Merge branch 'release_candidate'

update readme for release
add a possible fix for 'LatentDiffusion' object has no attribute 'lora_layer_mapping'
2023-05-14 13:35:07 +03:00 · 2023-05-14 13:34:50 +03:00 · 2023-05-14 13:31:03 +03:00 · 2023-05-13 20:47:32 +03:00 · 2023-05-13 20:46:50 +03:00 · 2023-05-13 20:25:03 +03:00
73 changed files with 927 additions and 451 deletions
@@ -1,3 +1,61 @@
+## 1.2.1
+
+### Features:
+ * add an option to always refer to lora by filenames
+
+### Bug Fixes:
+ * never refer to lora by an alias if multiple loras have same alias or the alias is called none
+ * fix upscalers disappearing after the user reloads UI
+ * allow bf16 in safe unpickler (resolves problems with loading some loras)
+ * allow web UI to be ran fully offline
+ * fix localizations not working
+ * fix error for loras: 'LatentDiffusion' object has no attribute 'lora_layer_mapping'
+
+## 1.2.0
+
+### Features:
+ * do not wait for stable diffusion model to load at startup
+ * add filename patterns: [denoising]
+ * directory hiding for extra networks: dirs starting with . will hide their cards on extra network tabs unless specifically searched for
+ * Lora: for the `<...>` text in prompt, use name of Lora that is in the metdata of the file, if present, instead of filename (both can be used to activate lora)
+ * Lora: read infotext params from kohya-ss's extension parameters if they are present and if his extension is not active
+ * Lora: Fix some Loras not working (ones that have 3x3 convolution layer)
+ * Lora: add an option to use old method of applying loras (producing same results as with kohya-ss)
+ * add version to infotext, footer and console output when starting
+ * add links to wiki for filename pattern settings
+ * add extended info for quicksettings setting and use multiselect input instead of a text field
+
+### Minor:
+ * gradio bumped to 3.29.0
+ * torch bumped to 2.0.1
+ * --subpath option for gradio for use with reverse proxy
+ * linux/OSX: use existing virtualenv if already active (the VIRTUAL_ENV environment variable)
+ * possible frontend optimization: do not apply localizations if there are none
+ * Add extra `None` option for VAE in XYZ plot
+ * print error to console when batch processing in img2img fails
+ * create HTML for extra network pages only on demand
+ * allow directories starting with . to still list their models for lora, checkpoints, etc
+ * put infotext options into their own category in settings tab
+ * do not show licenses page when user selects Show all pages in settings
+
+### Extensions:
+ * Tooltip localization support
+ * Add api method to get LoRA models with prompt
+
+### Bug Fixes:
+ * re-add /docs endpoint
+ * fix gamepad navigation
+ * make the lightbox fullscreen image function properly
+ * fix squished thumbnails in extras tab
+ * keep "search" filter for extra networks when user refreshes the tab (previously it showed everthing after you refreshed)
+ * fix webui showing the same image if you configure the generation to always save results into same file
+ * fix bug with upscalers not working properly
+ * Fix MPS on PyTorch 2.0.1, Intel Macs
+ * make it so that custom context menu from contextMenu.js only disappears after user's click, ignoring non-user click events
+ * prevent Reload UI button/link from reloading the page when it's not yet ready
+ * fix prompts from file script failing to read contents from a drag/drop file
+
+
 ## 1.1.1
 ### Bug Fixes:
 * fix an error that prevents running webui on torch<2.0 without --disable-safe-unpickle
@@ -1,6 +1,7 @@
 from modules import extra_networks, shared
 import lora

+
 class ExtraNetworkLora(extra_networks.ExtraNetwork):
    def __init__(self):
        super().__init__('lora')
@@ -4,7 +4,7 @@ import re
 import torch
 from typing import Union

-from modules import shared, devices, sd_models, errors
+from modules import shared, devices, sd_models, errors, scripts

 metadata_tags_order = {"ss_sd_model_name": 1, "ss_resolution": 2, "ss_clip_skip": 3, "ss_num_train_images": 10, "ss_tag_frequency": 20}

@@ -93,6 +93,7 @@ class LoraOnDisk:
            self.metadata = m

        self.ssmd_cover_images = self.metadata.pop('ssmd_cover_images', None)  # those are cover images and they are too big to display in UI as text
+        self.alias = self.metadata.get('ss_output_name', self.name)


 class LoraModule:
@@ -132,6 +133,10 @@ def load_lora(name, filename):

    sd = sd_models.read_state_dict(filename)

+    # this should not be needed but is here as an emergency fix for an unknown error people are experiencing in 1.2.0
+    if not hasattr(shared.sd_model, 'lora_layer_mapping'):
+        assign_lora_names_to_compvis_modules(shared.sd_model)
+
    keys_failed_to_match = {}
    is_sd2 = 'model_transformer_resblocks' in shared.sd_model.lora_layer_mapping

@@ -165,8 +170,10 @@ def load_lora(name, filename):
            module = torch.nn.Linear(weight.shape[1], weight.shape[0], bias=False)
        elif type(sd_module) == torch.nn.MultiheadAttention:
            module = torch.nn.Linear(weight.shape[1], weight.shape[0], bias=False)
-        elif type(sd_module) == torch.nn.Conv2d:
+        elif type(sd_module) == torch.nn.Conv2d and weight.shape[2:] == (1, 1):
            module = torch.nn.Conv2d(weight.shape[1], weight.shape[0], (1, 1), bias=False)
+        elif type(sd_module) == torch.nn.Conv2d and weight.shape[2:] == (3, 3):
+            module = torch.nn.Conv2d(weight.shape[1], weight.shape[0], (3, 3), bias=False)
        else:
            print(f'Lora layer {key_diffusers} matched a layer with unsupported type: {type(sd_module).__name__}')
            continue
@@ -199,11 +206,11 @@ def load_loras(names, multipliers=None):

    loaded_loras.clear()

-    loras_on_disk = [available_loras.get(name, None) for name in names]
+    loras_on_disk = [available_lora_aliases.get(name, None) for name in names]
    if any([x is None for x in loras_on_disk]):
        list_available_loras()

-        loras_on_disk = [available_loras.get(name, None) for name in names]
+        loras_on_disk = [available_lora_aliases.get(name, None) for name in names]

    for i, name in enumerate(names):
        lora = already_loaded.get(name, None)
@@ -232,6 +239,8 @@ def lora_calc_updown(lora, module, target):

        if up.shape[2:] == (1, 1) and down.shape[2:] == (1, 1):
            updown = (up.squeeze(2).squeeze(2) @ down.squeeze(2).squeeze(2)).unsqueeze(2).unsqueeze(3)
+        elif up.shape[2:] == (3, 3) or down.shape[2:] == (3, 3):
+            updown = torch.nn.functional.conv2d(down.permute(1, 0, 2, 3), up).permute(1, 0, 2, 3)
        else:
            updown = up @ down

@@ -240,6 +249,19 @@ def lora_calc_updown(lora, module, target):
        return updown


+def lora_restore_weights_from_backup(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn.MultiheadAttention]):
+    weights_backup = getattr(self, "lora_weights_backup", None)
+
+    if weights_backup is None:
+        return
+
+    if isinstance(self, torch.nn.MultiheadAttention):
+        self.in_proj_weight.copy_(weights_backup[0])
+        self.out_proj.weight.copy_(weights_backup[1])
+    else:
+        self.weight.copy_(weights_backup)
+
+
 def lora_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn.MultiheadAttention]):
    """
    Applies the currently selected set of Loras to the weights of torch layer self.
@@ -264,12 +286,7 @@ def lora_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn.Mu
        self.lora_weights_backup = weights_backup

    if current_names != wanted_names:
-        if weights_backup is not None:
-            if isinstance(self, torch.nn.MultiheadAttention):
-                self.in_proj_weight.copy_(weights_backup[0])
-                self.out_proj.weight.copy_(weights_backup[1])
-            else:
-                self.weight.copy_(weights_backup)
+        lora_restore_weights_from_backup(self)

        for lora in loaded_loras:
            module = lora.modules.get(lora_layer_name, None)
@@ -300,12 +317,45 @@ def lora_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn.Mu
        setattr(self, "lora_current_names", wanted_names)


+def lora_forward(module, input, original_forward):
+    """
+    Old way of applying Lora by executing operations during layer's forward.
+    Stacking many loras this way results in big performance degradation.
+    """
+
+    if len(loaded_loras) == 0:
+        return original_forward(module, input)
+
+    input = devices.cond_cast_unet(input)
+
+    lora_restore_weights_from_backup(module)
+    lora_reset_cached_weight(module)
+
+    res = original_forward(module, input)
+
+    lora_layer_name = getattr(module, 'lora_layer_name', None)
+    for lora in loaded_loras:
+        module = lora.modules.get(lora_layer_name, None)
+        if module is None:
+            continue
+
+        module.up.to(device=devices.device)
+        module.down.to(device=devices.device)
+
+        res = res + module.up(module.down(input)) * lora.multiplier * (module.alpha / module.up.weight.shape[1] if module.alpha else 1.0)
+
+    return res
+
+
 def lora_reset_cached_weight(self: Union[torch.nn.Conv2d, torch.nn.Linear]):
    setattr(self, "lora_current_names", ())
    setattr(self, "lora_weights_backup", None)


 def lora_Linear_forward(self, input):
+    if shared.opts.lora_functional:
+        return lora_forward(self, input, torch.nn.Linear_forward_before_lora)
+
    lora_apply_weights(self)

    return torch.nn.Linear_forward_before_lora(self, input)
@@ -318,6 +368,9 @@ def lora_Linear_load_state_dict(self, *args, **kwargs):


 def lora_Conv2d_forward(self, input):
+    if shared.opts.lora_functional:
+        return lora_forward(self, input, torch.nn.Conv2d_forward_before_lora)
+
    lora_apply_weights(self)

    return torch.nn.Conv2d_forward_before_lora(self, input)
@@ -343,24 +396,65 @@ def lora_MultiheadAttention_load_state_dict(self, *args, **kwargs):

 def list_available_loras():
    available_loras.clear()
+    available_lora_aliases.clear()
+    forbidden_lora_aliases.clear()
+    forbidden_lora_aliases.update({"none": 1})

    os.makedirs(shared.cmd_opts.lora_dir, exist_ok=True)

-    candidates = \
-        glob.glob(os.path.join(shared.cmd_opts.lora_dir, '**/*.pt'), recursive=True) + \
-        glob.glob(os.path.join(shared.cmd_opts.lora_dir, '**/*.safetensors'), recursive=True) + \
-        glob.glob(os.path.join(shared.cmd_opts.lora_dir, '**/*.ckpt'), recursive=True)
-
+    candidates = list(shared.walk_files(shared.cmd_opts.lora_dir, allowed_extensions=[".pt", ".ckpt", ".safetensors"]))
    for filename in sorted(candidates, key=str.lower):
        if os.path.isdir(filename):
            continue

        name = os.path.splitext(os.path.basename(filename))[0]
+        entry = LoraOnDisk(name, filename)

-        available_loras[name] = LoraOnDisk(name, filename)
+        available_loras[name] = entry

+        if entry.alias in available_lora_aliases:
+            forbidden_lora_aliases[entry.alias.lower()] = 1
+
+        available_lora_aliases[name] = entry
+        available_lora_aliases[entry.alias] = entry
+
+
+re_lora_name = re.compile(r"(.*)\s*\([0-9a-fA-F]+\)")
+
+
+def infotext_pasted(infotext, params):
+    if "AddNet Module 1" in [x[1] for x in scripts.scripts_txt2img.infotext_fields]:
+        return  # if the other extension is active, it will handle those fields, no need to do anything
+
+    added = []
+
+    for k, v in params.items():
+        if not k.startswith("AddNet Model "):
+            continue
+
+        num = k[13:]
+
+        if params.get("AddNet Module " + num) != "LoRA":
+            continue
+
+        name = params.get("AddNet Model " + num)
+        if name is None:
+            continue
+
+        m = re_lora_name.match(name)
+        if m:
+            name = m.group(1)
+
+        multiplier = params.get("AddNet Weight A " + num, "1.0")
+
+        added.append(f"<lora:{name}:{multiplier}>")
+
+    if added:
+        params["Prompt"] += "\n" + "".join(added)

 available_loras = {}
+available_lora_aliases = {}
+forbidden_lora_aliases = {}
 loaded_loras = []

 list_available_loras()
@@ -1,12 +1,12 @@
 import torch
 import gradio as gr
+from fastapi import FastAPI

 import lora
 import extra_networks_lora
 import ui_extra_networks_lora
 from modules import script_callbacks, ui_extra_networks, extra_networks, shared

-
 def unload():
    torch.nn.Linear.forward = torch.nn.Linear_forward_before_lora
    torch.nn.Linear._load_from_state_dict = torch.nn.Linear_load_state_dict_before_lora
@@ -49,8 +49,34 @@ torch.nn.MultiheadAttention._load_from_state_dict = lora.lora_MultiheadAttention
 script_callbacks.on_model_loaded(lora.assign_lora_names_to_compvis_modules)
 script_callbacks.on_script_unloaded(unload)
 script_callbacks.on_before_ui(before_ui)
+script_callbacks.on_infotext_pasted(lora.infotext_pasted)


 shared.options_templates.update(shared.options_section(('extra_networks', "Extra Networks"), {
    "sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in lora.available_loras]}, refresh=lora.list_available_loras),
+    "lora_preferred_name": shared.OptionInfo("Alias from file", "When adding to prompt, refer to lora by", gr.Radio, {"choices": ["Alias from file", "Filename"]}),
 }))
+
+
+shared.options_templates.update(shared.options_section(('compatibility', "Compatibility"), {
+    "lora_functional": shared.OptionInfo(False, "Lora: use old method that takes longer when you have multiple Loras active and produces same results as kohya-ss/sd-webui-additional-networks extension"),
+}))
+
+
+def create_lora_json(obj: lora.LoraOnDisk):
+    return {
+        "name": obj.name,
+        "alias": obj.alias,
+        "path": obj.filename,
+        "metadata": obj.metadata,
+    }
+
+
+def api_loras(_: gr.Blocks, app: FastAPI):
+    @app.get("/sdapi/v1/loras")
+    async def get_loras():
+        return [create_lora_json(obj) for obj in lora.available_loras.values()]
+
+
+script_callbacks.on_app_started(api_loras)
+
@@ -15,13 +15,19 @@ class ExtraNetworksPageLora(ui_extra_networks.ExtraNetworksPage):
    def list_items(self):
        for name, lora_on_disk in lora.available_loras.items():
            path, ext = os.path.splitext(lora_on_disk.filename)
+
+            if shared.opts.lora_preferred_name == "Filename" or lora_on_disk.alias.lower() in lora.forbidden_lora_aliases:
+                alias = name
+            else:
+                alias = lora_on_disk.alias
+
            yield {
                "name": name,
                "filename": path,
                "preview": self.find_preview(path),
                "description": self.find_description(path),
                "search_term": self.search_terms_from_path(lora_on_disk.filename),
-                "prompt": json.dumps(f"<lora:{name}:") + " + opts.extra_networks_default_multiplier + " + json.dumps(">"),
+                "prompt": json.dumps(f"<lora:{alias}:") + " + opts.extra_networks_default_multiplier + " + json.dumps(">"),
                "local_preview": f"{path}.{shared.opts.samples_format}",
                "metadata": json.dumps(lora_on_disk.metadata, indent=4) if lora_on_disk.metadata else None,
            }
@@ -6,7 +6,7 @@
 			<ul>
 				<a href="#" title="replace preview image with currently selected in gallery" onclick={save_card_preview}>replace preview</a>
 			</ul>
-			<span style="display:none" class='search_term'>{search_term}</span>
+			<span style="display:none" class='search_term{serach_only}'>{search_term}</span>
 		</div>
 		<span class='name'>{name}</span>
 		<span class='description'>{description}</span>
@@ -45,29 +45,24 @@ function dimensionChange(e, is_width, is_height){

 		var viewportOffset = targetElement.getBoundingClientRect();

-		viewportscale = Math.min(  targetElement.clientWidth/targetElement.naturalWidth, targetElement.clientHeight/targetElement.naturalHeight )
+		var viewportscale = Math.min(  targetElement.clientWidth/targetElement.naturalWidth, targetElement.clientHeight/targetElement.naturalHeight )

-		scaledx = targetElement.naturalWidth*viewportscale
-		scaledy = targetElement.naturalHeight*viewportscale
+		var scaledx = targetElement.naturalWidth*viewportscale
+		var scaledy = targetElement.naturalHeight*viewportscale

-		cleintRectTop    = (viewportOffset.top+window.scrollY)
-		cleintRectLeft   = (viewportOffset.left+window.scrollX)
-		cleintRectCentreY = cleintRectTop  + (targetElement.clientHeight/2)
-		cleintRectCentreX = cleintRectLeft + (targetElement.clientWidth/2)
+		var cleintRectTop    = (viewportOffset.top+window.scrollY)
+		var cleintRectLeft   = (viewportOffset.left+window.scrollX)
+		var cleintRectCentreY = cleintRectTop  + (targetElement.clientHeight/2)
+		var cleintRectCentreX = cleintRectLeft + (targetElement.clientWidth/2)

-		viewRectTop    = cleintRectCentreY-(scaledy/2)
-		viewRectLeft   = cleintRectCentreX-(scaledx/2)
-		arRectWidth  = scaledx
-		arRectHeight = scaledy
+		var arscale = Math.min(  scaledx/currentWidth, scaledy/currentHeight )
+		var arscaledx = currentWidth*arscale
+		var arscaledy = currentHeight*arscale

