import os import random import sys import json import argparse import contextlib from typing import Sequence, Mapping, Any, Union import torch from random import randrange def get_value_at_index(obj: Union[Sequence, Mapping], index: int) -> Any: """Returns the value at the given index of a sequence or mapping. If the object is a sequence (like list or string), returns the value at the given index. If the object is a mapping (like a dictionary), returns the value at the index-th key. Some return a dictionary, in these cases, we look for the "results" key Args: obj (Union[Sequence, Mapping]): The object to retrieve the value from. index (int): The index of the value to retrieve. Returns: Any: The value at the given index. Raises: IndexError: If the index is out of bounds for the object and the object is not a mapping. """ try: return obj[index] except KeyError: return obj["result"][index] def find_path(name: str, path: str = None) -> str: """ Recursively looks at parent folders starting from the given path until it finds the given name. Returns the path as a Path object if found, or None otherwise. """ # If no path is given, use the current working directory if path is None: if args is None or args.comfyui_directory is None: path = os.getcwd() else: path = args.comfyui_directory # Check if the current directory contains the name if name in os.listdir(path): path_name = os.path.join(path, name) print(f"{name} found: {path_name}") return path_name # Get the parent directory parent_directory = os.path.dirname(path) # If the parent directory is the same as the current directory, we've reached the root and stop the search if parent_directory == path: return None # Recursively call the function with the parent directory return find_path(name, parent_directory) def add_comfyui_directory_to_sys_path() -> None: """ Add 'ComfyUI' to the sys.path """ comfyui_path = find_path("ComfyUI") if comfyui_path is not None and os.path.isdir(comfyui_path): sys.path.append(comfyui_path) manager_path = os.path.join( comfyui_path, "custom_nodes", "ComfyUI-Manager", "glob" ) if os.path.isdir(manager_path) and os.listdir(manager_path): sys.path.append(manager_path) global has_manager has_manager = True import __main__ if getattr(__main__, "__file__", None) is None: __main__.__file__ = os.path.join(comfyui_path, "main.py") print(f"'{comfyui_path}' added to sys.path") def add_extra_model_paths() -> None: """ Parse the optional extra_model_paths.yaml file and add the parsed paths to the sys.path. """ from comfy.options import enable_args_parsing enable_args_parsing() from utils.extra_config import load_extra_path_config extra_model_paths = find_path("extra_model_paths.yaml") if extra_model_paths is not None: load_extra_path_config(extra_model_paths) else: print("Could not find the extra_model_paths config file.") def import_custom_nodes() -> None: """Find all custom nodes in the custom_nodes folder and add those node objects to NODE_CLASS_MAPPINGS This function sets up a new asyncio event loop, initializes the PromptServer, creates a PromptQueue, and initializes the custom nodes. """ if has_manager: try: import manager_core as manager except ImportError: print("Could not import manager_core, proceeding without it.") return else: if hasattr(manager, "get_config"): print("Patching manager_core.get_config to enforce offline mode.") try: get_config = manager.get_config def _get_config(*args, **kwargs): config = get_config(*args, **kwargs) config["network_mode"] = "offline" return config manager.get_config = _get_config except Exception as e: print("Failed to patch manager_core.get_config:", e) import asyncio import execution from nodes import init_extra_nodes import server # Creating a new event loop and setting it as the default loop loop = asyncio.new_event_loop() asyncio.set_event_loop(loop) async def inner(): # Creating an instance of PromptServer with the loop server_instance = server.PromptServer(loop) execution.PromptQueue(server_instance) # Initializing custom nodes await init_extra_nodes(init_custom_nodes=True) loop.run_until_complete(inner()) def save_image_wrapper(context, cls): if args.output is None: return cls from PIL import Image, ImageOps, ImageSequence from PIL.PngImagePlugin import PngInfo import numpy as np class WrappedSaveImage(cls): counter = 0 def save_images( self, images, filename_prefix="ComfyUI", prompt=None, extra_pnginfo=None ): if args.output is None: return super().save_images( images, filename_prefix, prompt, extra_pnginfo ) else: if len(images) > 1 and args.output == "-": raise ValueError("Cannot save multiple images to stdout") filename_prefix += self.prefix_append results = list() for batch_number, image in enumerate(images): i = 255.0 * image.cpu().numpy() img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8)) metadata = None if not args.disable_metadata: metadata = PngInfo() if prompt is not None: metadata.add_text("prompt", json.dumps(prompt)) if extra_pnginfo is not None: for x in extra_pnginfo: metadata.add_text(x, json.dumps(extra_pnginfo[x])) if args.output == "-": # Hack to briefly restore stdout if context is not None: context.