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c009d4f b7d4bc8 c009d4f b7d4bc8 c009d4f b7d4bc8 c009d4f b7d4bc8 c009d4f b7d4bc8 c009d4f b7d4bc8 c009d4f b7d4bc8 c009d4f b7d4bc8 c009d4f b7d4bc8 c009d4f b7d4bc8 c009d4f b7d4bc8 c009d4f b7d4bc8 c009d4f b7d4bc8 c009d4f b7d4bc8 c009d4f b7d4bc8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 | import yaml
import os
from collections import OrderedDict
CHECKPOINT_DIR = "models/checkpoints"
LORA_DIR = "models/loras"
EMBEDDING_DIR = "models/embeddings"
CONTROLNET_DIR = "models/controlnet"
MODEL_PATCHES_DIR = "models/model_patches"
DIFFUSION_MODELS_DIR = "models/diffusion_models"
VAE_DIR = "models/vae"
TEXT_ENCODERS_DIR = "models/text_encoders"
STYLE_MODELS_DIR = "models/style_models"
CLIP_VISION_DIR = "models/clip_vision"
IPADAPTER_DIR = "models/ipadapter"
IPADAPTER_FLUX_DIR = "models/ipadapter-flux"
INPUT_DIR = "input"
OUTPUT_DIR = "output"
CATEGORY_TO_DIR_MAP = {
"diffusion_models": DIFFUSION_MODELS_DIR,
"text_encoders": TEXT_ENCODERS_DIR,
"vae": VAE_DIR,
"checkpoints": CHECKPOINT_DIR,
"loras": LORA_DIR,
"controlnet": CONTROLNET_DIR,
"model_patches": MODEL_PATCHES_DIR,
"embeddings": EMBEDDING_DIR,
"style_models": STYLE_MODELS_DIR,
"clip_vision": CLIP_VISION_DIR,
"ipadapter": IPADAPTER_DIR,
"ipadapter-flux": IPADAPTER_FLUX_DIR
}
_PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
_MODEL_LIST_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'model_list.yaml')
_FILE_LIST_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'file_list.yaml')
_IPADAPTER_LIST_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'ipadapter.yaml')
_CONSTANTS_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'constants.yaml')
_MODEL_ARCHITECTURES_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'model_architectures.yaml')
_IMAGE_GEN_FEATURES_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'image_gen_features.yaml')
_MODEL_DEFAULTS_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'model_defaults.yaml')
def load_constants_from_yaml(filepath=_CONSTANTS_PATH):
if not os.path.exists(filepath):
print(f"Warning: Constants file not found at {filepath}. Using fallback values.")
return {}
with open(filepath, 'r', encoding='utf-8') as f:
return yaml.safe_load(f)
def load_architectures_config(filepath=_MODEL_ARCHITECTURES_PATH):
if not os.path.exists(filepath):
print(f"Warning: Architectures file not found at {filepath}.")
return {}
with open(filepath, 'r', encoding='utf-8') as f:
return yaml.safe_load(f)
def load_features_config(filepath=_IMAGE_GEN_FEATURES_PATH):
if not os.path.exists(filepath):
print(f"Warning: Features file not found at {filepath}.")
return {}
with open(filepath, 'r', encoding='utf-8') as f:
return yaml.safe_load(f)
def load_model_defaults(filepath=_MODEL_DEFAULTS_PATH):
if not os.path.exists(filepath):
print(f"Warning: Model defaults file not found at {filepath}.")
