update readme

Fix parsing text encoder blocks in some LoRAs

CHANGELOG.md

@@ -1,3 +1,22 @@
+## 1.5.1
+
+### Minor:
+ * support parsing text encoder blocks in some new LoRAs
+
+### Extensions and API:
+ * add postprocess_batch_list script callback
+
+### Bug Fixes:
+ * 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
+
+
 ## 1.5.0
 
 ### Features:

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

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/extensions.py

@@ -56,9 +56,11 @@ 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)
+        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'
 
     def do_read_info_from_repo(self):

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

@@ -717,7 +717,27 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
         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)
+        all_prompts = p.all_prompts[:]
+        all_negative_prompts = p.all_negative_prompts[:]
+        all_seeds = p.all_seeds[:]
+        all_subseeds = p.all_subseeds[:]
+
+        # apply changes to generation data
+        all_prompts[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.prompts
+        all_negative_prompts[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.negative_prompts
+        all_seeds[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.seeds
+        all_subseeds[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.subseeds
+
+        # update p.all_negative_prompts in case extensions changed the size of the batch
+        # create_infotext below uses it
+        old_negative_prompts = p.all_negative_prompts
+        p.all_negative_prompts = all_negative_prompts
+
+        try:
+            return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch, use_main_prompt)
+        finally:
+            # restore p.all_negative_prompts in case extensions changed the size of the batch
+            p.all_negative_prompts = old_negative_prompts
 
     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 +826,10 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
             if p.scripts is not None:
                 p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n)
 
+                postprocess_batch_list_args = scripts.PostprocessBatchListArgs(list(x_samples_ddim))
+                p.scripts.postprocess_batch_list(p, postprocess_batch_list_args, batch_number=n)
+                x_samples_ddim = postprocess_batch_list_args.images
+
             for i, x_sample in enumerate(x_samples_ddim):
                 p.batch_index = i
 

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:

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={