Merge branch 'AUTOMATIC1111:master' into openvino_custom_scripts

CHANGELOG.md

@@ -1,3 +1,28 @@
+## 1.5.1
+
+### Minor:
+ * support parsing text encoder blocks in some new LoRAs
+ * delete scale checker script due to user demand
+
+### Extensions and API:
+ * add postprocess_batch_list script callback
+
+### Bug Fixes:
+ * fix TI training for SD1
+ * fix reload altclip model error
+ * prepend the pythonpath instead of overriding it
+ * fix typo in SD_WEBUI_RESTARTING
+ * if txt2img/img2img raises an exception, finally call state.end()
+ * fix composable diffusion weight parsing
+ * restyle Startup profile for black users
+ * fix webui not launching with --nowebui
+ * catch exception for non git extensions
+ * fix some options missing from /sdapi/v1/options
+ * fix for extension update status always saying "unknown"
+ * fix display of extra network cards that have `<>` in the name
+ * update lora extension to work with python 3.8
+
+
 ## 1.5.0
 
 ### Features:

extensions-builtin/Lora/network.py

@@ -1,3 +1,4 @@
+from __future__ import annotations
 import os
 from collections import namedtuple
 import enum

extensions-builtin/Lora/networks.py

@@ -163,6 +163,11 @@ def load_network(name, network_on_disk):
             key = key_network_without_network_parts.replace("lora_te1_text_model", "0_transformer_text_model")
             sd_module = shared.sd_model.network_layer_mapping.get(key, None)
 
+            # some SD1 Loras also have correct compvis keys
+            if sd_module is None:
+                key = key_network_without_network_parts.replace("lora_te1_text_model", "transformer_text_model")
+                sd_module = shared.sd_model.network_layer_mapping.get(key, None)
+
         if sd_module is None:
             keys_failed_to_match[key_network] = key
             continue

javascript/badScaleChecker.js

@@ -1,108 +0,0 @@
-(function() {
-    var ignore = localStorage.getItem("bad-scale-ignore-it") == "ignore-it";
-
-    function getScale() {
-        var ratio = 0,
-            screen = window.screen,
-            ua = navigator.userAgent.toLowerCase();
-
-        if (window.devicePixelRatio !== undefined) {
-            ratio = window.devicePixelRatio;
-        } else if (~ua.indexOf('msie')) {
-            if (screen.deviceXDPI && screen.logicalXDPI) {
-                ratio = screen.deviceXDPI / screen.logicalXDPI;
-            }
-        } else if (window.outerWidth !== undefined && window.innerWidth !== undefined) {
-            ratio = window.outerWidth / window.innerWidth;
-        }
-
-        return ratio == 0 ? 0 : Math.round(ratio * 100);
-    }
-
-    var showing = false;
-
-    var div = document.createElement("div");
-    div.style.position = "fixed";
-    div.style.top = "0px";
-    div.style.left = "0px";
-    div.style.width = "100vw";
-    div.style.backgroundColor = "firebrick";
-    div.style.textAlign = "center";
-    div.style.zIndex = 99;
-
-    var b = document.createElement("b");
-    b.innerHTML = 'Bad Scale: ??% ';
-
-    div.appendChild(b);
-
-    var note1 = document.createElement("p");
-    note1.innerHTML = "Change your browser or your computer settings!";
-    note1.title = 'Just make sure "computer-scale" * "browser-scale" = 100% ,\n' +
-        "you can keep your computer-scale and only change this page's scale,\n" +
-        "for example: your computer-scale is 125%, just use [\"CTRL\"+\"-\"] to make your browser-scale of this page to 80%.";
-    div.appendChild(note1);
-
-    var note2 = document.createElement("p");
-    note2.innerHTML = " Otherwise, it will cause this page to not function properly!";
-    note2.title = "When you click \"Copy image to: [inpaint sketch]\" in some img2img's tab,\n" +
-        "if scale<100% the canvas will be invisible,\n" +
-        "else if scale>100% this page will take large amount of memory and CPU performance.";
-    div.appendChild(note2);
-
-    var btn = document.createElement("button");
-    btn.innerHTML = "Click here to ignore";
-
-    div.appendChild(btn);
-
-    function tryShowTopBar(scale) {
-        if (showing) return;
-
-        b.innerHTML = 'Bad Scale: ' + scale + '% ';
-
-        var updateScaleTimer = setInterval(function() {
-            var newScale = getScale();
-            b.innerHTML = 'Bad Scale: ' + newScale + '% ';
-            if (newScale == 100) {
-                var p = div.parentNode;
-                if (p != null) p.removeChild(div);
-                showing = false;
-                clearInterval(updateScaleTimer);
-                check();
-            }
-        }, 999);
-
-        btn.onclick = function() {
-            clearInterval(updateScaleTimer);
-            var p = div.parentNode;
-            if (p != null) p.removeChild(div);
-            ignore = true;
-            showing = false;
-            localStorage.setItem("bad-scale-ignore-it", "ignore-it");
-        };
-
-        document.body.appendChild(div);
-    }
-
-    function check() {
-        if (!ignore) {
-            var timer = setInterval(function() {
-                var scale = getScale();
-                if (scale != 100 && !ignore) {
-                    tryShowTopBar(scale);
-                    clearInterval(timer);
-                }
-                if (ignore) {
-                    clearInterval(timer);
-                }
-            }, 999);
-        }
-    }
-
-    if (document.readyState != "complete") {
-        document.onreadystatechange = function() {
-            if (document.readyState != "complete") check();
-        };
-    } else {
-        check();
-    }
-})();

