out_fname)
-
-        # if(not verify_ssl) and md5_checksum is None:
-        #     raise ValueError(
-        #         "If you set verify_ssl=False, then you should have a md5 checksum")
-        print("sdbk mlpr %d"%int(-1) )
-        print("sdbk mltl Checking Model")
-        
-        if (not dont_use_cache) and self.is_already_downloaded(
-                out_fname=out_fname, md5_checksum=md5_checksum):
-            if extract_zip:
-                if os.path.exists(out_abs_path.replace(".zip", "")):
-                    # TODO , actually check if the extracted is valid, but then
-                    # you might need spereate md5
-                    print("sdbk mldn")
-                    return out_abs_path.replace(".zip", "")
-            else:
-                print("sdbk mldn")
-                return out_abs_path
-
-        with open(out_abs_path, "wb") as f:
-            print("sdbk mltl " + self.title)
-            response = requests.get(url, stream=True, verify=verify_ssl)
-            total_length = response.headers.get('content-length')
-
-
-            if total_length is None:  # no content length header
-                f.write(response.content)
-            else:
-                dl = 0
-                total_length = int(total_length)
-                last_time = time.time()
-                for data in response.iter_content(chunk_size=4096):
-                    dl += len(data)
-                    f.write(data)
-                    done_percentage = 100* (dl / total_length)
-
-                    if time.time() - last_time > 0.1:
-                        last_time = time.time()
-                        print("sdbk mlpr %d"%int(done_percentage) ) # model loading percentage
-                        print("sdbk mlms %s"%("%.2fMB out of %.2fMB"%(dl/1000000 , total_length/1000000) ))
-
-        print("sdbk mlpr %d"%int(-1) )
-        print("sdbk mltl Checking Model")
-        print("sdbk mlms")
-
-        if md5_checksum is not None:
-            assert(get_md5_file(out_abs_path) ==
-                   md5_checksum), "The checksum for downloaded file failed."
-
-        if extract_zip:
-            print("sdbk mltl Extracting Model")
-
-            assert out_abs_path.lower().endswith(".zip")
-            with zipfile.ZipFile(out_abs_path, 'r') as zip_ref:
-                extract_path = out_abs_path.replace(
-                    ".zip", str(random.randint(0, 100000)))
-                zip_ref.extractall(extract_path)
-            out_abs_path = out_abs_path.replace(".zip", "")
-            dest = shutil.move(extract_path, out_abs_path)
-
-        print("sdbk mldn")
-        return out_abs_path
\ No newline at end of file
diff --git a/backends/stable_diffusion/environment_m1.yml b/backends/stable_diffusion/environment_m1.yml
deleted file mode 100644
index 6648d385..00000000
--- a/backends/stable_diffusion/environment_m1.yml
+++ /dev/null
@@ -1,134 +0,0 @@
-name: bee_env
-channels:
-  - apple
-  - conda-forge
-dependencies:
-  - absl-py=0.10.0=pyhd8ed1ab_1
-  - aiohttp=3.8.3=py39h02fc5c5_1
-  - aiosignal=1.2.0=pyhd8ed1ab_0
-  - altgraph=0.17.2=pyhd8ed1ab_1
-  - astunparse=1.6.3=pyhd8ed1ab_0
-  - async-timeout=4.0.2=pyhd8ed1ab_0
-  - attrs=22.1.0=pyh71513ae_1
-  - blinker=1.5=pyhd8ed1ab_0
-  - brotlipy=0.7.0=py39h02fc5c5_1005
-  - bzip2=1.0.8=h3422bc3_4
-  - c-ares=1.18.1=h3422bc3_0
-  - ca-certificates=2022.9.24=h4653dfc_0
-  - cached-property=1.5.2=hd8ed1ab_1
-  - cached_property=1.5.2=pyha770c72_1
-  - cachetools=4.2.4=pyhd8ed1ab_0
-  - certifi=2022.9.24=pyhd8ed1ab_0
-  - cffi=1.15.1=py39h7e6b969_1
-  - charset-normalizer=2.1.1=pyhd8ed1ab_0
-  - click=8.1.3=unix_pyhd8ed1ab_2
-  - cryptography=38.0.2=py39haa0b8cc_2
-  - freetype=2.12.1=hd633e50_0
-  - frozenlist=1.3.1=py39h02fc5c5_1
-  - gast=0.4.0=pyh9f0ad1d_0
-  - giflib=5.2.1=h27ca646_2
-  - google-auth=1.35.0=pyh6c4a22f_0
-  - google-auth-oauthlib=0.4.6=pyhd8ed1ab_0
-  - google-pasta=0.2.0=pyh8c360ce_0
-  - grpcio=1.49.1
-  - h5py=3.1.0=nompi_py39h99babb8_100
-  - hdf5=1.10.6=nompi_h0fc092c_1114
-  - idna=3.4=pyhd8ed1ab_0
-  - importlib-metadata=5.0.0=pyha770c72_1
-  - jpeg=9e=he4db4b2_2
-  - keras=2.6.0=pyhd8ed1ab_1
-  - keras-preprocessing=1.1.2=pyhd8ed1ab_0
-  - krb5=1.19.3=hf9b2bbe_0
-  - lcms2=2.12=had6a04f_0
-  - lerc=3.0=hbdafb3b_0
-  - libabseil=20220623.0=cxx17_h28b99d4_4
-  - libblas=3.9.0=16_osxarm64_openblas
-  - libcblas=3.9.0=16_osxarm64_openblas
-  - libclang=11.1.0=default_h0fdd720_1
-  - libcurl=7.86.0=hd538317_0
-  - libcxx=14.0.6=h2692d47_0
-  - libdeflate=1.10=h3422bc3_0
-  - libedit=3.1.20191231=hc8eb9b7_2
-  - libev=4.33=h642e427_1
-  - libffi=3.4.2=h3422bc3_5
-  - libgfortran=5.0.0=11_3_0_hd922786_25
-  - libgfortran5=11.3.0=hdaf2cc0_25
-  - libgrpc=1.49.1
-  - liblapack=3.9.0=16_osxarm64_openblas
-  - libllvm11=11.1.0=hfa12f05_5
-  - libnghttp2=1.47.0=h232270b_1
-  - libopenblas=0.3.21=openmp_hc731615_3
-  - libpng=1.6.38=h76d750c_0
-  - libprotobuf=3.21.9=hb5ab8b9_0
-  - libsqlite=3.39.4=h76d750c_0
-  - libssh2=1.10.0=hb80f160_3
-  - libtiff=4.3.0=h2810ee2_4
-  - libwebp=1.2.2=h0d20362_0
-  - libwebp-base=1.2.2=h3422bc3_1
-  - libxcb=1.13=h9b22ae9_1004
-  - libzlib=1.2.13=h03a7124_4
-  - llvm-openmp=14.0.4=hd125106_0
-  - macholib=1.16.2=pyhd8ed1ab_0
-  - markdown=3.4.1=pyhd8ed1ab_0
-  - markupsafe=2.1.1=py39h02fc5c5_2
-  - multidict=6.0.2=py39h02fc5c5_2
-  - ncurses=6.3=h07bb92c_1
-  - numpy=1.19.5=py39h54e5778_3
-  - oauthlib=3.2.2=pyhd8ed1ab_0
-  - openjpeg=2.5.0=hd370e0e_0
-  - openssl=1.1.1q=h03a7124_1
-  - opt_einsum=3.3.0=pyhd8ed1ab_1
-  - pillow=9.0.1=py39hd72dd6b_2
-  - pip=22.3=pyhd8ed1ab_0
-  - protobuf=4.21.9=py39h23fbdae_0
-  - pthread-stubs=0.4=h27ca646_1001
-  - pyasn1=0.4.8=py_0
-  - pyasn1-modules=0.2.7=py_0
-  - pycparser=2.21=pyhd8ed1ab_0
-  - pyinstaller-hooks-contrib=2022.11=pyhd8ed1ab_0
-  - pyjwt=2.6.0=pyhd8ed1ab_0
-  - pyopenssl=22.1.0=pyhd8ed1ab_0
-  - pysocks=1.7.1=pyha2e5f31_6
-  - python=3.9.10=hd16f9c5_2_cpython
-  - python_abi=3.9=2_cp39
-  - pyu2f=0.1.5=pyhd8ed1ab_0
-  - re2=2022.06.01=h9a09cb3_0
-  - readline=8.1.2=h46ed386_0
-  - requests=2.28.1=pyhd8ed1ab_1
-  - requests-oauthlib=1.3.1=pyhd8ed1ab_0
-  - rsa=4.9=pyhd8ed1ab_0
-  - scipy=1.9.1=py39h737da60_0
-  - setuptools=65.5.0=pyhd8ed1ab_0
-  - six=1.15.0=pyh9f0ad1d_0
-  - sqlite=3.39.4=h2229b38_0
-  - tensorboard=2.6.0=pyhd8ed1ab_1
-  - tensorboard-data-server=0.6.0=py39haa0b8cc_3
-  - tensorboard-plugin-wit=1.8.1=pyhd8ed1ab_0
-  - tensorflow-deps=2.6.0=0
-  - termcolor=1.1.0=pyhd8ed1ab_3
-  - tk=8.6.12=he1e0b03_0
-  - typing-extensions=3.7.4.3=0
-  - typing_extensions=3.7.4.3=py_0
-  - tzdata=2022e=h191b570_0
-  - urllib3=1.26.11=pyhd8ed1ab_0
-  - werkzeug=2.2.2=pyhd8ed1ab_0
-  - wheel=0.35.1=pyh9f0ad1d_0
-  - wrapt=1.12.1=py39h5161555_3
-  - xorg-libxau=1.0.9=h27ca646_0
-  - xorg-libxdmcp=1.1.3=h27ca646_0
-  - xz=5.2.6=h57fd34a_0
-  - yarl=1.8.1=py39h02fc5c5_0
-  - zipp=3.10.0=pyhd8ed1ab_0
-  - zlib=1.2.13=h03a7124_4
-  - zstd=1.5.2=h8128057_4
-  - pip:
-    - clang==5.0
-    - flatbuffers==1.12
-    - ftfy==6.1.1
-    - pyinstaller==5.2
-    - regex==2022.9.13
-    - tensorflow-estimator==2.10.0
-    - tensorflow-macos==2.6.0
-    - tensorflow-metal==0.1.2
-    - tqdm==4.64.1
-    - wcwidth==0.2.5
diff --git a/backends/stable_diffusion/schedulers/__init__.py b/backends/stable_diffusion/fake_interface/__init__.py
similarity index 100%
rename from backends/stable_diffusion/schedulers/__init__.py
rename to backends/stable_diffusion/fake_interface/__init__.py
diff --git a/backends/stable_diffusion/fake_interface.py b/backends/stable_diffusion/fake_interface/interface.py
similarity index 59%
rename from backends/stable_diffusion/fake_interface.py
rename to backends/stable_diffusion/fake_interface/interface.py
index 85f68ea2..48b36747 100644
--- a/backends/stable_diffusion/fake_interface.py
+++ b/backends/stable_diffusion/fake_interface/interface.py
@@ -3,15 +3,21 @@
 import time 
 
 class ModelInterface:
-    default_float_type = 'float16'
+    default_float_type = 'float32'
+    avail_float_types = ['float32']
+    avail_models = ["sd_1x" , "sd_2x" , "sd_1x_inpaint" ,  "sd_1x_controlnet"]
 
-    def __init__(self , *args , **k ):
+    def __init__(self, tdict,  dtype='float16', model_name="sd_1x", second_tdict=None ):
         pass
 
-    def run_unet(self, time_emb, text_emb, unet_inp):
+    def run_unet(self, time_emb, text_emb, unet_inp, control_inp=None,  control_weight=1):
         time.sleep(1.4)
         return np.copy(unet_inp)
 
+    def run_controlnet(self, time_emb, text_emb, unet_inp, hint_img ):
+        time.sleep(0.4)
+        return np.array([42])
+
     def run_dec(self, unet_out):
         time.sleep(1.4)
         return np.zeros((unet_out.shape[0] , unet_out.shape[1]*8 , unet_out.shape[2]*8 , unet_out.shape[3])) 
diff --git a/backends/stable_diffusion/requirements.txt b/backends/stable_diffusion/requirements.txt
index b108e7e8..5de5e590 100644
--- a/backends/stable_diffusion/requirements.txt
+++ b/backends/stable_diffusion/requirements.txt
@@ -1,6 +1,17 @@
 tensorflow==2.10.0
-h5py==3.7.0
-Pillow==9.2.0
-tqdm==4.64.1
-ftfy==6.1.1
-regex==2022.9.13
\ No newline at end of file
+numpy
+regex
+tqdm
+Pillow==9.4.0
+scipy
+ftfy
+fickling
+requests
+pyinstaller 
+onnxruntime
+opencv-python
+safetensors
+cython
+numexpr
+pandas
+scikit-image
\ No newline at end of file
diff --git a/backends/stable_diffusion/requirements_m1.txt b/backends/stable_diffusion/requirements_m1.txt
deleted file mode 100644
index 99be6127..00000000
--- a/backends/stable_diffusion/requirements_m1.txt
+++ /dev/null
@@ -1,9 +0,0 @@
-tensorflow-macos==2.10.0
-tensorflow-metal==0.6.0
-tensorflow_addons==0.17.1
-h5py==3.7.0
-Pillow==9.2.0
-tqdm==4.64.1
-protobuf==3.19
-ftfy==6.1.1
-regex==2022.9.13
\ No newline at end of file
diff --git a/backends/stable_diffusion/setup.py b/backends/stable_diffusion/setup.py
deleted file mode 100644
index fe62e7a6..00000000
--- a/backends/stable_diffusion/setup.py
+++ /dev/null
@@ -1,12 +0,0 @@
-from setuptools import find_packages, setup
-
-setup(
-    name="stable_diffusion_tf",
-    version="0.1",
-    description="Stable Diffusion in Tensorflow / Keras",
-    author="Divam Gupta",
-    author_email="guptadivam@gmail.com",
-    platforms=["any"],  # or more specific, e.g. "win32", "cygwin", "osx"
-    url="https://github.com/divamgupta/stable-diffusion-tensorflow",
-    packages=find_packages(),
-)
diff --git a/backends/stable_diffusion/stable_diffusion.py b/backends/stable_diffusion/stable_diffusion.py
deleted file mode 100644
index e2618863..00000000
--- a/backends/stable_diffusion/stable_diffusion.py
+++ /dev/null
@@ -1,711 +0,0 @@
-import numpy as np
-from tqdm import tqdm
-import math
-from clip_tokenizer import SimpleTokenizer , SimpleTokenizerV2
-import inspect
-
-from stdin_input import is_avail, get_input
-from PIL import Image, ImageOps
-import json
-import time
-import io
-from dataclasses import dataclass
-import os 
-import sys 
-import functools
-
-from control_processors.process_body_pose import process_image_body_pose
-from control_processors.process_midas_depth import process_image_midas_depth
-
-MAX_TEXT_LEN = 77
-
-
-dir_path = os.path.dirname(os.path.realpath(__file__))
-
-from tdict import TDict
-
-from schedulers.scheduling_ddim import DDIMScheduler
-from schedulers.scheduling_lms_discrete  import LMSDiscreteScheduler
-from schedulers.scheduling_pndm import PNDMScheduler
-from schedulers.k_euler_ancestral import KEulerAncestralSampler
-from schedulers.k_euler import KEulerSampler
-
-from utils.logging import log_object
-from utils.extra_model_utils import add_lora_ti_weights
-
-image_preprocess_model_paths = {
-    "body_pose" : None , 
-    "midas_depth" : None
-}
-
-
-def process_inp_img(input_image):
-    input_image = Image.open(input_image)
-    input_image = input_image.convert('RGB')
-    w , h = input_image.size
-    
-    if w > h:
-        new_w = 512
-        new_h  = round((h * new_w / w)/64)*64
-    else:
-        new_h = 512
-        new_w  = round((w * new_h / h)/64)*64
-
-    input_image_downscaled = ImageOps.fit(input_image, (new_w//8, new_h//8), method = Image.BILINEAR ,
-                   bleed = 0.0, centering =(0.5, 0.5))
-
-    input_image = ImageOps.fit(input_image, (new_w, new_h), method = Image.BILINEAR ,
-                   bleed = 0.0, centering =(0.5, 0.5))
-    input_image = np.array(input_image)[... , :3]
-    input_image_downscaled = np.array(input_image_downscaled)[... , :3]
-    input_image = (input_image.astype("float32") / 255.0)*2 - 1 
-    input_image_downscaled = (input_image_downscaled.astype("float32") / 255.0)*2 - 1 
-    return new_h , new_w  , input_image , input_image_downscaled
-
-
-
-@dataclass
-class SDRun():
-    
-    prompt: str
-
-    mode:str="txt2img"
-    tdict_path:str=None
-    dtype:str= "float16"
-
-    starting_img_given:bool = False 
-    do_masking:bool = False # if you wanna mask the latent at every sd step
-    img_height: int = None
-    img_width: int = None
-
-    inp_img_preprocesser:str = None # name of the preprocess fn 
-
-    negative_prompt:str=""
-
-    batch_size:int =1
-    num_steps:int =25
-    guidance_scale:float=7.5
-    seed:int=None
-    seed_type:str="np"
-    soft_seed:int=None
-    img_id:int = 1 
-
-    combine_unet_run:bool = False  # if it should do the cond + uncond in single batch
-
-    input_image:str =None
-    mask_image:str =None
-    
-    input_image_strength:float=0.5
-    second_tdict_path:str = None
-    weight_additions:tuple = ()
-
-
-def get_scheduler(name):
-    if name == "ddim":
-        return DDIMScheduler(
-            beta_start=0.00085,
-            beta_end=0.012,
-            beta_schedule="scaled_linear",
-            clip_sample= False,
-            num_train_timesteps= 1000,
-            set_alpha_to_one=False,
-            # steps_offset= 1,
-            trained_betas= None,
-            tensor_format="np",
-        )
-
-    if name == "ddim_v":
-        return DDIMScheduler(
-            beta_start=0.00085,
-            beta_end=0.012,
-            beta_schedule="scaled_linear",
-            clip_sample= False,
-            num_train_timesteps= 1000,
-            set_alpha_to_one=False,
-            # steps_offset= 1,
-            trained_betas= None,
-            tensor_format="np",
-            prediction_type="v_prediction"
-        )
-
-    if name == "lmsd":
-        return LMSDiscreteScheduler(
-            beta_start=0.00085,
-            beta_end=0.012,
-            beta_schedule="scaled_linear",
-            tensor_format="np")
-
-    if name == "pndm":
-        return PNDMScheduler(
-            beta_start=0.00085,
-            beta_end=0.012,
-            beta_schedule="scaled_linear",
-            skip_prk_steps = True,
-            tensor_format="np")
-
-    if name == "k_euler_ancestral":
-        return KEulerAncestralSampler()
-
-    if name == "k_euler":
-        return KEulerSampler()
-
-
-def dummy_callback(state="" , progress=-1):
-    pass
-
-
-
-def get_preprocess_function(preprocess_function_name):
-    if preprocess_function_name == "body_pose":
-        body_pose_model_path = image_preprocess_model_paths['body_pose']
-        return functools.partial(process_image_body_pose, model_path=body_pose_model_path)
-    elif preprocess_function_name == "midas_depth":
-        midas_depth_model_path = image_preprocess_model_paths['midas_depth']
-        return functools.partial(process_image_midas_depth, model_path=midas_depth_model_path)
-
-    else:
-        raise ValueError("invalid function name")
-
-
-tdict_model_versions = {}
-def get_tdict_model_version(tdict_path):
-    if tdict_path in tdict_model_versions:
-        return tdict_model_versions[tdict_path]
-    f = TDict(tdict_path, mode='r')
-    tdict_model_versions[ tdict_path] = f.ctdict_version
-    return tdict_model_versions[ tdict_path] 
-
-
-class StableDiffusion:
-    def __init__(self , ModelInterfaceClass ,  tdict_path , model_name="sd_1x",   callback=None , debug_output_path=None ):
-
-        self.ModelInterfaceClass = ModelInterfaceClass
-
-        if callback is None:
-            callback = dummy_callback
-       
-        self.tokenizer = SimpleTokenizer()
-        self.tokenizerv2 = SimpleTokenizerV2()
-
-        self.current_mode = None
-        self.callback = callback
-
-        self.debug_output_path = debug_output_path
-
-        self.current_model_name = model_name 
-        self.current_tdict_path = tdict_path
-        self.second_current_tdict_path = None
-        self.current_weight_additions = () #represents weights which are added on top, eg. Lora, TI etc
-        self.current_dtype = self.ModelInterfaceClass.default_float_type
-
-        if model_name is not None:
-            self.model = self.ModelInterfaceClass( TDict(self.current_tdict_path ), dtype=self.current_dtype, model_name=self.current_model_name )
-        else:
-            self.model = None
-
-
-    def prepare_model_interface(self , sd_run=None ):
-
-        dtype = sd_run.dtype
-        tdict_path = sd_run.tdict_path
-        second_tdict_path = sd_run.second_tdict_path
-
-        tdict_model_version = get_tdict_model_version(tdict_path) % 1000
-
-        if sd_run.mode == 'inpaint_15':
-            model_name = "sd_1x_inpaint"
-            if tdict_model_version != 13:
-                raise ValueError("The model selected is not compatable with SD1.5 inpainting.")
-        elif sd_run.mode == "controlnet":
-            model_name = "sd_1x_controlnet"
-            if tdict_model_version != 12:
-                raise ValueError("Only SD 1.x models are supported with controlnet")
-        else:
-            if tdict_model_version == 12 :
-                model_name = "sd_1x"
-            elif tdict_model_version == 15 :
-                if "sd_2x" in self.ModelInterfaceClass.avail_models:
-                    model_name = "sd_2x"
-                else:
-                    raise ValueError("SD 2.x is not supported with this version")
-            else:
-                raise ValueError("This model is not compatable with this operation")
-
-
-       
-
-        if self.current_model_name != model_name or self.current_dtype != dtype :
-            print("[SD] Creating model interface")
-            assert tdict_path is not None
-
-            if self.model is not None:
-                self.model.destroy()
-
-            if second_tdict_path is not None:
-                tdict2 = TDict(second_tdict_path)
-            else:
-                tdict2 = None
-
-            self.model = self.ModelInterfaceClass(TDict(tdict_path ) , dtype=dtype, model_name=model_name , second_tdict=tdict2)
-            self.current_tdict_path = tdict_path
-            self.second_current_tdict_path = second_tdict_path
-            self.current_dtype = dtype
-            self.current_model_name = model_name
-
-        weight_additions = sd_run.weight_additions
-
-        if tdict_path != self.current_tdict_path or second_tdict_path != self.second_current_tdict_path or weight_additions != self.current_weight_additions:
-            assert tdict_path is not None
-
-            tdict_1 = None
-
-            if (tdict_path == self.current_tdict_path and second_tdict_path == self.second_current_tdict_path and self.current_weight_additions == ()):
-                pass
-                # current weigh has already been loaded with some tdicts , and nothing has been added
-            else:
-                if second_tdict_path is not None:
-                    tdict2 = TDict(second_tdict_path)
-                else:
-                    tdict2 = None
-
-                tdict_1 = TDict(tdict_path)
-
-                self.model.load_from_tdict(tdict_1, tdict2 )
-
-                self.current_tdict_path = tdict_path
-                self.second_current_tdict_path = second_tdict_path
-
-            if weight_additions is not None and weight_additions != ():
-                if tdict_1 is None:
-                    tdict_1 = TDict(tdict_path)
-
-                print("[SD] Loading LoRA weights")
-                extra_weights = add_lora_ti_weights(tdict_1 , weight_additions )
-                self.model.load_from_state_dict(extra_weights )
-                self.current_weight_additions = weight_additions
-
-
-    def tokenize(self , prompt):
-        if self.current_model_name == "sd_2x":
-            inputs = self.tokenizerv2.encode(prompt)
-        else:
-            inputs = self.tokenizer.encode(prompt)
-            
-        if len(inputs) >= 77:
-            print("[SD] Prompt is too long, stripping it ")
-            inputs = inputs[:77]
-        if self.current_model_name == "sd_2x":
-            phrase = inputs + [0] * (77 - len(inputs))
-        else:
-            phrase = inputs + [49407] * (77 - len(inputs))
-        phrase = np.array(phrase)[None].astype("int32")
-        return phrase
-
-
-
-    def generate_text_emb(self, sd_run):
-        sd_run.tokens = self.tokenize(sd_run.prompt)
-        if sd_run.negative_prompt is None:
-            sd_run.negative_prompt = ""
-        sd_run.unconditional_tokens = self.tokenize(sd_run.negative_prompt)
-
-        pos_ids = np.array(list(range(77)))[None].astype("int32")
-
-        context = self.model.run_text_enc(sd_run.tokens, pos_ids)
-        unconditional_context = self.model.run_text_enc(sd_run.unconditional_tokens, pos_ids)
-
-        sd_run.context = np.repeat(context, sd_run.batch_size, axis=0)
-        sd_run.unconditional_context = np.repeat(unconditional_context, sd_run.batch_size, axis=0)
-
-        if self.debug_output_path  is not None:
-            log_object(sd_run.unconditional_context   , self.debug_output_path  , key="unconditional_context")
-            log_object(sd_run.context  , self.debug_output_path  , key="context")
-
-     
-    def maybe_process_inp_imgs(self, sd_run):
-
-        if sd_run.inp_img_preprocesser is not None: #if you want to preprocess input image
-            sd_run.input_image_orig = sd_run.input_image
-            outfname = sd_run.input_image + ".controlnet_processed_" + sd_run.inp_img_preprocesser  + ".jpg"
-            if not os.path.exists(outfname):
-                preprocess_function = get_preprocess_function(sd_run.inp_img_preprocesser)
-                preprocess_function(inp_fname=sd_run.input_image , out_fname=outfname)
-                assert os.path.exists(outfname)
-            sd_run.input_image = outfname
-
-
-        if sd_run.input_image is not None and sd_run.input_image != "": 
-            sd_run.img_height, sd_run.img_width, sd_run.input_image_processed , sd_run.input_image_processed_downscaled = process_inp_img(sd_run.input_image)
-            sd_run.input_image_processed = sd_run.input_image_processed[None]
-            sd_run.input_image_processed_downscaled = sd_run.input_image_processed_downscaled[None]
-
-        if sd_run.mask_image is not None and sd_run.mask_image != "":
-            h , w , mask_image , _ = process_inp_img(sd_run.mask_image)
-            assert h == sd_run.img_height , "Mask should be of the same size as inp image"
-            assert w == sd_run.img_width , "Mask should be of the same size as inp image"
-            mask_image = (mask_image + 1 )/2 
-            mask_image = mask_image[None]
-            mask_image = 1 - mask_image # repaint white keep black
-            mask_image = np.copy(mask_image[... , :1 ])
-            mask_image_sm = np.copy(mask_image[: , ::8 , ::8  ])
-
-            mask_image[mask_image < 0.5] = 0
-            mask_image[mask_image >= 0.5] = 1
-
-            mask_image_sm[mask_image_sm < 0.5] = 0
-            mask_image_sm[mask_image_sm >= 0.5] = 1
-
-            sd_run.processed_mask_downscaled = mask_image_sm
-            sd_run.processed_mask = mask_image
-
-
-    def prepare_timesteps(self, sd_run):
-        accepts_offset = "offset" in set(inspect.signature(self.scheduler.set_timesteps).parameters.keys())
-        extra_set_kwargs = {}
-        offset = 0
-        if accepts_offset:
-            offset = 1
-            extra_set_kwargs["offset"] = 1
-
-        self.scheduler.set_timesteps(sd_run.num_steps, **extra_set_kwargs)
-
-        sd_run.working_timesteps = self.scheduler.timesteps
-
-        if sd_run.starting_img_given: 
-            init_timestep = int(sd_run.num_steps * (1-sd_run.input_image_strength)) + offset
-            init_timestep = min(init_timestep, sd_run.num_steps)
-            sd_run.start_timestep = self.scheduler.timesteps[-init_timestep]
-            
-            t_start = max(sd_run.num_steps - init_timestep + offset, 0)
-            sd_run.working_timesteps = sd_run.working_timesteps[t_start:]
-
-
-
-
-    def get_noise(self, seed, shape, seed_type):
-        if  seed_type == 'np':
-            return np.random.RandomState(seed).normal(size=shape).astype('float32')
-        elif seed_type == 'pt':
-            import torch
-            torch.manual_seed(seed)
-            if len(shape) == 4:
-                shape = (shape[0] , shape[3] , shape[1] , shape[2])
-            a = torch.randn( (1,4,64,64) ).numpy().astype('float32')
-            return np.rollaxis(a , 1 , 4 )
-        else:
-            raise ValueError("Invalid seed type")
-
-
-    def get_encoded_img(self, sd_run , processes_img):
-        enc_out = self.model.run_enc(processes_img)
-        enc_out = np.repeat(enc_out, sd_run.batch_size, axis=0 )
-        enc_out_mu = enc_out[... , :4 ]
-        enc_out_logvar = enc_out[... , 4:]
-        enc_out_std = np.exp(0.5 * enc_out_logvar)
-
-        latent = enc_out_mu + enc_out_std*self.get_noise(sd_run.seed+1, enc_out_mu.shape , seed_type=sd_run.seed_type)
-        latent = 0.18215 * latent
-        return latent
-
-
-
-    def prepare_init_latent(self , sd_run):
-        n_h = sd_run.img_height // 8
-        n_w = sd_run.img_width // 8
-  
-        if not sd_run.starting_img_given:
-            latent_np = self.get_noise(sd_run.seed ,(sd_run.batch_size, n_h, n_w, 4) ,  seed_type=sd_run.seed_type)
-
-            if self.debug_output_path is not None:
-                log_object(latent_np , self.debug_output_path  , key="latent_np")
-
-            if sd_run.soft_seed is not None and sd_run.soft_seed >= 0:
-                # latent_np = latent_np + 0.1*self.get_noise(sd_run.soft_seed, latent_np.shape, seed_type=sd_run.seed_type ) #option 1 
-                nmask = (np.random.RandomState(sd_run.soft_seed).rand(*latent_np.shape ) > 0.99)
-                latent_np = latent_np*(1-nmask) + nmask*self.get_noise(sd_run.soft_seed, latent_np.shape , seed_type=sd_run.seed_type )
-
-            # latent_np = latent_np * np.float64(self.scheduler.init_noise_sigma)
-            sd_run.latent = latent_np
-
-            sd_run.latent  = sd_run.latent  * self.scheduler.initial_scale
-
-        else:
-            latent = self.get_encoded_img(sd_run , sd_run.input_image_processed )
-
-            if self.debug_output_path is not None:
-                log_object(latent  , self.debug_output_path  , key="encoded_img")
-
-            sd_run.encoded_img_unmasked = np.copy(latent)
-
-            start_timestep = np.array([self.t_to_i(sd_run.start_timestep)] * sd_run.batch_size, dtype=np.int64 )
-           
-            noise = self.get_noise(sd_run.seed , latent.shape , seed_type=sd_run.seed_type )
-
-            if self.debug_output_path is not None:
-                log_object(noise , self.debug_output_path  , key="noise_e")
-
-            latent = self.scheduler.add_noise(latent, noise, start_timestep )
-            sd_run.latent = latent
-
-        sd_run.init_latent = sd_run.latent
-
-        if self.debug_output_path is not None:
-            log_object(sd_run.init_latent  , self.debug_output_path  , key="sd_run_init_latent")
-
-        if sd_run.mode == "inpaint_15":
-            masked_img  = sd_run.input_image_processed * sd_run.processed_mask
-            sd_run.encoded_masked_img = self.get_encoded_img(sd_run , masked_img)
-
-
-        
-
-    def t_to_i(self, t):
-        i = list(self.scheduler.timesteps).index(t)
-        assert i >= 0
-        return i
-
-    def prepare_seed(self , sd_run):
-        try:
-            sd_run.seed = int(sd_run.seed)
-            if sd_run.seed < 1:
-                sd_run.seed = int(time.time()*100)%1002487 
-        except:
-            pass
-
-        if sd_run.seed is None:
-            sd_run.seed = int(time.time()*100)%1002487
-
-        if sd_run.soft_seed is not None and sd_run.soft_seed >= 0 :
-            sd_run.soft_seed = sd_run.soft_seed + 1234*sd_run.img_id
-        else:
-            sd_run.seed = sd_run.seed  + 1234*sd_run.img_id
-
-    def get_unet_out(self, sd_run):
-
-        t = sd_run.current_t
-        timestep_batch = np.array([t])
-        t_emb = self.timestep_embedding(timestep_batch)
-        t_emb = np.repeat(t_emb, sd_run.batch_size, axis=0)
-
-        latent_model_input = sd_run.latent
-        if sd_run.mode == "inpaint_15":
-            latent_model_input = np.concatenate([
-                latent_model_input , 
-                np.repeat( (1 - sd_run.processed_mask_downscaled ), sd_run.batch_size , axis=0) , 
-                sd_run.encoded_masked_img 
-            ], axis=-1)
-   
-        latent_model_input =  latent_model_input * self.scheduler.get_input_scale(self.t_to_i(t))
-
-        if sd_run.mode == "controlnet":
-            hint_img = (sd_run.input_image_processed+1)/2
-
-            if self.debug_output_path is not None:
-                log_object(hint_img , self.debug_output_path  , "hint_img")
-
-            if sd_run.combine_unet_run:
-                hint_img = np.repeat(hint_img, sd_run.batch_size, axis=0)
-            controls = self.model.run_controlnet(unet_inp=latent_model_input, time_emb=t_emb, text_emb=sd_run.context, hint_img=hint_img )
-        else:
-            controls = None
-
-        if self.debug_output_path is not None:
-            log_object(latent_model_input  , self.debug_output_path  , key="latent_model_input")
-            log_object(t_emb  , self.debug_output_path  , key="t_emb")
-            log_object(controls  , self.debug_output_path  , key="controls")
-
-        if sd_run.combine_unet_run:
-            latent_combined = np.concatenate([latent_model_input,latent_model_input])
-            temb_combined = np.concatenate([t_emb,t_emb])
-            text_emb_combined = np.concatenate([sd_run.unconditional_context , sd_run.context ])
-
-            o = self.model.run_unet(unet_inp=latent_combined, time_emb=temb_combined, text_emb=text_emb_combined , control_inp=controls)
-            sd_run.predicted_unconditional_latent = o[0: o.shape[0]//2 ]
-            sd_run.predicted_latent = o[o.shape[0]//2 :]
-        else:
-            sd_run.predicted_unconditional_latent = self.model.run_unet(unet_inp=latent_model_input, time_emb=t_emb, text_emb=sd_run.unconditional_context , control_inp=controls)
-            sd_run.predicted_latent = self.model.run_unet(unet_inp=latent_model_input, time_emb=t_emb, text_emb=sd_run.context, control_inp=controls)
-
-        if self.debug_output_path is not None:
-            log_object(sd_run.predicted_unconditional_latent  , self.debug_output_path  , key="unet_out_uncond")
-            log_object(sd_run.predicted_latent  , self.debug_output_path  , key="unet_out_cond")
-
-
-    def get_next_latent(self, sd_run ):
-        t = sd_run.current_t
-        noise_pred = sd_run.predicted_unconditional_latent + sd_run.guidance_scale * (sd_run.predicted_latent  - sd_run.predicted_unconditional_latent)
-
-        if self.debug_output_path is not None:
-            log_object(noise_pred  , self.debug_output_path  , key="noise_pred")
-        
-        accepts_eta = "eta" in set(inspect.signature(self.scheduler.step).parameters.keys())
-        extra_step_kwargs = {}
-        if accepts_eta:
-            eta = 0.0 # should be between 0 and 1, but 0 for now
-            extra_step_kwargs["eta"] = eta
-
-        step_seed = sd_run.seed + 10000 + self.t_to_i(t)*4242
-        latents = self.scheduler.step(noise_pred, self.t_to_i(t), sd_run.latent , seed=step_seed , **extra_step_kwargs)["prev_sample"]
-
-        if self.debug_output_path is not None:
-            log_object(latents  , self.debug_output_path  , key="latents_step")
-
-        if sd_run.do_masking:
-
-            latent_proper = np.copy(sd_run.encoded_img_unmasked)
-
-            noise = self.get_noise(sd_run.seed , latent_proper.shape , seed_type=sd_run.seed_type )
-            latent_proper = self.scheduler.add_noise(latent_proper, noise, np.array([self.t_to_i(sd_run.current_t)] * sd_run.batch_size, dtype=np.int64 ) )
-
-            latents = (latent_proper  * sd_run.processed_mask_downscaled) + (latents * (1 - sd_run.processed_mask_downscaled))
-
-        if self.debug_output_path is not None:
-            log_object(latents  , self.debug_output_path  , key="latents_mm")
-
-        # latents = self.scheduler.step(model_output=noise_pred, timestep=t , sample=sd_run.latent , **extra_step_kwargs)["prev_sample"]
-        sd_run.latent = latents
-
-
-
-    def generate(
-        self,
-        prompt, 
-        img_height, img_width,
-        batch_size=1,
-        num_steps=25,
-        guidance_scale=7.5,
-        temperature=None, 
-        seed=None,
-        seed_type="np",
-        soft_seed=None,
-        img_id=0,
-        input_image=None,
-        mask_image=None,
-        negative_prompt="",
-        input_image_strength=0.5,
-        scheduler='k_euler',
-        tdict_path=None, # if none then it will just use current one
-        second_tdict_path=None,
-        lora_tdict_paths={}, # {tdict_path: ratio}
-        inp_img_preprocesser=None, # for controlnet
-        dtype='float16',
-        mode="txt2img", # txt2img , img2img, inpaint_15
-    ):
-
-
-
-        self.scheduler = get_scheduler(scheduler)
-
-        assert mode in ['txt2img' , 'img2img' , 'inpaint_15', 'controlnet']
-
-        if dtype not in self.ModelInterfaceClass.avail_float_types:
-            dtype = self.ModelInterfaceClass.default_float_type
-
-        if tdict_path is None:
-            tdict_path = self.current_tdict_path
-
-        weight_additions = ()
-        for tpath in lora_tdict_paths:
-            weight_additions += (('lora' ,tpath , lora_tdict_paths[tpath] ),)
-
-        sd_run = SDRun(
-                prompt=prompt,
-                img_height=img_height,
-                img_width=img_width,
-                batch_size=batch_size,
-                num_steps=num_steps,
-                guidance_scale=guidance_scale,
-                seed=seed,
-                seed_type=seed_type,
-                soft_seed=soft_seed,
-                img_id=img_id,
-                input_image=input_image,
-                mask_image=mask_image,
-                negative_prompt=negative_prompt,
-                input_image_strength=input_image_strength,
-                tdict_path=tdict_path,
-                second_tdict_path=second_tdict_path,
-                weight_additions=weight_additions,
-                mode=mode,
-                dtype=dtype,
-                inp_img_preprocesser=inp_img_preprocesser,
-            )
-
-        if mode == "img2img":
-            assert input_image is not None and input_image != ""
-            sd_run.starting_img_given = True
-
-            if mask_image is not None and mask_image != "":
-                sd_run.do_masking = True
-
-        if mode == "controlnet":
-            assert input_image is not None and input_image != ""
-
-        signal = self.callback(state="Starting" , progress=-1  )
-        if signal == "stop":
-            return
-
-        self.prepare_model_interface(sd_run)
-
-        signal = self.callback(state="Encoding" , progress=-1  )
-        if signal == "stop":
-            return
-
-        self.prepare_seed(sd_run)
-        self.prepare_timesteps(sd_run)
-
-        if self.debug_output_path is not None:
-            log_object(sd_run , self.debug_output_path  , key="sd_run")
-
-        self.maybe_process_inp_imgs(sd_run)
-                
-        # Tokenize prompt (i.e. starting context)
-        self.generate_text_emb(sd_run)
-        self.prepare_init_latent(sd_run)
-
-        signal = self.callback(state="Generating" , progress=-1  )
-        if signal == "stop":
-            return
-
-        for i, t in tqdm(enumerate(sd_run.working_timesteps)):
-
-            sd_run.current_t = t
-            self.get_unet_out(sd_run)
-            self.get_next_latent(sd_run)
-
-            signal = self.callback(state="Generating" , progress=(100*(i+1)/len(sd_run.working_timesteps)) )
-            if signal == "stop":
-                return
-
-        signal = self.callback(state="Decoding" , progress=-1  )
-        if signal == "stop":
-            return
-
-        # Decoding stage
-        sd_run.latent = sd_run.latent/0.18215
-        decoded = self.model.run_dec(sd_run.latent)
-
-        if sd_run.do_masking:
-            decoded = (sd_run.input_image_processed  * sd_run.processed_mask) + (decoded * (1 - sd_run.processed_mask ))
-        
-        decoded = ((decoded + 1) / 2) * 255
-        ret = ({"img" : np.clip(decoded, 0, 255).astype("uint8")})
-
-        if sd_run.inp_img_preprocesser is not None:
-            ret['aux_img'] = sd_run.input_image
-
-        return ret
-
-
-    def timestep_embedding(self, timesteps, dim=320, max_period=10000):
-        half = dim // 2
-        freqs = np.exp(
-            -math.log(max_period) * np.arange(0, half, dtype="float32") / half
-        )
-        args = np.array(timesteps) * freqs
-        embedding = np.concatenate([np.cos(args), np.sin(args)])
-        return np.reshape(embedding , (1 , -1 ))
-
- 
-
-
diff --git a/backends/stable_diffusion/utils/__init__.py b/backends/stable_diffusion/stable_diffusion/__init__.py
similarity index 100%
rename from backends/stable_diffusion/utils/__init__.py
rename to backends/stable_diffusion/stable_diffusion/__init__.py
diff --git a/backends/stable_diffusion/clip_tokenizer/__init__.py b/backends/stable_diffusion/stable_diffusion/clip_tokenizer/__init__.py
similarity index 93%
rename from backends/stable_diffusion/clip_tokenizer/__init__.py
rename to backends/stable_diffusion/stable_diffusion/clip_tokenizer/__init__.py
index bfaaca62..c9e5296a 100644
--- a/backends/stable_diffusion/clip_tokenizer/__init__.py
+++ b/backends/stable_diffusion/stable_diffusion/clip_tokenizer/__init__.py
@@ -9,6 +9,22 @@
 # import tensorflow as tf
 # from tensorflow import keras
 
+def sdxl_text_projection_mat_path():
+    p = os.path.join(
+        os.path.dirname(os.path.abspath(__file__)), "xl_text_projection_mat.npy"
+    )
+    # print("checking " , p )
+    if os.path.exists(p):
+        return p
+    else:
+        p2 = os.path.join(
+            os.path.dirname(os.path.abspath(__file__)), "..",  ".." ,"xl_text_projection_mat.npy"
+        )
+        p2 = os.path.abspath(p2)
+        # print("checking " , p2 )
+        if os.path.exists(p2):
+            return p2
+        assert False
 
 
 @lru_cache()
@@ -21,7 +37,7 @@ def default_bpe():
         return p
     else:
         p2 = os.path.join(
-            os.path.dirname(os.path.abspath(__file__)),  ".." ,"bpe_simple_vocab_16e6.txt.gz"
+            os.path.dirname(os.path.abspath(__file__)), "..",  ".." ,"bpe_simple_vocab_16e6.txt.gz"
         )
         p2 = os.path.abspath(p2)
         # print("checking " , p2 )
diff --git a/backends/stable_diffusion/clip_tokenizer/bpe_simple_vocab_16e6.txt.gz b/backends/stable_diffusion/stable_diffusion/clip_tokenizer/bpe_simple_vocab_16e6.txt.gz
similarity index 100%
rename from backends/stable_diffusion/clip_tokenizer/bpe_simple_vocab_16e6.txt.gz
rename to backends/stable_diffusion/stable_diffusion/clip_tokenizer/bpe_simple_vocab_16e6.txt.gz
diff --git a/backends/stable_diffusion/stable_diffusion/clip_tokenizer/xl_text_projection_mat.npy b/backends/stable_diffusion/stable_diffusion/clip_tokenizer/xl_text_projection_mat.npy
new file mode 100644
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diff --git a/backends/stable_diffusion/stable_diffusion/control_processors/__init__.py b/backends/stable_diffusion/stable_diffusion/control_processors/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/backends/stable_diffusion/control_processors/process_body_pose.py b/backends/stable_diffusion/stable_diffusion/control_processors/process_body_pose.py
similarity index 100%
rename from backends/stable_diffusion/control_processors/process_body_pose.py
rename to backends/stable_diffusion/stable_diffusion/control_processors/process_body_pose.py
diff --git a/backends/stable_diffusion/stable_diffusion/control_processors/process_lineart.py b/backends/stable_diffusion/stable_diffusion/control_processors/process_lineart.py
new file mode 100644
index 00000000..72aaf5a0
--- /dev/null
+++ b/backends/stable_diffusion/stable_diffusion/control_processors/process_lineart.py
@@ -0,0 +1,31 @@
+
+import onnxruntime as ort
+import numpy as np 
+import cv2
+
+
+
+def process_image_lineart(inp_fname, out_fname, model_path):
+
+    im = cv2.imread(inp_fname)[... , ::-1 ]
+    im_h = im.shape[0]
+    im_w = im.shape[1]
+
+    im = cv2.resize(im , (512 , 512 )).astype("float32") #TODO change this 
+    im = np.rollaxis(im , 2, 0 )[None]/255.0 
+
+    ort_sess = ort.InferenceSession(model_path)
+
+    dep = ort_sess.run(None, {'input': im })[0][0][0]    
+
+    dep = ((1-dep)*255).clip(0, 255).astype('uint8')[... , None ]
+    dep = np.repeat(dep , 3 , axis=2)
+
+    dep = cv2.resize(dep , (im_w , im_h))
+    cv2.imwrite(out_fname , dep )
+
+
+if __name__ == "__main__":
+    process_image_lineart("/Users/divamgupta/Downloads/2T6A5407R-scaled.jpg" , "/tmp/a.png" , "/tmp/linart.onnx")
+    import os 
+    os.system("open /tmp/a.png")
\ No newline at end of file
diff --git a/backends/stable_diffusion/control_processors/process_midas_depth.py b/backends/stable_diffusion/stable_diffusion/control_processors/process_midas_depth.py
similarity index 89%
rename from backends/stable_diffusion/control_processors/process_midas_depth.py
rename to backends/stable_diffusion/stable_diffusion/control_processors/process_midas_depth.py
index b3f9bcff..d8fd43f8 100644
--- a/backends/stable_diffusion/control_processors/process_midas_depth.py
+++ b/backends/stable_diffusion/stable_diffusion/control_processors/process_midas_depth.py
@@ -47,6 +47,6 @@ def process_image_midas_depth(inp_fname, out_fname, model_path):
 