-		arscale = Math.min(  arRectWidth/currentWidth, arRectHeight/currentHeight )
-		arscaledx = currentWidth*arscale
-		arscaledy = currentHeight*arscale
-
-		arRectTop    = cleintRectCentreY-(arscaledy/2)
-		arRectLeft   = cleintRectCentreX-(arscaledx/2)
-		arRectWidth  = arscaledx
-		arRectHeight = arscaledy
+		var arRectTop    = cleintRectCentreY-(arscaledy/2)
+		var arRectLeft   = cleintRectCentreX-(arscaledx/2)
+		var arRectWidth  = arscaledx
+		var arRectHeight = arscaledy

 	    arPreviewRect.style.top  = arRectTop+'px';
 	    arPreviewRect.style.left = arRectLeft+'px';
@@ -4,7 +4,7 @@ contextMenuInit = function(){
  let menuSpecs = new Map();

  const uid = function(){
-    return Date.now().toString(36) + Math.random().toString(36).substr(2);
+    return Date.now().toString(36) + Math.random().toString(36).substring(2);
  }

  function showContextMenu(event,element,menuEntries){
@@ -16,8 +16,7 @@ contextMenuInit = function(){
      oldMenu.remove()
    }

-    let tabButton = uiCurrentTab
-    let baseStyle = window.getComputedStyle(tabButton)
+    let baseStyle = window.getComputedStyle(uiCurrentTab)

    const contextMenu = document.createElement('nav')
    contextMenu.id = "context-menu"
@@ -36,7 +35,7 @@ contextMenuInit = function(){
    menuEntries.forEach(function(entry){
      let contextMenuEntry = document.createElement('a')
      contextMenuEntry.innerHTML = entry['name']
-      contextMenuEntry.addEventListener("click", function(e) {
+      contextMenuEntry.addEventListener("click", function() {
        entry['func']();
      })
      contextMenuList.append(contextMenuEntry);
@@ -63,7 +62,7 @@ contextMenuInit = function(){

  function appendContextMenuOption(targetElementSelector,entryName,entryFunction){

-    currentItems = menuSpecs.get(targetElementSelector)
+    var currentItems = menuSpecs.get(targetElementSelector)

    if(!currentItems){
      currentItems = []
@@ -79,7 +78,7 @@ contextMenuInit = function(){
  }

  function removeContextMenuOption(uid){
-    menuSpecs.forEach(function(v,k) {
+    menuSpecs.forEach(function(v) {
      let index = -1
      v.forEach(function(e,ei){if(e['id']==uid){index=ei}})
      if(index>=0){
@@ -93,8 +92,7 @@ contextMenuInit = function(){
      return;
    }
    gradioApp().addEventListener("click", function(e) {
-      let source = e.composedPath()[0]
-      if(source.id && source.id.indexOf('check_progress')>-1){
+      if(! e.isTrusted){
        return
      }

@@ -112,7 +110,6 @@ contextMenuInit = function(){
        if(e.composedPath()[0].matches(k)){
          showContextMenu(e,e.composedPath()[0],v)
          e.preventDefault()
-          return
        }
      })
    });
@@ -69,8 +69,8 @@ function keyupEditAttention(event){

 	event.preventDefault();

-    closeCharacter = ')'
-    delta = opts.keyedit_precision_attention
+    var closeCharacter = ')'
+    var delta = opts.keyedit_precision_attention

    if (selectionStart > 0 && text[selectionStart - 1] == '<'){
        closeCharacter = '>'
@@ -91,8 +91,8 @@ function keyupEditAttention(event){
        selectionEnd += 1;
    }

-	end = text.slice(selectionEnd + 1).indexOf(closeCharacter) + 1;
-	weight = parseFloat(text.slice(selectionEnd + 1, selectionEnd + 1 + end));
+	var end = text.slice(selectionEnd + 1).indexOf(closeCharacter) + 1;
+	var weight = parseFloat(text.slice(selectionEnd + 1, selectionEnd + 1 + end));
 	if (isNaN(weight)) return;

 	weight += isPlus ? delta : -delta;
@@ -1,14 +1,14 @@

-function extensions_apply(_, _, disable_all){
+function extensions_apply(_disabled_list, _update_list, disable_all){
    var disable = []
    var update = []

    gradioApp().querySelectorAll('#extensions input[type="checkbox"]').forEach(function(x){
        if(x.name.startsWith("enable_") && ! x.checked)
-            disable.push(x.name.substr(7))
+            disable.push(x.name.substring(7))

        if(x.name.startsWith("update_") && x.checked)
-            update.push(x.name.substr(7))
+            update.push(x.name.substring(7))
    })

    restart_reload()
@@ -16,12 +16,12 @@ function extensions_apply(_, _, disable_all){
    return [JSON.stringify(disable), JSON.stringify(update), disable_all]
 }

-function extensions_check(_, _){
+function extensions_check(){
    var disable = []

    gradioApp().querySelectorAll('#extensions input[type="checkbox"]').forEach(function(x){
        if(x.name.startsWith("enable_") && ! x.checked)
-            disable.push(x.name.substr(7))
+            disable.push(x.name.substring(7))
    })

    gradioApp().querySelectorAll('#extensions .extension_status').forEach(function(x){
@@ -41,7 +41,7 @@ function install_extension_from_index(button, url){
    button.disabled = "disabled"
    button.value = "Installing..."

-    textarea = gradioApp().querySelector('#extension_to_install textarea')
+    var textarea = gradioApp().querySelector('#extension_to_install textarea')
    textarea.value = url
    updateInput(textarea)

@@ -1,4 +1,3 @@
-
 function setupExtraNetworksForTab(tabname){
    gradioApp().querySelector('#'+tabname+'_extra_tabs').classList.add('extra-networks')

@@ -10,16 +9,34 @@ function setupExtraNetworksForTab(tabname){
    tabs.appendChild(search)
    tabs.appendChild(refresh)

-    search.addEventListener("input", function(evt){
-        searchTerm = search.value.toLowerCase()
+    var applyFilter = function(){
+        var searchTerm = search.value.toLowerCase()

        gradioApp().querySelectorAll('#'+tabname+'_extra_tabs div.card').forEach(function(elem){
-            text = elem.querySelector('.name').textContent.toLowerCase() + " " + elem.querySelector('.search_term').textContent.toLowerCase()
-            elem.style.display = text.indexOf(searchTerm) == -1 ? "none" : ""
+            var searchOnly = elem.querySelector('.search_only')
+            var text = elem.querySelector('.name').textContent.toLowerCase() + " " + elem.querySelector('.search_term').textContent.toLowerCase()
+
+            var visible = text.indexOf(searchTerm) != -1
+
+            if(searchOnly && searchTerm.length < 4){
+                visible = false
+            }
+
+            elem.style.display = visible ? "" : "none"
        })
-    });
+    }
+
+    search.addEventListener("input", applyFilter);
+    applyFilter();
+
+    extraNetworksApplyFilter[tabname] = applyFilter;
 }

+function applyExtraNetworkFilter(tabname){
+    setTimeout(extraNetworksApplyFilter[tabname], 1);
+}
+
+var extraNetworksApplyFilter = {}
 var activePromptTextarea = {};

 function setupExtraNetworks(){
@@ -55,7 +72,7 @@ function tryToRemoveExtraNetworkFromPrompt(textarea, text){

    var partToSearch = m[1]
    var replaced = false
-    var newTextareaText = textarea.value.replaceAll(re_extranet_g, function(found, index){
+    var newTextareaText = textarea.value.replaceAll(re_extranet_g, function(found){
        m = found.match(re_extranet);
        if(m[1] == partToSearch){
            replaced = true;
@@ -96,9 +113,9 @@ function saveCardPreview(event, tabname, filename){
 }

 function extraNetworksSearchButton(tabs_id, event){
-    searchTextarea = gradioApp().querySelector("#" + tabs_id + ' > div > textarea')
-    button = event.target
-    text = button.classList.contains("search-all") ? "" : button.textContent.trim()
+    var searchTextarea = gradioApp().querySelector("#" + tabs_id + ' > div > textarea')
+    var button = event.target
+    var text = button.classList.contains("search-all") ? "" : button.textContent.trim()

    searchTextarea.value = text
    updateInput(searchTextarea)
@@ -133,7 +150,7 @@ function popup(contents){
 }

 function extraNetworksShowMetadata(text){
-    elem = document.createElement('pre')
+    var elem = document.createElement('pre')
    elem.classList.add('popup-metadata');
    elem.textContent = text;

@@ -165,7 +182,7 @@ function requestGet(url, data, handler, errorHandler){
 }

 function extraNetworksRequestMetadata(event, extraPage, cardName){
-    showError = function(){ extraNetworksShowMetadata("there was an error getting metadata"); }
+    var showError = function(){ extraNetworksShowMetadata("there was an error getting metadata"); }

    requestGet("./sd_extra_networks/metadata", {"page": extraPage, "item": cardName}, function(data){
        if(data && data.metadata){
@@ -23,7 +23,7 @@ let modalObserver = new MutationObserver(function(mutations) {
 });

 function attachGalleryListeners(tab_name) {
-	gallery = gradioApp().querySelector('#'+tab_name+'_gallery')
+	var gallery = gradioApp().querySelector('#'+tab_name+'_gallery')
 	gallery?.addEventListener('click', () => gradioApp().getElementById(tab_name+"_generation_info_button").click());
 	gallery?.addEventListener('keydown', (e) => {
 		if (e.keyCode == 37 || e.keyCode == 39) // left or right arrow
@@ -66,8 +66,8 @@ titles = {

    "Interrogate": "Reconstruct prompt from existing image and put it into the prompt field.",

-    "Images filename pattern": "Use following tags to define how filenames for images are chosen: [steps], [cfg], [clip_skip], [batch_number], [generation_number], [prompt_hash], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [model_name], [prompt_words], [date], [datetime], [datetime<Format>], [datetime<Format><Time Zone>], [job_timestamp], [hasprompt<prompt1|default><prompt2>..]; leave empty for default.",
-    "Directory name pattern": "Use following tags to define how subdirectories for images and grids are chosen: [steps], [cfg], [clip_skip], [batch_number], [generation_number], [prompt_hash], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [model_name], [prompt_words], [date], [datetime], [datetime<Format>], [datetime<Format><Time Zone>], [job_timestamp], [hasprompt<prompt1|default><prompt2>..]; leave empty for default.",
+    "Images filename pattern": "Use following tags to define how filenames for images are chosen: [steps], [cfg], [denoising], [clip_skip], [batch_number], [generation_number], [prompt_hash], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [model_name], [prompt_words], [date], [datetime], [datetime<Format>], [datetime<Format><Time Zone>], [job_timestamp], [hasprompt<prompt1|default><prompt2>..]; leave empty for default.",
+    "Directory name pattern": "Use following tags to define how subdirectories for images and grids are chosen: [steps], [cfg], [denoising], [clip_skip], [batch_number], [generation_number], [prompt_hash], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [model_name], [prompt_words], [date], [datetime], [datetime<Format>], [datetime<Format><Time Zone>], [job_timestamp], [hasprompt<prompt1|default><prompt2>..]; leave empty for default.",
    "Max prompt words": "Set the maximum number of words to be used in the [prompt_words] option; ATTENTION: If the words are too long, they may exceed the maximum length of the file path that the system can handle",

    "Loopback": "Performs img2img processing multiple times. Output images are used as input for the next loop.",
@@ -118,16 +118,18 @@ titles = {

 onUiUpdate(function(){
 	gradioApp().querySelectorAll('span, button, select, p').forEach(function(span){
-		tooltip = titles[span.textContent];
+		if (span.title) return;  // already has a title

-		if(!tooltip){
-		    tooltip = titles[span.value];
+		let tooltip = localization[titles[span.textContent]] || titles[span.textContent];
+
+    if(!tooltip){
+		    tooltip = localization[titles[span.value]] || titles[span.value];
 		}

 		if(!tooltip){
 			for (const c of span.classList) {
 				if (c in titles) {
-					tooltip = titles[c];
+					tooltip = localization[titles[c]] || titles[c];
 					break;
 				}
 			}
@@ -142,7 +144,7 @@ onUiUpdate(function(){
 	    if (select.onchange != null) return;

 	    select.onchange = function(){
-            select.title = titles[select.value] || "";
+            select.title = localization[titles[select.value]] || titles[select.value] || "";
 	    }
 	})
 })
@@ -1,16 +1,12 @@

-function setInactive(elem, inactive){
-    if(inactive){
-        elem.classList.add('inactive')
-    } else{
-        elem.classList.remove('inactive')
-    }
-}
-
 function onCalcResolutionHires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y){
-    hrUpscaleBy = gradioApp().getElementById('txt2img_hr_scale')
-    hrResizeX = gradioApp().getElementById('txt2img_hr_resize_x')
-    hrResizeY = gradioApp().getElementById('txt2img_hr_resize_y')
+    function setInactive(elem, inactive){
+        elem.classList.toggle('inactive', !!inactive)
+    }
+
+    var hrUpscaleBy = gradioApp().getElementById('txt2img_hr_scale')
+    var hrResizeX = gradioApp().getElementById('txt2img_hr_resize_x')
+    var hrResizeY = gradioApp().getElementById('txt2img_hr_resize_y')

    gradioApp().getElementById('txt2img_hires_fix_row2').style.display = opts.use_old_hires_fix_width_height ? "none" : ""

@@ -2,11 +2,10 @@
 * temporary fix for https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/668
 * @see https://github.com/gradio-app/gradio/issues/1721
 */
-window.addEventListener( 'resize', () => imageMaskResize());
 function imageMaskResize() {
    const canvases = gradioApp().querySelectorAll('#img2maskimg .touch-none canvas');
    if ( ! canvases.length ) {
-    canvases_fixed = false;
+    canvases_fixed = false; // TODO: this is unused..?
    window.removeEventListener( 'resize', imageMaskResize );
    return;
    }
@@ -15,7 +14,7 @@ function imageMaskResize() {
    const previewImage = wrapper.previousElementSibling;

    if ( ! previewImage.complete ) {
-        previewImage.addEventListener( 'load', () => imageMaskResize());
+        previewImage.addEventListener( 'load', imageMaskResize);
        return;
    }

@@ -24,7 +23,6 @@ function imageMaskResize() {
    const nw = previewImage.naturalWidth;
    const nh = previewImage.naturalHeight;
    const portrait = nh > nw;
-    const factor = portrait;

    const wW = Math.min(w, portrait ? h/nh*nw : w/nw*nw);
    const wH = Math.min(h, portrait ? h/nh*nh : w/nw*nh);
@@ -40,6 +38,7 @@ function imageMaskResize() {
        c.style.maxHeight = '100%';
        c.style.objectFit = 'contain';
    });
- }
-  
- onUiUpdate(() => imageMaskResize());
+}
+
+onUiUpdate(imageMaskResize);
+window.addEventListener( 'resize', imageMaskResize);
@@ -1,7 +1,6 @@
 window.onload = (function(){
    window.addEventListener('drop', e => {
        const target = e.composedPath()[0];
-        const idx = selected_gallery_index();
        if (target.placeholder.indexOf("Prompt") == -1) return;

        let prompt_target = get_tab_index('tabs') == 1 ? "img2img_prompt_image" : "txt2img_prompt_image";
@@ -57,7 +57,7 @@ function modalImageSwitch(offset) {
        })

        if (result != -1) {
-            nextButton = galleryButtons[negmod((result + offset), galleryButtons.length)]
+            var nextButton = galleryButtons[negmod((result + offset), galleryButtons.length)]
            nextButton.click()
            const modalImage = gradioApp().getElementById("modalImage");
            const modal = gradioApp().getElementById("lightboxModal");
@@ -144,15 +144,11 @@ function setupImageForLightbox(e) {
 }

 function modalZoomSet(modalImage, enable) {
-    if (enable) {
-        modalImage.classList.add('modalImageFullscreen');
-    } else {
-        modalImage.classList.remove('modalImageFullscreen');
-    }
+    if(modalImage) modalImage.classList.toggle('modalImageFullscreen', !!enable);
 }

 function modalZoomToggle(event) {
-    modalImage = gradioApp().getElementById("modalImage");
+    var modalImage = gradioApp().getElementById("modalImage");
    modalZoomSet(modalImage, !modalImage.classList.contains('modalImageFullscreen'))
    event.stopPropagation()
 }
@@ -179,7 +175,7 @@ function galleryImageHandler(e) {
 }

 onUiUpdate(function() {
-    fullImg_preview = gradioApp().querySelectorAll('.gradio-gallery > div > img')
+    var fullImg_preview = gradioApp().querySelectorAll('.gradio-gallery > div > img')
    if (fullImg_preview != null) {
        fullImg_preview.forEach(setupImageForLightbox);
    }
@@ -1,36 +1,57 @@
-    let delay = 350//ms
-    window.addEventListener('gamepadconnected', (e) => {
-        console.log("Gamepad connected!")
-        const gamepad = e.gamepad;
-        setInterval(() => {
-            const xValue = gamepad.axes[0].toFixed(2);
-            if (xValue < -0.3) {
-                modalPrevImage(e);
-            } else if (xValue > 0.3) {
-                modalNextImage(e);
-            }
-
-        }, delay);
-    });
-
-
-    /*
-    Primarily for vr controller type pointer devices.
-    I use the wheel event because there's currently no way to do it properly with web xr.
-     */
-
-    let isScrolling = false;
-    window.addEventListener('wheel', (e) => {
-        if (isScrolling) return;
-        isScrolling = true;
-
-        if (e.deltaX <= -0.6) {
+window.addEventListener('gamepadconnected', (e) => {
+    const index = e.gamepad.index;
+    let isWaiting = false;
+    setInterval(async () => {
+        if (!opts.js_modal_lightbox_gamepad || isWaiting) return;
+        const gamepad = navigator.getGamepads()[index];
+        const xValue = gamepad.axes[0];
+        if (xValue <= -0.3) {
            modalPrevImage(e);
-        } else if (e.deltaX >= 0.6) {
+            isWaiting = true;
+        } else if (xValue >= 0.3) {
            modalNextImage(e);
+            isWaiting = true;
        }
+        if (isWaiting) {
+            await sleepUntil(() => {
+                const xValue = navigator.getGamepads()[index].axes[0]
+                if (xValue < 0.3 && xValue > -0.3) {
+                    return true;
+                }
+            }, opts.js_modal_lightbox_gamepad_repeat);
+            isWaiting = false;
+        }
+    }, 10);
+});