modules/api/api.py

@@ -333,14 +333,16 @@ class Api:
                 p.outpath_grids = opts.outdir_txt2img_grids
                 p.outpath_samples = opts.outdir_txt2img_samples
 
-                shared.state.begin(job="scripts_txt2img")
-                if selectable_scripts is not None:
-                    p.script_args = script_args
-                    processed = scripts.scripts_txt2img.run(p, *p.script_args) # Need to pass args as list here
-                else:
-                    p.script_args = tuple(script_args) # Need to pass args as tuple here
-                    processed = process_images(p)
-                shared.state.end()
+                try:
+                    shared.state.begin(job="scripts_txt2img")
+                    if selectable_scripts is not None:
+                        p.script_args = script_args
+                        processed = scripts.scripts_txt2img.run(p, *p.script_args) # Need to pass args as list here
+                    else:
+                        p.script_args = tuple(script_args) # Need to pass args as tuple here
+                        processed = process_images(p)
+                finally:
+                    shared.state.end()
 
         b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
 
@@ -390,14 +392,16 @@ class Api:
                 p.outpath_grids = opts.outdir_img2img_grids
                 p.outpath_samples = opts.outdir_img2img_samples
 
-                shared.state.begin(job="scripts_img2img")
-                if selectable_scripts is not None:
-                    p.script_args = script_args
-                    processed = scripts.scripts_img2img.run(p, *p.script_args) # Need to pass args as list here
-                else:
-                    p.script_args = tuple(script_args) # Need to pass args as tuple here
-                    processed = process_images(p)
-                shared.state.end()
+                try:
+                    shared.state.begin(job="scripts_img2img")
+                    if selectable_scripts is not None:
+                        p.script_args = script_args
+                        processed = scripts.scripts_img2img.run(p, *p.script_args) # Need to pass args as list here
+                    else:
+                        p.script_args = tuple(script_args) # Need to pass args as tuple here
+                        processed = process_images(p)
+                finally:
+                    shared.state.end()
 
         b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
 
@@ -720,9 +724,9 @@ class Api:
             cuda = {'error': f'{err}'}
         return models.MemoryResponse(ram=ram, cuda=cuda)
 
-    def launch(self, server_name, port):
+    def launch(self, server_name, port, root_path):
         self.app.include_router(self.router)
-        uvicorn.run(self.app, host=server_name, port=port, timeout_keep_alive=shared.cmd_opts.timeout_keep_alive)
+        uvicorn.run(self.app, host=server_name, port=port, timeout_keep_alive=shared.cmd_opts.timeout_keep_alive, root_path=root_path)
 
     def kill_webui(self):
         restart.stop_program()

modules/api/models.py

@@ -208,11 +208,9 @@ class PreprocessResponse(BaseModel):
 fields = {}
 for key, metadata in opts.data_labels.items():
     value = opts.data.get(key)
-    optType = opts.typemap.get(type(metadata.default), type(metadata.default))
+    optType = opts.typemap.get(type(metadata.default), type(metadata.default)) if metadata.default else Any
 
