├── .github └── workflows │ └── publish.yml ├── AutoDownloadModels.json ├── LICENSE ├── README.md ├── __init__.py ├── nodes.py ├── pyproject.toml └── requirements.txt /.github/workflows/publish.yml: -------------------------------------------------------------------------------- 1 | name: Publish to Comfy registry 2 | on: 3 | workflow_dispatch: 4 | push: 5 | branches: 6 | - main 7 | - master 8 | paths: 9 | - "pyproject.toml" 10 | 11 | permissions: 12 | issues: write 13 | 14 | jobs: 15 | publish-node: 16 | name: Publish Custom Node to registry 17 | runs-on: ubuntu-latest 18 | if: ${{ github.repository_owner == 'AIExplorer25' }} 19 | steps: 20 | - name: Check out code 21 | uses: actions/checkout@v4 22 | with: 23 | submodules: true 24 | - name: Publish Custom Node 25 | uses: Comfy-Org/publish-node-action@v1 26 | with: 27 | ## Add your own personal access token to your Github Repository secrets and reference it here. 28 | personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }} 29 | -------------------------------------------------------------------------------- /AutoDownloadModels.json: -------------------------------------------------------------------------------- 1 | { 2 | "id": "ce319ced-e662-4184-98eb-d142fb7b245f", 3 | "revision": 0, 4 | "last_node_id": 32, 5 | "last_link_id": 34, 6 | "nodes": [ 7 | { 8 | "id": 17, 9 | "type": "GetModelsFromWorkflow", 10 | "pos": [ 11 | -972.2092895507812, 12 | -184.9186248779297 13 | ], 14 | "size": [ 15 | 480.0000305175781, 16 | 115.73332214355469 17 | ], 18 | "flags": {}, 19 | "order": 0, 20 | "mode": 2, 21 | "inputs": [], 22 | "outputs": [ 23 | { 24 | "name": "pa", 25 | "type": "STRING", 26 | "slot_index": 0, 27 | "links": [ 28 | 33 29 | ] 30 | } 31 | ], 32 | "properties": { 33 | "Node name for S&R": "GetModelsFromWorkflow" 34 | }, 35 | "widgets_values": [ 36 | "/workspace/ComfyUI/user/default/workflows/wanvideo_480p_I2V_FLUXLORA (1).json", 37 | "/workspace/ComfyUI/models/" 38 | ] 39 | }, 40 | { 41 | "id": 31, 42 | "type": "Display Any (rgthree)", 43 | "pos": [ 44 | -379.0292053222656, 45 | -190.2797393798828 46 | ], 47 | "size": [ 48 | 397.38232421875, 49 | 232.47381591796875 50 | ], 51 | "flags": {}, 52 | "order": 3, 53 | "mode": 2, 54 | "inputs": [ 55 | { 56 | "name": "source", 57 | "type": "*", 58 | "link": 33 59 | } 60 | ], 61 | "outputs": [], 62 | "properties": { 63 | "Node name for S&R": "Display Any (rgthree)" 64 | }, 65 | "widgets_values": [ 66 | "(umt5-xxl-enc-bf16.safetensors~~~text_encoders),(4x_NMKD-Siax_200k.pth~~~upscale_models),(open-clip-xlm-roberta-large-vit-huge-14_visual_fp16.safetensors~~~clip),(Wan2_1_VAE_fp32.safetensors~~~vae),(4x_NMKD-Siax_200k.pth~~~upscale_models),(FluxMythV2.safetensors~~~clip),(aidmaFLUXpro1.1-FLUX-V0.2.safetensors~~~clip),(aidmaHyperRealism-FLUX-V0.2.safetensors~~~clip),(film_net_fp32.pt~~~configs),(film_net_fp32.pt~~~configs),(flux1-dev-fp8.safetensors~~~vae),(Wan2_1-I2V-14B-720P_fp8_e4m3fn.safetensors~~~loras)" 67 | ] 68 | }, 69 | { 70 | "id": 30, 71 | "type": "Fast Groups Muter (rgthree)", 72 | "pos": [ 73 | -1744.7056884765625, 74 | -120.06262969970703 75 | ], 76 | "size": [ 77 | 519.0283203125, 78 | 149.43731689453125 79 | ], 80 | "flags": {}, 81 | "order": 1, 82 | "mode": 0, 83 | "inputs": [], 84 | "outputs": [ 85 | { 86 | "name": "OPT_CONNECTION", 87 | "type": "*", 88 | "links": null 89 | } 90 | ], 91 | "properties": { 92 | "matchColors": "", 93 | "matchTitle": "", 94 | "showNav": true, 95 | "sort": "position", 96 | "customSortAlphabet": "", 97 | "toggleRestriction": "default" 98 | } 99 | }, 100 | { 101 | "id": 20, 102 | "type": "Power Prompt - Simple (rgthree)", 103 | "pos": [ 104 | -980.2467041015625, 105 | 724.5652465820312 106 | ], 107 | "size": [ 108 | 833.0332641601562, 109 | 217.1599884033203 110 | ], 111 | "flags": {}, 112 | "order": 2, 113 | "mode": 0, 114 | "inputs": [ 115 | { 116 | "dir": 3, 117 | "name": "opt_clip", 118 | "shape": 7, 119 | "type": "CLIP", 120 | "link": null 121 | } 122 | ], 123 | "outputs": [ 124 | { 125 | "color_off": "#666665", 126 | "color_on": "#666665", 127 | "dir": 4, 128 | "name": "CONDITIONING", 129 | "type": "CONDITIONING", 130 | "links": null 131 | }, 132 | { 133 | "color_off": "#7F7", 134 | "color_on": "#7F7", 135 | "dir": 4, 136 | "name": "TEXT", 137 | "type": "STRING", 138 | "slot_index": 1, 139 | "links": [ 140 | 31 141 | ] 142 | } 143 | ], 144 | "properties": { 145 | "Node name for S&R": "Power Prompt - Simple (rgthree)", 146 | "combos_filter": "" 147 | }, 148 | "widgets_values": [ 149 | "(umt5-xxl-enc-bf16.safetensors~~~clip),(4x_NMKD-Siax_200k.pth~~~upscale_models),(open-clip-xlm-roberta-large-vit-huge-14_visual_fp16.safetensors~~~clip),(Wan2_1_VAE_fp32.safetensors~~~vae),(FluxMythV2.safetensors~~~loras),(aidmaFLUXpro1.1-FLUX-V0.2.safetensors~~~loras),(aidmaHyperRealism-FLUX-V0.2.safetensors~~~loras),(flux1-dev-fp8.safetensors~~~unet),(Wan2_1-I2V-14B-720P_fp8_e4m3fn.safetensors~~~unet)" 