new update

.gitignore

@@ -0,0 +1,207 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[codz]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py.cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# UV
+#   Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#uv.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+#poetry.toml
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#   pdm recommends including project-wide configuration in pdm.toml, but excluding .pdm-python.
+#   https://pdm-project.org/en/latest/usage/project/#working-with-version-control
+#pdm.lock
+#pdm.toml
+.pdm-python
+.pdm-build/
+
+# pixi
+#   Similar to Pipfile.lock, it is generally recommended to include pixi.lock in version control.
+#pixi.lock
+#   Pixi creates a virtual environment in the .pixi directory, just like venv module creates one
+#   in the .venv directory. It is recommended not to include this directory in version control.
+.pixi
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.envrc
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# Abstra
+# Abstra is an AI-powered process automation framework.
+# Ignore directories containing user credentials, local state, and settings.
+# Learn more at https://abstra.io/docs
+.abstra/
+
+# Visual Studio Code
+#  Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore 
+#  that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore
+#  and can be added to the global gitignore or merged into this file. However, if you prefer, 
+#  you could uncomment the following to ignore the entire vscode folder
+# .vscode/
+
+# Ruff stuff:
+.ruff_cache/
+
+# PyPI configuration file
+.pypirc
+
+# Cursor
+#  Cursor is an AI-powered code editor. `.cursorignore` specifies files/directories to
+#  exclude from AI features like autocomplete and code analysis. Recommended for sensitive data
+#  refer to https://docs.cursor.com/context/ignore-files
+.cursorignore
+.cursorindexingignore
+
+# Marimo
+marimo/_static/
+marimo/_lsp/
+__marimo__/

README.md

@@ -4,7 +4,7 @@ emoji: 🧩🖼️
 colorFrom: red
 colorTo: pink
 sdk: gradio
-sdk_version: 4.31.3
+sdk_version: 5.44.1
 app_file: app.py
 pinned: true
 license: mit

app.py

@@ -1,5 +1,6 @@
 import spaces
 import os
+from argparse import ArgumentParser
 from stablepy import (
     Model_Diffusers,
     SCHEDULE_TYPE_OPTIONS,
@@ -40,6 +41,7 @@ from constants import (
     DIFFUSERS_CONTROLNET_MODEL,
     IP_MODELS,
     MODE_IP_OPTIONS,
+    CACHE_HF_ROOT,
 )
 from stablepy.diffusers_vanilla.style_prompt_config import STYLE_NAMES
 import torch
@@ -60,6 +62,7 @@ from utils import (
     progress_step_bar,
     html_template_message,
     escape_html,
+    clear_hf_cache,
 )
 from image_processor import preprocessor_tab
 from datetime import datetime
@@ -72,11 +75,17 @@ from diffusers import FluxPipeline
 # import urllib.parse
 import subprocess
 
-subprocess.run("rm -rf /data-nvme/zerogpu-offload/*", env={}, shell=True)
+IS_ZERO_GPU = bool(os.getenv("SPACES_ZERO_GPU"))
+if IS_ZERO_GPU:
+    subprocess.run("rm -rf /data-nvme/zerogpu-offload/*", env={}, shell=True)
+IS_GPU_MODE = True if IS_ZERO_GPU else (True if torch.cuda.is_available() else False)
+img_path = "./images/"
+allowed_path = os.path.abspath(img_path)
+delete_cache_time = (9600, 9600) if IS_ZERO_GPU else (86400, 86400)
+
 ImageFile.LOAD_TRUNCATED_IMAGES = True
 torch.backends.cuda.matmul.allow_tf32 = True
 # os.environ["PYTORCH_NO_CUDA_MEMORY_CACHING"] = "1"
-print(os.getenv("SPACES_ZERO_GPU"))
 
 directories = [DIRECTORY_MODELS, DIRECTORY_LORAS, DIRECTORY_VAES, DIRECTORY_EMBEDS, DIRECTORY_UPSCALERS]
 for directory in directories:
@@ -84,19 +93,15 @@ for directory in directories:
 
 # Download stuffs
 for url in [url.strip() for url in DOWNLOAD_MODEL.split(',')]:
-    if not os.path.exists(f"./models/{url.split('/')[-1]}"):
-        download_things(DIRECTORY_MODELS, url, HF_TOKEN, CIVITAI_API_KEY)
+    download_things(DIRECTORY_MODELS, url, HF_TOKEN, CIVITAI_API_KEY)
 for url in [url.strip() for url in DOWNLOAD_VAE.split(',')]:
-    if not os.path.exists(f"./vaes/{url.split('/')[-1]}"):
-        download_things(DIRECTORY_VAES, url, HF_TOKEN, CIVITAI_API_KEY)
+    download_things(DIRECTORY_VAES, url, HF_TOKEN, CIVITAI_API_KEY)
 for url in [url.strip() for url in DOWNLOAD_LORA.split(',')]:
-    if not os.path.exists(f"./loras/{url.split('/')[-1]}"):
-        download_things(DIRECTORY_LORAS, url, HF_TOKEN, CIVITAI_API_KEY)
+    download_things(DIRECTORY_LORAS, url, HF_TOKEN, CIVITAI_API_KEY)
 
 # Download Embeddings
 for url_embed in DOWNLOAD_EMBEDS:
-    if not os.path.exists(f"./embedings/{url_embed.split('/')[-1]}"):
-        download_things(DIRECTORY_EMBEDS, url_embed, HF_TOKEN, CIVITAI_API_KEY)
+    download_things(DIRECTORY_EMBEDS, url_embed, HF_TOKEN, CIVITAI_API_KEY)
 
 # Build list models
 embed_list = get_model_list(DIRECTORY_EMBEDS)
@@ -114,15 +119,16 @@ vae_model_list.insert(0, "None")
 
 print('\033[33m🏁 Download and listing of valid models completed.\033[0m')
 
-flux_repo = "camenduru/FLUX.1-dev-diffusers"
-flux_pipe = FluxPipeline.from_pretrained(
-    flux_repo,
-    transformer=None,
-    torch_dtype=torch.bfloat16,
-).to("cuda")
-components = flux_pipe.components
-delete_model(flux_repo)
-# components = None
+components = None
+if IS_ZERO_GPU:
+    flux_repo = "camenduru/FLUX.1-dev-diffusers"
+    flux_pipe = FluxPipeline.from_pretrained(
+        flux_repo,
+        transformer=None,
+        torch_dtype=torch.bfloat16,
+    ).to("cuda")
+    components = flux_pipe.components
+    delete_model(flux_repo)
 
 #######################
 # GUI
@@ -132,7 +138,17 @@ diffusers.utils.logging.set_verbosity(40)
 warnings.filterwarnings(action="ignore", category=FutureWarning, module="diffusers")
 warnings.filterwarnings(action="ignore", category=UserWarning, module="diffusers")
 warnings.filterwarnings(action="ignore", category=FutureWarning, module="transformers")
-logger.setLevel(logging.DEBUG)
+
+parser = ArgumentParser(description='DiffuseCraft: Create images from text prompts.', add_help=True)
+parser.add_argument("--share", action="store_true", dest="share_enabled", default=False, help="Enable sharing")
+parser.add_argument('--theme', type=str, default="NoCrypt/miku", help='Set the theme (default: NoCrypt/miku)')
+parser.add_argument("--ssr", action="store_true", help="Enable SSR (Server-Side Rendering)")
+parser.add_argument("--log-level", type=str, default="INFO", choices=["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"], help="Set logging level (default: INFO)")
+args = parser.parse_args()
+
+logger.setLevel(
+    "INFO" if IS_ZERO_GPU else getattr(logging, args.log_level.upper())
+)
 
 CSS = """
 .contain { display: flex; flex-direction: column; }
@@ -142,6 +158,12 @@ CSS = """
 """
 
 
+def lora_chk(lora_):
+    if isinstance(lora_, str) and lora_.strip() not in ["", "None"]:
+        return lora_
+    return None
+
+
 class GuiSD:
     def __init__(self, stream=True):
         self.model = None
@@ -157,6 +179,15 @@ class GuiSD:
             removal_candidate = self.inventory.pop(0)
             delete_model(removal_candidate)
 
+        # Cleanup after 60 seconds of inactivity
+        lowPrioCleanup = max((datetime.now() - self.last_load).total_seconds(), 0) > 60
+        if lowPrioCleanup and not self.status_loading and get_used_storage_gb(CACHE_HF_ROOT) > (storage_floor_gb * 2):
+            print("Cleaning up Hugging Face cache...")
+            clear_hf_cache()
+            self.inventory = [
+                m for m in self.inventory if os.path.exists(m)
+            ]
+
     def update_inventory(self, model_name):
         if model_name not in single_file_model_list:
             self.inventory = [
@@ -167,15 +198,21 @@ class GuiSD:
     def load_new_model(self, model_name, vae_model, task, controlnet_model, progress=gr.Progress(track_tqdm=True)):
 
         # download link model > model_name
+        if model_name.startswith("http"):
+            yield f"Downloading model: {model_name}"
+            model_name = download_things(DIRECTORY_MODELS, model_name, HF_TOKEN, CIVITAI_API_KEY)
+            if not model_name:
+                raise ValueError("Error retrieving model information from URL")
 
-        self.update_storage_models()
+        if IS_ZERO_GPU:
+            self.update_storage_models()
 
         vae_model = vae_model if vae_model != "None" else None
         model_type = get_model_type(model_name)
         dtype_model = torch.bfloat16 if model_type == "FLUX" else torch.float16
 
         if not os.path.exists(model_name):
-            print("debug", model_name, vae_model, task, controlnet_model)
+            logger.debug(f"model_name={model_name}, vae_model={vae_model}, task={task}, controlnet_model={controlnet_model}")
             _ = download_diffuser_repo(
                 repo_name=model_name,
                 model_type=model_type,
@@ -220,10 +257,10 @@ class GuiSD:
                     type_model_precision=dtype_model,
                     retain_task_model_in_cache=False,
                     controlnet_model=controlnet_model,
-                    device="cpu",
+                    device="cpu" if IS_ZERO_GPU else None,
                     env_components=components,
                 )
-                self.model.advanced_params(image_preprocessor_cuda_active=True)
+                self.model.advanced_params(image_preprocessor_cuda_active=IS_GPU_MODE)
             else:
                 if self.model.base_model_id != model_name:
                     load_now_time = datetime.now()
@@ -233,7 +270,8 @@ class GuiSD:
                         print("Waiting for the previous model's time ops...")
                         time.sleep(9 - elapsed_time)
 
-                self.model.device = torch.device("cpu")
+                if IS_ZERO_GPU:
+                    self.model.device = torch.device("cpu")
                 self.model.load_pipe(
                     model_name,
                     task_name=TASK_STABLEPY[task],
@@ -387,7 +425,7 @@ class GuiSD:
         vae_msg = f"VAE: {vae_model}" if vae_model else ""
         msg_lora = ""
 
-        print("Config model:", model_name, vae_model, loras_list)
+        logger.debug(f"Config model: {model_name}, {vae_model}, {loras_list}")
 
         task = TASK_STABLEPY[task]
 
@@ -485,19 +523,19 @@ class GuiSD:
             "distance_threshold": distance_threshold,
             "recolor_gamma_correction": float(recolor_gamma_correction),
             "tile_blur_sigma": int(tile_blur_sigma),
-            "lora_A": lora1 if lora1 != "None" else None,
+            "lora_A": lora_chk(lora1),
             "lora_scale_A": lora_scale1,
-            "lora_B": lora2 if lora2 != "None" else None,
+            "lora_B": lora_chk(lora2),
             "lora_scale_B": lora_scale2,
-            "lora_C": lora3 if lora3 != "None" else None,
+            "lora_C": lora_chk(lora3),
             "lora_scale_C": lora_scale3,
-            "lora_D": lora4 if lora4 != "None" else None,
+            "lora_D": lora_chk(lora4),
             "lora_scale_D": lora_scale4,
-            "lora_E": lora5 if lora5 != "None" else None,
+            "lora_E": lora_chk(lora5),
             "lora_scale_E": lora_scale5,
-            "lora_F": lora6 if lora6 != "None" else None,
+            "lora_F": lora_chk(lora6),
             "lora_scale_F": lora_scale6,
-            "lora_G": lora7 if lora7 != "None" else None,
+            "lora_G": lora_chk(lora7),
             "lora_scale_G": lora_scale7,
             "textual_inversion": embed_list if textual_inversion else [],
             "syntax_weights": syntax_weights,  # "Classic"
@@ -555,11 +593,11 @@ class GuiSD:
         # kwargs for diffusers pipeline
         if guidance_rescale:
             pipe_params["guidance_rescale"] = guidance_rescale
-
-        self.model.device = torch.device("cuda:0")
-        if hasattr(self.model.pipe, "transformer") and loras_list != ["None"] * self.model.num_loras:
-            self.model.pipe.transformer.to(self.model.device)
-            print("transformer to cuda")
+        if IS_ZERO_GPU:
+            self.model.device = torch.device("cuda:0")
+            if hasattr(self.model.pipe, "transformer") and loras_list != ["None"] * self.model.num_loras:
+                self.model.pipe.transformer.to(self.model.device)
+                logger.debug("transformer to cuda")
 
         actual_progress = 0
         info_images = gr.update()
@@ -589,7 +627,7 @@ class GuiSD:
 
                 download_links = "<br>".join(
                     [
-                        f'<a href="{path.replace("/images/", "/file=/home/user/app/images/")}" download="{os.path.basename(path)}">Download Image {i + 1}</a>'
+                        f'<a href="{path.replace("/images/", f"/gradio_api/file={allowed_path}/")}" download="{os.path.basename(path)}">Download Image {i + 1}</a>'
                         for i, path in enumerate(image_path)
                     ]
                 )
@@ -698,7 +736,8 @@ def sd_gen_generate_pipeline(*args):
 
 @spaces.GPU(duration=15)
 def process_upscale(image, upscaler_name, upscaler_size):
-    if image is None: return None
+    if image is None:
+        return None
 
     from stablepy.diffusers_vanilla.utils import save_pil_image_with_metadata
     from stablepy import load_upscaler_model
@@ -715,7 +754,7 @@ def process_upscale(image, upscaler_name, upscaler_size):
 
         name_upscaler = f"./{DIRECTORY_UPSCALERS}/{name_upscaler.split('/')[-1]}"
 
-    scaler_beta = load_upscaler_model(model=name_upscaler, tile=0, tile_overlap=8, device="cuda", half=True)
+    scaler_beta = load_upscaler_model(model=name_upscaler, tile=(0 if IS_ZERO_GPU else 192), tile_overlap=8, device=("cuda" if IS_GPU_MODE else "cpu"), half=IS_GPU_MODE)
     image_up = scaler_beta.upscale(image, upscaler_size, True)
 
     image_path = save_pil_image_with_metadata(image_up, f'{os.getcwd()}/up_images', exif_image)
@@ -724,11 +763,11 @@ def process_upscale(image, upscaler_name, upscaler_size):
 
 
 # https://huggingface.co/spaces/BestWishYsh/ConsisID-preview-Space/discussions/1#674969a022b99c122af5d407
-dynamic_gpu_duration.zerogpu = True
-sd_gen_generate_pipeline.zerogpu = True
+# dynamic_gpu_duration.zerogpu = True
+# sd_gen_generate_pipeline.zerogpu = True
 sd_gen = GuiSD()
 