return {}
with open(filepath, 'r', encoding='utf-8') as f:
return yaml.safe_load(f)
def load_file_download_map(filepath=_FILE_LIST_PATH):
if not os.path.exists(filepath):
raise FileNotFoundError(f"The file list (for downloads) was not found at: {filepath}")
with open(filepath, 'r', encoding='utf-8') as f:
file_list_data = yaml.safe_load(f)
download_info_map = {}
for category, files in file_list_data.get('file', {}).items():
if isinstance(files, list):
for file_info in files:
if 'filename' in file_info:
file_info['category'] = category
download_info_map[file_info['filename']] = file_info
return download_info_map
def load_models_from_yaml(model_list_filepath=_MODEL_LIST_PATH, download_map=None):
if not os.path.exists(model_list_filepath):
raise FileNotFoundError(f"The model list file was not found at: {model_list_filepath}")
if download_map is None:
raise ValueError("download_map must be provided to load_models_from_yaml")
with open(model_list_filepath, 'r', encoding='utf-8') as f:
model_data = yaml.safe_load(f)
model_maps = {
"MODEL_MAP_CHECKPOINT": OrderedDict(),
"ALL_MODEL_MAP": OrderedDict(),
}
category_map_names = {
"Checkpoint": "MODEL_MAP_CHECKPOINT",
"Checkpoints": "MODEL_MAP_CHECKPOINT"
}
for category, architectures in model_data.items():
if category in category_map_names:
map_name = category_map_names[category]
if not isinstance(architectures, dict): continue
for arch, arch_data in architectures.items():
if not isinstance(arch_data, dict): continue
latent_type = arch_data.get('latent_type', 'latent')
models = arch_data.get('models', [])
if not isinstance(models, list): continue
for model in models:
display_name = model['display_name']
path_or_components = model.get('path') or model.get('components')
mod_category = model.get('category', None)
repo_id = ''
if isinstance(path_or_components, str):
download_info = download_map.get(path_or_components, {})
repo_id = download_info.get('repo_id', '')
model_tuple = (
repo_id,
path_or_components,
arch,
latent_type,
mod_category
)
model_maps[map_name][display_name] = model_tuple
model_maps["ALL_MODEL_MAP"][display_name] = model_tuple
return model_maps
try:
ALL_FILE_DOWNLOAD_MAP = load_file_download_map()
loaded_maps = load_models_from_yaml(download_map=ALL_FILE_DOWNLOAD_MAP)
MODEL_MAP_CHECKPOINT = loaded_maps["MODEL_MAP_CHECKPOINT"]
ALL_MODEL_MAP = loaded_maps["ALL_MODEL_MAP"]
category_to_model_type = {
"diffusion_models": "UNET",
"text_encoders": "TEXT_ENCODER",
"vae": "VAE",
"checkpoints": "SDXL",
"loras": "LORA",
"controlnet": "CONTROLNET",
"model_patches": "MODEL_PATCH",
"style_models": "STYLE",
"clip_vision": "CLIP_VISION",
"ipadapter": "IPADAPTER",
"ipadapter-flux": "IPADAPTER_FLUX"
}
for filename, file_info in ALL_FILE_DOWNLOAD_MAP.items():
if filename not in ALL_MODEL_MAP:
category = file_info.get('category')
model_type = category_to_model_type.get(category, 'UNKNOWN')
repo_id = file_info.get('repo_id', '')
ALL_MODEL_MAP[filename] = (repo_id, filename, model_type, None, None)
MODEL_TYPE_MAP = {k: v[2] for k, v in ALL_MODEL_MAP.items()}
ARCH_CATEGORIES_MAP = {}
for display_name, info in MODEL_MAP_CHECKPOINT.items():
arch = info[2]
cat = info[4] if len(info) > 4 else None
if arch not in ARCH_CATEGORIES_MAP:
ARCH_CATEGORIES_MAP[arch] = []
if cat and cat not in ARCH_CATEGORIES_MAP[arch]:
ARCH_CATEGORIES_MAP[arch].append(cat)
except Exception as e:
print(f"FATAL: Could not load model configuration from YAML. Error: {e}")
ALL_FILE_DOWNLOAD_MAP = {}
MODEL_MAP_CHECKPOINT, ALL_MODEL_MAP = {}, {}
MODEL_TYPE_MAP = {}
ARCH_CATEGORIES_MAP = {}
try:
_constants = load_constants_from_yaml()
MAX_LORAS = _constants.get('MAX_LORAS', 5)
MAX_EMBEDDINGS = _constants.get('MAX_EMBEDDINGS', 5)
MAX_CONDITIONINGS = _constants.get('MAX_CONDITIONINGS', 10)
MAX_CONTROLNETS = _constants.get('MAX_CONTROLNETS', 5)
MAX_IPADAPTERS = _constants.get('MAX_IPADAPTERS', 5)
LORA_SOURCE_CHOICES = _constants.get('LORA_SOURCE_CHOICES', ["Civitai", "File"])
RESOLUTION_MAP = _constants.get('RESOLUTION_MAP', {})
ARCHITECTURES_CONFIG = load_architectures_config()
FEATURES_CONFIG = load_features_config()
MODEL_DEFAULTS_CONFIG = load_model_defaults()
except Exception as e:
print(f"FATAL: Could not load constants from YAML. Error: {e}")
MAX_LORAS, MAX_EMBEDDINGS, MAX_CONDITIONINGS, MAX_CONTROLNETS, MAX_IPADAPTERS = 5, 5, 10, 5, 5
LORA_SOURCE_CHOICES = ["Civitai", "File"]
RESOLUTION_MAP = {}
ARCHITECTURES_CONFIG = {}
FEATURES_CONFIG = {}
MODEL_DEFAULTS_CONFIG = {} |