-    if metadata.default is None:
-        pass
-    elif metadata is not None:
+    if metadata is not None:
         fields.update({key: (Optional[optType], Field(default=metadata.default, description=metadata.label))})
     else:
         fields.update({key: (Optional[optType], Field())})

modules/extensions.py

@@ -56,10 +56,12 @@ class Extension:
                 self.do_read_info_from_repo()
 
                 return self.to_dict()
-
-        d = cache.cached_data_for_file('extensions-git', self.name, os.path.join(self.path, ".git"), read_from_repo)
-        self.from_dict(d)
-        self.status = 'unknown'
+        try:
+            d = cache.cached_data_for_file('extensions-git', self.name, os.path.join(self.path, ".git"), read_from_repo)
+            self.from_dict(d)
+        except FileNotFoundError:
+            pass
+        self.status = 'unknown' if self.status == '' else self.status
 
     def do_read_info_from_repo(self):
         repo = None

modules/launch_utils.py

@@ -196,7 +196,7 @@ def run_extension_installer(extension_dir):
 
     try:
         env = os.environ.copy()
-        env['PYTHONPATH'] = os.path.abspath(".")
+        env['PYTHONPATH'] = f"{os.path.abspath('.')}{os.pathsep}{env.get('PYTHONPATH', '')}"
 
         print(run(f'"{python}" "{path_installer}"', errdesc=f"Error running install.py for extension {extension_dir}", custom_env=env))
     except Exception as e:
@@ -233,7 +233,7 @@ def run_extensions_installers(settings_file):
 re_requirement = re.compile(r"\s*([-_a-zA-Z0-9]+)\s*(?:==\s*([-+_.a-zA-Z0-9]+))?\s*")
 
 
-def requrements_met(requirements_file):
+def requirements_met(requirements_file):
     """
     Does a simple parse of a requirements.txt file to determine if all rerqirements in it
     are already installed. Returns True if so, False if not installed or parsing fails.
@@ -293,7 +293,7 @@ def prepare_environment():
     try:
         # the existance of this file is a signal to webui.sh/bat that webui needs to be restarted when it stops execution
         os.remove(os.path.join(script_path, "tmp", "restart"))
-        os.environ.setdefault('SD_WEBUI_RESTARTING ', '1')
+        os.environ.setdefault('SD_WEBUI_RESTARTING', '1')
     except OSError:
         pass
 
@@ -354,7 +354,7 @@ def prepare_environment():
     if not os.path.isfile(requirements_file):
         requirements_file = os.path.join(script_path, requirements_file)
 
-    if not requrements_met(requirements_file):
+    if not requirements_met(requirements_file):
         run_pip(f"install -r \"{requirements_file}\"", "requirements")
 
     run_extensions_installers(settings_file=args.ui_settings_file)

modules/processing.py

@@ -600,8 +600,12 @@ def program_version():
     return res
 
 
-def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0, use_main_prompt=False):
-    index = position_in_batch + iteration * p.batch_size
+def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0, use_main_prompt=False, index=None, all_negative_prompts=None):
+    if index is None:
+        index = position_in_batch + iteration * p.batch_size
+
+    if all_negative_prompts is None:
+        all_negative_prompts = p.all_negative_prompts
 
     clip_skip = getattr(p, 'clip_skip', opts.CLIP_stop_at_last_layers)
     enable_hr = getattr(p, 'enable_hr', False)
@@ -617,12 +621,12 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Sampler": p.sampler_name,
         "CFG scale": p.cfg_scale,
         "Image CFG scale": getattr(p, 'image_cfg_scale', None),
-        "Seed": all_seeds[index],
+        "Seed": p.all_seeds[0] if use_main_prompt else all_seeds[index],
         "Face restoration": (opts.face_restoration_model if p.restore_faces else None),
         "Size": f"{p.width}x{p.height}",
         "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
         "Model": (None if not opts.add_model_name_to_info else shared.sd_model.sd_checkpoint_info.name_for_extra),
-        "Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),
+        "Variation seed": (None if p.subseed_strength == 0 else (p.all_subseeds[0] if use_main_prompt else all_subseeds[index])),
         "Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength),
         "Seed resize from": (None if p.seed_resize_from_w <= 0 or p.seed_resize_from_h <= 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
         "Denoising strength": getattr(p, 'denoising_strength', None),
@@ -642,7 +646,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
     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])
 
     prompt_text = p.prompt if use_main_prompt else all_prompts[index]
-    negative_prompt_text = f"\nNegative prompt: {p.all_negative_prompts[index]}" if p.all_negative_prompts[index] else ""
+    negative_prompt_text = f"\nNegative prompt: {all_negative_prompts[index]}" if all_negative_prompts[index] else ""
 
     return f"{prompt_text}{negative_prompt_text}\n{generation_params_text}".strip()
 
