mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-22 05:32:12 -03:00
544 lines
21 KiB
Python
544 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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from typing import List, Dict, Optional
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from dataclasses import dataclass
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from operator import itemgetter
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from ..config import config
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from ..utils.file_utils import load_metadata, get_file_info
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from .lora_cache import LoraCache
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from difflib import SequenceMatcher
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from .lora_hash_index import LoraHashIndex
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import sys
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logger = logging.getLogger(__name__)
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class LoraScanner:
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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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# 确保初始化只执行一次
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if not hasattr(self, '_initialized'):
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self._cache: Optional[LoraCache] = None
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self._hash_index = LoraHashIndex()
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self._initialization_lock = asyncio.Lock()
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self._initialization_task: Optional[asyncio.Task] = None
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self._initialized = True
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self.file_monitor = None # Add this line
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def set_file_monitor(self, monitor):
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"""Set file monitor instance"""
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self.file_monitor = monitor
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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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async def get_cached_data(self, force_refresh: bool = False) -> LoraCache:
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"""Get cached LoRA data, refresh if needed"""
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async with self._initialization_lock:
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# 如果缓存未初始化但需要响应请求，返回空缓存
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if self._cache is None and not force_refresh:
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return LoraCache(
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raw_data=[],
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sorted_by_name=[],
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sorted_by_date=[],
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folders=[]
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)
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# 如果正在初始化，等待完成
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if self._initialization_task and not self._initialization_task.done():
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try:
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await self._initialization_task
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except Exception as e:
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logger.error(f"Cache initialization failed: {e}")
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self._initialization_task = None
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if (self._cache is None or force_refresh):
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# 创建新的初始化任务
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if not self._initialization_task or self._initialization_task.done():
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self._initialization_task = asyncio.create_task(self._initialize_cache())
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try:
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await self._initialization_task
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except Exception as e:
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logger.error(f"Cache initialization failed: {e}")
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# 如果缓存已存在，继续使用旧缓存
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if self._cache is None:
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raise # 如果没有缓存，则抛出异常
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return self._cache
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async def _initialize_cache(self) -> None:
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"""Initialize or refresh the cache"""
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try:
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# Clear existing hash index
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self._hash_index.clear()
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# Scan for new data
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raw_data = await self.scan_all_loras()
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# Build hash index
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for lora_data in raw_data:
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if 'sha256' in lora_data and 'file_path' in lora_data:
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self._hash_index.add_entry(lora_data['sha256'], lora_data['file_path'])
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# Update cache
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self._cache = LoraCache(
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raw_data=raw_data,
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sorted_by_name=[],
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sorted_by_date=[],
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folders=[]
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)
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# Call resort_cache to create sorted views
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await self._cache.resort()
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self._initialization_task = None
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logger.info("LoRA Manager: Cache initialization completed")
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except Exception as e:
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logger.error(f"LoRA Manager: Error initializing cache: {e}")
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self._cache = LoraCache(
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raw_data=[],
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sorted_by_name=[],
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sorted_by_date=[],
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folders=[]
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)
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def fuzzy_match(self, text: str, pattern: str, threshold: float = 0.7) -> bool:
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"""
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Check if text matches pattern using fuzzy matching.
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Returns True if similarity ratio is above threshold.
