Rebuild JS artifacts (no functional changes)

Changes are auto-generated by TypeScript build (formatting/newlines only). No logic changes.

canvas_node.py

@@ -741,27 +741,124 @@ class LayerForgeNode:
         return None
 
 
+def _get_birefnet_base_paths():
+    paths = []
+
+    comfy_models_dir = getattr(folder_paths, "models_dir", None)
+    if comfy_models_dir:
+        paths.append(os.path.join(comfy_models_dir, "BiRefNet"))
+
+    legacy_models_dir = os.path.join(
+        os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))),
+        "models",
+        "BiRefNet"
+    )
+    paths.append(legacy_models_dir)
+
+    unique_paths = []
+    seen = set()
+    for path in paths:
+        normalized = os.path.normpath(path)
+        if normalized not in seen:
+            seen.add(normalized)
+            unique_paths.append(path)
+
+    return unique_paths
+
+
+def _is_valid_birefnet_model_dir(path):
+    if not os.path.isdir(path):
+        return False
+
+    try:
+        files = os.listdir(path)
+    except OSError:
+        return False
+
+    has_config = "config.json" in files
+    has_model = "model.safetensors" in files or "pytorch_model.bin" in files
+    has_backbone = "backbone_swin.pth" in files or "swin_base_patch4_window12_384_22kto1k.pth" in files
+    has_birefnet = "birefnet.pth" in files or any(f.endswith(".pth") for f in files)
+
+    return has_config and (has_model or has_backbone or has_birefnet)
+
+
+def _find_local_birefnet_model():
+    for base_path in _get_birefnet_base_paths():
+        if not os.path.isdir(base_path):
+            continue
+
+        if _is_valid_birefnet_model_dir(base_path):
+            return base_path
+
+        try:
+            existing_items = os.listdir(base_path)
+        except OSError:
+            continue
+
+        model_subdirs = [
+            d for d in existing_items
+            if os.path.isdir(os.path.join(base_path, d)) and
+            (d.startswith("models--") or d == "ZhengPeng7--BiRefNet")
+        ]
+
+        for subdir in model_subdirs:
+            snapshots_path = os.path.join(base_path, subdir, "snapshots")
+            if not os.path.isdir(snapshots_path):
+                continue
+
+            try:
+                snapshot_dirs = os.listdir(snapshots_path)
+            except OSError:
+                continue
+
+            for snapshot in snapshot_dirs:
+                snapshot_path = os.path.join(snapshots_path, snapshot)
+                if _is_valid_birefnet_model_dir(snapshot_path):
+                    return snapshot_path
+
+    return None
+
+
 class BiRefNetMatting:
     def __init__(self):
         self.model = None
         self.model_path = None
         self.model_cache = {}
-
+        self.base_paths = _get_birefnet_base_paths()
-        self.base_path = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))),
-                                      "models")
 
     def load_model(self, model_path):
         from json.decoder import JSONDecodeError
         try:
             if model_path not in self.model_cache:
-                full_model_path = os.path.join(self.base_path, "BiRefNet")
+                local_model_path = _find_local_birefnet_model()
-                log_info(f"Loading BiRefNet model from {full_model_path}...")
+                cache_dir = self.base_paths[0] if self.base_paths else None
+
+                if local_model_path:
+                    log_info(f"Loading BiRefNet model from local path {local_model_path}...")
+                    try:
+                        self.model = AutoModelForImageSegmentation.from_pretrained(
+                            local_model_path,
+                            trust_remote_code=True
+                        )
+                        self.model.eval()
+                        if torch.cuda.is_available():
+                            self.model = self.model.cuda()
+                        self.model_cache[model_path] = self.model
+                        log_info("Model loaded successfully from local disk")
+                        return
+                    except Exception as local_error:
+                        log_warn(f"Failed to load local BiRefNet model from {local_model_path}: {str(local_error)}")
+                        log_info("Falling back to Hugging Face model loading")
+
+                full_model_path = cache_dir or "BiRefNet"
+                log_info(f"Loading BiRefNet model from Hugging Face cache {full_model_path}...")
                 try:
                     # Try loading with additional configuration to handle compatibility issues
                     self.model = AutoModelForImageSegmentation.from_pretrained(
                         "ZhengPeng7/BiRefNet",
                         trust_remote_code=True,
-                        cache_dir=full_model_path,
+                        cache_dir=cache_dir,
                         # Add force_download=False to use cached version if available
                         force_download=False,
                         # Add local_files_only=False to allow downloading if needed
@@ -924,73 +1021,25 @@ async def check_matting_model(request):
             })
         
         # Check if model exists in cache
-        base_path = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))), "models")
+        local_model_path = _find_local_birefnet_model()
-        model_path = os.path.join(base_path, "BiRefNet")
 
