mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-21 21:22:11 -03:00
526 lines
21 KiB
Python
526 lines
21 KiB
Python
import json
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import os
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import logging
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import asyncio
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import shutil
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import time
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from typing import List, Dict, Optional, Set
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from ..utils.models import LoraMetadata
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from ..config import config
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from .model_scanner import ModelScanner
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from .lora_hash_index import LoraHashIndex
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from .settings_manager import settings
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from ..utils.constants import NSFW_LEVELS
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from ..utils.utils import fuzzy_match
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import sys
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logger = logging.getLogger(__name__)
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class LoraScanner(ModelScanner):
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"""Service for scanning and managing LoRA files"""
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_instance = None
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_lock = asyncio.Lock()
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def __new__(cls):
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if cls._instance is None:
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cls._instance = super().__new__(cls)
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return cls._instance
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def __init__(self):
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# Ensure initialization happens only once
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if not hasattr(self, '_initialized'):
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# Define supported file extensions
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file_extensions = {'.safetensors'}
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# Initialize parent class
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super().__init__(
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model_type="lora",
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model_class=LoraMetadata,
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file_extensions=file_extensions,
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hash_index=LoraHashIndex()
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)
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self._initialized = True
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@classmethod
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async def get_instance(cls):
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"""Get singleton instance with async support"""
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async with cls._lock:
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if cls._instance is None:
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cls._instance = cls()
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return cls._instance
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def get_model_roots(self) -> List[str]:
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"""Get lora root directories"""
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return config.loras_roots
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async def scan_all_models(self) -> List[Dict]:
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"""Scan all LoRA directories and return metadata"""
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all_loras = []
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# Create scan tasks for each directory
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scan_tasks = []
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for lora_root in self.get_model_roots():
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task = asyncio.create_task(self._scan_directory(lora_root))
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scan_tasks.append(task)
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# Wait for all tasks to complete
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for task in scan_tasks:
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try:
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loras = await task
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all_loras.extend(loras)
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except Exception as e:
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logger.error(f"Error scanning directory: {e}")
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return all_loras
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async def _scan_directory(self, root_path: str) -> List[Dict]:
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"""Scan a single directory for LoRA files"""
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loras = []
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original_root = root_path # Save original root path
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async def scan_recursive(path: str, visited_paths: set):
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"""Recursively scan directory, avoiding circular symlinks"""
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try:
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real_path = os.path.realpath(path)
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if real_path in visited_paths:
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logger.debug(f"Skipping already visited path: {path}")
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return
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visited_paths.add(real_path)
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with os.scandir(path) as it:
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entries = list(it)
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for entry in entries:
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try:
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if entry.is_file(follow_symlinks=True) and any(entry.name.endswith(ext) for ext in self.file_extensions):
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# Use original path instead of real path
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file_path = entry.path.replace(os.sep, "/")
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await self._process_single_file(file_path, original_root, loras)
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await asyncio.sleep(0)
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elif entry.is_dir(follow_symlinks=True):
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# For directories, continue scanning with original path
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await scan_recursive(entry.path, visited_paths)
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except Exception as e:
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logger.error(f"Error processing entry {entry.path}: {e}")
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except Exception as e:
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logger.error(f"Error scanning {path}: {e}")
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await scan_recursive(root_path, set())
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return loras
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async def _process_single_file(self, file_path: str, root_path: str, loras: list):
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"""Process a single file and add to results list"""
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try:
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result = await self._process_model_file(file_path, root_path)
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if result:
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loras.append(result)
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except Exception as e:
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logger.error(f"Error processing {file_path}: {e}")
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async def get_paginated_data(self, page: int, page_size: int, sort_by: str = 'name',
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folder: str = None, search: str = None, fuzzy_search: bool = False,
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base_models: list = None, tags: list = None,
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search_options: dict = None, hash_filters: dict = None) -> Dict:
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"""Get paginated and filtered lora data
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Args:
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page: Current page number (1-based)