-        setTimeout(() => {
-            isScrolling = false;
-        }, delay);
-    });
+/*
+Primarily for vr controller type pointer devices.
+I use the wheel event because there's currently no way to do it properly with web xr.
+ */
+let isScrolling = false;
+window.addEventListener('wheel', (e) => {
+    if (!opts.js_modal_lightbox_gamepad || isScrolling) return;
+    isScrolling = true;
+
+    if (e.deltaX <= -0.6) {
+        modalPrevImage(e);
+    } else if (e.deltaX >= 0.6) {
+        modalNextImage(e);
+    }
+
+    setTimeout(() => {
+        isScrolling = false;
+    }, opts.js_modal_lightbox_gamepad_repeat);
+});
+
+function sleepUntil(f, timeout) {
+    return new Promise((resolve) => {
+        const timeStart = new Date();
+        const wait = setInterval(function() {
+            if (f() || new Date() - timeStart > timeout) {
+                clearInterval(wait);
+                resolve();
+            }
+        }, 20);
+    });
+}
@@ -25,6 +25,10 @@ re_emoji = /[\p{Extended_Pictographic}\u{1F3FB}-\u{1F3FF}\u{1F9B0}-\u{1F9B3}]/u
 original_lines = {}
 translated_lines = {}

+function hasLocalization() {
+    return window.localization && Object.keys(window.localization).length > 0;
+}
+
 function textNodesUnder(el){
    var n, a=[], walk=document.createTreeWalker(el,NodeFilter.SHOW_TEXT,null,false);
    while(n=walk.nextNode()) a.push(n);
@@ -35,11 +39,11 @@ function canBeTranslated(node, text){
    if(! text) return false;
    if(! node.parentElement) return false;

-    parentType = node.parentElement.nodeName
+    var parentType = node.parentElement.nodeName
    if(parentType=='SCRIPT' || parentType=='STYLE' || parentType=='TEXTAREA') return false;

    if (parentType=='OPTION' || parentType=='SPAN'){
-        pnode = node
+        var pnode = node
        for(var level=0; level<4; level++){
            pnode = pnode.parentElement
            if(! pnode) break;
@@ -69,7 +73,7 @@ function getTranslation(text){
 }

 function processTextNode(node){
-    text = node.textContent.trim()
+    var text = node.textContent.trim()

    if(! canBeTranslated(node, text)) return

@@ -105,30 +109,52 @@ function processNode(node){
 }

 function dumpTranslations(){
-    dumped = {}
+    if(!hasLocalization()) {
+        // If we don't have any localization,
+        // we will not have traversed the app to find
+        // original_lines, so do that now.
+        processNode(gradioApp());
+    }
+    var dumped = {}
    if (localization.rtl) {
-        dumped.rtl = true
+        dumped.rtl = true;
    }

-    Object.keys(original_lines).forEach(function(text){
-        if(dumped[text] !== undefined)  return
+    for (const text in original_lines) {
+        if(dumped[text] !== undefined) continue;
+        dumped[text] = localization[text] || text;
+    }

-        dumped[text] = localization[text] || text
-    })
-
-    return dumped
+    return dumped;
 }

-onUiUpdate(function(m){
-    m.forEach(function(mutation){
-        mutation.addedNodes.forEach(function(node){
-            processNode(node)
-        })
-    });
-})
+function download_localization() {
+    var text = JSON.stringify(dumpTranslations(), null, 4)

+    var element = document.createElement('a');
+    element.setAttribute('href', 'data:text/plain;charset=utf-8,' + encodeURIComponent(text));
+    element.setAttribute('download', "localization.json");
+    element.style.display = 'none';
+    document.body.appendChild(element);
+
+    element.click();
+
+    document.body.removeChild(element);
+}
+
+document.addEventListener("DOMContentLoaded", function () {
+    if (!hasLocalization()) {
+        return;
+    }
+
+    onUiUpdate(function (m) {
+        m.forEach(function (mutation) {
+            mutation.addedNodes.forEach(function (node) {
+                processNode(node)
+            })
+        });
+    })

-document.addEventListener("DOMContentLoaded", function() {
    processNode(gradioApp())

    if (localization.rtl) {  // if the language is from right to left,
@@ -149,17 +175,3 @@ document.addEventListener("DOMContentLoaded", function() {
        })).observe(gradioApp(), { childList: true });
    }
 })
-
-function download_localization() {
-    text = JSON.stringify(dumpTranslations(), null, 4)
-
-    var element = document.createElement('a');
-    element.setAttribute('href', 'data:text/plain;charset=utf-8,' + encodeURIComponent(text));
-    element.setAttribute('download', "localization.json");
-    element.style.display = 'none';
-    document.body.appendChild(element);
-
-    element.click();
-
-    document.body.removeChild(element);
-}
@@ -2,15 +2,15 @@

 let lastHeadImg = null;

-notificationButton = null
+let notificationButton = null;

 onUiUpdate(function(){
    if(notificationButton == null){
        notificationButton = gradioApp().getElementById('request_notifications')

        if(notificationButton != null){
-            notificationButton.addEventListener('click', function (evt) {
-                Notification.requestPermission();
+            notificationButton.addEventListener('click', () => {
+                void Notification.requestPermission();
            },true);
        }
    }
@@ -1,16 +1,15 @@
 // code related to showing and updating progressbar shown as the image is being made

-function rememberGallerySelection(id_gallery){
+function rememberGallerySelection(){

 }

-function getGallerySelectedIndex(id_gallery){
+function getGallerySelectedIndex(){

 }

 function request(url, data, handler, errorHandler){
    var xhr = new XMLHttpRequest();
-    var url = url;
    xhr.open("POST", url, true);
    xhr.setRequestHeader("Content-Type", "application/json");
    xhr.onreadystatechange = function () {
@@ -107,7 +106,7 @@ function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgre
                divProgress.style.width = rect.width + "px";
            }

-            progressText = ""
+            let progressText = ""

            divInner.style.width = ((res.progress || 0) * 100.0) + '%'
            divInner.style.background = res.progress ? "" : "transparent"
@@ -1,7 +1,7 @@
 // various functions for interaction with ui.py not large enough to warrant putting them in separate files

 function set_theme(theme){
-    gradioURL = window.location.href
+    var gradioURL = window.location.href
    if (!gradioURL.includes('?__theme=')) {
      window.location.replace(gradioURL + '?__theme=' + theme);
    }
@@ -47,7 +47,7 @@ function extract_image_from_gallery(gallery){
        return [gallery[0]];
    }

-    index = selected_gallery_index()
+    var index = selected_gallery_index()

    if (index < 0 || index >= gallery.length){
        // Use the first image in the gallery as the default
@@ -58,7 +58,7 @@ function extract_image_from_gallery(gallery){
 }

 function args_to_array(args){
-    res = []
+    var res = []
    for(var i=0;i<args.length;i++){
        res.push(args[i])
    }
@@ -138,7 +138,7 @@ function get_img2img_tab_index() {
 }

 function create_submit_args(args){
-    res = []
+    var res = []
    for(var i=0;i<args.length;i++){
        res.push(args[i])
    }
@@ -160,7 +160,7 @@ function showSubmitButtons(tabname, show){
 }

 function showRestoreProgressButton(tabname, show){
-    button = gradioApp().getElementById(tabname + "_restore_progress")
+    var button = gradioApp().getElementById(tabname + "_restore_progress")
    if(! button) return

    button.style.display = show ? "flex" : "none"
@@ -207,8 +207,9 @@ function submit_img2img(){
    return res
 }

-function restoreProgressTxt2img(x){
+function restoreProgressTxt2img(){
    showRestoreProgressButton("txt2img", false)
+    var id = localStorage.getItem("txt2img_task_id")

    id = localStorage.getItem("txt2img_task_id")

@@ -220,10 +221,11 @@ function restoreProgressTxt2img(x){

    return id
 }
-function restoreProgressImg2img(x){
-    showRestoreProgressButton("img2img", false)

-    id = localStorage.getItem("img2img_task_id")
+function restoreProgressImg2img(){
+    showRestoreProgressButton("img2img", false)
+    
+    var id = localStorage.getItem("img2img_task_id")

    if(id) {
        requestProgress(id, gradioApp().getElementById('img2img_gallery_container'), gradioApp().getElementById('img2img_gallery'), function(){
@@ -252,7 +254,7 @@ function modelmerger(){


 function ask_for_style_name(_, prompt_text, negative_prompt_text) {
-    name_ = prompt('Style name:')
+    var name_ = prompt('Style name:')
    return [name_, prompt_text, negative_prompt_text]
 }

@@ -287,11 +289,11 @@ function recalculate_prompts_img2img(){
 }


-opts = {}
+var opts = {}
 onUiUpdate(function(){
 	if(Object.keys(opts).length != 0) return;

-	json_elem = gradioApp().getElementById('settings_json')
+	var json_elem = gradioApp().getElementById('settings_json')
 	if(json_elem == null) return;

    var textarea = json_elem.querySelector('textarea')
@@ -340,12 +342,15 @@ onUiUpdate(function(){
    registerTextarea('img2img_prompt', 'img2img_token_counter', 'img2img_token_button')
    registerTextarea('img2img_neg_prompt', 'img2img_negative_token_counter', 'img2img_negative_token_button')

-    show_all_pages = gradioApp().getElementById('settings_show_all_pages')
-    settings_tabs = gradioApp().querySelector('#settings div')
+    var show_all_pages = gradioApp().getElementById('settings_show_all_pages')
+    var settings_tabs = gradioApp().querySelector('#settings div')
    if(show_all_pages && settings_tabs){
        settings_tabs.appendChild(show_all_pages)
        show_all_pages.onclick = function(){
            gradioApp().querySelectorAll('#settings > div').forEach(function(elem){
+                if(elem.id == "settings_tab_licenses")
+                    return;
+
                elem.style.display = "block";
            })
        }
@@ -353,9 +358,9 @@ onUiUpdate(function(){
 })

 onOptionsChanged(function(){
-    elem = gradioApp().getElementById('sd_checkpoint_hash')
-    sd_checkpoint_hash = opts.sd_checkpoint_hash || ""
-    shorthash = sd_checkpoint_hash.substr(0,10)
+    var elem = gradioApp().getElementById('sd_checkpoint_hash')
+    var sd_checkpoint_hash = opts.sd_checkpoint_hash || ""
+    var shorthash = sd_checkpoint_hash.substring(0,10)

 	if(elem && elem.textContent != shorthash){
 	    elem.textContent = shorthash
@@ -390,7 +395,16 @@ function update_token_counter(button_id) {

 function restart_reload(){
    document.body.innerHTML='<h1 style="font-family:monospace;margin-top:20%;color:lightgray;text-align:center;">Reloading...</h1>';
-    setTimeout(function(){location.reload()},2000)
+
+    var requestPing = function(){
+        requestGet("./internal/ping", {}, function(data){
+            location.reload();
+        }, function(){
+            setTimeout(requestPing, 500);
+        })
+    }
+
+    setTimeout(requestPing, 2000);

    return []
 }
@@ -0,0 +1,41 @@
+// various hints and extra info for the settings tab
+
+onUiLoaded(function(){
+    createLink = function(elem_id, text, href){
+        var a = document.createElement('A')
+        a.textContent = text
+        a.target = '_blank';
+
+        elem = gradioApp().querySelector('#'+elem_id)
+        elem.insertBefore(a, elem.querySelector('label'))
+
+        return a
+    }
+
+    createLink("setting_samples_filename_pattern", "[wiki] ").href = "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Images-Filename-Name-and-Subdirectory"
+    createLink("setting_directories_filename_pattern", "[wiki] ").href = "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Images-Filename-Name-and-Subdirectory"
+
+    createLink("setting_quicksettings_list", "[info] ").addEventListener("click", function(event){
+        requestGet("./internal/quicksettings-hint", {}, function(data){
+            var table = document.createElement('table')
+            table.className = 'settings-value-table'
+
+            data.forEach(function(obj){
+                var tr = document.createElement('tr')
+                var td = document.createElement('td')
+                td.textContent = obj.name
+                tr.appendChild(td)
+
+                var td = document.createElement('td')
+                td.textContent = obj.label
+                tr.appendChild(td)
+
+                table.appendChild(tr)
+            })
+
+            popup(table);
+        })
+    });
+})
+
+
@@ -19,6 +19,7 @@ python = sys.executable
 git = os.environ.get('GIT', "git")
 index_url = os.environ.get('INDEX_URL', "")
 stored_commit_hash = None
+stored_git_tag = None
 dir_repos = "repositories"

 if 'GRADIO_ANALYTICS_ENABLED' not in os.environ:
@@ -70,6 +71,20 @@ def commit_hash():
    return stored_commit_hash


+def git_tag():
+    global stored_git_tag
+
+    if stored_git_tag is not None:
+        return stored_git_tag
+
+    try:
+        stored_git_tag = run(f"{git} describe --tags").strip()
+    except Exception:
+        stored_git_tag = "<none>"
+
+    return stored_git_tag
+
+
 def run(command, desc=None, errdesc=None, custom_env=None, live=False):
    if desc is not None:
        print(desc)
@@ -222,7 +237,7 @@ def run_extensions_installers(settings_file):


 def prepare_environment():
-    torch_command = os.environ.get('TORCH_COMMAND', "pip install torch==2.0.0 torchvision==0.15.1 --extra-index-url https://download.pytorch.org/whl/cu118")
+    torch_command = os.environ.get('TORCH_COMMAND', "pip install torch==2.0.1 torchvision==0.15.2 --extra-index-url https://download.pytorch.org/whl/cu118")
    requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")

    xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.17')
@@ -246,8 +261,10 @@ def prepare_environment():
        check_python_version()

    commit = commit_hash()
+    tag = git_tag()

    print(f"Python {sys.version}")
+    print(f"Version: {tag}")
    print(f"Commit hash: {commit}")

    if args.reinstall_torch or not is_installed("torch") or not is_installed("torchvision"):
@@ -570,20 +570,20 @@ class Api:
            filename = create_embedding(**args) # create empty embedding
            sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() # reload embeddings so new one can be immediately used
            shared.state.end()
-            return CreateResponse(info = "create embedding filename: {filename}".format(filename = filename))
+            return CreateResponse(info=f"create embedding filename: {filename}")
        except AssertionError as e:
            shared.state.end()
-            return TrainResponse(info = "create embedding error: {error}".format(error = e))
+            return TrainResponse(info=f"create embedding error: {e}")

    def create_hypernetwork(self, args: dict):
        try:
            shared.state.begin()
            filename = create_hypernetwork(**args) # create empty embedding
            shared.state.end()
-            return CreateResponse(info = "create hypernetwork filename: {filename}".format(filename = filename))
+            return CreateResponse(info=f"create hypernetwork filename: {filename}")
        except AssertionError as e:
            shared.state.end()
-            return TrainResponse(info = "create hypernetwork error: {error}".format(error = e))
+            return TrainResponse(info=f"create hypernetwork error: {e}")

    def preprocess(self, args: dict):
        try:
@@ -593,13 +593,13 @@ class Api:
            return PreprocessResponse(info = 'preprocess complete')
        except KeyError as e:
            shared.state.end()
-            return PreprocessResponse(info = "preprocess error: invalid token: {error}".format(error = e))
+            return PreprocessResponse(info=f"preprocess error: invalid token: {e}")
        except AssertionError as e:
            shared.state.end()
-            return PreprocessResponse(info = "preprocess error: {error}".format(error = e))
+            return PreprocessResponse(info=f"preprocess error: {e}")
        except FileNotFoundError as e:
            shared.state.end()
-            return PreprocessResponse(info = 'preprocess error: {error}'.format(error = e))
+            return PreprocessResponse(info=f'preprocess error: {e}')

    def train_embedding(self, args: dict):
        try:
@@ -617,10 +617,10 @@ class Api:
                if not apply_optimizations:
                    sd_hijack.apply_optimizations()
                shared.state.end()
-            return TrainResponse(info = "train embedding complete: filename: {filename} error: {error}".format(filename = filename, error = error))
+            return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
        except AssertionError as msg:
            shared.state.end()
-            return TrainResponse(info = "train embedding error: {msg}".format(msg = msg))
+            return TrainResponse(info=f"train embedding error: {msg}")

    def train_hypernetwork(self, args: dict):
        try:
@@ -641,10 +641,10 @@ class Api:
                if not apply_optimizations:
                    sd_hijack.apply_optimizations()
                shared.state.end()
-            return TrainResponse(info="train embedding complete: filename: {filename} error: {error}".format(filename=filename, error=error))
+            return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
        except AssertionError as msg:
            shared.state.end()
-            return TrainResponse(info="train embedding error: {error}".format(error=error))
+            return TrainResponse(info=f"train embedding error: {error}")

    def get_memory(self):
        try:
@@ -60,7 +60,7 @@ def wrap_gradio_call(func, extra_outputs=None, add_stats=False):
            max_debug_str_len = 131072 # (1024*1024)/8

            print("Error completing request", file=sys.stderr)
-            argStr = f"Arguments: {str(args)} {str(kwargs)}"
+            argStr = f"Arguments: {args} {kwargs}"
            print(argStr[:max_debug_str_len], file=sys.stderr)
            if len(argStr) > max_debug_str_len:
                print(f"(Argument list truncated at {max_debug_str_len}/{len(argStr)} characters)", file=sys.stderr)
@@ -73,7 +73,8 @@ def wrap_gradio_call(func, extra_outputs=None, add_stats=False):
            if extra_outputs_array is None:
                extra_outputs_array = [None, '']

