update animagine xl 3

.gitattributes

@@ -1,39 +0,0 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ckpt filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.mlmodel filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.npy filter=lfs diff=lfs merge=lfs -text
-*.npz filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pickle filter=lfs diff=lfs merge=lfs -text
-*.pkl filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-*.safetensors filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tar filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tgz filter=lfs diff=lfs merge=lfs -text
-*.wasm filter=lfs diff=lfs merge=lfs -text
-*.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
-*.zst filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
-images/amelia-watson.png filter=lfs diff=lfs merge=lfs -text
-images/furina.png filter=lfs diff=lfs merge=lfs -text
-images/pastel-style.png filter=lfs diff=lfs merge=lfs -text
-images/ufotable-style.png filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -1,162 +0,0 @@
-gradio_cached_examples/
-
-# Byte-compiled / optimized / DLL files
-__pycache__/
-*.py[cod]
-*$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
-
-# 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
-
-# pdm
-#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
-#pdm.lock
-#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
-#   in version control.
-#   https://pdm.fming.dev/#use-with-ide
-.pdm.toml
-
-# 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
-.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/

.pre-commit-config.yaml

@@ -1,36 +0,0 @@
-repos:
-- repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v4.2.0
-  hooks:
-  - id: check-executables-have-shebangs
-  - id: check-json
-  - id: check-merge-conflict
-  - id: check-shebang-scripts-are-executable
-  - id: check-toml
-  - id: check-yaml
-  - id: double-quote-string-fixer
-  - id: end-of-file-fixer
-  - id: mixed-line-ending
-    args: ['--fix=lf']
-  - id: requirements-txt-fixer
-  - id: trailing-whitespace
-- repo: https://github.com/myint/docformatter
-  rev: v1.4
-  hooks:
-  - id: docformatter
-    args: ['--in-place']
-- repo: https://github.com/pycqa/isort
-  rev: 5.12.0
-  hooks:
-    - id: isort
-- repo: https://github.com/pre-commit/mirrors-mypy
-  rev: v0.991
-  hooks:
-    - id: mypy
-      args: ['--ignore-missing-imports']
-      additional_dependencies: ['types-python-slugify']
-- repo: https://github.com/google/yapf
-  rev: v0.32.0
-  hooks:
-  - id: yapf
-    args: ['--parallel', '--in-place']

.style.yapf

@@ -1,5 +0,0 @@
-[style]
-based_on_style = pep8
-blank_line_before_nested_class_or_def = false
-spaces_before_comment = 2
-split_before_logical_operator = true

.vscode/settings.json

@@ -1,18 +0,0 @@
-{
-    "python.linting.enabled": true,
-    "python.linting.flake8Enabled": true,
-    "python.linting.pylintEnabled": false,
-    "python.linting.lintOnSave": true,
-    "python.formatting.provider": "yapf",
-    "python.formatting.yapfArgs": [
-        "--style={based_on_style: pep8, indent_width: 4, blank_line_before_nested_class_or_def: false, spaces_before_comment: 2, split_before_logical_operator: true}"
-    ],
-    "[python]": {
-        "editor.formatOnType": true,
-        "editor.codeActionsOnSave": {
-            "source.organizeImports": true
-        }
-    },
-    "editor.formatOnSave": true,
-    "files.insertFinalNewline": true
-}

README.md

@@ -1,5 +1,5 @@
 ---
-title: Animagine XL 2.0
+title: Animagine XL 3.0
 emoji: 🌍
 colorFrom: gray
 colorTo: purple

app.py

@@ -16,6 +16,8 @@ import base64
 import safetensors
 from io import BytesIO
 from typing import Tuple
+from datetime import datetime
+from PIL import PngImagePlugin
 import gradio_user_history as gr_user_history
 from huggingface_hub import hf_hub_download
 from safetensors.torch import load_file
@@ -23,7 +25,6 @@ from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer
 from lora_diffusers import LoRANetwork, create_network_from_weights
 from diffusers.models import AutoencoderKL
 from diffusers import (
-    LCMScheduler,
     StableDiffusionXLPipeline,
     StableDiffusionXLImg2ImgPipeline,
     DPMSolverMultistepScheduler,
@@ -38,12 +39,10 @@ from diffusers import (
     UniPCMultistepScheduler,
 )
 
