Update pyproject.toml

Added proper backend validation for both config.json and model.safetensors to confirm model availability. Updated frontend logic to use /matting/check-model response, preventing unnecessary download notifications.

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -1,20 +1,75 @@
 name: 🐞 Bug Report
-description: Report an error or unexpected behavior
+description: 'Report something that is not working correctly'
 title: "[BUG] "
 labels: [bug]
 body:
+  - type: checkboxes
+    attributes:
+      label: Prerequisites
+      options:
+        - label: I am running the latest version of [ComfyUI](https://github.com/comfyanonymous/ComfyUI/releases)
+          required: true
+        - label: I am running the latest version of [ComfyUI_frontend](https://github.com/Comfy-Org/ComfyUI_frontend/releases)
+          required: true
+        - label: I am running the latest version of LayerForge [Github](https://github.com/Azornes/Comfyui-LayerForge/releases) | [Manager](https://registry.comfy.org/publishers/azornes/nodes/layerforge)
+          required: true
+        - label: I have searched existing(open/closed) issues to make sure this isn't a duplicate
+          required: true
+
+  - type: textarea
+    id: description
+    attributes:
+      label: What happened?
+      description: A clear and concise description of the bug. Include screenshots or videos if helpful.
+      placeholder: |
+        Example: "When I connect a image to an Input, the connection line appears but the workflow fails to execute with an error message..."
+    validations:
+      required: true
+
+  - type: textarea
+    id: reproduce
+    attributes:
+      label: Steps to Reproduce
+      description: How can I reproduce this issue? Please attach your workflow (JSON or PNG) if needed.
+      placeholder: |
+        1. Connect Image to Input
+        2. Click Queue Prompt
+        3. See error
+    validations:
+      required: true
+
+  - type: dropdown
+    id: severity
+    attributes:
+      label: How is this affecting you?
+      options:
+        - Crashes ComfyUI completely
+        - Workflow won't execute
+        - Feature doesn't work as expected
+        - Visual/UI issue only
+        - Minor inconvenience
+    validations:
+      required: true
+    
+  - type: dropdown
+    id: browser
+    attributes:
+      label: Browser
+      description: Which browser are you using?
+      options:
+        - Chrome/Chromium
+        - Firefox
+        - Safari
+        - Edge
+        - Other
+    validations:
+      required: true
+
   - type: markdown
     attributes:
       value: |
-        **Thank you for reporting a bug!**  
-        Please follow these steps to capture all necessary information:
-
-        ### ✅ Before You Report:
-        1. Make sure you have the **latest versions**:
-           - [ComfyUI Github](https://github.com/comfyanonymous/ComfyUI/releases)
-           - [LayerForge Github](https://github.com/Azornes/Comfyui-LayerForge/releases) or via [ComfyUI Node Manager](https://registry.comfy.org/publishers/azornes/nodes/layerforge)
-        2. Gather the required logs:
-        
+        ## Additional Information (Optional)
+        *The following fields help me debug complex issues but are not required for most bug reports.*
         ### 🔍 Enable Debug Logs (for **full** logs):
         
         #### 1. Edit `config.js` (Frontend Logs):
@@ -46,75 +101,13 @@ body:
         ```
 
         ➡️ **Restart ComfyUI** after applying these changes to activate full logging.
-
-  - type: input
-    id: environment
-    attributes:
-      label: Environment (OS, ComfyUI version, LayerForge version)
-      placeholder: e.g. Windows 11, ComfyUI v0.3.43, LayerForge v1.2.4
-    validations:
-      required: true
-
-  - type: input
-    id: browser
-    attributes:
-      label: Browser & Version
-      placeholder: e.g. Chrome 115.0.0, Firefox 120.1.0
-    validations:
-      required: true
-
   - type: textarea
-    id: what_happened
+    id: console-errors
     attributes:
-      label: What Happened?
-      placeholder: Describe the issue you encountered
-    validations:
-      required: true
-
-  - type: textarea
-    id: steps
-    attributes:
-      label: Steps to Reproduce
-      placeholder: |
-        1. …
-        2. …
-        3. …
-    validations:
-      required: true
-
-  - type: textarea
-    id: expected
-    attributes:
-      label: Expected Behavior
-      placeholder: Describe what you expected to happen
-    validations:
-      required: true
-
-  - type: textarea
-    id: actual
-    attributes:
-      label: Actual Behavior
-      placeholder: Describe what happened instead
-    validations:
-      required: true
-
-  - type: textarea
-    id: backend_logs
-    attributes:
-      label: ComfyUI (Backend) Logs
-      description: |
-        After enabling DEBUG logs, please:
-        1. Restart ComfyUI.
-        2. Reproduce the issue.
-        3. Copy-paste the newest **TEXT** logs from the terminal/console here.
-    validations:
-      required: true
-
-  - type: textarea
-    id: console_logs
-    attributes:
-      label: Browser Console Logs
+      label: Console Errors
       description: |
+        If you see red error messages in the browser console (F12), paste them here
+        More info:
         After enabling DEBUG logs:
         1. Open Developer Tools → Console.
           - Chrome/Edge (Win/Linux): `Ctrl+Shift+J`  
@@ -128,11 +121,25 @@ body:
            - Safari: 🗑 icon or `Cmd+K`.
         3. Reproduce the issue.
         4. Copy-paste the **TEXT** logs here (no screenshots).
-    validations:
-      required: true
+      render: javascript
 
-  - type: markdown
+  - type: textarea
+    id: logs
     attributes:
-      value: |
-        **Optional:** You can also **attach a screenshot or video** to demonstrate the issue visually.  
-        Simply drag & drop or paste image/video files into this issue form. GitHub supports common image formats and MP4/GIF files.
+      label: Logs
+      description: |
+        If relevant, paste any terminal/server logs here
+        More info:
+        After enabling DEBUG logs, please:
+        1. Restart ComfyUI.
+        2. Reproduce the issue.
+        3. Copy-paste the newest **TEXT** logs from the terminal/console here.
+      render: shell
+
+  - type: textarea
+    id: additional
+    attributes:
+      label: Additional Context, Environment (OS, ComfyUI versions, ResolutionMaster version)
+      description: Any other information that might help (OS, GPU, specific nodes involved, etc.)
+
+      

.github/ISSUE_TEMPLATE/feature-request.yml

@@ -6,7 +6,19 @@ body:
   - type: markdown
     attributes:
       value: |
-        **Before suggesting a new feature, please make sure you are using the latest version of the project and that this functionality does not already exist.**
+        ## Before suggesting a new feature...
+        Please make sure of the following:
+
+        1. You are using the latest version of the project  
+        2. The functionality you want to propose does not already exist  
+
+        I also recommend using an AI assistant to check whether the feature is already included.  
+        To do this, simply:
+
+        - Copy and paste the entire **README.md** file  
+        - Ask if your desired feature is already covered  
+
+        This helps to avoid duplicate requests for features that are already available.
   - type: markdown
     attributes:
       value: |

.github/workflows/ComfyUIdownloads.yml

@@ -20,7 +20,7 @@ jobs:
           max_downloads=0
           top_node_json="{}"
           
-          for i in {1..20}; do
+          for i in {1..3}; do
             echo "Pobieranie danych z próby $i..."
             curl -s https://api.comfy.org/nodes/layerforge > tmp_$i.json
             

README.md

@@ -51,9 +51,16 @@ https://github.com/user-attachments/assets/9c7ce1de-873b-4a3b-8579-0fc67642af3a
 - **AI-Powered Matting:** Optional background removal for any layer using the `BiRefNet` model.
 - **Efficient Memory Management:** An automatic garbage collection system cleans up unused image data to keep the
   browser's storage footprint low.
-- **Workflow Integration:** Outputs a final composite **image** and a combined alpha **mask**, ready for any other
-  ComfyUI node.
-
+- **Inputs**
+    - **Image Input (optional):** Accepts a single image.  
+    - **Multiple Images:** If you need to feed in more than one image, use the **core ComfyUI Batch Image node**.  
+        - This lets you route multiple images into LayerForge.  
+        - You can then stack, arrange, and edit them as separate layers inside the canvas.
+  - **Mask Input (optional):** Accepts a single external mask.  
+    - When provided, the mask is applied directly to the **output area** of the LayerForge canvas when `Run` is triggered in ComfyUI.  
+- **Outputs**
+    - **Composite Image:** The final flattened result of your layer stack.  
+    - **Combined Alpha Mask:** A merged mask representing all visible layers, ready for downstream nodes.  
 ---
 