-            res = extra_outputs_array + [f"<div class='error'>{html.escape(type(e).__name__+': '+str(e))}</div>"]
+            error_message = f'{type(e).__name__}: {e}'
+            res = extra_outputs_array + [f"<div class='error'>{html.escape(error_message)}</div>"]

        shared.state.skipped = False
        shared.state.interrupted = False
@@ -102,3 +102,4 @@ parser.add_argument("--no-gradio-queue", action='store_true', help="Disables gra
 parser.add_argument("--skip-version-check", action='store_true', help="Do not check versions of torch and xformers")
 parser.add_argument("--no-hashing", action='store_true', help="disable sha256 hashing of checkpoints to help loading performance", default=False)
 parser.add_argument("--no-download-sd-model", action='store_true', help="don't download SD1.5 model even if no model is found in --ckpt-dir", default=False)
+parser.add_argument('--subpath', type=str, help='customize the subpath for gradio, use with reverse proxy')
@@ -156,13 +156,16 @@ class UpscalerESRGAN(Upscaler):

    def load_model(self, path: str):
        if "http" in path:
-            filename = load_file_from_url(url=self.model_url, model_dir=self.model_path,
-                                          file_name="%s.pth" % self.model_name,
-                                          progress=True)
+            filename = load_file_from_url(
+                url=self.model_url,
+                model_dir=self.model_path,
+                file_name=f"{self.model_name}.pth",
+                progress=True,
+            )
        else:
            filename = path
        if not os.path.exists(filename) or filename is None:
-            print("Unable to load %s from %s" % (self.model_path, filename))
+            print(f"Unable to load {self.model_path} from {filename}")
            return None

        state_dict = torch.load(filename, map_location='cpu' if devices.device_esrgan.type == 'mps' else None)
@@ -38,7 +38,7 @@ class RRDBNet(nn.Module):
        elif upsample_mode == 'pixelshuffle':
            upsample_block = pixelshuffle_block
        else:
-            raise NotImplementedError('upsample mode [{:s}] is not found'.format(upsample_mode))
+            raise NotImplementedError(f'upsample mode [{upsample_mode}] is not found')
        if upscale == 3:
            upsampler = upsample_block(nf, nf, 3, act_type=act_type, convtype=convtype)
        else:
@@ -261,10 +261,10 @@ class Upsample(nn.Module):

    def extra_repr(self):
        if self.scale_factor is not None:
-            info = 'scale_factor=' + str(self.scale_factor)
+            info = f'scale_factor={self.scale_factor}'
        else:
-            info = 'size=' + str(self.size)
-        info += ', mode=' + self.mode
+            info = f'size={self.size}'
+        info += f', mode={self.mode}'
        return info


@@ -350,7 +350,7 @@ def act(act_type, inplace=True, neg_slope=0.2, n_prelu=1, beta=1.0):
    elif act_type == 'sigmoid':  # [0, 1] range output
        layer = nn.Sigmoid()
    else:
-        raise NotImplementedError('activation layer [{:s}] is not found'.format(act_type))
+        raise NotImplementedError(f'activation layer [{act_type}] is not found')
    return layer


@@ -372,7 +372,7 @@ def norm(norm_type, nc):
    elif norm_type == 'none':
        def norm_layer(x): return Identity()
    else:
-        raise NotImplementedError('normalization layer [{:s}] is not found'.format(norm_type))
+        raise NotImplementedError(f'normalization layer [{norm_type}] is not found')
    return layer


@@ -388,7 +388,7 @@ def pad(pad_type, padding):
    elif pad_type == 'zero':
        layer = nn.ZeroPad2d(padding)
    else:
-        raise NotImplementedError('padding layer [{:s}] is not implemented'.format(pad_type))
+        raise NotImplementedError(f'padding layer [{pad_type}] is not implemented')
    return layer


@@ -432,7 +432,7 @@ def conv_block(in_nc, out_nc, kernel_size, stride=1, dilation=1, groups=1, bias=
               pad_type='zero', norm_type=None, act_type='relu', mode='CNA', convtype='Conv2D',
               spectral_norm=False):
    """ Conv layer with padding, normalization, activation """
-    assert mode in ['CNA', 'NAC', 'CNAC'], 'Wrong conv mode [{:s}]'.format(mode)
+    assert mode in ['CNA', 'NAC', 'CNAC'], f'Wrong conv mode [{mode}]'
    padding = get_valid_padding(kernel_size, dilation)
    p = pad(pad_type, padding) if pad_type and pad_type != 'zero' else None
    padding = padding if pad_type == 'zero' else 0
@@ -10,7 +10,8 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork):
        additional = shared.opts.sd_hypernetwork

        if additional != "None" and additional in shared.hypernetworks and len([x for x in params_list if x.items[0] == additional]) == 0:
-            p.all_prompts = [x + f"<hypernet:{additional}:{shared.opts.extra_networks_default_multiplier}>" for x in p.all_prompts]
+            hypernet_prompt_text = f"<hypernet:{additional}:{shared.opts.extra_networks_default_multiplier}>"
+            p.all_prompts = [f"{prompt}{hypernet_prompt_text}" for prompt in p.all_prompts]
            params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier]))

        names = []
@@ -59,6 +59,7 @@ def image_from_url_text(filedata):
        is_in_right_dir = ui_tempdir.check_tmp_file(shared.demo, filename)
        assert is_in_right_dir, 'trying to open image file outside of allowed directories'

+        filename = filename.rsplit('?', 1)[0]
        return Image.open(filename)

    if type(filedata) == list:
@@ -129,6 +130,7 @@ def connect_paste_params_buttons():
                _js=jsfunc,
                inputs=[binding.source_image_component],
                outputs=[destination_image_component, destination_width_component, destination_height_component] if destination_width_component else [destination_image_component],
+                show_progress=False,
            )

        if binding.source_text_component is not None and fields is not None:
@@ -140,6 +142,7 @@ def connect_paste_params_buttons():
                fn=lambda *x: x,
                inputs=[field for field, name in paste_fields[binding.source_tabname]["fields"] if name in paste_field_names],
                outputs=[field for field, name in fields if name in paste_field_names],
+                show_progress=False,
            )

        binding.paste_button.click(
@@ -147,6 +150,7 @@ def connect_paste_params_buttons():
            _js=f"switch_to_{binding.tabname}",
            inputs=None,
            outputs=None,
+            show_progress=False,
        )


@@ -265,8 +269,8 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
        v = v[1:-1] if v[0] == '"' and v[-1] == '"' else v
        m = re_imagesize.match(v)
        if m is not None:
-            res[k+"-1"] = m.group(1)
-            res[k+"-2"] = m.group(2)
+            res[f"{k}-1"] = m.group(1)
+            res[f"{k}-2"] = m.group(2)
        else:
            res[k] = v

@@ -409,12 +413,14 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component,
        fn=paste_func,
        inputs=[input_comp],
        outputs=[x[0] for x in paste_fields],
+        show_progress=False,
    )
    button.click(
        fn=None,
        _js=f"recalculate_prompts_{tabname}",
        inputs=[],
        outputs=[],
+        show_progress=False,
    )


@@ -13,7 +13,7 @@ cache_data = None


 def dump_cache():
-    with filelock.FileLock(cache_filename+".lock"):
+    with filelock.FileLock(f"{cache_filename}.lock"):
        with open(cache_filename, "w", encoding="utf8") as file:
            json.dump(cache_data, file, indent=4)

@@ -22,7 +22,7 @@ def cache(subsection):
    global cache_data

    if cache_data is None:
-        with filelock.FileLock(cache_filename+".lock"):
+        with filelock.FileLock(f"{cache_filename}.lock"):
            if not os.path.isfile(cache_filename):
                cache_data = {}
            else:
@@ -357,6 +357,7 @@ class FilenameGenerator:
        'generation_number': lambda self: NOTHING_AND_SKIP_PREVIOUS_TEXT if self.p.n_iter == 1 and self.p.batch_size == 1 else self.p.iteration * self.p.batch_size + self.p.batch_index + 1,
        'hasprompt': lambda self, *args: self.hasprompt(*args),  # accepts formats:[hasprompt<prompt1|default><prompt2>..]
        'clip_skip': lambda self: opts.data["CLIP_stop_at_last_layers"],
+        'denoising': lambda self: self.p.denoising_strength if self.p and self.p.denoising_strength else NOTHING_AND_SKIP_PREVIOUS_TEXT,
    }
    default_time_format = '%Y%m%d%H%M%S'

@@ -466,7 +467,7 @@ def get_next_sequence_number(path, basename):
    """
    result = -1
    if basename != '':
-        basename = basename + "-"
+        basename = f"{basename}-"

    prefix_length = len(basename)
    for p in os.listdir(path):
@@ -535,7 +536,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
        add_number = opts.save_images_add_number or file_decoration == ''

        if file_decoration != "" and add_number:
-            file_decoration = "-" + file_decoration
+            file_decoration = f"-{file_decoration}"

        file_decoration = namegen.apply(file_decoration) + suffix

@@ -565,7 +566,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i

    def _atomically_save_image(image_to_save, filename_without_extension, extension):
        # save image with .tmp extension to avoid race condition when another process detects new image in the directory
-        temp_file_path = filename_without_extension + ".tmp"
+        temp_file_path = f"{filename_without_extension}.tmp"
        image_format = Image.registered_extensions()[extension]

        if extension.lower() == '.png':
@@ -625,7 +626,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
    if opts.save_txt and info is not None:
        txt_fullfn = f"{fullfn_without_extension}.txt"
        with open(txt_fullfn, "w", encoding="utf8") as file:
-            file.write(info + "\n")
+            file.write(f"{info}\n")
    else:
        txt_fullfn = None

@@ -48,7 +48,8 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):

        try:
            img = Image.open(image)
-        except UnidentifiedImageError:
+        except UnidentifiedImageError as e:
+            print(e)
            continue
        # Use the EXIF orientation of photos taken by smartphones.
        img = ImageOps.exif_transpose(img)
@@ -28,7 +28,7 @@ def category_types():
 def download_default_clip_interrogate_categories(content_dir):
    print("Downloading CLIP categories...")

-    tmpdir = content_dir + "_tmp"
+    tmpdir = f"{content_dir}_tmp"
    category_types = ["artists", "flavors", "mediums", "movements"]

    try:
@@ -214,7 +214,7 @@ class InterrogateModels:
                        if shared.opts.interrogate_return_ranks:
                            res += f", ({match}:{score/100:.3f})"
                        else:
-                            res += ", " + match
+                            res += f", {match}"

        except Exception:
            print("Error interrogating", file=sys.stderr)
@@ -23,7 +23,7 @@ def list_localizations(dirname):
        localizations[fn] = file.path


-def localization_js(current_localization_name):
+def localization_js(current_localization_name: str) -> str:
    fn = localizations.get(current_localization_name, None)
    data = {}
    if fn is not None:
@@ -34,4 +34,4 @@ def localization_js(current_localization_name):
            print(f"Error loading localization from {fn}:", file=sys.stderr)
            print(traceback.format_exc(), file=sys.stderr)

-    return f"var localization = {json.dumps(data)}\n"
+    return f"window.localization = {json.dumps(data)}"
@@ -54,6 +54,11 @@ if has_mps:
        CondFunc('torch.cumsum', cumsum_fix_func, None)
        CondFunc('torch.Tensor.cumsum', cumsum_fix_func, None)
        CondFunc('torch.narrow', lambda orig_func, *args, **kwargs: orig_func(*args, **kwargs).clone(), None)
-    if version.parse(torch.__version__) == version.parse("2.0"):
+
        # MPS workaround for https://github.com/pytorch/pytorch/issues/96113
-        CondFunc('torch.nn.functional.layer_norm', lambda orig_func, x, normalized_shape, weight, bias, eps, **kwargs: orig_func(x.float(), normalized_shape, weight.float() if weight is not None else None, bias.float() if bias is not None else bias, eps).to(x.dtype), lambda *args, **kwargs: len(args) == 6)
+        CondFunc('torch.nn.functional.layer_norm', lambda orig_func, x, normalized_shape, weight, bias, eps, **kwargs: orig_func(x.float(), normalized_shape, weight.float() if weight is not None else None, bias.float() if bias is not None else bias, eps).to(x.dtype), lambda _, input, *args, **kwargs: len(args) == 4 and input.device.type == 'mps')
+
+        # MPS workaround for https://github.com/pytorch/pytorch/issues/92311
+        if platform.processor() == 'i386':
+            for funcName in ['torch.argmax', 'torch.Tensor.argmax']:
+                CondFunc(funcName, lambda _, input, *args, **kwargs: torch.max(input.float() if input.dtype == torch.int64 else input, *args, **kwargs)[1], lambda _, input, *args, **kwargs: input.device.type == 'mps')
@@ -22,9 +22,6 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None
    """
    output = []

-    if ext_filter is None:
-        ext_filter = []
-
    try:
        places = []

@@ -39,22 +36,14 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None
        places.append(model_path)

        for place in places:
-            if os.path.exists(place):
-                for file in glob.iglob(place + '**/**', recursive=True):
-                    full_path = file
-                    if os.path.isdir(full_path):
-                        continue
-                    if os.path.islink(full_path) and not os.path.exists(full_path):
-                        print(f"Skipping broken symlink: {full_path}")
-                        continue
-                    if ext_blacklist is not None and any([full_path.endswith(x) for x in ext_blacklist]):
-                        continue
-                    if len(ext_filter) != 0:
-                        model_name, extension = os.path.splitext(file)
-                        if extension not in ext_filter:
-                            continue
-                    if file not in output:
-                        output.append(full_path)
+            for full_path in shared.walk_files(place, allowed_extensions=ext_filter):
+                if os.path.islink(full_path) and not os.path.exists(full_path):
+                    print(f"Skipping broken symlink: {full_path}")
+                    continue
+                if ext_blacklist is not None and any([full_path.endswith(x) for x in ext_blacklist]):
+                    continue
+                if full_path not in output:
+                    output.append(full_path)

        if model_url is not None and len(output) == 0:
            if download_name is not None:
@@ -128,23 +117,6 @@ def move_files(src_path: str, dest_path: str, ext_filter: str = None):
        pass


-builtin_upscaler_classes = []
-forbidden_upscaler_classes = set()
-
-
-def list_builtin_upscalers():
-    load_upscalers()
-
-    builtin_upscaler_classes.clear()
-    builtin_upscaler_classes.extend(Upscaler.__subclasses__())
-
-
-def forbid_loaded_nonbuiltin_upscalers():
-    for cls in Upscaler.__subclasses__():
-        if cls not in builtin_upscaler_classes:
-            forbidden_upscaler_classes.add(cls)
-
-
 def load_upscalers():
    # We can only do this 'magic' method to dynamically load upscalers if they are referenced,
    # so we'll try to import any _model.py files before looking in __subclasses__
@@ -160,10 +132,17 @@ def load_upscalers():

    datas = []
    commandline_options = vars(shared.cmd_opts)
-    for cls in Upscaler.__subclasses__():
-        if cls in forbidden_upscaler_classes:
-            continue

+    # some of upscaler classes will not go away after reloading their modules, and we'll end
+    # up with two copies of those classes. The newest copy will always be the last in the list,
+    # so we go from end to beginning and ignore duplicates
+    used_classes = {}
+    for cls in reversed(Upscaler.__subclasses__()):
+        classname = str(cls)
+        if classname not in used_classes:
+            used_classes[classname] = cls
+
+    for cls in reversed(used_classes.values()):
        name = cls.__name__
        cmd_name = f"{name.lower().replace('upscaler', '')}_models_path"
        scaler = cls(commandline_options.get(cmd_name, None))
@@ -223,7 +223,7 @@ class DDPM(pl.LightningModule):
        for k in keys:
            for ik in ignore_keys:
                if k.startswith(ik):
-                    print("Deleting key {} from state_dict.".format(k))
+                    print(f"Deleting key {k} from state_dict.")
                    del sd[k]
        missing, unexpected = self.load_state_dict(sd, strict=False) if not only_model else self.model.load_state_dict(
            sd, strict=False)
@@ -386,7 +386,7 @@ class DDPM(pl.LightningModule):
        _, loss_dict_no_ema = self.shared_step(batch)
        with self.ema_scope():
            _, loss_dict_ema = self.shared_step(batch)
-            loss_dict_ema = {key + '_ema': loss_dict_ema[key] for key in loss_dict_ema}
+            loss_dict_ema = {f"{key}_ema": loss_dict_ema[key] for key in loss_dict_ema}
        self.log_dict(loss_dict_no_ema, prog_bar=False, logger=True, on_step=False, on_epoch=True)
        self.log_dict(loss_dict_ema, prog_bar=False, logger=True, on_step=False, on_epoch=True)

@@ -94,7 +94,7 @@ class NoiseScheduleVP:
        """

        if schedule not in ['discrete', 'linear', 'cosine']:
-            raise ValueError("Unsupported noise schedule {}. The schedule needs to be 'discrete' or 'linear' or 'cosine'".format(schedule))
+            raise ValueError(f"Unsupported noise schedule {schedule}. The schedule needs to be 'discrete' or 'linear' or 'cosine'")

        self.schedule = schedule
        if schedule == 'discrete':
@@ -469,7 +469,7 @@ class UniPC:
            t = torch.linspace(t_T**(1. / t_order), t_0**(1. / t_order), N + 1).pow(t_order).to(device)
            return t
        else:
-            raise ValueError("Unsupported skip_type {}, need to be 'logSNR' or 'time_uniform' or 'time_quadratic'".format(skip_type))
+            raise ValueError(f"Unsupported skip_type {skip_type}, need to be 'logSNR' or 'time_uniform' or 'time_quadratic'")

    def get_orders_and_timesteps_for_singlestep_solver(self, steps, order, skip_type, t_T, t_0, device):
        """
@@ -7,8 +7,8 @@ def connect(token, port, region):
    else:
        if ':' in token:
            # token = authtoken:username:password
-            account = token.split(':')[1] + ':' + token.split(':')[-1]
-            token = token.split(':')[0]
+            token, username, password = token.split(':', 2)
+            account = f"{username}:{password}"

    config = conf.PyngrokConfig(
        auth_token=token, region=region
@@ -16,7 +16,7 @@ for possible_sd_path in possible_sd_paths:
        sd_path = os.path.abspath(possible_sd_path)
        break

