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Add Copilot instructions for efficiency-nodes-comfyui
Co-authored-by: jags111 <5968619+jags111@users.noreply.github.com>
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# Copilot Instructions for Efficiency Nodes ComfyUI
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## Repository Overview
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This repository provides custom efficiency nodes for [ComfyUI](https://github.com/comfyanonymous/ComfyUI), a powerful node-based UI for Stable Diffusion. The nodes streamline workflows by combining multiple operations into efficient, cached, and preview-enabled nodes.
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## Project Structure
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- **`efficiency_nodes.py`**: Main file containing all 45+ node class definitions (4,464 lines)
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- **`tsc_utils.py`**: Utility functions for caching, tensor operations, and console messaging
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- **`__init__.py`**: Entry point that exports NODE_CLASS_MAPPINGS for ComfyUI
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- **`py/`**: Specialized modules for upscaling, sampling, encoding, and tiling
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- **`node_settings.json`**: Configuration for model caching behavior
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- **`requirements.txt`**: Python dependencies (clip-interrogator, simpleeval)
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## Core Architecture
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### Node Pattern
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All custom nodes follow the ComfyUI standard structure:
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```python
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class TSC_NodeName:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {...}, # Required inputs
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"optional": {...}, # Optional inputs
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"hidden": {...} # Hidden inputs (UNIQUE_ID, PROMPT)
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}
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RETURN_TYPES = ("TYPE1", "TYPE2")
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RETURN_NAMES = ("output1", "output2")
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FUNCTION = "method_name"
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CATEGORY = "Efficiency Nodes/SubCategory"
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def method_name(self, **kwargs):
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# Node logic here
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return (result1, result2)
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```
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### Naming Conventions
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- **Classes**: Use `TSC_` prefix (creator's initials) + descriptive name in PascalCase
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- Examples: `TSC_EfficientLoader`, `TSC_KSampler`, `TSC_XYplot`
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- **Methods**: Use snake_case for all methods
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- **Constants**: Use UPPER_SNAKE_CASE for module-level constants
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### Custom Data Types
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The repository defines several custom types for workflow composition:
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- `LORA_STACK`: Tuple for stacking multiple LoRA models
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- `CONTROL_NET_STACK`: Tuple for stacking ControlNet configurations
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- `SCRIPT`: Type for chaining script operations (XY Plot, HighRes-Fix, etc.)
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- `XY`: Type for XY plot data
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- `SDXL_TUPLE`: SDXL-specific configuration tuple
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## Key Patterns
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### 1. Wrapper Pattern
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Efficiency nodes wrap base ComfyUI nodes to add features:
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```python
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# Wraps KSampler with caching, preview, and script support
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class TSC_KSampler:
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def sample(self, ...):
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# Check cache
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# Execute base KSampler
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# Store results
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# Handle script execution
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# Return enhanced output
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```
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### 2. Caching System
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Use the caching utilities from `tsc_utils.py`:
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```python
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from tsc_utils import load_ksampler_results, store_ksampler_results
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# Load cached results
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cached = load_ksampler_results(unique_id, prompt)
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# Store results for future use
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store_ksampler_results(unique_id, prompt, results)
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```
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**Important**: Cache operations use `unique_id` and `prompt` from hidden inputs to ensure per-instance caching.
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### 3. Stack Pattern
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Support stacking for composable workflows:
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```python
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"optional": {
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"lora_stack": ("LORA_STACK",),
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"cnet_stack": ("CONTROL_NET_STACK",),
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}
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```
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### 4. Script System
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Nodes can execute scripts for advanced workflows:
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```python
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"optional": {
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"script": ("SCRIPT",),
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}
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# In node execution:
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if script:
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# Execute script logic (XY Plot, HighRes-Fix, etc.)
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```
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### 5. Dynamic UI Inputs
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Use `folder_paths` for dynamic dropdown population:
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```python
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import folder_paths
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"required": {
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"ckpt_name": (folder_paths.get_filename_list("checkpoints"),),
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"vae_name": (["Baked VAE"] + folder_paths.get_filename_list("vae"),),
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}
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```
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## Dependencies
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### Required
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- **PyTorch**: Core tensor operations
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- **PIL**: Image processing
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- **NumPy**: Array operations
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- **clip-interrogator**: Image captioning
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- **simpleeval**: Safe expression evaluation
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### ComfyUI Integration
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The code integrates with ComfyUI via `sys.path` manipulation:
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```python
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# Pattern used throughout codebase
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comfy_dir = os.path.abspath(os.path.join(my_dir, '..', '..'))
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sys.path.append(comfy_dir)
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from comfy import samplers, sd, utils
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# ... imports ...