@@ -716,9 +720,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
     else:
         p.all_subseeds = [int(subseed) + x for x in range(len(p.all_prompts))]
 
-    def infotext(iteration=0, position_in_batch=0, use_main_prompt=False):
-        return create_infotext(p, p.all_prompts, p.all_seeds, p.all_subseeds, comments, iteration, position_in_batch, use_main_prompt)
-
     if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings:
         model_hijack.embedding_db.load_textual_inversion_embeddings()
 
@@ -806,6 +807,16 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
             if p.scripts is not None:
                 p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n)
 
+                p.prompts = p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size]
+                p.negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size]
+
+                batch_params = scripts.PostprocessBatchListArgs(list(x_samples_ddim))
+                p.scripts.postprocess_batch_list(p, batch_params, batch_number=n)
+                x_samples_ddim = batch_params.images
+
+            def infotext(index=0, use_main_prompt=False):
+                return create_infotext(p, p.prompts, p.seeds, p.subseeds, use_main_prompt=use_main_prompt, index=index, all_negative_prompts=p.negative_prompts)
+
             for i, x_sample in enumerate(x_samples_ddim):
                 p.batch_index = i
 
@@ -814,7 +825,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
 
                 if p.restore_faces:
                     if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration:
-                        images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration")
+                        images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-before-face-restoration")
 
                     devices.torch_gc()
 
@@ -831,15 +842,15 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                 if p.color_corrections is not None and i < len(p.color_corrections):
                     if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction:
                         image_without_cc = apply_overlay(image, p.paste_to, i, p.overlay_images)
-                        images.save_image(image_without_cc, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction")
+                        images.save_image(image_without_cc, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-before-color-correction")
                     image = apply_color_correction(p.color_corrections[i], image)
 
                 image = apply_overlay(image, p.paste_to, i, p.overlay_images)
 
                 if opts.samples_save and not p.do_not_save_samples:
-                    images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p)
+                    images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p)
 
-                text = infotext(n, i)
+                text = infotext(i)
                 infotexts.append(text)
                 if opts.enable_pnginfo:
                     image.info["parameters"] = text
@@ -850,10 +861,10 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                     image_mask_composite = Image.composite(image.convert('RGBA').convert('RGBa'), Image.new('RGBa', image.size), images.resize_image(2, p.mask_for_overlay, image.width, image.height).convert('L')).convert('RGBA')
 
                     if opts.save_mask:
-                        images.save_image(image_mask, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask")
+                        images.save_image(image_mask, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-mask")
 
                     if opts.save_mask_composite:
-                        images.save_image(image_mask_composite, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask-composite")
+                        images.save_image(image_mask_composite, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-mask-composite")
 
                     if opts.return_mask:
                         output_images.append(image_mask)
@@ -894,7 +905,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
         p,
         images_list=output_images,
         seed=p.all_seeds[0],
-        info=infotext(),
+        info=infotexts[0],
         comments="".join(f"{comment}\n" for comment in comments),
         subseed=p.all_subseeds[0],
         index_of_first_image=index_of_first_image,

modules/prompt_parser.py

@@ -178,7 +178,7 @@ def get_learned_conditioning(model, prompts: SdConditioning | list[str], steps):
 
 
 re_AND = re.compile(r"\bAND\b")
-re_weight = re.compile(r"^(.*?)(?:\s*:\s*([-+]?(?:\d+\.?|\d*\.\d+)))?\s*$")
+re_weight = re.compile(r"^((?:\s|.)*?)(?:\s*:\s*([-+]?(?:\d+\.?|\d*\.\d+)))?\s*$")
 
 
 def get_multicond_prompt_list(prompts: SdConditioning | list[str]):

modules/scripts.py

@@ -16,6 +16,11 @@ class PostprocessImageArgs:
         self.image = image
 
 
+class PostprocessBatchListArgs:
+    def __init__(self, images):
+        self.images = images
+
+
 class Script:
     name = None
     """script's internal name derived from title"""
@@ -119,7 +124,7 @@ class Script:
 
     def after_extra_networks_activate(self, p, *args, **kwargs):
         """
-        Calledafter extra networks activation, before conds calculation
+        Called after extra networks activation, before conds calculation
         allow modification of the network after extra networks activation been applied
         won't be call if p.disable_extra_networks
 
