Option to directly clone the repo to custom_nodes

README.md

@@ -4,7 +4,9 @@ A small neural network to provide interoperability between the latents generated
 I wanted to see if it was possible to pass latents generated by the new SDXL model directly into SDv1.5 models without decoding and re-encoding them using a VAE first.
 
 ## Installation
-To install it, simply download [comfy_latent_interposer.py](https://github.com/city96/SD-Latent-Interposer/raw/main/comfy_latent_interposer.py) to your `ComfyUI/custom_nodes` folder. You may need to install hfhub using the command `pip install huggingface-hub` inside your venv.
+To install it, simply clone this repo to your custom_nodes folder using the following command: `git clone https://github.com/city96/SD-Latent-Interposer custom_nodes/SD-Latent-Interposer`.
+
+Alternatively, you can download the [comfy_latent_interposer.py](https://github.com/city96/SD-Latent-Interposer/raw/main/comfy_latent_interposer.py) file to your `ComfyUI/custom_nodes` folder as well. You may need to install hfhub using the command `pip install huggingface-hub` inside your venv.
 
 If you need the model weights for something else, they are [hosted on HF](https://huggingface.co/city96/SD-Latent-Interposer/tree/main) under the same Apache2 license as the rest of the repo.
 

__init__.py

@@ -0,0 +1,8 @@
+# only import if running as a custom node
+try:
+	import comfy.utils
+except ImportError:
+	pass
+else:
+	from .comfy_latent_interposer import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
+	__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS']