Merge pull request #1 from ComfyNodePRs/publish

Add Github Action for Publishing to Comfy Registry

.github/workflows/publish.yml

@@ -0,0 +1,28 @@
+name: Publish to Comfy registry
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - main
+      - master
+    paths:
+      - "pyproject.toml"
+
+permissions:
+  issues: write
+
+jobs:
+  publish-node:
+    name: Publish Custom Node to registry
+    runs-on: ubuntu-latest
+    if: ${{ github.repository_owner == 'SatadalAI' }}
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v4
+        with:
+          submodules: true
+      - name: Publish Custom Node
+        uses: Comfy-Org/publish-node-action@v1
+        with:
+          ## Add your own personal access token to your Github Repository secrets and reference it here.
+          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}

README.md

@@ -1,7 +1,7 @@
 # SATA Utility Node Suite for ComfyUI
 
 **Author:** Satadal  
-**Version:** 1.2.0  
+**Version:** 1.5.0  
 **License:** MIT  
 **Repository:** https://github.com/SatadalAI/SATA_UtilityNode
 
@@ -18,6 +18,7 @@ It includes:
 - **Resolution Machine:** Quick selection of model-specific image resolutions for popular models.
 - **Save Image w/Metadata:** saving images with meta data and with different file formats.
 - **Prompt Autocomplete:** Text widget with autocompletion, random selection, and preview capabilities.
+- **Latent Machine:** Advanced noise generation for creating empty latents initialized with specific noise patterns instead of standard Gaussian noise.
 
 ---
 
@@ -30,7 +31,6 @@ It includes:
 - **CPU-based Rescaling:** Efficient resizing using OpenCV.
 - **Supersampling:** Optional detail preservation for downscaling/fractional resizing.
 - **Rounding Modulus:** Ensures output dimensions align with model/UI constraints.
-- **Dual Output:** Returns both the processed image and a help/documentation link.
 
 ### 💬 Prompt Machine
 
@@ -70,6 +70,18 @@ It includes:
 - **Global Mode:** Optional setting to enable autocompletion on ALL text widgets in ComfyUI.
 - **Custom Data:** Add your own `.csv` or `.json` files to the `prompt` folder to extend the library.
 
+### 🌌 Latent Machine
+
+- **Advanced Noise Generation:** Create empty latents initialized with specific noise patterns instead of standard Gaussian noise.
+- **Noise Types:**
+    - **Gaussian (White):** Standard noise, good for sharp details.
+    - **Pink (1/f):** Balanced noise, great for photorealism and nature.
+    - **Brown (1/f²):** Smoother noise, ideal for backgrounds and anime.
+    - **Perlin:** Cloud-like structure, perfect for landscapes and fluids.
+    - **Plasma:** Very smooth, abstract blobs for sci-fi and alien terrains.
+- **Model Support:** Select between **4-channel** (SD1.5, SDXL, etc.) and **16-channel** (Flux, SD3) latents.
+- **Reproducibility:** Full seed support for consistent noise generation.
+
 
 ## 📦 Installation
 

__init__.py

@@ -6,6 +6,7 @@ from .nodes.resolution_machine import Resolution_Machine
 from .nodes.save_image_metadata import ImageSaveWithMetadata
 from .nodes.upscale_machine import Upscale_Machine
 from .nodes.prompt_autocomplete import PromptAutocomplete
+from .nodes.latent_machine import Latent_Machine
 
 # A dictionary that maps class names to class objects
 NODE_CLASS_MAPPINGS = {
@@ -14,6 +15,7 @@ NODE_CLASS_MAPPINGS = {
     "ImageSaveWithMetadata": ImageSaveWithMetadata,
     "Upscale_Machine": Upscale_Machine,
     "PromptAutocomplete": PromptAutocomplete,
+    "Latent_Machine": Latent_Machine,
 }
 
 # A dictionary that maps display names to class names
@@ -23,6 +25,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "Save Image w/Metadata": "ImageSaveWithMetadata",
     "Upscale Machine": "Upscale_Machine",
     "Prompt Autocomplete": "PromptAutocomplete",
+    "Latent Machine": "Latent_Machine",
 }
 