-assert sd_path is not None, "Couldn't find Stable Diffusion in any of: " + str(possible_sd_paths)
+assert sd_path is not None, f"Couldn't find Stable Diffusion in any of: {possible_sd_paths}"

 path_dirs = [
    (sd_path, 'ldm', 'Stable Diffusion', []),
@@ -458,6 +458,16 @@ def fix_seed(p):
    p.subseed = get_fixed_seed(p.subseed)


+def program_version():
+    import launch
+
+    res = launch.git_tag()
+    if res == "<none>":
+        res = None
+
+    return res
+
+
 def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0):
    index = position_in_batch + iteration * p.batch_size

@@ -483,13 +493,14 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
        "Init image hash": getattr(p, 'init_img_hash', None),
        "RNG": opts.randn_source if opts.randn_source != "GPU" else None,
        "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond,
+        "Version": program_version() if opts.add_version_to_infotext else None,
    }

    generation_params.update(p.extra_generation_params)

    generation_params_text = ", ".join([k if k == v else f'{k}: {generation_parameters_copypaste.quote(v)}' for k, v in generation_params.items() if v is not None])

-    negative_prompt_text = "\nNegative prompt: " + p.all_negative_prompts[index] if p.all_negative_prompts[index] else ""
+    negative_prompt_text = f"\nNegative prompt: {p.all_negative_prompts[index]}" if p.all_negative_prompts[index] else ""

    return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip()

@@ -769,7 +780,16 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:

    devices.torch_gc()

-    res = Processed(p, output_images, p.all_seeds[0], infotext(), comments="".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], index_of_first_image=index_of_first_image, infotexts=infotexts)
+    res = Processed(
+        p,
+        images_list=output_images,
+        seed=p.all_seeds[0],
+        info=infotext(),
+        comments="".join(f"\n\n{comment}" for comment in comments),
+        subseed=p.all_subseeds[0],
+        index_of_first_image=index_of_first_image,
+        infotexts=infotexts,
+    )

    if p.scripts is not None:
        p.scripts.postprocess(p, res)
@@ -96,7 +96,8 @@ def progressapi(req: ProgressRequest):
        if image is not None:
            buffered = io.BytesIO()
            image.save(buffered, format="png")
-            live_preview = 'data:image/png;base64,' + base64.b64encode(buffered.getvalue()).decode("ascii")
+            base64_image = base64.b64encode(buffered.getvalue()).decode('ascii')
+            live_preview = f"data:image/png;base64,{base64_image}"
            id_live_preview = shared.state.id_live_preview
        else:
            live_preview = None
@@ -28,9 +28,9 @@ class UpscalerRealESRGAN(Upscaler):
            for scaler in scalers:
                if scaler.local_data_path.startswith("http"):
                    filename = modelloader.friendly_name(scaler.local_data_path)
-                    local = next(iter([local_model for local_model in local_model_paths if local_model.endswith(filename + '.pth')]), None)
-                    if local:
-                        scaler.local_data_path = local
+                    local_model_candidates = [local_model for local_model in local_model_paths if local_model.endswith(f"{filename}.pth")]
+                    if local_model_candidates:
+                        scaler.local_data_path = local_model_candidates[0]

                if scaler.name in opts.realesrgan_enabled_models:
                    self.scalers.append(scaler)
@@ -47,7 +47,7 @@ class UpscalerRealESRGAN(Upscaler):

        info = self.load_model(path)
        if not os.path.exists(info.local_data_path):
-            print("Unable to load RealESRGAN model: %s" % info.name)
+            print(f"Unable to load RealESRGAN model: {info.name}")
            return img

        upsampler = RealESRGANer(
@@ -40,7 +40,7 @@ class RestrictedUnpickler(pickle.Unpickler):
            return getattr(collections, name)
        if module == 'torch._utils' and name in ['_rebuild_tensor_v2', '_rebuild_parameter', '_rebuild_device_tensor_from_numpy']:
            return getattr(torch._utils, name)
-        if module == 'torch' and name in ['FloatStorage', 'HalfStorage', 'IntStorage', 'LongStorage', 'DoubleStorage', 'ByteStorage', 'float32']:
+        if module == 'torch' and name in ['FloatStorage', 'HalfStorage', 'IntStorage', 'LongStorage', 'DoubleStorage', 'ByteStorage', 'float32', 'BFloat16Storage']:
            return getattr(torch, name)
        if module == 'torch.nn.modules.container' and name in ['ParameterDict']:
            return getattr(torch.nn.modules.container, name)
@@ -163,7 +163,8 @@ class Script:
        """helper function to generate id for a HTML element, constructs final id out of script name, tab and user-supplied item_id"""

        need_tabname = self.show(True) == self.show(False)
-        tabname = ('img2img' if self.is_img2img else 'txt2txt') + "_" if need_tabname else ""
+        tabkind = 'img2img' if self.is_img2img else 'txt2txt'
+        tabname = f"{tabkind}_" if need_tabname else ""
        title = re.sub(r'[^a-z_0-9]', '', re.sub(r'\s', '_', self.title().lower()))

        return f'script_{tabname}{title}_{item_id}'
@@ -526,7 +527,7 @@ def add_classes_to_gradio_component(comp):
    this adds gradio-* to the component for css styling (ie gradio-button to gr.Button), as well as some others
    """

-    comp.elem_classes = ["gradio-" + comp.get_block_name(), *(comp.elem_classes or [])]
+    comp.elem_classes = [f"gradio-{comp.get_block_name()}", *(comp.elem_classes or [])]

    if getattr(comp, 'multiselect', False):
        comp.elem_classes.append('multiselect')
@@ -75,7 +75,8 @@ def forward_old(self: sd_hijack_clip.FrozenCLIPEmbedderWithCustomWordsBase, text
    self.hijack.comments += hijack_comments

    if len(used_custom_terms) > 0:
-        self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms]))
+        embedding_names = ", ".join(f"{word} [{checksum}]" for word, checksum in used_custom_terms)
+        self.hijack.comments.append(f"Used embeddings: {embedding_names}")

    self.hijack.fixes = hijack_fixes
    return self.process_tokens(remade_batch_tokens, batch_multipliers)
@@ -256,6 +256,9 @@ def sub_quad_attention_forward(self, x, context=None, mask=None):
    k = k.unflatten(-1, (h, -1)).transpose(1,2).flatten(end_dim=1)
    v = v.unflatten(-1, (h, -1)).transpose(1,2).flatten(end_dim=1)

+    if q.device.type == 'mps':
+        q, k, v = q.contiguous(), k.contiguous(), v.contiguous()
+
    dtype = q.dtype
    if shared.opts.upcast_attn:
        q, k = q.float(), k.float()
@@ -18,7 +18,7 @@ class TorchHijackForUnet:
        if hasattr(torch, item):
            return getattr(torch, item)

-        raise AttributeError("'{}' object has no attribute '{}'".format(type(self).__name__, item))
+        raise AttributeError(f"'{type(self).__name__}' object has no attribute '{item}'")

    def cat(self, tensors, *args, **kwargs):
        if len(tensors) == 2:
@@ -2,6 +2,8 @@ import collections
 import os.path
 import sys
 import gc
+import threading
+
 import torch
 import re
 import safetensors.torch
@@ -45,7 +47,7 @@ class CheckpointInfo:
        self.model_name = os.path.splitext(name.replace("/", "_").replace("\\", "_"))[0]
        self.hash = model_hash(filename)

-        self.sha256 = hashes.sha256_from_cache(self.filename, "checkpoint/" + name)
+        self.sha256 = hashes.sha256_from_cache(self.filename, f"checkpoint/{name}")
        self.shorthash = self.sha256[0:10] if self.sha256 else None

        self.title = name if self.shorthash is None else f'{name} [{self.shorthash}]'
@@ -67,7 +69,7 @@ class CheckpointInfo:
            checkpoint_alisases[id] = self

    def calculate_shorthash(self):
-        self.sha256 = hashes.sha256(self.filename, "checkpoint/" + self.name)
+        self.sha256 = hashes.sha256(self.filename, f"checkpoint/{self.name}")
        if self.sha256 is None:
            return

@@ -404,13 +406,39 @@ def repair_config(sd_config):
 sd1_clip_weight = 'cond_stage_model.transformer.text_model.embeddings.token_embedding.weight'
 sd2_clip_weight = 'cond_stage_model.model.transformer.resblocks.0.attn.in_proj_weight'

-def load_model(checkpoint_info=None, already_loaded_state_dict=None, time_taken_to_load_state_dict=None):
+
+class SdModelData:
+    def __init__(self):
+        self.sd_model = None
+        self.lock = threading.Lock()
+
+    def get_sd_model(self):
+        if self.sd_model is None:
+            with self.lock:
+                try:
+                    load_model()
+                except Exception as e:
+                    errors.display(e, "loading stable diffusion model")
+                    print("", file=sys.stderr)
+                    print("Stable diffusion model failed to load", file=sys.stderr)
+                    self.sd_model = None
+
+        return self.sd_model
+
+    def set_sd_model(self, v):
+        self.sd_model = v
+
+
+model_data = SdModelData()
+
+
+def load_model(checkpoint_info=None, already_loaded_state_dict=None):
    from modules import lowvram, sd_hijack
    checkpoint_info = checkpoint_info or select_checkpoint()

-    if shared.sd_model:
-        sd_hijack.model_hijack.undo_hijack(shared.sd_model)
-        shared.sd_model = None
+    if model_data.sd_model:
+        sd_hijack.model_hijack.undo_hijack(model_data.sd_model)
+        model_data.sd_model = None
        gc.collect()
        devices.torch_gc()

@@ -464,7 +492,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None, time_taken_
    timer.record("hijack")

    sd_model.eval()
-    shared.sd_model = sd_model
+    model_data.sd_model = sd_model

    sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=True)  # Reload embeddings after model load as they may or may not fit the model

@@ -484,7 +512,7 @@ def reload_model_weights(sd_model=None, info=None):
    checkpoint_info = info or select_checkpoint()

    if not sd_model:
-        sd_model = shared.sd_model
+        sd_model = model_data.sd_model

    if sd_model is None:  # previous model load failed
        current_checkpoint_info = None
@@ -512,7 +540,7 @@ def reload_model_weights(sd_model=None, info=None):
        del sd_model
        checkpoints_loaded.clear()
        load_model(checkpoint_info, already_loaded_state_dict=state_dict)
-        return shared.sd_model
+        return model_data.sd_model

    try:
        load_model_weights(sd_model, checkpoint_info, state_dict, timer)
@@ -535,17 +563,15 @@ def reload_model_weights(sd_model=None, info=None):

    return sd_model

+
 def unload_model_weights(sd_model=None, info=None):
    from modules import lowvram, devices, sd_hijack
    timer = Timer()

-    if shared.sd_model:
-
-        # shared.sd_model.cond_stage_model.to(devices.cpu)
-        # shared.sd_model.first_stage_model.to(devices.cpu)
-        shared.sd_model.to(devices.cpu)
-        sd_hijack.model_hijack.undo_hijack(shared.sd_model)
-        shared.sd_model = None
+    if model_data.sd_model:
+        model_data.sd_model.to(devices.cpu)
+        sd_hijack.model_hijack.undo_hijack(model_data.sd_model)
+        model_data.sd_model = None
        sd_model = None
        gc.collect()
        devices.torch_gc()
@@ -111,7 +111,7 @@ def find_checkpoint_config_near_filename(info):
    if info is None:
        return None

-    config = os.path.splitext(info.filename)[0] + ".yaml"
+    config = f"{os.path.splitext(info.filename)[0]}.yaml"
    if os.path.exists(config):
        return config

@@ -198,7 +198,7 @@ class TorchHijack:
        if hasattr(torch, item):
            return getattr(torch, item)

-        raise AttributeError("'{}' object has no attribute '{}'".format(type(self).__name__, item))
+        raise AttributeError(f"'{type(self).__name__}' object has no attribute '{item}'")

    def randn_like(self, x):
        if self.sampler_noises:
@@ -89,7 +89,7 @@ def refresh_vae_list():

 def find_vae_near_checkpoint(checkpoint_file):
    checkpoint_path = os.path.splitext(checkpoint_file)[0]
-    for vae_location in [checkpoint_path + ".vae.pt", checkpoint_path + ".vae.ckpt", checkpoint_path + ".vae.safetensors"]:
+    for vae_location in [f"{checkpoint_path}.vae.pt", f"{checkpoint_path}.vae.ckpt", f"{checkpoint_path}.vae.safetensors"]:
        if os.path.isfile(vae_location):
            return vae_location

@@ -16,6 +16,7 @@ import modules.styles
 import modules.devices as devices
 from modules import localization, script_loading, errors, ui_components, shared_items, cmd_args
 from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir
+from ldm.models.diffusion.ddpm import LatentDiffusion

 demo = None

@@ -391,21 +392,20 @@ options_templates.update(options_section(('ui', "User interface"), {
    "return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"),
    "return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"),
    "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
-    "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
-    "add_model_name_to_info": OptionInfo(True, "Add model name to generation information"),
-    "disable_weights_auto_swap": OptionInfo(True, "When reading generation parameters from text into UI (from PNG info or pasted text), do not change the selected model/checkpoint."),
    "send_seed": OptionInfo(True, "Send seed when sending prompt or image to other interface"),
    "send_size": OptionInfo(True, "Send size when sending prompt or image to another interface"),
    "font": OptionInfo("", "Font for image grids that have text"),
    "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
    "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
+    "js_modal_lightbox_gamepad": OptionInfo(True, "Navigate image viewer with gamepad"),
+    "js_modal_lightbox_gamepad_repeat": OptionInfo(250, "Gamepad repeat period, in milliseconds"),
    "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."),
    "samplers_in_dropdown": OptionInfo(True, "Use dropdown for sampler selection instead of radio group"),
    "dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row"),
    "keyedit_precision_attention": OptionInfo(0.1, "Ctrl+up/down precision when editing (attention:1.1)", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
    "keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing <extra networks:0.9>", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
-    "keyedit_delimiters": OptionInfo(".,\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"),
-    "quicksettings": OptionInfo("sd_model_checkpoint", "Quicksettings list"),
+    "keyedit_delimiters": OptionInfo(".,\\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"),
+    "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}),
    "hidden_tabs": OptionInfo([], "Hidden UI tabs (requires restart)", ui_components.DropdownMulti, lambda: {"choices": [x for x in tab_names]}),
    "ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order"),
    "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order"),
@@ -413,6 +413,13 @@ options_templates.update(options_section(('ui', "User interface"), {
    "gradio_theme": OptionInfo("Default", "Gradio theme (requires restart)", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes})
 }))

+options_templates.update(options_section(('infotext', "Infotext"), {
+    "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
+    "add_model_name_to_info": OptionInfo(True, "Add model name to generation information"),
+    "add_version_to_infotext": OptionInfo(True, "Add program version to generation information"),
+    "disable_weights_auto_swap": OptionInfo(True, "When reading generation parameters from text into UI (from PNG info or pasted text), do not change the selected model/checkpoint."),
+}))
+
 options_templates.update(options_section(('ui', "Live previews"), {
    "show_progressbar": OptionInfo(True, "Show progressbar"),
    "live_previews_enable": OptionInfo(True, "Show live previews of the created image"),
@@ -542,6 +549,10 @@ class Options:
        with open(filename, "r", encoding="utf8") as file:
            self.data = json.load(file)

+        # 1.1.1 quicksettings list migration
+        if self.data.get('quicksettings') is not None and self.data.get('quicksettings_list') is None:
+            self.data['quicksettings_list'] = [i.strip() for i in self.data.get('quicksettings').split(',')]
+
        bad_settings = 0
        for k, v in self.data.items():
            info = self.data_labels.get(k, None)
@@ -600,13 +611,37 @@ class Options:
        return value


-
 opts = Options()
 if os.path.exists(config_filename):
    opts.load(config_filename)

+
+class Shared(sys.modules[__name__].__class__):
+    """
+    this class is here to provide sd_model field as a property, so that it can be created and loaded on demand rather than
+    at program startup.
+    """
+
+    sd_model_val = None
+
+    @property
+    def sd_model(self):
+        import modules.sd_models
+
+        return modules.sd_models.model_data.get_sd_model()
+
+    @sd_model.setter
+    def sd_model(self, value):
+        import modules.sd_models
+
+        modules.sd_models.model_data.set_sd_model(value)
+
+
+sd_model: LatentDiffusion = None  # this var is here just for IDE's type checking; it cannot be accessed because the class field above will be accessed instead
+sys.modules[__name__].__class__ = Shared
+
 settings_components = None
-"""assinged from ui.py, a mapping on setting anmes to gradio components repsponsible for those settings"""
+"""assinged from ui.py, a mapping on setting names to gradio components repsponsible for those settings"""

 latent_upscale_default_mode = "Latent"
 latent_upscale_modes = {
@@ -620,8 +655,6 @@ latent_upscale_modes = {

 sd_upscalers = []

-sd_model = None
-
 clip_model = None

 progress_print_out = sys.stdout
@@ -634,14 +667,19 @@ def reload_gradio_theme(theme_name=None):
    if not theme_name:
        theme_name = opts.gradio_theme

+    default_theme_args = dict(
+        font=["Source Sans Pro", 'ui-sans-serif', 'system-ui', 'sans-serif'],
+        font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'],
+    )
+
    if theme_name == "Default":
-        gradio_theme = gr.themes.Default()
+        gradio_theme = gr.themes.Default(**default_theme_args)
    else:
        try:
            gradio_theme = gr.themes.ThemeClass.from_hub(theme_name)
-        except requests.exceptions.ConnectionError:
-            print("Can't access HuggingFace Hub, falling back to default Gradio theme")
-            gradio_theme = gr.themes.Default()
+        except Exception as e:
+            errors.display(e, "changing gradio theme")
+            gradio_theme = gr.themes.Default(**default_theme_args)



