import os import sys from typing import Any, Mapping, Sequence, Union import torch from nunchaku.utils import get_precision 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: path = os.getcwd() # 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) 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. """ try: from main import load_extra_path_config except ImportError: print("Could not import load_extra_path_config from main.py. Looking in utils.extra_config instead.") 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.") add_comfyui_directory_to_sys_path() add_extra_model_paths() 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. """ import asyncio import execution import server from nodes import init_extra_nodes # Creating a new event loop and setting it as the default loop loop = asyncio.new_event_loop() asyncio.set_event_loop(loop) # Creating an instance of PromptServer with the loop server_instance = server.PromptServer(loop) execution.PromptQueue(server_instance) # Initializing custom nodes init_extra_nodes() from nodes import NODE_CLASS_MAPPINGS def main(precision: str): import_custom_nodes() with torch.inference_mode(): dualcliploader = NODE_CLASS_MAPPINGS["DualCLIPLoader"]() dualcliploader_38 = dualcliploader.load_clip( clip_name1="clip_l.safetensors", clip_name2="t5xxl_fp8_e4m3fn_scaled.safetensors", type="flux", device="default", ) cliptextencode = NODE_CLASS_MAPPINGS["CLIPTextEncode"]() cliptextencode_6 = cliptextencode.encode( text="Make the creature hold a sign that says 'Nunchaku is awesome', yarn art style, detailed, vibrant colors. Do not change other features.", clip=get_value_at_index(dualcliploader_38, 0), ) vaeloader = NODE_CLASS_MAPPINGS["VAELoader"]() vaeloader_39 = vaeloader.load_vae(vae_name="ae.safetensors") loadimageoutput = NODE_CLASS_MAPPINGS["LoadImageOutput"]() loadimageoutput_142 = loadimageoutput.load_image(image="yarn-art-pikachu.png [output]") imagestitch = NODE_CLASS_MAPPINGS["ImageStitch"]() imagestitch_146 = imagestitch.stitch( direction="right", match_image_size=True, spacing_width=0, spacing_color="white", image1=get_value_at_index(loadimageoutput_142, 0), ) fluxkontextimagescale = NODE_CLASS_MAPPINGS["FluxKontextImageScale"]() fluxkontextimagescale_42 = fluxkontextimagescale.scale(image=get_value_at_index(imagestitch_146, 0)) vaeencode = NODE_CLASS_MAPPINGS["VAEEncode"]() vaeencode_124 = vaeencode.encode( pixels=get_value_at_index(fluxkontextimagescale_42, 0), vae=get_value_at_index(vaeloader_39, 0), ) nunchakufluxditloader = NODE_CLASS_MAPPINGS["NunchakuFluxDiTLoader"]() nunchakufluxditloader_189 = nunchakufluxditloader.load_model( model_path=f"svdq-{precision}_r32-flux.1-kontext-dev.safetensors", cache_threshold=0, attention="nunchaku-fp16", cpu_offload="auto", device_id=0, data_type="bfloat16", i2f_mode="enabled", ) referencelatent = NODE_CLASS_MAPPINGS["ReferenceLatent"]() fluxguidance = NODE_CLASS_MAPPINGS["FluxGuidance"]() conditioningzeroout = NODE_CLASS_MAPPINGS["ConditioningZeroOut"]() ksampler = NODE_CLASS_MAPPINGS["KSampler"]() vaedecode = NODE_CLASS_MAPPINGS["VAEDecode"]() saveimage = NODE_CLASS_MAPPINGS["SaveImage"]() for q in range(1): referencelatent_177 = referencelatent.append( conditioning=get_value_at_index(cliptextencode_6, 0), latent=get_value_at_index(vaeencode_124, 0), ) fluxguidance_35 = fluxguidance.append(guidance=2.5, conditioning=get_value_at_index(referencelatent_177, 0)) conditioningzeroout_135 = conditioningzeroout.zero_out(conditioning=get_value_at_index(cliptextencode_6, 0)) ksampler_31 = ksampler.sample( seed=3569396000607825004, steps=20, cfg=1, sampler_name="euler", scheduler="simple", denoise=1, model=get_value_at_index(nunchakufluxditloader_189, 0), positive=get_value_at_index(fluxguidance_35, 0), negative=get_value_at_index(conditioningzeroout_135, 0), latent_image=get_value_at_index(vaeencode_124, 0), ) vaedecode_8 = vaedecode.decode( samples=get_value_at_index(ksampler_31, 0), vae=get_value_at_index(vaeloader_39, 0), ) saveimage_136 = saveimage.save_images(filename_prefix="ComfyUI", images=get_value_at_index(vaedecode_8, 0)) filename = saveimage_136["ui"]["images"][0]["filename"] path = os.path.join("output", filename) with open("image_path.txt", "w") as f: f.write(path) print(path) return path if __name__ == "__main__": main(get_precision())