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@@ -53,7 +53,7 @@ jobs:
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print('✓ All imports successful')
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# Test base node
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assert ComfyAssetsBaseNode.CATEGORY.startswith('ComfyAssets')
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assert 'ComfyAssets' in ComfyAssetsBaseNode.CATEGORY
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print('✓ Base node tests passed')
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# Test dimension extraction
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@@ -168,7 +168,7 @@ jobs:
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assert node.RETURN_TYPES[2] == 'INT'
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assert node.RETURN_TYPES[3] == 'FLOAT'
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assert node.RETURN_NAMES == ('sampler_name', 'scheduler', 'steps', 'cfg')
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assert node.CATEGORY == 'ComfyAssets/🌀 Samplers'
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assert node.CATEGORY == '🫶 ComfyAssets/🌀 Samplers'
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print('✓ Sampler Combo return types tests passed')
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# Test sampler combo functionality
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@@ -217,7 +217,7 @@ jobs:
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# Test return types
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assert node.RETURN_TYPES == ('INT',)
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assert node.RETURN_NAMES == ('seed',)
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assert node.CATEGORY == 'ComfyAssets/🌱 Seeds'
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assert node.CATEGORY == '🫶 ComfyAssets/🌱 Seeds'
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print('✓ Seed History return types tests passed')
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# Test seed output functionality
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@@ -333,7 +333,7 @@ jobs:
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assert res_class.RETURN_TYPES == ('INT', 'INT')
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assert res_class.RETURN_NAMES == ('width', 'height')
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assert res_class.CATEGORY.startswith('ComfyAssets/')
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assert 'ComfyAssets/' in res_class.CATEGORY
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print('✓ Resolution Calculator ComfyUI integration passed')
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# Test Width Height Selector
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@@ -354,7 +354,7 @@ jobs:
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assert wh_class.RETURN_TYPES == ('INT', 'INT')
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assert wh_class.RETURN_NAMES == ('width', 'height')
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assert wh_class.CATEGORY.startswith('ComfyAssets/')
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assert 'ComfyAssets/' in wh_class.CATEGORY
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print('✓ Width Height Selector ComfyUI integration passed')
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# Test Sampler Combo
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@@ -374,7 +374,7 @@ jobs:
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assert 'steps' in input_types['required']
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assert 'cfg' in input_types['required']
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assert sampler_class.CATEGORY.startswith('ComfyAssets/')
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assert 'ComfyAssets/' in sampler_class.CATEGORY
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print('✓ Sampler Combo ComfyUI integration passed')
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# Test Seed History
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@@ -393,7 +393,7 @@ jobs:
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assert seed_class.RETURN_TYPES == ('INT',)
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assert seed_class.RETURN_NAMES == ('seed',)
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assert seed_class.CATEGORY.startswith('ComfyAssets/')
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assert 'ComfyAssets/' in seed_class.CATEGORY
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print('✓ Seed History ComfyUI integration passed')
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print('🎉 All tools ComfyUI integration readiness tests passed!')
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@@ -8,7 +8,14 @@
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> A modular collection of essential custom ComfyUI nodes missing from the standard release.
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ComfyUI-KikoTools provides carefully crafted, production-ready nodes grouped under the **"ComfyAssets"** category. Each tool is designed with clean interfaces, comprehensive testing, and optimized performance for SDXL and FLUX workflows.
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ComfyUI-KikoTools provides carefully crafted, production-ready nodes under the "ComfyAssets" category.
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Each tool is built with clean interfaces, thorough testing, and optimized performance for SDXL and FLUX workflows.
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This project started out of frustration with keeping ComfyUI up to date and waiting for dozens of custom nodes to update—most of which I didn’t even use. After taking a hard look at my workflow, I realized I only needed one or two features from these nodes, many of which were abandoned or stuck in maintenance mode.
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I tried forking, patching, and submitting merge requests, but eventually decided to create my own curated collection of tools—fully supported and maintained by me. That’s how Kiko’s Tools was born.
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I’m sharing them here with the community, and I hope you find them as useful as I do.
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## 🚀 Features
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@@ -26,7 +33,10 @@ ComfyUI-KikoTools provides carefully crafted, production-ready nodes grouped und
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| [🤖 Gemini Prompt Engineer](#-gemini-prompt-engineer) | AI-powered image analysis and prompt generation | 🧠 Prompts |
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| [🔍 Display Any](#-display-any) | Universal debugging tool for any data type | 👁️ Display |
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| [🖼️ Image to Multiple Of](#️-image-to-multiple-of) | Adjust dimensions to multiples for compatibility | 🖼️ Resolution |
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| [🔤 Embedding Autocomplete](#-embedding-autocomplete) | Smart autocomplete for embeddings, LoRAs, and tags | ✍️ Text |
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| [📉 Image Scale Down By](#-image-scale-down-by) | Scale images down by a factor with quality preservation | 🖼️ Resolution |
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| [🎬 Film Grain](#-film-grain) | Add realistic film grain effects to images | 💾 Images |
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| [🔤 Embedding Autocomplete](#-embedding-autocomplete) | Smart autocomplete for embeddings, LoRAs, and tags | 🔧 Utils |
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| [🧹 Kiko Purge VRAM](#-kiko-purge-vram) | Intelligent VRAM management with detailed reporting | 🛠️ Utils |
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### 🧰 xyz-helpers Tools
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@@ -219,6 +229,41 @@ Adjusts image dimensions to be multiples of a specified value for model compatib
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||||

|
||||
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#### 📉 Image Scale Down By
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Efficiently scale images down by a specified factor with quality preservation.
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||||
- **Proportional Scaling**: Reduces both width and height by the same factor
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- **Quality Preservation**: Uses bilinear interpolation with antialiasing
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- **Batch Support**: Process multiple images simultaneously
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- **Memory Efficient**: Optimized for large image batches
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- **Flexible Factor**: Scale from 0.01x to 1.0x with 0.01 precision
|
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|
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**Use Cases:**
|
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- Create thumbnails or preview images
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- Reduce memory usage for large workflows
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- Generate image pyramids for multi-scale processing
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- Quick downsampling for performance optimization
|
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- Prepare images for web display or transmission
|
||||
|
||||
#### 🎬 Film Grain
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Add realistic analog film grain effects to generated images.
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|
||||
- **Realistic Grain Simulation**: Mimics actual film photography characteristics
|
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- **Grain Size Control**: Fine to coarse grain patterns (0.25x to 2.0x)
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- **Intensity Adjustment**: Variable strength from subtle to pronounced (0-10)
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- **Color Saturation**: Monochrome to full color grain (0-2)
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- **Shadow Lifting (Toe)**: Film-like shadow response curves
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- **Red Multiplier**: Adjust red channel independently for vintage looks
|
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- **Alpha Preservation**: Maintains transparency when present
|
||||
- **ITU-R BT.709 Color Space**: Professional color handling
|
||||
|
||||
**Use Cases:**
|
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- Add vintage film aesthetic to AI-generated images
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- Create cinematic looks with authentic grain patterns
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||||
- Simulate different film stocks (35mm, 16mm, etc.)
|
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- Add texture to overly smooth AI renders
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- Match grain from reference photography
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||||
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||||
#### 🎛️ Flux Sampler Params
|
||||
FLUX-optimized parameter generator with intelligent batch processing capabilities.
|
||||
|
||||
@@ -317,9 +362,9 @@ Unified interface for text encoding and sampler parameter management.
|
||||
**Intelligent autocomplete for embeddings, LoRAs, and custom tags in text prompts.**
|
||||
|
||||
<div align="center">
|
||||
<img src="ac-emb.png" width="30%" alt="Embedding Autocomplete" />
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||||
<img src="ac-lora.png" width="30%" alt="LoRA Autocomplete" />
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||||
<img src="ac-tag.png" width="30%" alt="Tag Autocomplete" />
|
||||
<img src="https://github.com/ComfyAssets/ComfyUI-KikoTools/blob/main/examples/ac-emb.png?raw=true" width="30%" alt="Embedding Autocomplete" />
|
||||
<img src="https://github.com/ComfyAssets/ComfyUI-KikoTools/blob/main/examples/ac-lora.png?raw=true" width="30%" alt="LoRA Autocomplete" />
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||||
<img src="https://github.com/ComfyAssets/ComfyUI-KikoTools/blob/main/examples/ac-tag.png?raw=true" width="30%" alt="Tag Autocomplete" />
|
||||
</div>
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||||
|
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This feature is an enhanced fork of the autocomplete functionality from [ComfyUI-Custom-Scripts](https://github.com/pythongosssss/ComfyUI-Custom-Scripts) by pythongosssss. We've modernized the codebase, fixed existing bugs, and added robust security features.
|
||||
@@ -351,6 +396,46 @@ This feature is an enhanced fork of the autocomplete functionality from [ComfyUI
|
||||
- Original autocomplete concept by [pythongosssss](https://github.com/pythongosssss/ComfyUI-Custom-Scripts)
|
||||
- Enhanced and modernized by KikoTools team
|
||||
|
||||
### 🧹 Kiko Purge VRAM
|
||||
**Intelligent GPU memory management with threshold-based triggering and detailed reporting.**
|
||||
|
||||
**Key Features:**
|
||||
- **4 Purge Modes**:
|
||||
- `soft`: Basic garbage collection and cache clearing
|
||||
- `aggressive`: Multiple GC passes with full CUDA cache clearing
|
||||
- `models_only`: Unload all models and clear model cache
|
||||
- `cache_only`: Clear CUDA cache without garbage collection
|
||||
- **Smart Thresholds**: Only purge when memory usage exceeds specified MB limit
|
||||
- **Detailed Reporting**: Shows before/after memory usage, freed MB, and timing
|
||||
- **Passthrough Design**: Acts as workflow checkpoint without disrupting data flow
|
||||
- **CPU Fallback**: Gracefully handles non-CUDA environments
|
||||
|
||||
**Use Cases:**
|
||||
- Free memory between heavy processing stages
|
||||
- Prevent OOM errors in complex workflows
|
||||
- Debug memory usage patterns
|
||||
- Optimize multi-model workflows
|
||||
- Clean up after batch processing
|
||||
|
||||
**Parameters:**
|
||||
- **anything**: Any input (passed through unchanged)
|
||||
- **mode**: Purge strategy selection
|
||||
- **report_memory**: Generate detailed memory statistics
|
||||
- **memory_threshold_mb**: Only purge if usage exceeds (0 = always purge)
|
||||
|
||||
**Example Output:**
|
||||
```
|
||||
Memory usage (5000.0 MB) exceeds threshold (4000 MB)
|
||||
|
||||
Memory Purge Report
|
||||
-------------------
|
||||
Mode: soft
|
||||
Memory Freed: 2500.0 MB
|
||||
Before: 5000.0 MB used (62.5%)
|
||||
After: 2500.0 MB used (31.3%)
|
||||
Time: 150.0ms
|
||||
```
|
||||
|
||||
### 💾 Kiko Save Image Features
|
||||
|
||||
**Use Cases:**
|
||||
@@ -585,6 +670,8 @@ Example workflow available: [xyz_helpers_lora_testing.json](examples/workflows/x
|
||||
| **Gemini Prompt Engineer** | AI-powered image analysis with dynamic model refresh | ✅ Complete | [Docs](examples/documentation/gemini_prompt.md) |
|
||||
| **Display Any** | Universal debugging tool for any data type or tensor shapes | ✅ Complete | [Docs](examples/documentation/display_any.md) |
|
||||
| **Image to Multiple Of** | Adjust image dimensions to multiples for model compatibility | ✅ Complete | [Docs](examples/documentation/image_to_multiple_of.md) |
|
||||
| **Image Scale Down By** | Efficiently scale images down by a specified factor | ✅ Complete | [Docs](examples/documentation/image_scale_down_by.md) |
|
||||
| **Film Grain** | Add realistic analog film grain effects to images | ✅ Complete | [Docs](examples/documentation/film_grain.md) |
|
||||
| **Flux Sampler Params** | FLUX-optimized parameter generator with batch support | ✅ Complete | [Docs](examples/documentation/flux_sampler_params.md) |
|
||||
| **LoRA Folder Batch** | Batch process multiple LoRAs from folders | ✅ Complete | [Docs](examples/documentation/lora_folder_batch.md) |
|
||||
| **Plot Parameters** | Visualize parameter effects with graphs | ✅ Complete | [Docs](examples/documentation/plot_parameters.md) |
|
||||
@@ -884,8 +971,9 @@ MIT License - see [LICENSE](LICENSE) file for details.
|
||||
|
||||
## 📈 Stats
|
||||
|
||||
- **Nodes**: 16 (10 core tools + 6 xyz-helpers)
|
||||
- **Categories**: 8 emoji-based categories for better organization
|
||||
- **Nodes**: 19 (13 core tools + 6 xyz-helpers)
|
||||
- **Features**: Embedding Autocomplete (settings-based, not a node)
|
||||
- **Categories**: 9 emoji-based categories for better organization
|
||||
- **Format Support**: 3 (PNG, JPEG, WebP with advanced controls)
|
||||
- **Presets**: 26 curated resolution presets
|
||||
- **Interactive Features**: 8+ (swap buttons, history UI, popup viewers, parameter visualization)
|
||||
|
||||
@@ -11,6 +11,7 @@ from .tools.gemini_prompt import GeminiPromptNode
|
||||
from .tools.image_scale_down_by import ImageScaleDownByNode
|
||||
from .tools.image_to_multiple_of import ImageToMultipleOfNode
|
||||
from .tools.kiko_film_grain import KikoFilmGrainNode
|
||||
from .tools.kiko_purge_vram import KikoPurgeVRAM
|
||||
from .tools.kiko_save_image import KikoSaveImageNode
|
||||
from .tools.resolution_calculator import ResolutionCalculatorNode
|
||||
from .tools.sampler_combo import SamplerComboCompactNode, SamplerComboNode
|
||||
@@ -40,13 +41,15 @@ NODE_CLASS_MAPPINGS = {
|
||||
"DisplayAny": DisplayAnyNode,
|
||||
"DisplayText": DisplayTextNode,
|
||||
"KikoFilmGrain": KikoFilmGrainNode,
|
||||
"KikoPurgeVRAM": KikoPurgeVRAM,
|
||||
"SamplerSelectHelper": SamplerSelectHelperNode,
|
||||
"SchedulerSelectHelper": SchedulerSelectHelperNode,
|
||||
"TextEncodeSamplerParams": TextEncodeSamplerParamsNode,
|
||||
"FluxSamplerParams": FluxSamplerParamsNode,
|
||||
"PlotParameters+": PlotParametersNode,
|
||||
"LoRAFolderBatch": LoRAFolderBatchNode,
|
||||
"KikoEmbeddingAutocomplete": KikoEmbeddingAutocomplete,
|
||||
# Note: KikoEmbeddingAutocomplete is not registered as a node
|
||||
# It's a settings-only feature accessed through ComfyUI settings menu
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
@@ -62,14 +65,15 @@ NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"GeminiPrompt": "Gemini Prompt Engineer",
|
||||
"DisplayAny": "Display Any",
|
||||
"DisplayText": "Display Text",
|
||||
"KikoFilmGrain": "Kiko Film Grain",
|
||||
"KikoFilmGrain": "Film Grain",
|
||||
"KikoPurgeVRAM": "Kiko Purge VRAM",
|
||||
"SamplerSelectHelper": "Sampler Select Helper",
|
||||
"SchedulerSelectHelper": "Scheduler Select Helper",
|
||||
"TextEncodeSamplerParams": "Text Encode for Sampler Params",
|
||||
"FluxSamplerParams": "Flux Sampler Parameters",
|
||||
"PlotParameters+": "Plot Parameters",
|
||||
"LoRAFolderBatch": "LoRA Folder Batch",
|
||||
"KikoEmbeddingAutocomplete": "🫶 Embedding Autocomplete Configuration",
|
||||
# KikoEmbeddingAutocomplete removed - settings only, not a node
|
||||
}
|
||||
|
||||
__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]
|
||||
|
||||
@@ -0,0 +1,8 @@
|
||||
"""AnyType for wildcard input matching in ComfyUI nodes."""
|
||||
|
||||
|
||||
class AnyType(str):
|
||||
"""A special type that matches any input type in ComfyUI."""
