docs: add comprehensive plan.md for session recovery

- Document all completed XYZ Grid node work
- List current issues and pending fixes
- Include technical patterns and code examples
- Add testing instructions and debug points
- Provide git commands for session recovery

.flake8

@@ -0,0 +1,35 @@
+[flake8]
+max-line-length = 127
+max-complexity = 10
+exclude = 
+    .git,
+    __pycache__,
+    .mypy_cache,
+    .pytest_cache,
+    venv,
+    env,
+    build,
+    dist,
+    *.egg-info,
+    .tox
+ignore = 
+    # W503: line break before binary operator (conflicts with Black)
+    W503,
+    # E203: whitespace before ':' (conflicts with Black)
+    E203,
+    # E501: line too long (we use max-line-length)
+    E501
+
+per-file-ignores =
+    # Allow unused imports in __init__.py files
+    __init__.py:F401,F403
+    # Allow assertions in tests
+    tests/*:S101
+    # Allow higher complexity for Gemini prompt module
+    kikotools/tools/gemini_prompt/logic.py:C901
+    kikotools/tools/gemini_prompt/models.py:C901
+    kikotools/tools/gemini_prompt/node.py:C901
+
+# Statistics
+count = True
+statistics = True

.gitattributes

@@ -0,0 +1,41 @@
+# Auto detect text files and perform LF normalization
+* text=auto
+
+# Python files
+*.py text eol=lf
+*.pyi text eol=lf
+
+# Configuration files
+*.json text eol=lf
+*.yaml text eol=lf
+*.yml text eol=lf
+*.toml text eol=lf
+*.ini text eol=lf
+*.cfg text eol=lf
+
+# Documentation
+*.md text eol=lf
+*.rst text eol=lf
+*.txt text eol=lf
+
+# Scripts
+*.sh text eol=lf
+*.bash text eol=lf
+
+# Git files
+.gitignore text eol=lf
+.gitattributes text eol=lf
+
+# ComfyUI specific
+*.workflow text eol=lf
+
+# Binary files
+*.png binary
+*.jpg binary
+*.jpeg binary
+*.gif binary
+*.webp binary
+*.safetensors binary
+*.ckpt binary
+*.pt binary
+*.pth binary

.github/ISSUE_TEMPLATE/bug_report.md

@@ -45,4 +45,4 @@ Paste any error messages or stack traces here
 If possible, attach the ComfyUI workflow file (.json) that reproduces the issue.
 
 **Additional context**
-Add any other context about the problem here.
+Add any other context about the problem here.

.github/ISSUE_TEMPLATE/feature_request.md

@@ -37,7 +37,7 @@ Describe how the tool should process inputs and generate outputs.
 
 **Model Compatibility:**
 - [ ] SDXL optimized
-- [ ] FLUX optimized  
+- [ ] FLUX optimized
 - [ ] General purpose
 - [ ] Specific model requirements: [describe]
 
@@ -64,4 +64,4 @@ Are there existing ComfyUI nodes that do something similar? How would this be di
 - [ ] Yes, I can help with implementation
 - [ ] Yes, I can help with testing
 - [ ] Yes, I can help with documentation
-- [ ] No, but I'd be happy to test it
+- [ ] No, but I'd be happy to test it

.github/dependabot.yml

@@ -0,0 +1,10 @@
+version: 2
+updates:
+  - package-ecosystem: "pip"
+    directory: "/"
+    schedule:
+      interval: "weekly"
+  - package-ecosystem: "github-actions"
+    directory: "/"
+    schedule:
+      interval: "weekly"

.github/workflows/code-quality.yml

@@ -1,4 +1,6 @@
 name: Code Quality
+permissions:
+  contents: read
 
 on:
   push:
@@ -14,12 +16,12 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Set up Python 3.10
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.10'
 
     - name: Cache pip dependencies
-      uses: actions/cache@v3
+      uses: actions/cache@v4
       with:
         path: ~/.cache/pip
         key: ${{ runner.os }}-pip-quality-${{ hashFiles('**/requirements-dev.txt') }}
@@ -59,7 +61,7 @@ jobs:
         import sys
         import os
         sys.path.insert(0, os.getcwd())
-        
+
         # Test that all imports work correctly
         try:
             from kikotools import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
@@ -67,47 +69,64 @@ jobs:
         except ImportError as e:
             print(f'Warning: Package-level imports failed: {e}')
             # This is expected since we don't have ComfyUI installed
-        
+
         # Test individual module imports
         from kikotools.base import ComfyAssetsBaseNode
         from kikotools.tools.resolution_calculator import ResolutionCalculatorNode
         from kikotools.tools.resolution_calculator.logic import extract_dimensions
         from kikotools.tools.resolution_calculator.node import ResolutionCalculatorNode as NodeClass
-        
+
+        # Test Width Height Selector imports
+        from kikotools.tools.width_height_selector import WidthHeightSelectorNode
+        from kikotools.tools.width_height_selector.logic import get_preset_dimensions
+        from kikotools.tools.width_height_selector.presets import PRESET_OPTIONS, PRESET_METADATA
+
+        # Test Sampler Combo imports
+        from kikotools.tools.sampler_combo import SamplerComboNode
+        from kikotools.tools.sampler_combo.logic import get_sampler_combo, SAMPLERS, SCHEDULERS
+
+        # Test Seed History imports
+        from kikotools.tools.seed_history import SeedHistoryNode
+        from kikotools.tools.seed_history.logic import generate_random_seed, validate_seed_value
+
+        # Test Kiko Save Image imports
+        from kikotools.tools.kiko_save_image import KikoSaveImageNode
+        from kikotools.tools.kiko_save_image.logic import process_image_batch, validate_save_inputs
+
         print('✓ All module imports successful')
         "
 
     - name: Check code style consistency
       run: |
         echo "Checking code style consistency..."
-        
+
         # Check for consistent naming
         find kikotools/ -name "*.py" -exec grep -l "class.*Node" {} \; | while read file; do
           if ! grep -q "ComfyAssetsBaseNode" "$file" && ! grep -q "class ComfyAssetsBaseNode" "$file"; then
             echo "Checking $file for ComfyUI node inheritance..."
           fi
         done
-        
+
         # Check for proper docstrings
         python -c "
         import ast
         import os
-        
+
         def check_docstrings(filepath):
             with open(filepath, 'r') as f:
                 tree = ast.parse(f.read())
-            
+
             for node in ast.walk(tree):
                 if isinstance(node, (ast.FunctionDef, ast.ClassDef)):
                     if not ast.get_docstring(node) and not node.name.startswith('_'):
                         print(f'Warning: {filepath}:{node.lineno} - {node.name} missing docstring')
-        
+
         for root, dirs, files in os.walk('kikotools'):
             for file in files:
                 if file.endswith('.py') and not file.startswith('__'):
                     filepath = os.path.join(root, file)
                     check_docstrings(filepath)
-        
+
         print('✓ Docstring check completed')
         "
 
@@ -117,7 +136,7 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Set up Python 3.10
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.10'
 
@@ -134,7 +153,7 @@ jobs:
     - name: Check for hardcoded secrets
       run: |
         echo "Checking for potential secrets..."
-        
+
         # Check for common secret patterns
         if grep -r -i "password\|secret\|key\|token" kikotools/ --include="*.py" | grep -v "# " | grep -v "def " | grep -v "class "; then
           echo "Warning: Potential hardcoded secrets found"
@@ -148,7 +167,7 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Set up Python 3.10
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.10'
 
@@ -163,61 +182,126 @@ jobs:
         import sys
         import os
         sys.path.insert(0, os.getcwd())
-        
+
         print('Checking architecture compliance...')
-        
+
         # Test separation of concerns
         from kikotools.tools.resolution_calculator import logic, node
-        
+
         # Logic module should not import node-specific things
         import inspect
         logic_source = inspect.getsource(logic)
-        
+
         if 'ComfyUI' in logic_source and 'INPUT_TYPES' not in logic_source:
             print('⚠️  Warning: Logic module contains ComfyUI-specific code')
         else:
             print('✓ Logic module properly separated')
-        
+
         # Node module should inherit from base
         from kikotools.tools.resolution_calculator.node import ResolutionCalculatorNode
         from kikotools.base import ComfyAssetsBaseNode
-        
+
         if issubclass(ResolutionCalculatorNode, ComfyAssetsBaseNode):
             print('✓ Node properly inherits from base class')
         else:
             print('❌ Node does not inherit from base class')
             sys.exit(1)
-        
+
         # Check that nodes have proper ComfyUI interface
         required_attrs = ['INPUT_TYPES', 'RETURN_TYPES', 'RETURN_NAMES', 'FUNCTION', 'CATEGORY']
+
+        # Test Resolution Calculator Node
         for attr in required_attrs:
             if not hasattr(ResolutionCalculatorNode, attr):
-                print(f'❌ Node missing required attribute: {attr}')
+                print(f'❌ ResolutionCalculatorNode missing required attribute: {attr}')
                 sys.exit(1)
-        
-        print('✓ All architecture checks passed')
+
+        # Test Width Height Selector Node
+        from kikotools.tools.width_height_selector.node import WidthHeightSelectorNode
+
+        if issubclass(WidthHeightSelectorNode, ComfyAssetsBaseNode):
+            print('✓ WidthHeightSelectorNode properly inherits from base class')
+        else:
+            print('❌ WidthHeightSelectorNode does not inherit from base class')
+            sys.exit(1)
+
+        for attr in required_attrs:
+            if not hasattr(WidthHeightSelectorNode, attr):
+                print(f'❌ WidthHeightSelectorNode missing required attribute: {attr}')
+                sys.exit(1)
+
+        # Test Sampler Combo Node
+        from kikotools.tools.sampler_combo.node import SamplerComboNode
+
+        if issubclass(SamplerComboNode, ComfyAssetsBaseNode):
+            print('✓ SamplerComboNode properly inherits from base class')
+        else:
+            print('❌ SamplerComboNode does not inherit from base class')
+            sys.exit(1)
+
+        for attr in required_attrs:
+            if not hasattr(SamplerComboNode, attr):
+                print(f'❌ SamplerComboNode missing required attribute: {attr}')
+                sys.exit(1)
+
+        # Test Seed History Node
+        from kikotools.tools.seed_history.node import SeedHistoryNode
+
+        if issubclass(SeedHistoryNode, ComfyAssetsBaseNode):
+            print('✓ SeedHistoryNode properly inherits from base class')
+        else:
+            print('❌ SeedHistoryNode does not inherit from base class')
+            sys.exit(1)
+
+        for attr in required_attrs:
+            if not hasattr(SeedHistoryNode, attr):
+                print(f'❌ SeedHistoryNode missing required attribute: {attr}')
+                sys.exit(1)
+
+        # Test Kiko Save Image Node
+        from kikotools.tools.kiko_save_image.node import KikoSaveImageNode
+
+        if issubclass(KikoSaveImageNode, ComfyAssetsBaseNode):
+            print('✓ KikoSaveImageNode properly inherits from base class')
+        else:
+            print('❌ KikoSaveImageNode does not inherit from base class')
+            sys.exit(1)
+
+        # KikoSaveImage is an output node, so it doesn't have RETURN_TYPES/RETURN_NAMES
+        save_required_attrs = ['INPUT_TYPES', 'FUNCTION', 'CATEGORY']
+        for attr in save_required_attrs:
+            if not hasattr(KikoSaveImageNode, attr):
+                print(f'❌ KikoSaveImageNode missing required attribute: {attr}')
+                sys.exit(1)
+
+        # Check that it's properly marked as an output node
+        if not hasattr(KikoSaveImageNode, 'OUTPUT_NODE') or not KikoSaveImageNode.OUTPUT_NODE:
+            print('❌ KikoSaveImageNode missing OUTPUT_NODE = True')
+            sys.exit(1)
+
+        print('✓ All architecture checks passed for all tools')
         "
 
     - name: Check test coverage expectations
       run: |
         python -c "
         import os
-        
+
         # Count test files vs implementation files
         test_files = 0
         impl_files = 0
-        
+
         for root, dirs, files in os.walk('tests'):
             test_files += len([f for f in files if f.startswith('test_') and f.endswith('.py')])
-        
+
         for root, dirs, files in os.walk('kikotools'):
             impl_files += len([f for f in files if f.endswith('.py') and not f.startswith('__')])
-        
+
         print(f'Implementation files: {impl_files}')
         print(f'Test files: {test_files}')
-        
+
         if test_files >= impl_files * 0.5:  # At least 50% test coverage by file count
             print('✓ Adequate test file coverage')
         else:
             print('⚠️  Warning: Low test file coverage')
-        "
+        "

.github/workflows/publish.yml

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

.github/workflows/release.yml

@@ -1,5 +1,8 @@
 name: Release
 
+permissions:
+  contents: read
+
 on:
   push:
     tags:
@@ -8,12 +11,14 @@ on:
 jobs:
   create-release:
     runs-on: ubuntu-latest
-    
+    permissions:
+      contents: write
+
     steps:
     - uses: actions/checkout@v4
 
     - name: Set up Python 3.10
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.10'
 
@@ -28,30 +33,30 @@ jobs:
         import sys
         import os
         sys.path.insert(0, os.getcwd())
-        
+
         # Run comprehensive tests before release
         from kikotools.base import ComfyAssetsBaseNode
         from kikotools.tools.resolution_calculator.logic import extract_dimensions, calculate_scaled_dimensions
         from kikotools.tools.resolution_calculator.node import ResolutionCalculatorNode
         import torch
-        
+
         print('Running pre-release validation...')
-        
+
         # Test all major functionality
         node = ResolutionCalculatorNode()
-        
+
         # Test various scenarios
         test_cases = [
             (torch.randn(1, 512, 512, 3), 2.0),
             (torch.randn(1, 1024, 1024, 3), 1.5),
             (torch.randn(1, 1216, 832, 3), 1.53),  # User scenario
         ]
-        
+
         for i, (image, scale) in enumerate(test_cases):
             width, height = node.calculate_resolution(scale, image=image)
             print(f'✓ Test case {i+1}: {image.shape[2]}×{image.shape[1]} → {width}×{height} (scale: {scale})')
             assert width % 8 == 0 and height % 8 == 0
-        
+
         print('🎉 All pre-release tests passed!')
         "
 
@@ -64,22 +69,22 @@ jobs:
       run: |
         cat > release_notes.md << 'EOF'
         ## ComfyUI-KikoTools ${{ steps.get_version.outputs.version }}
-        
+
         ### 🎉 What's New
-        
+
         #### Resolution Calculator Tool
         - **Smart Input Handling**: Works with both IMAGE and LATENT tensors
-        - **Model Optimized**: Specific optimizations for SDXL and FLUX models  
+        - **Model Optimized**: Specific optimizations for SDXL and FLUX models
         - **Constraint Enforcement**: Automatically ensures dimensions divisible by 8
         - **Flexible Scaling**: Supports scale factors from 1.0x to 8.0x
-        
+
         ### 📦 Installation
-        
+
         #### ComfyUI Manager
         1. Search for "ComfyUI-KikoTools"
         2. Click Install
         3. Restart ComfyUI
-        
+
         #### Manual Installation
         ```bash
         cd ComfyUI/custom_nodes/
@@ -87,29 +92,29 @@ jobs:
         cd ComfyUI-KikoTools
         pip install -r requirements-dev.txt
         ```
-        
+
         ### 🚀 Quick Start
-        
+
         Look for **ComfyAssets** nodes in your ComfyUI node browser!
-        
+
         ### 📊 Technical Details
-        
+
         - **Nodes**: 1 (Resolution Calculator)
         - **Test Coverage**: 100%
         - **Python Support**: 3.8+
         - **ComfyUI Compatibility**: Latest
-        
+
         ### 🐛 Bug Reports
-        
+
         Found an issue? Please report it [here](https://github.com/ComfyAssets/ComfyUI-KikoTools/issues).
-        
+
         ---
-        
+
         **Full Changelog**: https://github.com/ComfyAssets/ComfyUI-KikoTools/compare/v0.0.0...${{ steps.get_version.outputs.version }}
         EOF
 
     - name: Create GitHub Release
-      uses: softprops/action-gh-release@v1
+      uses: softprops/action-gh-release@v2
       with:
         tag_name: ${{ steps.get_version.outputs.version }}
         name: ComfyUI-KikoTools ${{ steps.get_version.outputs.version }}
@@ -128,18 +133,18 @@ jobs:
     runs-on: ubuntu-latest
     needs: create-release
     if: success()
-    
+
     steps:
     - name: Community notification placeholder
       run: |
         echo "🎉 Release ${{ needs.create-release.outputs.version }} created!"
         echo "Consider posting to:"
         echo "- ComfyUI Discord"
-        echo "- Reddit r/ComfyUI"  
+        echo "- Reddit r/ComfyUI"
         echo "- ComfyUI-Manager database"
         echo ""
         echo "Release includes:"
         echo "- Resolution Calculator tool"
         echo "- Complete documentation"
         echo "- Example workflows"
-        echo "- 100% test coverage"
+        echo "- 100% test coverage"

.github/workflows/tests.yml

@@ -1,5 +1,8 @@
 name: Tests
 
+permissions:
+  contents: read
+
 on:
   push:
     branches: [main, develop]
@@ -17,12 +20,12 @@ jobs:
       - uses: actions/checkout@v4
 
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
 
       - name: Cache pip dependencies
-        uses: actions/cache@v3
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pip
           key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements-dev.txt') }}
@@ -78,67 +81,318 @@ jobs:
           print('🎉 All tests passed!')
           "
 
-      - name: Test error handling
+      - name: Test Width Height Selector
         run: |
           python -c "
           import sys
           import os
           sys.path.insert(0, os.getcwd())
 
-          from kikotools.tools.resolution_calculator.node import ResolutionCalculatorNode
+          # Test Width Height Selector imports
+          from kikotools.tools.width_height_selector.node import WidthHeightSelectorNode
+          from kikotools.tools.width_height_selector.presets import PRESET_OPTIONS, PRESET_METADATA
+          from kikotools.tools.width_height_selector.logic import get_preset_dimensions
 
-          node = ResolutionCalculatorNode()
+          print('✓ Width Height Selector imports successful')
 
-          # Test error handling
-          try:
-              node.calculate_resolution(2.0)  # No input provided
-              assert False, 'Should have raised ValueError'
-          except ValueError:
-              print('✓ Error handling test passed')
+          # Test preset structure
+          assert len(PRESET_OPTIONS) > 0
+          assert 'custom' in PRESET_OPTIONS
+          assert len(PRESET_METADATA) > 0
+          print('✓ Preset structure tests passed')
 
-          # Test invalid scale factor
-          try:
-              node.calculate_resolution(0.0)  # Invalid scale
-              assert False, 'Should have raised ValueError'
-          except ValueError:
-              print('✓ Scale factor validation test passed')
+          # Test node interface
+          node = WidthHeightSelectorNode()
+          input_types = node.INPUT_TYPES()
+          assert 'required' in input_types
+          assert 'preset' in input_types['required']
+          assert 'width' in input_types['required']
+          assert 'height' in input_types['required']
+          print('✓ Node interface tests passed')
 
-          print('✓ All error handling tests passed')
+          # Test formatted presets
+          preset_options = input_types['required']['preset'][0]
+          assert 'custom' in preset_options
+          formatted_count = len([opt for opt in preset_options if ' - ' in opt and 'MP' in opt])
+          assert formatted_count > 0
+          print(f'✓ Found {formatted_count} formatted presets')
+
+          # Test dimension calculation
+          result = node.get_dimensions('1024×1024', 512, 512)
+          assert result == (1024, 1024)
+          print('✓ Dimension calculation tests passed')
+
+          # Test formatted preset dimensions
+          formatted_preset = '1024×1024 - 1:1 (1.1MP) - SDXL'
+          result = node.get_dimensions(formatted_preset, 512, 512)
+          assert result == (1024, 1024)
+          print('✓ Formatted preset tests passed')
+
+          # Test preset extraction
+          extracted = node._extract_preset_name(formatted_preset)
+          assert extracted == '1024×1024'
+          print('✓ Preset extraction tests passed')
+
+          print('🎉 All Width Height Selector tests passed!')
           "
 
-      - name: Test ComfyUI integration readiness
+      - name: Test Sampler Combo
         run: |
           python -c "
           import sys
           import os
           sys.path.insert(0, os.getcwd())
 
+          # Test Sampler Combo imports
+          from kikotools.tools.sampler_combo.node import SamplerComboNode
+          from kikotools.tools.sampler_combo.logic import (
+              get_sampler_combo, validate_sampler_settings, SAMPLERS, SCHEDULERS
+          )
+
+          print('✓ Sampler Combo imports successful')
+
+          # Test node interface
+          node = SamplerComboNode()
+          input_types = node.INPUT_TYPES()
+          assert 'required' in input_types
+          assert 'sampler_name' in input_types['required']
+          assert 'scheduler' in input_types['required']
+          assert 'steps' in input_types['required']
+          assert 'cfg' in input_types['required']
+          print('✓ Sampler Combo interface tests passed')
+
+          # Test return types
+          assert node.RETURN_TYPES == ('SAMPLER', SCHEDULERS, 'INT', 'FLOAT')
+          assert node.RETURN_NAMES == ('sampler_name', 'scheduler', 'steps', 'cfg')
+          assert node.CATEGORY == 'ComfyAssets'
+          print('✓ Sampler Combo return types tests passed')
+
+          # Test sampler combo functionality
+          result = node.get_sampler_combo('euler', 'normal', 20, 7.0)
+          assert result == ('euler', 'normal', 20, 7.0)
+          print('✓ Sampler combo functionality tests passed')
+
+          # Test validation
+          assert validate_sampler_settings('euler', 'normal', 20, 7.0) == True
+          print('✓ Sampler validation tests passed')
+
+          # Test available samplers and schedulers
+          samplers = node.get_available_samplers()
+          schedulers = node.get_available_schedulers()
+          assert len(samplers) > 0
+          assert len(schedulers) > 0
+          assert 'euler' in samplers
+          assert 'normal' in schedulers
+          print(f'✓ Found {len(samplers)} samplers and {len(schedulers)} schedulers')
+
+          print('🎉 All Sampler Combo tests passed!')
+          "
+
+      - name: Test Seed History
+        run: |
+          python -c "
+          import sys
+          import os
+          sys.path.insert(0, os.getcwd())
+
+          # Test Seed History imports
+          from kikotools.tools.seed_history.node import SeedHistoryNode
+          from kikotools.tools.seed_history.logic import (
+              generate_random_seed, validate_seed_value, sanitize_seed_value
+          )
+
+          print('✓ Seed History imports successful')
+
+          # Test node interface
+          node = SeedHistoryNode()
+          input_types = node.INPUT_TYPES()
+          assert 'required' in input_types
+          assert 'seed' in input_types['required']
+          print('✓ Seed History interface tests passed')
+
+          # Test return types
+          assert node.RETURN_TYPES == ('INT',)
+          assert node.RETURN_NAMES == ('seed',)
+          assert node.CATEGORY == 'ComfyAssets'
+          print('✓ Seed History return types tests passed')
+
+          # Test seed output functionality
+          result = node.output_seed(12345)
+          assert result == (12345,)
+          print('✓ Seed output functionality tests passed')
+
+          # Test seed validation
+          assert validate_seed_value(12345) == True
+          assert validate_seed_value(-1) == False
+          print('✓ Seed validation tests passed')
+
+          # Test seed generation
+          new_seed = generate_random_seed()
+          assert isinstance(new_seed, int)
+          assert validate_seed_value(new_seed) == True
+          print('✓ Seed generation tests passed')
+
+          # Test seed sanitization
+          clean_seed = sanitize_seed_value(12345)
+          assert clean_seed == 12345
+          print('✓ Seed sanitization tests passed')
+
+          # Test node helper methods
+          assert node.is_seed_in_range(12345) == True
+          assert node.is_seed_in_range(-1) == False
+          assert node.get_default_seed() == 12345
+          print('✓ Seed helper methods tests passed')
+
+          print('🎉 All Seed History tests passed!')
+          "
+
+      - name: Test error handling for all tools
+        run: |
+          python -c "
+          import sys
+          import os
+          sys.path.insert(0, os.getcwd())
+
+          print('=== Testing Error Handling for All Tools ===')
+
+          # Test Resolution Calculator error handling
           from kikotools.tools.resolution_calculator.node import ResolutionCalculatorNode
+          res_node = ResolutionCalculatorNode()
 
-          # Test ComfyUI interface requirements
-          node_class = ResolutionCalculatorNode
+          try:
+              res_node.calculate_resolution(2.0)  # No input provided
+              assert False, 'Should have raised ValueError'
+          except ValueError:
+              print('✓ Resolution Calculator error handling test passed')
 
-          # Check required class attributes
-          assert hasattr(node_class, 'INPUT_TYPES')
-          assert hasattr(node_class, 'RETURN_TYPES')
-          assert hasattr(node_class, 'RETURN_NAMES')
-          assert hasattr(node_class, 'FUNCTION')
-          assert hasattr(node_class, 'CATEGORY')
+          try:
+              res_node.calculate_resolution(0.0)  # Invalid scale
+              assert False, 'Should have raised ValueError'
+          except ValueError:
+              print('✓ Resolution Calculator scale factor validation test passed')
 
-          # Check INPUT_TYPES structure
-          input_types = node_class.INPUT_TYPES()
+          # Test Width Height Selector error handling
+          from kikotools.tools.width_height_selector.node import WidthHeightSelectorNode
+          wh_node = WidthHeightSelectorNode()
+
+          # Test invalid preset fallback
+          result = wh_node.get_dimensions('invalid_preset', 800, 600)
+          assert result == (800, 600)  # Should fallback to custom dimensions
+          print('✓ Width Height Selector invalid preset handling test passed')
+
+          # Test Sampler Combo error handling
+          from kikotools.tools.sampler_combo.node import SamplerComboNode
+          sampler_node = SamplerComboNode()
+
+          # Test with invalid sampler (should use safe defaults)
+          result = sampler_node.get_sampler_combo('invalid_sampler', 'normal', 20, 7.0)
+          assert result == ('euler', 'normal', 20, 7.0)  # Safe defaults
+          print('✓ Sampler Combo invalid input handling test passed')
+
+          # Test Seed History error handling
+          from kikotools.tools.seed_history.node import SeedHistoryNode
+          seed_node = SeedHistoryNode()
+
+          # Test invalid seed value (should use fallback)
+          result = seed_node.output_seed(-1)  # Invalid negative seed
+          assert result == (12345,)  # Fallback seed
+          print('✓ Seed History invalid seed handling test passed')
+
+          print('🎉 All error handling tests passed for all tools!')
+          "
+
+      - name: Test ComfyUI integration readiness for all tools
+        run: |
+          python -c "
+          import sys
+          import os
+          sys.path.insert(0, os.getcwd())
+
+          print('=== Testing ComfyUI Integration for All Tools ===')
+
+          # Test Resolution Calculator
+          from kikotools.tools.resolution_calculator.node import ResolutionCalculatorNode
+          res_class = ResolutionCalculatorNode
+
+          assert hasattr(res_class, 'INPUT_TYPES')
+          assert hasattr(res_class, 'RETURN_TYPES')
+          assert hasattr(res_class, 'RETURN_NAMES')
+          assert hasattr(res_class, 'FUNCTION')
+          assert hasattr(res_class, 'CATEGORY')
+
+          input_types = res_class.INPUT_TYPES()
           assert 'required' in input_types
           assert 'optional' in input_types
           assert 'scale_factor' in input_types['required']
           assert 'image' in input_types['optional']
           assert 'latent' in input_types['optional']
 
-          # Check return types
-          assert node_class.RETURN_TYPES == ('INT', 'INT')
-          assert node_class.RETURN_NAMES == ('width', 'height')
-          assert node_class.CATEGORY == 'ComfyAssets'
+          assert res_class.RETURN_TYPES == ('INT', 'INT')
+          assert res_class.RETURN_NAMES == ('width', 'height')
+          assert res_class.CATEGORY == 'ComfyAssets'
+          print('✓ Resolution Calculator ComfyUI integration passed')
 
-          print('✓ ComfyUI integration readiness tests passed')
+          # Test Width Height Selector
+          from kikotools.tools.width_height_selector.node import WidthHeightSelectorNode
+          wh_class = WidthHeightSelectorNode
+
+          assert hasattr(wh_class, 'INPUT_TYPES')
+          assert hasattr(wh_class, 'RETURN_TYPES')
+          assert hasattr(wh_class, 'RETURN_NAMES')
+          assert hasattr(wh_class, 'FUNCTION')
+          assert hasattr(wh_class, 'CATEGORY')
+
+          input_types = wh_class.INPUT_TYPES()
+          assert 'required' in input_types
+          assert 'preset' in input_types['required']
+          assert 'width' in input_types['required']
+          assert 'height' in input_types['required']
+
+          assert wh_class.RETURN_TYPES == ('INT', 'INT')
+          assert wh_class.RETURN_NAMES == ('width', 'height')
+          assert wh_class.CATEGORY == 'ComfyAssets'
+          print('✓ Width Height Selector ComfyUI integration passed')
+
+          # Test Sampler Combo
+          from kikotools.tools.sampler_combo.node import SamplerComboNode
+          sampler_class = SamplerComboNode
+
+          assert hasattr(sampler_class, 'INPUT_TYPES')
+          assert hasattr(sampler_class, 'RETURN_TYPES')
+          assert hasattr(sampler_class, 'RETURN_NAMES')
+          assert hasattr(sampler_class, 'FUNCTION')
+          assert hasattr(sampler_class, 'CATEGORY')
+
+          input_types = sampler_class.INPUT_TYPES()
+          assert 'required' in input_types
+          assert 'sampler_name' in input_types['required']
+          assert 'scheduler' in input_types['required']
+          assert 'steps' in input_types['required']
+          assert 'cfg' in input_types['required']
+
+          assert sampler_class.CATEGORY == 'ComfyAssets'
+          print('✓ Sampler Combo ComfyUI integration passed')
+
+          # Test Seed History
+          from kikotools.tools.seed_history.node import SeedHistoryNode
+          seed_class = SeedHistoryNode
+
+          assert hasattr(seed_class, 'INPUT_TYPES')
+          assert hasattr(seed_class, 'RETURN_TYPES')
+          assert hasattr(seed_class, 'RETURN_NAMES')
+          assert hasattr(seed_class, 'FUNCTION')
+          assert hasattr(seed_class, 'CATEGORY')
+
+          input_types = seed_class.INPUT_TYPES()
+          assert 'required' in input_types
+          assert 'seed' in input_types['required']
+
+          assert seed_class.RETURN_TYPES == ('INT',)
+          assert seed_class.RETURN_NAMES == ('seed',)
+          assert seed_class.CATEGORY == 'ComfyAssets'
+          print('✓ Seed History ComfyUI integration passed')
+
+          print('🎉 All tools ComfyUI integration readiness tests passed!')
           "
 
   test-package-structure:
@@ -147,7 +401,7 @@ jobs:
       - uses: actions/checkout@v4
 
       - name: Set up Python 3.10
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: "3.10"
 
@@ -163,14 +417,37 @@ jobs:
           test -d kikotools/base || (echo "kikotools/base directory missing" && exit 1)
           test -d kikotools/tools || (echo "kikotools/tools directory missing" && exit 1)
           test -d kikotools/tools/resolution_calculator || (echo "resolution_calculator directory missing" && exit 1)
+          test -d kikotools/tools/width_height_selector || (echo "width_height_selector directory missing" && exit 1)
+          test -d kikotools/tools/sampler_combo || (echo "sampler_combo directory missing" && exit 1)
+          test -d kikotools/tools/seed_history || (echo "seed_history directory missing" && exit 1)
           test -d tests || (echo "tests directory missing" && exit 1)
           test -d examples || (echo "examples directory missing" && exit 1)
+          test -d web || (echo "web directory missing" && exit 1)
 
           # Check key files
           test -f kikotools/__init__.py || (echo "kikotools/__init__.py missing" && exit 1)
           test -f kikotools/base/base_node.py || (echo "base_node.py missing" && exit 1)
-          test -f kikotools/tools/resolution_calculator/node.py || (echo "node.py missing" && exit 1)
-          test -f kikotools/tools/resolution_calculator/logic.py || (echo "logic.py missing" && exit 1)
+
+          # Resolution Calculator files
+          test -f kikotools/tools/resolution_calculator/node.py || (echo "resolution_calculator node.py missing" && exit 1)
+          test -f kikotools/tools/resolution_calculator/logic.py || (echo "resolution_calculator logic.py missing" && exit 1)
+
+          # Width Height Selector files
+          test -f kikotools/tools/width_height_selector/node.py || (echo "width_height_selector node.py missing" && exit 1)
+          test -f kikotools/tools/width_height_selector/logic.py || (echo "width_height_selector logic.py missing" && exit 1)
+          test -f kikotools/tools/width_height_selector/presets.py || (echo "width_height_selector presets.py missing" && exit 1)
+
+          # Sampler Combo files
+          test -f kikotools/tools/sampler_combo/node.py || (echo "sampler_combo node.py missing" && exit 1)
+          test -f kikotools/tools/sampler_combo/logic.py || (echo "sampler_combo logic.py missing" && exit 1)
+
+          # Seed History files
+          test -f kikotools/tools/seed_history/node.py || (echo "seed_history node.py missing" && exit 1)
+          test -f kikotools/tools/seed_history/logic.py || (echo "seed_history logic.py missing" && exit 1)
+
+          # Web files
+          test -f web/width_height_swap.js || (echo "width_height_swap.js missing" && exit 1)
+          test -f web/seed_history_ui.js || (echo "seed_history_ui.js missing" && exit 1)
 
           echo "✓ Package structure tests passed"
 
@@ -181,9 +458,15 @@ jobs:
 
       - name: Test documentation completeness
         run: |
-          # Check documentation files
+          # Check documentation files for all tools
           test -f examples/documentation/resolution_calculator.md || (echo "Resolution calculator docs missing" && exit 1)
-          test -f examples/workflows/resolution_calculator_example.json || (echo "Example workflow missing" && exit 1)
+          test -f examples/workflows/resolution_calculator_example.json || (echo "Resolution calculator workflow missing" && exit 1)
+          test -f examples/documentation/width_height_selector.md || (echo "Width height selector docs missing" && exit 1)
+          test -f examples/workflows/width_height_selector_example.json || (echo "Width height selector workflow missing" && exit 1)
+          test -f examples/documentation/sampler_combo.md || (echo "Sampler combo docs missing" && exit 1)
+          test -f examples/workflows/sampler_combo_example.json || (echo "Sampler combo workflow missing" && exit 1)
+          test -f examples/documentation/seed_history.md || (echo "Seed history docs missing" && exit 1)
+          test -f examples/workflows/seed_history_example.json || (echo "Seed history workflow missing" && exit 1)
 
           # Check README has key sections
           grep -q "Installation" README.md || (echo "README missing Installation section" && exit 1)

.gitignore

@@ -158,4 +158,8 @@ input/
 test_images/
 test_outputs/
 experiments/
-.claude/
+.claude/
+
+# Gemini model cache
+.gemini_models_cache.json
+CLAUDE.md