 # A dictionary that contains web directory information

js/prompt_autocomplete.js

@@ -3,7 +3,7 @@ import { app } from "../../../scripts/app.js";
 // Register extension
 app.registerExtension({
     name: "SATA_UtilityNode.PromptAutocomplete",
-    
+
     async setup() {
         // Add settings
         app.ui.settings.addSetting({
@@ -59,7 +59,7 @@ app.registerExtension({
                 const contentData = await contentResp.json();
                 this.snippetsCache[file] = contentData.items || [];
             }
-            console.log("[PromptAutocomplete] Loaded snippets:", Object.keys(this.snippetsCache));
+
         } catch (err) {
             console.error("[PromptAutocomplete] Failed to load snippets:", err);
         }
@@ -77,12 +77,12 @@ app.registerExtension({
         // Hook into the input element creation/usage
         // NOTE: ComfyUI's customtext widget often creates a textarea. 
         // We can try to find the textarea in the DOM if it's active, or hook the input callback.
-        
+
         // A more robust way for ComfyUI widgets:
         // The widget has an `inputEl` property if it's a DOM widget.
-        
+
         // Let's try to hook the `inputEl` if it exists, or wait for it.
-        
+
         // Helper to setup the listener
         function setupListener(input) {
             if (input.dataset.hasAutocomplete) return;
@@ -99,7 +99,7 @@ app.registerExtension({
             // If not, it might be created later. We can hook `onInput` or similar, 
             // but `inputEl` is usually created when the node is drawn or added.
             // Let's poll or hook draw? Hooking draw is safer to catch it.
-             widget.draw = function(ctx, node, widgetWidth, y, widgetHeight) {
+            widget.draw = function (ctx, node, widgetWidth, y, widgetHeight) {
                 const result = originalDraw?.apply(this, arguments);
                 if (this.inputEl) {
                     setupListener(this.inputEl);
@@ -110,7 +110,7 @@ app.registerExtension({
     },
 
     // --- Autocomplete Logic ---
-    
+
     popup: null,
     active: false,
     currentCategory: null, // null = showing categories, string = showing items
@@ -127,7 +127,7 @@ app.registerExtension({
 
         // Simple check: is the character before cursor the trigger?
         // Or are we in a "trigger session"?
-        
+
         // If we just typed the trigger
         if (e.data === trigger) {
             this.showPopup(input, cursor);
@@ -144,11 +144,11 @@ app.registerExtension({
             }
 
             const query = val.substring(lastTriggerIndex + 1, cursor);
-            
+
             // Check if we have a category selected (format: #category:query)
             // But wait, the plan said: Select Category -> Then Items.
             // So maybe we just filter categories first.
-            
+
             if (this.currentCategory) {
                 // We are inside a category
                 // Check if the query contains the category prefix? 
@@ -161,17 +161,17 @@ app.registerExtension({
                 // But how do we represent that in text? 
                 // Maybe we don't change text, just internal state?
                 // Standard way: #category:item
-                
+
                 // Let's parse the text to see where we are.
                 // If text is "#cat", we filter categories.
                 // If text is "#cat:ite", we filter items in "cat".
-                
+
                 const parts = query.split(":");
                 if (parts.length > 1) {
                     // We have a category selected
                     const catName = parts[0];
                     const itemQuery = parts.slice(1).join(":"); // rest is item query
-                    
+
                     // Check if catName is valid
                     if (this.snippetsCache[catName + ".csv"] || this.snippetsCache[catName + ".json"] || this.snippetsCache[catName]) {
                         // It's a valid category (roughly). 
@@ -184,7 +184,7 @@ app.registerExtension({
                         }
                     }
                 }
-                
+
                 // If no colon, or invalid category, we are filtering categories
                 this.currentCategory = null;
                 this.updateCategories(query);
@@ -192,17 +192,17 @@ app.registerExtension({
             } else {
                 // No category selected yet
                 // Check for colon
-                 const parts = query.split(":");
-                 if (parts.length > 1) {
-                     // Maybe user typed "style:" manually?
-                     const catName = parts[0];
-                     let key = Object.keys(this.snippetsCache).find(k => k.replace(/\.(csv|json)$/, "") === catName);
-                     if (key) {
-                         this.currentCategory = key;
-                         this.updateItems(parts.slice(1).join(":"));
-                         return;
-                     }
-                 }
+                const parts = query.split(":");
+                if (parts.length > 1) {
+                    // Maybe user typed "style:" manually?
+                    const catName = parts[0];
+                    let key = Object.keys(this.snippetsCache).find(k => k.replace(/\.(csv|json)$/, "") === catName);
+                    if (key) {
+                        this.currentCategory = key;
+                        this.updateItems(parts.slice(1).join(":"));
+                        return;
+                    }
+                }
 
                 this.updateCategories(query);
             }
@@ -289,10 +289,10 @@ app.registerExtension({
     updateItems(query) {
         if (!this.currentCategory) return;
         const items = this.snippetsCache[this.currentCategory] || [];
-        
+
         // Filter
         let matches = items.filter(i => i.toLowerCase().includes(query.toLowerCase()));
-        
+
         // Add "Random" option at top
         this.filteredItems = [
             { type: "random", value: "RANDOM", display: "🎲 Random" },
@@ -328,7 +328,7 @@ app.registerExtension({
             if (idx === this.selectedIndex) {
                 div.style.backgroundColor = "#444";
                 div.style.color = "#fff";
-                
+
                 // Show preview if it's a long item
                 if (item.type === "item" && item.value.length > 30) {
                     this.showPreview(item.value);
@@ -341,10 +341,10 @@ app.registerExtension({
                 this.selectedIndex = idx;
                 this.selectItem(this.activeInput); // We need reference to input
             };
-            
+
             this.popup.appendChild(div);
         });
-        
+
         // Keep active input ref
         const activeElement = document.activeElement;
         if (activeElement && activeElement.tagName === "TEXTAREA") {
@@ -370,7 +370,7 @@ app.registerExtension({
             });
             document.body.appendChild(this.previewBox);
         }
-        
+
         this.previewBox.textContent = text;
         const rect = this.popup.getBoundingClientRect();
         this.previewBox.style.left = `${rect.right + 5}px`;
@@ -402,16 +402,16 @@ app.registerExtension({
             this.currentCategory = item.value;
             // Don't close popup, just update to items
             // We need to update the input value first
-            
-             // Replace everything from trigger to cursor with trigger + textToInsert
+
+            // Replace everything from trigger to cursor with trigger + textToInsert
             const before = val.substring(0, lastTriggerIndex + 1); // includes trigger
             const after = val.substring(cursor);
             input.value = before + textToInsert + after;
-            
+
             // Move cursor
             const newCursor = lastTriggerIndex + 1 + textToInsert.length;
             input.setSelectionRange(newCursor, newCursor);
-            
+
             // Trigger input event manually to update state
             this.handleInput({ data: null }, input, null);
             return;
@@ -430,13 +430,13 @@ app.registerExtension({
         // Replace
         const before = val.substring(0, lastTriggerIndex); // remove trigger
         const after = val.substring(cursor);
-        
+
         // If we are replacing a category query like #style:something, we need to find the start of #
         // Actually, if we are in item mode, the text is "#style:query".
         // We want to replace the whole "#style:query" with "textToInsert".
-        
+
         input.value = before + textToInsert + after;
-        
+
         // Move cursor
         const newCursor = before.length + textToInsert.length;
         input.setSelectionRange(newCursor, newCursor);

js/prompt_machine.js

@@ -20,7 +20,7 @@ app.registerExtension({
         node.widgets.splice(index, 1);
 
         // Add proper dropdown
-        const nameWidget = node.addWidget("combo", "name", "None", () => {}, {
+        const nameWidget = node.addWidget("combo", "name", "None", () => { }, {
             values: ["None"]
         });
 