-DESCRIPTION = "Animagine XL 2.0"
-
+DESCRIPTION = "Animagine XL 3.0"
 if not torch.cuda.is_available():
     DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU. </p>"
 IS_COLAB = utils.is_google_colab() or os.getenv("IS_COLAB") == "1"
-ENABLE_REFINER_PROMPT = os.getenv("ENABLE_REFINER_PROMPT") == "1"
 MAX_SEED = np.iinfo(np.int32).max
 HF_TOKEN = os.getenv("HF_TOKEN")
 CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES") == "1"
@@ -52,7 +51,7 @@ MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "2048"))
 USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE") == "1"
 ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD") == "1"
 
-MODEL = os.getenv("MODEL", "Linaqruf/animagine-xl-2.0")
+MODEL = os.getenv("MODEL", "https://huggingface.co/Linaqruf/animagine-xl-3.0/blob/main/animagine-xl-3.0.safetensors")
 
 torch.backends.cudnn.deterministic = True
 torch.backends.cudnn.benchmark = False
@@ -60,17 +59,13 @@ torch.backends.cudnn.benchmark = False
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
 if torch.cuda.is_available():
-    if ENABLE_REFINER_PROMPT:
-        tokenizer = AutoTokenizer.from_pretrained("isek-ai/SDPrompt-RetNet-300M")
-        tuner = AutoModelForCausalLM.from_pretrained(
-            "isek-ai/SDPrompt-RetNet-300M",
-            trust_remote_code=True,
-        ).to(device)
     vae = AutoencoderKL.from_pretrained(
         "madebyollin/sdxl-vae-fp16-fix",
         torch_dtype=torch.float16,
     )
-    pipe = StableDiffusionXLPipeline.from_pretrained(
+    pipeline = StableDiffusionXLPipeline.from_single_file if MODEL.endswith(".safetensors") else StableDiffusionXLPipeline.from_pretrained
+    
+    pipe = pipeline(
         MODEL,
         vae=vae,
         torch_dtype=torch.float16,
@@ -100,7 +95,6 @@ def seed_everything(seed):
     torch.manual_seed(seed)
     torch.cuda.manual_seed_all(seed)
     np.random.seed(seed)
-    random.seed(seed)
     generator = torch.Generator()
     generator.manual_seed(seed)
     return generator
@@ -115,13 +109,6 @@ def get_image_path(base_path: str):
     return None
 
 
-def update_lcm_parameter(enable_lcm: bool = False):
-    if enable_lcm:
-        return (2, 8, gr.update(value="LCM"), gr.update(choices=["LCM"]))
-    else:
-        return (12, 50, gr.update(value="Euler a"), gr.update(choices=sampler_list))
-
-
 def update_selection(selected_state: gr.SelectData):
     lora_repo = sdxl_loras[selected_state.index]["repo"]
     lora_weight = sdxl_loras[selected_state.index]["multiplier"]
@@ -179,7 +166,6 @@ def get_scheduler(scheduler_config, name):
             scheduler_config
         ),
         "DDIM": lambda: DDIMScheduler.from_config(scheduler_config),
-        "LCM": lambda: LCMScheduler.from_config(scheduler_config),
     }
     return scheduler_map.get(name, lambda: None)()
 
@@ -194,10 +180,17 @@ def preprocess_prompt(
     style_name: str,
     positive: str,
     negative: str = "",
+    add_style: bool = True,
 ) -> Tuple[str, str]:
-    p, n = style_dict.get(style_name, styles["(None)"])
+    p, n = style_dict.get(style_name, style_dict["(None)"])
 
-    return p.format(prompt=positive), n + negative
+    if add_style and positive.strip():
+        formatted_positive = p.format(prompt=positive)
+    else:
+        formatted_positive = positive
+
+    combined_negative = n + negative
+    return formatted_positive, combined_negative
 
 
 def common_upscale(samples, width, height, upscale_method):
@@ -213,45 +206,6 @@ def upscale(samples, upscale_method, scale_by):
     return s
 