-with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
+with gr.Blocks(theme=args.theme, css=CSS, fill_width=True, fill_height=False, delete_cache=delete_cache_time) as app:
     gr.Markdown("# 🧩 DiffuseCraft")
     gr.Markdown(SUBTITLE_GUI)
     with gr.Tab("Generation"):
@@ -777,7 +816,7 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
 
                 actual_task_info = gr.HTML()
 
-                with gr.Row(equal_height=False, variant="default"):
+                with gr.Row(equal_height=False, variant="default", visible=IS_ZERO_GPU):
                     gpu_duration_gui = gr.Number(minimum=5, maximum=240, value=59, show_label=False, container=False, info="GPU time duration (seconds)")
                     with gr.Column():
                         verbose_info_gui = gr.Checkbox(value=False, container=False, label="Status info")
@@ -813,7 +852,22 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                             "Schedule type": gr.update(value="Automatic"),
                             "PAG": gr.update(value=.0),
                             "FreeU": gr.update(value=False),
+                            "Hires upscaler": gr.update(),
+                            "Hires upscale": gr.update(),
+                            "Hires steps": gr.update(),
+                            "Hires denoising strength": gr.update(),
+                            "Hires CFG": gr.update(),
+                            "Hires sampler": gr.update(),
+                            "Hires schedule type": gr.update(),
+                            "Image resolution": gr.update(value=1024),
+                            "Strength": gr.update(),
                         }
+
+                        # Generate up to 7 LoRAs
+                        for i in range(1, 8):
+                            valid_receptors[f"Lora_{i}"] = gr.update()
+                            valid_receptors[f"Lora_scale_{i}"] = gr.update()
+
                         valid_keys = list(valid_receptors.keys())
 
                         parameters = extract_parameters(base_prompt)
@@ -827,6 +881,36 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                                     parameters["Sampler"] = value_sampler
                                     parameters["Schedule type"] = s_type
 
+                        params_lora = []
+                        if ">" in parameters["prompt"] and "<" in parameters["prompt"]:
+                            params_lora = re.findall(r'<lora:[^>]+>', parameters["prompt"])
+                        if "Loras" in parameters:
+                            params_lora += re.findall(r'<lora:[^>]+>', parameters["Loras"])
+
+                        if params_lora:
+                            parsed_params = []
+                            for tag_l in params_lora:
+                                try:
+                                    inner = tag_l.strip("<>")        # remove < >
+                                    _, data_l = inner.split(":", 1)  # remove the "lora:" part
+                                    parts_l = data_l.split(":")
+
+                                    name_l = parts_l[0]
+                                    weight_l = float(parts_l[1]) if len(parts_l) > 1 else 1.0  # default weight = 1.0
+
+                                    parsed_params.append((name_l, weight_l))
+                                except Exception as e:
+                                    print(f"Error parsing LoRA tag {tag_l}: {e}")
+
+                            num_lora = 1
+                            for parsed_l, parsed_s in parsed_params:
+                                filtered_loras = [m for m in lora_model_list if parsed_l in m]
+                                if filtered_loras:
+                                    parameters[f"Lora_{num_lora}"] = filtered_loras[0]
+                                    parameters[f"Lora_scale_{num_lora}"] = parsed_s
+                                    num_lora += 1
+
+                        # continue = discard new value
                         for key, val in parameters.items():
                             # print(val)
                             if key in valid_keys:
@@ -834,9 +918,12 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                                     if key == "Sampler":
                                         if val not in scheduler_names:
                                             continue
-                                    if key == "Schedule type":
+                                    if key in ["Schedule type", "Hires schedule type"]:
                                         if val not in SCHEDULE_TYPE_OPTIONS:
-                                            val = "Automatic"
+                                            continue
+                                    if key == "Hires sampler":
+                                        if val not in POST_PROCESSING_SAMPLER:
+                                            continue
                                     elif key == "Clip skip":
                                         if "," in str(val):
                                             val = val.replace(",", "")
@@ -844,15 +931,15 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                                             val = True
                                     if key == "prompt":
                                         if ">" in val and "<" in val:
-                                            val = re.sub(r'<[^>]+>', '', val)
+                                            val = re.sub(r'<[^>]+>', '', val)  # Delete html and loras
                                             print("Removed LoRA written in the prompt")
                                     if key in ["prompt", "neg_prompt"]:
                                         val = re.sub(r'\s+', ' ', re.sub(r',+', ',', val)).strip()
-                                    if key in ["Steps", "width", "height", "Seed"]:
+                                    if key in ["Steps", "width", "height", "Seed", "Hires steps", "Image resolution"]:
                                         val = int(val)
                                     if key == "FreeU":
                                         val = True
-                                    if key in ["CFG scale", "PAG"]:
+                                    if key in ["CFG scale", "PAG", "Hires upscale", "Hires denoising strength", "Hires CFG", "Strength"]:
                                         val = float(val)
                                     if key == "Model":
                                         filtered_models = [m for m in model_list if val in m]
@@ -860,8 +947,12 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                                             val = filtered_models[0]
                                         else:
                                             val = name_model
+                                    if key == "Hires upscaler":
+                                        if val not in UPSCALER_KEYS:
+                                            continue
                                     if key == "Seed":
                                         continue
+
                                     valid_receptors[key] = gr.update(value=val)
                                     # print(val, type(val))
                                     # print(valid_receptors)
@@ -869,24 +960,6 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                                     print(str(e))
                         return [value for value in valid_receptors.values()]
 
-                    set_params_gui.click(
-                        run_set_params_gui, [prompt_gui, model_name_gui], [
-                            prompt_gui,
-                            neg_prompt_gui,
-                            steps_gui,
-                            img_width_gui,
-                            img_height_gui,
-                            seed_gui,
-                            sampler_gui,
-                            cfg_gui,
-                            clip_skip_gui,
-                            model_name_gui,
-                            schedule_type_gui,
-                            pag_scale_gui,
-                            free_u_gui,
-                        ],
-                    )
-
                     def run_clear_prompt_gui():
                         return gr.update(value=""), gr.update(value="")
                     clear_prompt_gui.click(
@@ -899,7 +972,7 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                         run_set_random_seed, [], seed_gui
                     )
 
-                num_images_gui = gr.Slider(minimum=1, maximum=5, step=1, value=1, label="Images")
+                num_images_gui = gr.Slider(minimum=1, maximum=(5 if IS_ZERO_GPU else 20), step=1, value=1, label="Images")
                 prompt_syntax_gui = gr.Dropdown(label="Prompt Syntax", choices=PROMPT_W_OPTIONS, value=PROMPT_W_OPTIONS[1][1])
                 vae_model_gui = gr.Dropdown(label="VAE Model", choices=vae_model_list, value=vae_model_list[0])
 
@@ -907,7 +980,7 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
 
                     upscaler_model_path_gui = gr.Dropdown(label="Upscaler", choices=UPSCALER_KEYS, value=UPSCALER_KEYS[0])
                     upscaler_increases_size_gui = gr.Slider(minimum=1.1, maximum=4., step=0.1, value=1.2, label="Upscale by")
-                    upscaler_tile_size_gui = gr.Slider(minimum=0, maximum=512, step=16, value=0, label="Upscaler Tile Size", info="0 = no tiling")
+                    upscaler_tile_size_gui = gr.Slider(minimum=0, maximum=512, step=16, value=(0 if IS_ZERO_GPU else 192), label="Upscaler Tile Size", info="0 = no tiling")
                     upscaler_tile_overlap_gui = gr.Slider(minimum=0, maximum=48, step=1, value=8, label="Upscaler Tile Overlap")
                     hires_steps_gui = gr.Slider(minimum=0, value=30, maximum=100, step=1, label="Hires Steps")
                     hires_denoising_strength_gui = gr.Slider(minimum=0.1, maximum=1.0, step=0.01, value=0.55, label="Hires Denoising Strength")
@@ -924,7 +997,8 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                         return gr.Dropdown(label=label, choices=lora_model_list, value="None", allow_custom_value=True, visible=visible)
 