.pre-commit-config.yaml

@@ -0,0 +1,84 @@
+# Pre-commit hooks configuration for ComfyUI-KikoTools
+# This ensures code quality checks are run before each commit
+
+repos:
+  # Python code formatting with Black
+  - repo: https://github.com/psf/black
+    rev: 25.1.0
+    hooks:
+      - id: black
+        language_version: python3.10
+        args: ['--line-length=88']  # Match CI configuration
+
+  # Python linting with flake8
+  - repo: https://github.com/pycqa/flake8
+    rev: 7.3.0
+    hooks:
+      - id: flake8
+        args: ['--max-line-length=88', '--max-complexity=10']
+        exclude: '^tests/'
+
+  # Python type checking with mypy
+  # Note: Mypy is disabled in pre-commit due to package name issue
+  # Run manually with: mypy kikotools/
+  # - repo: https://github.com/pre-commit/mirrors-mypy
+  #   rev: v1.8.0
+  #   hooks:
+  #     - id: mypy
+  #       args: ['--config-file=mypy.ini']
+  #       files: '^kikotools/'
+  #       exclude: '^tests/'
+  #       additional_dependencies: ['types-requests']
+
+  # Security checks with bandit
+  - repo: https://github.com/PyCQA/bandit
+    rev: 1.8.6
+    hooks:
+      - id: bandit
+        args: ['-ll', '-r']
+        files: '^kikotools/'
+
+  # General file checks
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v5.0.0
+    hooks:
+      - id: trailing-whitespace
+      - id: end-of-file-fixer
+      - id: check-yaml
+      - id: check-added-large-files
+        args: ['--maxkb=1000']
+      - id: check-case-conflict
+      - id: check-merge-conflict
+      - id: check-docstring-first
+      - id: debug-statements
+      - id: mixed-line-ending
+
+  # Check for hardcoded secrets
+  - repo: https://github.com/Yelp/detect-secrets
+    rev: v1.5.0
+    hooks:
+      - id: detect-secrets
+        args: ['--baseline', '.secrets.baseline']
+        exclude: '^(tests/|\.git/)'
+
+# Configuration for specific hooks
+default_language_version:
+  python: python3.10
+
+# Run hooks on all files by default
+fail_fast: false
+
+# Exclude patterns
+exclude: |
+  (?x)^(
+    \.git/|
+    \.mypy_cache/|
+    \.pytest_cache/|
+    __pycache__/|
+    build/|
+    dist/|
+    \.eggs/|
+    .*\.egg-info/|
+    venv/|
+    env/
+  )

.secrets.baseline

@@ -0,0 +1,164 @@
+{
+  "version": "1.5.0",
+  "plugins_used": [
+    {
+      "name": "ArtifactoryDetector"
+    },
+    {
+      "name": "AWSKeyDetector"
+    },
+    {
+      "name": "AzureStorageKeyDetector"
+    },
+    {
+      "name": "Base64HighEntropyString",
+      "limit": 4.5
+    },
+    {
+      "name": "BasicAuthDetector"
+    },
+    {
+      "name": "CloudantDetector"
+    },
+    {
+      "name": "DiscordBotTokenDetector"
+    },
+    {
+      "name": "GitHubTokenDetector"
+    },
+    {
+      "name": "GitLabTokenDetector"
+    },
+    {
+      "name": "HexHighEntropyString",
+      "limit": 3.0
+    },
+    {
+      "name": "IbmCloudIamDetector"
+    },
+    {
+      "name": "IbmCosHmacDetector"
+    },
+    {
+      "name": "IPPublicDetector"
+    },
+    {
+      "name": "JwtTokenDetector"
+    },
+    {
+      "name": "KeywordDetector",
+      "keyword_exclude": ""
+    },
+    {
+      "name": "MailchimpDetector"
+    },
+    {
+      "name": "NpmDetector"
+    },
+    {
+      "name": "OpenAIDetector"
+    },
+    {
+      "name": "PrivateKeyDetector"
+    },
+    {
+      "name": "PypiTokenDetector"
+    },
+    {
+      "name": "SendGridDetector"
+    },
+    {
+      "name": "SlackDetector"
+    },
+    {
+      "name": "SoftlayerDetector"
+    },
+    {
+      "name": "SquareOAuthDetector"
+    },
+    {
+      "name": "StripeDetector"
+    },
+    {
+      "name": "TelegramBotTokenDetector"
+    },
+    {
+      "name": "TwilioKeyDetector"
+    }
+  ],
+  "filters_used": [
+    {
+      "path": "detect_secrets.filters.allowlist.is_line_allowlisted"
+    },
+    {
+      "path": "detect_secrets.filters.common.is_ignored_due_to_verification_policies",
+      "min_level": 2
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_indirect_reference"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_likely_id_string"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_lock_file"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_not_alphanumeric_string"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_potential_uuid"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_prefixed_with_dollar_sign"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_sequential_string"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_swagger_file"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_templated_secret"
+    }
+  ],
+  "results": {
+    "examples/workflows/resolution_calculator_example.json": [
+      {
+        "type": "Hex High Entropy String",
+        "filename": "examples/workflows/resolution_calculator_example.json",
+        "hashed_secret": "5264b0f1a47aeafad88f33511dda3191b32dbf38",
+        "is_verified": false,
+        "line_number": 57
+      }
+    ],
+    "examples/workflows/sampler_combo_example.json": [
+      {
+        "type": "Hex High Entropy String",
+        "filename": "examples/workflows/sampler_combo_example.json",
+        "hashed_secret": "e3c1848dd1141985e412fa39922ac9ba37c4714d",
+        "is_verified": false,
+        "line_number": 348
+      }
+    ],
+    "examples/workflows/seed_history_example.json": [
+      {
+        "type": "Hex High Entropy String",
+        "filename": "examples/workflows/seed_history_example.json",
+        "hashed_secret": "e3c1848dd1141985e412fa39922ac9ba37c4714d",
+        "is_verified": false,
+        "line_number": 408
+      }
+    ],
+    "examples/workflows/width_height_selector_example.json": [
+      {
+        "type": "Hex High Entropy String",
+        "filename": "examples/workflows/width_height_selector_example.json",
+        "hashed_secret": "e3c1848dd1141985e412fa39922ac9ba37c4714d",
+        "is_verified": false,
+        "line_number": 425
+      }
+    ]
+  },
+  "generated_at": "2025-07-31T23:51:20Z"
+}

CODE_OF_CONDUCT.md

@@ -0,0 +1,128 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+We as members, contributors, and leaders pledge to make participation in our
+community a harassment-free experience for everyone, regardless of age, body
+size, visible or invisible disability, ethnicity, sex characteristics, gender
+identity and expression, level of experience, education, socio-economic status,
+nationality, personal appearance, race, religion, or sexual identity
+and orientation.
+
+We pledge to act and interact in ways that contribute to an open, welcoming,
+diverse, inclusive, and healthy community.
+
+## Our Standards
+
+Examples of behavior that contributes to a positive environment for our
+community include:
+
+* Demonstrating empathy and kindness toward other people
+* Being respectful of differing opinions, viewpoints, and experiences
+* Giving and gracefully accepting constructive feedback
+* Accepting responsibility and apologizing to those affected by our mistakes,
+  and learning from the experience
+* Focusing on what is best not just for us as individuals, but for the
+  overall community
+
+Examples of unacceptable behavior include:
+
+* The use of sexualized language or imagery, and sexual attention or
+  advances of any kind
+* Trolling, insulting or derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or email
+  address, without their explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+  professional setting
+
+## Enforcement Responsibilities
+
+Community leaders are responsible for clarifying and enforcing our standards of
+acceptable behavior and will take appropriate and fair corrective action in
+response to any behavior that they deem inappropriate, threatening, offensive,
+or harmful.
+
+Community leaders have the right and responsibility to remove, edit, or reject
+comments, commits, code, wiki edits, issues, and other contributions that are
+not aligned to this Code of Conduct, and will communicate reasons for moderation
+decisions when appropriate.
+
+## Scope
+
+This Code of Conduct applies within all community spaces, and also applies when
+an individual is officially representing the community in public spaces.
+Examples of representing our community include using an official e-mail address,
+posting via an official social media account, or acting as an appointed
+representative at an online or offline event.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported to the community leaders responsible for enforcement at
+.
+All complaints will be reviewed and investigated promptly and fairly.
+
+All community leaders are obligated to respect the privacy and security of the
+reporter of any incident.
+
+## Enforcement Guidelines
+
+Community leaders will follow these Community Impact Guidelines in determining
+the consequences for any action they deem in violation of this Code of Conduct:
+
+### 1. Correction
+
+**Community Impact**: Use of inappropriate language or other behavior deemed
+unprofessional or unwelcome in the community.
+
+**Consequence**: A private, written warning from community leaders, providing
+clarity around the nature of the violation and an explanation of why the
+behavior was inappropriate. A public apology may be requested.
+
+### 2. Warning
+
+**Community Impact**: A violation through a single incident or series
+of actions.
+
+**Consequence**: A warning with consequences for continued behavior. No
+interaction with the people involved, including unsolicited interaction with
+those enforcing the Code of Conduct, for a specified period of time. This
+includes avoiding interactions in community spaces as well as external channels
+like social media. Violating these terms may lead to a temporary or
+permanent ban.
+
+### 3. Temporary Ban
+
+**Community Impact**: A serious violation of community standards, including
+sustained inappropriate behavior.
+
+**Consequence**: A temporary ban from any sort of interaction or public
+communication with the community for a specified period of time. No public or
+private interaction with the people involved, including unsolicited interaction
+with those enforcing the Code of Conduct, is allowed during this period.
+Violating these terms may lead to a permanent ban.
+
+### 4. Permanent Ban
+
+**Community Impact**: Demonstrating a pattern of violation of community
+standards, including sustained inappropriate behavior,  harassment of an
+individual, or aggression toward or disparagement of classes of individuals.
+
+**Consequence**: A permanent ban from any sort of public interaction within
+the community.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage],
+version 2.0, available at
+https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
+
+Community Impact Guidelines were inspired by [Mozilla's code of conduct
+enforcement ladder](https://github.com/mozilla/diversity).
+
+[homepage]: https://www.contributor-covenant.org
+
+For answers to common questions about this code of conduct, see the FAQ at
+https://www.contributor-covenant.org/faq. Translations are available at
+https://www.contributor-covenant.org/translations.

Makefile

@@ -2,6 +2,22 @@
 
 .PHONY: help install test test-fast lint format type-check quality-check clean setup dev-test release-test
 
+# Python and virtual environment setup
+PYTHON := python3
+VENV_DIR := venv
+VENV_BIN := $(VENV_DIR)/bin
+VENV_PYTHON := $(VENV_BIN)/python
+VENV_PIP := $(VENV_BIN)/pip
+
+# Check if we're in a virtual environment, if not use venv
+ifeq ($(VIRTUAL_ENV),)
+	PYTHON_CMD := $(VENV_PYTHON)
+	PIP_CMD := $(VENV_PIP)
+else
+	PYTHON_CMD := python
+	PIP_CMD := pip
+endif
+
 # Default target
 help:
 	@echo "ComfyUI-KikoTools Development Commands"
@@ -28,44 +44,48 @@ help:
 	@echo "  help           - Show this help message"
 
 # Setup and installation
-setup:
-	@echo "Setting up ComfyUI-KikoTools development environment..."
-	python -m venv venv
-	@echo "Virtual environment created. Activate with:"
-	@echo "  source venv/bin/activate  (Linux/Mac)"
-	@echo "  venv\\Scripts\\activate     (Windows)"
-	@echo "Then run: make install"
+setup: $(VENV_DIR)
+	@echo "✅ ComfyUI-KikoTools development environment ready"
+	@echo "Virtual environment created. Dependencies installed."
 
-install:
+$(VENV_DIR):
+	@echo "Creating virtual environment..."
+	$(PYTHON) -m venv $(VENV_DIR)
 	@echo "Installing development dependencies..."
-	pip install --upgrade pip
-	pip install -r requirements-dev.txt
+	$(VENV_PIP) install --upgrade pip
+	$(VENV_PIP) install -r requirements-dev.txt
+	@echo "✅ Virtual environment created and dependencies installed"
+
+install: $(VENV_DIR)
+	@echo "Installing/updating development dependencies..."
+	$(PIP_CMD) install --upgrade pip
+	$(PIP_CMD) install -r requirements-dev.txt
 	@echo "✅ Dependencies installed"
 
 # Code quality
-format:
+format: $(VENV_DIR)
 	@echo "Formatting code with black..."
-	black .
+	$(PYTHON_CMD) -m black .
 	@echo "✅ Code formatted"
 
-lint:
+lint: $(VENV_DIR)
 	@echo "Linting with flake8..."
-	flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
-	flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+	$(PYTHON_CMD) -m flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics --exclude=venv
+	$(PYTHON_CMD) -m flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics --exclude=venv
 	@echo "✅ Linting completed"
 
-type-check:
+type-check: $(VENV_DIR)
 	@echo "Type checking with mypy..."
-	mypy kikotools/ --ignore-missing-imports --no-strict-optional || true
+	$(PYTHON_CMD) -m mypy kikotools/ --ignore-missing-imports --no-strict-optional || true
 	@echo "✅ Type checking completed"
 
 quality-check: format lint type-check
 	@echo "✅ All quality checks completed"
 
 # Testing
-dev-test:
+dev-test: $(VENV_DIR)
 	@echo "Running quick development test..."
-	@python -c "\
+	@$(PYTHON_CMD) -c "\
 	import sys, os; \
 	sys.path.insert(0, os.getcwd()); \
 	from kikotools.tools.resolution_calculator.node import ResolutionCalculatorNode; \
@@ -75,9 +95,9 @@ dev-test:
 	print(f'✅ Development test passed! Result: {result[0]}x{result[1]}'); \
 	"
 
-test-fast:
+test-fast: $(VENV_DIR)
 	@echo "Running core functionality tests..."
-	@python -c "\
+	@$(PYTHON_CMD) -c "\
 	import sys, os; \
 	sys.path.insert(0, os.getcwd()); \
 	from kikotools.base import ComfyAssetsBaseNode; \
@@ -103,7 +123,7 @@ test-fast:
 test: test-fast
 	@echo "Running comprehensive test suite..."
 	@echo "✅ Test case 1: 512×512 → 1024×1024 (scale: 2.0)"
-	@echo "✅ Test case 2: 1024×1024 → 1536×1536 (scale: 1.5)"  
+	@echo "✅ Test case 2: 1024×1024 → 1536×1536 (scale: 1.5)"
 	@echo "✅ Test case 3: 832×1216 → 1272×1864 (scale: 1.53)"
 	@echo "✅ Error handling test passed"
 	@echo "🎉 All comprehensive tests passed!"
@@ -146,13 +166,13 @@ ci: quality-check test
 	@echo "✅ CI checks passed!"
 
 # Tool-specific commands (can be extended for new tools)
-test-resolution-calculator:
+test-resolution-calculator: $(VENV_DIR)
 	@echo "Testing Resolution Calculator specifically..."
-	@python -c "import sys, os; sys.path.insert(0, os.getcwd()); from kikotools.tools.resolution_calculator.node import ResolutionCalculatorNode; import torch; node = ResolutionCalculatorNode(); scenarios = [('SDXL Portrait', torch.randn(1, 1216, 832, 3), 1.5), ('FLUX Square', torch.randn(1, 1024, 1024, 3), 2.0), ('User Scenario', torch.randn(1, 1216, 832, 3), 1.53)]; [print(f'✅ {name}: {image.shape[2]}×{image.shape[1]} → {node.calculate_resolution(scale, image=image)[0]}×{node.calculate_resolution(scale, image=image)[1]} ({scale}x)') for name, image, scale in scenarios]; print('🎉 Resolution Calculator tests completed!')"
+	@$(PYTHON_CMD) -c "import sys, os; sys.path.insert(0, os.getcwd()); from kikotools.tools.resolution_calculator.node import ResolutionCalculatorNode; import torch; node = ResolutionCalculatorNode(); scenarios = [('SDXL Portrait', torch.randn(1, 1216, 832, 3), 1.5), ('FLUX Square', torch.randn(1, 1024, 1024, 3), 2.0), ('User Scenario', torch.randn(1, 1216, 832, 3), 1.53)]; [print(f'✅ {name}: {image.shape[2]}×{image.shape[1]} → {node.calculate_resolution(scale, image=image)[0]}×{node.calculate_resolution(scale, image=image)[1]} ({scale}x)') for name, image, scale in scenarios]; print('🎉 Resolution Calculator tests completed!')"
 
-test-width-height-selector:
+test-width-height-selector: $(VENV_DIR)
 	@echo "Testing Width Height Selector specifically..."
-	@python -c "\
+	@$(PYTHON_CMD) -c "\
 	import sys, os; \
 	sys.path.insert(0, os.getcwd()); \
 	from kikotools.tools.width_height_selector.node import WidthHeightSelectorNode; \
@@ -176,4 +196,4 @@ test-width-height-selector:
 	"
 
 test-all-tools: test-resolution-calculator test-width-height-selector
-	@echo "🎉 All tool-specific tests completed!"
+	@echo "🎉 All tool-specific tests completed!"

README.md

@@ -14,6 +14,19 @@ ComfyUI-KikoTools provides carefully crafted, production-ready nodes grouped und
 
 ### ✨ Current Tools
 
+| Tool | Description | Category |
+|------|-------------|----------|
+| [📐 Resolution Calculator](#-resolution-calculator) | Calculate upscaled dimensions with model optimization | Image Processing |
+| [📏 Width Height Selector](#-width-height-selector) | Preset-based dimension selection with visual swap | Dimension Control |
+| [🎲 Seed History](#-seed-history) | Advanced seed tracking with interactive history | Generation Control |
+| [⚙️ Sampler Combo](#️-sampler-combo) | Unified sampling configuration interface | Sampling |
+| [📦 Empty Latent Batch](#-empty-latent-batch) | Create empty latent batches with preset support | Latent Generation |
+| [💾 Kiko Save Image](#-kiko-save-image) | Enhanced image saving with popup viewer | File Management |
+| [📋 Display Text](#-display-text) | Smart text display with prompt detection | Text Display |
+| [🤖 Gemini Prompt Engineer](#-gemini-prompt-engineer) | AI-powered image analysis and prompt generation | AI Integration |
+| [🔍 Display Any](#-display-any) | Universal debugging tool for any data type | Debugging |
+| [🖼️ Image to Multiple Of](#️-image-to-multiple-of) | Adjust dimensions to multiples for compatibility | Image Processing |
+
 #### 📐 Resolution Calculator
 Calculate upscaled dimensions from image or latent inputs with precision.
 
@@ -25,10 +38,12 @@ Calculate upscaled dimensions from image or latent inputs with precision.
 
 **Use Cases:**
 - Calculate target dimensions for upscaler nodes
-- Plan memory usage for large generations  
+- Plan memory usage for large generations
 - Ensure ComfyUI tensor compatibility
 - Optimize batch processing workflows
 
+![Resolution Calculator Example](examples/workflows/resolution_calculator_example.png)
+
 #### 📏 Width Height Selector
 Advanced preset-based dimension selection with visual swap button.
 
@@ -60,6 +75,8 @@ Advanced seed tracking with interactive history management and UI.
 - Maintain reproducibility across sessions
 - Compare results from different seeds efficiently
 
+![Seed History functionality is shown in various workflow examples]
+
 #### ⚙️ Sampler Combo
 Unified sampling configuration interface combining sampler, scheduler, steps, and CFG.
 
@@ -76,6 +93,136 @@ Unified sampling configuration interface combining sampler, scheduler, steps, an
 - Reduce node clutter in workflows
 - Quick sampling parameter experimentation
 
+#### 📦 Empty Latent Batch
+Advanced empty latent creation with preset support and batch processing capabilities.
+
+- **Preset Integration**: 26 curated resolution presets with model optimization
+- **Batch Processing**: Create multiple empty latents (1-64) in a single operation
+- **Visual Swap Button**: Interactive blue button for quick dimension swapping
+- **Smart Validation**: Automatic dimension sanitization for VAE compatibility
+- **Memory Estimation**: Built-in memory usage calculation and warnings
+- **Model-Aware Presets**: SDXL (~1MP), FLUX (high-res), and Ultra-wide options
+
+**Use Cases:**
+- Initialize batch processing workflows efficiently
+- Create consistent latent dimensions across model types
+- Optimize memory usage with batch size planning
+- Quick preset-based latent generation for different aspect ratios
+
+![Empty Latent Batch Example](examples/workflows/empty_latent_batch_example.png)
+
+#### 💾 Kiko Save Image
+Enhanced image saving with format selection, quality control, and floating popup viewer.
+
+- **Multiple Format Support**: Save as PNG, JPEG, or WebP with format-specific optimizations
+- **Advanced Quality Controls**: JPEG/WebP quality (1-100), PNG compression (0-9), WebP lossless mode
+- **Floating Popup Viewer**: Draggable, resizable window that shows saved images immediately
+- **Interactive Previews**: Click any image to open in new tab, download individual images
+- **Batch Selection**: Multi-select images for bulk actions (open all, download all)
+- **Format-Specific Settings**: Quality indicators, file size display, compression info
+- **Smart UI**: Auto-hide/show, minimize/maximize, roll-up functionality
+- **Popup Toggle**: Enable/disable popup viewer per save operation
+
+![Kiko Save Image Example](examples/workflows/kiko_save_image_example.png)
+
+#### 📋 Display Text
+Advanced text display node with intelligent formatting and enhanced user interaction.
+
+- **Smart Prompt Detection**: Automatically detects positive/negative prompt pairs and displays in split view
+- **Text Wrapping**: Proper word wrapping that reflows when node is resized
+- **Scrollable Content**: Mouse wheel scrolling for long texts with visual scroll indicators
+- **Copy Functionality**: Always-visible copy button with visual feedback
+- **Split View Mode**: Automatic detection and formatting of SDXL-style prompts
+- **Responsive Design**: Content adapts to node resizing with proper text reflow
+- **Clean Formatting**: Strips prompt labels when copying for direct use
+
+**Use Cases:**
+- Display generated prompts with proper formatting
+- Compare positive and negative prompts side-by-side
+- Copy prompts without manual label removal
+- View long text content with proper wrapping
+- Debug prompt generation workflows
+
+![Display Text Example](examples/workflows/display_text_example.png)
+
+#### 🤖 Gemini Prompt Engineer
+AI-powered image analysis using Google's Gemini to generate optimized prompts for various models.
+
+- **Multi-Model Support**: Generate prompts for FLUX, SDXL, Danbooru, and Video generation
+- **Smart Analysis**: Gemini analyzes composition, style, lighting, colors, and details
+- **Format-Specific Output**: FLUX artistic prompts, SDXL positive/negative pairs, Danbooru tags, Video motion descriptions
+- **Custom System Prompts**: Override templates with your own analysis instructions
+- **Flexible API Key Management**: Environment variable, config file, or direct input
+- **Visual Status Feedback**: Real-time processing indicators and error states
+- **Help Integration**: Built-in setup guide and documentation
+- **Dynamic Model Refresh**: Fetch latest Gemini models with refresh button
+- **Model Caching**: Persistent model list storage for offline access
+- **Enhanced SDXL Prompts**: Improved formatting with layered structure and quality boosters
+
+**Use Cases:**
+- Reverse-engineer prompts from reference images
+- Convert artistic descriptions between different AI model formats
+- Generate consistent style descriptions across workflows
+- Create detailed scene breakdowns for complex compositions
+- Analyze and replicate lighting/mood from existing artwork
+- Access latest Gemini models including 2.0 and 2.5 versions
+
+![Gemini Prompt Example](examples/workflows/gemini_prompt_example.png)
+
+#### 🔍 Display Any
+Universal debugging node that displays any type of input value or tensor information.
+
+- **Universal Input Acceptance**: Works with any data type (tensors, strings, numbers, lists, dicts)
+- **Two Display Modes**: Raw value showing string representation, or tensor shape extraction
+- **Nested Structure Support**: Finds tensors within complex nested data structures
+- **Debugging Focus**: Essential tool for understanding data flow and tensor dimensions
+- **Clean Output**: Formatted display directly in ComfyUI interface
+
+**Use Cases:**
+- Debug tensor dimensions at any point in workflow
+- Inspect latent space data structures
+- View metadata and configuration objects
+- Track shape changes through processing nodes
+- Understand complex data types in ComfyUI
+
+![Display Any Example](examples/workflows/display_any_example.png)
+
+#### 🖼️ Image to Multiple Of
+Adjusts image dimensions to be multiples of a specified value for model compatibility.
+
+- **Dimension Adjustment**: Ensures image dimensions are multiples of specified value (e.g., 64, 128)
+- **Two Processing Methods**: Center crop for minimal loss, or rescale to fit
+- **Model Compatibility**: Essential for models requiring specific dimension constraints
+- **Flexible Multiple Values**: Support from 1 to 256 with 16-step increments
+- **Preserves Quality**: Smart processing maintains image quality
+
+**Use Cases:**
+- Prepare images for VAE encoding (multiple of 8 requirement)
+- Ensure compatibility with specific model architectures
+- Standardize dimensions across image batches
+- Fix dimension errors in complex workflows
+- Optimize for tiled processing requirements
+
+![Image to Multiple Of Example](examples/workflows/image_to_multiple_of_example.png)
+
+### 💾 Kiko Save Image Features
+
+**Use Cases:**
+- Quick preview and management of saved images without file browser navigation
+- Compare multiple format outputs side-by-side (PNG vs JPEG vs WebP)
+- Batch download or open selected images efficiently
+- Monitor file sizes and compression effectiveness in real-time
+- Streamlined workflow for iterative image generation and saving
+
+**Why Better Than Standard Save Image:**
+- **Immediate Visual Feedback**: See your saved images instantly without opening file explorer
+- **Multi-Format Flexibility**: Choose optimal format for your use case (PNG for quality, JPEG for size, WebP for modern efficiency)
+- **Advanced Compression Control**: Fine-tune file sizes with format-specific quality settings
+- **Batch Operations**: Handle multiple images efficiently with selection and bulk actions
+- **Modern UI**: Floating, draggable interface that doesn't interrupt your workflow
+- **Smart Memory Usage**: File size indicators help optimize storage and sharing
+- **One-Click Access**: Direct image opening in browser tabs for quick sharing or review
+
 ### 🔧 Architecture Highlights
 
 - **Modular Design**: Each tool is self-contained and independently testable
@@ -113,8 +260,8 @@ Image Loader → Resolution Calculator → Upscaler
              ↘ scale_factor: 1.5    ↗
 ```
 
-**Input:** 832×1216 (SDXL portrait format)  
-**Scale:** 1.5x  
+**Input:** 832×1216 (SDXL portrait format)
+**Scale:** 1.5x
 **Output:** 1248×1824 (ready for upscaling)
 
 ### Width Height Selector Example
@@ -125,8 +272,8 @@ preset: "1920×1080"   ↘ 1920×1080      ↗
 [swap button]
 ```
 
-**Preset:** FLUX HD (1920×1080)  
-**Output:** 1920×1080 (16:9 cinematic)  
+**Preset:** FLUX HD (1920×1080)
+**Output:** 1920×1080 (16:9 cinematic)
 **Swap Button:** Click to get 1080×1920 (9:16 portrait)
 
 ### Seed History Example
@@ -137,8 +284,8 @@ Seed History → KSampler → VAE Decode → Save Image
 [History UI: 54321, 99999, 11111...]
 ```
 
-**Current Seed:** 12345  
-**History:** Auto-tracked previous seeds with timestamps  
+**Current Seed:** 12345
+**History:** Auto-tracked previous seeds with timestamps
 **Interaction:** Click any historical seed to reload instantly
 
 ### Sampler Combo Example
@@ -148,10 +295,89 @@ Sampler Combo → KSampler → VAE Decode → Save Image
 ⚙️ All Settings ↘ sampler/scheduler/steps/cfg ↗
 ```
 
-**Configuration:** euler, normal, 20 steps, CFG 7.0  
-**Output:** Complete sampling configuration in one node  
+**Configuration:** euler, normal, 20 steps, CFG 7.0
+**Output:** Complete sampling configuration in one node
 **Smart Features:** Recommendations and compatibility validation
 
+### Empty Latent Batch Example
+
+```
+Empty Latent Batch → KSampler → VAE Decode → Kiko Save Image
+📦 preset: "1024×1024" ↘ batch latents ↗                ↘ popup viewer ↗
+   batch_size: 4
+   [swap button]
+```
+
+**Preset:** SDXL Square (1024×1024)
+**Batch Size:** 4 empty latents
+**Output:** 4×4×128×128 latent tensor ready for sampling
+**Swap Button:** Click to switch to any available swapped preset
+
+### Kiko Save Image Example
+
+```
+Generate Image → Kiko Save Image → Floating Popup Viewer
+📷 output       ↘ format: WEBP   ↘ draggable window ↗
+                  quality: 85
+                  [popup: enabled]
+```
+
+**Format:** WebP (efficient compression, modern format)
+**Quality:** 85% (balanced size/quality)
+**Popup Viewer:** Floating, draggable window with saved images
+**Features:** Click images to open in new tabs, download individual files, batch selection
+**Advantages:** Immediate preview without file explorer, multi-format comparison, advanced quality controls
+
+### Display Text Example
+
+```
+Gemini Prompt → Display Text → Copy to Clipboard
+📋 SDXL prompt ↘ auto-split  ↘ [📋 Positive] [📋 Negative]
+                view          → formatted display
+```
+
+**Input:** Text with "Positive prompt:" and "Negative prompt:" sections
+**Output:** Split view with individual copy buttons
+**Features:** Text wrapping, scrolling, responsive resizing
+**Smart Detection:** Automatically formats SDXL-style prompts
+
+### Gemini Prompt Engineer Example
+```
+Load Image → Gemini Prompt → Display Text → Text Generation Model
+🖼️ reference ↘ type: SDXL   ↘ split view  ↘ "detailed portrait..."
+               [Refresh Models]             → SDXL model
+```
+
+**Input:** Reference image for style analysis
+**Prompt Type:** SDXL (positive/negative pairs with layered structure)
+**Model Selection:** Dynamic list with latest Gemini models (2.0, 2.5)
+**Output:** Optimized prompts following community best practices
+**API:** Requires Gemini API key (free tier available)
+**Refresh:** Click button to fetch latest available models
+
+### Display Any Example
+```
+Any Node → Display Any → Debug Output
+🔍 tensor  ↘ mode: shape ↘ "[[1, 3, 512, 512]]"
+```
+
+**Input:** Any data type (image, latent, config, etc.)
+**Mode:** "raw value" or "tensor shape"
+**Output:** Formatted display of value or tensor dimensions
+**Use Case:** Debug workflows, inspect data structures
+
+### Image to Multiple Of Example
+```
+Load Image → Image to Multiple Of → VAE Encode → KSampler
+🖼️ 513×769  ↘ multiple: 64    ↘ 512×768     → latent
+              method: crop
+```
+
+**Input:** Image with arbitrary dimensions
+**Multiple Of:** 64 (common for VAE compatibility)
+**Method:** "center crop" or "rescale"
+**Output:** Adjusted image with compatible dimensions
+
 ### Common Workflows
 
 <details>
@@ -160,7 +386,7 @@ Sampler Combo → KSampler → VAE Decode → Save Image
 ```json
 {
   "workflow": "Load SDXL portrait → Calculate 1.5x dimensions → Feed to upscaler",
-  "input_resolution": "832×1216", 
+  "input_resolution": "832×1216",
   "scale_factor": 1.5,
   "output_resolution": "1248×1824",
   "memory_efficient": true
@@ -175,7 +401,7 @@ Sampler Combo → KSampler → VAE Decode → Save Image
 {
   "workflow": "Generate latents → Calculate target size → Batch upscale",
   "input_resolution": "1024×1024",
-  "scale_factor": 2.0, 
+  "scale_factor": 2.0,
   "output_resolution": "2048×2048",
   "batch_optimized": true
 }
@@ -191,7 +417,13 @@ Sampler Combo → KSampler → VAE Decode → Save Image
 | **Resolution Calculator** | Calculate upscaled dimensions with model optimization | ✅ Complete | [Docs](examples/documentation/resolution_calculator.md) |
 | **Width Height Selector** | Preset-based dimension selection with 26 curated options | ✅ Complete | [Docs](examples/documentation/width_height_selector.md) |
 | **Seed History** | Advanced seed tracking with interactive history management | ✅ Complete | [Docs](examples/documentation/seed_history.md) |
-| **Sampler Combo** | Unified sampling configuration with smart recommendations | ✅ Complete | [Usage Examples](#sampler-combo-example) |
+| **Sampler Combo** | Unified sampling configuration with smart recommendations | ✅ Complete | [Docs](examples/documentation/sampler_combo.md) |
+| **Empty Latent Batch** | Create empty latent batches with preset support | ✅ Complete | [Docs](examples/documentation/empty_latent_batch.md) |
+| **Kiko Save Image** | Enhanced image saving with popup viewer and multi-format support | ✅ Complete | [Docs](examples/documentation/kiko_save_image.md) |
+| **Display Text** | Advanced text display with smart prompt detection and split view | ✅ Complete | [Docs](examples/documentation/display_text.md) |
+| **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) |
 | **Batch Image Processor** | Process multiple images with consistent settings | 🚧 Planned | Coming Soon |
 | **Advanced Prompt Utilities** | Enhanced prompt manipulation and generation | 🚧 Planned | Coming Soon |
 
@@ -201,7 +433,7 @@ Sampler Combo → KSampler → VAE Decode → Save Image
 
 **Inputs:**
 - `scale_factor` (FLOAT): 1.0-8.0, default 2.0
-- `image` (IMAGE, optional): Input image tensor  
+- `image` (IMAGE, optional): Input image tensor
 - `latent` (LATENT, optional): Input latent tensor
 
 **Outputs:**
@@ -223,7 +455,7 @@ Sampler Combo → KSampler → VAE Decode → Save Image
 
 **Outputs:**
 - `width` (INT): Selected or calculated width
-- `height` (INT): Selected or calculated height  
+- `height` (INT): Selected or calculated height
 
 **UI Features:**
 - Visual blue swap button in bottom-right corner
@@ -267,7 +499,7 @@ Sampler Combo → KSampler → VAE Decode → Save Image
 
 **Outputs:**
 - `sampler_name` (STRING): Selected sampler algorithm
-- `scheduler` (STRING): Selected scheduler algorithm  
+- `scheduler` (STRING): Selected scheduler algorithm
 - `steps` (INT): Validated step count
 - `cfg` (FLOAT): Validated CFG scale
 
@@ -278,6 +510,71 @@ Sampler Combo → KSampler → VAE Decode → Save Image
 - Graceful error handling with safe defaults
 - Comprehensive tooltips for user guidance
 
+#### Empty Latent Batch
+
+**Inputs:**
+- `preset` (DROPDOWN): 26 preset options + custom with formatted metadata display
+- `width` (INT): 64-8192, step 8, default 1024
+- `height` (INT): 64-8192, step 8, default 1024
+- `batch_size` (INT): 1-64, default 1
+
+**Outputs:**
+- `latent` (LATENT): Batch of empty latent tensors in ComfyUI format
+- `width` (INT): Final sanitized width (divisible by 8)
+- `height` (INT): Final sanitized height (divisible by 8)
+
+**UI Features:**
+- Visual blue swap button with hover and click feedback
+- Intelligent preset switching when swapping dimensions
+- Memory usage estimation and warnings for large batches
+- Auto-update width/height widgets when presets change
+
+**Batch Processing:**
+- Creates tensors with shape: [batch_size, 4, height//8, width//8]
+- Efficient memory allocation with torch.zeros
+- Validates batch size limits (1-64) with performance warnings
+- Compatible with all ComfyUI latent processing nodes
+
+**Preset Integration:**
+- Full access to 26 curated resolution presets from Width Height Selector
+- Model-aware categorization (SDXL, FLUX, Ultra-wide)
+- Formatted display with aspect ratio and megapixel information
+- Intelligent fallback to custom dimensions for invalid presets
+
+#### Kiko Save Image
+
+**Inputs:**
+- `images` (IMAGE): Batch of images to save
+- `filename_prefix` (STRING): Prefix for saved filenames, default "KikoSave"
+- `format` (DROPDOWN): Output format (PNG, JPEG, WEBP), default PNG
+- `quality` (INT): JPEG/WebP quality (1-100), default 90
+- `png_compress_level` (INT): PNG compression level (0-9), default 4
+- `webp_lossless` (BOOLEAN): Use lossless WebP compression, default False
+- `popup` (BOOLEAN): Enable popup viewer window, default True
+
+**Outputs:**
+- `UI`: Enhanced image preview data with popup viewer functionality
+
+**UI Features:**
+- Floating, draggable popup window showing saved images immediately
+- Interactive image grid with click-to-open functionality
+- Individual image download buttons with format-specific quality indicators
+- Batch selection with multi-select checkboxes for bulk operations
+- Window controls: minimize, maximize, roll-up, close, and dragging
+- Auto-hide/show behavior with smart positioning
+
+**Format Support:**
+- **PNG**: Lossless compression with metadata preservation, configurable compression levels
+- **JPEG**: Quality-controlled lossy compression with automatic transparency handling
+- **WebP**: Modern format with both lossy and lossless modes, superior compression ratios
+
+**Advanced Features:**
+- File size monitoring and display for optimization feedback
+- Format-specific quality indicators (PNG compression level, JPEG/WebP quality percentage)
+- Smart filename sanitization with timestamp-based uniqueness
+- Persistent popup viewer across multiple save operations
+- Toggle button integration in node UI for manual viewer control
+
 ## 🛠️ Development
 
 ### Prerequisites
@@ -300,6 +597,9 @@ source venv/bin/activate  # On Windows: venv\Scripts\activate
 # Install development dependencies
 pip install -r requirements-dev.txt
 
+# Install pre-commit hooks
+pre-commit install
+
 # Run tests
 python -c "
 import sys, os
@@ -316,13 +616,32 @@ print(f'✅ Development setup successful! Test result: {result[0]}x{result[1]}')
 
 ### Code Quality
 
-We maintain high code quality standards:
+We maintain high code quality standards with automated pre-commit hooks:
+
+#### Pre-commit Hooks
+
+Our pre-commit configuration automatically runs:
+- **Black**: Code formatting (127 char line length)
+- **Flake8**: Linting and style checks
+- **Bandit**: Security vulnerability scanning
+- **detect-secrets**: Prevents accidental secret commits
+- File checks: trailing whitespace, YAML validation, merge conflicts
+
+```bash
+# Run all pre-commit hooks manually
+pre-commit run --all-files
+
+# Update hooks to latest versions
+pre-commit autoupdate
+```
+
+#### Manual Code Quality Checks
 
 ```bash
 # Format code
 black .
 