@@ -34,7 +34,7 @@ app.registerExtension({
                 const resp = await fetch(`/sata/prompt_machine/names?csv=${encodeURIComponent(csvValue)}`);
                 const data = await resp.json();
                 namesConfig = data.names || ["None"];
-                console.log("[PromptMachineFrontend] Loaded names:", namesConfig);
+
                 refreshNames();
             } catch (err) {
                 console.error("[PromptMachineFrontend] Failed to load names:", err);
@@ -50,17 +50,52 @@ app.registerExtension({
                 nameWidget.value = available[0]; // safe fallback
             }
 
+            // Force update previews for the new name
+            updatePreviews(nameWidget.value);
+
             app.graph.change();
         }
 
         // Hook CSV change
         const oldCsvCallback = csvWidget.callback;
-        csvWidget.callback = function(value) {
+        csvWidget.callback = function (value) {
             if (oldCsvCallback) oldCsvCallback(value);
             loadNames(value); // refresh dynamically
         };
 
+        // --- Preview Logic ---
+        const posPreview = node.widgets.find(w => w.name === "positive_preview");
+        const negPreview = node.widgets.find(w => w.name === "negative_preview");
+        const notePreview = node.widgets.find(w => w.name === "note_preview");
+
+        async function updatePreviews(name) {
+            const csv = csvWidget.value;
+            if (!csv || !name || name === "None") return;
+
+            try {
+                const resp = await fetch(`/sata/prompt_machine/get?csv=${encodeURIComponent(csv)}&name=${encodeURIComponent(name)}`);
+                const data = await resp.json();
+
+                if (posPreview) posPreview.value = data.positive || "";
+                if (negPreview) negPreview.value = data.negative || "";
+                if (notePreview) notePreview.value = data.note || "";
+
+                app.graph.change();
+            } catch (err) {
+                console.error("[PromptMachineFrontend] Failed to load preview:", err);
+            }
+        }
+
+        // Hook Name change
+        const oldNameCallback = nameWidget.callback;
+        nameWidget.callback = function (value) {
+            if (oldNameCallback) oldNameCallback(value);
+            updatePreviews(value);
+        };
+
         // Initial sync
-        loadNames(csvWidget.value);
+        loadNames(csvWidget.value).then(() => {
+            updatePreviews(nameWidget.value);
+        });
     }
 });

js/resolution_machine.js

@@ -25,7 +25,7 @@ app.registerExtension({
             try {
                 const resp = await fetch("/SATA_UtilityNode/resolutions_config");
                 resolutionsConfig = await resp.json();
-                console.log("[Resolution_Machine] Loaded config:", resolutionsConfig);
+
             } catch (err) {
                 console.error("[Resolution_Machine] Failed to load config:", err);
             }
@@ -46,7 +46,7 @@ app.registerExtension({
                 resolutionWidget.value = available[0];
             }
 
-            console.log(`[Resolution_Machine] Resolutions for ${selectedModel}:`, available);
+
             app.graph.change();
             applyResolution(); // auto-apply width/height on refresh
         }
@@ -77,21 +77,70 @@ app.registerExtension({
             app.graph.change();
         }
 
+        // --- Preview Logic ---
+        const previewWidget = node.widgets.find(w => w.name === "dimension_preview");
+
+        function updatePreview() {
+            if (!previewWidget) return;
+            const w = widthWidget.value;
+            const h = heightWidget.value;
+            previewWidget.value = `${w} x ${h}`;
+        }
+
         // --- Hook model change ---
         const oldModelCallback = modelWidget.callback;
-        modelWidget.callback = function(value) {
+        modelWidget.callback = function (value) {
             if (oldModelCallback) oldModelCallback(value);
             refreshResolutions(value);
         };
 
         // --- Hook resolution change ---
         const oldResolutionCallback = resolutionWidget.callback;
-        resolutionWidget.callback = function(value) {
+        resolutionWidget.callback = function (value) {
             if (oldResolutionCallback) oldResolutionCallback(value);
             applyResolution();
         };
 
+        // Hook width/height changes for preview
+        const oldWidthCallback = widthWidget.callback;
+        widthWidget.callback = function (value) {
+            if (oldWidthCallback) oldWidthCallback(value);
+            updatePreview();
+        };
+        const oldHeightCallback = heightWidget.callback;
+        heightWidget.callback = function (value) {
+            if (oldHeightCallback) oldHeightCallback(value);
+            updatePreview();
+        };
+
+        // --- Add Swap Button ---
+        node.addWidget("button", "Swap Dimensions", null, () => {
+            const w = widthWidget.value;
+            const h = heightWidget.value;
+
+            // Swap values
+            widthWidget.value = h;
+            heightWidget.value = w;
+
+            // Force "Custom (manual)" to prevent preset overwrite
+            if (resolutionWidget.value !== "Custom (manual)") {
+                // Check if "Custom (manual)" exists in options
+                if (!resolutionWidget.options.values.includes("Custom (manual)")) {
+                    resolutionWidget.options.values.push("Custom (manual)");
+                }
+                resolutionWidget.value = "Custom (manual)";
+
+                // Unlock widgets since we are now in custom mode
+                widthWidget.disabled = false;
+                heightWidget.disabled = false;
+            }
+
+            updatePreview();
+            app.graph.change();
+        });
+
         // --- Initial sync ---
         refreshResolutions(modelWidget.value);
+        updatePreview();
     }
 });