 
-def prompt_completion(
-    input_text,
-    max_new_tokens=128,
-    do_sample=True,
-    temperature=1.0,
-    top_p=0.95,
-    top_k=20,
-    repetition_penalty=1.2,
-    num_beams=1,
-):
-    try:
-        if input_text.strip() == "":
-            return ""
-
-        inputs = tokenizer(
-            f"<s>{input_text}", return_tensors="pt", add_special_tokens=False
-        )["input_ids"].to(device)
-
-        result = tuner.generate(
-            inputs,
-            max_new_tokens=max_new_tokens,
-            do_sample=do_sample,
-            temperature=temperature,
-            top_p=top_p,
-            top_k=top_k,
-            repetition_penalty=repetition_penalty,
-            num_beams=num_beams,
-        )
-
-        return tokenizer.batch_decode(result, skip_special_tokens=True)[0]
-
-    except Exception as e:
-        print(f"An error occured: {e}")
-        raise
-
-    finally:
-        free_memory()
-
-
 def load_and_convert_thumbnail(model_path: str):
     with safetensors.safe_open(model_path, framework="pt") as f:
         metadata = f.metadata()
@@ -263,6 +217,27 @@ def load_and_convert_thumbnail(model_path: str):
         return image
     return None
 
+def load_wildcard_files(wildcard_dir):
+    wildcard_files = {}
+    for file in os.listdir(wildcard_dir):
+        if file.endswith(".txt"):
+            key = f"__{file.split('.')[0]}__"  # Create a key like __character__
+            wildcard_files[key] = os.path.join(wildcard_dir, file)
+    return wildcard_files
+
+def get_random_line_from_file(file_path):
+    with open(file_path, 'r') as file:
+        lines = file.readlines()
+        if not lines:
+            return ""
+        return random.choice(lines).strip()
+
+def add_wildcard(prompt, wildcard_files):
+    for key, file_path in wildcard_files.items():
+        if key in prompt:
+            wildcard_line = get_random_line_from_file(file_path)
+            prompt = prompt.replace(key, wildcard_line)
+    return prompt
 
 def generate(
     prompt: str,
@@ -270,20 +245,19 @@ def generate(
     seed: int = 0,
     custom_width: int = 1024,
     custom_height: int = 1024,
-    guidance_scale: float = 12.0,
-    num_inference_steps: int = 50,
+    guidance_scale: float = 7.0,
+    num_inference_steps: int = 28,
     use_lora: bool = False,
     lora_weight: float = 1.0,
     selected_state: str = "",
-    enable_lcm: bool = False,
     sampler: str = "Euler a",
-    aspect_ratio_selector: str = "1024 x 1024",
+    aspect_ratio_selector: str = "896 x 1152",
     style_selector: str = "(None)",
     quality_selector: str = "Standard",
     use_upscaler: bool = False,
     upscaler_strength: float = 0.5,
     upscale_by: float = 1.5,
-    refine_prompt: bool = False,
+    add_quality_tags: bool = True,
     profile: gr.OAuthProfile | None = None,
     progress=gr.Progress(track_tqdm=True),
 ) -> PIL.Image.Image:
@@ -291,7 +265,6 @@ def generate(
 
     network = None
     network_state = {"current_lora": None, "multiplier": None}
-    adapter_id = "Linaqruf/lcm-lora-sdxl-rank1"
 
     width, height = aspect_ratio_handler(
         aspect_ratio_selector,
@@ -299,14 +272,11 @@ def generate(
         custom_height,
     )
 
-    if ENABLE_REFINER_PROMPT:
-        if refine_prompt:
-            if not prompt:
-                prompt = random.choice(["1girl, solo", "1boy, solo"])
-            prompt = prompt_completion(prompt)
+    prompt = add_wildcard(prompt, wildcard_files)
 
+    
     prompt, negative_prompt = preprocess_prompt(
-        quality_prompt, quality_selector, prompt, negative_prompt
+        quality_prompt, quality_selector, prompt, negative_prompt, add_quality_tags
     )
     prompt, negative_prompt = preprocess_prompt(
         styles, style_selector, prompt, negative_prompt
@@ -316,6 +286,7 @@ def generate(
         width = width - (width % 8)
     if height % 8 != 0:
         height = height - (height % 8)
+        
     if use_lora:
         if not selected_state:
             raise Exception("You must Select a LoRA")
@@ -354,9 +325,6 @@ def generate(
                 "multiplier": None,
             }
 
