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Refactor example images code
This commit is contained in:
Will Miao
389
py/utils/example_images_download_manager.py
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389
py/utils/example_images_download_manager.py
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import logging
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import os
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import asyncio
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import json
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import time
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import aiohttp
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from aiohttp import web
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from ..services.service_registry import ServiceRegistry
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from .example_images_processor import ExampleImagesProcessor
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from .example_images_metadata import MetadataUpdater
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logger = logging.getLogger(__name__)
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# Download status tracking
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download_task = None
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is_downloading = False
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download_progress = {
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'total': 0,
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'completed': 0,
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'current_model': '',
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'status': 'idle', # idle, running, paused, completed, error
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'errors': [],
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'last_error': None,
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'start_time': None,
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'end_time': None,
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'processed_models': set(), # Track models that have been processed
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'refreshed_models': set() # Track models that had metadata refreshed
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}
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class DownloadManager:
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"""Manages downloading example images for models"""
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@staticmethod
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async def start_download(request):
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"""
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Start downloading example images for models
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Expects a JSON body with:
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{
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"output_dir": "path/to/output", # Base directory to save example images
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"optimize": true, # Whether to optimize images (default: true)
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"model_types": ["lora", "checkpoint"], # Model types to process (default: both)
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"delay": 1.0 # Delay between downloads to avoid rate limiting (default: 1.0)
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}
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"""
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global download_task, is_downloading, download_progress
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if is_downloading:
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# Create a copy for JSON serialization
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response_progress = download_progress.copy()
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response_progress['processed_models'] = list(download_progress['processed_models'])
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response_progress['refreshed_models'] = list(download_progress['refreshed_models'])
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return web.json_response({
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'success': False,
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'error': 'Download already in progress',
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'status': response_progress
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}, status=400)
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try:
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# Parse the request body
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data = await request.json()
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output_dir = data.get('output_dir')
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optimize = data.get('optimize', True)
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model_types = data.get('model_types', ['lora', 'checkpoint'])
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delay = float(data.get('delay', 0.2)) # Default to 0.2 seconds
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if not output_dir:
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return web.json_response({
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'success': False,
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'error': 'Missing output_dir parameter'
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}, status=400)
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# Create the output directory
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os.makedirs(output_dir, exist_ok=True)
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# Initialize progress tracking
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download_progress['total'] = 0
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download_progress['completed'] = 0
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download_progress['current_model'] = ''
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download_progress['status'] = 'running'
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download_progress['errors'] = []
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download_progress['last_error'] = None
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download_progress['start_time'] = time.time()
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download_progress['end_time'] = None
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# Get the processed models list from a file if it exists
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progress_file = os.path.join(output_dir, '.download_progress.json')
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if os.path.exists(progress_file):
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try:
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with open(progress_file, 'r', encoding='utf-8') as f:
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saved_progress = json.load(f)
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download_progress['processed_models'] = set(saved_progress.get('processed_models', []))
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logger.info(f"Loaded previous progress, {len(download_progress['processed_models'])} models already processed")
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except Exception as e:
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logger.error(f"Failed to load progress file: {e}")
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download_progress['processed_models'] = set()
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else:
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download_progress['processed_models'] = set()
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# Start the download task
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is_downloading = True
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download_task = asyncio.create_task(
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DownloadManager._download_all_example_images(
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output_dir,
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optimize,
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model_types,
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delay
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)
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)
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# Create a copy for JSON serialization
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response_progress = download_progress.copy()
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response_progress['processed_models'] = list(download_progress['processed_models'])
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response_progress['refreshed_models'] = list(download_progress['refreshed_models'])
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return web.json_response({
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'success': True,
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'message': 'Download started',
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'status': response_progress
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})
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except Exception as e:
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logger.error(f"Failed to start example images download: {e}", exc_info=True)
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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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@staticmethod
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async def get_status(request):
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"""Get the current status of example images download"""
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global download_progress
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# Create a copy of the progress dict with the set converted to a list for JSON serialization
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response_progress = download_progress.copy()
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response_progress['processed_models'] = list(download_progress['processed_models'])
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response_progress['refreshed_models'] = list(download_progress['refreshed_models'])
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return web.json_response({
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'success': True,
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'is_downloading': is_downloading,
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'status': response_progress
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})
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@staticmethod
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async def pause_download(request):
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"""Pause the example images download"""
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global download_progress
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if not is_downloading:
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return web.json_response({
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'success': False,
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'error': 'No download in progress'
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}, status=400)
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download_progress['status'] = 'paused'
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return web.json_response({
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'success': True,
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'message': 'Download paused'
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})
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@staticmethod
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async def resume_download(request):
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"""Resume the example images download"""
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global download_progress
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if not is_downloading:
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return web.json_response({
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'success': False,
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'error': 'No download in progress'
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}, status=400)
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if download_progress['status'] == 'paused':
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download_progress['status'] = 'running'
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return web.json_response({
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'success': True,
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'message': 'Download resumed'
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})
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else:
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return web.json_response({
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'success': False,
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'error': f"Download is in '{download_progress['status']}' state, cannot resume"
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}, status=400)
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@staticmethod
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async def _download_all_example_images(output_dir, optimize, model_types, delay):
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"""Download example images for all models"""
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global is_downloading, download_progress
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# Create independent download session
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connector = aiohttp.TCPConnector(
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ssl=True,
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limit=3,
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force_close=False,
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enable_cleanup_closed=True
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)
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timeout = aiohttp.ClientTimeout(total=None, connect=60, sock_read=60)
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independent_session = aiohttp.ClientSession(
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connector=connector,
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trust_env=True,
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timeout=timeout
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)
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try:
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# Get scanners
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scanners = []
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if 'lora' in model_types:
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lora_scanner = await ServiceRegistry.get_lora_scanner()
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scanners.append(('lora', lora_scanner))
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if 'checkpoint' in model_types:
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checkpoint_scanner = await ServiceRegistry.get_checkpoint_scanner()
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scanners.append(('checkpoint', checkpoint_scanner))
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# Get all models
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all_models = []
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for scanner_type, scanner in scanners:
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cache = await scanner.get_cached_data()
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if cache and cache.raw_data:
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for model in cache.raw_data:
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if model.get('sha256'):
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all_models.append((scanner_type, model, scanner))
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# Update total count
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download_progress['total'] = len(all_models)
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logger.info(f"Found {download_progress['total']} models to process")
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# Process each model
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for i, (scanner_type, model, scanner) in enumerate(all_models):
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# Main logic for processing model is here, but actual operations are delegated to other classes
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was_remote_download = await DownloadManager._process_model(
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scanner_type, model, scanner,
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output_dir, optimize, independent_session
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)
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# Update progress
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download_progress['completed'] += 1
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# Only add delay after remote download of models, and not after processing the last model
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if was_remote_download and i < len(all_models) - 1 and download_progress['status'] == 'running':
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await asyncio.sleep(delay)
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# Mark as completed
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download_progress['status'] = 'completed'
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download_progress['end_time'] = time.time()
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logger.info(f"Example images download completed: {download_progress['completed']}/{download_progress['total']} models processed")
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except Exception as e:
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error_msg = f"Error during example images download: {str(e)}"
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logger.error(error_msg, exc_info=True)
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download_progress['errors'].append(error_msg)
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download_progress['last_error'] = error_msg
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download_progress['status'] = 'error'
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download_progress['end_time'] = time.time()
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finally:
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# Close the independent session
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try:
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await independent_session.close()
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except Exception as e:
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logger.error(f"Error closing download session: {e}")
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# Save final progress to file