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sys.path.remove(comfy_dir)
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```
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### Optional Dependencies
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- **comfyui_controlnet_aux**: ControlNet preprocessing
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- **ComfyUI-AnimateDiff-Evolved**: AnimateDiff support
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Handle optional dependencies gracefully:
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```python
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try:
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import optional_module
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NODE_CLASS_MAPPINGS.update({"Node Name": NodeClass})
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except ImportError:
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pass
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```
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## Node Registration
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Nodes are registered in `NODE_CLASS_MAPPINGS` dictionary:
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```python
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NODE_CLASS_MAPPINGS = {
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"Display Name": TSC_ClassName,
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"KSampler (Efficient)": TSC_KSampler,
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"Efficient Loader": TSC_EfficientLoader,
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# ... more nodes
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}
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# Optional nodes added conditionally
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try:
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from simpleeval import simple_eval
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NODE_CLASS_MAPPINGS.update({
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"Simple Eval Examples": TSC_SimpleEval,
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})
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except ImportError:
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print("simpleeval not installed, skipping related nodes")
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```
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## Code Style Guidelines
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### Imports
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1. Standard library imports first
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2. Third-party imports (torch, PIL, numpy)
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3. ComfyUI imports (with path manipulation)
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4. Local imports (tsc_utils, py modules)
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### Error Handling
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Use the colored messaging functions from `tsc_utils.py`:
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```python
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from tsc_utils import error, warning, success
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try:
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# Operation
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success("Operation completed")
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except Exception as e:
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error(f"Operation failed: {e}")
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```
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### Input Validation
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Validate inputs in the INPUT_TYPES definition:
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```python
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"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
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"steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
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"cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}),
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"sampler_name": (comfy.samplers.KSampler.SAMPLERS,),
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```
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## Testing and Validation
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This repository does not have formal unit tests. Changes should be validated by:
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1. **Import Test**: Verify `__init__.py` imports successfully
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2. **ComfyUI Integration**: Load nodes in ComfyUI UI and verify they appear
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3. **Workflow Test**: Create test workflows and verify node functionality
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4. **Error Testing**: Test edge cases and ensure graceful error messages
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## Common Patterns to Follow
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### Adding a New Node
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1. Create class with `TSC_` prefix
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2. Define `INPUT_TYPES`, `RETURN_TYPES`, `FUNCTION`, `CATEGORY`
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3. Implement the function method
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4. Add to `NODE_CLASS_MAPPINGS`
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5. Test in ComfyUI workflow
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### Adding Optional Features
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1. Wrap in try/except for dependency checking
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2. Use `.update()` to add to NODE_CLASS_MAPPINGS
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3. Provide fallback or skip if dependency missing
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4. Print informative message about missing dependency
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### Working with Models
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1. Use `folder_paths` for model discovery
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2. Implement caching via `tsc_utils` functions
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3. Store loaded models in `loaded_objects` dict with unique IDs
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4. Handle model loading errors gracefully
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### Handling UI Updates
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1. Use hidden inputs for `UNIQUE_ID` and `PROMPT` tracking
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2. Return UI update dictionaries when needed
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3. Follow ComfyUI's output format for preview images
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## Performance Considerations
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- **Caching**: Always use caching for expensive operations (model loading, sampling)
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- **Memory**: Be mindful of GPU memory with large models
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- **Preview**: Implement progressive preview for long operations
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- **Batching**: Support batch processing where applicable
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## Documentation
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- Update README.md for new nodes
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- Add examples to the [project Wiki](https://github.com/jags111/efficiency-nodes-comfyui/wiki)
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- Include workflow JSON examples for complex nodes
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- Document any new configuration options in `node_settings.json`
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## Key Files to Understand
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1. **efficiency_nodes.py**: Study existing nodes for patterns
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2. **tsc_utils.py**: Understand caching and utility functions
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3. **py/bnk_adv_encode.py**: Advanced CLIP encoding examples
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4. **py/smZ_cfg_denoiser.py**: Custom denoiser implementation
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5. **__init__.py**: Entry point and version management
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## ComfyUI-Specific Tips
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- Nodes are instantiated fresh for each workflow execution
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- Use `UNIQUE_ID` from hidden inputs for per-node-instance state
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- `PROMPT` contains the full workflow graph
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- Return types must match RETURN_TYPES exactly
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- UI widgets are defined in INPUT_TYPES with tuples
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- Use `folder_paths` for discovering models/resources
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## Version Information
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- Current version: 2.0+ (see `CC_VERSION` in `__init__.py`)
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- Published to ComfyUI registry via `pyproject.toml`
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- Auto-publishes on main branch when `pyproject.toml` changes
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## Resources
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- [ComfyUI Repository](https://github.com/comfyanonymous/ComfyUI)
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- [Project Wiki](https://github.com/jags111/efficiency-nodes-comfyui/wiki)
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- [Project README](../README.md)
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- Original author: Luciano Cirino (TSC)
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- Current maintainer: jags111
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