mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2026-01-14 08:10:51 +08:00
224 lines
8.0 KiB
Python
224 lines
8.0 KiB
Python
import os
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import torch
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import hashlib
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import folder_paths
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from pathlib import Path
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# Standalone configuration - no external dependencies
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CACHE_DIR = os.path.join(folder_paths.output_directory, "cfz_conditioning_cache")
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# Simple proxy class for any type matching
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class AlwaysEqualProxy:
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def __init__(self, name):
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self.name = name
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def __eq__(self, other):
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return True
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def __ne__(self, other):
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return False
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any_type = AlwaysEqualProxy("*")
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# Simple version comparison function
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def compare_revision(target_revision):
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"""Simple version check - defaults to supporting lazy loading"""
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try:
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import comfy
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if hasattr(comfy, 'model_management') and hasattr(comfy.model_management, 'get_torch_device'):
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return True # Assume modern ComfyUI supports lazy loading
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except:
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pass
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return False
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lazy_options = {"lazy": True} if compare_revision(2543) else {}
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class save_conditioning:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"conditioning": ("CONDITIONING",), # Removed lazy_options
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"cache_name": ("STRING", {"default": "my_conditioning"}),
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}
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}
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RETURN_TYPES = ("CONDITIONING",)
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RETURN_NAMES = ("conditioning",)
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FUNCTION = "save_conditioning"
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CATEGORY = "CFZ Save-Load Conditioning"
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def save_conditioning(self, conditioning, cache_name):
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"""Save conditioning to cache with custom name"""
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# Ensure cache directory exists
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os.makedirs(CACHE_DIR, exist_ok=True)
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if not cache_name.strip():
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raise ValueError("Cache name cannot be empty")
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# Sanitize cache name (remove invalid characters)
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sanitized_name = self.sanitize_filename(cache_name)
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file_path = os.path.join(CACHE_DIR, f"{sanitized_name}.pt")
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file_path = self._resolve_path(file_path)
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print(f"[CFZ Save] Processed info:")
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print(f" - sanitized name: '{sanitized_name}'")
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print(f" - file path: {file_path}")
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# Check if conditioning is provided
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if conditioning is None:
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print("[CFZ Save] ✗ ERROR: Conditioning is None!")
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print("[CFZ Save] This suggests the CLIP Text Encode node is not connected properly")
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print("[CFZ Save] Or there's an issue with the node execution order")
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raise ValueError(f"No conditioning input provided for cache '{sanitized_name}'. Please connect conditioning input.")
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# Save conditioning (will overwrite if exists)
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try:
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print(f"[CFZ Save] Attempting to save conditioning...")
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torch.save(conditioning, file_path)
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print(f"[CFZ Save] ✓ Successfully saved: {sanitized_name}.pt")
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except Exception as e:
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print(f"[CFZ Save] ✗ Error saving: {e}")
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raise ValueError(f"Failed to save conditioning '{sanitized_name}': {str(e)}")
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return (conditioning,)
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def sanitize_filename(self, filename):
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"""Remove invalid characters from filename"""
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# Remove or replace invalid characters for filenames
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invalid_chars = '<>:"/\\|?*'
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for char in invalid_chars:
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filename = filename.replace(char, '_')
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# Remove leading/trailing spaces and dots
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filename = filename.strip(' .')
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# Ensure filename is not empty after sanitization
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if not filename:
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filename = "unnamed_conditioning"
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return filename
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def _resolve_path(self, path_str):
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"""Resolve file path using ComfyUI's path system"""
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try:
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return Path(folder_paths.get_annotated_filepath(str(path_str)))
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except:
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# Fallback to simple path if annotation fails
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return Path(path_str)
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@classmethod
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def IS_CHANGED(cls, conditioning, cache_name):
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# Change detection based on cache name
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return hashlib.sha256(f"{cache_name}".encode('utf-8')).hexdigest()
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@classmethod
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def VALIDATE_INPUTS(cls, conditioning, cache_name):
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"""Validate inputs before execution"""
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if not cache_name.strip():
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return "Cache name cannot be empty"
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return True
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class load_conditioning:
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@classmethod
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def INPUT_TYPES(cls):
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# Get list of cached files for dropdown
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cached_files = cls.get_cached_files()
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return {
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"required": {
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"cache_name": (cached_files, {"default": cached_files[0] if cached_files else ""}),
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},
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}
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RETURN_TYPES = ("CONDITIONING",)
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RETURN_NAMES = ("conditioning",)
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FUNCTION = "load_conditioning"
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CATEGORY = "CFZ Save-Load Conditioning"
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@classmethod
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def get_cached_files(cls):
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"""Get list of available cached conditioning files"""
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try:
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os.makedirs(CACHE_DIR, exist_ok=True)
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cache_files = []
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# Check if directory exists and is readable
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if not os.path.exists(CACHE_DIR):
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print(f"[CFZ Load] Cache directory doesn't exist: {CACHE_DIR}")
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return ["no_cache_directory"]
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for filename in os.listdir(CACHE_DIR):
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if filename.endswith('.pt'):
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# Remove .pt extension for display
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cache_name = filename[:-3]
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cache_files.append(cache_name)
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# Sort alphabetically
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cache_files.sort()
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# Return list with at least one option
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if cache_files:
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print(f"[CFZ Load] Found {len(cache_files)} cached files")
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return cache_files
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else:
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print("[CFZ Load] No cache files found")
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return ["no_cache_files_found"]
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except Exception as e:
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print(f"[CFZ Load] Error reading cache directory: {e}")
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return ["error_reading_cache"]
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def load_conditioning(self, cache_name):
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"""Load conditioning from selected cached file"""
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print(f"[CFZ Load] Loading conditioning:")
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print(f" - cache_name: '{cache_name}'")
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if cache_name in ["no_cache_files_found", "error_reading_cache", "no_cache_directory", ""]:
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raise ValueError("No valid cached conditioning file selected")
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file_path = os.path.join(CACHE_DIR, f"{cache_name}.pt")
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file_path = self._resolve_path(file_path)
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print(f" - file path: {file_path}")
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print(f" - file exists: {os.path.exists(file_path)}")
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if not os.path.exists(file_path):
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raise ValueError(f"Cached conditioning not found: {cache_name}.pt")
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try:
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cached_tensor = torch.load(file_path, map_location='cpu')
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print(f"[CFZ Load] ✓ Successfully loaded: {cache_name}.pt")
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print(f" - tensor type: {type(cached_tensor)}")
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return (cached_tensor,)
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except Exception as e:
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print(f"[CFZ Load] ✗ Error loading: {e}")
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raise ValueError(f"Error loading cached conditioning '{cache_name}': {str(e)}")
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def _resolve_path(self, path_str):
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"""Resolve file path using ComfyUI's path system"""
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try:
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return Path(folder_paths.get_annotated_filepath(str(path_str)))
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except:
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# Fallback to simple path if annotation fails
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return Path(path_str)
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@classmethod
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def IS_CHANGED(cls, cache_name):
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# Change detection based on selected cache file
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return cache_name
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@classmethod
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def VALIDATE_INPUTS(cls, cache_name):
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"""Validate inputs before execution"""
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if cache_name in ["no_cache_files_found", "error_reading_cache", "no_cache_directory", ""]:
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return "No cached conditioning files available"
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cache_path = os.path.join(CACHE_DIR, f"{cache_name}.pt")
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if not os.path.exists(cache_path):
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return f"Selected cache file does not exist: {cache_name}.pt"
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return True |