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page_size: Number of items per page
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sort_by: Sort method ('name' or 'date')
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folder: Filter by folder path
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search: Search term
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fuzzy_search: Use fuzzy matching for search
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base_models: List of base models to filter by
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tags: List of tags to filter by
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search_options: Dictionary with search options (filename, modelname, tags, recursive)
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hash_filters: Dictionary with hash filtering options (single_hash or multiple_hashes)
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"""
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cache = await self.get_cached_data()
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# Get default search options if not provided
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if search_options is None:
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search_options = {
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'filename': True,
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'modelname': True,
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'tags': False,
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'recursive': False,
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}
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# Get the base data set
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filtered_data = cache.sorted_by_date if sort_by == 'date' else cache.sorted_by_name
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# Apply hash filtering if provided (highest priority)
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if hash_filters:
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single_hash = hash_filters.get('single_hash')
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multiple_hashes = hash_filters.get('multiple_hashes')
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if single_hash:
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# Filter by single hash
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single_hash = single_hash.lower() # Ensure lowercase for matching
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filtered_data = [
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lora for lora in filtered_data
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if lora.get('sha256', '').lower() == single_hash
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]
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elif multiple_hashes:
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# Filter by multiple hashes
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hash_set = set(hash.lower() for hash in multiple_hashes) # Convert to set for faster lookup
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filtered_data = [
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lora for lora in filtered_data
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if lora.get('sha256', '').lower() in hash_set
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]
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# Jump to pagination
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total_items = len(filtered_data)
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start_idx = (page - 1) * page_size
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end_idx = min(start_idx + page_size, total_items)
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result = {
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'items': filtered_data[start_idx:end_idx],
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'total': total_items,
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'page': page,
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'page_size': page_size,
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'total_pages': (total_items + page_size - 1) // page_size
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}
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return result
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# Apply SFW filtering if enabled
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if settings.get('show_only_sfw', False):
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filtered_data = [
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lora for lora in filtered_data
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if not lora.get('preview_nsfw_level') or lora.get('preview_nsfw_level') < NSFW_LEVELS['R']
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]
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# Apply folder filtering
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if folder is not None:
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if search_options.get('recursive', False):
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# Recursive folder filtering - include all subfolders
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filtered_data = [
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lora for lora in filtered_data
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if lora['folder'].startswith(folder)
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]
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else:
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# Exact folder filtering
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filtered_data = [
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lora for lora in filtered_data
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if lora['folder'] == folder
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]
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# Apply base model filtering
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if base_models and len(base_models) > 0:
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filtered_data = [
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lora for lora in filtered_data
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if lora.get('base_model') in base_models
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]
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# Apply tag filtering
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if tags and len(tags) > 0:
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filtered_data = [
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lora for lora in filtered_data
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if any(tag in lora.get('tags', []) for tag in tags)
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]
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# Apply search filtering
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if search:
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search_results = []
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search_opts = search_options or {}
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for lora in filtered_data:
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# Search by file name
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if search_opts.get('filename', True):
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if fuzzy_match(lora.get('file_name', ''), search):
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search_results.append(lora)
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continue
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# Search by model name
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if search_opts.get('modelname', True):
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if fuzzy_match(lora.get('model_name', ''), search):
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search_results.append(lora)
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continue
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# Search by tags
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if search_opts.get('tags', False) and 'tags' in lora:
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if any(fuzzy_match(tag, search) for tag in lora['tags']):
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search_results.append(lora)
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continue
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filtered_data = search_results
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# Calculate pagination
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total_items = len(filtered_data)
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start_idx = (page - 1) * page_size
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end_idx = min(start_idx + page_size, total_items)
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result = {
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'items': filtered_data[start_idx:end_idx],
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'total': total_items,
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'page': page,
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'page_size': page_size,
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'total_pages': (total_items + page_size - 1) // page_size
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}
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return result
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async def move_model(self, source_path: str, target_path: str) -> bool:
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"""Move a model and its associated files to a new location"""
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try:
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# Keep original path format
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source_path = source_path.replace(os.sep, '/')
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target_path = target_path.replace(os.sep, '/')
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# Rest of the code remains unchanged
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base_name = os.path.splitext(os.path.basename(source_path))[0]
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source_dir = os.path.dirname(source_path)
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os.makedirs(target_path, exist_ok=True)
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target_lora = os.path.join(target_path, f"{base_name}.safetensors").replace(os.sep, '/')
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# Use real paths for file operations
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real_source = os.path.realpath(source_path)
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real_target = os.path.realpath(target_lora)
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file_size = os.path.getsize(real_source)
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if self.file_monitor:
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self.file_monitor.handler.add_ignore_path(
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real_source,
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file_size
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)
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self.file_monitor.handler.add_ignore_path(
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real_target,
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file_size
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)
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# Use real paths for file operations
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shutil.move(real_source, real_target)
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# Move associated files
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source_metadata = os.path.join(source_dir, f"{base_name}.metadata.json")
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if os.path.exists(source_metadata):
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target_metadata = os.path.join(target_path, f"{base_name}.metadata.json")
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shutil.move(source_metadata, target_metadata)
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metadata = await self._update_metadata_paths(target_metadata, target_lora)
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# Move preview file if exists
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preview_extensions = ['.preview.png', '.preview.jpeg', '.preview.jpg', '.preview.mp4',
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'.png', '.jpeg', '.jpg', '.mp4']
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for ext in preview_extensions:
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source_preview = os.path.join(source_dir, f"{base_name}{ext}")
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if os.path.exists(source_preview):
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target_preview = os.path.join(target_path, f"{base_name}{ext}")
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shutil.move(source_preview, target_preview)
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break
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# Update cache
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await self.update_single_lora_cache(source_path, target_lora, metadata)
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return True
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except Exception as e:
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logger.error(f"Error moving model: {e}", exc_info=True)
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return False
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async def update_single_lora_cache(self, original_path: str, new_path: str, metadata: Dict) -> bool:
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cache = await self.get_cached_data()
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# Find the existing item to remove its tags from count
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existing_item = next((item for item in cache.raw_data if item['file_path'] == original_path), None)
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if existing_item and 'tags' in existing_item:
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for tag in existing_item.get('tags', []):
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if tag in self._tags_count:
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self._tags_count[tag] = max(0, self._tags_count[tag] - 1)
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if self._tags_count[tag] == 0:
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del self._tags_count[tag]
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# Remove old path from hash index if exists
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self._hash_index.remove_by_path(original_path)
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# Remove the old entry from raw_data
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cache.raw_data = [
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item for item in cache.raw_data
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if item['file_path'] != original_path
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]
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if metadata:
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# If this is an update to an existing path (not a move), ensure folder is preserved
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if original_path == new_path:
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# Find the folder from existing entries or calculate it
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existing_folder = next((item['folder'] for item in cache.raw_data
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if item['file_path'] == original_path), None)
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if existing_folder:
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metadata['folder'] = existing_folder
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else:
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metadata['folder'] = self._calculate_folder(new_path)
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else:
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# For moved files, recalculate the folder
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metadata['folder'] = self._calculate_folder(new_path)
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# Add the updated metadata to raw_data
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cache.raw_data.append(metadata)
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# Update hash index with new path
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if 'sha256' in metadata:
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self._hash_index.add_entry(metadata['sha256'].lower(), new_path)
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# Update folders list
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all_folders = set(item['folder'] for item in cache.raw_data)
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cache.folders = sorted(list(all_folders), key=lambda x: x.lower())
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# Update tags count with the new/updated tags
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if 'tags' in metadata:
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for tag in metadata.get('tags', []):
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self._tags_count[tag] = self._tags_count.get(tag, 0) + 1
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# Resort cache
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await cache.resort()
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return True
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async def _update_metadata_paths(self, metadata_path: str, lora_path: str) -> Dict:
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"""Update file paths in metadata file"""
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try:
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with open(metadata_path, 'r', encoding='utf-8') as f:
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metadata = json.load(f)
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# Update file_path