-# Lint code  
+# Lint code
 flake8 .
 
 # Type checking
@@ -345,7 +664,7 @@ Following **Test-Driven Development (TDD)**:
 # Test structure
 tests/
 ├── unit/                    # Individual component tests
-├── integration/            # ComfyUI workflow tests  
+├── integration/            # ComfyUI workflow tests
 └── fixtures/              # Test data and workflows
 ```
 
@@ -398,13 +717,15 @@ MIT License - see [LICENSE](LICENSE) file for details.
 
 ## 📈 Stats
 
-- **Nodes**: 4 (Resolution Calculator, Width Height Selector, Seed History, Sampler Combo)
+- **Nodes**: 10 (Resolution Calculator, Width Height Selector, Seed History, Sampler Combo, Empty Latent Batch, Kiko Save Image, Display Text, Gemini Prompt Engineer, Display Any, Image to Multiple Of)
+- **Format Support**: 3 (PNG, JPEG, WebP with advanced controls)
 - **Presets**: 26 curated resolution presets
-- **Interactive Features**: 2 (Swap Button, History UI)
-- **Test Coverage**: 100% (180+ comprehensive tests)
+- **Interactive Features**: 6 (Width/Height Swap Button, Seed History UI, Empty Latent Batch Swap Button, Kiko Save Image Popup Viewer, Display Text Split View, Gemini Model Refresh)
+- **AI Integration**: Gemini API with 40+ model support
+- **Test Coverage**: 100% (200+ comprehensive tests)
 - **Python Version**: 3.8+
 - **ComfyUI Compatibility**: Latest
-- **Dependencies**: Minimal (PyTorch, NumPy)
+- **Dependencies**: Minimal (PyTorch, NumPy, Pillow, google-generativeai for Gemini)
 
 ---
 
@@ -414,4 +735,4 @@ MIT License - see [LICENSE](LICENSE) file for details.
 
 [⭐ Star this repo](https://github.com/ComfyAssets/ComfyUI-KikoTools) • [🐛 Report Bug](https://github.com/ComfyAssets/ComfyUI-KikoTools/issues) • [💡 Request Feature](https://github.com/ComfyAssets/ComfyUI-KikoTools/issues)
 
-</div>
+</div>

SECURITY.md

@@ -0,0 +1,66 @@
+# Security Policy
+
+## Supported Versions
+
+ComfyUI-KikoTools is actively maintained. We provide security updates for the following versions:
+
+| Version | Supported          |
+| ------- | ------------------ |
+| 1.x.x   | :white_check_mark: |
+| < 1.0   | :x:                |
+
+## Reporting a Vulnerability
+
+We take the security of ComfyUI-KikoTools seriously. If you believe you have found a security vulnerability, please report it to us as described below.
+
+### How to Report
+
+Please report security vulnerabilities by [opening a new issue](https://github.com/ComfyAssets/ComfyUI-KikoTools/issues/new) with the following:
+
+- Use the title prefix `[SECURITY]`
+- Provide a clear description of the vulnerability
+- Include steps to reproduce the issue
+- Specify the version(s) affected
+- If possible, suggest a fix or mitigation
+
+### What to Expect
+
+- **Response Time**: We aim to acknowledge receipt within 48 hours
+- **Investigation**: We will investigate and validate the reported vulnerability
+- **Updates**: We will keep you informed about the progress
+- **Resolution**: Once verified, we will work on a fix and release it as soon as possible
+- **Credit**: We will acknowledge your contribution in the release notes (unless you prefer to remain anonymous)
+
+### Scope
+
+Security vulnerabilities in scope include:
+
+- Code execution vulnerabilities in node implementations
+- Path traversal or file system access issues
+- API key or credential exposure
+- Dependency vulnerabilities that affect the project
+- Any issue that could compromise user data or system security
+
+### Out of Scope
+
+The following are generally not considered security vulnerabilities:
+
+- Issues in ComfyUI core (report these to the ComfyUI project)
+- Performance issues
+- Bugs that don't have security implications
+- Feature requests
+
+## Security Best Practices
+
+When using ComfyUI-KikoTools:
+
+- Keep your installation up to date
+- Store API keys (like Gemini API keys) securely using environment variables
+- Review generated files before sharing them
+- Be cautious with custom prompts that might expose sensitive information
+
+## Contact
+
+For urgent security matters, you can also reach out to the maintainers directly through GitHub.
+
+Thank you for helping keep ComfyUI-KikoTools secure!

__init__.py

@@ -3,12 +3,39 @@ ComfyUI-KikoTools: Modular collection of custom ComfyUI nodes
 All nodes are grouped under the "ComfyAssets" category
 """
 
-from .kikotools import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
+import re
+from pathlib import Path
+
+try:
+    from .kikotools import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
+except ImportError:
+    # Fallback for testing environment
+    from kikotools import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
 
 # Tell ComfyUI where to find our JavaScript extensions
 WEB_DIRECTORY = "./web"
 
-# Print startup message
-print("\033[94m[ComfyUI-KikoTools] Loaded with swap button support!\033[0m")
+
+def get_version():
+    """Parse version from pyproject.toml"""
+    try:
+        pyproject_path = Path(__file__).parent / "pyproject.toml"
+        if pyproject_path.exists():
+            content = pyproject_path.read_text()
+            match = re.search(r'version\s*=\s*["\']([^"\']+)["\']', content)
+            if match:
+                return match.group(1)
+    except Exception:
+        pass
+    return "unknown"
+
+
+# Print startup message with loaded tools
+print()
+print(f"\033[94m[ComfyUI-KikoTools] Version:\033[0m {get_version()}")
+for node_key, display_name in NODE_DISPLAY_NAME_MAPPINGS.items():
+    print(f"🫶 \033[94mLoaded:\033[0m {display_name}")
+print(f"\033[94mTotal: {len(NODE_CLASS_MAPPINGS)} tools loaded\033[0m")
+print()
 
 __all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS", "WEB_DIRECTORY"]

comfyui_xyz_grid_plan.md

@@ -0,0 +1,148 @@
+# ComfyUI XYZ Grid Comparison Nodes
+
+## Project Objective
+Create a modular suite of ComfyUI nodes for visual grid-based comparisons across parameters such as:
+
+- Models
+- LoRAs
+- Schedulers
+- Samplers
+- CFG Scale
+- Steps
+- Clip Skip
+- VAEs
+- Flux Guidance (custom model settings)
+
+The tool will support X, Y, and optional Z axis configuration using a polished, intuitive UI with no scripting or coding required.
+
+---
+
+## Design Goals
+
+- **Modular Architecture:** Built as multiple nodes (not monolithic)
+- **Standard Node Compatibility:** Work with *any* KSampler, Model Loader, etc.
+- **User Friendly UI:** Dropdowns, toggles, and visual input—no syntax or scripting
+- **Flexible Axis Mapping:** Any parameter can go on X, Y, or Z
+- **Dynamic Grid Generation:** One-click execution queues all combinations
+- **Labeling:** Automatic overlay and metadata support with clean presentation
+- **High Performance:** Smart resource caching and sequential queuing
+
+---
+
+## Key Nodes
+
+### 1. `XYZ Plot Controller`
+- Main config node
+- Allows axis selection (X, Y, optional Z)
+- Outputs: axis values, labels, grid ID
+- Automatically queues image generation
+
+### 2. `Image Grid Combiner`
+- Accepts image + axis metadata
+- Assembles a labeled grid (or multiple grids)
+- Outputs: grid image(s), optional metadata (label list, value list)
+
+---
+
+## Parameter Types
+Supported as axis values:
+- Model (checkpoint)
+- LoRA (file)
+- VAE
+- Sampler (Euler, DPM++, etc.)
+- Scheduler
+- CFG Scale (float list)
+- Steps (int list)
+- Clip Skip
+- Prompt (swap full prompt or use template)
+- Seed
+- Custom (e.g., Flux guidance strength)
+
+---
+
+## UI Design
+
+### Axis Config (for X, Y, Z)
+- Dropdown: Select parameter type
+- Input: List of values (dynamic UI)
+  - File pickers (models, LoRAs)
+  - Number range or CSV (steps, CFG)
+  - Text input (prompts)
+- Label customization
+  - Prefix: optional (e.g., CFG=, Sampler:)
+  - Label format: full, short, value only
+
+### Execution
+- One-click generate
+- Internally queues all combinations (X * Y * Z)
+- Reuses sampler, model loader, etc.
+- Supports caching to avoid repeated loads
+
+---
+
+## Output Behavior
+- Combiner tracks image count
+- Assembles grid when complete
+- Draws axis labels using PIL
+- Handles Z axis by outputting multiple grids
+- Preview as images come in
+- Metadata export (optional JSON/text)
+
+---
+
+## Example Use Cases
+
+### Model vs CFG
+- X: Models A/B
+- Y: CFG [5,10,15]
+- Output: 2x3 grid with axis labels
+
+### Prompt vs Sampler
+- X: Prompt variations
+- Y: Samplers
+- Output: labeled comparison grid
+
+### LoRA vs Seed, Z=Strength
+- X: LoRA name
+- Y: Seeds
+- Z: LoRA strength
+- Output: Multiple 2D grids, one per Z value
+
+---
+
+## Development Phases
+
+### Phase 1: MVP
+- X/Y support
+- Core image generation loop
+- Grid image stitching
+
+### Phase 2: Z Axis + More Parameters
+- Prompt, LoRA, Flux guidance, etc.
+
+### Phase 3: UI Polish
+- Dynamic widgets
+- Label controls, error handling
+
+### Phase 4: Performance & Optimization
+- Model caching
+- Memory handling
+- Abort/resume logic
+
+### Phase 5: Docs & Examples
+- Example workflows
+- Visual documentation
+
+---
+
+## References & Inspirations
+- [TinyTerra ComfyUI_tinyterraNodes](https://github.com/TinyTerra/ComfyUI_tinyterraNodes)
+- [kenjiqq/qq-nodes-comfyui](https://github.com/kenjiqq/qq-nodes-comfyui)
+- [jags111/efficiency-nodes-comfyui](https://github.com/jags111/efficiency-nodes-comfyui)
+- [shockz-comfy/comfy-easy-grids](https://github.com/shockz-comfy/comfy-easy-grids)
+
+---
+
+## Final Outcome
+A polished, no-code, modular XYZ plotting system in ComfyUI for exploring image generation across any combination of models, settings, or parameters with professional-grade visual output.
+

docs/RGTHREE_WIDGET_FRAMEWORK.md

@@ -0,0 +1,394 @@
+# RGThree-Style Dynamic Widget Framework for ComfyUI
+
+This document explains how to implement RGThree's Power Lora Loader-style dynamic widget system in your own ComfyUI nodes. This framework provides a clean UI with toggles, dynamic widget management, and proper persistence across page refreshes.
+
+## Key Features
+
+- **Dynamic widget addition/removal** - Users can add/remove items at runtime
+- **Toggle switches** - Clean circular toggles instead of checkboxes
+- **Strength controls** - Arrow buttons with editable values for fine control
+- **Right-click context menus** - Only on the item name area
+- **Full persistence** - All values persist across page refreshes
+- **Hide/show widgets** - Proper cleanup when switching between types
+
+## Core Implementation Pattern
+
+### 1. Node Setup in JavaScript
+
+```javascript
+app.registerExtension({
+    name: "YourExtension.YourNode",
+    
+    async beforeRegisterNodeDef(nodeType, nodeData, app) {
+        if (nodeData.name === "YourNodeName") {
+            const onNodeCreated = nodeType.prototype.onNodeCreated;
+            
+            nodeType.prototype.onNodeCreated = function() {
+                const node = this;
+                
+                if (onNodeCreated) {
+                    onNodeCreated.apply(this, arguments);
+                }
+                
+                // Enable widget serialization
+                this.serialize_widgets = true;
+                
+                // Track widget visibility
+                this.hiddenWidgets = new Set();
+                
+                // Initialize storage for dynamic widgets
+                if (!node.dynamicWidgets) {
+                    node.dynamicWidgets = {
+                        category1: [],
+                        category2: []
+                    };
+                }
+                
+                // Store references to buttons and text widgets
+                if (!node.addButtons) {
+                    node.addButtons = {};
+                }
+                if (!node.textWidgets) {
+                    node.textWidgets = {};
+                }
+            };
+        }
+    }
+});
+```
+
+### 2. Custom Widget Class
+
+```javascript
+class DynamicWidget {
+    constructor(name, value) {
+        this.name = name;
+        this._value = value;
+        this.type = "custom_dynamic_widget";
+        this.y = 0;
+        this.options = {};
+        
+        // Mouse tracking for drag operations
+        this.mouseState = {
+            dragging: false,
+            startX: 0,
+            startValue: 0,
+            lastClickTime: 0
+        };
+    }
+    
+    get value() {
+        return this._value;
+    }
+    
+    set value(v) {
+        this._value = v;
+    }
+    
+    serializeValue(node, index) {
+        // Return a deep copy to prevent modification
+        return this._value ? { ...this._value } : null;
+    }
+    
+    draw(ctx, node, width, y) {
+        const margin = 10;
+        const innerMargin = 3;
+        const height = LiteGraph.NODE_WIDGET_HEIGHT;
+        const midY = y + height / 2;
+        let posX = margin;
+        
+        ctx.save();
+        
+        // Draw background
+        ctx.fillStyle = "rgba(0,0,0,0.2)";
+        ctx.beginPath();
+        ctx.roundRect(posX, y + 2, width - margin * 2, height - 4, [height * 0.5]);
+        ctx.fill();
+        
+        // Draw toggle (Power Lora style)
+        const toggleRadius = height * 0.36;
+        const toggleBgWidth = height * 1.5;
+        
+        // Toggle background
+        ctx.beginPath();
+        ctx.roundRect(posX + 4, y + 4, toggleBgWidth - 8, height - 8, [height * 0.5]);
+        ctx.globalAlpha = app.canvas.editor_alpha * 0.25;
+        ctx.fillStyle = "rgba(255,255,255,0.45)";
+        ctx.fill();
+        ctx.globalAlpha = app.canvas.editor_alpha;
+        
+        // Toggle circle
+        const toggleX = this.value.on ? posX + height : posX + height * 0.5;
+        ctx.fillStyle = this.value.on ? "#89B" : "#888";
+        ctx.beginPath();
+        ctx.arc(toggleX, midY, toggleRadius, 0, Math.PI * 2);
+        ctx.fill();
+        
+        this.toggleBounds = [posX, toggleBgWidth];
+        posX += toggleBgWidth + innerMargin;
+        
+        // Apply opacity if disabled
+        if (!this.value.on) {
+            ctx.globalAlpha = app.canvas.editor_alpha * 0.4;
+        }
+        
+        // Draw strength controls (if applicable)
+        if (this.value.strength !== undefined) {
+            let strengthX = width - margin - innerMargin;
+            
+            // Draw arrows and value
+            // ... (implement arrow drawing as shown in xyz_plot_controller.js)
+        }
+        
+        // Draw item name
+        ctx.fillStyle = LiteGraph.WIDGET_TEXT_COLOR;
+        ctx.textAlign = "left";
+        ctx.textBaseline = "middle";
+        ctx.fillText(this.value.name || "None", posX, midY);
+        
+        ctx.restore();
+    }
+    
+    mouse(event, pos, node) {
+        // Handle mouse events for toggle and controls
+        if (event.type === "mousedown") {
+            // Check toggle bounds
+            if (pos[0] >= this.toggleBounds[0] && 
+                pos[0] <= this.toggleBounds[0] + this.toggleBounds[1]) {
+                this.value.on = !this.value.on;
+                node.setDirtyCanvas(true, true);
+                return true;
+            }
+            // Handle other controls...
+        }
+        return false;
+    }
+}
+```
+
+### 3. Configuration and Restoration
+
+```javascript
+// Override onConfigure for proper restoration
+const onConfigure = nodeType.prototype.onConfigure;
+nodeType.prototype.onConfigure = function(info) {
+    // Mark as configured to prevent duplicate initialization
+    this._configured = true;
+    
+    // Store widget values before ComfyUI modifies them
+    const savedWidgetValues = [...(info.widgets_values || [])];
+    
+    // Clear tracking for fresh restoration
+    if (!this.hiddenWidgets) {
+        this.hiddenWidgets = new Set();
+    }
+    this.dynamicWidgets = { /* categories */ };
+    this.addButtons = {};
+    this.textWidgets = {};
+    
+    // Let ComfyUI restore base widgets
+    if (onConfigure) {
+        onConfigure.call(this, info);
+    }
+    
+    // Restore dynamic widgets from saved values
+    // ... (implement restoration logic)
+    
+    // Manually restore text widget values
+    for (let i = 0; i < this.widgets.length && i < savedWidgetValues.length; i++) {
+        const widget = this.widgets[i];
+        const savedValue = savedWidgetValues[i];
+        
+        if (widget && typeof savedValue === 'string' && savedValue !== '') {
+            widget.value = savedValue;
+            if (widget.inputEl) {
+                widget.inputEl.value = savedValue;
+            }
+        }
+    }
+};
+```
+
+### 4. Serialization Override
+
+```javascript
+// Override onSerialize to fix widget value persistence
+const origOnSerialize = nodeType.prototype.onSerialize;
+nodeType.prototype.onSerialize = function(info) {
+    // Let ComfyUI serialize first
+    if (origOnSerialize) {
+        origOnSerialize.call(this, info);
+    }
+    
+    // Fix empty text widget values
+    if (info.widgets_values && this.widgets) {
+        for (let i = 0; i < this.widgets.length && i < info.widgets_values.length; i++) {
+            const widget = this.widgets[i];
+            const serializedValue = info.widgets_values[i];
+            
+            // If serialized value is empty but widget has value, fix it
+            if ((serializedValue === '' || serializedValue === null) && 
+                widget && widget.value !== '' && widget.value !== null) {
+                info.widgets_values[i] = widget.value;
+            }
+            
+            // Also check inputEl for text widgets
+            if (widget && widget.inputEl && widget.inputEl.value && 
+                (serializedValue === '' || serializedValue === null)) {
+                info.widgets_values[i] = widget.inputEl.value;
+            }
+        }
+    }
+};
+```
+
+### 5. Right-Click Context Menu
+
+```javascript
+// Override getSlotInPosition to detect clicks on widget areas
+const originalGetSlotInPosition = node.getSlotInPosition;
+node.getSlotInPosition = function(x, y) {
+    const slot = originalGetSlotInPosition ? originalGetSlotInPosition.call(this, x, y) : null;
+    if (!slot) {
+        // Check if we clicked on a dynamic widget's name area
+        const localX = x - this.pos[0];
+        const localY = y - this.pos[1];
+        
+        for (const w of this.widgets || []) {
+            if (w.type === "custom_dynamic_widget" && w.y && 
+                localY > w.y && localY < w.y + LiteGraph.NODE_WIDGET_HEIGHT) {
+                // Check if click is within name bounds
+                if (w.nameBounds && localX >= w.nameBounds[0] && 
+                    localX <= w.nameBounds[0] + w.nameBounds[1]) {
+                    return { widget: w, output: { type: "DYNAMIC_WIDGET" } };
+                }
+            }
+        }
+    }
+    return slot;
+};
+
+// Override getSlotMenuOptions for context menu
+const originalGetSlotMenuOptions = node.getSlotMenuOptions;
+node.getSlotMenuOptions = function(slot) {
+    if (slot?.output?.type === "DYNAMIC_WIDGET") {
+        const widget = slot.widget;
+        
+        const menuItems = [
+            {
+                content: `${widget.value.on ? "⚫" : "🟢"} Toggle ${widget.value.on ? "Off" : "On"}`,
+                callback: () => {
+                    widget.value.on = !widget.value.on;
+                    this.setDirtyCanvas(true, true);
+                }
+            },
+            {
+                content: `⬆️ Move Up`,
+                disabled: !canMoveUp,
+                callback: () => { /* implement move */ }
+            },
+            {
+                content: `⬇️ Move Down`,
+                disabled: !canMoveDown,
+                callback: () => { /* implement move */ }
+            },
+            {
+                content: `🗑️ Remove`,
+                callback: () => { /* implement remove */ }
+            }
+        ];
+        
+        new LiteGraph.ContextMenu(menuItems, {
+            title: "WIDGET OPTIONS",
+            event: app.canvas.last_mouse_event || window.event
+        });
+        
+        return null; // Prevent default menu
+    }
+    
+    return originalGetSlotMenuOptions ? originalGetSlotMenuOptions.call(this, slot) : null;
+};
+```
+
+### 6. Widget Visibility Management
+
+```javascript
+function updateWidgets(node, category, type, skipClear = false) {
+    // Hide/show widgets instead of removing them
+    if (!skipClear) {
+        // Hide all widgets for this category
+        node.widgets?.forEach(widget => {
+            if (widget.name?.includes(category)) {
+                widget.hidden = true;
+                widget.computeSize = () => [0, 0];
+                node.hiddenWidgets?.add(widget.name);
+            }
+        });
+        
+        // Clear dynamic widgets
+        if (node.dynamicWidgets[category]) {
+            while (node.dynamicWidgets[category].length > 0) {
+                const widget = node.dynamicWidgets[category].pop();
+                const index = node.widgets.indexOf(widget);
+                if (index > -1) {
+                    node.widgets.splice(index, 1);
+                }
+            }
+        }
+    }
+    
+    // Add or unhide widgets based on type
+    if (needsTextWidget(type)) {
+        const widgetName = `${category}_text`;
+        let existingWidget = node.widgets?.find(w => w.name === widgetName);
+        
+        if (!existingWidget) {
+            // Create new widget
+            const textWidget = ComfyWidgets.STRING(node, widgetName, ["STRING", {
+                default: "",
+                multiline: true
+            }]);
+            node.textWidgets[category] = textWidget.widget;
+        } else {
+            // Unhide existing widget
+            existingWidget.hidden = false;
+            existingWidget.computeSize = () => [node.size[0] - 20, LiteGraph.NODE_WIDGET_HEIGHT];
+            node.hiddenWidgets?.delete(existingWidget.name);
+            node.textWidgets[category] = existingWidget;
+        }
+    }
+}
+```
+
+## Best Practices
+
+1. **Always use hide/show instead of remove/add** for text widgets to preserve values
+2. **Track widget state** in dedicated objects (dynamicWidgets, textWidgets, etc.)
+3. **Override serialization** to ensure ComfyUI properly saves widget values
+4. **Use skipClear flags** during restoration to prevent widget clearing
+5. **Implement proper mouse bounds checking** for custom controls
+6. **Store metadata** (_axis, _type) with widget values for easier restoration
+7. **Don't auto-resize nodes** - respect user's manual sizing
+
+## Common Pitfalls to Avoid
+
+1. **Don't remove widgets during configure** - this loses their values
+2. **Don't rely on widget indices** - they can change
+3. **Don't forget to handle inputEl** for text widgets
+4. **Don't create widgets without checking if they exist** first
+5. **Always deep copy values** when serializing to prevent modification
+
+## Testing Checklist
+
+- [ ] Widgets persist across page refresh
+- [ ] Toggle states are maintained
+- [ ] Strength/value controls work with click and drag
+- [ ] Right-click menu only appears on name area
+- [ ] Moving widgets up/down works correctly
+- [ ] Removing widgets works without errors
+- [ ] Switching between types doesn't leave artifacts
+- [ ] All text input types persist (numbers, ranges, prompts)
+- [ ] Hidden widgets don't take up visual space
+- [ ] Widget values serialize correctly in workflow JSON
+
+This framework provides a robust foundation for creating professional, user-friendly ComfyUI nodes with dynamic widget management that matches the quality of RGThree's implementations.

docs/RGTHREE_WIDGET_FRAMEWORK_EXAMPLE.md

@@ -0,0 +1,684 @@
+# RGThree Widget Framework - Complete Example Implementation
+
+This file provides a complete, working example of implementing the RGThree-style widget framework for a hypothetical "Advanced Sampler Controller" node.
+
+## Complete Implementation Example
+
+```javascript
+// File: web/advanced_sampler_controller.js
+
+import { app } from "../../scripts/app.js";
+import { ComfyWidgets } from "../../scripts/widgets.js";
+
+// Widget counter for unique names
+let widgetCounter = 0;
+
+// Custom dynamic widget class
+class SamplerDynamicWidget {
+    constructor(name, value) {
+        this.name = name;
+        this._value = value;
+        this.type = "sampler_dynamic_widget";
+        this.y = 0;
+        this.options = {};
+        
+        // Mouse state for drag operations
+        this.mouseState = {
+            dragging: false,
+            startX: 0,
+            startValue: 0,
+            lastClickTime: 0
+        };
+    }
+    
+    get value() {
+        return this._value;
+    }
+    
+    set value(v) {
+        this._value = v;
+    }
+    
+    serializeValue(node, index) {
+        return this._value ? { ...this._value } : null;
+    }
+    
+    draw(ctx, node, width, y) {
+        const margin = 10;
+        const innerMargin = 3;
+        const height = LiteGraph.NODE_WIDGET_HEIGHT;
+        const midY = y + height / 2;
+        let posX = margin;
+        
+        ctx.save();
+        
+        // Background
+        ctx.fillStyle = "rgba(0,0,0,0.2)";
+        ctx.beginPath();
+        ctx.roundRect(posX, y + 2, width - margin * 2, height - 4, [height * 0.5]);
+        ctx.fill();
+        
+        // Toggle
+        const toggleRadius = height * 0.36;
+        const toggleBgWidth = height * 1.5;
+        
+        // Toggle background
+        ctx.beginPath();
+        ctx.roundRect(posX + 4, y + 4, toggleBgWidth - 8, height - 8, [height * 0.5]);
+        ctx.globalAlpha = app.canvas.editor_alpha * 0.25;
+        ctx.fillStyle = "rgba(255,255,255,0.45)";
+        ctx.fill();
+        ctx.globalAlpha = app.canvas.editor_alpha;
+        
+        // Toggle circle
+        const toggleX = this.value.on ? posX + height : posX + height * 0.5;
+        ctx.fillStyle = this.value.on ? "#89B" : "#888";
+        ctx.beginPath();
+        ctx.arc(toggleX, midY, toggleRadius, 0, Math.PI * 2);
+        ctx.fill();
+        
+        // Store bounds for mouse interaction
+        this.toggleBounds = [posX, toggleBgWidth];
+        posX += toggleBgWidth + innerMargin;
+        
+        // Apply opacity if disabled
+        if (!this.value.on) {
+            ctx.globalAlpha = app.canvas.editor_alpha * 0.4;
+        }
+        
+        // Strength controls and value
+        let strengthX = width - margin - innerMargin;
+        
+        // Down arrow
+        const arrowSize = 10;
+        const arrowX = strengthX - arrowSize;
+        
+        ctx.fillStyle = "#666";
+        ctx.beginPath();
+        ctx.moveTo(arrowX + arrowSize/2, midY + 3);
+        ctx.lineTo(arrowX + 2, midY - 3);
+        ctx.lineTo(arrowX + arrowSize - 2, midY - 3);
+        ctx.closePath();
+        ctx.fill();
+        
+        this.downArrowBounds = [arrowX, arrowSize];
+        strengthX = arrowX - innerMargin;
+        
+        // Up arrow
+        const upArrowX = strengthX - arrowSize;
+        ctx.beginPath();
+        ctx.moveTo(upArrowX + arrowSize/2, midY - 3);
+        ctx.lineTo(upArrowX + 2, midY + 3);
+        ctx.lineTo(upArrowX + arrowSize - 2, midY + 3);
+        ctx.closePath();
+        ctx.fill();
+        
+        this.upArrowBounds = [upArrowX, arrowSize];
+        strengthX = upArrowX - innerMargin;
+        
+        // Strength value
+        const strengthText = this.value.strength.toFixed(2);
+        ctx.fillStyle = LiteGraph.WIDGET_TEXT_COLOR;
+        ctx.textAlign = "center";
+        ctx.font = `${ctx.font}`;
+        const textMetrics = ctx.measureText(strengthText);
+        const strengthTextX = strengthX - textMetrics.width/2 - 4;
+        
+        // Draggable background
+        ctx.fillStyle = "rgba(255,255,255,0.1)";
+        ctx.beginPath();
+        ctx.roundRect(strengthTextX - textMetrics.width/2 - 2, y + 4, 
+                      textMetrics.width + 4, height - 8, [3]);
+        ctx.fill();
+        
+        // Value text
+        ctx.fillStyle = this.value.on ? "#FFF" : "#AAA";
+        ctx.fillText(strengthText, strengthTextX, midY);
+        
+        this.strengthBounds = [strengthTextX - textMetrics.width/2 - 2, textMetrics.width + 4];
+        
+        // Name
+        const nameX = posX;
+        const maxNameWidth = strengthTextX - textMetrics.width/2 - nameX - 10;
+        
+        ctx.textAlign = "left";
+        ctx.fillStyle = LiteGraph.WIDGET_TEXT_COLOR;
+        
+        // Clip long names
+        const displayName = this.value.name || "None";
+        let truncatedName = displayName;
+        if (ctx.measureText(displayName).width > maxNameWidth) {
+            while (truncatedName.length > 0 && 
+                   ctx.measureText(truncatedName + "...").width > maxNameWidth) {
+                truncatedName = truncatedName.slice(0, -1);
+            }
+            truncatedName += "...";
+        }
+        
+        ctx.fillText(truncatedName, nameX, midY);
+        
+        // Store name bounds for right-click detection
+        this.nameBounds = [nameX, ctx.measureText(truncatedName).width];
+        
+        ctx.restore();
+    }
+    
+    mouse(event, pos, node) {
+        const margin = 10;
+        const localX = pos[0] - margin;
+        
+        if (event.type === "mousedown") {
+            // Toggle click
+            if (localX >= this.toggleBounds[0] && 
+                localX <= this.toggleBounds[0] + this.toggleBounds[1]) {
+                this.value.on = !this.value.on;
+                node.setDirtyCanvas(true, true);
+                return true;
+            }
+            
+            // Up arrow
+            if (localX >= this.upArrowBounds[0] && 
+                localX <= this.upArrowBounds[0] + this.upArrowBounds[1]) {
+                this.value.strength = Math.min(this.value.strength + 0.1, 10);
+                node.setDirtyCanvas(true, true);
+                return true;
+            }
+            
+            // Down arrow
+            if (localX >= this.downArrowBounds[0] && 
+                localX <= this.downArrowBounds[0] + this.downArrowBounds[1]) {
+                this.value.strength = Math.max(this.value.strength - 0.1, -10);
+                node.setDirtyCanvas(true, true);
+                return true;
+            }
+            
+            // Strength drag start
+            if (localX >= this.strengthBounds[0] && 
+                localX <= this.strengthBounds[0] + this.strengthBounds[1]) {
+                this.mouseState.dragging = true;
+                this.mouseState.startX = pos[0];
+                this.mouseState.startValue = this.value.strength;
+                
+                // Double-click detection
+                const now = Date.now();
+                if (now - this.mouseState.lastClickTime < 300) {
+                    // Double-click - show input dialog
+                    const newValue = prompt("Enter strength value:", this.value.strength);
+                    if (newValue !== null && !isNaN(parseFloat(newValue))) {
+                        this.value.strength = Math.max(-10, Math.min(10, parseFloat(newValue)));
+                        node.setDirtyCanvas(true, true);
+                    }
+                    this.mouseState.dragging = false;
+                }
+                this.mouseState.lastClickTime = now;
+                return true;
+            }
+        }
+        else if (event.type === "mousemove" && this.mouseState.dragging) {
+            const deltaX = pos[0] - this.mouseState.startX;
+            const sensitivity = 0.01;
+            this.value.strength = Math.max(-10, Math.min(10, 
+                this.mouseState.startValue + deltaX * sensitivity));
+            node.setDirtyCanvas(true, true);
+            return true;
+        }
+        else if (event.type === "mouseup") {
+            this.mouseState.dragging = false;
+        }
+        
+        return false;
+    }
+    
+    computeSize() {
+        return [node.size[0], LiteGraph.NODE_WIDGET_HEIGHT];
+    }
+}
+
+// Main extension registration
+app.registerExtension({
+    name: "Example.AdvancedSamplerController",
+    
+    async beforeRegisterNodeDef(nodeType, nodeData, app) {
+        if (nodeData.name === "AdvancedSamplerController") {
+            const onNodeCreated = nodeType.prototype.onNodeCreated;
+            
+            nodeType.prototype.onNodeCreated = function() {
+                const node = this;
+                
+                if (onNodeCreated) {
+                    onNodeCreated.apply(this, arguments);
+                }
+                
+                // Enable widget serialization
+                this.serialize_widgets = true;
+                
+                // Initialize tracking
+                this.hiddenWidgets = new Set();
+                
+                // Initialize storage
+                if (!node.dynamicWidgets) {
+                    node.dynamicWidgets = {
+                        samplers: [],
+                        schedulers: []
+                    };
+                }
+                
+                if (!node.addButtons) {
+                    node.addButtons = {};
+                }
+                
+                if (!node.textWidgets) {
+                    node.textWidgets = {};
+                }
+                
+                // Override configuration
+                const onConfigure = nodeType.prototype.onConfigure;
+                nodeType.prototype.onConfigure = function(info) {
+                    this._configured = true;
+                    
+                    // Save widget values before ComfyUI modifies them
+                    const savedWidgetValues = [...(info.widgets_values || [])];
+                    
+                    // Clear for fresh restoration
+                    if (!this.hiddenWidgets) {
+                        this.hiddenWidgets = new Set();
+                    }
+                    this.dynamicWidgets = {
+                        samplers: [],
+                        schedulers: []
+                    };
+                    this.addButtons = {};
+                    this.textWidgets = {};
+                    
+                    // Let ComfyUI restore base widgets
+                    if (onConfigure) {
+                        onConfigure.call(this, info);
+                    }
+                    
+                    // Restore dynamic widgets
+                    let widgetIndex = this.widgets.length;
+                    for (let i = widgetIndex; i < savedWidgetValues.length; i++) {
+                        const value = savedWidgetValues[i];
+                        if (value && typeof value === 'object' && value._type) {
+                            const widget = new SamplerDynamicWidget(
+                                `dynamic_${widgetCounter++}`,
+                                value
+                            );
+                            this.addCustomWidget(widget);
+                            
+                            if (this.dynamicWidgets[value._type]) {
+                                this.dynamicWidgets[value._type].push(widget);
+                            }
+                        }
+                    }
+                    
+                    // Restore text widget values
+                    for (let i = 0; i < this.widgets.length && i < savedWidgetValues.length; i++) {
+                        const widget = this.widgets[i];
+                        const savedValue = savedWidgetValues[i];
+                        
+                        if (widget && typeof savedValue === 'string' && savedValue !== '') {
+                            widget.value = savedValue;
+                            if (widget.inputEl) {
+                                widget.inputEl.value = savedValue;
+                            }
+                        }
+                    }
+                    
+                    // Update UI based on restored state
+                    if (this.widgets?.length > 0) {
+                        const typeWidget = this.widgets.find(w => w.name === "sampler_type");
+                        if (typeWidget) {
+                            updateTypeWidgets(this, typeWidget.value, true);
+                        }
+                    }
+                };
+                
+                // Override serialization
+                const origOnSerialize = nodeType.prototype.onSerialize;
+                nodeType.prototype.onSerialize = function(info) {
+                    if (origOnSerialize) {
+                        origOnSerialize.call(this, info);
+                    }
+                    
+                    // Fix empty text widget values
+                    if (info.widgets_values && this.widgets) {
+                        for (let i = 0; i < this.widgets.length && i < info.widgets_values.length; i++) {
+                            const widget = this.widgets[i];
+                            const serializedValue = info.widgets_values[i];
+                            
+                            if ((serializedValue === '' || serializedValue === null) && 
+                                widget && widget.value !== '' && widget.value !== null) {
+                                info.widgets_values[i] = widget.value;
+                            }
+                            
+                            if (widget && widget.inputEl && widget.inputEl.value && 
+                                (serializedValue === '' || serializedValue === null)) {
+                                info.widgets_values[i] = widget.inputEl.value;
+                            }
+                        }
+                    }
+                };
+                
+                // Implement right-click context menu
+                implementContextMenu(node);
+                
+                // Widget change handlers
+                const samplerWidget = this.widgets.find(w => w.name === "sampler_type");
+                if (samplerWidget) {
+                    const origCallback = samplerWidget.callback;
+                    samplerWidget.callback = function() {
+                        if (origCallback) {
+                            origCallback.apply(this, arguments);
+                        }
+                        updateTypeWidgets(node, samplerWidget.value);
+                    };
+                }
+            };
+        }
+    }
+});
+
+// Helper function to update widgets based on type
+function updateTypeWidgets(node, type, skipClear = false) {
+    if (!skipClear) {
+        // Hide text widgets
+        node.widgets?.forEach(widget => {
+            if (widget.name?.includes("custom_values")) {
+                widget.hidden = true;
+                widget.computeSize = () => [0, 0];
+                node.hiddenWidgets?.add(widget.name);
+            }
+        });
+        
+        // Clear dynamic widgets
+        if (node.dynamicWidgets.samplers) {
+            while (node.dynamicWidgets.samplers.length > 0) {
+                const widget = node.dynamicWidgets.samplers.pop();
+                const index = node.widgets.indexOf(widget);
+                if (index > -1) {
+                    node.widgets.splice(index, 1);
+                }
+            }
+        }
+    }
+    
+    // Add or unhide widgets based on type
+    if (type === "custom") {
+        const widgetName = "custom_values";
+        let existingWidget = node.widgets?.find(w => w.name === widgetName);
+        
+        if (!existingWidget) {
+            const textWidget = ComfyWidgets.STRING(node, widgetName, ["STRING", {
+                default: "",
+                multiline: true
+            }]);
+            node.textWidgets.custom = textWidget.widget;
+        } else {
+            existingWidget.hidden = false;
+            existingWidget.computeSize = () => [node.size[0] - 20, LiteGraph.NODE_WIDGET_HEIGHT];
+            node.hiddenWidgets?.delete(existingWidget.name);
+            node.textWidgets.custom = existingWidget;
+        }
+    } else if (type === "samplers") {
+        // Add button for samplers
+        if (!node.addButtons.samplers) {
+            const button = node.addWidget("button", "+ Add Sampler", null, () => {
+                addDynamicWidget(node, "samplers");
+            });
+            node.addButtons.samplers = button;
+        }
+    }
+}
+
+// Helper function to add dynamic widgets
+function addDynamicWidget(node, type) {
+    const widget = new SamplerDynamicWidget(
+        `dynamic_${widgetCounter++}`,
+        {
+            on: true,
+            name: type === "samplers" ? "euler" : "normal",
+            strength: 1.0,
+            _type: type
+        }
+    );
+    
+    node.addCustomWidget(widget);
+    node.dynamicWidgets[type].push(widget);
+}
+
+// Helper function to implement context menu
+function implementContextMenu(node) {
+    const originalGetSlotInPosition = node.getSlotInPosition;
+    node.getSlotInPosition = function(x, y) {
+        const slot = originalGetSlotInPosition ? originalGetSlotInPosition.call(this, x, y) : null;
+        if (!slot) {
+            const localX = x - this.pos[0];
+            const localY = y - this.pos[1];
+            
+            for (const w of this.widgets || []) {
+                if (w.type === "sampler_dynamic_widget" && w.y && 
+                    localY > w.y && localY < w.y + LiteGraph.NODE_WIDGET_HEIGHT) {
+                    if (w.nameBounds && localX >= w.nameBounds[0] && 
+                        localX <= w.nameBounds[0] + w.nameBounds[1]) {
+                        return { widget: w, output: { type: "SAMPLER_WIDGET" } };
+                    }
+                }
+            }
+        }
+        return slot;
+    };
+    
+    const originalGetSlotMenuOptions = node.getSlotMenuOptions;
+    node.getSlotMenuOptions = function(slot) {
+        if (slot?.output?.type === "SAMPLER_WIDGET") {
+            const widget = slot.widget;
+            const arrayName = widget.value._type;
+            const array = this.dynamicWidgets[arrayName];
+            const currentIndex = array.indexOf(widget);
+            
+            const menuItems = [
+                {
+                    content: `${widget.value.on ? "⚫" : "🟢"} Toggle ${widget.value.on ? "Off" : "On"}`,
+                    callback: () => {
+                        widget.value.on = !widget.value.on;
+                        this.setDirtyCanvas(true, true);
+                    }
+                },
+                {
+                    content: `⬆️ Move Up`,
+                    disabled: currentIndex === 0,
+                    callback: () => {
+                        if (currentIndex > 0) {
+                            // Swap in array
+                            [array[currentIndex - 1], array[currentIndex]] = 
+                            [array[currentIndex], array[currentIndex - 1]];
+                            
+                            // Swap in widgets
+                            const widgetIndex = this.widgets.indexOf(widget);
+                            const prevWidget = array[currentIndex];
+                            const prevIndex = this.widgets.indexOf(prevWidget);
+                            
+                            if (widgetIndex > -1 && prevIndex > -1) {
+                                [this.widgets[prevIndex], this.widgets[widgetIndex]] = 
+                                [this.widgets[widgetIndex], this.widgets[prevIndex]];
+                            }
+                            
+                            this.setDirtyCanvas(true, true);
+                        }
+                    }
+                },
+                {
+                    content: `⬇️ Move Down`,
+                    disabled: currentIndex === array.length - 1,
+                    callback: () => {
+                        if (currentIndex < array.length - 1) {
+                            // Swap in array
+                            [array[currentIndex], array[currentIndex + 1]] = 
+                            [array[currentIndex + 1], array[currentIndex]];
+                            
+                            // Swap in widgets
+                            const widgetIndex = this.widgets.indexOf(widget);
+                            const nextWidget = array[currentIndex];
+                            const nextIndex = this.widgets.indexOf(nextWidget);
+                            
+                            if (widgetIndex > -1 && nextIndex > -1) {
+                                [this.widgets[widgetIndex], this.widgets[nextIndex]] = 
+                                [this.widgets[nextIndex], this.widgets[widgetIndex]];
+                            }
+                            
+                            this.setDirtyCanvas(true, true);
+                        }
+                    }
+                },
+                null, // Separator
+                {
+                    content: `🗑️ Remove`,
+                    callback: () => {
+                        const index = array.indexOf(widget);
+                        if (index > -1) {
+                            array.splice(index, 1);
+                        }
+                        const wIndex = this.widgets.indexOf(widget);
+                        if (wIndex > -1) {
+                            this.widgets.splice(wIndex, 1);
+                        }
+                        this.setDirtyCanvas(true, true);
+                    }
+                }
+            ];
+            
+            new LiteGraph.ContextMenu(menuItems, {
+                title: "SAMPLER OPTIONS",
+                event: app.canvas.last_mouse_event || window.event
+            });
+            
+            return null;
+        }
+        
+        return originalGetSlotMenuOptions ? originalGetSlotMenuOptions.call(this, slot) : null;
+    };
+}
+```
+
+## Python Node Definition
+
+```python
+# File: kikotools/tools/advanced_sampler_controller/node.py
+
+class AdvancedSamplerController:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "sampler_type": (["samplers", "custom", "schedulers"], {
+                    "default": "samplers"
+                }),
+                "enabled": ("BOOLEAN", {"default": True}),
+            },
+            "optional": {
+                "custom_values": ("STRING", {"multiline": True, "default": ""}),
+            }
+        }
+    
+    RETURN_TYPES = ("SAMPLER_CONFIG",)
+    RETURN_NAMES = ("config",)
+    FUNCTION = "process"
+    CATEGORY = "ComfyAssets"
+    
+    def process(self, sampler_type, enabled, custom_values="", **kwargs):
+        config = {
+            "type": sampler_type,
+            "enabled": enabled,
+            "samplers": [],
+            "custom": custom_values
+        }
+        
+        # Process dynamic widgets
+        for key, value in kwargs.items():
+            if isinstance(value, dict) and value.get("_type") == "samplers":
+                if value.get("on", False):
+                    config["samplers"].append({
+                        "name": value.get("name"),
+                        "strength": value.get("strength", 1.0)
+                    })
+        
+        return (config,)
+```
+
+## Key Implementation Points
+
+1. **Widget Class Design**
+   - Custom widget class with proper value getter/setter
+   - `serializeValue` method for persistence
+   - Complete `draw` and `mouse` methods
+   - Proper bounds tracking for all interactive elements
+
+2. **Node Setup**
+   - `serialize_widgets = true` in onNodeCreated
+   - Tracking objects for dynamic widgets, buttons, and text widgets
+   - Hidden widgets set for visibility management
+
+3. **Configuration Override**
+   - Save widget values before ComfyUI modifies them
+   - Clear tracking objects for fresh restoration
+   - Restore dynamic widgets from saved values
+   - Manually restore text widget values
+
+4. **Serialization Override**
+   - Fix empty text widget values
+   - Check both widget.value and widget.inputEl.value
+   - Ensure all widget types persist correctly
+
+5. **Context Menu Implementation**
+   - Override getSlotInPosition to detect widget clicks
+   - Check name bounds for right-click detection
+   - Return custom slot type for menu trigger
+   - Override getSlotMenuOptions for menu items
+
+6. **Widget Management**
+   - Hide/show pattern instead of remove/add
+   - Proper cleanup when switching types
+   - Dynamic widget arrays for organization
+   - Button widgets for adding new items
+
+## Testing Your Implementation
+
+1. **Create Test Workflow**
+   ```json
+   {
+     "nodes": [{
+       "type": "AdvancedSamplerController",
+       "widgets_values": [
+         "samplers",
+         true,
+         "",
+         {
+           "on": true,
+           "name": "euler",
+           "strength": 0.8,
+           "_type": "samplers"
+         }
+       ]
+     }]
+   }
+   ```
+
+2. **Test Checklist**
+   - [ ] Add dynamic widgets with button
+   - [ ] Toggle on/off states persist
+   - [ ] Strength values persist after refresh
+   - [ ] Right-click menu only on name area
+   - [ ] Move up/down works correctly
+   - [ ] Remove widget works
+   - [ ] Switch types doesn't leave artifacts
+   - [ ] Text values persist
+   - [ ] Double-click to edit strength works
+
+3. **Debug Tips**
+   - Add console.log in key methods
+   - Check browser console for errors
+   - Verify widget array contents
+   - Test with workflow JSON export/import
+
+This complete example demonstrates all aspects of the RGThree widget framework and can be adapted for any custom node that needs dynamic widget management with professional UI/UX.

example.py

@@ -0,0 +1,366 @@
+import os
+from typing import Tuple
+
+import comfy.sd
+import comfy.utils
+import torch
+import torch.nn.functional as F
+from comfy.sd import CLIP
+from diffusers import ConsistencyDecoderVAE
+from folder_paths import get_folder_paths
+from huggingface_hub import hf_hub_download
+from torch import Tensor
+
+
+def find_or_create_cache():
+    cwd = os.getcwd()
+    if os.path.exists(os.path.join(cwd, "ComfyUI")):
+        cwd = os.path.join(cwd, "ComfyUI")
+    if os.path.exists(os.path.join(cwd, "models")):
+        cwd = os.path.join(cwd, "models")
+    if not os.path.exists(os.path.join(cwd, "huggingface_cache")):
+        print("Creating huggingface_cache directory within comfy")
+        os.mkdir(os.path.join(cwd, "huggingface_cache"))
+
+    return str(os.path.join(cwd, "huggingface_cache"))
+
+
+class ConsistencyDecoder:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {"latent": ("LATENT",)}}
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "decode"
+    CATEGORY = "latent"
+
+    def __init__(self):
+        self.vae = (
+            ConsistencyDecoderVAE.from_pretrained(
+                "openai/consistency-decoder",
+                torch_dtype=torch.float16,
+                variant="fp16",
+                use_safetensors=True,
+                cache_dir=find_or_create_cache(),
+            )
+            .eval()
+            .to("cuda")
+        )
+
+    def _decode(self, latent):
+        """Used when patching another vae."""
+        return self.vae.decode(latent.half().cuda()).sample
+
+    def decode(self, latent):
+        """Used for standalone decoding."""
+        sample = self._decode(latent["samples"])
+        sample = sample.clamp(-1, 1).movedim(1, -1).add(1.0).mul(0.5).cpu()
+        return (sample,)
+
+
+class PatchDecoderTiled:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {"vae": ("VAE",)}}
+
+    RETURN_TYPES = ("VAE",)
+    FUNCTION = "patch"
+    category = "vae"
+
+    def __init__(self):
+        self.vae = ConsistencyDecoder()
+
+    def patch(self, vae):
+        del vae.first_stage_model.decoder
+        vae.first_stage_model.decode = self.vae._decode
+        vae.decode = (
+            lambda x: vae.decode_tiled_(
+                x,
+                tile_x=512,
+                tile_y=512,
+                overlap=64,
+            )
+            .to("cuda")
+            .movedim(1, -1)
+        )
+
+        return (vae,)
+
+
+# quick node to set SDXL-friendly aspect ratios in 1024^2
+# adapted from throttlekitty
+class SDXLAspectRatio:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+            }
+        }
+
+    RETURN_TYPES = ("INT", "INT")
+    RETURN_NAMES = ("width", "height")
+    FUNCTION = "run"
+    CATEGORY = "image"
+
+    def run(self, image: Tensor) -> Tuple[int, int]:
+        _, height, width, _ = image.shape
+        aspect_ratio = width / height
+
+        aspect_ratios = (
+            (1 / 1, 1024, 1024),
+            (2 / 3, 832, 1216),
+            (3 / 4, 896, 1152),
+            (5 / 8, 768, 1216),
+            (9 / 16, 768, 1344),
+            (9 / 19, 704, 1472),
+            (9 / 21, 640, 1536),
+            (3 / 2, 1216, 832),
+            (4 / 3, 1152, 896),
+            (8 / 5, 1216, 768),
+            (16 / 9, 1344, 768),
+            (19 / 9, 1472, 704),
+            (21 / 9, 1536, 640),
+        )
+
+        # find the closest aspect ratio
+        closest = min(aspect_ratios, key=lambda x: abs(x[0] - aspect_ratio))
+
+        return (closest[1], closest[2])
+
+
+class ImageToMultipleOf:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "multiple_of": (
+                    "INT",
+                    {
+                        "default": 64,
+                        "min": 1,
+                        "max": 256,
+                        "step": 16,
+                        "display": "number",
+                    },
+                ),
+                "method": (["center crop", "rescale"],),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("image",)
+    FUNCTION = "run"
+    CATEGORY = "image"
+
+    def run(self, image: Tensor, multiple_of: int, method: str) -> Tuple[Tensor]:
+        """Center crop the image to a specific multiple of a number."""
+        _, height, width, _ = image.shape
+
+        new_height = height - (height % multiple_of)
+        new_width = width - (width % multiple_of)
+
+        if method == "rescale":
+            return (
+                F.interpolate(
+                    image.unsqueeze(0),
+                    size=(new_height, new_width),
+                    mode="bilinear",
+                    align_corners=False,
+                ).squeeze(0),
+            )
+        else:
+            top = (height - new_height) // 2
+            left = (width - new_width) // 2
+            bottom = top + new_height
+            right = left + new_width
+            return (image[:, top:bottom, left:right, :],)
+
+
+class HFHubLoraLoader:
+    def __init__(self):
+        self.loaded_lora = None
+        self.loaded_lora_path = None
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "model": ("MODEL",),
+                "clip": ("CLIP",),
+                "repo_id": ("STRING", {"default": ""}),
+                "subfolder": ("STRING", {"default": ""}),
+                "filename": ("STRING", {"default": ""}),
+                "strength_model": (
+                    "FLOAT",
+                    {"default": 1.0, "min": -20.0, "max": 20.0, "step": 0.01},
+                ),
+                "strength_clip": (
+                    "FLOAT",
+                    {"default": 1.0, "min": -20.0, "max": 20.0, "step": 0.01},
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("MODEL", "CLIP")
+    FUNCTION = "load_lora"
+
+    CATEGORY = "loaders"
+
+    def load_lora(
+        self,
+        model,
+        clip,
+        repo_id: str,
+        subfolder: str,
+        filename: str,
+        strength_model: float,
+        strength_clip: float,
+    ):
+        if strength_model == 0 and strength_clip == 0:
+            return (model, clip)
+
+        lora_path = hf_hub_download(
+            repo_id=repo_id.strip(),
+            subfolder=(
+                None
+                if subfolder is None or subfolder.strip() == ""
+                else subfolder.strip()
+            ),
+            filename=filename.strip(),
+            cache_dir=find_or_create_cache(),
+        )
+
+        lora = None
+        if self.loaded_lora is not None:
+            if self.loaded_lora_path == lora_path:
+                lora = self.loaded_lora
+            else:
+                self.loaded_lora = None
+                self.loaded_lora_path = None
+
+        if lora is None:
+            lora = comfy.utils.load_torch_file(lora_path, safe_load=True)
+            self.loaded_lora = lora
+            self.loaded_lora_path = lora_path
+
+        model_lora, clip_lora = comfy.sd.load_lora_for_models(
+            model, clip, lora, strength_model, strength_clip
+        )
+        return (model_lora, clip_lora)
+
+
+class HFHubEmbeddingLoader:
+    """Load a text model embedding from Huggingface Hub.
+    The connected CLIP model is not manipulated."""
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "clip": ("CLIP",),
+                "repo_id": ("STRING", {"default": ""}),
+                "subfolder": ("STRING", {"default": ""}),
+                "filename": ("STRING", {"default": ""}),
+            }
+        }
+
+    RETURN_TYPES = ("CLIP",)
+    FUNCTION = "download_embedding"
+
+    CATEGORY = "n/a"
+
+    def download_embedding(
+        self,
+        clip: CLIP,  # added to signify it's best put in between nodes
+        repo_id: str,
+        subfolder: str,
+        filename: str,
+    ):
+        hf_hub_download(
+            repo_id=repo_id.strip(),
+            subfolder=(
+                None
+                if subfolder is None or subfolder.strip() == ""
+                else subfolder.strip()
+            ),
+            filename=filename.strip(),
+            local_dir=get_folder_paths("embeddings")[0],
+        )
+
+        return (clip,)
+
+
+class GlifVariable:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "variable": (
+                    [
+                        "",
+                    ],
+                ),
+                "fallback": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "single_line": True,
+                    },
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("STRING", "INT", "FLOAT")
+    FUNCTION = "do_it"
+
+    CATEGORY = "glif/variables"
+
+    @classmethod
+    def VALIDATE_INPUTS(cls, variable: str, fallback: str):
+        # Since we populate dynamically, comfy will report invalid inputs. Override to always return True
+        return True
+
+    def do_it(self, variable: str, fallback: str):
+        variable = variable.strip()
+        fallback = fallback.strip()
+        if variable == "" or (variable.startswith("{") and variable.endswith("}")):
+            variable = fallback
+
+        int_val = 0
+        float_val = 0.0
+        string_val = f"{variable}"
+        try:
+            int_val = int(variable)
+        except Exception:
+            pass
+        try:
+            float_val = float(variable)
+        except Exception:
+            pass
+        return (string_val, int_val, float_val)
+
+
+NODE_CLASS_MAPPINGS = {
+    "GlifConsistencyDecoder": ConsistencyDecoder,
+    "GlifPatchConsistencyDecoderTiled": PatchDecoderTiled,
+    "SDXLAspectRatio": SDXLAspectRatio,
+    "ImageToMultipleOf": ImageToMultipleOf,
+    "HFHubLoraLoader": HFHubLoraLoader,
+    "HFHubEmbeddingLoader": HFHubEmbeddingLoader,
+    "GlifVariable": GlifVariable,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "GlifConsistencyDecoder": "Consistency VAE Decoder",
+    "GlifPatchConsistencyDecoderTiled": "Patch Consistency VAE Decoder",
+    "SDXLAspectRatio": "Image to SDXL compatible WH",
+    "ImageToMultipleOf": "Image to Multiple of",
+    "HFHubLoraLoader": "Load HF Lora",
+    "HFHubEmbeddingLoader": "Load HF Embedding",
+    "GlifVariable": "Glif Variable",
+}

examples/documentation/display_any.md

@@ -0,0 +1,120 @@
+# Display Any
+
+The Display Any node is a debugging and inspection tool that can display any type of input value in ComfyUI. It's particularly useful for understanding data structures and tensor shapes during workflow development.
+
+## Features
+
+- **Universal Input**: Accepts any type of input data (tensors, strings, numbers, lists, dictionaries, etc.)
+- **Two Display Modes**:
+  - **Raw Value**: Shows the string representation of the input
+  - **Tensor Shape**: Extracts and displays the shapes of any tensors found in the input
+- **Nested Structure Support**: Can find tensors within nested dictionaries and lists
+- **UI Output**: Displays results directly in the ComfyUI interface
+
+## Inputs
+
+- **input** (*): Any value you want to display or inspect
+- **mode** (DROPDOWN): Display mode selection
+  - `raw value`: Shows the complete string representation of the input
+  - `tensor shape`: Extracts and shows shapes of any tensors in the input
+
+## Outputs
+
+- **display_text** (STRING): The formatted display text
+
+## Usage Examples
+
+### 1. Display Simple Values
+
+Connect any output to see its raw value:
+```
+String Input: "Hello, ComfyUI!"
+Mode: raw value
+Output: "Hello, ComfyUI!"
+```
+
+### 2. Inspect Tensor Shapes
+
+Great for debugging image processing pipelines:
+```
+Image Tensor: [1, 3, 512, 512]
+Mode: tensor shape
+Output: "[[1, 3, 512, 512]]"
+```
+
+### 3. Debug Complex Data Structures
+
+View nested data structures with multiple tensors:
+```python
+Input: {
+    "images": tensor([1, 3, 256, 256]),
+    "masks": [tensor([256, 256]), tensor([256, 256, 1])],
+    "config": {"steps": 20}
+}
+Mode: tensor shape
+Output: "[[1, 3, 256, 256], [256, 256], [256, 256, 1]]"
+```
+
+### 4. Workflow Debugging
+
+Use Display Any nodes at various points in your workflow to understand data flow:
+- After loading images to verify dimensions
+- Before/after processing nodes to track shape changes
+- To inspect conditioning or latent data structures
+- To view metadata or configuration dictionaries
+
+## Use Cases
+
+### Image Pipeline Debugging
+Place Display Any nodes after image loading and processing nodes to track dimension changes:
+```
+Load Image → Display Any (tensor shape) → Resize → Display Any (tensor shape)
+```
+
+### Latent Space Inspection
+Understand latent dimensions in your workflows:
+```
+VAE Encode → Display Any (tensor shape) → KSampler → Display Any (raw value)
+```
+
+### Configuration Verification
+Display complex configuration objects to ensure correct settings:
+```
+Config Node → Display Any (raw value) → Processing Node
+```
+
+## Tips
+
+1. **Multiple Display Nodes**: You can use multiple Display Any nodes in a single workflow to track data at different stages
+
+2. **Tensor Shape Mode**: Particularly useful when working with:
+   - Image batches to verify batch size
+   - Latent tensors to understand dimensions
+   - Mask arrays to check compatibility
+
+3. **Raw Value Mode**: Best for:
+   - String prompts and text
+   - Configuration dictionaries
+   - Debugging node outputs
+   - Understanding data structure
+
+4. **No Tensors Found**: If you see "No tensors found in input" in tensor shape mode, the input doesn't contain any tensor-like objects (numpy arrays, torch tensors, etc.)
+
+## Technical Notes
+
+- The node uses `str()` for raw value display, providing Python's string representation
+- Tensor shape detection works with any object that has a `shape` attribute
+- Nested structure traversal supports dictionaries, lists, and tuples
+- The output is both displayed in the UI and available as a string output for further processing
+
+## Example Workflow Integration
+
+```
+[Load Image] → [Image Processing] → [Display Any (tensor shape)]
+                                           ↓
+                                    "[[1, 3, 512, 512]]"
+                                           ↓
+[Text Multiline] ← [Concatenate] ← "Image dimensions: "
+```
+
+This creates a text output showing the current image dimensions that can be used elsewhere in your workflow.

examples/documentation/display_text.md

@@ -0,0 +1,147 @@
+# Display Text
+
+The Display Text node provides advanced text display capabilities with smart formatting, interactive features, and responsive design for ComfyUI workflows.
+
+## Features
+
+- **Smart Prompt Detection**: Automatically detects and formats SDXL-style positive/negative prompt pairs
+- **Text Wrapping**: Proper word wrapping that reflows when node is resized
+- **Scrollable Content**: Mouse wheel scrolling for long texts with visual indicators
+- **Copy Functionality**: Always-visible copy button with visual feedback
+- **Split View Mode**: Side-by-side display for prompt pairs
+- **Responsive Design**: Content adapts to node resizing
+
+## Inputs
+
+- **text** (STRING): The text to display
+  - Can be a single text block
+  - Can contain "Positive prompt:" and "Negative prompt:" sections for automatic split view
+
+## Outputs
+
+- **text** (STRING): Pass-through of the input text
+
+## Display Modes
+
+### Single Text Mode
+
+When the input is regular text without prompt markers, it displays as a single scrollable text area with:
+- Word wrapping at word boundaries
+- Vertical scrolling for long content
+- Single copy button for the entire text
+
+### Split View Mode
+
+Automatically activated when text contains both "Positive prompt:" and "Negative prompt:" sections:
+- Side-by-side display with 50/50 split
+- Independent scrolling for each section
+- Separate copy buttons for each prompt
+- Labels are stripped when copying (clean prompts)
+
+## Usage Examples
+
+### 1. Display Generated Prompts
+
+```
+Gemini Prompt → Display Text → Copy to workflow
+```
+The node automatically detects SDXL format and shows positive/negative prompts side-by-side.
+
+### 2. Debug Text Processing
+
+```
+Text Processing → Display Text → Further Processing
+```
+View intermediate text processing results with proper formatting.
+
+### 3. Show Long Descriptions
+
+```
+Load Text → Display Text → Review
+```
+Display long text content with scrolling and word wrapping.
+
+## Interactive Features
+
+### Copy Button
+- Always visible in the top-right corner
+- Shows "✓ Copied!" feedback on click
+- In split view: separate buttons for each section
+- Strips prompt labels for clean copying
+
+### Scrolling
+- Mouse wheel scrolling when hovering over text
+- Visual indicators appear when content is scrollable
+- Smooth scrolling with proper boundaries
+- Independent scrolling in split view mode
+
+### Resizing
+- Text reflows when node width changes
+- Maintains readability at different sizes
+- Split view maintains 50/50 proportions
+- Minimum height ensures usability
+
+## Smart Prompt Detection
+
+The node intelligently detects prompt formats:
+
+1. **SDXL Format**: 
+   - Looks for "Positive prompt:" and "Negative prompt:" markers
+   - Case-insensitive detection
+   - Handles various formatting styles
+
+2. **Label Stripping**:
+   - When copying from split view, labels are removed
+   - "Positive prompt: beautiful sunset" → "beautiful sunset"
+   - Clean prompts ready for direct use
+
+## Styling
+
+- **Font**: Monospace for consistent alignment
+- **Colors**: 
+  - Text: Light gray (#ddd) on dark background
+  - Background: Semi-transparent dark (#1a1a1a)
+  - Borders: Subtle gray (#333)
+- **Spacing**: Comfortable padding and line height
+- **Visual Feedback**: Hover effects on interactive elements
+
+## Use Cases
+
+### Prompt Engineering Workflows
+- Display AI-generated prompts with proper formatting
+- Compare positive and negative prompts side-by-side
+- Copy refined prompts without manual cleanup
+
+### Text Processing Pipelines
+- Debug text transformations at each step
+- View formatted outputs from text nodes
+- Monitor prompt construction workflows
+
+### Documentation and Notes
+- Display workflow instructions
+- Show generation parameters
+- Present formatted metadata
+
+## Technical Details
+
+- **Text Processing**: Preserves original text while adding display formatting
+- **Responsive Design**: CSS-based layout adapts to node dimensions
+- **Event Handling**: Proper event propagation for ComfyUI compatibility
+- **Memory Efficient**: Only renders visible text portions
+
+## Tips
+
+1. **For Long Prompts**: The scrolling feature handles texts of any length efficiently
+2. **Quick Copy**: Use the copy buttons to quickly grab prompts for other nodes
+3. **Resizing**: Drag node edges to find optimal display width for your content
+4. **Split View**: Works best with SDXL-format prompts but handles any dual-section text
+
+## Integration Example
+
+```
+[Gemini Prompt Engineer] → [Display Text] → [Copy Button Click]
+         ↓                        ↓                    ↓
+   SDXL Format            Split View Display    Clean Prompts
+```
+
+This creates a seamless workflow from prompt generation to usage, with the Display Text node providing the visual interface for review and interaction.

examples/documentation/empty_latent_batch.md

@@ -0,0 +1,222 @@
+# Empty Latent Batch Documentation
+
+## Overview
+
+The Empty Latent Batch is a ComfyUI node that creates empty latent tensors with batch support and preset integration. It combines the preset functionality of Width Height Selector with efficient batch processing capabilities, making it ideal for batch workflows and optimized generation pipelines.
+
+## Features
+
+### 🎯 **Preset Integration**
+- **26 Curated Presets**: Full access to SDXL, FLUX, and Ultra-wide presets
+- **Formatted Display**: Shows aspect ratio, megapixels, and model group
+- **Smart Fallback**: Automatic fallback to custom dimensions for invalid presets
+- **Model Optimization**: Preset categories optimized for different model types
+
+### 📦 **Batch Processing**
+- **Configurable Batch Size**: Create 1-64 empty latents in single operation
+- **Memory Efficient**: Uses torch.zeros for optimal memory allocation
+- **Batch Validation**: Prevents excessive memory usage with warnings
+- **ComfyUI Compatible**: Standard latent format for seamless integration
+
+### 🔄 **Visual Swap Button**
+- **Interactive UI**: Blue swap button with hover and click feedback
+- **Preset-Aware Swapping**: Intelligent switching between matching presets
+- **Custom Dimension Support**: Simple value swapping for custom inputs
+- **Visual Feedback**: Button state changes during interaction
+
+### ✅ **Smart Validation**
+- **Dimension Sanitization**: Automatic adjustment to divisible-by-8 constraint
+- **Memory Estimation**: Built-in memory usage calculation
+- **Error Handling**: Graceful handling of invalid inputs with helpful messages
+- **Logging**: Detailed operation logging for debugging
+
+## Node Interface
+
+### Inputs
+- **preset**: Dropdown with 26 formatted preset options + custom
+- **width**: Custom width (64-8192, step 8, default 1024)
+- **height**: Custom height (64-8192, step 8, default 1024)
+- **batch_size**: Number of latents to create (1-64, default 1)
+
+### Outputs
+- **latent**: Dictionary containing batch of empty latent tensors
+- **width**: Final sanitized width (guaranteed divisible by 8)
+- **height**: Final sanitized height (guaranteed divisible by 8)
+
+## Preset Reference
+
+The Empty Latent Batch node uses the same 26 curated presets as the Width Height Selector:
+
+### SDXL Presets (~1 Megapixel)
+Optimized for SDXL models with ~1MP resolution constraint.
+
+### FLUX Presets (High Resolution)
+Higher resolution presets optimized for FLUX models with better quality/speed balance.
+
+### Ultra-Wide Presets (Modern Ratios)
+Modern aspect ratios for ultra-wide and panoramic generation.
+
+*For complete preset details, see [Width Height Selector Documentation](width_height_selector.md#preset-reference)*
+
+## Usage Examples
+
+### Basic Empty Latent Creation
+1. **Select Preset**: Choose from dropdown (e.g., "1024×1024 - 1:1 (1.0MP) - SDXL")
+2. **Set Batch Size**: Enter desired number of latents (e.g., 4)
+3. **Connect Output**: Link latent output to KSampler or other processing nodes
+
+### Custom Batch Creation
+1. **Set Preset**: Select "custom"
+2. **Enter Dimensions**: Input width and height manually
+3. **Set Batch Size**: Configure number of latents needed
+4. **Validation**: Automatic sanitization ensures compatibility
+
+### Orientation Swapping
+1. **Choose Preset**: Any preset (e.g., "1920×1080")
+2. **Click Swap Button**: Blue button in bottom-right corner
+3. **Result**: Gets swapped preset if available, or custom dimensions with swapped values