-    if enable_lcm:
-        pipe.load_lora_weights(adapter_id)
-
     backup_scheduler = pipe.scheduler
     pipe.scheduler = get_scheduler(pipe.scheduler.config, sampler)
 
@@ -371,10 +339,9 @@ def generate(
         "num_inference_steps": num_inference_steps,
         "seed": seed,
         "sampler": sampler,
-        "enable_lcm": enable_lcm,
         "sdxl_style": style_selector,
+        "add_quality_tags": add_quality_tags,
         "quality_tags": quality_selector,
-        "refine_prompt": refine_prompt,
     }
 
     if use_lora:
@@ -440,9 +407,24 @@ def generate(
                 profile=profile,
                 metadata=metadata,
             )
+        if image and IS_COLAB:
+            current_time = datetime.now().strftime("%Y%m%d_%H%M%S")
+            output_directory = "./outputs"
+            os.makedirs(output_directory, exist_ok=True)
+            filename = f"image_{current_time}.png"
+            filepath = os.path.join(output_directory, filename)
+
+            # Convert metadata to a string and save as a text chunk in the PNG
+            metadata_str = json.dumps(metadata)
+            info = PngImagePlugin.PngInfo()
+            info.add_text("metadata", metadata_str)
+            image.save(filepath, "PNG", pnginfo=info)
+            print(f"Image saved as {filepath} with metadata")
+
         return image, metadata
+
     except Exception as e:
-        print(f"An error occured: {e}")
+        print(f"An error occurred: {e}")
         raise
     finally:
         if network:
@@ -450,8 +432,6 @@ def generate(
             network = None
         if use_lora:
             del lora_sd, text_encoders
-        if enable_lcm:
-            pipe.unload_lora_weights()
         if use_upscaler:
             del upscaler_pipe
         pipe.scheduler = backup_scheduler
@@ -459,33 +439,33 @@ def generate(
 
 
 examples = [
-    "face focus, cute, 1girl, green hair, sweater, looking at viewer, upper body, beanie, outdoors, night, turtleneck",
-    "face focus, bishounen, 1boy, green hair, sweater, looking at viewer, upper body, beanie, outdoors, night, turtleneck",
-    "face focus, fu xuan, 1girl, solo, yellow eyes, dress, looking at viewer, hair rings, bare shoulders, long hair, hair ornament, purple hair, bangs, forehead jewel, frills, tassel, jewelry, pink hair",
-    "face focus, bishounen, 1boy, zhongli, looking at viewer, upper body, outdoors, night",
-    "a girl with mesmerizing blue eyes peers at the viewer. Her long, white hair flows gracefully, adorned with stunning blue butterfly hair ornaments",
+    "1girl, arima kana, oshi no ko, solo, idol, idol clothes, one eye closed, red shirt, black skirt, black headwear, gloves, stage light, singing, open mouth, crowd, smile, pointing at viewer",
+    "1girl, c.c., code geass, white shirt, long sleeves, turtleneck, sitting, looking at viewer, eating, pizza, plate, fork, knife, table, chair, table, restaurant, cinematic angle, cinematic lighting",
+    "1girl, sakurauchi riko, \(love live\), queen hat, noble coat, red coat, noble shirt, sitting, crossed legs, gentle smile, parted lips, throne, cinematic angle",
+    "1girl, amiya \(arknights\), arknights, dirty face, outstretched hand, close-up, cinematic angle, foreshortening, dark, dark background",
+    "A boy and a girl, Emiya Shirou and Artoria Pendragon from fate series, having their breakfast in the dining room. Emiya Shirou wears white t-shirt and jacket. Artoria Pendragon wears white dress with blue neck ribbon. Rice, soup, and minced meats are served on the table. They look at each other while smiling happily",
 ]
 