|
||||
|
||||
def __ne__(self, other):
|
||||
return False
|
||||
@@ -20,7 +20,7 @@ class ComfyAssetsBaseNode:
|
||||
- Consistent return type handling
|
||||
"""
|
||||
|
||||
CATEGORY = "ComfyAssets"
|
||||
CATEGORY = "🫶 ComfyAssets"
|
||||
|
||||
def validate_inputs(self, **kwargs) -> None:
|
||||
"""
|
||||
|
||||
@@ -38,7 +38,7 @@ class DisplayAnyNode(ComfyAssetsBaseNode):
|
||||
return True
|
||||
|
||||
RETURN_TYPES = ("STRING",)
|
||||
CATEGORY = "ComfyAssets/👁️ Display"
|
||||
CATEGORY = "🫶 ComfyAssets/👁️ Display"
|
||||
RETURN_NAMES = ("display_text",)
|
||||
FUNCTION = "display"
|
||||
OUTPUT_NODE = True # This node displays output in the UI
|
||||
|
||||
@@ -19,7 +19,7 @@ class DisplayTextNode(ComfyAssetsBaseNode):
|
||||
RETURN_NAMES = ("text",)
|
||||
OUTPUT_NODE = True
|
||||
FUNCTION = "display_text"
|
||||
CATEGORY = "ComfyAssets/👁️ Display"
|
||||
CATEGORY = "🫶 ComfyAssets/👁️ Display"
|
||||
|
||||
DESCRIPTION = """
|
||||
Displays text in the UI with a copy-to-clipboard feature.
|
||||
|
||||
@@ -17,7 +17,7 @@ class KikoEmbeddingAutocomplete:
|
||||
"""Node that provides embedding autocomplete functionality."""
|
||||
|
||||
DISPLAY_NAME = "🫶 Embedding Autocomplete Settings"
|
||||
CATEGORY = "ComfyAssets"
|
||||
CATEGORY = "🫶 ComfyAssets"
|
||||
|
||||
# Settings definition for the settings registry
|
||||
SETTINGS = {
|
||||
|
||||
@@ -96,7 +96,7 @@ class EmptyLatentBatchNode(ComfyAssetsBaseNode):
|
||||
RETURN_TYPES = ("LATENT", "INT", "INT")
|
||||
RETURN_NAMES = ("latent", "width", "height")
|
||||
FUNCTION = "create_empty_latent"
|
||||
CATEGORY = "ComfyAssets/📦 Latents"
|
||||
CATEGORY = "🫶 ComfyAssets/📦 Latents"
|
||||
|
||||
def create_empty_latent(
|
||||
self, preset: str, width: int, height: int, batch_size: int
|
||||
|
||||
@@ -51,7 +51,7 @@ class GeminiPromptNode(ComfyAssetsBaseNode):
|
||||
RETURN_TYPES = ("STRING", "STRING")
|
||||
RETURN_NAMES = ("prompt", "negative_prompt")
|
||||
FUNCTION = "generate_prompt"
|
||||
CATEGORY = "ComfyAssets/🧠 Prompts"
|
||||
CATEGORY = "🫶 ComfyAssets/🧠 Prompts"
|
||||
|
||||
DESCRIPTION = """
|
||||
Analyzes images using Google's Gemini AI to generate optimized prompts.
|
||||
|
||||
@@ -35,7 +35,7 @@ class ImageScaleDownByNode(ComfyAssetsBaseNode):
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("IMAGE",)
|
||||
CATEGORY = "ComfyAssets/🖼️ Resolution"
|
||||
CATEGORY = "🫶 ComfyAssets/🖼️ Resolution"
|
||||
RETURN_NAMES = ("images",)
|
||||
FUNCTION = "scale_down"
|
||||
|
||||
|
||||
@@ -36,7 +36,7 @@ class ImageToMultipleOfNode(ComfyAssetsBaseNode):
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("IMAGE",)
|
||||
CATEGORY = "ComfyAssets/🖼️ Resolution"
|
||||
CATEGORY = "🫶 ComfyAssets/🖼️ Resolution"
|
||||
RETURN_NAMES = ("image",)
|
||||
FUNCTION = "process"
|
||||
|
||||
|
||||
@@ -85,7 +85,7 @@ class KikoFilmGrainNode(ComfyAssetsBaseNode):
|
||||
RETURN_TYPES = ("IMAGE",)
|
||||
RETURN_NAMES = ("image",)
|
||||
FUNCTION = "apply_grain"
|
||||
CATEGORY = "ComfyAssets/image"
|
||||
CATEGORY = "🫶 ComfyAssets/💾 Images"
|
||||
DESCRIPTION = "Apply realistic film grain effect with customizable parameters"
|
||||
|
||||
def apply_grain(
|
||||
|
||||
@@ -0,0 +1,3 @@
|
||||
from .node import KikoPurgeVRAM
|
||||
|
||||
__all__ = ["KikoPurgeVRAM"]
|
||||
@@ -0,0 +1,130 @@
|
||||
import gc
|
||||
from typing import Dict, Tuple
|
||||
|
||||
try:
|
||||
import torch
|
||||
|
||||
TORCH_AVAILABLE = True
|
||||
except ImportError:
|
||||
TORCH_AVAILABLE = False
|
||||
|
||||
try:
|
||||
import comfy.model_management as mm
|
||||
|
||||
COMFY_AVAILABLE = True
|
||||
except ImportError:
|
||||
COMFY_AVAILABLE = False
|
||||
|
||||
|
||||
def get_memory_stats() -> Dict[str, float]:
|
||||
stats = {
|
||||
"cuda_available": False,
|
||||
"free_mb": 0,
|
||||
"total_mb": 0,
|
||||
"used_mb": 0,
|
||||
"used_percent": 0,
|
||||
}
|
||||
|
||||
if TORCH_AVAILABLE and torch.cuda.is_available():
|
||||
stats["cuda_available"] = True
|
||||
free, total = torch.cuda.mem_get_info()
|
||||
free_mb = free / (1024 * 1024)
|
||||
total_mb = total / (1024 * 1024)
|
||||
used_mb = total_mb - free_mb
|
||||
|
||||
stats["free_mb"] = free_mb
|
||||
stats["total_mb"] = total_mb
|
||||
stats["used_mb"] = used_mb
|
||||
stats["used_percent"] = (used_mb / total_mb) * 100 if total_mb > 0 else 0
|
||||
|
||||
return stats
|
||||
|
||||
|
||||
def purge_memory(mode: str = "soft", unload_models: bool = False) -> float:
|
||||
before_stats = get_memory_stats()
|
||||
|
||||
if mode == "soft":
|
||||
# Basic garbage collection and cache clearing
|
||||
gc.collect()
|
||||
if TORCH_AVAILABLE and torch.cuda.is_available():
|
||||
torch.cuda.empty_cache()
|
||||
|
||||
elif mode == "aggressive":
|
||||
# Multiple passes of garbage collection with full cache clearing
|
||||
gc.collect()
|
||||
gc.collect()
|
||||
if TORCH_AVAILABLE and torch.cuda.is_available():
|
||||
torch.cuda.synchronize()
|
||||
torch.cuda.empty_cache()
|
||||
torch.cuda.ipc_collect()
|
||||
|
||||
elif mode == "models_only":
|
||||
# Only unload models
|
||||
if COMFY_AVAILABLE:
|
||||
mm.unload_all_models()
|
||||
mm.soft_empty_cache()
|
||||
gc.collect()
|
||||
|
||||
elif mode == "cache_only":
|
||||
# Only clear cache without garbage collection
|
||||
if TORCH_AVAILABLE and torch.cuda.is_available():
|
||||
torch.cuda.empty_cache()
|
||||
|
||||
# Handle model unloading for non-model-specific modes
|
||||
if unload_models and mode not in ["models_only"]:
|
||||
if COMFY_AVAILABLE:
|
||||
mm.unload_all_models()
|
||||
mm.soft_empty_cache()
|
||||
|
||||
after_stats = get_memory_stats()
|
||||
freed_mb = before_stats["used_mb"] - after_stats["used_mb"]
|
||||
|
||||
return max(0, freed_mb)
|
||||
|
||||
|
||||
def format_memory_report(
|
||||
before: Dict[str, float], after: Dict[str, float], mode: str, elapsed_ms: float
|
||||
) -> str:
|
||||
if not before.get("cuda_available", True):
|
||||
return (
|
||||
"Memory Purge Report\n"
|
||||
"-------------------\n"
|
||||
"CUDA not available - CPU memory management only\n"
|
||||
f"Mode: {mode}\n"
|
||||
f"Time: {elapsed_ms:.1f}ms"
|
||||
)
|
||||
|
||||
freed_mb = before["used_mb"] - after["used_mb"]
|
||||
|
||||
report = [
|
||||
"Memory Purge Report",
|
||||
"-------------------",
|
||||
f"Mode: {mode}",