+4. **Widget Update**: Width/height widgets automatically update
+
+### Memory-Aware Batch Processing
+1. **Large Batch**: Set batch_size to 16 or higher
+2. **Memory Warning**: Node provides memory usage estimation
+3. **Optimization**: Choose appropriate resolution preset for available VRAM
+
+## Common Workflows
+
+### Batch Generation Pipeline
+```
+Empty Latent Batch → KSampler → VAE Decode → Save Image
+(batch_size: 4)      ↓         ↓            ↓
+                   4 samples  4 images    4 files
+```
+- Create 4 empty latents at once
+- Process all through sampling
+- Generate 4 images in single operation
+- Efficient for parameter exploration
+
+### Model Comparison Workflow
+```
+Empty Latent Batch → [Multiple KSamplers] → [Multiple VAE Decoders] → Compare Results
+(batch_size: 8)      ↓                      ↓                        ↓
+                   Split batch            Process variants         Side-by-side
+```
+- Create consistent batch of empty latents
+- Split across different samplers/models
+- Compare results with identical starting conditions
+
+### Upscaling Preparation
+```
+Empty Latent Batch → KSampler → VAE Decode → Resolution Calculator → Upscaler
+(832×1216, batch:4)  ↓         ↓            ↓                     ↓
+                   Sample    Decode       Calculate 2x           Upscale batch
+```
+- Generate batch at base resolution
+- Calculate upscale dimensions
+- Process entire batch through upscaler
+
+### Aspect Ratio Exploration
+```
+Empty Latent Batch → [Clone to multiple orientations] → Parallel Processing
+(1920×1080)          ↓                                  ↓
+[Swap Button] →    Portrait & Landscape versions      Compare orientations
+```
+- Start with base preset
+- Use swap button to create orientation variants
+- Process both simultaneously
+
+## Advanced Features
+
+### Memory Estimation
+The node provides built-in memory estimation for batch operations:
+
+```python
+# Example memory calculations
+Batch Size: 4, Resolution: 1024×1024
+Latent Tensor: 4 × 4 × 128 × 128 = 262,144 elements
+Memory Usage: 262,144 × 4 bytes = 1.0 MB per batch
+```
+
+### Intelligent Preset Handling
+- **Formatted Display**: Shows full metadata in dropdown
+- **Original Extraction**: Extracts original preset name from formatted strings
+- **Validation**: Verifies preset exists before processing
+- **Fallback Logic**: Uses custom dimensions if preset is invalid
+
+### Batch Size Optimization
+- **Performance Warnings**: Alerts for large batch sizes
+- **Memory Limits**: Prevents excessive memory allocation
+- **Hardware Awareness**: Considers available system resources
+
+## Tips and Best Practices
+
+### Batch Size Selection
+- **Small Batches (1-4)**: Good for testing and development
+- **Medium Batches (5-16)**: Efficient for most production workflows
+- **Large Batches (17-64)**: Only for high-memory systems and specific use cases
+
+### Preset Selection
+- **SDXL Projects**: Use SDXL presets for memory efficiency
+- **FLUX Projects**: Use FLUX presets for optimal quality
+- **Ultra-wide Projects**: Ensure sufficient VRAM for large resolutions
+- **Custom Projects**: Use custom dimensions for specific requirements
+
+### Memory Management
+- Monitor memory usage with large batches
+- Use appropriate resolution presets for available VRAM
+- Consider splitting very large batches across multiple nodes
+- Clear GPU memory between large batch operations
+
+### Workflow Integration
+- Always connect all three outputs (latent, width, height)
+- Use width/height outputs for downstream dimension calculations
+- Combine with Resolution Calculator for upscaling workflows
+- Leverage batch processing for efficient parameter exploration
+
+## Troubleshooting
+
+### Common Issues
+- **Out of Memory**: Reduce batch_size or use lower resolution presets
+- **Invalid Dimensions**: Node automatically sanitizes to valid values
+- **Preset Not Found**: Falls back to custom dimensions with warning
+- **Swap Button Not Working**: Ensure node is not collapsed and button is visible
+
+### Performance Optimization
+- **Batch Size**: Start with smaller batches and increase as needed
+- **Resolution**: Use appropriate presets for your model and VRAM
+- **Memory Monitoring**: Watch for memory warnings and adjust accordingly
+- **Cleanup**: Clear unused tensors between large batch operations
+
+### Error Handling
+- **Dimension Validation**: Automatic rounding to nearest valid values
+- **Batch Size Limits**: Clamped to 1-64 range with warnings
+- **Memory Allocation**: Graceful handling of insufficient memory
+- **Preset Fallbacks**: Automatic fallback to custom dimensions
+
+## Technical Details
+
+### Latent Tensor Format
+- **Shape**: [batch_size, 4, height//8, width//8]
+- **Data Type**: torch.float32
+- **Initialization**: torch.zeros for clean empty state
+- **Memory Layout**: Contiguous tensor for optimal performance
+
+### Validation Pipeline
+1. **Preset Extraction**: Parse formatted preset strings
+2. **Dimension Calculation**: Get base dimensions from preset or custom
+3. **Sanitization**: Ensure divisible-by-8 constraint
+4. **Batch Validation**: Check batch size limits
+5. **Memory Estimation**: Calculate expected memory usage
+6. **Tensor Creation**: Allocate and initialize latent tensor
+
+### UI Integration
+- **JavaScript Extension**: Custom UI for swap button functionality
+- **Widget Synchronization**: Auto-update width/height when preset changes
+- **Visual Feedback**: Hover effects and click animations
+- **Event Handling**: Proper mouse event management
+
+### Swap Button Implementation
+- **Position Calculation**: Dynamic positioning based on node size
+- **State Management**: Visual feedback for button interactions
+- **Preset Intelligence**: Smart switching between compatible presets
+- **Fallback Logic**: Custom dimension swapping when preset not available

examples/documentation/gemini_prompt.md

@@ -0,0 +1,209 @@
+# Gemini Prompt Engineer
+
+The Gemini Prompt Engineer node uses Google's Gemini AI to analyze images and generate optimized prompts for various AI image generation models.
+
+## Features
+
+- **Multi-Model Support**: Generate prompts optimized for FLUX, SDXL, Danbooru, and Video generation
+- **Custom Prompts**: Override templates with your own system prompts
+- **Visual Feedback**: UI shows processing status and error states
+- **Flexible API Key Management**: Multiple ways to provide API credentials
+- **Dynamic Model Selection**: Fetch and use latest Gemini models with refresh button
+- **Model Caching**: Persistent storage of available models for offline access
+- **Help Integration**: Built-in setup guide accessible via help button
+
+## Setup
+
+### 1. Get API Key
+
+Get your free Gemini API key from [Google AI Studio](https://makersuite.google.com/app/apikey)
+
+### 2. Install Dependencies
+
+```bash
+pip install google-generativeai
+```
+
+### 3. Configure API Key
+
+Choose one of these methods:
+
+1. **Environment Variable** (Recommended):
+   ```bash
+   export GEMINI_API_KEY="your-api-key-here"
+   ```
+
+2. **Config File**:
+   Create `gemini_config.json` in your ComfyUI root directory:
+   ```json
+   {
+     "api_key": "your-api-key-here"
+   }
+   ```
+
+3. **Node Input**:
+   Enter the API key directly in the node's `api_key` field
+
+## Inputs
+
+- **image** (IMAGE): The image to analyze
+- **prompt_type** (DROPDOWN): Type of prompt to generate
+  - `flux`: Detailed artistic prompts with quality markers
+  - `sdxl`: Positive/negative prompt pairs with weight emphasis
+  - `danbooru`: Anime-style booru tags with underscores
+  - `video`: Motion and temporal descriptions for video generation
+- **model** (DROPDOWN): Gemini model selection
+  - Dynamically populated list of available models
+  - Includes latest models like gemini-2.0-flash-exp
+  - Click refresh button to update model list
+- **api_key** (STRING, optional): Gemini API key if not set elsewhere
+- **custom_prompt** (STRING, optional): Override template with custom system prompt
+
+## Outputs
+
+- **prompt** (STRING): Generated prompt text
+- **negative_prompt** (STRING): Negative prompt (only populated for SDXL format)
+
+## Prompt Type Details
+
+### FLUX Format
+Generates detailed prompts optimized for FLUX models:
+- Starts with main subject and action
+- Includes style and medium descriptors
+- Adds lighting and atmosphere details
+- Uses quality markers like "4K", "highly detailed", "award-winning"
+
+Example output:
+```
+majestic mountain landscape at golden hour, oil painting style, dramatic lighting with sun rays piercing through clouds, wide angle composition, warm color palette with orange and purple hues, highly detailed, 4K resolution, trending on ArtStation, photorealistic rendering
+```
+
+### SDXL Format
+Generates positive and negative prompt pairs with enhanced structure:
+- Layered positive prompts: main subject → style → composition → technical
+- Comprehensive negative prompts to avoid common issues
+- Uses parentheses for emphasis: `(detailed eyes:1.2)`
+- Includes quality boosters and technical specifications
+
+Example output:
+```
+Positive prompt:
+beautiful woman with flowing red hair, elegant pose, (detailed eyes:1.2), serene expression
+oil painting style, renaissance art influence, classical portraiture
+golden hour lighting, warm color palette, soft shadows, dramatic chiaroscuro
+centered composition, rule of thirds, shallow depth of field, bokeh background
+masterpiece, best quality, highly detailed, 8k uhd, professional artwork
+
+Negative prompt:
+low quality, worst quality, blurry, out of focus, pixelated, low resolution
+bad anatomy, deformed features, extra limbs, missing limbs, disconnected limbs
+poorly drawn face, poorly drawn hands, amateur drawing, bad proportions
+oversaturated, overexposed, underexposed, bad lighting, harsh shadows
+jpeg artifacts, watermark, signature, text, cropped, duplicate
+```
+
+### Danbooru Format
+Generates booru-style tags for anime artwork:
+- Uses underscores for multi-word concepts
+- Includes character count descriptors (1girl, 2boys)
+- Orders tags from most to least important
+
+Example output:
+```
+1girl, solo, long_hair, blue_eyes, blonde_hair, school_uniform, serafuku, pleated_skirt, thighhighs, smile, looking_at_viewer, classroom, sitting, desk, window, sunlight, highres, masterpiece
+```
+
+### Video Format
+Generates prompts for video generation models:
+- Describes motion and camera movements
+- Includes temporal markers and transitions
+- Specifies technical details like fps and duration
+
+Example output:
+```
+Aerial shot slowly descending toward a misty forest at dawn, camera smoothly transitions to tracking shot following a deer through the trees, photorealistic style, soft golden hour lighting with fog, 10 second duration, 4K resolution 24fps, ending with close-up of deer looking at camera
+```
+
+## Custom System Prompts
+
+You can override any template by providing your own system prompt. This is useful for:
+- Specialized use cases
+- Different language outputs
+- Custom formatting requirements
+- Integration with specific workflows
+
+Example custom prompt:
+```
+You are an expert at analyzing images and creating simple, concise descriptions.
+Focus only on the main subject and primary colors.
+Keep your response under 50 words.
+```
+
+## Error Handling
+
+The node provides clear error messages for common issues:
+- Missing API key
+- API request failures
+- Invalid image inputs
+- Rate limiting
+
+Errors are displayed in the prompt output for easy debugging.
+
+## Model Selection
+
+### Dynamic Model List
+- Click the refresh button (🔄) next to the model dropdown to fetch latest models
+- Models are fetched from Google's API and include all available versions
+- Common models include:
+  - `gemini-2.0-flash-exp`: Latest experimental flash model
+  - `gemini-1.5-pro`: Advanced model with larger context
+  - `gemini-1.5-flash`: Fast and efficient for most tasks
+
+### Model Caching
+- Available models are cached locally for offline access
+- Cache persists across ComfyUI sessions
+- Refresh button updates the cache with latest models
+
+## UI Features
+
+### Help Button
+- Click the help button (?) for quick setup instructions
+- Shows API key setup methods
+- Links to Google AI Studio for key generation
+
+### Status Indicators
+- Processing spinner during API calls
+- Error messages displayed in red
+- Success feedback when prompt is generated
+
+## Tips
+
+1. **API Usage**: Gemini has generous free tier limits, but be mindful of rate limits
+2. **Image Quality**: Higher resolution images provide better analysis results
+3. **Prompt Refinement**: You can chain multiple Gemini nodes with different custom prompts
+4. **Caching**: Results are not cached, so identical images will make new API calls
+5. **Model Selection**: Use flash models for faster responses, pro models for complex analysis
+
+## Example Workflow
+
+1. Load an image using Load Image node
+2. Connect to Gemini Prompt Engineer
+3. Select appropriate prompt_type for your target model
+4. Connect prompt output to your generation model
+5. For SDXL, connect both prompt and negative_prompt outputs
+
+## Troubleshooting
+
+**"API key not found" error**:
+- Check environment variable is set correctly
+- Verify config file path and JSON format
+- Try entering key directly in node
+
+**"No response generated" error**:
+- Check internet connection
+- Verify API key is valid
+- Image might be too large (resize if needed)
+
+**Import error for google-generativeai**:
+- Run `pip install google-generativeai` in your ComfyUI environment
+- Restart ComfyUI after installation

examples/documentation/image_to_multiple_of.md

@@ -0,0 +1,82 @@
+# Image to Multiple Of
+
+## Overview
+
+The **Image to Multiple Of** node adjusts image dimensions to be multiples of a specified value. This is particularly useful for models that require input dimensions to be multiples of certain values (e.g., 8, 16, 32, 64) for optimal performance or compatibility.
+
+## Purpose
+
+Many AI models, especially diffusion models and VAEs, require input dimensions to be multiples of specific values due to their architecture (e.g., downsampling layers). This node ensures your images meet these requirements without manual calculation.
+
+## Inputs
+
+- **image** (IMAGE, required): The input image to process
+- **multiple_of** (INT, required): The value that dimensions should be multiple of
+  - Default: 64
+  - Range: 1-256
+  - Step: 16
+- **method** (COMBO, required): Processing method
+  - Options: "center crop", "rescale"
+
+## Outputs
+
+- **image** (IMAGE): Processed image with dimensions adjusted to multiples of the specified value
+
+## Processing Methods
+
+### Center Crop
+- Crops the image from the center to achieve the target dimensions
+- Preserves image quality but may lose edge content
+- Best for images where the important content is centered
+
+### Rescale
+- Resizes the image to the target dimensions using bilinear interpolation
+- Keeps all content but may slightly affect image quality
+- Best when you need to preserve all image content
+
+## Usage Examples
+
+### Example 1: Prepare for VAE Encoding
+```
+Load Image → Image to Multiple Of (multiple_of: 64) → VAE Encode
+```
+
+### Example 2: Prepare for Specific Model Requirements
+```
+Load Image → Image to Multiple Of (multiple_of: 32) → Model Processing
+```
+
+### Example 3: Batch Processing
+```
+Load Images → Image to Multiple Of (multiple_of: 16, method: rescale) → Batch Process
+```
+
+## Technical Details
+
+- Supports batch processing (processes all images in a batch)
+- Works with any number of channels (RGB, RGBA, grayscale, etc.)
+- Calculates the largest dimensions that are less than or equal to the original size
+- For center crop: crops equally from all sides to maintain centering
+- For rescale: uses bilinear interpolation with align_corners=False
+
+## Common Use Cases
+
+1. **VAE Preprocessing**: Ensure images are compatible with VAE encoders that require dimensions divisible by 64
+2. **Model Compatibility**: Adjust images for models with specific architectural requirements
+3. **Batch Uniformity**: Ensure all images in a batch have dimensions that meet model requirements
+4. **Performance Optimization**: Some models perform better with dimensions that are powers of 2
+
+## Tips
+
+- Use **center crop** when your subject is centered and you don't mind losing edge details
+- Use **rescale** when you need to preserve all image content
+- Common multiple_of values: 8, 16, 32, 64, 128
+- For Stable Diffusion models, 64 is typically recommended
+- For some upscaling models, 32 or 16 may be sufficient
+
+## Error Handling
+
+The node will raise an error if:
+- The image dimensions are smaller than the specified multiple_of value
+- Invalid input types are provided
+- The resulting dimensions would be 0 or negative

examples/documentation/kiko_save_image.md

@@ -0,0 +1,213 @@
+# Kiko Save Image
+
+Enhanced image saving node with multiple format support, quality controls, and an interactive floating popup viewer for ComfyUI.
+
+## Features
+
+- **Multiple Format Support**: Save as PNG, JPEG, or WebP with format-specific optimizations
+- **Advanced Quality Controls**: Fine-tune compression settings per format
+- **Floating Popup Viewer**: Interactive window showing saved images immediately
+- **Batch Operations**: Multi-select images for bulk actions
+- **File Size Display**: Real-time feedback on compression effectiveness
+- **Smart UI**: Auto-hide, draggable, resizable popup window
+
+## Inputs
+
+- **images** (IMAGE): Batch of images to save
+- **filename_prefix** (STRING): Prefix for saved filenames
+  - Default: "KikoSave"
+  - Supports subfolder paths (e.g., "outputs/renders/final")
+- **format** (DROPDOWN): Output format selection
+  - `PNG`: Lossless compression, best quality
+  - `JPEG`: Lossy compression, smaller files
+  - `WEBP`: Modern format, best compression ratio
+- **quality** (INT): JPEG/WebP quality level
+  - Range: 1-100 (default: 90)
+  - Higher values = better quality, larger files
+- **png_compress_level** (INT): PNG compression level
+  - Range: 0-9 (default: 4)
+  - Higher values = smaller files, slower saving
+- **webp_lossless** (BOOLEAN): Use lossless WebP compression
+  - Default: False (lossy)
+  - True: Lossless compression like PNG
+- **popup** (BOOLEAN): Enable popup viewer window
+  - Default: True
+  - Toggle per save operation
+
+## Outputs
+
+- **UI**: Enhanced preview data with interactive popup viewer
+
+## Popup Viewer Features
+
+### Window Controls
+- **Drag Handle**: Click and drag the header to move window
+- **Minimize Button**: Collapse to title bar only
+- **Maximize Button**: Expand to larger viewing size
+- **Roll-up Button**: Show/hide content area
+- **Close Button**: Hide the popup (can reopen with toggle)
+
+### Image Grid
+- **Thumbnails**: Click any image to open full-size in new tab
+- **File Info**: Shows filename and size for each image
+- **Quality Indicators**: 
+  - PNG: Compression level (0-9)
+  - JPEG/WebP: Quality percentage
+- **Batch Selection**: Checkboxes for multi-select operations
+
+### Bulk Actions
+- **Open All Selected**: Opens selected images in new tabs
+- **Download All Selected**: Downloads selected images as a batch
+- **Individual Downloads**: Download button per image
+
+### Smart Behavior
+- **Auto-positioning**: Appears in convenient screen location
+- **Persistence**: Stays open across multiple saves
+- **Auto-hide**: Can be minimized when not needed
+- **Responsive**: Adapts to different image counts
+
+## Format Details
+
+### PNG Format
+- **Pros**: Lossless quality, transparency support, wide compatibility
+- **Cons**: Larger file sizes
+- **Best for**: Final outputs, images with transparency, archival
+- **Compression**: 0 (none) to 9 (maximum)
+  - Level 4 (default) balances size and speed
+  - Level 9 for maximum compression (slow)
+
+### JPEG Format
+- **Pros**: Smaller files, fast loading, universal support
+- **Cons**: Lossy compression, no transparency
+- **Best for**: Web images, previews, photos
+- **Quality**: 1-100%
+  - 90% (default) excellent quality with good compression
+  - 95%+ for near-lossless quality
+  - 70-85% for web optimization
+
+### WebP Format
+- **Pros**: Best compression ratios, supports transparency, modern
+- **Cons**: Limited software support
+- **Best for**: Web deployment, storage optimization
+- **Modes**:
+  - Lossy (default): Excellent compression with quality control
+  - Lossless: PNG-like quality with better compression
+
+## Usage Examples
+
+### High-Quality Archive
+```
+Format: PNG
+Compression: 0-2
+Use Case: Final renders for portfolio or client delivery
+```
+
+### Web Optimization
+```
+Format: JPEG or WebP
+Quality: 80-85
+Use Case: Website images, social media posts
+```
+
+### Balanced Storage
+```
+Format: WebP
+Quality: 90
+Lossless: False
+Use Case: Large batches with storage constraints
+```
+
+### Transparency Preservation
+```
+Format: PNG or WebP (lossless)
+Use Case: Logos, UI elements, cutout images
+```
+
+## Workflow Integration
+
+### Basic Save
+```
+Generate → Kiko Save Image
+           format: PNG
+           popup: enabled
+```
+
+### Format Comparison
+```
+Generate → Kiko Save Image (PNG)    → Compare file sizes
+        ↘ Kiko Save Image (JPEG)   ↗
+        ↘ Kiko Save Image (WebP)   ↗
+```
+
+### Batch Processing
+```
+Batch Generate → Kiko Save Image → Popup Viewer
+                 ↓                  ↓
+                4 images        Select best results
+```
+
+## Tips and Best Practices
+
+1. **Format Selection**:
+   - Use PNG for maximum quality and transparency
+   - Use JPEG for photographs without transparency
+   - Use WebP for modern web deployment
+
+2. **Quality Settings**:
+   - Start with defaults (90 for JPEG/WebP, 4 for PNG)
+   - Adjust based on file size requirements
+   - Preview results in popup before finalizing
+
+3. **Popup Management**:
+   - Drag to second monitor for larger workspace
+   - Use roll-up to save screen space
+   - Disable popup for automated workflows
+
+4. **Batch Operations**:
+   - Use checkboxes to select multiple images
+   - Open all in tabs for side-by-side comparison
+   - Download all for quick collection
+
+5. **File Organization**:
+   - Use subfolders in filename_prefix
+   - Include descriptive prefixes
+   - Let ComfyUI handle timestamp suffixes
+
+## Advantages Over Standard Save Image
+
+- **Immediate Preview**: No need to navigate file system
+- **Format Flexibility**: Choose optimal format per use case
+- **Quality Control**: Fine-tune compression settings
+- **Batch Management**: Handle multiple images efficiently
+- **Modern UI**: Floating interface doesn't interrupt workflow
+- **File Size Awareness**: See compression effectiveness immediately
+- **Quick Access**: One-click opening and downloading
+
+## Technical Details
+
+- **Image Processing**: Uses Pillow for format conversion
+- **Metadata**: Preserves ComfyUI metadata in saved files
+- **File Naming**: Automatic timestamp and counter suffixes
+- **Memory Efficiency**: Processes images individually
+- **Thread Safety**: Proper handling of concurrent saves
+
+## Troubleshooting
+
+**Popup not appearing**:
+- Check that popup input is enabled
+- Look for minimized window
+- Try toggling the popup button in node
+
+**WebP not working**:
+- Ensure Pillow has WebP support
+- Update Pillow: `pip install --upgrade pillow`
+
+**Large file sizes**:
+- Increase compression (PNG) or reduce quality (JPEG/WebP)
+- Consider switching formats
+- Check image dimensions
+
+**Can't see all images**:
+- Scroll within the popup grid
+- Maximize the popup window
+- Images are shown newest first

examples/documentation/resolution_calculator.md

@@ -98,4 +98,4 @@ The Resolution Calculator integrates seamlessly with:
 - Standard ComfyUI image loaders
 - VAE encode/decode operations
 - Upscaler nodes (ESRGAN, Real-ESRGAN, etc.)
-- Custom latent processing workflows
+- Custom latent processing workflows

examples/documentation/sampler_combo.md

@@ -0,0 +1,208 @@
+# Sampler Combo Documentation
+
+## Overview
+
+The Sampler Combo is a unified ComfyUI node that combines sampler, scheduler, steps, and CFG settings into a single interface. It reduces workflow complexity while ensuring compatible parameter combinations and providing optimization recommendations.
+
+## Features
+
+### 🎯 **Unified Configuration**
+- Single node for all sampling parameters
+- Compatible sampler + scheduler combinations
+- Optimized steps and CFG recommendations
+- Reduced workflow complexity
+
+### 🧠 **Smart Recommendations**
+- Scheduler suggestions based on selected sampler
+- Optimal steps range for each sampler
+- CFG scale recommendations
+- Compatibility warnings and suggestions
+
+### ✅ **Built-in Validation**
+- Parameter validation and sanitization
+- Error handling with safe defaults
+- Performance optimization hints
+- Real-time compatibility checking
+
+### 📊 **Analysis Tools**
+- Combo configuration analysis
+- Performance assessment
+- Optimization recommendations
+- Compatibility scoring
+
+## Node Interface
+
+### Inputs
+- **sampler_name**: Dropdown with available sampling algorithms
+- **scheduler**: Dropdown with compatible schedulers
+- **steps**: Integer slider (1-100 steps)
+- **cfg**: Float slider (0.0-20.0 CFG scale)
+
+### Outputs
+- **sampler_name**: Selected sampler algorithm
+- **scheduler**: Selected scheduler algorithm
+- **steps**: Number of sampling steps
+- **cfg**: CFG scale value
+
+## Available Samplers
+
+### Primary Samplers
+| Sampler | Type | Speed | Quality | Best For |
+|---------|------|-------|---------|----------|
+| euler | Deterministic | Fast | Good | General use |
+| euler_ancestral | Stochastic | Fast | Good | Creative variation |
+| heun | Higher-order | Medium | Better | Quality focus |
+| dpm_2 | Multi-step | Medium | Good | Balanced |
+| dpm_2_ancestral | Stochastic | Medium | Good | Creative quality |
+| lms | Linear | Fast | Good | Simple scenes |
+| dpm_fast | Optimized | Very Fast | Good | Speed priority |
+| dpm_adaptive | Adaptive | Variable | Best | Automatic tuning |
+
+### Advanced Samplers
+| Sampler | Type | Speed | Quality | Best For |
+|---------|------|-------|---------|----------|
+| dpmpp_2s_ancestral | Advanced | Medium | Better | High quality |
+| dpmpp_2m | Optimized | Fast | Better | Speed + quality |
+| dpmpp_2m_sde | Stochastic | Medium | Best | Maximum quality |
+| dpmpp_3m_sde | Latest | Medium | Best | Cutting edge |
+| ddim | Classic | Fast | Good | Compatibility |
+| uni_pc | Unified | Fast | Better | Efficiency |
+
+## Available Schedulers
+
+### Linear Schedulers
+- **normal**: Standard linear schedule
+- **linear**: Basic linear distribution
+- **sgm_uniform**: Uniform distribution
+
+### Advanced Schedulers
+- **karras**: Karras noise schedule (recommended)
+- **exponential**: Exponential decay
+- **polyexponential**: Polynomial exponential
+- **beta**: Beta distribution schedule
+
+### Specialized Schedulers
+- **cosine**: Cosine annealing schedule
+- **simple**: Simplified schedule
+- **ddim_uniform**: DDIM uniform schedule
+- **laplace**: Laplace distribution
+
+## Optimization Guidelines
+
+### Recommended Combinations
+
+#### Speed Optimized
+```
+Sampler: euler or dpm_fast
+Scheduler: normal or simple
+Steps: 15-25
+CFG: 6.0-8.0
+```
+
+#### Quality Optimized
+```
+Sampler: dpmpp_2m_sde or dpmpp_3m_sde
+Scheduler: karras
+Steps: 25-35
+CFG: 7.0-9.0
+```
+
+#### Balanced
+```
+Sampler: dpmpp_2m or heun
+Scheduler: karras or normal
+Steps: 20-30
+CFG: 7.0-8.5
+```
+
+### Steps Recommendations
+
+| Sampler Type | Min Steps | Optimal | Max Steps |
+|--------------|-----------|---------|-----------|
+| Fast (euler, dpm_fast) | 10 | 20 | 30 |
+| Standard (heun, dpm_2) | 15 | 25 | 40 |
+| Advanced (dpmpp_*) | 20 | 30 | 50 |
+| Adaptive | 10 | 25 | 100 |
+
+### CFG Scale Guidelines
+
+| Content Type | CFG Range | Recommended |
+|--------------|-----------|-------------|
+| Photorealistic | 5.0-8.0 | 7.0 |
+| Artistic/Stylized | 7.0-12.0 | 9.0 |
+| Abstract/Creative | 8.0-15.0 | 11.0 |
+| Text/Details | 10.0-20.0 | 13.0 |
+
+## Usage Examples
+
+### Basic Configuration
+```
+sampler_name: euler
+scheduler: normal
+steps: 20
+cfg: 7.0
+```
+
+### High Quality Setup
+```
+sampler_name: dpmpp_2m_sde
+scheduler: karras
+steps: 30
+cfg: 8.0
+```
+
+### Speed Priority
+```
+sampler_name: dpm_fast
+scheduler: simple
+steps: 15
+cfg: 6.5
+```
+
+## Advanced Features
+
+### Compatibility Analysis
+The node provides real-time analysis of parameter compatibility:
+- Scheduler compatibility with selected sampler
+- Steps optimization for sampler type
+- CFG scale recommendations
+- Performance impact assessment
+
+### Error Handling
+- Invalid samplers default to 'euler'
+- Invalid schedulers default to 'normal'
+- Out-of-range steps clamped to valid range
+- Invalid CFG values sanitized to safe defaults
+
+### Performance Tips
+1. **Use Karras scheduler** for most samplers (better quality)
+2. **Start with 20-30 steps** for most use cases
+3. **Keep CFG 6.0-9.0** for realistic images
+4. **Try dpmpp_2m** for best speed/quality balance
+5. **Use euler** for fastest generation
+
+## Troubleshooting
+
+### Common Issues
+- **Slow generation**: Try euler or dpm_fast samplers
+- **Poor quality**: Increase steps or try dpmpp_2m_sde
+- **Overcooked images**: Lower CFG scale
+- **Underdetailed**: Increase CFG or steps
+- **Artifacts**: Try karras scheduler or different sampler
+
+### Performance Optimization
+- **GPU Memory**: Lower steps if running out of VRAM
+- **Speed**: Use euler + normal + 15-20 steps
+- **Quality**: Use dpmpp_2m_sde + karras + 25-30 steps
+- **Compatibility**: Stick to euler/heun for broad model support
+
+## Integration
+
+The Sampler Combo node outputs are compatible with all standard ComfyUI sampling nodes:
+- KSampler
+- KSamplerAdvanced
+- Custom sampling workflows
+- Upscaling pipelines
+- Img2img workflows
+
+Connect the outputs directly to your sampling node inputs for streamlined configuration.

examples/documentation/seed_history.md

@@ -164,4 +164,4 @@ See the `examples/workflows/` directory for complete workflow examples demonstra
 - Basic seed tracking workflow
 - Creative iteration with history
 - Technical reproducibility setup
-- Batch processing with seed management
+- Batch processing with seed management

examples/documentation/width_height_selector.md

@@ -147,7 +147,7 @@ Width Height Selector → EmptyLatentImage → Resolution Calculator → Upscale
 
 ### Aspect Ratio Considerations
 - **Portrait**: 3:4, 2:3, 13:19 work well for people
-- **Landscape**: 16:9, 19:13, 7:4 for scenes and objects  
+- **Landscape**: 16:9, 19:13, 7:4 for scenes and objects
 - **Square**: 1:1 for centered compositions
 - **Ultra-wide**: 21:9+ for panoramic and cinematic shots
 
@@ -192,4 +192,4 @@ Width Height Selector → EmptyLatentImage → Resolution Calculator → Upscale
 ### Preset Organization
 - Categorized by model optimization
 - Sorted by aspect ratio within categories
-- Comprehensive tooltips for each preset
+- Comprehensive tooltips for each preset

examples/workflows/display_any_example.json

@@ -0,0 +1,379 @@
+{
+  "id": "display-any-example",
+  "revision": 0,
+  "last_node_id": 11,
+  "last_link_id": 9,
+  "nodes": [
+    {
+      "id": 1,
+      "type": "DisplayAny",
+      "pos": [
+        400,
+        270
+      ],
+      "size": [
+        210,
+        60
+      ],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "input",
+          "type": "*",
+          "link": 1
+        }
+      ],
+      "outputs": [
+        {
+          "name": "display_text",
+          "type": "STRING",
+          "links": [
+            8
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayAny"
+      },
+      "widgets_values": [
+        "tensor shape"
+      ]
+    },
+    {
+      "id": 2,
+      "type": "LoadImage",
+      "pos": [
+        50,
+        270
+      ],
+      "size": [
+        315,
+        314
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            1,
+            5
+          ]
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.47",
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "example.png",
+        "image"
+      ]
+    },
+    {
+      "id": 4,
+      "type": "DisplayAny",
+      "pos": [
+        400,
+        520
+      ],
+      "size": [
+        210,
+        70
+      ],
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "input",
+          "type": "*",
+          "link": 7
+        }
+      ],
+      "outputs": [
+        {
+          "name": "display_text",
+          "type": "STRING",
+          "links": [
+            9
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayAny"
+      },
+      "widgets_values": [
+        "raw value"
+      ]
+    },
+    {
+      "id": 7,
+      "type": "VAELoader",
+      "pos": [
+        -250,
+        410
+      ],
+      "size": [
+        270,
+        58
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "VAE",
+          "type": "VAE",
+          "links": [
+            6
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.47",
+        "Node name for S&R": "VAELoader"
+      },
+      "widgets_values": [
+        "ae.safetensors"
+      ]
+    },
+    {
+      "id": 8,
+      "type": "VAEEncode",
+      "pos": [
+        430,
+        390
+      ],
+      "size": [
+        140,
+        46
+      ],
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "pixels",
+          "type": "IMAGE",
+          "link": 5
+        },
+        {
+          "name": "vae",
+          "type": "VAE",
+          "link": 6
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "links": [
+            7
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.47",
+        "Node name for S&R": "VAEEncode"
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 9,
+      "type": "DisplayText",
+      "pos": [
+        640,
+        270
+      ],
+      "size": [
+        450,
+        278
+      ],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "link": 8
+        }
+      ],
+      "outputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayText"
+      },
+      "widgets_values": [
+        null
+      ]
+    },
+    {
+      "id": 10,
+      "type": "DisplayText",
+      "pos": [
+        640,
+        610
+      ],
+      "size": [
+        590,
+        278
+      ],
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "link": 9
+        }
+      ],
+      "outputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayText"
+      },
+      "widgets_values": [
+        null
+      ]
+    },
+    {
+      "id": 11,
+      "type": "MarkdownNote",
+      "pos": [
+        -320,
+        530
+      ],
+      "size": [
+        350,
+        270
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Display Any Example\n\nUniversal debugging tool:\n- Accepts ANY input type\n- Two modes: raw value or tensor shape\n- Finds tensors in nested structures\n\nUse cases:\n- Debug tensor dimensions\n- Inspect latent data\n- View config objects\n- Track data flow\n\nConnect anything to see its contents!"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    }
+  ],
+  "links": [
+    [
+      1,
+      2,
+      0,
+      1,
+      0,
+      "IMAGE"
+    ],
+    [
+      5,
+      2,
+      0,
+      8,
+      0,
+      "IMAGE"
+    ],
+    [
+      6,
+      7,
+      0,
+      8,
+      1,
+      "VAE"
+    ],
+    [
+      7,
+      8,
+      0,
+      4,
+      0,
+      "*"
+    ],
+    [
+      8,
+      1,
+      0,
+      9,
+      0,
+      "STRING"
+    ],
+    [
+      9,
+      4,
+      0,
+      10,
+      0,
+      "STRING"
+    ]
+  ],
+  "groups": [
+    {
+      "id": 1,
+      "title": "Display Any",
+      "bounding": [
+        -400,
+        130,
+        1740,
+        850
+      ],
+      "color": "#ffffff",
+      "font_size": 24,
+      "flags": {}
+    }
+  ],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 0.6115909044841477,
+      "offset": [
+        689.1392030323894,
+        -27.435530779258137
+      ]
+    },
+    "frontendVersion": "1.23.4",
+    "VHS_latentpreview": true,
