fix: isolate extra unet paths from checkpoints to prevent type misclassification

Refactor _prepare_checkpoint_paths() to return a tuple instead of having
side effects on instance variables. This prevents extra unet paths from
being incorrectly classified as checkpoints when processing extra paths.

- Changed return type from List[str] to Tuple[List[str], List[str], List[str]]
  (all_paths, checkpoint_roots, unet_roots)
- Updated _init_checkpoint_paths() and _apply_library_paths() callers
- Fixed extra paths processing to properly isolate main and extra roots
- Updated test_checkpoint_path_overlap.py tests for new API

This ensures models in extra unet paths are correctly identified as
diffusion_model type and don't appear in checkpoints list.
This commit is contained in:
Will Miao
2026-03-17 22:03:57 +08:00
parent 70c150bd80
commit 2dae4c1291
8 changed files with 838 additions and 124 deletions

View File

@@ -112,6 +112,112 @@ def get_lora_info_absolute(lora_name):
return asyncio.run(_get_lora_info_absolute_async())
def get_checkpoint_info_absolute(checkpoint_name):
"""Get the absolute checkpoint path and metadata from cache
Supports ComfyUI-style model names (e.g., "folder/model_name.ext")
Args:
checkpoint_name: The model name, can be:
- ComfyUI format: "folder/model_name.safetensors"
- Simple name: "model_name"
Returns:
tuple: (absolute_path, metadata) where absolute_path is the full
file system path to the checkpoint file, or original checkpoint_name if not found,
metadata is the full model metadata dict or None
"""
async def _get_checkpoint_info_absolute_async():
from ..services.service_registry import ServiceRegistry
scanner = await ServiceRegistry.get_checkpoint_scanner()
cache = await scanner.get_cached_data()
# Get model roots for matching
model_roots = scanner.get_model_roots()
# Normalize the checkpoint name
normalized_name = checkpoint_name.replace(os.sep, "/")
for item in cache.raw_data:
file_path = item.get("file_path", "")
if not file_path:
continue
# Format the stored path as ComfyUI-style name
formatted_name = _format_model_name_for_comfyui(file_path, model_roots)
# Match by formatted name
if formatted_name == normalized_name or formatted_name == checkpoint_name:
return file_path, item
# Also try matching by basename only (for backward compatibility)
file_name = item.get("file_name", "")
if (
file_name == checkpoint_name
or file_name == os.path.splitext(normalized_name)[0]
):
return file_path, item
return checkpoint_name, None
try:
# Check if we're already in an event loop
loop = asyncio.get_running_loop()
# If we're in a running loop, we need to use a different approach
# Create a new thread to run the async code
import concurrent.futures
def run_in_thread():
new_loop = asyncio.new_event_loop()
asyncio.set_event_loop(new_loop)
try:
return new_loop.run_until_complete(
_get_checkpoint_info_absolute_async()
)
finally:
new_loop.close()
with concurrent.futures.ThreadPoolExecutor() as executor:
future = executor.submit(run_in_thread)
return future.result()
except RuntimeError:
# No event loop is running, we can use asyncio.run()
return asyncio.run(_get_checkpoint_info_absolute_async())
def _format_model_name_for_comfyui(file_path: str, model_roots: list) -> str:
"""Format file path to ComfyUI-style model name (relative path with extension)
Example: /path/to/checkpoints/Illustrious/model.safetensors -> Illustrious/model.safetensors
Args:
file_path: Absolute path to the model file
model_roots: List of model root directories
Returns:
ComfyUI-style model name with relative path and extension
"""
# Normalize path separators
normalized_path = file_path.replace(os.sep, "/")
# Find the matching root and get relative path
for root in model_roots:
normalized_root = root.replace(os.sep, "/")
# Ensure root ends with / for proper matching
if not normalized_root.endswith("/"):
normalized_root += "/"
if normalized_path.startswith(normalized_root):
rel_path = normalized_path[len(normalized_root) :]
return rel_path
# If no root matches, just return the basename with extension
return os.path.basename(file_path)
def fuzzy_match(text: str, pattern: str, threshold: float = 0.85) -> bool:
"""
Check if text matches pattern using fuzzy matching.