 quality_prompt_list = [
     {
         "name": "(None)",
         "prompt": "{prompt}",
-        "negative_prompt": "",
+        "negative_prompt": "nsfw, lowres, ",
     },
     {
         "name": "Standard",
-        "prompt": "masterpiece, best quality, {prompt}",
-        "negative_prompt": "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry",
+        "prompt": "{prompt}, masterpiece, best quality",
+        "negative_prompt": "nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, artist name, ",
     },
     {
         "name": "Light",
-        "prompt": "(masterpiece), best quality, expressive eyes, perfect face, {prompt}",
-        "negative_prompt": "(low quality, worst quality:1.2), 3d, watermark, signature, ugly, poorly drawn",
+        "prompt": "{prompt}, (masterpiece), best quality, perfect face",
+        "negative_prompt": "nsfw, (low quality, worst quality:1.2), 3d, watermark, signature, ugly, poorly drawn, ",
     },
     {
         "name": "Heavy",
-        "prompt": "(masterpiece), (best quality), (ultra-detailed), {prompt}, illustration, disheveled hair, detailed eyes, perfect composition, moist skin, intricate details, earrings",
-        "negative_prompt": "longbody, lowres, bad anatomy, bad hands, missing fingers, pubic hair, extra digit, fewer digits, cropped, worst quality, low quality",
+        "prompt": "{prompt}, (masterpiece), (best quality), (ultra-detailed), illustration, disheveled hair, perfect composition, moist skin, intricate details, earrings",
+        "negative_prompt": "nsfw, longbody, lowres, bad anatomy, bad hands, missing fingers, pubic hair, extra digit, fewer digits, cropped, worst quality, low quality, ",
     },
 ]
 
@@ -519,48 +499,48 @@ style_list = [
     },
     {
         "name": "Cinematic",
-        "prompt": "cinematic still {prompt} . emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
-        "negative_prompt": "cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured",
+        "prompt": "{prompt}, cinematic still, emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
+        "negative_prompt": "nsfw, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured",
     },
     {
         "name": "Photographic",
-        "prompt": "cinematic photo {prompt} . 35mm photograph, film, bokeh, professional, 4k, highly detailed",
-        "negative_prompt": "drawing, painting, crayon, sketch, graphite, impressionist, noisy, blurry, soft, deformed, ugly",
+        "prompt": "{prompt}, cinematic photo, 35mm photograph, film, bokeh, professional, 4k, highly detailed",
+        "negative_prompt": "nsfw, drawing, painting, crayon, sketch, graphite, impressionist, noisy, blurry, soft, deformed, ugly",
     },
     {
         "name": "Anime",
-        "prompt": "anime artwork {prompt} . anime style, key visual, vibrant, studio anime,  highly detailed",
-        "negative_prompt": "photo, deformed, black and white, realism, disfigured, low contrast",
+        "prompt": "{prompt}, anime artwork, anime style, key visual, vibrant, studio anime,  highly detailed",
+        "negative_prompt": "nsfw, photo, deformed, black and white, realism, disfigured, low contrast",
     },
     {
         "name": "Manga",
-        "prompt": "manga style {prompt} . vibrant, high-energy, detailed, iconic, Japanese comic style",
-        "negative_prompt": "ugly, deformed, noisy, blurry, low contrast, realism, photorealistic, Western comic style",
+        "prompt": "{prompt}, manga style, vibrant, high-energy, detailed, iconic, Japanese comic style",
+        "negative_prompt": "nsfw, ugly, deformed, noisy, blurry, low contrast, realism, photorealistic, Western comic style",
     },
     {
         "name": "Digital Art",
-        "prompt": "concept art {prompt} . digital artwork, illustrative, painterly, matte painting, highly detailed",
-        "negative_prompt": "photo, photorealistic, realism, ugly",
+        "prompt": "{prompt}, concept art, digital artwork, illustrative, painterly, matte painting, highly detailed",
+        "negative_prompt": "nsfw, photo, photorealistic, realism, ugly",
     },
     {
         "name": "Pixel art",
-        "prompt": "pixel-art {prompt} . low-res, blocky, pixel art style, 8-bit graphics",
-        "negative_prompt": "sloppy, messy, blurry, noisy, highly detailed, ultra textured, photo, realistic",
+        "prompt": "{prompt}, pixel-art, low-res, blocky, pixel art style, 8-bit graphics",
+        "negative_prompt": "nsfw, sloppy, messy, blurry, noisy, highly detailed, ultra textured, photo, realistic",
     },
     {
         "name": "Fantasy art",
-        "prompt": "ethereal fantasy concept art of  {prompt} . magnificent, celestial, ethereal, painterly, epic, majestic, magical, fantasy art, cover art, dreamy",
-        "negative_prompt": "photographic, realistic, realism, 35mm film, dslr, cropped, frame, text, deformed, glitch, noise, noisy, off-center, deformed, cross-eyed, closed eyes, bad anatomy, ugly, disfigured, sloppy, duplicate, mutated, black and white",
+        "prompt": "{prompt}, ethereal fantasy concept art, magnificent, celestial, ethereal, painterly, epic, majestic, magical, fantasy art, cover art, dreamy",
+        "negative_prompt": "nsfw, photographic, realistic, realism, 35mm film, dslr, cropped, frame, text, deformed, glitch, noise, noisy, off-center, deformed, cross-eyed, closed eyes, bad anatomy, ugly, disfigured, sloppy, duplicate, mutated, black and white",
     },
     {
         "name": "Neonpunk",
-        "prompt": "neonpunk style {prompt} . cyberpunk, vaporwave, neon, vibes, vibrant, stunningly beautiful, crisp, detailed, sleek, ultramodern, magenta highlights, dark purple shadows, high contrast, cinematic, ultra detailed, intricate, professional",
-        "negative_prompt": "painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured",
+        "prompt": "{prompt}, neonpunk style, cyberpunk, vaporwave, neon, vibes, vibrant, stunningly beautiful, crisp, detailed, sleek, ultramodern, magenta highlights, dark purple shadows, high contrast, cinematic, ultra detailed, intricate, professional",
+        "negative_prompt": "nsfw, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured",
     },
     {
         "name": "3D Model",
-        "prompt": "professional 3d model {prompt} . octane render, highly detailed, volumetric, dramatic lighting",
-        "negative_prompt": "ugly, deformed, noisy, low poly, blurry, painting",
+        "prompt": "{prompt}, professional 3d model, octane render, highly detailed, volumetric, dramatic lighting",
+        "negative_prompt": "nsfw, ugly, deformed, noisy, low poly, blurry, painting",
     },
 ]
 