 
 if __name__ == "__main__":
-    process_image("/Users/divamgupta/Downloads/bed.jpg" , "/tmp/a.png")
+    process_image_midas_depth("/Users/divamgupta/Downloads/2T6A5407R-scaled.jpg" , "/tmp/a.png" , "/Users/divamgupta/Downloads/midas_monodepth.onnx")
     import os 
     os.system("open /tmp/a.png")
\ No newline at end of file
diff --git a/backends/stable_diffusion/stable_diffusion/plugins/__init__.py b/backends/stable_diffusion/stable_diffusion/plugins/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/backends/stable_diffusion/stable_diffusion/plugins/base_plugin.py b/backends/stable_diffusion/stable_diffusion/plugins/base_plugin.py
new file mode 100644
index 00000000..b51f85be
--- /dev/null
+++ b/backends/stable_diffusion/stable_diffusion/plugins/base_plugin.py
@@ -0,0 +1,6 @@
+
+
+class BasePlugin:
+
+    def __init__(self , parent=None):
+        self.parent = parent
\ No newline at end of file
diff --git a/backends/stable_diffusion/stable_diffusion/plugins/controlnet.py b/backends/stable_diffusion/stable_diffusion/plugins/controlnet.py
new file mode 100644
index 00000000..5fd4349d
--- /dev/null
+++ b/backends/stable_diffusion/stable_diffusion/plugins/controlnet.py
@@ -0,0 +1,117 @@
+import os
+import functools
+
+from ..control_processors.process_body_pose import process_image_body_pose
+from ..control_processors.process_midas_depth import process_image_midas_depth
+from ..control_processors.process_lineart import process_image_lineart
+
+
+from ..utils.image_preprocess import process_inp_img
+from ..utils.logging import log_object
+
+from .base_plugin import BasePlugin
+
+import numpy as np
+
+
+
+
+def get_preprocess_function(preprocess_function_name , model_path ):
+    if preprocess_function_name == "body_pose":
+        return functools.partial(process_image_body_pose, model_path=model_path)
+    elif preprocess_function_name == "midas_depth":
+        return functools.partial(process_image_midas_depth, model_path=model_path)
+    elif preprocess_function_name == "line_art":
+        return functools.partial(process_image_lineart, model_path=model_path)
+
+    else:
+        raise ValueError("invalid function name")
+
+
+
+class ControlNetPlugin(BasePlugin):
+    
+    def hook_pre_generate(self, sd_run):
+
+        if sd_run.controlnet_model is not None and sd_run.controlnet_model != "" and  sd_run.controlnet_model != "None":
+            if "sd_1x_controlnet" not in self.parent.ModelInterfaceClass.avail_models:
+                raise ValueError("ControlNet is not supported in this version. Please upgrade.") 
+            sd_run.is_control_net = True
+            sd_run.second_tdict_path = sd_run.controlnet_tdict_path
+            assert sd_run.controlnet_input_image_path is not None and sd_run.controlnet_input_image_path != ""
+
+            if sd_run.do_controlnet_preprocess:
+                if sd_run.controlnet_model == "Depth":                    
+                    sd_run.controlnet_inp_img_preprocesser = "midas_depth"
+                elif sd_run.controlnet_model == "BodyPose":
+                    sd_run.controlnet_inp_img_preprocesser = "body_pose"
+                elif sd_run.controlnet_model == "LineArt":
+                    sd_run.controlnet_inp_img_preprocesser = "line_art"
+                else:
+                    raise ValueError("Generate control not supported for " +  sd_run.controlnet_model )
+
+        if sd_run.is_control_net:
+            assert ( sd_run.controlnet_input_image_path is not None and sd_run.controlnet_input_image_path != "" ) , "ControlNet Input Missing"
+
+        if sd_run.controlnet_inp_img_preprocesser is not None and not sd_run.is_control_net:
+            raise ValueError("Enexpected ControlNet Input preprocessor")
+        
+        if sd_run.do_controlnet_preprocess:
+            sd_run.controlnet_inp_img_preprocesser
+
+        
+    def hook_post_generate(self, sd_run):
+        if (sd_run.controlnet_inp_img_preprocesser is not None) and  (sd_run.controlnet_model != "Inpaint"):
+            sd_run.ret['aux_img'] = sd_run.controlnet_input_image_path
+
+    def hook_post_process_inp_imgs(self, sd_run):
+        # process control net images 
+        if (sd_run.controlnet_inp_img_preprocesser is not None) and (sd_run.controlnet_model != "Inpaint")  : #if you want to preprocess input image, but for inpaint no need to save the control file
+            outfname = sd_run.controlnet_input_image_path + ".controlnet_processed_" + sd_run.controlnet_inp_img_preprocesser  + ".jpg"
+            if not os.path.exists(outfname):
+                preprocess_function = get_preprocess_function(sd_run.controlnet_inp_img_preprocesser, sd_run.controlnet_inp_img_preprocesser_model_path)
+                preprocess_function(inp_fname=sd_run.controlnet_input_image_path , out_fname=outfname)
+                assert os.path.exists(outfname)
+            sd_run.controlnet_input_image_path = outfname
+
+        if sd_run.controlnet_input_image_path is not None and sd_run.controlnet_input_image_path != "" and (sd_run.controlnet_model != "Inpaint"): 
+            
+            _, _, sd_run.controlnet_input_image_processed , _ = process_inp_img(sd_run.controlnet_input_image_path , image_size=None, new_w=sd_run.img_width , new_h=sd_run.img_height )
+            sd_run.controlnet_input_image_processed = sd_run.controlnet_input_image_processed[None]
+
+        # special case for inpaint preprocess
+        if (sd_run.controlnet_inp_img_preprocesser is not None) and (sd_run.controlnet_model == "Inpaint"):
+            # hhere mask is the control image, but we also need input image 
+
+            sd_run.encoded_img_orig = np.copy(self.parent.get_encoded_img(sd_run , sd_run.input_image_processed ))
+            mmm = (sd_run.processed_mask < 0.5 )[0]
+            mmm = np.repeat(mmm , 3 , 2 )
+            inpp = np.copy(sd_run.input_image_processed[0])
+            inpp[mmm] = -3
+            sd_run.controlnet_input_image_processed = inpp[None]
+
+
+
+    def hook_mid_get_unet_out(self, sd_run):
+        if sd_run.is_control_net:
+            hint_img = (sd_run.controlnet_input_image_processed+1)/2
+
+            if self.parent.debug_output_path is not None:
+                log_object(hint_img , self.parent.debug_output_path  , "hint_img")
+
+            if sd_run.combine_unet_run:
+                hint_img = np.repeat(hint_img, sd_run.batch_size, axis=0)
+            sd_run.controls = self.parent.model.run_controlnet(unet_inp=sd_run.latent_model_input, time_emb=sd_run.t_emb, text_emb=sd_run.context, hint_img=hint_img )
+            iter_i = self.parent.t_to_i(sd_run.current_t)
+            iter_frac = iter_i / sd_run.num_steps
+            
+            sd_run.control_weight_current_uncond = sd_run.control_weight
+            sd_run.control_weight_current_cond = sd_run.control_weight
+
+            if sd_run.controlnet_guess_mode:
+                sd_run.control_weight_current_uncond = 0
+
+            if self.parent.debug_output_path is not None:
+                log_object(sd_run.controls  , self.parent.debug_output_path  , key="sd_run.controls")
+        else:
+            sd_run.controls = None
\ No newline at end of file
diff --git a/backends/stable_diffusion/stable_diffusion/plugins/inpainting.py b/backends/stable_diffusion/stable_diffusion/plugins/inpainting.py
new file mode 100644
index 00000000..4810ee7c
--- /dev/null
+++ b/backends/stable_diffusion/stable_diffusion/plugins/inpainting.py
@@ -0,0 +1,83 @@
+from .base_plugin import BasePlugin
+import numpy as np
+from ..utils.image_preprocess import process_inp_img , post_process_mask
+import cv2
+
+class MaskInpainting(BasePlugin):
+
+
+    def hook_pre_generate(self, sd_run):
+        if sd_run.mode == "img2img"  :
+            if sd_run.mask_image_path is not None and sd_run.mask_image_path != "" or sd_run.get_mask_from_image_alpha:
+                sd_run.do_masking_diffusion = True
+
+
+    def hook_post_process_inp_imgs(self, sd_run):
+        if (sd_run.mask_image_path is not None and sd_run.mask_image_path != "") or (sd_run.get_mask_from_image_alpha):
+            
+            mask_image = None 
+
+            if sd_run.mask_image_path is not None and sd_run.mask_image_path != "":
+                h , w , mask_image , _ = process_inp_img(sd_run.mask_image_path ,  image_size=sd_run.inp_image_resize_mode , new_w=sd_run.img_width , new_h=sd_run.img_height  )
+
+            if sd_run.get_mask_from_image_alpha:
+                h , w , mask_image_alp , _ = process_inp_img(sd_run.input_image_path , only_read_alpha=True ,  image_size=sd_run.inp_image_resize_mode , new_w=sd_run.img_width , new_h=sd_run.img_height  )
+
+                if mask_image is None:
+                    mask_image = mask_image_alp
+                else:
+                    mask_image = np.maximum(mask_image , mask_image_alp)
+                
+            assert mask_image is not None
+            assert h == sd_run.img_height , "Mask should be of the same size as inp image"
+            assert w == sd_run.img_width , "Mask should be of the same size as inp image"
+            mask_image = (mask_image + 1 )/2 
+
+            if sd_run.get_mask_from_image_alpha:
+                mask_image = cv2.dilate(mask_image, np.ones((20, 20), np.uint8))
+            mask_image[mask_image < 0.5] = 0
+            mask_image[mask_image >= 0.5] = 1
+           
+            
+            if sd_run.blur_mask:
+                oo = (mask_image*255).astype('uint8')
+                oo = cv2.dilate(oo, np.ones((10, 10), np.uint8)) 
+                oo = cv2.blur( oo  ,(10,10))
+                mask_image = oo.astype('float32')/255
+                                                   
+            mask_image = 1 - mask_image # repaint white keep black
+            mask_image = np.copy(mask_image[... , :1 ])
+            
+            if sd_run.do_masking_diffusion or True:
+                mask_image_sm = cv2.resize(mask_image , (mask_image.shape[1]//8 , mask_image.shape[0]//8) )[: , : , None]
+            else:
+                mask_image_sm = np.copy(mask_image[::8 , ::8])
+
+            mask_image = mask_image[None]
+            mask_image_sm = mask_image_sm[None]
+
+            if not sd_run.do_masking_diffusion:
+                mask_image[mask_image < 0.5] = 0
+                mask_image[mask_image >= 0.5] = 1
+
+            mask_image_sm[mask_image_sm < 0.5] = 0
+            mask_image_sm[mask_image_sm >= 0.5] = 1
+
+            sd_run.processed_mask_downscaled = mask_image_sm
+            sd_run.processed_mask = mask_image
+    
+    def hook_post_get_next_latent(self, sd_run):
+        
+        if sd_run.do_masking_diffusion:
+
+            latent_proper = np.copy(sd_run.encoded_img_orig)
+
+            noise = self.parent.get_modded_noise(sd_run.seed , latent_proper.shape , seed_type=sd_run.seed_type, small_mod_seed=sd_run.small_mod_seed  )
+            latent_proper = self.parent.scheduler.add_noise(latent_proper, noise, np.array([self.parent.t_to_i(sd_run.current_t)] * sd_run.batch_size, dtype=np.int64 ) )
+
+            sd_run.next_latents = (latent_proper  * sd_run.processed_mask_downscaled) + (sd_run.next_latents * (1 - sd_run.processed_mask_downscaled))
+    
+    def hook_mid_decode(self, sd_run):
+        if sd_run.do_masking_diffusion:
+            sd_run.decoded = (sd_run.input_image_processed  * sd_run.processed_mask) + (sd_run.decoded * (1 - sd_run.processed_mask ))
+
diff --git a/backends/stable_diffusion/stable_diffusion/plugins/plugin_system.py b/backends/stable_diffusion/stable_diffusion/plugins/plugin_system.py
new file mode 100644
index 00000000..9021b157
--- /dev/null
+++ b/backends/stable_diffusion/stable_diffusion/plugins/plugin_system.py
@@ -0,0 +1,38 @@
+
+
+class StableDiffusionPluginMixin:
+
+    def plugin_system_init(self):
+        self.hooks = {}
+
+        
+
+    def register_hook(self, fn_name , fn_stage, function):
+        hook_ident = fn_name + "_" + fn_stage
+        print("[SD] registered" , hook_ident)
+        if hook_ident not in self.hooks:
+            self.hooks[hook_ident] = []
+        self.hooks[hook_ident].append(function)
+
+    def run_plugin_hook( self, fn_name , fn_stage, sd_run, *args , **kwargs ):
+        hook_ident = fn_name + "_" + fn_stage
+        if hook_ident not in self.hooks:
+            return
+        for fn in self.hooks[hook_ident]:
+            fn(sd_run , *args , **kwargs)
+
+    def add_plugin(self , plugin_class):
+        plugin_object = plugin_class(parent=self)
+        hooks_list = [method for method in dir(plugin_object) if method.startswith('hook_')]
+
+        print(hooks_list)
+
+        for hook in hooks_list:
+            hook_stage = hook.split("_")[1]
+            hook_fn_name = "_".join(hook.split("_")[2:])
+
+            hook_fn = getattr(plugin_object , hook)
+
+            self.register_hook(hook_fn_name , hook_stage , hook_fn )
+
+    
diff --git a/backends/stable_diffusion/stable_diffusion/plugins/sd15_inpainting.py b/backends/stable_diffusion/stable_diffusion/plugins/sd15_inpainting.py
new file mode 100644
index 00000000..815583da
--- /dev/null
+++ b/backends/stable_diffusion/stable_diffusion/plugins/sd15_inpainting.py
@@ -0,0 +1,36 @@
+from .base_plugin import BasePlugin
+import numpy as np
+import cv2
+
+class Sd15Inpainting(BasePlugin):
+
+    def hook_pre_generate(self, sd_run):
+        if sd_run.is_sd15_inpaint:
+            assert (sd_run.input_image_path is not None and sd_run.input_image_path != "") , "No input image specified"
+            # if sd_run.mode != "txt2img":
+            #     raise ValueError("SD15 Inpaint can only run in txt2img mode")
+            if (not sd_run.get_mask_from_image_alpha) and (sd_run.mask_image_path is None or sd_run.mask_image_path == ""):
+                raise ValueError("With SD15, the mask should be present")
+            
+            
+                
+    
+    def hook_post_prepare_init_latent(self, sd_run):
+        if sd_run.is_sd15_inpaint:
+            masked_img  = sd_run.input_image_processed * (sd_run.processed_mask > 0.5 )
+            sd_run.encoded_masked_img = self.parent.get_encoded_img(sd_run , masked_img)
+
+            assert sd_run.processed_mask_downscaled.shape[0] == 1, "batch_size > 1 not supported "
+
+            if sd_run.do_masking_diffusion:
+                sd_run.encoded_img_orig = np.copy(sd_run.encoded_masked_img)
+            
+         
+
+    def hook_mid_get_unet_out(self, sd_run):
+        if sd_run.is_sd15_inpaint:
+            sd_run.latent_model_input = np.concatenate([
+                sd_run.latent_model_input , 
+                np.repeat( (1 - sd_run.processed_mask_downscaled ), sd_run.batch_size , axis=0) , 
+                sd_run.encoded_masked_img 
+            ], axis=-1) #TODO verify if we have to concat before or after prescale
\ No newline at end of file
diff --git a/backends/stable_diffusion/stable_diffusion/schedulers/__init__.py b/backends/stable_diffusion/stable_diffusion/schedulers/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/backends/stable_diffusion/stable_diffusion/schedulers/get_scheduler.py b/backends/stable_diffusion/stable_diffusion/schedulers/get_scheduler.py
new file mode 100644
index 00000000..da04a80e
--- /dev/null
+++ b/backends/stable_diffusion/stable_diffusion/schedulers/get_scheduler.py
@@ -0,0 +1,60 @@
+
+from .scheduling_ddim import DDIMScheduler
+from .scheduling_lms_discrete  import LMSDiscreteScheduler
+from .scheduling_pndm import PNDMScheduler
+from .k_euler_ancestral import KEulerAncestralSampler
+from .k_euler import KEulerSampler
+from .karras_scheduler import KarrasSampler
+
+def get_scheduler(name):
+    if name == "ddim":
+        return DDIMScheduler(
+            beta_start=0.00085,
+            beta_end=0.012,
+            beta_schedule="scaled_linear",
+            clip_sample= False,
+            num_train_timesteps= 1000,
+            set_alpha_to_one=False,
+            # steps_offset= 1,
+            trained_betas= None,
+            tensor_format="np",
+        )
+
+    if name == "ddim_v":
+        return DDIMScheduler(
+            beta_start=0.00085,
+            beta_end=0.012,
+            beta_schedule="scaled_linear",
+            clip_sample= False,
+            num_train_timesteps= 1000,
+            set_alpha_to_one=False,
+            # steps_offset= 1,
+            trained_betas= None,
+            tensor_format="np",
+            prediction_type="v_prediction"
+        )
+
+    if name == "lmsd":
+        return LMSDiscreteScheduler(
+            beta_start=0.00085,
+            beta_end=0.012,
+            beta_schedule="scaled_linear",
+            tensor_format="np")
+
+    if name == "pndm":
+        return PNDMScheduler(
+            beta_start=0.00085,
+            beta_end=0.012,
+            beta_schedule="scaled_linear",
+            skip_prk_steps = True,
+            tensor_format="np")
+
+    if name == "k_euler_ancestral":
+        return KEulerAncestralSampler()
+
+    if name == "k_euler":
+        return KEulerSampler()
+    
+    
+    if name == "karras":
+        return KarrasSampler()
diff --git a/backends/stable_diffusion/schedulers/k_euler.py b/backends/stable_diffusion/stable_diffusion/schedulers/k_euler.py
similarity index 100%
rename from backends/stable_diffusion/schedulers/k_euler.py
rename to backends/stable_diffusion/stable_diffusion/schedulers/k_euler.py
diff --git a/backends/stable_diffusion/schedulers/k_euler_ancestral.py b/backends/stable_diffusion/stable_diffusion/schedulers/k_euler_ancestral.py
similarity index 100%
rename from backends/stable_diffusion/schedulers/k_euler_ancestral.py
rename to backends/stable_diffusion/stable_diffusion/schedulers/k_euler_ancestral.py
diff --git a/backends/stable_diffusion/stable_diffusion/schedulers/karras_scheduler.py b/backends/stable_diffusion/stable_diffusion/schedulers/karras_scheduler.py
new file mode 100644
index 00000000..596044f9
--- /dev/null
+++ b/backends/stable_diffusion/stable_diffusion/schedulers/karras_scheduler.py
@@ -0,0 +1,171 @@
+import numpy as np
+
+class KarrasOperations:
+    def __init__(self, linear_start, linear_end, timesteps, steps):
+        self.linear_start = linear_start
+        self.linear_end = linear_end
+        self.timesteps = timesteps
+        self.steps = steps
+
+    @property
+    def betas(self):
+        start = np.sqrt(self.linear_start)
+        length = np.sqrt(self.linear_end) - start
+        betas = [start + i * length / (self.timesteps - 1) for i in range(self.timesteps)]
+        return [beta**2 for beta in betas]
+
+    @property
+    def alphas_cumprod(self):
+        cumprod = 1.0
+        return [cumprod := cumprod * (1 - beta) for beta in self.betas]
+
+    def karras_sigmas(self, range_, rho=7.0):
+        assert len(range_) == 2 
+        min_inv_rho = range_[0]**(1.0 / rho)
+        max_inv_rho = range_[1]**(1.0 / rho)
+        sigmas = [
+            (max_inv_rho + i * (min_inv_rho - max_inv_rho) / (self.steps - 1))**rho
+            for i in range(self.steps)
+        ]
+        sigmas.append(0)
+        return sigmas
+
+    def fixed_step_sigmas(self, range_, sigmas_for_timesteps):
+        sigmas = []
+        for i in range(self.steps):
+            timestep = (self.steps - 1 - i) / (self.steps - 1) * (self.timesteps - 1)
+            low_idx = int(np.floor(timestep))
+            high_idx = min(low_idx + 1, self.timesteps - 1)
+            w = timestep - low_idx
+            log_sigma = (1 - w) * np.log(sigmas_for_timesteps[low_idx]) + w * np.log(sigmas_for_timesteps[high_idx])
+            sigmas.append(np.exp(log_sigma))
+        sigmas.append(0)
+        return sigmas
+
+    @staticmethod
+    def sigmas_from_alphas_cumprod(alphas_cumprod):
+        return [np.sqrt((1 - alpha) / alpha) for alpha in alphas_cumprod]
+
+    @staticmethod
+    def timestep(sigma, sigmas):
+        if sigma <= sigmas[0]:
+            return 0
+        elif sigma >= sigmas[-1]:
+            return float(len(sigmas) - 1)
+
+        high_idx = len(sigmas) - 1
+        low_idx = 0
+
+        while low_idx < high_idx - 1:
+            mid_idx = (low_idx + high_idx) // 2
+            if sigma < sigmas[mid_idx]:
+                high_idx = mid_idx
+            else:
+                low_idx = mid_idx
+
+        assert sigmas[high_idx - 1] <= sigma <= sigmas[high_idx]
+
+        low = np.log(sigmas[high_idx - 1])
+        high = np.log(sigmas[high_idx])
+        log_sigma = np.log(sigma)
+        w = min(max((low - log_sigma) / (low - high), 0), 1)
+        return (1.0 - w) * float(high_idx - 1) + w * float(high_idx)
+
+
+
+
+
+class KarrasSampler():
+    def __init__(self ):
+        pass 
+
+    def set_timesteps(self, n_inference_steps, n_training_steps=1000): #dg
+
+        self.karras = KarrasOperations(linear_start=0.00085, linear_end=0.012, timesteps=n_training_steps, steps=n_inference_steps )
+
+        # timesteps = np.linspace(n_training_steps - 1, 0, n_inference_steps)
+
+        sigmasForTimesteps =  KarrasOperations.sigmas_from_alphas_cumprod(self.karras.alphas_cumprod) 
+        sigmas =  self.karras.karras_sigmas(range_=np.array([sigmasForTimesteps[0], sigmasForTimesteps[999] ]))
+        sigmas = np.array(sigmas)
+
+
+        timesteps = [ self.karras.timestep(sigma=s , sigmas=sigmasForTimesteps ) for s in sigmas[:-1]  ]
+        timesteps = np.array(timesteps)
+
+        self.sigmas = sigmas
+        self.initial_scale = sigmas.max()
+        self.timesteps = timesteps
+        self.n_inference_steps = n_inference_steps
+        self.n_training_steps = n_training_steps
+        self.step_count = 0
+
+        self.oldDenoised = None
+
+
+    def get_input_scale(self, step_count=None):
+        if step_count is None:
+            step_count = self.step_count
+        sigma = self.sigmas[step_count]
+        return 1 / (sigma ** 2 + 1) ** 0.5
+
+    def add_noise(self, latent, noise, idx ): #dg
+        for i in idx:
+            assert idx[0] == i
+        sc = self.sigmas[idx[0]]
+        return latent + noise*sc
+
+    # output is predicted noise et
+    # step is the step id, found using t_to_i
+    def step(self, output , step_count , latents , seed=None ): #dg
+        
+        sigma = self.sigmas[step_count]
+        cOut = -1*sigma
+        sigmas = self.sigmas
+        
+        x = latents.copy()
+
+        denoised = x + cOut * output
+        h = np.log(self.sigmas[step_count]) - np.log(self.sigmas[step_count + 1])
+
+        if self.oldDenoised is not None and step_count < self.karras.steps - 1 :
+            oldDenoised = self.oldDenoised
+
+            hLast = np.log(sigmas[step_count - 1]) - np.log(sigmas[step_count])
+            r = (h / hLast) / 2
+            denoisedD = (1 + r) * denoised - r * oldDenoised
+            w = sigmas[step_count + 1] / sigmas[step_count]
+            x = w * x - (w - 1) * denoisedD
+        elif step_count ==  self.karras.steps - 1:
+            x = denoised
+
+        else:
+            w = sigmas[step_count + 1] / sigmas[step_count]
+            x = w * x - (w - 1) * denoised
+    
+        self.oldDenoised = denoised
+        return {"prev_sample": x } #latents
+    
+
+
+
+if __name__ == "__main__":
+
+
+
+    # model = Karras(linear_start=0.1, linear_end=0.9, timesteps=10, steps=5)
+    model = KarrasOperations(linear_start=0.00085, linear_end=0.012, timesteps=1_000, steps=10 )
+
+    alphas_cumprod =  model.alphas_cumprod
+    sigmasForTimesteps =  KarrasOperations.sigmas_from_alphas_cumprod(model.alphas_cumprod) 
+    sigmas = model.karras_sigmas(range_=np.array([sigmasForTimesteps[0], sigmasForTimesteps[-1] ]))
+
+    print(sigmas )
+    # print("Sigmas From Alphas Cumprod:", KarrasOperations.sigmas_from_alphas_cumprod(model.alphas_cumprod))
+
+
+
+    # print("Betas:", model.betas)
+    # print("Alphas Cumprod:", model.alphas_cumprod)
+    # print("Fixed Step Sigmas:", model.fixed_step_sigmas(range_=np.array([0.1, 0.9]), sigmas_for_timesteps=model.betas))
+    # print("Timestep:", Karras.timestep(sigma=0.5, sigmas=model.karras_sigmas(range_=np.array([0.1, 0.9]))))
\ No newline at end of file
diff --git a/backends/stable_diffusion/schedulers/scheduler_mixin.py b/backends/stable_diffusion/stable_diffusion/schedulers/scheduler_mixin.py
similarity index 100%
rename from backends/stable_diffusion/schedulers/scheduler_mixin.py
rename to backends/stable_diffusion/stable_diffusion/schedulers/scheduler_mixin.py
diff --git a/backends/stable_diffusion/schedulers/scheduling_ddim.py b/backends/stable_diffusion/stable_diffusion/schedulers/scheduling_ddim.py
similarity index 100%
rename from backends/stable_diffusion/schedulers/scheduling_ddim.py
rename to backends/stable_diffusion/stable_diffusion/schedulers/scheduling_ddim.py
diff --git a/backends/stable_diffusion/schedulers/scheduling_lms_discrete.py b/backends/stable_diffusion/stable_diffusion/schedulers/scheduling_lms_discrete.py
similarity index 100%
rename from backends/stable_diffusion/schedulers/scheduling_lms_discrete.py
rename to backends/stable_diffusion/stable_diffusion/schedulers/scheduling_lms_discrete.py
diff --git a/backends/stable_diffusion/schedulers/scheduling_pndm.py b/backends/stable_diffusion/stable_diffusion/schedulers/scheduling_pndm.py
similarity index 100%
rename from backends/stable_diffusion/schedulers/scheduling_pndm.py
rename to backends/stable_diffusion/stable_diffusion/schedulers/scheduling_pndm.py
diff --git a/backends/stable_diffusion/stable_diffusion/sd_run.py b/backends/stable_diffusion/stable_diffusion/sd_run.py
new file mode 100644
index 00000000..3b8ccae8
--- /dev/null
+++ b/backends/stable_diffusion/stable_diffusion/sd_run.py
@@ -0,0 +1,63 @@
+from dataclasses import dataclass
+
+
+@dataclass
+class SDRun():
+    
+    prompt: str
+
+    is_sd2:bool = False
+
+    mode:str="txt2img"
+    tdict_path:str=None
+    dtype:str= "float16"
+
+    starting_img_given:bool = False 
+    do_masking_diffusion:bool = False # if you wanna mask the latent at every sd step
+    img_height: int = None
+    img_width: int = None
+
+    negative_prompt:str=""
+
+    batch_size:int =1
+    num_steps:int =25
+    guidance_scale:float=7.5
+    seed:int=None
+    seed_type:str="np"
+    small_mod_seed:int=None
+    img_id:int = 0
+    scheduler:str = "__default_for_model__"
+
+    combine_unet_run:bool = False  # if it should do the cond + uncond in single batch
+
+    input_image_path:str =None
+    inp_image_resize_mode:str = "legacy_auto"
+
+    mask_image_path:str =None
+    get_mask_from_image_alpha:bool = False
+    get_binary_mask_from_colored_mask:bool = True #if the mask_image_path is a colored mask, and this option will extract binary mask from it
+    blur_mask:bool = False
+    infill_alpha:bool = False #infill the image first
+    infill_mask:bool = False #not used, infill the mask
+
+    force_use_given_size:bool = False # this will set inp_image_resize_mode to none
+    input_image_strength:float=0.5
+    second_tdict_path:str = None
+    lora_tdict_paths:tuple = ()
+
+    controlnet_model:str = None
+    do_controlnet_preprocess:bool = False
+    controlnet_input_image_path:str = None
+    controlnet_inp_img_preprocesser:str = None # name of the preprocess fn 
+    is_control_net:bool = False
+    controlnet_inp_img_preprocesser_model_path:str = None
+    controlnet_tdict_path:str = None
+    control_weight:float = 1.0
+    control_weight_current_cond:float = 1.0
+    control_weight_current_uncond:float = 1.0
+    controlnet_guess_mode:bool = False
+    
+    is_sd15_inpaint:bool = False
+    do_v_prediction:bool = False
+
+    is_clip_skip_2:bool = False
diff --git a/backends/stable_diffusion/stable_diffusion/stable_diffusion.py b/backends/stable_diffusion/stable_diffusion/stable_diffusion.py
new file mode 100644
index 00000000..8e7e222a
--- /dev/null
+++ b/backends/stable_diffusion/stable_diffusion/stable_diffusion.py
@@ -0,0 +1,547 @@
+import numpy as np
+from tqdm import tqdm
+import math
+from .clip_tokenizer import SimpleTokenizer , SimpleTokenizerV2, sdxl_text_projection_mat_path
+import inspect
+
+import time
+import os 
+import copy
+
+
+MAX_TEXT_LEN = 77
+
+
+dir_path = os.path.dirname(os.path.realpath(__file__))
+
+from tdict import TDict
+
+from .schedulers.get_scheduler import get_scheduler
+
+from .utils.logging import log_object
+from .utils.extra_model_utils import add_lora_ti_weights
+from .utils.image_preprocess import process_inp_img 
+
+from .plugins.plugin_system import StableDiffusionPluginMixin
+from .utils.utils import get_tdict_model_version
+
+from .plugins.controlnet import ControlNetPlugin
+from .plugins.sd15_inpainting import Sd15Inpainting
+from .plugins.inpainting import MaskInpainting
+
+from .utils.model_interface import create_sd_model_with_weights
+
+def dummy_callback(state="" , progress=-1):
+    pass
+
+
+
+class ModelContainer():
+
+    def __init__(self):
+        self.reset()
+
+    def reset(self):
+        try:
+            self.model.destroy()
+        except:
+            pass
+        
+        self.model=None
+        self.model_type=None
+        self.model_config=None
+        self.weights_config=None
+
+
+class StableDiffusion(StableDiffusionPluginMixin):
+    def __init__(self , model_container , ModelInterfaceClass ,  tdict_path , model_name="sd_1x",   callback=None , debug_output_path=None ):
+
+        self.ModelInterfaceClass = ModelInterfaceClass
+        self.model_container = model_container
+
+        if callback is None:
+            callback = dummy_callback
+
+        self.plugin_system_init()
+       
+        self.tokenizer = SimpleTokenizer()
+        self.tokenizerv2 = SimpleTokenizerV2()
+
+        self.sd_base_version = 1
+
+        self.current_mode = None
+        self.callback = callback
+
+        self.debug_output_path = debug_output_path
+
+        assert model_name is None
+        assert tdict_path is None # for now
+
+      
+
+        
+        self.add_plugin(MaskInpainting)
+        self.add_plugin(Sd15Inpainting)
+        self.add_plugin(ControlNetPlugin)
+
+        self.model = None
+
+        self.sdxl_pooled_emb_text_proj_mat = np.load(sdxl_text_projection_mat_path())
+
+
+    def prepare_model_interface(self , sd_run=None ):
+
+        # self.run_plugin_hook('prepare_model_interface' , 'pre' , sd_run)
+
+        dtype = sd_run.dtype
+        tdict_path = sd_run.tdict_path
+        second_tdict_path = sd_run.second_tdict_path
+
+        tdict_model_version = get_tdict_model_version(tdict_path) % 1000
+
+        if sd_run.is_control_net and sd_run.is_sd15_inpaint:
+            raise ValueError("ControlNet with SD1.5 inpaint is not supported.")
+
+        if sd_run.is_sd15_inpaint:
+            model_name = "sd_1x_inpaint"
+            if tdict_model_version != 13:
+                raise ValueError("The model selected is not compatable with SD1.5 inpainting.")
+        elif sd_run.is_control_net:
+            model_name = "sd_1x_controlnet"
+            if tdict_model_version != 12:
+                raise ValueError("Only SD 1.x models are supported with controlnet")
+        else:
+            if tdict_model_version == 31 : 
+                model_name = "sdxl_base"
+            elif tdict_model_version == 12 :
+                model_name = "sd_1x"
+            elif tdict_model_version == 15 :
+                if "sd_2x" in self.ModelInterfaceClass.avail_models:
+                    model_name = "sd_2x"
+                else:
+                    raise ValueError("SD 2.x is not supported with this version")
+            else:
+                raise ValueError("This model is not compatable with this operation")
+            
+        # self.run_plugin_hook('prepare_model_interface' , 'mid' , sd_run)
+        
+
+
+
+        if self.model_container.model_type != "SD_normal":
+            self.model_container.reset()
+
+        model_config = ("SD_normal" , model_name, dtype)
+        weights_config = (tdict_path, second_tdict_path, sd_run.weight_additions)
+
+        create_sd_model_with_weights(self.ModelInterfaceClass, self.model_container, model_config, weights_config)
+        self.model = self.model_container.model
+
+        sd_run.model_name = model_name
+
+        if "2x" in model_name:
+            self.sd_base_version = 2
+        if "xl" in model_name:
+            self.sd_base_version = 3
+        else :
+            self.sd_base_version = 1
+
+
+
+    def tokenize(self , prompt):
+        
+        if self.sd_base_version == 2:
+            inputs = self.tokenizerv2.encode(prompt)
+        else:
+            inputs = self.tokenizer.encode(prompt)
+            
+        if len(inputs) >= 77:
+            print("[SD] Prompt is too long, stripping it ")
+            inputs = inputs[:77]
+        if self.sd_base_version == 2:
+            phrase = inputs + [0] * (77 - len(inputs))
+        else:
+            phrase = inputs + [49407] * (77 - len(inputs))
+        phrase = np.array(phrase)[None].astype("int32")
+
+
+        return phrase
+
+
+
+    def generate_text_emb(self, sd_run):
+        sd_run.tokens = self.tokenize(sd_run.prompt)
+        if sd_run.negative_prompt is None:
+            sd_run.negative_prompt = ""
+        sd_run.unconditional_tokens = self.tokenize(sd_run.negative_prompt)
+
+        pos_ids = np.array(list(range(77)))[None].astype("int32")
+
+        context = self.model.run_text_enc(sd_run.tokens, pos_ids)
+        unconditional_context = self.model.run_text_enc(sd_run.unconditional_tokens, pos_ids)
+
+        if self.sd_base_version == 3:
+            context, penultimate_context = context
+            unconditional_context, penultimate_uncond_context = unconditional_context
+
+        sd_run.context = np.repeat(context, sd_run.batch_size, axis=0)
+        sd_run.unconditional_context = np.repeat(unconditional_context, sd_run.batch_size, axis=0)
+        if self.sd_base_version == 3:
+            sd_run.penultimate_context = np.repeat(penultimate_context, sd_run.batch_size, axis=0)
+            sd_run.penultimate_uncond_context = np.repeat(penultimate_uncond_context, sd_run.batch_size, axis=0)
+
+        if self.debug_output_path  is not None:
+            log_object(sd_run.unconditional_context   , self.debug_output_path  , key="unconditional_context")
+            log_object(sd_run.context  , self.debug_output_path  , key="context")
+        
+        self.run_plugin_hook("generate_text_emb" , "post" , sd_run)
+
+     
+    def maybe_process_inp_imgs(self, sd_run):
+
+        if sd_run.input_image_path is not None and sd_run.input_image_path != "": 
+
+            sd_run.img_height, sd_run.img_width, sd_run.input_image_processed , sd_run.input_image_processed_downscaled = process_inp_img(sd_run.input_image_path, image_size=sd_run.inp_image_resize_mode , new_w=sd_run.img_width , new_h=sd_run.img_height  )
+            sd_run.input_image_processed = sd_run.input_image_processed[None]
+            sd_run.input_image_processed_downscaled = sd_run.input_image_processed_downscaled[None]
+
+        self.run_plugin_hook("process_inp_imgs", "post", sd_run)
+
+
+    def prepare_timesteps(self, sd_run):
+        accepts_offset = "offset" in set(inspect.signature(self.scheduler.set_timesteps).parameters.keys())
+        extra_set_kwargs = {}
+        offset = 0
+        if accepts_offset:
+            offset = 1
+            extra_set_kwargs["offset"] = 1
+
+        self.scheduler.set_timesteps(sd_run.num_steps, **extra_set_kwargs)
+
+        sd_run.working_timesteps = self.scheduler.timesteps
+
+        if sd_run.starting_img_given: 
+            init_timestep = int(sd_run.num_steps * (1-sd_run.input_image_strength)) + offset
+            init_timestep = min(init_timestep, sd_run.num_steps)
+            sd_run.start_timestep = self.scheduler.timesteps[-init_timestep]
+            
+            t_start = max(sd_run.num_steps - init_timestep + offset, 0)
+            sd_run.working_timesteps = sd_run.working_timesteps[t_start:]
+
+
+
+
+    def get_noise(self, seed, shape, seed_type):
+        if  seed_type == 'np':
+            return np.random.RandomState(seed).normal(size=shape).astype('float32')
+        elif seed_type == 'pt':
+            import torch
+            torch.manual_seed(seed)
+            assert shape == (1,64,64,4), "only implemnted for (1,64,64,4)"
+            if len(shape) == 4:
+                shape = (shape[0] , shape[3] , shape[1] , shape[2])
+            a = torch.randn( (1,4,64,64) ).numpy().astype('float32')
+            return np.rollaxis(a , 1 , 4 )
+        else:
+            raise ValueError("Invalid seed type")
+        
+    def get_modded_noise(self, seed, shape ,seed_type , small_mod_seed):
+        noise = self.get_noise(seed, shape , seed_type)
+        if small_mod_seed is not None and small_mod_seed >= 0:
+            nmask = (np.random.RandomState(small_mod_seed).rand(*noise.shape ) > 0.99)
+            noise = noise*(1-nmask) + nmask*self.get_noise(small_mod_seed, noise.shape , seed_type=seed_type )
+
+        return noise
+
+
+    def get_encoded_img(self, sd_run , processes_img):
+        enc_out = self.model.run_enc(processes_img)
+        enc_out = np.repeat(enc_out, sd_run.batch_size, axis=0 )
+        enc_out_mu = enc_out[... , :4 ]
+        enc_out_logvar = enc_out[... , 4:]
+        enc_out_std = np.exp(0.5 * enc_out_logvar)
+
+        latent = enc_out_mu + enc_out_std*self.get_noise(sd_run.seed+1, enc_out_mu.shape , seed_type=sd_run.seed_type)
+        latent = 0.18215 * latent
+        return latent
+
+
+
+    def prepare_init_latent(self , sd_run):
+        n_h = sd_run.img_height // 8
+        n_w = sd_run.img_width // 8
+  
+        if not sd_run.starting_img_given:
+            latent_np = self.get_modded_noise(sd_run.seed ,(sd_run.batch_size, n_h, n_w, 4) ,  seed_type=sd_run.seed_type, small_mod_seed=sd_run.small_mod_seed  )
+
+            if self.debug_output_path is not None:
+                log_object(latent_np , self.debug_output_path  , key="latent_np")
+
+            # latent_np = latent_np * np.float64(self.scheduler.init_noise_sigma)
+            sd_run.latent = latent_np
+
+            sd_run.latent  = sd_run.latent  * self.scheduler.initial_scale
+
+        else:
+            latent = self.get_encoded_img(sd_run , sd_run.input_image_processed )
+
+            if self.debug_output_path is not None:
+                log_object(latent  , self.debug_output_path  , key="encoded_img")
+
+            sd_run.encoded_img_orig = np.copy(latent)
+
+            start_timestep = np.array([self.t_to_i(sd_run.start_timestep)] * sd_run.batch_size, dtype=np.int64 )
+           
+            noise = self.get_modded_noise(sd_run.seed , latent.shape , seed_type=sd_run.seed_type, small_mod_seed=sd_run.small_mod_seed  )
+
+            if self.debug_output_path is not None:
+                log_object(noise , self.debug_output_path  , key="noise_e")
+
+            latent = self.scheduler.add_noise(latent, noise, start_timestep )
+            sd_run.latent = latent
+
+        sd_run.init_latent = sd_run.latent
+
+        if self.debug_output_path is not None:
+            log_object(sd_run.init_latent  , self.debug_output_path  , key="sd_run_init_latent")
+
+        self.run_plugin_hook("prepare_init_latent" , "post" , sd_run)
+
+
+
+        
+
+    def t_to_i(self, t):
+        i = list(self.scheduler.timesteps).index(t)
+        assert i >= 0
+        return i
+
+    def prepare_seed(self , sd_run):
+        try:
+            sd_run.seed = int(sd_run.seed)
+            if sd_run.seed < 1:
+                sd_run.seed = int(time.time()*100)%1002487 
+        except:
+            pass
+
+        if sd_run.seed is None:
+            sd_run.seed = int(time.time()*100)%1002487
+
+        if sd_run.small_mod_seed is not None and sd_run.small_mod_seed >= 0 :
+            sd_run.small_mod_seed = sd_run.small_mod_seed + 1234*sd_run.img_id
+        else:
+            sd_run.seed = sd_run.seed  + 1234*sd_run.img_id
+
+    def prepare_time_embed(self, sd_run):
+        t = sd_run.current_t
+        timestep_batch = np.array([t])
+        t_emb = self.timestep_embedding(timestep_batch)
+        sd_run.t_emb = np.repeat(t_emb, sd_run.batch_size, axis=0)
+
+    def get_unet_out(self, sd_run):
+
+        sd_run.controls = None
+
+        self.prepare_time_embed(sd_run)
+
+        sd_run.latent_model_input = sd_run.latent
+
+        sd_run.latent_model_input =  sd_run.latent_model_input * self.scheduler.get_input_scale(self.t_to_i(sd_run.current_t))
+
+        self.run_plugin_hook("get_unet_out" , "mid" , sd_run)
+
+        if self.debug_output_path is not None:
+            log_object(sd_run.latent_model_input  , self.debug_output_path  , key="sd_run.latent_model_input")
+            log_object(sd_run.t_emb  , self.debug_output_path  , key="sd_run")
+
+        if self.sd_base_version == 3:
+            fixed_vector_cond = self.get_sdxl_fixed_vector(sd_run, is_cond=True) #np.zeros((1,2816)).astype(float)
+            fixed_vector_uncond = self.get_sdxl_fixed_vector(sd_run, is_cond=False )
+        else:
+            fixed_vector_cond = None
+            fixed_vector_uncond = None
+            
+
+        if sd_run.combine_unet_run:
+            latent_combined = np.concatenate([sd_run.latent_model_input,sd_run.latent_model_input])
+            temb_combined = np.concatenate([sd_run.t_emb,sd_run.t_emb])
+            text_emb_combined = np.concatenate([sd_run.unconditional_context , sd_run.context ])
+            assert sd_run.control_weight_current_cond == sd_run.control_weight_current_uncond, "not supported"
+            o = self.model.run_unet(unet_inp=latent_combined, time_emb=temb_combined, text_emb=text_emb_combined , control_inp=sd_run.controls, control_weight=sd_run.control_weight_current_cond, fixed_vector=fixed_vector )
+            sd_run.predicted_unconditional_latent = o[0: o.shape[0]//2 ]
+            sd_run.predicted_latent = o[o.shape[0]//2 :]
+        else:
+            sd_run.predicted_unconditional_latent = self.model.run_unet(unet_inp=sd_run.latent_model_input, time_emb=sd_run.t_emb, text_emb=sd_run.unconditional_context , control_inp=sd_run.controls, control_weight=(sd_run.control_weight_current_uncond), fixed_vector=fixed_vector_uncond)
+            sd_run.predicted_latent = self.model.run_unet(unet_inp=sd_run.latent_model_input, time_emb=sd_run.t_emb, text_emb=sd_run.context, control_inp=sd_run.controls, control_weight=(sd_run.control_weight_current_cond) , fixed_vector=fixed_vector_cond )
+
+        if self.debug_output_path is not None:
+            log_object(sd_run.predicted_unconditional_latent  , self.debug_output_path  , key="unet_out_uncond")
+            log_object(sd_run.predicted_latent  , self.debug_output_path  , key="unet_out_cond")
+
+
+    def get_next_latent(self, sd_run ):
+        t = sd_run.current_t
+        noise_pred = sd_run.predicted_unconditional_latent + sd_run.guidance_scale * (sd_run.predicted_latent  - sd_run.predicted_unconditional_latent)
+
+        if self.debug_output_path is not None:
+            log_object(noise_pred  , self.debug_output_path  , key="noise_pred")
+        
+        accepts_eta = "eta" in set(inspect.signature(self.scheduler.step).parameters.keys())
+        extra_step_kwargs = {}
+        if accepts_eta:
+            eta = 0.0 # should be between 0 and 1, but 0 for now
+            extra_step_kwargs["eta"] = eta
+
+        step_seed = sd_run.seed + 10000 + self.t_to_i(t)*4242
+        sd_run.next_latents = self.scheduler.step(noise_pred, self.t_to_i(t), sd_run.latent , seed=step_seed , **extra_step_kwargs)["prev_sample"]
+
+        if self.debug_output_path is not None:
+            log_object(sd_run.next_latents  , self.debug_output_path  , key="latents_step")
+
+        self.run_plugin_hook("get_next_latent" , "post" , sd_run)
+
+        # sd_run.next_latents = self.scheduler.step(model_output=noise_pred, timestep=t , sample=sd_run.latent , **extra_step_kwargs)["prev_sample"]
+        sd_run.latent = sd_run.next_latents
+
+
+
+    def generate(
+        self,
+        sd_run_params
+    ):
+        
+        sd_run = copy.deepcopy(sd_run_params)
+
+        if sd_run.input_image_strength > 1:
+            sd_run.input_image_strength = sd_run.input_image_strength/100.0
+        
+        if sd_run.do_v_prediction:
+            if sd_run.scheduler not in ['ddim']:
+                raise ValueError("V-prediction only works with DDIM")
+            sd_run.scheduler = sd_run.scheduler + "_v"
+
+        if sd_run.force_use_given_size:
+            sd_run.inp_image_resize_mode = None
+
+        
+        
+        
+        assert sd_run.mode in ['txt2img' , 'img2img' ]
+        
+        if sd_run.dtype not in self.ModelInterfaceClass.avail_float_types:
+            sd_run.dtype = self.ModelInterfaceClass.default_float_type
+        
+        sd_run.weight_additions = ()
+        for tpath in sd_run.lora_tdict_paths:
+            sd_run.weight_additions += (('lora' ,tpath , sd_run.lora_tdict_paths[tpath] ),)
+
+        if sd_run.is_clip_skip_2 :
+            assert self.sd_base_version == 1, "Clip skip is only supported with 1.x models"
+            sd_run.weight_additions += (('clip_skip_2' , None , None),)
+
+        
+        self.run_plugin_hook("generate" , "pre", sd_run)
+
+        if sd_run.mode == "img2img"  :
+            assert sd_run.input_image_path is not None and sd_run.input_image_path != ""
+            sd_run.starting_img_given = True
+
+
+        if self.callback(state="Starting" , progress=-1  )  == "stop":
+            return
+
+        self.prepare_model_interface(sd_run)
+
+        if sd_run.scheduler == "__default_for_model__":
+            sd_run.scheduler = "karras"
+            # if sd_run.model_name == "sdxl_base":
+            #     sd_run.scheduler = "karras"
+            # else:
+            #     sd_run.scheduler = "ddim"
+
+        self.scheduler = get_scheduler(sd_run.scheduler)
+
+
+        if self.callback(state="Encoding" , progress=-1  ) == "stop":
+            return
+
+        self.prepare_seed(sd_run)
+        self.prepare_timesteps(sd_run)
+
+        if self.debug_output_path is not None:
+            log_object(sd_run , self.debug_output_path  , key="sd_run")
+
+        self.maybe_process_inp_imgs(sd_run)
+                
+        # Tokenize prompt (i.e. starting context)
+        self.generate_text_emb(sd_run)
+        self.prepare_init_latent(sd_run)
+
+        if self.callback(state="Generating" , progress=-1  ) == "stop":
+            return
+
+        for i, t in tqdm(enumerate(sd_run.working_timesteps)):
+
+            sd_run.current_t = t
+            self.get_unet_out(sd_run)
+            self.get_next_latent(sd_run)
+
+            if self.callback(state="Generating" , progress=(100*(i+1)/len(sd_run.working_timesteps)) )  == "stop":
+                return
+
+        if self.callback(state="Decoding" , progress=-1 ) == "stop":
+            return
+
+        # Decoding stage
+        sd_run.latent = sd_run.latent/0.18215
+        sd_run.decoded = self.model.run_dec(sd_run.latent)
+
+        self.run_plugin_hook("decode" , "mid" , sd_run)
+        
+        sd_run.decoded = ((sd_run.decoded + 1) / 2) * 255
+        sd_run.ret = ({"img" : np.clip(sd_run.decoded, 0, 255).astype("uint8")})
+
+        self.run_plugin_hook("generate" , "post" , sd_run)
+        
+        return sd_run.ret
+    
+    def get_sdxl_fixed_vector(self, sd_run, is_cond):
+        height_emb = self.timestep_embedding(sd_run.img_height , dim=256 )
+        width_emb = self.timestep_embedding(sd_run.img_width , dim=256 )
+        zero_emb = self.timestep_embedding(0 , dim=256 )
+
+        # used in refine:
+        aesth_emb = self.timestep_embedding(6 , dim=256 )
+        neg_aesth_emb = self.timestep_embedding(2.5 , dim=256 )
+
+        if is_cond: 
+            if 49407 in list(sd_run.tokens[0]) :
+                last_tok_index = list(sd_run.tokens[0]).index( 49407 )
+            else:
+                last_tok_index = -1 
+            pooled = sd_run.penultimate_context[: , last_tok_index ]
+        else:
+            if 49407 in list(sd_run.unconditional_tokens[0]) :
+                last_tok_index = list(sd_run.unconditional_tokens[0]).index( 49407 )
+            else:
+                last_tok_index = -1 
+
+            pooled = sd_run.penultimate_uncond_context[: , last_tok_index ]
+
+        pooled = pooled @ self.sdxl_pooled_emb_text_proj_mat
+
+
+        vec = np.concatenate([pooled, height_emb, width_emb, zero_emb, zero_emb, height_emb, width_emb ], axis=-1)
+        assert vec.shape == (1, 2816)
+        return vec
+
+
+
+    def timestep_embedding(self, timesteps, dim=320, max_period=10000):
+        half = dim // 2
+        freqs = np.exp(
+            -math.log(max_period) * np.arange(0, half, dtype="float32") / half
+        )
+        args = np.array(timesteps) * freqs
+        embedding = np.concatenate([np.cos(args), np.sin(args)])
+        return np.reshape(embedding , (1 , -1 ))
diff --git a/backends/stable_diffusion/stable_diffusion/utils/__init__.py b/backends/stable_diffusion/stable_diffusion/utils/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/backends/stable_diffusion/utils/extra_model_utils.py b/backends/stable_diffusion/stable_diffusion/utils/extra_model_utils.py
similarity index 68%
rename from backends/stable_diffusion/utils/extra_model_utils.py
rename to backends/stable_diffusion/stable_diffusion/utils/extra_model_utils.py
index 98f65726..d9914f0f 100644
--- a/backends/stable_diffusion/utils/extra_model_utils.py
+++ b/backends/stable_diffusion/stable_diffusion/utils/extra_model_utils.py
@@ -53,3 +53,24 @@ def add_lora_ti_weights(src_tdict , weight_additions_list):
             add_lora_weights(src_tdict , state_dict, m_tdict ,  power )
 
     return state_dict
+
+def clip_skip_2_patch_weights(src_tdict, weight_additions_list ,  current_weight_additions):
+    is_skip = False
+    for add_model_fn , _ , _ in weight_additions_list:
+        if add_model_fn == "clip_skip_2":
+            is_skip = True
+
+    if is_skip:
+        src_tdict.init_read()
+        for k in src_tdict.keys():
+            if k in [
+                "cond_stage_model.transformer.text_model.encoder.layers.11.mlp.fc2.weight",
+                "cond_stage_model.transformer.text_model.encoder.layers.11.mlp.fc2.bias",
+                "cond_stage_model.transformer.text_model.encoder.layers.11.self_attn.out_proj.weight",
+                "cond_stage_model.transformer.text_model.encoder.layers.11.self_attn.out_proj.bias"
+            ]:
+                current_weight_additions[k] = (src_tdict.read_key(k).copy() * 0).astype('float16')
+
+    return current_weight_additions
+
+
diff --git a/backends/stable_diffusion/stable_diffusion/utils/image_preprocess.py b/backends/stable_diffusion/stable_diffusion/utils/image_preprocess.py
new file mode 100644
index 00000000..768d4874
--- /dev/null
+++ b/backends/stable_diffusion/stable_diffusion/utils/image_preprocess.py
@@ -0,0 +1,40 @@
+from PIL import Image, ImageOps, ImageFilter
+import numpy as np
+
+def process_inp_img(input_image, image_size="legacy_auto",new_w=None , new_h=None , only_read_alpha=False):
+    input_image = Image.open(input_image)
+
+    if only_read_alpha:
+        input_image = input_image.split()[-1] #only keep the last channel
+        input_image = ImageOps.invert(input_image)
+
+    input_image = input_image.convert('RGB')
+
+    if image_size == "legacy_auto":
+        w , h = input_image.size
+        if w > h:
+            new_w = 512
+            new_h  = round((h * new_w / w)/64)*64
+        else:
+            new_h = 512
+            new_w  = round((w * new_h / h)/64)*64
+
+    input_image_downscaled = ImageOps.fit(input_image, (new_w//8, new_h//8), method = Image.ANTIALIAS ,
+                   bleed = 0.0, centering =(0.5, 0.5))
+
+    input_image = ImageOps.fit(input_image, (new_w, new_h), method = Image.ANTIALIAS ,
+                   bleed = 0.0, centering =(0.5, 0.5))
+    input_image = np.array(input_image)[... , :3]
+    input_image_downscaled = np.array(input_image_downscaled)[... , :3]
+    input_image = (input_image.astype("float32") / 255.0)*2 - 1 
+    input_image_downscaled = (input_image_downscaled.astype("float32") / 255.0)*2 - 1 
+    return new_h , new_w  , input_image , input_image_downscaled
+
+def post_process_mask(im , dilate=None, erode=None, blur=None):
+    im = Image.fromarray((( im + 1 )*255/2).astype('uint8') )
+    if dilate is not None:
+        im = im.filter(ImageFilter.MaxFilter(dilate))
+    if erode is not None:
+        im = im.filter(ImageFilter.MinFilter(dilate))
+    return (np.array(im).astype("float32")/ 255.0)*2 - 1 
+
diff --git a/backends/stable_diffusion/utils/logging.py b/backends/stable_diffusion/stable_diffusion/utils/logging.py
similarity index 100%
rename from backends/stable_diffusion/utils/logging.py
rename to backends/stable_diffusion/stable_diffusion/utils/logging.py
diff --git a/backends/stable_diffusion/stable_diffusion/utils/model_interface.py b/backends/stable_diffusion/stable_diffusion/utils/model_interface.py
new file mode 100644
index 00000000..1d432d82
--- /dev/null
+++ b/backends/stable_diffusion/stable_diffusion/utils/model_interface.py
@@ -0,0 +1,65 @@
+from tdict import TDict
+from .extra_model_utils import add_lora_ti_weights, clip_skip_2_patch_weights
+
+
+def load_weights_model(model_container, weights_config):
+    assert model_container.model_config[0] == "SD_normal"
+    assert model_container.model_type == "SD_normal"
+
+    if model_container.weights_config == weights_config:
+        return
+
+    tdict_path, second_tdict_path, weight_additions = weights_config
+    cur_tdict_path, cur_second_tdict_path, cur_weight_additions = model_container.weights_config
+
+    tdict_1 = None
+
+    if tdict_path == cur_tdict_path and second_tdict_path == cur_second_tdict_path and cur_weight_additions == ():
+        # the main tdicts are already loaded, just load the additional weights
+        pass 
+    else:
+        if second_tdict_path is not None:
+            tdict2 = TDict(second_tdict_path)
+        else:
+            tdict2 = None
+        tdict_1 = TDict(tdict_path)
+        print("[SD] Loading weights")
+        model_container.model.load_from_tdict(tdict_1, tdict2 )
+        model_container.weights_config = tdict_path, second_tdict_path, ()
+
+    if weight_additions is not None and weight_additions != ():
+        if tdict_1 is None:
+            tdict_1 = TDict(tdict_path)
+        
+        print("[SD] Loading LoRA weights")
+        extra_weights = add_lora_ti_weights(tdict_1 , weight_additions )
+        extra_weights = clip_skip_2_patch_weights(tdict_1 , weight_additions, extra_weights )
+
+
+        model_container.model.load_from_state_dict(extra_weights )
+        model_container.weights_config = tdict_path, second_tdict_path, extra_weights
+
+def create_sd_model_with_weights(ModelInterfaceClass, model_container, model_config, weights_config):
+    model_type, model_name, dtype = model_config
+    tdict_path, second_tdict_path, weight_additions = weights_config
+
+    assert model_type == "SD_normal"
+
+    if model_container.model_config != model_config:
+        model_container.reset()
+        print("[SD] Creating model interface")
+        assert tdict_path is not None
+
+        if second_tdict_path is not None:
+            tdict2 = TDict(second_tdict_path)
+        else:
+            tdict2 = None
+
+        model_container.model = ModelInterfaceClass(TDict(tdict_path ) , dtype=dtype, model_name=model_name , second_tdict=tdict2)
+        model_container.model_type = "SD_normal"
+        model_container.model_config = model_type, model_name, dtype
+        model_container.weights_config = tdict_path, second_tdict_path, ()
+
+    load_weights_model(model_container , weights_config)
+
+
diff --git a/backends/stable_diffusion/stdin_input.py b/backends/stable_diffusion/stable_diffusion/utils/stdin_input.py
similarity index 100%
rename from backends/stable_diffusion/stdin_input.py
rename to backends/stable_diffusion/stable_diffusion/utils/stdin_input.py
diff --git a/backends/stable_diffusion/stable_diffusion/utils/utils.py b/backends/stable_diffusion/stable_diffusion/utils/utils.py
new file mode 100644
index 00000000..035f7838
--- /dev/null
+++ b/backends/stable_diffusion/stable_diffusion/utils/utils.py
@@ -0,0 +1,55 @@
+from tdict import TDict
+from ..sd_run import SDRun 
+import math
+from dataclasses import fields
+from .stdin_input import is_avail, get_input
+
+
+tdict_model_versions = {}
+def get_tdict_model_version(tdict_path):
+    if tdict_path in tdict_model_versions:
+        return tdict_model_versions[tdict_path]
+    f = TDict(tdict_path, mode='r')
+    tdict_model_versions[ tdict_path] = f.ctdict_version
+    return tdict_model_versions[ tdict_path] 
+
+
+def get_sd_run_from_dict(d):
+
+    if 'input_img' in d:
+        d['input_image_path'] = d['input_img']
+    if 'mask_image' in d:
+        d['mask_image_path'] = d['mask_image']
+    if 'model_tdict_path' in d:
+        d['tdict_path'] = d['model_tdict_path']
+
+    if 'batch_size' not in d:
+        d['batch_size'] = 1
+    if 'num_imgs' not in d:
+        d['num_imgs'] = 1
+
+    d2 = {}
+    SD_keys = [ff.name for ff in fields(SDRun) ]
+    for k in d:
+        if k in SD_keys:
+            d2[k] = d[k]
+            print(k, "k")
+
+    sd_run = SDRun(**d2)
+
+    if sd_run.input_image_path is not None and  sd_run.input_image_path != ""  and ( not sd_run.is_sd15_inpaint):
+        sd_run.mode = "img2img"
+    else:
+        sd_run.mode  = "txt2img"
+
+    
+    if "sd_mode_override" in d:
+        sd_run.mode = d["sd_mode_override"]
+
+    return sd_run
+
+
+def sd_bee_stop_callback(state="" , progress=-1):
+    if is_avail():
+        if "__stop__" in get_input():
+            return "stop"
\ No newline at end of file
diff --git a/backends/stable_diffusion/test_assets/ddd.png b/backends/stable_diffusion/test_assets/ddd.png
deleted file mode 100644
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diff --git a/backends/stable_diffusion/test_assets/inp_command_strings.txt b/backends/stable_diffusion/test_assets/inp_command_strings.txt
deleted file mode 100644
index 50b89fae..00000000
--- a/backends/stable_diffusion/test_assets/inp_command_strings.txt
+++ /dev/null
@@ -1 +0,0 @@
-b2py t2im {"prompt" : "india from space" , "seed":42}
diff --git a/backends/stable_diffusion/test_assets/mmm.png b/backends/stable_diffusion/test_assets/mmm.png
deleted file mode 100644
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diff --git a/backends/stable_diffusion/tests.py b/backends/stable_diffusion/tests.py
deleted file mode 100644
index 7bd24d42..00000000
--- a/backends/stable_diffusion/tests.py
+++ /dev/null
@@ -1,564 +0,0 @@
-
-
-import os 
-import sys
-from PIL import Image
-
-dir_path = os.path.dirname(os.path.realpath(__file__))
-sys.path.append(os.path.join(dir_path , "../model_converter"))
-model_interface_path = os.environ.get('MODEL_INTERFACE_PATH')  or "../stable_diffusion_tf_models" 
-sys.path.append( os.path.join(dir_path , model_interface_path) )
-
-from interface import ModelInterface
-from stable_diffusion import StableDiffusion
-
-p_14 = "/Users/divamgupta/.diffusionbee/downloads/sd-v1-4_fp16.tdict"
-
-p_21 = "/Users/divamgupta/Downloads/v2-1_768-nonema-pruned.tdict"
-
-
-sd = StableDiffusion( ModelInterface , p_14 , model_name=None, callback=None)
-
-
-
-def test_1():
-
-    img = sd.generate(
-            prompt="a tree" , 
-            img_height=512, 
-            img_width=512, 
-            seed=1, 
-            tdict_path=None,
-            batch_size=1,
-            dtype=ModelInterface.default_float_type,
-            scheduler='ddim',
-            mode="txt2img" )
-
-    gt_p = "./test_assets/outputs/a_tree_1_ddim.png"
-
-    Image.fromarray(img['img'][0]).show()
-
-
-def test_1_pt_seed():
-
-    img = sd.generate(
-            prompt="a tree" , 
-            img_height=512, 
-            img_width=512, 
-            seed=1417326105, 
-            seed_type="pt",
-            tdict_path=None,
-            batch_size=1,
-            dtype=ModelInterface.default_float_type,
-            scheduler='ddim',
-            mode="txt2img" )
-
-    gt_p = "./test_assets/outputs/a_tree_pt_1417326105.jpg"
-
-    Image.fromarray(img['img'][0]).show()
-
-
-
-
-
-def test_2():
-
-    img = sd.generate(
-            prompt="a fantasy tiger rightening , Fangs and tusks , massive square jaw with underbite , cybernetic eye , smoking lit cigar , Heavy and crude industrial sci " , 
-            img_height=512, 
-            img_width=512, 
-            seed=145, 
-            tdict_path=None,
-            batch_size=1,
-            dtype=ModelInterface.default_float_type,
-            scheduler='k_euler_ancestral',
-            mode="txt2img" )
-    gt_p = "./test_assets/outputs/tiger_k_euler_ancestral_145.png"
-
-    Image.fromarray(img['img'][0]).show()
-
-
-
-
-
-def test_3():
-
-    img = sd.generate(
-            prompt="a fantasy tiger rightening , Fangs and tusks , massive square jaw with underbite , cybernetic eye , smoking lit cigar , Heavy and crude industrial sci " , 
-            img_height=512, 
-            img_width=512, 
-            seed=145, 
-            tdict_path=None,
-            batch_size=1,
-            dtype=ModelInterface.default_float_type,
-            scheduler='lmsd',
-            mode="txt2img" )
-    gt_p = "./test_assets/outputs/tiger_lmsd_145.png"
-
-    Image.fromarray(img['img'][0]).show()
-
-
-def test_4():
-
-    img = sd.generate(
-            prompt="a fantasy tiger rightening , Fangs and tusks , massive square jaw with underbite , cybernetic eye , smoking lit cigar , Heavy and crude industrial sci " , 
-            img_height=512, 
-            img_width=512, 
-            seed=145, 
-            tdict_path=None,
-            batch_size=1,
-            dtype=ModelInterface.default_float_type,
-            scheduler='pndm',
-            mode="txt2img" )
-
-    gt_p = "./test_assets/outputs/tiger_pndm_145.png"
-
-    Image.fromarray(img['img'][0]).show()
-
-
-
-def test_5():
-
-    inp = "./test_assets/mmm.png"
-    mas = "./test_assets/ddd.png"
-
-    img = sd.generate(
-        prompt="Face of red cat, high resolution, sitting on a park bench" , 
-        img_height=512, 
-        img_width=512, 
-        seed=443136, 
-        input_image=inp, 
-        mask_image=mas,  
-        scheduler='ddim',
-        tdict_path="/Users/divamgupta/.diffusionbee/downloads/sd-v1-5-inpainting_fp16.tdict",
-        mode="inpaint_15" )
-
-    gt_p = "./test_assets/outputs/inp_out_443136.png"
-    Image.fromarray(img['img'][0]).show()
-
-
-def test_5_5():
-
-    inp = "./test_assets/mmm.png"
-    mas = "./test_assets/ddd.png"
-
-    img = sd.generate(
-        prompt="Face of yellow cat, high resolution, sitting on a park bench" , 
-        img_height=512, 
-        img_width=512, 
-        seed=44136, 
-        input_image=inp, 
-        mask_image=mas,  
-        num_steps=50,
-        scheduler='ddim',
-        tdict_path="/Users/divamgupta/.diffusionbee/downloads/sd-v1-5-inpainting_fp16.tdict",
-        mode="inpaint_15" )
-
-    gt_p = "./test_assets/outputs/inp_out_2_443136.png"
-    Image.fromarray(img['img'][0]).show()
-
-
-
-
-def test_6():
-
-    inp = "./test_assets/mmm.png"
-    mas = "./test_assets/ddd.png"
-
-    img = sd.generate(
-        prompt="yellow cat, high resolution, sitting on a park bench" , 
-        img_height=512, 
-        img_width=512, 
-        seed=678, 
-        input_image=inp, 
-        mask_image=mas,  
-        scheduler='ddim',
-        tdict_path="/Users/divamgupta/.diffusionbee/downloads/sd-v1-5-inpainting_fp16.tdict",
-        mode="inpaint_15" )
-    gt_p = "./test_assets/outputs/inp_out_678.png"
-    Image.fromarray(img['img'][0]).show()
-
-
-def test_7():
-
-    img = sd.generate(
-            prompt="a tree" , 
-            img_height=512, 
-            img_width=512, 
-            seed=1, 
-            batch_size=2,
-            tdict_path=None,
-            dtype=ModelInterface.default_float_type,
-            scheduler='ddim',
-            mode="txt2img" )
-
-    gt_p = "./test_assets/outputs/a_tree_1_ddim.png"
-    gt_p2 = "./test_assets/outputs/a_tree_1_ddim_2.png"
-
-
-    Image.fromarray(img['img'][0]).show()
-    Image.fromarray(img['img'][1]).show()
-
-
-
-
-def test_ctrl_1():
-    inp = "./test_assets/scribble_turtle.png"
-
-    img = sd.generate(
-            prompt="a turtle" , 
-            img_height=512, 
-            img_width=512, 
-            seed=6378, 
-            tdict_path=None,
-            second_tdict_path="/Users/divamgupta/.diffusionbee/downloads/just_control_sd15_scribble_fp16.tdict",
-            batch_size=1,
-            dtype="float16",
-            scheduler='ddim',
-            num_steps=10,
-            input_image=inp,
-            mode="controlnet" )
-
-    Image.fromarray(img['img'][0]).show()
-
-
-
-def test_sd2_1():
-
-    img = sd.generate(
-            prompt="a tree" , 
-            img_height=512, 
-            img_width=512, 
-            seed=1, 
-            num_steps=25,
-            tdict_path="/Users/divamgupta/.diffusionbee/custom_models/v2-1_512-ema-pruned.tdict",
-            batch_size=1,
-            dtype=ModelInterface.default_float_type,
-            scheduler='ddim',
-            mode="txt2img" )
-
-    # a_tree_1_sd2.png
-
-    Image.fromarray(img['img'][0]).show()
-
-
-
-def test_sd2_3():
-
-    img = sd.generate(
-            prompt="Face of yellow cat, high resolution, sitting on a park bench" , 
-            img_height=512, 
-            img_width=512, 
-            seed=111, 
-            num_steps=50,
-            tdict_path="/Users/divamgupta/.diffusionbee/custom_models/v2-1_512-ema-pruned.tdict",
-            batch_size=1,
-            dtype=ModelInterface.default_float_type,
-            scheduler='ddim',
-            mode="txt2img" )
-
-    # sd2_a_cat_111_test_sd2_3.png
-
-    Image.fromarray(img['img'][0]).show()
-
-
-
-def test_sd2_2():
-
-    img = sd.generate(
-            prompt="dog" , 
-            img_height=512, 
-            img_width=512, 
-            seed=1, 
-            num_steps=5,
-            tdict_path="/Users/divamgupta/.diffusionbee/custom_models/djzJovianSkyshipV21_0.tdict",
-            batch_size=1,
-            dtype='float16',
-            scheduler='ddim',
-            mode="txt2img" )
-
-    Image.fromarray(img['img'][0]).show()
-
-
-
-
-
-
-def test_sd2_4():
-
-    img = sd.generate(
-            prompt="a tree" , 
-            img_height=512, 
-            img_width=512, 
-            seed=13, 
-            num_steps=30,
-            tdict_path="/Volumes/ext_drive_1/sd_data_models/v2-1_768-nonema-pruned.tdict",
-            dtype="float32",
-            scheduler='ddim_v',
-            mode="txt2img" )
-
-    # sd2_a_cat_111_test_sd2_3.png
-
-    Image.fromarray(img['img'][0]).show()
-
-
-
-
-def test_lr_1():
-
-    img = sd.generate(
-            prompt="masterpiece,best quality,toon,3D,simple design, Pixar style,house, sandbox ,Peach and Mint,tree ,Florist, Arial view" , 
-            negative_prompt="lowres, bad anatomy, bad hands,text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry,tree on the roof,",
-            img_height=512, 
-            img_width=512, 
-            seed=1456, 
-            batch_size=1,
-            # tdict_path="/Users/divamgupta/Downloads/merge.tdict",
-            tdict_path="/Volumes/ext_drive_1/sd_data_models/sd-v1-5_fp16.tdict",
-            dtype=ModelInterface.default_float_type,
-            scheduler='ddim',
-            mode="txt2img" )
-
-    gt_p = "./test_assets/outputs/a_tree_1_ddim.png"
-
-    Image.fromarray(img['img'][0]).show()
-
-
-
-
-def test_1_torchseed():
-
-    img = sd.generate(
-            prompt="a tree" , 
-            img_height=512, 
-            img_width=512, 
-            seed=1417326105, 
-            tdict_path="/Volumes/ext_drive_1/sd_data_models/sd-v1-5_fp16.tdict",
-            batch_size=1,
-            dtype=ModelInterface.default_float_type,
-            scheduler='ddim',
-            mode="txt2img" )
-
-    Image.fromarray(img['img'][0]).show()
-
-
-
-
-
-def test_lr_2():
-
-    img = sd.generate(
-            prompt="masterpiece,best quality,toon,3D,simple design, Pixar style,house, sandbox ,Peach and Mint,tree ,Florist, Arial view" , 
-            negative_prompt="lowres, bad anatomy, bad hands,text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry,tree on the roof,",
-            img_height=512, 
-            img_width=512, 
-            seed=1456, 
-            batch_size=1,
-            tdict_path="/Users/divamgupta/Downloads/merge.tdict",
-            # tdict_path="/Volumes/ext_drive_1/sd_data_models/sd-v1-5_fp16.tdict",
-            dtype=ModelInterface.default_float_type,
-            scheduler='ddim',
-            mode="txt2img" )
-
-    gt_p = "./test_assets/outputs/a_tree_1_ddim.png"
-
-    Image.fromarray(img['img'][0]).show()
-
-
-
-
-def test_lr_3():
-
-    img = sd.generate(
-            prompt="masterpiece,best quality,toon,3D,simple design, Pixar style,house, sandbox ,Peach and Mint,tree ,Florist, Arial view" , 
-            negative_prompt="lowres, bad anatomy, bad hands,text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry,tree on the roof,",
-            img_height=512, 
-            img_width=512, 
-            seed=1456, 
-            batch_size=1,
-            tdict_path="/Volumes/ext_drive_1/sd_data_models/sd-v1-5_fp16.tdict",
-            dtype=ModelInterface.default_float_type,
-            scheduler='ddim',   
-            num_steps=25,
-            lora_tdict_paths={"/Users/divamgupta/Downloads/lora.tdict" : 1.0 },
-            mode="txt2img" )
-
-    gt_p = "./test_assets/outputs/a_tree_1_ddim.png"
-
-    Image.fromarray(img['img'][0]).show()
-
-
-def test_lr_31():
-
-    img = sd.generate(
-            prompt="masterpiece,best quality,toon,3D,simple design, Pixar style,house, sandbox ,Peach and Mint,tree ,Florist, Arial view" , 
-            negative_prompt="lowres, bad anatomy, bad hands,text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry,tree on the roof,",
-            img_height=512-128, 
-            img_width=512+128, 
-            seed=1456, 
-            batch_size=1,
-            tdict_path="/Volumes/ext_drive_1/sd_data_models/sd-v1-5_fp16.tdict",
-            dtype=ModelInterface.default_float_type,
-            num_steps=25,
-            scheduler='ddim',   
-            lora_tdict_paths={"/Users/divamgupta/Downloads/lora.tdict" : 1.0 },
-            mode="txt2img" )
-
-    gt_p = "./test_assets/outputs/a_tree_1_ddim.png"
-
-    Image.fromarray(img['img'][0]).show()
-
-
-def test_lr_32():
-
-    img = sd.generate(
-            prompt="masterpiece,best quality,toon,3D,simple design, Pixar style,house, sandbox ,Peach and Mint,tree ,Florist, Arial view" , 
-            negative_prompt="lowres, bad anatomy, bad hands,text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry,tree on the roof,",
-            img_height=512-128, 
-            img_width=512+128, 
-            seed=1456, 
-            batch_size=1,
-            tdict_path=p_14,
-            dtype=ModelInterface.default_float_type,
-            num_steps=25,
-            scheduler='ddim',   
-            lora_tdict_paths={"/Users/divamgupta/Downloads/lora.tdict" : 1.0 },
-            mode="txt2img" )
-
-    gt_p = "./test_assets/outputs/a_tree_1_ddim.png"
-
-    Image.fromarray(img['img'][0]).show()
-
-
-
-
-# test_lr_1()
-
-def test_11():
-
-    img = sd.generate(
-            prompt="a tree" , 
-            img_height=512, 
-            img_width=512, 
-            seed=1, 
-            tdict_path=None,
-            batch_size=1,
-            num_steps=5,
-            dtype=ModelInterface.default_float_type,
-            scheduler='ddim',
-            mode="txt2img" )
-
-    gt_p = "./test_assets/outputs/a_tree_1_ddim.png"
-
-    Image.fromarray(img['img'][0]).show()
-
-
-
-test_11()
-
-exit()
-
-
-
-# inp = "./test_assets/yoga1.jpg"
-
-
-# img = sd.generate(
-#         prompt="a man doing yoga, Underwater series /// High detail RAW color photo professional, highly detail face: 1.4, a detailed portrait of a woman floating underwater wearing long flowing dress, nymph style, amazing underwater, detailed skin, wet clothes, wet hair, see-through clothes, lens flare, shade, tindal effect, lens flare, backlighting, bokeh " , 
-#         img_height=512, 
-#         img_width=512, 
-#         seed=6378, 
-#         tdict_path=None,
-#         second_tdict_path="/Users/divamgupta/Downloads/just_control_sd15_openpose_fp16.tdict",
-#         batch_size=1,
-#         dtype=ModelInterface.default_float_type,
-#         scheduler='ddim',
-#         num_steps=25,
-#         input_image=inp,
-#         inp_img_preprocesser="body_pose",
-#         mode="controlnet" )
-
-
-# Image.fromarray(img[0]).show()
-
-
-
-
-
-# Image.fromarray(img['img'][0]).show()
-
-
-# img = sd.generate(
-#         prompt="a tortoise" , 
-#         img_height=512, 
-#         img_width=512, 
-#         seed=678, 
-#         tdict_path=None,
-#         batch_size=1,
-#         dtype=ModelInterface.default_float_type,
-#         scheduler='ddim',
-#         input_image=inp,
-#         mode="txt2img" )
-
-
-# Image.fromarray(img[0]).show()
-
-
-inp = "./test_assets/mmm.png"
-mas = "./test_assets/ddd.png"
-
-
-
-
-for cur_run_id in range(2):
-    img = sd.generate(
-        prompt="a haloween bedroom" , 
-        img_height=512+64, 
-        img_width=512-64, 
-        seed=678, 
-        tdict_path=None,
-        batch_size=1,
-        dtype=ModelInterface.default_float_type,
-        scheduler='ddim',
-        input_image_strength=0.4,
-        input_image="bedroom2.jpg",
-        mode="img2img" )
-    Image.fromarray(img[0]).show()
-
-for cur_run_id in range(2):
-    img = sd.generate(
-        prompt="modern disney a blue colored baby lion with lots of fur" , 
-        img_height=512-64, 
-        img_width=512, 
-        seed=34, 
-        num_steps=25,
-        batch_size=1,
-        tdict_path="/Users/divamgupta/.diffusionbee/custom_models/moDi-v1-pruned.tdict",
-        dtype=ModelInterface.default_float_type,
-        scheduler='ddim',
-        mode="txt2img" )
-    Image.fromarray(img[0]).show()
-
-img = sd.generate(
-    prompt="modern disney a blue colored baby lion with lots of fur" , 
-    img_height=512, 
-    img_width=512, 
-    seed=34, 
-    tdict_path=None,
-    mode="txt2img" )
-Image.fromarray(img[0]).show()
-
-
-img = sd.generate(
-    prompt="Face of red cat, high resolution, sitting on a park bench" , 
-    img_height=512, 
-    img_width=512, 
-    seed=443136, 
-    input_image=inp, 
-    mask_image=mas,  
-    tdict_path="/Users/divamgupta/Downloads/sd-v1-5-inpainting.tdict",
-    mode="inpaint_15" )
-Image.fromarray(img[0]).show()
-
-
-
diff --git a/backends/stable_diffusion_tf_models/interface.py b/backends/stable_diffusion_tf_models/interface.py
index d029eae9..606b62cc 100644
--- a/backends/stable_diffusion_tf_models/interface.py
+++ b/backends/stable_diffusion_tf_models/interface.py
@@ -158,11 +158,13 @@ def __init__(self, tdict,  dtype='float16', model_name="sd_1x", second_tdict=Non
         self.load_from_tdict(tdict, second_tdict=second_tdict)
 
 
-    def run_unet(self, time_emb, text_emb, unet_inp, control_inp=None):
+    def run_unet(self, time_emb, text_emb, unet_inp, control_inp=None,  control_weight=1, fixed_vector=None  ):
         time_emb = np.array(time_emb).astype('float32')
         text_emb = np.array(text_emb).astype('float32')
         unet_inp = np.array(unet_inp).astype('float32')
         inps = [unet_inp, time_emb, text_emb]
+        assert fixed_vector is None, "Fixed vector not supported"
+        assert control_weight == 1 or control_weight == 1.0 , "Control weight not supported"
         if control_inp is not None:
             inps = inps + [ np.array(c).astype('float32') for c in control_inp ]
         return np.array(self.diffusion_model_f(inps ))
diff --git a/DOCUMENTATION.md b/docs/DOCUMENTATION.md
similarity index 100%
rename from DOCUMENTATION.md
rename to docs/DOCUMENTATION.md
diff --git a/docs/Running_from_source.md b/docs/Running_from_source.md
new file mode 100644
index 00000000..a6e2ba40
--- /dev/null
+++ b/docs/Running_from_source.md
@@ -0,0 +1,47 @@
+## How to run DiffusionBee from source 
+
+Install the following
+- Miniforge 
+- Nodejs v16
+
+
+Clone the repo: 
+
+```
+git clone https://github.com/divamgupta/diffusionbee-stable-diffusion-ui
+
+```
+
+
+
+
+Create the conda environment and activate it:
+
+```
+conda create -n diffusion_bee_env  python=3.9.10
+conda activate diffusion_bee_env
+
+```
+
+Install the python packages :
+
+```
+cd diffusionbee-stable-diffusion-ui/backends/stable_diffusion
+pip install -r requirements.txt
+
+```
+
+Install the npm packages 
+
+```
+cd diffusionbee-stable-diffusion-ui/electron_app
+npm install
+```
+
+
+Run the app
+
+```
+npm run electron:serve 
+
+```
\ No newline at end of file
diff --git a/electron_app/.gitignore b/electron_app/.gitignore
index e0c4a0a5..934fd0ff 100644
--- a/electron_app/.gitignore
+++ b/electron_app/.gitignore
@@ -2,6 +2,9 @@
 node_modules
 /dist
 