|
||||
f"Memory Freed: {freed_mb:.1f} MB",
|
||||
f"Before: {before['used_mb']:.1f} MB used ({before['used_percent']:.1f}%)",
|
||||
f"After: {after['used_mb']:.1f} MB used ({after['used_percent']:.1f}%)",
|
||||
f"Time: {elapsed_ms:.1f}ms",
|
||||
]
|
||||
|
||||
return "\n".join(report)
|
||||
|
||||
|
||||
def should_purge(threshold_mb: int) -> Tuple[bool, str]:
|
||||
if threshold_mb <= 0:
|
||||
return True, ""
|
||||
|
||||
stats = get_memory_stats()
|
||||
|
||||
if not stats["cuda_available"]:
|
||||
return True, "CUDA not available, proceeding with CPU memory management"
|
||||
|
||||
if stats["used_mb"] >= threshold_mb:
|
||||
return (
|
||||
True,
|
||||
f"Memory usage ({stats['used_mb']:.1f} MB) exceeds threshold ({threshold_mb} MB)",
|
||||
)
|
||||
else:
|
||||
return (
|
||||
False,
|
||||
f"Memory usage ({stats['used_mb']:.1f} MB) below threshold ({threshold_mb} MB)",
|
||||
)
|
||||
@@ -0,0 +1,102 @@
|
||||
import time
|
||||
from typing import Any, Dict, Tuple
|
||||
|
||||
try:
|
||||
from ...base.base_node import ComfyAssetsBaseNode as BaseNode
|
||||
from ...base.any_type import AnyType
|
||||
except ImportError:
|
||||
# Fallback for testing environment
|
||||
from kikotools.base.base_node import ComfyAssetsBaseNode as BaseNode
|
||||
from kikotools.base.any_type import AnyType
|
||||
from .logic import get_memory_stats, purge_memory, format_memory_report, should_purge
|
||||
|
||||
any_type = AnyType("*")
|
||||
|
||||
|
||||
class KikoPurgeVRAM(BaseNode):
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls) -> Dict[str, Any]:
|
||||
return {
|
||||
"required": {
|
||||
"anything": (any_type, {}),
|
||||
"mode": (
|
||||
["soft", "aggressive", "models_only", "cache_only"],
|
||||
{
|
||||
"default": "soft",
|
||||
"tooltip": "Purge mode: soft (basic), aggressive (thorough), models_only (unload models), cache_only (clear cache)",
|
||||
},
|
||||
),
|
||||
"report_memory": (
|
||||
"BOOLEAN",
|
||||
{
|
||||
"default": True,
|
||||
"tooltip": "Generate detailed memory usage report",
|
||||
},
|
||||
),
|
||||
},
|
||||
"optional": {
|
||||
"memory_threshold_mb": (
|
||||
"INT",
|
||||
{
|
||||
"default": 0,
|
||||
"min": 0,
|
||||
"max": 48000,
|
||||
"step": 100,
|
||||
"tooltip": "Only purge if memory usage exceeds this threshold (0 = always purge)",
|
||||
},
|
||||
),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = (any_type, "STRING")
|
||||
RETURN_NAMES = ("passthrough", "memory_report")
|
||||
FUNCTION = "purge_vram"
|
||||
CATEGORY = "🫶 ComfyAssets/🛠️ Utils"
|
||||
OUTPUT_NODE = True
|
||||
DESCRIPTION = "Purge VRAM to free up GPU memory during workflow execution. Passes through any input unchanged."
|
||||
|
||||
def purge_vram(
|
||||
self,
|
||||
anything: Any,
|
||||
mode: str,
|
||||
report_memory: bool,
|
||||
memory_threshold_mb: int = 0,
|
||||
) -> Tuple[Any, str]:
|
||||
# Check if we should purge based on threshold
|
||||
should_run, threshold_msg = should_purge(memory_threshold_mb)
|
||||
|
||||
if not should_run:
|
||||
if report_memory:
|
||||
return anything, f"Memory purge skipped: {threshold_msg}"
|
||||
else:
|
||||
return anything, ""
|
||||
|
||||
# Get before stats
|
||||
before_stats = get_memory_stats() if report_memory else None
|
||||
start_time = time.time()
|
||||
|
||||
# Determine if we should unload models
|
||||
unload_models = mode in ["models_only", "aggressive"]
|
||||
|
||||
# Perform memory purge
|
||||
purge_memory(mode=mode, unload_models=unload_models)
|
||||
|
||||
# Calculate elapsed time
|
||||
elapsed_ms = (time.time() - start_time) * 1000
|
||||
|
||||
# Generate report if requested
|
||||
if report_memory:
|
||||
after_stats = get_memory_stats()
|
||||
report = format_memory_report(before_stats, after_stats, mode, elapsed_ms)
|
||||
if threshold_msg and memory_threshold_mb > 0:
|
||||
report = f"{threshold_msg}\n\n{report}"
|
||||
else:
|
||||
report = ""
|
||||
|
||||
# Pass through the input unchanged
|
||||
return anything, report
|
||||
|
||||
|
||||
NODE_CLASS_MAPPINGS = {"KikoPurgeVRAM": KikoPurgeVRAM}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {"KikoPurgeVRAM": "Kiko Purge VRAM"}
|
||||
@@ -95,7 +95,7 @@ class KikoSaveImageNode(ComfyAssetsBaseNode):
|
||||
}
|
||||
|
||||
RETURN_TYPES = ()
|
||||
CATEGORY = "ComfyAssets/💾 Images"
|
||||
CATEGORY = "🫶 ComfyAssets/💾 Images"
|
||||
FUNCTION = "save_images"
|
||||
OUTPUT_NODE = True
|
||||
|
||||
|
||||
@@ -60,7 +60,7 @@ class ResolutionCalculatorNode(ComfyAssetsBaseNode):
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("INT", "INT")
|
||||
CATEGORY = "ComfyAssets/🖼️ Resolution"
|
||||
CATEGORY = "🫶 ComfyAssets/🖼️ Resolution"
|
||||
RETURN_NAMES = ("width", "height")
|
||||
FUNCTION = "calculate_resolution"
|
||||
|
||||
|
||||
@@ -63,7 +63,7 @@ class SamplerComboCompactNode(ComfyAssetsBaseNode):
|
||||
RETURN_TYPES = ("SAMPLER", SCHEDULERS, "INT", "FLOAT")
|
||||
RETURN_NAMES = ("sampler", "scheduler", "steps", "cfg")
|
||||
FUNCTION = "get_combo"
|
||||
CATEGORY = "ComfyAssets/🌀 Samplers"
|
||||
CATEGORY = "🫶 ComfyAssets/🌀 Samplers"
|
||||
|
||||
def get_combo(
|
||||
self, sampler: str, sched: str, steps: int, cfg: float
|
||||
|
||||
@@ -68,7 +68,7 @@ class SamplerComboNode(ComfyAssetsBaseNode):
|
||||
RETURN_TYPES = ("SAMPLER", SCHEDULERS, "INT", "FLOAT")
|
||||
RETURN_NAMES = ("sampler_name", "scheduler", "steps", "cfg")
|
||||
FUNCTION = "get_sampler_combo"
|
||||
CATEGORY = "ComfyAssets/🌀 Samplers"
|
||||
CATEGORY = "🫶 ComfyAssets/🌀 Samplers"
|
||||
|
||||
def get_sampler_combo(
|
||||
self, sampler_name: str, scheduler: str, steps: int, cfg: float
|
||||
|
||||
@@ -38,7 +38,7 @@ class SeedHistoryNode(ComfyAssetsBaseNode):
|
||||
RETURN_TYPES = ("INT",)
|
||||
RETURN_NAMES = ("seed",)
|
||||
FUNCTION = "output_seed"
|
||||
CATEGORY = "ComfyAssets/🌱 Seeds"
|
||||
CATEGORY = "🫶 ComfyAssets/🌱 Seeds"
|
||||
|
||||
def output_seed(self, seed: int) -> Tuple[int]:
|
||||
"""
|
||||
|
||||
@@ -85,7 +85,7 @@ class WidthHeightSelectorNode(ComfyAssetsBaseNode):
|
||||
RETURN_TYPES = ("INT", "INT")
|
||||
RETURN_NAMES = ("width", "height")
|
||||
FUNCTION = "get_dimensions"
|
||||
CATEGORY = "ComfyAssets/🖼️ Resolution"
|
||||
CATEGORY = "🫶 ComfyAssets/🖼️ Resolution"
|
||||
|
||||