-        # Look for the actual BiRefNet model structure
+        if local_model_path:
-        model_files_exist = False
-        if os.path.exists(model_path):
-            # BiRefNet model from Hugging Face has a specific structure
-            # Check for subdirectories that indicate the model is downloaded
-            existing_items = os.listdir(model_path) if os.path.isdir(model_path) else []
-            
-            # Look for the model subdirectory (usually named with the model ID)
-            model_subdirs = [d for d in existing_items if os.path.isdir(os.path.join(model_path, d)) and 
-                           (d.startswith("models--") or d == "ZhengPeng7--BiRefNet")]
-            
-            if model_subdirs:
-                # Found model subdirectory, check inside for actual model files
-                for subdir in model_subdirs:
-                    subdir_path = os.path.join(model_path, subdir)
-                    # Navigate through the cache structure
-                    if os.path.exists(os.path.join(subdir_path, "snapshots")):
-                        snapshots_path = os.path.join(subdir_path, "snapshots")
-                        snapshot_dirs = os.listdir(snapshots_path) if os.path.isdir(snapshots_path) else []
-                        
-                        for snapshot in snapshot_dirs:
-                            snapshot_path = os.path.join(snapshots_path, snapshot)
-                            snapshot_files = os.listdir(snapshot_path) if os.path.isdir(snapshot_path) else []
-                            
-                            # Check for essential files - BiRefNet uses model.safetensors
-                            has_config = "config.json" in snapshot_files
-                            has_model = "model.safetensors" in snapshot_files or "pytorch_model.bin" in snapshot_files
-                            has_backbone = "backbone_swin.pth" in snapshot_files or "swin_base_patch4_window12_384_22kto1k.pth" in snapshot_files
-                            has_birefnet = "birefnet.pth" in snapshot_files or any(f.endswith(".pth") for f in snapshot_files)
-                            
-                            # Model is valid if it has config and either model.safetensors or other model files
-                            if has_config and (has_model or has_backbone or has_birefnet):
-                                model_files_exist = True
-                                log_info(f"Found model files in: {snapshot_path} (config: {has_config}, model: {has_model})")
-                                break
-                    
-                    if model_files_exist:
-                        break
-            
-            # Also check if there are .pth files directly in the model_path
-            if not model_files_exist:
-                direct_files = existing_items
-                has_config = "config.json" in direct_files
-                has_model_files = any(f.endswith((".pth", ".bin", ".safetensors")) for f in direct_files)
-                model_files_exist = has_config and has_model_files
-                
-                if model_files_exist:
-                    log_info(f"Found model files directly in: {model_path}")
-        
-        if model_files_exist:
             # Model files exist, assume it's ready
-            log_info("BiRefNet model files detected")
+            log_info(f"BiRefNet model files detected at {local_model_path}")
             return web.json_response({
                 "available": True,
                 "reason": "ready",
-                "message": "Model is ready to use"
+                "message": "Model is ready to use",
+                "model_path": local_model_path
             })
         else:
-            log_info(f"BiRefNet model not found in {model_path}")
+            searched_paths = _get_birefnet_base_paths()
+            log_info(f"BiRefNet model not found in any of: {searched_paths}")
             return web.json_response({
                 "available": False,
                 "reason": "not_downloaded",
                 "message": "The matting model needs to be downloaded. This will happen automatically when you first use the matting feature (requires internet connection).",
-                "model_path": model_path
+                "model_path": searched_paths[0] if searched_paths else None
             })
             
     except Exception as e:

js/CanvasInteractions.js

@@ -599,7 +599,8 @@ export class CanvasInteractions {
                     // so handlePasteEvent can access e.clipboardData for system images.
                     if (this.canvas.canvasLayers.internalClipboard.length > 0) {
                         this.canvas.canvasLayers.pasteLayers();
-                    } else {
+                    }
+                    else {
                         // Don't preventDefault - let paste event fire for system clipboard
                         handled = false;
                     }

js/utils/WebSocketManager.js

@@ -140,5 +140,6 @@ class WebSocketManager {
         }
     }
 }
-const wsUrl = `ws://${window.location.host}/layerforge/canvas_ws`;
+const protocol = location.protocol === "https:" ? "wss:" : "ws:";
+const wsUrl = `${protocol}//${location.host}/layerforge/canvas_ws`;
 export const webSocketManager = new WebSocketManager(wsUrl);

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "layerforge"
 description = "Photoshop-like layered canvas editor to your ComfyUI workflow. This node is perfect for complex compositing, inpainting, and outpainting, featuring multi-layer support, masking, blend modes, and precise transformations. Includes optional AI-powered background removal for streamlined image editing."
-version = "1.5.12"
+version = "1.5.13"
 license = { text = "MIT License" }
 dependencies = ["torch", "torchvision", "transformers", "aiohttp", "numpy", "tqdm", "Pillow"]
 

src/utils/WebSocketManager.ts

@@ -168,5 +168,6 @@ class WebSocketManager {
     }
 }
 
-const wsUrl = `ws://${window.location.host}/layerforge/canvas_ws`;
+const protocol = location.protocol === "https:" ? "wss:" : "ws:";
+const wsUrl = `${protocol}//${location.host}/layerforge/canvas_ws`;
 export const webSocketManager = new WebSocketManager(wsUrl);