+build_config.json
+dist_electron
+./dist_electron
 
 # local env files
 .env.local
@@ -24,5 +27,3 @@ pnpm-debug.log*
 
 #Electron-builder output
 /dist_electron
-
-build_config.json
\ No newline at end of file
diff --git a/electron_app/.nvmrc b/electron_app/.nvmrc
deleted file mode 100644
index 3b3a53bf..00000000
--- a/electron_app/.nvmrc
+++ /dev/null
@@ -1 +0,0 @@
-16.20.0
\ No newline at end of file
diff --git a/electron_app/afterSignHook.js b/electron_app/afterSignHook.js
deleted file mode 100644
index 4fa5a815..00000000
--- a/electron_app/afterSignHook.js
+++ /dev/null
@@ -1,35 +0,0 @@
-require('dotenv').config();
-const fs = require('fs');
-const path = require('path');
-var electron_notarize = require('electron-notarize');
-
-module.exports = async function (params) {
-    if (process.platform !== 'darwin') {
-        return;
-    }
-
-    console.log('afterSign hook triggered', params);
-
-    let appId = 'com.diffusionbee.diffusionbee'
-
-    let appPath = path.join(params.appOutDir, `${params.packager.appInfo.productFilename}.app`);
-    if (!fs.existsSync(appPath)) {
-        console.log('skip');
-        return;
-    }
-
-    console.log(`Notarizing ${appId} found at ${appPath}`);
-
-    try {
-        await electron_notarize.notarize({
-            appBundleId: appId,
-            appPath: appPath,
-            appleId: process.env.APPLE_ID,
-            appleIdPassword: process.env.APPLE_ID_PASSWORD,
-        });
-    } catch (error) {
-        console.error(error);
-    }
-
-    console.log(`Done notarizing ${appId}`);
-};
\ No newline at end of file
diff --git a/electron_app/package-lock.json b/electron_app/package-lock.json
index cf3d5af9..a4b3af30 100644
--- a/electron_app/package-lock.json
+++ b/electron_app/package-lock.json
@@ -1,12 +1,12 @@
 {
   "name": "DiffusionBee",
-  "version": "1.5.1",
-  "lockfileVersion": 2,
+  "version": "2.3.0",
+  "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "DiffusionBee",
-      "version": "1.5.1",
+      "version": "2.3.0",
       "hasInstallScript": true,
       "dependencies": {
         "@codekraft-studio/vue-record": "^0.0.3",
@@ -16,17 +16,21 @@
         "bootstrap": "^5.1.3",
         "bootstrap-vue": "^2.21.2",
         "chart.js": "^2.9.4",
-        "core-js": "^3.6.5",
+        "core-js": "^3.8.3",
         "electron-context-menu": "^3.5.0",
         "electron-localshortcut": "^3.2.1",
         "electron-notarize": "^1.2.1",
         "electron-settings": "^4.0.2",
         "fuse.js": "^6.6.2",
         "javascript-time-ago": "^2.3.13",
+        "js-yaml": "^4.1.0",
         "konva": "^8.3.13",
         "nsfwjs": "^2.4.2",
+        "path": "^0.12.7",
+        "stream": "^0.0.2",
         "v-click-outside": "^3.1.2",
-        "vue": "^2.6.11",
+        "verte": "^0.0.12",
+        "vue": "^2.6.14",
         "vue-apexcharts": "^1.6.2",
         "vue-chartjs": "^3.5.1",
         "vue-click-outside": "^1.1.0",
@@ -37,61 +41,100 @@
         "vue-web-cam": "^1.9.0"
       },
       "devDependencies": {
-        "@vue/cli-plugin-babel": "~4.5.0",
-        "@vue/cli-plugin-eslint": "~4.5.0",
-        "@vue/cli-service": "~4.5.0",
+        "@babel/core": "^7.12.16",
+        "@babel/eslint-parser": "^7.12.16",
+        "@vue/cli-plugin-babel": "~5.0.0",
+        "@vue/cli-plugin-eslint": "~5.0.0",
+        "@vue/cli-service": "~5.0.0",
         "babel-eslint": "^10.1.0",
-        "electron": "^13.0.0",
+        "electron": "^13.6.9",
         "electron-builder": "^23.3.3",
         "electron-devtools-installer": "^3.1.0",
-        "eslint": "^6.7.2",
-        "eslint-plugin-vue": "^6.2.2",
-        "vue-cli-plugin-electron-builder": "~2.1.1",
-        "vue-template-compiler": "^2.6.11"
+        "eslint": "^7.32.0",
+        "eslint-plugin-vue": "^8.0.3",
+        "vue-cli-plugin-electron-builder": "^2.1.1",
+        "vue-template-compiler": "^2.6.14"
+      }
+    },
+    "node_modules/@aashutoshrathi/word-wrap": {
+      "version": "1.2.6",
+      "resolved": "https://registry.npmjs.org/@aashutoshrathi/word-wrap/-/word-wrap-1.2.6.tgz",
+      "integrity": "sha512-1Yjs2SvM8TflER/OD3cOjhWWOZb58A2t7wpE2S9XfBYTiIl+XFhQG2bjy4Pu1I+EAlCNUzRDYDdFwFYUKvXcIA==",
+      "dev": true,
+      "engines": {
+        "node": ">=0.10.0"
+      }
+    },
+    "node_modules/@achrinza/node-ipc": {
+      "version": "9.2.8",
+      "resolved": "https://registry.npmjs.org/@achrinza/node-ipc/-/node-ipc-9.2.8.tgz",
+      "integrity": "sha512-DSzEEkbMYbAUVlhy7fg+BzccoRuSQzqHbIPGxGv19OJ2WKwS3/9ChAnQcII4g+GujcHhyJ8BUuOVAx/S5uAfQg==",
+      "dev": true,
+      "dependencies": {
+        "@node-ipc/js-queue": "2.0.3",
+        "event-pubsub": "4.3.0",
+        "js-message": "1.0.7"
+      },
+      "engines": {
+        "node": "8 || 9 || 10 || 11 || 12 || 13 || 14 || 15 || 16 || 17 || 18 || 19 || 20 || 21"
+      }
+    },
+    "node_modules/@ampproject/remapping": {
+      "version": "2.2.1",
+      "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.2.1.tgz",
+      "integrity": "sha512-lFMjJTrFL3j7L9yBxwYfCq2k6qqwHyzuUl/XBnif78PWTJYyL/dfowQHWE3sp6U6ZzqWiiIZnpTMO96zhkjwtg==",
+      "dev": true,
+      "dependencies": {
+        "@jridgewell/gen-mapping": "^0.3.0",
+        "@jridgewell/trace-mapping": "^0.3.9"
+      },
+      "engines": {
+        "node": ">=6.0.0"
       }
     },
     "node_modules/@babel/code-frame": {
-      "version": "7.16.7",
-      "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.16.7.tgz",
-      "integrity": "sha512-iAXqUn8IIeBTNd72xsFlgaXHkMBMt6y4HJp1tIaK465CWLT/fG1aqB7ykr95gHHmlBdGbFeWWfyB4NJJ0nmeIg==",
+      "version": "7.23.5",
+      "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.23.5.tgz",
+      "integrity": "sha512-CgH3s1a96LipHCmSUmYFPwY7MNx8C3avkq7i4Wl3cfa662ldtUe4VM1TPXX70pfmrlWTb6jLqTYrZyT2ZTJBgA==",
       "dev": true,
       "dependencies": {
-        "@babel/highlight": "^7.16.7"
+        "@babel/highlight": "^7.23.4",
+        "chalk": "^2.4.2"
       },
       "engines": {
         "node": ">=6.9.0"
       }
     },
     "node_modules/@babel/compat-data": {
-      "version": "7.16.8",
-      "resolved": "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.16.8.tgz",
-      "integrity": "sha512-m7OkX0IdKLKPpBlJtF561YJal5y/jyI5fNfWbPxh2D/nbzzGI4qRyrD8xO2jB24u7l+5I2a43scCG2IrfjC50Q==",
+      "version": "7.23.5",
+      "resolved": "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.23.5.tgz",
+      "integrity": "sha512-uU27kfDRlhfKl+w1U6vp16IuvSLtjAxdArVXPa9BvLkrr7CYIsxH5adpHObeAGY/41+syctUWOZ140a2Rvkgjw==",
       "dev": true,
       "engines": {
         "node": ">=6.9.0"
       }
     },
     "node_modules/@babel/core": {
-      "version": "7.16.12",
-      "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.16.12.tgz",
-      "integrity": "sha512-dK5PtG1uiN2ikk++5OzSYsitZKny4wOCD0nrO4TqnW4BVBTQ2NGS3NgilvT/TEyxTST7LNyWV/T4tXDoD3fOgg==",
-      "dev": true,
-      "dependencies": {
-        "@babel/code-frame": "^7.16.7",
-        "@babel/generator": "^7.16.8",
-        "@babel/helper-compilation-targets": "^7.16.7",
-        "@babel/helper-module-transforms": "^7.16.7",
-        "@babel/helpers": "^7.16.7",
-        "@babel/parser": "^7.16.12",
-        "@babel/template": "^7.16.7",
-        "@babel/traverse": "^7.16.10",
-        "@babel/types": "^7.16.8",
-        "convert-source-map": "^1.7.0",
+      "version": "7.23.6",
+      "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.23.6.tgz",
+      "integrity": "sha512-FxpRyGjrMJXh7X3wGLGhNDCRiwpWEF74sKjTLDJSG5Kyvow3QZaG0Adbqzi9ZrVjTWpsX+2cxWXD71NMg93kdw==",
+      "dev": true,
+      "dependencies": {
+        "@ampproject/remapping": "^2.2.0",
+        "@babel/code-frame": "^7.23.5",
+        "@babel/generator": "^7.23.6",
+        "@babel/helper-compilation-targets": "^7.23.6",
+        "@babel/helper-module-transforms": "^7.23.3",
+        "@babel/helpers": "^7.23.6",
+        "@babel/parser": "^7.23.6",
+        "@babel/template": "^7.22.15",
+        "@babel/traverse": "^7.23.6",
+        "@babel/types": "^7.23.6",
+        "convert-source-map": "^2.0.0",
         "debug": "^4.1.0",
         "gensync": "^1.0.0-beta.2",
-        "json5": "^2.1.2",
-        "semver": "^6.3.0",
-        "source-map": "^0.5.0"
+        "json5": "^2.2.3",
+        "semver": "^6.3.1"
       },
       "engines": {
         "node": ">=6.9.0"
@@ -101,76 +144,94 @@
         "url": "https://opencollective.com/babel"
       }
     },
+    "node_modules/@babel/eslint-parser": {
+      "version": "7.23.3",
+      "resolved": "https://registry.npmjs.org/@babel/eslint-parser/-/eslint-parser-7.23.3.tgz",
+      "integrity": "sha512-9bTuNlyx7oSstodm1cR1bECj4fkiknsDa1YniISkJemMY3DGhJNYBECbe6QD/q54mp2J8VO66jW3/7uP//iFCw==",
+      "dev": true,
+      "dependencies": {
+        "@nicolo-ribaudo/eslint-scope-5-internals": "5.1.1-v1",
+        "eslint-visitor-keys": "^2.1.0",
+        "semver": "^6.3.1"
+      },
+      "engines": {
+        "node": "^10.13.0 || ^12.13.0 || >=14.0.0"
+      },
+      "peerDependencies": {
+        "@babel/core": "^7.11.0",
+        "eslint": "^7.5.0 || ^8.0.0"
+      }
+    },
     "node_modules/@babel/generator": {
-      "version": "7.16.8",
-      "resolved": "https://registry.npmjs.org/@babel/generator/-/generator-7.16.8.tgz",
-      "integrity": "sha512-1ojZwE9+lOXzcWdWmO6TbUzDfqLD39CmEhN8+2cX9XkDo5yW1OpgfejfliysR2AWLpMamTiOiAp/mtroaymhpw==",
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diff --git a/electron_app/package.json b/electron_app/package.json
index 3dad7439..2db98b8f 100644
--- a/electron_app/package.json
+++ b/electron_app/package.json
@@ -1,7 +1,7 @@
 {
   "name": "DiffusionBee",
-  "version": "1.7.4",
-  "build_number": "0024",
+  "version": "2.3.0",
+  "build_number": "0029",
   "website": "https://diffusionbee.com",
   "description": "Diffusion Bee - Stable Diffusion App.",
   "is_dev": false,
@@ -26,17 +26,21 @@
     "bootstrap": "^5.1.3",
     "bootstrap-vue": "^2.21.2",
     "chart.js": "^2.9.4",
-    "core-js": "^3.6.5",
+    "core-js": "^3.8.3",
     "electron-context-menu": "^3.5.0",
     "electron-localshortcut": "^3.2.1",
     "electron-notarize": "^1.2.1",
     "electron-settings": "^4.0.2",
     "fuse.js": "^6.6.2",
     "javascript-time-ago": "^2.3.13",
+    "js-yaml": "^4.1.0",
     "konva": "^8.3.13",
     "nsfwjs": "^2.4.2",
+    "path": "^0.12.7",
+    "stream": "^0.0.2",
     "v-click-outside": "^3.1.2",
-    "vue": "^2.6.11",
+    "verte": "^0.0.12",
+    "vue": "^2.6.14",
     "vue-apexcharts": "^1.6.2",
     "vue-chartjs": "^3.5.1",
     "vue-click-outside": "^1.1.0",
@@ -47,17 +51,19 @@
     "vue-web-cam": "^1.9.0"
   },
   "devDependencies": {
-    "@vue/cli-plugin-babel": "~4.5.0",
-    "@vue/cli-plugin-eslint": "~4.5.0",
-    "@vue/cli-service": "~4.5.0",
+    "@babel/core": "^7.12.16",
+    "@babel/eslint-parser": "^7.12.16",
+    "@vue/cli-plugin-babel": "~5.0.0",
+    "@vue/cli-plugin-eslint": "~5.0.0",
+    "@vue/cli-service": "~5.0.0",
     "babel-eslint": "^10.1.0",
-    "electron": "^13.0.0",
+    "electron": "^13.6.9",
     "electron-builder": "^23.3.3",
     "electron-devtools-installer": "^3.1.0",
-    "eslint": "^6.7.2",
-    "eslint-plugin-vue": "^6.2.2",
-    "vue-cli-plugin-electron-builder": "~2.1.1",
-    "vue-template-compiler": "^2.6.11"
+    "eslint": "^7.32.0",
+    "eslint-plugin-vue": "^8.0.3",
+    "vue-cli-plugin-electron-builder": "^2.1.1",
+    "vue-template-compiler": "^2.6.14"
   },
   "eslintConfig": {
     "root": true,
@@ -71,7 +77,10 @@
     "parserOptions": {
       "parser": "babel-eslint"
     },
-    "rules": {}
+    "rules": {
+      "vue/multi-word-component-names": "off",
+      "vue/no-mutating-props": "off"
+    }
   },
   "browserslist": [
     "> 1%",
diff --git a/electron_app/src/App.vue b/electron_app/src/App.vue
index 0c065759..4699e3a1 100644
--- a/electron_app/src/App.vue
+++ b/electron_app/src/App.vue
@@ -4,115 +4,34 @@
         <!-- <img alt="Vue logo" src="./assets/logo.png"> -->
         
         <StableDiffusion ref="stable_diffusion"> </StableDiffusion>
-
-            
-
+        <SDManager :app="app" ref="sd_manager"> </SDManager>
+        <AssetsManager ref="assets_manager"> </AssetsManager>
         
         <div v-if="app_state.is_start_screen">
             <transition name="slide_show">
                 <SplashScreen v-if="app_state.show_splash_screen"></SplashScreen>
             </transition>
         </div>
-        <ApplicationFrame ref="app_frame" v-else title="DiffusionBee - Stable Diffusion App"
-
-            @menu_item_click_about="show_about"
-            @menu_item_click_help="open_url('https://diffusionbee.com/')"
-            @menu_item_click_close="close_window"
-            @menu_item_click_discord="open_url('https://discord.gg/t6rC5RaJQn')"
-            @menu_item_click_model_license="open_url('https://diffusionbee.com/MODEL_LICENSE.txt')"
-            @menu_item_click_oss_license="open_url('https://diffusionbee.com/OPEN_SOURCE_LICENSES.txt')"
-
+        <ApplicationFrame ref="app_frame" v-else :title="current_applet_title + ' - ' + 'DiffusionBee'" :sidebar_item_on_click="sidebar_item_on_click"
+        :sidebar_items="
+            (all_pages_ready ) ?  $refs.router.all_sidebar_items : []
+        " :selected_sidebar_item_id="current_selected_tab"
+        :on_home_click="on_home_click"
         > 
-            <template v-slot:txt2img>
-                <ImgGenerate v-if="is_mounted && stable_diffusion.is_ready()"  :app_state="app_state" :stable_diffusion="stable_diffusion"></ImgGenerate>
-                <div  v-else  class="animatable_content_box ">
-                    <LoaderModal :loading_percentage="stable_diffusion.loading_percentage" :loading_desc="stable_diffusion.model_loading_msg"  :loading_title="stable_diffusion.model_loading_title ||'Loading Model'"> </LoaderModal>
-                    <div class="bottom_float"> <p>Please make sure you have around 8GB of free space for the models.</p> </div>
-               
-                </div>
-
-               
-            </template>
-
-            <template v-slot:img2img>
-
-                <Img2Img  ref="img2img" v-if="is_mounted && stable_diffusion.is_ready()"  :app_state="app_state" :stable_diffusion="stable_diffusion"></Img2Img>
-                <div  v-else  class="animatable_content_box ">
-                    <LoaderModal :loading_percentage="stable_diffusion.loading_percentage" :loading_desc="stable_diffusion.model_loading_msg"  :loading_title="stable_diffusion.model_loading_title ||'Loading Model'"> </LoaderModal>
-                    <div class="bottom_float"> <p>Please make sure you have around 8GB of free space for the models.</p> </div>
-                </div>
-
-            </template>
-
-
-             <template v-slot:controlnet>
-                <KeepAlive>
-                    <ControlNet  ref="controlnet" v-if="is_mounted && stable_diffusion.is_ready()"  :app_state="app_state" :stable_diffusion="stable_diffusion"></ControlNet>
-                     <div  v-else  class="animatable_content_box ">
-                        <LoaderModal :loading_percentage="stable_diffusion.loading_percentage" :loading_desc="stable_diffusion.model_loading_msg"  :loading_title="stable_diffusion.model_loading_title ||'Loading Model'"> </LoaderModal>
-                        <div class="bottom_float"> <p>Please make sure you have around 8GB of free space for the models.</p> </div>
-                    </div>
-                </KeepAlive>
-               
-
-            </template>
-
-
-            <template v-slot:outpainting>
-                
-                <Outpainting  ref="outpaint" v-if="is_mounted && stable_diffusion.is_ready()"  :app_state="app_state" :stable_diffusion="stable_diffusion"></Outpainting>
-                <div  v-else  class="animatable_content_box ">
-                    <LoaderModal :loading_percentage="stable_diffusion.loading_percentage" :loading_desc="stable_diffusion.model_loading_msg"  :loading_title="stable_diffusion.model_loading_title ||'Loading Model'"> </LoaderModal>
-                    <div class="bottom_float"> <p>Please make sure you have around 8GB of free space for the models.</p> </div>
-                </div>
-                
-            </template>
-
-            <template v-slot:inpainting>
-                
-                <Inpainting  ref="inpaint" v-if="is_mounted && stable_diffusion.is_ready()"  :app_state="app_state" :stable_diffusion="stable_diffusion"></Inpainting>
-                <div  v-else  class="animatable_content_box ">
-                    <LoaderModal :loading_percentage="stable_diffusion.loading_percentage" :loading_desc="stable_diffusion.model_loading_msg"  :loading_title="stable_diffusion.model_loading_title ||'Loading Model'"> </LoaderModal>
-                    <div class="bottom_float"> <p>Please make sure you have around 8GB of free space for the models.</p> </div>
-                </div>
-                
-            </template>
-
-            <template v-slot:upscale_img>
-                <UpscaleImage  :app_state="app_state" ref="upscale_img"></UpscaleImage>
-            </template>
-
-            
-
             
-
-            <template v-slot:history>
-                <History :app_state="app_state"></History>
+            <template v-slot:main_content>
+                <PagesRouter  v-if="is_mounted && stable_diffusion.is_ready()"  :app="app" ref="router" > </PagesRouter>
             </template>
 
-            <template v-slot:settings>
-                <Settings :app_state="app_state"></Settings>
+            <template v-slot:main_toolbar>
+                <MainToolbar  v-if="is_mounted"  :app="app" ref="toolbar" > </MainToolbar>
             </template>
 
-            <template v-slot:logs>
-                <div class="animatable_content_box ">
-                    <p>Logs : </p>
-
-                    <p>
-                        <span style="white-space: pre-line">{{app_state.logs}}</span>
-                    </p>
 
-                </div>
-
-            </template>
         </ApplicationFrame>
 
         <LoaderModal v-if="app_state.global_loader_modal_msg" :loading_percentage="-1"  :loading_title="app_state.global_loader_modal_msg"> </LoaderModal>
 
-           
-
-       
-
     </div>
 </template>
 <script>
@@ -121,17 +40,14 @@ import { bind_app_component } from "./py_vue_bridge.js"
 import { send_to_py } from "./py_vue_bridge.js"
 import {native_confirm, native_alert } from "./native_functions_vue_bridge.js"
 import StableDiffusion from "./StableDiffusion.vue"
+import SDManager from "./SDManager.vue"
+import AssetsManager from "./AssetsManager.vue"
+
 import SplashScreen from './components_bare/SplashScreen.vue'
 import ApplicationFrame from './components_bare/ApplicationFrame.vue'
-import ImgGenerate from './components/ImgGenerate.vue'
-import Img2Img from './components/Img2Img.vue'
-import ControlNet from "./components/ControlNet.vue"
-import Outpainting from './components/Outpainting.vue'
-import UpscaleImage from './components/UpscaleImage.vue'
-import Inpainting from "./components/Inpainting.vue"
-import History from './components/History.vue'
-import Settings from './components/Settings.vue'
 
+import PagesRouter from "./components/PagesRouter.vue"
+import MainToolbar from "./components/MainToolbar.vue"
 
 import LoaderModal from './components_bare/LoaderModal.vue'
 import Vue from "vue"
@@ -145,21 +61,22 @@ export default
     components: {
         SplashScreen,
         ApplicationFrame,
-        ImgGenerate, 
+        AssetsManager,
         StableDiffusion,
+        SDManager,
         LoaderModal,
-        History,
-        Img2Img,
-        Outpainting,
-        UpscaleImage, 
-        Inpainting,
-        Settings,
-        ControlNet
+        PagesRouter,
+        MainToolbar
+       
     },
 
     mounted() {
-
+        this.app = this;
+        window.app = this.app; // so that we can access from console
         this.stable_diffusion = this.$refs.stable_diffusion;
+        this.stable_diffusion_manager = this.$refs.sd_manager;
+        this.stable_diffusion_manager.stable_diffusion = this.stable_diffusion;
+        this.assets_manager = this.$refs.assets_manager;
 
         bind_app_component(this);
         send_to_py("strt");
@@ -171,15 +88,18 @@ export default
 
         let that = this;
 
-        setTimeout( function(){
-             
-            that.app_state.is_start_screen = false;
-        }  , 5000)
+        this.start_screen_interval = setInterval( function(){
+            console.log(that.stable_diffusion.is_input_avai)
+            if(that.stable_diffusion && that.stable_diffusion.is_input_avail){
+                that.app_state.is_start_screen = false;
+                clearInterval(that.start_screen_interval)
+            }
+            
+        }  , 1500)
 
         this.is_mounted = true;
 
-
-        let data = window.ipcRenderer.sendSync('load_data');
+        let data = window.ipcRenderer.sendSync('load_data', 'app_data_2.json');
         if(!data.history){
             data.history = {}
         }
@@ -195,7 +115,6 @@ export default
         if( data ){
             Vue.set(this.app_state , 'app_data' , data)
         }
-            
      
     },
 
@@ -205,6 +124,7 @@ export default
             handler: function(new_value) {
                 if (new_value == false) {
                     if(this.is_screen_frozen){
+                        console.log("Unfreeze win!")
                         window.ipcRenderer.sendSync('unfreeze_win', '');
                         this.is_screen_frozen = false;
                     }
@@ -212,6 +132,7 @@ export default
                 }
                 else{
                     if(!this.is_screen_frozen){
+                        console.log("Freeze win!")
                         window.ipcRenderer.sendSync('freeze_win', '');
                         this.is_screen_frozen = true;
                     }
@@ -223,33 +144,46 @@ export default
         'app_state.app_data': {
 
             handler: function(new_value) {
-                window.ipcRenderer.sendSync('save_data', new_value );
+                window.ipcRenderer.sendSync('save_data', new_value , "app_data_2.json");
             },
             deep: true
         } , 
-        
 
+        'is_sd_avail' : {
+            handler: function() {
+                this.set_show_dialog_on_quit()
+            },
+            deep: true
+        }
+        
     },
 
     computed : {
+        is_sd_avail(){
+            if(!this.is_mounted)
+                return false
+            return this.$refs.stable_diffusion.is_input_avail 
+        }
     },
 
     methods: {
 
         main_screen() {
 
-
         },
 
-        
-        change_startscreen_tab(tab_name){
-            let that = this;
-            setTimeout( function(){
-                that.$refs.start_screen.on_sidebar_click(tab_name);
-            } , 50 )
-            
+        show_toast(msg){
+            Vue.$toast.default(msg)
         },
 
+        sidebar_item_on_click(t){
+            this.current_selected_tab = t;
+            this.functions.switch_page(t);
+        }, 
+
+        on_home_click(){
+            this.functions.switch_page("Homepage")
+        },
        
         check_for_updates(){
             
@@ -275,20 +209,9 @@ export default
             xmlHttp.send(null);
         },
 
-        switch_frame_tab(tab_name){
-            // switch the tab of the frame 
-            this.$refs.app_frame.selected_tab = tab_name;
-        } , 
-
         set_show_dialog_on_quit(){
             // determine whether electron process should show a confirmation message while closing or not 
-            if(! this.$refs.stable_diffusion.is_ready() )
-            {
-                this.should_show_dialog_on_quit = true;
-                this.show_dialog_on_quit_msg = 'Model has not finished loading. Are you sure you want to quit?';
-                window.ipcRenderer.sendSync('show_dialog_on_quit', this.show_dialog_on_quit_msg);
-            }
-            else if( ! this.$refs.stable_diffusion.is_input_avail )
+            if( ! this.$refs.stable_diffusion.is_input_avail )
             {
                 this.should_show_dialog_on_quit = true;
                 this.show_dialog_on_quit_msg = 'Images are still being generated. Are you sure you want to quit?';
@@ -301,24 +224,7 @@ export default
             }
         } , 
 
-        show_about(){
-            window.ipcRenderer.sendSync('show_about', '');
-        },
-        show_help(){
-            window.ipcRenderer.sendSync('open_url', "https://diffusionbee.com");
-        } ,
-
-        open_url(url){
-            window.ipcRenderer.sendSync('open_url', url);
-        } ,
-
-        menu_item_click_discord(){
-            window.ipcRenderer.sendSync('open_url', "https://discord.gg/t6rC5RaJQn");
-        },
-
-        close_window(){
-            window.ipcRenderer.sendSync('close_window', '');
-        }
+        
     },
 
     data() {
@@ -329,13 +235,21 @@ export default
             show_dialog_on_quit_msg : "" ,  // the message to show while quiting 
             show_splash_screen : true , // is showing the loading splash screen
             logs : "",
+
             global_loader_modal_msg : "",
+            registered_ext_applets : {}, // {id, title, desc, icon, inputs, outputs }
             app_data: {history : {}},
         };
 
         return {
-            is_mounted : false,
+            current_build_number : Number(require('../package.json').build_number), 
+            all_pages_ready: false, // set to true by PagesRouter
+            is_mounted : false, // set when app is mounted
+            functions: {},
             app_state: app_state,
+            app: this , // will be set after mount
+            current_selected_tab : "Homepage",
+            current_applet_title: "Home",
             is_screen_frozen : true , 
             is_dev : require('../package.json').is_dev ||  require('../package.json').build_number.includes("dev") ,
         }
diff --git a/electron_app/src/AssetsManager.vue b/electron_app/src/AssetsManager.vue
new file mode 100644
index 00000000..a7211727
--- /dev/null
+++ b/electron_app/src/AssetsManager.vue
@@ -0,0 +1,224 @@
+<template>
+    <div>
+    </div>
+</template>
+<script>
+
+import Vue from 'vue'
+
+// import { contextBridge, ipcRenderer } from 'electron'
+
+// contextBridge.exposeInMainWorld('ipcRenderer', ipcRenderer)
+// contextBridge.exposeInMainWorld('ipcRenderer_on', ipcRenderer.on)
+
+
+function download_file(url, dest, md5_hash , onProgress, onSuccess, onError) {
+    const downloadId = Date.now().toString() + Math.random().toString().substr(2);
+    window.bind_ipc_download_on(downloadId, function(m){
+        // progresss
+        onProgress(m);
+    }, function(file_hash){
+        // sucdesss 
+        if(md5_hash == file_hash){
+            onSuccess(file_hash)
+        } else{
+            onError("failed to match checksum")
+        }
+        window.unbind_ipc_download_on(downloadId)
+        
+    }, function(m){
+        // error 
+        window.unbind_ipc_download_on(downloadId)
+        onError(m)
+    } )
+    window.ipcRenderer.send('download-file', url, dest, downloadId);
+}
+
+
+export default {
+    name: 'AssetsManager.vue',
+    props: {},
+    components: {},
+    mounted() {
+
+    },
+    data() {
+        let downloaded_assets_storage = window.ipcRenderer.sendSync('load_data' , 'downloaded_assets.json'); // get from local storage
+        let local_assets_storage = window.ipcRenderer.sendSync('load_data' , 'locally_loaded_assets.json'); // get from local storage
+
+        return {
+            downloaded_assets: downloaded_assets_storage ,
+            local_assets: local_assets_storage , 
+            downloading: {} , // id , status : done/downloading/error/not_downloaded , progress , hash, 
+            //TODO : ignore the certificate but see the signature
+        };
+    },
+
+    watch:{
+         'downloaded_assets': {
+            handler: function(new_value) {
+                window.ipcRenderer.sendSync('save_data', new_value , 'downloaded_assets.json');
+            },
+            deep: true
+        } , 
+
+         'local_assets': {
+            handler: function(new_value) {
+                window.ipcRenderer.sendSync('save_data', new_value , 'locally_loaded_assets.json');
+            },
+            deep: true
+        } , 
+
+    },
+
+    computed: {
+        all_avail_assets(){
+            return { // update the dict
+              ...this.downloaded_assets ,
+              ...this.local_assets
+            }
+        }
+    },
+
+    methods: {
+
+        add_local_asset(asset_details, cb ){
+            asset_details = JSON.parse(JSON.stringify(asset_details))
+            let that = this;
+            let asset_id = asset_details.id;
+            let asset_filename = asset_details.filename;
+
+            if(asset_details.post_process && asset_details.post_process == 'convert_sd_to_tdict' ){
+                asset_details.post_process_params = asset_details.post_process_params || {}
+                let model_name = asset_id + "_" + asset_filename
+                window.ipcRenderer.invoke('add_custom_pytorch_models', asset_details.asset_path_raw,  model_name, asset_details.post_process_params ).then((result) => {
+                    that.is_custom_model_loading = false
+                    if(result.success){
+                            
+                            asset_details.model_meta_data = asset_details.model_meta_data || {}
+                            asset_details.asset_path = result.model_path 
+
+                            asset_details.model_meta_data  = { // update the dict
+                              ...asset_details.model_meta_data ,
+                              ...result.metadata
+                            }
+
+                          Vue.set( that.local_assets , asset_id , asset_details)
+                          cb("success", asset_details)
+                    } else {
+                        cb("error" , result.error)
+                    }
+                })
+            } else {
+                 Vue.set( that.local_assets , asset_id , asset_details)
+            }
+
+
+        }, 
+
+        get_downloaded_asset_path(asset_id){
+            return (this.downloaded_assets[asset_id] || this.local_assets[asset_id] || {}).asset_path
+        },
+
+        get_downloaded_asset(asset_id){
+            return (this.downloaded_assets[asset_id] || this.local_assets[asset_id] )
+        },
+
+        delete_asset(asset_id){
+            
+            let asset_details = this.downloaded_assets[asset_id] || this.local_assets[asset_id] || this.downloading[asset_id] 
+            
+            Vue.delete(this.downloaded_assets, asset_id );
+            Vue.delete(this.downloading, asset_id );
+            Vue.delete(this.local_assets, asset_id );
+
+            window.ipcRenderer.sendSync('delete_file',  asset_details.asset_path );
+        },
+
+        download_asset(asset_details){
+            asset_details = JSON.parse(JSON.stringify(asset_details))
+            let that = this;
+            let asset_id = asset_details.id;
+            let asset_hash = asset_details.md5;
+            let asset_filename = asset_details.filename;
+
+            if(this.downloaded_assets[asset_id]){
+                return;
+            }
+            if(this.downloading[asset_id] && this.downloading[asset_id].status == 'done' ){
+                return;
+            }
+
+            // const path = require('path');
+            let dir = window.ipcRenderer.sendSync('get_assets_dir') 
+            // let dest_path = path.join(dir, asset_id + "_" + asset_filename)
+            let dest_path =  dir + "/" +  asset_id + "_" + asset_filename
+            asset_details.asset_path_raw = dest_path
+
+            let convert_to_tdict = false;
+
+            if(asset_details.post_process && asset_details.post_process == 'convert_sd_to_tdict' ){
+                convert_to_tdict = true
+            }
+
+            function on_progress(progress){
+                if(convert_to_tdict)
+                    progress = Math.round(progress*0.9)
+                console.log("downlaod progress "+ progress)
+                Vue.set( that.downloading[asset_id] , 'progress' , progress)
+            }
+
+            function on_success(){
+
+                if(convert_to_tdict){
+
+                        asset_details.post_process_params = asset_details.post_process_params || {}
+                        asset_details.post_process_params.delete_origional_always = true;
+                        let model_name = asset_id + "_" + asset_filename
+                        window.ipcRenderer.invoke('add_custom_pytorch_models', asset_details.asset_path_raw,  model_name, asset_details.post_process_params ).then((result) => {
+                            that.is_custom_model_loading = false
+                            if(result.success){
+                                // todo update the metadata 
+                                asset_details.model_meta_data = asset_details.model_meta_data || {}
+                                asset_details.asset_path = result.model_path 
+
+                                asset_details.model_meta_data  = { // update the dict
+                                  ...asset_details.model_meta_data ,
+                                  ...result.metadata
+                                }
+
+                                Vue.set( that.downloading[asset_id] , 'status' , 'done')
+                                Vue.set( that.downloaded_assets , asset_id , asset_details)
+
+                            } else {
+                                Vue.set( that.downloading[asset_id] , 'status' , 'error')
+                                Vue.set( that.downloading[asset_id] , 'error' , result.error.slice(-30)  )
+                            }
+                        })
+                } else {
+                    asset_details.asset_path = asset_details.asset_path_raw
+                    Vue.set( that.downloading[asset_id] , 'status' , 'done')
+                    Vue.set( that.downloaded_assets , asset_id , asset_details)
+                }
+
+            }
+
+            function on_error(error ){
+                Vue.set( that.downloading[asset_id] , 'status' , 'error')
+                Vue.set( that.downloading[asset_id] , 'error' , error )
+            }
+
+            Vue.set( that.downloading  , asset_id , asset_details)
+            Vue.set( that.downloading[asset_id] , 'status' , 'downloading')
+
+            download_file( asset_details.url , dest_path , asset_hash  , on_progress , on_success ,  on_error )
+
+        }
+            
+    },
+}
+</script>
+<style>
+</style>
+<style scoped>
+</style>
\ No newline at end of file
diff --git a/electron_app/src/SDManager.vue b/electron_app/src/SDManager.vue
new file mode 100644
index 00000000..376a9131
--- /dev/null
+++ b/electron_app/src/SDManager.vue
@@ -0,0 +1,302 @@
+<template>
+    <div></div>
+</template>
+<script>
+
+import Vue from 'vue'
+
+export default {
+    name: 'SDManager',
+    props: {
+        app : Object, 
+    },
+    components: {},
+    mounted() {
+
+    },
+    data() {
+        return {
+            queue : {
+                groups_todo : [],
+                current_group : undefined,
+            } , 
+            group_gallery_mapping : {} , 
+            worker_state : "idle",
+            stable_diffusion: null,
+            current_job_index : undefined , 
+            current_group_id : undefined 
+        };
+    },
+
+    computed:{
+        is_ready(){
+            return this.stable_diffusion.is_input_avail
+        },
+        is_stopping(){
+            return this.stable_diffusion.is_stopping
+        },
+    },
+
+    methods: {
+
+        // call this 
+        add_job(gen_options, raw_form_options ,gallery_component){
+            gen_options = JSON.parse(JSON.stringify(gen_options))
+            let group_options = {group_id : Math.random().toString() , jobs:[] }
+            let n = gen_options.num_imgs
+            for(let i=0 ; i < n  ; i ++ ){
+                raw_form_options = JSON.parse(JSON.stringify(raw_form_options))
+                gen_options = JSON.parse(JSON.stringify(gen_options))
+                gen_options['job_id'] = Math.random().toString();
+                gen_options['image_no'] = i 
+                gen_options['job_state'] = "todo";
+                gen_options['num_imgs'] = 1 
+
+                if((!gen_options['seed']) || gen_options['seed'] < 0 ){
+                    gen_options['seed'] = Math.floor(Math.random()*1000000)
+                }
+
+                raw_form_options['seed'] = gen_options['seed']
+                raw_form_options['small_mod_seed'] = gen_options['small_mod_seed']
+                raw_form_options['num_imgs'] = gen_options['num_imgs']
+                gen_options.raw_form_options = raw_form_options
+
+                
+                group_options.jobs.push(gen_options)
+                gen_options = JSON.parse(JSON.stringify(gen_options))
+
+                if(gen_options['small_mod_seed'])
+                    gen_options['small_mod_seed'] += 1
+                else
+                    gen_options['seed'] += 1234
+
+            }
+            this.add_job_group( group_options , gallery_component )
+
+        }, 
+
+        add_job_group(gen_options , gallery_component ){
+            gen_options = JSON.parse(JSON.stringify(gen_options))
+            console.log("adding job group ")
+            console.log(gen_options)
+            this.queue.groups_todo.push(gen_options);
+            this.group_gallery_mapping[gen_options.group_id] = gallery_component;
+            let imgs = []
+            for(let i=0 ; i <gen_options.jobs.length ; i++ ){
+                imgs.push({})
+            }
+            gallery_component.add_group({group_id: gen_options.group_id , num_imgs : gen_options.jobs.length, imgs: imgs , img_width:gen_options.jobs[0].img_width , img_height: gen_options.jobs[0].img_height})
+            gallery_component.scroll_to_top()
+            if(this.stable_diffusion.is_input_avail){
+                this.get_and_do_job()
+            }
+        },
+
+        finish_current_job(){
+            // if the whole group is finished
+            let is_group_done = true;
+
+            for(let job of this.queue.current_group.jobs  ){
+                if(job.job_state != "done")
+                    is_group_done = false
+            }
+            if(is_group_done){
+                // so that there are no empty loading items in gallry 
+                let current_group_id = this.current_group_id
+                let gallery = this.group_gallery_mapping[this.current_group_id]
+                let gallery_group = gallery.get_group( this.current_group_id )
+                let n_done = 0
+                for(let img of gallery_group.imgs){
+                    if(img.image_url)
+                        n_done += 1
+                }
+                gallery_group.num_imgs = n_done;
+                gallery_group.imgs = gallery_group.imgs.slice(0,n_done)
+
+                gallery.update_group( gallery_group  )
+
+                this.current_group_id = undefined;
+                this.queue.current_group = undefined;
+
+                 
+
+                // also update the hisroty
+                this.app.functions.add_to_history(current_group_id  , gallery_group )
+
+            }
+
+            this.current_job_index = undefined;
+
+        },
+
+        do_job(job){
+            let that = this;
+            console.log("dong job");
+            console.log(job.prompt)
+            if(!this.stable_diffusion.is_input_avail){
+                alert("ERROR, stable_diffusion not available. ")
+                return
+            }
+
+            if(!this.stable_diffusion){
+                alert("ERROR, stable_diffusion not found. ")
+                return
+            }
+
+            
+
+            let callbacks = {
+                on_img(img){
+
+                    let img_path = img.generated_img_path
+                    let aug_img_path = img.aux_output_image_path
+
+                    console.log("on img " + that.current_group_id + " " + that.current_job_index)
+                    if(that.current_group_id == undefined){
+                        console.log("whoops 1")
+                        return;
+                    }
+
+                    if(that.current_job_index == undefined){
+                        console.log("whoops 2")
+                        return
+                    }
+
+                    that.queue.current_group.jobs[that.current_job_index].generated_img = img_path ;
+                    that.queue.current_group.jobs[that.current_job_index].aux_output_img = aug_img_path ;
+                    that.queue.current_group.jobs[that.current_job_index].job_state = "done"
+                    console.log("an image done "+ that.queue.current_group.jobs[that.current_job_index].job_state )
+                    let gallery = that.group_gallery_mapping[that.current_group_id]
+                    let gallery_group = gallery.get_group( that.current_group_id )
+                    let el_to_update = gallery_group.imgs[ that.queue.current_group.jobs[that.current_job_index].image_no ]
+                    el_to_update.image_url = img_path ;
+                    el_to_update.aux_img_url = aug_img_path ;
+                    el_to_update.description = job.prompt.slice(0, 250 ) ;
+                    el_to_update.params = JSON.parse(JSON.stringify(job)) ;
+
+                    gallery.update_group( gallery_group  )
+                    that.finish_current_job()
+
+                },
+                on_progress(p ){
+                    
+                    if(that.current_group_id == undefined)
+                        return;
+
+                    if(that.current_job_index == undefined)
+                        return
+
+                    that.queue.current_group.jobs[that.current_job_index].done_percentage = p ;
+                    that.done_percentage = p;
+                    
+                    let gallery = that.group_gallery_mapping[that.current_group_id]
+                    let gallery_group = gallery.get_group( that.current_group_id )
+                    let el_to_update = gallery_group.imgs[ that.queue.current_group.jobs[that.current_job_index].image_no ]
+                    el_to_update.done_percentage = p ;
+                    gallery.update_group( gallery_group  )
+
+                },
+                on_err(err){
+                    console.log("errorrr ")
+                    that.queue.current_group.jobs[that.current_job_index].generated_img = "ERROR" ;
+                    that.queue.current_group.jobs[that.current_job_index].job_state = "done";
+                    that.backend_error = err;
+
+                    let gallery = that.group_gallery_mapping[that.current_group_id]
+                    let gallery_group = gallery.get_group( that.current_group_id )
+                    let el_to_update = gallery_group.imgs[ that.queue.current_group.jobs[that.current_job_index].image_no ]
+                    console.log("errorrr 0")
+
+                    el_to_update.image_url = "ERROR" ;
+                    el_to_update.description = err ;
+
+
+                    that.finish_current_job()
+
+                },
+            }
+
+            for(let i=0; i <  that.queue.current_group.jobs.length; i++ ){
+                if(that.queue.current_group.jobs[i].job_id == job.job_id){
+                     this.current_job_index = i ;
+                }
+            }
+            console.log("got in dex " + this.current_job_index )
+
+            this.stable_diffusion.text_to_img(job, callbacks, 'txt2img');
+
+        },
+
+        get_and_do_job(){
+            console.log("checking ")
+            if(this.queue.current_group != undefined){
+                console.log("current_group not undefined ")
+                let job_todo = undefined;
+                for(let job of this.queue.current_group.jobs){
+                    if(job.job_state == "todo" || job.job_state == "doing"){
+                        job_todo = job
+                        this.current_group_id = this.queue.current_group.group_id;
+                        break
+                    }
+                }
+
+                if(job_todo == undefined){
+                    console.log("job_todo undefined ")
+                    // all jobs of that groups are done 
+                    this.queue.current_group = undefined;
+                    return this.get_and_do_job()
+                } else {
+                    console.log("got a new job " + job_todo.job_id + " "  + job_todo.job_state + " " + job_todo.prompt )
+                    this.do_job(job_todo)
+                    return
+                }
+
+            } else if(this.queue.groups_todo.length > 0 ){
+                this.queue.current_group = this.queue.groups_todo.shift()
+                console.log("found  a new group " + this.queue.current_group.group_id)
+                return this.get_and_do_job()
+            } else {
+                console.log("i think no other jobs are there for now")
+            }
+        },
+
+
+        stop_all(){
+            if(this.queue.current_group != undefined &&    this.current_job_index != undefined){
+                console.log("jjj1")
+                for(let job of this.queue.current_group.jobs  ){
+                    job.job_state = "done"
+                }
+                console.log("jjj")
+                this.finish_current_job()
+            }
+
+            for(let group of this.queue.groups_todo){
+                let gallery = this.group_gallery_mapping[group.group_id];
+                gallery.delete_group(group.group_id)
+            }
+            Vue.set(this.queue , 'groups_todo' , [] ) 
+
+            this.stable_diffusion.interupt();
+
+        },
+    },
+
+     watch: {
+        'stable_diffusion.is_input_avail': {
+            handler: function(new_value) {
+                if(new_value == true){
+                    console.log("invoking")
+                    this.get_and_do_job()
+                    
+                }
+            },
+            deep: true
+        } , 
+    }
+}
+</script>
+<style>
+</style>
+<style scoped>
+</style>
\ No newline at end of file
diff --git a/electron_app/src/StableDiffusion.vue b/electron_app/src/StableDiffusion.vue
index feb44a6e..bc7b502f 100644
--- a/electron_app/src/StableDiffusion.vue
+++ b/electron_app/src/StableDiffusion.vue
@@ -29,6 +29,7 @@ export default {
     },
     data() {
         return {
+            is_stopping: false,
             is_backend_loaded : false,
             is_model_downloading: false, 
             is_input_avail : false,
@@ -54,57 +55,25 @@ export default {
                 this.is_model_downloading = false;
             }
             if(msg_code == "inrd"){
-                this.is_input_avail = true;
-                this.attached_cbs = undefined;
+                console.log("cps unset inrd ")
+                this.is_stopping = false
+                this.is_input_avail = true; // note : is_input_avail can be watched so set this at last pls
             }
             if(msg_code == "inwk"){
                 this.is_input_avail = false;
             }
 
-            // removing the nsfw thing as it does not run in m1 build
-            // if(msg_code == "nwim"){
-            //     let impath = msg.substring(5).trim()
-
-            //     const img = new Image();
-            //     img.src = "file://" + impath;
-
-            //     img.attached_cbs = this.attached_cbs;
-
-            //     // check for nsfw content
-            //     img.onload = () => {
-            //         if (this.$parent.app_state.app_data.settings.nsfw_filter == true) {
-            //             if (img.attached_cbs) {
-            //                 if (img.attached_cbs.on_img)
-            //                     img.attached_cbs.on_img(impath);
-            //             }
-            //         }
-            //         else {
-            //             const nsfwjs = require('nsfwjs');
-            //             nsfwjs.load()
-            //                 .then(model => model.classify(img))
-            //                 .catch(() => {
-            //                     console.log("cant run nsfw")
-            //                 })
-            //                 .then(predictions => {
-            //                     if (predictions && (predictions[0].className ==  'Hentai' || predictions[0].className ==  'Porn')) {
-            //                             impath = "nsfw_" + Math.random();
-            //                     }
-            //                     if (img.attached_cbs) {
-            //                         if (img.attached_cbs.on_img)
-            //                             img.attached_cbs.on_img(impath);
-            //                     }
-            //                 });
-            //         }
-            //     }
-            // }
             if(msg_code == "nwim"){
                 if (this.$parent.app_state.app_data.settings.notification_sound == true) {
                     notification_sound.play();
                 }
-                let impath = msg.substring(5).trim()
+                let img = msg.substring(5).trim()
+                img = JSON.parse(img)
                 if(this.attached_cbs){
                     if(this.attached_cbs.on_img)
-                        this.attached_cbs.on_img(impath);
+                        this.attached_cbs.on_img(img);
+                } else {
+                    console.log("got new img but cbs none")
                 }
             }
 
@@ -173,6 +142,8 @@ export default {
                         this.attached_cbs.on_progress(p, iter_time);
                     }
                         
+                } else {
+                    console.log("got new msg but cbs none")
                 }
 
             }
@@ -182,6 +153,8 @@ export default {
 
         interupt(){
             send_to_py("t2im __stop__")
+            console.log("cps unset st ")
+            this.is_stopping = true
             this.attached_cbs = undefined;
         },
 
@@ -191,9 +164,27 @@ export default {
             return this.is_backend_loaded
         },
 
+        run_applet(applet_name , params , callbacks ){
+
+
+            if(!this.is_input_avail)
+                return;
+            
+            this.is_stopping = false
+
+            this.generated_by = applet_name;
+            this.attached_cbs = callbacks;
+
+            this.generation_state_msg = "Running " + applet_name
+
+            send_to_py("rapp " + applet_name + " " + JSON.stringify(params)) 
+            
+        },
+
         text_to_img(prompt_params, callbacks, generated_by){
             if(!this.is_input_avail)
                 return;
+            this.is_stopping = false
             let tokens = [49406].concat((get_tokens(prompt_params.prompt))).concat([49407])
             tokens.filter(n => n != null && n != undefined)
             prompt_params.prompt_tokens = tokens;
@@ -218,6 +209,7 @@ export default {
             this.last_iter_t = Date.now()
             this.generated_by = generated_by;
             this.attached_cbs = callbacks;
+            console.log("cps set ")
             this.generation_state_msg = ""
             this.remaining_times = ""
             this.iter_times = []
diff --git a/electron_app/src/assets/css/theme.css b/electron_app/src/assets/css/theme.css
index 68e38395..4e94496c 100644
--- a/electron_app/src/assets/css/theme.css
+++ b/electron_app/src/assets/css/theme.css
@@ -10,6 +10,51 @@
     --menu-background: #eaebef;
 }
 
+
+
+@media (prefers-color-scheme: dark) {
+     :root {
+        --color-bg: #1E1E1E;
+        --sidebar-color: #323232;
+        --text-color-solid: #ffffff;
+        --thin-border-color: #1A1A1A;
+        --title-icon_color: rgba(255, 255, 255, 0.55);
+        --button-highlight-one : rgba(255,255,255,0.05);
+        --border-color-invert : rgba(255,255,255,0.15);
+        --border-color-invert-extralight : rgba(255,255,255,0.03);
+        --canvas-toolbox-bg :  #303030;
+        --options-input-bg : #303030;
+        --text-invert-color : rgba(255,255,255,0.8);
+        --input-form-el-color : #2c2c2c;
+
+     }
+}
+
+@media (prefers-color-scheme: light) {
+    :root {
+        --color-bg: #FFFFFF;
+        --sidebar-color: rgb(244, 245, 245);
+        --text-color-solid: #000000;
+        --thin-border-color: #E6E6E6;
+        --title-icon_color: rgba(0, 0, 0, 0.55);
+         --button-highlight-one : rgba(0,0,0,0.05);
+         --border-color-invert : rgba(0,0,0,0.15);
+         --border-color-invert-extralight : rgba(0,0,0,0.03);
+         --canvas-toolbox-bg : #F1F4FA;
+         --options-input-bg : #F1F4FA;
+         --text-invert-color : rgba(0,0,0,0.8);
+         --input-form-el-color : #F1F4FA;
+     }
+}
+
+
+
+body {
+    background-color: var(--color-bg);
+}
+
+
+
 @media (prefers-color-scheme: light) {
      :root {
         --slider-progress: #8cb8f2;
@@ -17,9 +62,7 @@
         --slider-circle: #3174f1;
         --slider-border: white;
     }
-    body {
-        background-color: #F2F2F2;
-    }
+    
     h1 {
         color: rgba(0, 0, 0, 0.9);
     }
@@ -53,7 +96,7 @@
         background-color: rgba(0, 0, 0, 0.06);
     }
     .tab_content_frame {
-        background-color: #F2F2F2;
+/*        background-color: #F2F2F2;*/
     }
     .animatable_content_box {
         background-color: #F2F2F2;
@@ -90,10 +133,7 @@
     .dropdown-item {
         color: rgba(0, 0, 0, 0.9);
     }
-    .title_bar {
-        background-color: var(--background);
-        border-color: #E6E6E6;
-    }
+     
     .tabs_bar {
         background-color: var(--background);
         border-color: #E6E6E6;
@@ -103,7 +143,7 @@
     }
     .loader_box {
         color: rgba(255, 255, 255, 0.9);
-        background-color: white;
+        background-color: #F1F4FA;
     }
     .logo_splash_screen {
         content: url("..//logo_splash.png")
@@ -150,9 +190,7 @@
         --slider-circle: #07296d;
         --slider-border: #222222;
     }
-    body {
-        background-color: #303030;
-    }
+   
     h1 {
         color: rgba(255, 255, 255, 0.9);
     }
@@ -178,7 +216,7 @@
         background-color: rgba(255, 255, 255, 0.08);
     }
     .tab_content_frame {
-        background-color: #303030;
+/*        background-color: #303030;*/
     }
     .animatable_content_box {
         background-color: #1c1c1c;
@@ -236,16 +274,11 @@
     .app_title span {
         color: rgba(255, 255, 255, 0.9);
     }
-    .title_bar {
-        border-color: var(--border-dark);
-        background-color: #302e2f;
-    }
+     
     .tabs_bar {
         border-color: var(--border-dark);
     }
-    #app {
-        background-color: var(--background-dark);
-    }
+    
     .text_bg {
         background-color: rgba(255, 255, 255, 0.1);
     }
diff --git a/electron_app/src/assets/imgs/blank_illus4.png b/electron_app/src/assets/imgs/blank_illus4.png
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diff --git a/electron_app/src/assets/imgs/page_icon_imgs/models.png b/electron_app/src/assets/imgs/page_icon_imgs/models.png
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diff --git a/electron_app/src/assets/imgs/page_icon_imgs/models0.png b/electron_app/src/assets/imgs/page_icon_imgs/models0.png
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diff --git a/electron_app/src/assets/imgs/page_icon_imgs/upscale.png b/electron_app/src/assets/imgs/page_icon_imgs/upscale.png
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diff --git a/electron_app/src/background.js b/electron_app/src/background.js
index c4ce0856..e2f6e174 100644
--- a/electron_app/src/background.js
+++ b/electron_app/src/background.js
@@ -57,7 +57,7 @@ async function createWindow() {
 		titleBarStyle : (is_windows ) ? 'default' : 'hidden' , 
 		titleBarOverlay : is_windows, 
 		maximizable : false,
-		trafficLightPosition: { x: 10, y: 10 },
+		trafficLightPosition: { x: 18, y: 20 },
 		webPreferences: {
 			webSecurity: false,
 
@@ -74,8 +74,9 @@ async function createWindow() {
 
 	electronLocalshortcut.register(win, ['CommandOrControl+R','CommandOrControl+Shift+R', 'F5'], () => {}) //  make the refresh shortcuts blank
 
+	
 	win.setSize(770, 550);
-	win.setResizable(false);
+	// win.setResizable(false);
 	win.setMaximizable(false);
 
 	// save the window state on resize , move, etc 
@@ -105,8 +106,12 @@ async function createWindow() {
 
 
 
-
-	nativeTheme.themeSource = 'system';
+	if(is_windows){
+		nativeTheme.themeSource = 'light';
+	} else {
+		nativeTheme.themeSource = 'system';
+	}
+	
 
 	if (process.env.WEBPACK_DEV_SERVER_URL) {
 		// Load the url of the dev server if in development mode
@@ -159,7 +164,7 @@ app.setAboutPanelOptions({
 	applicationVersion: require('../package.json').version,
 	version: require('../package.json').build_number,
 	credits: require('../package.json').description,
-	copyright: "Copyright © 2022 " + require('../package.json').name,
+	copyright: "Copyright © 2023 " + require('../package.json').name,
 	website: require('../package.json').website
 });
 
diff --git a/electron_app/src/bridge.js b/electron_app/src/bridge.js
index f39a2bbc..0976c4d4 100644
--- a/electron_app/src/bridge.js
+++ b/electron_app/src/bridge.js
@@ -10,6 +10,7 @@ var last_few_err = ""
 
 let RESTART_BACKEND_ON_CLOSE = false
 
+const path = require('path');
 