                     def lora_scale_slider(label, visible=True):
-                        return gr.Slider(minimum=-2, maximum=2, step=0.01, value=0.33, label=label, visible=visible)
+                        val_lora = 2 if IS_ZERO_GPU else 8
+                        return gr.Slider(minimum=-val_lora, maximum=val_lora, step=0.01, value=0.33, label=label, visible=visible)
 
                     lora1_gui = lora_dropdown("Lora1")
                     lora_scale_1_gui = lora_scale_slider("Lora Scale 1")
@@ -936,10 +1010,10 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                     lora_scale_4_gui = lora_scale_slider("Lora Scale 4")
                     lora5_gui = lora_dropdown("Lora5")
                     lora_scale_5_gui = lora_scale_slider("Lora Scale 5")
-                    lora6_gui = lora_dropdown("Lora6", visible=False)
-                    lora_scale_6_gui = lora_scale_slider("Lora Scale 6", visible=False)
-                    lora7_gui = lora_dropdown("Lora7", visible=False)
-                    lora_scale_7_gui = lora_scale_slider("Lora Scale 7", visible=False)
+                    lora6_gui = lora_dropdown("Lora6", visible=(not IS_ZERO_GPU))
+                    lora_scale_6_gui = lora_scale_slider("Lora Scale 6", visible=(not IS_ZERO_GPU))
+                    lora7_gui = lora_dropdown("Lora7", visible=(not IS_ZERO_GPU))
+                    lora_scale_7_gui = lora_scale_slider("Lora Scale 7", visible=(not IS_ZERO_GPU))
 
                     with gr.Accordion("From URL", open=False, visible=True):
                         text_lora = gr.Textbox(
@@ -948,7 +1022,7 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                             lines=1,
                             info="It has to be .safetensors files, and you can also download them from Hugging Face.",
                         )
-                        romanize_text = gr.Checkbox(value=False, label="Transliterate name", visible=False)
+                        romanize_text = gr.Checkbox(value=False, label="Transliterate name", visible=(not IS_ZERO_GPU))
                         button_lora = gr.Button("Get and Refresh the LoRA Lists")
                         new_lora_status = gr.HTML()
                         button_lora.click(
@@ -1013,8 +1087,8 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                     preprocess_resolution_gui = gr.Slider(minimum=64, maximum=2048, step=64, value=512, label="Preprocessor Resolution")
                     low_threshold_gui = gr.Slider(minimum=1, maximum=255, step=1, value=100, label="'CANNY' low threshold")
                     high_threshold_gui = gr.Slider(minimum=1, maximum=255, step=1, value=200, label="'CANNY' high threshold")
-                    value_threshold_gui = gr.Slider(minimum=1, maximum=2.0, step=0.01, value=0.1, label="'MLSD' Hough value threshold")
-                    distance_threshold_gui = gr.Slider(minimum=1, maximum=20.0, step=0.01, value=0.1, label="'MLSD' Hough distance threshold")
+                    value_threshold_gui = gr.Slider(minimum=0.0, maximum=2.0, step=0.01, value=0.1, label="'MLSD' Hough value threshold")
+                    distance_threshold_gui = gr.Slider(minimum=0.0, maximum=20.0, step=0.01, value=0.1, label="'MLSD' Hough distance threshold")
                     recolor_gamma_correction_gui = gr.Number(minimum=0., maximum=25., value=1., step=0.001, label="'RECOLOR' gamma correction")
                     tile_blur_sigma_gui = gr.Number(minimum=0, maximum=100, value=9, step=1, label="'TILE' blur sigma")
 
@@ -1049,7 +1123,7 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                         gr.Info(f"{len(sd_gen.model.STYLE_NAMES)} styles loaded")
                         return gr.update(value=None, choices=sd_gen.model.STYLE_NAMES)
 
-                    style_button.click(load_json_style_file, [style_json_gui], [style_prompt_gui])                        
+                    style_button.click(load_json_style_file, [style_json_gui], [style_prompt_gui])
 
                 with gr.Accordion("Textual inversion", open=False, visible=False):
                     active_textual_inversion_gui = gr.Checkbox(value=False, label="Active Textual Inversion in prompt")
@@ -1099,20 +1173,62 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                     hires_before_adetailer_gui = gr.Checkbox(value=False, label="Hires Before Adetailer")
                     hires_after_adetailer_gui = gr.Checkbox(value=True, label="Hires After Adetailer")
                     generator_in_cpu_gui = gr.Checkbox(value=False, label="Generator in CPU")
+                    with gr.Column(visible=(not IS_ZERO_GPU)):
+                        image_storage_location_gui = gr.Textbox(value=img_path, label="Image Storage Location")
+                        disable_progress_bar_gui = gr.Checkbox(value=False, label="Disable Progress Bar")
+                        leave_progress_bar_gui = gr.Checkbox(value=True, label="Leave Progress Bar")
 
                 with gr.Accordion("More settings", open=False, visible=False):
                     loop_generation_gui = gr.Slider(minimum=1, value=1, label="Loop Generation")
                     retain_task_cache_gui = gr.Checkbox(value=False, label="Retain task model in cache")
-                    leave_progress_bar_gui = gr.Checkbox(value=True, label="Leave Progress Bar")
-                    disable_progress_bar_gui = gr.Checkbox(value=False, label="Disable Progress Bar")
                     display_images_gui = gr.Checkbox(value=False, label="Display Images")
                     image_previews_gui = gr.Checkbox(value=True, label="Image Previews")
-                    image_storage_location_gui = gr.Textbox(value="./images", label="Image Storage Location")
                     retain_compel_previous_load_gui = gr.Checkbox(value=False, label="Retain Compel Previous Load")
                     retain_detailfix_model_previous_load_gui = gr.Checkbox(value=False, label="Retain Detailfix Model Previous Load")
                     retain_hires_model_previous_load_gui = gr.Checkbox(value=False, label="Retain Hires Model Previous Load")
                     xformers_memory_efficient_attention_gui = gr.Checkbox(value=False, label="Xformers Memory Efficient Attention")
 
+                set_params_gui.click(
+                    run_set_params_gui, [prompt_gui, model_name_gui], [
+                        prompt_gui,
+                        neg_prompt_gui,
+                        steps_gui,
+                        img_width_gui,
+                        img_height_gui,
+                        seed_gui,
+                        sampler_gui,
+                        cfg_gui,
+                        clip_skip_gui,
+                        model_name_gui,
+                        schedule_type_gui,
+                        pag_scale_gui,
+                        free_u_gui,
+                        upscaler_model_path_gui,
+                        upscaler_increases_size_gui,
+                        hires_steps_gui,
+                        hires_denoising_strength_gui,
+                        hires_guidance_scale_gui,
+                        hires_sampler_gui,
+                        hires_schedule_type_gui,
+                        image_resolution_gui,
+                        strength_gui,
+                        lora1_gui,
+                        lora_scale_1_gui,
+                        lora2_gui,
+                        lora_scale_2_gui,
+                        lora3_gui,
+                        lora_scale_3_gui,
+                        lora4_gui,
+                        lora_scale_4_gui,
+                        lora5_gui,
+                        lora_scale_5_gui,
+                        lora6_gui,
+                        lora_scale_6_gui,
+                        lora7_gui,
+                        lora_scale_7_gui,
+                    ],
+                )
+
         with gr.Accordion("Examples and help", open=False, visible=True):
             gr.Markdown(HELP_GUI)
             gr.Markdown(EXAMPLES_GUI_HELP)
@@ -1168,10 +1284,21 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
                             # "hsl(360, 120, 120)" # in fact any valid colorstring
                         ]
                     ),
-                    eraser=gr.Eraser(default_size="16")
+                    eraser=gr.Eraser(default_size="16"),
+                    render=True,
+                    visible=False,
+                    interactive=False,
                 )
+
+                show_canvas = gr.Button("SHOW INPAINT CANVAS")
+
+                def change_visibility_canvas():
+                    return gr.update(visible=True, interactive=True), gr.update(visible=False)
+                show_canvas.click(change_visibility_canvas, [], [image_base, show_canvas])
+
                 invert_mask = gr.Checkbox(value=False, label="Invert mask")
                 btn = gr.Button("Create mask")
+
             with gr.Column(scale=1):
                 img_source = gr.Image(interactive=False)
                 img_result = gr.Image(label="Mask image", show_label=True, interactive=False)
@@ -1363,10 +1490,12 @@ with gr.Blocks(theme="NoCrypt/miku", css=CSS) as app:
         show_progress="minimal",
     )
 
