i

launch.py

@@ -7,13 +7,13 @@ from modules.launch_util import commit_hash, fooocus_tag, is_installed, run, pyt
 from modules.model_loader import load_file_from_url
 from modules.path import modelfile_path
 
-
 REINSTALL_ALL = False
 
 
 def prepare_environment():
     torch_index_url = os.environ.get('TORCH_INDEX_URL', "https://download.pytorch.org/whl/cu118")
-    torch_command = os.environ.get('TORCH_COMMAND', f"pip install torch==2.0.1 torchvision==0.15.2 --extra-index-url {torch_index_url}")
+    torch_command = os.environ.get('TORCH_COMMAND',
+                                   f"pip install torch==2.0.1 torchvision==0.15.2 --extra-index-url {torch_index_url}")
     requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
 
     xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.20')
@@ -41,7 +41,8 @@ def prepare_environment():
                 run_pip(f"install -U -I --no-deps {xformers_package}", "xformers", live=True)
             else:
                 print("Installation of xformers is not supported in this version of Python.")
-                print("You can also check this and build manually: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers#building-xformers-on-windows-by-duckness")
+                print(
+                    "You can also check this and build manually: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers#building-xformers-on-windows-by-duckness")
                 if not is_installed("xformers"):
                     exit(0)
         elif platform.system() == "Linux":
@@ -54,8 +55,10 @@ def prepare_environment():
 
 
 model_filenames = [
-    ('sd_xl_base_1.0.safetensors', 'https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/sd_xl_base_1.0.safetensors'),
-    ('sd_xl_refiner_1.0.safetensors', 'https://huggingface.co/stabilityai/stable-diffusion-xl-refiner-1.0/resolve/main/sd_xl_refiner_1.0.safetensors')
+    ('sd_xl_base_1.0.safetensors',
+     'https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/sd_xl_base_1.0.safetensors'),
+    ('sd_xl_refiner_1.0.safetensors',
+     'https://huggingface.co/stabilityai/stable-diffusion-xl-refiner-1.0/resolve/main/sd_xl_refiner_1.0.safetensors')
 ]
 
 
@@ -69,4 +72,3 @@ prepare_environment()
 download_models()
 
 from webui import *
-

modules/launch_util.py

@@ -8,11 +8,9 @@ import logging
 
 from functools import lru_cache
 
-
 logging.getLogger("torch.distributed.nn").setLevel(logging.ERROR)  # sshh...
 logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage())
 
-
 python = sys.executable
 git = os.environ.get('GIT', "git")
 default_command_live = (os.environ.get('LAUNCH_LIVE_OUTPUT') == "1")
@@ -40,12 +38,14 @@ def git_clone(url, dir, name, commithash=None):
         if commithash is None:
             return
 
-        current_hash = run(f'"{git}" -C "{dir}" rev-parse HEAD', None, f"Couldn't determine {name}'s hash: {commithash}", live=False).strip()
+        current_hash = run(f'"{git}" -C "{dir}" rev-parse HEAD', None,
+                           f"Couldn't determine {name}'s hash: {commithash}", live=False).strip()
         if current_hash == commithash:
             return
 
         run(f'"{git}" -C "{dir}" fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}")
-        run(f'"{git}" -C "{dir}" checkout {commithash}', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}", live=True)
+        run(f'"{git}" -C "{dir}" checkout {commithash}', f"Checking out commit for {name} with hash: {commithash}...",
+            f"Couldn't checkout commit {commithash} for {name}", live=True)
         return
 
     run(f'"{git}" clone "{url}" "{dir}"', f"Cloning {name} into {dir}...", f"Couldn't clone {name}", live=True)
@@ -101,7 +101,8 @@ def run(command, desc=None, errdesc=None, custom_env=None, live: bool = default_
 
 def run_pip(command, desc=None, live=default_command_live):
     index_url_line = f' --index-url {index_url}' if index_url != '' else ''
-    return run(f'"{python}" -m pip {command} --prefer-binary{index_url_line}', desc=f"Installing {desc}", errdesc=f"Couldn't install {desc}", live=live)
+    return run(f'"{python}" -m pip {command} --prefer-binary{index_url_line}', desc=f"Installing {desc}",
+               errdesc=f"Couldn't install {desc}", live=live)
 
 
 re_requirement = re.compile(r"\s*([-_a-zA-Z0-9]+)\s*(?:==\s*([-+_.a-zA-Z0-9]+))?\s*")

modules/model_loader.py

@@ -3,11 +3,11 @@ from urllib.parse import urlparse
 
 
 def load_file_from_url(
-    url: str,
-    *,
-    model_dir: str,
-    progress: bool = True,
-    file_name: str | None = None,
+        url: str,
+        *,
+        model_dir: str,
+        progress: bool = True,
+        file_name: str | None = None,
 ) -> str:
     """Download a file from `url` into `model_dir`, using the file present if possible.
 

webui.py

@@ -1,4 +1,6 @@
 import os
+import random
+
 from comfy.sd import load_checkpoint_guess_config
 
 from nodes import (
@@ -11,7 +13,6 @@ from nodes import (
 
 from modules.path import modelfile_path
 
-
 xl_base_filename = os.path.join(modelfile_path, 'sd_xl_base_1.0.safetensors')
 xl_refiner_filename = os.path.join(modelfile_path, 'sd_xl_refiner_1.0.safetensors')
 
@@ -22,10 +23,25 @@ opCLIPTextEncode = CLIPTextEncode()
 opEmptyLatentImage = EmptyLatentImage()
 opKSamplerAdvanced = KSamplerAdvanced()
 
+positive_conditions = opCLIPTextEncode.encode(clip=xl_base_clip, text='a handsome man in forest')[0]
+negative_conditions = opCLIPTextEncode.encode(clip=xl_base_clip, text='bad, ugly')[0]
 
-positive_embedding = opCLIPTextEncode.encode(clip=xl_base_clip, text='a handsome man in forest')
-negative_embedding = opCLIPTextEncode.encode(clip=xl_base_clip, text='bad, ugly')
+initial_latent_image = opEmptyLatentImage.generate(width=1024, height=1536, batch_size=1)[0]
 
-initial_latent_image = opEmptyLatentImage.generate(width=1024, height=1536, batch_size=1)
+samples = opKSamplerAdvanced.sample(
+    add_noise="enable",
+    noise_seed=random.randint(1, 2 ** 64),
+    steps=25,
+    cfg=9,
+    sampler_name="euler",
+    scheduler="normal",
+    start_at_step=0,
+    end_at_step=25,
+    return_with_leftover_noise="enable",
+    model=xl_base,
+    positive=positive_conditions,
+    negative=negative_conditions,
+    latent_image=initial_latent_image,
+)
 
 a = 0