mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-22 05:32:12 -03:00
304 lines
14 KiB
Python
304 lines
14 KiB
Python
import logging
|
|
import os
|
|
import json
|
|
import asyncio
|
|
from typing import Dict
|
|
from ..utils.models import LoraMetadata, CheckpointMetadata
|
|
from ..utils.constants import CARD_PREVIEW_WIDTH
|
|
from ..utils.exif_utils import ExifUtils
|
|
from .service_registry import ServiceRegistry
|
|
|
|
# Download to temporary file first
|
|
import tempfile
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
class DownloadManager:
|
|
_instance = None
|
|
_lock = asyncio.Lock()
|
|
|
|
@classmethod
|
|
async def get_instance(cls):
|
|
"""Get singleton instance of DownloadManager"""
|
|
async with cls._lock:
|
|
if cls._instance is None:
|
|
cls._instance = cls()
|
|
return cls._instance
|
|
|
|
def __init__(self):
|
|
# Check if already initialized for singleton pattern
|
|
if hasattr(self, '_initialized'):
|
|
return
|
|
self._initialized = True
|
|
|
|
self._civitai_client = None # Will be lazily initialized
|
|
|
|
async def _get_civitai_client(self):
|
|
"""Lazily initialize CivitaiClient from registry"""
|
|
if self._civitai_client is None:
|
|
self._civitai_client = await ServiceRegistry.get_civitai_client()
|
|
return self._civitai_client
|
|
|
|
async def _get_lora_scanner(self):
|
|
"""Get the lora scanner from registry"""
|
|
return await ServiceRegistry.get_lora_scanner()
|
|
|
|
async def _get_checkpoint_scanner(self):
|
|
"""Get the checkpoint scanner from registry"""
|
|
return await ServiceRegistry.get_checkpoint_scanner()
|
|
|
|
async def download_from_civitai(self, download_url: str = None, model_hash: str = None,
|
|
model_version_id: str = None, save_dir: str = None,
|
|
relative_path: str = '', progress_callback=None,
|
|
model_type: str = "lora") -> Dict:
|
|
"""Download model from Civitai
|
|
|
|
Args:
|
|
download_url: Direct download URL for the model
|
|
model_hash: SHA256 hash of the model
|
|
model_version_id: Civitai model version ID
|
|
save_dir: Directory to save the model to
|
|
relative_path: Relative path within save_dir
|
|
progress_callback: Callback function for progress updates
|
|
model_type: Type of model ('lora' or 'checkpoint')
|
|
|
|
Returns:
|
|
Dict with download result
|
|
"""
|
|
try:
|
|
# Update save directory with relative path if provided
|
|
if relative_path:
|
|
save_dir = os.path.join(save_dir, relative_path)
|
|
# Create directory if it doesn't exist
|
|
os.makedirs(save_dir, exist_ok=True)
|
|
|
|
# Get civitai client
|
|
civitai_client = await self._get_civitai_client()
|
|
|
|
# Get version info based on the provided identifier
|
|
version_info = None
|
|
error_msg = None
|
|
|
|
if model_hash:
|
|
# Get model by hash
|
|
version_info = await civitai_client.get_model_by_hash(model_hash)
|
|
elif model_version_id:
|
|
# Use model version ID directly
|
|
version_info, error_msg = await civitai_client.get_model_version_info(model_version_id)
|
|
elif download_url:
|
|
# Extract version ID from download URL
|
|
version_id = download_url.split('/')[-1]
|
|
version_info, error_msg = await civitai_client.get_model_version_info(version_id)
|
|
|
|
|
|
if not version_info:
|
|
if error_msg and "model not found" in error_msg.lower():
|
|
return {'success': False, 'error': f'Model not found on Civitai: {error_msg}'}
|
|
return {'success': False, 'error': error_msg or 'Failed to fetch model metadata'}
|
|
|
|
# Check if this is an early access model
|
|
if version_info.get('earlyAccessEndsAt'):
|
|
early_access_date = version_info.get('earlyAccessEndsAt', '')
|
|
# Convert to a readable date if possible
|
|
try:
|
|
from datetime import datetime
|
|
date_obj = datetime.fromisoformat(early_access_date.replace('Z', '+00:00'))
|
|
formatted_date = date_obj.strftime('%Y-%m-%d')
|
|
early_access_msg = f"This model requires early access payment (until {formatted_date}). "
|
|
except:
|
|
early_access_msg = "This model requires early access payment. "
|
|
|
|
early_access_msg += "Please ensure you have purchased early access and are logged in to Civitai."