def get_dimensions(self, preset: str, width: int, height: int) -> Tuple[int, int]:
|
||||
"""
|
||||
|
||||
@@ -125,7 +125,7 @@ class FluxSamplerParamsNode(ComfyAssetsBaseNode):
|
||||
RETURN_TYPES = ("LATENT", "SAMPLER_PARAMS")
|
||||
RETURN_NAMES = ("latent", "params")
|
||||
FUNCTION = "process_batch"
|
||||
CATEGORY = "ComfyAssets/🧰 xyz-helpers"
|
||||
CATEGORY = "🫶 ComfyAssets/🧰 xyz-helpers"
|
||||
|
||||
def process_batch(
|
||||
self,
|
||||
|
||||
@@ -80,7 +80,7 @@ class LoRAFolderBatchNode(ComfyAssetsBaseNode):
|
||||
RETURN_TYPES = ("LORA_PARAMS", "STRING", "INT")
|
||||
RETURN_NAMES = ("lora_params", "lora_list", "lora_count")
|
||||
FUNCTION = "batch_loras"
|
||||
CATEGORY = "ComfyAssets/🧰 xyz-helpers"
|
||||
CATEGORY = "🫶 ComfyAssets/🧰 xyz-helpers"
|
||||
|
||||
def batch_loras(
|
||||
self,
|
||||
|
||||
@@ -113,7 +113,7 @@ class PlotParametersNode(ComfyAssetsBaseNode):
|
||||
RETURN_TYPES = ("IMAGE",)
|
||||
RETURN_NAMES = ("image",)
|
||||
FUNCTION = "plot_parameters"
|
||||
CATEGORY = "ComfyAssets/🧰 xyz-helpers"
|
||||
CATEGORY = "🫶 ComfyAssets/🧰 xyz-helpers"
|
||||
|
||||
def plot_parameters(
|
||||
self,
|
||||
|
||||
@@ -30,7 +30,7 @@ class SamplerSelectHelperNode(ComfyAssetsBaseNode):
|
||||
RETURN_TYPES = ("STRING",)
|
||||
RETURN_NAMES = ("selected_samplers",)
|
||||
FUNCTION = "select_samplers"
|
||||
CATEGORY = "ComfyAssets/🧰 xyz-helpers"
|
||||
CATEGORY = "🫶 ComfyAssets/🧰 xyz-helpers"
|
||||
|
||||
def select_samplers(self, **sampler_flags) -> Tuple[str]:
|
||||
"""
|
||||
|
||||
@@ -30,7 +30,7 @@ class SchedulerSelectHelperNode(ComfyAssetsBaseNode):
|
||||
RETURN_TYPES = ("STRING",)
|
||||
RETURN_NAMES = ("selected_schedulers",)
|
||||
FUNCTION = "select_schedulers"
|
||||
CATEGORY = "ComfyAssets/🧰 xyz-helpers"
|
||||
CATEGORY = "🫶 ComfyAssets/🧰 xyz-helpers"
|
||||
|
||||
def select_schedulers(self, **scheduler_flags) -> Tuple[str]:
|
||||
"""
|
||||
|
||||
@@ -40,7 +40,7 @@ class TextEncodeSamplerParamsNode(ComfyAssetsBaseNode):
|
||||
RETURN_TYPES = ("CONDITIONING",)
|
||||
RETURN_NAMES = ("conditioning",)
|
||||
FUNCTION = "encode_prompts"
|
||||
CATEGORY = "ComfyAssets/🧰 xyz-helpers"
|
||||
CATEGORY = "🫶 ComfyAssets/🧰 xyz-helpers"
|
||||
|
||||
def encode_prompts(self, text: str, clip: Any) -> Tuple[Any]:
|
||||
"""
|
||||
|
||||
+1
-1
@@ -5,7 +5,7 @@ build-backend = "setuptools.build_meta"
|
||||
[project]
|
||||
name = "kikotools"
|
||||
description = "Simple tools for ComfyUI"
|
||||
version = "1.0.12"
|
||||
version = "1.0.15"
|
||||
license = {text = "MIT"}
|
||||
dependencies = []
|
||||
|
||||
|
||||
@@ -0,0 +1,299 @@
|
||||
import sys
|
||||
from unittest.mock import patch, MagicMock
|
||||
|
||||
import pytest
|
||||
|
||||
# Mock comfy modules
|
||||
sys.modules["comfy"] = MagicMock()
|
||||
sys.modules["comfy.model_management"] = MagicMock()
|
||||
|
||||
from kikotools.tools.kiko_purge_vram.logic import (
|
||||
purge_memory,
|
||||
get_memory_stats,
|
||||
format_memory_report,
|
||||
)
|
||||
|
||||
|
||||
class TestMemoryStats:
|
||||
@patch("torch.cuda.is_available")
|
||||
@patch("torch.cuda.mem_get_info")
|
||||
def test_get_memory_stats_with_cuda(self, mock_mem_info, mock_cuda_available):
|
||||
mock_cuda_available.return_value = True
|
||||
mock_mem_info.return_value = (4000000000, 8000000000) # 4GB free, 8GB total
|
||||
|
||||
stats = get_memory_stats()
|
||||
|
||||
assert stats["cuda_available"] is True
|
||||
assert stats["free_mb"] == pytest.approx(3814.7, rel=0.1)
|
||||
assert stats["total_mb"] == pytest.approx(7629.4, rel=0.1)
|
||||
assert stats["used_mb"] == pytest.approx(3814.7, rel=0.1)
|
||||
assert stats["used_percent"] == pytest.approx(50.0, rel=0.1)
|
||||
|
||||
@patch("torch.cuda.is_available")
|
||||
def test_get_memory_stats_without_cuda(self, mock_cuda_available):
|
||||
mock_cuda_available.return_value = False
|
||||
|
||||
stats = get_memory_stats()
|
||||
|
||||
assert stats["cuda_available"] is False
|
||||
assert stats["free_mb"] == 0
|
||||
assert stats["total_mb"] == 0
|
||||
assert stats["used_mb"] == 0
|
||||
assert stats["used_percent"] == 0
|
||||
|
||||
|
||||
class TestMemoryPurge:
|
||||
@patch("torch.cuda.is_available")
|
||||
@patch("torch.cuda.empty_cache")
|
||||
@patch("torch.cuda.ipc_collect")
|
||||
@patch("gc.collect")
|
||||
def test_purge_memory_soft_mode(
|
||||
self, mock_gc, mock_ipc, mock_empty_cache, mock_cuda
|
||||
):
|
||||
mock_cuda.return_value = True
|
||||
|
||||
with patch(
|
||||
"kikotools.tools.kiko_purge_vram.logic.get_memory_stats"
|
||||
) as mock_stats:
|
||||
mock_stats.side_effect = [
|
||||
{"used_mb": 4000, "free_mb": 4000},
|
||||
{"used_mb": 2000, "free_mb": 6000},
|
||||
]
|
||||
|
||||
freed_mb = purge_memory(mode="soft", unload_models=False)
|
||||
|
||||
mock_gc.assert_called_once()
|
||||
mock_empty_cache.assert_called_once()
|
||||
mock_ipc.assert_not_called()
|
||||
assert freed_mb == 2000
|
||||
|
||||
@patch("torch.cuda.is_available")
|
||||
@patch("torch.cuda.empty_cache")
|
||||
@patch("torch.cuda.ipc_collect")
|
||||
@patch("torch.cuda.synchronize")
|
||||
@patch("gc.collect")
|
||||
def test_purge_memory_aggressive_mode(
|
||||
self, mock_gc, mock_sync, mock_ipc, mock_empty_cache, mock_cuda
|
||||
):
|
||||
mock_cuda.return_value = True
|
||||
|
||||
with patch(
|
||||
"kikotools.tools.kiko_purge_vram.logic.get_memory_stats"
|
||||
) as mock_stats:
|
||||
mock_stats.side_effect = [
|
||||
{"used_mb": 4000, "free_mb": 4000},
|
||||
{"used_mb": 1500, "free_mb": 6500},
|
||||
]
|
||||
|
||||
freed_mb = purge_memory(mode="aggressive", unload_models=False)
|
||||
|
||||
assert mock_gc.call_count == 2
|
||||
mock_empty_cache.assert_called()
|
||||
mock_ipc.assert_called_once()
|
||||
mock_sync.assert_called_once()
|
||||
assert freed_mb == 2500
|
||||
|
||||
@patch("kikotools.tools.kiko_purge_vram.logic.COMFY_AVAILABLE", True)
|
||||
@patch("kikotools.tools.kiko_purge_vram.logic.mm.unload_all_models")
|
||||
@patch("kikotools.tools.kiko_purge_vram.logic.mm.soft_empty_cache")
|
||||
@patch("torch.cuda.is_available")
|
||||
@patch("gc.collect")
|
||||
def test_purge_memory_models_only(
|
||||
self, mock_gc, mock_cuda, mock_soft_empty, mock_unload
|
||||
):
|
||||
mock_cuda.return_value = True
|
||||
|
||||
with patch(
|
||||
"kikotools.tools.kiko_purge_vram.logic.get_memory_stats"