+    "VHS_latentpreviewrate": 0,
+    "VHS_MetadataImage": true,
+    "VHS_KeepIntermediate": true
+  },
+  "version": 0.4
+}

examples/workflows/display_text_example.json

@@ -0,0 +1,144 @@
+{
+  "id": "display-text-example",
+  "revision": 0,
+  "last_node_id": 6,
+  "last_link_id": 2,
+  "nodes": [
+    {
+      "id": 1,
+      "type": "DisplayText",
+      "pos": [
+        -160,
+        70
+      ],
+      "size": [
+        500,
+        400
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "link": 2
+        }
+      ],
+      "outputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayText"
+      },
+      "widgets_values": [
+        null
+      ]
+    },
+    {
+      "id": 4,
+      "type": "easy positive",
+      "pos": [
+        -620,
+        70
+      ],
+      "size": [
+        400,
+        200
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "positive",
+          "type": "STRING",
+          "links": [
+            2
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfyui-easy-use",
+        "ver": "1.3.1",
+        "Node name for S&R": "easy positive"
+      },
+      "widgets_values": [
+        "Positive prompt:\nbeautiful landscape, mountains in background, sunset lighting, golden hour, professional photography, high resolution, detailed textures, vibrant colors, masterpiece\n\nNegative prompt:\nlow quality, blurry, pixelated, bad composition, oversaturated, underexposed, amateur"
+      ],
+      "color": "#232",
+      "bgcolor": "#353"
+    },
+    {
+      "id": 6,
+      "type": "MarkdownNote",
+      "pos": [
+        -620,
+        330
+      ],
+      "size": [
+        360,
+        250
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Display Text Example\n\nSmart text display with:\n- Auto-detection of SDXL prompt format\n- Split view for positive/negative prompts\n- Text wrapping and scrolling\n- Copy buttons (strips labels)\n- Responsive resizing\n\nTry editing the text to see:\n1. Single text mode (no prompt markers)\n2. Split view mode (with Positive/Negative prompts)\n\nPerfect for displaying Gemini-generated prompts!"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    }
+  ],
+  "links": [
+    [
+      2,
+      4,
+      0,
+      1,
+      0,
+      "STRING"
+    ]
+  ],
+  "groups": [
+    {
+      "id": 1,
+      "title": "Display Text",
+      "bounding": [
+        -750,
+        -60,
+        1240,
+        700
+      ],
+      "color": "#ffffff",
+      "font_size": 24,
+      "flags": {}
+    }
+  ],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 0.90909090909091,
+      "offset": [
+        720,
+        30
+      ]
+    },
+    "frontendVersion": "1.23.4",
+    "VHS_latentpreview": true,
+    "VHS_latentpreviewrate": 0,
+    "VHS_MetadataImage": true,
+    "VHS_KeepIntermediate": true
+  },
+  "version": 0.4
+}

examples/workflows/empty_latent_batch_example.json

@@ -0,0 +1,301 @@
+{
+  "id": "empty-latent-batch-example",
+  "revision": 0,
+  "last_node_id": 9,
+  "last_link_id": 8,
+  "nodes": [
+    {
+      "id": 1,
+      "type": "EmptyLatentBatch",
+      "pos": [
+        350,
+        350
+      ],
+      "size": [
+        370,
+        210
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "latent",
+          "type": "LATENT",
+          "slot_index": 0,
+          "links": []
+        },
+        {
+          "name": "width",
+          "type": "INT",
+          "slot_index": 1,
+          "links": [
+            4
+          ]
+        },
+        {
+          "name": "height",
+          "type": "INT",
+          "slot_index": 2,
+          "links": [
+            5
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "EmptyLatentBatch"
+      },
+      "widgets_values": [
+        "896×1152 - 7:9 (1.0MP) - SDXL",
+        896,
+        1152,
+        4
+      ]
+    },
+    {
+      "id": 2,
+      "type": "Note",
+      "pos": [
+        -50,
+        320
+      ],
+      "size": [
+        350,
+        250
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {
+        "text": "Empty Latent Batch Example\n\nThis node creates empty latent tensors with:\n- 26 preset resolutions for SDXL/FLUX/Ultra-wide\n- Batch size support (1-64)\n- Interactive swap button\n- Memory usage estimation\n\nConnect to:\n- KSampler for image generation\n- Other latent processing nodes\n\nOutputs sanitized dimensions divisible by 8."
+      },
+      "widgets_values": [
+        "Empty Latent Batch Example\n\nThis node creates empty latent tensors with:\n- 26 preset resolutions for SDXL/FLUX/Ultra-wide\n- Batch size support (1-64)\n- Interactive swap button\n- Memory usage estimation\n\nConnect to:\n- KSampler for image generation\n- Other latent processing nodes\n\nOutputs sanitized dimensions divisible by 8."
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 5,
+      "type": "DisplayAny",
+      "pos": [
+        760,
+        280
+      ],
+      "size": [
+        210,
+        60
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "input",
+          "type": "*",
+          "link": 4
+        }
+      ],
+      "outputs": [
+        {
+          "name": "display_text",
+          "type": "STRING",
+          "links": [
+            7
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayAny"
+      },
+      "widgets_values": [
+        "raw value"
+      ]
+    },
+    {
+      "id": 6,
+      "type": "DisplayAny",
+      "pos": [
+        770,
+        500
+      ],
+      "size": [
+        210,
+        60
+      ],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "input",
+          "type": "*",
+          "link": 5
+        }
+      ],
+      "outputs": [
+        {
+          "name": "display_text",
+          "type": "STRING",
+          "links": [
+            8
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayAny"
+      },
+      "widgets_values": [
+        "raw value"
+      ]
+    },
+    {
+      "id": 8,
+      "type": "DisplayText",
+      "pos": [
+        1000,
+        280
+      ],
+      "size": [
+        210,
+        138
+      ],
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "link": 7
+        }
+      ],
+      "outputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayText"
+      },
+      "widgets_values": [
+        null
+      ]
+    },
+    {
+      "id": 9,
+      "type": "DisplayText",
+      "pos": [
+        1010,
+        500
+      ],
+      "size": [
+        210,
+        138
+      ],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "link": 8
+        }
+      ],
+      "outputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayText"
+      },
+      "widgets_values": [
+        null
+      ]
+    }
+  ],
+  "links": [
+    [
+      4,
+      1,
+      1,
+      5,
+      0,
+      "*"
+    ],
+    [
+      5,
+      1,
+      2,
+      6,
+      0,
+      "*"
+    ],
+    [
+      7,
+      5,
+      0,
+      8,
+      0,
+      "STRING"
+    ],
+    [
+      8,
+      6,
+      0,
+      9,
+      0,
+      "STRING"
+    ]
+  ],
+  "groups": [
+    {
+      "id": 1,
+      "title": "Empty Latent",
+      "bounding": [
+        -110,
+        120,
+        1440,
+        620
+      ],
+      "color": "#ffffff",
+      "font_size": 24,
+      "flags": {}
+    }
+  ],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 0.8264462809917358,
+      "offset": [
+        156.41790912499965,
+        -2.272547312500285
+      ]
+    },
+    "frontendVersion": "1.23.4",
+    "VHS_latentpreview": true,
+    "VHS_latentpreviewrate": 0,
+    "VHS_MetadataImage": true,
+    "VHS_KeepIntermediate": true
+  },
+  "version": 0.4
+}

examples/workflows/gemini_prompt_example.json

@@ -0,0 +1,207 @@
+{
+  "id": "gemini-prompt-example",
+  "revision": 0,
+  "last_node_id": 6,
+  "last_link_id": 4,
+  "nodes": [
+    {
+      "id": 2,
+      "type": "LoadImage",
+      "pos": [
+        300,
+        30
+      ],
+      "size": [
+        315,
+        314
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            3
+          ]
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.47",
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "example.png",
+        "image"
+      ]
+    },
+    {
+      "id": 3,
+      "type": "DisplayText",
+      "pos": [
+        1070,
+        30
+      ],
+      "size": [
+        500,
+        400
+      ],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "link": 4
+        }
+      ],
+      "outputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayText"
+      },
+      "widgets_values": [
+        null
+      ]
+    },
+    {
+      "id": 5,
+      "type": "GeminiPrompt",
+      "pos": [
+        640,
+        30
+      ],
+      "size": [
+        400,
+        276
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 3
+        }
+      ],
+      "outputs": [
+        {
+          "name": "prompt",
+          "type": "STRING",
+          "links": [
+            4
+          ]
+        },
+        {
+          "name": "negative_prompt",
+          "type": "STRING",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "GeminiPrompt"
+      },
+      "widgets_values": [
+        "sdxl",
+        "gemini-2.0-flash",
+        "1234-1234-1234-1234",
+        "",
+        true,
+        null,
+        null,
+        null
+      ]
+    },
+    {
+      "id": 6,
+      "type": "MarkdownNote",
+      "pos": [
+        300,
+        410
+      ],
+      "size": [
+        400,
+        240
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Gemini Prompt Engineer Example\n\nAI-powered image analysis:\n- Analyzes image content and style\n- Generates optimized prompts for FLUX/SDXL/Danbooru/Video\n- Dynamic model selection with refresh button\n- Custom system prompt override\n\nSetup:\n1. Get free API key from Google AI Studio\n2. Set GEMINI_API_KEY env var or use config file\n3. Click refresh button to get latest models\n\nDisplayText automatically shows split view for SDXL prompts!"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    }
+  ],
+  "links": [
+    [
+      3,
+      2,
+      0,
+      5,
+      0,
+      "IMAGE"
+    ],
+    [
+      4,
+      5,
+      0,
+      3,
+      0,
+      "STRING"
+    ]
+  ],
+  "groups": [
+    {
+      "id": 1,
+      "title": "Gemini Prompt Engineer",
+      "bounding": [
+        210,
+        -110,
+        1460,
+        850
+      ],
+      "color": "#ffffff",
+      "font_size": 24,
+      "flags": {}
+    }
+  ],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 0.7513148009015777,
+      "offset": [
+        97.5582232217803,
+        133.12148846503663
+      ]
+    },
+    "frontendVersion": "1.23.4",
+    "VHS_latentpreview": true,
+    "VHS_latentpreviewrate": 0,
+    "VHS_MetadataImage": true,
+    "VHS_KeepIntermediate": true
+  },
+  "version": 0.4
+}

examples/workflows/image_to_multiple_of_example.json

@@ -0,0 +1,552 @@
+{
+  "id": "3cd0ac86-8d11-41e5-9d8b-6621bc810ee6",
+  "revision": 0,
+  "last_node_id": 21,
+  "last_link_id": 21,
+  "nodes": [
+    {
+      "id": 1,
+      "type": "LoadImage",
+      "pos": [
+        -80,
+        850
+      ],
+      "size": [
+        315,
+        314.0000305175781
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "label": "IMAGE",
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            13
+          ]
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.47",
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "example.png",
+        "image"
+      ]
+    },
+    {
+      "id": 8,
+      "type": "GetNode",
+      "pos": [
+        540,
+        840
+      ],
+      "size": [
+        210,
+        34
+      ],
+      "flags": {
+        "collapsed": true
+      },
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "UPSCALE_MODEL",
+          "type": "UPSCALE_MODEL",
+          "links": []
+        }
+      ],
+      "title": "Get_upscale_skin_model",
+      "properties": {
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        "upscale_skin_model"
+      ]
+    },
+    {
+      "id": 9,
+      "type": "ImageUpscaleWithModel",
+      "pos": [
+        530,
+        810
+      ],
+      "size": [
+        221.98202514648438,
+        60
+      ],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "upscale_model",
+          "type": "UPSCALE_MODEL",
+          "link": 16
+        },
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 5
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            10,
+            21
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.28",
+        "Node name for S&R": "ImageUpscaleWithModel",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 10,
+      "type": "ImageToMultipleOf",
+      "pos": [
+        1000,
+        810
+      ],
+      "size": [
+        230,
+        82
+      ],
+      "flags": {},
+      "order": 9,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 6
+        }
+      ],
+      "outputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "links": [
+            18
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfyui-glifnodes",
+        "ver": "1.0.0",
+        "Node name for S&R": "ImageToMultipleOf",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        65,
+        "center crop"
+      ]
+    },
+    {
+      "id": 13,
+      "type": "ImageScaleBy",
+      "pos": [
+        760,
+        810
+      ],
+      "size": [
+        220,
+        82
+      ],
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 10
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            6,
+            19
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.28",
+        "Node name for S&R": "ImageScaleBy",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        "lanczos",
+        0.5000000000000001
+      ]
+    },
+    {
+      "id": 14,
+      "type": "ImageUpscaleWithModel",
+      "pos": [
+        280,
+        830
+      ],
+      "size": [
+        221.98202514648438,
+        60
+      ],
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "upscale_model",
+          "type": "UPSCALE_MODEL",
+          "link": 15
+        },
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 13
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            5,
+            20
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.28",
+        "Node name for S&R": "ImageUpscaleWithModel",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 15,
+      "type": "UpscaleModelLoader",
+      "pos": [
+        -90,
+        720
+      ],
+      "size": [
+        320,
+        60
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "UPSCALE_MODEL",
+          "type": "UPSCALE_MODEL",
+          "links": [
+            15
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.28",
+        "Node name for S&R": "UpscaleModelLoader",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        "4x-ClearRealityV1.pth"
+      ],
+      "color": "#232",
+      "bgcolor": "#353"
+    },
+    {
+      "id": 16,
+      "type": "UpscaleModelLoader",
+      "pos": [
+        140,
+        610
+      ],
+      "size": [
+        320,
+        60
+      ],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "UPSCALE_MODEL",
+          "type": "UPSCALE_MODEL",
+          "links": [
+            16
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.28",
+        "Node name for S&R": "UpscaleModelLoader",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        "1xSkinContrast-High-SuperUltraCompact.pth"
+      ],
+      "color": "#232",
+      "bgcolor": "#353"
+    },
+    {
+      "id": 18,
+      "type": "PreviewImage",
+      "pos": [
+        1260,
+        810
+      ],
+      "size": [
+        270,
+        280
+      ],
+      "flags": {},
+      "order": 11,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 18
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.47",
+        "Node name for S&R": "PreviewImage"
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 19,
+      "type": "PreviewImage",
+      "pos": [
+        1010,
+        940
+      ],
+      "size": [
+        210,
+        258
+      ],
+      "flags": {},
+      "order": 10,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 19
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.47",
+        "Node name for S&R": "PreviewImage"
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 20,
+      "type": "PreviewImage",
+      "pos": [
+        520,
+        940
+      ],
+      "size": [
+        210,
+        258
+      ],
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 20
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.47",
+        "Node name for S&R": "PreviewImage"
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 21,
+      "type": "PreviewImage",
+      "pos": [
+        750,
+        940
+      ],
+      "size": [
+        210,
+        258
+      ],
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 21
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.47",
+        "Node name for S&R": "PreviewImage"
+      },
+      "widgets_values": []
+    }
+  ],
+  "links": [
+    [
+      5,
+      14,
+      0,
+      9,
+      1,
+      "IMAGE"
+    ],
+    [
+      6,
+      13,
+      0,
+      10,
+      0,
+      "IMAGE"
+    ],
+    [
+      10,
+      9,
+      0,
+      13,
+      0,
+      "IMAGE"
+    ],
+    [
+      13,
+      1,
+      0,
+      14,
+      1,
+      "IMAGE"
+    ],
+    [
+      15,
+      15,
+      0,
+      14,
+      0,
+      "UPSCALE_MODEL"
+    ],
+    [
+      16,
+      16,
+      0,
+      9,
+      0,
+      "UPSCALE_MODEL"
+    ],
+    [
+      18,
+      10,
+      0,
+      18,
+      0,
+      "IMAGE"
+    ],
+    [
+      19,
+      13,
+      0,
+      19,
+      0,
+      "IMAGE"
+    ],
+    [
+      20,
+      14,
+      0,
+      20,
+      0,
+      "IMAGE"
+    ],
+    [
+      21,
+      9,
+      0,
+      21,
+      0,
+      "IMAGE"
+    ]
+  ],
+  "groups": [
+    {
+      "id": 1,
+      "title": "Image to Multiple of",
+      "bounding": [
+        -180,
+        420,
+        1800,
+        830
+      ],
+      "color": "#ffffff",
+      "font_size": 24,
+      "flags": {}
+    }
+  ],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 0.6655312045216585,
+      "offset": [
+        292.51725658775155,
+        -375.0766486499791
+      ]
+    },
+    "frontendVersion": "1.23.4",
+    "VHS_latentpreview": true,
+    "VHS_latentpreviewrate": 0,
+    "VHS_MetadataImage": true,
+    "VHS_KeepIntermediate": true
+  },
+  "version": 0.4
+}

examples/workflows/kiko_save_image_example.json

@@ -0,0 +1,147 @@
+{
+  "id": "kiko-save-image-example",
+  "revision": 0,
+  "last_node_id": 4,
+  "last_link_id": 1,
+  "nodes": [
+    {
+      "id": 1,
+      "type": "KikoSaveImage",
+      "pos": [
+        390,
+        80
+      ],
+      "size": [
+        400,
+        390
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 1
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "KikoSaveImage"
+      },
+      "widgets_values": [
+        "KikoSave",
+        "PNG",
+        90,
+        4,
+        false,
+        true
+      ]
+    },
+    {
+      "id": 2,
+      "type": "LoadImage",
+      "pos": [
+        -10,
+        80
+      ],
+      "size": [
+        315,
+        314
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            1
+          ]
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.47",
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "example.png",
+        "image"
+      ]
+    },
+    {
+      "id": 4,
+      "type": "MarkdownNote",
+      "pos": [
+        -10,
+        460
+      ],
+      "size": [
+        370,
+        270
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Kiko Save Image Example\n\nEnhanced image saving with:\n- Format selection: PNG, JPEG, WebP\n- Quality controls per format\n- Floating popup viewer (draggable)\n- Batch operations support\n- File size display\n\nPopup Features:\n- Click images to open in new tab\n- Download individual or selected images\n- Minimize/maximize/roll-up controls\n- Persistent across saves\n\nTry different formats to compare file sizes!"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    }
+  ],
+  "links": [
+    [
+      1,
+      2,
+      0,
+      1,
+      0,
+      "IMAGE"
+    ]
+  ],
+  "groups": [
+    {
+      "id": 1,
+      "title": "Kiko save Image",
+      "bounding": [
+        -110,
+        -60,
+        1020,
+        870
+      ],
+      "color": "#ffffff",
+      "font_size": 24,
+      "flags": {}
+    }
+  ],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 0.7513148009015777,
+      "offset": [
+        648.1018911400128,
+        110.02838653698085
+      ]
+    },
+    "frontendVersion": "1.23.4",
+    "VHS_latentpreview": true,
+    "VHS_latentpreviewrate": 0,
+    "VHS_MetadataImage": true,
+    "VHS_KeepIntermediate": true
+  },
+  "version": 0.4
+}

examples/workflows/resolution_calculator_example.json

@@ -1,47 +1,355 @@
 {
-  "last_node_id": 3,
-  "last_link_id": 2,
+  "id": "41469b2d-d616-479d-879a-95cdc6074a37",
+  "revision": 0,
+  "last_node_id": 11,
+  "last_link_id": 9,
   "nodes": [
     {
       "id": 1,
       "type": "ResolutionCalculator",
-      "pos": [100, 100],
-      "size": {"0": 315, "1": 126},
+      "pos": [
+        -30,
+        210
+      ],
+      "size": [
+        315,
+        126
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "shape": 7,
+          "type": "IMAGE",
+          "link": 5
+        },
+        {
+          "name": "latent",
+          "shape": 7,
+          "type": "LATENT",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "width",
+          "type": "INT",
+          "slot_index": 0,
+          "links": [
+            6
+          ]
+        },
+        {
+          "name": "height",
+          "type": "INT",
+          "slot_index": 1,
+          "links": [
+            7
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "965ad60c74d7f25b1acce890d9c06518e46e6d0b",
+        "Node name for S&R": "ResolutionCalculator",
+        "aux_id": "ComfyAssets/ComfyUI-KikoTools",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        2.5
+      ]
+    },
+    {
+      "id": 6,
+      "type": "LoadImage",
+      "pos": [
+        -340,
+        210
+      ],
+      "size": [
+        274.080078125,
+        314
+      ],
       "flags": {},
       "order": 0,
       "mode": 0,
-      "inputs": [
-        {"name": "image", "type": "IMAGE", "link": null},
-        {"name": "latent", "type": "LATENT", "link": null}
-      ],
+      "inputs": [],
       "outputs": [
-        {"name": "width", "type": "INT", "links": [1], "slot_index": 0},
-        {"name": "height", "type": "INT", "links": [2], "slot_index": 1}
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            5
+          ]
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null
+        }
       ],
-      "properties": {},
-      "widgets_values": [2.0],
-      "category": "ComfyAssets"
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "LoadImage",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        "image-2025-06-13-105737.jpg",
+        "image"
+      ]
     },
     {
-      "id": 2,
-      "type": "Note",
-      "pos": [450, 100],
-      "size": {"0": 400, "1": 200},
+      "id": 7,
+      "type": "MarkdownNote",
+      "pos": [
+        -350,
+        610
+      ],
+      "size": [
+        410,
+        200
+      ],
       "flags": {},
       "order": 1,
       "mode": 0,
       "inputs": [],
       "outputs": [],
-      "properties": {"text": "Resolution Calculator Example\n\nThis node calculates upscaled dimensions from:\n- IMAGE tensors (connect from image loaders)\n- LATENT tensors (connect from VAE encode/generation)\n\nUse cases:\n- Calculate target dimensions for upscalers\n- Plan memory usage for large generations\n- Ensure dimensions are divisible by 8\n\nScale factors optimized for SDXL and FLUX models."},
-      "widgets_values": ["Resolution Calculator Example\n\nThis node calculates upscaled dimensions from:\n- IMAGE tensors (connect from image loaders)\n- LATENT tensors (connect from VAE encode/generation)\n\nUse cases:\n- Calculate target dimensions for upscalers\n- Plan memory usage for large generations\n- Ensure dimensions are divisible by 8\n\nScale factors optimized for SDXL and FLUX models."]
+      "properties": {},
+      "widgets_values": [
+        "Resolution Calculator Example\n\nThis node calculates upscaled dimensions from:\n- IMAGE tensors (connect from image loaders)\n- LATENT tensors (connect from VAE encode/generation)\n\nUse cases:\n- Calculate target dimensions for upscalers\n- Plan memory usage for large generations\n- Ensure dimensions are divisible by 8\n\nScale factors optimized for SDXL and FLUX models."
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 8,
+      "type": "DisplayAny",
+      "pos": [
+        330,
+        160
+      ],
+      "size": [
+        270,
+        58
+      ],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "input",
+          "type": "*",
+          "link": 6
+        }
+      ],
+      "outputs": [
+        {
+          "name": "display_text",
+          "type": "STRING",
+          "links": [
+            8
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayAny"
+      },
+      "widgets_values": [
+        "raw value"
+      ]
+    },
+    {
+      "id": 9,
+      "type": "DisplayAny",
+      "pos": [
+        330,
+        310
+      ],
+      "size": [
+        270,
+        58
+      ],
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "input",
+          "type": "*",
+          "link": 7
+        }
+      ],
+      "outputs": [
+        {
+          "name": "display_text",
+          "type": "STRING",
+          "links": [
+            9
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayAny"
+      },
+      "widgets_values": [
+        "raw value"
+      ]
+    },
+    {
+      "id": 10,
+      "type": "DisplayText",
+      "pos": [
+        670,
+        160
+      ],
+      "size": [
+        210,
+        138
+      ],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "link": 8
+        }
+      ],
+      "outputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayText"
+      },
+      "widgets_values": [
+        null
+      ]
+    },
+    {
+      "id": 11,
+      "type": "DisplayText",
+      "pos": [
+        660,
+        400
+      ],
+      "size": [
+        210,
+        138
+      ],
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "link": 9
+        }
+      ],
+      "outputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "ver": "271cd020c1b2f78e7ee40c1f08e70191fed00012",
+        "Node name for S&R": "DisplayText"
+      },
+      "widgets_values": [
+        null
+      ]
     }
   ],
   "links": [
-    [1, 1, 0, 3, 0, "INT"],
-    [2, 1, 1, 3, 1, "INT"]
+    [
+      5,
+      6,
+      0,
+      1,
+      0,
+      "IMAGE"
+    ],
+    [
+      6,
+      1,
+      0,
+      8,
+      0,
+      "*"
+    ],
+    [
+      7,
+      1,
+      1,
+      9,
+      0,
+      "*"
+    ],
+    [
+      8,
+      8,
+      0,
+      10,
+      0,
+      "STRING"
+    ],
+    [
+      9,
+      9,
+      0,
+      11,
+      0,
+      "STRING"
+    ]
+  ],
+  "groups": [
+    {
+      "id": 1,
+      "title": "Resolution Calculator",
+      "bounding": [
+        -480,
+        20,
+        1480,
+        880
+      ],
+      "color": "#ffffff",
+      "font_size": 24,
+      "flags": {}
+    }
   ],
-  "groups": [],
   "config": {},
-  "extra": {},
+  "extra": {
+    "ue_links": [],
+    "ds": {
+      "scale": 0.45000000000000145,
+      "offset": [
+        1248.1498802376432,
+        256.0155843113725
+      ]
+    },
+    "links_added_by_ue": [],
+    "frontendVersion": "1.23.4",
+    "VHS_latentpreview": true,
+    "VHS_latentpreviewrate": 0,
+    "VHS_MetadataImage": true,
+    "VHS_KeepIntermediate": true
+  },
   "version": 0.4
 }

examples/workflows/sampler_combo_example.json

@@ -0,0 +1,537 @@
+{
+  "id": "972425bd-9910-484d-ad09-f142f534fc61",
+  "revision": 0,
+  "last_node_id": 10,
+  "last_link_id": 13,
+  "nodes": [
+    {
+      "id": 7,
+      "type": "CLIPTextEncode",
+      "pos": [
+        120,
+        390
+      ],
+      "size": [
+        425.27801513671875,
+        180.6060791015625
+      ],
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 5
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "slot_index": 0,
+          "links": [
+            6
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "CLIPTextEncode",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        "text, watermark"
+      ]
+    },
+    {
+      "id": 5,
+      "type": "EmptyLatentImage",
+      "pos": [
+        180,
+        610
+      ],
+      "size": [
+        315,
+        106
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "slot_index": 0,
+          "links": [
+            2
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "EmptyLatentImage",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        512,
+        512,
+        1
+      ]
+    },
+    {
+      "id": 3,
+      "type": "KSampler",
+      "pos": [
+        863,
+        186
+      ],
+      "size": [
+        315,
+        571
+      ],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "model",
+          "type": "MODEL",
+          "link": 1
+        },
+        {
+          "name": "positive",
+          "type": "CONDITIONING",
+          "link": 4
+        },
+        {
+          "name": "negative",
+          "type": "CONDITIONING",
+          "link": 6
+        },
+        {
+          "name": "latent_image",
+          "type": "LATENT",
+          "link": 2
+        },
+        {
+          "name": "steps",
+          "type": "INT",
+          "widget": {
+            "name": "steps"
+          },
+          "link": 12
+        },
+        {
+          "name": "cfg",
+          "type": "FLOAT",
+          "widget": {
+            "name": "cfg"
+          },
+          "link": 13
+        },
+        {
+          "name": "sampler_name",
+          "type": "COMBO",
+          "widget": {
+            "name": "sampler_name"
+          },
+          "link": 10
+        },
+        {
+          "name": "scheduler",
+          "type": "COMBO",
+          "widget": {
+            "name": "scheduler"
+          },
+          "link": 11
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "slot_index": 0,
+          "links": [
+            7
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "KSampler",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        555950987049067,
+        "randomize",
+        20,
+        8,
+        "euler",
+        "normal",
+        1,
+        ""
+      ]
+    },
+    {
+      "id": 8,
+      "type": "VAEDecode",
+      "pos": [
+        1209,
+        188
+      ],
+      "size": [
+        210,
+        46
+      ],
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "samples",
+          "type": "LATENT",
+          "link": 7
+        },
+        {
+          "name": "vae",
+          "type": "VAE",
+          "link": 8
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "slot_index": 0,
+          "links": [
+            9
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "VAEDecode",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 9,
+      "type": "SaveImage",
+      "pos": [
+        1451,
+        189
+      ],
+      "size": [
+        210,
+        270
+      ],
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 9
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "SaveImage",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        "ComfyUI"
+      ]
+    },
+    {
+      "id": 6,
+      "type": "CLIPTextEncode",
+      "pos": [
+        120,
+        180
+      ],
+      "size": [
+        422.84503173828125,
+        164.31304931640625
+      ],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 3
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "slot_index": 0,
+          "links": [
+            4
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "CLIPTextEncode",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        "beautiful scenery nature glass bottle landscape, , purple galaxy bottle,"
+      ]
+    },
+    {
+      "id": 10,
+      "type": "SamplerCombo",
+      "pos": [
+        550,
+        290
+      ],
+      "size": [
+        300,
+        200
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "sampler_name",
+          "type": "COMBO",
+          "slot_index": 0,
+          "links": [
+            10
+          ]
+        },
+        {
+          "name": "scheduler",
+          "type": "COMBO",
+          "slot_index": 1,
+          "links": [
+            11
+          ]
+        },
+        {
+          "name": "steps",
+          "type": "INT",
+          "slot_index": 2,
+          "links": [
+            12
+          ]
+        },
+        {
+          "name": "cfg",
+          "type": "FLOAT",
+          "slot_index": 3,
+          "links": [
+            13
+          ]
+        }
+      ],
+      "properties": {
+        "aux_id": "ComfyAssets/ComfyUI-KikoTools",
+        "ver": "dcf2d679c1a1091c54c2aa8cc04724236723227d",
+        "widget_ue_connectable": {},
+        "Node name for S&R": "SamplerCombo"
+      },
+      "widgets_values": [
+        "dpmpp_2m",
+        "karras",
+        25,
+        7.5
+      ]
+    },
+    {
+      "id": 4,
+      "type": "CheckpointLoaderSimple",
+      "pos": [
+        -220,
+        180
+      ],
+      "size": [
+        315,
+        98
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "MODEL",
+          "type": "MODEL",
+          "slot_index": 0,
+          "links": [
+            1
+          ]
+        },
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "slot_index": 1,
+          "links": [
+            3,
+            5
+          ]
+        },
+        {
+          "name": "VAE",
+          "type": "VAE",
+          "slot_index": 2,
+          "links": [
+            8
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "CheckpointLoaderSimple",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        "sdxl_ckpt/realvisxlV40_v40LightningBakedvae.safetensors"
+      ]
+    }
+  ],
+  "links": [
+    [
+      1,
+      4,
+      0,
+      3,
+      0,
+      "MODEL"
+    ],
+    [
+      2,
+      5,
+      0,
+      3,
+      3,
+      "LATENT"
+    ],
+    [
+      3,
+      4,
+      1,
+      6,
+      0,
+      "CLIP"
+    ],
+    [
+      4,
+      6,
+      0,
+      3,
+      1,
+      "CONDITIONING"
+    ],
+    [
+      5,
+      4,
+      1,
+      7,
+      0,
+      "CLIP"
+    ],
+    [
+      6,
+      7,
+      0,
+      3,
+      2,
+      "CONDITIONING"
+    ],
+    [
+      7,
+      3,
+      0,
+      8,
+      0,
+      "LATENT"
+    ],
+    [
+      8,
+      4,
+      2,
+      8,
+      1,
+      "VAE"
+    ],
+    [
+      9,
+      8,
+      0,
+      9,
+      0,
+      "IMAGE"
+    ],
+    [
+      10,
+      10,
+      0,
+      3,
+      6,
+      "COMBO"
+    ],
+    [
+      11,
+      10,
+      1,
+      3,
+      7,
+      "COMBO"
+    ],
+    [
+      12,
+      10,
+      2,
+      3,
+      4,
+      "INT"
+    ],
+    [
+      13,
+      10,
+      3,
+      3,
+      5,
+      "FLOAT"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {
+    "ue_links": [],
+    "links_added_by_ue": [],
+    "ds": {
+      "scale": 0.9740024562304554,
+      "offset": [
+        75.10666660323399,
+        -252.18018113111526
+      ]
+    },
+    "frontendVersion": "1.21.7",
+    "VHS_latentpreview": true,
+    "VHS_latentpreviewrate": 0,
+    "VHS_MetadataImage": true,
+    "VHS_KeepIntermediate": true
+  },
+  "version": 0.4
+}

examples/workflows/seed_history_example.json

@@ -1,192 +1,111 @@
 {
-  "last_node_id": 8,
-  "last_link_id": 7,
+  "id": "972425bd-9910-484d-ad09-f142f534fc61",
+  "revision": 0,
+  "last_node_id": 11,
+  "last_link_id": 14,
   "nodes": [
     {
-      "id": 1,
-      "type": "SeedHistory",
+      "id": 7,
+      "type": "CLIPTextEncode",
       "pos": [
-        100,
-        100
+        120,
+        390
       ],
-      "size": {
-        "0": 280,
-        "1": 320
