Dariusz L
236ca180e9
Replace direct uses of the logging module and module-level loggers with the centralized log_system.log_funcs (log_debug/log_info/log_warn/log_error/log_exception) across multiple modules. Updated imports and removed unused logging.getLogger() instances in downloader, scanner, sources (civitai, huggingface, model_list, popular), workflow_analyzer, workflow_updater, and __init__.py. Minor message/text tweaks and import formatting applied; behavior unchanged aside from routing logs through the shared logging helpers.
529 lines
18 KiB
Python
529 lines
18 KiB
Python
"""
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Model Downloader Module
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Handles downloading models from various sources with progress tracking.
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"""
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import os
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import threading
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import time
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import requests
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from typing import Dict, Any, Optional, Callable, List
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from pathlib import Path
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from collections import deque
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from .log_system.log_funcs import (
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log_debug,
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log_info,
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log_warn,
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log_error,
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log_exception,
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)
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try:
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import folder_paths
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except ImportError:
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folder_paths = None
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# Download state tracking
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download_progress: Dict[str, Dict[str, Any]] = {}
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download_lock = threading.Lock()
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cancelled_downloads: set = set()
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# Speed calculation settings
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SPEED_HISTORY_SIZE = 5 # Number of samples for smoothing
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CHUNK_SIZE = 1024 * 1024 # 1MB chunks for faster downloads
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CLI_LOG_INTERVAL = 5 # Log progress to CLI every N seconds
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def format_bytes(bytes_value: int) -> str:
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"""Format bytes to human readable string (e.g., 1.5 GB)."""
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if bytes_value == 0:
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return "0 B"
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k = 1024
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sizes = ["B", "KB", "MB", "GB", "TB"]
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i = 0
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while bytes_value >= k and i < len(sizes) - 1:
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bytes_value /= k
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i += 1
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return f"{bytes_value:.1f} {sizes[i]}"
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def get_download_directory(category: str) -> Optional[str]:
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"""
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Get the appropriate download directory for a model category.
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Args:
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category: Model category (e.g., 'checkpoints', 'loras', 'vae')
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Returns:
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Absolute path to the download directory, or None if not found
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"""
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global folder_paths
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if folder_paths is None:
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# Try to import again - ComfyUI might have initialized since last check
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try:
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import folder_paths as fp
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folder_paths = fp
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except ImportError:
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return None
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# Map common category names to folder_paths keys
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category_map = {
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"checkpoint": "checkpoints",
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"checkpoints": "checkpoints",
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"lora": "loras",
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"loras": "loras",
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"vae": "vae",
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"controlnet": "controlnet",
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"clip": "clip",
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"clip_vision": "clip_vision",
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"upscaler": "upscale_models",
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"upscale_models": "upscale_models",
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"embeddings": "embeddings",
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"embedding": "embeddings",
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"diffusion_models": "diffusion_models",
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"unet": "diffusion_models",
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"text_encoders": "text_encoders",
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"text_encoder": "text_encoders",
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"ipadapter": "ipadapter",
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"ip-adapter": "ipadapter",
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# Legacy/unsupported categories map to checkpoints as fallback
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"default": "upscale_models", # Model list uses "default" for upscalers
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}
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folder_key = category_map.get(category.lower(), category.lower())
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try:
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paths = folder_paths.get_folder_paths(folder_key)
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if paths:
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# Return the first path (usually the main models directory)
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return paths[0]
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# If category not found, try to get any models directory as fallback
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all_names = folder_paths.get_folder_names()
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if all_names:
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# Fall back to first available directory
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fallback_paths = folder_paths.get_folder_paths(all_names[0])
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if fallback_paths:
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return fallback_paths[0]
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except Exception as e:
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log_debug(f"Could not get folder path for {folder_key}: {e}")
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return None
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def generate_download_id() -> str:
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"""Generate a unique download ID."""
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import uuid
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return str(uuid.uuid4())[:8]
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def download_file(
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url: str,
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dest_path: str,
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download_id: str,
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headers: Optional[Dict[str, str]] = None,
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chunk_size: int = None,
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progress_callback: Optional[Callable[[int, int], None]] = None,
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) -> Dict[str, Any]:
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"""
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Download a file from URL with progress tracking and speed calculation.
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Args:
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url: URL to download from
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dest_path: Destination file path
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download_id: Unique ID for tracking this download
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headers: Optional HTTP headers (for auth tokens)
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chunk_size: Download chunk size in bytes (defaults to 1MB)
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progress_callback: Optional callback(downloaded_bytes, total_bytes)
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Returns:
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Result dictionary with status and info
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"""
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global download_progress, cancelled_downloads
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# Use default 1MB chunk size if not specified
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if chunk_size is None:
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chunk_size = CHUNK_SIZE
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result = {
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"success": False,
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"download_id": download_id,
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"path": dest_path,
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"error": None,
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"size": 0,
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}
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# Initialize progress tracking with speed calculation
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start_time = time.time()
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speed_history: deque = deque(maxlen=SPEED_HISTORY_SIZE)
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last_speed_update = start_time
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last_downloaded = 0
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last_cli_log = start_time # Track when we last logged to CLI
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with download_lock:
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download_progress[download_id] = {
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"status": "starting",
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"progress": 0,
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"total_size": 0,
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"downloaded": 0,
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"filename": os.path.basename(dest_path),
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"url": url,
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"error": None,
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"speed": 0, # bytes per second
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"start_time": start_time,
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}
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try:
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# Ensure destination directory exists
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os.makedirs(os.path.dirname(dest_path), exist_ok=True)
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# Verbose logging - what model and from where
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filename = os.path.basename(dest_path)
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source = (
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"HuggingFace"
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if "huggingface.co" in url
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else "CivitAI"
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if "civitai.com" in url
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else "URL"
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)
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print(f"\n[Model Linker] Starting download: {filename}")
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print(f"[Model Linker] Source: {source}")
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print(f"[Model Linker] URL: {url}")
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# Start download
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response = requests.get(url, headers=headers, stream=True, timeout=30)
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response.raise_for_status()
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# Get total size
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total_size = int(response.headers.get("content-length", 0))
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total_size_str = format_bytes(total_size) if total_size > 0 else "unknown"
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print(f"[Model Linker] Size: {total_size_str}")
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with download_lock:
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download_progress[download_id]["total_size"] = total_size
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download_progress[download_id]["status"] = "downloading"
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downloaded = 0
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# Download with progress and speed calculation
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cancelled = False
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with open(dest_path, "wb") as f:
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for chunk in response.iter_content(chunk_size=chunk_size):
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# Check for cancellation
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if download_id in cancelled_downloads:
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cancelled = True
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break
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if chunk:
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f.write(chunk)
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downloaded += len(chunk)
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# Calculate speed with smoothing
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current_time = time.time()
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time_delta = current_time - last_speed_update
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# Update speed every 0.5 seconds to avoid too frequent calculations
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if time_delta >= 0.5:
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bytes_delta = downloaded - last_downloaded
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instant_speed = (
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bytes_delta / time_delta if time_delta > 0 else 0
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)
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speed_history.append(instant_speed)
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# Calculate smoothed speed (average of recent samples)
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smoothed_speed = (
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sum(speed_history) / len(speed_history)
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if speed_history
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else 0
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)
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last_speed_update = current_time
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last_downloaded = downloaded
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# Update progress with speed
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with download_lock:
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download_progress[download_id]["downloaded"] = downloaded
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download_progress[download_id]["speed"] = int(
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smoothed_speed
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)
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if total_size > 0:
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download_progress[download_id]["progress"] = int(
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(downloaded / total_size) * 100
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)
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# CLI progress logging (every CLI_LOG_INTERVAL seconds)
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if current_time - last_cli_log >= CLI_LOG_INTERVAL:
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last_cli_log = current_time
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progress_pct = (
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int((downloaded / total_size) * 100)
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if total_size > 0
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else 0
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)
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downloaded_str = format_bytes(downloaded)
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total_str = (
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format_bytes(total_size) if total_size > 0 else "?"
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)
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speed_str = format_bytes(int(smoothed_speed)) + "/s"
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print(
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f"[Model Linker] Progress: {downloaded_str} / {total_str} ({progress_pct}%) - {speed_str}"
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)
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else:
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# Just update downloaded bytes without recalculating speed
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with download_lock:
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download_progress[download_id]["downloaded"] = downloaded
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if total_size > 0:
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download_progress[download_id]["progress"] = int(
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(downloaded / total_size) * 100
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)
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if progress_callback:
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progress_callback(downloaded, total_size)
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# Handle cancellation after file is closed (so we can delete it on Windows)
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# Also check if cancellation was requested while we were finishing up
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if cancelled or download_id in cancelled_downloads:
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with download_lock:
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download_progress[download_id]["status"] = "cancelled"
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# Clean up partial/incomplete file
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try:
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if os.path.exists(dest_path):
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os.remove(dest_path)
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print(
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f"[Model Linker] Cancelled: {filename} - incomplete file deleted"
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)
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else:
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print(f"[Model Linker] Cancelled: {filename} - no file to delete")
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except Exception as e:
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print(
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f"[Model Linker] Warning: Could not delete incomplete file {dest_path}: {e}"
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)
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# Try harder on Windows - sometimes the file handle takes a moment to release
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try:
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time.sleep(0.5) # time is already imported at module level
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if os.path.exists(dest_path):
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os.remove(dest_path)
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print(
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f"[Model Linker] Cancelled: {filename} - incomplete file deleted (delayed)"
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)
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except Exception:
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pass
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result["error"] = "Download cancelled"
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cancelled_downloads.discard(download_id)
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return result
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# Success
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with download_lock:
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download_progress[download_id]["status"] = "completed"
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download_progress[download_id]["progress"] = 100
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download_progress[download_id]["speed"] = 0 # Reset speed on completion
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result["success"] = True
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result["size"] = downloaded
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# CLI completion log
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elapsed = time.time() - start_time
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avg_speed = downloaded / elapsed if elapsed > 0 else 0
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print(f"[Model Linker] ✓ Download complete: {filename}")
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print(
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f"[Model Linker] Size: {format_bytes(downloaded)}, Time: {elapsed:.1f}s, Avg speed: {format_bytes(int(avg_speed))}/s"
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)
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except requests.exceptions.RequestException as e:
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error_msg = str(e)
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# Check for specific HTTP errors
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if hasattr(e, "response") and e.response is not None:
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status_code = e.response.status_code
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if status_code in [401, 403]:
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if "huggingface.co" in url:
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error_msg = f"Unauthorized (HTTP {status_code}): HuggingFace token may be required."
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elif "civitai.com" in url:
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error_msg = f"Unauthorized (HTTP {status_code}): CivitAI API key may be required."
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else:
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error_msg = (
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f"Unauthorized (HTTP {status_code}): Authentication required."
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)
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elif status_code == 404:
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error_msg = "Model not found (HTTP 404): The file may have been moved or deleted."