-app.queue()
-
-app.launch(
-    show_error=True,
-    debug=True,
-    allowed_paths=["./images/"],
-)
+if __name__ == "__main__":
+    app.queue()
+    app.launch(
+        show_error=True,
+        share=args.share_enabled,
+        debug=True,
+        ssr_mode=args.ssr,
+        allowed_paths=[allowed_path],
+    )

constants.py

@@ -9,6 +9,8 @@ from stablepy import (
     IP_ADAPTERS_SDXL,
 )
 
+IS_ZERO_GPU = bool(os.getenv("SPACES_ZERO_GPU"))
+
 # - **Download Models**
 DOWNLOAD_MODEL = "https://huggingface.co/TechnoByte/MilkyWonderland/resolve/main/milkyWonderland_v40.safetensors"
 
@@ -23,12 +25,12 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'Laxhar/noobai-XL-1.1',
     'Laxhar/noobai-XL-Vpred-1.0',
     'black-forest-labs/FLUX.1-dev',
+    'black-forest-labs/FLUX.1-Krea-dev',
     'John6666/blue-pencil-flux1-v021-fp8-flux',
     'John6666/wai-ani-flux-v10forfp8-fp8-flux',
     'John6666/xe-anime-flux-v04-fp8-flux',
     'John6666/lyh-anime-flux-v2a1-fp8-flux',
     'John6666/carnival-unchained-v10-fp8-flux',
-    'John6666/iniverse-mix-xl-sfwnsfw-fluxdfp16nsfwv11-fp8-flux',
     'Freepik/flux.1-lite-8B-alpha',
     'shauray/FluxDev-HyperSD-merged',
     'mikeyandfriends/PixelWave_FLUX.1-dev_03',
@@ -37,23 +39,19 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     # 'ostris/OpenFLUX.1',
     'shuttleai/shuttle-3-diffusion',
     'Laxhar/noobai-XL-1.0',
-    'John6666/noobai-xl-nai-xl-epsilonpred10version-sdxl',
     'Laxhar/noobai-XL-0.77',
     'John6666/noobai-xl-nai-xl-epsilonpred075version-sdxl',
     'Laxhar/noobai-XL-0.6',
     'John6666/noobai-xl-nai-xl-epsilonpred05version-sdxl',
     'John6666/noobai-cyberfix-v10-sdxl',
     'John6666/noobaiiter-xl-vpred-v075-sdxl',
-    'John6666/ntr-mix-illustrious-xl-noob-xl-v40-sdxl',
-    'John6666/ntr-mix-illustrious-xl-noob-xl-ntrmix35-sdxl',
-    'John6666/ntr-mix-illustrious-xl-noob-xl-v777-sdxl',
-    'John6666/ntr-mix-illustrious-xl-noob-xl-v777forlora-sdxl',
+    'John6666/ripplemix-noob-vpred10-illustrious01-v14-sdxl',
+    'John6666/sigmaih-15-sdxl',
     'John6666/ntr-mix-illustrious-xl-noob-xl-xi-sdxl',
     'John6666/ntr-mix-illustrious-xl-noob-xl-xii-sdxl',
     'John6666/ntr-mix-illustrious-xl-noob-xl-xiii-sdxl',
     'John6666/mistoon-anime-v10illustrious-sdxl',
-    'John6666/hassaku-xl-illustrious-v10-sdxl',
-    'John6666/hassaku-xl-illustrious-v10style-sdxl',
+    'John6666/hassaku-xl-illustrious-v22-sdxl',
     'John6666/haruki-mix-illustrious-v10-sdxl',
     'John6666/noobreal-v10-sdxl',
     'John6666/complicated-noobai-merge-vprediction-sdxl',
@@ -64,6 +62,7 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'Laxhar/noobai-XL-Vpred-0.65',
     'Laxhar/noobai-XL-Vpred-0.6',
     'John6666/cat-tower-noobai-xl-checkpoint-v14vpred-sdxl',
+    'John6666/cat-tower-noobai-xl-checkpoint-v15vpred-sdxl',
     'John6666/noobai-xl-nai-xl-vpred05version-sdxl',
     'John6666/noobai-fusion2-vpred-itercomp-v1-sdxl',
     'John6666/noobai-xl-nai-xl-vpredtestversion-sdxl',
@@ -74,19 +73,34 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'John6666/obsession-illustriousxl-v21-sdxl',
     'John6666/obsession-illustriousxl-v30-sdxl',
     'John6666/obsession-illustriousxl-v31-sdxl',
+    'John6666/one-obsession-13-sdxl',
+    'John6666/one-obsession-14-24d-sdxl',
+    'John6666/one-obsession-15-noobai-sdxl',
+    'John6666/one-obsession-v16-noobai-sdxl',
+    'John6666/prefect-illustrious-xl-v3-sdxl',
     'John6666/wai-nsfw-illustrious-v70-sdxl',
+    'John6666/wai-nsfw-illustrious-sdxl-v140-sdxl',
     'John6666/illustrious-pony-mix-v3-sdxl',
-    'John6666/nova-anime-xl-illustriousv10-sdxl',
-    'John6666/nova-orange-xl-v30-sdxl',
+    'John6666/nova-anime-xl-il-v90-sdxl',
+    'John6666/nova-anime-xl-il-v110-sdxl',
+    'John6666/nova-orange-xl-re-v10-sdxl',
+    'John6666/nova-orange-xl-v110-sdxl',
+    'John6666/nova-orange-xl-re-v20-sdxl',
+    'John6666/nova-unreal-xl-v60-sdxl',
+    'John6666/nova-unreal-xl-v70-sdxl',
+    'John6666/nova-unreal-xl-v80-sdxl',
+    'John6666/nova-cartoon-xl-v40-sdxl',
     'John6666/silvermoon-mix03-illustrious-v10-sdxl',
     'eienmojiki/Anything-XL',
     'eienmojiki/Starry-XL-v5.2',
+    'votepurchase/plantMilkModelSuite_walnut',
     'John6666/meinaxl-v2-sdxl',
     'Eugeoter/artiwaifu-diffusion-2.0',
     'comin/IterComp',
-    'John6666/epicrealism-xl-vxiabeast-sdxl',
-    'John6666/epicrealism-xl-v10kiss2-sdxl',
     'John6666/epicrealism-xl-v8kiss-sdxl',
+    'John6666/epicrealism-xl-v10kiss2-sdxl',
+    'John6666/epicrealism-xl-vxiabeast-sdxl',
+    'John6666/epicrealism-xl-vxvii-crystal-clear-realism-sdxl',
     'misri/zavychromaxl_v80',
     'SG161222/RealVisXL_V4.0',
     'SG161222/RealVisXL_V5.0',
@@ -102,8 +116,10 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'John6666/ebara-mfcg-pony-mix-v12-sdxl',
     'John6666/t-ponynai3-v51-sdxl',
     'John6666/t-ponynai3-v65-sdxl',
+    'John6666/t-ponynai3-v7-sdxl',
     'John6666/prefect-pony-xl-v3-sdxl',
     'John6666/prefect-pony-xl-v4-sdxl',
+    'John6666/prefect-pony-xl-v50-sdxl',
     'John6666/mala-anime-mix-nsfw-pony-xl-v5-sdxl',
     'John6666/wai-ani-nsfw-ponyxl-v10-sdxl',
     'John6666/wai-real-mix-v11-sdxl',
@@ -111,13 +127,14 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'John6666/wai-c-v6-sdxl',
     'John6666/iniverse-mix-xl-sfwnsfw-pony-guofeng-v43-sdxl',
     'John6666/sifw-annihilation-xl-v2-sdxl',
+    'John6666/sifw-annihilation-xl-v305illustrious-beta-sdxl',
     'John6666/photo-realistic-pony-v5-sdxl',
     'John6666/pony-realism-v21main-sdxl',
     'John6666/pony-realism-v22main-sdxl',
-    'John6666/cyberrealistic-pony-v63-sdxl',
-    'John6666/cyberrealistic-pony-v64-sdxl',
+    'John6666/pony-realism-v23-ultra-sdxl',
     'John6666/cyberrealistic-pony-v65-sdxl',
     'John6666/cyberrealistic-pony-v7-sdxl',
+    'John6666/cyberrealistic-pony-v127-alternative-sdxl',
     'GraydientPlatformAPI/realcartoon-pony-diffusion',
     'John6666/nova-anime-xl-pony-v5-sdxl',
     'John6666/autismmix-sdxl-autismmix-pony-sdxl',
@@ -127,13 +144,15 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'John6666/duchaiten-pony-real-v11fix-sdxl',
     'John6666/duchaiten-pony-real-v20-sdxl',
     'John6666/duchaiten-pony-xl-no-score-v70-sdxl',
-    'Spestly/OdysseyXL-3.0',
-    'Spestly/OdysseyXL-4.0',
     'KBlueLeaf/Kohaku-XL-Zeta',
     'cagliostrolab/animagine-xl-3.1',
+    'cagliostrolab/animagine-xl-4.0',
     'yodayo-ai/kivotos-xl-2.0',
     'yodayo-ai/holodayo-xl-2.1',
     'yodayo-ai/clandestine-xl-1.0',
+    'https://huggingface.co/chemwolf/Karmix-XL-v0/resolve/main/Karmix-XL-v0.safetensors?download=true',
+    'https://civitai.com/api/download/models/128713?type=Model&format=SafeTensor&size=pruned&fp=fp16',
+    'https://civitai.com/models/30240?modelVersionId=125771',
     'digiplay/majicMIX_sombre_v2',
     'digiplay/majicMIX_realistic_v6',
     'digiplay/majicMIX_realistic_v7',
@@ -159,9 +178,9 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'GraydientPlatformAPI/realcartoon3d-17',
     'GraydientPlatformAPI/realcartoon-pixar11',
     'GraydientPlatformAPI/realcartoon-real17',
-    'nitrosocke/Ghibli-Diffusion',
 ]
 
