alphard/ComfyUI-Lora-Manager
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refactor: Extract common methods for Lora handling into utils.py and update references in lora_loader.py and lora_stacker.py

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Will Miao
2025-04-20 21:35:36 +08:00
parent f64c03543a
commit 9bb9e7b64d
3 changed files with 62 additions and 95 deletions
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52
py/nodes/lora_loader.py
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@@ -5,7 +5,7 @@ from ..services.lora_scanner import LoraScanner
from ..config import config
import asyncio
import os
from .utils import FlexibleOptionalInputType, any_type
from .utils import FlexibleOptionalInputType, any_type, get_lora_info, extract_lora_name, get_loras_list
logger = logging.getLogger(__name__)
@@ -32,48 +32,6 @@ class LoraManagerLoader:
RETURN_TYPES = ("MODEL", "CLIP", IO.STRING, IO.STRING)
RETURN_NAMES = ("MODEL", "CLIP", "trigger_words", "loaded_loras")
FUNCTION = "load_loras"
async def get_lora_info(self, lora_name):
"""Get the lora path and trigger words from cache"""
scanner = await LoraScanner.get_instance()
cache = await scanner.get_cached_data()
for item in cache.raw_data:
if item.get('file_name') == lora_name:
file_path = item.get('file_path')
if file_path:
for root in config.loras_roots:
root = root.replace(os.sep, '/')
if file_path.startswith(root):
relative_path = os.path.relpath(file_path, root).replace(os.sep, '/')
# Get trigger words from civitai metadata
civitai = item.get('civitai', {})
trigger_words = civitai.get('trainedWords', []) if civitai else []
return relative_path, trigger_words
return lora_name, [] # Fallback if not found
def extract_lora_name(self, lora_path):
"""Extract the lora name from a lora path (e.g., 'IL\\aorunIllstrious.safetensors' -> 'aorunIllstrious')"""
# Get the basename without extension
basename = os.path.basename(lora_path)
return os.path.splitext(basename)[0]
def _get_loras_list(self, kwargs):
"""Helper to extract loras list from either old or new kwargs format"""
if 'loras' not in kwargs:
return []
loras_data = kwargs['loras']
# Handle new format: {'loras': {'__value__': [...]}}
if isinstance(loras_data, dict) and '__value__' in loras_data:
return loras_data['__value__']
# Handle old format: {'loras': [...]}
elif isinstance(loras_data, list):
return loras_data
# Unexpected format
else:
logger.warning(f"Unexpected loras format: {type(loras_data)}")
return []
def load_loras(self, model, text, **kwargs):
"""Loads multiple LoRAs based on the kwargs input and lora_stack."""
@@ -89,14 +47,14 @@ class LoraManagerLoader:
model, clip = LoraLoader().load_lora(model, clip, lora_path, model_strength, clip_strength)
# Extract lora name for trigger words lookup
lora_name = self.extract_lora_name(lora_path)
_, trigger_words = asyncio.run(self.get_lora_info(lora_name))
lora_name = extract_lora_name(lora_path)
_, trigger_words = asyncio.run(get_lora_info(lora_name))
all_trigger_words.extend(trigger_words)
loaded_loras.append(f"{lora_name}: {model_strength}")
# Then process loras from kwargs with support for both old and new formats
loras_list = self._get_loras_list(kwargs)
loras_list = get_loras_list(kwargs)
for lora in loras_list:
if not lora.get('active', False):
continue
@@ -105,7 +63,7 @@ class LoraManagerLoader:
strength = float(lora['strength'])
# Get lora path and trigger words
lora_path, trigger_words = asyncio.run(self.get_lora_info(lora_name))
lora_path, trigger_words = asyncio.run(get_lora_info(lora_name))
# Apply the LoRA using the resolved path
model, clip = LoraLoader().load_lora(model, clip, lora_path, strength, strength)