@@ -156,6 +161,25 @@ class Script:
 
         pass
 
+    def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, *args, **kwargs):
+        """
+        Same as postprocess_batch(), but receives batch images as a list of 3D tensors instead of a 4D tensor.
+        This is useful when you want to update the entire batch instead of individual images.
+
+        You can modify the postprocessing object (pp) to update the images in the batch, remove images, add images, etc.
+        If the number of images is different from the batch size when returning,
+        then the script has the responsibility to also update the following attributes in the processing object (p):
+          - p.prompts
+          - p.negative_prompts
+          - p.seeds
+          - p.subseeds
+
+        **kwargs will have same items as process_batch, and also:
+          - batch_number - index of current batch, from 0 to number of batches-1
+        """
+
+        pass
+
     def postprocess_image(self, p, pp: PostprocessImageArgs, *args):
         """
         Called for every image after it has been generated.
@@ -536,6 +560,14 @@ class ScriptRunner:
             except Exception:
                 errors.report(f"Error running postprocess_batch: {script.filename}", exc_info=True)
 
+    def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, **kwargs):
+        for script in self.alwayson_scripts:
+            try:
+                script_args = p.script_args[script.args_from:script.args_to]
+                script.postprocess_batch_list(p, pp, *script_args, **kwargs)
+            except Exception:
+                errors.report(f"Error running postprocess_batch_list: {script.filename}", exc_info=True)
+
     def postprocess_image(self, p, pp: PostprocessImageArgs):
         for script in self.alwayson_scripts:
             try:

modules/sd_hijack.py

@@ -243,7 +243,7 @@ class StableDiffusionModelHijack:
         ldm.modules.diffusionmodules.openaimodel.UNetModel.forward = sd_unet.UNetModel_forward
 
     def undo_hijack(self, m):
-        if type(m.cond_stage_model) == xlmr.BertSeriesModelWithTransformation:
+        if type(m.cond_stage_model) == sd_hijack_xlmr.FrozenXLMREmbedderWithCustomWords:
             m.cond_stage_model = m.cond_stage_model.wrapped
 
         elif type(m.cond_stage_model) == sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords:

modules/sd_hijack_clip.py

@@ -270,12 +270,17 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
 
         z = self.encode_with_transformers(tokens)
 
+        pooled = getattr(z, 'pooled', None)
+
         # restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise
         batch_multipliers = torch.asarray(batch_multipliers).to(devices.device)
         original_mean = z.mean()
-        z *= batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape)
+        z = z * batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape)
         new_mean = z.mean()
-        z *= (original_mean / new_mean)
+        z = z * (original_mean / new_mean)
+
+        if pooled is not None:
+            z.pooled = pooled
 
         return z
 

modules/ui_extra_networks.py

@@ -253,7 +253,7 @@ class ExtraNetworksPage:
             "prompt": item.get("prompt", None),
             "tabname": quote_js(tabname),
             "local_preview": quote_js(item["local_preview"]),
-            "name": item["name"],
+            "name": html.escape(item["name"]),
             "description": (item.get("description") or "" if shared.opts.extra_networks_card_show_desc else ""),
             "card_clicked": onclick,
             "save_card_preview": '"' + html.escape(f"""return saveCardPreview(event, {quote_js(tabname)}, {quote_js(item["local_preview"])})""") + '"',

style.css

@@ -423,15 +423,16 @@ div#extras_scale_to_tab div.form{
 }
 
 table.popup-table{
-    background: white;
+    background: var(--body-background-fill);
+    color: var(--body-text-color);
     border-collapse: collapse;
     margin: 1em;
-    border: 4px solid white;
+    border: 4px solid var(--body-background-fill);
 }
 
 table.popup-table td{
     padding: 0.4em;
-    border: 1px solid #ccc;
+    border: 1px solid rgba(128, 128, 128, 0.5);
     max-width: 36em;
 }
 

webui.py

@@ -374,7 +374,7 @@ def api_only():
     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,
-        root_path = f"/{cmd_opts.subpath}"
+        root_path=f"/{cmd_opts.subpath}" if cmd_opts.subpath else ""
     )
 
 
@@ -407,7 +407,7 @@ def webui():
             ssl_verify=cmd_opts.disable_tls_verify,
             debug=cmd_opts.gradio_debug,
             auth=gradio_auth_creds,
-            inbrowser=cmd_opts.autolaunch and os.getenv('SD_WEBUI_RESTARTING ') != '1',
+            inbrowser=cmd_opts.autolaunch and os.getenv('SD_WEBUI_RESTARTING') != '1',
             prevent_thread_lock=True,
             allowed_paths=cmd_opts.gradio_allowed_path,
             app_kwargs={