update model dB

support .zip file model

glob/manager_core.py

@@ -15,6 +15,7 @@ import threading
 import json
 import time
 import yaml
+import zipfile
 
 glob_path = os.path.join(os.path.dirname(__file__))  # ComfyUI-Manager/glob
 sys.path.append(glob_path)
@@ -22,7 +23,7 @@ sys.path.append(glob_path)
 import cm_global
 from manager_util import *
 
-version = [2, 29]
+version = [2, 30]
 version_str = f"V{version[0]}.{version[1]}" + (f'.{version[2]}' if len(version) > 2 else '')
 
 comfyui_manager_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
@@ -1156,3 +1157,30 @@ async def extract_nodes_from_workflow(filepath, mode='local', channel_url='defau
 
     return used_exts, unknown_nodes
 
+
+def unzip(model_path):
+    if not os.path.exists(model_path):
+        print(f"[ComfyUI-Manager] unzip: File not found: {model_path}")
+        return False
+
+    base_dir = os.path.dirname(model_path)
+    filename = os.path.basename(model_path)
+    target_dir = os.path.join(base_dir, filename[:-4])
+
+    os.makedirs(target_dir, exist_ok=True)
+
+    with zipfile.ZipFile(model_path, 'r') as zip_ref:
+        zip_ref.extractall(target_dir)
+
+    # Check if there's only one directory inside the target directory
+    contents = os.listdir(target_dir)
+    if len(contents) == 1 and os.path.isdir(os.path.join(target_dir, contents[0])):
+        nested_dir = os.path.join(target_dir, contents[0])
+        # Move each file and sub-directory in the nested directory up to the target directory
+        for item in os.listdir(nested_dir):
+            shutil.move(os.path.join(nested_dir, item), os.path.join(target_dir, item))
+        # Remove the now empty nested directory
+        os.rmdir(nested_dir)
+
+    os.remove(model_path)
+    return True

glob/manager_server.py

@@ -508,7 +508,12 @@ def check_model_installed(json_obj):
         item['installed'] = 'None'
 
         if model_path is not None:
-            if os.path.exists(model_path):
+            if model_path.endswith('.zip'):
+                if os.path.exists(model_path[:-4]):
+                    item['installed'] = 'True'
+                else:
+                    item['installed'] = 'False'
+            elif os.path.exists(model_path):
                 item['installed'] = 'True'
             else:
                 item['installed'] = 'False'
@@ -915,10 +920,17 @@ async def install_model(request):
                     model_url.startswith('https://github.com') or model_url.startswith('https://huggingface.co') or model_url.startswith('https://heibox.uni-heidelberg.de')):
                 model_dir = get_model_dir(json_data)
                 download_url(model_url, model_dir, filename=json_data['filename'])
+                if model_path.endswith('.zip'):
+                    res = core.unzip(model_path)
+                else:
+                    res = True
 
-                return web.json_response({}, content_type='application/json')
+                if res:
+                    return web.json_response({}, content_type='application/json')
             else:
                 res = download_url_with_agent(model_url, model_path)
+                if res and model_path.endswith('.zip'):
+                    res = core.unzip(model_path)
         else:
             print(f"Model installation error: invalid model type - {json_data['type']}")
 
@@ -926,7 +938,6 @@ async def install_model(request):
             return web.json_response({}, content_type='application/json')
     except Exception as e:
         print(f"[ERROR] {e}", file=sys.stderr)
-        pass
 
     return web.Response(status=400)
 

model-list.json

@@ -2571,6 +2571,16 @@
       "reference": "https://huggingface.co/InstantX/InstantID",
       "filename": "diffusion_pytorch_model.safetensors",
       "url": "https://huggingface.co/InstantX/InstantID/resolve/main/ControlNetModel/diffusion_pytorch_model.safetensors"
+    },
+    {
+      "name": "MonsterMMORPG/insightface (for InstantID)",
+      "type": "insightface",
+      "base": "SDXL",
+      "save_path": "insightface/models",
+      "description": "MonsterMMORPG insightface model for cubiq/InstantID",
+      "reference": "https://huggingface.co/MonsterMMORPG/tools/tree/main",
+      "filename": "antelopev2.zip",
+      "url": "https://huggingface.co/MonsterMMORPG/tools/resolve/main/antelopev2.zip"
     }
   ]
 }

node_db/new/model-list.json

@@ -1,5 +1,15 @@
 {
   "models": [
+    {
+      "name": "MonsterMMORPG/insightface (for InstantID)",
+      "type": "insightface",
+      "base": "SDXL",
+      "save_path": "insightface/models",
+      "description": "MonsterMMORPG insightface model for cubiq/InstantID",
+      "reference": "https://huggingface.co/MonsterMMORPG/tools/tree/main",
+      "filename": "antelopev2.zip",
+      "url": "https://huggingface.co/MonsterMMORPG/tools/resolve/main/antelopev2.zip"
+    },
     {
       "name": "InstantID/ip-adapter",
       "type": "instantid",
@@ -691,27 +701,6 @@
       "reference": "https://huggingface.co/guoyww/animatediff",
       "filename": "v3_sd15_adapter.ckpt",
       "url": "https://huggingface.co/guoyww/animatediff/resolve/main/v3_sd15_adapter.ckpt"
-    },
-
-    {
-      "name": "Segmind-Vega",
-      "type": "checkpoints",
-      "base": "segmind-vega",
-      "save_path": "checkpoints/segmind-vega",
-      "description": "The Segmind-Vega Model is a distilled version of the Stable Diffusion XL (SDXL), offering a remarkable 70% reduction in size and an impressive 100% speedup while retaining high-quality text-to-image generation capabilities.",
-      "reference": "https://huggingface.co/segmind/Segmind-Vega",
-      "filename": "segmind-vega.safetensors",
-      "url": "https://huggingface.co/segmind/Segmind-Vega/resolve/main/segmind-vega.safetensors"
-    },
-    {
-      "name": "Segmind-VegaRT - Latent Consistency Model (LCM) LoRA of Segmind-Vega",
-      "type": "lora",
-      "base": "segmind-vega",
-      "save_path": "loras/segmind-vega",
-      "description": "Segmind-VegaRT a distilled consistency adapter for Segmind-Vega that allows to reduce the number of inference steps to only between 2 - 8 steps.",
-      "reference": "https://huggingface.co/segmind/Segmind-VegaRT",
-      "filename": "pytorch_lora_weights.safetensors",
-      "url": "https://huggingface.co/segmind/Segmind-VegaRT/resolve/main/pytorch_lora_weights.safetensors"
     }
   ]
 }