 function start_bridge() {
 
@@ -22,7 +23,7 @@ function start_bridge() {
         python = require('child_process').spawn( bin_path );
     }
     else if (fs.existsSync(script_path)) {
-        python = require('child_process').spawn('python3', [script_path]);
+        python = require('child_process').spawn('python', [script_path]);
     }
     else{
         const path = require('path');
diff --git a/electron_app/src/components/AppletPage.vue b/electron_app/src/components/AppletPage.vue
new file mode 100644
index 00000000..d8d3c590
--- /dev/null
+++ b/electron_app/src/components/AppletPage.vue
@@ -0,0 +1,128 @@
+<template>
+    <BasicSDApplet
+        :app=app 
+        :input_form=input_form
+        :sd_options=input_form_options
+        :name="'applet_' + applet_id "
+        :required_assets="[]"
+        ref="basic_sd_applet"
+    >
+        
+
+        <template v-slot:input_buttons>
+            
+            <div class="l_button button_medium"   style="float:right" v-if="is_mounted && !(stable_diffusion.is_input_avail) && stable_diffusion.generated_by==applet_id " > 
+                Running 
+                <MoonLoader   class="moonloader1" color="#3E7BFA" size="25px" style="zoom:0.6; float:right; margin-left: 15px;"></MoonLoader>
+            </div>
+            <div v-else @click="start" class="l_button button_colored button_medium" style="float:right">Start</div>
+
+
+            <span v-if="is_stop_avail && is_mounted &&  stable_diffusion.generated_by==applet_id && !stable_diffusion.is_input_avail "   >
+                <div v-if="is_stopping" class="l_button button_medium button_colored" style="float:right; float:right ;  " >Stopping ...</div>
+                <div v-else class="l_button button_medium button_colored" style="float:right; float:right ;  " @click="stop_all">Stop</div>
+            </span>
+
+
+
+            
+
+        </template>
+
+        <template v-slot:output_workpace>
+
+            <div v-if="backend_error" style="padding: 20px"> 
+                 <p style="color:red"> Error : {{ backend_error  }} </p>
+            </div>
+            
+            <div v-if="!backend_error" style="padding: 20px"> 
+                <Form ref="output_form"  :form_data="output_form"  :form_values="out_vals" :form_save_key="'out'+applet_id"  ></Form>
+                
+            </div>
+             
+        </template>
+
+    </BasicSDApplet>
+</template>
+<script>
+
+import BasicSDApplet from "../components/BasicSDApplet.vue"
+import Form from "../components_bare/Form.vue"
+import MoonLoader from 'vue-spinner/src/MoonLoader.vue'
+
+export default {
+    name: 'AppletPage',
+    props: {
+        app:Object,
+        input_form : Array,
+        applet_id: String, 
+        output_form:Array,
+        is_stop_avail:Boolean
+
+    },
+    components: { BasicSDApplet, Form , MoonLoader},
+    mounted() {
+        this.stable_diffusion = this.app.stable_diffusion
+        this.is_mounted = true
+    },
+    data() {
+        return {
+            is_mounted: false,
+            input_form_options: {}, 
+            out_vals : {},
+            backend_error : "",
+            is_stopping: true
+        };
+    },
+    methods: {
+        start(){
+            if(!this.is_mounted)
+                return;
+            
+            if(!(this.stable_diffusion.is_input_avail)){
+                this.app.show_toast("Currently some images are being generated. Please wait for them to finish or stop them.")
+                return;
+            }
+
+            if(!this.$refs.basic_sd_applet.check_input_form_n_show_error()){
+                return
+            }
+
+            this.is_stopping = false
+
+            let options =  this.$refs.basic_sd_applet.get_sd_form_outputs()
+
+            let that = this
+
+            let callbacks = {
+                on_img(){
+                },
+                on_progress(){                    
+                },
+                on_err(err){
+                    that.app.show_toast("Error : " + err)
+                    that.backend_error = err;
+                },
+            }
+
+            this.backend_error = ""
+
+            this.stable_diffusion.run_applet( this.applet_id ,options , callbacks );
+                
+        } , 
+        stop_all(){
+            if(!this.is_mounted)
+                return;
+            this.is_stopping = true;
+            this.stable_diffusion.interupt();
+            
+        }
+    },
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components/BasicSDApplet.vue b/electron_app/src/components/BasicSDApplet.vue
new file mode 100644
index 00000000..2f492361
--- /dev/null
+++ b/electron_app/src/components/BasicSDApplet.vue
@@ -0,0 +1,313 @@
+<template>
+    <TwoColAppletLayout>
+        
+        <template v-slot:input_workspace>
+              <slot name="input_workspace_pre_form"></slot>
+              <Form ref="form"  :form_data="input_form_elements_processed"  :form_values="sd_options" :form_save_key="'1fdaedjdfddeef1'+name" :tags="all_tags" ></Form>
+              <div @click="$refs.form.reset_to_default()" class="l_button" style="margin-left:-10px"> Reset to default </div>
+              <slot name="input_workspace_post_form"></slot>
+        </template>
+
+        <template v-slot:input_buttons>
+            <slot name="input_buttons"></slot>
+        </template>
+
+        <template v-slot:output_workpace>
+            <div class="model_dialog_container" v-if="to_download_left.length > 0 ">
+                
+            </div>
+            <div class="model_dialog" v-if="to_download_left.length > 0 ">
+                <h2> You need to download the following models to generate: </h2>
+                <br>
+                <p>{{to_download_left[0].title}}</p> <DownloadButton :app=app  :asset_details="to_download_left[0]"> </DownloadButton>
+            </div>
+
+            <slot name="output_workpace"></slot>
+        </template>
+
+    </TwoColAppletLayout>
+</template>
+<script>
+
+import Form from "../components_bare/Form.vue"
+import TwoColAppletLayout from "../components_bare/TwoColAppletLayout.vue"
+import DownloadButton from "./DownloadButton.vue"
+import Vue from 'vue'
+import {find_in_form_recursive} from "../utils.js"
+
+function prep_sd_options(options){
+    options = JSON.parse(JSON.stringify(options))
+
+
+    if(options.seed)
+        options.seed = Number(options.seed);
+    else if(options.seed != undefined)
+        options.seed = Math.floor(Math.random() * 100000);
+
+    if(options.seed < 0){
+        options.seed = Math.floor(Math.random() * 100000);
+    }
+
+    return options
+}
+
+
+
+export default {
+    name: 'BasicSDApplet',
+    props: {
+        app:Object, 
+        input_form : Array,
+        sd_options: Object,
+        name:String,
+        form_tags: Array,
+        required_assets : Array, 
+        model_options_types : Array, // what kind of models should it show in teh dropdown ( sd, sd_inpaint etc )
+    },
+    components: {Form  , TwoColAppletLayout, DownloadButton },
+    mounted() {
+
+    },
+    data() {
+        return {
+            input_form_options: {}
+        };
+    },
+    methods: {
+        
+        // given an options dict, load those values inthe form
+        load_options(options){
+            console.log("load")
+            console.log(options)
+            let raw_options = options; // the unprocessed form ouptuts
+            if(options.raw_form_options){
+                raw_options = options.raw_form_options
+            }
+
+            for(let k of Object.keys(options)){
+                if(raw_options[k] != undefined){
+                    console.log("setting " + k )
+                    Vue.set(this.sd_options, k ,  raw_options[k])
+                }
+                    
+            }
+        } , 
+
+        request_ojects_from_img_element(object_name , object ){
+            console.log(object_name)
+            if(object_name == "get_mask_img_b64"){
+                this.get_mask_img_b64 = object
+            }
+
+            if(object_name == "get_mask_b64"){
+                this.get_mask_b64 = object
+            }
+            
+       },
+
+        get_sd_form_outputs(){
+            let options = this.$refs.form.post_processed_form_outputs()
+            options = prep_sd_options(options)
+
+            options.applet_name = this.name
+
+            // map the selected avail model to the tdict
+            if(options.selected_sd_model){
+                options.model_tdict_path = this.app.assets_manager.get_downloaded_asset_path(options.selected_sd_model)
+
+                let asset = this.app.assets_manager.get_downloaded_asset(options.selected_sd_model)
+                let asset_metadata = (asset||{}).model_meta_data
+                if(asset_metadata && asset_metadata.do_v_prediction){
+                    options.do_v_prediction = true 
+                }
+
+                if(asset_metadata && asset_metadata.trigger_word && options.prompt && !(options.prompt.includes(asset_metadata.trigger_word)) ){
+                    options.prompt = asset_metadata.trigger_word + " " + options.prompt
+                }
+            }
+
+            // if possible get the input image masks and stuff
+            if(options.input_img){
+                if(this.get_mask_b64){
+                    let mask_b64 = this.get_mask_b64()
+                    if(mask_b64){
+                        options.mask_image = (window.ipcRenderer.sendSync('save_b64_image',  mask_b64 , true ))
+                    }
+                }
+                if(this.get_mask_img_b64){
+                    let mask_img_b64 = this.get_mask_img_b64()
+                    if(mask_img_b64){
+                        options.input_image_with_mask =  (window.ipcRenderer.sendSync('save_b64_image',  mask_img_b64  ))
+                    }
+                }
+            }
+
+            return options
+        } , 
+
+        check_input_form_n_show_error(){
+            if(this.to_download_left.length > 0){
+                this.app.show_toast("First you need to download the model to generate")
+                return false;
+            } 
+
+            if( this.get_sd_form_outputs().prompt != undefined && this.get_sd_form_outputs().prompt.trim() == ""){
+                console.log(this.get_sd_form_outputs())
+                this.app.show_toast('You need to enter a prompt')
+                return false;
+            }
+
+            if(this.sd_options.selected_sd_model){
+                if(!(this.app.assets_manager.get_downloaded_asset_path(this.sd_options.selected_sd_model))){
+                    this.app.show_toast("Model not found. Please select a valid model.")
+                    return false                    
+                }
+            }
+
+            return true;
+        },
+
+    },
+    computed : {
+        all_tags(){
+            console.log("sddd options ")
+            console.log(this.sd_options)
+            let l = (this.form_tags || []).concat( this.sd_options.is_adv_mode ? ['advanced']:[]  )
+            return l
+        } , 
+
+        input_form_elements_processed(){
+            let form = JSON.parse(JSON.stringify(this.input_form))
+            
+
+            // add the avail models to the form
+            let el = find_in_form_recursive( "selected_sd_model" , form)
+            if(el){
+                let assets = Object.values(this.app.assets_manager.all_avail_assets)
+                assets = assets.filter(x => x.model_meta_data && (this.model_options_types ||["sd_model"]).includes(x.model_meta_data.type))
+                let new_ids = assets.map(x => x.id)
+                for( let idd of new_ids){
+                    if(!el['options'].includes(idd))
+                        el['options'].push(idd)
+                }
+            }
+
+            // get the functions to get the mask and stuff
+            el =  find_in_form_recursive( "input_img" , form)
+            if(el && el.draw_mask && el.store_masked_image){
+                el.request_objects_from_element = "yes"
+                el.request_objects_from_element_fn = this.request_ojects_from_img_element
+            }
+
+            // for SDXL make sure that we only allow certain schedulers ( disabled for now )
+            // if(this.sd_options && this.sd_options.selected_sd_model){
+            //     let selected_asset =  this.app.assets_manager.all_avail_assets[this.sd_options.selected_sd_model  ]
+            //     if(selected_asset &&  selected_asset.model_meta_data && selected_asset.model_meta_data.sd_type && selected_asset.model_meta_data.sd_type == "sdxl_base"  ){
+            //         let el2 = find_in_form_recursive( "scheduler" , form)
+            //         if(el2){
+            //             el2['default_value'] = "karras"
+            //             el2['options'].splice(0, el2['options'].length);
+            //             el2['options'].push("karras")
+                        
+            //         }
+            //     } 
+            // }
+
+            // for sdxl make use different image sizes
+            if(this.sd_options && this.sd_options.selected_sd_model){
+                let selected_asset =  this.app.assets_manager.all_avail_assets[this.sd_options.selected_sd_model  ]
+                if(selected_asset &&  selected_asset.model_meta_data && selected_asset.model_meta_data.sd_type && selected_asset.model_meta_data.sd_type == "sdxl_base"  ){
+                    let el2 = find_in_form_recursive( "img_width" , form)
+                    if(el2){
+                        el2['default_value'] = 768
+                        el2['options'].splice(0, el2['options'].length);
+                        el2['options'].push(  576, 640, 704, 768, 832, 896 , 960 , 1024, 1088  , 1152 , 1216  )
+                        
+                    }
+
+                    let el3 = find_in_form_recursive( "img_height" , form)
+                    if(el3){
+                        el3['default_value'] = 768
+                        el3['options'].splice(0, el3['options'].length);
+                        el3['options'].push(   576, 640, 704, 768, 832, 896 , 960 , 1024, 1088  , 1152 , 1216  )
+                        
+                    }
+
+                    // Vue.set(this.sd_options , 'img_width',768  )
+                    // Vue.set(this.sd_options , 'img_height',768  )
+
+                } 
+            }
+
+
+
+            return form;
+        },
+
+        required_assets_modified(){
+            let ret = []
+            if(!this.required_assets){
+                ret = []
+            } else {
+                ret = JSON.parse(JSON.stringify(this.required_assets))
+            }
+
+            if(  this.sd_options.selected_sd_model == "Default_SD1.5"){
+                ret.push( { 
+                    id : 'Default_SD1.5' , 
+                    filename: 'sd-v1-5_fp16.tdict' ,   
+                    md5: 'a36c79b8edb4b21b75e50d5834d1f4ae' , 
+                    is_stock_model : true,
+                    url : 'https://huggingface.co/divamgupta/stable_diffusion_mps/resolve/main/sd-v1-5_fp16.tdict' , 
+                    title: "Stable Diffusion 1.5 (Default)", 
+                    model_meta_data : {"type" : "sd_model", "float_type" : "float16" ,  "sd_type" : "SD_1x" }
+                } )
+            }
+            
+            return ret
+        },
+
+        to_download_left(){
+            let to_download = []
+           
+            for(let asset of this.required_assets_modified){
+                let asset_id = asset.id
+                if(!(this.app.is_mounted && this.app.assets_manager.downloaded_assets[asset_id] && this.app.assets_manager.downloaded_assets[asset_id].status == 'done')){
+                    to_download.push(asset)
+                }
+            }
+            return to_download
+        }
+    }
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+
+.model_dialog_container{
+    position: fixed;
+    left: calc(    var(--sidebar-width )  + 360px );
+    right:0 ;
+    bottom:0;
+    background-color: rgba(0,0,0,0.3);
+/*    height: 100%;*/
+    z-index: 900;
+    top: var(--titlebar-height);
+}
+
+.model_dialog{
+    position: fixed;
+    width: 250px ;
+    height:170px;
+    background: var(--options-input-bg );
+    left: calc( 50% +  var(--sidebar-width ) /2 + 175px );
+    top:50%;
+     transform: translateY(-50%) translateX(-50%);
+    z-index: 1000;
+    padding:20px;
+}
+
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components/ControlNet.vue b/electron_app/src/components/ControlNet.vue
deleted file mode 100644
index dac13b28..00000000
--- a/electron_app/src/components/ControlNet.vue
+++ /dev/null
@@ -1,319 +0,0 @@
-@import '../assets/css/theme.css';
-
-<template>
-     <div  class="animatable_content_box ">
-        <div class="left_half">
-            <!-- <p>Input Image:</p>
-            <img class="gal_img" style="width: 90%;" src="https://colormadehappy.com/wp-content/uploads/2022/02/How-to-draw-a-cute-dog-6.jpg"/> 
-         -->
-
-            <div v-if="inp_img" @drop.prevent="onDragFile" @dragover.prevent class="image_area" :class="{ crosshair_cur  : is_inpaint }"  style="height: calc(100% - 200px);  border-radius: 16px; padding:5px;">
-                <ImageCanvas ref="inp_img_canvas" :is_inpaint="is_inpaint" :image_source="inp_img"  :is_disabled="!stable_diffusion.is_input_avail" canvas_id="ctrlnet" canvas_d_id="ctrlnetd" ></ImageCanvas>
-            </div>
-                <div v-else @drop.prevent="onDragFile" @dragover.prevent @click="open_input_image" class="image_area" :class="{ pointer_cursor  : is_sd_active }" style="height: calc(100% - 200px);  border-radius: 16px; padding:5px;">
-                    <center>
-                    <p style="margin-top: calc( 50vh - 180px); opacity: 70%;" >Click to add input image</p>
-                </center>
-            </div>
-
-            <div v-if="inp_img && stable_diffusion.is_input_avail" class="l_button" @click="open_input_image" >Change Image</div>
-            <div v-if="inp_img && stable_diffusion.is_input_avail" class="l_button" @click="inp_img =''">Clear</div>
-          
-
-            <br> <br> 
-            <textarea 
-                    v-model="prompt" 
-                    placeholder="Enter your prompt here" 
-                    style="border-radius: 12px 12px 12px 12px; width: calc(100%); resize: none; " 
-                    class="form-control"  
-                    v-bind:class="{ 'disabled' : !stable_diffusion.is_input_avail}"
-                    :rows="is_negative_prompt_avail ? 2:3"></textarea>
-            <textarea 
-                    v-if="is_negative_prompt_avail"
-                    v-model="negative_prompt" 
-                    placeholder="Enter your negative prompt here" 
-                    style="border-radius: 12px 12px 12px 12px; width: calc(100%); resize: none; margin-top: 5px; " 
-                    class="form-control negative_prompt_tb"  
-                    v-bind:class="{ 'disabled' : !stable_diffusion.is_input_avail}"
-                    :rows="1"></textarea>
-
-            <div v-if="stable_diffusion.is_input_avail" class="content_toolbox" style="margin-top:10px; margin-bottom:-10px;">
-                <div class="l_button button_medium button_colored" style="float:right ; " @click="generate_img2img" >Generate</div>
-                <SDOptionsDropdown :options_model_values="this_object" :elements_hidden="['img_h' , 'img_w' ]" :elements_extra="['controlnet']"  > </SDOptionsDropdown>
-            </div>
-            <div v-else-if="stable_diffusion.generated_by=='controlnet'"  class="content_toolbox" style="margin-top:10px; margin-bottom:-10px;">
-                <div v-if="is_stopping" class="l_button button_medium button_colored" style="float:right" @click="stop_generation">Stopping ...</div>
-                <div v-else class="l_button button_medium button_colored" style="float:right" @click="stop_generation">Stop</div>
-            </div>
-            <br><br>
-            <p style="opacity:0.5; zoom:0.8"> Please describe the complete image which you want to see as the output. </p>
-        
-        </div>
-
-        <div  class="right_half">
-
-        
-            <div v-if="generated_images.length > 0 " >
-
-                <br> <br>
-                <div   v-for="img in generated_images" :key="img" >
-                    <center>
-                        
-                        <ImageItem :app_state="app_state" :path="img" :style_obj="{ 'width': '75%' }"></ImageItem>
-
-                    </center>
-                    <br>
-                </div>
-                
-            </div>
-
-            <div v-if="backend_error" style="color:red ; margin-top:50px;">
-                <div class="center loader_box">
-                    <p>Error: {{backend_error}} </p>
-                </div>
-            </div>
-
-            <div v-if="!stable_diffusion.is_input_avail && stable_diffusion.generated_by=='controlnet'">
-                <LoaderModal :loading_percentage="done_percentage" loading_title="Generating" :loading_desc="stable_diffusion.generation_state_msg" :remaining_times="stable_diffusion.remaining_times"></LoaderModal>
-            </div>
-            
-
-        </div>
-
-
-     </div>
-</template>
-<script>
-import ImageItem from '../components/ImageItem.vue'
-import ImageCanvas from '../components_bare/ImageCanvas.vue'
-
-import LoaderModal from '../components_bare/LoaderModal.vue'
-import Vue from 'vue'
-import SDOptionsDropdown from '../components_bare/SDOptionsDropdown.vue'
-
-export default {
-    name: 'ControlNet',
-    props: {
-        app_state : Object   , 
-        stable_diffusion : Object,
-    },
-    components: { LoaderModal, ImageItem, ImageCanvas, SDOptionsDropdown },
-    mounted() {
-
-    },
-    computed:{
-        is_sd_active(){
-            return this.stable_diffusion.is_input_avail;
-        },
-        this_object(){
-            return this;
-        }
-    },
-    watch: {
-        'inp_img': {
-            handler: function() {
-                this.is_inpaint = false;
-            },
-            deep: true
-        } , 
-    },
-    data() {
-        return {
-            prompt : '',
-            inp_img : '',
-            num_imgs:1,
-            dif_steps: 25,
-            batch_size:1 ,
-            seed: '',
-            generated_images : [],
-            backend_error : "",
-            done_percentage : -1,
-            is_stopping : false,
-            inp_img_strength : 0.3 , 
-            img_h : 512 , 
-            img_w : 512 , 
-            is_inpaint : false,
-            guidence_scale : 7.5 , 
-
-            is_negative_prompt_avail : false, 
-            negative_prompt : "",
-            selected_model : 'Default', 
-            selected_control: "Body Pose",
-            do_controlnet_preprocess: "Yes",
-        };
-    },
-    methods: {
-
-        generate_img2img(){
-
-            let seed = 0;
-            if(this.seed)
-                seed = Number(this.seed);
-            else
-                seed = Math.floor(Math.random() * 100000);
-
-            if(this.prompt.trim() == ""){
-                Vue.$toast.default('You need to enter a prompt')
-                return;
-            }
-                
-
-            if(!this.inp_img){
-                Vue.$toast.default('You need to add an input image')
-                return;
-            }
-                
-
-            let input_image = window.ipcRenderer.sendSync('save_b64_image',  this.$refs.inp_img_canvas.get_img_b64()  );
-            let input_image_with_mask;
-            let mask_img;
-            if(this.is_inpaint)
-            { 
-                input_image_with_mask = window.ipcRenderer.sendSync('save_b64_image',  this.$refs.inp_img_canvas.get_img_mask_bg4() );
-                mask_img = window.ipcRenderer.sendSync('save_b64_image',  this.$refs.inp_img_canvas.get_mask_b46() , true );
-            } else {
-                input_image_with_mask = input_image;
-                mask_img = undefined;
-            }
-            
-            let control_names = {"Body Pose" : "body_pose" , "Depth" : "depth" , "Scribble": "scribble"}
-
-            let params = {
-                prompt : this.prompt , 
-                W : -1 , 
-                H : -1, 
-                seed :seed,
-                scale : this.guidence_scale , 
-                ddim_steps : this.dif_steps, 
-                num_imgs : this.num_imgs , 
-                batch_size : this.batch_size , 
-                img_strength : this.inp_img_strength,
-                input_image : input_image,
-                is_inpaint : this.is_inpaint , 
-
-                control_name: control_names[this.selected_control],
-                do_controlnet: true, 
-                do_controlnet_preprocess: (this.do_controlnet_preprocess == "Yes"),                
-            }
-
-            if(this.selected_model && this.selected_model != "Default" && this.app_state.app_data.custom_models[this.selected_model] ){
-                params.model_id = -1;
-                params.custom_model_path =  this.app_state.app_data.custom_models[this.selected_model].path;
-            }
-
-
-            if(this.is_inpaint)
-                params['mask_image'] = mask_img;
-
-            if(this.is_negative_prompt_avail)
-                params['negative_prompt'] = this.negative_prompt;
-
-            let that = this;
-            this.backend_error = "";
-            Vue.set(this,'generated_images' ,[]);
-            this.done_percentage = -1;
-
-            let history_key = Math.random();
-
-            let callbacks = {
-                on_img(img_path){
-                    that.generated_images.push(img_path);
-
-                    let p = {
-                            "prompt":that.prompt , "seed": seed, "key":history_key , "imgs" : [] , "inp_img": input_image_with_mask,
-                            "dif_steps" : that.dif_steps , "inp_img_strength" : that.inp_img_strength, "model_version": that.stable_diffusion.model_version , "guidence_scale" : that.guidence_scale, "controlnet" : that.selected_control , "controlnet_preprocess" : that.do_controlnet_preprocess , 
-                        }
-                    if(that.stable_diffusion.model_version)
-                        p['model_version'] = that.stable_diffusion.model_version;
-                    if(that.is_negative_prompt_avail)
-                        p['negative_prompt'] = that.negative_prompt;
-
-                    if(!(that.app_state.app_data.history[history_key]))
-                        Vue.set(that.app_state.app_data.history, history_key , p );
-                    
-                    that.app_state.app_data.history[history_key].imgs.push(img_path)
-
-                    console.log(that.app_state.app_data.history)
-
-                },
-                on_progress(p){
-                    that.done_percentage = p;
-                    
-                },
-                on_err(err){
-                    that.backend_error = err;
-                },
-            }
-
-            this.is_stopping = false;
-
-
-           if(this.stable_diffusion)
-                this.stable_diffusion.text_to_img(params, callbacks, 'controlnet');
-        } , 
-
-        open_input_image(){
-            if( !this.stable_diffusion.is_input_avail)
-                return;
-            let img_path = window.ipcRenderer.sendSync('file_dialog',  'img_file' );
-            if(img_path && img_path != 'NULL'){
-                this.inp_img = img_path;
-                this.is_inpaint = false;
-            }      
-        },
-        onDragFile(e){
-            if( !this.stable_diffusion.is_input_avail)
-                return;
-            if(!e.dataTransfer.files[0].type.startsWith('image/'))
-                return;
-            let img_path = e.dataTransfer.files[0].path;
-            if(img_path && img_path != 'NULL'){
-                this.inp_img = img_path;
-                this.is_inpaint = false;
-            }      
-        },
-
-        stop_generation(){
-            this.is_stopping = true;
-            this.stable_diffusion.interupt();
-        },
-    },
-}
-</script>
-<style>
-    .left_half{
-        position: absolute;
-        top :2px;
-        bottom: 3px;
-        left : 2px ;
-        padding: 20px;
-        width: calc(100vw / 2 - 10px);
-        border-right: 1px solid ;
-        border-color: rgba(0,0,0,0.1);
-    }
-
-    @media (prefers-color-scheme: dark) {
-        .left_half{
-            border-color: #606060;
-        }
-    }
-
-    .right_half{
-        position: absolute;
-        top :2px;
-        bottom: 3px;
-        right : 3px ;
-        padding: 20px;
-        width: calc(100vw / 2 - 10px);
-        overflow-y: auto;
-    }
-
-    .pointer_cursor{
-        cursor: pointer;
-    }
-</style>
-<style scoped>
-    .crosshair_cur{
-        cursor: crosshair;
-    }
-</style>
\ No newline at end of file
diff --git a/electron_app/src/components/DownloadButton.vue b/electron_app/src/components/DownloadButton.vue
new file mode 100644
index 00000000..531bfae6
--- /dev/null
+++ b/electron_app/src/components/DownloadButton.vue
@@ -0,0 +1,71 @@
+<template>
+    <div>
+        <div v-if="is_downloaded" >
+             <!-- <p>Downloaded </p> -->
+             <div @click="deletee" class="l_button button_colored">Delete</div>
+
+        </div>
+
+        <div v-else-if="is_downloading" class="l_button">
+             <b-progress :value="app.assets_manager.downloading[asset_details.id].progress" style="height: 10px; width:200px"></b-progress>
+             {{app.assets_manager.downloading[asset_details.id].progress || 0  }}%
+        </div>
+
+        <div v-else-if="is_error"  >
+            <p style="color:red; margin-bottom:5px">  Error : {{app.assets_manager.downloading[asset_details.id].error}} </p>
+            <div @click="downloadd" class="l_button button_colored">Download Again</div>
+        </div>
+
+
+        <div v-else class="l_button button_colored" @click="downloadd">Download</div>
+        
+    </div>
+</template>
+<script>
+export default {
+    name: 'Downloadutton',
+    props: { app:Object , asset_details:Object },
+    components: {},
+    mounted() {
+
+    },
+    data() {
+        return {};
+    },
+    methods: {
+        downloadd(){
+            this.app.assets_manager.download_asset(this.asset_details)
+        }, 
+        deletee(){
+            this.app.assets_manager.delete_asset(this.asset_details.id)
+        }
+    },
+
+    computed: {
+        is_downloaded(){
+            let asset_id = this.asset_details.id
+
+            if(this.asset_details.is_locally_imported)
+                return true;
+
+            if(this.app.is_mounted && this.app.assets_manager.downloaded_assets[asset_id] && this.app.assets_manager.downloaded_assets[asset_id].status == 'done'){
+                return true
+            } else {
+                return false
+            }
+        } , 
+        is_downloading(){
+            let asset_id = this.asset_details.id
+            return (this.app.is_mounted && this.app.assets_manager.downloading[asset_id]&& this.app.assets_manager.downloading[asset_id].status == 'downloading')
+        } , 
+        is_error(){
+            let asset_id = this.asset_details.id
+            return (this.app.is_mounted && this.app.assets_manager.downloading[asset_id]&& this.app.assets_manager.downloading[asset_id].status == 'error')
+        }
+    }
+}
+</script>
+<style>
+</style>
+<style scoped>
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components/GenerationGallery.vue b/electron_app/src/components/GenerationGallery.vue
new file mode 100644
index 00000000..37e46b47
--- /dev/null
+++ b/electron_app/src/components/GenerationGallery.vue
@@ -0,0 +1,158 @@
+<template>
+    <div class="generation_gallery_div" :id="div_id">
+
+        <div v-if="groups_with_non_zero_imgs.length == 0 " style="width:30% ; height: 30% ; margin-left:35%; top:50% ; transform: translateY(50%);">
+            <!-- <img src="../assets/imgs/blank_illus4_dark.png" style="opacity:0.3; width: 100%; height: 100%;  object-fit: contain;">  -->
+
+            <picture >
+                <source srcset="../assets/imgs/blank_illus4_dark.png" media="(prefers-color-scheme: dark)">
+                <img  style="opacity:0.3; width: 100%; height: 100%;  object-fit: contain;" src="../assets/imgs/blank_illus4.png">
+            </picture>
+
+            <center style="opacity: 0.5">
+                <h2 style="margin-top: 20px;"> No images to display </h2>
+                <p > Enter a prompt to generate images using AI.</p>
+            </center>
+            
+        </div>
+
+
+        <GalleryPane v-else v-for="group in groups_with_non_zero_imgs"  :key="group.group_id" :n_imgs="group.num_imgs" :img_w="group.img_width" :img_h="group.img_height" :image_data="group.imgs" :menu_items="menu_items" :on_menu_item_click="on_image_menu_item_click" :on_image_click="on_image_click"> </GalleryPane>
+    </div>
+</template>
+<script>
+
+import GalleryPane from "../components_bare/GalleryPane.vue"
+import Vue from 'vue'
+import {image_manu_functions} from "./image_menu_functions.js"
+import {open_popup} from "../utils"
+
+export default {
+    name: 'GenerationGallery',
+    props: {
+        app: Object,
+        n_to_keep: Number,
+        menu_items_skip: Array,
+    },
+    components: {GalleryPane},
+    mounted() {
+
+    },
+    data() {
+
+        let menu_items = []
+        for(let fn of Object.keys(image_manu_functions)){
+            if( !((this.menu_items_skip || []).includes(fn)))
+                menu_items.push({id: fn , text: image_manu_functions[fn].text })
+        }
+
+        return {
+            groups : [],
+            menu_items :menu_items,
+            div_id: Math.random().toString(),
+        };
+    },
+    computed: {
+        groups_with_non_zero_imgs(){
+            let ret = []
+            for(let group of this.groups){
+                if(group.num_imgs > 0 )
+                    ret.push(group)
+            }
+            return ret;
+        }
+    },
+    methods: {
+
+        scroll_to_top(){
+            document.getElementById(this.div_id).parentNode.scrollTo({ top: 0, behavior: 'smooth' });
+        },
+
+        on_image_menu_item_click(menu_item_id , image_item_data){
+            image_manu_functions[menu_item_id](this.app , image_item_data )
+        },
+
+        on_image_click(image_item_data){
+            open_popup('file://' + image_item_data.image_url)
+        },
+
+        add_group(group){
+            this.groups.unshift(group);
+
+            this.clear_old_groups( this.n_to_keep || 10)
+
+        }, 
+
+        clear_old_groups(n_to_keep){
+
+            n_to_keep = n_to_keep||0
+
+            let idx_to_rm = []
+            let n_finish = 0
+
+            // delete groups beyond last 10 finished and the ones with zero imgs 
+            for(let i = 0 ; i < this.groups.length ; i++){
+                let group = this.groups[i]
+                let is_group_finished = true 
+                
+                for(let im of group.imgs){
+                    if(!im.image_url){
+                        is_group_finished = false
+                    }
+                }
+
+                if(is_group_finished && group.imgs.length > 0 ){
+                    n_finish += 1
+                }
+
+                if(group.imgs.length == 0)
+                    idx_to_rm.push(i)
+                else if(n_finish > n_to_keep)
+                    idx_to_rm.push(i)
+
+            }
+
+
+            for (let i = idx_to_rm.length -1; i >= 0; i--)
+                this.groups.splice(idx_to_rm[i],1);
+        },
+
+        delete_group(group_id){
+            for(let i=0; i <   this.groups.length ; i++){
+                if(this.groups[i].group_id == group_id){
+                    this.groups.splice(i, 1);
+                    break
+                }
+            }
+        } , 
+
+        update_group(new_group_data){
+            for(let i=0 ; i < this.groups.length ; i++ ){
+                if(this.groups[i].group_id == new_group_data.group_id){
+                    new_group_data = JSON.parse(JSON.stringify(new_group_data))
+                    Vue.set(this.groups , i , new_group_data ) 
+                }
+            }
+        },
+
+        get_group(group_id){
+            for(let i=0 ; i < this.groups.length ; i++ ){
+                if(this.groups[i].group_id == group_id){
+                    return this.groups[i]
+                }
+            }
+        }, 
+
+        clear_all(){
+            Vue.set(this, "groups" , [])
+        }
+
+    },
+}
+</script>
+<style>
+</style>
+<style scoped>
+    
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components/History.vue b/electron_app/src/components/History.vue
deleted file mode 100644
index d8d6ed5a..00000000
--- a/electron_app/src/components/History.vue
+++ /dev/null
@@ -1,220 +0,0 @@
-@import '../assets/css/theme.css';
-<template>
-    <div  class="animatable_content_box ">
-
-        <b-form-input
-            @input="currentPage=1"
-            onkeypress="return event.keyCode != 13;"
-            size="sm"
-            placeholder="Search by prompt text"
-            v-model="searchText"
-            autofocus
-            debounce="200"
-            style="max-width: 240px; float: left; margin-right: 30px;"
-            id="searchText"
-        />
-
-        <div @click="toggle_order()" style="float:right; margin-bottom: 20px;" class="l_button">
-          {{this.app_state.show_history_in_oldest_first ? "Oldest": "Newest"}} First
-        </div>
-        <div @click="clear_history()" style="float:right; margin-bottom: 20px;" class="l_button">
-          Clear History
-        </div>
-        <div v-if="Object.values(app_state.app_data.history).length > 0">
-            <div v-if="get_history.length > 30">
-                <b-pagination
-                    v-model="currentPage"
-                    :total-rows="get_history.length"
-                    :per-page="30"
-                />
-            </div>
-            <div v-for="history_box in get_history.slice((currentPage - 1) * 30, currentPage * 30)" :key="history_box.key" style="clear: both;">
-
-            
-                <div @click="delete_hist(history_box.key)" style="float:right; margin-top: 10px;"  class="l_button">Delete</div>
-                <!-- <div @click="share_on_arthub(history_box)" style="float:right; margin-top: 10px;"  class="l_button">Share</div> -->
-
-                <b-dropdown left variant="link" size="sm" toggle-class="text-decoration-none" no-caret style="float:right; margin-top: 5px;">
-                    <template #button-content>
-                        <div   class=" l_button "  >
-                            Share 
-                        </div>
-                    </template>
-                    <b-dropdown-item-button   @click="share_on_arthub(history_box)"  >Share on ArtHub.ai</b-dropdown-item-button>
-                </b-dropdown>
-
-                
-                <p class="history_box_info text_bg" style="user-select: text;">
-                    <img  v-if="history_box.inp_img" :src="'file://' + history_box.inp_img" style="height:50px">
-                    <br  v-if="history_box.inp_img" >
-                    <br  v-if="history_box.inp_img" >
-              
-                    <span style="opacity: 0.5;" v-if="get_box_params_str(history_box)"> {{get_box_params_str(history_box)}} </span>
-                    <br   v-if="get_box_params_str(history_box)">
-                    
-                    {{history_box.prompt}}
-
-
-                </p>
-                
-                <div v-for="img in history_box.imgs" :key="img" class="history_box">
-                
-                    <ImageItem :app_state="app_state" :hide_extra_save_button="true" :path="img" :style_obj="{height:'100%'}"></ImageItem>
-                
-                </div>
-                <div style="clear: both; display: table; margin-bottom: 10px;">
-                </div>
-                
-                <hr>
-
-
-            </div>
-
-            <div v-if="get_history.length > 30">
-                <b-pagination
-                    v-model="currentPage"
-                    :total-rows="get_history.length"
-                    :per-page="30"
-                />
-            </div>
-
-        </div>
-        <div v-else>
-            <div class="center">
-                    <p>No images generated yet.</p>
-            </div>
-        </div>
-    </div>
-</template>
-<script>
-import ImageItem from '../components/ImageItem.vue'
-import {native_confirm} from "../native_functions_vue_bridge.js";
-import {share_on_arthub} from '../utils.js'
-
-import Vue from 'vue'
-import Fuse from 'fuse.js'
-
-export default {
-    name: 'History',
-    props: {
-        app_state : Object,
-    },
-    components: {
-        ImageItem
-    },
-    mounted() {
-
-    },
-    data() {
-        return {
-            searchText: '',
-            currentPage: 1,
-        };
-    },
-
-    computed: {
-      get_history() {
-          let history = Object.values(this.app_state.app_data.history);
-          const that = this;
-          const list = this.app_state.show_history_in_oldest_first ? history : history.reverse();
-          if (that.searchText.trim() === '') {
-            return list;
-          }
-          
-          const fuse = new Fuse(list, {
-            keys: ['prompt'],
-            useExtendedSearch: true,
-          });
-
-          return fuse.search(that.searchText).map(r => r.item);
-
-       },
-    },
-
-    methods: {
-        delete_hist(k){
-            Vue.delete( this.app_state.app_data.history , k );
-        },
-
-        
-
-        toggle_order() {
-           Vue.set( this.app_state, "show_history_in_oldest_first", !this.app_state.show_history_in_oldest_first);
-        },
-
-        get_box_params_dict(box){
-            let r = {};
-            let vals = {"seed" : "Seed" , "guidence_scale" : "Scale" , "dif_steps":"Steps"  , "inp_img_strength" : "Image Strength" , "img_w":"Img Width" , "img_h": "Img Height" , "negative_prompt" : "Negative Prompt" , "model_version":"model_version", "selected_sampler":"Sampler" , "use_soft_seed":"Similar Imgs", "controlnet": "controlnet" , "controlnet_preprocess":"controlnet_preprocess"}
-            for(let k in vals)
-                if( box[k])
-                    r[vals[k]] =  box[k];
-            return r;
-        },
-
-        get_box_params_str(box){
-            let r = "";
-            let d = this.get_box_params_dict(box)
-            for(let k in d)
-                    r += " " +k  +  " : " + d[k] + " |";
-            if(r.charAt(r.length - 1) == "|")
-                r = r.slice(0, -1);
-            return r;
-        },
-
-         clear_history(){
-            if (native_confirm("Are you sure you want to clear history?")){
-                Vue.set( this.app_state.app_data, "history", {});
-            }
-        },
-
-        share_on_arthub(box){
-            this.app_state.global_loader_modal_msg = "Uploading";
-            let params = this.get_box_params_dict(box);
-            let that = this;
-            share_on_arthub(box.imgs , params , box.prompt).then((
-                function(){ that.app_state.global_loader_modal_msg = ""}
-            )).catch(
-                function(){alert("Error in uploading.") ; that.app_state.global_loader_modal_msg = ""}
-            )
-        }
-
-    },
-}
-</script>
-<style>
-.page-item .page-link{
-    outline: none !important;
-   box-shadow: none;
-}
-.page-item .page-link{
-    font-size: 13px;
-}
-@media (prefers-color-scheme: dark) {
-    .page-item .page-link, .page-item.disabled .page-link{
-        background-color:#303030;
-        border-color: #303030;
-        color:rgba(255, 255, 255, 0.5);
-    }
-    .page-item.active .page-link{
-        background-color:#606060;
-        border-color: #606060;
-    }
-}
-</style>
-<style scoped>
-.history_box_info {
-   
-    padding :12px;
-    border-radius: 5px;
-    max-width: calc(100vw - 200px );
-}
-
-
-
-.history_box {
-    height:230px;
-    float:left;
-    margin-right: 10px;
-    margin-bottom: 30px;
-}
-</style>
diff --git a/electron_app/src/components/Img2Img.vue b/electron_app/src/components/Img2Img.vue
deleted file mode 100644
index 8594126a..00000000
--- a/electron_app/src/components/Img2Img.vue
+++ /dev/null
@@ -1,313 +0,0 @@
-@import '../assets/css/theme.css';
-
-<template>
-     <div  class="animatable_content_box ">
-        <div class="left_half">
-            <!-- <p>Input Image:</p>
-            <img class="gal_img" style="width: 90%;" src="https://colormadehappy.com/wp-content/uploads/2022/02/How-to-draw-a-cute-dog-6.jpg"/> 
-         -->
-
-            <div v-if="inp_img" @drop.prevent="onDragFile" @dragover.prevent class="image_area" :class="{ crosshair_cur  : is_inpaint }"  style="height: calc(100% - 200px);  border-radius: 16px; padding:5px;">
-                <ImageCanvas ref="inp_img_canvas" :is_inpaint="is_inpaint" :image_source="inp_img"  :is_disabled="!stable_diffusion.is_input_avail" canvas_id="img2imgcan" canvas_d_id="img2imgcand" ></ImageCanvas>
-            </div>
-                <div v-else @drop.prevent="onDragFile" @dragover.prevent @click="open_input_image" class="image_area" :class="{ pointer_cursor  : is_sd_active }" style="height: calc(100% - 200px);  border-radius: 16px; padding:5px;">
-                    <center>
-                    <p style="margin-top: calc( 50vh - 180px); opacity: 70%;" >Click to add input image</p>
-                </center>
-            </div>
-
-            <div v-if="inp_img && stable_diffusion.is_input_avail" class="l_button" @click="open_input_image" >Change Image</div>
-            <div v-if="inp_img && stable_diffusion.is_input_avail" class="l_button" @click="inp_img =''">Clear</div>
-            <div v-if="inp_img && stable_diffusion.is_input_avail && !is_inpaint" class="l_button" @click="is_inpaint = !is_inpaint ">Draw Mask</div>
-            <div v-if="inp_img && stable_diffusion.is_input_avail && is_inpaint" class="l_button" @click="is_inpaint = !is_inpaint ">Remove Mask</div>
-
-            <br> <br> 
-            <textarea 
-                    v-model="prompt" 
-                    placeholder="Enter your prompt here" 
-                    style="border-radius: 12px 12px 12px 12px; width: calc(100%); resize: none; " 
-                    class="form-control"  
-                    v-bind:class="{ 'disabled' : !stable_diffusion.is_input_avail}"
-                    :rows="is_negative_prompt_avail ? 2:3"></textarea>
-            <textarea 
-                    v-if="is_negative_prompt_avail"
-                    v-model="negative_prompt" 
-                    placeholder="Enter your negative prompt here" 
-                    style="border-radius: 12px 12px 12px 12px; width: calc(100%); resize: none; margin-top: 5px; " 
-                    class="form-control negative_prompt_tb"  
-                    v-bind:class="{ 'disabled' : !stable_diffusion.is_input_avail}"
-                    :rows="1"></textarea>
-
-            <div v-if="stable_diffusion.is_input_avail" class="content_toolbox" style="margin-top:10px; margin-bottom:-10px;">
-                <div class="l_button button_medium button_colored" style="float:right ; " @click="generate_img2img" >Generate</div>
-                <SDOptionsDropdown :options_model_values="this_object" :elements_hidden="['img_h' , 'img_w' ]" > </SDOptionsDropdown>
-            </div>
-            <div v-else-if="stable_diffusion.generated_by=='img2img'"  class="content_toolbox" style="margin-top:10px; margin-bottom:-10px;">
-                <div v-if="is_stopping" class="l_button button_medium button_colored" style="float:right" @click="stop_generation">Stopping ...</div>
-                <div v-else class="l_button button_medium button_colored" style="float:right" @click="stop_generation">Stop</div>
-            </div>
-            <br><br>
-            <p style="opacity:0.5; zoom:0.8"> Please describe the complete image which you want to see as the output. </p>
-        
-        </div>
-
-        <div  class="right_half">
-
-        
-            <div v-if="generated_images.length > 0 " >
-
-                <br> <br>
-                <div   v-for="img in generated_images" :key="img" >
-                    <center>
-                        
-                        <ImageItem :app_state="app_state" :path="img" :style_obj="{ 'width': '75%' }"></ImageItem>
-
-                    </center>
-                    <br>
-                </div>
-                
-            </div>
-
-            <div v-if="backend_error" style="color:red ; margin-top:50px;">
-                <div class="center loader_box">
-                    <p>Error: {{backend_error}} </p>
-                </div>
-            </div>
-
-            <div v-if="!stable_diffusion.is_input_avail && stable_diffusion.generated_by=='img2img'">
-                <LoaderModal :loading_percentage="done_percentage" loading_title="Generating" :loading_desc="stable_diffusion.generation_state_msg" :remaining_times="stable_diffusion.remaining_times"></LoaderModal>
-            </div>
-            
-
-        </div>
-
-
-     </div>
-</template>
-<script>
-import ImageItem from '../components/ImageItem.vue'
-import ImageCanvas from '../components_bare/ImageCanvas.vue'
-
-import LoaderModal from '../components_bare/LoaderModal.vue'
-import Vue from 'vue'
-import SDOptionsDropdown from '../components_bare/SDOptionsDropdown.vue'
-
-export default {
-    name: 'Img2Img',
-    props: {
-        app_state : Object   , 
-        stable_diffusion : Object,
-    },
-    components: { LoaderModal, ImageItem, ImageCanvas, SDOptionsDropdown },
-    mounted() {
-
-    },
-    computed:{
-        is_sd_active(){
-            return this.stable_diffusion.is_input_avail;
-        },
-        this_object(){
-            return this;
-        }
-    },
-    watch: {
-        'inp_img': {
-            handler: function() {
-                this.is_inpaint = false;
-            },
-            deep: true
-        } , 
-    },
-    data() {
-        return {
-            prompt : '',
-            inp_img : '',
-            num_imgs:1,
-            dif_steps: 25,
-            batch_size:1 ,
-            seed: '',
-            generated_images : [],
-            backend_error : "",
-            done_percentage : -1,
-            is_stopping : false,
-            inp_img_strength : 0.3 , 
-            img_h : 512 , 
-            img_w : 512 , 
-            is_inpaint : false,
-            guidence_scale : 7.5 , 
-
-            is_negative_prompt_avail : false, 
-            negative_prompt : "",
-            selected_model : 'Default'
-        };
-    },
-    methods: {
-
-        generate_img2img(){
-
-            let seed = 0;
-            if(this.seed)
-                seed = Number(this.seed);
-            else
-                seed = Math.floor(Math.random() * 100000);
-
-            if(this.prompt.trim() == ""){
-                Vue.$toast.default('You need to enter a prompt')
-                return;
-            }
-                
-
-            if(!this.inp_img){
-                Vue.$toast.default('You need to add an input image')
-                return;
-            }
-                
-
-            let input_image = window.ipcRenderer.sendSync('save_b64_image',  this.$refs.inp_img_canvas.get_img_b64()  );
-            let input_image_with_mask;
-            let mask_img;
-            if(this.is_inpaint)
-            { 
-                input_image_with_mask = window.ipcRenderer.sendSync('save_b64_image',  this.$refs.inp_img_canvas.get_img_mask_bg4() );
-                mask_img = window.ipcRenderer.sendSync('save_b64_image',  this.$refs.inp_img_canvas.get_mask_b46() , true );
-            } else {
-                input_image_with_mask = input_image;
-                mask_img = undefined;
-            }
-            
-
-            let params = {
-                prompt : this.prompt , 
-                W : -1 , 
-                H : -1, 
-                seed :seed,
-                scale : this.guidence_scale , 
-                ddim_steps : this.dif_steps, 
-                num_imgs : this.num_imgs , 
-                batch_size : this.batch_size , 
-                img_strength : this.inp_img_strength,
-                input_image : input_image,
-                is_inpaint : this.is_inpaint                
-            }
-
-            if(this.selected_model && this.selected_model != "Default" && this.app_state.app_data.custom_models[this.selected_model] ){
-                params.model_id = -1;
-                params.custom_model_path =  this.app_state.app_data.custom_models[this.selected_model].path;
-            }
-
-
-            if(this.is_inpaint)
-                params['mask_image'] = mask_img;
-
-            if(this.is_negative_prompt_avail)
-                params['negative_prompt'] = this.negative_prompt;
-
-            let that = this;
-            this.backend_error = "";
-            Vue.set(this,'generated_images' ,[]);
-            this.done_percentage = -1;
-
-            let history_key = Math.random();
-
-            let callbacks = {
-                on_img(img_path){
-                    that.generated_images.push(img_path);
-
-                    let p = {
-                            "prompt":that.prompt , "seed": seed, "key":history_key , "imgs" : [] , "inp_img": input_image_with_mask,
-                            "dif_steps" : that.dif_steps , "inp_img_strength" : that.inp_img_strength, "model_version": that.stable_diffusion.model_version , "guidence_scale" : that.guidence_scale , 
-                        }
-                    if(that.stable_diffusion.model_version)
-                        p['model_version'] = that.stable_diffusion.model_version;
-                    if(that.is_negative_prompt_avail)
-                        p['negative_prompt'] = that.negative_prompt;
-
-                    if(!(that.app_state.app_data.history[history_key]))
-                        Vue.set(that.app_state.app_data.history, history_key , p );
-                    
-                    that.app_state.app_data.history[history_key].imgs.push(img_path)
-
-                    console.log(that.app_state.app_data.history)
-
-                },
-                on_progress(p){
-                    that.done_percentage = p;
-                    
-                },
-                on_err(err){
-                    that.backend_error = err;
-                },
-            }
-
-            this.is_stopping = false;
-
-
-           if(this.stable_diffusion)
-                this.stable_diffusion.text_to_img(params, callbacks, 'img2img');
-        } , 
-
-        open_input_image(){
-            if( !this.stable_diffusion.is_input_avail)
-                return;
-            let img_path = window.ipcRenderer.sendSync('file_dialog',  'img_file' );
-            if(img_path && img_path != 'NULL'){
-                this.inp_img = img_path;
-                this.is_inpaint = false;
-            }      
-        },
-        onDragFile(e){
-            if( !this.stable_diffusion.is_input_avail)
-                return;
-            if(!e.dataTransfer.files[0].type.startsWith('image/'))
-                return;
-            let img_path = e.dataTransfer.files[0].path;
-            if(img_path && img_path != 'NULL'){
-                this.inp_img = img_path;
-                this.is_inpaint = false;
-            }      
-        },
-
-        stop_generation(){
-            this.is_stopping = true;
-            this.stable_diffusion.interupt();
-        },
-    },
-}
-</script>
-<style>
-    .left_half{
-        position: absolute;
-        top :2px;
-        bottom: 3px;
-        left : 2px ;
-        padding: 20px;
-        width: calc(100vw / 2 - 10px);
-        border-right: 1px solid ;
-        border-color: rgba(0,0,0,0.1);
-    }
-
-    @media (prefers-color-scheme: dark) {
-        .left_half{
-            border-color: #606060;
-        }
-    }
-
-    .right_half{
-        position: absolute;
-        top :2px;
-        bottom: 3px;
-        right : 3px ;
-        padding: 20px;
-        width: calc(100vw / 2 - 10px);
-        overflow-y: auto;
-    }
-
-    .pointer_cursor{
-        cursor: pointer;
-    }
-</style>
-<style scoped>
-    .crosshair_cur{
-        cursor: crosshair;
-    }
-</style>
\ No newline at end of file
diff --git a/electron_app/src/components/ImgGenerate.vue b/electron_app/src/components/ImgGenerate.vue
deleted file mode 100644
index 47d61ae1..00000000
--- a/electron_app/src/components/ImgGenerate.vue
+++ /dev/null
@@ -1,364 +0,0 @@
-@import '../assets/css/theme.css';
-<template>
-    <div  class="animatable_content_box ">
-        <div v-if="stable_diffusion.is_backend_loaded">
-            <div class="textbox_section" >
-                <textarea 
-                    v-model="prompt" 
-                    placeholder="Enter your prompt here" 
-                    style="border-radius: 12px 12px 12px 12px; width: calc(100%); resize: none; " 
-                    class="form-control"  
-                    v-bind:class="{ 'disabled' : !stable_diffusion.is_input_avail}"
-                    :rows="is_negative_prompt_avail ? 2:3"></textarea>
-
-                <textarea 
-                    v-if="is_negative_prompt_avail"
-                    v-model="negative_prompt" 
-                    placeholder="Enter your negative prompt here" 
-                    style="border-radius: 12px 12px 12px 12px; width: calc(100%); resize: none; margin-top: 5px; " 
-                    class="form-control negative_prompt_tb"  
-                    v-bind:class="{ 'disabled' : !stable_diffusion.is_input_avail}"
-                    :rows="1"></textarea>
-
-                <div v-if="stable_diffusion.is_input_avail" class="content_toolbox" style="margin-top:10px; margin-bottom:-10px;">
-                    
-                    <div class="l_button button_medium button_colored" style="float:right ; " @click="generate_from_prompt">Generate</div>
-
-                    <SDOptionsDropdown :options_model_values="this_object" :elements_extra="['sampler' , 'use_soft_seed']"  :elements_hidden="[ 'inp_img_strength' ]"> </SDOptionsDropdown>
-
-                    <div style="float:right; margin-top: -5px; " >
-                        <b-dropdown id="dropdown-form" variant="link" ref="dropdown" toggle-class="text-decoration-none" no-caret >
-                        
-                            <template #button-content>
-                                <div class="l_button"  style="margin-right: -20px;" >Styles</div>
-                            </template>
-
-                            <b-dropdown-form style="width: 540px ; ">
-
-                                <div style="max-height: calc(100vh - 300px); overflow-y: scroll;">
-                                    <div v-for="modifier in modifiers" :key="modifier[0]">
-                                        <p>{{modifier[0]}}</p>
-                                        <div v-for="tag in modifier[1]" @click="add_style(tag)" :key="tag" class="l_button button_small button_colored" style="float:left; margin-bottom: 7px;">{{tag}}</div>
-
-                                        <div style="clear: both; display: table; margin-bottom: 3px;"> </div>
-                                        <hr>
-                                    </div>
-
-                                    <p>Source : cmdr2</p>
-                                </div>
-
-                                
-  
-                            </b-dropdown-form>
-                        </b-dropdown>
-                    </div>
-
-                    <div style="float:right; margin-top: -5px; " >
-                        <b-dropdown id="dropdown-form" variant="link" ref="dropdown" toggle-class="text-decoration-none" no-caret >
-                            <template #button-content>
-                                <div class="l_button"  style="margin-right: -20px;" >Model : <span style="font-weight:">{{selected_model.substring(0, 10)}} <font-awesome-icon icon="chevron-down" />  </span></div>
-                            </template>
-                            <b-dropdown-item v-for="option in ['Default'].concat(Object.keys(app_state.app_data.custom_models))" :key="option" @click="selected_model = option" >
-                                {{option}}
-                            </b-dropdown-item>
-                            <hr style="opacity:0.1">
-                            <b-dropdown-item @click="$parent.$parent.$refs.app_frame.selectTab('settings')">
-                                Add New Model
-                            </b-dropdown-item>
-                            <!-- <b-dropdown-item @click="$parent.$parent.$refs.app_frame.selectTab('settings')">
-                                Browse Models
-                            </b-dropdown-item> -->
-                        </b-dropdown>
-                            
-                    </div>
-
-                    <div class="l_button button_medium" style="float:right ;margin-right: -10px; margin-top: -1px;" @click="open_arthub">Prompt Ideas</div>
-
-
-                    
-                </div>
-                <div v-else-if="stable_diffusion.generated_by=='txt2img'"  class="content_toolbox" style="margin-top:10px; margin-bottom:-10px;">
-                    <div v-if="is_stopping" class="l_button button_medium button_colored" style="float:right" @click="stop_generation">Stopping ...</div>
-                    <div v-else class="l_button button_medium button_colored" style="float:right" @click="stop_generation">Stop</div>
-                </div>
-            </div>
-
-
-            <div v-if="generated_images.length == 1" >
-                <center>
-                    <ImageItem :app_state="app_state"  :path="generated_images[0]" :style_obj="{ 'width': 'calc(100vh - 390px )' , 'margin-top': '60px' }"></ImageItem>
-                </center>
-            </div>
-            
-            <div>
-                <br> 
-                <b-row v-if="generated_images.length > 1"  class="justify-content-md-center" >
-
-                    <b-col  v-for="img in generated_images" :key="img" style="margin-top:80px"  md="6" lg="4" xl="3"  >
-                        <center>
-                            
-                            <ImageItem :app_state="app_state"  :path="img" :style_obj="{'max-width' :'85%'}"></ImageItem>
-                        </center>
-                    </b-col>
-                        
-
-                
-                </b-row>
-                <br> 
-            </div>
-
-            <div v-if="backend_error" style="color:red ; margin-top:50px;">
-                <div class="center loader_box">
-                     <p>Error: {{backend_error}} </p>
-                </div>
-            </div>
-        </div>
-
-        <div v-if="!stable_diffusion.is_input_avail && stable_diffusion.generated_by=='txt2img'">
-            <LoaderModal :loading_percentage="done_percentage" loading_title="Generating" :loading_desc="stable_diffusion.generation_state_msg" :remaining_times="stable_diffusion.remaining_times"></LoaderModal>
-        </div>
-    
-    <div class="bottom_float">
-        <p>Please close other applications for best speed.</p>
-    </div>
-
-    <div @click="share_current_arthub"  v-if="generated_images.length > 0"  class="l_button bottom_float" style="right : 10px; bottom : 15px; background-color: inherit; cursor: pointer;">Share on ArtHub.ai</div>
-
-
-</div>
-
-
-
-</template>
-<script>
-
-import LoaderModal from '../components_bare/LoaderModal.vue'
-import Vue from 'vue'
-import ImageItem from '../components/ImageItem.vue'
-import {share_on_arthub} from '../utils.js'
-import SDOptionsDropdown from '../components_bare/SDOptionsDropdown.vue'
-
-export default {
-    name: 'ImgGenerate',
-    props: {
-        app_state : Object   , 
-        stable_diffusion : Object,
-    },
-    components: { LoaderModal, ImageItem, SDOptionsDropdown },
-    mounted() {
-       
-    },
-    data() {
-        return {
-            img_w : 512, 
-            img_h : 512 , 
-            dif_steps : 25,
-            guidence_scale : 7.5 , 
-            is_adv_options : false , 
-            seed : ""  , 
-            prompt : "",
-            num_imgs : 1,
-            batch_size : 1 , 
-            generated_images : [],
-            backend_error : "",
-            done_percentage : -1,
-            is_stopping : false,
-            use_soft_seed:"No",
-            modifiers : require("../modifiers.json"),
-            is_negative_prompt_avail : false, 
-            negative_prompt : "",
-            selected_model : 'Default',
-            selected_sampler : 'ddim',
-        };
-        
-    },
-    computed: {
-        this_object(){
-            return this;
-        }
-    },
-    methods: {
-        generate_from_prompt(){
-            let seed = 0;
-            if(this.seed)
-                seed = Number(this.seed);
-            else
-                seed = Math.floor(Math.random() * 100000);
-
-            this.computed_seed = seed;
-
-
-            let params = {
-                prompt : this.prompt , 
-                W : Number(this.img_w) , 
-                H : Number(this.img_h) , 
-                seed :seed,
-                scale : this.guidence_scale , 
-                ddim_steps : this.dif_steps, 
-                num_imgs : this.num_imgs , 
-                batch_size : this.batch_size ,
-                scheduler: this.selected_sampler,
-            }
-
-            if(this.selected_model && this.selected_model != "Default" && this.app_state.app_data.custom_models[this.selected_model] ){
-                params.model_id = -1;
-                params.custom_model_path =  this.app_state.app_data.custom_models[this.selected_model].path;
-            }
-
-            if(this.is_negative_prompt_avail)
-                params['negative_prompt'] = this.negative_prompt;
-
-            if(this.use_soft_seed == 'Yes')
-                params['soft_seed'] = 1
-
-            let that = this;
-
-            if(this.prompt.trim() == ""){
-                Vue.$toast.default('You need to enter a prompt to generate an image')
-                return;
-            }
-                
-
-            this.backend_error = "";
-            Vue.set(this,'generated_images' ,[]);
-            this.done_percentage = -1;
-
-            let history_key = Math.random();
-
-            let callbacks = {
-                on_img(img_path){
-                    that.generated_images.push(img_path);
-
-                    if(!(that.app_state.app_data.history[history_key])){
-                        let p = {
-                            "prompt":that.prompt , "seed": seed, "img_w":that.img_w , "img_h":that.img_h ,  "key":history_key , "imgs" : [],
-                            "guidence_scale" : that.guidence_scale , "dif_steps" : that.dif_steps , "use_soft_seed" : that.use_soft_seed,
-                            "selected_sampler" : that.selected_sampler
-                        }
-                        if(that.stable_diffusion.model_version)
-                            p['model_version'] = that.stable_diffusion.model_version;
-                        if(that.is_negative_prompt_avail)
-                            p['negative_prompt'] = that.negative_prompt;
-                        Vue.set(that.app_state.app_data.history, history_key , p);
-                    }
-                        
-
-                    
-                    that.app_state.app_data.history[history_key].imgs.push(img_path)
-
-                    console.log(that.app_state.app_data.history)
-
-                },
-                on_progress(p ){
-                    that.done_percentage = p;                
-                },
-                on_err(err){
-                    that.backend_error = err;
-                },
-            }
-
-            this.is_stopping = false;
-
-
-           if(this.stable_diffusion)
-                this.stable_diffusion.text_to_img(params, callbacks, 'txt2img');
-        } , 
-
-
-        open_arthub(){
-            window.ipcRenderer.sendSync('open_url', "https://arthub.ai");
-        },
-
-        stop_generation(){
-            this.is_stopping = true;
-            this.stable_diffusion.interupt();
-        },
-
-        add_style(tag){
-            this.prompt += ", " + tag;
-        },
-
-        share_current_arthub(){
-            this.app_state.global_loader_modal_msg = "Uploading";
-            let params =  {
-                "Img Width": Number(this.img_w) , 
-                "Img Height" : Number(this.img_h) , 
-                Seed :this.computed_seed,
-                Scale : this.guidence_scale , 
-                Steps : this.dif_steps ,
-                sampler_name : "bee" + this.selected_sampler, 
-                model_version: this.stable_diffusion.model_version
-            }
-            if(this.is_negative_prompt_avail)
-                params['Negative Prompt'] = this.negative_prompt;
-
-            let that = this;
-            share_on_arthub( that.generated_images , params , that.prompt).then((
-                function(){ that.app_state.global_loader_modal_msg = ""}
-            )).catch(
-                function(){alert("Error in uploading.") ; that.app_state.global_loader_modal_msg = ""}
-            )
-        },
-
-    },
-}
-</script>
-<style>
-   .center {
-      margin: 0;
-      position: absolute;
-      top: 50%;
-      left: 50%;
-      -ms-transform: translate(-50%, -50%);
-      transform: translate(-50%, -50%);
-    }
-
-    .disabled{
-        pointer-events:none;
-        opacity: 0.5;
-    }
-
-    .loader_box{
-       padding: 20px;
-        /*height: calc(160px);*/
-        border-radius: 12px 12px 12px 12px;
-    }
-
-
-    .ad_form_box{
-        float:left; 
-        background-color: rgba(0, 0, 0, 0.1); 
-        padding:10px ; 
-        margin-right: 10px;
-         border-radius: 3px 3px 3px 3px;
-    }
-
-    .gal_img{
-        border-radius: 12px 12px 12px 12px;
-        /* background-color: white; */
-        border-style: solid;
-        border-width: 1px;
-        border-color: rgba(0, 0, 0, 0.1);
-        cursor: pointer;
-        box-shadow: 0px 0px 1.76351px rgba(40, 41, 61, 0.04), 0px 3.52703px 7.05405px rgba(96, 97, 112, 0.16);
-
-    }
-
-    @media (prefers-color-scheme: dark) {
-        .gal_img{
-            border-color: rgba(255, 255, 255, 0.3);
-        }
-    }
-
-    .negative_prompt_tb{
-        color:brown !important;
-    }
-
-    @media (prefers-color-scheme: dark) {
-        .negative_prompt_tb{
-            color:rgb(210, 0, 0) !important ;
-        }
-
-    }
-
-</style>
diff --git a/electron_app/src/components/Inpainting.vue b/electron_app/src/components/Inpainting.vue
deleted file mode 100644
index f6a94730..00000000
--- a/electron_app/src/components/Inpainting.vue
+++ /dev/null
@@ -1,310 +0,0 @@
-<template>
-    <div  class="animatable_content_box ">
-        <div class="content_toolbox" style="margin-bottom: -13px; ">
-            
-            <div v-if="inp_img && stable_diffusion.is_input_avail" class="l_button" style="float:right " @click="clear" > Reset</div>
-            <div v-if="undo_history.length > 0  && stable_diffusion.is_input_avail" class="l_button" style="float:right " @click="do_undo" > Undo</div>
-            <div v-if="inp_img " class="l_button" style="float:right " @click="save_img" > Save Image</div>
-            <div v-if="retry_params  && stable_diffusion.is_input_avail" class="l_button" style="float:right "   @click="generate(true)"> Retry</div>
-            
-            
-            <div v-if="stable_diffusion.is_input_avail && inp_img"   style="float:right ; margin-right: 10px" >
-                <input v-model="stroke_size_no" style="zoom:0.8; margin-top: 7px; width:100px" type="range"
-                        min="1" max="100" >                
-            </div>
-            <div v-if="stable_diffusion.is_input_avail && inp_img"   class="l_button no_hover_bg" style="float:right ; margin-right: -5px; " > Stroke Size</div>
-            
-
-        </div>
-
-        <div class="inapint_container" @drop.prevent="onDragFile" @dragover.prevent>
-            <ImageCanvas style="cursor: crosshair;"  v-if="inp_img"  ref="inp_img_canvas" :is_inpaint="true" :image_source="inp_img"  :is_disabled="!stable_diffusion.is_input_avail" id="inpaint"  canvas_id="inpaintcan" canvas_d_id="inpaintcand" :stroke_size_no="stroke_size_no" ></ImageCanvas>
-            <div v-else @click="open_input_image" style=" "  :class="{ pointer_cursor  : is_sd_active }" >
-                <center>
-                    <p style="padding-top: calc( 50vh - 115px);padding-bottom: calc( 50vh - 155px);  opacity: 70%;" >Click to add input image and draw a mask</p>
-                </center>
-            </div>
-        </div>
-
-        <div class="bottom_toolbox"> 
-            <textarea 
-                    v-model="prompt" 
-                    placeholder="Enter your prompt here" 
-                    style="border-radius: 12px 12px 12px 12px; resize: none; " 
-                    class="form-control inpaint_textbox"  
-                    v-bind:class="{ 'disabled' : !stable_diffusion.is_input_avail}"
-                    :rows="1">
-
-                    <!-- v-bind:class="{ 'disabled' : !stable_diffusion.is_input_avail}" -->
-            </textarea>
-
-            <div  v-if="stable_diffusion.is_input_avail" @click="generate()"  class="l_button button_medium button_colored" style="float:right ; margin-top: 4px; ">Inpaint</div>
-            <span v-else-if="stable_diffusion.generated_by=='inpainting'"   >
-                <div v-if="is_stopping" class="l_button button_medium button_colored" style="float:right ; margin-top: 4px; " @click="stop_generation">Stopping</div>
-                <div v-else class="l_button button_medium button_colored" style="float:right ; margin-top: 4px; " @click="stop_generation">Stop</div>
-            </span>
-
-        </div>
-
-        <div v-if="backend_error" style="color:red ; margin-top:50px;">
-            <div class="center loader_box">
-                <p>Error: {{backend_error}} </p>
-            </div>
-        </div>
-
-        <div v-if="!stable_diffusion.is_input_avail && stable_diffusion.generated_by=='inpainting'">
-            <LoaderModal :loading_percentage="done_percentage" loading_title="Generating" :loading_desc="stable_diffusion.generation_state_msg" :remaining_times="stable_diffusion.remaining_times"></LoaderModal>
-        </div>
-
-
-    </div>
-   
-   
-     
-</template>
-<script>
-
-import ImageCanvas from '../components_bare/ImageCanvas.vue'
-import LoaderModal from '../components_bare/LoaderModal.vue'
-import Vue from 'vue'
-
-
-export default {
-    name: 'Inpainting',
-    props: {
-        app_state : Object   , 
-        stable_diffusion : Object,
-    },
-    components: {LoaderModal ,ImageCanvas  },
-    mounted() {
-
-    },
-    computed:{
-        is_sd_active(){
-            return this.stable_diffusion.is_input_avail;
-        }
-    },
-    data() {
-        return {
-            prompt: "",
-            inp_img : "",
-            input_img_orig : "", // the first input image after reset
-            backend_error : "",
-            done_percentage : -1,
-            is_stopping : false,
-            undo_history : [],
-            retry_params: undefined,
-            stroke_size_no : "30",
-            "history_key" : "",
-        };
-    },
-    methods: {
-        
-         generate(is_retry){
-
-            let seed = 0;
-            if(this.seed)
-                seed = Number(this.seed);
-            else
-                seed = Math.floor(Math.random() * 100000);
-
-            let prompt ;
-            let input_image;
-            let mask_img ;
-
-            if(is_retry && this.retry_params){
-                prompt = this.retry_params.prompt;
-                input_image = this.retry_params.input_image;
-                mask_img = this.retry_params.mask_img;
-            }
-            else{
-                if(this.prompt.trim() == ""){
-                    Vue.$toast.default('You need to enter a prompt')
-                    return;
-                }
-                
-
-                if(!this.inp_img){
-                    Vue.$toast.default('You need to add an input image')
-                    return;
-                }
-                    
-
-                if(!this.$refs.inp_img_canvas.is_something_drawn){
-                    Vue.$toast.default('You need to draw a mask')
-                    return;
-                }
-                   
-
-                prompt = this.prompt;
-
-                input_image = window.ipcRenderer.sendSync('save_b64_image',  this.$refs.inp_img_canvas.get_img_b64(), true  );
-                mask_img = window.ipcRenderer.sendSync('save_b64_image',  this.$refs.inp_img_canvas.get_mask_b46() , true );
-            }
-
-            this.retry_params = {input_image:input_image , mask_img:mask_img , prompt:prompt  }
-            
-            let params = {
-                prompt : prompt , 
-                W : -1 , 
-                H : -1, 
-                seed :seed,
-                scale : this.guidence_scale , 
-                input_image : input_image,
-                is_inpaint :  true ,
-                mask_image: mask_img , 
-                model_id: 1 , 
-            }
-
-            let that = this;
-            this.backend_error = "";
-            this.done_percentage = -1;
-
-            this.undo_history.push(input_image)
-
-            let callbacks = {
-                on_img(img_path){
-                    that.inp_img = img_path
-                    that.$refs.inp_img_canvas.clear_inpaint()
-
-                    if(that.history_key ){
-                        let p = {
-                            "prompt": "Inpainting: " +  that.prompt , "key":that.history_key , "imgs" : [img_path] , "inp_img": that.input_img_orig,
-                            "model_version": that.stable_diffusion.model_version , "guidence_scale" : that.guidence_scale , 
-                        }                
-                        Vue.set(that.app_state.app_data.history, that.history_key , p );
-                    }
-                    
-                    
-
-                    
-                },
-                on_progress(p){
-                    that.done_percentage = p;
-                    
-                },
-                on_err(err){
-                    that.backend_error = err;
-                },
-            }
-
-            this.is_stopping = false;
-
-
-           if(this.stable_diffusion)
-                this.stable_diffusion.text_to_img(params, callbacks, 'inpainting');
-        } , 
-
-        set_inp_image(img_path){
-            this.inp_img = img_path;
-            this.undo_history = []
-            this.input_img_orig = img_path
-            this.history_key = Math.random()+"inp"
-
-            if(this.$refs.inp_img_canvas){
-                this.$refs.inp_img_canvas.clear_inpaint()
-            }
-        },
-
-        open_input_image(){
-            if( !this.stable_diffusion.is_input_avail)
-                return;
-            let img_path = window.ipcRenderer.sendSync('file_dialog',  'img_file' );
-            if(img_path && img_path != 'NULL'){
-               this.set_inp_image(img_path)
-            }
-        },
-
-        onDragFile(e) {
-            if (!this.stable_diffusion.is_input_avail)
-                return;
-            if (!e.dataTransfer.files[0].type.startsWith('image/'))
-                return;
-            let img_path = e.dataTransfer.files[0].path;
-            this.set_inp_image(img_path)
-        },
-
-        do_undo(){
-            let a = this.undo_history.pop()
-            if(a){
-                this.inp_img = a;
-                if(this.$refs.inp_img_canvas){
-                    this.$refs.inp_img_canvas.clear_inpaint()
-                }
-            }
-                
-        },
-
-        save_img(){
-            let out_path = window.ipcRenderer.sendSync('save_dialog' );
-            if(!out_path)
-                return
-            
-            let org_path = window.ipcRenderer.sendSync('save_b64_image',  this.$refs.inp_img_canvas.get_img_b64()  );
-            if(!org_path)
-                return
-            org_path = org_path.replaceAll("file://" , "")
-            window.ipcRenderer.sendSync('save_file', org_path+"||" +out_path);
-        },
-
-        clear(){
-            if(this.$refs.inp_img_canvas){
-                this.$refs.inp_img_canvas.clear_inpaint()
-            }
-            this.inp_img = ""
-            this.undo_history = []
-            this.prompt = ""
-            this.input_img_orig = ""
-            this.history_key = ""
-            this.retry_params  = undefined
-        },
-
-        stop_generation(){
-            this.is_stopping = true;
-            this.stable_diffusion.interupt();
-        },
-        
-    },
-}
-</script>
-<style>
- .inapint_container{
-
-        border-color: rgb(206, 212, 218);
-        border-width: 1px;
-        border-style: solid;
-
-        width:  80vw ; 
-        height: calc(100vh - 230px) ;  
-        margin-left:10vw ;
-        margin-top: 30px; 
-
-    }
-
-    .bottom_toolbox{
-        position: absolute;
-        
-        bottom:20px;
-        width: 80vw ; 
-        margin-left:10vw ;
-
-        /* width: calc(100vw - 20px) ; 
-        margin-left:10px ; */
-
-
-    }
-
-    .inpaint_textbox{
-        float:left;
-        max-width: calc(100% - 100px);
-    }   
-
-    @media (prefers-color-scheme: dark) {
-        .inapint_container{
-            border-color: #606060
-        }
-    }
-
-</style>
-<style scoped>
-</style>
\ No newline at end of file
diff --git a/electron_app/src/components/MainToolbar.vue b/electron_app/src/components/MainToolbar.vue
new file mode 100644
index 00000000..fc640098
--- /dev/null
+++ b/electron_app/src/components/MainToolbar.vue
@@ -0,0 +1,154 @@
+<template>
+    <div> 
+        
+        <MoonLoader v-if="is_sd_busy" class="moonloader1" color="var(--title-icon_color)" size="20px" style="position:fixed; margin-left:18px; margin-top:5px; z-index:20 ; pointer-events: none;"></MoonLoader>
+
+        
+        <b-dropdown right variant="link" offset="40"  size="sm" toggle-class="text-decoration-none" no-caret style="margin-right: -11px ;">
+            <template #button-content>
+               <span class="title_bar_icon" > 
+                   <!--  <svg width="16" height="20" viewBox="0 0 16 20" fill="none" xmlns="http://www.w3.org/2000/svg" style=" margin-top:-2px ">
+                      <path :d="icon_library['share']" />
+                    </svg> -->
+
+                    
+                    <font-awesome-icon   icon="inbox" style="zoom:1.15;" :style="{'opacity' :!(is_sd_busy)+0 }"/>
+                    
+                 </span>
+            </template>
+            
+             <b-dropdown-form style=" width: 250px;max-height: calc(100vh - 300px); overflow-y: scroll;  " class="dropdown-bubble">
+                <div v-if="app.is_mounted && !(app.stable_diffusion.is_input_avail)">
+                    <h2>Status : Generating Images</h2>
+                    <p  > Generation speed : {{app.stable_diffusion.generation_state_msg || "--"}}</p>
+                    <p  > Current image ETA : {{app.stable_diffusion.remaining_times || "--"}}</p>
+                </div>
+                <h2 v-else >Status : Idle</h2>
+                <p>Images remaining : {{n_jobs_left}} </p> 
+                <div @click="stop_all" v-if="(!is_stopping) &&( n_jobs_left > 0 || (app.is_mounted && !(app.stable_diffusion.is_input_avail)))" class="l_button button_small button_colored">Stop All</div>
+                 <div v-if="is_stopping && (n_jobs_left > 0 || (app.is_mounted && !(app.stable_diffusion.is_input_avail)))" class="l_button button_small button_colored">Stopping</div>
+             </b-dropdown-form>
+            
+        </b-dropdown>
+
+       
+
+     <!--    <span class="title_bar_icon"> 
+            <svg width="16" height="20" viewBox="0 0 16 20" fill="none" xmlns="http://www.w3.org/2000/svg">
+              <path :d="icon_library['share']"  />
+            </svg>
+        </span>
+
+         <span class="title_bar_icon"> 
+            <svg width="16" height="20" viewBox="0 0 16 20" fill="none" xmlns="http://www.w3.org/2000/svg">
+              <path :d="icon_library['share']" />
+            </svg>
+         </span> -->
+
+         <b-dropdown right variant="link" size="sm" toggle-class="text-decoration-none" no-caret>
+                <template #button-content>
+                   <span class="title_bar_icon" > 
+                        <font-awesome-icon   icon="ellipsis-v" style="zoom:1.15"/>
+                     </span>
+                </template>
+                
+                <b-dropdown-item-button @click="show_help" >Help</b-dropdown-item-button>
+                <b-dropdown-item-button @click="open_url('https://discord.gg/t6rC5RaJQn')"  >Start Discord Chat</b-dropdown-item-button>
+                <b-dropdown-item-button  @click="app.functions.switch_page('Logs')" >Show Logs</b-dropdown-item-button>
+
+                <b-dropdown-item-button @click="open_url('https://diffusionbee.com/MODEL_LICENSE.txt')" >Model License</b-dropdown-item-button>
+                <b-dropdown-item-button @click="open_url('https://diffusionbee.com/OPEN_SOURCE_LICENSES.txt')" >Open-source Licences</b-dropdown-item-button>
+
+                <b-dropdown-item-button @click="show_about"  >About</b-dropdown-item-button>
+                <b-dropdown-item-button  @click="app.functions.switch_page('ContactUs')" >Contact Us</b-dropdown-item-button>
+                <b-dropdown-item-button  @click="app.functions.switch_page('ContactUs')" >Report Issues</b-dropdown-item-button>
+
+
+                <b-dropdown-item-button   @click="app.functions.switch_page('Settings')"  >Settings</b-dropdown-item-button>
+
+                <b-dropdown-item-button @click="close_window"  >Close</b-dropdown-item-button>
+                <!-- #TODO set these menu items via python -->
+                
+         </b-dropdown>
+    </div>
+</template>
+<script>
+
+import { icon_library } from "../components_bare/icon_library.js"
+import MoonLoader from 'vue-spinner/src/MoonLoader.vue'
+
+
+export default {
+    name: 'MainToolbar',
+    props: { app:Object , asset_details:Object },
+    components: {MoonLoader},
+    mounted() {
+
+    },
+    data() {
+        return {
+            icon_library:icon_library
+        };
+    },
+    methods: {
+        stop_all(){
+            this.app.stable_diffusion_manager.stop_all() 
+        },
+
+        show_about(){
+            window.ipcRenderer.sendSync('show_about', '');
+        },
+        show_help(){
+            window.ipcRenderer.sendSync('open_url', "https://diffusionbee.com");
+        } ,
+
+        open_url(url){
+            window.ipcRenderer.sendSync('open_url', url);
+        } ,
+
+        close_window(){
+            window.ipcRenderer.sendSync('close_window', '');
+        }
+
+    },
+
+    computed: {
+
+        is_sd_busy(){
+            return this.app.is_mounted && !(this.app.stable_diffusion.is_input_avail)
+        },
+
+        n_jobs_left(){
+
+            if(!this.app.is_mounted)
+                return 0
+            let n = 0
+            if(this.app.stable_diffusion_manager.queue.current_group){
+                for(let job of this.app.stable_diffusion_manager.queue.current_group.jobs)
+                    if(job.job_state != 'done')
+                        n += 1
+            }
+
+            if(this.app.stable_diffusion_manager.queue.groups_todo){
+                for(let group of this.app.stable_diffusion_manager.queue.groups_todo)
+                    n += group.jobs.length
+            }
+
+            return n;
+        },
+
+        is_stopping(){
+            if(this.app.stable_diffusion_manager   )
+                return this.app.stable_diffusion_manager.is_stopping
+            return false
+        }
+    } 
+}
+</script>
+<style>
+</style>
+<style scoped>
+    .title_bar_icon{
+        max-height: 50px;
+    }
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components/Outpainting.vue b/electron_app/src/components/Outpainting.vue
deleted file mode 100644
index f3d59300..00000000
--- a/electron_app/src/components/Outpainting.vue
+++ /dev/null
@@ -1,570 +0,0 @@
-<template>
-     <div  class="animatable_content_box ">
-
-        <div class="content_toolbox" style="margin-bottom: 5px; margin-top: -5px ;">
-            <div class="l_button" v-if="stable_diffusion.is_input_avail"  style="float:right "  @click="init_state"> Reset</div>
-            <div class="l_button"  v-if="is_stage_modified && stable_diffusion.is_input_avail"   style="float:right "  @click="save_image"> Save Image </div>
-            <div v-if="undo_history.length > 0 && stable_diffusion.is_input_avail " class="l_button"  style="float:right " @click="do_undo" > Undo </div>
-            <div class="l_button" v-if="stable_diffusion.is_input_avail"  style="float:right "  @click="add_ext_img"> Add Image</div>
-            <div class="l_button" v-if="stable_diffusion.is_input_avail && is_stage_modified"  style="float:right "  @click="is_eraser_enabled=!is_eraser_enabled; freeze_last_resizable_img()"> {{is_eraser_enabled?'Stop':'Start'}} Erasing</div>
-            
-        </div>
-       
-        <div id="outpainting_container" @drop.prevent="onDragFile" @dragover.prevent style="  ">
-        </div>
-        <textarea 
-                    v-model="prompt" 
-                    placeholder="Enter your prompt here" 
-                    style="border-radius: 12px 12px 12px 12px; width: calc(100%); resize: none; " 
-                    class="form-control outpaint_textbox"  
-                    v-bind:class="{ 'disabled' : !stable_diffusion.is_input_avail}"
-                    :rows="is_negative_prompt_avail ? 1:2">
-        </textarea>
-        <textarea 
-                    v-if="is_negative_prompt_avail"
-                    v-model="negative_prompt" 
-                    placeholder="Enter your negative prompt here" 
-                    style="border-radius: 12px 12px 12px 12px; width: calc(100%);font-size:13px; margin-top:14px; resize: none; " 
-                    class="form-control outpaint_textbox"  
-                    v-bind:class="{ 'disabled' : !stable_diffusion.is_input_avail}"
-                    :rows="is_negative_prompt_avail ? 1:2">
-        </textarea>
-
-       
-        
-        
-        <div v-if="stable_diffusion.is_input_avail" style="margin-top: 15px">
-            <SDOptionsDropdown :style="is_negative_prompt_avail?'margin-top:-43px':''" :options_model_values="this_object"  :elements_hidden="[ 'num_imgs', 'inp_img_strength', 'batch_size', 'guidence_scale', 'img_h', 'custom_model', 'seed']"> </SDOptionsDropdown>
-            <div  class="l_button button_medium button_colored" style="float:right ; " @click="generate()" >Generate</div>
-        </div>
-        <span v-else-if="stable_diffusion.generated_by=='outpainting'"   >
-            <div v-if="is_stopping" class="l_button button_medium button_colored" style="float:right; float:right ; margin-top: 20px; " @click="stop_generation">Stopping ...</div>
-            <div v-else class="l_button button_medium button_colored" style="float:right; float:right ; margin-top: 20px; " @click="stop_generation">Stop</div>
-        </span>
-
-
-        <div v-if="backend_error" style="color:red ; margin-top:50px;">
-            <div class="center loader_box">
-                <p>Error: {{backend_error}} </p>
-            </div>
-        </div>
-
-        <div v-if="!stable_diffusion.is_input_avail && stable_diffusion.generated_by=='outpainting'">
-            <LoaderModal :loading_percentage="done_percentage" loading_title="Generating" :loading_desc="stable_diffusion.generation_state_msg" :remaining_times="stable_diffusion.remaining_times"></LoaderModal>
-        </div>
-
-        <p style="opacity:0.5; zoom:0.8; float:left; max-width: calc(100vw - 200px); margin-bottom: 0; "> Please describe image you want to draw in the box. </p>
-
-     </div>
-</template>
-<script>
-import Konva from 'konva';
-import LoaderModal from '../components_bare/LoaderModal.vue'
-import Vue from 'vue'
-import SDOptionsDropdown from '../components_bare/SDOptionsDropdown.vue'
-
-function onVisible(element, callback) {
-  new IntersectionObserver((entries, observer) => {
-    entries.forEach(entry => {
-      if(entry.intersectionRatio > 0) {
-        callback(element);
-        observer;
-        // observer.disconnect();
-      }
-    });
-  }).observe(element);
-}
-
-
-export default {
-    name: 'Outpainting',
-    props: {
-        app_state : Object   , 
-        stable_diffusion : Object,
-    },
-    components: {LoaderModal, SDOptionsDropdown},
-    mounted() {
-           this.init_state();
-           this.resize_stage()
-    },
-    data() {
-        return {
-            stage : undefined,
-            stage_w : 1000 , 
-            stage_h : 400 ,
-            prompt : "" ,
-
-            undo_history : [],
-            is_stage_modified: false, 
-            is_stopping : false,
-            backend_error : "",
-            done_percentage : -1,
-
-            is_earasing: false, 
-            is_eraser_enabled: false,
-            is_negative_prompt_avail : false,
-            negative_prompt : "",
-            selected_model : 'Default'
-        };
-    },
-    watch: {
-        'stable_diffusion.is_input_avail': {
-            handler: function() {
-                if(this.stable_diffusion.is_input_avail && (!this.is_eraser_enabled))
-                    this.box.draggable(true)
-                else
-                    this.box.draggable(false)
-            },
-            deep: true
-        } , 
-        'is_eraser_enabled' : {
-            handler: function() {
-                if(this.stable_diffusion.is_input_avail && (!this.is_eraser_enabled))
-                    this.box.draggable(true)
-                else
-                    this.box.draggable(false)
-            },
-            deep: true
-        } , 
-    },
-    computed:{
-        this_object(){
-            return this;
-        }
-    },
-    methods: {
-        init_state(){
-            let that = this;
-            this.stage_h = this.stage_w / (window.innerWidth  / ( window.innerHeight - 230 ));
-
-            this.prompt = ""
-
-            this.canvas_bg_color = "#F2F2F2"
-            let box_color = '#4070f7'
-            if (window.matchMedia && window.matchMedia('(prefers-color-scheme: dark)').matches) {
-                // dark mode
-                this.canvas_bg_color = "#1c1c1c"
-            }
-
-            this.freeze_last_resizable_img()
-
-            this.undo_history = []
-            this.is_stage_modified = false
-
-
-            this.stage = new Konva.Stage({
-                container: 'outpainting_container',   // id of container <div>
-                width: this.stage_w,
-                height: this.stage_h
-            });
-
-            let rectX = this.stage.width() / 2 - 100;
-            let rectY = this.stage.height() / 2 - 100;
-
-            let box = new Konva.Rect({
-                x: rectX,
-                y: rectY,
-                width: 200,
-                height: 200,
-                stroke: box_color,
-                strokeWidth: 1,
-                draggable: true,
-            });
-            this.box = box;
-
-            // add cursor styling
-            box.on('mouseover', function () {
-                if(!that.is_eraser_enabled)
-                    document.body.style.cursor = 'move';
-                else 
-                    document.body.style.cursor = 'default';
-
-            });
-            box.on('mouseout', function () {
-                document.body.style.cursor = 'default';
-            });
-
-            this.alpha_layer = new Konva.Layer({opacity	:1 });
-            this.stage.add(this.alpha_layer);
-
-            let bg = new Konva.Rect({
-                                x: 0,
-                                y: 0,
-                                width: this.stage.width(),
-                                height: this.stage.height(),
-                                fill : "white",
-                            });
-            this.alpha_layer.add(bg);
-                    
-
-            this.images_layer = new Konva.Layer({opacity:1});
-            this.stage.add(this.images_layer);
-
-            bg = new Konva.Rect({
-                                x: 0,
-                                y: 0,
-                                width: this.stage.width(),
-                                height: this.stage.height(),
-                                fill : this.canvas_bg_color,
-                            });
-            this.images_layer.add(bg);
-
-            
-
-
-            this.box_layer = new Konva.Layer();
-            this.stage.add(this.box_layer);
-            this.box_layer.add(box);
-
-            let tr = new Konva.Transformer({keepRatio : true , rotateEnabled:false , flipEnabled:false, enabledAnchors: ['top-left', 'top-right', 'bottom-left', 'bottom-right']  });
-            this.box_layer.add(tr);
-            tr.nodes([box]);
-            
-            box.on('transform', function () {
-                box.setAttrs({
-                    width: Math.round(box.width() * box.scaleX()),
-                    height: Math.round(box.height() * box.scaleY()),
-                    scaleX: 1,
-                    scaleY: 1
-                });
-            });
-            
-            this.resize_stage()
-            
-
-            window.addEventListener('resize', this.resize_stage);
-            onVisible(document.querySelector("#outpainting_container") , this.resize_stage )
-
-            this.init_eraser()
-        },
-
-        init_eraser(){
-            let that = this;
-            this.stage.on('mousedown touchstart', function () {
-                if(!that.is_eraser_enabled)
-                    return;
-                that.is_earasing = true;
-                let pos = that.stage.getPointerPosition();
-                let sx = that.stage.scale().x
-                let sy = that.stage.scale().y
-                
-                that.lastLine = new Konva.Line({
-                    stroke: that.canvas_bg_color,
-                    strokeWidth: 15,
-                    globalCompositeOperation: 'source-over',
-                    // round cap for smoother lines
-                    lineCap: 'round',
-                    lineJoin: 'round',
-                    // add point twice, so we have some drawings even on a simple click
-                    points:[pos.x/sx, pos.y/sy, pos.x/sx, pos.y/sy],
-                });
-
-                
-
-                that.lastLine_alpha = new Konva.Line({
-                    stroke: 'white',
-                    strokeWidth: 20,
-                    globalCompositeOperation: 'source-over',
-                    
-                    // round cap for smoother lines
-                    lineCap: 'round',
-                    lineJoin: 'round',
-                    // add point twice, so we have some drawings even on a simple click
-                    points: [pos.x/sx, pos.y/sy, pos.x/sx, pos.y/sy],
-                });
-
-                that.undo_history.push({alpha : that.lastLine_alpha  , img : that.lastLine })
-
-
-                that.images_layer.add(that.lastLine);
-                that.alpha_layer.add(that.lastLine_alpha)
-            });
-
-
-            this.stage.on('mouseup touchend', function () {
-                that.is_earasing  = false;
-                that.is_eraser_enabled = false;
-            });
-
-            this.stage.on('mousemove touchmove', function () {
-                if (! that.is_earasing  ) {
-                    return;
-                }
-                if(!that.is_eraser_enabled)
-                    return;
-
-                let sx = that.stage.scale().x
-                let sy = that.stage.scale().y
-                const pos = that.stage.getPointerPosition();
-                let newPoints = that.lastLine.points().concat([pos.x/sx, pos.y/sy]);
-                that.lastLine.points(newPoints);
-                that.lastLine_alpha.points(newPoints);
-            });
-
-        },
-
-        freeze_last_resizable_img(){
-            if(this.last_resizable_img){
-                this.last_resizable_img.img.draggable(false)
-                this.last_resizable_img.tr.destroy()
-                this.last_resizable_img = undefined
-            }
-        },
-
-        resize_stage() {
-            let container = document.querySelector('#outpainting_container');
-
-            // now we need to fit stage into parent container
-            let containerWidth = container.offsetWidth;
-            if(containerWidth < 10 )
-                return;
-
-            // but we also make the full scene visible
-            // so we need to scale all objects on canvas
-            let scale = containerWidth / this.stage_w;
-
-            this.stage.width(this.stage_w * scale - 5 );
-            this.stage.height(this.stage_h * scale);
-            this.stage.scale({ x: scale, y: scale });
-        } , 
-
-
-        add_img_to_stage(img_path, is_resizable  ){
-            
-            let that = this;
-            let scale =  that.box.scaleX()
-
-            this.freeze_last_resizable_img()
-
-            Konva.Image.fromURL('file://'+ img_path , function (imgg) {
-            
-
-                imgg.setAttrs({
-                    x: that.box.x(),
-                    y: that.box.y(),
-                    scaleX: scale,
-                    scaleY: scale,
-                    });
-
-
-                if (imgg.width() == imgg.height()){
-                    imgg.setAttrs({
-                        width: that.box.width(),
-                        height: that.box.height(),
-                    });
-                }
-                
-                
-                that.images_layer.add(imgg);
-
-                let box = new Konva.Rect({
-                                x: imgg.x()+2,
-                                y: imgg.y()+2,
-                                width: imgg.width()-4/scale,
-                                height: imgg.height()-4/scale,
-                                scaleX: scale,
-                                scaleY: scale ,
-                                fill : "black",
-                                strokeWidth : 0,
-                            });
-
-
-                that.alpha_layer.add(box);
-                that.undo_history.push({alpha : box , img : imgg })
-                that.is_stage_modified = true
-
-                if(is_resizable){
-                    imgg.draggable(true)
-                    let tr = new Konva.Transformer({keepRatio : true , rotateEnabled:false , flipEnabled:false  });
-                    that.images_layer.add(tr);
-                    tr.nodes([imgg]);
-                    that.last_resizable_img = { img: imgg, tr:tr }
-
-                    imgg.on('transformend',     function () {
-                        box.height(imgg.height() - 4/imgg.scaleY())
-                        box.width(imgg.width() - 4/imgg.scaleX())
-                        box.x(imgg.x() + 2)
-                        box.y(imgg.y() + 2)
-                        box.scaleY(imgg.scaleY() )
-                        box.scaleX(imgg.scaleX() )
-                    });
-
-                    imgg.on('dragmove',     function () {
-                        box.height(imgg.height() - 4/imgg.scaleY())
-                        box.width(imgg.width() - 4/imgg.scaleX())
-                        box.x(imgg.x() + 2)
-                        box.y(imgg.y() + 2)
-                        box.scaleY(imgg.scaleY() )
-                        box.scaleX(imgg.scaleX() )
-                    });
-
-
-                }
-
-
-            });
-        } , 
-
-        add_ext_img(){
-            if( !this.stable_diffusion.is_input_avail)
-                return;
-            let img_path = window.ipcRenderer.sendSync('file_dialog',  'img_file' );
-            if(img_path && img_path != 'NULL'){
-                this.add_img_to_stage(img_path, true)
-            }
-        },
-
-        get_img_of_box(is_mask=false){
-            let s = this.stage.scale().x
-            let layer;
-            if(is_mask)
-                layer = this.alpha_layer
-            else
-                layer = this.images_layer
-
-            let data_uri = layer.toDataURL({ 
-                pixelRatio: 3 , 
-                x:  this.box.x() * s  , 
-                y: this.box.y()  * s   , 
-                width: this.box.width() * s , 
-                height: this.box.height() * s } );
-            let img_url = window.ipcRenderer.sendSync('save_b64_image',  data_uri , true );
-            console.log(img_url)
-            return img_url
-        } , 
-
-        stop_generation(){
-            this.is_stopping = true;
-            this.stable_diffusion.interupt();
-        },
-
-        save_image(){
-            let img_b64 = this.images_layer.toDataURL({ pixelRatio: 3})
-
-            let out_path = window.ipcRenderer.sendSync('save_dialog' );
-            if(!out_path)
-                return
-            let org_path = window.ipcRenderer.sendSync('save_b64_image',  img_b64 , true );
-            org_path = org_path.replaceAll("file://" , "")
-            window.ipcRenderer.sendSync('save_file', org_path+"||" +out_path);
-
-
-        },
-
-        onDragFile(e) {
-           if (!this.stable_diffusion.is_input_avail)
-               return;
-           if (!e.dataTransfer.files[0].type.startsWith('image/'))
-               return;
-           let img_path = e.dataTransfer.files[0].path;
-           this.add_img_to_stage(img_path, true)
-       },
-
-        do_undo(){
-            this.freeze_last_resizable_img()
-            let im = this.undo_history.pop()
-            im.img.destroy()
-            im.alpha.destroy()
-
-        },
-
-        generate(){
-
-            
-
-            if(this.prompt == ""){
-                Vue.$toast.default('You need to enter a prompt')
-                return; 
-            }
-                
-
-            if(this.last_resizable_img){
-                this.freeze_last_resizable_img()
-                setTimeout(this.generate, 100); // there is delay coz the rectangle wont go away
-                return;
-            }
-
-            let img_path = this.get_img_of_box(false)
-            let mask_path = this.get_img_of_box(true)
-
-            
-
-            this.prev_canvas_b64 = this.images_layer.toDataURL()
-
-            let seed = 0;
-            if(this.seed)
-                seed = Number(this.seed);
-            else
-                seed = Math.floor(Math.random() * 100000);
-
-            let params = {
-                prompt : this.prompt , 
-                W : -1 , 
-                H : -1, 
-                seed :seed,
-                mask_image: mask_path ,
-                input_image : img_path,
-                model_id: 1 , 
-                is_inpaint : true,
-            }
-
-            this.backend_error = "";
-            this.done_percentage = -1;
-            this.is_stopping = false;
-
-            if(this.is_negative_prompt_avail)
-                params['negative_prompt'] = this.negative_prompt;
-
-            let that = this;
-
-            let callbacks = {
-                on_img(img_path){
-                    that.add_img_to_stage(img_path)
-                },
-                on_progress(p){
-                    that.done_percentage = p;
-                    
-                },
-                on_err(err){
-                    that.backend_error = err;
-                },
-            }
-
-            if(this.is_negative_prompt_avail)
-                params['negative_prompt'] = this.negative_prompt;
-
-            if(this.stable_diffusion)
-                this.stable_diffusion.text_to_img(params, callbacks, 'outpainting');
-
-
-        }
-
-    },
-}
-</script>
-<style>
-    #outpainting_container{
-        /* background-color: #e5e5f7; */
-        /* opacity: 0.8; */
-        /* background-image: radial-gradient( rgba(255,255,255,0.25) 0.5px, rgba(0,0,0,0) 0.5px); */
-        background-size: 10px 10px;
-        border-color: rgb(206, 212, 218);
-        border-width: 1px;
-        border-style: solid;
-
-    }
-
-    @media (prefers-color-scheme: dark) {
-        #outpainting_container{
-            border-color: #606060
-        }
-    }
-
-    .outpaint_textbox{
-        margin-top: 15px; 
-        max-width: calc(100vw - 160px);
-        float:left
-    }
-</style>
-<style scoped>
-</style>
\ No newline at end of file
diff --git a/electron_app/src/components/PagesRouter.vue b/electron_app/src/components/PagesRouter.vue
new file mode 100644
index 00000000..80c372c8
--- /dev/null
+++ b/electron_app/src/components/PagesRouter.vue
@@ -0,0 +1,173 @@
+<template>
+    
+    <div style=" width: 100%; height: 100%;">
+        
+        <!-- always open pages -->
+        <div v-for="page_id in Object.keys(always_on_pages)"  :key="page_id" style="display:none" class="tpage"   :class="{ bl_display : current_open_page_id ===  page_id }">
+             <component  :app="app" :is="page_id" :ref="page_id"></component>
+        </div>
+
+        <!-- applets -->
+        <div v-for="applet_id in Object.keys(app.app_state.registered_ext_applets)"  :key="applet_id" style="display:none" class="tpage"   :class="{ bl_display : current_open_page_id ===  applet_id }">
+             <AppletPage 
+                :app="app" 
+                :applet_id="applet_id" 
+                :ref="applet_id" 
+                :input_form="app.app_state.registered_ext_applets[applet_id].inputs" 
+                :output_form="app.app_state.registered_ext_applets[applet_id].outputs" 
+                :is_stop_avail="app.app_state.registered_ext_applets[applet_id].is_stop_avail"
+            > </AppletPage>
+        </div>
+
+
+    </div>
+
+</template>
+<script>
+
+
+import Txt2Img from "../pages/Txt2Img.vue"
+import Img2Img from "../pages/Img2Img.vue"
+import Training from "../pages/Training.vue"
+import Inpainting from "../pages/Inpainting.vue"
+
+import History from "../pages/History.vue"
+import Homepage from "../pages/Homepage.vue"
+import ModelStore from "../pages/ModelStore.vue"
+import Logs from "../pages/Logs.vue"
+import ContactUs from "../pages/ContactUs.vue"
+
+import Settings from "../pages/Settings.vue"
+import PostProcessImage from "../pages/PostProcessImage.vue"
+import AppletPage from "../components/AppletPage.vue"
+
+import Vue from 'vue'
+
+export default {
+    name: 'PagerRouter',
+    props: {
+        app:Object, 
+    },
+    components: {
+        Txt2Img, Img2Img , Inpainting , AppletPage , History, Homepage , ModelStore, 
+        Logs, ContactUs , Settings, PostProcessImage, Training
+    },
+    mounted() {
+        this.app.functions.switch_page = this.switch_page; 
+        this.app.all_pages_ready = true;
+    },
+    data() {
+
+        let always_on_pages = { Homepage:Homepage  , Txt2Img:Txt2Img , Img2Img:Img2Img , 
+            Inpainting:Inpainting , PostProcessImage:PostProcessImage  , ModelStore:ModelStore , History:History, Logs:Logs, Settings:Settings , Training:Training, ContactUs:ContactUs  }
+
+        let last_opened_timmings = {}
+
+        let v =  window.localStorage.getItem( 'last_opened_times_7768' )
+        if(v){
+            last_opened_timmings = JSON.parse(v)
+        }
+
+        return {
+            current_open_page_id : 'Homepage',
+            last_opened_timmings : last_opened_timmings,
+            always_on_pages : always_on_pages         };
+    },
+    methods: {
+         switch_page(page_id){
+            this.current_open_page_id = page_id;
+            this.app.current_selected_tab = page_id
+            this.app.current_applet_title = this.current_applet_title()
+
+            Vue.set(this.last_opened_timmings , page_id , Date.now()  )
+
+            window.localStorage.setItem('last_opened_times_7768', JSON.stringify(this.last_opened_timmings));
+
+        }, 
+
+        current_applet_title(){
+            for( let el of this.all_applet_items){
+                if( el.id == this.current_open_page_id ){
+                    return el.text;
+                }
+            }
+            return ""
+        },
+    },
+    computed: {
+
+        
+
+        all_applet_items(){
+            let items = []
+            for(let page_id of Object.keys(this.always_on_pages) ){
+                    items.push( { id: page_id , 
+                        text : this.always_on_pages[page_id].title , 
+                        description: this.always_on_pages[page_id].description, 
+                        icon : this.always_on_pages[page_id].icon , 
+                        img_icon:this.always_on_pages[page_id].img_icon , 
+                        sidebar_show: this.always_on_pages[page_id].sidebar_show ,  
+                        home_category:this.always_on_pages[page_id].home_category } )
+            }
+
+            // todo : in future count the last used N applets, and then show them on sidebar, and sort them alphabetically
+            for(let applet_id of Object.keys(this.app.app_state.registered_ext_applets)){
+                let applet = this.app.app_state.registered_ext_applets[applet_id]
+                items.push( { id: applet.id  , 
+                    text : applet.title , 
+                    icon : applet.icon , 
+                    description : applet.description , 
+                    home_category: applet.home_category,
+                    sidebar_show: applet.sidebar_show,
+                    img_icon:( applet.img_icon ? require(("../assets/imgs/page_icon_imgs/").concat(applet.img_icon) ) : undefined )
+                } )
+            }
+
+            return items
+        },
+
+        all_sidebar_items(){
+            let always_on_items =  this.all_applet_items.filter(x => x.sidebar_show == "always");
+
+            let always_on_items_dict = {}
+            for(let a of always_on_items)
+                always_on_items_dict[a.id] = a 
+
+            let never_on_items =  this.all_applet_items.filter(x => x.sidebar_show == "never");
+
+            let never_on_items_dict = {}
+            for(let a of never_on_items)
+                never_on_items_dict[a.id] = a 
+
+            let llist = []
+            for(let k in this.last_opened_timmings){
+                if(always_on_items_dict[k] == undefined && never_on_items_dict[k] == undefined)
+                    llist.push([k , this.last_opened_timmings[k] ])
+            }
+            
+
+            llist = llist.sort((a, b) => b[1] - a[1]) // sort from large time to small time
+            llist = llist.slice(0,5)
+            llist = llist.map( x => x[0])            
+
+            let last_5_opened_items =  this.all_applet_items.filter(x => llist.includes(x.id) );
+
+            return always_on_items.concat(last_5_opened_items);
+
+        }
+    }
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+.tpage{
+    width: 100%;
+    height: 100%;
+}
+
+.bl_display{
+    display:block !important;
+}
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components/SDImageGenerationApplet.vue b/electron_app/src/components/SDImageGenerationApplet.vue
new file mode 100644
index 00000000..886734c3
--- /dev/null
+++ b/electron_app/src/components/SDImageGenerationApplet.vue
@@ -0,0 +1,163 @@
+<template>
+
+    <BasicSDApplet
+        :app=app 
+        :input_form=form_data
+        :sd_options=sd_options
+        :name=name
+        :form_tags=form_tags
+        :required_assets=required_assets
+        ref="basic_sd_applet"
+    >   
+        
+        <template v-slot:input_buttons>
+            <div v-if="app.stable_diffusion_manager.is_ready" @click="generate" class="l_button button_colored button_medium" style="float:right">Generate</div>
+
+            <div v-else-if="is_input_changed_after_last_run " @click="generate" class="l_button button_colored button_medium" style="float:right">Add to Queue</div>
+
+            <div v-if="(!app.stable_diffusion_manager.is_ready) && !is_stopping"  @click="stop_all" class="l_button button_colored button_medium" style="float:right">Stop all</div>
+            <div v-if="(!app.stable_diffusion_manager.is_ready) && is_stopping" class="l_button button_colored button_medium" style="float:right">Stopping ...</div>
+
+        </template>
+
+        <template v-slot:output_workpace>
+            
+            
+            
+            
+            <GenerationGallery  :app="app" ref="gallery"> </GenerationGallery>
+        </template>
+
+    </BasicSDApplet>
+
+</template>
+<script>
+
+import GenerationGallery from "./GenerationGallery.vue"
+import BasicSDApplet from "../components/BasicSDApplet.vue"
+import { controlnet_check_inputs , controlnet_proc_form_outputs , controlnet_required_assets } from "../utils/controlnet_frontend_utils.js"
+import Vue from 'vue'
+
+export default {
+    name: 'SDImageGenerationApplet.vue',
+    props: {
+        app:Object, 
+        form_data: Array,
+        name:String,
+        form_tags: Array,
+        postprocess_form_options_fn: Function, // if you want to append   modify the input options valus from form 
+        check_options_input_fn : Function, // if you want to add checks to the inpus 
+    },
+    components: { GenerationGallery , BasicSDApplet  },
+    mounted() {
+        this.is_mounted = true
+    },
+    data() {
+        return {
+            sd_options : {},
+            is_input_changed_after_last_run : false, 
+            is_mounted : false,
+        };
+    },
+    methods: {
+        generate(){
+
+            this.is_input_changed_after_last_run = false
+
+            if(!this.$refs.basic_sd_applet.check_input_form_n_show_error()){
+                return
+            }
+
+            if(this.check_options_input_fn){
+                if(!(this.check_options_input_fn()))
+                    return
+            }
+
+            if(!controlnet_check_inputs(this, Vue)){
+                return
+            }
+            
+            let sd_options_object = this.get_sd_form_outputs()
+            this.app.stable_diffusion_manager.add_job(sd_options_object, this.sd_options  ,  this.$refs.gallery)
+        }, 
+
+        get_sd_form_outputs(){
+            let options =  this.$refs.basic_sd_applet.get_sd_form_outputs()
+            if(this.postprocess_form_options_fn)
+                options = this.postprocess_form_options_fn(options)
+
+            controlnet_proc_form_outputs(this , options)
+
+            return options
+        },
+
+        stop_all(){
+            this.app.stable_diffusion_manager.stop_all() 
+        },
+        load_options(options){
+            this.$refs.basic_sd_applet.load_options(options)
+        } , 
+
+        generate_similar_images(options){
+            options = JSON.parse(JSON.stringify(options))
+            if(!this.is_sd_ready){
+                this.app.show_toast('Currently some images are already being generated. Please wait for them to finish.')
+                return false
+            }
+            this.$refs.basic_sd_applet.$refs.form.reset_to_default()
+            options.raw_form_options.is_adv_mode = true
+            options.raw_form_options.small_mod_seed = Math.floor(Math.random()*1000) + 1 
+            options.is_adv_mode = true
+            options.small_mod_seed = Math.floor(Math.random()*1000)+ 1 
+            options.num_imgs = 4
+            options.raw_form_options.num_imgs = 4
+            this.load_options(options)
+            Vue.nextTick(this.generate)
+            return true;
+        } ,
+
+    },  
+
+    computed:{
+        all_tags(){
+            let l = this.form_tags.concat( this.sd_options.is_adv_mode ? ['advanced']:[]  )
+            return l
+        } , 
+        required_assets(){
+            // what is left to download
+            let to_download = []
+
+            controlnet_required_assets(this , to_download)
+            return to_download;
+        } , 
+        is_sd_ready(){
+            if(this.app.stable_diffusion_manager)
+                return this.app.stable_diffusion_manager.is_ready
+            return false
+        } , 
+
+        is_stopping(){
+            if(this.app.stable_diffusion_manager   )
+                return this.app.stable_diffusion_manager.is_stopping
+            return false
+        }
+    },
+
+    watch : {
+       
+        'sd_options': {
+            handler: function() {
+                this.is_input_changed_after_last_run = true
+            },
+            deep: true
+        } , 
+
+    },
+
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components/Settings.vue b/electron_app/src/components/Settings.vue
deleted file mode 100644
index 1cc3c3ff..00000000
--- a/electron_app/src/components/Settings.vue
+++ /dev/null
@@ -1,190 +0,0 @@
-<template>
-    <div  class="animatable_content_box ">
-
-        <div  v-if="!is_custom_model_loading">
-            <h1>Settings</h1>
-            <br>
-           <h2>General Settings</h2>
-            <br>
-            <div class="setting_box">
-            <div class="settings_left">
-            <h3>Notification sound</h3>
-            <p>To play a notification sound when generation of an image is completed</p>
-            </div>
-            <hr>
-            <div style="float:right;margin-right: 9px;align-self: center;" >
-                <label class="switch">
-                    <input type="checkbox" v-model="app_state.app_data.settings.notification_sound" checked>
-                    <span class="toggle round"></span>
-                </label>
-            </div>
-            </div>
-            <hr>
-             <!-- 
-            <div class="setting_box">
-            <div class="settings_left">
-            <h2>Allow NSFW Content</h2>
-            <p>Allows image generation considered NSFW</p>
-            </div>
-            <hr>
-            <div style="float:right;margin-right: 9px;align-self: center;" >
-                <label class="switch">
-            <input type="checkbox" v-model="app_state.app_data.settings.nsfw_filter">
-            <span class="toggle round"></span>
-            </label>
-            </div>
-            </div>
-            <hr> -->
-            <div class="l_button button_colored" style="float:right" @click="add_model"  >Add New Model</div>
-
-            <h2>Custom Models</h2>
-            <p style="zoom:1"> Supported models : SD1.x , SD2.x - .ckpt and .safetensors  </p>
-            <p style="zoom:0.8"> Note: If you import SD2.x 768 model, you might need to use ddim_v sampler to get better results.    </p>
-
-            
-            <!-- <br> -->
-            <hr> 
-            <div v-for="model in Object.values(this.app_state.app_data.custom_models)" :key="model.name">
-                <div class="l_button" @click="delete_model(model.name)" style="float:right">Remove</div>
-                <p> Name : {{model.name}} </p>
-                <p> Path : {{model.orig_path}} </p>
-                <hr> 
-            </div>
-        </div>
-        <div v-else>
-            <LoaderModal :loading_percentage="-1" loading_title="Importing model"></LoaderModal>
-        </div>
-
-    </div>
-</template>
-<script>
-import LoaderModal from '../components_bare/LoaderModal.vue'
-import Vue from 'vue'
-
-
-export default {
-    name: 'Settings',
-    props: {
-        app_state : Object , 
-    },
-    components: {LoaderModal},
-    mounted() {
-
-    },
-    data() {
-        return {
-            is_custom_model_loading:false,
-        };
-    },
-    methods: {
-        delete_model(k){
-            let model_path = this.app_state.app_data.custom_models[k].path;
-            window.ipcRenderer.sendSync('delete_file',  model_path );
-            Vue.delete( this.app_state.app_data.custom_models , k );
-        },
-        add_model(){
-            let that = this;
-            
-            let pytorch_model_path = window.ipcRenderer.sendSync('file_dialog',  "weights_file" );
-            if(!pytorch_model_path)
-                return;
-
-            if(pytorch_model_path == "NULL")
-                return;
-
-            let model_name = pytorch_model_path.replaceAll("\\" , "/").split("/");
-            model_name = model_name[model_name.length - 1].split(".")[0]
-
-
-            if(model_name.trim() == ""){
-                alert("Put non empty model name");
-                return;
-            }
-
-            if(that.app_state.app_data.custom_models[model_name]){
-                alert("this model name "+ model_name +" already exists")
-                return;
-            }
-
-            that.is_custom_model_loading = true
-            window.ipcRenderer.invoke('add_custom_pytorch_models', pytorch_model_path , model_name ).then((result) => {
-                that.is_custom_model_loading = false
-                if(result.success){
-                    Vue.set( that.app_state.app_data.custom_models , model_name ,  {"name":model_name , "path": result.model_path, "orig_path" : pytorch_model_path }  );
-                } else {
-                    alert("Error " + result.error )
-                }
-                
-            })
-        }
-    },
-}
-</script>
-<style>
-</style>
-<style scoped>
-.switch {
-  position: relative;
-  display: inline-block;
-  width: 60px;
-  height: 30px;
-}
-
-.switch input { 
-  opacity: 0;
-  width: 0;
-  height: 0;
-}
-
-.toggle {
-  position: absolute;
-  cursor: pointer;
-  top: 0;
-  left: 0;
-  right: 0;
-  bottom: 0;
-  background-color: #ccc;
-  -webkit-transition: .4s;
-  transition: .4s;
-}
-
-.toggle:before {
-  position: absolute;
-  content: "";
-  height: 22px;
-  width: 23px;
-  left: 5px;
-  bottom: 4px;
-  background-color: white;
-  -webkit-transition: .4s;
-  transition: .4s;
-}
-
-input:checked + .toggle {
-  background-color: #3E7BFA;
-}
-
-
-input:checked + .toggle:before {
-  transform: translateX(27px);
-}
-
-.toggle.round {
-  border-radius: 34px;
-}
-
-.toggle.round:before {
-  border-radius: 50%;
-}
-
-
-.setting_box{
-    display: flex;
-    flex-direction: row;
-}
-
-.settings_left{
-    flex: 1 1 auto;
-}
-
-</style>
\ No newline at end of file
diff --git a/electron_app/src/components/UpscaleImage.vue b/electron_app/src/components/UpscaleImage.vue
deleted file mode 100644
index d2ba3ba4..00000000
--- a/electron_app/src/components/UpscaleImage.vue
+++ /dev/null
@@ -1,60 +0,0 @@
-@import '../assets/css/theme.css';
-
-<template>
-    <div  class="animatable_content_box ">
-
-        <div v-if="output_image">
-            
-            <center>
-                <h2>Image Upscaled 4x</h2>
-                <ImageItem :hide_dropdown="true" :app_state="app_state"  :path="output_image" :style_obj="{ 'max-height': '90%' , 'max-width': '80%' , 'margin-top': '30px' }"></ImageItem>
-            </center>
-        </div>
-        <div v-else-if="error">
-            <p>{{error}}</p>
-        </div>
-        <div v-else>
-            <LoaderModal :loading_percentage="-1" loading_title="Upscaling"></LoaderModal>
-        </div>
-    </div>
-</template>
-<script>
-
-import LoaderModal from '../components_bare/LoaderModal.vue'
-import ImageItem from '../components/ImageItem.vue'
-
-
-export default {
-    name: 'UpscaleImage',
-    props: {
-        app_state : Object , 
-    },
-    components: {LoaderModal ,  ImageItem },
-    mounted() {
-
-    },
-    data() {
-        return {
-            output_image : "",
-            error : "",
-        };
-    },
-    methods: {
-        do_upscale(in_img){
-            let that = this;
-            that.output_image = "";
-            this.error = "";
-            window.ipcRenderer.invoke('run_realesrgan', in_img.split("?")[0] ).then((result) => {
-                if(result) 
-                    that.output_image = result;
-                else
-                    that.error = "Error in upscaling this image";
-            })
-        }
-    },
-}
-</script>
-<style>
-</style>
-<style scoped>
-</style>
\ No newline at end of file
diff --git a/electron_app/src/components/ImageItem.vue b/electron_app/src/components/_REM_ImageItem.vue
similarity index 100%
rename from electron_app/src/components/ImageItem.vue
rename to electron_app/src/components/_REM_ImageItem.vue
diff --git a/electron_app/src/components/image_menu_functions.js b/electron_app/src/components/image_menu_functions.js
new file mode 100644
index 00000000..13e83b15
--- /dev/null
+++ b/electron_app/src/components/image_menu_functions.js
@@ -0,0 +1,113 @@
+
+let image_manu_functions = {}
+
+image_manu_functions['save_image'] =  function (app, image_item_data){
+	app;
+	image_item_data;
+
+	if(!image_item_data.image_url)
+        return;
+    let im_path = image_item_data.image_url.split("?")[0];
+
+    let seed = (image_item_data.params || {}).seed || ""
+
+    let suggested_fname = (image_item_data.description || "Image").substring(0, 100) + "_" + seed
+    let out_path = window.ipcRenderer.sendSync('save_dialog', suggested_fname);
+    if(!out_path)
+        return
+    let org_path = im_path.replaceAll("file://" , "")
+    window.ipcRenderer.sendSync('save_file', org_path+"||" +out_path);
+
+}
+image_manu_functions['save_image'] .text = "Save Image"
+
+image_manu_functions['send_img_2_img'] =  function (app, image_item_data){
+	app.functions.send_to_img2img( image_item_data.image_url )
+	
+}
+image_manu_functions['send_img_2_img'].text = "Send to Img2Img"
+
+image_manu_functions['send_outpaint'] =  function (app, image_item_data){
+
+	app.functions.send_to_outpaint( image_item_data.image_url )
+	
+}
+image_manu_functions['send_outpaint'].text = "Send to AI Canvas"
+
+
+
+image_manu_functions['send_inpaint'] =  function (app, image_item_data){
+
+	app.functions.send_to_inpaint( image_item_data.image_url )
+	
+}
+image_manu_functions['send_inpaint'].text = "Send to Inpainting"
+
+
+
+image_manu_functions['send_img_2_img_with_params'] =  function (app, image_item_data){
+
+	let image_params = JSON.parse(JSON.stringify(image_item_data.params))
+	app.functions.send_to_img2img( image_item_data.image_url , image_params )
+	
+}
+image_manu_functions['send_img_2_img_with_params'].text = "Send to Img2Img with params"
+
+
+
+image_manu_functions['use_params_current_page'] =  function (app, image_item_data){
+	
+	let image_params = JSON.parse(JSON.stringify(image_item_data.params))
+
+	let router = app.$refs.router 
+	let cur_page_id = router.current_open_page_id 
+
+	router.$refs[ cur_page_id ][0].$refs.sd_applet.load_options(image_params)
+	
+}
+image_manu_functions['use_params_current_page'].text = "Use parameters"
+
+
+
+image_manu_functions['copy_params'] =  function (app, image_item_data){
+	app;
+	image_item_data;
+	const remove_keys = ['generated_img', 'done_percentage', 'prompt_tokens' , 
+	'job_state', 'job_id', "raw_form_options" ,  'negative_prompt_tokens' ,"input_image_with_mask" , "model_tdict_path" ,
+	"controlnet_tdict_path" , "controlnet_inp_img_preprocesser_model_path" , "aux_output_img" ]
+	let image_params = JSON.parse(JSON.stringify(image_item_data.params))
+	for(let k of remove_keys)
+		image_params[k] = undefined;
+	window.ipcRenderer.sendSync('copy_to_clipboard' ,  JSON.stringify(image_params , null, 4))
+	
+}
+image_manu_functions['copy_params'].text = "Copy all parameters"
+
+
+
+image_manu_functions['send_to_postprocess'] =  function (app, image_item_data){
+
+	app.functions.send_to_postprocess( image_item_data.image_url )
+	
+}
+image_manu_functions['send_to_postprocess'].text = "Send to Upscaler"
+
+image_manu_functions['generate_similar_images'] =  function (app, image_item_data){
+
+	if( (!image_item_data.params) || image_item_data.params.applet_name != "txt2img"){
+		app.show_toast("Only available for images generated using TextToImage")
+		return
+	}
+
+	let router = app.$refs.router 
+
+	if(router.$refs[ "Txt2Img" ][0].$refs.sd_applet.generate_similar_images( image_item_data.params))
+		app.functions.switch_page("Txt2Img")
+	// app.functions.generate_similar_images( image_item_data.params )
+	
+}
+image_manu_functions['generate_similar_images'].text = "Generate similar images"
+
+
+
+export {image_manu_functions}
\ No newline at end of file
diff --git a/electron_app/src/components_bare/ApplicationFrame.vue b/electron_app/src/components_bare/ApplicationFrame.vue
index e248c7c8..0f49c21f 100644
--- a/electron_app/src/components_bare/ApplicationFrame.vue
+++ b/electron_app/src/components_bare/ApplicationFrame.vue
@@ -1,116 +1,106 @@
 <template>
     <div class="main_frame">
-        <div class="title_bar">
-            <div class="app_title" v-bind:class="{ 'fullscreen' :is_fullscreen||detect_windows_os() }">
-                <span @click="$emit('on_title_click',{})"> {{title}} </span>
-                <div style="float: right; margin-right: 10px; margin-top: -8.5px;" class="">
-                    <b-dropdown right variant="link" size="sm" toggle-class="text-decoration-none" no-caret>
-                        <template #button-content>
-                            <div style="" class="tab l_button">
-                                <font-awesome-icon icon="bars" />
-                            </div>
-                        </template>
-                        
-                        <b-dropdown-item-button @click="$emit('menu_item_click_help',{})">Help</b-dropdown-item-button>
-                        <b-dropdown-item-button @click="$emit('menu_item_click_discord',{})">Start Discord Chat</b-dropdown-item-button>
-                        <b-dropdown-item-button @click="selectTab('logs')">Show Logs</b-dropdown-item-button>
-
-                        <b-dropdown-item-button @click="$emit('menu_item_click_model_license',{})">Model License</b-dropdown-item-button>
-                        <b-dropdown-item-button @click="$emit('menu_item_click_oss_license',{})">Open-source Licences</b-dropdown-item-button>
-
-                        <b-dropdown-item-button @click="$emit('menu_item_click_about',{})">About</b-dropdown-item-button>
-
-                        <b-dropdown-item-button @click="selectTab('settings')">Settings</b-dropdown-item-button>
-
-                        <b-dropdown-item-button @click="$emit('menu_item_click_close',{})">Close</b-dropdown-item-button>
-                        <!-- #TODO set these menu items via python -->
-                        
-                    </b-dropdown>
-                </div>
-                <!-- <div style="float: right; margin-right:0" class="tab l_button"><font-awesome-icon icon="bars" /></div> -->
-            </div>
-        </div>
-        <div class="tabs_bar">
-            <div @click="selectTab('txt2img')" class="tab l_button" v-bind:class="{ 'button_colored' : selected_tab === 'txt2img'}">Text To Image</div>
-            <div @click="selectTab('img2img')" class="tab l_button" v-bind:class="{ 'button_colored' : selected_tab === 'img2img'}">Image To Image</div>
-            <div @click="selectTab('inpainting')" class="tab l_button" v-bind:class="{ 'button_colored' : selected_tab === 'inpainting'}">Inpainting</div>
-            <div @click="selectTab('outpainting')" class="tab l_button" v-bind:class="{ 'button_colored' : selected_tab === 'outpainting'}">Outpainting</div>
-            <div @click="selectTab('controlnet')" class="tab l_button" v-bind:class="{ 'button_colored' : selected_tab === 'controlnet'}">ControlNet</div>
-            <div @click="selectTab('history')" class="tab l_button" v-bind:class="{ 'button_colored' : selected_tab === 'history'}">History</div>
-        </div>
-        <div class="tab_content_frame">
-            <div class="tab_content">
-                
-
-                <div style="display:none"  :class="{ bl_display : selected_tab === 'txt2img'  }" >
-                    <slot name="txt2img"></slot>
-                </div>
-
-                <div  style="display:none"  :class="{ bl_display : selected_tab === 'img2img'  }" >
-                    <slot name="img2img"></slot>
-                </div>
 