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try:
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progress_file = os.path.join(output_dir, '.download_progress.json')
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with open(progress_file, 'w', encoding='utf-8') as f:
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json.dump({
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'processed_models': list(download_progress['processed_models']),
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'refreshed_models': list(download_progress['refreshed_models']),
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'completed': download_progress['completed'],
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'total': download_progress['total'],
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'last_update': time.time(),
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'status': download_progress['status']
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}, f, indent=2)
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except Exception as e:
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logger.error(f"Failed to save progress file: {e}")
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# Set download status to not downloading
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is_downloading = False
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@staticmethod
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async def _process_model(scanner_type, model, scanner, output_dir, optimize, independent_session):
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"""Process a single model download"""
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global download_progress
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# Check if download is paused
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while download_progress['status'] == 'paused':
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await asyncio.sleep(1)
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# Check if download should continue
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if download_progress['status'] != 'running':
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logger.info(f"Download stopped: {download_progress['status']}")
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return False # Return False to indicate no remote download happened
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model_hash = model.get('sha256', '').lower()
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model_name = model.get('model_name', 'Unknown')
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model_file_path = model.get('file_path', '')
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model_file_name = model.get('file_name', '')
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try:
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# Update current model info
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download_progress['current_model'] = f"{model_name} ({model_hash[:8]})"
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# Skip if already processed
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if model_hash in download_progress['processed_models']:
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logger.debug(f"Skipping already processed model: {model_name}")
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return False
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# Create model directory
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model_dir = os.path.join(output_dir, model_hash)
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os.makedirs(model_dir, exist_ok=True)
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# First check for local example images - local processing doesn't need delay
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local_images_processed = await ExampleImagesProcessor.process_local_examples(
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model_file_path, model_file_name, model_name, model_dir, optimize
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)
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# If we processed local images, update metadata
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if local_images_processed:
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await MetadataUpdater.update_metadata_from_local_examples(
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model_hash, model, scanner_type, scanner, model_dir
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)
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download_progress['processed_models'].add(model_hash)
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return False # Return False to indicate no remote download happened
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# If no local images, try to download from remote
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elif model.get('civitai') and model.get('civitai', {}).get('images'):
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images = model.get('civitai', {}).get('images', [])
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success, is_stale = await ExampleImagesProcessor.download_model_images(
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model_hash, model_name, images, model_dir, optimize, independent_session
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)
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# If metadata is stale, try to refresh it
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if is_stale and model_hash not in download_progress['refreshed_models']:
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await MetadataUpdater.refresh_model_metadata(
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model_hash, model_name, scanner_type, scanner
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)
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# Get the updated model data
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updated_model = await MetadataUpdater.get_updated_model(
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model_hash, scanner
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)
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if updated_model and updated_model.get('civitai', {}).get('images'):
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# Retry download with updated metadata
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updated_images = updated_model.get('civitai', {}).get('images', [])
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success, _ = await ExampleImagesProcessor.download_model_images(
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model_hash, model_name, updated_images, model_dir, optimize, independent_session
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)
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# Only mark as processed if all images were downloaded successfully
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if success:
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download_progress['processed_models'].add(model_hash)
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return True # Return True to indicate a remote download happened
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# Save progress periodically
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if download_progress['completed'] % 10 == 0 or download_progress['completed'] == download_progress['total'] - 1:
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DownloadManager._save_progress(output_dir)
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return False # Default return if no conditions met
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except Exception as e:
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error_msg = f"Error processing model {model.get('model_name')}: {str(e)}"
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logger.error(error_msg, exc_info=True)
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download_progress['errors'].append(error_msg)
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download_progress['last_error'] = error_msg
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return False # Return False on exception
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@staticmethod
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def _save_progress(output_dir):
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"""Save download progress to file"""
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global download_progress
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try:
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progress_file = os.path.join(output_dir, '.download_progress.json')
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with open(progress_file, 'w', encoding='utf-8') as f:
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json.dump({
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'processed_models': list(download_progress['processed_models']),
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'refreshed_models': list(download_progress['refreshed_models']),
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'completed': download_progress['completed'],
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'total': download_progress['total'],
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'last_update': time.time()
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}, f, indent=2)
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except Exception as e:
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logger.error(f"Failed to save progress file: {e}")
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