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feat(lora-loader): Load LoRAs using lower-level API to bypass folder_paths validation

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- Add get_lora_info_absolute() function to return absolute file paths
- Replace LoraLoader().load_lora() with comfy.utils.load_torch_file() +
  comfy.sd.load_lora_for_models() to enable loading LoRAs from any path
- This allows LoRA Manager to load LoRAs from non-standard paths (multi-library support)
- Fixes #805
This commit is contained in:
Will Miao
2026-02-23 18:06:15 +08:00
parent 1f5baec7fd
commit 70398ed985
2 changed files with 65 additions and 14 deletions
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33
py/nodes/lora_loader.py
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@@ -1,7 +1,8 @@
import logging
import re
from nodes import LoraLoader
from ..utils.utils import get_lora_info
import comfy.utils # type: ignore
import comfy.sd # type: ignore
from ..utils.utils import get_lora_info_absolute
from .utils import FlexibleOptionalInputType, any_type, extract_lora_name, get_loras_list, nunchaku_load_lora
logger = logging.getLogger(__name__)
@@ -58,12 +59,13 @@ class LoraLoaderLM:
model = nunchaku_load_lora(model, lora_path, model_strength)
# clip remains unchanged for Nunchaku models
else:
# Use default loader for standard models
model, clip = LoraLoader().load_lora(model, clip, lora_path, model_strength, clip_strength)
# Use lower-level API to load LoRA directly without folder_paths validation
lora = comfy.utils.load_torch_file(lora_path, safe_load=True)
model, clip = comfy.sd.load_lora_for_models(model, clip, lora, model_strength, clip_strength)
# Extract lora name for trigger words lookup
lora_name = extract_lora_name(lora_path)
_, trigger_words = get_lora_info(lora_name)
_, trigger_words = get_lora_info_absolute(lora_name)
all_trigger_words.extend(trigger_words)
# Add clip strength to output if different from model strength (except for Nunchaku models)
@@ -84,7 +86,7 @@ class LoraLoaderLM:
clip_strength = float(lora.get('clipStrength', model_strength))
# Get lora path and trigger words
lora_path, trigger_words = get_lora_info(lora_name)
lora_path, trigger_words = get_lora_info_absolute(lora_name)
# Apply the LoRA using the appropriate loader
if is_nunchaku_model:
@@ -92,8 +94,9 @@ class LoraLoaderLM:
model = nunchaku_load_lora(model, lora_path, model_strength)
# clip remains unchanged
else:
# Use default loader for standard models
model, clip = LoraLoader().load_lora(model, clip, lora_path, model_strength, clip_strength)
# Use lower-level API to load LoRA directly without folder_paths validation
lora = comfy.utils.load_torch_file(lora_path, safe_load=True)
model, clip = comfy.sd.load_lora_for_models(model, clip, lora, model_strength, clip_strength)
# Include clip strength in output if different from model strength and not a Nunchaku model
if not is_nunchaku_model and abs(model_strength - clip_strength) > 0.001:
@@ -199,12 +202,13 @@ class LoraTextLoaderLM:
model = nunchaku_load_lora(model, lora_path, model_strength)
# clip remains unchanged for Nunchaku models
else:
# Use default loader for standard models
model, clip = LoraLoader().load_lora(model, clip, lora_path, model_strength, clip_strength)
# Use lower-level API to load LoRA directly without folder_paths validation
lora = comfy.utils.load_torch_file(lora_path, safe_load=True)
model, clip = comfy.sd.load_lora_for_models(model, clip, lora, model_strength, clip_strength)
# Extract lora name for trigger words lookup
lora_name = extract_lora_name(lora_path)
_, trigger_words = get_lora_info(lora_name)
_, trigger_words = get_lora_info_absolute(lora_name)
all_trigger_words.extend(trigger_words)
# Add clip strength to output if different from model strength (except for Nunchaku models)
@@ -221,7 +225,7 @@ class LoraTextLoaderLM:
clip_strength = lora['clip_strength']
# Get lora path and trigger words
lora_path, trigger_words = get_lora_info(lora_name)
lora_path, trigger_words = get_lora_info_absolute(lora_name)
# Apply the LoRA using the appropriate loader
if is_nunchaku_model:
@@ -229,8 +233,9 @@ class LoraTextLoaderLM:
model = nunchaku_load_lora(model, lora_path, model_strength)
# clip remains unchanged
else:
# Use default loader for standard models
model, clip = LoraLoader().load_lora(model, clip, lora_path, model_strength, clip_strength)
# Use lower-level API to load LoRA directly without folder_paths validation
lora = comfy.utils.load_torch_file(lora_path, safe_load=True)
model, clip = comfy.sd.load_lora_for_models(model, clip, lora, model_strength, clip_strength)
# Include clip strength in output if different from model strength and not a Nunchaku model
if not is_nunchaku_model and abs(model_strength - clip_strength) > 0.001: