class AlwaysEqualProxy(str): def __eq__(self, _): return True def __ne__(self, _): return False class TautologyStr(str): def __ne__(self, other): return False class ByPassTypeTuple(tuple): def __getitem__(self, index): if index>0: index=0 item = super().__getitem__(index) if isinstance(item, str): return TautologyStr(item) return item comfy_ui_revision = None def get_comfyui_revision(): try: import git import os import folder_paths repo = git.Repo(os.path.dirname(folder_paths.__file__)) comfy_ui_revision = len(list(repo.iter_commits('HEAD'))) except: comfy_ui_revision = "Unknown" return comfy_ui_revision import sys import importlib.util import importlib.metadata import comfy.model_management as mm import gc from packaging import version from server import PromptServer def is_package_installed(package): try: module = importlib.util.find_spec(package) return module is not None except ImportError as e: print(e) return False def install_package(package, v=None, compare=True, compare_version=None): run_install = True if is_package_installed(package): try: installed_version = importlib.metadata.version(package) if v is not None: if compare_version is None: compare_version = v if not compare or version.parse(installed_version) >= version.parse(compare_version): run_install = False else: run_install = False except: run_install = False if run_install: import subprocess package_command = package + '==' + v if v is not None else package PromptServer.instance.send_sync("easyuse-toast", {'content': f"Installing {package_command}...", 'duration': 5000}) result = subprocess.run([sys.executable, '-s', '-m', 'pip', 'install', package_command], capture_output=True, text=True) if result.returncode == 0: PromptServer.instance.send_sync("easyuse-toast", {'content': f"{package} installed successfully", 'type': 'success', 'duration': 5000}) print(f"Package {package} installed successfully") return True else: PromptServer.instance.send_sync("easyuse-toast", {'content': f"{package} installed failed", 'type': 'error', 'duration': 5000}) print(f"Package {package} installed failed") return False else: return False def compare_revision(num): global comfy_ui_revision if not comfy_ui_revision: comfy_ui_revision = get_comfyui_revision() return True if comfy_ui_revision == 'Unknown' or int(comfy_ui_revision) >= num else False def find_tags(string: str, sep="/") -> list[str]: """ find tags from string use the sep for split Note: string may contain the \\ or / for path separator """ if not string: return [] string = string.replace("\\", "/") while "//" in string: string = string.replace("//", "/") if string and sep in string: return string.split(sep)[:-1] return [] from comfy.model_base import BaseModel import comfy.supported_models import comfy.supported_models_base def get_sd_version(model): base: BaseModel = model.model model_config: comfy.supported_models.supported_models_base.BASE = base.model_config if isinstance(model_config, comfy.supported_models.SDXL): return 'sdxl' elif isinstance(model_config, comfy.supported_models.SDXLRefiner): return 'sdxl_refiner' elif isinstance( model_config, (comfy.supported_models.SD15, comfy.supported_models.SD20) ): return 'sd1' elif isinstance( model_config, (comfy.supported_models.SVD_img2vid) ): return 'svd' elif isinstance(model_config, comfy.supported_models.SD3): return 'sd3' elif isinstance(model_config, comfy.supported_models.HunyuanDiT): return 'hydit' elif isinstance(model_config, comfy.supported_models.Flux): return 'flux' elif isinstance(model_config, comfy.supported_models.GenmoMochi): return 'mochi' else: return 'unknown' def find_nearest_steps(clip_id, prompt): """Find the nearest KSampler or preSampling node that references the given id.""" def check_link_to_clip(node_id, clip_id, visited=None, node=None): """Check if a given node links directly or indirectly to a loader node.""" if visited is None: visited = set() if node_id in visited: return False visited.add(node_id) if "pipe" in node["inputs"]: link_ids = node["inputs"]["pipe"] for id in link_ids: if id != 0 and id == str(clip_id): return True return False for id in prompt: node = prompt[id] if "Sampler" in node["class_type"] or "sampler" in node["class_type"] or "Sampling" in node["class_type"]: # Check if this KSampler node directly or indirectly references the given CLIPTextEncode node if check_link_to_clip(id, clip_id, None, node): steps = node["inputs"]["steps"] if "steps" in node["inputs"] else 1 return steps return 1 def find_wildcards_seed(clip_id, text, prompt): """ Find easy wildcards seed value""" def find_link_clip_id(id, seed, wildcard_id): node = prompt[id] if "positive" in node['inputs']: link_ids = node["inputs"]["positive"] if type(link_ids) == list: for id in link_ids: if id != 0: if id == wildcard_id: wildcard_node = prompt[wildcard_id] seed = wildcard_node["inputs"]["seed"] if "seed" in wildcard_node["inputs"] else None if seed is None: seed = wildcard_node["inputs"]["seed_num"] if "seed_num" in wildcard_node["inputs"] else None return seed else: return find_link_clip_id(id, seed, wildcard_id) else: return None else: return None if "__" in text: seed = None for id in prompt: node = prompt[id] if "wildcards" in node["class_type"]: wildcard_id = id return find_link_clip_id(str(clip_id), seed, wildcard_id) return seed else: return None def is_linked_styles_selector(prompt, unique_id, prompt_type='positive'): unique_id = unique_id.split('.')[len(unique_id.split('.')) - 1] if "." in unique_id else unique_id inputs_values = prompt[unique_id]['inputs'][prompt_type] if prompt_type in prompt[unique_id][ 'inputs'] else None if type(inputs_values) == list and inputs_values != 'undefined' and inputs_values[0]: return True if prompt[inputs_values[0]] and prompt[inputs_values[0]]['class_type'] == 'easy stylesSelector' else False else: return False use_mirror = False def get_local_filepath(url, dirname, local_file_name=None): """Get local file path when is already downloaded or download it""" import os from server import PromptServer from urllib.parse import urlparse from torch.hub import download_url_to_file global use_mirror if not os.path.exists(dirname): os.makedirs(dirname) if not local_file_name: parsed_url = urlparse(url) local_file_name = os.path.basename(parsed_url.path) destination = os.path.join(dirname, local_file_name) if not os.path.exists(destination): try: if use_mirror: url = url.replace('huggingface.co', 'hf-mirror.com') print(f'downloading {url} to {destination}') PromptServer.instance.send_sync("easyuse-toast", {'content': f'Downloading model to {destination}, please wait...', 'duration': 10000}) download_url_to_file(url, destination) except Exception as e: use_mirror = True url = url.replace('huggingface.co', 'hf-mirror.com') print(f'无法从huggingface下载，正在尝试从 {url} 下载...') PromptServer.instance.send_sync("easyuse-toast", {'content': f'无法连接huggingface，正在尝试从 {url} 下载...', 'duration': 10000}) try: download_url_to_file(url, destination) except Exception as err: PromptServer.instance.send_sync("easyuse-toast", {'content': f'无法从 {url} 下载模型', 'type':'error'}) raise Exception(f'无法从 {url} 下载，错误信息：{str(err.args[0])}') return destination def to_lora_patch_dict(state_dict: dict) -> dict: """ Convert raw lora state_dict to patch_dict that can be applied on modelpatcher.""" patch_dict = {} for k, w in state_dict.items(): model_key, patch_type, weight_index = k.split('::') if model_key not in patch_dict: patch_dict[model_key] = {} if patch_type not in patch_dict[model_key]: patch_dict[model_key][patch_type] = [None] * 16 patch_dict[model_key][patch_type][int(weight_index)] = w patch_flat = {} for model_key, v in patch_dict.items(): for patch_type, weight_list in v.items(): patch_flat[model_key] = (patch_type, weight_list) return patch_flat def easySave(images, filename_prefix, output_type, prompt=None, extra_pnginfo=None): """Save or Preview Image""" from nodes import PreviewImage, SaveImage if output_type in ["Hide", "None"]: return list() elif output_type in ["Preview", "Preview&Choose"]: filename_prefix = 'easyPreview' results = PreviewImage().save_images(images, filename_prefix, prompt, extra_pnginfo) return results['ui']['images'] else: results = SaveImage().save_images(images, filename_prefix, prompt, extra_pnginfo) return results['ui']['images'] def getMetadata(filepath): with open(filepath, "rb") as file: # https://github.com/huggingface/safetensors#format # 8 bytes: N, an unsigned little-endian 64-bit integer, containing the size of the header header_size = int.from_bytes(file.read(8), "little", signed=False) if header_size <= 0: raise BufferError("Invalid header size") header = file.read(header_size) if header_size <= 0: raise BufferError("Invalid header") return header def cleanGPUUsedForce(): gc.collect() mm.unload_all_models() mm.soft_empty_cache()