 ## 🚀 Installation
@@ -248,6 +255,11 @@ This project is licensed under the MIT License. Feel free to use, modify, and di
 
 ---
 
+## 💖 Support / Sponsorship
+
+If you’d like to support my work:  
+👉 [GitHub Sponsors](https://github.com/sponsors/Azornes)
+
 ## 🙏 Acknowledgments
 
 Based on the original [**Comfyui-Ycanvas**](https://github.com/yichengup/Comfyui-Ycanvas) by yichengup. This fork

canvas_node.py

@@ -64,6 +64,8 @@ class BiRefNetConfig(PretrainedConfig):
 
     def __init__(self, bb_pretrained=False, **kwargs):
         self.bb_pretrained = bb_pretrained
+        # Add the missing is_encoder_decoder attribute for compatibility with newer transformers
+        self.is_encoder_decoder = False
         super().__init__(**kwargs)
 
 
@@ -755,16 +757,32 @@ class BiRefNetMatting:
                 full_model_path = os.path.join(self.base_path, "BiRefNet")
                 log_info(f"Loading BiRefNet model from {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=full_model_path,
+                        # Add force_download=False to use cached version if available
+                        force_download=False,
+                        # Add local_files_only=False to allow downloading if needed
+                        local_files_only=False
                     )
                     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 Hugging Face")
+                except AttributeError as e:
+                    if "'Config' object has no attribute 'is_encoder_decoder'" in str(e):
+                        log_error("Compatibility issue detected with transformers library. This has been fixed in the code.")
+                        log_error("If you're still seeing this error, please clear the model cache and try again.")
+                        raise RuntimeError(
+                            "Model configuration compatibility issue detected. "
+                            f"Please delete the model cache directory '{full_model_path}' and restart ComfyUI. "
+                            "This will download a fresh copy of the model with the updated configuration."
+                        ) from e
+                    else:
+                        raise e
                 except JSONDecodeError as e:                    
                     log_error(f"JSONDecodeError: Failed to load model from {full_model_path}. The model's config.json may be corrupted.")
                     raise RuntimeError(
@@ -894,6 +912,95 @@ class BiRefNetMatting:
 
 _matting_lock = None
 
+@PromptServer.instance.routes.get("/matting/check-model")
+async def check_matting_model(request):
+    """Check if the matting model is available and ready to use"""
+    try:
+        if not TRANSFORMERS_AVAILABLE:
+            return web.json_response({
+                "available": False,
+                "reason": "missing_dependency",
+                "message": "The 'transformers' library is required for the matting feature. Please install it by running: pip install transformers"
+            })
+        
+        # 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")
+        model_path = os.path.join(base_path, "BiRefNet")
+        
+        # Look for the actual BiRefNet model structure
+        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")
+            return web.json_response({
+                "available": True,
+                "reason": "ready",
+                "message": "Model is ready to use"
+            })
+        else:
+            log_info(f"BiRefNet model not found in {model_path}")
+            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
+            })
+            
+    except Exception as e:
+        log_error(f"Error checking matting model: {str(e)}")
+        return web.json_response({
+            "available": False,
+            "reason": "error",
+            "message": f"Error checking model status: {str(e)}"
+        }, status=500)
+
 @PromptServer.instance.routes.post("/matting")
 async def matting(request):
     global _matting_lock

