mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-24 14:42:11 -03:00
481 lines
20 KiB
Python
481 lines
20 KiB
Python
import os
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import json
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import jinja2
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from aiohttp import web
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import logging
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from ..utils.routes_common import ModelRouteUtils
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from ..utils.constants import NSFW_LEVELS
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from ..services.civitai_client import CivitaiClient
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from ..services.websocket_manager import ws_manager
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from ..services.checkpoint_scanner import CheckpointScanner
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from ..config import config
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from ..services.settings_manager import settings
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from ..utils.utils import fuzzy_match
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logger = logging.getLogger(__name__)
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class CheckpointsRoutes:
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"""API routes for checkpoint management"""
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def __init__(self):
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self.scanner = CheckpointScanner()
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self.template_env = jinja2.Environment(
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loader=jinja2.FileSystemLoader(config.templates_path),
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autoescape=True
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)
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def setup_routes(self, app):
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"""Register routes with the aiohttp app"""
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app.router.add_get('/checkpoints', self.handle_checkpoints_page)
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app.router.add_get('/api/checkpoints', self.get_checkpoints)
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app.router.add_post('/api/checkpoints/fetch-all-civitai', self.fetch_all_civitai)
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app.router.add_get('/api/checkpoints/base-models', self.get_base_models)
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app.router.add_get('/api/checkpoints/top-tags', self.get_top_tags)
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app.router.add_get('/api/checkpoints/scan', self.scan_checkpoints)
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app.router.add_get('/api/checkpoints/info/{name}', self.get_checkpoint_info)
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# Add new routes for model management similar to LoRA routes
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app.router.add_post('/api/checkpoints/delete', self.delete_model)
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app.router.add_post('/api/checkpoints/fetch-civitai', self.fetch_civitai)
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app.router.add_post('/api/checkpoints/replace-preview', self.replace_preview)
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async def get_checkpoints(self, request):
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"""Get paginated checkpoint data"""
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try:
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# Parse query parameters
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page = int(request.query.get('page', '1'))
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page_size = min(int(request.query.get('page_size', '20')), 100)
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sort_by = request.query.get('sort', 'name')
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folder = request.query.get('folder', None)
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search = request.query.get('search', None)
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fuzzy_search = request.query.get('fuzzy_search', 'false').lower() == 'true'
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base_models = request.query.getall('base_model', [])
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tags = request.query.getall('tag', [])
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# Process search options
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search_options = {
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'filename': request.query.get('search_filename', 'true').lower() == 'true',
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'modelname': request.query.get('search_modelname', 'true').lower() == 'true',
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'tags': request.query.get('search_tags', 'false').lower() == 'true',
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'recursive': request.query.get('recursive', 'false').lower() == 'true',
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}
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# Process hash filters if provided
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hash_filters = {}
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if 'hash' in request.query:
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hash_filters['single_hash'] = request.query['hash']
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elif 'hashes' in request.query:
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try:
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hash_list = json.loads(request.query['hashes'])
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if isinstance(hash_list, list):
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hash_filters['multiple_hashes'] = hash_list
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except (json.JSONDecodeError, TypeError):
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pass
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# Get data from scanner
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result = await self.get_paginated_data(
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page=page,
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page_size=page_size,
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sort_by=sort_by,
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folder=folder,
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search=search,
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fuzzy_search=fuzzy_search,
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base_models=base_models,
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tags=tags,
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search_options=search_options,
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hash_filters=hash_filters
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)
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# Format response items
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formatted_result = {
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'items': [self._format_checkpoint_response(cp) for cp in result['items']],
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'total': result['total'],
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'page': result['page'],
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'page_size': result['page_size'],
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'total_pages': result['total_pages']
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}
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# Return as JSON
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return web.json_response(formatted_result)
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except Exception as e:
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logger.error(f"Error in get_checkpoints: {e}", exc_info=True)
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return web.json_response({"error": str(e)}, status=500)
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async def get_paginated_data(self, page, page_size, sort_by='name',
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folder=None, search=None, fuzzy_search=False,
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base_models=None, tags=None,
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search_options=None, hash_filters=None):
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"""Get paginated and filtered checkpoint data"""
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cache = await self.scanner.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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cp for cp in filtered_data
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if cp.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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cp for cp in filtered_data
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if cp.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 in settings
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if settings.get('show_only_sfw', False):
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filtered_data = [
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cp for cp in filtered_data
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if not cp.get('preview_nsfw_level') or cp.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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cp for cp in filtered_data
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if cp['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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cp for cp in filtered_data
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if cp['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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cp for cp in filtered_data