__exit__(None, None, None) try: img.save( sys.stdout.buffer, format="png", pnginfo=metadata, compress_level=self.compress_level, ) finally: if context is not None: context.__enter__() else: subfolder = "" if len(images) == 1: if os.path.isdir(args.output): subfolder = args.output file = "output.png" else: subfolder, file = os.path.split(args.output) if subfolder == "": subfolder = os.getcwd() else: if os.path.isdir(args.output): subfolder = args.output file = filename_prefix else: subfolder, file = os.path.split(args.output) if subfolder == "": subfolder = os.getcwd() files = os.listdir(subfolder) file_pattern = file while True: filename_with_batch_num = file_pattern.replace( "%batch_num%", str(batch_number) ) file = ( f"{filename_with_batch_num}_{self.counter:05}.png" ) self.counter += 1 if file not in files: break img.save( os.path.join(subfolder, file), pnginfo=metadata, compress_level=self.compress_level, ) print("Saved image to", os.path.join(subfolder, file)) results.append( { "filename": file, "subfolder": subfolder, "type": self.type, } ) return {"ui": {"images": results}} return WrappedSaveImage def parse_arg(s: Any, default: Any = None) -> Any: """Parses a JSON string, returning it unchanged if the parsing fails.""" if __name__ == "__main__" or not isinstance(s, str): return s try: return json.loads(s) except json.JSONDecodeError: return s parser = argparse.ArgumentParser( description="A converted ComfyUI workflow. Node inputs listed below. Values passed should be valid JSON (assumes string if not valid JSON)." ) parser.add_argument( "--ckpt_name1", default="SDXLCheckpoint.safetensors", help='Argument 0, input `ckpt_name` for node "Load Checkpoint" id 14 (autogenerated)', ) parser.add_argument( "--text2", default="Xx_negative_xX", help='Argument 0, input `text` for node "CLIP Text Encode (Prompt)" id 7 (autogenerated)', ) parser.add_argument( "--text3", default="Xx_positive_xX", help='Argument 0, input `text` for node "CLIPTextEncode with BREAK syntax" id 15 (autogenerated)', ) parser.add_argument( "--image4", default="Fast_00076_.png [output]", help='Argument 0, input `image` for node "Load Image (from Outputs)" id 24 (autogenerated)', ) parser.add_argument( "--seed5", default=550873067544100, help='Argument 1, input `seed` for node "KSampler" id 3 (autogenerated)', ) parser.add_argument( "--steps6", default=28, help='Argument 2, input `steps` for node "KSampler" id 3 (autogenerated)', ) parser.add_argument( "--cfg7", default=4.5, help='Argument 3, input `cfg` for node "KSampler" id 3 (autogenerated)', ) parser.add_argument( "--sampler_name8", default="euler_ancestral", help='Argument 4, input `sampler_name` for node "KSampler" id 3 (autogenerated)', ) parser.add_argument( "--scheduler9", default="normal", help='Argument 5, input `scheduler` for node "KSampler" id 3 (autogenerated)', ) parser.add_argument( "--denoise10", default=0.87, help='Argument 9, input `denoise` for node "KSampler" id 3 (autogenerated)', ) parser.add_argument( "--filename_prefix11", default="Fixed", help='Argument 1, input `filename_prefix` for node "Save Image" id 9 (autogenerated)', ) parser.add_argument( "--queue-size", "-q", type=int, default=1, help="How many times the workflow will be executed (default: 1)", ) parser.add_argument( "--comfyui-directory", "-c", default=None, help="Where to look for ComfyUI (default: current directory)", ) parser.add_argument( "--output", "-o", default=None, help="The location to save the output image. Either a file path, a directory, or - for stdout (default: the ComfyUI output directory)", ) parser.add_argument( "--disable-metadata", action="store_true", help="Disables writing workflow metadata to the outputs", ) comfy_args = [sys.argv[0]] if __name__ == "__main__" and "--" in sys.argv: idx = sys.argv.index("--") comfy_args += sys.argv[idx + 1 :] sys.argv = sys.argv[:idx] args = None if __name__ == "__main__": args = parser.parse_args() sys.argv = comfy_args if args is not None and args.output is not None and args.output == "-": ctx = contextlib.redirect_stdout(sys.stderr) else: ctx = contextlib.nullcontext() PROMPT_DATA = json.loads( '{"3": {"inputs": {"seed": 550873067544100, "steps": 28, "cfg": 4.5, "sampler_name": "euler_ancestral", "scheduler": "normal", "denoise": 0.87, "model": ["14", 0], "positive": ["15", 0], "negative": ["7", 0], "latent_image": ["22", 0]}, "class_type": "KSampler", "_meta": {"title": "KSampler"}}, "7": {"inputs": {"text": "Xx_negative_xX", "clip": ["14", 1]}, "class_type": "CLIPTextEncode", "_meta": {"title": "CLIP Text Encode (Prompt)"}}, "8": {"inputs": {"samples": ["3", 0], "vae": ["14", 2]}, "class_type": "VAEDecode", "_meta": {"title": "VAE