js/CanvasView.js

@@ -343,11 +343,38 @@ async function createCanvasWidget(node, widget, app) {
                         const button = e.target.closest('.matting-button');
                         if (button.classList.contains('loading'))
                             return;
-                        const spinner = $el("div.matting-spinner");
-                        button.appendChild(spinner);
-                        button.classList.add('loading');
-                        showInfoNotification("Starting background removal process...", 2000);
                         try {
+                            // First check if model is available
+                            const modelCheckResponse = await fetch("/matting/check-model");
+                            const modelStatus = await modelCheckResponse.json();
+                            if (!modelStatus.available) {
+                                switch (modelStatus.reason) {
+                                    case 'missing_dependency':
+                                        showErrorNotification(modelStatus.message, 8000);
+                                        return;
+                                    case 'not_downloaded':
+                                        showWarningNotification("The matting model needs to be downloaded first. This will happen automatically when you proceed (requires internet connection).", 5000);
+                                        // Ask user if they want to proceed with download
+                                        if (!confirm("The matting model needs to be downloaded (about 1GB). This is a one-time download. Do you want to proceed?")) {
+                                            return;
+                                        }
+                                        showInfoNotification("Downloading matting model... This may take a few minutes.", 10000);
+                                        break;
+                                    case 'corrupted':
+                                        showErrorNotification(modelStatus.message, 8000);
+                                        return;
+                                    case 'error':
+                                        showErrorNotification(`Error checking model: ${modelStatus.message}`, 5000);
+                                        return;
+                                }
+                            }
+                            // Proceed with matting
+                            const spinner = $el("div.matting-spinner");
+                            button.appendChild(spinner);
+                            button.classList.add('loading');
+                            if (modelStatus.available) {
+                                showInfoNotification("Starting background removal process...", 2000);
+                            }
                             if (canvas.canvasSelection.selectedLayers.length !== 1) {
                                 throw new Error("Please select exactly one image layer for matting.");
                             }
@@ -363,7 +390,20 @@ async function createCanvasWidget(node, widget, app) {
                             if (!response.ok) {
                                 let errorMsg = `Server error: ${response.status} - ${response.statusText}`;
                                 if (result && result.error) {
-                                    errorMsg = `Error: ${result.error}. Details: ${result.details || 'Check console'}`;
+                                    // Handle specific error types
+                                    if (result.error === "Network Connection Error") {
+                                        showErrorNotification("Failed to download the matting model. Please check your internet connection and try again.", 8000);
+                                        return;
+                                    }
+                                    else if (result.error === "Matting Model Error") {
+                                        showErrorNotification(result.details || "Model loading error. Please check the console for details.", 8000);
+                                        return;
+                                    }
+                                    else if (result.error === "Dependency Not Found") {
+                                        showErrorNotification(result.details || "Missing required dependencies.", 8000);
+                                        return;
+                                    }
+                                    errorMsg = `${result.error}: ${result.details || 'Check console'}`;
                                 }
                                 throw new Error(errorMsg);
                             }
@@ -383,11 +423,16 @@ async function createCanvasWidget(node, widget, app) {
                         catch (error) {
                             log.error("Matting error:", error);
                             const errorMessage = error.message || "An unknown error occurred.";
-                            showErrorNotification(`Matting Failed: ${errorMessage}`);
+                            if (!errorMessage.includes("Network Connection Error") &&
+                                !errorMessage.includes("Matting Model Error") &&
+                                !errorMessage.includes("Dependency Not Found")) {
+                                showErrorNotification(`Matting Failed: ${errorMessage}`);
+                            }
                         }
                         finally {
                             button.classList.remove('loading');
-                            if (button.contains(spinner)) {
+                            const spinner = button.querySelector('.matting-spinner');
+                            if (spinner && button.contains(spinner)) {
                                 button.removeChild(spinner);
                             }
                         }

js/utils/ImageUploadUtils.js

@@ -1,3 +1,4 @@
+// @ts-ignore
 import { api } from "../../../scripts/api.js";
 import { createModuleLogger } from "./LoggerUtils.js";
 import { withErrorHandling, createValidationError, createNetworkError } from "../ErrorHandler.js";

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 = "1.5.9"
+version = "1.5.10"
 license = { text = "MIT License" }
 dependencies = ["torch", "torchvision", "transformers", "aiohttp", "numpy", "tqdm", "Pillow"]
 

src/CanvasView.ts

@@ -418,13 +418,46 @@ async function createCanvasWidget(node: ComfyNode, widget: any, app: ComfyApp):
                         const button = (e.target as HTMLElement).closest('.matting-button') as HTMLButtonElement;
                         if (button.classList.contains('loading')) return;
 