-                <div  style="display:none"  :class="{ bl_display : selected_tab === 'controlnet'  }" >
-                    <slot name="controlnet"></slot>
-                </div>
 
-                <div  v-if="selected_tab === 'history' " style="display:none"  :class="{ bl_display : selected_tab === 'history'  }" >
-                    <slot name="history"></slot>
-                </div>
-                
-                
+        <div class="sidebar" v-if="is_sidebar_open">
+           <div class="sidebar_drag"> 
+                 <span class="title_bar_icon" style="float:right; margin-top: 15px; margin-right:10px; padding:0; padding-left: 13px; padding-top:2px ;" @click="is_sidebar_open = !is_sidebar_open"  > 
+                   <svg width="20" height="16" viewBox="0 0 20 16" fill="none" xmlns="http://www.w3.org/2000/svg">
+                       <path :d="icon_library['sidebar_collapse']"  />
+                    </svg>
+                </span>
 
-                <div  style="display:none"  :class="{ bl_display : selected_tab === 'upscale_img'  }" >
-                    <slot name="upscale_img"></slot>
-                </div>
+           </div>
 
-                <div style="display:none"  :class="{ bl_display : selected_tab === 'inpainting'  }" >
-                    <slot name="inpainting"></slot>
-                </div>
+           <p class="sidebar_cat"> Tools </p>
 
+           <div v-for="sidebar_item in sidebar_items" :key="sidebar_item.id" class="sidebar_item "  :class="{ sidebar_item_selected : sidebar_item.id ===  selected_sidebar_item_id }" @click="sidebar_item_on_click(sidebar_item.id)"> 
 
-                <div style="display:none"  :class="{ bl_display : selected_tab === 'outpainting'  }" >
-                    <slot name="outpainting"></slot>
-                </div>
+              <svg v-if="icon_library[sidebar_item.icon]" class="sidebar_icon" width="15px" height="15px"  style="height: 15px; width: 15px; margin-top:-3px; margin-right:3px;"  v-html="icon_library[sidebar_item.icon]"> </svg>
 
-                <div style="display:none"  :class="{ bl_display : selected_tab === 'settings'  }" >
-                    <slot name="settings"></slot>
-                </div>
+              <font-awesome-icon v-else class="sidebar_icon" :icon="sidebar_item.icon" />
 
+                 {{sidebar_item.text}}
+             </div>
 
+       
+        </div>
 
+        <div class="title_bar">
+            <div class="app_title_sidebar_collapsed" v-if="(!is_sidebar_open)"  v-bind:class="{'app_title_sidebar_collapsed_mac':is_mac}"> 
+                 <span class="title_bar_icon" style=" margin-right: -10px ; margin-left: 10px;" @click="is_sidebar_open = !is_sidebar_open" > 
+                   <svg width="20" height="16" viewBox="0 0 20 16" fill="none" xmlns="http://www.w3.org/2000/svg">
+                     <path :d="icon_library['sidebar_collapse']" />
+                   </svg>
+                 </span>
 
-                <div  v-if="selected_tab === 'logs' " style="display:none"  :class="{ bl_display : selected_tab === 'logs'  }" >
-                    <slot name="logs"></slot>
-                </div>
+                 <span class="title_bar_icon" style=" margin-right: -10px ; margin-left: 10px;" @click="on_home_click" > 
+                   <font-awesome-icon   icon="home" style="zoom:1.15; margin-bottom: -2px;"  />
+                 </span>
 
-                
-                
+            </div>
+            <div class="app_title" >
+                <span @click="$emit('on_title_click',{})"> {{title}} </span>
+            </div>
+             <div class="title_bar_icons">
+                <!-- <font-awesome-icon  class="title_bar_icon" icon="file-image" />  -->
 
+                <slot name="main_toolbar"></slot>
+            </div>
 
-             
+        </div>
+        
+        <div class="tab_content_frame">
+            <div class="tab_content">
+                <slot name="main_content"></slot>
             </div>
 
+            
+
 
         </div>
     </div>
 </template>
 <script>
 
+import { icon_library } from "./icon_library.js"
+
 export default {
     name: 'ApplicationFrame',
     components: {},
     props: {
         title: String,
+        sidebar_items: Array,
+        selected_sidebar_item_id: String,
+        sidebar_item_on_click: Function, 
+        on_home_click : Function
+
     },
 
     data: function() {
         return {
+            icon_library : icon_library , 
+
             selected_tab: 'txt2img' ,
             is_fullscreen: false ,
+            is_sidebar_open: true,
         }
     },
 
+     watch: {
+        'is_sidebar_open': {
+
+            handler: function(is_open) {
+                if(is_open){
+                    document.querySelector(':root').style.setProperty("--sidebar-width" , "200px")
+                } else {
+                    document.querySelector(':root').style.setProperty("--sidebar-width" , "0px")
+                }
+            },
+            deep: true
+        } , 
+    },
+
     mounted() {
         window.addEventListener('resize', this.detect_fullscreen);
     },
@@ -118,6 +108,12 @@ export default {
         window.removeEventListener('resize', this.detect_fullscreen);
     },
 
+    computed: {
+        is_mac(){
+            return !(this.detect_windows_os())
+        }
+    },
+
     methods: {
         selectTab(tab) {
             this.selected_tab = tab;
@@ -150,8 +146,12 @@ export default {
     --main-font-text: -apple-system, BlinkMacSystemFont, sans-serif;
     /*SF Pro Text;*/
 
+     --sidebar-width: 200px;
+     --titlebar-height: 55px;
+    
 }
 
+
 html {
     user-select: none;
     -moz-user-select: none;
@@ -163,11 +163,20 @@ body {
     font-family: var(--main-font);
 }
 
+
 .bl_display{
     display:block !important;
 }
 
 
+.sidebar_icon > path{
+    fill:#0A84FF;
+}
+
+.sidebar_icon > svg > path{
+    fill:#0A84FF;
+}
+
 .l_button {
     display: inline-block;
     margin: 0px;
@@ -247,6 +256,7 @@ body {
     ;
 }
 
+
 p {
     font-family: var(--main-font);
     font-style: normal;
@@ -317,29 +327,6 @@ img {
 }
 
 
-.animatable_content_box {
-    height: calc(100vh - 40px - 35px - 2px);
-    position: fixed;
-    width: 100%;
-    padding: 20px;
-    overflow: auto;
-}
-
-
-/*the slide transitions */
-
-.slide_show-enter-active,
-.slide_show-leave-enter {
-    transform: translateX(0);
-    transition: all .25s linear;
-
-}
-
-.slide_show-enter,
-.slide_show-leave-to {
-    transform: translateX(100%);
-    transition: all .25s linear;
-}
 
 /*overriding some styles of bootstrap dropdown*/
 .dropdown-item {
@@ -377,23 +364,97 @@ img {
 }
 
 
+.title_bar_icon{
+    color : var(--title-icon_color);
+    padding : 8px;
+    padding-right: 8px;
+    padding-left: 8px;
+
+    margin-right: 2px;
+    margin-left: 2px;
+    
+    height: calc(100% - 24px);
+    width:50px;
+    border-radius: 5px;
+
+/*    background: rgba(0, 0, 0, 0.05);*/
+    -webkit-app-region: none;
+    
+}
+
+.title_bar_icon svg{
+    fill : var(--title-icon_color);
+}
+
+.title_bar_icon:hover{
+    background-color: var(--button-highlight-one);
+}
+
+
+
+::-webkit-scrollbar {
+    appearance: none;
+    width: 7px;
+    padding-right: 7px;
+}
+::-webkit-scrollbar-thumb {
+    border-radius: 4px;
+    background-color: var(--border-color-invert);
+}
+
+
+
 </style>
 <!-- Add "scoped" attribute to limit CSS to this component only -->
 <style scoped>
+
+
 .title_bar {
-    height: 35px;
-    width: 100%;
+    height: var(--titlebar-height);
+    width: calc( 100vw - var(--sidebar-width) );
     /*background: red;*/
+    margin-left : var(--sidebar-width);
     -webkit-user-select: none;
     -webkit-app-region: drag;
     border-width: 0px;
     border-bottom-width: 1px;
     border-style: solid;
+    border-color: var( --thin-border-color);
+}
+
+
+.title_bar_icons{
+    float: right;
+    margin-right: 20px; 
+    height: var(--titlebar-height);
+    margin-top: 16px;
+}
+
+
+
+
+
+.sidebar_drag{
+    -webkit-user-select: none;
+    -webkit-app-region: drag;
+    height: var(--titlebar-height);
+}
+
+.app_title_sidebar_collapsed{
+    float:left;
+    height: var(--titlebar-height);
+    margin-top: 16px;
+
+}
+
+.app_title_sidebar_collapsed_mac{
+    margin-left: 72px;
 }
 
 .app_title {
-    padding-left: 80px;
-    padding-top: 10px;
+    float: left;
+    padding-left: 22px;
+    padding-top: 20px;
 
     font-family: var(--main-font-text);
     font-style: normal;
@@ -406,53 +467,135 @@ img {
     color: #000000;
 }
 
-.app_title.fullscreen{
-    padding-left: 22px;
+
+
+
+
+
+.sidebar{
+    position: fixed;
+    top:0 ;
+    left: 0 ;
+    bottom: 0 ;
+    background-color: var(--sidebar-color);
+ 
+    width: var(--sidebar-width) ;
 }
 
-@media (display-mode: fullscreen) {
-    .app_title {
-        /*works in chrome but not electron*/
-        display: none;
-        background-color: red;
-    }
+
+.sidebar_cat{
+   
+    color: rgba(0, 0, 0, 0.27);
+    font-family: var(--main-font-text);
+    font-style: normal;
+    font-weight: 600;
+    font-size: 12px;
+    line-height: 13px;
+    /* identical to box height, or 130% */
+
+    letter-spacing: 0.12px;
+    margin-left: 15px ;
+    margin-top: 15px ;
+    margin-bottom: 7px;
 }
 
-.tabs_bar {
-    height: 40px;
-    width: 100%;
-    border-width: 0px;
-    border-bottom-width: 1px;
-    border-style: solid;
 
-    padding-top: 8px;
-    padding-left: 20px;
-    padding-right: 20px;
+.sidebar_item{
+
+    font-family: var(--main-font-text);
+    font-style: normal;
+    font-weight: 400;
+    font-size: 14px;
+    line-height: 14px;
+    /* identical to box height, or 127% */
+
+    letter-spacing: 0.06px;
+
+    /* Dark/Text */
+
+    color: var(--text-color-solid);;
+    margin-left: 15px ;
+    margin-right: 15px ;
+    margin-bottom: 4px ;
+
+    padding-right: 15px;
+    padding-left: 15px;
+    padding-bottom: 7px;
+    padding-top: 7px;
+
+    border-radius: 5px;
+
+    
 }
 
-.tab_content_frame {
-    width: 100%;
-    height: calc(100vh - 40px  - 35px - 2px);
-    overflow: auto;
+.sidebar_icon{
+    margin-right: 5px;
+    color: #0A84FF;
 }
 
-.tab_content {
-    /*padding: 20px;*/
+.sidebar_item_selected{
+     background: rgba(0, 0, 0, 0.1);
+}
 
+.sidebar_item:hover{
+    background-color: var(--button-highlight-one);
 }
 
-.vertical-center {
-    margin: 0;
+
+.tab_content_frame{
     position: absolute;
-    top: 50%;
-    -ms-transform: translateY(-50%);
-    transform: translateY(-50%);
+    margin-left: var(--sidebar-width);
+    height: calc( 100vh - var(--titlebar-height) );
+    width: calc(100% - var(--sidebar-width) );
 }
 
-.tab {
+.tab_content{
+    height:100%; 
+    width:100%; 
+}
 
-    margin-right: 10px;
-    cursor: pointer;
+@media (prefers-color-scheme: dark) {
+    .sidebar_item_selected{
+        background: rgba(255, 255, 255, 0.1);
+    }
 
+    .sidebar_cat{
+         color: rgba(255, 255, 255, 0.40);
+    }
 }
+
+
+
+
+/*DROPDOWN buggle */
+
+.dropdown-bubble {
+  margin-top: 10em;
+}
+
+.dropdown-bubble:before,
+.dropdown-bubble:after{
+  content: ' ';
+  display: block;
+  border-style: solid;
+  border-width: 0 7px 7px 7px;
+  border-color: transparent;
+  position: absolute;
+  left: 193px;
+}
+
+.dropdown-bubble:before {
+  top: -2px;
+  border-bottom-color: rgba(255,255,255,0.5);
+}
+
+.dropdown-bubble:after {
+  top: -2px;
+    border-bottom-color: rgb(34, 34, 34) ;
+}
+
+
+
+
+
 </style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/CircleProgress.vue b/electron_app/src/components_bare/CircleProgress.vue
new file mode 100644
index 00000000..6f2d5cd4
--- /dev/null
+++ b/electron_app/src/components_bare/CircleProgress.vue
@@ -0,0 +1,94 @@
+<template>
+
+   <div class="progress_circ">
+        <svg class="progress-circle" width="200px" height="200px" xmlns="http://www.w3.org/2000/svg">
+            <circle class="progress-circle-back"
+                    cx="80" cy="80" r="74"></circle>
+            <circle class="progress-circle-prog" v-if="done_percentage >= 0 "
+                    cx="80" cy="80" r="74" :style="'stroke-dasharray: '+ 475*(done_percentage)/100 +' 999 ;   '"></circle>
+            <circle class="progress-circle-prog" v-else
+                    cx="80" cy="80" r="74" :style="'stroke-dasharray: '+ 475*(10)/100 +' 999 ; stroke-dashoffset: '+offset_val+'px; '"></circle>
+        </svg>
+    </div>  
+
+</template>
+<script>
+export default {
+    name: 'CircleProgress',
+    props: {
+        done_percentage:Number,
+    },
+    components: {},
+
+    created: function(){
+        let that = this;
+          this.counterInterval =  setInterval(
+            function()
+            {
+               that.offset_val += -10;
+               if(that.offset_val < -400)
+                that.offset_val = 0
+            }.bind(this), 20);
+      },
+      destoyed: function(){
+        clearInterval( this.counterInterval )
+      },
+
+
+    mounted() {
+
+    },
+    data() {
+        return {
+            offset_val: 0 
+        };
+    },
+    methods: {
+
+    },
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+
+.progress_circ {
+/*    position: absolute;   */
+    height: 160px;
+    width: 160px;
+    zoom : 0.5;
+/*    top: 50%;*/
+/*    left: 50%;*/
+/*    margin: -80px 0 0 -80px;*/
+}
+
+.progress-circle {
+  transform: rotate(-90deg);
+    margin-top: -40px;
+}
+
+.progress-circle-back {
+    fill: none; 
+    stroke: var(--border-color-invert-extralight);
+    stroke-width:10px;
+}
+
+.progress-circle-prog {
+    fill: none; 
+    stroke: #3d6ffa ;
+    stroke-width: 10px;  
+    stroke-dasharray: 0 999;    
+    stroke-dashoffset: 0px;
+    transition: stroke-dasharray 0.2s linear 0s;
+}
+
+.progress-text {
+    width: 100%;
+    position: absolute;
+    top: 60px;
+    text-align: center;
+    font-size: 2em;
+}
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/Form.vue b/electron_app/src/components_bare/Form.vue
index 6d2d03d4..8111cf5f 100644
--- a/electron_app/src/components_bare/Form.vue
+++ b/electron_app/src/components_bare/Form.vue
@@ -2,18 +2,13 @@
     <div>
         <!-- <FormInput v-model="dd" input_type="textbox" question="name" :contraints="['non_empty','is_float' , 'maxval_50' ,'minval_25']"></FormInput> -->
 
-        <FormInput v-for="form_el in form_entries_to_show"
-            v-model="form_values[form_el.id]" 
+        <ResolveInputComponent v-for="form_el in filtered_form_data"
             ref="form_element"
-            :id="form_el.id" 
+            :form_values="form_values" 
+            :config="form_el"
             :key="form_el.id"
-            :input_type="form_el.input_type"
-            :question="form_el.question" 
-            :contraints="form_el.contraints" 
-            :is_disabled="form_el.is_disabled || is_disabled"
-            :options="form_el.options"
             >
-        </FormInput>
+        </ResolveInputComponent>
 
         <!-- <p   v-if="!is_valid"> Invalid  </p> -->
 
@@ -22,7 +17,8 @@
 </template>
 <script>
 
-import FormInput from '../components_bare/FormInput.vue'
+import ResolveInputComponent from './inputform/ResolveInputComponent.vue'
+import Vue from 'vue'
 
 
 // TODO: add conditional rendering of some form elements based on values of other elements
@@ -32,46 +28,225 @@ export default {
     props: {
         form_data : Array , // [ {...} , {} ]
         is_disabled : Boolean, 
+        form_values: Object,
+        tags: Array,
+        form_save_key : String, 
+        
     },
-    components: {FormInput},
+    components: {ResolveInputComponent},
     mounted() {
+        if(this.form_save_key){
+            this.keys_to_save = this.collect_savable_keys()
+
+            for( let key of this.keys_to_save ){
+                let v = window.localStorage.getItem(this.form_save_key + "__" + key  );
+                if(v != null && v != undefined && v != "undefined" && v != "null"){
+                    Vue.set(this.form_values , key , v )
+                }
+            }
+
+        }
+
+        this.has_mounted = true;
 
     },
     data() {
         let ret = {
-            form_values : {}
+            // form_values : {}
+            has_mounted : false,
         };
 
-        for( let form_el of this.form_data){
-            ret.form_values[form_el.id] = form_el.value;
-        }
+        // for( let form_el of this.form_data){
+        //     let first_option = undefined
+        //     if(form_el.options && form_el.options.length > 0 ){
+        //         first_option = form_el.options[0]
+        //     }
+        //     ret.form_values[form_el.id] = form_el.value || first_option;
+        // }
 
         return ret;
     },
     methods: {
+
+        collect_savable_keys(elements){
+
+            if(!elements){
+                elements = this.form_data;
+            }
+
+            let ret = []
+            for( let form_el of elements){
+                if( form_el.is_persistant ){
+                    ret.push(form_el.id)
+                }
+                if(form_el.children && form_el.children.length > 0){
+                    ret = ret.concat(this.collect_savable_keys(form_el.children))
+                }
+            }
+
+            return ret;
+        },
+
+        reset_to_default(elements){
+            if(!elements){
+                elements = this.form_data;
+            }
+            for( let form_el of elements){
+                if( this.form_values[form_el.id] != undefined  && form_el.default_value ){
+                    Vue.set(this.form_values , form_el.id , form_el.default_value  )
+                } else if(this.form_values[form_el.id] != undefined){
+                    this.form_values[form_el.id] = ""
+                }
+
+                if(form_el.children && form_el.children.length > 0){
+                    this.reset_to_default(form_el.children)
+                }
+            }
+
+        },
+
         is_render_condition_satisfied(render_condition){
             if( render_condition['comparator'] == "eq" && this.form_values[render_condition['lhs']] == render_condition['rhs']  )
                 return true;
             else
                 return false;
         },
-        are_form_entry_conditions_safisfied(render_conditions){
+        are_form_entry_conditions_safisfied(render_conditions){ // see if ALL of them are satisfied
+            for( let render_condition of render_conditions ){
+                if(( this.is_render_condition_satisfied(render_condition) ))
+                    return true ;
+            }
+            return false;
+        },
+
+        are_form_entry_conditions_safisfied_AND(render_conditions){ // see if ALL of them are satisfied
             for( let render_condition of render_conditions ){
                 if(!( this.is_render_condition_satisfied(render_condition) ))
                     return false ;
             }
             return true;
+        },
+
+        post_processed_form_outputs(elements , ret ){
+
+            if(!elements){
+                elements = this.filtered_form_data;
+            }
+
+            if(!ret){
+                ret = {}
+            }
+
+            for(let form_el of elements){
+                if(this.form_values[form_el.id] != undefined){
+                    if(form_el.output_type){
+                        if(form_el.output_type == 'int'){
+                            ret[form_el.id] = Math.round(Number(this.form_values[form_el.id]))
+                        } else if(form_el.output_type == 'float'){
+                            ret[form_el.id] = Number(this.form_values[form_el.id])
+                        }else if(form_el.output_type == 'str'){
+                            ret[form_el.id] = this.form_values[form_el.id].toString()
+                        }else if(form_el.output_type == 'bool'){
+                            if(this.form_values[form_el.id] == "true" || this.form_values[form_el.id].toString().toLowerCase() == "yes"){
+                                ret[form_el.id] = true
+                            } else if(this.form_values[form_el.id] == "false" || this.form_values[form_el.id].toString().toLowerCase() == "no"){
+                                ret[form_el.id] = false
+                            } else if(this.form_values[form_el.id] ){
+                                ret[form_el.id] = true
+                            } else {
+                                ret[form_el.id] = false
+                            }
+                        }
+                    } else {
+                        ret[form_el.id] = this.form_values[form_el.id]
+                    }
+                    
+                }
+
+                if(form_el.children && form_el.children.length > 0){
+                    this.post_processed_form_outputs(form_el.children , ret )
+                }
+
+            }
+
+            return ret;
+
+        } , 
+
+        filter_form_data(form_data){
+            let ret = []
+            let tags = this.tags || []
+            for( let form_el of form_data){
+                let is_allowed = true;
+
+                if(form_el.include_in != undefined && form_el.include_in.length > 0 ){
+                    // if any tags then allow else dissallow
+                    if( (tags.filter(value => form_el.include_in.includes(value))).length > 0 ){
+                        is_allowed = true
+                    } else {
+                        is_allowed = false
+                    }
+                }
+
+                if(form_el.cond_include_in != undefined && form_el.cond_include_in.length > 0  ){
+                    if(this.are_form_entry_conditions_safisfied(form_el.cond_include_in)){
+                        is_allowed = true 
+                    } 
+                }
+
+                if(form_el.cond_include_in_AND != undefined && form_el.cond_include_in_AND.length > 0  ){
+                    if(this.are_form_entry_conditions_safisfied_AND(form_el.cond_include_in_AND)){
+                        is_allowed = true 
+                    } 
+                }
+
+                if(form_el.exclude_in != undefined && form_el.exclude_in.length > 0 ){
+                    if( (tags.filter(value => form_el.exclude_in.includes(value))).length > 0 ){
+                        is_allowed = false
+                    } 
+                }
+
+                if(form_el.include_in_AND != undefined  ){
+                    for(let t of form_el.include_in_AND){
+                        if( ! tags.includes(t) ){
+                            is_allowed = false
+                        }
+                    }
+                }
+
+                if(is_allowed){
+                    if(form_el.children){
+                        let filtered_children = this.filter_form_data(form_el.children)
+                        let new_form_el = {}
+                        for(let k in form_el){
+                            new_form_el[k] = form_el[k]
+                        }
+                        new_form_el['children'] = filtered_children
+                        ret.push(new_form_el)
+                    } else {
+                        ret.push(form_el)
+                    }
+                    
+                }
+                    
+            }
+            return ret
         }
+
+
     },
 
     watch : {
        
-        'form_data': {
+        'form_values': {
             handler: function() {
-                for( let form_el of this.form_data){
-                        this.form_values[form_el.id] = form_el.value;
+                if(!this.has_mounted)
+                    return;
+                if(this.form_save_key){
+                    for( let key of this.keys_to_save ){
+                        window.localStorage.setItem(this.form_save_key + "__" + key , this.form_values[key]);
                     }
-
+                }
             },
             deep: true
         } , 
@@ -80,24 +255,11 @@ export default {
 
     computed : {
 
-        form_entries_to_show(){
-
-            let ret = [];
-            for( let form_el of this.form_data){
-                if( form_el.render_conditions  && form_el.render_conditions.length > 0 ){
-                    if( this.are_form_entry_conditions_safisfied( form_el.render_conditions  ) ){
-                        ret.push( form_el );
-                    }
-                } else {
-                    ret.push( form_el );
-                }
-            }
-
-            return ret;
-        } , 
+        filtered_form_data(){ //TODO make it recursive //TODO also allow dymamic filters
+            return this.filter_form_data(this.form_data)
+        },
 
         is_valid(){
-            console.log((this.$refs));
 