nodes/latent_machine.py

@@ -0,0 +1,148 @@
+import torch
+import torch.fft
+import random
+
+class Latent_Machine:
+    """
+    Creates an empty latent initialized with Power-Law (1/f) noise, Perlin-like noise, or Plasma noise.
+    Supports 4-channel (SD1.5/SDXL) and 16-channel (Flux/SD3) latents.
+    """
+    
+    def __init__(self):
+        self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "width": ("INT", {"default": 512, "min": 64, "max": 8192, "step": 8}),
+                "height": ("INT", {"default": 512, "min": 64, "max": 8192, "step": 8}),
+                "batch_size": ("INT", {"default": 1, "min": 1, "max": 64}),
+                "model_type": ([
+                    "SD1.5/SDXL/PicsArt/Kolors/Auraflow (4ch)",
+                    "Flux/Qwen/SD3/Lumina (16ch)"
+                ],),
+                "noise_type": ([
+                    "Gaussian (White): Sharp Architecture, Text, intricate mechanics",
+                    "Pink (1/f): Photorealism, Portraits, Nature",
+                    "Brown (1/f²): Anime, Digital Art, Bokeh/Backgrounds",
+                    "Perlin : Fantasy landscapes, Fluids, Hair/Fabric",
+                    "Plasma : Sci-Fi, Abstract, Alien terrain"
+                ],),
+                "intensity": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.1}),
+                "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
+            }
+        }
+
+    RETURN_TYPES = ("LATENT",)
+    FUNCTION = "generate_noise"
+    CATEGORY = "SATA_UtilityNode"
+
+    def generate_noise(self, width, height, batch_size, model_type, noise_type, intensity, seed):
+        # Set seed for reproducibility
+        torch.manual_seed(seed)
+        random.seed(seed)
+        
+        # Determine channels based on model type
+        if "16ch" in model_type:
+            c = 16
+        else:
+            c = 4
+            
+        # Latent dimensions (compressed by 8)
+        h = height // 8
+        w = width // 8
+        
+        # Generate base noise
+        if "Gaussian" in noise_type:
+            noise = torch.randn((batch_size, c, h, w), device=self.device)
+            
+        elif "Perlin" in noise_type:
+            # Multi-Octave Value Noise Approximation
+            noise = self.generate_perlin_approx(batch_size, c, h, w)
+            
+        else:
+            # FFT-based Power Law Noise (Pink, Brown, Plasma)
+            if "Pink" in noise_type:
+                alpha = 1.0
+            elif "Brown" in noise_type:
+                alpha = 2.0
+            elif "Plasma" in noise_type:
+                alpha = 3.0 # Very smooth
+            else:
+                alpha = 0.0 # Fallback to white
+                
+            noise = self.generate_power_law_noise(batch_size, c, h, w, alpha)
+
+        # Normalize standard deviation to match expected latent variance (approx 1.0 for standard Gaussian)
+        # This ensures intensity works consistently across different noise types
+        current_std = noise.std()
+        if current_std > 1e-6:
+            noise = noise / current_std
+            
+        # Apply intensity
+        noise = noise * intensity
+
+        return ({"samples": noise},)
+
+    def generate_power_law_noise(self, batch_size, c, h, w, alpha):
+        # Generate White Noise (Standard Gaussian)
+        white_noise = torch.randn((batch_size, c, h, w), device=self.device)
+        
+        # Convert to Frequency Domain (FFT)
+        fft_noise = torch.fft.fft2(white_noise)
+        
+        # Create Frequency Grid
+        y = torch.fft.fftfreq(h, device=self.device)
+        x = torch.fft.fftfreq(w, device=self.device)
+        dy, dx = torch.meshgrid(y, x, indexing='ij')
+        
+        # Calculate distance from center (frequency magnitude)
+        # Add epsilon to avoid division by zero at DC component
+        frequency_magnitude = torch.sqrt(dy**2 + dx**2) + 1e-8
+        
+        # Apply Power Law Scaling: Amplitude ~ 1 / f^(alpha/2)
+        scale = 1.0 / (frequency_magnitude ** (alpha / 2.0))
+        
+        # Zero out the DC component (mean brightness) to keep it neutral
+        scale[0, 0] = 0 
+        
+        fft_structured = fft_noise * scale
+        
+        # Convert back to Spatial Domain (Inverse FFT)
+        structured_noise = torch.fft.ifft2(fft_structured).real
+        
+        return structured_noise
+
+    def generate_perlin_approx(self, batch_size, c, h, w):
+        """
+        Generates a Perlin-like noise by blending upsampled noise from multiple octaves.
+        This is faster than calculating actual Perlin noise per pixel on the CPU/GPU.
+        """
+        noise = torch.zeros((batch_size, c, h, w), device=self.device)
+        
+        # Octaves: scale down, generate noise, scale up
+        octaves = [2, 4, 8, 16]
+        weights = [0.5, 0.25, 0.125, 0.0625] # 1/f amplitude falloff
+        
+        total_weight = 0
+        
+        for scale, weight in zip(octaves, weights):
+            # Calculate small dimensions
+            sh, sw = max(1, h // scale), max(1, w // scale)
+            
+            # Generate random noise at this scale
+            small_noise = torch.randn((batch_size, c, sh, sw), device=self.device)
+            
+            # Upsample to full size using bicubic interpolation for smoothness
+            upsampled = torch.nn.functional.interpolate(
+                small_noise, size=(h, w), mode='bicubic', align_corners=False
+            )
+            
+            noise += upsampled * weight
+            total_weight += weight
+            
+        # Add a bit of fine-grained white noise for texture
+        noise += torch.randn((batch_size, c, h, w), device=self.device) * 0.05
+        
+        return noise

nodes/prompt_machine.py

@@ -107,6 +107,11 @@ class Prompt_Machine:
                 }),
                 # make 'name' a free text field (STRING) — avoids list validation problems
                 "name": ("STRING", {"default": default_name}),
+            },
+            "optional": {
+                 "positive_preview": ("STRING", {"multiline": True, "forceInput": False, "default": ""}),
+                 "negative_preview": ("STRING", {"multiline": True, "forceInput": False, "default": ""}),
+                 "note_preview": ("STRING", {"multiline": True, "forceInput": False, "default": ""}),
             }
         }
 
@@ -115,10 +120,10 @@ class Prompt_Machine:
     FUNCTION = "get_prompts"
     CATEGORY = "SATA_UtilityNode"
 
-    def get_prompts(self, csv_file, name):
-        print(f"[PromptMachine] get_prompts - csv_file={csv_file}, name={name}")
+    def get_prompts(self, csv_file, name, positive_preview=None, negative_preview=None, note_preview=None):
+
         pos, neg, note = read_prompt_row(csv_file, name)
-        print(f"[PromptMachine] get_prompts -> pos_len={len(pos)}, neg_len={len(neg)}, note_len={len(note)}")
+
         return (pos, neg, note)
 