|
||||
) as mock_stats:
|
||||
mock_stats.side_effect = [
|
||||
{"used_mb": 6000, "free_mb": 2000},
|
||||
{"used_mb": 1000, "free_mb": 7000},
|
||||
]
|
||||
|
||||
freed_mb = purge_memory(mode="models_only", unload_models=True)
|
||||
|
||||
mock_unload.assert_called_once()
|
||||
mock_soft_empty.assert_called_once()
|
||||
mock_gc.assert_called()
|
||||
assert freed_mb == 5000
|
||||
|
||||
@patch("torch.cuda.is_available")
|
||||
@patch("torch.cuda.empty_cache")
|
||||
@patch("gc.collect")
|
||||
def test_purge_memory_cache_only(self, mock_gc, mock_empty_cache, mock_cuda):
|
||||
mock_cuda.return_value = True
|
||||
|
||||
with patch(
|
||||
"kikotools.tools.kiko_purge_vram.logic.get_memory_stats"
|
||||
) as mock_stats:
|
||||
mock_stats.side_effect = [
|
||||
{"used_mb": 3000, "free_mb": 5000},
|
||||
{"used_mb": 2500, "free_mb": 5500},
|
||||
]
|
||||
|
||||
freed_mb = purge_memory(mode="cache_only", unload_models=False)
|
||||
|
||||
mock_gc.assert_not_called()
|
||||
mock_empty_cache.assert_called_once()
|
||||
assert freed_mb == 500
|
||||
|
||||
@patch("torch.cuda.is_available")
|
||||
def test_purge_memory_no_cuda(self, mock_cuda):
|
||||
mock_cuda.return_value = False
|
||||
|
||||
with patch("gc.collect") as mock_gc:
|
||||
freed_mb = purge_memory(mode="soft", unload_models=False)
|
||||
|
||||
mock_gc.assert_called_once()
|
||||
assert freed_mb == 0
|
||||
|
||||
|
||||
class TestMemoryReport:
|
||||
def test_format_memory_report_with_improvement(self):
|
||||
before = {
|
||||
"used_mb": 4000,
|
||||
"free_mb": 4000,
|
||||
"total_mb": 8000,
|
||||
"used_percent": 50,
|
||||
}
|
||||
after = {"used_mb": 2000, "free_mb": 6000, "total_mb": 8000, "used_percent": 25}
|
||||
|
||||
report = format_memory_report(before, after, mode="soft", elapsed_ms=150)
|
||||
|
||||
assert "Memory Purge Report" in report
|
||||
assert "Mode: soft" in report
|
||||
assert "Memory Freed: 2000.0 MB" in report
|
||||
assert "Before: 4000.0 MB used (50.0%)" in report
|
||||
assert "After: 2000.0 MB used (25.0%)" in report
|
||||
assert "Time: 150.0ms" in report
|
||||
|
||||
def test_format_memory_report_no_improvement(self):
|
||||
before = {
|
||||
"used_mb": 2000,
|
||||
"free_mb": 6000,
|
||||
"total_mb": 8000,
|
||||
"used_percent": 25,
|
||||
}
|
||||
after = {"used_mb": 2000, "free_mb": 6000, "total_mb": 8000, "used_percent": 25}
|
||||
|
||||
report = format_memory_report(before, after, mode="cache_only", elapsed_ms=50)
|
||||
|
||||
assert "Memory Freed: 0.0 MB" in report
|
||||
assert "Time: 50.0ms" in report
|
||||
|
||||
def test_format_memory_report_no_cuda(self):
|
||||
before = {
|
||||
"used_mb": 0,
|
||||
"free_mb": 0,
|
||||
"total_mb": 0,
|
||||
"used_percent": 0,
|
||||
"cuda_available": False,
|
||||
}
|
||||
after = {
|
||||
"used_mb": 0,
|
||||
"free_mb": 0,
|
||||
"total_mb": 0,
|
||||
"used_percent": 0,
|
||||
"cuda_available": False,
|
||||
}
|
||||
|
||||
report = format_memory_report(before, after, mode="soft", elapsed_ms=10)
|
||||
|
||||
assert "CUDA not available" in report
|
||||
|
||||
|
||||
class TestKikoPurgeVRAMNode:
|
||||
@patch("kikotools.tools.kiko_purge_vram.node.format_memory_report")
|
||||
@patch("kikotools.tools.kiko_purge_vram.node.purge_memory")
|
||||
@patch("kikotools.tools.kiko_purge_vram.node.get_memory_stats")
|
||||
@patch("kikotools.tools.kiko_purge_vram.node.should_purge")
|
||||
def test_node_execute_with_threshold(
|
||||
self, mock_should_purge, mock_stats, mock_purge, mock_format
|
||||
):
|
||||
from kikotools.tools.kiko_purge_vram.node import KikoPurgeVRAM
|
||||
|
||||
mock_should_purge.return_value = (
|
||||
True,
|
||||
"Memory usage (5000.0 MB) exceeds threshold (4000 MB)",
|
||||
)
|
||||
mock_stats.side_effect = [
|
||||
{
|
||||
"used_mb": 5000,
|
||||
"free_mb": 3000,
|
||||
"total_mb": 8000,
|
||||
"used_percent": 62.5,
|
||||
"cuda_available": True,
|
||||
},
|
||||
{
|
||||
"used_mb": 2000,
|
||||
"free_mb": 6000,
|
||||
"total_mb": 8000,
|
||||
"used_percent": 25,
|
||||
"cuda_available": True,
|
||||
},
|
||||
]
|
||||
mock_purge.return_value = 3000
|
||||
mock_format.return_value = "Memory Purge Report\n-------------------\nMode: soft\nMemory Freed: 3000.0 MB"
|
||||
|
||||
node = KikoPurgeVRAM()
|
||||
test_input = "test_data"
|
||||
|
||||
result, report = node.purge_vram(
|
||||
anything=test_input,
|
||||
mode="soft",
|
||||
report_memory=True,
|
||||
memory_threshold_mb=4000,
|
||||
)
|
||||
|
||||
assert result == test_input
|
||||
assert "Memory Freed: 3000.0 MB" in report
|
||||
mock_purge.assert_called_once_with(mode="soft", unload_models=False)
|
||||
|
||||
@patch("kikotools.tools.kiko_purge_vram.logic.get_memory_stats")
|
||||
def test_node_skip_below_threshold(self, mock_stats):
|
||||
from kikotools.tools.kiko_purge_vram.node import KikoPurgeVRAM
|
||||
|
||||
mock_stats.return_value = {
|
||||
"used_mb": 2000,
|
||||
"free_mb": 6000,
|
||||
"total_mb": 8000,
|
||||
"used_percent": 25,
|
||||
"cuda_available": True,
|
||||
}
|
||||
|
||||
node = KikoPurgeVRAM()
|
||||
test_input = "test_data"
|
||||
|
||||
with patch("kikotools.tools.kiko_purge_vram.logic.purge_memory") as mock_purge:
|
||||
result, report = node.purge_vram(
|
||||
anything=test_input,
|
||||
mode="soft",
|
||||
report_memory=True,
|
||||
memory_threshold_mb=3000,
|
||||
)
|
||||
|
||||
assert result == test_input
|
||||
assert "below threshold" in report.lower()
|
||||
mock_purge.assert_not_called()
|
||||
|
||||
def test_node_input_types(self):
|
||||
from kikotools.tools.kiko_purge_vram.node import KikoPurgeVRAM
|
||||
|
||||
input_types = KikoPurgeVRAM.INPUT_TYPES()
|
||||
|
||||
assert "required" in input_types
|
||||
assert "optional" in input_types
|
||||
assert "anything" in input_types["required"]
|
||||
assert "mode" in input_types["required"]
|
||||
assert "report_memory" in input_types["required"]
|
||||
assert "memory_threshold_mb" in input_types["optional"]
|
||||
|
||||
def test_node_properties(self):
|
||||
from kikotools.tools.kiko_purge_vram.node import KikoPurgeVRAM
|
||||
|
||||
assert KikoPurgeVRAM.FUNCTION == "purge_vram"
|
||||
assert KikoPurgeVRAM.CATEGORY == "🫶 ComfyAssets/🛠️ Utils"
|
||||
assert KikoPurgeVRAM.OUTPUT_NODE is True
|
||||
assert len(KikoPurgeVRAM.RETURN_TYPES) == 2
|
||||
assert KikoPurgeVRAM.RETURN_NAMES == ("passthrough", "memory_report")
|
||||
@@ -0,0 +1,258 @@
|
||||
import { app } from "../../scripts/app.js";
|
||||
import { $el } from "../../scripts/ui.js";
|
||||
|
||||
// Custom colors feature with extended options based on PR #433
|
||||
// Adds custom color pickers for nodes with full, title, and background options
|
||||
|
||||
const colorShade = (col, amt) => {
|
||||
col = col.replace(/^#/, "");
|
||||
if (col.length === 3) col = col[0] + col[0] + col[1] + col[1] + col[2] + col[2];
|
||||
|
||||
let [r, g, b] = col.match(/.{2}/g);
|
||||
[r, g, b] = [parseInt(r, 16) + amt, parseInt(g, 16) + amt, parseInt(b, 16) + amt];
|
||||
|
||||
r = Math.max(Math.min(255, r), 0).toString(16);
|
||||
g = Math.max(Math.min(255, g), 0).toString(16);
|
||||
b = Math.max(Math.min(255, b), 0).toString(16);
|
||||
|
||||
const rr = (r.length < 2 ? "0" : "") + r;
|
||||
const gg = (g.length < 2 ? "0" : "") + g;
|
||||
const bb = (b.length < 2 ? "0" : "") + b;
|
||||
|
||||
return `#${rr}${gg}${bb}`;
|
||||
};
|
||||
|
||||
app.registerExtension({
|
||||
name: "kikotools.customColors",
|
||||
async init() {
|
||||
// Register settings
|
||||
app.ui.settings.addSetting({
|
||||
id: "kikotools.custom_colors.enabled",
|
||||
name: "🫶 Custom Colors: Enable",
|
||||
type: "boolean",
|
||||
defaultValue: false,
|
||||
tooltip: "Enable custom color picker options in node context menu",
|
||||
});
|
||||
|
||||
app.ui.settings.addSetting({
|
||||
id: "kikotools.custom_colors.show_full",
|
||||
name: "🫶 Custom Colors: Show Full Color Option",
|
||||
type: "boolean",
|
||||
defaultValue: true,
|
||||
tooltip: "Show option to change both title and background colors",
|
||||
});
|
||||
|
||||
app.ui.settings.addSetting({
|
||||
id: "kikotools.custom_colors.show_title",
|
||||
name: "🫶 Custom Colors: Show Title Color Option",
|
||||
type: "boolean",
|
||||
defaultValue: true,
|
||||
tooltip: "Show option to change only title color",
|
||||
});
|
||||
|
||||
app.ui.settings.addSetting({
|
||||
id: "kikotools.custom_colors.show_bg",
|
||||
name: "🫶 Custom Colors: Show Background Color Option",
|
||||
type: "boolean",
|
||||
defaultValue: true,
|
||||
tooltip: "Show option to change only background color",
|
||||
});
|
||||
|
||||
app.ui.settings.addSetting({
|
||||
id: "kikotools.custom_colors.auto_shade",
|
||||
name: "🫶 Custom Colors: Auto-shade Title",
|
||||
type: "boolean",
|
||||
defaultValue: true,
|
||||
tooltip: "Automatically apply shading to title color for better contrast",
|
||||
});
|
||||
},
|
||||
|
||||
setup() {
|
||||
let pickerFull, pickerTitle, pickerBG;
|
||||
let activeNode;
|
||||
|
||||
// Check if feature is enabled
|
||||
const isEnabled = () => {
|
||||
const setting = app.ui.settings.getSettingValue("kikotools.custom_colors.enabled");
|
||||
return setting !== undefined ? setting : false;
|
||||
};
|
||||
|
||||
const getSettings = () => ({
|
||||
showFull: app.ui.settings.getSettingValue("kikotools.custom_colors.show_full") !== false,
|
||||
showTitle: app.ui.settings.getSettingValue("kikotools.custom_colors.show_title") !== false,
|
||||
showBG: app.ui.settings.getSettingValue("kikotools.custom_colors.show_bg") !== false,
|
||||
autoShade: app.ui.settings.getSettingValue("kikotools.custom_colors.auto_shade") !== false,
|
||||
});
|
||||
|
||||
// Helper function to apply color to node(s)
|
||||
const applyColorToNodes = (colorValue, colorType, node) => {
|
||||
const settings = getSettings();
|
||||
const graphcanvas = LGraphCanvas.active_canvas;
|
||||
const nodes = (!graphcanvas.selected_nodes || Object.keys(graphcanvas.selected_nodes).length <= 1)
|
||||
? [node]
|
||||
: Object.values(graphcanvas.selected_nodes);
|
||||
|
||||
nodes.forEach(n => {
|
||||
if (colorValue) {
|
||||
if (n.constructor === LiteGraph.LGraphGroup) {
|
||||
// For groups, only set the main color
|
||||
if (colorType === 'full' || colorType === 'bg') {
|
||||
n.color = colorValue;
|
||||
}
|
||||
} else {
|
||||
// For regular nodes
|
||||
switch(colorType) {
|
||||
case 'full':
|
||||
n.color = settings.autoShade ? colorShade(colorValue, 20) : colorValue;
|
||||
n.bgcolor = colorValue;
|
||||
break;
|
||||
case 'title':
|
||||
n.color = colorValue;
|
||||
break;
|
||||
case 'bg':
|
||||
n.bgcolor = colorValue;
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
node.setDirtyCanvas(true, true);
|
||||
};
|
||||
|
||||
// Create color picker input if not exists
|
||||
const createPicker = (type) => {
|
||||
const picker = $el("input", {
|
||||
type: "color",
|
||||
parent: document.body,
|
||||
style: {
|
||||
display: "none",
|
||||
},
|
||||
});
|
||||
|
||||
picker.onchange = () => {
|
||||
if (activeNode) {
|
||||
applyColorToNodes(picker.value, type, activeNode);
|
||||
}
|
||||
};
|
||||
|
||||
return picker;
|
||||
};
|
||||
|
||||
// Hook into the node colors menu
|
||||
const onMenuNodeColors = LGraphCanvas.onMenuNodeColors;
|
||||
LGraphCanvas.onMenuNodeColors = function (value, options, e, menu, node) {
|
||||
const r = onMenuNodeColors.apply(this, arguments);
|
||||
|
||||
// Only add custom options if enabled
|
||||
if (!isEnabled()) return r;
|
||||
|
||||
const settings = getSettings();
|
||||
|
||||
requestAnimationFrame(() => {
|
||||
const menus = document.querySelectorAll(".litecontextmenu");
|
||||
for (let i = menus.length - 1; i >= 0; i--) {
|
||||
if (menus[i].firstElementChild.textContent.includes("No color") ||
|
||||
menus[i].firstElementChild.value?.content?.includes("No color")) {
|
||||
|
||||
// Add Custom Full option
|
||||
if (settings.showFull) {
|
||||
$el(
|
||||
"div.litemenu-entry.submenu",
|
||||
{
|
||||
parent: menus[i],
|
||||
$: (el) => {
|
||||
el.onclick = () => {
|
||||
LiteGraph.closeAllContextMenus();
|
||||
if (!pickerFull) {
|
||||
pickerFull = createPicker('full');
|
||||
}
|
||||
activeNode = null;
|
||||
pickerFull.value = node.bgcolor || "#000000";
|
||||
activeNode = node;
|
||||
pickerFull.click();
|
||||
};
|
||||
},
|
||||
},
|
||||
[
|
||||
$el("span", {
|
||||
style: {
|
||||
paddingLeft: "4px",
|
||||
display: "block",
|
||||
},
|
||||
textContent: "🫶 Custom Full",
|
||||
}),
|
||||
]
|
||||
);
|
||||
}
|
||||
|
||||
// Add Custom Title option
|
||||
if (settings.showTitle) {
|
||||
$el(
|
||||