             //a simple hacky way t o make is_valid reactive wrt the form_values 
             let dd = '';
@@ -113,8 +275,6 @@ export default {
                 }
 
             return true;
-
-            
         }
     }
 }
diff --git a/electron_app/src/components_bare/FormInput.vue b/electron_app/src/components_bare/FormInput.vue
deleted file mode 100644
index c3653d27..00000000
--- a/electron_app/src/components_bare/FormInput.vue
+++ /dev/null
@@ -1,160 +0,0 @@
-<template>
-    <div>
-        <b-row style="margin-bottom: 10px ;">
-
-            <b-col cols="12" v-if="input_type == 'label'">
-                <label  style="padding-top: 6px; font-size: 13px; "><span v-if="get_color_from_text(question)" style="padding-right:15px; margin-right: 5px" :style="{'background-color':get_color_from_text(question) }" ></span>  {{remove_color_from_text(question)}}</label>
-
-            </b-col>
-
-            <b-col cols="4" v-if="input_type != 'label'">
-                <label  style="padding-top: 6px; font-size: 13px; "><span v-if="get_color_from_text(question)" style="padding-right:15px; margin-right: 5px" :style="{'background-color':get_color_from_text(question) }" ></span>  {{remove_color_from_text(question)}}</label>
-
-            </b-col>
-            <b-col cols="8" v-if="input_type != 'label'">
-                <!-- for text box input -->
-                <input v-if="input_type == 'textbox'" style="font-size: 13px;" class="form-control"  @input="$emit('input',$event.target.value); on_input_changed()" :value="value" :disabled=is_disabled>
-                <!-- for drop down input -->
-                <select :disabled=is_disabled  v-if="input_type == 'dropdown'" style="font-size: 13px;"  class="form-select" @input="$emit('input',$event.target.value) ; on_input_changed()" :value="value"  >
-                    <option v-for="option in options" :value="option" :key=
-                    "option">{{option}}</option>
-                </select>
-                <!-- the boolean yes no input -->
-                <div v-if="input_type == 'yes_no'">
-                    <b-row>
-                        <b-col cols="6">
-                              <input v-model=value2 value="yes" @input="$emit('input',value2); on_input_changed()" class="form-check-input" type="radio" :name=id  :disabled=is_disabled >
-
-                            Yes 
-                        </b-col>
-                        <b-col cols="6">
-                              <input v-model=value2 value="no" @input="$emit('input',value2); on_input_changed()" class="form-check-input" type="radio" :name=id  :disabled=is_disabled>
-
-                             No
-                        </b-col>
-                    </b-row>
-                </div>
-                <p style="color:red" v-if="invalid_prompt_str">{{invalid_prompt_str}}</p>
-            </b-col>
-
-            
-
-        </b-row>
-    </div>
-</template>
-<script>
-
-import {get_color_from_text, remove_color_from_text} from "../utils.js"
-
-
-
-function isItNumber(str) {
-  return /^-?[0-9]+(e[0-9]+)?(\.[0-9]+)?$/.test(str);
-}
-
-
-export default {
-    name: 'FormInput',
-    props: {
-        value : String , 
-        id : String , 
-        question: String,
-        input_type: String, // textbox, dropdown, yes_no
-        options: Array, // options for the dropdown
-        is_disabled : Boolean , 
-        contraints : Array , // list of all validation checks applied on the input element
-
-    },
-    components: {},
-    mounted() {
-
-    },
-    data() {
-        return {
-            value2 : this.value , // for the initial value of the yes / no input 
-            is_form_entry_fresh : this.value == "" // used to deterimine if the element is empty and value has not been changed yet
-        };
-    },
-    methods: {
-        on_input_changed(){
-            this.is_form_entry_fresh = false;
-        },
-        get_color_from_text(t){
-            return get_color_from_text(t)
-        },
-
-        remove_color_from_text(t){
-            return remove_color_from_text(t)
-        },
-        is_input_valid(){
-            for( let constraint of ( this.contraints|| []) ){
-                if( constraint == "non_empty" ){
-                    if( (! this.value) ||(this.value == ""))
-                        return {
-                            "is_valid" : false, 
-                            "msg" : "The value cannot be empty"
-                        }
-                }
-                else if( constraint == "is_int" ){
-                    if( parseInt(this.value).toString() != this.value.toString()  ){
-                        return{
-                            "is_valid" : false, 
-                            "msg" : "The value should be a valid integer"
-                        }
-                    }
-                }
-                else if( constraint == "is_float" ){
-                    if(!isItNumber(this.value)){
-                        return{
-                            "is_valid" : false, 
-                            "msg" : "The value should be a valid float number"
-                        }
-                    }
-                }
-                else if( constraint.startsWith("maxval_") ){
-                    let max_val = parseFloat( constraint.split("maxval_")[1]);
-                    if( parseFloat(this.value) > max_val){
-                        return{
-                            "is_valid" : false, 
-                            "msg" : "The value should not greater than " + max_val
-                        }
-                    }
-                }
-                else if( constraint.startsWith("minval_") ){
-                    let min_val = parseFloat( constraint.split("minval_")[1]);
-                    if( parseFloat(this.value) < min_val){
-                        return{
-                            "is_valid" : false, 
-                            "msg" : "The value should not less than " + min_val
-                        }
-                    }
-                }
-            }
-
-            return {
-                "is_valid" : true , 
-                "msg" : ""
-            }
-        },
-    },
-    watch : {
-        value : function(val){
-            this.value2 = val; 
-        } , 
-    },
-
-    computed : {
-        invalid_prompt_str(){
-            if(this.is_disabled)
-                return "";
-            if(this.is_form_entry_fresh)
-                return "";
-            return this.is_input_valid()['msg']  ;
-        }
-    }
-}
-</script>
-<style>
-</style>
-<style scoped>
-</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/GalleryContainerBare.vue b/electron_app/src/components_bare/GalleryContainerBare.vue
deleted file mode 100644
index 2da02120..00000000
--- a/electron_app/src/components_bare/GalleryContainerBare.vue
+++ /dev/null
@@ -1,96 +0,0 @@
-<template>
-    <div>
-        <div v-if="  title!='' || n_count >=0 " class="gallery_title">
-            <h2 v-if="  title!=''" style="float:left">{{title}}</h2>
-            <div v-if="n_count >=0 " type="submit" class="l_button button_white rounded_button" @click="$emit('more_imgs_cb',{})" style="margin-right: 20px ; float: right; "> {{n_count}} items <i style="margin-left: 5px; color: rgb(58, 164, 251); font-size: 12px;">
-                    <font-awesome-icon icon="chevron-right" /></i></div>
-        </div>
-        <div class="gallery_container">
-            <GalleryItem 
-                v-for="item in items" 
-                v-bind:is_px500_less_size_gallery="is_px500_less_size_gallery" 
-                v-bind:key="item.key" 
-                v-bind:item_id="item.key" 
-                @on_click_cb="on_click_cb"
-                @on_double_click_cb="on_double_click_cb"
-                :tag="item.tag" 
-                :description="item.description"
-                :type="item.type || 'full_img' "
-                :tag_color="item.tag_color"
-                :audio_url="item.audio_url"
-                :video_url="item.video_url"
-                :title="item.title"
-                :ref="item.key"
-                :dont_unselect_on_outside_click="keep_one_selected"
-                :url="item.url"> </GalleryItem>
-        </div>
-    </div>
-</template>
-<script>
-import GalleryItem from './GalleryItem.vue'
-
-
-export default {
-    name: 'GalleryContainerBare',
-    components: { GalleryItem },
-    props: {items : Array, 
-        title : String , 
-        n_count : Number , 
-        is_px500_less_size_gallery : Boolean ,
-        on_click_callback : Function,
-        on_double_click_callback : Function,
-        keep_one_selected : Boolean , // if set to true it wont unselect if you click anywehre outside the gallery. 
-    },
-    mounted() {
-        if(this.keep_one_selected){
-            if(this.items.length > 0 ){
-                this.selected_gallery_key = this.items[0].key;
-                this.$refs[this.items[0].key][0].selected = true;
-            }
-        }
-    },
-    methods:{
-        on_click_cb(k){
-
-            if( this.keep_one_selected &&  this.selected_gallery_key && this.selected_gallery_key!=k )
-            {
-                this.$refs[this.selected_gallery_key][0].selected = false;
-            }
-            this.selected_gallery_key = k;
-            if(this.on_click_callback)
-                this.on_click_callback(k);
-        } , 
-
-        on_double_click_cb(k){
-            if(this.on_double_click_callback){                
-                this.on_double_click_callback(k);
-            }
-        } , 
-    }
-}
-</script>
-<style>
-
-
-
-.gallery_title {
-   
-    padding-bottom: 10px;
-    padding-left: 10px;
-    /*display: flex;
-    flex-wrap: wrap;*/
-}
-
-
-.gallery_container {
-    display: flex;
-    flex-wrap: wrap;
-    margin-bottom: 20px;
-}
-
-.gallery_title:after {
-    content: "";
-    display: table;
-    clear: both;
-}
-</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/GalleryImage.vue b/electron_app/src/components_bare/GalleryImage.vue
new file mode 100644
index 00000000..295c95a9
--- /dev/null
+++ b/electron_app/src/components_bare/GalleryImage.vue
@@ -0,0 +1,139 @@
+<template>
+    <div    class="gal_item">
+        <div class="gal_item_inner" style="height: 100%; width: 100%;   ">
+
+
+            <div v-if="image_url == 'ERROR'"  style="width:100% ; height:100%;   border-style: solid ; border-color: var(--border-color-invert); border-width: 1px;  padding: 20px; "  >
+                <p> Error : {{description}} </p>
+            </div>
+
+            <div style="height: 100%; width: 100%;   " v-else>
+
+                <img class="aux_img" v-if="aux_img_url" :src="'file://' + aux_img_url"  style="position:absolute; opacity:0.8; top:0 ; left:0; width:30% ; height:30%; object-fit: cover;   ">
+                
+                <div v-if="description && image_url" @click="on_image_click(self)" class="gall_top_right_btn_container " style="position:absolute; bottom:5px ; left:5px ; right:0px; padding:20px; background: linear-gradient(to top, rgba(0,0,0,1), rgba(0,0,0,0)); color:white ; font-size: 12px;margin-right: 5px ; padding-top:20px">
+                    {{description}}
+                </div>
+
+                 <div v-if="image_url" class="cdiv gall_top_right_btn_container" style=" position:absolute ; margin-top:7px ; margin-left:7px "  >
+                    <b-dropdown left variant="link" size="sm" toggle-class="text-decoration-none" no-caret>
+                        <template #button-content>
+                            <div   class=" l_button button_colored" style="background-color: rgba(0,0,0,0.6);">
+                                Actions 
+                                <!-- <font-awesome-icon icon="bars" /> -->
+                            </div>
+                        </template>
+                        <b-dropdown-item-button v-for="menu_item in menu_items" :key="menu_item.id" @click="on_menu_item_click(menu_item.id , self )">{{menu_item.text}}</b-dropdown-item-button>
+                    </b-dropdown>
+                 </div>
+
+
+                 <div style="position:absolute ; top: 50% ; left: 50% ;  transform: translate(-50%, -50%);"  v-if="(!image_url) && (done_percentage != undefined)" >
+                     <CircleProgress :done_percentage="done_percentage"> </CircleProgress>
+                 </div>
+
+
+                
+
+                
+                <img @click="on_image_click(self)" v-if="image_url"   style="  width:100% ; height:100%; object-fit: cover;  object-position:0px 0px; " :src=" 'file://' + image_url">
+                <img  v-bind:class="{ 'animate-flicker': (done_percentage == undefined) }" class="animate-flicker"   v-else :width="img_w" :height="img_h"  style="width:100% ; height:100%;   object-position:0px 0px;  border-style: solid ; border-color: var(--border-color-invert); border-width: 1px;   " src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==">
+
+
+                
+
+
+            </div>
+
+
+        </div>
+        
+    </div>
+
+</template>
+<script>
+
+import CircleProgress from "./CircleProgress.vue"
+
+
+export default {
+    name: 'EmptyComponent',
+    props: {
+        image_url : String,
+        aux_img_url: String,
+        img_w:Number, 
+        img_h:Number,
+        description: String, 
+        menu_items : Array,
+        params: Object,
+        done_percentage: Number,
+        on_menu_item_click : Function, 
+        on_image_click: Function,
+    },
+    components: {CircleProgress},
+    mounted() {
+
+    },
+    data() {
+        return {
+            self : this,
+        };
+    },
+    methods: {
+
+    },
+}
+</script>
+<style>
+
+.cdiv > div > .dropdown-menu{
+    font-size: 13px !important;
+}
+
+</style>
+
+<style scoped>
+
+
+@keyframes flickerAnimation {
+  0%   { background-color:var(--border-color-invert-extralight); }
+  50%  { background-color: rgba(0, 0, 0, 0.0); }
+  100% { background-color:var(--border-color-invert-extralight); }
+}
+
+
+.animate-flicker {
+   -webkit-animation: flickerAnimation 1s infinite;
+   -moz-animation: flickerAnimation 1s infinite;
+   -o-animation: flickerAnimation 1s infinite;
+    animation: flickerAnimation 1s infinite;
+
+}
+
+
+.gal_item{
+    position: relative;
+    padding:5px;
+}
+
+.gall_top_right_btn_container{
+    display: none;
+}
+
+.gal_item_inner:hover > div > .gall_top_right_btn_container{
+    display: block;
+    /*opacity: 0.1;*/
+}
+
+
+.aux_img{
+    display: block;
+}
+
+.gal_item_inner:hover > div > .aux_img{
+    display: none;
+    /*opacity: 0.1;*/
+}
+
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/GalleryItem.vue b/electron_app/src/components_bare/GalleryItem.vue
deleted file mode 100644
index cd6a2b6f..00000000
--- a/electron_app/src/components_bare/GalleryItem.vue
+++ /dev/null
@@ -1,423 +0,0 @@
-<template>
-    <div v-click-outside="unclick_card_body" class="responsive_gallery_container " v-bind:class="{ 'px500_less_size_gallery' :  is_px500_less_size_gallery , 'is_full_size' : is_full_size }">
-        <div v-on:click="click_card_body() ; $emit('on_click_cb', item_id) "  class="gallery_card" v-bind:class="{ 'selected' : selected }">
-
-             
-
-            <video class="gallery_img" v-if="type=='full_img' && video_url && is_full_size" width="100%" :src="video_url"  controls disablePictureInPicture> </video>   
-            <img   class="gallery_img"  v-else-if="type=='full_img'" :src="url" >
-                
-            
-
-            <div v-if="type == 'img_text' "   style="height: 100%;"  >
-               
-               
-                <img class="gallery_img" style="height:70% ; max-height: 70%; width: 100%;"  :src="url" >
-                <div class="gall_title">
-                    <p>
-                        <b style="white-space: nowrap;">{{title}}</b>
-                        <br>
-                        {{description}}
-                    </p>
-                </div>
-            </div>
-
-
-
-            <div v-if="type == 'text' "  >
-                <div class = "paragraph_container" style="padding:16px; overflow: hidden ">
-                    <div class="paragraph_container_inner">
-                        <p style=" font-size: 16px ; line-height: 22px ; font-weight: normal ; color:rgba(0, 0, 0, 0.6);">{{description}} </p>
-                    </div>
-                    
-                </div>
-                
-            </div>
-
-            
-
-            <div v-if="top_right_icon || top_right_button_text" class="gall_top_right_btn_container">
-                <div v-on:click.stop @click=" $emit('on_click_top_right_btn', item_id)" class="l_button button_grey" style="margin-right: 0;">
-                     <font-awesome-icon v-if=top_right_icon :icon="top_right_icon" /> {{top_right_button_text}}
-                </div>
-            </div>
-
-             <div v-if="audio_url" class="audio_button_container" >
-                <IconAudioPlayer :audio_url="audio_url" ></IconAudioPlayer> 
-            </div>
-            
-
-            <div v-if="tag" class="gall_tag_container">
-                <div class="gall_tag l_button" :style="{'background-color':tag_color}" >
-                    <div v-if="tag !=  '__loading__'">{{tag}}</div>
-                    <MoonLoader v-else  color="#ffffff" size="17px"></MoonLoader>
-                </div>
-
-            </div>
-        </div>
-    </div>
-</template>
-<script>
-
-import MoonLoader from 'vue-spinner/src/MoonLoader.vue'
-import IconAudioPlayer from './IconAudioPlayer.vue'
-
-export default {
-    name: 'GalleryItem',
-    props: {
-        type: {type: String  , default:"full_img"} , // full_img , img_text , text 
-        tag: String,
-        tag_color : String ,
-        item_id : String ,
-        url: String,
-        audio_url: String , 
-        video_url: String,
-        is_px500_less_size_gallery: Boolean,
-        is_full_size: Boolean , 
-        title : String , 
-        description : String , 
-        dont_unselect_on_outside_click : Boolean,
-        top_right_icon : String, // if you wannna show a FA icon on top right of the item , eg delete
-        top_right_button_text : String, // if you wannna show text button on top right
-
-    },
-
-    components: { MoonLoader , IconAudioPlayer },
-
-    data() {
-        return {
-            selected: false
-        }
-    },
-
-    methods: {
-
-        // when you click outside the item
-        unclick_card_body: function() {
-            if(this.dont_unselect_on_outside_click)
-                return;
-            else
-                this.selected = false
-        },
-
-
-        double_clicked() {
-            this.$emit('on_double_click_cb', this.item_id);
-        },
-
-
-        click_card_body: function() {
-            if (this.just_selected) {
-                this.double_clicked()
-                return
-            }
-
-            this.just_selected = true
-            const thatt = this
-            setTimeout(function() { thatt.just_selected = false }, 200)
-
-            this.selected = true
-        }
-
-
-    }
-}
-</script>
-<style>
-@media (min-width: 576px) {
-    .responsive_gallery_container {
-        -ms-flex: 0 0 50.0%;
-        -webkit-box-flex: 0;
-        flex: 0 0 50.0%;
-        max-width: 50.0%;
-    }
-}
-
-@media (min-width: 668px) {
-    .responsive_gallery_container {
-        -ms-flex: 0 0 33.333333%;
-        -webkit-box-flex: 0;
-        flex: 0 0 33.333333%;
-        max-width: 33.333333%;
-    }
-}
-
-@media (min-width: 892px) {
-    .responsive_gallery_container {
-        -ms-flex: 0 0 25%;
-        -webkit-box-flex: 0;
-        flex: 0 0 25%;
-        max-width: 25%;
-    }
-}
-
-@media (min-width: 1100px) {
-    .responsive_gallery_container {
-        -ms-flex: 0 0 20%;
-        -webkit-box-flex: 0;
-        flex: 0 0 20%;
-        max-width: 20%;
-    }
-}
-
-@media (min-width: 1600px) {
-    .responsive_gallery_container {
-        -ms-flex: 0 0 16.6667%;
-        -webkit-box-flex: 0;
-        flex: 0 0 16.6667%;
-        max-width: 16.6667%;
-    }
-}
-
-@media (min-width: 1900px) {
-    .responsive_gallery_container {
-        -ms-flex: 0 0 14.2857142857%;
-        -webkit-box-flex: 0;
-        flex: 0 0 14.2857142857%;
-        max-width: 14.2857142857%;
-    }
-}
-
-@media (min-width: 2100px) {
-    .responsive_gallery_container {
-        -ms-flex: 0 0 12.5%;
-        -webkit-box-flex: 0;
-        flex: 0 0 12.5%;
-        max-width: 12.5%;
-    }
-}
-
-@media (min-width: 2400px) {
-    .responsive_gallery_container {
-        -ms-flex: 0 0 11.1111111111%;
-        -webkit-box-flex: 0;
-        flex: 0 0 11.1111111111%;
-        max-width: 11.1111111111%;
-    }
-}
-</style>
-<!-- Add "scoped" attribute to limit CSS to this component only -->
-<style scoped>
-.gall_tag_container {
-    /*background: red;*/
-    position: absolute;
-    /*height: 300px;*/
-    bottom: 20px;
-    left: 20px;
-
-
-}
-
-
-.audio_button_container {
-    /*background: red;*/
-    position: absolute;
-    /*height: 300px;*/
-    top: 10px;
-    left: 10px;
-}
-
-
-.gall_top_right_btn_container {
-    /*background: red;*/
-    position: absolute;
-    /*height: 300px;*/
-    top: 10px;
-    right: 10px;
-    display: none;
-
-}
-
-
-.gallery_card:hover > .gall_top_right_btn_container{
-    display: block;
-    /*opacity: 0.1;*/
-}
-
-
-.gall_tag {
-
-    background: rgba(62, 123, 250, 0.8);
-    color: #FFFFFF;
-
-}
-
-.gallery_card {
-
-    position: relative;
-    padding:0px;
-    margin: 7px;
-    height: 184px;
-
-    position: relative;
-    display: flex;
-    flex-direction: column;
-    -webkit-box-pack: justify;
-    justify-content: space-between;
-
-    background-repeat: no-repeat;
-    background-position: center center;
-    background-size: cover;
-
-    border-radius: 12px 12px 12px 12px;
-    background-color: white;
-    border-style: solid;
-    border-width: 1px;
-    border-color: rgba(0, 0, 0, 0.1);
-
-
-    overflow: hidden;
-    box-shadow: 0px 0px 1.76351px rgba(40, 41, 61, 0.04), 0px 3.52703px 7.05405px rgba(96, 97, 112, 0.16);
-
-    /*width: 100%;*/
-
-    /*-webkit-app-region: none;*/
-    
-
-}
-
-
-.gallery_img {
-   
-
-    object-fit: cover;
-    height: 100%;
-    max-width: 100%;
-    max-height: 100%;
-    margin: 0;
-    padding: 0px;
-
-}
-
-
-
-
-.selected {
-    /*   border-width: 2px;
-            border-color: #6e47e2;
-            border-color: #4ca4ff;*/
-    box-shadow: 0px 0px 0 3px #4ca4ff;
-}
-
-
-.gall_title{
-    padding: 10px;
-    margin-bottom: 10px;
-}
-
-
-
-.paragraph_container_inner{
-    height: 94px;
-}
-
-
-
-
-/*if the gallery is at a location where the width is shortened by 500 px , ie when there a large img on right side*/
-
-@media (min-width: 6px) {
-    .responsive_gallery_container.px500_less_size_gallery {
-        -ms-flex: 0 0 100.0%;
-        -webkit-box-flex: 0;
-        flex: 0 0 100.0%;
-        max-width: 100.0%;
-    }
-}
-
-
-@media (min-width: 900px) {
-    .responsive_gallery_container.px500_less_size_gallery {
-        -ms-flex: 0 0 50.0%;
-        -webkit-box-flex: 0;
-        flex: 0 0 50.0%;
-        max-width: 50.0%;
-    }
-}
-
-@media (min-width: 1168px) {
-    .responsive_gallery_container.px500_less_size_gallery {
-        -ms-flex: 0 0 33.333333%;
-        -webkit-box-flex: 0;
-        flex: 0 0 33.333333%;
-        max-width: 33.333333%;
-    }
-}
-
-@media (min-width: 1392px) {
-    .responsive_gallery_container.px500_less_size_gallery {
-        -ms-flex: 0 0 25%;
-        -webkit-box-flex: 0;
-        flex: 0 0 25%;
-        max-width: 25%;
-    }
-}
-
-@media (min-width: 1600px) {
-    .responsive_gallery_container.px500_less_size_gallery {
-        -ms-flex: 0 0 20%;
-        -webkit-box-flex: 0;
-        flex: 0 0 20%;
-        max-width: 20%;
-    }
-}
-
-@media (min-width: 2100px) {
-    .responsive_gallery_container.px500_less_size_gallery {
-        -ms-flex: 0 0 16.6667%;
-        -webkit-box-flex: 0;
-        flex: 0 0 16.6667%;
-        max-width: 16.6667%;
-    }
-}
-
-@media (min-width: 2400px) {
-    .responsive_gallery_container.px500_less_size_gallery {
-        -ms-flex: 0 0 14.2857142857%;
-        -webkit-box-flex: 0;
-        flex: 0 0 14.2857142857%;
-        max-width: 14.2857142857%;
-    }
-}
-
-@media (min-width: 2600px) {
-    .responsive_gallery_container.px500_less_size_gallery {
-        -ms-flex: 0 0 12.5%;
-        -webkit-box-flex: 0;
-        flex: 0 0 12.5%;
-        max-width: 12.5%;
-    }
-}
-
-@media (min-width: 3000px) {
-    .responsive_gallery_container.px500_less_size_gallery {
-        -ms-flex: 0 0 11.1111111111%;
-        -webkit-box-flex: 0;
-        flex: 0 0 11.1111111111%;
-        max-width: 11.1111111111%;
-    }
-}
-
-
-.responsive_gallery_container.is_full_size {
-    -ms-flex: 0 0 100.0%;
-    -webkit-box-flex: 0;
-    flex: 0 0 100.0%;
-    max-width: 100.0%;
-}
-
-.is_full_size>div > div {
-    height: auto ;
-}
-
-.is_full_size > div {
-    height: auto;
-}
-
-.is_full_size > div > div > .paragraph_container > .paragraph_container_inner{
-    height: auto;
-    min-height: 100px;
-    margin-bottom: 40px;
-}
-
-</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/GalleryPane.vue b/electron_app/src/components_bare/GalleryPane.vue
new file mode 100644
index 00000000..c11111ef
--- /dev/null
+++ b/electron_app/src/components_bare/GalleryPane.vue
@@ -0,0 +1,214 @@
+<template>
+    <div :id="rand_id" class="gallery_pane"  >
+
+
+        <div class="inner_pane" :style="inner_pane_style">
+            <GalleryImage  v-for="img in image_data_with_extra" :key="img.job_id"  :image_url="img.image_url" :aux_img_url="img.aux_img_url" :description="img.description" :img_w="img_w" :img_h="img_h" :done_percentage="img.done_percentage" :menu_items="menu_items" :on_menu_item_click="on_menu_item_click" :on_image_click="on_image_click" :params="img.params"> </GalleryImage>
+        </div>
+
+    </div>
+
+</template>
+<script>
+
+import GalleryImage from "./GalleryImage.vue"
+
+
+export default {
+    name: 'GalleryPane',
+    props: {
+        n_imgs: Number,
+        img_w:Number, 
+        img_h:Number,
+        image_data: Array, 
+        always_fixed_col_size : Number, 
+
+        menu_items : Array,
+        on_menu_item_click : Function, 
+        on_image_click:Function,
+
+    },
+    components: {GalleryImage},
+    mounted() {
+        this.ro = new ResizeObserver(this.on_resize);
+        this.ro.observe( document.getElementById(this.rand_id) );
+        this.on_resize()
+    },
+    
+    beforeDestroy(){
+        this.ro.disconnect()
+    },
+
+    computed: {
+        image_data_with_extra(){
+
+            let extra = [];
+            for(let i=0; i< this.n_imgs - this.image_data.length ; i ++ ){
+                extra.push({})
+            }
+
+            return this.image_data.concat(extra)
+        }
+    },
+
+    data() {
+        let d =  {
+
+            rand_id : Math.random().toString(),
+            inner_pane_style: {},
+             
+        };
+
+        
+
+        // for(let i=0 ; i < this.n_imgs ; i++){
+        //     d['imgs'].push(i)
+        // }
+
+        return d; 
+    },
+
+    watch: {
+        'image_data': {
+            handler: function() {
+                this.on_resize()
+            },
+            deep: false
+        } , 
+    }, 
+
+    methods: {
+        on_resize(){
+
+
+            // let pane_h = document.getElementById(this.rand_id).offsetHeight
+            let pane_w = document.getElementById(this.rand_id).offsetWidth
+            let th = parseInt(getComputedStyle(document.body).getPropertyValue('--titlebar-height'))
+            let pane_h =  window.innerHeight - 30 - th;
+
+            let parent_aspect_ratio = (pane_h / pane_w);
+
+            let MAX_ALLOWED_IMG_W = 350
+            let n_col_max = Math.ceil(pane_w/MAX_ALLOWED_IMG_W)
+            let n_row_max = Math.ceil(pane_h/((MAX_ALLOWED_IMG_W * this.img_h)/this.img_w))
+
+            if( this.always_fixed_col_size ||  this.n_imgs > n_col_max * n_row_max  ){
+               let n_col = n_col_max
+
+               if(this.always_fixed_col_size)
+                n_col = Math.ceil(pane_w/this.always_fixed_col_size)
+
+               let col_size = 100 / n_col
+               let col_size_pad = (5 / n_col)
+               let col_size_s =  "calc("+col_size+"% - "+col_size_pad+"px  ) "
+               col_size_s = col_size_s.repeat(n_col)
+
+               this.inner_pane_style = { "grid-template-columns" : col_size_s , "width" : "100%"}
+               document.getElementById(this.rand_id).style.height = "auto"
+               return;
+            }
+            else{
+                document.getElementById(this.rand_id).style.height = "calc( 100vh - var(--titlebar-height) - 30px )"
+            }
+
+
+            let n_imgs = Math.min(this.n_imgs, n_col_max * n_row_max)
+            let best_aspect = 100000
+            let best_col_row = {}
+            for(let n=1 ; n<=Math.min(10 , n_imgs, n_col_max); n++){
+                let nr = Math.ceil(n_imgs / n )
+                let this_aspect = ( this.img_h *  nr ) / (this.img_w *  n)
+                if (Math.abs(parent_aspect_ratio - this_aspect ) < Math.abs(parent_aspect_ratio - best_aspect )){
+                    best_aspect = this_aspect;
+                    best_col_row = {'row' : nr , "col" : n }
+                }
+
+            }
+
+            let n_row = best_col_row.row
+            let n_col = best_col_row.col
+
+
+            // if(this.n_imgs == 4 && (n_row*n_col >=6) )
+            // {
+            //     n_row = 2;
+            //     n_col = 2;
+            // }
+
+            if(n_row * n_col > this.n_imgs){
+                let extra_space = n_row * n_col - 1 - this.n_imgs;
+                if(extra_space >= (n_row - 1) ){
+                    n_col -= 1;
+                }
+            }
+
+
+            let canv_h = this.img_h *  n_row
+            let canv_w = this.img_w *  n_col
+
+
+            let aspect_ratio_string = canv_w + "/" + canv_h
+
+            let col_size = 100 / n_col
+            let col_size_pad = 5 / n_col
+            let col_size_s =  "calc("+col_size+"% - "+col_size_pad+"px  ) "
+            col_size_s = col_size_s.repeat(n_col)
+
+            let row_size = 100 / n_row
+            let row_size_pad = 5 / n_row
+            let row_size_s =  "calc("+row_size+"% - "+row_size_pad+"px  ) "
+            row_size_s = row_size_s.repeat(n_row)
+
+
+
+
+            if((pane_h / pane_w) > (canv_h / canv_w)){
+                // width should be 100%
+                this.inner_pane_style = {"width" : "100%", "aspect-ratio" : aspect_ratio_string, "grid-template-columns" : col_size_s, "grid-template-rows" : row_size_s}
+            } else {
+                this.inner_pane_style = {"height" : "calc( 100vh - var(--titlebar-height) - 40px )", "aspect-ratio" : aspect_ratio_string, "grid-template-columns" : col_size_s, "grid-template-rows" : row_size_s}     
+            }
+        }, 
+    },
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+
+.gallery_pane{
+/*    height: calc( 100vh - var(--titlebar-height) - 30px );*/
+    width: calc( 100% - 30px);
+    background-color: rgba(0,0,0,0.06);
+    margin: 15px; 
+    display: grid;
+    place-items: center;
+    border-radius: 5px;
+    position: relative;
+
+}
+
+
+
+.inner_pane{
+/*    background-color: green;*/
+    object-fit: contain;
+
+    padding-left:5px;
+    padding-top:5px;
+    
+    display: grid;
+/*    grid-template-columns: calc(50% - 2.5px  ) calc(50% - 2.5px );*/
+/*    grid-gap:10px;*/
+
+
+}
+
+
+img{
+/*    max-height: calc( ( 100vh - var(--titlebar-height) - 30px ) /2 - 20px );*/
+}
+
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/ImageCanvas.vue b/electron_app/src/components_bare/ImageCanvas.vue
index 6f4344d8..ca3cd7ac 100644
--- a/electron_app/src/components_bare/ImageCanvas.vue
+++ b/electron_app/src/components_bare/ImageCanvas.vue
@@ -1,6 +1,6 @@
 <template>
     <div style="height:100% ; width:100%; position:  relative;">
-        <img id="myImg" :src="'file://'+image_source" style="display:none">
+        <img  @load="on_img_load2" :id="canvas_d_id+'img'" :src="'file://'+image_source" style="display:none">
         <canvas :id="canvas_d_id" style="width:100% ; height:100%; position: absolute ; top:0 , left:0  " ></canvas>
         <canvas :id="canvas_id" style="width:100% ; height:100%; position: absolute ; top:0 , left:0 ; opacity:0.7" ></canvas>
        
@@ -27,6 +27,7 @@ export default {
         canvas_d_id : String, 
         canvas_id: String,
         stroke_size_no : String,
+        on_img_load: Function, 
     },
     components: {},
     computed: {
@@ -82,6 +83,11 @@ export default {
     },
     methods: {
 
+        on_img_load2(){
+            if(this.on_img_load)
+                 this.on_img_load()
+        },
+
         findxy(res, e) {
 
             if(!(this.is_inpaint))
@@ -143,6 +149,11 @@ export default {
 
         },
 
+        get_size(){
+            let img =  document.getElementById(this.canvas_d_id+"img")
+            return {width: img.width ,height: img.height }
+        },
+
         on_resize(){
             let canvas = document.getElementById(this.canvas_id);
             let canvasD = document.getElementById(this.canvas_d_id);
@@ -219,7 +230,7 @@ export default {
         get_img_b64(){
             return this.canvasD.toDataURL();
         } , 
-        get_mask_b46(){
+        get_mask_b64(){
             let canvas = document.createElement('canvas');
             canvas.width = this.canvas.width;
             canvas.height = this.canvas.height;
@@ -232,7 +243,7 @@ export default {
             return canvas.toDataURL();
 
         }, 
-        get_img_mask_bg4(){
+        get_img_mask_b64(){
             let canvas = document.createElement('canvas');
             canvas.width = this.canvasD.width;
             canvas.height = this.canvasD.height;
@@ -241,6 +252,21 @@ export default {
             ctx.drawImage(this.canvas, 0, 0);
             
             return canvas.toDataURL();
+        } , 
+
+        get_mask_for_cache(){
+            return this.canvas.toDataURL();
+        },
+       
+       restore_mask(mask_b64){
+            let canvas = this.canvas;
+            let ctx =  canvas.getContext("2d");
+            
+            var image = new Image();
+            image.onload = function() {
+                ctx.drawImage(image, 0, 0);
+            };
+            image.src = mask_b64
         }
     },
 
diff --git a/electron_app/src/components_bare/LoaderModal.vue b/electron_app/src/components_bare/LoaderModal.vue
index cc726215..df4960e3 100644
--- a/electron_app/src/components_bare/LoaderModal.vue
+++ b/electron_app/src/components_bare/LoaderModal.vue
@@ -54,7 +54,7 @@ export default {
 <style scoped>
     .center {
       margin: 0;
-      position: absolute;
+      position: fixed;
       top: 50%;
       left: 50%;
       -ms-transform: translate(-50%, -50%);
diff --git a/electron_app/src/components_bare/SDOptionsDropdown.vue b/electron_app/src/components_bare/SDOptionsDropdown.vue
deleted file mode 100644
index 34b10872..00000000
--- a/electron_app/src/components_bare/SDOptionsDropdown.vue
+++ /dev/null
@@ -1,534 +0,0 @@
-<template>
-    <div style="float:right;margin-top: -5px;">
-        <b-dropdown id="dropdown-form" variant="link" ref="dropdown" toggle-class="text-decoration-none" no-caret>
-
-            <template #button-content>
-                <div class="l_button" style="">Options</div>
-            </template>
-
-            <b-dropdown-form style="min-width: 350px;max-height: calc(100vh - 300px); overflow-y: scroll;">
-                <br>
-                <div style="display: flex;flex-wrap: wrap;justify-content: center;gap: 15px;">
-
-
-                    <span v-if="elements_extra && elements_extra.includes('controlnet')">
-                        <div class="options_title">
-                            <div class="options_title_box" style="width: 165px;">
-                                <span>ControlNet Model</span>
-                                <span class="options_desc">What aspect of the input image it should use to generate the image.</span>
-                            </div>
-                            <div class="options_input" style="width: 115px;">
-                                <svg width="18" height="19" viewBox="0 0 18 19" fill="none"
-                                    xmlns="http://www.w3.org/2000/svg">
-                                    <path d="M12 5.5H12.01" stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M14 1.5H4C2.34315 1.5 1 2.84315 1 4.5V14.5C1 16.1569 2.34315 17.5 4 17.5H14C15.6569 17.5 17 16.1569 17 14.5V4.5C17 2.84315 15.6569 1.5 14 1.5Z"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M1 12.5L5 8.50001C5.45606 8.06117 5.97339 7.83014 6.5 7.83014C7.02661 7.83014 7.54394 8.06117 8 8.50001L13 13.5"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M11 11.5L12 10.5C12.4561 10.0612 12.9734 9.83014 13.5 9.83014C14.0266 9.83014 14.5439 10.0612 15 10.5L17 12.5"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                </svg>
-
-                                <b-form-select v-model="options_model_values.selected_control"
-                                    :options="['Body Pose' , 'Depth' , 'Scribble' ]"
-                                    required></b-form-select>
-                            </div>
-                        </div>
-                    </span>
-
-                    <span v-if="elements_extra && elements_extra.includes('controlnet')">
-                        <div class="options_title">
-                            <div class="options_title_box" style="width: 165px;">
-                                <span>Automatically generate control</span>
-                                <span class="options_desc">If it should automatically generate the control. If you select No, you have to input raw control image.</span>
-                            </div>
-                            <div class="options_input" style="width: 115px;">
-                                <svg width="18" height="19" viewBox="0 0 18 19" fill="none"
-                                    xmlns="http://www.w3.org/2000/svg">
-                                    <path d="M12 5.5H12.01" stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M14 1.5H4C2.34315 1.5 1 2.84315 1 4.5V14.5C1 16.1569 2.34315 17.5 4 17.5H14C15.6569 17.5 17 16.1569 17 14.5V4.5C17 2.84315 15.6569 1.5 14 1.5Z"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M1 12.5L5 8.50001C5.45606 8.06117 5.97339 7.83014 6.5 7.83014C7.02661 7.83014 7.54394 8.06117 8 8.50001L13 13.5"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M11 11.5L12 10.5C12.4561 10.0612 12.9734 9.83014 13.5 9.83014C14.0266 9.83014 14.5439 10.0612 15 10.5L17 12.5"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                </svg>
-
-                                <b-form-select v-model="options_model_values.do_controlnet_preprocess"
-                                    :options="['Yes' , 'No' ]"
-                                    required></b-form-select>
-                            </div>
-                        </div>
-                    </span>
-
-
-
-                    <span v-if="!elements_hidden.includes('inp_img_strength')">
-                        <div style="display: flex;flex-direction: column;width: 300px;">
-                            <div class="options_title_box">
-                                <span>Input Strength</span>
-                                <span class="options_desc">How  closely to stick to the input image.  (lower
-                                    numbers makes the AI do more change)</span>
-                            </div>
-                            <input type="range" min="10" max="90"  :value="options_model_values.inp_img_strength*100"   step='0.01' class="slider"
-                                @input="SetStrength" list='tickmarks'>
-                            <div id="tickmarks">
-                                <p>10</p>
-                                <p>30</p>
-                                <p>40</p>
-                                <p>70</p>
-                                <p>90</p>
-                            </div>
-                        </div>
-                    </span>
-
-
-                    <span v-if="!elements_hidden.includes('num_imgs')">
-                        <div class="options_title">
-                            <div class="options_title_box" style="width: 205px;">
-                                <span>Number of images</span>
-                                <span class="options_desc">How many images are generated in total.</span>
-                            </div>
-                            <div class="options_input" style="width: 75px;">
-                                <svg width="18" height="19" viewBox="0 0 18 19" fill="none"
-                                    xmlns="http://www.w3.org/2000/svg">
-                                    <path d="M12 5.5H12.01" stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M14 1.5H4C2.34315 1.5 1 2.84315 1 4.5V14.5C1 16.1569 2.34315 17.5 4 17.5H14C15.6569 17.5 17 16.1569 17 14.5V4.5C17 2.84315 15.6569 1.5 14 1.5Z"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M1 12.5L5 8.50001C5.45606 8.06117 5.97339 7.83014 6.5 7.83014C7.02661 7.83014 7.54394 8.06117 8 8.50001L13 13.5"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M11 11.5L12 10.5C12.4561 10.0612 12.9734 9.83014 13.5 9.83014C14.0266 9.83014 14.5439 10.0612 15 10.5L17 12.5"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                </svg>
-                                <b-form-select v-model="options_model_values.num_imgs" id="num_imgs"
-                                    :options="[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 30, 50, 100]"
-                                    required>
-                                </b-form-select>
-
-                            </div>
-                        </div>
-                    </span>                    
-
-                    <span v-if="!elements_hidden.includes('img_h')">
-                        <div class="options_title">
-                            <div class="options_title_box" style="width: 115px;">
-                                <span>Resolution</span>
-                            </div>
-                            <div style="display: inline-flex;gap: 22px;">
-                                <div class="options_input" style="justify-content: center;width: 75px;">
-                                    <svg width="18" height="20" viewBox="0 0 13 13" fill="none"
-                                        xmlns="http://www.w3.org/2000/svg">
-                                        <path
-                                            d="M2.74162 6.09644V3.05541C2.74162 2.78657 2.84842 2.52873 3.03852 2.33863C3.22862 2.14853 3.48646 2.04173 3.7553 2.04173H9.83736C10.1062 2.04173 10.364 2.14853 10.5541 2.33863C10.7442 2.52873 10.851 2.78657 10.851 3.05541V6.09644"
-                                            stroke="#A2A3AA" stroke-width="1.01368" stroke-linecap="round"
-                                            stroke-linejoin="round" />
-                                        <path d="M5.78269 9.1374H2.23482" stroke="#A2A3AA" stroke-width="1.01368"
-                                            stroke-linecap="round" stroke-linejoin="round" />
-                                        <path d="M11.3579 9.1374H7.81006" stroke="#A2A3AA" stroke-width="1.01368"
-                                            stroke-linecap="round" stroke-linejoin="round" />
-                                        <path d="M3.75533 7.61689L2.23482 9.1374L3.75533 10.6579" stroke="#A2A3AA"
-                                            stroke-width="1.01368" stroke-linecap="round" stroke-linejoin="round" />
-                                        <path d="M9.83737 7.61689L11.3579 9.1374L9.83737 10.6579" stroke="#A2A3AA"
-                                            stroke-width="1.01368" stroke-linecap="round" stroke-linejoin="round" />
-                                    </svg>
-
-
-                                    <b-form-select v-model="options_model_values.img_w"
-                                        :options="[64 * 4, 64 * 5, 64 * 6, 64 * 7, 64 * 8, 64 * 9, 64 * 10, 64 * 11, 64 * 12, 64*13 , 64*14]"
-                                        required></b-form-select>
-                                </div>
-                                <div class="options_input" style="justify-content: center;width: 75px;">
-                                    <svg width="18" height="20" viewBox="0 0 14 13" fill="none"
-                                        xmlns="http://www.w3.org/2000/svg">
-                                        <path
-                                            d="M7.05545 10.1511H4.01442C3.74558 10.1511 3.48775 10.0443 3.29765 9.85425C3.10755 9.66414 3.00075 9.40631 3.00075 9.13747V3.05541C3.00075 2.78657 3.10755 2.52873 3.29765 2.33863C3.48775 2.14853 3.74558 2.04173 4.01442 2.04173H7.05545"
-                                            stroke="#A2A3AA" stroke-width="1.01368" stroke-linecap="round"
-                                            stroke-linejoin="round" />
-                                        <path d="M10.0965 7.11V10.6579" stroke="#A2A3AA" stroke-width="1.01368"
-                                            stroke-linecap="round" stroke-linejoin="round" />
-                                        <path d="M10.0965 1.53483V5.0827" stroke="#A2A3AA" stroke-width="1.01368"
-                                            stroke-linecap="round" stroke-linejoin="round" />
-                                        <path d="M8.57599 9.1374L10.0965 10.6579L11.617 9.1374" stroke="#A2A3AA"
-                                            stroke-width="1.01368" stroke-linecap="round" stroke-linejoin="round" />
-                                        <path d="M8.57599 3.05534L10.0965 1.53483L11.617 3.05534" stroke="#A2A3AA"
-                                            stroke-width="1.01368" stroke-linecap="round" stroke-linejoin="round" />
-                                    </svg>
-                                    <b-form-select v-model="options_model_values.img_h"
-                                        :options="[64 * 4, 64 * 5, 64 * 6, 64 * 7, 64 * 8, 64 * 9, 64 * 10, 64 * 11, 64 * 12, 64*13 , 64*14]"
-                                        required></b-form-select>
-                                </div>
-                            </div>
-
-                        </div>
-                    </span>
-
-                    <span v-if="!elements_hidden.includes('seed')">
-                        <div class="options_title">
-                            <div class="options_title_box" style="width: 155px;">
-                                <span>Seed</span>
-                                <span class="options_desc">Starting point for iterations (any random
-                                    number will do; DB will pick one if left blank)</span>
-                            </div>
-                            <div class="options_input" style="width: 125px;">
-                                <svg style="height: auto;" width="20" height="20" viewBox="0 0 20 19" fill="none"
-                                    xmlns="http://www.w3.org/2000/svg">
-                                    <path
-                                        d="M10 7.5C10 5.9087 9.36786 4.38258 8.24264 3.25736C7.11742 2.13214 5.5913 1.5 4 1.5H1V3.5C1 5.0913 1.63214 6.61742 2.75736 7.74264C3.88258 8.86786 5.4087 9.5 7 9.5H10"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" />
-                                    <path
-                                        d="M10 11.5C10 9.9087 10.6321 8.38258 11.7574 7.25736C12.8826 6.13214 14.4087 5.5 16 5.5H19V6.5C19 8.0913 18.3679 9.61742 17.2426 10.7426C16.1174 11.8679 14.5913 12.5 13 12.5H10"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" />
-                                    <path d="M10 17.5V7.5" stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                </svg>
-
-                                <b-form-input onkeypress="return event.keyCode != 13;" class="custom-input"
-                                    v-model="options_model_values.seed" type="number" width="70" value="100" maxlength="5"
-                                    placeholder="-1"></b-form-input>
-                            </div>
-                        </div>
-                    </span>
-
-                    <span v-if="!elements_hidden.includes('batch_size')">
-                        <b-form-group inline label="" style="margin-bottom: 6px;">
-                                <div class="options_title">
-                                    <div class="options_title_box" style="width: 205px;">
-                                        <span>Steps</span>
-                                        <span class="options_desc">Iterations of the image (more steps means more detail &
-                                            more processing time - best to start around 10)</span>
-                                    </div>
-                                    <div class="options_input" style="width: 75px;">
-                                        <svg width="18" height="15" viewBox="0 0 18 15" fill="none"
-                                            xmlns="http://www.w3.org/2000/svg">
-                                            <path d="M1 13.5H5V9.5H9V5.5H13V1.5H17" stroke="#A2A3AA" stroke-width="2"
-                                                stroke-linecap="round" stroke-linejoin="round" />
-                                        </svg>
-
-                                        <b-form-select v-model="options_model_values.dif_steps"
-                                            :options="[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75]"
-                                            required></b-form-select>
-                                    </div>
-                                </div>
-                        </b-form-group>
-                    </span>
-
-                    <span v-if="elements_extra && elements_extra.includes('sampler')">
-                        <div class="options_title">
-                            <div class="options_title_box" style="width: 165px;">
-                                <span>Sampler</span>
-                                <span class="options_desc">The sampling algorithm used by Stable Diffusion to generate images.</span>
-                            </div>
-                            <div class="options_input" style="width: 115px;">
-                                <svg width="18" height="19" viewBox="0 0 18 19" fill="none"
-                                    xmlns="http://www.w3.org/2000/svg">
-                                    <path d="M12 5.5H12.01" stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M14 1.5H4C2.34315 1.5 1 2.84315 1 4.5V14.5C1 16.1569 2.34315 17.5 4 17.5H14C15.6569 17.5 17 16.1569 17 14.5V4.5C17 2.84315 15.6569 1.5 14 1.5Z"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M1 12.5L5 8.50001C5.45606 8.06117 5.97339 7.83014 6.5 7.83014C7.02661 7.83014 7.54394 8.06117 8 8.50001L13 13.5"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M11 11.5L12 10.5C12.4561 10.0612 12.9734 9.83014 13.5 9.83014C14.0266 9.83014 14.5439 10.0612 15 10.5L17 12.5"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                </svg>
-
-                                <b-form-select v-model="options_model_values.selected_sampler"
-                                    :options="['ddim' , 'lmsd' , 'pndm' , 'k_euler_ancestral' , 'k_euler' , 'ddim_v' ]"
-                                    required></b-form-select>
-                            </div>
-                        </div>
-                    </span>
-
-                     <span v-if="elements_extra && elements_extra.includes('use_soft_seed')">
-                        <div class="options_title">
-                            <div class="options_title_box" style="width: 205px;">
-                                <span>Similar images</span>
-                                <span class="options_desc">If it should generate similar images for a given seed.</span>
-                            </div>
-                            <div class="options_input" style="width: 75px;">
-                                <svg width="18" height="19" viewBox="0 0 18 19" fill="none"
-                                    xmlns="http://www.w3.org/2000/svg">
-                                    <path d="M12 5.5H12.01" stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M14 1.5H4C2.34315 1.5 1 2.84315 1 4.5V14.5C1 16.1569 2.34315 17.5 4 17.5H14C15.6569 17.5 17 16.1569 17 14.5V4.5C17 2.84315 15.6569 1.5 14 1.5Z"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M1 12.5L5 8.50001C5.45606 8.06117 5.97339 7.83014 6.5 7.83014C7.02661 7.83014 7.54394 8.06117 8 8.50001L13 13.5"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M11 11.5L12 10.5C12.4561 10.0612 12.9734 9.83014 13.5 9.83014C14.0266 9.83014 14.5439 10.0612 15 10.5L17 12.5"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                </svg>
-                                <b-form-select v-model="options_model_values.use_soft_seed" id="use_soft_seed"
-                                    :options="['Yes' , 'No']"
-                                    required>
-                                </b-form-select>
-
-                            </div>
-                        </div>
-                    </span>           
-
-
-                    <span v-if="!elements_hidden.includes('guidence_scale')">
-                        <b-form-group inline label="" style="margin-bottom: 6px;">
-                            <div style="display: flex;flex-direction: column;width: 300px;">
-                                <div class="options_title_box">
-                                    <span>Guidance scale</span>
-                                    <span class="options_desc">How closely to follow your prompt (lower
-                                        numbers give the AI more creativity)</span>
-                                </div>
-                                <input type="range" min="0" max="20" v-model="options_model_values.guidence_scale" step='0.01' class="slider"
-                                    @input="SetGuidenceScale" list='tickmarks'>
-                                <div id="tickmarks">
-                                    <p>0</p>
-                                    <p>5</p>
-                                    <p>10</p>
-                                    <p>15</p>
-                                    <p>20</p>
-                                </div>
-                            </div>
-                        </b-form-group>
-                    </span>
-
-
-                    <span v-if="!elements_hidden.includes('batch_size')">
-                        <div class="options_title">
-                            <div class="options_title_box" style="width: 205px;">
-                                <span>Batch size</span>
-                                <span class="options_desc">How many images are created at the sametime. (Leave at 1 if
-                                    you have 16GB or less RAM)</span>
-                            </div>
-                            <div class="options_input" style="width: 75px;">
-                                <svg width="18" height="19" viewBox="0 0 18 19" fill="none"
-                                    xmlns="http://www.w3.org/2000/svg">
-                                    <path
-                                        d="M15 5.5H7C5.89543 5.5 5 6.39543 5 7.5V15.5C5 16.6046 5.89543 17.5 7 17.5H15C16.1046 17.5 17 16.6046 17 15.5V7.5C17 6.39543 16.1046 5.5 15 5.5Z"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M13 5.5V3.5C13 2.96957 12.7893 2.46086 12.4142 2.08579C12.0391 1.71071 11.5304 1.5 11 1.5H3C2.46957 1.5 1.96086 1.71071 1.58579 2.08579C1.21071 2.46086 1 2.96957 1 3.5V11.5C1 12.0304 1.21071 12.5391 1.58579 12.9142C1.96086 13.2893 2.46957 13.5 3 13.5H5"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                </svg>
-                                <b-form-select v-model="options_model_values.batch_size" :options="[1, 2, 3, 4, 5, 6]"
-                                    required></b-form-select>
-                            </div>
-                        </div>
-
-                    </span>
-
-                    
-
-                    <span v-if="!elements_hidden.includes('custom_model')">
-                        <div class="options_title">
-                            <div class="options_title_box" style="width: 165px;">
-                                <span>Custom Model</span>
-                                <span class="options_desc">You can use a custom stable diffusion model. Open settings to add a ckpt model.</span>
-                            </div>
-                            <div class="options_input" style="width: 115px;">
-                                <svg width="18" height="19" viewBox="0 0 18 19" fill="none"
-                                    xmlns="http://www.w3.org/2000/svg">
-                                    <path d="M12 5.5H12.01" stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M14 1.5H4C2.34315 1.5 1 2.84315 1 4.5V14.5C1 16.1569 2.34315 17.5 4 17.5H14C15.6569 17.5 17 16.1569 17 14.5V4.5C17 2.84315 15.6569 1.5 14 1.5Z"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M1 12.5L5 8.50001C5.45606 8.06117 5.97339 7.83014 6.5 7.83014C7.02661 7.83014 7.54394 8.06117 8 8.50001L13 13.5"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                    <path
-                                        d="M11 11.5L12 10.5C12.4561 10.0612 12.9734 9.83014 13.5 9.83014C14.0266 9.83014 14.5439 10.0612 15 10.5L17 12.5"
-                                        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
-                                        stroke-linejoin="round" />
-                                </svg>
-
-                                <b-form-select v-model="options_model_values.selected_model"
-                                    :options="['Default'].concat(Object.keys(options_model_values.app_state.app_data.custom_models))"
-                                    required></b-form-select>
-                            </div>
-                        </div>
-                    </span>
-
-                    <div class="options_title">
-                        <div class="options_title_box" style="width: 205px;">
-                            <span>Negative Prompt</span>
-                            <span class="options_desc">Negative prompt allows adding things to avoid in the image,</span>
-                        </div>
-                        <div class="options_input" style="width: 75px;">
-                            <div v-if="(!options_model_values.is_negative_prompt_avail) && !elements_hidden.includes('nagative_prompt')"
-                                class="l_button"
-                                @click="options_model_values.is_negative_prompt_avail = !options_model_values.is_negative_prompt_avail">
-                                Enable </div>
-                            <div v-else class="l_button"
-                                @click="options_model_values.is_negative_prompt_avail = !options_model_values.is_negative_prompt_avail">
-                                Disable</div>
-                        </div>
-                    </div>
-
-
-
-                    
-                </div>
-                <br>
-            </b-dropdown-form>
-        </b-dropdown>
-    </div>
-</template>
-<script>
-export default {
-    name: 'SDOptionsDropdown',
-    props: {
-        options_model_values: Object,
-        elements_hidden: Array,
-        elements_extra:Array, 
-    },
-    components: {},
-    mounted() {
-        this.$nextTick(function () {
-            var sliders = document.getElementsByClassName('slider');
-            for (var i = 0; i < sliders.length; i++) {
-                var slider = sliders[i];
-                var value = slider.value / (slider.max) * (100 - slider.min);
-                slider.style.background = 'linear-gradient(to right, var(--slider-progress) 0%, var(--slider-progress) ' + value + '%, var(--slider-progress_end) ' + value + '%, var(--slider-progress_end) 100%)';
-            }
-        })
-    },
-    data() {
-        return {};
-    },
-    methods: {
-        SetStrength(e) {
-            var value = (e.target.value - e.target.min) / (e.target.max - e.target.min) * 100
-            e.target.style.background = 'linear-gradient(to right, var(--slider-progress) 0%, var(--slider-progress) ' + value + '%, var(--slider-progress_end) ' + value + '%, var(--slider-progress_end) 100%)'
-            this.options_model_values.inp_img_strength = Number(e.target.value / 100);
-        },
-        SetGuidenceScale(e) {
-            var value = (e.target.value - e.target.min) / (e.target.max - e.target.min) * 100
-            e.target.style.background = 'linear-gradient(to right, var(--slider-progress) 0%, var(--slider-progress) ' + value + '%, var(--slider-progress_end) ' + value + '%, var(--slider-progress_end) 100%)'
-            this.options_model_values.guidence_scale = Number(e.target.value)
-        }
-    },
-}
-</script>
-<style scoped>
-.b-dropdown ::-webkit-scrollbar {
-    appearance: none;
-    width: 7px;
-}
-.b-dropdown ::-webkit-scrollbar-thumb {
-    border-radius: 4px;
-    background-color: rgba(0, 0, 0, .5);
-    box-shadow: 0 0 1px rgba(255, 255, 255, .5);
-}
-.options_title {
-    display: flex;
-    flex-direction: row;
-    align-items: center;
-    justify-content: space-around;
-    width: 330px;
-}
-
-.options_title_box span {
-    font-weight: 600;
-    font-size: 14px;
-    line-height: 19px;
-}
-
-.options_title_box .options_desc {
-    font-weight: 400;
-    font-size: 12px;
-}
-
-.custom-select {
-    appearance: none;
-    outline: none;
-    border: none;
-    background: none;
-    min-width: 20px;
-    font-weight: 600;
-    font-size: 14px;
-    line-height: 19px;
-    text-align: center;
-    cursor: pointer;
-    padding-left: 32px;
-
-}
-
-.options_input svg {
-    margin-right: -32px;
-}
-
-.custom-input {
-    border: none;
-    background: none;
-    min-width: 20px;
-    font-weight: 600;
-    font-size: 14px;
-    line-height: 19px;
-    text-align: center;
-}
-
-.custom-input::-webkit-outer-spin-button,
-.custom-input::-webkit-inner-spin-button {
-    appearance: none;
-    margin: 0;
-}
-
-.slider {
-    background: linear-gradient(to right, var(--slider-progress) 0%, var(--slider-progress) 37.5%, var(--slider-progress_end) 37.5%, var(--slider-progress_end) 100%);
-    border-radius: 8px;
-    height: 15px;
-    margin-top: 4px;
-    outline: none;
-    transition: background 450ms ease-in;
-    appearance: none;
-    cursor: pointer;
-}
-
-.slider::-webkit-slider-thumb {
-    appearance: none;
-    width: 25px;
-    height: 25px;
-    border-radius: 50%;
-    border: 3px solid var(--slider-border);
-    background: var(--slider-circle);
-}
-
-#tickmarks {
-    display: flex;
-    justify-content: space-between;
-    padding: 0 10px;
-}
-</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/TwoColAppletLayout.vue b/electron_app/src/components_bare/TwoColAppletLayout.vue
new file mode 100644
index 00000000..4fbe692c
--- /dev/null
+++ b/electron_app/src/components_bare/TwoColAppletLayout.vue
@@ -0,0 +1,77 @@
+<template>
+    <div class="applet_container" style="width:100% ; height:100%;  ">
+        
+        <div class="left_controls" style="height: 100%; max-width: 350px;   ">
+            <div class="left_controls_inputs " style="padding: 20px">
+                <slot name="input_workspace"></slot>
+            </div>
+           
+            <div style="padding:10px;">
+                <slot name="input_buttons"></slot>
+            </div>
+
+        </div>
+
+        <div class="right_workpace">
+            <slot name="output_workpace"></slot>
+        </div>
+        
+    </div>
+</template>
+<script>
+
+export default {
+    name: 'TwoColAppletLayout',
+    props: {
+        app:Object, 
+    },
+    components: {   },
+    mounted() {
+
+    },
+    data() {
+        return {
+           
+        };
+    },
+    methods: {
+        
+    },  
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+.applet_container{
+  display: flex;
+  flex-wrap: wrap;
+   justify-content: center;
+   align-items: center;
+
+}
+
+.right_workpace{
+    height: 100%;
+    width: calc( 100% - 350px);
+    overflow-y: auto;
+}
+
+.left_controls{
+    border-width: 0px;
+    border-right-width: 1px;
+    border-style: solid;
+    border-color: var( --thin-border-color);
+    height: 100%;
+
+}
+
+.left_controls_inputs{
+    max-height: calc( 100% - 50px );
+    overflow-y: auto;
+    width: 100%;
+
+}
+
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/empty_component.vue b/electron_app/src/components_bare/empty_component.vue
index 02fb2e50..23ed00e6 100644
--- a/electron_app/src/components_bare/empty_component.vue
+++ b/electron_app/src/components_bare/empty_component.vue
@@ -3,7 +3,7 @@
 <script>
 export default {
     name: 'EmptyComponent',
-    props: {},
+    props: { app:Object , asset_details:Object },
     components: {},
     mounted() {
 
