The ComfyUI-to-Python-Extension is a powerful tool that translates the ComfyUI workflow into executable Python code. Designed to bridge the gap between ComfyUI's visual interface and Python's programming environment, this script facilitates the seamless transition from design to code execution. Whether you're a data scientist, a software developer, or an AI enthusiast, this tool streamlines the process of implementing ComfyUI workflows in Python. The output makes it easy to queue a large amount of images for generation and provides a base script to easily modify for experimination.
Convert this:
To this:
import random import sys sys.path.append("../") from nodes import ( KSamplerAdvanced, EmptyLatentImage, VAEDecodeTiled, SaveImage, CLIPTextEncode, CheckpointLoaderSimple, ) def main(): checkpointloadersimple = CheckpointLoaderSimple() checkpointloadersimple_4 = checkpointloadersimple.load_checkpoint( ckpt_name="sd_xl_base_1.0.safetensors" ) emptylatentimage = EmptyLatentImage() emptylatentimage_5 = emptylatentimage.generate( width=1024, height=1024, batch_size=1 ) cliptextencode = CLIPTextEncode() cliptextencode_6 = cliptextencode.encode( text="evening sunset scenery blue sky nature, glass bottle with a galaxy in it", clip=checkpointloadersimple_4[1], ) cliptextencode_7 = cliptextencode.encode( text="text, watermark", clip=checkpointloadersimple_4[1] ) checkpointloadersimple_12 = checkpointloadersimple.load_checkpoint( ckpt_name="sd_xl_refiner_1.0.safetensors" ) cliptextencode_15 = cliptextencode.encode( text="evening sunset scenery blue sky nature, glass bottle with a galaxy in it", clip=checkpointloadersimple_12[1], ) cliptextencode_16 = cliptextencode.encode( text="text, watermark", clip=checkpointloadersimple_12[1] ) ksampleradvanced = KSamplerAdvanced() vaedecodetiled = VAEDecodeTiled() saveimage = SaveImage() for q in range(1, 10): ksampleradvanced_10 = ksampleradvanced.sample( add_noise="enable", noise_seed=random.randint(1, 2**64), steps=25, cfg=8, sampler_name="euler", scheduler="normal", start_at_step=0, end_at_step=20, return_with_leftover_noise="enable", model=checkpointloadersimple_4[0], positive=cliptextencode_6[0], negative=cliptextencode_7[0], latent_image=emptylatentimage_5[0], ) ksampleradvanced_11 = ksampleradvanced.sample( add_noise="disable", noise_seed=random.randint(1, 2**64), steps=25, cfg=8, sampler_name="euler", scheduler="normal", start_at_step=20, end_at_step=10000, return_with_leftover_noise="disable", model=checkpointloadersimple_12[0], positive=cliptextencode_15[0], negative=cliptextencode_16[0], latent_image=ksampleradvanced_10[0], ) vaedecodetiled_17 = vaedecodetiled.decode( samples=ksampleradvanced_11[0], vae=checkpointloadersimple_12[2] ) saveimage_19 = saveimage.save_images( filename_prefix="ComfyUI", images=vaedecodetiled_17[0].detach() ) if __name__ == "__main__": main() -
Clone this repo
git clone https://github.com/pydn/ComfyUI-to-Python-Extension.git
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Install requirements
pip install -r requirements.txt
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Copy files into ComfyUI: Copy
ComfyUI-to-Python-Extension/into the parent folder of your cloned version of ComfyUI.After copying
ComfyUI-to-Python-Extension/your localComfyUIdirectory should look like this:/comfy /comfy_extras /ComfyUI-to-Python-Extension /custom_nodes /input /models /output /script_examples /web .gitignore LICENSE README.md comfyui_screenshot.png cuda_mollac.py execution.py extra_model_paths.yaml.example folder_paths.py latent_preview.py main.py nodes.py requirements.txt server.py -
Navigate to the
ComfyUI-to-Python-Extensionfolder in your localComfyUIdirectory. -
Run the Script: Use the following command to run the script with a specific JSON file:
python generate_python_code.py