150 | ] 151 | }, 152 | { 153 | "id": 28, 154 | "type": "AutoDownloadALLModels", 155 | "pos": [ 156 | -582.1441650390625, 157 | 537.7410888671875 158 | ], 159 | "size": [ 160 | 490.72662353515625, 161 | 110.66668701171875 162 | ], 163 | "flags": {}, 164 | "order": 4, 165 | "mode": 0, 166 | "inputs": [ 167 | { 168 | "name": "modelandpath", 169 | "type": "STRING", 170 | "widget": { 171 | "name": "modelandpath" 172 | }, 173 | "link": 31 174 | } 175 | ], 176 | "outputs": [ 177 | { 178 | "name": "status", 179 | "type": "STRING", 180 | "links": [ 181 | 34 182 | ] 183 | } 184 | ], 185 | "properties": { 186 | "Node name for S&R": "AutoDownloadALLModels" 187 | }, 188 | "widgets_values": [ 189 | "", 190 | "Kijai/WanVideo_comfy,latent-consistency/lcm-lora-sdv1-5" 191 | ] 192 | }, 193 | { 194 | "id": 32, 195 | "type": "Display Any (rgthree)", 196 | "pos": [ 197 | 38.63861083984375, 198 | 664.4175415039062 199 | ], 200 | "size": [ 201 | 430.5312805175781, 202 | 179.4630584716797 203 | ], 204 | "flags": {}, 205 | "order": 5, 206 | "mode": 0, 207 | "inputs": [ 208 | { 209 | "name": "source", 210 | "type": "*", 211 | "link": 34 212 | } 213 | ], 214 | "outputs": [], 215 | "properties": { 216 | "Node name for S&R": "Display Any (rgthree)" 217 | }, 218 | "widgets_values": [ 219 | "" 220 | ] 221 | } 222 | ], 223 | "links": [ 224 | [ 225 | 31, 226 | 20, 227 | 1, 228 | 28, 229 | 0, 230 | "STRING" 231 | ], 232 | [ 233 | 33, 234 | 17, 235 | 0, 236 | 31, 237 | 0, 238 | "*" 239 | ], 240 | [ 241 | 34, 242 | 28, 243 | 0, 244 | 32, 245 | 0, 246 | "*" 247 | ] 248 | ], 249 | "groups": [ 250 | { 251 | "id": 1, 252 | "title": "Step1", 253 | "bounding": [ 254 | -1059.1004638671875, 255 | -397.3572998046875, 256 | 1683.384033203125, 257 | 695.924560546875 258 | ], 259 | "color": "#3f789e", 260 | "font_size": 24, 261 | "flags": {} 262 | }, 263 | { 264 | "id": 2, 265 | "title": "Step2", 266 | "bounding": [ 267 | -1064.10205078125, 268 | 340.75189208984375, 269 | 1843.4385986328125, 270 | 764.5194702148438 271 | ], 272 | "color": "#3f789e", 273 | "font_size": 24, 274 | "flags": {} 275 | } 276 | ], 277 | "config": {}, 278 | "extra": { 279 | "ds": { 280 | "scale": 0.42409761837248494, 281 | "offset": [ 282 | 1269.256013741986, 283 | -114.20634772143546 284 | ] 285 | }, 286 | "VHS_latentpreview": false, 287 | "VHS_latentpreviewrate": 0, 288 | "VHS_MetadataImage": true, 289 | "VHS_KeepIntermediate": true, 290 | "node_versions": { 291 | "ComfyUI_AutoDownloadModels": "efa381365abe8b02e640cd231cbf8e8cc2af5f74", 292 | "rgthree-comfy": "ab37a0bd377a4443d04896b34a9491ddb1cb014b" 293 | } 294 | }, 295 | "version": 0.4 296 | } -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # ComfyUI_AutoDownloadModels 2 | This custom node helps to auto download models from huggingface 3 | -------------------------------------------------------------------------------- /__init__.py: -------------------------------------------------------------------------------- 1 | from .nodes import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS 2 | 3 | __all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"] -------------------------------------------------------------------------------- /nodes.py: -------------------------------------------------------------------------------- 1 | import os 2 | from huggingface_hub import hf_hub_download 3 | import hf_transfer 4 | import json 5 | from rapidfuzz import process, fuzz 6 | from collections import Counter 7 | from huggingface_hub import list_models 8 | from huggingface_hub import HfApi 9 | import subprocess 10 | import sys 11 | 12 | 13 | class AutoDownloadModels: 14 | @classmethod 15 | def INPUT_TYPES(s): 16 | return { 17 | "required": { 18 | "repo_id": ("STRING", {"tooltip": "Enter hugging face repo id"}), 19 | "model_name": ("STRING", {"tooltip": "Enter hugging face model name to download"}), 20 | "path_to_download": ("STRING", {"tooltip": "Enter to download the model to"}), 21 | }, 22 | } 23 | RETURN_TYPES = ("STRING",) 24 | RETURN_NAMES = ("path",) 25 | FUNCTION = "DownloadModel" 26 | CATEGORY = "DownloadModel" 27 | DESCRIPTION = "This node downloads models from huggingface models" 28 | 29 | def DownloadModel(self, repo_id, model_name, path_to_download): 30 | model_path = hf_hub_download(repo_id=repo_id, filename=model_name, local_dir=path_to_download) 31 | 32 | return (model_path,) 33 | 34 | 35 | class WANModelsAutoDownload: 36 | @classmethod 37 | def INPUT_TYPES(s): 38 | return { 39 | "required": { 40 | 41 | "Wan2_1_Fun_Control_14B_fp8_e4m3fn": ("BOOLEAN", {"tooltip": "select to download Wan2_1_Fun_Control_14B_fp8_e4m3fn"}), 