@@ -701,3 +739,20 @@ def html(filename):
            return file.read()

    return ""
+
+
+def walk_files(path, allowed_extensions=None):
+    if not os.path.exists(path):
+        return
+
+    if allowed_extensions is not None:
+        allowed_extensions = set(allowed_extensions)
+
+    for root, dirs, files in os.walk(path):
+        for filename in files:
+            if allowed_extensions is not None:
+                _, ext = os.path.splitext(filename)
+                if ext not in allowed_extensions:
+                    continue
+
+            yield os.path.join(root, filename)
@@ -74,7 +74,7 @@ class StyleDatabase:
    def save_styles(self, path: str) -> None:
        # Always keep a backup file around
        if os.path.exists(path):
-            shutil.copy(path, path + ".bak")
+            shutil.copy(path, f"{path}.bak")

        fd = os.open(path, os.O_RDWR|os.O_CREAT)
        with os.fdopen(fd, "w", encoding="utf-8-sig", newline='') as file:
@@ -111,7 +111,7 @@ def focal_point(im, settings):
      if corner_centroid is not None:
        color = BLUE
        box = corner_centroid.bounding(max_size * corner_centroid.weight)
-        d.text((box[0], box[1]-15), "Edge: %.02f" % corner_centroid.weight, fill=color)
+        d.text((box[0], box[1]-15), f"Edge: {corner_centroid.weight:.02f}", fill=color)
        d.ellipse(box, outline=color)
        if len(corner_points) > 1:
          for f in corner_points:
@@ -119,7 +119,7 @@ def focal_point(im, settings):
      if entropy_centroid is not None:
        color = "#ff0"
        box = entropy_centroid.bounding(max_size * entropy_centroid.weight)
-        d.text((box[0], box[1]-15), "Entropy: %.02f" % entropy_centroid.weight, fill=color)
+        d.text((box[0], box[1]-15), f"Entropy: {entropy_centroid.weight:.02f}", fill=color)
        d.ellipse(box, outline=color)
        if len(entropy_points) > 1:
          for f in entropy_points:
@@ -127,7 +127,7 @@ def focal_point(im, settings):
      if face_centroid is not None:
        color = RED
        box = face_centroid.bounding(max_size * face_centroid.weight)
-        d.text((box[0], box[1]-15), "Face: %.02f" % face_centroid.weight, fill=color)
+        d.text((box[0], box[1]-15), f"Face: {face_centroid.weight:.02f}", fill=color)
        d.ellipse(box, outline=color)
        if len(face_points) > 1:
          for f in face_points:
@@ -72,7 +72,7 @@ class PersonalizedBase(Dataset):
            except Exception:
                continue

-            text_filename = os.path.splitext(path)[0] + ".txt"
+            text_filename = f"{os.path.splitext(path)[0]}.txt"
            filename = os.path.basename(path)

            if os.path.exists(text_filename):
@@ -63,9 +63,9 @@ def save_pic_with_caption(image, index, params: PreprocessParams, existing_capti
    image.save(os.path.join(params.dstdir, f"{basename}.png"))

    if params.preprocess_txt_action == 'prepend' and existing_caption:
-        caption = existing_caption + ' ' + caption
+        caption = f"{existing_caption} {caption}"
    elif params.preprocess_txt_action == 'append' and existing_caption:
-        caption = caption + ' ' + existing_caption
+        caption = f"{caption} {existing_caption}"
    elif params.preprocess_txt_action == 'copy' and existing_caption:
        caption = existing_caption

@@ -174,7 +174,7 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
        params.src = filename

        existing_caption = None
-        existing_caption_filename = os.path.splitext(filename)[0] + '.txt'
+        existing_caption_filename = f"{os.path.splitext(filename)[0]}.txt"
        if os.path.exists(existing_caption_filename):
            with open(existing_caption_filename, 'r', encoding="utf8") as file:
                existing_caption = file.read()
@@ -69,7 +69,7 @@ class Embedding:
                'hash': self.checksum(),
                'optimizer_state_dict': self.optimizer_state_dict,
            }
-            torch.save(optimizer_saved_dict, filename + '.optim')
+            torch.save(optimizer_saved_dict, f"{filename}.optim")

    def checksum(self):
        if self.cached_checksum is not None:
@@ -437,8 +437,8 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
    optimizer = torch.optim.AdamW([embedding.vec], lr=scheduler.learn_rate, weight_decay=0.0)
    if shared.opts.save_optimizer_state:
        optimizer_state_dict = None
-        if os.path.exists(filename + '.optim'):
-            optimizer_saved_dict = torch.load(filename + '.optim', map_location='cpu')
+        if os.path.exists(f"{filename}.optim"):
+            optimizer_saved_dict = torch.load(f"{filename}.optim", map_location='cpu')
            if embedding.checksum() == optimizer_saved_dict.get('hash', None):
                optimizer_state_dict = optimizer_saved_dict.get('optimizer_state_dict', None)
    
@@ -599,7 +599,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
                        data = torch.load(last_saved_file)
                        info.add_text("sd-ti-embedding", embedding_to_b64(data))

-                        title = "<{}>".format(data.get('name', '???'))
+                        title = f"<{data.get('name', '???')}>"

                        try:
                            vectorSize = list(data['string_to_param'].values())[0].shape[0]
@@ -608,8 +608,8 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st

                        checkpoint = sd_models.select_checkpoint()
                        footer_left = checkpoint.model_name
-                        footer_mid = '[{}]'.format(checkpoint.shorthash)
-                        footer_right = '{}v {}s'.format(vectorSize, steps_done)
+                        footer_mid = f'[{checkpoint.shorthash}]'
+                        footer_right = f'{vectorSize}v {steps_done}s'

                        captioned_image = caption_image_overlay(image, title, footer_left, footer_mid, footer_right)
                        captioned_image = insert_image_data_embed(captioned_image, data)
@@ -101,7 +101,7 @@ def visit(x, func, path=""):
        for c in x.children:
            visit(c, func, path)
    elif x.label is not None:
-        func(path + "/" + str(x.label), x)
+        func(f"{path}/{x.label}", x)


 def add_style(name: str, prompt: str, negative_prompt: str):
@@ -166,7 +166,7 @@ def process_interrogate(interrogation_function, mode, ii_input_dir, ii_output_di
            img = Image.open(image)
            filename = os.path.basename(image)
            left, _ = os.path.splitext(filename)
-            print(interrogation_function(img), file=open(os.path.join(ii_output_dir, left + ".txt"), 'a'))
+            print(interrogation_function(img), file=open(os.path.join(ii_output_dir, f"{left}.txt"), 'a'))

        return [gr.update(), None]

@@ -182,29 +182,29 @@ def interrogate_deepbooru(image):


 def create_seed_inputs(target_interface):
-    with FormRow(elem_id=target_interface + '_seed_row', variant="compact"):
-        seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed')
+    with FormRow(elem_id=f"{target_interface}_seed_row", variant="compact"):
+        seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=f"{target_interface}_seed")
        seed.style(container=False)
-        random_seed = ToolButton(random_symbol, elem_id=target_interface + '_random_seed', label='Random seed')
-        reuse_seed = ToolButton(reuse_symbol, elem_id=target_interface + '_reuse_seed', label='Reuse seed')
+        random_seed = ToolButton(random_symbol, elem_id=f"{target_interface}_random_seed", label='Random seed')
+        reuse_seed = ToolButton(reuse_symbol, elem_id=f"{target_interface}_reuse_seed", label='Reuse seed')

-        seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)
+        seed_checkbox = gr.Checkbox(label='Extra', elem_id=f"{target_interface}_subseed_show", value=False)

    # Components to show/hide based on the 'Extra' checkbox
    seed_extras = []

-    with FormRow(visible=False, elem_id=target_interface + '_subseed_row') as seed_extra_row_1:
+    with FormRow(visible=False, elem_id=f"{target_interface}_subseed_row") as seed_extra_row_1:
        seed_extras.append(seed_extra_row_1)
-        subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed')
+        subseed = gr.Number(label='Variation seed', value=-1, elem_id=f"{target_interface}_subseed")
        subseed.style(container=False)
-        random_subseed = ToolButton(random_symbol, elem_id=target_interface + '_random_subseed')
-        reuse_subseed = ToolButton(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
-        subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')
+        random_subseed = ToolButton(random_symbol, elem_id=f"{target_interface}_random_subseed")
+        reuse_subseed = ToolButton(reuse_symbol, elem_id=f"{target_interface}_reuse_subseed")
+        subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=f"{target_interface}_subseed_strength")

    with FormRow(visible=False) as seed_extra_row_2:
        seed_extras.append(seed_extra_row_2)
-        seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w')
-        seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h')
+        seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=f"{target_interface}_seed_resize_from_w")
+        seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=f"{target_interface}_seed_resize_from_h")

    random_seed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[seed])
    random_subseed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[subseed])
@@ -765,7 +765,7 @@ def create_ui():
                    )
                    button.click(
                        fn=lambda: None,
-                        _js="switch_to_"+name.replace(" ", "_"),
+                        _js=f"switch_to_{name.replace(' ', '_')}",
                        inputs=[],
                        outputs=[],
                    )
@@ -828,7 +828,7 @@ def create_ui():
                        with FormGroup():
                            with FormRow():
                                cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
-                                image_cfg_scale = gr.Slider(minimum=0, maximum=3.0, step=0.05, label='Image CFG Scale', value=1.5, elem_id="img2img_image_cfg_scale", visible=shared.sd_model and shared.sd_model.cond_stage_key == "edit")
+                                image_cfg_scale = gr.Slider(minimum=0, maximum=3.0, step=0.05, label='Image CFG Scale', value=1.5, elem_id="img2img_image_cfg_scale", visible=False)
                            denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")

                    elif category == "seed":
@@ -1462,18 +1462,18 @@ def create_ui():
        elif t == bool:
            comp = gr.Checkbox
        else:
-            raise Exception(f'bad options item type: {str(t)} for key {key}')
+            raise Exception(f'bad options item type: {t} for key {key}')

-        elem_id = "setting_"+key
+        elem_id = f"setting_{key}"

        if info.refresh is not None:
            if is_quicksettings:
                res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))
-                create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key)
+                create_refresh_button(res, info.refresh, info.component_args, f"refresh_{key}")
            else:
                with FormRow():
                    res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))
-                    create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key)
+                    create_refresh_button(res, info.refresh, info.component_args, f"refresh_{key}")
        else:
            res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))

@@ -1525,7 +1525,7 @@ def create_ui():

        result = gr.HTML(elem_id="settings_result")

-        quicksettings_names = [x.strip() for x in opts.quicksettings.split(",")]
+        quicksettings_names = opts.quicksettings_list
        quicksettings_names = {x: i for i, x in enumerate(quicksettings_names) if x != 'quicksettings'}

        quicksettings_list = []
@@ -1545,7 +1545,7 @@ def create_ui():
                        current_tab.__exit__()

                    gr.Group()
-                    current_tab = gr.TabItem(elem_id="settings_{}".format(elem_id), label=text)
+                    current_tab = gr.TabItem(elem_id=f"settings_{elem_id}", label=text)
                    current_tab.__enter__()
                    current_row = gr.Column(variant='compact')
                    current_row.__enter__()
@@ -1566,7 +1566,7 @@ def create_ui():
                current_row.__exit__()
                current_tab.__exit__()

-            with gr.TabItem("Actions", id="actions"):
+            with gr.TabItem("Actions", id="actions", elem_id="settings_tab_actions"):
                request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
                download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
                reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
@@ -1574,7 +1574,7 @@ def create_ui():
                    unload_sd_model = gr.Button(value='Unload SD checkpoint to free VRAM', elem_id="sett_unload_sd_model")
                    reload_sd_model = gr.Button(value='Reload the last SD checkpoint back into VRAM', elem_id="sett_reload_sd_model")

-            with gr.TabItem("Licenses", id="licenses"):
+            with gr.TabItem("Licenses", id="licenses", elem_id="settings_tab_licenses"):
                gr.HTML(shared.html("licenses.html"), elem_id="licenses")

            gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
@@ -1664,7 +1664,7 @@ def create_ui():
            for interface, label, ifid in interfaces:
                if label in shared.opts.hidden_tabs:
                    continue
-                with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid):
+                with gr.TabItem(label, id=ifid, elem_id=f"tab_{ifid}"):
                    interface.render()

        if os.path.exists(os.path.join(script_path, "notification.mp3")):
@@ -1693,11 +1693,9 @@ def create_ui():
                show_progress=info.refresh is not None,
            )

-        text_settings.change(
-            fn=lambda: gr.update(visible=shared.sd_model and shared.sd_model.cond_stage_key == "edit"),
-            inputs=[],
-            outputs=[image_cfg_scale],
-        )
+        update_image_cfg_scale_visibility = lambda: gr.update(visible=shared.sd_model and shared.sd_model.cond_stage_key == "edit")
+        text_settings.change(fn=update_image_cfg_scale_visibility, inputs=[], outputs=[image_cfg_scale])
+        demo.load(fn=update_image_cfg_scale_visibility, inputs=[], outputs=[image_cfg_scale])

        button_set_checkpoint = gr.Button('Change checkpoint', elem_id='change_checkpoint', visible=False)
        button_set_checkpoint.click(
@@ -1773,10 +1771,10 @@ def create_ui():

    def loadsave(path, x):
        def apply_field(obj, field, condition=None, init_field=None):
-            key = path + "/" + field
+            key = f"{path}/{field}"

            if getattr(obj, 'custom_script_source', None) is not None:
-              key = 'customscript/' + obj.custom_script_source + '/' + key
+              key = f"customscript/{obj.custom_script_source}/{key}"

            if getattr(obj, 'do_not_save_to_config', False):
                return
@@ -1865,12 +1863,11 @@ def webpath(fn):


 def javascript_html():
-    script_js = os.path.join(script_path, "script.js")
-    head = f'<script type="text/javascript" src="{webpath(script_js)}"></script>\n'
+    # Ensure localization is in `window` before scripts
+    head = f'<script type="text/javascript">{localization.localization_js(shared.opts.localization)}</script>\n'

-    inline = f"{localization.localization_js(shared.opts.localization)};"
-    if cmd_opts.theme is not None:
-        inline += f"set_theme('{cmd_opts.theme}');"
+    script_js = os.path.join(script_path, "script.js")
+    head += f'<script type="text/javascript" src="{webpath(script_js)}"></script>\n'

    for script in modules.scripts.list_scripts("javascript", ".js"):
        head += f'<script type="text/javascript" src="{webpath(script.path)}"></script>\n'
@@ -1878,7 +1875,8 @@ def javascript_html():
    for script in modules.scripts.list_scripts("javascript", ".mjs"):
        head += f'<script type="module" src="{webpath(script.path)}"></script>\n'

-    head += f'<script type="text/javascript">{inline}</script>\n'
+    if cmd_opts.theme:
+        head += f'<script type="text/javascript">set_theme(\"{cmd_opts.theme}\");</script>\n'

    return head

@@ -1925,7 +1923,7 @@ def versions_html():

    python_version = ".".join([str(x) for x in sys.version_info[0:3]])
    commit = launch.commit_hash()
-    short_commit = commit[0:8]
+    tag = launch.git_tag()

    if shared.xformers_available:
        import xformers
@@ -1934,6 +1932,8 @@ def versions_html():
        xformers_version = "N/A"

    return f"""
+version: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/{commit}">{tag}</a>
+ • 
 python: <span title="{sys.version}">{python_version}</span>
  • 
 torch: {getattr(torch, '__long_version__',torch.__version__)}
@@ -1942,7 +1942,21 @@ xformers: {xformers_version}
  • 
 gradio: {gr.__version__}
  • 
-commit: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/{commit}">{short_commit}</a>
- • 
 checkpoint: <a id="sd_checkpoint_hash">N/A</a>
 """
+
+
+def setup_ui_api(app):
+    from pydantic import BaseModel, Field
+    from typing import List
+
+    class QuicksettingsHint(BaseModel):
+        name: str = Field(title="Name of the quicksettings field")
+        label: str = Field(title="Label of the quicksettings field")
+
+    def quicksettings_hint():
+        return [QuicksettingsHint(name=k, label=v.label) for k, v in opts.data_labels.items()]
+
+    app.add_api_route("/internal/quicksettings-hint", quicksettings_hint, methods=["GET"], response_model=List[QuicksettingsHint])
+
+    app.add_api_route("/internal/ping", lambda: {}, methods=["GET"])
@@ -61,7 +61,8 @@ def save_config_state(name):
    if not name:
        name = "Config"
    current_config_state["name"] = name
-    filename = os.path.join(config_states_dir, datetime.now().strftime("%Y_%m_%d-%H_%M_%S") + "_" + name + ".json")
+    timestamp = datetime.now().strftime('%Y_%m_%d-%H_%M_%S')
+    filename = os.path.join(config_states_dir, f"{timestamp}_{name}.json")
    print(f"Saving backup of webui/extension state to {filename}.")
    with open(filename, "w", encoding="utf-8") as f:
        json.dump(current_config_state, f)
@@ -69,7 +69,9 @@ class ExtraNetworksPage:
        pass

    def link_preview(self, filename):
-        return "./sd_extra_networks/thumb?filename=" + urllib.parse.quote(filename.replace('\\', '/')) + "&mtime=" + str(os.path.getmtime(filename))
+        quoted_filename = urllib.parse.quote(filename.replace('\\', '/'))
+        mtime = os.path.getmtime(filename)
+        return f"./sd_extra_networks/thumb?filename={quoted_filename}&mtime={mtime}"

    def search_terms_from_path(self, filename, possible_directories=None):
        abspath = os.path.abspath(filename)
@@ -89,19 +91,22 @@ class ExtraNetworksPage:

        subdirs = {}
        for parentdir in [os.path.abspath(x) for x in self.allowed_directories_for_previews()]:
-            for x in glob.glob(os.path.join(parentdir, '**/*'), recursive=True):
-                if not os.path.isdir(x):
-                    continue
+            for root, dirs, files in os.walk(parentdir):
+                for dirname in dirs:
+                    x = os.path.join(root, dirname)