"div.litemenu-entry.submenu",
|
||||
{
|
||||
parent: menus[i],
|
||||
$: (el) => {
|
||||
el.onclick = () => {
|
||||
LiteGraph.closeAllContextMenus();
|
||||
if (!pickerTitle) {
|
||||
pickerTitle = createPicker('title');
|
||||
}
|
||||
activeNode = null;
|
||||
pickerTitle.value = node.color || "#000000";
|
||||
activeNode = node;
|
||||
pickerTitle.click();
|
||||
};
|
||||
},
|
||||
},
|
||||
[
|
||||
$el("span", {
|
||||
style: {
|
||||
paddingLeft: "4px",
|
||||
display: "block",
|
||||
},
|
||||
textContent: "🫶 Custom Title",
|
||||
}),
|
||||
]
|
||||
);
|
||||
}
|
||||
|
||||
// Add Custom BG option
|
||||
if (settings.showBG) {
|
||||
$el(
|
||||
"div.litemenu-entry.submenu",
|
||||
{
|
||||
parent: menus[i],
|
||||
$: (el) => {
|
||||
el.onclick = () => {
|
||||
LiteGraph.closeAllContextMenus();
|
||||
if (!pickerBG) {
|
||||
pickerBG = createPicker('bg');
|
||||
}
|
||||
activeNode = null;
|
||||
pickerBG.value = node.bgcolor || "#000000";
|
||||
activeNode = node;
|
||||
pickerBG.click();
|
||||
};
|
||||
},
|
||||
},
|
||||
[
|
||||
$el("span", {
|
||||
style: {
|
||||
paddingLeft: "4px",
|
||||
display: "block",
|
||||
},
|
||||
textContent: "🫶 Custom BG",
|
||||
}),
|
||||
]
|
||||
);
|
||||
}
|
||||
|
||||
break;
|
||||
}
|
||||
}
|
||||
});
|
||||
return r;
|
||||
};
|
||||
},
|
||||
});
|
||||
@@ -0,0 +1,157 @@
|
||||
import { app } from "../../scripts/app.js";
|
||||
import { api } from "../../scripts/api.js";
|
||||
|
||||
// Adds follow execution feature when enabled in settings
|
||||
// Adds menu options to toggle follow execution and go to executing node
|
||||
|
||||
app.registerExtension({
|
||||
name: "kikotools.followExecution",
|
||||
async init() {
|
||||
// Register settings in ComfyUI's settings panel
|
||||
app.ui.settings.addSetting({
|
||||
id: "kikotools.follow_execution.enabled",
|
||||
name: "🫶 Follow Execution: Enable",
|
||||
type: "boolean",
|
||||
defaultValue: false,
|
||||
tooltip: "Enable follow execution feature in canvas right-click menu",
|
||||
});
|
||||
|
||||
app.ui.settings.addSetting({
|
||||
id: "kikotools.follow_execution.show_goto_node",
|
||||
name: "🫶 Follow Execution: Show 'Go to node' menu",
|
||||
type: "boolean",
|
||||
defaultValue: true,
|
||||
tooltip: "Show 'Go to node' submenu in canvas menu",
|
||||
});
|
||||
|
||||
app.ui.settings.addSetting({
|
||||
id: "kikotools.follow_execution.auto_start",
|
||||
name: "🫶 Follow Execution: Auto-start",
|
||||
type: "boolean",
|
||||
defaultValue: false,
|
||||
tooltip: "Automatically start following execution when workflow starts",
|
||||
});
|
||||
},
|
||||
|
||||
async setup() {
|
||||
let followExecution = false;
|
||||
let isEnabled = false;
|
||||
|
||||
// Check if the feature is enabled in settings
|
||||
const checkEnabled = () => {
|
||||
const setting = app.ui.settings.getSettingValue("kikotools.follow_execution.enabled");
|
||||
isEnabled = setting !== undefined ? setting : false;
|
||||
|
||||
// If disabled, turn off follow execution
|
||||
if (!isEnabled && followExecution) {
|
||||
followExecution = false;
|
||||
}
|
||||
};
|
||||
|
||||
// Check for auto-start setting
|
||||
const checkAutoStart = () => {
|
||||
const autoStart = app.ui.settings.getSettingValue("kikotools.follow_execution.auto_start");
|
||||
if (autoStart && isEnabled) {
|
||||
followExecution = true;
|
||||
}
|
||||
};
|
||||
|
||||
// Initialize settings on startup
|
||||
checkEnabled();
|
||||
checkAutoStart();
|
||||
|
||||
// Center on the executing node
|
||||
const centerNode = (id) => {
|
||||
if (!followExecution || !id || !isEnabled) return;
|
||||
const node = app.graph.getNodeById(id);
|
||||
if (!node) return;
|
||||
app.canvas.centerOnNode(node);
|
||||
};
|
||||
|
||||
// Listen for execution events
|
||||
api.addEventListener("executing", ({ detail }) => centerNode(detail));
|
||||
|
||||
// Listen for execution start to handle auto-start
|
||||
api.addEventListener("execution_start", () => {
|
||||
checkEnabled();
|
||||
checkAutoStart();
|
||||
});
|
||||
|
||||
// Extend canvas menu options
|
||||
const orig = LGraphCanvas.prototype.getCanvasMenuOptions;
|
||||
LGraphCanvas.prototype.getCanvasMenuOptions = function () {
|
||||
const options = orig.apply(this, arguments);
|
||||
|
||||
// Check if feature is enabled before adding menu items
|
||||
checkEnabled();
|
||||
if (!isEnabled) return options;
|
||||
|
||||
// Add separator
|
||||
options.push(null);
|
||||
|
||||
// Add follow execution toggle
|
||||
options.push({
|
||||
content: followExecution ? "🫶 Stop following execution" : "🫶 Follow execution",
|
||||
callback: () => {
|
||||
followExecution = !followExecution;
|
||||
if (followExecution) {
|
||||
centerNode(app.runningNodeId);
|
||||
}
|
||||
},
|
||||
});
|
||||
|
||||
// Add go to executing node option if a node is currently executing
|
||||
if (app.runningNodeId) {
|
||||
options.push({
|
||||
content: "🫶 Show executing node",
|
||||
callback: () => {
|
||||
const node = app.graph.getNodeById(app.runningNodeId);
|
||||
if (!node) return;
|
||||
app.canvas.centerOnNode(node);
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
// Add go to node by type submenu
|
||||
const showGoToNode = app.ui.settings.getSettingValue("kikotools.follow_execution.show_goto_node");
|
||||
if (showGoToNode !== false) { // Default to true if not set
|
||||
const nodes = app.graph._nodes;
|
||||
const types = nodes.reduce((p, n) => {
|
||||
if (n.type in p) {
|
||||
p[n.type].push(n);
|
||||
} else {
|
||||
p[n.type] = [n];
|
||||
}
|
||||
return p;
|
||||
}, {});
|
||||
|
||||
options.push({
|
||||
content: "🫶 Go to node",
|
||||
has_submenu: true,
|
||||
submenu: {
|
||||
options: Object.keys(types)
|
||||
.sort()
|
||||
.map((t) => ({
|
||||
content: t,
|
||||
has_submenu: true,
|
||||
submenu: {
|
||||
options: types[t]
|
||||
.sort((a, b) => {
|
||||
return a.pos[0] - b.pos[0];
|
||||
})
|
||||
.map((n) => ({
|
||||
content: `${n.getTitle()} - #${n.id} (${Math.round(n.pos[0])}, ${Math.round(n.pos[1])})`,
|
||||
callback: () => {
|
||||
app.canvas.centerOnNode(n);
|
||||
},
|
||||
})),
|
||||
},
|
||||
})),
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
return options;
|
||||
};
|
||||
},
|
||||
});
|
||||
Reference in New Issue
Block a user