42 | "Wan2_1_Fun_InP_14B_fp8_e4m3fn": ("BOOLEAN", {"tooltip": "select to download Wan2_1_Fun_InP_14B_fp8_e4m3fn"}), 43 | "Wan2_1_I2V_14B_480P_fp8_e4m3fn": ("BOOLEAN", {"tooltip": "select to download Wan2_1_I2V_14B_480P_fp8_e4m3fn"}), 44 | "Wan2_1_I2V_14B_480P_fp8_e5m2": ("BOOLEAN", {"tooltip": "select to download Wan2_1_I2V_14B_480P_fp8_e5m2"}), 45 | "Wan2_1_I2V_14B_720P_fp8_e4m3fn": ("BOOLEAN", {"tooltip": "select to download Wan2_1_I2V_14B_720P_fp8_e4m3fn"}), 46 | "Wan2_1_I2V_14B_720P_fp8_e5m2": ("BOOLEAN", {"tooltip": "select to download Wan2_1_I2V_14B_720P_fp8_e5m2"}), 47 | "Wan2_1_T2V_14B_fp8_e4m3fn": ("BOOLEAN", {"tooltip": "select to download Wan2_1_T2V_14B_fp8_e4m3fn"}), 48 | "Wan2_1_T2V_14B_fp8_e5m2": ("BOOLEAN", {"tooltip": "select to download Wan2_1_T2V_14B_fp8_e5m2"}), 49 | "Wan2_1_T2V_1_3B_bf16": ("BOOLEAN", {"tooltip": "select to download Wan2_1_T2V_1_3B_bf16"}), 50 | "Wan2_1_T2V_1_3B_fp32": ("BOOLEAN", {"tooltip": "select to download Wan2_1_T2V_1_3B_fp32"}), 51 | "Wan2_1_T2V_1_3B_fp8_e4m3fn": ("BOOLEAN", {"tooltip": "select to download Wan2_1_T2V_1_3B_fp8_e4m3fn"}), 52 | "Wan2_1_VAE_bf16": ("BOOLEAN", {"tooltip": "select to download Wan2_1_VAE_bf16"}), 53 | "Wan2_1_VAE_fp32": ("BOOLEAN", {"tooltip": "select to download Wan2_1_VAE_fp32"}), 54 | "open_clip_xlm_roberta_large_vit_huge_14_visual_fp16": ("BOOLEAN", {"tooltip": "select to download open_clip_xlm_roberta_large_vit_huge_14_visual_fp16"}), 55 | "open_clip_xlm_roberta_large_vit_huge_14_visual_fp32": ("BOOLEAN", {"tooltip": "select to download open_clip_xlm_roberta_large_vit_huge_14_visual_fp32"}), 56 | "taew2_1": ("BOOLEAN", {"tooltip": "select to download taew2_1"}), 57 | "umt5_xxl_enc_bf16": ("BOOLEAN", {"tooltip": "select to download umt5_xxl_enc_bf16"}), 58 | "umt5_xxl_enc_fp8_e4m3fn": ("BOOLEAN", {"tooltip": "select to download umt5_xxl_enc_fp8_e4m3fn"}), 59 | 60 | }, 61 | } 62 | RETURN_TYPES = ("STRING",) 63 | RETURN_NAMES = ("path",) 64 | FUNCTION = "DownloadModel" 65 | CATEGORY = "DownloadModel" 66 | DESCRIPTION = "This node downloads ALL Kijay's WAN models from huggingface models" 67 | 68 | def DownloadModel(self, Wan2_1_Fun_Control_14B_fp8_e4m3fn , Wan2_1_Fun_InP_14B_fp8_e4m3fn , Wan2_1_I2V_14B_480P_fp8_e4m3fn , Wan2_1_I2V_14B_480P_fp8_e5m2 , Wan2_1_I2V_14B_720P_fp8_e4m3fn , Wan2_1_I2V_14B_720P_fp8_e5m2 , Wan2_1_T2V_14B_fp8_e4m3fn , Wan2_1_T2V_14B_fp8_e5m2 , Wan2_1_T2V_1_3B_bf16 , Wan2_1_T2V_1_3B_fp32 , Wan2_1_T2V_1_3B_fp8_e4m3fn , Wan2_1_VAE_bf16 , Wan2_1_VAE_fp32 , open_clip_xlm_roberta_large_vit_huge_14_visual_fp16 , open_clip_xlm_roberta_large_vit_huge_14_visual_fp32 , taew2_1 , umt5_xxl_enc_bf16 , umt5_xxl_enc_fp8_e4m3fn): 69 | status="" 70 | if(Wan2_1_Fun_Control_14B_fp8_e4m3fn): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="Wan2.1-Fun-Control-14B_fp8_e4m3fn.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 71 | if(Wan2_1_Fun_InP_14B_fp8_e4m3fn): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="Wan2.1-Fun-InP-14B_fp8_e4m3fn.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 72 | if(Wan2_1_I2V_14B_480P_fp8_e4m3fn): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="Wan2_1-I2V-14B-480P_fp8_e4m3fn.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 73 | if(Wan2_1_I2V_14B_480P_fp8_e5m2): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="Wan2_1-I2V-14B-480P_fp8_e5m2.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 74 | if(Wan2_1_I2V_14B_720P_fp8_e4m3fn): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="Wan2_1-I2V-14B-720P_fp8_e4m3fn.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 75 | if(Wan2_1_I2V_14B_720P_fp8_e5m2): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="Wan2_1-I2V-14B-720P_fp8_e5m2.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 76 | if(Wan2_1_T2V_14B_fp8_e4m3fn): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="Wan2_1-T2V-14B_fp8_e4m3fn.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 77 | if(Wan2_1_T2V_14B_fp8_e5m2): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="Wan2_1-T2V-14B_fp8_e5m2.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 78 | if(Wan2_1_T2V_1_3B_bf16): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="Wan2_1-T2V-1_3B_bf16.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 79 | if(Wan2_1_T2V_1_3B_fp32): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="Wan2_1-T2V-1_3B_fp32.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 80 | if(Wan2_1_T2V_1_3B_fp8_e4m3fn): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="Wan2_1-T2V-1_3B_fp8_e4m3fn.