-                subdir = os.path.abspath(x)[len(parentdir):].replace("\\", "/")
-                while subdir.startswith("/"):
-                    subdir = subdir[1:]
+                    if not os.path.isdir(x):
+                        continue

-                is_empty = len(os.listdir(x)) == 0
-                if not is_empty and not subdir.endswith("/"):
-                    subdir = subdir + "/"
+                    subdir = os.path.abspath(x)[len(parentdir):].replace("\\", "/")
+                    while subdir.startswith("/"):
+                        subdir = subdir[1:]

-                subdirs[subdir] = 1
+                    is_empty = len(os.listdir(x)) == 0
+                    if not is_empty and not subdir.endswith("/"):
+                        subdir = subdir + "/"
+
+                    subdirs[subdir] = 1

        if subdirs:
            subdirs = {"": 1, **subdirs}
@@ -157,8 +162,20 @@ class ExtraNetworksPage:
        if metadata:
            metadata_button = f"<div class='metadata-button' title='Show metadata' onclick='extraNetworksRequestMetadata(event, {json.dumps(self.name)}, {json.dumps(item['name'])})'></div>"

+        local_path = ""
+        filename = item.get("filename", "")
+        for reldir in self.allowed_directories_for_previews():
+            absdir = os.path.abspath(reldir)
+
+            if filename.startswith(absdir):
+                local_path = filename[len(absdir):]
+
+        # if this is true, the item must not be show in the default view, and must instead only be
+        # shown when searching for it
+        serach_only = "/." in local_path or "\\." in local_path
+
        args = {
-            "style": f"'{height}{width}{background_image}'",
+            "style": f"'display: none; {height}{width}{background_image}'",
            "prompt": item.get("prompt", None),
            "tabname": json.dumps(tabname),
            "local_preview": json.dumps(item["local_preview"]),
@@ -168,6 +185,7 @@ class ExtraNetworksPage:
            "save_card_preview": '"' + html.escape(f"""return saveCardPreview(event, {json.dumps(tabname)}, {json.dumps(item["local_preview"])})""") + '"',
            "search_term": item.get("search_term", ""),
            "metadata_button": metadata_button,
+            "serach_only": " search_only" if serach_only else "",
        }

        return self.card_page.format(**args)
@@ -209,6 +227,11 @@ def intialize():
 class ExtraNetworksUi:
    def __init__(self):
        self.pages = None
+        """gradio HTML components related to extra networks' pages"""
+
+        self.page_contents = None
+        """HTML content of the above; empty initially, filled when extra pages have to be shown"""
+
        self.stored_extra_pages = None

        self.button_save_preview = None
@@ -236,17 +259,22 @@ def pages_in_preferred_order(pages):
 def create_ui(container, button, tabname):
    ui = ExtraNetworksUi()
    ui.pages = []
+    ui.pages_contents = []
    ui.stored_extra_pages = pages_in_preferred_order(extra_pages.copy())
    ui.tabname = tabname

    with gr.Tabs(elem_id=tabname+"_extra_tabs") as tabs:
        for page in ui.stored_extra_pages:
-            with gr.Tab(page.title, id=page.title.lower().replace(" ", "_")):
+            page_id = page.title.lower().replace(" ", "_")

-                page_elem = gr.HTML(page.create_html(ui.tabname))
+            with gr.Tab(page.title, id=page_id):
+                elem_id = f"{tabname}_{page_id}_cards_html"
+                page_elem = gr.HTML('', elem_id=elem_id)
                ui.pages.append(page_elem)

-    filter = gr.Textbox('', show_label=False, elem_id=tabname+"_extra_search", placeholder="Search...", visible=False)
+                page_elem.change(fn=lambda: None, _js='function(){applyExtraNetworkFilter(' + json.dumps(tabname) + '); return []}', inputs=[], outputs=[])
+
+    gr.Textbox('', show_label=False, elem_id=tabname+"_extra_search", placeholder="Search...", visible=False)
    button_refresh = gr.Button('Refresh', elem_id=tabname+"_extra_refresh")

    ui.button_save_preview = gr.Button('Save preview', elem_id=tabname+"_save_preview", visible=False)
@@ -254,19 +282,22 @@ def create_ui(container, button, tabname):

    def toggle_visibility(is_visible):
        is_visible = not is_visible
-        return is_visible, gr.update(visible=is_visible), gr.update(variant=("secondary-down" if is_visible else "secondary"))
+
+        if is_visible and not ui.pages_contents:
+            refresh()
+
+        return is_visible, gr.update(visible=is_visible), gr.update(variant=("secondary-down" if is_visible else "secondary")), *ui.pages_contents

    state_visible = gr.State(value=False)
-    button.click(fn=toggle_visibility, inputs=[state_visible], outputs=[state_visible, container, button])
+    button.click(fn=toggle_visibility, inputs=[state_visible], outputs=[state_visible, container, button, *ui.pages])

    def refresh():
-        res = []
-
        for pg in ui.stored_extra_pages:
            pg.refresh()
-            res.append(pg.create_html(ui.tabname))

-        return res
+        ui.pages_contents = [pg.create_html(ui.tabname) for pg in ui.stored_extra_pages]
+
+        return ui.pages_contents

    button_refresh.click(fn=refresh, inputs=[], outputs=ui.pages)

@@ -36,7 +36,7 @@ def save_pil_to_file(pil_image, dir=None):
    if already_saved_as and os.path.isfile(already_saved_as):
        register_tmp_file(shared.demo, already_saved_as)

-        file_obj = Savedfile(already_saved_as)
+        file_obj = Savedfile(f'{already_saved_as}?{os.path.getmtime(already_saved_as)}')
        return file_obj

    if shared.opts.temp_dir != "":
@@ -5,7 +5,7 @@ basicsr
 fonts
 font-roboto
 gfpgan
-gradio==3.28.1
+gradio==3.29.0
 numpy
 omegaconf
 opencv-contrib-python
@@ -3,7 +3,7 @@ transformers==4.25.1
 accelerate==0.18.0
 basicsr==1.4.2
 gfpgan==1.3.8
-gradio==3.28.1
+gradio==3.29.0
 numpy==1.23.5
 Pillow==9.4.0
 realesrgan==0.3.0
@@ -77,7 +77,7 @@ return process_images(p)
        module.display = display

        indent = " " * indent_level
-        indented = code.replace('\n', '\n' + indent)
+        indented = code.replace('\n', f"\n{indent}")
        body = f"""def __webuitemp__():
 {indent}{indented}
 __webuitemp__()"""
@@ -84,7 +84,7 @@ class Script(scripts.Script):
                    p.color_corrections = initial_color_corrections

                if append_interrogation != "None":
-                    p.prompt = original_prompt + ", " if original_prompt != "" else ""
+                    p.prompt = f"{original_prompt}, " if original_prompt else ""
                    if append_interrogation == "CLIP":
                        p.prompt += shared.interrogator.interrogate(p.init_images[0])
                    elif append_interrogation == "DeepBooru":
@@ -100,30 +100,29 @@ def cmdargs(line):

 def load_prompt_file(file):
    if file is None:
-        lines = []
+        return None, gr.update(), gr.update(lines=7)
    else:
        lines = [x.strip() for x in file.decode('utf8', errors='ignore').split("\n")]
-
-    return None, "\n".join(lines), gr.update(lines=7)
+        return None, "\n".join(lines), gr.update(lines=7)


 class Script(scripts.Script):
    def title(self):
        return "Prompts from file or textbox"

-    def ui(self, is_img2img):       
+    def ui(self, is_img2img):
        checkbox_iterate = gr.Checkbox(label="Iterate seed every line", value=False, elem_id=self.elem_id("checkbox_iterate"))
        checkbox_iterate_batch = gr.Checkbox(label="Use same random seed for all lines", value=False, elem_id=self.elem_id("checkbox_iterate_batch"))

        prompt_txt = gr.Textbox(label="List of prompt inputs", lines=1, elem_id=self.elem_id("prompt_txt"))
        file = gr.File(label="Upload prompt inputs", type='binary', elem_id=self.elem_id("file"))

-        file.change(fn=load_prompt_file, inputs=[file], outputs=[file, prompt_txt, prompt_txt])
+        file.change(fn=load_prompt_file, inputs=[file], outputs=[file, prompt_txt, prompt_txt], show_progress=False)

        # We start at one line. When the text changes, we jump to seven lines, or two lines if no \n.
        # We don't shrink back to 1, because that causes the control to ignore [enter], and it may
        # be unclear to the user that shift-enter is needed.
-        prompt_txt.change(lambda tb: gr.update(lines=7) if ("\n" in tb) else gr.update(lines=2), inputs=[prompt_txt], outputs=[prompt_txt])
+        prompt_txt.change(lambda tb: gr.update(lines=7) if ("\n" in tb) else gr.update(lines=2), inputs=[prompt_txt], outputs=[prompt_txt], show_progress=False)
        return [checkbox_iterate, checkbox_iterate_batch, prompt_txt]

    def run(self, p, checkbox_iterate, checkbox_iterate_batch, prompt_txt: str):
@@ -222,7 +222,7 @@ axis_options = [
    AxisOption("Denoising", float, apply_field("denoising_strength")),
    AxisOptionTxt2Img("Hires upscaler", str, apply_field("hr_upscaler"), choices=lambda: [*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]]),
    AxisOptionImg2Img("Cond. Image Mask Weight", float, apply_field("inpainting_mask_weight")),
-    AxisOption("VAE", str, apply_vae, cost=0.7, choices=lambda: list(sd_vae.vae_dict)),
+    AxisOption("VAE", str, apply_vae, cost=0.7, choices=lambda: ['None'] + list(sd_vae.vae_dict)),
    AxisOption("Styles", str, apply_styles, choices=lambda: list(shared.prompt_styles.styles)),
    AxisOption("UniPC Order", int, apply_uni_pc_order, cost=0.5),
    AxisOption("Face restore", str, apply_face_restore, format_value=format_value),
@@ -346,7 +346,7 @@ class SharedSettingsStackHelper(object):
        self.CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers
        self.vae = opts.sd_vae
        self.uni_pc_order = opts.uni_pc_order
-  
+
    def __exit__(self, exc_type, exc_value, tb):
        opts.data["sd_vae"] = self.vae
        opts.data["uni_pc_order"] = self.uni_pc_order
@@ -399,7 +399,7 @@ class Script(scripts.Script):
                include_sub_grids = gr.Checkbox(label='Include Sub Grids', value=False, elem_id=self.elem_id("include_sub_grids"))
            with gr.Column():
                margin_size = gr.Slider(label="Grid margins (px)", minimum=0, maximum=500, value=0, step=2, elem_id=self.elem_id("margin_size"))
-        
+
        with gr.Row(variant="compact", elem_id="swap_axes"):
            swap_xy_axes_button = gr.Button(value="Swap X/Y axes", elem_id="xy_grid_swap_axes_button")
            swap_yz_axes_button = gr.Button(value="Swap Y/Z axes", elem_id="yz_grid_swap_axes_button")
@@ -439,7 +439,7 @@ class Script(scripts.Script):
        z_type.change(fn=select_axis, inputs=[z_type,z_values_dropdown], outputs=[fill_z_button,z_values,z_values_dropdown])

        def get_dropdown_update_from_params(axis,params):
-            val_key = axis + " Values"
+            val_key = f"{axis} Values"
            vals = params.get(val_key,"")
            valslist = [x.strip() for x in chain.from_iterable(csv.reader(StringIO(vals))) if x]
            return gr.update(value = valslist)
@@ -490,7 +490,7 @@ class Script(scripts.Script):
                        start = int(mc.group(1))
                        end   = int(mc.group(2))
                        num   = int(mc.group(3)) if mc.group(3) is not None else 1
-                        
+
                        valslist_ext += [int(x) for x in np.linspace(start=start, stop=end, num=num).tolist()]
                    else:
                        valslist_ext.append(val)
@@ -512,7 +512,7 @@ class Script(scripts.Script):
                        start = float(mc.group(1))
                        end   = float(mc.group(2))
                        num   = int(mc.group(3)) if mc.group(3) is not None else 1
-                        
+
                        valslist_ext += np.linspace(start=start, stop=end, num=num).tolist()
                    else:
                        valslist_ext.append(val)
@@ -1,3 +1,6 @@
+/* temporary fix to load default gradio font in frontend instead of backend */
+
+@import url('https://fonts.googleapis.com/css2?family=Source+Sans+Pro:wght@400;600&display=swap');

 /* general gradio fixes */

@@ -125,6 +128,10 @@ div.gradio-html.min{
    text-decoration: none;
 }

+a{
+    font-weight: bold;
+    cursor: pointer;
+}


 /* general styled components */
@@ -246,7 +253,7 @@ button.custom-button{
    }
 }

-#txt2img_gallery img, #img2img_gallery img{
+#txt2img_gallery img, #img2img_gallery img, #extras_gallery img{
    object-fit: scale-down;
 }
 #txt2img_actions_column, #img2img_actions_column {
@@ -397,6 +404,18 @@ div#extras_scale_to_tab div.form{
    margin: 0 1.2em;
 }

+table.settings-value-table{
+    background: white;
+    border-collapse: collapse;
+    margin: 1em;
+    border: 4px solid white;
+}
+
+table.settings-value-table td{
+    padding: 0.4em;
+    border: 1px solid #ccc;
+    max-width: 36em;
+}

 /* live preview */
 .progressDiv{
@@ -534,6 +553,8 @@ div#extras_scale_to_tab div.form{
 #lightboxModal > img.modalImageFullscreen{
    object-fit: contain;
    height: 100%;
+    width: 100%;
+    min-height: 0;
 }

 .modalPrev,
@@ -6,6 +6,8 @@ import signal
 import re
 import warnings
 import json
+from threading import Thread
+
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.middleware.gzip import GZipMiddleware
@@ -179,30 +181,22 @@ def initialize():
    gfpgan.setup_model(cmd_opts.gfpgan_models_path)
    startup_timer.record("setup gfpgan")

-    modelloader.list_builtin_upscalers()
-    startup_timer.record("list builtin upscalers")
-
    modules.scripts.load_scripts()
    startup_timer.record("load scripts")

+    modelloader.load_upscalers()
+    startup_timer.record("load upscalers") #Is this necessary? I don't know.
+
    modules.sd_vae.refresh_vae_list()
    startup_timer.record("refresh VAE")

    modules.textual_inversion.textual_inversion.list_textual_inversion_templates()
    startup_timer.record("refresh textual inversion templates")

-    try:
-        modules.sd_models.load_model()
-    except Exception as e:
-        errors.display(e, "loading stable diffusion model")
-        print("", file=sys.stderr)
-        print("Stable diffusion model failed to load, exiting", file=sys.stderr)
-        exit(1)
-    startup_timer.record("load SD checkpoint")
+    # load model in parallel to other startup stuff
+    Thread(target=lambda: shared.sd_model).start()

-    shared.opts.data["sd_model_checkpoint"] = shared.sd_model.sd_checkpoint_info.title
-
-    shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()))
+    shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()), call=False)
    shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
    shared.opts.onchange("sd_vae_as_default", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
    shared.opts.onchange("temp_dir", ui_tempdir.on_tmpdir_changed)
@@ -286,7 +280,6 @@ def api_only():
    print(f"Startup time: {startup_timer.summary()}.")
    api.launch(server_name="0.0.0.0" if cmd_opts.listen else "127.0.0.1", port=cmd_opts.port if cmd_opts.port else 7861)

-
 def webui():
    launch_api = cmd_opts.api
    initialize()
@@ -313,6 +306,16 @@ def webui():
                for line in file.readlines():
                    gradio_auth_creds += [x.strip() for x in line.split(',') if x.strip()]

+        # this restores the missing /docs endpoint
+        if launch_api and not hasattr(FastAPI, 'original_setup'):
+            def fastapi_setup(self):
+                self.docs_url = "/docs"
+                self.redoc_url = "/redoc"
+                self.original_setup()
+
+            FastAPI.original_setup = FastAPI.setup
+            FastAPI.setup = fastapi_setup
+
        app, local_url, share_url = shared.demo.launch(
            share=cmd_opts.share,
            server_name=server_name,
@@ -339,6 +342,7 @@ def webui():
        setup_middleware(app)

        modules.progress.setup_progress_api(app)
+        modules.ui.setup_ui_api(app)

        if launch_api:
            create_api(app)
@@ -350,6 +354,11 @@ def webui():

        print(f"Startup time: {startup_timer.summary()}.")

+        if cmd_opts.subpath:
+            redirector = FastAPI()
+            redirector.get("/")
+            mounted_app = gradio.mount_gradio_app(redirector, shared.demo, path=f"/{cmd_opts.subpath}")
+
        wait_on_server(shared.demo)
        print('Restarting UI...')