 

nodes/resolution_machine.py

@@ -40,6 +40,9 @@ class Resolution_Machine:
                 "resolution": (resolutions, {"default": default_resolution}),
                 "custom_width": ("INT", {"default": 512, "min": 1, "max": 8192}),
                 "custom_height": ("INT", {"default": 512, "min": 1, "max": 8192}),
+            },
+            "optional": {
+                "dimension_preview": ("STRING", {"multiline": False, "forceInput": False, "default": ""}),
             }
         }
 
@@ -48,7 +51,7 @@ class Resolution_Machine:
     FUNCTION = "get_resolution"
     CATEGORY = "SATA_UtilityNode"
 
-    def get_resolution(self, model, resolution, custom_width, custom_height):
+    def get_resolution(self, model, resolution, custom_width, custom_height, dimension_preview=None):
         config = load_config()
 
         if model not in config:
@@ -67,7 +70,7 @@ class Resolution_Machine:
             entry = resolutions[resolution]
             width, height = entry["width"], entry["height"]
 
-        print(f"[{NODE_NAME}] Model={model}, Resolution={resolution}, Output=({width}, {height})")
+
         return (width, height)
 
 

pyproject.toml

@@ -1,7 +1,43 @@
 [project]
+name = "sata_utilitynode"
+description = "A collection of utility nodes including image upscale,touchpad support and CSV-driven prompt machine for ComfyUI."
+version = "1.0.0"
+license = {file = "LICENSE"} 
+# classifiers = [
+#     # For OS-independent nodes (works on all operating systems)
+#     "Operating System :: OS Independent",
+#
+#     # OR for OS-specific nodes, specify the supported systems:
+#     "Operating System :: Microsoft :: Windows",  # Windows specific
+#     "Operating System :: POSIX :: Linux",  # Linux specific
+#     "Operating System :: MacOS",  # macOS specific
+#
+#     # GPU Accelerator support. Pick the ones that are supported by your extension.
+#     "Environment :: GPU :: NVIDIA CUDA",    # NVIDIA CUDA support
+#     "Environment :: GPU :: AMD ROCm",       # AMD ROCm support
+#     "Environment :: GPU :: Intel Arc",      # Intel Arc support
+#     "Environment :: NPU :: Huawei Ascend",  # Huawei Ascend support
+#     "Environment :: GPU :: Apple Metal",    # Apple Metal support
+# ]
+
+dependencies = ["opencv-python>=4.5.0", "spandrel", "nvidia-tensorrt>=8.0", "onnx>=1.12.0", "onnxruntime-gpu>=1.12.0"]
+
+[project.urls]
+Repository = "https://github.com/SatadalAI/SATA_UtilityNode"
+#  Used by Comfy Registry https://registry.comfy.org
+Documentation = "https://github.com/SatadalAI/SATA_UtilityNode/wiki"
+"Bug Tracker" = "https://github.com/SatadalAI/SATA_UtilityNode/issues"
+
+[tool.comfy]
+PublisherId = ""
+DisplayName = "SATA_UtilityNode"
+Icon = ""
+includes = [] 
+# "requires-comfyui" = ">=1.0.0"  # ComfyUI version compatibility
+
 name = "comfyui_sata_utilitynode"
 description = "ComfyUI utility nodes collection providing features like prompt machine, resolution machine, and upscale machine to enhance workflow efficiency."
-version = "1.2.0"
+version = "1.5.0"
 license = "MIT"
 
 [project.urls]
@@ -11,4 +47,4 @@ Repository = "https://github.com/SatadalAI/SATA_UtilityNode"
 [tool.comfy]
 PublisherId = "SatadalAI"
 DisplayName = "SATA_UtilityNode"
-Icon = ""
+Icon = ""

requirements.txt

@@ -1,5 +1,3 @@
 opencv-python>=4.5.0
 spandrel
-nvidia-tensorrt>=8.0
-onnx>=1.12.0
-onnxruntime-gpu>=1.12.0
+piexif