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 81 | if(Wan2_1_VAE_bf16): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="Wan2_1_VAE_bf16.safetensors", local_dir="/workspace/ComfyUI/models/vae/"); status=status+model_path+" done." 82 | if(Wan2_1_VAE_fp32): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="Wan2_1_VAE_fp32.safetensors", local_dir="/workspace/ComfyUI/models/vae/"); status=status+model_path+" done." 83 | if(open_clip_xlm_roberta_large_vit_huge_14_visual_fp16): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="open-clip-xlm-roberta-large-vit-huge-14_visual_fp16.safetensors", local_dir="/workspace/ComfyUI/models/clip/"); status=status+model_path+" done." 84 | if(open_clip_xlm_roberta_large_vit_huge_14_visual_fp32): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="open-clip-xlm-roberta-large-vit-huge-14_visual_fp32.safetensors", local_dir="/workspace/ComfyUI/models/clip/"); status=status+model_path+" done." 85 | if(taew2_1): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="taew2_1.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 86 | if(umt5_xxl_enc_bf16): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="umt5-xxl-enc-bf16.safetensors", local_dir="/workspace/ComfyUI/models/clip/"); status=status+model_path+" done." 87 | if(umt5_xxl_enc_fp8_e4m3fn): model_path = hf_hub_download(repo_id="Kijai/WanVideo_comfy", filename="umt5-xxl-enc-fp8_e4m3fn.safetensors", local_dir="/workspace/ComfyUI/models/clip/"); status=status+model_path+" done." 88 | 89 | 90 | return (model_path,) 91 | 92 | class ALIMAMAFUNCONTROLWANModelsAutoDownload: 93 | @classmethod 94 | def INPUT_TYPES(s): 95 | return { 96 | "required": { 97 | 98 | "Wan2_1_VAE_pth": ("BOOLEAN", {"tooltip": "select to download Wan2_1_VAE_pth"}), 99 | "diffusion_pytorch_model": ("BOOLEAN", {"tooltip": "select to download diffusion_pytorch_model"}), 100 | "models_clip_open_clip_xlm_roberta_large_vit_huge_14_pth": ("BOOLEAN", {"tooltip": "select to download models_clip_open_clip_xlm_roberta_large_vit_huge_14_pth"}), 101 | "models_t5_umt5_xxl_enc_bf16_pth": ("BOOLEAN", {"tooltip": "select to download models_t5_umt5_xxl_enc_bf16_pth"}), 102 | 103 | }, 104 | } 105 | RETURN_TYPES = ("STRING",) 106 | RETURN_NAMES = ("path",) 107 | FUNCTION = "DownloadModel" 108 | CATEGORY = "DownloadModel" 109 | DESCRIPTION = "This node downloads ALL Kijay's WAN models from huggingface models" 110 | 111 | def DownloadModel(self, Wan2_1_VAE_pth , diffusion_pytorch_model , models_clip_open_clip_xlm_roberta_large_vit_huge_14_pth , models_t5_umt5_xxl_enc_bf16_pth 112 | ): 113 | status="" 114 | if(Wan2_1_VAE_pth): model_path = hf_hub_download(repo_id="alibaba-pai/Wan2.1-Fun-1.3B-Control", filename="Wan2.1_VAE.pth", local_dir="/workspace/ComfyUI/models/vae/"); status=status+model_path+" done." 115 | if(diffusion_pytorch_model): model_path = hf_hub_download(repo_id="alibaba-pai/Wan2.1-Fun-1.3B-Control", filename="diffusion_pytorch_model.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 116 | if(models_clip_open_clip_xlm_roberta_large_vit_huge_14_pth): model_path = hf_hub_download(repo_id="alibaba-pai/Wan2.1-Fun-1.3B-Control", filename="models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth", local_dir="/workspace/ComfyUI/models/clip/"); status=status+model_path+" done." 117 | if(models_t5_umt5_xxl_enc_bf16_pth): model_path = hf_hub_download(repo_id="alibaba-pai/Wan2.1-Fun-1.3B-Control", filename="models_t5_umt5-xxl-enc-bf16.pth", local_dir="/workspace/ComfyUI/models/clip/"); status=status+model_path+" done." 118 | 119 | return (model_path,) 120 | class WANALMAMAModelsAutoDownload: 121 | @classmethod 122 | def INPUT_TYPES(s): 123 | return { 124 | "required": { 125 | 126 | "split_files_clip_vision_clip_vision_h": ("BOOLEAN", {"tooltip": "select to download split_files_clip_vision_clip_vision_h"}), 127 | "split_files_diffusion_models_wan2_1_i2v_480p_14B_bf16": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_i2v_480p_14B_bf16"}), 128 | "split_files_diffusion_models_wan2_1_i2v_480p_14B_fp16": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_i2v_480p_14B_fp16"}), 129 | "split_files_diffusion_models_wan2_1_i2v_480p_14B_fp8_e4m3fn": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_i2v_480p_14B_fp8_e4m3fn"}), 130 | "split_files_diffusion_models_wan2_1_i2v_480p_14B_fp8_scaled": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_i2v_480p_14B_fp8_scaled"}), 131 | "split_files_diffusion_models_wan2_1_i2v_720p_14B_bf16": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_i2v_720p_14B_bf16"}), 132 | "split_files_diffusion_models_wan2_1_i2v_720p_14B_fp16": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_i2v_720p_14B_fp16"}), 133 | "split_files_diffusion_models_wan2_1_i2v_720p_14B_fp8_e4m3fn": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_i2v_720p_14B_fp8_e4m3fn"}), 134 | "split_files_diffusion_models_wan2_1_i2v_720p_14B_fp8_scaled": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_i2v_720p_14B_fp8_scaled"}), 