@@ -601,15 +581,35 @@ quality_prompt = {
 #     for item in sdxl_loras
 # ]
 
+wildcard_files = load_wildcard_files("wildcard")
+
 with gr.Blocks(css="style.css", theme="NoCrypt/miku@1.2.1") as demo:
     title = gr.HTML(
         f"""<h1><span>{DESCRIPTION}</span></h1>""",
         elem_id="title",
     )
     gr.Markdown(
-        f"""Gradio demo for [Linaqruf/animagine-xl-2.0](https://huggingface.co/Linaqruf/animagine-xl-2.0)""",
+        f"""Gradio demo for [cagliostrolab/animagine-xl-3.0](https://huggingface.co/cagliostrolab/animagine-xl-3.0)""",
         elem_id="subtitle",
     )
+    gr.Markdown(
+        f"""Prompting is a bit different in this iteration, we train the model like this:
+        ```
+        1girl/1boy, character name, from what series, everything else in any order. 
+        ```
+        Prompting Tips
+        ```
+        1. Quality Tags: `masterpiece, best quality, high quality, normal quality, worst quality, low quality`
+        2. Year Tags: `oldest, early, mid, late, newest`
+        3. Rating tags: `rating: general, rating: sensitive, rating: questionable, rating: explicit, nsfw`
+        4. Escape character: `character name \(series\)`
+        5. Recommended settings: `Euler a, cfg 5-7, 25-28 steps`
+        6. It's recommended to use the exact danbooru tags for more accurate result
+        7. To use character wildcard, add this syntax to the prompt `__character__`.
+        ```
+        """,
+        elem_id="subtitle",
+    )   
     gr.DuplicateButton(
         value="Duplicate Space for private use",
         elem_id="duplicate-button",
@@ -630,22 +630,16 @@ with gr.Blocks(css="style.css", theme="NoCrypt/miku@1.2.1") as demo:
                         max_lines=5,
                         placeholder="Enter a negative prompt",
                     )
-                    with gr.Accordion(label="Quality Prompt Presets", open=False):
+                    with gr.Accordion(label="Quality Tags", open=True):
+                        add_quality_tags = gr.Checkbox(label="Add Quality Tags", value=False)
                         quality_selector = gr.Dropdown(
-                            label="Quality Prompt Presets",
-                            show_label=False,
+                            label="Quality Tags Presets",
                             interactive=True,
                             choices=list(quality_prompt.keys()),
                             value="Standard",
                         )
                     with gr.Row():
-                        enable_lcm = gr.Checkbox(label="Enable LCM", value=False)
                         use_lora = gr.Checkbox(label="Use LoRA", value=False)
-                        refine_prompt = gr.Checkbox(
-                            label="Refine prompt",
-                            value=False,
-                            visible=ENABLE_REFINER_PROMPT,
-                        )
                 with gr.Group(visible=False) as lora_group:
                     selector_info = gr.Text(
                         label="Selected LoRA",
@@ -679,7 +673,7 @@ with gr.Blocks(css="style.css", theme="NoCrypt/miku@1.2.1") as demo:
                     aspect_ratio_selector = gr.Radio(
                         label="Aspect Ratio",
                         choices=aspect_ratios,
-                        value="1024 x 1024",
+                        value="896 x 1152",
                         container=True,
                     )
                 with gr.Group():
@@ -735,16 +729,16 @@ with gr.Blocks(css="style.css", theme="NoCrypt/miku@1.2.1") as demo:
                         guidance_scale = gr.Slider(
                             label="Guidance scale",
                             minimum=1,
-                            maximum=20,
+                            maximum=12,
                             step=0.1,
-                            value=12.0,
+                            value=7.0,
                         )
                         num_inference_steps = gr.Slider(
                             label="Number of inference steps",
                             minimum=1,
-                            maximum=100,
+                            maximum=50,
                             step=1,
-                            value=50,
+                            value=28,
                         )
 
             with gr.Tab("Past Generation"):
@@ -773,18 +767,6 @@ with gr.Blocks(css="style.css", theme="NoCrypt/miku@1.2.1") as demo:
         queue=False,
         show_progress=False,
     )
-    enable_lcm.change(
-        update_lcm_parameter,
-        inputs=enable_lcm,
-        outputs=[
-            guidance_scale,
-            num_inference_steps,
-            sampler,
-            sampler,
-        ],
-        queue=False,
-        api_name=False,
-    )
     use_lora.change(
         fn=lambda x: gr.update(visible=x),
         inputs=use_lora,
@@ -818,7 +800,6 @@ with gr.Blocks(css="style.css", theme="NoCrypt/miku@1.2.1") as demo:
         use_lora,
         lora_weight,
         selected_state,
-        enable_lcm,
         sampler,
         aspect_ratio_selector,
         style_selector,
@@ -826,7 +807,7 @@ with gr.Blocks(css="style.css", theme="NoCrypt/miku@1.2.1") as demo:
         use_upscaler,
         upscaler_strength,
         upscale_by,
-        refine_prompt,
+        add_quality_tags
     ]
 