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if cp.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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cp for cp in filtered_data
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if any(tag in cp.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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for cp in filtered_data:
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# Search by file name
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if search_options.get('filename', True):
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if fuzzy_search:
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if fuzzy_match(cp.get('file_name', ''), search):
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search_results.append(cp)
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continue
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elif search.lower() in cp.get('file_name', '').lower():
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search_results.append(cp)
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continue
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# Search by model name
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if search_options.get('modelname', True):
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if fuzzy_search:
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if fuzzy_match(cp.get('model_name', ''), search):
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search_results.append(cp)
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continue
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elif search.lower() in cp.get('model_name', '').lower():
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search_results.append(cp)
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continue
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# Search by tags
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if search_options.get('tags', False) and 'tags' in cp:
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if any((fuzzy_match(tag, search) if fuzzy_search else search.lower() in tag.lower()) for tag in cp['tags']):
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search_results.append(cp)
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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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def _format_checkpoint_response(self, checkpoint):
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"""Format checkpoint data for API response"""
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return {
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"model_name": checkpoint["model_name"],
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"file_name": checkpoint["file_name"],
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"preview_url": config.get_preview_static_url(checkpoint.get("preview_url", "")),
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"preview_nsfw_level": checkpoint.get("preview_nsfw_level", 0),
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"base_model": checkpoint.get("base_model", ""),
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"folder": checkpoint["folder"],
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"sha256": checkpoint.get("sha256", ""),
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"file_path": checkpoint["file_path"].replace(os.sep, "/"),
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"file_size": checkpoint.get("size", 0),
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"modified": checkpoint.get("modified", ""),
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"tags": checkpoint.get("tags", []),
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"modelDescription": checkpoint.get("modelDescription", ""),
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"from_civitai": checkpoint.get("from_civitai", True),
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"notes": checkpoint.get("notes", ""),
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"model_type": checkpoint.get("model_type", "checkpoint"),
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"civitai": ModelRouteUtils.filter_civitai_data(checkpoint.get("civitai", {}))
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}
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async def fetch_all_civitai(self, request: web.Request) -> web.Response:
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"""Fetch CivitAI metadata for all checkpoints in the background"""
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try:
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cache = await self.scanner.get_cached_data()
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total = len(cache.raw_data)
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processed = 0
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success = 0
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needs_resort = False
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# Prepare checkpoints to process
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to_process = [
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cp for cp in cache.raw_data
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if cp.get('sha256') and (not cp.get('civitai') or 'id' not in cp.get('civitai')) and cp.get('from_civitai', True)
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]
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total_to_process = len(to_process)
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# Send initial progress
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await ws_manager.broadcast({
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'status': 'started',
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'total': total_to_process,
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'processed': 0,
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'success': 0
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})
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# Process each checkpoint
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for cp in to_process:
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try:
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original_name = cp.get('model_name')
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if await ModelRouteUtils.fetch_and_update_model(
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sha256=cp['sha256'],
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file_path=cp['file_path'],
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model_data=cp,
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update_cache_func=self.scanner.update_single_model_cache
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):
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success += 1
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if original_name != cp.get('model_name'):
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needs_resort = True
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processed += 1
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# Send progress update
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await ws_manager.broadcast({
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'status': 'processing',
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'total': total_to_process,
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'processed': processed,
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'success': success,
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'current_name': cp.get('model_name', 'Unknown')
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})
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except Exception as e:
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logger.error(f"Error fetching CivitAI data for {cp['file_path']}: {e}")
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if needs_resort:
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await cache.resort(name_only=True)
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# Send completion message
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await ws_manager.broadcast({
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'status': 'completed',
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'total': total_to_process,
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'processed': processed,
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'success': success
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})
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return web.json_response({
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"success": True,
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"message": f"Successfully updated {success} of {processed} processed checkpoints (total: {total})"
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})
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except Exception as e:
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# Send error message
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await ws_manager.broadcast({
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'status': 'error',
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'error': str(e)
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})
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logger.error(f"Error in fetch_all_civitai for checkpoints: {e}")
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return web.Response(text=str(e), status=500)
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async def get_top_tags(self, request: web.Request) -> web.Response:
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"""Handle request for top tags sorted by frequency"""
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try:
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# Parse query parameters
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limit = int(request.query.get('limit', '20'))