@@ -376,7 +385,6 @@ def webui():

        localization.list_localizations(cmd_opts.localizations_dir)

-        modelloader.forbid_loaded_nonbuiltin_upscalers()
        modules.scripts.reload_scripts()
        startup_timer.record("load scripts")

@@ -153,24 +153,31 @@ else
    cd "${clone_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/%s/, aborting...\e[0m" "${install_dir}" "${clone_dir}"; exit 1; }
 fi

-printf "\n%s\n" "${delimiter}"
-printf "Create and activate python venv"
-printf "\n%s\n" "${delimiter}"
-cd "${install_dir}"/"${clone_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/%s/, aborting...\e[0m" "${install_dir}" "${clone_dir}"; exit 1; }
-if [[ ! -d "${venv_dir}" ]]
+if [[ -z "${VIRTUAL_ENV}" ]];
 then
-    "${python_cmd}" -m venv "${venv_dir}"
-    first_launch=1
-fi
-# shellcheck source=/dev/null
-if [[ -f "${venv_dir}"/bin/activate ]]
-then
-    source "${venv_dir}"/bin/activate
+    printf "\n%s\n" "${delimiter}"
+    printf "Create and activate python venv"
+    printf "\n%s\n" "${delimiter}"
+    cd "${install_dir}"/"${clone_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/%s/, aborting...\e[0m" "${install_dir}" "${clone_dir}"; exit 1; }
+    if [[ ! -d "${venv_dir}" ]]
+    then
+        "${python_cmd}" -m venv "${venv_dir}"
+        first_launch=1
+    fi
+    # shellcheck source=/dev/null
+    if [[ -f "${venv_dir}"/bin/activate ]]
+    then
+        source "${venv_dir}"/bin/activate
+    else
+        printf "\n%s\n" "${delimiter}"
+        printf "\e[1m\e[31mERROR: Cannot activate python venv, aborting...\e[0m"
+        printf "\n%s\n" "${delimiter}"
+        exit 1
+    fi
 else
    printf "\n%s\n" "${delimiter}"
-    printf "\e[1m\e[31mERROR: Cannot activate python venv, aborting...\e[0m"
+    printf "python venv already activate: ${VIRTUAL_ENV}"
    printf "\n%s\n" "${delimiter}"
-    exit 1
 fi

 # Try using TCMalloc on Linux
Author	SHA1	Message	Date
AUTOMATIC	89f9faa633	Merge branch 'release_candidate'	2023-05-14 13:35:07 +03:00
AUTOMATIC	dbd13dee3a	update readme for release	2023-05-14 13:34:50 +03:00
AUTOMATIC	b9abdb50a3	add a possible fix for 'LatentDiffusion' object has no attribute 'lora_layer_mapping'	2023-05-14 13:31:03 +03:00
AUTOMATIC	d7e9ac2aff	update readme	2023-05-13 20:47:32 +03:00
AUTOMATIC1111	86ff43b930	Merge pull request #10335 from akx/l10n-dis-take-2 Localization fixes	2023-05-13 20:46:50 +03:00
AUTOMATIC	2053745c8f	Merge branch 'v1.2.0-hotfix' into release_candidate	2023-05-13 20:25:03 +03:00
AUTOMATIC	27f7fbf35c	update readme	2023-05-13 20:24:48 +03:00
AUTOMATIC1111	12c78138dd	Merge pull request #10324 from catboxanon/offline Allow web UI to be ran fully offline	2023-05-13 20:22:09 +03:00
AUTOMATIC1111	063848798c	Merge pull request #10339 from catboxanon/bf16 Allow bf16 in safe unpickler	2023-05-13 20:21:39 +03:00
AUTOMATIC	7e3539df6f	fix upscalers disappearing after the user reloads UI	2023-05-13 20:21:11 +03:00
AUTOMATIC	477199357f	add an option to always refer to lora by filenames never refer to lora by an alias if multiple loras have same alias or the alias is called none	2023-05-13 20:15:37 +03:00
AUTOMATIC	b08500cec8	Merge branch 'release_candidate'	2023-05-13 08:16:37 +03:00
AUTOMATIC	231562ea13	update changelog for release	2023-05-13 08:16:20 +03:00
AUTOMATIC	8ca50f8240	fix broken prompts from file	2023-05-11 14:49:14 +03:00
AUTOMATIC	f5ea1e9d92	bump torch version	2023-05-10 07:26:42 +03:00
AUTOMATIC	d50b95b5a3	fix an issue preventing the program from starting if the user specifies a bad gradio theme	2023-05-10 07:14:13 +03:00
AUTOMATIC	921dc4639b	Merge branch 'dev' into release_candidate	2023-05-10 06:53:25 +03:00
AUTOMATIC	f07af8db64	bump gradio version for all suffering musicians	2023-05-10 06:52:51 +03:00
AUTOMATIC	c8791c1d37	Merge branch 'dev' into release_candidate	2023-05-09 22:42:37 +03:00
AUTOMATIC	31397986e7	changelog	2023-05-09 22:42:02 +03:00
AUTOMATIC1111	d6a9b22c19	Merge pull request #10232 from akx/eff Fix up string formatting/concatenation to f-strings where feasible	2023-05-09 22:40:51 +03:00
AUTOMATIC1111	ccbb361845	Merge pull request #10209 from AUTOMATIC1111/quicksettings-migration 1.1.1 quicksettings list migration	2023-05-09 22:29:08 +03:00
Aarni Koskela	3ba6c3c83c	Fix up string formatting/concatenation to f-strings where feasible	2023-05-09 22:25:39 +03:00
AUTOMATIC1111	8fb16ceb28	Merge pull request #10214 from AUTOMATIC1111/refresh-fix Refresh fix	2023-05-09 15:29:48 +03:00
Sakura-Luna	e7dbefc340	refresh fix	2023-05-09 19:06:00 +08:00
w-e-w	d1ff57e1cb	1.1.1 quicksettings list migration	2023-05-09 18:14:12 +09:00
AUTOMATIC	ad6ec02261	prevent Reload UI button/link from reloading the page when it's not yet ready	2023-05-09 11:42:47 +03:00
AUTOMATIC	eb95809501	rework loras api	2023-05-09 11:25:46 +03:00
AUTOMATIC1111	7e02a00c81	Merge pull request #10194 from DumoeDss/dev Add api method to get LoRA models with prompt	2023-05-09 11:12:13 +03:00
AUTOMATIC	11ae5399f6	make it so that custom context menu from contextMenu.js only disappears after user's click, ignoring non-user click events	2023-05-09 10:52:14 +03:00
AUTOMATIC1111	ea05ddfec8	Merge pull request #10201 from brkirch/mps-nan-fixes Fix MPS on PyTorch 2.0.1, Intel Macs	2023-05-09 10:28:24 +03:00
brkirch	de401d8ffb	Fix generation with k-diffusion/UniPC on x64 Macs	2023-05-09 01:10:13 -04:00
brkirch	9efb809f7c	Remove PyTorch 2.0 check Apparently the commit in the main branch of pytorch/pytorch that fixes this issue didn't make it into PyTorch 2.0.1, and since it is unclear exactly which release will have it we'll just always apply the workaround so a crash doesn't occur regardless.	2023-05-09 01:10:13 -04:00
AUTOMATIC	2b96a7b694	add links to wiki for filename pattern settings add extended info for quicksettings setting	2023-05-08 16:46:35 +03:00
AUTOMATIC	5edb0acfeb	use multiselect for quicksettings (this also resets the existing setting)	2023-05-08 15:38:25 +03:00
Sayo	f9abe4cddc	Add api method to get LoRA models with prompt	2023-05-08 20:38:10 +08:00
AUTOMATIC	fc966c0299	do not show licenses page when user selects Show all pages in settings	2023-05-08 15:30:32 +03:00
AUTOMATIC	eabea24eb8	put infotext options into their own category in settings tab	2023-05-08 15:26:23 +03:00
AUTOMATIC	ab4ab4e595	add version to infotext, footer and console output when starting	2023-05-08 15:23:49 +03:00
brkirch	7aab389d6f	Fix for Unet NaNs	2023-05-08 08:16:56 -04:00
AUTOMATIC	505a10ad92	use file modification time instead of current time for #9760	2023-05-08 15:09:20 +03:00
AUTOMATIC1111	879ed5422c	Merge pull request #9760 from Sakura-Luna/refresh Fix gallery not being refreshed correctly	2023-05-08 15:06:02 +03:00
AUTOMATIC1111	b3a44385b1	Merge pull request #10025 from acncagua/Upscaler_initialization Initialize the upscalers	2023-05-08 15:03:59 +03:00
Sayo	34a82a345a	Add api method to get LoRA models	2023-05-08 19:55:05 +08:00
AUTOMATIC	6a5901a3fd	update changelog	2023-05-08 12:45:22 +03:00
AUTOMATIC	f62540b2d2	Revert "add mtime to served images in gallery to prevent cache from showing old images" This reverts commit `669b518cbd`.	2023-05-08 12:18:22 +03:00
AUTOMATIC	18fb2162a4	disable useless progress display when pasting infotext using the blur button	2023-05-08 12:17:36 +03:00
AUTOMATIC	ec0da07236	Lora: add an option to use old method of applying loras	2023-05-08 12:07:43 +03:00
AUTOMATIC	083dc3c76a	directory hiding for extra networks: dirs starting with . will hide their cards on extra network tabs unless specifically searched for create HTML for extra network pages only on demand allow directories starting with . to still list their models for lora, checkpoints, etc keep "search" filter for extra networks when user refreshes the page	2023-05-08 11:33:45 +03:00
AUTOMATIC1111	855f83f92c	Merge pull request #10041 from AUTOMATIC1111/print-exception-#9219 print PIL.UnidentifiedImageError	2023-05-08 09:12:56 +03:00
AUTOMATIC1111	d1d7dd2a44	Merge pull request #10067 from dongweiming/x-y-z-plot Add extra `None` option for VAE	2023-05-08 09:03:59 +03:00
AUTOMATIC1111	fa21e6ae63	Merge pull request #9616 from Sakura-Luna/tooltip Tooltip localization support	2023-05-08 09:01:33 +03:00
AUTOMATIC1111	73d956454f	Merge branch 'dev' into tooltip	2023-05-08 09:01:25 +03:00
AUTOMATIC1111	b15bbef798	Merge pull request #10089 from AUTOMATIC1111/LoraFix Fix some Lora's not working	2023-05-08 08:45:26 +03:00
AUTOMATIC1111	67c884196d	Merge pull request #9955 from akx/noop-localization-unless-required Make localization.js do nothing if there's no localization to do	2023-05-08 08:43:11 +03:00
AUTOMATIC	669b518cbd	add mtime to served images in gallery to prevent cache from showing old images	2023-05-08 08:36:24 +03:00
AUTOMATIC	e4a66bb8e3	make lightbox properly display whole picture without cutting of parts when the picture is very wide.	2023-05-08 08:21:38 +03:00
AUTOMATIC1111	a6529a78c3	Merge pull request #10113 from missionfloyd/extras-thumbnails Fix stretched thumbnails on extras tab	2023-05-08 08:21:24 +03:00
AUTOMATIC1111	0141ab1387	Merge pull request #10140 from Archeb/patch-1 style.css: Make the image in the ImageViewer be resized correctly	2023-05-08 08:15:36 +03:00
AUTOMATIC1111	66428667c5	Merge pull request #10146 from missionfloyd/gamepad-option Fix gamepad navigation	2023-05-08 08:09:12 +03:00
AUTOMATIC1111	6ac33fe9d1	Merge pull request #10133 from AUTOMATIC1111/filename-pattern-denoising_strength Filename pattern denoising strength	2023-05-08 08:04:02 +03:00
AUTOMATIC	160780283a	put all code for /docs in same place and make it work properly with UI reloads	2023-05-08 07:57:17 +03:00
AUTOMATIC1111	064eda930c	Merge pull request #10168 from mouhao/master Fix missing /docs endpoint in newer gradio versions	2023-05-08 07:47:06 +03:00
AUTOMATIC	2473bafa67	read infotext params from the other extension for Lora if it's not active	2023-05-08 07:28:30 +03:00
mouhao	0cb582b50c	Merge pull request #1 from mouhao/mouhao-patch-1 Update webui.py	2023-05-07 21:03:28 +08:00
mouhao	5427b7128d	Update webui.py Fix missing /docs endpoint in newer gradio versions Newer versions of gradio (>=3.27.1) have removed the /docs endpoint by default. This commit adds it back to enable accessing the API documentation.	2023-05-07 20:54:48 +08:00
AUTOMATIC	2cb3b0be1d	if present, use Lora's "ss_output_name" field to refer to it in prompt	2023-05-07 08:25:34 +03:00
missionfloyd	85bd9b3d31	Work with multiple gamepads	2023-05-06 22:47:35 -06:00
missionfloyd	99f3bf07d2	gamepad repeat option	2023-05-06 22:16:51 -06:00
missionfloyd	cca5782d18	Improve joypad performance	2023-05-06 22:00:13 -06:00
missionfloyd	5cbc1c5d43	Fix spelling	2023-05-05 23:03:32 -06:00
missionfloyd	a46c23b10f	Make gamepad navigation optional	2023-05-05 22:48:27 -06:00
蚊子	8462d07116	style.css: Make the image in the ImageViewer be resized correctly	2023-05-06 01:17:39 +01:00
w-e-w	381674739e	add denoising strength filename pattern	2023-05-06 02:24:33 +09:00
w-e-w	cde0d642f3	add denoising strength filename pattern	2023-05-06 02:20:33 +09:00
missionfloyd	79a6c5a666	Fix stretched thumbnails on extras tab	2023-05-05 03:51:51 -06:00
Sakura-Luna	a3cdf9aaf8	Reopen image fix	2023-05-05 15:52:34 +08:00
Aarni Koskela	16f0739db0	Make localization.js do nothing if there's no localization to do	2023-05-04 20:18:01 +03:00
Leo Mozoloa	c3eced22fc	Fix some Lora's not working	2023-05-04 16:14:33 +02:00
Sakura-Luna	8bc4a3a2a8	Refresh fix	2023-05-04 15:59:42 +08:00
Sakura-Luna	91a15dca80	Use a new way to solve webpage refresh	2023-05-04 14:38:15 +08:00
Sakura-Luna	5c66fedb64	Revert "Fix gallery not being refreshed correctly" This reverts commit `2c24e09dfc`.	2023-05-04 14:08:22 +08:00
Sakura-Luna	35e5916af9	Revert "Add img2img refreshed correctly" This reverts commit `988dd02632`.	2023-05-04 14:08:21 +08:00
Sakura-Luna	29e13867bf	Revert "Refresh bug fix" This reverts commit `eff00413ae`.	2023-05-04 14:08:20 +08:00
Acncagua Slt	1bebb50da9	No double calls will be made Do not call load_upscalers in list_builtin_upscalers	2023-05-04 11:59:22 +09:00
Weiming Dong	251be61a80	Add extra `None` option for VAE	2023-05-04 07:59:52 +08:00
w-e-w	14e55a3301	print PIL.UnidentifiedImageError	2023-05-03 14:28:59 +09:00
Acncagua Slt	efe98ca090	Initialize the upscalers Add modelloader.load_upscalers to def initialize()	2023-05-03 00:44:16 +09:00
AUTOMATIC1111	335428c2c8	Merge pull request #9140 from yedpodtrzitko/yed/reuse-existing-venv feat: use existing virtualenv if already active	2023-05-02 11:05:00 +03:00
AUTOMATIC	14b70aa97b	revert unwanted change from #9865	2023-05-02 11:03:11 +03:00
AUTOMATIC1111	4b6808f6ed	Merge pull request #9865 from catalpaaa/subpath-support add subpath support	2023-05-02 11:01:27 +03:00
AUTOMATIC	4499bead4c	Merge branch 'master' into dev	2023-05-02 09:25:47 +03:00
AUTOMATIC	b1717c0a48	do not load wait for shared.sd_model to load at startup	2023-05-02 09:08:00 +03:00
catalpaaa	9eb5b3e90f	Merge branch 'experimental' into subpath-support	2023-05-01 11:59:21 -07:00
AUTOMATIC1111	696c338ee2	Merge pull request #9953 from akx/js-misc-fixes Miscellaneous JS fixes	2023-05-01 14:39:52 +03:00
AUTOMATIC1111	50f63e2247	Merge branch 'dev' into js-misc-fixes	2023-05-01 14:39:46 +03:00
AUTOMATIC	b463b8a126	Merge branch 'release_candidate' into dev	2023-05-01 14:09:53 +03:00
AUTOMATIC	f57445f7c4	Merge branch 'release_candidate' into dev	2023-05-01 14:01:29 +03:00
AUTOMATIC	74d249f6dd	Merge branch 'release_candidate' into dev	2023-05-01 12:48:28 +03:00
Aarni Koskela	c714300265	Use substring instead of deprecated substr	2023-04-30 22:26:11 +03:00
Aarni Koskela	4bb441bb08	Remove redundant return	2023-04-30 22:26:11 +03:00
Aarni Koskela	b7269f781c	Mark Notification.requestPermission's retval as purposely ignored	2023-04-30 22:26:11 +03:00
Aarni Koskela	f6a40a2ffa	Fix unused variables	2023-04-30 22:26:11 +03:00
Aarni Koskela	8ccc27127b	Fix a whole bunch of implicit globals	2023-04-30 22:08:52 +03:00
Aarni Koskela	34a6ad80d5	Use classList.toggle wherever possible	2023-04-30 14:48:02 +03:00
Aarni Koskela	ee973dcf1d	imageMaskFix.js: fix event listeners to not use anonymous trampoline	2023-04-30 14:46:03 +03:00
Aarni Koskela	13d8d65ef9	hints: don't process elements that already have a title	2023-04-30 14:46:03 +03:00
AUTOMATIC	5e4a0e3d24	attempt to fix broken github CI	2023-04-29 23:02:23 +03:00
catalpaaa	ecdc6471e7	bump gradio to 3.28	2023-04-28 12:23:53 -07:00
catalpaaa	b2f6e0704e	add subpath support	2023-04-25 07:27:24 -07:00
Sakura-Luna	eff00413ae	Refresh bug fix	2023-04-21 12:34:38 +08:00
Sakura-Luna	988dd02632	Add img2img refreshed correctly	2023-04-20 15:09:19 +08:00
Sakura-Luna	2c24e09dfc	Fix gallery not being refreshed correctly	2023-04-20 14:53:37 +08:00
Sakura-Luna	57a3d146e3	Tooltip localization support	2023-04-14 14:09:33 +08:00
yedpodtrzitko	0d2cf9ac18	feat: use existing virtualenv if already active	2023-03-29 16:35:37 +07:00