-                        const spinner = $el("div.matting-spinner") as HTMLDivElement;
-                        button.appendChild(spinner);
-                        button.classList.add('loading');
-                        
-                        showInfoNotification("Starting background removal process...", 2000);
-
                         try {
+                            // First check if model is available
+                            const modelCheckResponse = await fetch("/matting/check-model");
+                            const modelStatus = await modelCheckResponse.json();
+                            
+                            if (!modelStatus.available) {
+                                switch (modelStatus.reason) {
+                                    case 'missing_dependency':
+                                        showErrorNotification(modelStatus.message, 8000);
+                                        return;
+                                    
+                                    case 'not_downloaded':
+                                        showWarningNotification("The matting model needs to be downloaded first. This will happen automatically when you proceed (requires internet connection).", 5000);
+                                        
+                                        // Ask user if they want to proceed with download
+                                        if (!confirm("The matting model needs to be downloaded (about 1GB). This is a one-time download. Do you want to proceed?")) {
+                                            return;
+                                        }
+                                        showInfoNotification("Downloading matting model... This may take a few minutes.", 10000);
+                                        break;
+                                    
+                                    case 'corrupted':
+                                        showErrorNotification(modelStatus.message, 8000);
+                                        return;
+                                    
+                                    case 'error':
+                                        showErrorNotification(`Error checking model: ${modelStatus.message}`, 5000);
+                                        return;
+                                }
+                            }
+
+                            // Proceed with matting
+                            const spinner = $el("div.matting-spinner") as HTMLDivElement;
+                            button.appendChild(spinner);
+                            button.classList.add('loading');
+                            
+                            if (modelStatus.available) {
+                                showInfoNotification("Starting background removal process...", 2000);
+                            }
+
                             if (canvas.canvasSelection.selectedLayers.length !== 1) {
                                 throw new Error("Please select exactly one image layer for matting.");
                             }
@@ -443,7 +476,18 @@ async function createCanvasWidget(node: ComfyNode, widget: any, app: ComfyApp):
                             if (!response.ok) {
                                 let errorMsg = `Server error: ${response.status} - ${response.statusText}`;
                                 if (result && result.error) {
-                                    errorMsg = `Error: ${result.error}. Details: ${result.details || 'Check console'}`;
+                                    // Handle specific error types
+                                    if (result.error === "Network Connection Error") {
+                                        showErrorNotification("Failed to download the matting model. Please check your internet connection and try again.", 8000);
+                                        return;
+                                    } else if (result.error === "Matting Model Error") {
+                                        showErrorNotification(result.details || "Model loading error. Please check the console for details.", 8000);
+                                        return;
+                                    } else if (result.error === "Dependency Not Found") {
+                                        showErrorNotification(result.details || "Missing required dependencies.", 8000);
+                                        return;
+                                    }
+                                    errorMsg = `${result.error}: ${result.details || 'Check console'}`;
                                 }
                                 throw new Error(errorMsg);
                             }
@@ -468,10 +512,15 @@ async function createCanvasWidget(node: ComfyNode, widget: any, app: ComfyApp):
                         } catch (error: any) {
                             log.error("Matting error:", error);
                             const errorMessage = error.message || "An unknown error occurred.";
-                            showErrorNotification(`Matting Failed: ${errorMessage}`);
+                            if (!errorMessage.includes("Network Connection Error") && 
+                                !errorMessage.includes("Matting Model Error") &&
+                                !errorMessage.includes("Dependency Not Found")) {
+                                showErrorNotification(`Matting Failed: ${errorMessage}`);
+                            }
                         } finally {
                             button.classList.remove('loading');
-                            if (button.contains(spinner)) {
+                            const spinner = button.querySelector('.matting-spinner');
+                            if (spinner && button.contains(spinner)) {
                                 button.removeChild(spinner);
                             }
                         }

src/SAMDetectorIntegration.ts

@@ -1,3 +1,4 @@
+// @ts-ignore
 import { api } from "../../scripts/api.js";
 // @ts-ignore
 import { ComfyApp } from "../../scripts/app.js";

src/utils/ImageUploadUtils.ts

@@ -1,3 +1,4 @@
+// @ts-ignore
 import { api } from "../../../scripts/api.js";
 import { createModuleLogger } from "./LoggerUtils.js";
 import { withErrorHandling, createValidationError, createNetworkError } from "../ErrorHandler.js";