@@ -14,6 +14,10 @@ export default {
     methods: {
 
     },
+
+    computed: {
+        
+    }
 }
 </script>
 <style>
diff --git a/electron_app/src/components_bare/icon_library.js b/electron_app/src/components_bare/icon_library.js
new file mode 100644
index 00000000..b3dacd66
--- /dev/null
+++ b/electron_app/src/components_bare/icon_library.js
@@ -0,0 +1,124 @@
+
+
+let icon_library = {}
+
+
+
+icon_library['share'] = "M8.3042 13.0146C8.66113 13.0146 8.96826 12.7158 8.96826 12.3672V3.84229L8.91846 2.59717L9.47461 3.18652L10.7363 4.53125C10.8525 4.66406 11.0186 4.73047 11.1846 4.73047C11.5249 4.73047 11.7905 4.48145 11.7905 4.14111C11.7905 3.9668 11.7158 3.83398 11.5913 3.70947L8.78564 1.00342C8.61963 0.837402 8.47852 0.779297 8.3042 0.779297C8.13818 0.779297 7.99707 0.837402 7.82275 1.00342L5.01709 3.70947C4.89258 3.83398 4.82617 3.9668 4.82617 4.14111C4.82617 4.48145 5.0752 4.73047 5.42383 4.73047C5.58154 4.73047 5.76416 4.66406 5.88037 4.53125L7.13379 3.18652L7.69824 2.59717L7.64844 3.84229V12.3672C7.64844 12.7158 7.94727 13.0146 8.3042 13.0146ZM3.54785 19.5142H13.0688C14.8037 19.5142 15.6753 18.6509 15.6753 16.9409V8.65674C15.6753 6.94678 14.8037 6.0835 13.0688 6.0835H10.7529V7.41992H13.0439C13.8657 7.41992 14.3389 7.86816 14.3389 8.73145V16.8662C14.3389 17.7295 13.8657 18.1777 13.0439 18.1777H3.56445C2.73438 18.1777 2.27783 17.7295 2.27783 16.8662V8.73145C2.27783 7.86816 2.73438 7.41992 3.56445 7.41992H5.86377V6.0835H3.54785C1.81299 6.0835 0.941406 6.94678 0.941406 8.65674V16.9409C0.941406 18.6509 1.81299 19.5142 3.54785 19.5142Z"
+
+icon_library['sidebar_collapse'] = "M2.81982 15.7852H17.1802C18.9233 15.7852 19.7866 14.9219 19.7866 13.2119V3.07666C19.7866 1.3667 18.9233 0.503418 17.1802 0.503418H2.81982C1.08496 0.503418 0.213379 1.3584 0.213379 3.07666V13.2119C0.213379 14.9302 1.08496 15.7852 2.81982 15.7852ZM2.83643 14.4487C2.00635 14.4487 1.5498 14.0088 1.5498 13.1455V3.14307C1.5498 2.27979 2.00635 1.83984 2.83643 1.83984H6.53857V14.4487H2.83643ZM17.1636 1.83984C17.9854 1.83984 18.4502 2.27979 18.4502 3.14307V13.1455C18.4502 14.0088 17.9854 14.4487 17.1636 14.4487H7.8418V1.83984H17.1636ZM4.94482 4.91943C5.19385 4.91943 5.41797 4.69531 5.41797 4.45459C5.41797 4.20557 5.19385 3.98975 4.94482 3.98975H3.16016C2.91113 3.98975 2.69531 4.20557 2.69531 4.45459C2.69531 4.69531 2.91113 4.91943 3.16016 4.91943H4.94482ZM4.94482 7.06934C5.19385 7.06934 5.41797 6.84521 5.41797 6.59619C5.41797 6.34717 5.19385 6.13965 4.94482 6.13965H3.16016C2.91113 6.13965 2.69531 6.34717 2.69531 6.59619C2.69531 6.84521 2.91113 7.06934 3.16016 7.06934H4.94482ZM4.94482 9.21094C5.19385 9.21094 5.41797 9.00342 5.41797 8.75439C5.41797 8.50537 5.19385 8.28955 4.94482 8.28955H3.16016C2.91113 8.28955 2.69531 8.50537 2.69531 8.75439C2.69531 9.00342 2.91113 9.21094 3.16016 9.21094H4.94482Z"
+
+
+
+
+// icon_library['star'] = "
+icon_library['star'] = `
+<svg  width="100%" height="100%" viewBox="0 0 14 12" fill="none" xmlns="http://www.w3.org/2000/svg">
+    <path d="M3.3208 11.5303C3.54102 11.7021 3.82031 11.6431 4.15332 11.4014L6.99463 9.31201L9.84131 11.4014C10.1743 11.6431 10.4482 11.7021 10.6738 11.5303C10.894 11.3638 10.9424 11.0898 10.8081 10.6978L9.68555 7.35693L12.5537 5.29443C12.8867 5.05811 13.021 4.81104 12.9351 4.54248C12.8491 4.28467 12.5967 4.15576 12.1831 4.16113L8.66504 4.18262L7.59619 0.825684C7.46729 0.428223 7.27393 0.229492 6.99463 0.229492C6.7207 0.229492 6.52734 0.428223 6.39844 0.825684L5.32959 4.18262L1.81152 4.16113C1.39795 4.15576 1.14551 4.28467 1.05957 4.54248C0.968262 4.81104 1.10791 5.05811 1.44092 5.29443L4.30908 7.35693L3.18652 10.6978C3.05225 11.0898 3.10059 11.3638 3.3208 11.5303ZM4.09424 10.4668C4.0835 10.4561 4.08887 10.4507 4.09424 10.4185L5.16309 7.34619C5.23828 7.13672 5.19531 6.97021 5.00732 6.84131L2.33252 4.99365C2.30566 4.97754 2.30029 4.9668 2.30566 4.95068C2.31104 4.93457 2.32178 4.93457 2.354 4.93457L5.60352 4.99365C5.82373 4.99902 5.96338 4.90771 6.0332 4.6875L6.96777 1.57764C6.97314 1.54541 6.98389 1.53467 6.99463 1.53467C7.01074 1.53467 7.02148 1.54541 7.02686 1.57764L7.96143 4.6875C8.03125 4.90771 8.1709 4.99902 8.39111 4.99365L11.6406 4.93457C11.6729 4.93457 11.6836 4.93457 11.689 4.95068C11.6943 4.9668 11.6836 4.97754 11.6621 4.99365L8.9873 6.84131C8.79932 6.97021 8.75635 7.13672 8.83154 7.34619L9.90039 10.4185C9.90576 10.4507 9.91113 10.4561 9.90039 10.4668C9.88965 10.4829 9.87354 10.4722 9.85205 10.4561L7.26855 8.48486C7.09668 8.35059 6.89795 8.35059 6.72607 8.48486L4.14258 10.4561C4.12109 10.4722 4.10498 10.4829 4.09424 10.4668Z" fill="#007AFF"/>
+</svg>
+`
+
+
+icon_library["two_boxes"] = `
+    <svg width="100%" height="100%" viewBox="0 0 18 19" fill="none"
+        xmlns="http://www.w3.org/2000/svg">
+        <path
+            d="M15 5.5H7C5.89543 5.5 5 6.39543 5 7.5V15.5C5 16.6046 5.89543 17.5 7 17.5H15C16.1046 17.5 17 16.6046 17 15.5V7.5C17 6.39543 16.1046 5.5 15 5.5Z"
+            stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
+            stroke-linejoin="round" />
+        <path
+            d="M13 5.5V3.5C13 2.96957 12.7893 2.46086 12.4142 2.08579C12.0391 1.71071 11.5304 1.5 11 1.5H3C2.46957 1.5 1.96086 1.71071 1.58579 2.08579C1.21071 2.46086 1 2.96957 1 3.5V11.5C1 12.0304 1.21071 12.5391 1.58579 12.9142C1.96086 13.2893 2.46957 13.5 3 13.5H5"
+            stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
+            stroke-linejoin="round" />
+    </svg>
+
+`
+
+
+icon_library["photo"] = `
+   <svg width="100%" height="100%" viewBox="0 0 18 19" fill="none"
+	    xmlns="http://www.w3.org/2000/svg">
+	    <path d="M12 5.5H12.01" stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
+	        stroke-linejoin="round" />
+	    <path
+	        d="M14 1.5H4C2.34315 1.5 1 2.84315 1 4.5V14.5C1 16.1569 2.34315 17.5 4 17.5H14C15.6569 17.5 17 16.1569 17 14.5V4.5C17 2.84315 15.6569 1.5 14 1.5Z"
+	        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
+	        stroke-linejoin="round" />
+	    <path
+	        d="M1 12.5L5 8.50001C5.45606 8.06117 5.97339 7.83014 6.5 7.83014C7.02661 7.83014 7.54394 8.06117 8 8.50001L13 13.5"
+	        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
+	        stroke-linejoin="round" />
+	    <path
+	        d="M11 11.5L12 10.5C12.4561 10.0612 12.9734 9.83014 13.5 9.83014C14.0266 9.83014 14.5439 10.0612 15 10.5L17 12.5"
+	        stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
+	        stroke-linejoin="round" />
+	</svg>
+
+`
+
+icon_library['img_width'] = `
+
+<svg width="100%" height="100%" viewBox="0 0 13 13" fill="none"
+    xmlns="http://www.w3.org/2000/svg">
+    <path
+        d="M2.74162 6.09644V3.05541C2.74162 2.78657 2.84842 2.52873 3.03852 2.33863C3.22862 2.14853 3.48646 2.04173 3.7553 2.04173H9.83736C10.1062 2.04173 10.364 2.14853 10.5541 2.33863C10.7442 2.52873 10.851 2.78657 10.851 3.05541V6.09644"
+        stroke="#A2A3AA" stroke-width="1.01368" stroke-linecap="round"
+        stroke-linejoin="round" />
+    <path d="M5.78269 9.1374H2.23482" stroke="#A2A3AA" stroke-width="1.01368"
+        stroke-linecap="round" stroke-linejoin="round" />
+    <path d="M11.3579 9.1374H7.81006" stroke="#A2A3AA" stroke-width="1.01368"
+        stroke-linecap="round" stroke-linejoin="round" />
+    <path d="M3.75533 7.61689L2.23482 9.1374L3.75533 10.6579" stroke="#A2A3AA"
+        stroke-width="1.01368" stroke-linecap="round" stroke-linejoin="round" />
+    <path d="M9.83737 7.61689L11.3579 9.1374L9.83737 10.6579" stroke="#A2A3AA"
+        stroke-width="1.01368" stroke-linecap="round" stroke-linejoin="round" />
+</svg>
+`
+
+
+icon_library['img_height'] = `
+<svg width="100%" height="100%" viewBox="0 0 14 13" fill="none"
+        xmlns="http://www.w3.org/2000/svg">
+        <path
+            d="M7.05545 10.1511H4.01442C3.74558 10.1511 3.48775 10.0443 3.29765 9.85425C3.10755 9.66414 3.00075 9.40631 3.00075 9.13747V3.05541C3.00075 2.78657 3.10755 2.52873 3.29765 2.33863C3.48775 2.14853 3.74558 2.04173 4.01442 2.04173H7.05545"
+            stroke="#A2A3AA" stroke-width="1.01368" stroke-linecap="round"
+            stroke-linejoin="round" />
+        <path d="M10.0965 7.11V10.6579" stroke="#A2A3AA" stroke-width="1.01368"
+            stroke-linecap="round" stroke-linejoin="round" />
+        <path d="M10.0965 1.53483V5.0827" stroke="#A2A3AA" stroke-width="1.01368"
+            stroke-linecap="round" stroke-linejoin="round" />
+        <path d="M8.57599 9.1374L10.0965 10.6579L11.617 9.1374" stroke="#A2A3AA"
+            stroke-width="1.01368" stroke-linecap="round" stroke-linejoin="round" />
+        <path d="M8.57599 3.05534L10.0965 1.53483L11.617 3.05534" stroke="#A2A3AA"
+            stroke-width="1.01368" stroke-linecap="round" stroke-linejoin="round" />
+    </svg>
+`
+
+icon_library['seed'] = `
+<svg style="height: auto;" width="100%" height="20" viewBox="0 0 20 19" fill="none"
+        xmlns="http://www.w3.org/2000/svg">
+        <path
+            d="M10 7.5C10 5.9087 9.36786 4.38258 8.24264 3.25736C7.11742 2.13214 5.5913 1.5 4 1.5H1V3.5C1 5.0913 1.63214 6.61742 2.75736 7.74264C3.88258 8.86786 5.4087 9.5 7 9.5H10"
+            stroke="#A2A3AA" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" />
+        <path
+            d="M10 11.5C10 9.9087 10.6321 8.38258 11.7574 7.25736C12.8826 6.13214 14.4087 5.5 16 5.5H19V6.5C19 8.0913 18.3679 9.61742 17.2426 10.7426C16.1174 11.8679 14.5913 12.5 13 12.5H10"
+            stroke="#A2A3AA" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" />
+        <path d="M10 17.5V7.5" stroke="#A2A3AA" stroke-width="2" stroke-linecap="round"
+            stroke-linejoin="round" />
+    </svg>
+
+
+`
+
+icon_library['steps'] = `
+<svg width="100%" height="100%" viewBox="0 0 18 15" fill="none"
+        xmlns="http://www.w3.org/2000/svg">
+        <path d="M1 13.5H5V9.5H9V5.5H13V1.5H17" stroke="#A2A3AA" stroke-width="2"
+            stroke-linecap="round" stroke-linejoin="round" />
+    </svg>
+
+`
+
+
+
+export {icon_library}
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/Accordian.vue b/electron_app/src/components_bare/inputform/Accordian.vue
new file mode 100644
index 00000000..0a94498a
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/Accordian.vue
@@ -0,0 +1,51 @@
+<template>
+    <div style="margin-left:-15px; margin-right:-15px; margin-bottom: -10px;">
+         <div class="options_title_box" v-b-toggle="'collapse-'+rand_no"  style="width: 100%; background-color: rgba(0,0,0,0.1); padding:9px; display:block">
+             <span  >{{config.title}}</span> <span style="float:right; margin-right:4px"  >+ </span>
+        </div>
+        
+        <b-collapse :id="'collapse-'+rand_no">
+            <div style="border-width: 1px; border-color:rgba(0,0,0,0.1); border-style: solid; padding: 15px">
+             
+             <ResolveInputComponent
+                 v-for="child_config in config.children"
+                 :form_values="form_values" 
+                 :config="child_config"
+                 :key="child_config.id"
+            > </ResolveInputComponent>
+        </div>
+    </b-collapse>
+        
+        
+        <br>
+    </div>
+
+</template>
+<script>
+
+import ResolveInputComponent from "./ResolveInputComponent.vue"
+
+export default {
+    name: 'Accordian',
+    props: {
+        config: Object , 
+        form_values: Object,
+    },
+    components: {'ResolveInputComponent':ResolveInputComponent},
+    mounted() {
+
+    },
+    data() {
+        return {
+            rand_no : Math.random().toString()
+        };
+    },
+    methods: {
+
+    },
+}
+</script>
+<style>
+</style>
+<style scoped>
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/BetterSelector.vue b/electron_app/src/components_bare/inputform/BetterSelector.vue
new file mode 100644
index 00000000..a2665321
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/BetterSelector.vue
@@ -0,0 +1,115 @@
+<template>
+    <div class="img_container"> 
+
+        <div v-for="option in zipped" :key="option.id"> 
+            <div 
+                :class="{ selected : form_values[config.id] == option.id }"  
+                @click="form_values[config.id] = option.id" 
+                style="float:left" > 
+                    <img class="grid_img" src="https://hips.hearstapps.com/hmg-prod/images/dog-puppy-on-garden-royalty-free-image-1586966191.jpg?crop=0.752xw:1.00xh;0.175xw,0&resize=1200:*">
+                    <span class="clear"></span>
+                    <center> 
+                        <p style="margin-bottom: 4px; zoom: 0.8">{{  option.val }}  </p>
+                    </center>
+                    
+                </div>
+
+                
+        </div>
+        <span class="clear"></span>
+    </div>
+</template>
+<script>
+
+import FormInputMixin from "./FormInputMixin.vue"
+import { icon_library } from "../icon_library.js"
+import Vue from "vue"
+
+export default {
+name: 'BetterSelector',
+mixins: [FormInputMixin],
+props: {
+    config: Object , 
+    form_values: Object,
+},
+components: {},
+
+mounted() {
+    if(this.form_values[this.config.id] === undefined){
+        Vue.set( this.form_values  , this.config.id  , this.config.default_value || this.config.options[0])
+    } 
+},
+data() {
+    return {
+        icon_library:icon_library,
+    };
+},
+methods: {
+
+},
+
+computed: {
+    zipped(){
+        let ret = []
+        for(let i=0 ; i < this.config.options.length; i++ ){
+            ret.push({id : this.config.options[i] , val :this.config.option_vals[i]  } )
+        }
+        return ret
+    }
+},
+
+watch : {
+   
+   'config.options': {
+       handler: function() {
+          if(!this.config.options.includes(this.form_values[this.config.id])){
+              if(this.config.options.length > 0){
+                if( this.config.default_value != undefined && this.config.options.includes(this.config.default_value) ){
+                    Vue.set(this.form_values,this.config.id , this.config.default_value )
+                } else {
+                    Vue.set(this.form_values,this.config.id , this.config.options[0] )
+                }
+                
+              }
+          }
+       },
+       deep: true
+   } , 
+
+},
+
+
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+.selected > img {
+    border-color: #3E7BFA;
+    border-width: 1;
+    border-style: solid;
+}
+
+span.clear { clear: left; display: block; }
+
+
+.grid_img{
+    height:93px;
+    width:93px;
+    margin:3px
+}
+
+.grid_img_five{
+    height: 53px;
+    width: 53px;
+    margin:3px
+}
+
+
+.img_container{
+    /* padding:10px; */
+    margin-bottom: 20px;
+}
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/Checkbox.vue b/electron_app/src/components_bare/inputform/Checkbox.vue
new file mode 100644
index 00000000..60f1a222
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/Checkbox.vue
@@ -0,0 +1,151 @@
+<template>
+
+   <div style="margin-left: 80px; padding-bottom:10px"> 
+        <!-- <input  :id="rand_id" type="checkbox"  @input="set_val()"> -->
+        <label class="switch" >
+            <input  :id="rand_id"  type="checkbox"  @input="set_val()" >
+            <span class="toggle round"></span>
+        </label>
+
+  </div> 
+
+</template>
+<script>
+
+import FormInputMixin from "./FormInputMixin.vue"
+import Vue from 'vue'
+
+export default {
+    name: 'Checkbox',
+    mixins: [FormInputMixin],
+    props: {
+        config: Object , 
+        form_values: Object,
+    },
+    components: {},
+    mounted() {
+
+       if(this.form_values[this.config.id] === undefined){
+            Vue.set( this.form_values  , this.config.id  , this.config.default_value || false )
+        } 
+        
+        this.set_el()
+    },
+    data() {
+        if(this.form_values[this.config.id] == 'true'){
+            Vue.set(this.form_values , this.config.id , true)
+        }
+        if(this.form_values[this.config.id] == 'false'){
+            Vue.set(this.form_values , this.config.id , false)
+        }
+
+        return {
+            rand_id : Math.random()
+        };
+    },
+    methods: {
+        set_val() {
+            let el = document.getElementById(this.rand_id)
+            let value = el.checked
+            Vue.set(this.form_values , this.config.id , value)
+        }, 
+        set_el(){
+
+            if(this.form_values[this.config.id] == 'true'){
+                Vue.set(this.form_values , this.config.id , true)
+            }
+            if(this.form_values[this.config.id] == 'false'){
+                Vue.set(this.form_values , this.config.id , false)
+            }   
+
+            let el = document.getElementById(this.rand_id)
+            let val = this.form_values[this.config.id]
+           
+            if(val == true  ){
+               el.checked = true
+            }
+            else{
+               el.checked = false
+            }
+        }
+    },
+
+    computed:{
+
+        cur_val(){
+            return this.form_values[this.config.id]
+        }
+    } , 
+
+    watch: {
+        'cur_val' : {
+            handler: function() {
+              this.set_el()
+            },
+            deep: false
+        } , 
+    }
+
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+.switch {
+  position: relative;
+  display: inline-block;
+  width: 60px;
+  height: 30px;
+  zoom:0.7;
+}
+
+.switch input { 
+  opacity: 0;
+  width: 0;
+  height: 0;
+}
+
+.toggle {
+  position: absolute;
+  cursor: pointer;
+  top: 0;
+  left: 0;
+  right: 0;
+  bottom: 0;
+  background-color: var(--input-form-el-color);
+  -webkit-transition: .4s;
+  transition: .4s;
+}
+
+.toggle:before {
+  position: absolute;
+  content: "";
+  height: 22px;
+  width: 23px;
+  left: 5px;
+  bottom: 4px;
+  background-color: white;
+  -webkit-transition: .4s;
+  transition: .4s;
+}
+
+input:checked + .toggle {
+  background-color: #3E7BFA;
+}
+
+
+input:checked + .toggle:before {
+  transform: translateX(27px);
+}
+
+.toggle.round {
+  border-radius: 34px;
+}
+
+.toggle.round:before {
+  border-radius: 50%;
+}
+
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/Dropdown.vue b/electron_app/src/components_bare/inputform/Dropdown.vue
new file mode 100644
index 00000000..43e76ccf
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/Dropdown.vue
@@ -0,0 +1,74 @@
+<template>
+
+        <div class="options_input" style="width: 95px; margin-left: 6px;">
+            <!-- <span v-html="icon_library"></span> -->
+            
+            <svg width="19px" height="19px"  v-html="icon_library[config.icon]"> </svg>
+
+
+            <b-form-select v-model="form_values[config.id]" :options="config.options"
+                required></b-form-select>
+        </div>
+</template>
+<script>
+
+import FormInputMixin from "./FormInputMixin.vue"
+import { icon_library } from "../icon_library.js"
+import Vue from "vue"
+
+export default {
+    name: 'Dropdown',
+    mixins: [FormInputMixin],
+    props: {
+        config: Object , 
+        form_values: Object,
+    },
+    components: {},
+    
+    mounted() {
+        if(this.form_values[this.config.id] === undefined){
+            Vue.set( this.form_values  , this.config.id  , this.config.default_value || this.config.options[0])
+        }
+        this.reset_selected_if_invalid()
+    },
+    data() {
+        return {
+            icon_library:icon_library,
+        };
+    },
+    methods: {
+        // if the selected option not in options list then reset the selected 
+        reset_selected_if_invalid(){
+            if(!this.config.options.includes(this.form_values[this.config.id])){
+                  if(this.config.options.length > 0){
+                    if( this.config.default_value != undefined && this.config.options.includes(this.config.default_value) ){
+                        Vue.set(this.form_values,this.config.id , this.config.default_value )
+                    } else {
+                        Vue.set(this.form_values,this.config.id , this.config.options[0] )
+                    }
+                    
+                  }
+              }
+        }
+    },
+
+    watch : {
+       
+       'config.options': {
+           handler: function() {
+              this.reset_selected_if_invalid()
+           },
+           deep: true
+       } , 
+
+   },
+
+
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/FilePathTextBox.vue b/electron_app/src/components_bare/inputform/FilePathTextBox.vue
new file mode 100644
index 00000000..155255c6
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/FilePathTextBox.vue
@@ -0,0 +1,57 @@
+<template>
+
+    <div class="options_input" style="width: 100%;">
+        
+
+        <b-form-input onkeypress="return event.keyCode != 13;" class="custom-input"
+               v-model="form_values[config.id]" :placeholder="config.placeholder"  :type="config.type"   style="height: 20px;"
+             ></b-form-input>
+        <div @click="choose_path" class="l_button button_small button_colored"> Choose </div>
+
+        <br>
+    </div>
+
+
+</template>
+<script>
+
+import FormInputMixin from "./FormInputMixin.vue"
+import { icon_library } from "../icon_library.js"
+import Vue from 'vue'
+
+
+export default {
+    name: 'FilePathTextBox',
+    mixins: [FormInputMixin],
+    props: {
+         config: Object , 
+        form_values: Object,
+    },
+    components: {},
+    mounted() {
+        if(this.form_values[this.config.id] === undefined && this.config.default_value ){
+            Vue.set( this.form_values  , this.config.id  , this.config.default_value  )
+        } 
+    },
+    data() {
+        return {
+            icon_library:icon_library,
+        };
+    },
+    methods: {
+        choose_path(){
+            let file_path = window.ipcRenderer.sendSync('file_dialog',  this.config.path_type );
+            
+            if(file_path && file_path != 'NULL'){
+                
+                Vue.set(this.form_values , this.config.id , file_path)
+            }  
+        }
+    },
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/FormInputMixin.vue b/electron_app/src/components_bare/inputform/FormInputMixin.vue
new file mode 100644
index 00000000..8f760e26
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/FormInputMixin.vue
@@ -0,0 +1,95 @@
+<script>
+
+function isItNumber(str) {
+  return /^-?[0-9]+(e[0-9]+)?(\.[0-9]+)?$/.test(str);
+}
+
+
+export default {
+    data: () => ({
+      is_form_entry_fresh : true 
+    }),
+    methods: {
+        
+        on_input_changed(){
+            this.is_form_entry_fresh = false;
+        },
+        
+        is_input_valid(){
+
+            for( let constraint of ( this.contraints|| []) ){
+                if( constraint == "non_empty" ){
+                    if( (! this.value) ||(this.value == ""))
+                        return {
+                            "is_valid" : false, 
+                            "msg" : "The value cannot be empty"
+                        }
+                }
+                else if( constraint == "is_int" ){
+                    if( parseInt(this.value).toString() != this.value.toString()  ){
+                        return{
+                            "is_valid" : false, 
+                            "msg" : "The value should be a valid integer"
+                        }
+                    }
+                }
+                else if( constraint == "is_float" ){
+                    if(!isItNumber(this.value)){
+                        return{
+                            "is_valid" : false, 
+                            "msg" : "The value should be a valid float number"
+                        }
+                    }
+                }
+                else if( constraint.startsWith("maxval_") ){
+                    let max_val = parseFloat( constraint.split("maxval_")[1]);
+                    if( parseFloat(this.value) > max_val){
+                        return{
+                            "is_valid" : false, 
+                            "msg" : "The value should not greater than " + max_val
+                        }
+                    }
+                }
+                else if( constraint.startsWith("minval_") ){
+                    let min_val = parseFloat( constraint.split("minval_")[1]);
+                    if( parseFloat(this.value) < min_val){
+                        return{
+                            "is_valid" : false, 
+                            "msg" : "The value should not less than " + min_val
+                        }
+                    }
+                }
+            }
+
+            return {
+                "is_valid" : true , 
+                "msg" : ""
+            }
+        },
+
+    },
+
+     watch : {
+       
+        'value': {
+            handler: function() {
+               this.on_input_changed()
+            },
+            deep: true
+        } , 
+
+    },
+
+
+    computed: {
+        invalid_prompt_str(){
+            if(this.is_disabled)
+                return "";
+            if(this.is_form_entry_fresh)
+                return "";
+            return this.is_input_valid()['msg']  ;
+        }
+    }
+}
+
+</script>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/ImageInput.vue b/electron_app/src/components_bare/inputform/ImageInput.vue
new file mode 100644
index 00000000..0f9ae5b8
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/ImageInput.vue
@@ -0,0 +1,128 @@
+<template>
+
+   <div>
+
+        <div v-if="form_values[config.id]" @drop.prevent="onDragFile" @dragover.prevent class="image_area" :class="{ crosshair_cur  : is_inpaint }"  style="height: 300px;  border-radius: 5px; padding:5px;">
+            <ImageCanvas :on_img_load="on_img_load" ref="inp_img_canvas" :is_inpaint="is_inpaint" :image_source="form_values[config.id]"  :is_disabled="false"  :canvas_id="rand_id" :canvas_d_id="rand_id+'d' "  ></ImageCanvas>
+        </div>
+        <div v-else @drop.prevent="onDragFile" @dragover.prevent @click="open_input_image" class="image_area" :class="{ pointer_cursor  : is_input_avail }" style="height:150px;  border-radius: 5px; padding:5px;">
+                <center>
+                <p style="margin-top: 60px; opacity: 70%; font-size: 13px;" >Click to add input image</p>
+            </center>
+        </div>
+
+        <div v-if="form_values[config.id] && is_input_avail" class="l_button" @click="open_input_image" >Change Image</div>
+        <div v-if="form_values[config.id] && is_input_avail" class="l_button" @click="form_values[config.id] =''">Clear</div>
+        <div v-if="form_values[config.id] && config.draw_mask && is_input_avail && !is_inpaint" class="l_button" @click="is_inpaint = !is_inpaint ">Draw Mask</div>
+        <div v-if="form_values[config.id] && config.draw_mask && is_input_avail && is_inpaint" class="l_button" @click="is_inpaint = !is_inpaint ">Remove Mask</div>
+
+        <br v-if="form_values[config.id] && is_input_avail"> 
+
+        <!-- <div style="height: 340px;  "> </div>
+        <ImageCanvas ref="inp_img_canvas" :is_inpaint="true" image_source="/Users/divamgupta/Downloads/512_576-1.png"  :is_disabled="false" :canvas_id="rand_id" :canvas_d_id="rand_id+'d' " ></ImageCanvas> -->
+
+     <br>
+  </div> 
+
+</template>
+<script>
+
+import FormInputMixin from "./FormInputMixin.vue"
+import { icon_library } from "../icon_library.js"
+import ImageCanvas from "../ImageCanvas.vue"
+import Vue from 'vue'
+
+export default {
+    name: 'ImageInput',
+    mixins: [FormInputMixin],
+    props: {
+         config: Object , 
+        form_values: Object,
+    },
+    components: {ImageCanvas},
+    mounted() {
+        if(this.config.request_objects_from_element){
+            // the Applet / component needs to laod the image b64 etc
+            // so the applet provised the function request_objects_from_element in the config
+            // the form input component calls that function to give it the function to request the base64
+            this.config.request_objects_from_element_fn("get_mask_img_b64" , this.get_mask_img_b64)
+            this.config.request_objects_from_element_fn("get_mask_b64" , this.get_mask_b64)
+        }
+    },
+    data() {
+        return {
+            is_inpaint: false,
+            is_input_avail: true,
+            icon_library:icon_library,
+            rand_id:  Math.random().toString()
+        };
+    },
+    methods: {
+        open_input_image(){
+            
+            let img_path = window.ipcRenderer.sendSync('file_dialog',  'img_file' );
+            if(img_path && img_path != 'NULL'){
+                Vue.set(this.form_values , this.config.id , img_path)
+                this.is_inpaint = false;
+            }      
+        },
+        onDragFile(e){
+           
+            if(!e.dataTransfer.files[0].type.startsWith('image/'))
+                return;
+            let img_path = e.dataTransfer.files[0].path;
+            if(img_path && img_path != 'NULL'){
+                Vue.set(this.form_values , this.config.id , img_path)
+                this.is_inpaint = false;
+            }      
+        },
+
+        on_img_load(){
+            if(this.config.get_img_size){
+                Vue.set(this.form_values , this.config.id + "__AUX__height" , this.get_size().height )
+                Vue.set(this.form_values , this.config.id + "__AUX__width" , this.get_size().width )
+            }
+        },  
+
+        get_mask_img_b64(){
+            return this.$refs.inp_img_canvas.get_img_mask_b64() 
+        },
+
+        get_mask_b64(){
+            if(this.is_inpaint){
+                return  this.$refs.inp_img_canvas.get_mask_b64() 
+            } else {
+                return undefined
+            }
+        } , 
+
+        get_size(){
+            return this.$refs.inp_img_canvas.get_size()
+        },
+
+    },
+
+    computed:{
+        img_src(){
+            return this.form_values[this.config.id]
+        }
+    },
+
+    watch: {
+        'img_src': {
+
+            handler: function() {
+                this.is_inpaint = false
+            },
+            deep: true
+        } , 
+    }
+}
+</script>
+<style>
+</style>
+<style scoped>
+.crosshair_cur{
+        cursor: crosshair;
+    }
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/InputWithDesc.vue b/electron_app/src/components_bare/inputform/InputWithDesc.vue
new file mode 100644
index 00000000..9f24053d
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/InputWithDesc.vue
@@ -0,0 +1,46 @@
+<template>
+    <div>
+        <div :class="box_css_class">
+            <div class="options_title_box" :style="{width: config.full_width?'100%':'205px'}">
+                <span>{{config.title}}</span>
+                <span class="options_desc">{{config.description}}</span>
+            </div>
+            <ResolveInputComponent
+                 v-for="child_config in config.children"
+                 :form_values="form_values" 
+                 :config="child_config"
+                 :key="child_config.id"
+            > </ResolveInputComponent>
+        </div>
+        <br>
+    </div>
+
+</template>
+<script>
+
+import ResolveInputComponent from "./ResolveInputComponent.vue"
+
+export default {
+    name: 'InputWithDesc',
+    props: {
+        config: Object , 
+        form_values: Object,
+    },
+    components: {'ResolveInputComponent':ResolveInputComponent},
+    mounted() {
+
+    },
+    data() {
+        return {
+            box_css_class : this.config.full_width? "options_title_full":"options_title"
+        };
+    },
+    methods: {
+
+    },
+}
+</script>
+<style>
+</style>
+<style scoped>
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/OutputImage.vue b/electron_app/src/components_bare/inputform/OutputImage.vue
new file mode 100644
index 00000000..ab2aca28
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/OutputImage.vue
@@ -0,0 +1,62 @@
+<template>
+    <div> 
+        <div class="options_input" style="width: 100%;">
+         
+            <img :src="'file://'+config.img_path" style="max-width: 100%;"> 
+            <div v-if="config.is_save" @click="save_image" class="l_button" > Save </div>
+        
+        </div>
+    <br> 
+    </div>
+    
+</template>
+<script>
+
+import FormInputMixin from "./FormInputMixin.vue"
+import { icon_library } from "../icon_library.js"
+
+
+export default {
+    name: 'OutputImage',
+    mixins: [FormInputMixin],
+    props: {
+         config: Object , 
+        form_values: Object,
+    },
+    components: {},
+    mounted() {
+      
+    },
+    data() {
+        return {
+            icon_library:icon_library,
+        };
+    },
+    methods: {
+
+        save_image(){
+
+            let image_url = this.config.img_path
+          
+            if(!image_url)
+                return;
+            let im_path = image_url.split("?")[0];
+
+
+            let suggested_fname = "Output"
+            let out_path = window.ipcRenderer.sendSync('save_dialog', suggested_fname, this.config.save_ext );
+            if(!out_path)
+                return
+            let org_path = im_path.replaceAll("file://" , "")
+            window.ipcRenderer.sendSync('save_file', org_path+"||" +out_path);
+
+        }
+       
+    },
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/OutputText.vue b/electron_app/src/components_bare/inputform/OutputText.vue
new file mode 100644
index 00000000..80e01c92
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/OutputText.vue
@@ -0,0 +1,42 @@
+<template>
+    <div> 
+        <div class="options_input" style="width: 100%;">
+        <p style="white-space: pre-line; margin-bottom: 1px;" > {{ config.text }} </p>
+        
+    </div>
+    <br> 
+    </div>
+    
+</template>
+<script>
+
+import FormInputMixin from "./FormInputMixin.vue"
+import { icon_library } from "../icon_library.js"
+
+
+export default {
+    name: 'OutputText',
+    mixins: [FormInputMixin],
+    props: {
+         config: Object , 
+        form_values: Object,
+    },
+    components: {},
+    mounted() {
+      
+    },
+    data() {
+        return {
+            icon_library:icon_library,
+        };
+    },
+    methods: {
+       
+    },
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/ResolveInputComponent.vue b/electron_app/src/components_bare/inputform/ResolveInputComponent.vue
new file mode 100644
index 00000000..54f3e7bf
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/ResolveInputComponent.vue
@@ -0,0 +1,147 @@
+<template>
+
+    <span>
+        <component   :is="config.component" :config="config"  :form_values="form_values" ></component>
+    </span>
+
+</template>
+<script>
+
+import Dropdown from "./Dropdown.vue"
+import Slider from "./Slider.vue"
+import Textbox from "./Textbox.vue"
+import Textarea from "./Textarea.vue"
+import ImageInput from "./ImageInput.vue"
+import Checkbox from "./Checkbox.vue"
+import FilePathTextBox from "./FilePathTextBox.vue"
+// import InputWithDesc from "./InputWithDesc.vue"
+import OutputText from "./OutputText.vue"
+import OutputImage from "./OutputImage.vue"
+import BetterSelector from "./BetterSelector.vue"
+
+
+export default {
+    name: 'ResolveInputComponent',
+    props: {
+        config: Object , 
+        form_values: Object,
+    },
+    components: { 'Dropdown':Dropdown , 'Slider':Slider, 'Textbox':Textbox , 'Textarea':Textarea, 'ImageInput':ImageInput , 'Checkbox':Checkbox , 'FilePathTextBox':FilePathTextBox , OutputText:OutputText, OutputImage:OutputImage , BetterSelector:BetterSelector },
+    beforeCreate: function () {
+         this.$options.components.InputWithDesc = require('./InputWithDesc.vue').default // use this as circular
+         this.$options.components.Accordian = require('./Accordian.vue').default // use this as circular
+    },
+
+    mounted() {
+
+    },
+    data() {
+        return {};
+    },
+    methods: {
+
+    },
+}
+</script>
+<style>
+
+.b-dropdown ::-webkit-scrollbar {
+    appearance: none;
+    width: 7px;
+}
+.b-dropdown ::-webkit-scrollbar-thumb {
+    border-radius: 4px;
+    background-color: rgba(0, 0, 0, .5);
+    box-shadow: 0 0 1px rgba(255, 255, 255, .5);
+}
+.options_title {
+    display: flex;
+    flex-direction: row;
+    align-items: center;
+/*    justify-content: space-around;*/
+    width: 100%;
+}
+
+.options_title_full{
+     display: flex;
+     flex-direction: column;
+     width: 100%;
+}
+
+.options_title_box span {
+    font-weight: 600;
+    font-size: 14px;
+    line-height: 19px;
+}
+
+.options_title_box .options_desc {
+    font-weight: 400;
+    font-size: 12px;
+}
+
+.custom-select {
+    appearance: none;
+    outline: none;
+    border: none;
+    background: none;
+    min-width: 20px;
+    font-weight: 600;
+    font-size: 14px;
+    line-height: 19px;
+    text-align: center;
+    cursor: pointer;
+    padding-left: 32px;
+
+}
+
+.options_input svg {
+    margin-right: -32px;
+}
+
+.custom-input {
+    border: none;
+    background: none;
+    min-width: 20px;
+    font-weight: 600;
+    font-size: 14px;
+    line-height: 19px;
+    text-align: center;
+}
+
+.custom-input::-webkit-outer-spin-button,
+.custom-input::-webkit-inner-spin-button {
+    appearance: none;
+    margin: 0;
+}
+
+.slider {
+    background: linear-gradient(to right, var(--slider-progress) 0%, var(--slider-progress) 0%, var(--slider-progress_end) 0%, var(--slider-progress_end) 100%);
+    border-radius: 8px;
+    height: 15px;
+    margin-top: 4px;
+    outline: none;
+    transition: background 450ms ease-in;
+    appearance: none;
+    cursor: pointer;
+}
+
+.slider::-webkit-slider-thumb {
+    appearance: none;
+    width: 25px;
+    height: 25px;
+    border-radius: 50%;
+    border: 3px solid var(--slider-border);
+    background: var(--slider-circle);
+}
+
+#tickmarks {
+    display: flex;
+    justify-content: space-between;
+    padding: 0 10px;
+    font-size: 12px;
+    margin-top: -10px ;
+}
+
+</style>
+<style scoped>
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/Slider.vue b/electron_app/src/components_bare/inputform/Slider.vue
new file mode 100644
index 00000000..7b712f32
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/Slider.vue
@@ -0,0 +1,98 @@
+<template>
+   <div>
+        <p style="float:right; margin-bottom:0px; opacity:0.4 "> {{form_values[this.config.id]}} </p>
+
+        <input :id="rand_id" type="range" :min="config.min_val" :max="config.max_val" @input="set_val(); set_slider();" :value="form_values[config.id]"  step='0.01' class="slider"
+             list='tickmarks' style="width: 100%;">
+
+        
+
+        <div id="tickmarks">
+            <p>{{tick_vals[0]}}</p>
+            <p>{{tick_vals[1]}}</p>
+            <p>{{tick_vals[2]}}</p>
+            <p>{{tick_vals[3]}}</p>
+             <p>{{tick_vals[4]}}</p>
+            <!-- <p>20</p> -->
+        </div>
+
+        
+
+   </div>
+</template>
+<script>
+
+import FormInputMixin from "./FormInputMixin.vue"
+import Vue from 'vue'
+
+export default {
+    name: 'Slider',
+    mixins: [FormInputMixin],
+    props: {
+         config: Object , 
+         form_values: Object,
+    },
+    components: {},
+    mounted() {
+        this.set_slider()
+
+        if(this.form_values[this.config.id] === undefined && this.config.default_value ){
+            Vue.set( this.form_values  , this.config.id  , this.config.default_value  )
+        } 
+
+    },
+
+    data() {
+        return {
+            rand_id : Math.random()
+        };
+    },
+    methods: {
+        set_val() {
+            let el = document.getElementById(this.rand_id)
+            let value = (el.value - el.min) / (el.max - el.min) * 100
+            value = Number(el.value) + ""
+            Vue.set(this.form_values , this.config.id , value)
+        } , 
+
+        set_slider(){
+            let el = document.getElementById(this.rand_id)
+            let value = Number(this.form_values[this.config.id] - el.min) * ( 100/(el.max - el.min)) ;
+             el.style.background = 'linear-gradient(to right, var(--slider-progress) 0%, var(--slider-progress) ' + value + '%, var(--slider-progress_end) ' + value + '%, var(--slider-progress_end) 100%)'
+        },
+
+        is_input_valid(){
+            return true;
+        }
+
+    },
+    computed:{
+        tick_vals(){
+            return [ this.config.min_val, 
+                Math.round(this.config.min_val + (this.config.max_val-this.config.min_val)/4) , 
+                Math.round(this.config.min_val + 2*(this.config.max_val-this.config.min_val)/4  )  , 
+                Math.round(this.config.min_val + 3*(this.config.max_val-this.config.min_val)/4  )  , 
+                this.config.max_val  ]
+        } , 
+
+        cur_val(){
+            return this.form_values[this.config.id]
+        }
+    } , 
+
+    watch: {
+        'cur_val' : {
+            handler: function() {
+               this.set_slider()
+            },
+            deep: false
+        } , 
+    }
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/Textarea.vue b/electron_app/src/components_bare/inputform/Textarea.vue
new file mode 100644
index 00000000..2bdc68d7
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/Textarea.vue
@@ -0,0 +1,49 @@
+<template>
+
+   <div> 
+
+        <textarea 
+            v-model="form_values[config.id]" 
+            style="border-radius: 5px 5px 5px 5px; width: calc(100%); resize: none; " 
+            class="form-control"  
+            :placeholder="config.placeholder || '' " 
+            :rows="config.is_small? 3 : 7"></textarea>
+         <br>
+    
+  </div> 
+
+</template>
+<script>
+
+import FormInputMixin from "./FormInputMixin.vue"
+import { icon_library } from "../icon_library.js"
+import Vue from 'vue'
+
+export default {
+    name: 'Textarea',
+    mixins: [FormInputMixin],
+    props: {
+         config: Object , 
+        form_values: Object,
+    },
+    components: {},
+    mounted() {
+        if(this.form_values[this.config.id] === undefined && this.config.default_value != undefined ){
+            Vue.set( this.form_values  , this.config.id  , this.config.default_value  )
+        } 
+    },
+    data() {
+        return {
+            icon_library:icon_library,
+        };
+    },
+    methods: {
+
+    },
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/components_bare/inputform/Textbox.vue b/electron_app/src/components_bare/inputform/Textbox.vue
new file mode 100644
index 00000000..092c9368
--- /dev/null
+++ b/electron_app/src/components_bare/inputform/Textbox.vue
@@ -0,0 +1,47 @@
+<template>
+
+    <div class="options_input" style="width: 125px;">
+        
+         <svg style="height:auto" width="19px" height="19px"  v-html="icon_library[config.icon]"> </svg>
+
+        <b-form-input onkeypress="return event.keyCode != 13;" class="custom-input"
+               v-model="form_values[config.id]" :placeholder="config.placeholder"  :type="config.type" width="70"  style="height: 20px;"
+             ></b-form-input>
+    </div>
+
+</template>
+<script>
+
+import FormInputMixin from "./FormInputMixin.vue"
+import { icon_library } from "../icon_library.js"
+import Vue from 'vue'
+
+
+export default {
+    name: 'Textbox',
+    mixins: [FormInputMixin],
+    props: {
+         config: Object , 
+        form_values: Object,
+    },
+    components: {},
+    mounted() {
+        if(this.form_values[this.config.id] === undefined && this.config.default_value != undefined){
+            Vue.set( this.form_values  , this.config.id  , this.config.default_value  )
+        } 
+    },
+    data() {
+        return {
+            icon_library:icon_library,
+        };
+    },
+    methods: {
+
+    },
+}
+</script>
+<style>
+</style>
+<style scoped>
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/fake_backend.py b/electron_app/src/fake_backend.py
index feedc439..64c31db6 100644
--- a/electron_app/src/fake_backend.py
+++ b/electron_app/src/fake_backend.py
@@ -4,6 +4,7 @@
 import copy
 import random
 import os
+import cv2
 
 class Unbuffered(object):
     def __init__(self, stream):
@@ -26,11 +27,18 @@ def __getattr__(self, attr):
 time.sleep(1)
 
 
+if len(sys.argv) > 1 and  sys.argv[1] == "convert_model":
+    time.sleep(4)
+    exit()
+
+
+
 sample_path = os.path.join(  os.path.dirname(os.path.abspath(__file__)),  "assets",  "sample.png"  )
 
 print("sdbk mltl downloading model")
 for i in range(100):
-    time.sleep(0.06)
+    time.sleep(0.02)
+
     print("sdbk mlpr %d"%i ) # model loading percentage
     print("sdbk mlms done %s of 100.0"%i)
 
@@ -41,23 +49,38 @@ def __getattr__(self, attr):
 
 
 def process_opt(opts):
-    if random.randint(0,10) > 7:
-        print("sdbk errr just a random error lol")
-        return
+    
 
     if 'num_imgs' not in opts:
         opts['num_imgs'] = 1
 
-    for _ in range(opts['num_imgs']):
+    for nn in range(opts['num_imgs']):
+
+        
+        if  opts['seed'] < 20:
+            print("sdbk errr just a random error lol")
+            return
+
+        print("sdbk dnpr "+str(-1) ) 
+        time.sleep(0.8)
         for i in range(0,100,5):
             print("sdbk dnpr "+str(i) ) # done percentage
             time.sleep(0.1)
-        impath = sample_path + "?%d"%random.randint(0,10000)
+            # if opts['seed'] > 2:
+            #     time.sleep(100.1)
+        print("sdbk dnpr "+str(-1) ) 
+        time.sleep(0.8)
+        impath = sample_path 
+        im = cv2.imread(impath)
+        im = cv2.resize(im , ( opts['img_width'] , opts['img_height'] ) )
+        new_p =  "/tmp/%d_%d.png"%( opts['img_width'] , opts['img_height'])
+        cv2.imwrite( new_p ,  im )
 
         # if 'input_image' in opts:
         #     impath = opts['input_image']
+        ret_dict = {"generated_img_path" : (new_p) }
 
-        print("sdbk nwim %s"%(impath) ) # new image generated
+        print("sdbk nwim %s"%(json.dumps(ret_dict)) ) # new image generated
     
 while True:
         print("sdbk inrd") # input ready
diff --git a/electron_app/src/forms/sample_ext_applet.json b/electron_app/src/forms/sample_ext_applet.json
new file mode 100644
index 00000000..95738389
--- /dev/null
+++ b/electron_app/src/forms/sample_ext_applet.json
@@ -0,0 +1,33 @@
+{
+	"id" : "sample" , 
+	"title" : "hiofh ",
+	"icon" : "star" ,
+	"home_category" : "misc",
+	"inputs" : [
+		{
+	        "id" : "prompt",
+	        "component": "Textarea",
+	        "placeholder" : "custom applet "
+	    },
+	    {
+	        "id": "7657836",
+	        "component": "InputWithDesc",
+	        "title": "Seed",
+	        "description": "Starting point for iterations (any random number will do; DB will pick one if left blank).",
+	        "children": [
+	            {
+	                "id": "seed",
+	                "component": "Textbox",
+	                "icon": "seed",
+	                "placeholder" : "-1",
+	                "type" : "number",
+	                "is_persistant" : true
+	            }
+	        ]
+	    }
+	] , 
+	"outputs": [
+		
+	]
+
+}
\ No newline at end of file
diff --git a/electron_app/src/forms/sd_options_adv.json b/electron_app/src/forms/sd_options_adv.json
new file mode 100644
index 00000000..f1c3f31d
--- /dev/null
+++ b/electron_app/src/forms/sd_options_adv.json
@@ -0,0 +1,433 @@
+[
+    {
+            "id" : "input_img",
+            "component" : "ImageInput",
+            "include_in" : ["img2img"] , 
+            "get_img_size" : true,
+            "draw_mask": true,
+            "store_masked_image" : true
+
+    },
+    {
+        "id" : "prompt",
+        "component": "Textarea",
+        "placeholder" : "Enter your prompt here",
+        "default_value" : ""
+    },
+
+    {
+        "id" : "negative_prompt",
+        "component": "Textarea",
+        "placeholder" : "Enter your negative prompt here",
+        "is_small" : true,
+        "include_in" : ["advanced"]
+    },
+    
+    {
+        "id": "is_adv_mode_desc",
+        "component": "InputWithDesc",
+        "title": "Advanced Options",
+        "description": "",
+        "children": [
+            {
+                "id": "is_adv_mode",
+                "component": "Checkbox",
+                "default_value" : false,
+                "is_persistant" : true
+            }
+        ]
+    },
+
+    {
+        "id": "selected_sd_model_desc",
+        "component": "InputWithDesc",
+        "title": "Model",
+        "description": "The Stable Diffusion model used to generate images.",
+        "children": [
+            {
+                "id": "selected_sd_model",
+                "component": "Dropdown",
+                "options": ["Default_SD1.5" ],
+                "icon": "photo",
+                "output_type" : "str",
+                "default_value" : "Default_SD1.5",
+                "is_persistant" : true
+            }
+        ]
+    },
+
+    {
+        "id": "input_image_strength_desc",
+        "component": "InputWithDesc",
+        "title": "Input Strength",
+        "full_width": true,
+        "include_in" : ["img2img", "input_image_strength"],
+        "description": "How  closely to stick to the input image.  (lower numbers makes the AI do more change)",
+        "children": [
+            {
+                "id": "input_image_strength",
+                "component": "Slider",
+                "is_persistant" : true,
+                "max_val" : 100,
+                "min_val" : 2, 
+                "output_type" : "float",
+                "default_value" : 30
+            }
+        ]
+    },
+    {
+        "id": "67854325222",
+        "component": "InputWithDesc",
+        "title": "Specify image dimensions",
+        "include_in_AND" : ["advanced" , "img2img"],
+        "description": "If you want to specify dimensions for output images.",
+        "children": [
+            {
+                "id": "force_use_given_size",
+                "component": "Checkbox",
+                "output_type" : "bool",
+                "default_value" : false,
+                "is_persistant" : false
+            }
+        ]
+    } ,
+
+    {
+        "id": "resolution_desc",
+        "component": "InputWithDesc",
+        "title": "Resolution",
+        "include_in" : [ "txt2img" ],
+        "cond_include_in_AND" : [  {"lhs" : "force_use_given_size"  , "comparator":"eq" , "rhs": true } ,  {"lhs" : "is_adv_mode"  , "comparator":"eq" , "rhs": true }],
+        "description": "",
+        "children": [
+            {
+                "id": "img_width",
+                "component": "Dropdown",
+                "options": [256, 320, 384, 448, 512, 576, 640, 704, 768, 832, 896],
+                "icon": "img_width",
+                "output_type" : "int",
+                "default_value" : 512,
+                "is_persistant" : true
+            },
+            {
+                "id": "img_height",
+                "component": "Dropdown",
+                "options": [256, 320, 384, 448, 512, 576, 640, 704, 768, 832, 896],
+                "default_value" : 512,
+                "icon": "img_height",
+                "output_type" : "int",
+                "is_persistant" : true
+            }
+        ]
+    },
+
+    {
+        "id": "num_imgs_desc",
+        "component": "InputWithDesc",
+        "title": "Number of images",
+        "exclude_in" : [ "inpainting" ,  "outpainting" ],
+        "description": "How many images are generated in total.",
+        "children": [
+            {
+                "id": "num_imgs",
+                "component": "Dropdown",
+                "options": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 30, 50, 100 , 500 , 2000],
+                "icon": "photo",
+                "default_value" : 1,
+                "output_type" : "int",
+                "type" : "number",
+                "is_persistant" : true
+            }
+        ]
+    },
+
+    {
+        "id": "seed_desc",
+        "component": "InputWithDesc",
+        "title": "Seed",
+        "description": "",
+        "children": [
+            {
+                "id": "seed",
+                "component": "Textbox",
+                "icon": "seed",
+                "placeholder" : "-1",
+                "output_type" : "int",
+                "type" : "number",
+                "is_persistant" : false
+            }
+        ]
+    },
+
+    {
+        "id": "num_steps_desc",
+        "component": "InputWithDesc",
+        "title": "Sampling Steps",
+        "description": "",
+        "children": [
+            {
+                "id": "num_steps",
+                "component": "Dropdown",
+                "options": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75],
+                "icon": "steps",
+                "type" : "number",
+                "output_type" : "int",
+                "default_value" : 25,
+                "is_persistant" : true
+            }
+        ]
+    },
+
+    {
+        "id": "diffusion_acc",
+        "component": "Accordian",
+        "title": "Diffusion",
+        "include_in" : ["advanced"],
+        "children": [
+            {
+                "id": "43545455",
+                "component": "InputWithDesc",
+                "title": "Sampler",
+                "description": "The sampling algorithm used by DiffusionBee.",
+                "children": [
+                    {
+                        "id": "scheduler",
+                        "component": "Dropdown",
+                        "options": [ "karras", "ddim" , "lmsd" , "pndm" , "k_euler_ancestral", "k_euler" ],
+                        "icon": "photo",
+                        "output_type" : "str",
+                        "default_value" : "karras",
+                        "is_persistant" : true
+                    }
+                ]
+            },
+            {
+                "id": "53454543",
+                "component": "InputWithDesc",
+                "title": "Steps",
+                "description": "Iterations of the image (more steps means more detail & more processing time - best to start around 10)",
+                "children": [
+                    {
+                        "id": "num_steps",
+                        "component": "Dropdown",
+                        "options": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75],
+                        "icon": "steps",
+                        "type" : "number",
+                        "output_type" : "int",
+                        "default_value" : 25,
+                        "is_persistant" : true
+                    }
+                ]
+            },
+            {
+                "id": "32e43434",
+                "component": "InputWithDesc",
+                "title": "Guidance Scale",
+                "full_width": true,
+                "description": "How closely to follow your prompt (lower numbers give the AI more creativity)",
+                "children": [
+                    {
+                        "id": "guidance_scale",
+                        "component": "Slider",
+                        "is_persistant" : true,
+                        "max_val" : 20,
+                        "output_type" : "float",
+                        "min_val" : 1, 
+                        "default_value" : 7.5
+                    }
+                ]
+            }
+        ]
+    },
+    {
+        "id": "seed_acc",
+        "component": "Accordian",
+        "title": "Seed",
+        "include_in" : ["advanced"],
+        "children": [
+            {
+                "id": "765655",
+                "component": "InputWithDesc",
+                "title": "Seed",
+                "description": "Starting point for iterations (any random number will do; DB will pick one if left blank).",
+                "children": [
+                    {
+                        "id": "seed",
+                        "component": "Textbox",
+                        "icon": "seed",
+                        "placeholder" : "-1",
+                        "type" : "number",
+                        "output_type" : "int",
+                        "is_persistant" : false
+                    }
+                ]
+            } , 
+            {
+                "id": "76565345",
+                "component": "InputWithDesc",
+                "title": "Small Modification Seed",
+                "description": "If you want to do small variations in the images.",
+                "children": [
+                    {
+                        "id": "small_mod_seed",
+                        "component": "Textbox",
+                        "icon": "seed",
+                        "placeholder" : "-1",
+                        "type" : "number",
+                        "output_type" : "int",
+                        "is_persistant" : false
+                    }
+                ]
+            } 
+        ]
+    }, 
+
+    {
+        "id": "inpaint_options_acc",
+        "component": "Accordian",
+        "title": "Inpainting Options",
+        "include_in" : ["outpainting", "img2img" , "inpainting"],
+        "include_in_AND" : ["advanced"],
+        "children": [
+            {
+                "id": "inp_only_update_masked_desc",
+                "component": "InputWithDesc",
+                "title": "Only update masked",
+                "include_in" : ["outpainting", "inpainting"],
+                "description": "This will forcefully only update the transparent/masked region.",
+                "children": [
+                    {
+                        "id": "inp_only_update_masked",
+                        "component": "Checkbox",
+                        "default_value" : true,
+                        "is_persistant" : false
+                    }
+                ]
+            } , 
+            {
+                "id": "blur_mask_desc",
+                "component": "InputWithDesc",
+                "title": "Smoothen Mask",
+                "include_in" : ["img2img"],
+                "description": "This will make the masked image smoother.",
+                "children": [
+                    {
+                        "id": "blur_mask",
+                        "component": "Checkbox",
+                        "default_value" : false,
+                        "is_persistant" : true
+                    }
+                ]
+            }
+        ]
+    },
+
+    {
+        "id": "controlnet_acc",
+        "component": "Accordian",
+        "title": "ControlNet",
+        "include_in" : ["advanced"],
+        "exclude_in" : [ "outpainting" , "inpainting"],
+        "children": [
+            
+            {
+                "id": "344345435",
+                "component": "InputWithDesc",
+                "title": "ControlNet Model",
+                "description": "",
+                "children": [
+                    {
+                        "id": "controlnet_model",
+                        "component": "Dropdown",
+                        "options": ["None" , "Depth" , "BodyPose" , "Scribble"  , "LineArt" , "Tile" ],
+                        "default_value" : "None",
+                        "icon": "photo",
+                        "is_persistant" : false
+                    }
+                ]
+            } , 
+            {
+                "id" : "controlnet_input_image_path",
+                "component" : "ImageInput"
+            } , 
+            {
+                "id": "678545",
+                "component": "InputWithDesc",
+                "title": "Automatically generate control?",
+                "description": "If you select No, you have to input raw control image.",
+                "children": [
+                    {
+                        "id": "do_controlnet_preprocess",
+                        "component": "Dropdown",
+                        "options": ["Yes" , "No"   ],
+                        "output_type" : "bool",
+                        "default_value" : "No",
+                        "icon": "photo",
+                        "is_persistant" : false
+                    }
+                ]
+            } , 
+            {
+                "id": "43434",
+                "component": "InputWithDesc",
+                "title": "ControlNet Importance",
+                "description": "The strength of the ControlNet input. For most cases leave it at 1.0.",
+                "children": [
+                    {
+                        "id": "control_weight",
+                        "component": "Textbox",
+                        "placeholder" : "1.0",
+                        "type" : "number",
+                        "default_value" : "1.0",
+                        "output_type" : "float",
+                        "is_persistant" : false
+                    }
+                ]
+            } 
+
+        ]
+    } , 
+
+    {
+        "id": "misc_acc",
+        "component": "Accordian",
+        "title": "Misc",
+        "include_in" : ["advanced"],
+        "children": [
+            {
+                "id": "678545",
+                "component": "InputWithDesc",
+                "title": "V-Prediction",
+                "description": "If it should use V-Prediction. Mostly used in SD2.X 768 models. ",
+                "children": [
+                    {
+                        "id": "do_v_prediction",
+                        "component": "Checkbox",
+                        "output_type" : "bool",
+                        "default_value" : false,
+                        "is_persistant" : false
+                    }
+                ]
+            } , 
+
+            {
+                "id": "678545222",
+                "component": "InputWithDesc",
+                "title": "Clip Skip 2",
+                "description": "If you want to set clip skip as 2. ",
+                "children": [
+                    {
+                        "id": "is_clip_skip_2",
+                        "component": "Checkbox",
+                        "output_type" : "bool",
+                        "default_value" : false,
+                        "is_persistant" : false
+                    }
+                ]
+            } 
+
+        ]
+    } 
+
+
+]
\ No newline at end of file
diff --git a/electron_app/src/init_vue_libs.js b/electron_app/src/init_vue_libs.js
index e671aa4f..f40ce47b 100644
--- a/electron_app/src/init_vue_libs.js
+++ b/electron_app/src/init_vue_libs.js
@@ -2,12 +2,14 @@ import Vue from 'vue'
 
 
 
+
 // add the fond awesome stuff
 import { library } from '@fortawesome/fontawesome-svg-core'
 import { faChevronRight, faStopCircle, faPlayCircle , faPlus , faChevronLeft , 
 	faFileImage  , faFileAudio , faFile , faBars , faAngleDown , faTrash, faChevronDown ,
 	faGlobe, faFolder, faCamera, faKeyboard,
-	faMusic , faMicrophone , faTimes , faCheck } from '@fortawesome/free-solid-svg-icons'
+	faMusic , faMicrophone , faTimes , faCheck , faHandPaper , faExpandArrowsAlt, faEraser , faUndo , faRedo, faImage, faMicrochip , faCube , 
+	faMagic, faSave, faHistory, faCubes, faImages, faHome , faPaintBrush, faCircle , faMask, faTools, faThList, faEllipsisV, faInbox} from '@fortawesome/free-solid-svg-icons'
 import { FontAwesomeIcon } from '@fortawesome/vue-fontawesome'
 
 library.add(faBars)
@@ -24,6 +26,16 @@ library.add(faKeyboard)
 library.add(faMicrophone)
 library.add(faPlus)
 library.add(faFile)
+library.add(faExpandArrowsAlt)
+library.add(faEraser)
+library.add(faHandPaper)
+library.add(faImage)
+library.add(faMicrochip)
+library.add(faCube)
+library.add(faMagic)
+library.add(faSave)
+library.add(faUndo)
+library.add(faRedo)
 
 library.add(faAngleDown)
 library.add(faTrash)
@@ -32,8 +44,17 @@ library.add(faMusic)
 library.add(faCamera)
 library.add(faTimes)
 library.add(faCheck)
-
-
+library.add(faHistory)
+library.add(faCubes)
+library.add(faImages)
+library.add(faHome)
+library.add(faPaintBrush)
+library.add(faCircle)
+library.add(faMask)
+library.add(faTools)
+library.add(faThList)
+library.add(faEllipsisV)
+library.add(faInbox)
 
 Vue.component('font-awesome-icon', FontAwesomeIcon)
 Vue.config.productionTip = false
diff --git a/electron_app/src/main.js b/electron_app/src/main.js
index aaab1e0f..b58d68dd 100644
--- a/electron_app/src/main.js
+++ b/electron_app/src/main.js
@@ -1,3 +1,7 @@
+
+
+
+
 import Vue from 'vue'
 
 
diff --git a/electron_app/src/native_functions.js b/electron_app/src/native_functions.js
index 8ff1e11a..2eaee61f 100644
--- a/electron_app/src/native_functions.js
+++ b/electron_app/src/native_functions.js
@@ -1,7 +1,9 @@
-import { ipcMain, dialog } from 'electron'
+import { ipcMain, dialog, clipboard } from 'electron'
 import { app , screen } from 'electron'
 import settings from 'electron-settings';
 
+const path = require('path');
+
 var win;
 
 
@@ -21,21 +23,16 @@ console.log(require('os').totalmem()/(1000000000) + " Is the total memory")
 
 ipcMain.on('save_dialog', (event, ...args) => {
 
-    const seed = args[1] ? args[1] : "0"
-    const prompt = args[0] ? args[0] : "Untitled"
-    let filename = ''
-    if (seed === '0') {
-        filename = prompt
-    } else {
-        filename = seed + '-' + prompt
-    }
+    const filename = args[0] ? args[0] : "Untitled"
+    const ext = args[1] ? args[1] : "png"
+   
     let trimmedFilename = filename.substring(0, 254) // filename size limit
      let save_path = dialog.showSaveDialogSync({
             title: 'Save Image',
             defaultPath: trimmedFilename,
             filters: [{
               name: 'Image',
-              extensions: ['png']
+              extensions: [ext]
             }]
           })
 
@@ -143,7 +140,15 @@ ipcMain.on('save_file', (event, arg) => {
 })
 
 
+ipcMain.on('copy_to_clipboard', (event, arg) => {
+    clipboard.writeText(arg)
+    event.returnValue = '';
+})
+
 
+ipcMain.on('get_from_clipboard', (event, arg) => {
+    event.returnValue = clipboard.readText();
+})
 
 
 ipcMain.on('show_dialog_on_quit', (event, msg) => {
@@ -193,17 +198,19 @@ ipcMain.on('unfreeze_win', (event, arg) => {
                 win.setSize(850, 650, false);
             } else {
                win.setPosition( windowState.x  ,  windowState.y  , false);
+               win.setMinimumSize(1070, 700);
                 win.setSize(windowState.width, windowState.height , false); 
             }
 
             
         }
         else{
+            win.setMinimumSize(1070, 700);
             win.setSize(850, 650, false);
         }
 
-
-        win.setResizable(true);
+        win.setMinimumSize(1070, 700);
+        // win.setResizable(true);
         win.setMaximizable(true);
 
 
@@ -222,8 +229,9 @@ ipcMain.on('freeze_win', (event, arg) => {
     if (win) {
 	win.savable=false;
 	win.restore()
+        win.setMinimumSize(770, 550)
         win.setSize(770, 550, false); 
-        win.setResizable(false);
+        // win.setResizable(false);
         win.setMaximizable(false);
 
         const primaryDisplay = screen.getPrimaryDisplay()
@@ -367,7 +375,8 @@ ipcMain.on('save_b64_image', (event, b64_str, save_to_tmp ) => {
 })
 
 
-ipcMain.on('save_data', (event, arg) => {
+
+function save_json(data , fname ){
     const path = require('path');
     const fs = require('fs');
     const homedir = require('os').homedir();
@@ -378,31 +387,45 @@ ipcMain.on('save_data', (event, arg) => {
         fs.mkdirSync(save_dir, { recursive: true });
     }
 
-    let data_path = path.join(homedir , ".diffusionbee" , "data.json")
-    fs.writeFileSync( data_path, JSON.stringify(arg) );
-    event.returnValue = true ;
+    let data_path = path.join(homedir , ".diffusionbee" , fname )
+    fs.writeFileSync( data_path, JSON.stringify(data) );
+}
 
-})
 
 
-ipcMain.on('load_data', (event, arg) => {
+function load_data(fname){
     const path = require('path');
     const fs = require('fs');
     const homedir = require('os').homedir();
-    let data_path = path.join(homedir , ".diffusionbee" , "data.json");
+    let data_path = path.join(homedir , ".diffusionbee" , fname );
 
     if (fs.existsSync(data_path)){
         let json_str = fs.readFileSync( data_path );
         try {
-            event.returnValue = JSON.parse(json_str);
+            return JSON.parse(json_str);
           } catch (error) {
-            event.returnValue = {} ;
+            return {} ;
           }
     }
     else{
-        event.returnValue = {} ;
+        return {} ;
     }       
+}
+
+ipcMain.on('save_data', (event, arg , fname ) => {
+    if(fname)
+        save_json(arg, fname)
+    else
+        save_json(arg, "data.json")
+    event.returnValue = true ;
+})
 
+
+ipcMain.on('load_data', (event, fname) => {
+    if(fname)
+        event.returnValue = load_data(fname)
+    else
+        event.returnValue = load_data("data.json")
 })
 
 
@@ -451,12 +474,12 @@ function run_realesrgan(input_path , cb ){
 
 
 
-function add_custom_pytorch_models(pytorch_model_path, model_name, cb ){
+function add_custom_pytorch_models(pytorch_model_path, model_name, convert_params , cb ){
     
     const path = require('path');
     const fs = require('fs');
     const homedir = require('os').homedir();
-    let models_path = path.join(homedir , ".diffusionbee" , "custom_models");
+    let models_path = path.join(homedir , ".diffusionbee" , "imported_models");
 
     if (!fs.existsSync(models_path)){
         fs.mkdirSync(models_path, { recursive: true });
@@ -465,7 +488,7 @@ function add_custom_pytorch_models(pytorch_model_path, model_name, cb ){
 
     let script_path = process.env.PY_SCRIPT || "../backends/stable_diffusion/diffusionbee_backend.py"; 
     
-    let out_path =  path.join(homedir , ".diffusionbee" , "custom_models" , model_name+".tdict" );
+    let out_path =  path.join(homedir , ".diffusionbee" , "imported_models" , model_name+".tdict" );
     let proc;
     if (fs.existsSync(script_path)) {
         proc = require('child_process').spawn( "python3"  , [ script_path ,  "convert_model" ,  pytorch_model_path , out_path ]);
@@ -477,6 +500,7 @@ function add_custom_pytorch_models(pytorch_model_path, model_name, cb ){
 
     
     let errors = ""
+    let std_out_all = ""
 
     proc.stderr.on('data', (data) => {
         console.error(`sr stderr: ${data}`);
@@ -485,9 +509,17 @@ function add_custom_pytorch_models(pytorch_model_path, model_name, cb ){
 
     proc.stdout.on('data', (data) => {
         console.error(`sr sdtout: ${data}`);
+        std_out_all += data
     });
 
     proc.on('close', (code) => {
+
+        if(convert_params.delete_origional_always){
+            try{
+                fs.unlinkSync(pytorch_model_path);
+            } catch {}
+        }
+
         if(code != 0){
             cb({success:false , error:errors  })
             try{
@@ -495,15 +527,28 @@ function add_custom_pytorch_models(pytorch_model_path, model_name, cb ){
             } catch {}
         }
         else{
-            cb({success:true, model_path:out_path })
+            if(convert_params.delete_origional_on_success){
+                try{
+                    fs.unlinkSync(pytorch_model_path);
+                } catch {}
+            }
+
+            let converted_model_data = {}
+            for(let l of std_out_all.split("\n")){
+                if(l.includes("__converted_model_data__")){
+                    converted_model_data = JSON.parse(l.replace( "__converted_model_data__", "") )
+                }
+            }
+
+            cb({success:true, model_path:out_path , metadata : converted_model_data })
         }
        
     });
 }
 
 
-ipcMain.handle('add_custom_pytorch_models', async (event, pytorch_model_path, model_name ) => {
-    const result = await new Promise(resolve => add_custom_pytorch_models( pytorch_model_path, model_name  , resolve));
+ipcMain.handle('add_custom_pytorch_models', async (event, pytorch_model_path, model_name, convert_params ) => {
+    const result = await new Promise(resolve => add_custom_pytorch_models( pytorch_model_path, model_name , convert_params , resolve));
     return result
 })
 
@@ -520,11 +565,11 @@ ipcMain.handle('run_realesrgan', async (event, arg) => {
 
 
 
-ipcMain.on('list_custom_models', (event, arg) => {
+ipcMain.on('list_imported_models', (event, arg) => {
     const path = require('path');
     const fs = require('fs');
     const homedir = require('os').homedir();
-    let models_path = path.join(homedir , ".diffusionbee" , "custom_models");
+    let models_path = path.join(homedir , ".diffusionbee" , "imported_models");
 
     if (!fs.existsSync(models_path)){
         fs.mkdirSync(models_path, { recursive: true });
@@ -536,6 +581,85 @@ ipcMain.on('list_custom_models', (event, arg) => {
 
 
 