135 | "split_files_diffusion_models_wan2_1_t2v_1_3B_bf16": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_t2v_1_3B_bf16"}), 136 | "split_files_diffusion_models_wan2_1_t2v_1_3B_fp16": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_t2v_1_3B_fp16"}), 137 | "split_files_diffusion_models_wan2_1_t2v_14B_bf16": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_t2v_14B_bf16"}), 138 | "split_files_diffusion_models_wan2_1_t2v_14B_fp16": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_t2v_14B_fp16"}), 139 | "split_files_diffusion_models_wan2_1_t2v_14B_fp8_e4m3fn": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_t2v_14B_fp8_e4m3fn"}), 140 | "split_files_diffusion_models_wan2_1_t2v_14B_fp8_scaled": ("BOOLEAN", {"tooltip": "select to download split_files_diffusion_models_wan2_1_t2v_14B_fp8_scaled"}), 141 | "split_files_text_encoders_umt5_xxl_fp16": ("BOOLEAN", {"tooltip": "select to download split_files_text_encoders_umt5_xxl_fp16"}), 142 | "split_files_text_encoders_umt5_xxl_fp8_e4m3fn_scaled": ("BOOLEAN", {"tooltip": "select to download split_files_text_encoders_umt5_xxl_fp8_e4m3fn_scaled"}), 143 | "split_files_vae_wan_2_1_vae": ("BOOLEAN", {"tooltip": "select to download split_files_vae_wan_2_1_vae"}), 144 | 145 | }, 146 | } 147 | RETURN_TYPES = ("STRING",) 148 | RETURN_NAMES = ("path",) 149 | FUNCTION = "DownloadModel" 150 | CATEGORY = "DownloadModel" 151 | DESCRIPTION = "This node downloads ALL ALIMAMA's WAN models from huggingface Comfy-Org/Wan_2.1_ComfyUI_repackaged repo" 152 | 153 | def DownloadModel(self, split_files_clip_vision_clip_vision_h , split_files_diffusion_models_wan2_1_i2v_480p_14B_bf16 , split_files_diffusion_models_wan2_1_i2v_480p_14B_fp16 , split_files_diffusion_models_wan2_1_i2v_480p_14B_fp8_e4m3fn , split_files_diffusion_models_wan2_1_i2v_480p_14B_fp8_scaled , split_files_diffusion_models_wan2_1_i2v_720p_14B_bf16 , split_files_diffusion_models_wan2_1_i2v_720p_14B_fp16 , split_files_diffusion_models_wan2_1_i2v_720p_14B_fp8_e4m3fn , split_files_diffusion_models_wan2_1_i2v_720p_14B_fp8_scaled , split_files_diffusion_models_wan2_1_t2v_1_3B_bf16 , split_files_diffusion_models_wan2_1_t2v_1_3B_fp16 , split_files_diffusion_models_wan2_1_t2v_14B_bf16 , split_files_diffusion_models_wan2_1_t2v_14B_fp16 , split_files_diffusion_models_wan2_1_t2v_14B_fp8_e4m3fn , split_files_diffusion_models_wan2_1_t2v_14B_fp8_scaled , split_files_text_encoders_umt5_xxl_fp16 , split_files_text_encoders_umt5_xxl_fp8_e4m3fn_scaled , split_files_vae_wan_2_1_vae): 154 | status="" 155 | if(split_files_clip_vision_clip_vision_h): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/clip_vision/clip_vision_h.safetensors", local_dir="/workspace/ComfyUI/models/clip_vision/"); status=status+model_path+" done." 156 | if(split_files_diffusion_models_wan2_1_i2v_480p_14B_bf16): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_i2v_480p_14B_bf16.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 157 | if(split_files_diffusion_models_wan2_1_i2v_480p_14B_fp16): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_i2v_480p_14B_fp16.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 158 | if(split_files_diffusion_models_wan2_1_i2v_480p_14B_fp8_e4m3fn): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_i2v_480p_14B_fp8_e4m3fn.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 159 | if(split_files_diffusion_models_wan2_1_i2v_480p_14B_fp8_scaled): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_i2v_480p_14B_fp8_scaled.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 160 | if(split_files_diffusion_models_wan2_1_i2v_720p_14B_bf16): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_i2v_720p_14B_bf16.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 161 | if(split_files_diffusion_models_wan2_1_i2v_720p_14B_fp16): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_i2v_720p_14B_fp16.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 162 | if(split_files_diffusion_models_wan2_1_i2v_720p_14B_fp8_e4m3fn): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_i2v_720p_14B_fp8_e4m3fn.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 163 | if(split_files_diffusion_models_wan2_1_i2v_720p_14B_fp8_scaled): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_i2v_720p_14B_fp8_scaled.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 164 | if(split_files_diffusion_models_wan2_1_t2v_1_3B_bf16): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_t2v_1.3B_bf16.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 165 | if(split_files_diffusion_models_wan2_1_t2v_1_3B_fp16): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_t2v_1.3B_fp16.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 166 | if(split_files_diffusion_models_wan2_1_t2v_14B_bf16): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_t2v_14B_bf16.