|
|
logger.warning(f"Early access model detected: {version_info.get('name', 'Unknown')}")
|
|
|
|
# We'll still try to download, but log a warning and prepare for potential failure
|
|
if progress_callback:
|
|
await progress_callback(1) # Show minimal progress to indicate we're trying
|
|
|
|
# Report initial progress
|
|
if progress_callback:
|
|
await progress_callback(0)
|
|
|
|
# 2. Get file information
|
|
file_info = next((f for f in version_info.get('files', []) if f.get('primary')), None)
|
|
if not file_info:
|
|
return {'success': False, 'error': 'No primary file found in metadata'}
|
|
|
|
# 3. Prepare download
|
|
file_name = file_info['name']
|
|
save_path = os.path.join(save_dir, file_name)
|
|
|
|
# 5. Prepare metadata based on model type
|
|
if model_type == "checkpoint":
|
|
metadata = CheckpointMetadata.from_civitai_info(version_info, file_info, save_path)
|
|
logger.info(f"Creating CheckpointMetadata for {file_name}")
|
|
else:
|
|
metadata = LoraMetadata.from_civitai_info(version_info, file_info, save_path)
|
|
logger.info(f"Creating LoraMetadata for {file_name}")
|
|
|
|
# 5.1 Get and update model tags, description and creator info
|
|
model_id = version_info.get('modelId')
|
|
if model_id:
|
|
model_metadata, _ = await civitai_client.get_model_metadata(str(model_id))
|
|
if model_metadata:
|
|
if model_metadata.get("tags"):
|
|
metadata.tags = model_metadata.get("tags", [])
|
|
if model_metadata.get("description"):
|
|
metadata.modelDescription = model_metadata.get("description", "")
|
|
if model_metadata.get("creator"):
|
|
metadata.civitai["creator"] = model_metadata.get("creator")
|
|
|
|
# 6. Start download process
|
|
result = await self._execute_download(
|
|
download_url=file_info.get('downloadUrl', ''),
|
|
save_dir=save_dir,
|
|
metadata=metadata,
|
|
version_info=version_info,
|
|
relative_path=relative_path,
|
|
progress_callback=progress_callback,
|
|
model_type=model_type
|
|
)
|
|
|
|
return result
|
|
|
|
except Exception as e:
|
|
logger.error(f"Error in download_from_civitai: {e}", exc_info=True)
|
|
# Check if this might be an early access error
|
|
error_str = str(e).lower()
|
|
if "403" in error_str or "401" in error_str or "unauthorized" in error_str or "early access" in error_str:
|
|
return {'success': False, 'error': f"Early access restriction: {str(e)}. Please ensure you have purchased early access and are logged in to Civitai."}
|
|
return {'success': False, 'error': str(e)}
|
|
|
|
async def _execute_download(self, download_url: str, save_dir: str,
|
|
metadata, version_info: Dict,
|
|
relative_path: str, progress_callback=None,
|
|
model_type: str = "lora") -> Dict:
|
|
"""Execute the actual download process including preview images and model files"""
|
|
try:
|
|
civitai_client = await self._get_civitai_client()
|
|
save_path = metadata.file_path
|
|
metadata_path = os.path.splitext(save_path)[0] + '.metadata.json'
|
|
|
|
# Download preview image if available
|
|
images = version_info.get('images', [])
|
|
if images:
|
|
# Report preview download progress
|
|
if progress_callback:
|
|
await progress_callback(1) # 1% progress for starting preview download
|
|
|
|
# Check if it's a video or an image
|
|
is_video = images[0].get('type') == 'video'
|
|
|
|
if (is_video):
|
|
# For videos, use .mp4 extension
|
|
preview_ext = '.mp4'
|
|
preview_path = os.path.splitext(save_path)[0] + preview_ext
|
|
|
|
# Download video directly
|
|
if await civitai_client.download_preview_image(images[0]['url'], preview_path):
|
|
metadata.preview_url = preview_path.replace(os.sep, '/')
|
|
metadata.preview_nsfw_level = images[0].get('nsfwLevel', 0)