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with download_lock:
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download_progress[download_id]["status"] = "error"
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download_progress[download_id]["error"] = error_msg
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result["error"] = error_msg
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# CLI error log
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print(f"[Model Linker] ✗ Download failed: {os.path.basename(dest_path)}")
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print(f"[Model Linker] Error: {error_msg}")
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# Clean up partial file
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try:
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if os.path.exists(dest_path):
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os.remove(dest_path)
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except:
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pass
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except Exception as e:
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error_msg = str(e)
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with download_lock:
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download_progress[download_id]["status"] = "error"
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download_progress[download_id]["error"] = error_msg
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result["error"] = error_msg
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# CLI error log
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print(f"[Model Linker] ✗ Download failed: {os.path.basename(dest_path)}")
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print(f"[Model Linker] Error: {error_msg}")
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log_error(f"Download error: {e}", exc_info=True)
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return result
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def download_model(
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url: str,
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filename: str,
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category: str,
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download_id: Optional[str] = None,
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headers: Optional[Dict[str, str]] = None,
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subfolder: str = "",
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) -> Dict[str, Any]:
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"""
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Download a model to the appropriate directory.
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Args:
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url: URL to download from
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filename: Filename to save as
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category: Model category for directory selection
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download_id: Optional download ID (generated if not provided)
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headers: Optional HTTP headers
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subfolder: Optional subfolder within category directory
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Returns:
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Result dictionary
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"""
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if download_id is None:
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download_id = generate_download_id()
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# Get destination directory
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dest_dir = get_download_directory(category)
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if not dest_dir:
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return {
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"success": False,
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"download_id": download_id,
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"error": f"Could not find directory for category: {category}",
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}
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# Add subfolder if specified
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if subfolder:
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dest_dir = os.path.join(dest_dir, subfolder)
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dest_path = os.path.join(dest_dir, filename)
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# Check if file already exists
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if os.path.exists(dest_path):
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return {
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"success": False,
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"download_id": download_id,
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"error": f"File already exists: {dest_path}",
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"path": dest_path,
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}
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return download_file(url, dest_path, download_id, headers)
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def get_progress(download_id: str) -> Optional[Dict[str, Any]]:
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"""Get progress for a specific download."""
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with download_lock:
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return download_progress.get(download_id, {}).copy()
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def get_all_progress() -> Dict[str, Dict[str, Any]]:
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"""Get progress for all downloads."""
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with download_lock:
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return {k: v.copy() for k, v in download_progress.items()}
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def cancel_download(download_id: str) -> bool:
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"""Cancel a download in progress."""
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cancelled_downloads.add(download_id)
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return True
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def clear_completed_downloads():
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"""Clear completed/failed downloads from progress tracking."""
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with download_lock:
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to_remove = [
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did
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for did, info in download_progress.items()
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if info.get("status") in ("completed", "error", "cancelled")
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]
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for did in to_remove:
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del download_progress[did]
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cancelled_downloads.discard(did)
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def start_background_download(
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url: str,
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filename: str,
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category: str,
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headers: Optional[Dict[str, str]] = None,
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subfolder: str = "",
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) -> str:
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"""
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Start a download in a background thread.
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Returns:
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download_id for tracking progress
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"""
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download_id = generate_download_id()
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# Pre-initialize progress dict so it's always available for polling
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# even if download fails before download_file is called
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with download_lock:
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download_progress[download_id] = {
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"status": "starting",
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"progress": 0,
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"total_size": 0,
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"downloaded": 0,
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"filename": filename,
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"url": url,
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"error": None,
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"speed": 0,
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"start_time": time.time(),
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}
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def run_download():
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try:
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result = download_model(
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url, filename, category, download_id, headers, subfolder
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)
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if not result.get("success"):
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# Mark as error if download failed
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with download_lock:
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if download_id in download_progress:
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download_progress[download_id]["status"] = "error"
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download_progress[download_id]["error"] = result.get(
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"error", "Download failed"
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)
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except Exception as e:
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# Ensure any exception is captured and logged
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with download_lock:
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download_progress[download_id] = {
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"status": "error",
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"progress": 0,
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"total_size": 0,
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"downloaded": 0,
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"filename": filename,
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"url": url,
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"error": str(e),
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"speed": 0,
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"start_time": time.time(),
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}
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thread = threading.Thread(target=run_download, daemon=True)
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thread.start()
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return download_id
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