+
+
+ipcMain.on('get_assets_dir', (event, arg) => {
+    const path = require('path');
+    const fs = require('fs');
+    const homedir = require('os').homedir();
+    let assets_path = path.join(homedir , ".diffusionbee" , "downloaded_assets");
+
+    if (!fs.existsSync(assets_path)) {
+        fs.mkdirSync(assets_path, { recursive: true });
+    }
+
+    event.returnValue = assets_path;
+});
+
+
+
+ipcMain.on('download-file', (event, url, dest, downloadId) => {
+  
+  const fs = require('fs');
+  const path = require('path');
+
+  const file = fs.createWriteStream(dest);
+  const request = require('request');
+
+  const crypto = require('crypto');
+
+  let hash = crypto.createHash('md5');
+
+  request.get({
+      url,
+      followRedirect: true,
+      rejectUnauthorized: false, // ignore SSL certificate errors,
+      timeout: 20000 , //20s
+    })
+    .on('response', response => {
+      const totalBytes = parseInt(response.headers['content-length'], 10);
+      let downloadedBytes = 0;
+
+      response.on('data', chunk => {
+        downloadedBytes += chunk.length;
+        hash.update(chunk);
+        const progress = Math.round((downloadedBytes / totalBytes) * 100);
+        try { 
+           event.sender.send(`to_download`, {fn:'progress' , download_id: downloadId , msg:progress });
+        } catch (err) {
+            console.log(err)
+        }
+        
+      });
+
+      response.pipe(file);
+
+    })
+    .on('error', err => {
+      fs.unlink(dest, () => {});
+
+        try {
+           event.sender.send(`to_download`, {fn:'error' , download_id: downloadId , msg:err.message  });
+        } catch (err) {
+           console.log(err)
+        }
+        
+      
+    })
+    .on('end', () => {
+
+        const hashValue = hash.digest('hex');
+        
+        try {
+           event.sender.send(`to_download`, {fn:'success' , download_id: downloadId , msg: hashValue  });
+        } catch (err) {
+           console.log(err)
+        }
+        
+    });
+});
+
+
 console.log("native functions imported")
 
 
diff --git a/electron_app/src/pages/BlankPage.vue b/electron_app/src/pages/BlankPage.vue
new file mode 100644
index 00000000..c69c2282
--- /dev/null
+++ b/electron_app/src/pages/BlankPage.vue
@@ -0,0 +1,31 @@
+<template>
+</template>
+<script>
+const BlankPage ={
+    name: 'BlankPage',
+    props: {app:Object, },
+    components: {},
+    mounted() {
+
+    },
+    data() {
+        return {};
+    },
+    methods: {
+
+    },
+}
+
+export default BlankPage;
+BlankPage.title = "BlankPage"
+BlankPage.icon = "file"
+BlankPage.img_icon = require("../assets/imgs/page_icon_imgs/default.png")
+BlankPage.home_category = undefined
+BlankPage.description = "desc .. "
+// add this to the always_on_pages to the PagesRouter
+
+</script>
+<style>
+</style>
+<style scoped>
+</style>
\ No newline at end of file
diff --git a/electron_app/src/pages/ContactUs.vue b/electron_app/src/pages/ContactUs.vue
new file mode 100644
index 00000000..5bf4a3f1
--- /dev/null
+++ b/electron_app/src/pages/ContactUs.vue
@@ -0,0 +1,58 @@
+<template>
+    <div style="width: 100%; height :100% ; overflow:auto; padding:30px">
+        <div class="model_dialog"> 
+            <h2 style="white-space: pre-line"> 
+                To contact us, please send an email at :
+                <br><br>
+                diffusionbee@proton.me
+            </h2> <br>            
+            <p>We will get back to you as soon as possible</p>
+        </div>
+       
+    </div>
+    
+</template>
+
+<script>
+const ContactUs = {
+    name: 'ContactUs',
+    props: {app:Object, },
+    components: {},
+    mounted() {
+
+    },
+    data() {
+        return {};
+    },
+    methods: {
+
+    },
+}
+
+export default ContactUs;
+ContactUs.title = "Contact Us"
+ContactUs.icon = "file"
+ContactUs.img_icon = require("../assets/imgs/page_icon_imgs/default.png")
+ContactUs.home_category = undefined
+ContactUs.hide_in_sidebar = true
+ContactUs.sidebar_show = "never"
+// add this to the always_on_pages to the PagesRouter
+
+</script>
+<style>
+</style>
+
+<style scoped>
+.model_dialog{
+    position: fixed;
+    width: 250px ;
+    height:170px;
+    background: var(--options-input-bg );
+    left: calc( 50% -  var(--sidebar-width ) /2 + 175px );
+    top:50%;
+     transform: translateY(-50%) translateX(-50%);
+    z-index: 1000;
+    padding:20px;
+}
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/pages/History.vue b/electron_app/src/pages/History.vue
new file mode 100644
index 00000000..fe425384
--- /dev/null
+++ b/electron_app/src/pages/History.vue
@@ -0,0 +1,302 @@
+
+<template>
+    <div  style="width:100%; height:100%; ">
+
+        <!-- toolbox -->
+        <div style="height: 60px ; padding:10px ; width:100% ">
+            
+            <b-form-input
+                @input="currentPage=1"
+                onkeypress="return event.keyCode != 13;"
+                size="sm"
+                placeholder="Search by prompt text"
+                v-model="searchText"
+                autofocus
+                debounce="200"
+                style="max-width: 240px; float: left; margin-right: 30px;"
+                id="searchText"
+            />
+
+            <div @click="toggle_order()" style="float:right; margin-bottom: 20px;" class="l_button">
+              {{this.show_history_in_oldest_first ? "Newest": "Oldest"}} First
+            </div>
+            <div @click="clear_history()" style="float:right; margin-bottom: 20px;" class="l_button">
+              Clear History
+            </div>
+
+            <div v-if="Object.values(history).length > 0">
+                <div v-if="history_to_show.length > 30">
+                    <b-pagination
+                        v-model="currentPage"
+                        :total-rows="history_to_show.length"
+                        :per-page="30"
+                    />
+                </div>
+            </div>
+
+        </div>
+
+        <div style="height: calc(100% - 60px) ; width: 100% ; overflow-y:auto;">
+            <div v-if="Object.values(history).length > 0">
+
+                <hr>
+        
+                <div v-for="group in history_to_show.slice((currentPage - 1) * 30, currentPage * 30)" :key="group.key" style="clear: both;">
+
+                
+                    <div @click="delete_hist(group.key)" style="float:right; margin-top: 10px;"  class="l_button">Delete</div>
+                    <!-- <div @click="share_on_arthub(group)" style="float:right; margin-top: 10px;"  class="l_button">Share</div> -->
+
+                    <b-dropdown left variant="link" size="sm" toggle-class="text-decoration-none" no-caret style="float:right; margin-top: 5px;">
+                        <template #button-content>
+                            <div   class=" l_button "  >
+                                Share 
+                            </div>
+                        </template>
+                        <b-dropdown-item-button   @click="share_on_arthub(group)"  >Share on ArtHub.ai</b-dropdown-item-button>
+                    </b-dropdown>
+
+                    
+                    <p class="history_box_info " style="user-select: text;">
+                        <img  v-for=" img in get_inp_imgs_from_group(group)" :src="'file://' +img" :key="img" style="height:50px">
+                        <br  v-if="get_inp_imgs_from_group(group).length > 0 " >
+                        <br  v-if="get_inp_imgs_from_group(group).length > 0 " >
+                  
+                        <span style="opacity: 0.5;" v-if="get_box_params_str(group)"> {{get_box_params_str(group)}} </span>
+                        <br   v-if="get_box_params_str(group)">
+                        
+                        {{group.params.prompt}}
+
+
+                    </p>
+                    
+                    <GalleryPane :n_imgs="group.num_imgs"  :img_w="group.img_width"  :img_h="group.img_height"  :image_data="group.imgs" :menu_items="menu_items" :on_menu_item_click="on_image_menu_item_click"   :always_fixed_col_size="300"  :on_image_click="on_image_click" > </GalleryPane>
+
+
+                    <div style="clear: both; display: table; margin-bottom: 10px;">
+                    </div>
+                    
+                    <hr>
+
+
+                </div>
+
+
+            </div>
+            <div v-else>
+                <div class="center">
+                        <p>No images generated yet.</p>
+                </div>
+            </div>
+        </div>
+    </div>
+</template>
+<script>
+import {native_confirm} from "../native_functions_vue_bridge.js";
+import {share_on_arthub} from '../utils.js'
+import GalleryPane from "../components_bare/GalleryPane.vue"
+import {image_manu_functions} from "../components/image_menu_functions.js"
+import {open_popup , form_params_to_text , form_params_to_readable_dict, migrate_history_only_once} from "../utils"
+
+import Vue from 'vue'
+import Fuse from 'fuse.js'
+
+const History =  {
+    name: 'History',
+    props: {
+        app:Object, 
+    },
+    components: {
+        GalleryPane
+    },
+    mounted() {
+        this.app.functions.add_to_history = this.add_to_history
+    },
+    data() {
+        let history = {}
+        let hist = window.ipcRenderer.sendSync('load_data' , 'history.json')
+        if(hist.history){
+            history = hist.history;
+        }
+
+        try {
+            let new_items = migrate_history_only_once( history)
+            for(let k in new_items){
+                history[k] = new_items[k]
+            }
+        } catch (error) {
+            console.error(error);
+        }
+
+        
+
+        let menu_items = []
+        for(let fn of Object.keys(image_manu_functions)){
+            if(fn != "use_params_current_page")
+            {
+                menu_items.push({id: fn , text: image_manu_functions[fn].text })
+            }
+        }
+
+
+        return {
+            app_state : this.app.app_state,
+            searchText: '',
+            currentPage: 1,
+            history : history,
+            show_history_in_oldest_first : false,
+            menu_items :menu_items,
+        };
+    },
+
+    computed: {
+      history_to_show() {
+          let history = Object.values(this.history);
+          const that = this;
+          const list = this.show_history_in_oldest_first ? history : history.reverse();
+          if (that.searchText.trim() === '') {
+            return list;
+          }
+          
+          const fuse = new Fuse(list, {
+            keys: ['prompt'],
+            useExtendedSearch: true,
+          });
+
+          return fuse.search(that.searchText).map(r => r.item);
+
+       },
+    },
+
+    watch: {
+        'history': {
+            handler: function() {
+                this.save_history()
+            },
+            deep: false
+        } , 
+    }, 
+
+
+    methods: {
+
+
+        get_inp_imgs_from_group(group){
+
+            let ret = []
+
+            let i1 = (group.params || {}).input_image_with_mask
+            if(i1 && i1 != "" && i1 != 'undefined')
+                ret.push(i1)
+
+            if( (group.params || {}).controlnet_input_image_path )
+                ret.push( (group.params || {}).controlnet_input_image_path )
+
+            return ret
+        },
+
+
+        add_to_history(k , history_vals ){
+            history_vals = JSON.parse(JSON.stringify(history_vals))
+            console.log("got to hist")
+            console.log(history_vals)
+            if(history_vals.imgs.length == 0)
+                return
+            history_vals.params = history_vals.imgs[0].params
+            history_vals.key = k
+            history_vals.prompt = history_vals.params.prompt
+            Vue.set(this.history ,  k , history_vals )
+        },
+
+        on_image_click(image_item_data){
+            open_popup('file://' + image_item_data.image_url)
+        },
+
+        delete_hist(k){
+            Vue.delete( this.history , k );
+        },
+
+        save_history(){
+            window.ipcRenderer.sendSync('save_data', {"history": this.history} , 'history.json');
+        },
+
+        toggle_order() {
+           Vue.set( this, "show_history_in_oldest_first", !this.show_history_in_oldest_first);
+        },
+
+        on_image_menu_item_click(menu_item_id , image_item_data){
+            image_manu_functions[menu_item_id](this.app , image_item_data )
+        },
+
+        get_box_params_str(box){
+            return form_params_to_text(box.params)
+        },
+
+         clear_history(){
+            if (native_confirm("Are you sure you want to clear history?")){
+                Vue.set( this , "history", {});
+            }
+        },
+
+        share_on_arthub(box){
+            this.app.app_state.global_loader_modal_msg = "Uploading";
+            let params = form_params_to_readable_dict(box.params);
+            let that = this;
+            let imgs = (box.imgs.map(x => x.image_url ) )
+            share_on_arthub( imgs , params , box.prompt).then((
+                function(){ that.app.app_state.global_loader_modal_msg = ""}
+            )).catch(
+                function(e ){ console.log(e); alert("Error in uploading.") ; that.app.app_state.global_loader_modal_msg = ""}
+            )
+        }
+
+    },
+}
+
+export default History;
+History.title = "History"
+History.icon = "history"
+History.description = "View generated images"
+History.img_icon = require("../assets/imgs/page_icon_imgs/history.png")
+History.home_category = "pages"
+History.sidebar_show = "always"
+
+
+</script>
+<style>
+.page-item .page-link{
+    outline: none !important;
+   box-shadow: none;
+}
+.page-item .page-link{
+    font-size: 13px;
+}
+@media (prefers-color-scheme: dark) {
+    .page-item .page-link, .page-item.disabled .page-link{
+        background-color:#303030;
+        border-color: #303030;
+        color:rgba(255, 255, 255, 0.5);
+    }
+    .page-item.active .page-link{
+        background-color:#606060;
+        border-color: #606060;
+    }
+}
+</style>
+<style scoped>
+.history_box_info {
+   
+    padding :12px;
+    border-radius: 5px;
+    max-width: calc(100vw - 200px );
+}
+
+
+
+.history_box {
+    height:230px;
+    float:left;
+    margin-right: 10px;
+    margin-bottom: 30px;
+}
+</style>
diff --git a/electron_app/src/pages/Homepage.vue b/electron_app/src/pages/Homepage.vue
new file mode 100644
index 00000000..153d6f17
--- /dev/null
+++ b/electron_app/src/pages/Homepage.vue
@@ -0,0 +1,139 @@
+<template>
+
+    <div class="main_container">
+
+        <div v-for="category in categories" :key="category[0]"> 
+            <h2> {{category[1]}} </h2>
+            <div class="icon_container">
+                <div v-for="item in all_icons(category[0]) " 
+                    :key="item.id" 
+                    v-bind:style="{ 'background-image': 'url(' +( item.img_icon || default_img )+ ')' }"
+                    @click="app.functions.switch_page(item.id)" 
+                    class="select_app"> 
+                    <div class="select_app_desc"> 
+                        <h2>  {{item.text}}</h2> 
+                        <p> {{item.description}} </p>
+                        <div class="l_button button_colored" style="margin-top: 10px;"> Open </div>
+                    </div> 
+                </div>
+            
+            </div>
+
+            <br> 
+        </div>
+        <hr>
+       
+
+    </div>
+
+    
+</template>
+<script>
+const Home ={
+    name: 'Home',
+    props: {app:Object, },
+    components: {},
+    mounted() {
+
+    },
+    data() {
+        return {
+
+            categories: [
+                ["main" , "All AI Tools"],
+                ["pages" , "Pages"],
+                ["misc" , "Miscellaneous"],
+            ]
+        };
+    },
+    methods: {
+        all_icons(category){
+            let ret = []
+            let items = (this.app.all_pages_ready ) ?  this.app.$refs.router.all_applet_items : [];
+            for(let item of items){
+                if(item.home_category == category)
+                    ret.push(item)
+            }
+            return ret;
+        }, 
+    },
+    computed: {
+        
+
+        default_img(){
+            return require("../assets/imgs/page_icon_imgs/default1.png")
+        }
+    }
+}
+
+export default Home;
+Home.title = "Home"
+Home.icon = "home"
+Home.home_category = undefined
+Home.sidebar_show = "always"
+// add this to the always_on_pages to the PagesRouter
+
+</script>
+<style>
+</style>
+<style scoped>
+
+.main_container{
+    padding: 20px;
+    width: 100%;
+    height: 100%;
+    overflow: auto;
+}
+
+.icon_container{
+    display: flex;
+   flex-wrap: wrap;
+}
+
+.select_app{
+    width:280px;
+    height: 230px;
+    margin: 5px;
+    background-size: contain;
+    background-color: var(--sidebar-color);
+    position: relative;
+}
+
+@media only screen and (max-width: 1730px) {
+  .select_app {
+    width : calc(20% - 10px)
+  }
+}
+
+
+
+@media only screen and (max-width: 1430px) {
+  .select_app {
+    width : calc(25% - 10px)
+  }
+}
+
+
+@media only screen and (max-width: 1200px) {
+  .select_app {
+    width : calc(33% - 10px)
+  }
+}
+
+
+
+
+.select_app_desc{
+    background-color: var(--sidebar-color); ;
+    padding: 15px;
+    position: absolute;
+    bottom: 0;
+    width: 100%;
+}
+
+.select_app_desc > p{
+    margin-bottom: 3px;
+}
+
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/pages/Img2Img.vue b/electron_app/src/pages/Img2Img.vue
new file mode 100644
index 00000000..ab55d315
--- /dev/null
+++ b/electron_app/src/pages/Img2Img.vue
@@ -0,0 +1,81 @@
+<template>
+    <SDImageGenerationApplet 
+        ref="sd_applet"   
+        name="img2img" :form_data="form_data" :form_tags="[  'img2img']" :app="app" 
+        :check_options_input_fn="check_options_input_fn"
+        :postprocess_form_options_fn="postprocess_form_options_fn"> </SDImageGenerationApplet>
+</template>
+<script>
+
+
+import SDImageGenerationApplet from "../components/SDImageGenerationApplet.vue"
+import Vue from 'vue'
+
+
+const Img2Img = {
+    name: 'Img2Img',
+    props: {
+        app:Object, 
+    },
+    components: {SDImageGenerationApplet},
+    mounted() {
+        this.app.functions.send_to_img2img = this.send_to_img2img; 
+    },
+    data() {
+        let form_data = require("../forms/sd_options_adv.json")
+        
+        return {
+            form_data:form_data, 
+        };
+    },
+    methods: {
+       send_to_img2img(im_path, params ){
+          Vue.set( this.$refs.sd_applet.sd_options , "input_img" ,  im_path );
+          if(params){
+             params = JSON.parse(JSON.stringify(params))
+             params.input_img = undefined
+             params.seed = undefined
+             if(params.raw_form_options)
+                params.raw_form_options.input_img = undefined
+                params.raw_form_options.seed = undefined
+             this.$refs.sd_applet.load_options(params)
+          }
+          this.app.functions.switch_page("Img2Img")
+
+       }, 
+
+       check_options_input_fn(){
+            if((!this.$refs.sd_applet.sd_options.input_img) || this.$refs.sd_applet.sd_options.input_img=="" ){
+                this.app.show_toast("You need to specify an input image")
+                return false
+            } else {
+                return true
+            }
+       }, 
+
+       postprocess_form_options_fn(options){
+            if(!options.img_width){
+                options.img_width = this.$refs.sd_applet.sd_options.input_img__AUX__width
+            }
+            if(!options.img_height){
+                options.img_height = this.$refs.sd_applet.sd_options.input_img__AUX__height
+            }
+
+            return options
+       }
+    },
+}
+
+export default Img2Img;
+Img2Img.title = "Image to image"
+Img2Img.description = "Transform images with text descriptions"
+Img2Img.icon = "images"
+Img2Img.img_icon = require("../assets/imgs/page_icon_imgs/img2img.png")
+Img2Img.home_category = "main"
+Img2Img.sidebar_show = "always"
+
+</script>
+<style>
+</style>
+<style scoped>
+</style>
\ No newline at end of file
diff --git a/electron_app/src/pages/Inpainting.vue b/electron_app/src/pages/Inpainting.vue
new file mode 100644
index 00000000..ba239487
--- /dev/null
+++ b/electron_app/src/pages/Inpainting.vue
@@ -0,0 +1,387 @@
+<template>
+
+    <BasicSDApplet
+        :app=app 
+        :input_form=input_form_elements_processed
+        :sd_options=sd_options
+        name="inpainting"
+        :form_tags="form_tags_computed"
+        :required_assets=required_assets
+        ref="basic_sd_applet"
+        :model_options_types="model_options_types"
+    >   
+        
+        <template v-slot:input_buttons>
+            
+            <div v-if="is_mounted && stable_diffusion.is_input_avail"  @click="generate(false)" class="l_button button_colored button_medium" style="float:right">Generate</div>
+            <div v-if="is_mounted && stable_diffusion.is_input_avail"  @click="clear_canvas" class="l_button button_medium" style="float:right">Clear Stage</div>
+            
+            <span v-else-if="is_mounted &&  stable_diffusion.generated_by=='Inpainting'"   >
+                <div v-if="is_stopping" class="l_button button_medium button_colored" style="float:right; float:right ;  " >Stopping ...</div>
+                <div v-else class="l_button button_medium button_colored" style="float:right; float:right ;  " @click="stop_all">Stop</div>
+            </span>
+
+        </template>
+
+        <template v-slot:output_workpace>
+            <div>
+                <br> 
+                <div v-if="(redo_history.length > 0 ||  undo_history.length > 0) && is_mounted && stable_diffusion.is_input_avail" class="l_button" style="float:right " @click="do_redo" > Redo</div>
+                <div v-if="(redo_history.length > 0 ||  undo_history.length > 0)  && is_mounted && stable_diffusion.is_input_avail" class="l_button" style="float:right " @click="do_undo" > Undo</div>
+                <div class="l_button" style="float:right " @click="open_input_image" > Open </div>
+                <div  v-if="inp_img"  class="l_button" style="float:right "  @click="save_img" > Save </div>
+                <div v-if="inp_img"   class="l_button" style="float:right " @click="$refs.inp_img_canvas.clear_inpaint()" > Clear Mask</div>
+
+                <div v-if="is_mounted && stable_diffusion.is_input_avail && inp_img"   style="float:right ; margin-right: 10px" >
+                    <input v-model="stroke_size_no" style="zoom:0.8; margin-top: 7px; width:100px" type="range"
+                            min="1" max="200" >                
+                </div>
+                <div v-if="is_mounted && stable_diffusion.is_input_avail && inp_img"   class="l_button no_hover_bg" style="float:right ; margin-right: -5px; " > Stroke Size</div>
+
+                <br> 
+            </div>
+
+            <div class="inapint_container"  @drop.prevent="onDragFile" @dragover.prevent > 
+                <ImageCanvas style="cursor: crosshair;"  v-if="inp_img"  ref="inp_img_canvas" :is_inpaint="true" :image_source="inp_img"  :is_disabled="!stable_diffusion.is_input_avail" id="inpaint"  canvas_id="inpaintcan" canvas_d_id="inpaintcand" :stroke_size_no="stroke_size_no" ></ImageCanvas>
+                <div v-else @click="open_input_image" style=" "  :class="{ pointer_cursor  : is_sd_active }" >
+                    <center>
+                        <p style="padding-top: calc( 50vh - 115px);padding-bottom: calc( 50vh - 155px);  opacity: 70%;" >Click to add input image and draw a mask</p>
+                    </center>
+                </div>
+            </div>
+
+            <div v-if="is_post_generate_box_showing" class="post_generate_box"> 
+                <div  class="l_button button_medium" @click="discard_generation"  > Discard </div>
+                <div  class="l_button button_colored button_medium" @click="is_post_generate_box_showing = false"  > Keep </div>
+                <div  class="l_button button_colored button_medium"  @click="retry_generatge" > Retry </div>
+               
+            </div>
+            
+            
+            
+            <div style="" v-if="is_mounted && !stable_diffusion.is_input_avail && stable_diffusion.generated_by=='Inpainting'">
+                <LoaderModal  :loading_percentage="done_percentage" loading_title="Generating" :loading_desc="stable_diffusion.generation_state_msg" :remaining_times="stable_diffusion.remaining_times"></LoaderModal>
+            </div>
+
+        </template>
+
+    </BasicSDApplet>
+
+</template>
+
+
+
+<script>
+
+import LoaderModal from '../components_bare/LoaderModal.vue'
+import BasicSDApplet from "../components/BasicSDApplet.vue"
+import ImageCanvas from '../components_bare/ImageCanvas.vue'
+
+import {find_in_form_recursive} from "../utils.js"
+import {inpaint_assets , prep_sd_optins} from "../utils/in_out_paint_utils.js"
+
+
+const Inpainting = {
+    name: 'Inpainting.vue',
+    props: {
+        app:Object, 
+    },
+    components: { LoaderModal, BasicSDApplet , ImageCanvas  },
+    mounted() {
+        this.stable_diffusion = this.app.stable_diffusion
+        this.app.functions.send_to_inpaint = this.send_to_inpaint; 
+        this.is_mounted = true
+    },
+    data() {
+        return {
+            sd_options : {"num_imgs":"1"},
+            backend_error : "",
+            is_mounted: false,
+            is_stopping : false,
+            undo_history : [],
+            redo_history : [],
+            done_percentage: -1,
+            retry_params: undefined,
+            inp_img: "",
+            is_post_generate_box_showing : false,
+            stroke_size_no: "30",
+
+
+        };
+    },
+    computed : {
+
+        is_sd_active(){
+            if(!this.is_mounted)
+                return false;
+            return this.stable_diffusion.is_input_avail;
+        },
+
+        required_assets(){
+            return inpaint_assets(this , "Generative Fill");
+        }, 
+
+        form_tags_computed(){
+            if(this.sd_options.outpaint_function_name =="Image To Image"){
+                return ['inpainting', 'input_image_strength']
+            }
+
+            return ['inpainting']
+        },
+
+        model_options_types(){
+            return ["sd_model" ,"sd_model_inpaint"]
+            
+        },
+
+        input_form_elements_processed(){
+            let form_or = require("../forms/sd_options_adv.json")
+            form_or = JSON.parse(JSON.stringify(form_or))
+            let el = find_in_form_recursive( "selected_sd_model" , form_or)
+
+            el['options'] = [ "SD1.5_Inpainting" , "Default_SD1.5" ]
+
+            return form_or
+        }
+    },
+    methods: {
+        generate(is_retry){
+
+            if(!(this.stable_diffusion.is_input_avail))
+                return;
+
+            if(!this.$refs.basic_sd_applet.check_input_form_n_show_error()){
+                return
+            }
+
+            this.is_stopping = false;
+            this.backend_error = "";
+            this.done_percentage = -1;
+
+            this.is_post_generate_box_showing = false
+
+
+            let sd_options_object = this.$refs.basic_sd_applet.get_sd_form_outputs()
+
+            let img_url
+            let img_mask_url
+
+            if(this.retry_params == undefined)
+                this.retry_params = {}
+
+            if(is_retry){
+                img_url = this.retry_params.img_url
+                img_mask_url = this.retry_params.img_mask_url
+                
+            } else {
+                let box_img_b64 = this.$refs.inp_img_canvas.get_img_b64();
+                img_url = window.ipcRenderer.sendSync('save_b64_image',  box_img_b64 , true );
+
+
+                let box_mask_img_b64 =  this.$refs.inp_img_canvas.get_mask_b64();
+                img_mask_url = window.ipcRenderer.sendSync('save_b64_image',  box_mask_img_b64 , true );
+
+                this.retry_params.mask_b64_image = box_mask_img_b64
+                this.retry_mask_cached =  this.$refs.inp_img_canvas.get_mask_for_cache()
+            }
+
+
+            
+            
+            this.retry_params.img_url = img_url
+            this.retry_params.img_mask_url = img_mask_url
+            
+
+
+
+            console.log(img_url)
+            console.log(img_mask_url)
+
+            sd_options_object.input_img = img_url
+
+            prep_sd_optins(this , sd_options_object , "Generative Fill" , img_mask_url)
+
+            let that = this;
+
+            this.undo_history.push(img_url)
+            this.redo_history =  []
+
+            let callbacks = {
+                on_img(img_path){
+                    that.$refs.inp_img_canvas.clear_inpaint()
+                    that.inp_img = img_path.generated_img_path
+                    that.is_post_generate_box_showing = true
+
+                },
+                on_progress(p){
+                    that.done_percentage = p;
+                    
+                },
+                on_err(err){
+                    that.app.show_toast("Error : " + err)
+                    that.backend_error = err;
+                },
+            }
+                
+            this.stable_diffusion.text_to_img(sd_options_object, callbacks, 'Inpainting');
+           
+        }, 
+
+        retry_generatge(){
+            let that = this
+            this.inp_img = this.retry_params.img_url
+            setTimeout(function(){
+                that.$refs.inp_img_canvas.restore_mask(that.retry_mask_cached)
+            } , 150 ) 
+            this.generate(true)
+        },
+
+        do_undo(){
+            if(this.undo_history.length == 0)
+                return;
+
+            this.is_post_generate_box_showing = false
+            let a = this.undo_history.pop()
+
+            if(a){
+                this.redo_history.push(this.inp_img)
+                this.inp_img = a;
+                if(this.$refs.inp_img_canvas){
+                    this.$refs.inp_img_canvas.clear_inpaint()
+                }
+            }
+                
+        },
+
+        do_redo(){
+            if(this.redo_history.length == 0)
+                return;
+            this.is_post_generate_box_showing = false
+            let a = this.redo_history.pop()
+            if(a){
+                this.undo_history.push(this.inp_img )
+                this.inp_img = a;
+                if(this.$refs.inp_img_canvas){
+                    this.$refs.inp_img_canvas.clear_inpaint()
+                }
+               
+            }
+            
+        },
+
+        discard_generation(){
+            this.inp_img = this.retry_params.img_url
+            let that = this;
+            setTimeout(function(){
+                that.$refs.inp_img_canvas.restore_mask(that.retry_mask_cached)
+            } , 150 ) 
+            this.is_post_generate_box_showing = false
+            
+        },
+
+        onDragFile(e) {
+            if (!this.stable_diffusion.is_input_avail)
+                return;
+            if (!e.dataTransfer.files[0].type.startsWith('image/'))
+                return;
+            let img_path = e.dataTransfer.files[0].path;
+            this.set_inp_image(img_path)
+        },
+
+        set_inp_image(img_path){
+            this.is_post_generate_box_showing = false
+            this.inp_img = img_path;
+            this.undo_history = []
+            this.redo_history = []
+            this.input_img_orig = img_path
+            this.history_key = Math.random()+"inp"
+            if(this.$refs.inp_img_canvas){
+                this.$refs.inp_img_canvas.clear_inpaint()
+            }
+        },
+
+
+        open_input_image(){
+            if( !this.stable_diffusion.is_input_avail)
+                return;
+            let img_path = window.ipcRenderer.sendSync('file_dialog',  'img_file' );
+            if(img_path && img_path != 'NULL'){
+               this.set_inp_image(img_path)
+            }
+        },
+
+        stop_all(){
+            this.is_post_generate_box_showing = false
+            this.is_stopping = true;
+            this.stable_diffusion.interupt();
+        }, 
+
+        clear_canvas(){
+            this.is_post_generate_box_showing = false
+            if(this.$refs.inp_img_canvas){
+                this.$refs.inp_img_canvas.clear_inpaint()
+            }
+            this.inp_img = ""
+            this.undo_history = []
+            this.redo_history = []
+            this.prompt = ""
+            this.input_img_orig = ""
+            this.history_key = ""
+            this.retry_params  = undefined
+        },
+
+        save_img(){
+            let out_path = window.ipcRenderer.sendSync('save_dialog' );
+            if(!out_path)
+                return
+            
+            let org_path = window.ipcRenderer.sendSync('save_b64_image',  this.$refs.inp_img_canvas.get_img_b64()  );
+            if(!org_path)
+                return
+            org_path = org_path.replaceAll("file://" , "")
+            window.ipcRenderer.sendSync('save_file', org_path+"||" +out_path);
+        },
+
+       
+        send_to_inpaint(im_path ){
+          this.set_inp_image(im_path)
+          this.app.functions.switch_page("Inpainting")
+
+       }
+    },  
+}
+
+export default Inpainting;
+Inpainting.title = "Inpainting"
+Inpainting.description = "Add or remove objects from an image"
+Inpainting.icon = "paint-brush"
+Inpainting.img_icon = require("../assets/imgs/page_icon_imgs/inpainting.png")
+Inpainting.home_category = "main"
+Inpainting.sidebar_show = "always"
+
+</script>
+<style>
+</style>
+
+<style scoped>
+
+.inapint_container{
+        border-color:var(--border-color-invert);
+        border-width: 1px;
+        border-style: solid;
+        width:  calc(100% - 30px) ; 
+        height: calc(100% - 30px - 70px) ;  
+        margin-left:15px ;
+        margin-top: 15px; 
+    }
+
+.post_generate_box{
+    position: fixed;
+    background-color: var(--canvas-toolbox-bg );
+    padding:18px;
+    margin-top: -100px;
+    right:50px
+}
+
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/pages/Logs.vue b/electron_app/src/pages/Logs.vue
new file mode 100644
index 00000000..8e7b3f96
--- /dev/null
+++ b/electron_app/src/pages/Logs.vue
@@ -0,0 +1,39 @@
+<template>
+    <div style="width: 100%; height :100% ; overflow:auto; padding:10px">
+        <h2> Logs </h2>
+        <p style="white-space: pre-line"> 
+            {{app.app_state.logs}}
+        </p>
+    </div>
+    
+</template>
+<script>
+const Logs = {
+    name: 'Logs',
+    props: {app:Object, },
+    components: {},
+    mounted() {
+
+    },
+    data() {
+        return {};
+    },
+    methods: {
+
+    },
+}
+
+export default Logs;
+Logs.title = "Logs"
+Logs.icon = "file"
+Logs.img_icon = require("../assets/imgs/page_icon_imgs/default.png")
+Logs.home_category = undefined
+Logs.hide_in_sidebar = true
+Logs.sidebar_show = "never"
+// add this to the always_on_pages to the PagesRouter
+
+</script>
+<style>
+</style>
+<style scoped>
+</style>
\ No newline at end of file
diff --git a/electron_app/src/pages/ModelStore.vue b/electron_app/src/pages/ModelStore.vue
new file mode 100644
index 00000000..e2baf969
--- /dev/null
+++ b/electron_app/src/pages/ModelStore.vue
@@ -0,0 +1,262 @@
+<template>
+    <div class="main_container">
+
+        <div class="l_button button_colored button_medium" style="float:right;" @click="import_model_locally"> Import From Computer </div>
+        <br><br>
+        <hr>
+
+        <h2 v-if="downloaded_models_list.length > 0 || is_local_model_importing"> My Models </h2>
+        <div v-if="downloaded_models_list.length > 0 || is_local_model_importing" class="icon_container">
+
+            <div v-if="is_local_model_importing"  class="model_card" style="padding:20px">
+                <h2>Importing model</h2>
+                <br>
+                 <MoonLoader class="moonloader" color="#000000" size="50px" style="zoom:0.4"></MoonLoader>
+            </div>
+
+            <div v-for="model in downloaded_models_list" :key="model.id" class="model_card" v-bind:style="{ 'background-image': 'url(' + (model.img_url || default_img_url )+ ')' }">
+                 <div class="card_desc"> 
+                    <h2> {{model.title || model.id}} </h2> 
+                    <p> {{model.description}} </p> 
+                    <p style="zoom:0.7"> {{ model_metadata_to_str(model) }}</p>
+                    <DownloadButton :app=app  :asset_details="model"> </DownloadButton>
+                </div> 
+            </div>
+
+        </div>
+
+        <br>
+
+
+        <h2> Available Models </h2>
+        <div class="icon_container">
+
+            <div v-for="model in not_downloaded_models_list" :key="model.id" class="model_card" v-bind:style="{ 'background-image': 'url(' + (model.img_url || default_img_url) + ')' }">
+                 <div class="card_desc"> 
+                    <h2> {{model.title || model.id}} </h2> 
+                    <p> {{model.description}} </p> 
+                    <p style="zoom:0.7"> {{ model_metadata_to_str(model) }}</p>
+                    <DownloadButton v-if="!(model.min_version) || model.min_version <= app.current_build_number" :app=app  :asset_details="model"> </DownloadButton>
+                    <p  style="color:red" v-if="model.min_version && model.min_version > app.current_build_number"> You need to update DiffusionBee to use this model</p>
+                </div> 
+            </div>
+
+        </div>
+
+        <br> <hr> 
+        <div @click="load_models_list_from_web" class="l_button"> Refresh </div>
+
+        
+
+    </div>
+</template>
+<script>
+
+import Vue from 'vue'
+
+import DownloadButton from "../components/DownloadButton.vue"
+import MoonLoader from 'vue-spinner/src/MoonLoader.vue'
+
+const ModelStore ={
+    name: 'ModelStore',
+    props: {app:Object, },
+    components: {DownloadButton, MoonLoader},
+    mounted() {
+        this.load_models_list_local_storage()
+        this.load_models_list_from_web()
+    },
+    data() {
+        return {
+            is_local_model_importing : false, 
+            default_img_url : require("../assets/imgs/page_icon_imgs/default.png"),
+            models_list : [], 
+        };
+    },
+    computed: {
+        downloaded_models_list(){
+            if(!this.app.is_mounted)
+                return []
+
+            let ret = []
+            for(let k in this.app.assets_manager.all_avail_assets){
+                ret.unshift(this.app.assets_manager.all_avail_assets[k])
+            }
+            return ret;
+        } , 
+        not_downloaded_models_list(){
+            let that = this
+            return this.models_list.filter(model  => !(that.app.is_mounted && that.app.assets_manager.downloaded_assets[model.id]))
+        }
+    },
+    methods: {
+        load_models_list_from_web(){
+            let that = this;
+
+            let user_id = window.ipcRenderer.sendSync('get_instance_id' , '');
+            let models_url = "https://models.diffusionbee.com/list_models?user_id="+user_id;
+            
+            fetch(models_url, {cache: "no-store"})
+                .then(response => response.json())
+                .then(data =>  that.models_list = (data || that.models_list) )
+                .then(() => console.log(that.models_list))
+                .then(() =>  that.save_models_list_local_storage() )
+
+            
+        } ,     
+
+        load_models_list_local_storage(){
+            let models = window.localStorage.getItem("models_store")
+            if(models){
+                models = JSON.parse(models)
+            }
+            Vue.set(this , 'models_list' , models)
+        } , 
+
+        save_models_list_local_storage(){
+             window.localStorage.setItem('models_store' , JSON.stringify(this.models_list));
+        } , 
+
+        model_metadata_to_str(asset_details){
+            if(!asset_details.model_meta_data)
+                return ""
+
+            let r = ""
+
+            if(asset_details.model_meta_data.sd_type)
+                r += " " + asset_details.model_meta_data.sd_type
+
+            if(asset_details.model_meta_data.float_type)
+                r += " " + asset_details.model_meta_data.float_type
+            
+            return r
+        },
+
+        import_model_locally(){
+
+            if(this.is_local_model_importing)
+            {
+                this.app.show_toast("Model is already importing. Please wait")
+                return;
+            }
+
+            let that = this;
+            //TODO maybe ask for stuff like v-prediction , ckip_slip, image_size, trigger word,  before importing
+            let pytorch_model_path = window.ipcRenderer.sendSync('file_dialog',  "weights_file" );
+            if(!pytorch_model_path)
+                return;
+
+            if(pytorch_model_path == "NULL")
+                return;
+
+            let model_name = pytorch_model_path.replaceAll("\\" , "/").split("/");
+            model_name = model_name[model_name.length - 1].split(".")[0]
+
+
+            if(model_name.trim() == ""){
+                this.app.show_toast("Put non empty model name");
+                return;
+            }
+
+            if(this.app.assets_manager.all_avail_assets[model_name]){
+                this.app.show_toast("A model with this name already exists");
+                return;
+            }
+
+            let asset_details = {
+                id : model_name ,
+                filename: model_name , 
+                asset_path_raw: pytorch_model_path, 
+                post_process : "convert_sd_to_tdict", 
+                is_locally_imported : true, 
+                model_meta_data : {"type" : "sd_model" }
+            }
+
+            this.is_local_model_importing = true;
+
+            this.app.assets_manager.add_local_asset(asset_details , function(result, err ){
+                if(result == "success" ){
+                    that.is_local_model_importing = false;
+                } else {
+                    that.is_local_model_importing = false;
+                    that.app.show_toast("Error while importing " + err )
+                }
+
+            })
+        }
+    },
+}
+
+export default ModelStore;
+ModelStore.title = "Models"
+ModelStore.icon = "cubes"
+ModelStore.description = "Download, imoport and manage models"
+ModelStore.img_icon = require("../assets/imgs/page_icon_imgs/models.png")
+ModelStore.home_category = "pages"
+ModelStore.sidebar_show = "always"
+// add this to the always_on_pages to the PagesRouter
+
+</script>
+<style>
+</style>
+<style scoped>
+
+.main_container{
+    padding: 20px;
+    width: 100%;
+    height: 100%;
+    overflow: auto;
+}
+
+.icon_container{
+    display: flex;
+   flex-wrap: wrap;
+}
+
+.model_card{
+    width:230px;
+    height: 170px;
+    margin: 5px;
+    background-size: contain;
+    background-color: var(--sidebar-color);
+    position: relative;
+}
+
+
+@media only screen and (max-width: 1730px) {
+  .model_card {
+    width : calc(20% - 10px)
+  }
+}
+
+
+
+@media only screen and (max-width: 1430px) {
+  .model_card {
+    width : calc(25% - 10px)
+  }
+}
+
+
+@media only screen and (max-width: 1200px) {
+  .model_card {
+    width : calc(33% - 10px)
+  }
+}
+
+
+
+.card_desc{
+    background-color: var(--sidebar-color); ;
+    padding: 5px;
+    position: absolute;
+    bottom: 0;
+    width: 100%;
+}
+
+.card_desc > p{
+    margin-bottom: 3px;
+}
+
+
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/pages/PostProcessImage.vue b/electron_app/src/pages/PostProcessImage.vue
new file mode 100644
index 00000000..c273952a
--- /dev/null
+++ b/electron_app/src/pages/PostProcessImage.vue
@@ -0,0 +1,146 @@
+<template>
+    <BasicSDApplet
+        :app=app 
+        :input_form=form_data
+        :sd_options=sd_options
+        :name="'img_post_process'"
+        :form_tags="['img_post_process']"
+        :required_assets=[]
+        ref="basic_sd_applet"
+    >   
+
+    <template v-slot:input_buttons>
+            <div v-if="!is_running"  @click="upscale" class="l_button button_colored button_medium" style="float:right">Upscale</div>
+    </template>
+
+    <template v-slot:output_workpace>
+        <GenerationGallery  :menu_items_skip="['use_params_current_page']" :app="app" :n_to_keep="2" ref="gallery"> </GenerationGallery>
+    </template>
+
+
+    </BasicSDApplet>
+</template>
+<script>
+
+import BasicSDApplet from "../components/BasicSDApplet.vue"
+import GenerationGallery from "../components/GenerationGallery.vue"
+import Vue from 'vue'
+
+const PostProcessImage = {
+    name: 'PostProcessImage',
+    props: {app:Object, },
+    components: {BasicSDApplet, GenerationGallery},
+    mounted() {
+        this.app.functions.send_to_postprocess = this.send_to_postprocess; 
+    },
+    data() {
+        return {
+            form_data:[
+                {
+                    "id" : "input_img",
+                    "component" : "ImageInput",
+                    "get_img_size" : true,
+                }, 
+
+                {
+                    "id": "65453545",
+                    "component": "InputWithDesc",
+                    "title": "Upscaler",
+                    "description": "",
+                    "children": [
+                        {
+                            "id": "model",
+                            "component": "Dropdown",
+                            "options": ["Real-ESRGAN"],
+                            "icon": "photo",
+                            "default_value" : "Real-ESRGAN" , 
+                            "is_persistant" : true
+                        }
+                    ]
+                },
+            ], 
+            sd_options : {},
+            is_running : false,
+
+        };
+    },
+    methods: {
+
+        send_to_postprocess(im_path ){
+          Vue.set( this.sd_options , "input_img" ,  im_path );
+          this.app.functions.switch_page("PostProcessImage")
+       },
+
+        upscale(){
+
+            let in_img = this.sd_options.input_img
+
+            if(!in_img || in_img==''){
+                this.app.show_toast('Please select an input image first')
+                return
+            }
+                
+
+            let that = this
+
+            if(that.is_running)
+                return
+
+            this.$refs.gallery.clear_all()
+
+            let h = this.sd_options['input_img__AUX__height' ] 
+            let w = this.sd_options['input_img__AUX__width' ]
+
+            if(h > 2048 || w > 2048){
+                this.app.show_toast('Input image is too large')
+                return
+            }
+
+            this.$refs.gallery.add_group({
+                group_id : 1 ,
+                num_imgs: 1 , 
+                img_height: h , 
+                img_width:  w, 
+                
+                imgs : [{params : {}, done_percentage: -1 } ]
+            })
+            
+            that.is_running = true
+            window.ipcRenderer.invoke('run_realesrgan', in_img.split("?")[0] ).then((result) => {
+                let gallery_group = that.$refs.gallery.get_group(1 )
+                let el_to_update = gallery_group.imgs[ 0  ]
+
+                if(result) 
+                {
+                    el_to_update.image_url = result ;
+                }
+                else{
+                    console.log("got error while upscale")
+                    el_to_update.image_url = "ERROR" ;
+                    el_to_update.description = "Error in upscaling the image" ;
+                }
+
+                this.$refs.gallery.update_group(gallery_group)
+                that.is_running = false
+            })
+
+
+        }
+    },
+}
+
+export default PostProcessImage;
+PostProcessImage.title = "Upscaler"
+PostProcessImage.description = "Use AI to increase the resolution of an image."
+PostProcessImage.icon = "expand-arrows-alt"
+PostProcessImage.img_icon = require("../assets/imgs/page_icon_imgs/upscale.png")
+PostProcessImage.home_category = "main"
+PostProcessImage.sidebar_show = "always"
+
+// add this to the always_on_pages to the PagesRouter
+
+</script>
+<style>
+</style>
+<style scoped>
+</style>
\ No newline at end of file
diff --git a/electron_app/src/pages/Settings.vue b/electron_app/src/pages/Settings.vue
new file mode 100644
index 00000000..ad48e8e1
--- /dev/null
+++ b/electron_app/src/pages/Settings.vue
@@ -0,0 +1,121 @@
+<template>
+    <div style="width:100%; height:100%; overflow: auto; padding: 20px;">
+        
+     <h1>Settings</h1>
+        <br>
+       <h2>General Settings</h2>
+        <br>
+        <div class="setting_box">
+        <div class="settings_left">
+        <h3>Notification sound</h3>
+        <p>To play a notification sound when generation of an image is completed</p>
+        </div>
+        
+        <div style="float:right;margin-right: 9px;align-self: center;" >
+            <label class="switch">
+                <input type="checkbox" v-model="app.app_state.app_data.settings.notification_sound" checked>
+                <span class="toggle round"></span>
+            </label>
+        </div>
+        </div>
+        <hr>
+
+
+    </div>
+</template>
+<script>
+const Settings ={
+    name: 'Settings',
+    props: {app:Object, },
+    components: {},
+    mounted() {
+
+    },
+    data() {
+        return {};
+    },
+    methods: {
+
+    },
+}
+
+export default Settings;
+Settings.title = "Settings"
+Settings.icon = "tools"
+Settings.img_icon = require("../assets/imgs/page_icon_imgs/settings.png")
+Settings.home_category = "pages"
+Settings.hide_in_sidebar = true
+
+// add this to the always_on_pages to the PagesRouter
+
+</script>
+<style>
+</style>
+<style scoped>
+
+.setting_box{
+    display: flex;
+    flex-direction: row;
+}
+
+.settings_left{
+    flex: 1 1 auto;
+}
+
+.switch {
+  position: relative;
+  display: inline-block;
+  width: 60px;
+  height: 30px;
+}
+
+.switch input { 
+  opacity: 0;
+  width: 0;
+  height: 0;
+}
+
+.toggle {
+  position: absolute;
+  cursor: pointer;
+  top: 0;
+  left: 0;
+  right: 0;
+  bottom: 0;
+  background-color: #ccc;
+  -webkit-transition: .4s;
+  transition: .4s;
+}
+
+.toggle:before {
+  position: absolute;
+  content: "";
+  height: 22px;
+  width: 23px;
+  left: 5px;
+  bottom: 4px;
+  background-color: white;
+  -webkit-transition: .4s;
+  transition: .4s;
+}
+
+input:checked + .toggle {
+  background-color: #3E7BFA;
+}
+
+
+input:checked + .toggle:before {
+  transform: translateX(27px);
+}
+
+.toggle.round {
+  border-radius: 34px;
+}
+
+.toggle.round:before {
+  border-radius: 50%;
+}
+
+
+
+</style>
\ No newline at end of file
diff --git a/electron_app/src/pages/Training.vue b/electron_app/src/pages/Training.vue
new file mode 100644
index 00000000..d8294f7d
--- /dev/null
+++ b/electron_app/src/pages/Training.vue
@@ -0,0 +1,37 @@
+<template>
+    <div style=" width: 100%; height: 100%; padding:30px"> 
+        <h2> Coming Soon </h2>
+        
+    </div>
+</template>
+
+<script>
+const Training ={
+    name: 'Training',
+    props: {app:Object, },
+    components: {},
+    mounted() {
+
+    },
+    data() {
+        return {};
+    },
+    methods: {
+
+    },
+}
+
+
+export default Training;
+Training.title = "Training"
+Training.icon = "file"
+Training.img_icon = require("../assets/imgs/page_icon_imgs/training.png")
+Training.home_category = "main"
+Training.description = "Train a model on your own images using DreamBooth."
+// add this to the always_on_pages to the PagesRouter
+
+</script>
+<style>
+</style>
+<style scoped>
+</style>
\ No newline at end of file
diff --git a/electron_app/src/pages/Txt2Img.vue b/electron_app/src/pages/Txt2Img.vue
new file mode 100644
index 00000000..29eaa236
--- /dev/null
+++ b/electron_app/src/pages/Txt2Img.vue
@@ -0,0 +1,45 @@
+<template>
+    <SDImageGenerationApplet ref="sd_applet" name="txt2img"  :form_data="form_data" :form_tags="[ 'txt2img']" :app="app"> </SDImageGenerationApplet>
+</template>
+<script>
+
+
+import SDImageGenerationApplet from "../components/SDImageGenerationApplet.vue"
+
+
+const Txt2Img =  {
+    name: 'Txt2Img',
+    props: {
+        app:Object, 
+    },
+    components: {SDImageGenerationApplet},
+    mounted() {
+
+    },
+    data() {
+        let form_data = require("../forms/sd_options_adv.json")
+        return {
+            form_data:form_data
+        };
+    },
+    methods: {
+       
+    },
+}
+
+
+Txt2Img.title = "Text to image"
+Txt2Img.icon = "file-image"
+Txt2Img.description = "Generate images with text descriptions"
+Txt2Img.img_icon = require("../assets/imgs/page_icon_imgs/txt2img.png")
+Txt2Img.home_category = "main"
+Txt2Img.sidebar_show = "always"
+
+export default Txt2Img;
+
+
+</script>
+<style>
+</style>
+<style scoped>
+</style>
\ No newline at end of file
diff --git a/electron_app/src/preload.js b/electron_app/src/preload.js
index 0fa31d46..b79e0f27 100644
--- a/electron_app/src/preload.js
+++ b/electron_app/src/preload.js
@@ -6,7 +6,7 @@ contextBridge.exposeInMainWorld('ipcRenderer', ipcRenderer)
 contextBridge.exposeInMainWorld('ipcRenderer_on', ipcRenderer.on)
 
 var bind_ipc_renderer_on_fn = undefined;
-
+var bind_ipc_download_on_fns = {}
 
 function bind_ipc_renderer_on(fn) {
     bind_ipc_renderer_on_fn = fn;
@@ -14,26 +14,42 @@ function bind_ipc_renderer_on(fn) {
 
 contextBridge.exposeInMainWorld('bind_ipc_renderer_on', bind_ipc_renderer_on)
 
-
 ipcRenderer.on("to_renderer", (e, data) => { // the msg channel which is used for electron to send msges to browser / renderer
     if (bind_ipc_renderer_on_fn)
         bind_ipc_renderer_on_fn(data)
 });
 
 
-// Expose ipcRenderer to the client ( not using it yet )
-// contextBridge.exposeInMainWorld('ipcRenderer', {
-//   send: (channel, data) => {
-//     let validChannels = ['client_channel'] // <-- Array of all ipcRenderer Channels used in the client
-//     if (validChannels.includes(channel)) {
-//       ipcRenderer.send(channel, data)
-//     }
-//   },
-//   receive: (channel, func) => {
-//     let validChannels = ['electron_channel'] // <-- Array of all ipcMain Channels used in the electron
-//     if (validChannels.includes(channel)) {
-//       // Deliberately strip event as it includes `sender`
-//       ipcRenderer.on(channel, (event, ...args) => func(...args))
-//     }
-//   }
-// })
\ No newline at end of file
+function bind_ipc_download_on( download_id,  fn_progress , fn_success, fn_error ) {
+    console.log("gineded " + download_id)
+    bind_ipc_download_on_fns[download_id] = {
+        "progress" : fn_progress,
+        "success" : fn_success,
+        "error" : fn_error,
+    }
+}
+
+contextBridge.exposeInMainWorld('bind_ipc_download_on', bind_ipc_download_on)
+
+
+function unbind_ipc_download_on( download_id ){
+    bind_ipc_download_on_fns[download_id] = undefined;
+}
+
+
+
+contextBridge.exposeInMainWorld('unbind_ipc_download_on', unbind_ipc_download_on)
+
+
+ipcRenderer.on("to_download", (e, data) => { // the msg channel which is used for electron to send msges to browser / download
+    if(!bind_ipc_download_on_fns[data.download_id]){
+        console.log("no fn di "+ data.download_id)
+        return 
+    }
+    if(!bind_ipc_download_on_fns[data.download_id][data.fn]){
+        console.log("no fn d ")
+        return
+    }
+    bind_ipc_download_on_fns[data.download_id][data.fn](data.msg)
+});
+
diff --git a/electron_app/src/py_vue_bridge.js b/electron_app/src/py_vue_bridge.js
index 7c998d57..4936563f 100644
--- a/electron_app/src/py_vue_bridge.js
+++ b/electron_app/src/py_vue_bridge.js
@@ -60,7 +60,11 @@ function on_msg_from_py(msg) {
 
 function add_log(msg) {
     if (app_component_object) {
-        Vue.set(app_component_object.app_state, 'logs' , app_component_object.app_state.logs + "\n" + msg );
+        let out = app_component_object.app_state.logs + "\n" + msg
+        if( out.length > 10000000){
+            out = out.slice(-1 * 5000000 )
+        }
+        Vue.set(app_component_object.app_state, 'logs' , out );
     }
     
 }
diff --git a/electron_app/src/utils.js b/electron_app/src/utils.js
index e321fc56..eacf44a7 100644
--- a/electron_app/src/utils.js
+++ b/electron_app/src/utils.js
@@ -146,6 +146,7 @@ async function temp_upload_img(img_path) {
 // this will only be called when the user clicks to upload thier data for sharing. 
 async function share_on_arthub(imgs , params,  prompt ) {
     let urls = [];
+
     for(let im of imgs)
         if(im != 'nsfw')
             urls.push( await temp_upload_img(im))
@@ -160,12 +161,169 @@ async function share_on_arthub(imgs , params,  prompt ) {
     share_url += "description="+ prompt + "&";
     if(!params.model_version)
         params.model_version = ""
-    params.model_version = "DiffusionBee" + params.model_version  ;
+    params.model_version = "DiffusionBee" + params.model_version + (params.Model? "_"+params.Model : "") ;
     share_url += "params="+ JSON.stringify(params) + "&"
     share_url += "images="+ urls.join(',')
     window.ipcRenderer.sendSync('open_url', share_url );
 }
 
 
+function form_params_to_readable_dict(form_params){
+
+    let r = {};
+    let vals = {"seed" : "Seed" , "guidence_scale" : "Scale" , "num_steps":"Steps"  ,  "steps":"Steps"  ,  "guidance_scale": "Guidance Scale",
+          "inp_img_strength" : "Image Strength" , "input_image_strength": "Image Strength"  , "img_width":"Img Width" , "img_height": "Img Height" , 
+           "negative_prompt" : "Negative Prompt" , "model_version":"model_version", "scheduler":"Sampler" , 
+           "selected_sd_model" : "Model", "controlnet_model" : "ControlNet" , "applet_name" : "Mode", 
+           "small_mod_seed":"Small Modification Seed", "controlnet": "controlnet" , "controlnet_preprocess":"controlnet_preprocess" , "control_weight":"ControlNet Importance" , "is_clip_skip_2": "Clip Skip 2"}
+
+    for(let k in vals)
+        if( form_params[k])
+            r[vals[k]] =  form_params[k];
+
+    return r;
+   
+}
+
+
+// convert the dict from the output of a form to readable text
+function form_params_to_text(form_params){
+    let t = ""
+   let r = form_params_to_readable_dict(form_params)
+    for(let k in r)
+            t += " " +k  +  " : " + r[k] + " |";
+    if(t.charAt(t.length - 1) == "|")
+        t = t.slice(0, -1);
+    return t;
+
+}
+
+function find_in_form_recursive(id , form_elements){
+    for(let el of form_elements ){
+        if(el.id == id){
+            return el 
+        }
+
+        if(el.children){
+            let ans =  find_in_form_recursive(id , el.children)
+            if(ans)
+                return ans
+        }
+    }
+    return undefined
+}
+
+
+function migrate_history_only_once( current_new_history ){
+
+    let v =  window.ipcRenderer.sendSync('load_data', 'migration_data.json');
+    if(v.is_history_migrated){
+        console.log("already migrated hisro")
+         return {};
+    }
+
+
+    let app_data_v1 =  window.ipcRenderer.sendSync('load_data', 'data.json');
+    let new_history = {}
+
+    //todo make sure it only runs once 
+
+    if(app_data_v1.history){
+        let old_hisotry = app_data_v1.history
+        console.log(old_hisotry)
+        for(let k in old_hisotry){
+
+            // let a = 2
+            // if(a > 1)
+            //     continue
+
+            if(current_new_history[k])
+                continue
+
+    
+
+            let new_item = {}
+            let old_item = old_hisotry[k]
+            let old_aux_img_url = undefined
+            if(old_item.controlnet && old_item.controlnet_preprocess == "Yes" ){
+                // remove first image 
+                old_aux_img_url = old_item.imgs.shift();
+            }
+
+            new_item.group_id = k;
+            new_item.img_height = old_item.img_h;
+            new_item.img_width = old_item.img_w;
+            new_item.key = k;
+            new_item.num_imgs = old_item.imgs.length;
+            new_item.prompt = old_item.prompt;
+            new_item.params = {}
+            new_item.params.applet_name = "txt2img"
+
+            if(old_item.inp_img && !(old_item.controlnet) ){
+                new_item.params.applet_name = "img2img"
+                new_item.params.input_image_strength = old_item.inp_img_strength
+                new_item.params.input_image_with_mask = old_item.inp_img
+                new_item.params.input_img = old_item.inp_img
+            }
+
+            new_item.params.num_imgs = 1
+            if(old_item.dif_steps)  
+                new_item.params.num_steps = old_item.dif_steps
+            new_item.params.img_height =  old_item.img_h;
+            new_item.params.img_width =  old_item.img_w;
+            new_item.params.is_adv_mode = true 
+            new_item.params.job_state = "done"
+            if( old_item.selected_sampler)
+                new_item.params.scheduler = old_item.selected_sampler
+            
+            new_item.params.guidance_scale = old_item.guidence_scale 
+            new_item.params.controlnet_model = old_item.controlnet
+            if(old_item.controlnet){
+                new_item.params.controlnet_input_image_path = old_item.inp_img
+
+            }
+            if(old_item.controlnet_preprocess == "Yes"){
+                new_item.do_controlnet_preprocess = true
+            }
+
+            new_item.params.prompt = new_item.prompt
+
+            new_item.params.seed = old_item.seed 
+            new_item.params.selected_sd_model = old_item.model_version
+            
+            new_item.params.raw_form_options = JSON.parse(JSON.stringify(new_item.params))
+
+            new_item.imgs = []
+            for(let i=0; i< new_item.num_imgs ; i++ ){
+                let img_item = {}
+                img_item.description = new_item.prompt
+                img_item.done_percentage = -1 
+                img_item.image_url = old_item.imgs[i]
+                img_item.params = JSON.parse(JSON.stringify(new_item.params))
+
+                if(old_item.controlnet){
+                    img_item.aux_img_url = old_aux_img_url
+                }
+
+                img_item.params.seed += 1234*i 
+                img_item.params.raw_form_options = JSON.parse(JSON.stringify(img_item.params))
+                new_item.imgs.push(img_item)
+            }
+
+            // add_to_history(k ,new_item  )
+            console.log("migrated item")
+            console.log(new_item)
+            new_history[k] = new_item
+        }
+    }
+
+    
+    v.is_history_migrated = true;
+    window.ipcRenderer.sendSync('save_data', v , "migration_data.json");
+
+
+    return new_history;
+}
+
 
-export { compute_n_cols , compute_time_remaining , resolve_asset_illustration , simple_hash , open_popup, share_on_arthub}
\ No newline at end of file
+export { compute_n_cols , compute_time_remaining , resolve_asset_illustration , simple_hash , open_popup, share_on_arthub, form_params_to_text, find_in_form_recursive, form_params_to_readable_dict, migrate_history_only_once}
\ No newline at end of file
diff --git a/electron_app/src/utils/controlnet_frontend_utils.js b/electron_app/src/utils/controlnet_frontend_utils.js
new file mode 100644
index 00000000..56b2ece7
--- /dev/null
+++ b/electron_app/src/utils/controlnet_frontend_utils.js
@@ -0,0 +1,184 @@
+
+
+function controlnet_required_assets(self , to_download){
+    if( self.sd_options.controlnet_model && self.sd_options.controlnet_model == "Depth" ){
+        to_download.push( {
+            "id": "just_control_sd15_depth_fp16",
+            "filename": "just_control_sd15_depth_fp16.tdict",
+            "md5": "652bb2d467e37ba8253b7361973c82b6",
+            "url": "https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/just_control_sd15_depth_fp16.tdict",
+            "title": "ControlNet Depth",
+            is_stock_model : true,
+            "description": "ControlNet Depth. Works with MiDaS depth.",
+            model_meta_data : {"type" : "controlnet_model" , "sd_type" : "SD_1x", "float_type" : "float16" }
+        })
+
+        if( self.sd_options.do_controlnet_preprocess == true || self.sd_options.do_controlnet_preprocess == "Yes" ){
+            to_download.push( {
+                "id": "midas_monodepth",
+                "filename": "midas_monodepth.onnx",
+                "md5": "3ad9d8a9d820214d2bfe65c0d37683a7",
+                is_stock_model : true,
+                "url": "https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/midas_monodepth.onnx",
+                "title": "MiDaS Depth Extractor",
+                "description": "MiDaS Depth Extractor, for processing ControlNet input.",
+                model_meta_data : {"type" : "controlnet_preprocess_model"   }
+            })
+        }
+    }
+
+    if( self.sd_options.controlnet_model && self.sd_options.controlnet_model == "BodyPose" ){
+        to_download.push( {
+            "id": "just_control_sd15_openpose_fp16",
+            "filename": "just_control_sd15_openpose_fp16.tdict",
+            "md5": "81077e9fe3472ed2242a7a3d8035b6eb",
+            "url": "https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/just_control_sd15_openpose_fp16.tdict",
+            "title": "ControlNet Body",
+            is_stock_model : true,
+            "description": "ControlNet Body model. Works with OpenPose poses.",
+            model_meta_data : {"type" : "controlnet_model" , "sd_type" : "SD_1x", "float_type" : "float16" }
+        })
+
+        if(  self.sd_options.do_controlnet_preprocess == true || self.sd_options.do_controlnet_preprocess == "Yes" ){
+            to_download.push( {
+                "id": "body_pose_model",
+                "filename": "body_pose_model.onnx",
+                "md5": "51499a50aff296971a99605f32c7e8e7",
+                is_stock_model : true,
+                "url": "https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/body_pose_model.onnx",
+                "title": "OpenPose Extractor",
+                "description": "OpenPose Extractor, for processing ControlNet input.",
+                model_meta_data : {"type" : "controlnet_preprocess_model"   }
+            })
+        }
+
+        
+    }
+
+    if( self.sd_options.controlnet_model && self.sd_options.controlnet_model == "LineArt" ){
+        to_download.push( {
+            "id": "just_control_v11p_sd15_lineart",
+            "filename": "just_control_v11p_sd15_lineart.tdict",
+            "md5": "5917957e792a5b4399714bf44240034d",
+            "url": "https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/just_control_v11p_sd15_lineart.tdict",
+            "title": "ControlNet LineArt",
+            is_stock_model : true,
+            "description": "ControlNet LineArt model. ",
+            model_meta_data : {"type" : "controlnet_model" , "sd_type" : "SD_1x", "float_type" : "float16" }
+        })
+
+        if(  self.sd_options.do_controlnet_preprocess == true || self.sd_options.do_controlnet_preprocess == "Yes" ){
+            to_download.push( {
+                "id": "lineart_model",
+                "filename": "lineart_model.onnx",
+                "md5": "667d0d7cad9449f3a6db135b526f2279",
+                is_stock_model : true,
+                "url": "https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/linart.onnx",
+                "title": "LineArt Extractor",
+                "description": "LineArt Extractor, for processing ControlNet input.",
+                model_meta_data : {"type" : "controlnet_preprocess_model"   }
+            })
+        }
+    }
+
+
+    if( self.sd_options.controlnet_model && self.sd_options.controlnet_model == "Scribble" ){
+        to_download.push( {
+            "id": "just_control_sd15_scribble_fp16",
+            "filename": "just_control_sd15_scribble_fp16.tdict",
+            "md5": "2d29e2d006035919180e2f8b6decc40a",
+            is_stock_model : true,
+            "url": "https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/just_control_sd15_scribble_fp16.tdict",
+            "title": "ControlNet Scribble",
+            "description": "ControlNet Scribble model.",
+            model_meta_data : {"type" : "controlnet_model" , "sd_type" : "SD_1x", "float_type" : "float16" }
+        })
+    }
+
+    
+
+    if( self.sd_options.controlnet_model && self.sd_options.controlnet_model == "Tile" ){
+        to_download.push( {
+            "id": "just_control_v11f1e_sd15_tile_fp16",
+            "filename": "just_control_v11f1e_sd15_tile_fp16.tdict",
+            "md5": "7f3eb2dbb810ec1a643e2ec31cc2892e",
+            is_stock_model : true,
+            "url": "https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/just_control_v11f1e_sd15_tile_fp16.tdict",
+            "title": "ControlNet Tile",
+            "description": "ControlNet Tile model.",
+            model_meta_data : {"type" : "controlnet_model" , "sd_type" : "SD_1x", "float_type" : "float16" }
+        })
+    }
+
+
+
+    if( self.sd_options.controlnet_model && self.sd_options.controlnet_model == "Inpaint" ){
+        to_download.push( {
+            "id": "just_control_v11p_sd15_inpaint_fp16",
+            "filename": "just_control_v11p_sd15_inpaint_fp16.tdict",
+            "md5": "3ad9d8a9d820214d2bfe65c0d37683a7",
+            is_stock_model : true,
+            "url": "https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/just_control_v11p_sd15_inpaint_fp16.tdict",
+            "title": "ControlNet Inpaint",
+            "description": "ControlNet Inpaint model.",
+            model_meta_data : {"type" : "controlnet_model" , "sd_type" : "SD_1x", "float_type" : "float16" }
+        })
+        
+    }
+
+
+
+
+
+
+}
+
+function controlnet_proc_form_outputs(self , options){
+    if(options.controlnet_model && options.controlnet_model == "Depth" ){
+        options.controlnet_tdict_path = self.app.assets_manager.get_downloaded_asset_path("just_control_sd15_depth_fp16")
+
+        if(options.do_controlnet_preprocess)
+            options.controlnet_inp_img_preprocesser_model_path = self.app.assets_manager.get_downloaded_asset_path("midas_monodepth")
+
+    }
+
+    if(options.controlnet_model && options.controlnet_model == "BodyPose" ){
+        options.controlnet_tdict_path = self.app.assets_manager.get_downloaded_asset_path("just_control_sd15_openpose_fp16")
+
+        if(options.do_controlnet_preprocess)
+            options.controlnet_inp_img_preprocesser_model_path = self.app.assets_manager.get_downloaded_asset_path("body_pose_model")
+    }
+
+    if(options.controlnet_model && options.controlnet_model == "LineArt" ){
+        options.controlnet_tdict_path = self.app.assets_manager.get_downloaded_asset_path("just_control_v11p_sd15_lineart")
+
+        if(options.do_controlnet_preprocess)
+            options.controlnet_inp_img_preprocesser_model_path = self.app.assets_manager.get_downloaded_asset_path("lineart_model")
+    }
+
+
+    if(options.controlnet_model && options.controlnet_model == "Scribble" ){
+        options.controlnet_tdict_path = self.app.assets_manager.get_downloaded_asset_path("just_control_sd15_scribble_fp16")
+    }
+
+    if(options.controlnet_model && options.controlnet_model == "Tile" ){
+        options.controlnet_tdict_path = self.app.assets_manager.get_downloaded_asset_path("just_control_v11f1e_sd15_tile_fp16")
+    }
+
+}
+
+function controlnet_check_inputs(self , vue){
+    
+    if(self.sd_options.controlnet_model && self.sd_options.controlnet_model != "None" ){
+        if((!self.sd_options.controlnet_input_image_path) || self.sd_options.controlnet_input_image_path == ""){
+            vue.$toast.default("You have selected a ControlNet model but not specified an image.")
+             return false;
+        }
+        
+    } 
+
+    return true
+}
+
+
+export { controlnet_check_inputs , controlnet_proc_form_outputs , controlnet_required_assets }
\ No newline at end of file
diff --git a/electron_app/src/utils/in_out_paint_utils.js b/electron_app/src/utils/in_out_paint_utils.js
new file mode 100644
index 00000000..a5c7cba4
--- /dev/null
+++ b/electron_app/src/utils/in_out_paint_utils.js
@@ -0,0 +1,90 @@
+
+
+function inpaint_assets(self , mode ){
+    let to_download = []
+    if((!self.sd_options.selected_sd_model) || self.sd_options.selected_sd_model == "SD1.5_Inpainting"){
+        to_download.push( { 
+            id : "SD1.5_Inpainting", 
+            filename: 'sd-v1-5-inpainting_fp16.tdict' ,   
+            md5: '68303f49cca00968c39abddc20b622a6' , 
+            is_stock_model : true,
+            url : 'https://huggingface.co/divamgupta/stable_diffusion_mps/resolve/main/sd-v1-5-inpainting_fp16.tdict' , 
+            title: "SD 1.5 Inpainting by RunwayML", 
+            model_meta_data : {"type" : "sd_model_inpaint", "float_type" : "float16" ,  "sd_type" : "SD_1x_inpaint" }
+        } )
+    }
+
+    // in generative fill, if a non inpaintgin model selected then it needs the contorlnet inpaint
+    if(mode == "Generative Fill"){
+        if((!self.sd_options.selected_sd_model) || self.sd_options.selected_sd_model == "Default_SD1.5" || 
+            (self.app.assets_manager.all_avail_assets[self.sd_options.selected_sd_model] && (self.app.assets_manager.all_avail_assets[self.sd_options.selected_sd_model].model_meta_data||{}).type == "sd_model" )){
+
+            to_download.push( {
+                "id": "just_control_v11p_sd15_inpaint_fp16",
+                "filename": "just_control_v11p_sd15_inpaint_fp16.tdict",
+                "md5": "08a0a43ff75a4a4941fbb885c50d7874",
+                is_stock_model : true,
+                "url": "https://huggingface.co/divamgupta/controlnet_tensorflow/resolve/main/just_control_v11p_sd15_inpaint_fp16.tdict",
+                "title": "ControlNet Inpaint",
+                "description": "ControlNet Inpaint model.",
+                model_meta_data : {"type" : "controlnet_model" , "sd_type" : "SD_1x", "float_type" : "float16" }
+            })
+        }
+    }
+
+    return to_download;
+}
+
+function prep_sd_optins(self , sd_options_object, mode , img_mask_url){
+    if(!sd_options_object.num_imgs)
+        sd_options_object.num_imgs = 1
+
+    if( mode == "Text To Image") {
+        sd_options_object.sd_mode_override = "txt2img"
+    } else {
+
+        if(mode == "Generative Fill"){
+        
+            let is_control_inpaint = false 
+            
+        
+            if((self.app.assets_manager.all_avail_assets[self.sd_options.selected_sd_model].model_meta_data||{}).type == "sd_model" ){
+                is_control_inpaint = true
+                
+            }   
+
+            if(is_control_inpaint){
+                sd_options_object.do_masking_diffusion = true
+                sd_options_object.controlnet_model ="Inpaint"
+                sd_options_object.controlnet_inp_img_preprocesser="Inpaint"
+                sd_options_object.controlnet_input_image_path="NULL"
+                sd_options_object.is_control_net=true
+                sd_options_object.controlnet_guess_mode=true
+                sd_options_object.guidance_scale = ( (sd_options_object.guidance_scale || 7.5) - 3.5 )
+                if(sd_options_object.guidance_scale <= 1)
+                    sd_options_object.guidance_scale = 1
+                sd_options_object.sd_mode_override = "txt2img"
+                sd_options_object.controlnet_tdict_path= self.app.assets_manager.get_downloaded_asset_path("just_control_v11p_sd15_inpaint_fp16")
+
+            } else {
+                // SD1.5 inpaint
+                sd_options_object.is_sd15_inpaint = true
+                sd_options_object.sd_mode_override = "txt2img"
+            }
+        } else {
+            // Image to Image case
+            sd_options_object.infill_alpha = true
+        }
+
+        sd_options_object.get_mask_from_image_alpha = true;
+
+        if(self.sd_options.inp_only_update_masked){
+            sd_options_object.blur_mask = true
+            sd_options_object.do_masking_diffusion = true
+            
+        }
+        sd_options_object.mask_image_path = img_mask_url
+    }
+}
+
+export { prep_sd_optins ,  inpaint_assets }
\ No newline at end of file
diff --git a/electron_app/vue.config.js b/electron_app/vue.config.js
index 15ffc8d5..b0eb97a1 100644
--- a/electron_app/vue.config.js
+++ b/electron_app/vue.config.js
@@ -1,4 +1,3 @@
-
 try {
     var build_config = require('./build_config.json');
     console.log(build_config + "\n\n\n\n\n")
@@ -18,6 +17,7 @@ module.exports = {
             builderOptions: {
                 appId: 'com.diffusionbee.diffusionbee',
                 artifactName: "DiffusionBee"+(build_config.build_name||"")+"-${version}.${ext}",
+
                 afterSign: "./afterSignHook.js",
                 "extraResources": [{
                     "from": process.env.BACKEND_BUILD_PATH , 
@@ -32,9 +32,9 @@ module.exports = {
                     "hardenedRuntime": true,
                     "entitlements": "build/entitlements.mac.plist",
                     "entitlementsInherit": "build/entitlements.mac.plist",
-                    "minimumSystemVersion": build_config.min_os_version || "11.0.0",
+                    "minimumSystemVersion": build_config.min_os_version || "12.6.0",
                     "extendInfo": {
-                        "LSMinimumSystemVersion": build_config.min_os_version || "11.0.0"
+                        "LSMinimumSystemVersion": build_config.min_os_version || "12.6.0"
                     } , 
                     
                     "target": {
diff --git a/package-lock.json b/package-lock.json
new file mode 100644
index 00000000..468f0dfc
--- /dev/null
+++ b/package-lock.json
@@ -0,0 +1,6 @@
+{
+  "name": "diffusion_bee_public",
+  "lockfileVersion": 2,
+  "requires": true,
+  "packages": {}
+}