|
|
with open(metadata_path, 'w', encoding='utf-8') as f:
|
|
json.dump(metadata.to_dict(), f, indent=2, ensure_ascii=False)
|
|
else:
|
|
# For images, use WebP format for better performance
|
|
with tempfile.NamedTemporaryFile(suffix='.png', delete=False) as temp_file:
|
|
temp_path = temp_file.name
|
|
|
|
# Download the original image to temp path
|
|
if await civitai_client.download_preview_image(images[0]['url'], temp_path):
|
|
# Optimize and convert to WebP
|
|
preview_path = os.path.splitext(save_path)[0] + '.webp'
|
|
|
|
# Use ExifUtils to optimize and convert the image
|
|
optimized_data, _ = ExifUtils.optimize_image(
|
|
image_data=temp_path,
|
|
target_width=CARD_PREVIEW_WIDTH,
|
|
format='webp',
|
|
quality=85,
|
|
preserve_metadata=False
|
|
)
|
|
|
|
# Save the optimized image
|
|
with open(preview_path, 'wb') as f:
|
|
f.write(optimized_data)
|
|
|
|
# Update metadata
|
|
metadata.preview_url = preview_path.replace(os.sep, '/')
|
|
metadata.preview_nsfw_level = images[0].get('nsfwLevel', 0)
|
|
with open(metadata_path, 'w', encoding='utf-8') as f:
|
|
json.dump(metadata.to_dict(), f, indent=2, ensure_ascii=False)
|
|
|
|
# Remove temporary file
|
|
try:
|
|
os.unlink(temp_path)
|
|
except Exception as e:
|
|
logger.warning(f"Failed to delete temp file: {e}")
|
|
|
|
# Report preview download completion
|
|
if progress_callback:
|
|
await progress_callback(3) # 3% progress after preview download
|
|
|
|
# Download model file with progress tracking
|
|
success, result = await civitai_client._download_file(
|
|
download_url,
|
|
save_dir,
|
|
os.path.basename(save_path),
|
|
progress_callback=lambda p: self._handle_download_progress(p, progress_callback)
|
|
)
|
|
|
|
if not success:
|
|
# Clean up files on failure
|
|
for path in [save_path, metadata_path, metadata.preview_url]:
|
|
if path and os.path.exists(path):
|
|
os.remove(path)
|
|
return {'success': False, 'error': result}
|
|
|
|
# 4. Update file information (size and modified time)
|
|
metadata.update_file_info(save_path)
|
|
|
|
# 5. Final metadata update
|
|
with open(metadata_path, 'w', encoding='utf-8') as f:
|
|
json.dump(metadata.to_dict(), f, indent=2, ensure_ascii=False)
|
|
|
|
# 6. Update cache based on model type
|
|
if model_type == "checkpoint":
|
|
scanner = await self._get_checkpoint_scanner()
|
|
logger.info(f"Updating checkpoint cache for {save_path}")
|
|
else:
|
|
scanner = await self._get_lora_scanner()
|
|
logger.info(f"Updating lora cache for {save_path}")
|
|
|
|
# Convert metadata to dictionary
|
|
metadata_dict = metadata.to_dict()
|
|
|
|
# Add model to cache and save to disk in a single operation
|
|
await scanner.add_model_to_cache(metadata_dict, relative_path)
|
|
|
|
# Report 100% completion
|
|
if progress_callback:
|
|
await progress_callback(100)
|
|
|
|
return {
|
|
'success': True
|
|
}
|
|
|
|
except Exception as e:
|
|
logger.error(f"Error in _execute_download: {e}", exc_info=True)
|
|
# Clean up partial downloads
|
|
for path in [save_path, metadata_path]:
|
|
if path and os.path.exists(path):
|
|
os.remove(path)
|
|
return {'success': False, 'error': str(e)}
|
|
|
|
async def _handle_download_progress(self, file_progress: float, progress_callback):
|
|
"""Convert file download progress to overall progress
|
|
|
|
Args:
|
|
file_progress: Progress of file download (0-100)
|
|
progress_callback: Callback function for progress updates
|
|
"""
|
|
if progress_callback:
|
|
# Scale file progress to 3-100 range (after preview download)
|
|
overall_progress = 3 + (file_progress * 0.97) # 97% of progress for file download
|
|
await progress_callback(round(overall_progress)) |