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update sampler helper, add lora support

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Inoland
2025-09-07 15:32:05 +04:00
parent 14785d1843
commit ee10862c8d
3 changed files with 101 additions and 36 deletions
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src/comfyui_ino_nodes/configs/creator_loras.json
-14
View File
@@ -1,14 +0,0 @@
{
"models": [
{
"name": "KarlaKush",
"base_model": "flux1dev",
"trigger_word": "karlakush2org",
"lora_file": "flux1dev/creators/karlakush2org_V005_.safetensors",
"weight_type": "fp16",
"strength_model": 0.9,
"strength_clip": 0.9,
"description": ""
}
]
}
src/comfyui_ino_nodes/configs/loras.json
+28
View File
@@ -0,0 +1,28 @@
{
"models": [
{
"name": "KarlaKush",
"base_model": "flux1dev",
"type": "person",
"trigger_word": "karlakush2org",
"file": "flux1dev/creators/karlakush2org_V005_.safetensors",
"weight_type": "fp16",
"strength_model": 0.9,
"strength_clip": 0.9,
"trigger_words": "",
"description": ""
},
{
"name": "RealisticAmplifier",
"base_model": "flux1dev",
"type": "finetune",
"trigger_word": "d1g1cam",
"file": "flux1dev/Digicam.safetensors",
"weight_type": "fp16",
"strength_model": 0.9,
"strength_clip": 0.9,
"trigger_words": "",
"description": "UltraReal Fine-Tune"
}
]
}
src/comfyui_ino_nodes/utils/sampler_helper.py
+73 -22
View File
@@ -16,27 +16,15 @@ def _as_float(v, default):
try: return float(v)
except (TypeError, ValueError): return default
def _get_model_type (model_type: str = "model") -> str:
"""Get model type from config."""
if model_type == "model" or model_type is None or model_type == "":
type_final = "models"
elif model_type == "creator_lora":
type_final = "creator_loras"
else:
type_final = model_type
return type_final
def _resolve_models_path(config: str = "default", model_type: str = "") -> Path:
def _resolve_models_path(config: str = "default", model_type: str = "models") -> Path:
"""Resolve models .json path. 'default' => ../configs/models.json (relative to this file)."""
type_final = _get_model_type(model_type)
if config == "default":
base_dir = Path(__file__).resolve().parent.parent # comfyui_ino_nodes/
return (base_dir / "configs" / f"{type_final}.json").resolve()
return (base_dir / "configs" / f"{model_type}.json").resolve()
return Path(config).expanduser().resolve()
def _load_models_list(config: str = "default", model_type: str = "") -> List[Dict]:
def _load_models_list(config: str = "default", model_type: str = "models") -> List[Dict]:
"""Load models list with file-mtime cache."""
path = _resolve_models_path(config, model_type)
if not path.exists():
@@ -59,13 +47,13 @@ def _load_models_list(config: str = "default", model_type: str = "") -> List[Dic
return cache["_models"]
def get_models(config: str = "default", config_type: str = "model") -> Tuple[List[str], List[Dict]]:
def get_models(config: str = "default", model_type: str = "models") -> Tuple[List[str], List[Dict]]:
"""
Return (names, models):
- names: list of model names (strings)
- models: list of model dicts
"""
models = deepcopy(_load_models_list(config, config_type))
models = deepcopy(_load_models_list(config, model_type))
names = [m.get("name", "") for m in models if isinstance(m, dict)]
return names, models
@@ -78,6 +66,55 @@ def get_model_by_name(name: str, models: List[Dict]) -> Dict:
raise KeyError(f"Model '{name}' not found.")
def prepare_lora_config(lora_config: str) -> Dict:
"""Prepare LoRA config"""
if not lora_config or lora_config == "" or lora_config == "none":
return {
"use_lora": False,
"lora_config": None
}
if isinstance(lora_config, str):
config_str = lora_config.strip()
try:
model_cfg = json.loads(config_str)
except json.JSONDecodeError as e:
return {
"use_lora": False,
"lora_config": None
}
elif isinstance(lora_config, dict):
model_cfg = lora_config
else:
return {
"use_lora": False,
"lora_config": None
}
return {
"use_lora": True,
"lora_config": model_cfg
}
def load_lora(config_str, model, clip):
"""Load LoRA"""
from nodes import LoraLoader
prepared_config = prepare_lora_config(config_str)
if prepared_config["use_lora"]:
config_dict = prepared_config["lora_config"]
lora_loader = LoraLoader()
lora_loaded = lora_loader.load_lora(
model=model,
clip=clip,
lora_name=config_dict["file"],
strength_model=config_dict["strength_model"],
strength_clip=config_dict["strength_clip"]
)
return lora_loaded[0], lora_loaded[1]
else:
return model, clip
class InoGetModelConfig:
"""
@@ -118,7 +155,7 @@ class InoGetLoraConfig:
return {
"required": {
"enabled": ("BOOLEAN", {"default": True, "label_off": "OFF", "label_on": "ON"}),
"lora": (list(get_models(config="default", config_type="creator_lora")[0]), {"tooltip": "The name of the LoRA."}),
"lora": (list(get_models(config="default", model_type="loras")[0]), {"tooltip": "The name of the LoRA."}),
}
}
@@ -135,7 +172,7 @@ class InoGetLoraConfig:
):
if not enabled:
return (lora, "", )
model_cfg = get_model_by_name(lora, get_models(config="default", config_type="creator_lora")[1])
model_cfg = get_model_by_name(lora, get_models(config="default", model_type="loras")[1])
return (lora, model_cfg, )
@@ -199,7 +236,7 @@ class InoLoadSamplerModels:
else:
raise TypeError("`config` must be a JSON string or a dict.")
from nodes import UNETLoader, CLIPLoader, DualCLIPLoader, VAELoader, LoraLoader
from nodes import UNETLoader, CLIPLoader, DualCLIPLoader, VAELoader
unet_loader = UNETLoader()
load_unet = unet_loader.load_unet(
@@ -229,11 +266,25 @@ class InoLoadSamplerModels:
vae_name=model_cfg["vae"],
)
print(f"lora1_name: {lora_1_config}")
print(f"lora2_name: {lora_2_config}")
model_loaded = load_unet[0]
clip_loaded = load_clip[0]
lora_1_loaded = load_lora(lora_1_config, model_loaded, clip_loaded)
model_loaded = lora_1_loaded[0]
clip_loaded = lora_1_loaded[1]
lora_2_loaded = load_lora(lora_2_config, model_loaded, clip_loaded)
model_loaded = lora_2_loaded[0]
clip_loaded = lora_2_loaded[1]
lora_3_loaded = load_lora(lora_3_config, model_loaded, clip_loaded)
model_loaded = lora_3_loaded[0]
clip_loaded = lora_3_loaded[1]
lora_4_loaded = load_lora(lora_4_config, model_loaded, clip_loaded)
model_loaded = lora_4_loaded[0]
clip_loaded = lora_4_loaded[1]
return ( model_loaded, clip_loaded, load_vae[0], )