Decode"}}, "9": {"inputs": {"filename_prefix": "Fixed", "images": ["8", 0]}, "class_type": "SaveImage", "_meta": {"title": "Save Image"}}, "14": {"inputs": {"ckpt_name": "SDXLCheckpoint.safetensors"}, "class_type": "CheckpointLoaderSimple", "_meta": {"title": "Load Checkpoint"}}, "15": {"inputs": {"text": "Xx_positive_xX", "clip": ["14", 1]}, "class_type": "CLIPTextEncodeWithBreak", "_meta": {"title": "CLIPTextEncode with BREAK syntax"}}, "22": {"inputs": {"pixels": ["24", 0], "vae": ["14", 2]}, "class_type": "VAEEncode", "_meta": {"title": "VAE Encode"}}, "24": {"inputs": {"image": "Fast_00076_.png [output]", "refresh": "refresh"}, "class_type": "LoadImageOutput", "_meta": {"title": "Load Image (from Outputs)"}}}' ) def import_custom_nodes() -> None: """Find all custom nodes in the custom_nodes folder and add those node objects to NODE_CLASS_MAPPINGS This function sets up a new asyncio event loop, initializes the PromptServer, creates a PromptQueue, and initializes the custom nodes. """ if has_manager: try: import manager_core as manager except ImportError: print("Could not import manager_core, proceeding without it.") return else: if hasattr(manager, "get_config"): print("Patching manager_core.get_config to enforce offline mode.") try: get_config = manager.get_config def _get_config(*args, **kwargs): config = get_config(*args, **kwargs) config["network_mode"] = "offline" return config manager.get_config = _get_config except Exception as e: print("Failed to patch manager_core.get_config:", e) import asyncio import execution from nodes import init_extra_nodes import server # Creating a new event loop and setting it as the default loop loop = asyncio.new_event_loop() asyncio.set_event_loop(loop) async def inner(): # Creating an instance of PromptServer with the loop server_instance = server.PromptServer(loop) execution.PromptQueue(server_instance) # Initializing custom nodes await init_extra_nodes(init_custom_nodes=True) loop.run_until_complete(inner()) _custom_nodes_imported = False _custom_path_added = False def main(*func_args, **func_kwargs): global args, _custom_nodes_imported, _custom_path_added if __name__ == "__main__": if args is None: args = parser.parse_args() else: defaults = dict( (arg, parser.get_default(arg)) for arg in ["queue_size", "comfyui_directory", "output", "disable_metadata"] + [ "ckpt_name1", "text2", "text3", "image4", "seed5", "steps6", "cfg7", "sampler_name8", "scheduler9", "denoise10", "filename_prefix11", ] ) all_args = dict() all_args.update(defaults) all_args.update(func_kwargs) args = argparse.Namespace(**all_args) with ctx: if not _custom_path_added: add_comfyui_directory_to_sys_path() add_extra_model_paths() _custom_path_added = True if not _custom_nodes_imported: import_custom_nodes() _custom_nodes_imported = True from nodes import NODE_CLASS_MAPPINGS with torch.inference_mode(), ctx: checkpointloadersimple = NODE_CLASS_MAPPINGS["CheckpointLoaderSimple"]() checkpointloadersimple_14 = checkpointloadersimple.load_checkpoint( ckpt_name=parse_arg(args.ckpt_name1) ) cliptextencode = NODE_CLASS_MAPPINGS["CLIPTextEncode"]() cliptextencode_7 = cliptextencode.encode( text=parse_arg(args.text2), clip=get_value_at_index(checkpointloadersimple_14, 1), ) cliptextencodewithbreak = NODE_CLASS_MAPPINGS["CLIPTextEncodeWithBreak"]() cliptextencodewithbreak_15 = cliptextencodewithbreak.encode( text=parse_arg(args.text3), clip=get_value_at_index(checkpointloadersimple_14, 1), ) loadimageoutput = NODE_CLASS_MAPPINGS["LoadImageOutput"]() loadimageoutput_24 = loadimageoutput.load_image(image=parse_arg(args.image4)) vaeencode = NODE_CLASS_MAPPINGS["VAEEncode"]() vaeencode_22 = vaeencode.encode( pixels=get_value_at_index(loadimageoutput_24, 0), vae=get_value_at_index(checkpointloadersimple_14, 2), ) ksampler = NODE_CLASS_MAPPINGS["KSampler"]() vaedecode = NODE_CLASS_MAPPINGS["VAEDecode"]() saveimage = save_image_wrapper(ctx, NODE_CLASS_MAPPINGS["SaveImage"])() for q in range(args.queue_size): ksampler_3 = ksampler.sample( seed=randrange(1000000000), steps=parse_arg(args.steps6), cfg=parse_arg(args.cfg7), sampler_name=parse_arg(args.sampler_name8), scheduler=parse_arg(args.scheduler9), denoise=parse_arg(args.denoise10), model=get_value_at_index(checkpointloadersimple_14, 0), positive=get_value_at_index(cliptextencodewithbreak_15, 0), negative=get_value_at_index(cliptextencode_7, 0), latent_image=get_value_at_index(vaeencode_22, 0), ) vaedecode_8 = vaedecode.decode( samples=get_value_at_index(ksampler_3, 0), vae=get_value_at_index(checkpointloadersimple_14, 2), ) if __name__ != "__main__": return dict( filename_prefix=parse_arg(args.filename_prefix11), images=get_value_at_index(vaedecode_8, 0), prompt=PROMPT_DATA, ) else: saveimage_9 = saveimage.save_images( filename_prefix=parse_arg(args.filename_prefix11), images=get_value_at_index(vaedecode_8, 0), prompt=PROMPT_DATA, ) if __name__ == "__main__": main()