# ComfyUI-TOO-Pack 🎨

**Tetsuoo's custom nodes pack for ComfyUI** A collection of utility nodes designed to enhance your ComfyUI workflow with smart image loading, metadata management, widget extraction, Krita integration and more. **Category:** `TOO-Pack` --- ## 📦 Installation ```bash cd ComfyUI/custom_nodes git clone https://github.com/tetsuoo-online/Comfyui-TOO-Pack ``` ### Requirements - **ComfyUI** (latest version recommended) - **Python** 3.8+ - **PyTorch** - **Pillow** (PIL) - **NumPy** --- ## 🎯 Nodes Overview | Node | Category | Description | |------|----------|-------------| | [Simple Image Loader](#simple-image-loader-) | `TOO-Pack/image` | Simple image loader with a dynamic preview, no need to start the workflow :) | | [Smart Image Loader](#smart-image-loader-) | `TOO-Pack/image` | Flexible image loader with multiple sources | | [Smart Image Saver](#smart-image-saver-) | `TOO-Pack/image` | Intelligent saver with flexible naming and metadata | | [Smart Image Saver (Advanced)](#smart-image-saver-advanced-) | `TOO-Pack/image` | Advanced saver with dynamic naming and A1111/Civitai metadata | | [TOO Crop Image](#too-crop-image-) | `TOO-Pack/image` | Interactive cropping tool | | [TOO Lora Grid](#too-lora-grid-) | `TOO-Pack/image` | Special KSampler for making LoRA grids | | [TOO Lora Grid Advanced](#too-lora-grid-advanced-) | `TOO-Pack/image` | Advanced KSampler for making LoRA grids - Adapted from SamplerCustomAdvanced node | | [TOO Image Grid From Batch with Alpha](#too-image-grid-from-batch) | `TOO-Pack/image` | Grid from batch that preserves the alpha channel | | [TOO lmage Metadata](#too-image-metadata-) | `TOO-Pack/image` | Metadata editing | | [Krita Bridge](#krita-bridge-) | `TOO-Pack/image` | Auto-load images from Krita | | [Extract Widget From Node](#extract-widget-from-node-) | `TOO-Pack/utils` | Extract widget values from workflow nodes | | [Collection Categorizer](#collection-categorizer-llm-) | `TOO-Pack/utils` | Categorize files with local LLM (Ollama) | | [Time Converter](#time-converter-) | `TOO-Pack/utils` | Quick tool for converting seconds/min/hours | --- ## 📚 Node Documentation ### Simple Image Loader 🖼

Click to expand full documentation

An image loader that show instant preview with any path. You're no longer limited to ComfyUI/input folder.
The idea was inspired by the Load Image (Path) node from [comfyui-VideoHelperSuite](https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite), with a few more features.

#### Features - 🖼️ **Image input via path** img_path will work with any path on your computer, it doesn't have to be in ComfyUI folders - 🖼️ **Image Preview** Instant preview, no need to start the workflow. Can be toggled on/off - 📊 **A1111/Civitai** metadata extraction - 🔄 **ComfyUI** workflow extraction - **Returns file path** of loaded image #### Parameters **Required Parameters** | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | **img_path** | STRING | Direct path to an image file | - | **Outputs** | Parameter | Type | Description | |-----------|------|-------------| | **IMAGE** | IMAGE | The loaded image (from image input or widgets) | | **FILE_PATH** | STRING | Path of loaded file | | **metadata** | METADATA | A1111/Civitai metadata extracted from file | | **workflow** | WORKFLOW | ComfyUI workflow extracted from file |

--- ### Smart Image Loader 🖼

Click to expand full documentation

A flexible image loader that supports multiple input sources with metadata extraction. #### Features - **Multiple sources**: txt, direct path, directory, or direct image - **Smart priority order** with configurable inputs - **Random selection** with reproducible seed - **Multiple formats** supported (PNG, JPG, JPEG, BMP, WEBP, TIFF) - 🖼️ **Image Preview** - 📊 **A1111/Civitai** metadata extraction - 🔄 **ComfyUI** workflow extraction - **Returns file path** of loaded image #### Parameters **Required Parameters** | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | **seed** | INT | Seed for reproducible random selection | `0` | | **img_dir_level** | INT | Subdirectory depth: -1=all, 0=current, 1-10=levels | `0` | | **show_preview** | BOOLEAN | Show image preview in the node | `True` | **Optional Parameters** | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | **txt_path** | STRING | Path to text file containing image paths | - | | **img_path** | STRING | Direct path to an image file | - | | **img_directory** | STRING | Path to directory containing images | - | | **image** | IMAGE | Direct image input (priority for IMAGE output) | - | **Outputs** | Parameter | Type | Description | |-----------|------|-------------| | **IMAGE** | IMAGE | The loaded image (from image input or widgets) | | **FILE_PATH** | STRING | Path of loaded file | | **metadata** | METADATA | A1111/Civitai metadata extracted from file | | **workflow** | WORKFLOW | ComfyUI workflow extracted from file | #### Priority Order The node loads images in this order (from highest to lowest priority): 1. **image** ⚡ : Uses the provided image input (for passing images only - does not load metadata or workflow) 2. **txt_path** 📄 : Randomly selects a path from text file 3. **img_path** 🖼 : Loads the specific image file 4. **img_directory** 📁 : Randomly selects an image from directory #### Usage Examples **Case 1: Text file with image list** ```python # Content of image_list.txt: # /path/to/image1.png # /path/to/image2.jpg # /path/to/image3.webp txt_path = "/path/to/image_list.txt" seed = 42 # Reproducible ``` **Case 2: Direct path to image** ```python img_path = "/path/to/specific/image.png" ``` **Case 3: Image directory** ```python img_directory = "/path/to/images/" seed = 123 ``` **Case 4: Combination with priority** ```python txt_path = "/path/to/list.txt" # Priority 1 img_path = "/path/to/fallback.png" # Priority 2 (if txt_path fails) img_directory = "/path/to/backup/" # Priority 3 (if img_path fails) ``` #### Technical Details **Text file format (txt_path)** The text file should contain one image path per line: ``` /home/user/images/photo1.png /home/user/images/photo2.jpg /home/user/images/photo3.webp ``` - Empty lines are ignored - UTF-8 encoding supported - A random path is selected using the seed **Seed handling** - **seed = 0**: Different random selection each run - **seed > 0**: Identical selection with same parameters (reproducible) **FILE_PATH values** | Value | Description | |-------|-------------| | Full path | Image loaded from txt_path, img_path or img_directory | | `"external_input"` | Image provided via image parameter | | `"none"` | No valid source found (error) |

--- ### Smart Image Saver 💾

Click to expand full documentation

An intelligent image saver that replaces the SAVE_IMG subgraph with flexible filename customization.

#### Features - **Flexible naming**: Customizable prefix, suffix, and separator - **Date tokens**: YYYY, MM, DD, HH, mm, ss, timestamp support - **Smart metadata extraction**: Auto-extract seed and model name from workflow - **Node targeting**: Target nodes by class name or direct ID (#10) - **Multiple formats**: WEBP (lossy/lossless), PNG, JPG/JPEG - **Metadata preservation**: Saves prompt and workflow in EXIF/PNG info #### Parameters **Required Parameters** | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | **images** | IMAGE | Images to save | - | | **output_folder** | STRING | Output folder (supports date tokens) | `YYYY-MM-DD` | | **prefix** | STRING | Filename prefix (supports date tokens) | `ComfyUI_YYYY-MM-DD_HHmmss` | | **seed_node_name** | STRING | Node containing seed (class name or #ID) | `KSampler` | | **model_node_name** | STRING | Node containing model (class name or #ID) | `CheckpointLoaderSimple` | | **suffix** | STRING | Filename suffix (supports date tokens) | `""` | | **output_format** | COMBO | Image format | `webp` | | **quality** | INT | Compression quality (1-100) | `97` | **Outputs** | Parameter | Type | Description | |-----------|------|-------------| | **images** | IMAGE | Pass-through of input images | | **filepath** | STRING | Path of the first saved file | #### Filename Structure The node builds filenames in this order: ``` [prefix]_[seed]_[model_name]_[suffix].[format] ``` Elements are joined by the separator. Empty elements are skipped. #### Usage Examples **Case 1: Basic usage with date folder** ```python output_folder = "YYYY-MM-DD" # → 2024-01-30/ prefix = "render_YYYYMMDD" # → render_20240130 seed_node_name = "KSampler" model_node_name = "CheckpointLoaderSimple" ``` **Output:** `2024-01-30/render_20240130_123456_mymodel.webp` **Case 2: Target node by ID** ```python seed_node_name = "#10" # Target node with ID 10 model_node_name = "#5" # Target node with ID 5 ``` **Case 3: Disable seed or model** ```python seed_node_name = "" # Don't include seed model_node_name = "" # Don't include model prefix = "my_render" suffix = "HHmmss" # Add timestamp ``` **Output:** `my_render_143025.webp` #### Date Tokens All date tokens are replaced with current date/time values: | Token | Description | Example | |-------|-------------|---------| | `YYYY` | Year (4 digits) | 2024 | | `MM` | Month (2 digits) | 01 | | `DD` | Day (2 digits) | 30 | | `HH` | Hour 24h (2 digits) | 14 | | `mm` | Minutes (2 digits) | 30 | | `ss` | Seconds (2 digits) | 25 | | `timestamp` | Unix timestamp | 1706626225 | #### Node Targeting **By class name:** ```python seed_node_name = "KSampler" model_node_name = "CheckpointLoaderSimple" ``` **By ID:** ```python seed_node_name = "#10" # Targets node with ID 10 ```

--- ### Smart Image Saver (Advanced) 💾

Click to expand full documentation

Node for saving images with advanced file naming and A1111/Civitai Auto V3 compatible metadata. **Category:** TOO-Pack/image #### Features - Dynamic file naming with workflow extraction - Metadata injection/editing - Support for 3 universal inputs (`any1`, `any2`, `any3`) - Automatic model and LoRA extraction with hash calculation - Targeted text replacement - Customizable date formatting - A1111/Civitai compatible metadata - Output formats: PNG, JPG, WebP #### Inputs | Parameter | Type | Description | |-----------|------|-------------| | `images` | IMAGE | Images to save (required) | | `metadata` | METADATA | Optional metadata | | `workflow` | WORKFLOW | Workflow to embed | | `any1` | * | Universal input 1 | | `any2` | * | Universal input 2 | | `any3` | * | Universal input 3 | #### Outputs | Output | Type | Description | |--------|------|-------------| | `images` | IMAGE | Images passthrough | | `filepath` | STRING | Saved file path | #### Configuration (JS Interface) ##### DATA Create custom data fields for metadata and naming. **Value formats:** - **Static text:** `"my_text"` - **Widget extraction:** `#123:widget_name` (node ID) or `ClassName:widget_name` - **Any input:** `[any1]`, `[any2]`, `[any3]` **Example:** ``` name: positive value: #45:text name: model_used value: [any1] ``` ##### DATE FORMAT Format dates for naming. - **date1:** Date format (e.g. `YYYY-MM-DD`) - **date2:** Time format (e.g. `HHmmss`) - **date3:** Custom format **Available tokens:** `YYYY`, `YY`, `MM`, `DD`, `HH`, `mm`, `ss`, `timestamp` ##### MODEL Automatic model extraction. **Value:** `#123:ckpt_name` or `[any1]` The node automatically calculates: - Model name (basename without extension) - Model hash (first 10 characters of SHA256) ##### LORAS Automatic LoRA extraction with Civitai-compatible hash. **Add multiple loras:** - Lora 1: `#45:lora_name` or `[any1]` - Lora 2: `#67:lora_name` or `[any2]` **Multiline support:** If `[any1]` contains: ``` lora1.safetensors lora2.safetensors ``` → Both are parsed automatically ##### TEXT REPLACE Replace text in fields before naming. **Target:** - Empty or `[any1]`/`[any2]`/`[any3]` → Apply to all fields - `positive` → Apply only to "positive" field - `model` → Apply only to model **Example:** ``` target: positive in: (masterpiece) out: ``` → Removes "(masterpiece)" from positive prompt ##### NAMING Build filename with available elements. **Available fields:** - `output_folder` : Output subfolder - `prefix` : File prefix - `extra1`, `extra2`, `extra3` : Additional fields - `model` : Model name - `suffix` : File suffix - `separator` : Separator character (default: `_`) **Available sources:** - Empty (ignored) - `[any1]`, `[any2]`, `[any3]` : Universal inputs - Data field name: `positive`, `seed`, `steps`, etc. - `model`, `loras` : Extracted values - `%date1`, `%date2`, `%date3` : Formatted dates **Naming example:** ``` prefix: %date1 extra1: positive model: model suffix: seed separator: _ ``` → `2025-02-12_beautiful_landscape_MyModel_12345.webp` ##### OUTPUT Output configuration. - **format:** `png`, `jpg`, `webp` - **quality:** 1-100 (for jpg/webp) - **save metadata:** Include A1111 metadata - **embed workflow:** Embed ComfyUI workflow (except JPG) #### Usage Examples ##### Example 1: Naming with model and seed **Configuration:** ``` DATA: - name: seed, value: #10:seed MODEL: - extract: KSampler:ckpt_name NAMING: - prefix: %date1 - model: model - suffix: seed - separator: _ ``` **Result:** `2025-02-12_MyCheckpoint_8675309.webp` ##### Example 2: LoRA extraction from any1 **Workflow:** ``` ExtractWidgetFromNode → any1 (TOO Smart Image Saver) ``` **Configuration:** ``` LORAS: - lora 1: [any1] NAMING: - prefix: %date1 - extra1: loras ``` **If any1 contains:** ``` style_lora_v2.safetensors quality_lora_v1.safetensors ``` **Generated metadata:** ``` Lora hashes: "style_lora_v2: a1b2c3d4e5f6, quality_lora_v1: f6e5d4c3b2a1" ``` ##### Example 3: Prompt cleanup with Text Replace **Configuration:** ``` TEXT REPLACE: - target: positive - in: (masterpiece, best quality) - out: NAMING: - prefix: positive ``` **If positive = "beautiful landscape, (masterpiece, best quality)"** **→ Filename:** `beautiful_landscape.webp` #### Practical Use Cases ##### 1. Multi-LoRA Workflow Use `ExtractWidgetFromNode` to retrieve all used LoRAs → connect to `any1` → The node automatically calculates all hashes for Civitai compatibility. ##### 2. Organization by Model Configure `output_folder: model` to automatically sort images by model used. ##### 3. Complete Metadata Create data fields for all important parameters (seed, steps, cfg, sampler, scheduler) → The node generates complete A1111 metadata readable by Civitai and Automatic1111. ##### 4. Smart Naming Use `any` inputs to inject dynamic information from other nodes (tags, descriptions, scores, etc.). #### Tips - **Data fields** are flexible: create as many fields as needed - **[any1]**, **[any2]**, **[any3]** accept any data type (converted to string) - **Multiline** is supported for loras: one line = one lora - **LoRA hashes** exclude safetensors metadata (Civitai AutoV3 compatible) - **Text replace** applies to extracted values before filename construction - **Empty lines** in data fields are automatically ignored - The **metadata** input has priority over node data fields, unless data fields are explicitly set (enables metadata injection/editing)

--- ### Extract Widget From Node 🔧

Click to expand full documentation

Extracts specific widget values from any node in the ComfyUI workflow. #### Features - **Targeted extraction** of specific widgets by name - **Multiple widgets** supported (comma-separated) - **Multi-node support**: Targets all nodes matching class name - **Direct ID targeting** with `#ID` syntax - **Intelligent parsing** of nested structures - **"on" filter**: Ignores disabled elements #### Parameters **Required Parameters** | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | **node_name** | STRING | Node class name or `#ID` to target | - | | **widget_names** | STRING | Widget name(s) to extract (comma-separated) | - | **Outputs** | Parameter | Type | Description | |-----------|------|-------------| | **extracted_values** | STRING | Extracted values (multiline if multiple) | #### Usage Examples **Case 1: Extract a single widget** ```python node_name = "KSampler" widget_names = "seed" ``` **Output:** `"12345"` **Case 2: Extract multiple widgets** ```python node_name = "CLIPTextEncode" widget_names = "text, strength" ``` **Output:** ``` beautiful landscape, masterpiece 0.85 ``` **Case 3: Target specific node by ID** ```python node_name = "#10" widget_names = "ckpt_name" ``` **Case 4: Extract from multiple matching nodes** ```python node_name = "LoraLoader" widget_names = "lora_name" ``` **Output (if 2 LoraLoader nodes exist):** ``` style_lora.safetensors detail_lora.safetensors ``` #### Technical Details **Node Targeting** The node supports two targeting modes: 1. **By class name** (e.g., `"KSampler"`) - Finds **all nodes** of this class - Extracts from all matching nodes 2. **By ID** (e.g., `"#10"`) - Targets **specific node** with ID 10 - Only one node targeted **Widget Extraction** - **Simple values**: `"my_value"` - **Multiple values**: Separated by newlines - **Comma support**: `"widget1, widget2"` extracts both **Nested Dictionary Handling** The node intelligently handles nested dictionaries: **Simple structure:** ```json { "lora_name": "my_lora.safetensors", "strength_model": 0.85 } ``` **Nested structure (Power Lora Loader):** ```json { "loras": { "on": true, "lora_name": "my_lora.safetensors", "strength_model": 0.85 } } ``` The node automatically extracts values from both structures. **"on" filter** If a dictionary contains `"on": false`, its values are **ignored**. #### Advanced Use Cases **1. Extract prompts from workflow** ```python node_name = "CLIPTextEncode" widget_names = "text" ``` **2. Retrieve used seeds** ```python node_name = "KSampler" widget_names = "seed" ``` **3. List all loaded models** ```python node_name = "CheckpointLoader" widget_names = "ckpt_name" ``` **4. Extract control parameters** ```python node_name = "ControlNetLoader" widget_names = "control_net_name, strength" ```

--- ### TOO Crop Image 🖼

Click to expand full documentation

Interactive tool for cropping your image before output.

If you use the image input then the cropping will apply to it. However the interactive preview works only with img_path input so you will need to use that. You can also use only img_path like you would with a Simple Image Loader

--- ### TOO LoRA Grid 🧪

Click to expand full documentation

Modified KSampler to test loras and output an image grid.

A ComfyUI node to test multiple LoRA files and compare their effects in an image grid, with optional labels and footer text. --- ## Inputs (high-level) - model: MODEL - clip: CLIP - vae: VAE - positive: CONDITIONING - negative: CONDITIONING - latent_image: LATENT — used as the sampling starting point - loras: STRING (multiline) — one entry per line (see format below) - seed, steps, cfg (float guidance), sampler_name, scheduler, denoise - grid_cols, grid_padding — grid layout controls - add_labels (bool), label_height, font_size, label_color, bg_color - footer_text — optional footer displayed beneath grid --- ## LoRA multiline format Each non-comment line is one grid cell. Lines starting with `#` are ignored. Supported entry forms: - `path/to/lora.safetensors` Apply LoRA at default strength 1.0 (if no explicit weight). - `path/to/lora.safetensors:0.8` Apply LoRA at explicit strength (float). - `path/to/lora.safetensors:"label"` A null slot — the node will sample WITHOUT applying any LoRA but will show the custom label. Useful for control comparisons. Notes: - If extension is omitted, the node will try common extensions: `.safetensors`, `.pt`, `.ckpt`. - You may include a filename without path; the node resolves via project LoRA folders (uses `folder_paths.get_full_path("loras", ...)`). Example `loras` widget content: ``` any_lora.safetensors:"no lora" # test LoRAs my_style_lora.safetensors:0.7 other_lora:0.5 missing_lora # will be logged as not found ``` ## Grid & label rendering - Labels and footer use PIL ImageFont: - The node tries these fonts (in order): `arial.ttf`, `DejaVuSans.ttf`, `LiberationSans-Regular.ttf`. - If none load, it falls back to `ImageFont.load_default()` (Pillow's bitmap font). - Footer text is wrapped to grid width and supports multi-line content. - Colors accept hex strings (e.g., `#ffffff` for white, `#111111` for dark background). - `grid_cols` controls number of columns; rows are computed automatically. --- ## Caching - The node caches per-entry decoded tensors and labels in an in-memory `_cache` keyed by a hash of: - model/clip/vae/positive/negative object signatures, `loras` text, seed, steps, cfg, sampler/scheduler, denoise, and a short hash of the latent image bytes. - Cache avoids re-sampling identical requests; change any parameter or the latent image and a new sample will be produced. --- ## Tips - Use null slots (`:"label"`) to include a no-LoRA baseline in the grid for direct comparison. - Use `has_explicit_weight` (via `:0.8`) to show exact strength in labels. - Keep `grid_cols` reasonable for readability; increase padding or label height if text overlaps images. - If you run ComfyUI in a container, ensure fonts are installed for consistent label rendering. --- ## Limitations - One sample per LoRA entry — not intended for batch/randomized comparisons unless you feed different latents/seeds. - In-memory caching will not persist across process restarts. - The node tries to resolve LoRA paths via the project's LoRA folders; non-standard locations may not be found.

--- ### TOO Image Grid From Batch

Click to expand full documentation

Creates an image grid from a batch while preserving transparency (alpha channel).

## Parameters ### Images (required) The batch of images to arrange in a grid. Format: RGBA or RGB. ### Grid Cols (required) Number of columns in the grid. ### Grid Rows (required) Number of rows in the grid. ### Padding (required) Space in pixels between images. Min: 0 | Max: 100 | Default: 0 ## Output A single image containing the grid composed of the batch images. ## Notes - If the batch contains fewer images than the grid (rows × cols), missing cells are filled with transparency. - Transparency is fully preserved. - The batch images must have the same dimensions.

--- ### TOO Image Metadata 🖼

Click to expand full documentation

Editing tool for A1111/Civitai metadata.

Very straight forward, you will need TOO Simple Image Loader or TOO Smart Image Loader to input the metadata to modify. Any empty field will be ignored, the node will not erase any original metadata unless you specify something.
For the model field you might want to follow A1111/Civitai syntax [``Model hash: , Model: modelName``] -> Only 1 model can be input, as far as I know... Maybe something to investigate later x)
As for the loras, the syntax is [``Lora hashes: ":,:,:"``] -> As many loras as necessary

--- ### Krita Bridge 🎨

Click to expand full documentation

Automatically loads the latest image from the `input/krita/` folder for seamless Krita integration. #### Features - **Automatic loading** of latest image from krita folder - **Real-time detection** of new files - **Auto-update** during generation - **Alpha support**: extracts alpha channel as mask - **Auto-create** folder if doesn't exist - **No parameters** - works directly #### Parameters **Required Parameters** **No parameters required** - The node works automatically! **Outputs** | Parameter | Type | Description | |-----------|------|-------------| | **image** | IMAGE | The loaded image (RGB) | | **mask** | MASK | Mask extracted from alpha channel | #### Setup **Working Directory** The node automatically loads from: ``` ComfyUI/input/krita/ ``` If the folder doesn't exist, it's created automatically on first launch. **Export from Krita** 1. **Open Krita** 2. **Create or modify** your image 3. **Export as PNG**: `File > Export` 4. **Destination**: `ComfyUI/input/krita/filename.png` 5. The node automatically detects the new file **Recommended Workflow** ``` Krita → Export PNG → ComfyUI/input/krita/ → Krita Bridge → [your workflow] ``` #### Usage Examples **Case 1: Simple loading** ```python # No configuration needed # Node automatically loads latest image ``` **Case 2: Using alpha mask** ```python # Connect 'mask' to a mask node (Mask Composite, etc.) # Krita image's alpha channel becomes usable mask ``` **Case 3: Iterative Krita ↔ ComfyUI workflow** ``` 1. Draw in Krita 2. Export → input/krita/sketch.png 3. ComfyUI detects and generates 4. Get result 5. Refine in Krita 6. Re-export → Node loads new version ``` **Case 4: Inpainting with Krita mask** ```python # Workflow: # Krita Bridge (image + mask) → Inpaint Model → VAE Decode # Krita's alpha mask defines inpainting area ``` #### Technical Details **File Detection** The node: 1. Scans `input/krita/` folder for all `.png` files 2. Finds file with **most recent modification** 3. Compares timestamp with last loaded file 4. Reloads if change detected **Alpha Channel Handling** **RGBA image (with transparency):** - RGB channels → `image` output - Alpha channel → `mask` output (0-1 values) **RGB image (no transparency):** - RGB → `image` output - Uniform white mask → `mask` output **Automatic Update** The `IS_CHANGED` function returns current timestamp, forcing ComfyUI to: - Re-evaluate node on every execution - Detect new files in real-time - Update image automatically #### Krita Integration **Krita Configuration** 1. **Set default export folder** - `Settings > Configure Krita > General` - Set default folder: `ComfyUI/input/krita/` 2. **Keyboard shortcut for quick export** - `Settings > Configure Krita > Keyboard Shortcuts` - Assign key to `Export` - Example: `Ctrl+Shift+E` 3. **Export format** - Format: **PNG** - Compression: as preferred - **Important**: Enable "Save alpha channel" if using mask **Optimal Workflow** ``` ┌─────────┐ Export PNG ┌──────────────┐ │ Krita │ ───────────────> │ input/krita/ │ └─────────┘ └──────────────┘ │ ▼ ┌──────────────┐ │ Krita Bridge │ └──────────────┘ │ ┌────────────────┴────────────────┐ ▼ ▼ ┌────────┐ ┌──────┐ │ image │ │ mask │ └────────┘ └──────┘ ```

--- ### Collection Categorizer (LLM) 🗂

Click to expand full documentation

A ComfyUI node that automatically scans your folders and categorizes content with a local LLM (Ollama). #### Features - **Automatic scanning** of folders (video files, archives, documents) - **Smart categorization** via local LLM (Ollama) - **Recursive scanning** of subfolders (optional) - **Reproducible seed** for identical results - **Custom Ollama models** supported - **Auto-save** JSON output - **Compatible** with Collection Manager - **100% local** - no external APIs #### Parameters **Main Parameters** | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | **ollama_model** | COMBO | LLM model to use (or "custom") | `qwen2.5:7b` | | **custom_ollama_model** | STRING | Model name if "custom" selected | - | | **folder_path** | STRING | Path to folder to scan | - | | **scan_subfolders** | BOOLEAN | Recursively scan subfolders | `False` | | **save_json** | BOOLEAN | Auto-save JSON output | `True` | | **collection_title** | STRING | Collection title | `Ma Collection` | | **content_type** | COMBO | Content type (or "custom") | `films` | **Optional Parameters** | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | **custom_type_name** | STRING | Type name if "custom" selected | - | | **custom_categories** | STRING | Custom categorization criteria (multiline) | (empty = LLM decides) | | **seed** | INT | Seed for reproducible results | `0` (random) | **Outputs** | Parameter | Type | Description | |-----------|------|-------------| | **json_output** | STRING | The complete collection JSON | | **summary** | STRING | Categorization summary | #### Usage Examples **Case 1: Movies with automatic categories** ```python content_type = "films" custom_categories = "" # Empty # LLM decides categories (Genre, Era, etc.) ``` **Case 2: TV Series with custom criteria** ```python content_type = "series" custom_categories = "Genre, Year, Studio" # LLM categorizes by these criteria ``` **Case 3: Custom type** ```python content_type = "custom" custom_type_name = "Documentaries" custom_categories = "Theme, Duration" ``` **Case 4: Custom model** ```python ollama_model = "custom" custom_ollama_model = "mistral:7b" ``` **Case 5: Reproducible results** ```python seed = 42 # Always same result with same parameters ``` #### Installation **Requirements** 1. **Ollama** installed and running ```bash # Download: https://ollama.ai ollama --version ``` 2. **Python requests** (for local HTTP API) ```bash pip install requests --break-system-packages ``` 3. **At least one LLM model** ```bash ollama pull qwen2.5:7b ``` #### Supported File Types **Videos** `.mp4`, `.mkv`, `.avi`, `.mov`, `.wmv`, `.flv` **Archives** `.cbz`, `.cbr`, `.zip`, `.rar` **Documents** `.epub`, `.pdf`, `.mobi` **Folders** Subfolders are treated as individual items (unless `scan_subfolders` is enabled) #### Recommended Models | Model | Size | Speed | Quality | Usage | |-------|------|-------|---------|--------| | **qwen2.5:7b** | 7B | ⚡⚡⚡ | ⭐⭐⭐⭐ | Recommended | | **gemma3:12b** | 12B | ⚡⚡ | ⭐⭐⭐⭐⭐ | Best quality | | **llama3.1:8b** | 8B | ⚡⚡⚡ | ⭐⭐⭐⭐ | Very reliable | | **gemma3:4b** | 4B | ⚡⚡⚡⚡ | ⭐⭐⭐ | Fast | #### Output Format (JSON) ```json { "title": "My Collection", "icon": "🎬", "type": "Films", "filename": "films.json", "categories": [ { "id": 1, "name": "Science Fiction", "subcategories": [], "games": ["Blade Runner", "The Matrix"] }, { "id": 2, "name": "Comedy", "subcategories": [], "games": ["Superbad", "The Hangover"] } ] } ```

--- ### Time Converter 🕥

Click to expand full documentation

A Quick tool for converting seconds/min/hours.

--- ## 🗺 ToDo - Extract Widget From Node : aiming at nodes using name, title or ID --- ## 📄 License MIT License --- ## 👤 Author **Tetsuoo** --- ## 🙏 Credits - **Claude AI ❤** - AI assistant extraordinaire - **ComfyUI** - Amazing node-based interface - **Ollama** - Local LLM runtime - **Krita** - Open-source digital painting software

Name	Type	Default	Description
model	MODEL		—
clip	CLIP		—
lora_list	STRING		—
strength	FLOAT	1.00-10–10	—

Lora Queue Helper

Inputs (4)

Outputs (3)