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"""
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if not pattern or not text:
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return False
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# Convert both to lowercase for case-insensitive matching
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text = text.lower()
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pattern = pattern.lower()
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# Split pattern into words
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search_words = pattern.split()
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# Check each word
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for word in search_words:
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# First check if word is a substring (faster)
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if word in text:
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continue
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# If not found as substring, try fuzzy matching
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# Check if any part of the text matches this word
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found_match = False
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for text_part in text.split():
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ratio = SequenceMatcher(None, text_part, word).ratio()
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if ratio >= threshold:
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found_match = True
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break
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if not found_match:
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return False
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# All words found either as substrings or fuzzy matches
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return True
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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: bool = False,
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recursive: bool = False, base_models: list = None):
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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: Use fuzzy matching for search
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recursive: Include subfolders when folder filter is applied
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base_models: List of base models to filter by
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"""
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cache = await self.get_cached_data()
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# 先获取基础数据集
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filtered_data = cache.sorted_by_date if sort_by == 'date' else cache.sorted_by_name
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# 应用文件夹过滤
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if folder is not None:
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if recursive:
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# 递归模式：匹配所有以该文件夹开头的路径
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filtered_data = [
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item for item in filtered_data
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if item['folder'].startswith(folder + '/') or item['folder'] == folder
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]
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else:
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# 非递归模式：只匹配确切的文件夹
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filtered_data = [
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item for item in filtered_data
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if item['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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item for item in filtered_data
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if item.get('base_model') in base_models
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]
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# 应用搜索过滤
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if search:
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if fuzzy:
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filtered_data = [
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item for item in filtered_data
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if any(
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self.fuzzy_match(str(value), search)
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for value in [
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item.get('model_name', ''),
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item.get('base_model', '')
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]
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if value
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)
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]
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else:
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# Original exact search logic
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filtered_data = [
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item for item in filtered_data
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if search in str(item.get('model_name', '')).lower()
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]
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# 计算分页
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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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def invalidate_cache(self):
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"""Invalidate the current cache"""
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self._cache = None
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async def scan_all_loras(self) -> List[Dict]:
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"""Scan all LoRA directories and return metadata"""
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all_loras = []
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# 分目录异步扫描
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scan_tasks = []
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for loras_root in config.loras_roots:
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task = asyncio.create_task(self._scan_directory(loras_root))
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scan_tasks.append(task)
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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 # 保存原始根路径
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async def scan_recursive(path: str, visited_paths: set):
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"""递归扫描目录，避免循环链接"""
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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 entry.name.endswith('.safetensors'):
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# 使用原始路径而不是真实路径
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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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# 对于目录，使用原始路径继续扫描
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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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"""处理单个文件并添加到结果列表"""
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try:
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result = await self._process_lora_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 _process_lora_file(self, file_path: str, root_path: str) -> Dict:
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"""Process a single LoRA file and return its metadata"""
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# Try loading existing metadata
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metadata = await load_metadata(file_path)
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if metadata is None:
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# Create new metadata if none exists
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metadata = await get_file_info(file_path)
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# Convert to dict and add folder info
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lora_data = metadata.to_dict()
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rel_path = os.path.relpath(file_path, root_path)
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folder = os.path.dirname(rel_path)
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lora_data['folder'] = folder.replace(os.path.sep, '/')
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return lora_data
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async def update_preview_in_cache(self, file_path: str, preview_url: str) -> bool:
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"""Update preview URL in cache for a specific lora
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Args:
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file_path: The file path of the lora to update
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preview_url: The new preview URL
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Returns:
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bool: True if the update was successful, False if cache doesn't exist or lora wasn't found
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"""
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if self._cache is None:
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return False
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return await self._cache.update_preview_url(file_path, preview_url)
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async def scan_single_lora(self, file_path: str) -> Optional[Dict]:
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"""Scan a single LoRA file and return its metadata"""
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try:
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if not os.path.exists(os.path.realpath(file_path)):
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return None
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# 获取基本文件信息
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metadata = await get_file_info(file_path)
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if not metadata:
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return None
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folder = self._calculate_folder(file_path)
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# 确保 folder 字段存在
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metadata_dict = metadata.to_dict()
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metadata_dict['folder'] = folder or ''
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return metadata_dict
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except Exception as e:
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logger.error(f"Error scanning {file_path}: {e}")
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return None
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def _calculate_folder(self, file_path: str) -> str:
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"""Calculate the folder path for a LoRA file"""
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# 使用原始路径计算相对路径
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for root in config.loras_roots:
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if file_path.startswith(root):
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rel_path = os.path.relpath(file_path, root)
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return os.path.dirname(rel_path).replace(os.path.sep, '/')
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return ''
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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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# 保持原始路径格式
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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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# 其余代码保持不变
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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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# 使用真实路径进行文件操作
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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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# 使用真实路径进行文件操作
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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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# 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'], 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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# 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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# Add new methods for 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)
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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)
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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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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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|
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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
|
|
if index_entries > 0:
|
|
print("\nSample hash index entries:", file=sys.stderr)
|
|
count = 0
|
|
for hash_val, path in self._hash_index._hash_to_path.items():
|
|
if count < 5: # Just show the first 5
|
|
print(f"Hash: {hash_val[:8]}... -> Path: {path}", file=sys.stderr)
|
|
count += 1
|
|
else:
|
|
break
|
|
else:
|
|
print("Hash index not initialized", file=sys.stderr)
|
|
|
|
# Try looking up by a known hash for testing
|
|
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)
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|
|
|
# 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)
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|
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