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metadata['file_path'] = lora_path.replace(os.sep, '/')
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# Update preview_url if exists
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if 'preview_url' in metadata:
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preview_dir = os.path.dirname(lora_path)
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preview_name = os.path.splitext(os.path.basename(metadata['preview_url']))[0]
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preview_ext = os.path.splitext(metadata['preview_url'])[1]
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new_preview_path = os.path.join(preview_dir, f"{preview_name}{preview_ext}")
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metadata['preview_url'] = new_preview_path.replace(os.sep, '/')
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# Save updated metadata
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with open(metadata_path, 'w', encoding='utf-8') as f:
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json.dump(metadata, f, indent=2, ensure_ascii=False)
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return metadata
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except Exception as e:
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logger.error(f"Error updating metadata paths: {e}", exc_info=True)
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# Lora-specific hash index functionality
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def has_lora_hash(self, sha256: str) -> bool:
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"""Check if a LoRA with given hash exists"""
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return self._hash_index.has_hash(sha256.lower())
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def get_lora_path_by_hash(self, sha256: str) -> Optional[str]:
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"""Get file path for a LoRA by its hash"""
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return self._hash_index.get_path(sha256.lower())
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def get_lora_hash_by_path(self, file_path: str) -> Optional[str]:
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"""Get hash for a LoRA by its file path"""
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return self._hash_index.get_hash(file_path)
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def get_preview_url_by_hash(self, sha256: str) -> Optional[str]:
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"""Get preview static URL for a LoRA by its hash"""
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# Get the file path first
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file_path = self._hash_index.get_path(sha256.lower())
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if not file_path:
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return None
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# Determine the preview file path (typically same name with different extension)
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base_name = os.path.splitext(file_path)[0]
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preview_extensions = ['.preview.png', '.preview.jpeg', '.preview.jpg', '.preview.mp4',
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'.png', '.jpeg', '.jpg', '.mp4']
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for ext in preview_extensions:
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preview_path = f"{base_name}{ext}"
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if os.path.exists(preview_path):
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# Convert to static URL using config
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return config.get_preview_static_url(preview_path)
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return None
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async def get_top_tags(self, limit: int = 20) -> List[Dict[str, any]]:
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"""Get top tags sorted by count"""
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# Make sure cache is initialized
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await self.get_cached_data()
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# Sort tags by count in descending order
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sorted_tags = sorted(
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[{"tag": tag, "count": count} for tag, count in self._tags_count.items()],
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key=lambda x: x['count'],
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reverse=True
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)
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# Return limited number
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return sorted_tags[:limit]
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async def get_base_models(self, limit: int = 20) -> List[Dict[str, any]]:
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"""Get base models used in loras sorted by frequency"""
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# Make sure cache is initialized
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cache = await self.get_cached_data()
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# Count base model occurrences
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base_model_counts = {}
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for lora in cache.raw_data:
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if 'base_model' in lora and lora['base_model']:
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base_model = lora['base_model']
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base_model_counts[base_model] = base_model_counts.get(base_model, 0) + 1
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# Sort base models by count
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sorted_models = [{'name': model, 'count': count} for model, count in base_model_counts.items()]
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sorted_models.sort(key=lambda x: x['count'], reverse=True)
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# Return limited number
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return sorted_models[:limit]
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async def diagnose_hash_index(self):
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"""Diagnostic method to verify hash index functionality"""
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print("\n\n*** DIAGNOSING LORA HASH INDEX ***\n\n", file=sys.stderr)
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# First check if the hash index has any entries
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if hasattr(self, '_hash_index'):
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index_entries = len(self._hash_index._hash_to_path)
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print(f"Hash index has {index_entries} entries", file=sys.stderr)
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# Print a few example entries if available
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if index_entries > 0:
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print("\nSample hash index entries:", file=sys.stderr)
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count = 0
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for hash_val, path in self._hash_index._hash_to_path.items():
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if count < 5: # Just show the first 5
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print(f"Hash: {hash_val[:8]}... -> Path: {path}", file=sys.stderr)
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count += 1
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else:
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break
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else:
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print("Hash index not initialized", file=sys.stderr)
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# Try looking up by a known hash for testing
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if not hasattr(self, '_hash_index') or not self._hash_index._hash_to_path:
|
|
print("No hash entries to test lookup with", file=sys.stderr)
|
|
return
|
|
|
|
test_hash = next(iter(self._hash_index._hash_to_path.keys()))
|
|
test_path = self._hash_index.get_path(test_hash)
|
|
print(f"\nTest lookup by hash: {test_hash[:8]}... -> {test_path}", file=sys.stderr)
|
|
|
|
# Also test reverse lookup
|
|
test_hash_result = self._hash_index.get_hash(test_path)
|
|
print(f"Test reverse lookup: {test_path} -> {test_hash_result[:8]}...\n\n", file=sys.stderr)
|
|
|
|
async def get_lora_info_by_name(self, name):
|
|
"""Get LoRA information by name"""
|
|
try:
|
|
# Get cached data
|
|
cache = await self.get_cached_data()
|
|
|
|
# Find the LoRA by name
|
|
for lora in cache.raw_data:
|
|
if lora.get("file_name") == name:
|
|
return lora
|
|
|
|
return None
|
|
except Exception as e:
|
|
logger.error(f"Error getting LoRA info by name: {e}", exc_info=True)
|
|
return None
|
|
|