     prompt.submit(

demo.ipynb

@@ -1,62 +1,93 @@
 {
-  "cells": [
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "PeEyOhUDHhzF"
-      },
-      "outputs": [],
-      "source": [
-        "import os\n",
-        "import subprocess\n",
-        "\n",
-        "ROOT_DIR = \"/content\"\n",
-        "REPO_URL = \"https://huggingface.co/spaces/Linaqruf/animagine-xl\"\n",
-        "REPO_DIR = os.path.join(ROOT_DIR, \"animagine-xl-gui\")\n",
-        "\n",
-        "os.environ[\"HF_TOKEN\"] = \"\"\n",
-        "os.environ[\"ENABLE_REFINER_PROMPT\"] = \"1\"\n",
-        "\n",
-        "def clone(url, dir, branch=None):\n",
-        "    subprocess.run([\"git\", \"clone\", url, dir], check=True)\n",
-        "    if branch:\n",
-        "        subprocess.run([\"git\", \"checkout\", branch], cwd=dir, check=True)\n",
-        "\n",
-        "def install_deps(dir):\n",
-        "    subprocess.run([\"pip\", \"install\", \"-r\", \"requirements.txt\"], cwd=dir, check=True)\n",
-        "\n",
-        "def main():\n",
-        "    if not os.path.exists(REPO_DIR):\n",
-        "        print(f\"Cloning Repository to {REPO_DIR}\")\n",
-        "        clone(REPO_URL, REPO_DIR)\n",
-        "        print(f\"Installing required python libraries\")\n",
-        "        install_deps(REPO_DIR)\n",
-        "        print(\"Done!\")\n",
-        "\n",
-        "    os.chdir(REPO_DIR)\n",
-        "    !python app.py\n",
-        "\n",
-        "if __name__ == \"__main__\":\n",
-        "    main()\n"
-      ]
-    }
-  ],
-  "metadata": {
-    "accelerator": "GPU",
-    "colab": {
-      "machine_shape": "hm",
-      "provenance": [],
-      "gpuType": "A100"
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    }
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "538a3f0c-50c1-4952-9fcc-070d365c9a0f",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import subprocess\n",
+    "from threading import Timer\n",
+    "from queue import Queue\n",
+    "\n",
+    "ROOT_DIR = \"/content\"\n",
+    "REPO_URL = \"https://huggingface.co/spaces/Linaqruf/animagine-xl\"\n",
+    "REPO_DIR = os.path.join(ROOT_DIR, \"cagliostro-webui\")\n",
+    "NGROK_TOKEN = \"\"\n",
+    "\n",
+    "os.environ[\"HF_TOKEN\"] = \"\"\n",
+    "os.environ[\"IS_COLAB\"] = \"1\"\n",
+    "os.environ[\"MODEL\"] = \"https://huggingface.co/cagliostrolab/animagine-xl-3.0/blob/main/animagine-xl-3.0.safetensors\"\n",
+    "os.environ[\"CACHE_EXAMPLES\"] = \"1\"\n",
+    "\n",
+    "def clone(url, dir, branch=None):\n",
+    "    subprocess.run([\"git\", \"clone\", url, dir], check=True)\n",
+    "    if branch:\n",
+    "        subprocess.run([\"git\", \"checkout\", branch], cwd=dir, check=True)\n",
+    "\n",
+    "def install_deps(dir):\n",
+    "    subprocess.run([\"pip\", \"install\", \"-r\", \"requirements.txt\"], cwd=dir, check=True)\n",
+    "\n",
+    "def ngrok_tunnel(port,queue,auth_token):\n",
+    "    ngrok.set_auth_token(auth_token)\n",
+    "    url = ngrok.connect(port)\n",
+    "    queue.put(url)\n",
+    "\n",
+    "def main():\n",
+    "    if not os.path.exists(REPO_DIR):\n",
+    "        print(f\"Cloning Repository to {REPO_DIR}\")\n",
+    "        clone(REPO_URL, REPO_DIR)\n",
+    "    print(f\"Installing required python libraries\")\n",
+    "    install_deps(REPO_DIR)\n",
+    "    print(\"Done!\")\n",
+    "\n",
+    "    os.chdir(REPO_DIR)\n",
+    "    \n",
+    "    if NGROK_TOKEN:\n",
+    "        try:\n",
+    "            from pyngrok import conf,ngrok\n",
+    "        except:\n",
+    "            !pip install -qqqq --upgrade setuptools\n",
+    "            !pip install -qqqq -U pyngrok\n",
+    "            from pyngrok import conf,ngrok\n",
+    "                                \n",
+    "        ngrok_output_queue = Queue()\n",
+    "        ngrok_thread = Timer(2, ngrok_tunnel, args=(7860, ngrok_output_queue, NGROK_TOKEN))\n",
+    "        ngrok_thread.start()\n",
+    "        ngrok_thread.join()\n",
+    "        \n",
+    "        print(ngrok_output_queue.get())  \n",
+    "    \n",
+    "    !python app.py\n",
+    "\n",
+    "if __name__ == \"__main__\":\n",
+    "    main()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
   },
-  "nbformat": 4,
-  "nbformat_minor": 0
-}
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}