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 167 | if(split_files_diffusion_models_wan2_1_t2v_14B_fp16): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_t2v_14B_fp16.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 168 | if(split_files_diffusion_models_wan2_1_t2v_14B_fp8_e4m3fn): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_t2v_14B_fp8_e4m3fn.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 169 | if(split_files_diffusion_models_wan2_1_t2v_14B_fp8_scaled): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/diffusion_models/wan2.1_t2v_14B_fp8_scaled.safetensors", local_dir="/workspace/ComfyUI/models/unet/"); status=status+model_path+" done." 170 | if(split_files_text_encoders_umt5_xxl_fp16): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/text_encoders/umt5_xxl_fp16.safetensors", local_dir="/workspace/ComfyUI/models/clip/"); status=status+model_path+" done." 171 | if(split_files_text_encoders_umt5_xxl_fp8_e4m3fn_scaled): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors", local_dir="/workspace/ComfyUI/models/clip/"); status=status+model_path+" done." 172 | if(split_files_vae_wan_2_1_vae): model_path = hf_hub_download(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/vae/wan_2.1_vae.safetensors", local_dir="/workspace/ComfyUI/models/vae/"); status=status+model_path+" done." 173 | 174 | return (model_path,) 175 | 176 | class AutoDownloadALLModels: 177 | @classmethod 178 | def INPUT_TYPES(s): 179 | return { 180 | "required": { 181 | "modelandpath": ("STRING", {"tooltip": "Enter hugging face repo id"}), 182 | "repo_ids_manual": ("STRING", {"tooltip": "Enter hugging face repo id"}), 183 | }, 184 | } 185 | RETURN_TYPES = ("STRING",) 186 | RETURN_NAMES = ("status",) 187 | FUNCTION = "DownloadALLModel" 188 | CATEGORY = "DownloadALLModel" 189 | DESCRIPTION = "This node downloads models from huggingface models" 190 | 191 | def DownloadALLModel(self, modelandpath, repo_ids_manual): 192 | manualrepoids=repo_ids_manual.split(",") 193 | split_text = modelandpath.strip("()").split("),(") 194 | status=[] 195 | for item in split_text: 196 | try: 197 | print(item) 198 | model_name, folder_name = item.split("~~~") 199 | mname, extension = model_name.rsplit('.', 1) 200 | repo_ids=self.search_huggingface_models(mname,limit=5) 201 | for repo in repo_ids: 202 | status.append(repo) 203 | repo_id="" 204 | if(len(repo_ids)>0): 205 | repo_id=repo_ids[0] 206 | model_file_name=self.search_file_in_repo(repo_id,model_name) 207 | model_path = hf_hub_download(repo_id=repo_id, filename=model_file_name, local_dir="/workspace/ComfyUI/models/"+folder_name+"/") 208 | status.append(model_path) 209 | else: 210 | for manualrepo in manualrepoids: 211 | model_file_name=self.search_file_in_repo(manualrepo,model_name) 212 | if(model_file_name!=None): 213 | model_path = hf_hub_download(repo_id=manualrepo, filename=model_file_name, local_dir="/workspace/ComfyUI/models/"+folder_name+"/") 214 | status.append(model_path) 215 | break 216 | 217 | 218 | 219 | 220 | 221 | 222 | except Exception as e: 223 | print(f"Error: Cannot process '{item}'. Exception: {e}") 224 | status.append(f"Error: Cannot process '{item}'. Exception: {e}") 225 | 226 | return (", ".join(status),) 227 | 228 | def search_file_in_repo(self,repo_id, filename): 229 | """ 230 | Searches for a specific file inside a Hugging Face repository. 231 | 232 | Args: 233 | repo_id (str): The Hugging Face repo ID (e.g., "gemasai/4x_NMKD-Siax_200k"). 234 | filename (str): The filename to search for. 235 | 236 | Returns: 237 | str or None: The file path if found, otherwise None. 238 | """ 239 | api = HfApi() 240 | files = api.list_repo_files(repo_id) 241 | 242 | for file in files: 243 | if filename in file: 244 | return file # Return the matching file path 245 | 246 | return None # Return None if file is not found 247 | def search_huggingface_models(self, query, limit=10): 248 | """ 249 | Searches for models on Hugging Face based on the query. 250 | 251 | Args: 252 | query (str): The search keyword. 253 | limit (int): Maximum number of results to return. 254 | 255 | Returns: 256 | list: A list of matching model names. 257 | """ 258 | models = list_models(search=query, limit=limit) 259 | #model=models[0] 260 | #return model.id 261 | return [model.id for model in models] # Extract only model IDs 262 | class GetModelsFromWorkflow: 263 | @classmethod 264 | def INPUT_TYPES(s): 265 | return { 266 | "required": { 267 | "workflow_path": ("STRING", {"tooltip": "Enter path of your workflow"}), 268 | "models_folder_path": ("STRING", {"default":"/workspace/ComfyUI/models/", "tooltip": "Enter path of your workflow"}), 269 | }, 270 | } 271 | RETURN_TYPES = ("STRING",) 272 | RETURN_NAMES = ("pa",) 273 | FUNCTION = "find_ml_models" 274 | CATEGORY = "DownloadModel" 275 | DESCRIPTION = "This node maps models from huggingface to folders" 276 | 277 | 278 | 279 | 280 | 281 | def get_folders_list(self, directory_path): 282 | """ 283 | Returns a list of folder names inside the given directory. 