+
 DIFFUSERS_FORMAT_LORAS = [
     "nerijs/animation2k-flux",
     "XLabs-AI/flux-RealismLora",
@@ -183,8 +202,11 @@ DIRECTORY_VAES = 'vaes'
 DIRECTORY_EMBEDS = 'embedings'
 DIRECTORY_UPSCALERS = 'upscalers'
 
-CACHE_HF = "/home/user/.cache/huggingface/hub/"
 STORAGE_ROOT = "/home/user/"
+CACHE_HF_ROOT = os.path.expanduser("~/.cache/huggingface")
+CACHE_HF = os.path.join(CACHE_HF_ROOT, "hub")
+if IS_ZERO_GPU:
+    os.environ["HF_HOME"] = CACHE_HF
 
 TASK_STABLEPY = {
     'txt2img': 'txt2img',
@@ -226,6 +248,7 @@ UPSCALER_DICT_GUI = {
     # "realesr-general-x4v3": "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth",
     # "realesr-general-wdn-x4v3": "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-wdn-x4v3.pth",
     "4x-UltraSharp": "https://huggingface.co/Shandypur/ESRGAN-4x-UltraSharp/resolve/main/4x-UltraSharp.pth",
+    "Real-ESRGAN-Anime-finetuning": "https://huggingface.co/danhtran2mind/Real-ESRGAN-Anime-finetuning/resolve/main/Real-ESRGAN-Anime-finetuning.pth",
     "4x_foolhardy_Remacri": "https://huggingface.co/FacehugmanIII/4x_foolhardy_Remacri/resolve/main/4x_foolhardy_Remacri.pth",
     "Remacri4xExtraSmoother": "https://huggingface.co/hollowstrawberry/upscalers-backup/resolve/main/ESRGAN/Remacri%204x%20ExtraSmoother.pth",
     "AnimeSharp4x": "https://huggingface.co/hollowstrawberry/upscalers-backup/resolve/main/ESRGAN/AnimeSharp%204x.pth",
@@ -359,9 +382,11 @@ SUBTITLE_GUI = (
     " to perform different tasks in image generation."
 )
 
+msg_zero = "" if not IS_ZERO_GPU else "- The current space runs on a ZERO GPU which is assigned for approximately 60 seconds; Therefore, if you submit expensive tasks, the operation may be canceled upon reaching the maximum allowed time with 'GPU TASK ABORTED'."
+
 HELP_GUI = (
-    """### Help:
-    - The current space runs on a ZERO GPU which is assigned for approximately 60 seconds; Therefore, if you submit expensive tasks, the operation may be canceled upon reaching the maximum allowed time with 'GPU TASK ABORTED'.
+    f"""### Help:
+    {msg_zero}
     - Distorted or strange images often result from high prompt weights, so it's best to use low weights and scales, and consider using Classic variants like 'Classic-original'.
     - For better results with Pony Diffusion, try using sampler DPM++ 1s or DPM2 with Compel or Classic prompt weights.
     """
@@ -485,7 +510,7 @@ EXAMPLES_GUI = [
         20,
         4.0,
         -1,
-        "loras/Coloring_book_-_LineArt.safetensors",
+        ("loras/Coloring_book_-_LineArt.safetensors" if os.path.exists("loras/Coloring_book_-_LineArt.safetensors") else "None"),
         1.0,
         "DPM++ 2M SDE",
         1024,
@@ -580,6 +605,7 @@ EXAMPLES_GUI = [
 RESOURCES = (
     """### Resources
     - John6666's space has some great features you might find helpful [link](https://huggingface.co/spaces/John6666/DiffuseCraftMod).
-    - You can also try the image generator in Colab’s free tier, which provides free GPU [link](https://github.com/R3gm/SD_diffusers_interactive).
+    - Try the image generator in Colab’s free tier, which provides free GPU [link](https://github.com/R3gm/SD_diffusers_interactive).
+    - `DiffuseCraft` in Colab:[link](https://github.com/R3gm/DiffuseCraft?tab=readme-ov-file#diffusecraft).
     """
-)
+)

image_processor.py

@@ -92,8 +92,8 @@ def preprocessor_tab():
                     pre_processor_resolution = gr.Slider(minimum=64, maximum=2048, step=64, value=512, label="Preprocessor Resolution")
                     pre_low_threshold = gr.Slider(minimum=1, maximum=255, step=1, value=100, label="'CANNY' low threshold")
                     pre_high_threshold = gr.Slider(minimum=1, maximum=255, step=1, value=200, label="'CANNY' high threshold")
-                    pre_value_threshold = gr.Slider(minimum=1, maximum=2.0, step=0.01, value=0.1, label="'MLSD' Hough value threshold")
-                    pre_distance_threshold = gr.Slider(minimum=1, maximum=20.0, step=0.01, value=0.1, label="'MLSD' Hough distance threshold")
+                    pre_value_threshold = gr.Slider(minimum=0., maximum=2.0, step=0.01, value=0.1, label="'MLSD' Hough value threshold")
+                    pre_distance_threshold = gr.Slider(minimum=0., maximum=20.0, step=0.01, value=0.1, label="'MLSD' Hough distance threshold")
                     pre_recolor_mode = gr.Dropdown(label="'RECOLOR' mode", choices=["luminance", "intensity"], value="luminance")
                     pre_recolor_gamma_correction = gr.Number(minimum=0., maximum=25., value=1., step=0.001, label="'RECOLOR' gamma correction")
                     pre_blur_k_size = gr.Number(minimum=0, maximum=100, value=9, step=1, label="'BLUR' sigma")