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# Validate limit
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if limit < 1 or limit > 100:
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limit = 20 # Default to a reasonable limit
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# Get top tags
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top_tags = await self.scanner.get_top_tags(limit)
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return web.json_response({
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'success': True,
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'tags': top_tags
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})
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except Exception as e:
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logger.error(f"Error getting top tags: {str(e)}", exc_info=True)
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return web.json_response({
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'success': False,
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'error': 'Internal server error'
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}, status=500)
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async def get_base_models(self, request: web.Request) -> web.Response:
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"""Get base models used in loras"""
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try:
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# Parse query parameters
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limit = int(request.query.get('limit', '20'))
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# Validate limit
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if limit < 1 or limit > 100:
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limit = 20 # Default to a reasonable limit
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# Get base models
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base_models = await self.scanner.get_base_models(limit)
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return web.json_response({
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'success': True,
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'base_models': base_models
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})
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except Exception as e:
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logger.error(f"Error retrieving base models: {e}")
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return web.json_response({
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'success': False,
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'error': str(e)
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}, status=500)
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async def scan_checkpoints(self, request):
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"""Force a rescan of checkpoint files"""
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try:
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await self.scanner.get_cached_data(force_refresh=True)
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return web.json_response({"status": "success", "message": "Checkpoint scan completed"})
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except Exception as e:
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logger.error(f"Error in scan_checkpoints: {e}", exc_info=True)
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return web.json_response({"error": str(e)}, status=500)
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async def get_checkpoint_info(self, request):
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"""Get detailed information for a specific checkpoint by name"""
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try:
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name = request.match_info.get('name', '')
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checkpoint_info = await self.scanner.get_checkpoint_info_by_name(name)
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if checkpoint_info:
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return web.json_response(checkpoint_info)
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else:
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return web.json_response({"error": "Checkpoint not found"}, status=404)
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except Exception as e:
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logger.error(f"Error in get_checkpoint_info: {e}", exc_info=True)
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return web.json_response({"error": str(e)}, status=500)
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async def handle_checkpoints_page(self, request: web.Request) -> web.Response:
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"""Handle GET /checkpoints request"""
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try:
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# 检查缓存初始化状态，根据initialize_in_background的工作方式调整判断逻辑
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is_initializing = (
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self.scanner._cache is None or
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len(self.scanner._cache.raw_data) == 0 or
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hasattr(self.scanner, '_is_initializing') and self.scanner._is_initializing
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)
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if is_initializing:
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# 如果正在初始化，返回一个只包含加载提示的页面
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template = self.template_env.get_template('checkpoints.html')
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rendered = template.render(
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folders=[], # 空文件夹列表
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is_initializing=True, # 新增标志
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settings=settings, # Pass settings to template
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request=request # Pass the request object to the template
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)
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logger.info("Checkpoints page is initializing, returning loading page")
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else:
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# 正常流程 - 获取已经初始化好的缓存数据
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try:
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cache = await self.scanner.get_cached_data(force_refresh=False)
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template = self.template_env.get_template('checkpoints.html')
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rendered = template.render(
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folders=cache.folders,
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is_initializing=False,
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settings=settings, # Pass settings to template
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request=request # Pass the request object to the template
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)
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except Exception as cache_error:
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logger.error(f"Error loading checkpoints cache data: {cache_error}")
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# 如果获取缓存失败，也显示初始化页面
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template = self.template_env.get_template('checkpoints.html')
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rendered = template.render(
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folders=[],
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is_initializing=True,
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settings=settings,
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request=request
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)
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logger.info("Checkpoints cache error, returning initialization page")
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return web.Response(
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text=rendered,
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content_type='text/html'
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)
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except Exception as e:
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logger.error(f"Error handling checkpoints request: {e}", exc_info=True)
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return web.Response(
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text="Error loading checkpoints page",
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status=500
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)
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async def delete_model(self, request: web.Request) -> web.Response:
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"""Handle checkpoint model deletion request"""
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return await ModelRouteUtils.handle_delete_model(request, self.scanner)
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async def fetch_civitai(self, request: web.Request) -> web.Response:
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"""Handle CivitAI metadata fetch request for checkpoints"""
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return await ModelRouteUtils.handle_fetch_civitai(request, self.scanner)
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async def replace_preview(self, request: web.Request) -> web.Response:
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"""Handle preview image replacement for checkpoints"""
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return await ModelRouteUtils.handle_replace_preview(request, self.scanner)
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