284 | 285 | Args: 286 | directory_path (str): The path to the directory. 287 | 288 | Returns: 289 | list: A list containing folder names. 290 | """ 291 | try: 292 | return [f for f in os.listdir(directory_path) if os.path.isdir(os.path.join(directory_path, f))] 293 | except FileNotFoundError: 294 | print("Error: Directory not found.") 295 | return [] 296 | except PermissionError: 297 | print("Error: Permission denied.") 298 | return [] 299 | 300 | def find_ml_models(self, workflow_path, models_folder_path): 301 | """ 302 | Finds all ML models inside a JSON file that belong to predefined folder categories. 303 | 304 | Args: 305 | json_path (str): Path to the JSON file. 306 | base_directory (str): Path to the base directory where models might be stored. 307 | 308 | Returns: 309 | tuple: (list of model files, list of nodes containing models) 310 | """ 311 | model_extensions = { 312 | ".safetensors", ".pth", ".pkl", ".bin", ".onnx", ".h5", ".ckpt", ".tflite", 313 | ".pb", ".joblib", ".pt", ".tar", ".npz", ".mar", ".npy", ".mlmodel", 314 | ".hdf5", ".weights", ".model", ".caffemodel", ".pbtxt" 315 | } 316 | 317 | valid_folders = {'checkpoints', 'controlnet', 'gligen', 'style_models', 'vae', 'clip', 318 | 'diffusers', 'hypernetworks', 'text_encoders', 'vae_approx', 'clip_vision', 319 | 'diffusion_models', 'loras', 'unet', 'ckpt', 'configs', 'embeddings', 320 | 'photomaker', 'upscale_models'} 321 | 322 | existing_folders = set(self.get_folders_list(models_folder_path)) 323 | 324 | model_files = [] 325 | model_nodes = [] 326 | 327 | with open(workflow_path, "r", encoding="utf-8") as f: 328 | data = json.load(f) 329 | 330 | for node in data.get("nodes", []): 331 | properties = node.get("properties", {}) 332 | 333 | if "models" in properties and isinstance(properties["models"], list): 334 | for model in properties["models"]: 335 | if isinstance(model, dict) and "name" in model: 336 | model_name = model["name"] 337 | if any(model_name.endswith(ext) for ext in model_extensions): 338 | model_path = model.get("directory", "") 339 | if model_path in valid_folders and model_path in existing_folders: 340 | model_files.append(model_name) 341 | model_nodes.append(node) 342 | 343 | if "widgets_values" in node: 344 | for value in node["widgets_values"]: 345 | if isinstance(value, str) and any(value.endswith(ext) for ext in model_extensions): 346 | model_files.append(value) 347 | model_nodes.append(node) 348 | 349 | model_mappings = [] 350 | 351 | for model, node in zip(model_files, model_nodes): 352 | node_type = node.get("type", "").lower() 353 | 354 | # Default to 'checkpoints' if no match is found 355 | probable_folder = "checkpoints" 356 | nodecontent=json.dumps(node, ensure_ascii=False).lower() 357 | probable_folder_percentage=self.calculate_partial_word_percentage(valid_folders, nodecontent, threshold=80) 358 | 359 | probable_folder=probable_folder_percentage[0] 360 | 361 | model_mappings.append(f"("+model+ "~~~"+ probable_folder+")") 362 | 363 | print(len(model_mappings)) 364 | formatted_string = ",".join(model_mappings) 365 | print(formatted_string) 366 | return (formatted_string,) 367 | 368 | 369 | 370 | def calculate_partial_word_percentage(self, valid_folders, big_text, threshold=80): 371 | """ 372 | Calculates the percentage of each word in valid_folders that appears fully or partially in big_text. 373 | 374 | Args: 375 | valid_folders (set): A set of words to check. 376 | big_text (str): The large text to analyze. 377 | threshold (int): The similarity threshold (default: 80). 378 | 379 | Returns: 380 | dict: Dictionary with words as keys and their occurrence percentage as values. 381 | """ 382 | big_text_lower = big_text.lower().split() # Convert text to lowercase and split into words 383 | total_words = len(big_text_lower) # Total words in the big text 384 | 385 | word_percentages = {} 386 | 387 | # Check each folder name for full or partial presence 388 | for word in valid_folders: 389 | matches = process.extract(word.lower(), big_text_lower, scorer=fuzz.partial_ratio, limit=None) 390 | match_count = sum(1 for match in matches if match[1] >= threshold) # Count words with high similarity 391 | 392 | # Calculate percentage 393 | word_percentages[word] = (match_count / total_words) * 100 if total_words > 0 else 0 394 | best_match = max(word_percentages.items(), key=lambda x: x[1], default=(None, 0)) 395 | return best_match 396 | 397 | 398 | 399 | 400 | 401 | 402 | class ShowModelsAndFolderMappings: 403 | @classmethod 404 | def INPUT_TYPES(s): 405 | return { 406 | "required": { 407 | "mappings": ("STRING",), 408 | }, 409 | } 410 | 411 | FUNCTION = "ShowMappings" 412 | CATEGORY = "ShowMappings" 413 | RETURN_TYPES = ("STRING",) 414 | RETURN_NAMES = ("Models Paths",) 415 | DESCRIPTION = "This node downloads models from huggingface models" 416 | 417 | def ShowMappings(self, mappings): 418 | print(len(mappings)) 419 | formatted_list = [] 420 | for mapping in mappings: 421 | print("H-------------------------------") 422 | print(mapping) 423 | formatted_item = "("+mapping+")" 424 | formatted_list.append(formatted_item) 425 | formatted_string = ",".join(formatted_list) 426 | print("Helloooooooooo2") 427 | print(formatted_string) 428 | return formatted_string 429 | 430 | 431 | 432 | 433 | 434 | class SetModelPath: 435 | @classmethod 436 | def INPUT_TYPES(s): 437 | return { 438 | "required": { 439 | "modelandpath": ("STRING", {"tooltip": "Enter hugging face repo id"}), 440 | }, 441 | } 442 | RETURN_TYPES = ("STRING",) 443 | RETURN_NAMES = ("modelpath",) 444 | FUNCTION = "SetModelPath" 445 | CATEGORY = "SetModelPath" 446 | DESCRIPTION = "This node downloads models from huggingface models" 447 | 448 | def SetModelPath(self, modelandpath): 449 | 450 | 451 | return (modelandpath,) 452 | 453 | 454 | 455 | class AutoInstallRequirements_txt: 456 | @classmethod 457 | def INPUT_TYPES(s): 458 | return { 459 | "required": { 460 | "custom_nodes_path": ("STRING", {"tooltip": "Enter custom_nodes_path"}), 461 | 462 | }, 463 | } 464 | RETURN_TYPES = ("STRING",) 465 | RETURN_NAMES = ("status",) 466 | FUNCTION = "InstallAllCustomNodes" 467 | CATEGORY = "InstallAllCustomNodes" 468 | DESCRIPTION = "This node downloads models from huggingface models" 469 | 470 | def InstallAllCustomNodes(self, custom_nodes_path): 471 | status=[] 472 | requirements_files = [] 473 | for root, dirs, files in os.walk(custom_nodes_path): 474 | if 'ComfyUI-Manager' in root: 475 | continue 476 | for file in files: 477 | if file == "requirements.txt": 478 | full_path = os.path.join(root, file) 479 | requirements_files.append(full_path) 480 | for file in requirements_files: 481 | if os.path.isfile(file): 482 | try: 483 | status.append("Working on - "+file) 484 | result = subprocess.run( 485 | [sys.executable, "-m", "pip", "install", "-r", file], 486 | check=True, 487 | capture_output=True, 488 | text=True 489 | ) 490 | 491 | status.append(result.stdout) 492 | except subprocess.CalledProcessError as e: 493 | 494 | status.append(e.stderr) 495 | 496 | 497 | return ("/n ".join(status),) 498 | NODE_CLASS_MAPPINGS = { 499 | "AutoDownloadModels": AutoDownloadModels, 500 | "ShowModelsAndFolderMappings": ShowModelsAndFolderMappings, 501 | "GetModelsFromWorkflow": GetModelsFromWorkflow, 502 | "SetModelPath": SetModelPath, 503 | "AutoDownloadALLModels": AutoDownloadALLModels, 504 | "WANModelsAutoDownload": WANModelsAutoDownload, 505 | "WANALMAMAModelsAutoDownload": WANALMAMAModelsAutoDownload, 506 | "ALIMAMAFUNCONTROLWANModelsAutoDownload": ALIMAMAFUNCONTROLWANModelsAutoDownload, 507 | "AutoInstallRequirements_txt": AutoInstallRequirements_txt, 508 | 509 | 510 | 511 | 512 | } 513 | NODE_DISPLAY_NAME_MAPPINGS = { 514 | "AutoDownloadModels": "Auto Download Models", 515 | "ShowModelsAndFolderMappings": "Show Models And Folder Mappings", 516 | "GetModelsFromWorkflow": "Get Models From Workflow", 517 | "SetModelPath": "Set Model Path", 518 | "AutoDownloadALLModels": "Auto Download ALL Models", 519 | "WANModelsAutoDownload": "Auto Download ALL WAN Models from Kijai's repo", 520 | "WANALMAMAModelsAutoDownload": "Auto Download ALL WAN Models from Comfy-Org/Wan_2.1_ComfyUI_repackaged", 521 | "ALIMAMAFUNCONTROLWANModelsAutoDownload": "Auto Download ALL WAN Models fromalibaba-pai/Wan2.1-Fun-1.3B-Control", 522 | "AutoInstallRequirements_txt": "Auto Install All Custom Nodes Requirements_txt", 523 | } 524 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [project] 2 | name = "autodownloadmodels" 3 | description = "This custom node helps to auto download models from huggingface." 4 | version = "1.0.0" 5 | license = {file = "LICENSE"} 6 | dependencies = ["huggingface_hub[hf_transfer]", "hf_transfer", "rapidfuzz"] 7 | 8 | [project.urls] 9 | Repository = "https://github.com/AIExplorer25/ComfyUI_AutoDownloadModels" 10 | # Used by Comfy Registry https://comfyregistry.org 11 | 12 | [tool.comfy] 13 | PublisherId = "aiexplorer25" 14 | DisplayName = "ComfyUI_AutoDownloadModels" 15 | Icon = "" 16 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | huggingface_hub[hf_transfer] 2 | hf_transfer 3 | rapidfuzz --------------------------------------------------------------------------------