packages.txt

@@ -1,3 +1,3 @@
 git-lfs
-aria2 -y
+aria2
 ffmpeg

pre-requirements.txt

@@ -0,0 +1 @@
+pip>=23.0.0

requirements.txt

@@ -1,7 +1,13 @@
 stablepy==0.6.2
-torch==2.2.0
+torch==2.5.1
+diffusers
 gdown
 opencv-python
 unidecode
 pydantic==2.10.6
-huggingface_hub==0.29.3
+huggingface_hub
+hf_transfer
+hf_xet
+spaces
+gradio==5.44.1
+matplotlib-inline

utils.py

@@ -9,6 +9,7 @@ from constants import (
     DIRECTORY_LORAS,
     DIRECTORY_MODELS,
     DIFFUSECRAFT_CHECKPOINT_NAME,
+    CACHE_HF_ROOT,
     CACHE_HF,
     STORAGE_ROOT,
 )
@@ -28,6 +29,7 @@ from urllib3.util import Retry
 import shutil
 import subprocess
 
+IS_ZERO_GPU = bool(os.getenv("SPACES_ZERO_GPU"))
 USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:127.0) Gecko/20100101 Firefox/127.0'
 
 
@@ -66,7 +68,8 @@ class ModelInformation:
         )
         self.filename_url = self.filename_url if self.filename_url else ""
         self.description = json_data.get("description", "")
-        if self.description is None: self.description = ""
+        if self.description is None:
+            self.description = ""
         self.model_name = json_data.get("model", {}).get("name", "")
         self.model_type = json_data.get("model", {}).get("type", "")
         self.nsfw = json_data.get("model", {}).get("nsfw", False)
@@ -76,118 +79,175 @@ class ModelInformation:
         self.original_json = copy.deepcopy(json_data)
 
 
-def retrieve_model_info(url):
-    json_data = request_json_data(url)
-    if not json_data:
-        return None
-    model_descriptor = ModelInformation(json_data)
-    return model_descriptor
+def get_civit_params(url):
+    try:
+        json_data = request_json_data(url)
+        mdc = ModelInformation(json_data)
+        if mdc.download_url and mdc.filename_url:
+            return mdc.download_url, mdc.filename_url, mdc.model_url
+        else:
+            ValueError("Invalid Civitai model URL")
+    except Exception as e:
+        print(f"Error retrieving Civitai metadata: {e} — fallback to direct download")
+        return url, None, None
 
 
-def download_things(directory, url, hf_token="", civitai_api_key="", romanize=False):
-    url = url.strip()
-    downloaded_file_path = None
+def civ_redirect_down(url, dir_, civitai_api_key, romanize, alternative_name):
+    filename_base = filename = None
 
-    if "drive.google.com" in url:
-        original_dir = os.getcwd()
-        os.chdir(directory)
-        os.system(f"gdown --fuzzy {url}")
-        os.chdir(original_dir)
-    elif "huggingface.co" in url:
-        url = url.replace("?download=true", "")
-        # url = urllib.parse.quote(url, safe=':/')  # fix encoding
-        if "/blob/" in url:
-            url = url.replace("/blob/", "/resolve/")
-        user_header = f'"Authorization: Bearer {hf_token}"'
+    if alternative_name:
+        output_path = os.path.join(dir_, alternative_name)
+        if os.path.exists(output_path):
+            return output_path, alternative_name
 
-        filename = unidecode(url.split('/')[-1]) if romanize else url.split('/')[-1]
+    # Follow the redirect to get the actual download URL
+    curl_command = (
+        f'curl -L -sI --connect-timeout 5 --max-time 5 '
+        f'-H "Content-Type: application/json" '
+        f'-H "Authorization: Bearer {civitai_api_key}" "{url}"'
+    )
 
-        if hf_token:
-            os.system(f"aria2c --console-log-level=error --summary-interval=10 --header={user_header} -c -x 16 -k 1M -s 16 {url} -d {directory}  -o {filename}")
-        else:
-            os.system(f"aria2c --optimize-concurrent-downloads --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 {url} -d {directory}  -o {filename}")
+    headers = os.popen(curl_command).read()
 
-        downloaded_file_path = os.path.join(directory, filename)
+    # Look for the redirected "Location" URL
+    location_match = re.search(r'location: (.+)', headers, re.IGNORECASE)
 
-    elif "civitai.com" in url:
+    if location_match:
+        redirect_url = location_match.group(1).strip()
 
-        if not civitai_api_key:
-            print("\033[91mYou need an API key to download Civitai models.\033[0m")
-
-        model_profile = retrieve_model_info(url)
-        if (
-            model_profile is not None
-            and model_profile.download_url
-            and model_profile.filename_url
-        ):
-            url = model_profile.download_url
-            filename = unidecode(model_profile.filename_url) if romanize else model_profile.filename_url
-        else:
-            if "?" in url:
-                url = url.split("?")[0]
-            filename = ""
+        # Extract the filename from the redirect URL's "Content-Disposition"
+        filename_match = re.search(r'filename%3D%22(.+?)%22', redirect_url)
+        if filename_match:
+            encoded_filename = filename_match.group(1)
+            # Decode the URL-encoded filename
+            decoded_filename = urllib.parse.unquote(encoded_filename)
 
-        url_dl = url + f"?token={civitai_api_key}"
-        print(f"Filename: {filename}")
+            filename = unidecode(decoded_filename) if romanize else decoded_filename
+            # print(f"Filename redirect: {filename}")
 
-        param_filename = ""
-        if filename:
-            param_filename = f"-o '{filename}'"
+    filename_base = alternative_name if alternative_name else filename
+    if not filename_base:
+        return None, None
+    elif os.path.exists(os.path.join(dir_, filename_base)):
+        return os.path.join(dir_, filename_base), filename_base
 
-        aria2_command = (
-            f'aria2c --console-log-level=error --summary-interval=10 -c -x 16 '
-            f'-k 1M -s 16 -d "{directory}" {param_filename} "{url_dl}"'
-        )
+    aria2_command = (
+        f'aria2c --console-log-level=error --summary-interval=10 -c -x 16 '
+        f'-k 1M -s 16 -d "{dir_}" -o "{filename_base}" "{redirect_url}"'
+    )
+    r_code = os.system(aria2_command)  # noqa
+
+    # if r_code != 0:
+    #     raise RuntimeError(f"Failed to download file: {filename_base}. Error code: {r_code}")
+
+    output_path = os.path.join(dir_, filename_base)
+    if not os.path.exists(output_path):
+        return None, filename_base
+
+    return output_path, filename_base
+
+
+def civ_api_down(url, dir_, civitai_api_key, civ_filename):
+    """
+    This method is susceptible to being blocked because it generates a lot of temp redirect links with aria2c.
+    If an API key limit is reached, generating a new API key and using it can fix the issue.
+    """
+    output_path = None
+
+    url_dl = url + f"?token={civitai_api_key}"
+    if not civ_filename:
+        aria2_command = f'aria2c -c -x 1 -s 1 -d "{dir_}" "{url_dl}"'
         os.system(aria2_command)
+    else:
+        output_path = os.path.join(dir_, civ_filename)
+        if not os.path.exists(output_path):
+            aria2_command = (
+                f'aria2c --console-log-level=error --summary-interval=10 -c -x 16 '
+                f'-k 1M -s 16 -d "{dir_}" -o "{civ_filename}" "{url_dl}"'
+            )
+            os.system(aria2_command)
+
+    return output_path
+
+
+def drive_down(url, dir_):
+    import gdown
+
+    output_path = None
 
-        if param_filename and os.path.exists(os.path.join(directory, filename)):
-            downloaded_file_path = os.path.join(directory, filename)
-
-        # # PLAN B
-        # # Follow the redirect to get the actual download URL
-        # curl_command = (
-        #     f'curl -L -sI --connect-timeout 5 --max-time 5 '
-        #     f'-H "Content-Type: application/json" '
-        #     f'-H "Authorization: Bearer {civitai_api_key}" "{url}"'
-        # )
-
-        # headers = os.popen(curl_command).read()
-
-        # # Look for the redirected "Location" URL
-        # location_match = re.search(r'location: (.+)', headers, re.IGNORECASE)
-
-        # if location_match:
-        #     redirect_url = location_match.group(1).strip()
-
-        #     # Extract the filename from the redirect URL's "Content-Disposition"
-        #     filename_match = re.search(r'filename%3D%22(.+?)%22', redirect_url)
-        #     if filename_match:
-        #         encoded_filename = filename_match.group(1)
-        #         # Decode the URL-encoded filename
-        #         decoded_filename = urllib.parse.unquote(encoded_filename)
-
-        #         filename = unidecode(decoded_filename) if romanize else decoded_filename
-        #         print(f"Filename: {filename}")
-
-        #         aria2_command = (
-        #             f'aria2c --console-log-level=error --summary-interval=10 -c -x 16 '
-        #             f'-k 1M -s 16 -d "{directory}" -o "{filename}" "{redirect_url}"'
-        #         )
-        #         return_code = os.system(aria2_command)
-
-        #         # if return_code != 0:
-        #         #     raise RuntimeError(f"Failed to download file: {filename}. Error code: {return_code}")
-        #         downloaded_file_path = os.path.join(directory, filename)
-        #         if not os.path.exists(downloaded_file_path):
-        #             downloaded_file_path = None
-
-        # if not downloaded_file_path:
-        #     # Old method
-        #     if "?" in url:
-        #         url = url.split("?")[0]
-        #     url = url + f"?token={civitai_api_key}"
-        #     os.system(f"aria2c --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 -d {directory} {url}")
+    drive_id, _ = gdown.parse_url.parse_url(url, warning=False)
+    dir_files = os.listdir(dir_)
 
+    for dfile in dir_files:
+        if drive_id in dfile:
+            output_path = os.path.join(dir_, dfile)
+            break
+
+    if not output_path:
+        original_path = gdown.download(url, f"{dir_}/", fuzzy=True)
+
+        dir_name, base_name = os.path.split(original_path)
+        name, ext = base_name.rsplit(".", 1)
+        new_name = f"{name}_{drive_id}.{ext}"
+        output_path = os.path.join(dir_name, new_name)
+
+        os.rename(original_path, output_path)
+
+    return output_path
+
+
+def hf_down(url, dir_, hf_token, romanize):
+    url = url.replace("?download=true", "")
+    # url = urllib.parse.quote(url, safe=':/')  # fix encoding
+
+    filename = unidecode(url.split('/')[-1]) if romanize else url.split('/')[-1]
+    output_path = os.path.join(dir_, filename)
+
+    if os.path.exists(output_path):
+        return output_path
+
+    if "/blob/" in url:
+        url = url.replace("/blob/", "/resolve/")
+
+    if hf_token:
+        user_header = f'"Authorization: Bearer {hf_token}"'
+        os.system(f"aria2c --console-log-level=error --summary-interval=10 --header={user_header} -c -x 16 -k 1M -s 16 {url} -d {dir_}  -o {filename}")
+    else:
+        os.system(f"aria2c --optimize-concurrent-downloads --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 {url} -d {dir_}  -o {filename}")
+
+    return output_path
+
+
+def download_things(directory, url, hf_token="", civitai_api_key="", romanize=False):
+    url = url.strip()
+    downloaded_file_path = None
+
+    if "drive.google.com" in url:
+        downloaded_file_path = drive_down(url, directory)
+    elif "huggingface.co" in url:
+        downloaded_file_path = hf_down(url, directory, hf_token, romanize)
+    elif "civitai.com" in url:
+        if not civitai_api_key:
+            msg = "You need an API key to download Civitai models."
+            print(f"\033[91m{msg}\033[0m")
+            gr.Warning(msg)
+            return None
+
+        url, civ_filename, civ_page = get_civit_params(url)
+        if civ_page and not IS_ZERO_GPU:
+            print(f"\033[92mCivitai model: {civ_filename} [page: {civ_page}]\033[0m")
+
+        downloaded_file_path, civ_filename = civ_redirect_down(url, directory, civitai_api_key, romanize, civ_filename)
+
+        if not downloaded_file_path:
+            msg = (
+                "Download failed.\n"
+                "If this is due to an API limit, generating a new API key may resolve the issue.\n"
+                "Attempting to download using the old method..."
+            )
+            print(msg)
+            gr.Warning(msg)
+            downloaded_file_path = civ_api_down(url, directory, civitai_api_key, civ_filename)
     else:
         os.system(f"aria2c --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 -d {directory} {url}")
 
@@ -216,14 +276,15 @@ def extract_parameters(input_string):
         if "Steps:" in input_string:
             input_string = input_string.replace("Steps:", "Negative prompt: Steps:")
         else:
-            print("Invalid metadata")
+            msg = "Generation data is invalid."
+            gr.Warning(msg)
+            print(msg)
             parameters["prompt"] = input_string
             return parameters
 
     parm = input_string.split("Negative prompt:")
     parameters["prompt"] = parm[0].strip()
     if "Steps:" not in parm[1]:
-        print("Steps not detected")
         parameters["neg_prompt"] = parm[1].strip()
         return parameters
     parm = parm[1].split("Steps:")
@@ -306,7 +367,8 @@ def get_model_type(repo_id: str):
             model = api.model_info(repo_id=repo_id, timeout=5.0)
             tags = model.tags
             for tag in tags:
-                if tag in MODEL_TYPE_CLASS.keys(): return MODEL_TYPE_CLASS.get(tag, default)
+                if tag in MODEL_TYPE_CLASS.keys():
+                    return MODEL_TYPE_CLASS.get(tag, default)
 
     except Exception:
         return default
@@ -433,9 +495,9 @@ def get_folder_size_gb(folder_path):
     return total_size_gb
 
 
-def get_used_storage_gb():
+def get_used_storage_gb(path_storage=STORAGE_ROOT):
     try:
-        used_gb = get_folder_size_gb(STORAGE_ROOT)
+        used_gb = get_folder_size_gb(path_storage)
         print(f"Used Storage: {used_gb:.2f} GB")
     except Exception as e:
         used_gb = 999
@@ -455,6 +517,21 @@ def delete_model(removal_candidate):
             shutil.rmtree(diffusers_model)
 
 
+def clear_hf_cache():
+    """
+    Clears the entire Hugging Face cache at ~/.cache/huggingface.
+    Hugging Face will re-download models as needed later.
+    """
+    try:
+        if os.path.exists(CACHE_HF_ROOT):
+            shutil.rmtree(CACHE_HF_ROOT, ignore_errors=True)
+            print(f"Hugging Face cache cleared: {CACHE_HF_ROOT}")
+        else:
+            print(f"No Hugging Face cache found at: {CACHE_HF_ROOT}")
+    except Exception as e:
+        print(f"Error clearing Hugging Face cache: {e}")
+
+
 def progress_step_bar(step, total):
     # Calculate the percentage for the progress bar width
     percentage = min(100, ((step / total) * 100))