Improve support for extra models

README.md

@@ -1,14 +1,14 @@
-ComfyUI Distributed
+ComfyUI LTS
 =======
 
-A vanilla, up-to-date fork of [ComfyUI](https://github.com/comfyanonymous/comfyui).
+A vanilla, up-to-date fork of [ComfyUI](https://github.com/comfyanonymous/comfyui) intended for long term support (LTS) from [Hidden Switch](https://hiddenswitch.com).
 
 ### New Features
 
 - Run with `comfyui` in your command line.
 - [Installable](#installing) via `pip`: `pip install git+https://github.com/hiddenswitch/ComfyUI.git`.
 - [Distributed](#distributed-multi-process-and-multi-gpu-comfy) with support for multiple GPUs, multiple backends and frontends, including in containers, using RabbitMQ.
-- [Installable custom nodes](#custom-nodes) via `pip`.
+- [Installable custom nodes](#custom-nodes) via `pip`, including LTS support for forked nodes from the community.
 - [New configuration options](#command-line-arguments) for directories, models and metrics.
 - [API](#using-comfyui-as-an-api--programmatically) support, using the vanilla ComfyUI API and new API endpoints.
 - [Embed](#embedded) ComfyUI as a library inside your Python application. No server or frontend needed.
@@ -184,6 +184,12 @@ Clone the repository containing the custom nodes into `custom_nodes/` in your wo
 
 ### Installable Custom Nodes
 
+These packages have been adapted to be installable with `pip` and download models to the correct places, using the **Known Models** functionality:
+
+- **ControlNet Auxiliary Preprocessors**: `pip install git+https://github.com/AppMana/comfyui_controlnet_aux.git`.
+- **LayerDiffuse**: `pip install git+https://github.com/hiddenswitch/ComfyUI-layerdiffuse.git`.
+- **Extra Models**: `pip install git+https://github.com/AppMana/ComfyUI_ExtraModels.git`. You will need `xformers`.
+
 Run `pip install git+https://github.com/owner/repository`, replacing the `git` repository with the installable custom nodes URL. This is just the GitHub URL. 
 
 ## Authoring Custom Nodes

comfy/model_downloader.py

@@ -284,7 +284,12 @@ KNOWN_DIFF_CONTROLNETS = [
 
 KNOWN_APPROX_VAES = [
     HuggingFile("madebyollin/taesd", "taesd_decoder.safetensors"),
-    HuggingFile("madebyollin/taesdxl", "taesdxl_decoder.safetensors")
+    HuggingFile("madebyollin/taesdxl", "taesdxl_decoder.safetensors"),
+]
+
+KNOWN_VAES = [
+    HuggingFile("stabilityai/sdxl-vae", "sdxl_vae.safetensors"),
+    HuggingFile("stabilityai/sd-vae-ft-mse-original", "vae-ft-mse-840000-ema-pruned.safetensors"),
 ]
 
 

comfy/nodes/base_nodes.py

@@ -26,7 +26,7 @@ from ..cli_args import args
 from ..cmd import folder_paths, latent_preview
 from ..images import open_image
 from ..model_downloader import get_filename_list_with_downloadable, get_or_download, KNOWN_CHECKPOINTS, \
-    KNOWN_CLIP_VISION_MODELS, KNOWN_GLIGEN_MODELS, KNOWN_UNCLIP_CHECKPOINTS, KNOWN_LORAS, KNOWN_CONTROLNETS, KNOWN_DIFF_CONTROLNETS
+    KNOWN_CLIP_VISION_MODELS, KNOWN_GLIGEN_MODELS, KNOWN_UNCLIP_CHECKPOINTS, KNOWN_LORAS, KNOWN_CONTROLNETS, KNOWN_DIFF_CONTROLNETS, KNOWN_VAES, KNOWN_APPROX_VAES
 from ..nodes.common import MAX_RESOLUTION
 from .. import controlnet
 from ..open_exr import load_exr
@@ -616,8 +616,8 @@ class LoraLoaderModelOnly(LoraLoader):
 class VAELoader:
     @staticmethod
     def vae_list():
-        vaes = folder_paths.get_filename_list("vae")
-        approx_vaes = folder_paths.get_filename_list("vae_approx")
+        vaes = get_filename_list_with_downloadable("vae", KNOWN_VAES)
+        approx_vaes = get_filename_list_with_downloadable("vae_approx", KNOWN_APPROX_VAES)
         sdxl_taesd_enc = False
         sdxl_taesd_dec = False
         sd1_taesd_enc = False
@@ -673,7 +673,7 @@ class VAELoader:
         if vae_name in ["taesd", "taesdxl"]:
             sd_ = self.load_taesd(vae_name)
         else:
-            vae_path = folder_paths.get_full_path("vae", vae_name)
+            vae_path = get_or_download("vae", vae_name, KNOWN_VAES)
             sd_ = utils.load_torch_file(vae_path)
         vae = sd.VAE(sd=sd_)
         return (vae,)

setup.py

@@ -41,8 +41,6 @@ The package index to torch built against CPU features.
 """
 cpu_torch_index = ("https://download.pytorch.org/whl/cpu", "https://download.pytorch.org/whl/nightly/cpu")
 
-# xformers not required for new torch
-
 """
 Indicates if this is installing an editable (develop) mode package
 """