+      "size": [
+        425.27801513671875,
+        180.6060791015625
+      ],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 5
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "slot_index": 0,
+          "links": [
+            6
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "CLIPTextEncode",
+        "widget_ue_connectable": {}
       },
+      "widgets_values": [
+        "text, watermark"
+      ]
+    },
+    {
+      "id": 5,
+      "type": "EmptyLatentImage",
+      "pos": [
+        180,
+        610
+      ],
+      "size": [
+        315,
+        106
+      ],
       "flags": {},
       "order": 0,
       "mode": 0,
       "inputs": [],
       "outputs": [
         {
-          "name": "seed",
-          "type": "INT",
-          "links": [
-            1
-          ],
-          "shape": 3
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "SeedHistory"
-      },
-      "widgets_values": [
-        12345
-      ],
-      "color": "#2a363b",
-      "bgcolor": "#3f5159"
-    },
-    {
-      "id": 2,
-      "type": "CheckpointLoaderSimple",
-      "pos": [
-        100,
-        450
-      ],
-      "size": {
-        "0": 315,
-        "1": 98
-      },
-      "flags": {},
-      "order": 1,
-      "mode": 0,
-      "outputs": [
-        {
-          "name": "MODEL",
-          "type": "MODEL",
+          "name": "LATENT",
+          "type": "LATENT",
+          "slot_index": 0,
           "links": [
             2
-          ],
-          "shape": 3
-        },
-        {
-          "name": "CLIP",
-          "type": "CLIP",
-          "links": [
-            3
-          ],
-          "shape": 3
-        },
-        {
-          "name": "VAE",
-          "type": "VAE",
-          "links": [
-            4
-          ],
-          "shape": 3
+          ]
         }
       ],
       "properties": {
-        "Node name for S&R": "CheckpointLoaderSimple"
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "EmptyLatentImage",
+        "widget_ue_connectable": {}
       },
       "widgets_values": [
-        "sd_xl_base_1.0.safetensors"
+        512,
+        512,
+        1
       ]
     },
     {
       "id": 3,
-      "type": "CLIPTextEncode",
-      "pos": [
-        450,
-        100
-      ],
-      "size": {
-        "0": 400,
-        "1": 200
-      },
-      "flags": {},
-      "order": 2,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "clip",
-          "type": "CLIP",
-          "link": 3
-        }
-      ],
-      "outputs": [
-        {
-          "name": "CONDITIONING",
-          "type": "CONDITIONING",
-          "links": [
-            5
-          ],
-          "shape": 3
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "CLIPTextEncode"
-      },
-      "widgets_values": [
-        "a beautiful landscape with mountains and lakes, sunset, detailed, photorealistic"
-      ],
-      "color": "#232",
-      "bgcolor": "#353"
-    },
-    {
-      "id": 4,
-      "type": "CLIPTextEncode",
-      "pos": [
-        450,
-        350
-      ],
-      "size": {
-        "0": 400,
-        "1": 200
-      },
-      "flags": {},
-      "order": 3,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "clip",
-          "type": "CLIP",
-          "link": 3
-        }
-      ],
-      "outputs": [
-        {
-          "name": "CONDITIONING",
-          "type": "CONDITIONING",
-          "links": [
-            6
-          ],
-          "shape": 3
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "CLIPTextEncode"
-      },
-      "widgets_values": [
-        "blurry, low quality, distorted, ugly, deformed"
-      ],
-      "color": "#322",
-      "bgcolor": "#533"
-    },
-    {
-      "id": 5,
       "type": "KSampler",
       "pos": [
-        900,
-        100
+        863,
+        186
+      ],
+      "size": [
+        315,
+        571
       ],
-      "size": {
-        "0": 315,
-        "1": 262
-      },
       "flags": {},
-      "order": 4,
+      "order": 6,
       "mode": 0,
       "inputs": [
         {
           "name": "model",
           "type": "MODEL",
-          "link": 2
+          "link": 1
         },
         {
           "name": "positive",
           "type": "CONDITIONING",
-          "link": 5
+          "link": 4
         },
         {
           "name": "negative",
@@ -196,84 +115,89 @@
         {
           "name": "latent_image",
           "type": "LATENT",
-          "link": null
+          "link": 2
         },
         {
           "name": "seed",
           "type": "INT",
-          "link": 1,
           "widget": {
             "name": "seed"
-          }
+          },
+          "link": 14
+        },
+        {
+          "name": "steps",
+          "type": "INT",
+          "widget": {
+            "name": "steps"
+          },
+          "link": 12
+        },
+        {
+          "name": "cfg",
+          "type": "FLOAT",
+          "widget": {
+            "name": "cfg"
+          },
+          "link": 13
+        },
+        {
+          "name": "sampler_name",
+          "type": "COMBO",
+          "widget": {
+            "name": "sampler_name"
+          },
+          "link": 10
+        },
+        {
+          "name": "scheduler",
+          "type": "COMBO",
+          "widget": {
+            "name": "scheduler"
+          },
+          "link": 11
         }
       ],
       "outputs": [
         {
           "name": "LATENT",
           "type": "LATENT",
+          "slot_index": 0,
           "links": [
             7
-          ],
-          "shape": 3
+          ]
         }
       ],
       "properties": {
-        "Node name for S&R": "KSampler"
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "KSampler",
+        "widget_ue_connectable": {}
       },
       "widgets_values": [
-        12345,
+        231413202715030,
         "randomize",
         20,
         8,
         "euler",
         "normal",
-        1
+        1,
+        ""
       ]
     },
     {
-      "id": 6,
-      "type": "EmptyLatentImage",
-      "pos": [
-        900,
-        400
-      ],
-      "size": {
-        "0": 315,
-        "1": 106
-      },
-      "flags": {},
-      "order": 5,
-      "mode": 0,
-      "outputs": [
-        {
-          "name": "LATENT",
-          "type": "LATENT",
-          "links": [],
-          "shape": 3
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "EmptyLatentImage"
-      },
-      "widgets_values": [
-        1024,
-        1024,
-        1
-      ]
-    },
-    {
-      "id": 7,
+      "id": 8,
       "type": "VAEDecode",
       "pos": [
-        1300,
-        100
+        1209,
+        188
+      ],
+      "size": [
+        210,
+        46
       ],
-      "size": {
-        "0": 210,
-        "1": 46
-      },
       "flags": {},
-      "order": 6,
+      "order": 7,
       "mode": 0,
       "inputs": [
         {
@@ -284,126 +208,437 @@
         {
           "name": "vae",
           "type": "VAE",
-          "link": 4
+          "link": 8
         }
       ],
       "outputs": [
         {
           "name": "IMAGE",
           "type": "IMAGE",
-          "links": [],
-          "shape": 3
+          "slot_index": 0,
+          "links": [
+            9
+          ]
         }
       ],
       "properties": {
-        "Node name for S&R": "VAEDecode"
-      }
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "VAEDecode",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": []
     },
     {
-      "id": 8,
+      "id": 9,
       "type": "SaveImage",
       "pos": [
-        1300,
-        200
+        1451,
+        189
+      ],
+      "size": [
+        210,
+        270
       ],
-      "size": {
-        "0": 315,
-        "1": 270
-      },
       "flags": {},
-      "order": 7,
+      "order": 8,
       "mode": 0,
       "inputs": [
         {
           "name": "images",
           "type": "IMAGE",
-          "link": null
+          "link": 9
         }
       ],
+      "outputs": [],
       "properties": {
-        "Node name for S&R": "SaveImage"
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "SaveImage",
+        "widget_ue_connectable": {}
       },
       "widgets_values": [
         "ComfyUI"
       ]
+    },
+    {
+      "id": 6,
+      "type": "CLIPTextEncode",
+      "pos": [
+        120,
+        180
+      ],
+      "size": [
+        422.84503173828125,
+        164.31304931640625
+      ],
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 3
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "slot_index": 0,
+          "links": [
+            4
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "CLIPTextEncode",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        "beautiful scenery nature glass bottle landscape, , purple galaxy bottle,"
+      ]
+    },
+    {
+      "id": 4,
+      "type": "CheckpointLoaderSimple",
+      "pos": [
+        -220,
+        180
+      ],
+      "size": [
+        315,
+        98
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "MODEL",
+          "type": "MODEL",
+          "slot_index": 0,
+          "links": [
+            1
+          ]
+        },
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "slot_index": 1,
+          "links": [
+            3,
+            5
+          ]
+        },
+        {
+          "name": "VAE",
+          "type": "VAE",
+          "slot_index": 2,
+          "links": [
+            8
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.40",
+        "Node name for S&R": "CheckpointLoaderSimple",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        "sdxl_ckpt/realvisxlV40_v40LightningBakedvae.safetensors"
+      ]
+    },
+    {
+      "id": 10,
+      "type": "SamplerCombo",
+      "pos": [
+        550,
+        360
+      ],
+      "size": [
+        300,
+        200
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "sampler_name",
+          "type": "COMBO",
+          "slot_index": 0,
+          "links": [
+            10
+          ]
+        },
+        {
+          "name": "scheduler",
+          "type": "COMBO",
+          "slot_index": 1,
+          "links": [
+            11
+          ]
+        },
+        {
+          "name": "steps",
+          "type": "INT",
+          "slot_index": 2,
+          "links": [
+            12
+          ]
+        },
+        {
+          "name": "cfg",
+          "type": "FLOAT",
+          "slot_index": 3,
+          "links": [
+            13
+          ]
+        }
+      ],
+      "properties": {
+        "aux_id": "ComfyAssets/ComfyUI-KikoTools",
+        "ver": "dcf2d679c1a1091c54c2aa8cc04724236723227d",
+        "Node name for S&R": "SamplerCombo",
+        "widget_ue_connectable": {}
+      },
+      "widgets_values": [
+        "dpmpp_2m",
+        "karras",
+        25,
+        7.5
+      ]
+    },
+    {
+      "id": 11,
+      "type": "SeedHistory",
+      "pos": [
+        550,
+        100
+      ],
+      "size": [
+        290,
+        220
+      ],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "seed",
+          "type": "INT",
+          "links": [
+            14
+          ]
+        }
+      ],
+      "properties": {
+        "aux_id": "ComfyAssets/ComfyUI-KikoTools",
+        "ver": "dcf2d679c1a1091c54c2aa8cc04724236723227d",
+        "widget_ue_connectable": {},
+        "Node name for S&R": "SeedHistory"
+      },
+      "widgets_values": [
+        893082183398485,
+        "randomize",
+        ""
+      ],
+      "color": "#2a363b",
+      "bgcolor": "#3f5159",
+      "hasBeenResized": true,
+      "seedHistory": [
+        {
+          "seed": 893082183398485,
+          "timestamp": 1750032481153,
+          "dateString": "6/15/2025, 5:08:01 PM"
+        },
+        {
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+          "timestamp": 1750014787315,
+          "dateString": "6/15/2025, 12:13:07 PM"
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+          "timestamp": 1750012659402,
+          "dateString": "6/15/2025, 11:37:39 AM"
+        },
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+          "timestamp": 1750011284415,
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+          "timestamp": 1750011223416,
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+        {
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+          "timestamp": 1750011181407,
+          "dateString": "6/15/2025, 11:13:01 AM"
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+          "timestamp": 1750005515384,
+          "dateString": "6/15/2025, 9:38:35 AM"
+        },
+        {
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+          "timestamp": 1750005462384,
+          "dateString": "6/15/2025, 9:37:42 AM"
+        },
+        {
+          "seed": 267914687236127,
+          "timestamp": 1750005354713,
+          "dateString": "6/15/2025, 9:35:54 AM"
+        }
+      ]
     }
   ],
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     [
       1,
-      1,
-      0,
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       4,
-      "INT"
-    ],
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       0,
-      5,
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       0,
       "MODEL"
     ],
     [
-      3,
       2,
-      1,
+      5,
+      0,
       3,
+      3,
+      "LATENT"
+    ],
+    [
+      3,
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       0,
       "CLIP"
     ],
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       4,
-      2,
-      2,
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+    ],
+    [
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       7,
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+      "CLIP"
+    ],
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+      0,
+      "LATENT"
+    ],
+    [
+      8,
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       1,
       "VAE"
     ],
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-      5,
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+    ],
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       3,
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+    ],
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       1,
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     ],
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       2,
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       0,
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-      "LATENT"
+      3,
+      4,
+      "INT"
     ]
   ],
   "groups": [],
   "config": {},
   "extra": {
+    "ue_links": [],
+    "links_added_by_ue": [],
     "ds": {
-      "scale": 0.9090909090909091,
+      "scale": 0.9740024562304554,
       "offset": [
-        -45.45454545454545,
-        -9.090909090909092
+        2.9611945935278796,
+        36.50023864466208
       ]
     },
-    "info": {
-      "name": "Seed History Example",
-      "author": "ComfyUI-KikoTools",
-      "description": "Example workflow demonstrating the Seed History tool for tracking and managing seed values with an interactive UI.",
-      "version": "1.0",
-      "created": "2024-06-14",
-      "modified": "2024-06-14"
-    }
+    "frontendVersion": "1.21.7",
+    "VHS_latentpreview": true,
+    "VHS_latentpreviewrate": 0,
+    "VHS_MetadataImage": true,
+    "VHS_KeepIntermediate": true
   },
   "version": 0.4
-}
+}

examples/xyz_grid/README.md

@@ -0,0 +1,129 @@
+# XYZ Grid Examples
+
+This directory contains example workflows demonstrating the XYZ Grid nodes for ComfyUI.
+
+## Overview
+
+The XYZ Grid system allows you to create parameter comparison grids with any combination of:
+- Models/Checkpoints
+- Samplers
+- Schedulers
+- CFG Scale
+- Steps
+- Clip Skip
+- VAEs
+- LoRAs
+- Prompts
+- Seeds
+- Flux Guidance
+- Denoise strength
+
+## Basic Usage
+
+1. Add an **XYZ Plot Controller** node to your workflow
+2. Configure X and Y axes (and optionally Z for multiple grids)
+3. Connect the appropriate outputs to your generation nodes
+4. Add an **Image Grid Combiner** node
+5. Connect your generated images to the combiner
+6. Run once - the system handles all iterations automatically!
+
+## Node Descriptions
+
+### XYZ Plot Controller
+
+The main configuration node that drives the grid generation.
+
+**Inputs:**
+- `x_axis_type`: Parameter type for X axis (horizontal)
+- `x_values`: Values to iterate over (comma-separated or range syntax)
+- `y_axis_type`: Parameter type for Y axis (vertical)
+- `y_values`: Values to iterate over
+- `z_axis_type`: (Optional) Parameter type for Z axis (multiple grids)
+- `z_values`: Values for Z axis
+- `auto_queue`: Enable automatic execution queuing
+
+**Outputs:**
+- `grid_data`: Configuration data for the combiner
+- `x_string`, `x_int`, `x_float`: Current X value in different types
+- `y_string`, `y_int`, `y_float`: Current Y value in different types
+- `z_string`, `z_int`, `z_float`: Current Z value in different types
+- `batch_id`: Unique identifier for this grid batch
+
+### Image Grid Combiner
+
+Collects generated images and assembles them into labeled grids.
+
+**Inputs:**
+- `images`: Generated images from your workflow
+- `grid_data`: Configuration from XYZ Plot Controller
+- `font_size`: Size of label text (default: 20)
+- `grid_gap`: Pixel gap between images (default: 10)
+- `label_height`: Height of label area (default: 30)
+- `include_labels`: Whether to add labels (default: true)
+
+**Outputs:**
+- `grid_image`: The assembled grid image(s)
+- `grid_info`: Information about the grid
+
+## Value Syntax
+
+### Lists
+Use comma-separated values:
+```
+euler, euler_ancestral, dpm_2, dpm_2_ancestral
+```
+
+### Ranges
+Use colon syntax for numeric ranges:
+```
+5:10:1     # From 5 to 10, step 1 → [5, 6, 7, 8, 9, 10]
+0.5:2:0.5  # From 0.5 to 2, step 0.5 → [0.5, 1.0, 1.5, 2.0]
+10:50:10   # From 10 to 50, step 10 → [10, 20, 30, 40, 50]
+```
+
+### Model/File Selection
+Use the quick-select dropdowns or type filenames:
+```
+model1.safetensors, model2.ckpt, checkpoint_v3.pt
+```
+
+## Connection Examples
+
+### Varying Sampler
+1. Set X axis to "sampler"
+2. Connect `x_string` output to KSampler's `sampler_name` input
+
+### Varying CFG Scale
+1. Set Y axis to "cfg_scale"
+2. Connect `y_float` output to KSampler's `cfg` input
+
+### Varying Model
+1. Set X axis to "model"
+2. Connect `x_string` output to CheckpointLoader's `ckpt_name` input
+
+### Varying Prompt
+1. Set Y axis to "prompt"
+2. Enter different prompts on separate lines in `y_values`
+3. Connect `y_string` output to CLIPTextEncode's `text` input
+
+## Tips and Tricks
+
+1. **Memory Management**: The system includes intelligent model caching. For large grids with multiple models, it will optimize loading order.
+
+2. **Progress Tracking**: Watch the node title for progress updates (e.g., "XYZ Plot Controller [3/12]")
+
+3. **Large Grids**: Be mindful of total image count. The node shows a warning for grids over 100 images.
+
+4. **Z-Axis**: When using Z-axis, you'll get multiple grid images - one for each Z value.
+
+5. **Label Customization**: Use prefixes to clarify labels (e.g., "CFG=" for CFG values)
+
+## Workflow Files
+
+- `basic_model_cfg_grid.json`: Compare 2 models across 3 CFG values
+- `sampler_comparison.json`: Compare all samplers at different step counts
+- `prompt_variations.json`: Test prompt variations across different models
+- `advanced_3d_grid.json`: Use Z-axis for LoRA strength variations
+- `flux_guidance_test.json`: Test Flux-specific parameters
+
+Load these workflows in ComfyUI to see practical examples of the XYZ Grid system in action!

examples/xyz_grid/advanced_3d_grid.json

@@ -0,0 +1,244 @@
+{
+  "last_node_id": 12,
+  "last_link_id": 18,
+  "nodes": [
+    {
+      "id": 1,
+      "type": "XYZPlotController",
+      "pos": [50, 100],
+      "size": [500, 450],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "grid_data", "type": "XYZ_GRID", "links": [10]},
+        {"name": "x_string", "type": "STRING", "links": [11]},
+        {"name": "y_int", "type": "INT", "links": [12]},
+        {"name": "z_float", "type": "FLOAT", "links": [13]}
+      ],
+      "properties": {},
+      "widgets_values": [
+        "lora",
+        "None, style_lora_v1.safetensors, detail_lora_v2.safetensors, anime_lora_v3.safetensors",
+        "LoRA: ",
+        "seed", 
+        "100, 200, 300, 400, 500",
+        "Seed: ",
+        true,
+        "denoise",
+        "0.4, 0.7, 1.0",
+        "Strength: ",
+        true,
+        false
+      ]
+    },
+    {
+      "id": 2,
+      "type": "CheckpointLoaderSimple",
+      "pos": [600, 100],
+      "size": [315, 98],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "MODEL", "type": "MODEL", "links": [1, 14]},
+        {"name": "CLIP", "type": "CLIP", "links": [2, 3, 15]},
+        {"name": "VAE", "type": "VAE", "links": [4]}
+      ],
+      "properties": {},
+      "widgets_values": ["sd_xl_base_1.0.safetensors"]
+    },
+    {
+      "id": 3,
+      "type": "LoraLoader",
+      "pos": [950, 100],
+      "size": [315, 126],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {"name": "model", "type": "MODEL", "link": 14},
+        {"name": "clip", "type": "CLIP", "link": 15},
+        {"name": "lora_name", "type": "STRING", "link": 11}
+      ],
+      "outputs": [
+        {"name": "MODEL", "type": "MODEL", "links": [16]},
+        {"name": "CLIP", "type": "CLIP", "links": [17, 18]}
+      ],
+      "properties": {},
+      "widgets_values": ["None", 1.0, 1.0]
+    },
+    {
+      "id": 4,
+      "type": "CLIPTextEncode",
+      "pos": [600, 250],
+      "size": [400, 200],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {"name": "clip", "type": "CLIP", "link": 17}
+      ],
+      "outputs": [
+        {"name": "CONDITIONING", "type": "CONDITIONING", "links": [5]}
+      ],
+      "properties": {},
+      "widgets_values": ["a magical forest with glowing mushrooms and fairy lights, ethereal atmosphere, fantasy art"]
+    },
+    {
+      "id": 5,
+      "type": "CLIPTextEncode",
+      "pos": [600, 500],
+      "size": [400, 200],
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {"name": "clip", "type": "CLIP", "link": 18}
+      ],
+      "outputs": [
+        {"name": "CONDITIONING", "type": "CONDITIONING", "links": [6]}
+      ],
+      "properties": {},
+      "widgets_values": ["blurry, low quality, distorted"]
+    },
+    {
+      "id": 6,
+      "type": "EmptyLatentImage",
+      "pos": [1300, 100],
+      "size": [315, 106],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "LATENT", "type": "LATENT", "links": [7]}
+      ],
+      "properties": {},
+      "widgets_values": [512, 512, 1]
+    },
+    {
+      "id": 7,
+      "type": "KSampler",
+      "pos": [1050, 350],
+      "size": [315, 262],
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {"name": "model", "type": "MODEL", "link": 16},
+        {"name": "positive", "type": "CONDITIONING", "link": 5},
+        {"name": "negative", "type": "CONDITIONING", "link": 6},
+        {"name": "latent_image", "type": "LATENT", "link": 7},
+        {"name": "seed", "type": "INT", "link": 12},
+        {"name": "denoise", "type": "FLOAT", "link": 13}
+      ],
+      "outputs": [
+        {"name": "LATENT", "type": "LATENT", "links": [8]}
+      ],
+      "properties": {},
+      "widgets_values": [0, "fixed", 20, 7.5, "dpmpp_2m", "karras", 1.0]
+    },
+    {
+      "id": 8,
+      "type": "VAEDecode",
+      "pos": [1400, 350],
+      "size": [210, 46],
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {"name": "samples", "type": "LATENT", "link": 8},
+        {"name": "vae", "type": "VAE", "link": 4}
+      ],
+      "outputs": [
+        {"name": "IMAGE", "type": "IMAGE", "links": [9]}
+      ],
+      "properties": {}
+    },
+    {
+      "id": 9,
+      "type": "ImageGridCombiner",
+      "pos": [1650, 350],
+      "size": [315, 200],
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {"name": "images", "type": "IMAGE", "link": 9},
+        {"name": "grid_data", "type": "XYZ_GRID", "link": 10}
+      ],
+      "outputs": [
+        {"name": "grid_image", "type": "IMAGE", "links": [19]},
+        {"name": "grid_info", "type": "STRING", "links": null}
+      ],
+      "properties": {},
+      "widgets_values": [18, 8, 30, 30, true]
+    },
+    {
+      "id": 10,
+      "type": "SaveImage",
+      "pos": [2000, 350],
+      "size": [315, 270],
+      "flags": {},
+      "order": 9,
+      "mode": 0,
+      "inputs": [
+        {"name": "images", "type": "IMAGE", "link": 19}
+      ],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": ["lora_seed_strength_3d_grid"]
+    }
+  ],
+  "links": [
+    [1, 2, 0, 7, 0, "MODEL"],
+    [2, 2, 1, 4, 0, "CLIP"],
+    [3, 2, 1, 5, 0, "CLIP"],
+    [4, 2, 2, 8, 1, "VAE"],
+    [5, 4, 0, 7, 1, "CONDITIONING"],
+    [6, 5, 0, 7, 2, "CONDITIONING"],
+    [7, 6, 0, 7, 3, "LATENT"],
+    [8, 7, 0, 8, 0, "LATENT"],
+    [9, 8, 0, 9, 0, "IMAGE"],
+    [10, 1, 0, 9, 1, "XYZ_GRID"],
+    [11, 1, 1, 3, 2, "STRING"],
+    [12, 1, 4, 7, 4, "INT"],
+    [13, 1, 7, 7, 5, "FLOAT"],
+    [14, 2, 0, 3, 0, "MODEL"],
+    [15, 2, 1, 3, 1, "CLIP"],
+    [16, 3, 0, 7, 0, "MODEL"],
+    [17, 3, 1, 4, 0, "CLIP"],
+    [18, 3, 1, 5, 0, "CLIP"],
+    [19, 9, 0, 10, 0, "IMAGE"]
+  ],
+  "groups": [
+    {
+      "title": "3D XYZ Grid Configuration",
+      "bounding": [30, 20, 540, 530],
+      "color": "#3f789e"
+    },
+    {
+      "title": "LoRA Loading Pipeline",
+      "bounding": [580, 20, 700, 220],
+      "color": "#8b4c7a"
+    },
+    {
+      "title": "Generation Pipeline",
+      "bounding": [580, 240, 1060, 480],
+      "color": "#4c7a3f"
+    },
+    {
+      "title": "Grid Assembly & Output",
+      "bounding": [1630, 270, 700, 400],
+      "color": "#7a4c3f"
+    }
+  ],
+  "config": {},
+  "extra": {
+    "info": "This advanced workflow demonstrates 3D grid functionality with X=LoRA (4 options including None), Y=Seed (5 values), and Z=Denoise strength (3 values). This generates 3 separate 4x5 grids, one for each denoise strength, totaling 60 images. Perfect for finding the optimal LoRA and strength combination across different seeds."
+  },
+  "version": 0.4
+}

examples/xyz_grid/advanced_xyz_controller.json

@@ -0,0 +1,64 @@
+{
+  "last_node_id": 5,
+  "last_link_id": 6,
+  "nodes": [
+    {
+      "id": 1,
+      "type": "XYZPlotController",
+      "pos": [100, 100],
+      "size": [400, 300],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "grid_data", "type": "XYZ_GRID", "links": [1]},
+        {"name": "x_string", "type": "STRING", "links": null},
+        {"name": "x_int", "type": "INT", "links": null},
+        {"name": "x_float", "type": "FLOAT", "links": null},
+        {"name": "y_string", "type": "STRING", "links": null},
+        {"name": "y_int", "type": "INT", "links": null},
+        {"name": "y_float", "type": "FLOAT", "links": null},
+        {"name": "z_string", "type": "STRING", "links": null},
+        {"name": "z_int", "type": "INT", "links": null},
+        {"name": "z_float", "type": "FLOAT", "links": null},
+        {"name": "batch_id", "type": "STRING", "links": null}
+      ],
+      "properties": {},
+      "widgets_values": [
+        "models",
+        "cfg_scale", 
+        "none",
+        true
+      ]
+    },
+    {
+      "id": 2,
+      "type": "ImageGridCombiner",
+      "pos": [600, 100],
+      "size": [315, 200],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [
+        {"name": "images", "type": "IMAGE", "link": null},
+        {"name": "grid_data", "type": "XYZ_GRID", "link": 1}
+      ],
+      "outputs": [
+        {"name": "grid_image", "type": "IMAGE", "links": null},
+        {"name": "grid_info", "type": "STRING", "links": null}
+      ],
+      "properties": {},
+      "widgets_values": [20, 10, 30, 30, true]
+    }
+  ],
+  "links": [
+    [1, 1, 0, 2, 1, "XYZ_GRID"]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {
+    "info": "Example workflow showing the new advanced XYZ Plot Controller with dynamic widget addition."
+  },
+  "version": 0.4
+}

examples/xyz_grid/basic_model_cfg_grid.json

@@ -0,0 +1,213 @@
+{
+  "last_node_id": 10,
+  "last_link_id": 15,
+  "nodes": [
+    {
+      "id": 1,
+      "type": "XYZPlotController",
+      "pos": [100, 100],
+      "size": [400, 300],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "grid_data", "type": "XYZ_GRID", "links": [10]},
+        {"name": "x_string", "type": "STRING", "links": [11]},
+        {"name": "y_float", "type": "FLOAT", "links": [12]}
+      ],
+      "properties": {},
+      "widgets_values": [
+        "model",
+        "sd_xl_base_1.0.safetensors, dreamshaperXL_v2.safetensors",
+        "Model: ",
+        "cfg_scale", 
+        "5, 7.5, 10",
+        "CFG: ",
+        true,
+        "none",
+        "",
+        "",
+        true,
+        false
+      ]
+    },
+    {
+      "id": 2,
+      "type": "CheckpointLoaderSimple",
+      "pos": [550, 100],
+      "size": [315, 98],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [
+        {"name": "ckpt_name", "type": "STRING", "link": 11}
+      ],
+      "outputs": [
+        {"name": "MODEL", "type": "MODEL", "links": [1]},
+        {"name": "CLIP", "type": "CLIP", "links": [2, 3]},
+        {"name": "VAE", "type": "VAE", "links": [4]}
+      ],
+      "properties": {},
+      "widgets_values": ["sd_xl_base_1.0.safetensors"]
+    },
+    {
+      "id": 3,
+      "type": "CLIPTextEncode",
+      "pos": [550, 250],
+      "size": [400, 200],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {"name": "clip", "type": "CLIP", "link": 2}
+      ],
+      "outputs": [
+        {"name": "CONDITIONING", "type": "CONDITIONING", "links": [5]}
+      ],
+      "properties": {},
+      "widgets_values": ["a beautiful landscape with mountains and a lake, highly detailed, professional photography"]
+    },
+    {
+      "id": 4,
+      "type": "CLIPTextEncode",
+      "pos": [550, 500],
+      "size": [400, 200],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {"name": "clip", "type": "CLIP", "link": 3}
+      ],
+      "outputs": [
+        {"name": "CONDITIONING", "type": "CONDITIONING", "links": [6]}
+      ],
+      "properties": {},
+      "widgets_values": ["blurry, low quality, distorted"]
+    },
+    {
+      "id": 5,
+      "type": "EmptyLatentImage",
+      "pos": [1000, 100],
+      "size": [315, 106],
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "LATENT", "type": "LATENT", "links": [7]}
+      ],
+      "properties": {},
+      "widgets_values": [1024, 1024, 1]
+    },
+    {
+      "id": 6,
+      "type": "KSampler",
+      "pos": [1000, 250],
+      "size": [315, 262],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {"name": "model", "type": "MODEL", "link": 1},
+        {"name": "positive", "type": "CONDITIONING", "link": 5},
+        {"name": "negative", "type": "CONDITIONING", "link": 6},
+        {"name": "latent_image", "type": "LATENT", "link": 7},
+        {"name": "cfg", "type": "FLOAT", "link": 12}
+      ],
+      "outputs": [
+        {"name": "LATENT", "type": "LATENT", "links": [8]}
+      ],
+      "properties": {},
+      "widgets_values": [42, "fixed", 20, 7.5, "euler", "normal", 1]
+    },
+    {
+      "id": 7,
+      "type": "VAEDecode",
+      "pos": [1350, 250],
+      "size": [210, 46],
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {"name": "samples", "type": "LATENT", "link": 8},
+        {"name": "vae", "type": "VAE", "link": 4}
+      ],
+      "outputs": [
+        {"name": "IMAGE", "type": "IMAGE", "links": [9]}
+      ],
+      "properties": {}
+    },
+    {
+      "id": 8,
+      "type": "ImageGridCombiner",
+      "pos": [1600, 250],
+      "size": [315, 200],
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {"name": "images", "type": "IMAGE", "link": 9},
+        {"name": "grid_data", "type": "XYZ_GRID", "link": 10}
+      ],
+      "outputs": [
+        {"name": "grid_image", "type": "IMAGE", "links": [13]},
+        {"name": "grid_info", "type": "STRING", "links": null}
+      ],
+      "properties": {},
+      "widgets_values": [20, 10, 30, 30, true]
+    },
+    {
+      "id": 9,
+      "type": "SaveImage",
+      "pos": [1950, 250],
+      "size": [315, 270],
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {"name": "images", "type": "IMAGE", "link": 13}
+      ],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": ["model_cfg_comparison"]
+    }
+  ],
+  "links": [
+    [1, 2, 0, 6, 0, "MODEL"],
+    [2, 2, 1, 3, 0, "CLIP"],
+    [3, 2, 1, 4, 0, "CLIP"],
+    [4, 2, 2, 7, 1, "VAE"],
+    [5, 3, 0, 6, 1, "CONDITIONING"],
+    [6, 4, 0, 6, 2, "CONDITIONING"],
+    [7, 5, 0, 6, 3, "LATENT"],
+    [8, 6, 0, 7, 0, "LATENT"],
+    [9, 7, 0, 8, 0, "IMAGE"],
+    [10, 1, 0, 8, 1, "XYZ_GRID"],
+    [11, 1, 1, 2, 0, "STRING"],
+    [12, 1, 5, 6, 4, "FLOAT"],
+    [13, 8, 0, 9, 0, "IMAGE"]
+  ],
+  "groups": [
+    {
+      "title": "XYZ Grid Setup",
+      "bounding": [80, 20, 440, 380],
+      "color": "#3f789e"
+    },
+    {
+      "title": "Image Generation",
+      "bounding": [530, 20, 1050, 720],
+      "color": "#4c7a3f"
+    },
+    {
+      "title": "Grid Output",
+      "bounding": [1580, 170, 700, 400],
+      "color": "#7a4c3f"
+    }
+  ],
+  "config": {},
+  "extra": {
+    "info": "This workflow demonstrates a basic 2x3 grid comparing two models at three different CFG scale values. The XYZ Plot Controller automatically handles all 6 iterations."
+  },
+  "version": 0.4
+}

examples/xyz_grid/flux_guidance_test.json

@@ -0,0 +1,235 @@
+{
+  "last_node_id": 11,
+  "last_link_id": 16,
+  "nodes": [
+    {
+      "id": 1,
+      "type": "XYZPlotController",
+      "pos": [100, 100],
+      "size": [450, 350],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "grid_data", "type": "XYZ_GRID", "links": [10]},
+        {"name": "x_float", "type": "FLOAT", "links": [11]},
+        {"name": "y_float", "type": "FLOAT", "links": [12]}
+      ],
+      "properties": {},
+      "widgets_values": [
+        "flux_guidance",
+        "1.0:5.0:0.5",
+        "Guidance: ",
+        "cfg_scale", 
+        "1.0, 3.0, 5.0, 7.0",
+        "CFG: ",
+        true,
+        "none",
+        "",
+        "",
+        true,
+        false
+      ]
+    },
+    {
+      "id": 2,
+      "type": "CheckpointLoaderSimple",
+      "pos": [600, 100],
+      "size": [315, 98],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "MODEL", "type": "MODEL", "links": [1]},
+        {"name": "CLIP", "type": "CLIP", "links": [2, 3]},
+        {"name": "VAE", "type": "VAE", "links": [4]}
+      ],
+      "properties": {},
+      "widgets_values": ["flux1-dev.safetensors"]
+    },
+    {
+      "id": 3,
+      "type": "FluxGuidance",
+      "pos": [950, 100],
+      "size": [315, 58],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {"name": "conditioning", "type": "CONDITIONING", "link": 14},
+        {"name": "guidance", "type": "FLOAT", "link": 11}
+      ],
+      "outputs": [
+        {"name": "CONDITIONING", "type": "CONDITIONING", "links": [5]}
+      ],
+      "properties": {},
+      "widgets_values": [3.5]
+    },
+    {
+      "id": 4,
+      "type": "CLIPTextEncode",
+      "pos": [600, 250],
+      "size": [400, 200],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {"name": "clip", "type": "CLIP", "link": 2}
+      ],
+      "outputs": [
+        {"name": "CONDITIONING", "type": "CONDITIONING", "links": [14]}
+      ],
+      "properties": {},
+      "widgets_values": ["a stunning digital artwork of a phoenix rising from ashes, vibrant colors, dramatic lighting, highly detailed feathers with fire effects"]
+    },
+    {
+      "id": 5,
+      "type": "CLIPTextEncode",
+      "pos": [600, 500],
+      "size": [400, 200],
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {"name": "clip", "type": "CLIP", "link": 3}
+      ],
+      "outputs": [
+        {"name": "CONDITIONING", "type": "CONDITIONING", "links": [6]}
+      ],
+      "properties": {},
+      "widgets_values": [""]
+    },
+    {
+      "id": 6,
+      "type": "EmptyLatentImage",
+      "pos": [1050, 250],
+      "size": [315, 106],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "LATENT", "type": "LATENT", "links": [7]}
+      ],
+      "properties": {},
+      "widgets_values": [1024, 1024, 1]
+    },
+    {
+      "id": 7,
+      "type": "KSamplerAdvanced",
+      "pos": [1050, 400],
+      "size": [315, 334],
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {"name": "model", "type": "MODEL", "link": 1},
+        {"name": "positive", "type": "CONDITIONING", "link": 5},
+        {"name": "negative", "type": "CONDITIONING", "link": 6},
+        {"name": "latent_image", "type": "LATENT", "link": 7},
+        {"name": "cfg", "type": "FLOAT", "link": 12}
+      ],
+      "outputs": [
+        {"name": "LATENT", "type": "LATENT", "links": [8]}
+      ],
+      "properties": {},
+      "widgets_values": ["enable", 42, "fixed", 20, 1.0, "euler", "simple", 0, 20, "disable"]
+    },
+    {
+      "id": 8,
+      "type": "VAEDecode",
+      "pos": [1400, 400],
+      "size": [210, 46],
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {"name": "samples", "type": "LATENT", "link": 8},
+        {"name": "vae", "type": "VAE", "link": 4}
+      ],
+      "outputs": [
+        {"name": "IMAGE", "type": "IMAGE", "links": [9]}
+      ],
+      "properties": {}
+    },
+    {
+      "id": 9,
+      "type": "ImageGridCombiner",
+      "pos": [1650, 400],
+      "size": [315, 200],
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {"name": "images", "type": "IMAGE", "link": 9},
+        {"name": "grid_data", "type": "XYZ_GRID", "link": 10}
+      ],
+      "outputs": [
+        {"name": "grid_image", "type": "IMAGE", "links": [15]},
+        {"name": "grid_info", "type": "STRING", "links": null}
+      ],
+      "properties": {},
+      "widgets_values": [20, 10, 30, 30, true]
+    },
+    {
+      "id": 10,
+      "type": "SaveImage",
+      "pos": [2000, 400],
+      "size": [315, 270],
+      "flags": {},
+      "order": 9,
+      "mode": 0,
+      "inputs": [
+        {"name": "images", "type": "IMAGE", "link": 15}
+      ],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": ["flux_guidance_cfg_grid"]
+    }
+  ],
+  "links": [
+    [1, 2, 0, 7, 0, "MODEL"],
+    [2, 2, 1, 4, 0, "CLIP"],
+    [3, 2, 1, 5, 0, "CLIP"],
+    [4, 2, 2, 8, 1, "VAE"],
+    [5, 3, 0, 7, 1, "CONDITIONING"],
+    [6, 5, 0, 7, 2, "CONDITIONING"],
+    [7, 6, 0, 7, 3, "LATENT"],
+    [8, 7, 0, 8, 0, "LATENT"],
+    [9, 8, 0, 9, 0, "IMAGE"],
+    [10, 1, 0, 9, 1, "XYZ_GRID"],
+    [11, 1, 2, 3, 1, "FLOAT"],
+    [12, 1, 5, 7, 4, "FLOAT"],
+    [14, 4, 0, 3, 0, "CONDITIONING"],
+    [15, 9, 0, 10, 0, "IMAGE"]
+  ],
+  "groups": [
+    {
+      "title": "Flux Parameter Grid Setup",
+      "bounding": [80, 20, 490, 430],
+      "color": "#3f789e"
+    },
+    {
+      "title": "Flux Model Pipeline",
+      "bounding": [580, 20, 450, 200],
+      "color": "#8b4c7a"
+    },
+    {
+      "title": "Generation Pipeline",
+      "bounding": [580, 240, 810, 520],
+      "color": "#4c7a3f"
+    },
+    {
+      "title": "Grid Output",
+      "bounding": [1630, 320, 700, 400],
+      "color": "#7a4c3f"
+    }
+  ],
+  "config": {},
+  "extra": {
+    "info": "This workflow demonstrates testing Flux-specific parameters. It creates a 9x4 grid comparing Flux guidance values (1.0 to 5.0 in 0.5 steps) against different CFG scales. This is useful for finding the optimal balance between Flux guidance and traditional CFG for your specific use case. Note: Requires Flux model and FluxGuidance node."
+  },
+  "version": 0.4
+}

examples/xyz_grid/prompt_variations.json

@@ -0,0 +1,213 @@
+{
+  "last_node_id": 10,
+  "last_link_id": 15,
+  "nodes": [
+    {
+      "id": 1,
+      "type": "XYZPlotController",
+      "pos": [100, 100],
+      "size": [450, 400],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "grid_data", "type": "XYZ_GRID", "links": [10]},
+        {"name": "x_string", "type": "STRING", "links": [11]},
+        {"name": "y_string", "type": "STRING", "links": [12]}
+      ],
+      "properties": {},
+      "widgets_values": [
+        "model",
+        "sd_xl_base_1.0.safetensors, dreamshaperXL_v2.safetensors, juggernautXL_v8.safetensors",
+        "",
+        "prompt", 
+        "a serene japanese garden with cherry blossoms\na futuristic cyberpunk city at night\na medieval castle on a misty mountain\nan underwater coral reef teeming with life\na cozy cabin in a snowy forest",
+        "",
+        true,
+        "none",
+        "",
+        "",
+        true,
+        false
+      ]
+    },
+    {
+      "id": 2,
+      "type": "CheckpointLoaderSimple",
+      "pos": [600, 100],
+      "size": [315, 98],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [
+        {"name": "ckpt_name", "type": "STRING", "link": 11}
+      ],
+      "outputs": [
+        {"name": "MODEL", "type": "MODEL", "links": [1]},
+        {"name": "CLIP", "type": "CLIP", "links": [2, 3]},
+        {"name": "VAE", "type": "VAE", "links": [4]}
+      ],
+      "properties": {},
+      "widgets_values": ["sd_xl_base_1.0.safetensors"]
+    },
+    {
+      "id": 3,
+      "type": "CLIPTextEncode",
+      "pos": [600, 250],
+      "size": [400, 200],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {"name": "clip", "type": "CLIP", "link": 2},
+        {"name": "text", "type": "STRING", "link": 12, "widget": {"name": "text"}}
+      ],
+      "outputs": [
+        {"name": "CONDITIONING", "type": "CONDITIONING", "links": [5]}
+      ],
+      "properties": {},
+      "widgets_values": ["beautiful scenery"]
+    },
+    {
+      "id": 4,
+      "type": "CLIPTextEncode",
+      "pos": [600, 500],
+      "size": [400, 200],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {"name": "clip", "type": "CLIP", "link": 3}
+      ],
+      "outputs": [
+        {"name": "CONDITIONING", "type": "CONDITIONING", "links": [6]}
+      ],
+      "properties": {},
+      "widgets_values": ["blurry, low quality, distorted, ugly, poorly drawn"]
+    },
+    {
+      "id": 5,
+      "type": "EmptyLatentImage",
+      "pos": [1050, 100],
+      "size": [315, 106],
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "LATENT", "type": "LATENT", "links": [7]}
+      ],
+      "properties": {},
+      "widgets_values": [768, 768, 1]
+    },
+    {
+      "id": 6,
+      "type": "KSampler",
+      "pos": [1050, 250],
+      "size": [315, 262],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {"name": "model", "type": "MODEL", "link": 1},
+        {"name": "positive", "type": "CONDITIONING", "link": 5},
+        {"name": "negative", "type": "CONDITIONING", "link": 6},
+        {"name": "latent_image", "type": "LATENT", "link": 7}
+      ],
+      "outputs": [
+        {"name": "LATENT", "type": "LATENT", "links": [8]}
+      ],
+      "properties": {},
+      "widgets_values": [789012, "fixed", 25, 7.5, "dpmpp_2m", "karras", 1]
+    },
+    {
+      "id": 7,
+      "type": "VAEDecode",
+      "pos": [1400, 250],
+      "size": [210, 46],
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {"name": "samples", "type": "LATENT", "link": 8},
+        {"name": "vae", "type": "VAE", "link": 4}
+      ],
+      "outputs": [
+        {"name": "IMAGE", "type": "IMAGE", "links": [9]}
+      ],
+      "properties": {}
+    },
+    {
+      "id": 8,
+      "type": "ImageGridCombiner",
+      "pos": [1650, 250],
+      "size": [315, 200],
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {"name": "images", "type": "IMAGE", "link": 9},
+        {"name": "grid_data", "type": "XYZ_GRID", "link": 10}
+      ],
+      "outputs": [
+        {"name": "grid_image", "type": "IMAGE", "links": [13]},
+        {"name": "grid_info", "type": "STRING", "links": null}
+      ],
+      "properties": {},
+      "widgets_values": [20, 10, 35, 35, true]
+    },
+    {
+      "id": 9,
+      "type": "SaveImage",
+      "pos": [2000, 250],
+      "size": [315, 270],
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {"name": "images", "type": "IMAGE", "link": 13}
+      ],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": ["prompt_model_variations"]
+    }
+  ],
+  "links": [
+    [1, 2, 0, 6, 0, "MODEL"],
+    [2, 2, 1, 3, 0, "CLIP"],
+    [3, 2, 1, 4, 0, "CLIP"],
+    [4, 2, 2, 7, 1, "VAE"],
+    [5, 3, 0, 6, 1, "CONDITIONING"],
+    [6, 4, 0, 6, 2, "CONDITIONING"],
+    [7, 5, 0, 6, 3, "LATENT"],
+    [8, 6, 0, 7, 0, "LATENT"],
+    [9, 7, 0, 8, 0, "IMAGE"],
+    [10, 1, 0, 8, 1, "XYZ_GRID"],
+    [11, 1, 1, 2, 0, "STRING"],
+    [12, 1, 4, 3, 1, "STRING"],
+    [13, 8, 0, 9, 0, "IMAGE"]
+  ],
+  "groups": [
+    {
+      "title": "Prompt x Model Grid Setup",
+      "bounding": [80, 20, 490, 480],
+      "color": "#3f789e"
+    },
+    {
+      "title": "Image Generation Pipeline",
+      "bounding": [580, 20, 1050, 720],
+      "color": "#4c7a3f"
+    },
+    {
+      "title": "Grid Assembly & Output",
+      "bounding": [1630, 170, 700, 400],
+      "color": "#7a4c3f"
+    }
+  ],
+  "config": {},
+  "extra": {
+    "info": "This workflow creates a 3x5 grid comparing 3 different models with 5 diverse prompt scenarios. Great for seeing how different models interpret various styles and subjects. The Y axis connects directly to the positive prompt input, automatically switching prompts for each row."
+  },
+  "version": 0.4
+}

examples/xyz_grid/sampler_comparison.json

@@ -0,0 +1,212 @@
+{
+  "last_node_id": 10,
+  "last_link_id": 15,
+  "nodes": [
+    {
+      "id": 1,
+      "type": "XYZPlotController",
+      "pos": [100, 100],
+      "size": [400, 350],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "grid_data", "type": "XYZ_GRID", "links": [10]},
+        {"name": "x_string", "type": "STRING", "links": [11]},
+        {"name": "y_int", "type": "INT", "links": [12]}
+      ],
+      "properties": {},
+      "widgets_values": [
+        "sampler",
+        "euler, euler_ancestral, heun, dpm_2, dpm_2_ancestral, lms, dpm_fast, dpm_adaptive, dpmpp_2s_ancestral, dpmpp_sde, dpmpp_2m, ddim",
+        "",
+        "steps", 
+        "10, 20, 30, 50",
+        "Steps: ",
+        true,
+        "none",
+        "",
+        "",
+        true,
+        false
+      ]
+    },
+    {
+      "id": 2,
+      "type": "CheckpointLoaderSimple",
+      "pos": [550, 100],
+      "size": [315, 98],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "MODEL", "type": "MODEL", "links": [1]},
+        {"name": "CLIP", "type": "CLIP", "links": [2, 3]},
+        {"name": "VAE", "type": "VAE", "links": [4]}
+      ],
+      "properties": {},
+      "widgets_values": ["sd_xl_base_1.0.safetensors"]
+    },
+    {
+      "id": 3,
+      "type": "CLIPTextEncode",
+      "pos": [550, 250],
+      "size": [400, 200],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {"name": "clip", "type": "CLIP", "link": 2}
+      ],
+      "outputs": [
+        {"name": "CONDITIONING", "type": "CONDITIONING", "links": [5]}
+      ],
+      "properties": {},
+      "widgets_values": ["a majestic dragon soaring through clouds, fantasy art, highly detailed, epic lighting"]
+    },
+    {
+      "id": 4,
+      "type": "CLIPTextEncode",
+      "pos": [550, 500],
+      "size": [400, 200],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {"name": "clip", "type": "CLIP", "link": 3}
+      ],
+      "outputs": [
+        {"name": "CONDITIONING", "type": "CONDITIONING", "links": [6]}
+      ],
+      "properties": {},
+      "widgets_values": ["blurry, low quality, distorted, ugly"]
+    },
+    {
+      "id": 5,
+      "type": "EmptyLatentImage",
+      "pos": [1000, 100],
+      "size": [315, 106],
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {"name": "LATENT", "type": "LATENT", "links": [7]}
+      ],
+      "properties": {},
+      "widgets_values": [512, 512, 1]
+    },
+    {
+      "id": 6,
+      "type": "KSampler",
+      "pos": [1000, 250],
+      "size": [315, 262],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {"name": "model", "type": "MODEL", "link": 1},
+        {"name": "positive", "type": "CONDITIONING", "link": 5},
+        {"name": "negative", "type": "CONDITIONING", "link": 6},
+        {"name": "latent_image", "type": "LATENT", "link": 7},
+        {"name": "sampler_name", "type": "combo", "link": 11},
+        {"name": "steps", "type": "INT", "link": 12}
+      ],
+      "outputs": [
+        {"name": "LATENT", "type": "LATENT", "links": [8]}
+      ],
+      "properties": {},
+      "widgets_values": [123456, "fixed", 20, 8.0, "euler", "normal", 1]
+    },
+    {
+      "id": 7,
+      "type": "VAEDecode",
+      "pos": [1350, 250],
+      "size": [210, 46],
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {"name": "samples", "type": "LATENT", "link": 8},
+        {"name": "vae", "type": "VAE", "link": 4}
+      ],
+      "outputs": [
+        {"name": "IMAGE", "type": "IMAGE", "links": [9]}
+      ],
+      "properties": {}
+    },
+    {
+      "id": 8,
+      "type": "ImageGridCombiner",
+      "pos": [1600, 250],
+      "size": [315, 200],
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {"name": "images", "type": "IMAGE", "link": 9},
+        {"name": "grid_data", "type": "XYZ_GRID", "link": 10}
+      ],
+      "outputs": [
+        {"name": "grid_image", "type": "IMAGE", "links": [13]},
+        {"name": "grid_info", "type": "STRING", "links": null}
+      ],
+      "properties": {},
+      "widgets_values": [16, 8, 25, 25, true]
+    },
+    {
+      "id": 9,
+      "type": "SaveImage",
+      "pos": [1950, 250],
+      "size": [315, 270],
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {"name": "images", "type": "IMAGE", "link": 13}
+      ],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": ["sampler_steps_comparison"]
+    }
+  ],
+  "links": [
+    [1, 2, 0, 6, 0, "MODEL"],
+    [2, 2, 1, 3, 0, "CLIP"],
+    [3, 2, 1, 4, 0, "CLIP"],
+    [4, 2, 2, 7, 1, "VAE"],
+    [5, 3, 0, 6, 1, "CONDITIONING"],
+    [6, 4, 0, 6, 2, "CONDITIONING"],
+    [7, 5, 0, 6, 3, "LATENT"],
+    [8, 6, 0, 7, 0, "LATENT"],
+    [9, 7, 0, 8, 0, "IMAGE"],
+    [10, 1, 0, 8, 1, "XYZ_GRID"],
+    [11, 1, 1, 6, 4, "combo"],
+    [12, 1, 4, 6, 5, "INT"],
+    [13, 8, 0, 9, 0, "IMAGE"]
+  ],
+  "groups": [
+    {
+      "title": "Sampler vs Steps Grid",
+      "bounding": [80, 20, 440, 430],
+      "color": "#3f789e"
+    },
+    {
+      "title": "Image Generation",
+      "bounding": [530, 20, 1050, 720],
+      "color": "#4c7a3f"
+    },
+    {
+      "title": "Grid Output",
+      "bounding": [1580, 170, 700, 400],
+      "color": "#7a4c3f"
+    }
+  ],
+  "config": {},
+  "extra": {
+    "info": "This workflow creates a 12x4 grid comparing 12 different samplers at 4 step counts (10, 20, 30, 50). Perfect for finding the optimal sampler and step count for your use case. Note: Using smaller image size (512x512) due to the large number of generations (48 total)."
+  },
+  "version": 0.4
+}

examples/xyz_grid_test_workflow.json

@@ -0,0 +1,238 @@
+{
+  "last_node_id": 20,
+  "last_link_id": 30,
+  "nodes": [
+    {
+      "id": 1,
+      "type": "XYZPrompt",
+      "pos": [100, 100],
+      "size": {"0": 350, "1": 400},
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "outputs": [
+        {"name": "prompts", "type": "XYZ_PROMPTS", "links": [1]},
+        {"name": "positive", "type": "STRING", "links": [2]},
+        {"name": "negative", "type": "STRING", "links": [3]},
+        {"name": "count", "type": "INT", "links": null}
+      ],
+      "properties": {"Node name for S&R": "XYZPrompt"},
+      "widgets_values": [
+        true,
+        true,
+        "a beautiful landscape",
+        "ugly, blurry, watermark",
+        "a serene mountain scene",
+        "a vibrant cityscape at night",
+        "a peaceful forest path"
+      ]
+    },
+    {
+      "id": 2,
+      "type": "XYZPlotController",
+      "pos": [500, 100],
+      "size": {"0": 400, "1": 500},
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [
+        {"name": "prompts", "type": "XYZ_PROMPTS", "link": 1}
+      ],
+      "outputs": [
+        {"name": "grid_data", "type": "XYZ_GRID", "links": [4]},
+        {"name": "x_string", "type": "STRING", "links": [5]},
+        {"name": "x_int", "type": "INT", "links": null},
+        {"name": "x_float", "type": "FLOAT", "links": null},
+        {"name": "y_string", "type": "STRING", "links": null},
+        {"name": "y_int", "type": "INT", "links": [6]},
+        {"name": "y_float", "type": "FLOAT", "links": null},
+        {"name": "z_string", "type": "STRING", "links": null},
+        {"name": "z_int", "type": "INT", "links": null},
+        {"name": "z_float", "type": "FLOAT", "links": null},
+        {"name": "batch_id", "type": "STRING", "links": null}
+      ],
+      "properties": {"Node name for S&R": "XYZPlotController"},
+      "widgets_values": [
+        "prompt",
+        "steps",
+        "none",
+        true,
+        "20\n30\n40",
+        ""
+      ]
+    },
+    {
+      "id": 3,
+      "type": "CheckpointLoaderSimple",
+      "pos": [100, 550],
+      "size": {"0": 315, "1": 98},
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "outputs": [
+        {"name": "MODEL", "type": "MODEL", "links": [7]},
+        {"name": "CLIP", "type": "CLIP", "links": [8, 9]},
+        {"name": "VAE", "type": "VAE", "links": [10]}
+      ],
+      "properties": {"Node name for S&R": "CheckpointLoaderSimple"},
+      "widgets_values": ["sd_xl_base_1.0.safetensors"]
+    },
+    {
+      "id": 4,
+      "type": "CLIPTextEncode",
+      "pos": [500, 650],
+      "size": {"0": 400, "1": 200},
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {"name": "clip", "type": "CLIP", "link": 8},
+        {"name": "text", "type": "STRING", "link": 2, "widget": {"name": "text"}}
+      ],
+      "outputs": [
+        {"name": "CONDITIONING", "type": "CONDITIONING", "links": [11]}
+      ],
+      "properties": {"Node name for S&R": "CLIPTextEncode"},
+      "widgets_values": [""]
+    },
+    {
+      "id": 5,
+      "type": "CLIPTextEncode",
+      "pos": [500, 900],
+      "size": {"0": 400, "1": 200},
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {"name": "clip", "type": "CLIP", "link": 9},
+        {"name": "text", "type": "STRING", "link": 3, "widget": {"name": "text"}}
+      ],
+      "outputs": [
+        {"name": "CONDITIONING", "type": "CONDITIONING", "links": [12]}
+      ],
+      "properties": {"Node name for S&R": "CLIPTextEncode"},
+      "widgets_values": [""]
+    },
+    {
+      "id": 6,
+      "type": "EmptyLatentImage",
+      "pos": [950, 550],
+      "size": {"0": 315, "1": 106},
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "outputs": [
+        {"name": "LATENT", "type": "LATENT", "links": [13]}
+      ],
+      "properties": {"Node name for S&R": "EmptyLatentImage"},
+      "widgets_values": [1024, 1024, 1]
+    },
+    {
+      "id": 7,
+      "type": "KSampler",
+      "pos": [950, 700],
+      "size": {"0": 315, "1": 262},
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {"name": "model", "type": "MODEL", "link": 7},
+        {"name": "positive", "type": "CONDITIONING", "link": 11},
+        {"name": "negative", "type": "CONDITIONING", "link": 12},
+        {"name": "latent_image", "type": "LATENT", "link": 13},
+        {"name": "steps", "type": "INT", "link": 6, "widget": {"name": "steps"}}
+      ],
+      "outputs": [
+        {"name": "LATENT", "type": "LATENT", "links": [14]}
+      ],
+      "properties": {"Node name for S&R": "KSampler"},
+      "widgets_values": [
+        156680208700286,
+        "randomize",
+        20,
+        8,
+        "euler",
+        "normal",
+        1
+      ]
+    },
+    {
+      "id": 8,
+      "type": "VAEDecode",
+      "pos": [1300, 700],
+      "size": {"0": 210, "1": 46},
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {"name": "samples", "type": "LATENT", "link": 14},
+        {"name": "vae", "type": "VAE", "link": 10}
+      ],
+      "outputs": [
+        {"name": "IMAGE", "type": "IMAGE", "links": [15]}
+      ],
+      "properties": {"Node name for S&R": "VAEDecode"}
+    },
+    {
+      "id": 9,
+      "type": "ImageGridCombiner",
+      "pos": [1550, 700],
+      "size": {"0": 315, "1": 202},
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {"name": "images", "type": "IMAGE", "link": 15},
+        {"name": "grid_data", "type": "XYZ_GRID", "link": 4}
+      ],
+      "outputs": [
+        {"name": "grid_image", "type": "IMAGE", "links": [16]},
+        {"name": "grid_info", "type": "STRING", "links": null}
+      ],
+      "properties": {"Node name for S&R": "ImageGridCombiner"},
+      "widgets_values": [20, 10, 30, 30, true]
+    },
+    {
+      "id": 10,
+      "type": "SaveImage",
+      "pos": [1900, 700],
+      "size": {"0": 315, "1": 270},
+      "flags": {},
+      "order": 9,
+      "mode": 0,
+      "inputs": [
+        {"name": "images", "type": "IMAGE", "link": 16}
+      ],
+      "properties": {},
+      "widgets_values": ["xyz_grid"]
+    }
+  ],
+  "links": [
+    [1, 1, 0, 2, 0, "XYZ_PROMPTS"],
+    [2, 1, 1, 4, 1, "STRING"],
+    [3, 1, 2, 5, 1, "STRING"],
+    [4, 2, 0, 9, 1, "XYZ_GRID"],
+    [5, 2, 1, 4, 1, "STRING"],
+    [6, 2, 5, 7, 4, "INT"],
+    [7, 3, 0, 7, 0, "MODEL"],
+    [8, 3, 1, 4, 0, "CLIP"],
+    [9, 3, 1, 5, 0, "CLIP"],
+    [10, 3, 2, 8, 1, "VAE"],
+    [11, 4, 0, 7, 1, "CONDITIONING"],
+    [12, 5, 0, 7, 2, "CONDITIONING"],
+    [13, 6, 0, 7, 3, "LATENT"],
+    [14, 7, 0, 8, 0, "LATENT"],
+    [15, 8, 0, 9, 0, "IMAGE"],
+    [16, 9, 0, 10, 0, "IMAGE"]
+  ],
+  "groups": [
+    {
+      "title": "XYZ Grid Test Workflow",
+      "bounding": [80, 20, 2160, 1100],
+      "color": "#3f789e"
+    }
+  ],
+  "config": {},
+  "extra": {},
+  "version": 0.4
+}

kikotools/__init__.py

@@ -7,6 +7,14 @@ from .tools.resolution_calculator import ResolutionCalculatorNode
 from .tools.width_height_selector import WidthHeightSelectorNode
 from .tools.seed_history import SeedHistoryNode
 from .tools.sampler_combo import SamplerComboNode, SamplerComboCompactNode
+from .tools.empty_latent_batch import EmptyLatentBatchNode
+from .tools.kiko_save_image import KikoSaveImageNode
+from .tools.image_to_multiple_of import ImageToMultipleOfNode
+from .tools.image_scale_down_by import ImageScaleDownByNode
+from .tools.gemini_prompt import GeminiPromptNode
+from .tools.display_any import DisplayAnyNode
+from .tools.display_text import DisplayTextNode
+from .tools.xyz_grid import XYZPlotController, ImageGridCombiner, XYZPrompt
 
 # ComfyUI node registration mappings
 NODE_CLASS_MAPPINGS = {
@@ -15,6 +23,16 @@ NODE_CLASS_MAPPINGS = {
     "SeedHistory": SeedHistoryNode,
     "SamplerCombo": SamplerComboNode,
     "SamplerComboCompact": SamplerComboCompactNode,
+    "EmptyLatentBatch": EmptyLatentBatchNode,
+    "KikoSaveImage": KikoSaveImageNode,
+    "ImageToMultipleOf": ImageToMultipleOfNode,
+    "ImageScaleDownBy": ImageScaleDownByNode,
+    "GeminiPrompt": GeminiPromptNode,
+    "DisplayAny": DisplayAnyNode,
+    "DisplayText": DisplayTextNode,
+    "XYZPlotController": XYZPlotController,
+    "ImageGridCombiner": ImageGridCombiner,
+    "XYZPrompt": XYZPrompt,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -23,6 +41,16 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "SeedHistory": "Seed History",
     "SamplerCombo": "Sampler Combo",
     "SamplerComboCompact": "Sampler Combo (Compact)",
+    "EmptyLatentBatch": "Empty Latent Batch",
+    "KikoSaveImage": "Kiko Save Image",
+    "ImageToMultipleOf": "Image to Multiple of",
+    "ImageScaleDownBy": "Image Scale Down By",
+    "GeminiPrompt": "Gemini Prompt Engineer",
+    "DisplayAny": "Display Any",
+    "DisplayText": "Display Text",
+    "XYZPlotController": "XYZ Plot Controller",
+    "ImageGridCombiner": "Image Grid Combiner",
+    "XYZPrompt": "XYZ Prompt",
 }
 
 __all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]

kikotools/tools/display_any/__init__.py

@@ -0,0 +1,5 @@
+"""DisplayAny tool for ComfyUI."""
+
+from .node import DisplayAnyNode
+
+__all__ = ["DisplayAnyNode"]

kikotools/tools/display_any/logic.py

@@ -0,0 +1,64 @@
+"""Logic for DisplayAny node - displays any input value or tensor shape."""
+
+from typing import Any, List, Union
+
+
+def get_tensor_shapes(input_value: Any) -> List[List[int]]:
+    """Extract tensor shapes from nested structures.
+
+    Args:
+        input_value: Any input value that may contain tensors
+
+    Returns:
+        List of tensor shapes found in the input
+    """
+    shapes = []
+
+    def extract_shapes(value: Any) -> None:
+        """Recursively extract shapes from nested structures."""
+        if isinstance(value, dict):
+            for v in value.values():
+                extract_shapes(v)
+        elif isinstance(value, (list, tuple)):
+            for item in value:
+                extract_shapes(item)
+        elif hasattr(value, "shape"):
+            # Handle tensors (numpy arrays, torch tensors, etc.)
+            shapes.append(list(value.shape))
+
+    extract_shapes(input_value)
+    return shapes
+
+
+def format_display_value(input_value: Any, mode: str = "raw value") -> str:
+    """Format input value for display based on selected mode.
+
+    Args:
+        input_value: Any input value to display
+        mode: Display mode - "raw value" or "tensor shape"
+
+    Returns:
+        Formatted string representation of the input
+    """
+    if mode == "tensor shape":
+        shapes = get_tensor_shapes(input_value)
+        if shapes:
+            return str(shapes)
+        else:
+            return "No tensors found in input"
+
+    # Default to raw value display
+    return str(input_value)
+
+
+def validate_display_mode(mode: str) -> bool:
+    """Validate if the display mode is supported.
+
+    Args:
+        mode: Display mode to validate
+
+    Returns:
+        True if mode is valid, False otherwise
+    """
+    valid_modes = ["raw value", "tensor shape"]
+    return mode in valid_modes

kikotools/tools/display_any/node.py

@@ -0,0 +1,66 @@
+"""DisplayAny node for ComfyUI - displays any input value or tensor information."""
+
+from typing import Any, Dict, Tuple
+
+from ...base import ComfyAssetsBaseNode
+from .logic import format_display_value, validate_display_mode
+
+
+# Define AnyType for wildcard input matching
+class AnyType(str):
+    """A special type that matches any input type in ComfyUI."""
+
+    def __ne__(self, other):
+        return False
+
+
+class DisplayAnyNode(ComfyAssetsBaseNode):
+    """Display any input value or tensor shape information.
+
+    This node can display any type of input in two modes:
+    - Raw value: Shows the string representation of the input
+    - Tensor shape: Extracts and displays shapes of any tensors in the input
+    """
+
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """Define input types for the node."""
+        return {
+            "required": {
+                "input": (AnyType("*"), {}),  # Accept any type of input
+                "mode": (["raw value", "tensor shape"],),
+            },
+        }
+
+    @classmethod
+    def VALIDATE_INPUTS(cls, **kwargs) -> bool:
+        """Validate inputs - always returns True as we accept any input."""
+        return True
+
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("display_text",)
+    FUNCTION = "display"
+    OUTPUT_NODE = True  # This node displays output in the UI
+
+    def display(self, input: Any, mode: str = "raw value") -> Dict[str, Any]:
+        """Display the input value according to the selected mode.
+
+        Args:
+            input: Any input value to display
+            mode: Display mode - "raw value" or "tensor shape"
+
+        Returns:
+            Dictionary with UI display and result
+        """
+        # Validate mode
+        if not validate_display_mode(mode):
+            mode = "raw value"  # Default to raw value if invalid
+
+        # Format the display text
+        display_text = format_display_value(input, mode)
+
+        # Return both UI display and result
+        return {
+            "ui": {"text": display_text},
+            "result": (display_text,),
+        }

kikotools/tools/display_text/__init__.py

@@ -0,0 +1,5 @@
+"""Display Text tool for ComfyUI."""
+
+from .node import DisplayTextNode, NODE_DISPLAY_NAME
+
+__all__ = ["DisplayTextNode", "NODE_DISPLAY_NAME"]

kikotools/tools/display_text/node.py

@@ -0,0 +1,48 @@
+"""Display Text node implementation."""
+
+from ...base import ComfyAssetsBaseNode
+
+
+class DisplayTextNode(ComfyAssetsBaseNode):
+    """Displays text in the ComfyUI interface with copy-to-clipboard functionality."""
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        """Define input types for the node."""
+        return {
+            "required": {
+                "text": ("STRING", {"forceInput": True}),
+            },
+        }
+
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("text",)
+    OUTPUT_NODE = True
+    FUNCTION = "display_text"
+    CATEGORY = "ComfyAssets"
+
+    DESCRIPTION = """
+Displays text in the UI with a copy-to-clipboard feature.
+
+Features:
+- Shows text content in a readable format
+- Copy button appears on hover
+- Passes text through for chaining
+"""
+
+    def display_text(self, text):
+        """Display the text and pass it through.
+
+        Args:
+            text: Input text to display
+
+        Returns:
+            Tuple containing the text
+        """
+        # The actual display happens in the frontend
+        # We just pass the text through
+        return {"ui": {"text": [text]}, "result": (text,)}
+
+
+# Node display name
+NODE_DISPLAY_NAME = "Display Text"

kikotools/tools/empty_latent_batch/__init__.py

@@ -0,0 +1,5 @@
+"""Empty Latent Batch tool for ComfyUI."""
+
+from .node import EmptyLatentBatchNode
+
+__all__ = ["EmptyLatentBatchNode"]

kikotools/tools/empty_latent_batch/logic.py

@@ -0,0 +1,101 @@
+"""Logic for creating empty latent tensors with batch support."""
+
+import torch
+from typing import Dict, Tuple
+
+
+def create_empty_latent_batch(
+    width: int, height: int, batch_size: int = 1
+) -> Dict[str, torch.Tensor]:
+    """
+    Create empty latent tensor with batch support.
+
+    Args:
+        width: Width in pixels (will be divided by 8 for latent space)
+        height: Height in pixels (will be divided by 8 for latent space)
+        batch_size: Number of latents in the batch
+
+    Returns:
+        Dictionary containing the latent samples tensor
+
+    Raises:
+        ValueError: If dimensions are invalid
+    """
+    # Validate inputs
+    if width <= 0 or height <= 0:
+        raise ValueError(f"Width and height must be positive, got {width}x{height}")
+
+    if batch_size <= 0:
+        raise ValueError(f"Batch size must be positive, got {batch_size}")
+
+    # Ensure dimensions are divisible by 8 (VAE requirement)
+    if width % 8 != 0 or height % 8 != 0:
+        raise ValueError(
+            f"Width and height must be divisible by 8, got {width}x{height}"
+        )
+
+    # Convert pixel dimensions to latent space (divide by 8)
+    latent_width = width // 8
+    latent_height = height // 8
+
+    # Create empty latent tensor
+    # ComfyUI latent format: [batch, channels, height, width]
+    # Standard VAE uses 4 channels
+    latent_tensor = torch.zeros(batch_size, 4, latent_height, latent_width)
+
+    return {"samples": latent_tensor}
+
+
+def validate_dimensions(width: int, height: int) -> bool:
+    """
+    Validate that dimensions are suitable for latent creation.
+
+    Args:
+        width: Width in pixels
+        height: Height in pixels
+
+    Returns:
+        True if dimensions are valid
+    """
+    # Check basic constraints
+    if width <= 0 or height <= 0:
+        return False
+
+    # Check divisibility by 8
+    if width % 8 != 0 or height % 8 != 0:
+        return False
+
+    # Check reasonable size limits (64x64 to 8192x8192)
+    if width < 64 or height < 64:
+        return False
+
+    if width > 8192 or height > 8192:
+        return False
+
+    return True
+
+
+def sanitize_dimensions(width: int, height: int) -> Tuple[int, int]:
+    """
+    Sanitize dimensions to ensure they meet latent requirements.
+
+    Args:
+        width: Input width
+        height: Input height
+
+    Returns:
+        Tuple of (sanitized_width, sanitized_height)
+    """
+    # Ensure minimum dimensions
+    width = max(64, width)
+    height = max(64, height)
+
+    # Ensure maximum dimensions
+    width = min(8192, width)
+    height = min(8192, height)
+
+    # Round to nearest multiple of 8
+    width = (width + 7) // 8 * 8
+    height = (height + 7) // 8 * 8
+
+    return width, height

kikotools/tools/empty_latent_batch/node.py

@@ -0,0 +1,309 @@
+"""Empty Latent Batch node for ComfyUI."""
+
+import torch
+from typing import Dict, Tuple
+
+from ...base.base_node import ComfyAssetsBaseNode
+from .logic import (
+    create_empty_latent_batch,
+    validate_dimensions,
+    sanitize_dimensions,
+)
+from ..width_height_selector.logic import get_preset_dimensions
+from ..width_height_selector.presets import (
+    PRESET_OPTIONS,
+    PRESET_METADATA,
+)
+
+
+class EmptyLatentBatchNode(ComfyAssetsBaseNode):
+    """
+    Empty Latent Batch node for creating empty latent tensors with batch support.
+
+    Creates empty latent tensors with specified dimensions and batch size,
+    compatible with ComfyUI's latent format for use with VAE and diffusion models.
+    """
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        """Define the input types for the ComfyUI node."""
+        # Create formatted preset options with metadata
+        preset_options = ["custom"]  # Custom first
+
+        # Add formatted presets with metadata
+        for preset_name in PRESET_OPTIONS.keys():
+            if preset_name != "custom":
+                metadata = PRESET_METADATA.get(preset_name)
+                if metadata:
+                    formatted_option = (
+                        f"{preset_name} - {metadata.aspect_ratio} "
+                        f"({metadata.megapixels:.1f}MP) - {metadata.model_group}"
+                    )
+                    preset_options.append(formatted_option)
+                else:
+                    preset_options.append(preset_name)
+
+        return {
+            "required": {
+                "preset": (
+                    preset_options,
+                    {
+                        "default": "custom",
+                        "tooltip": "Select from optimized resolution presets or use "
+                        "custom dimensions. SDXL presets are ~1MP, FLUX presets are "
+                        "higher resolution, Ultra-wide presets support modern "
+                        "aspect ratios.",
+                    },
+                ),
+                "width": (
+                    "INT",
+                    {
+                        "default": 1024,
+                        "min": 64,
+                        "max": 8192,
+                        "step": 8,
+                        "tooltip": "Custom width in pixels (must be multiple of 8). "
+                        "Used when preset is 'custom' or as fallback for invalid "
+                        "presets. This will be converted to latent space dimensions.",
+                    },
+                ),
+                "height": (
+                    "INT",
+                    {
+                        "default": 1024,
+                        "min": 64,
+                        "max": 8192,
+                        "step": 8,
+                        "tooltip": "Custom height in pixels (must be multiple of 8). "
+                        "Used when preset is 'custom' or as fallback for invalid "
+                        "presets. This will be converted to latent space dimensions.",
+                    },
+                ),
+                "batch_size": (
+                    "INT",
+                    {
+                        "default": 1,
+                        "min": 1,
+                        "max": 64,
+                        "step": 1,
+                        "tooltip": "Number of empty latents to create in the batch. "
+                        "Useful for batch processing workflows.",
+                    },
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("LATENT", "INT", "INT")
+    RETURN_NAMES = ("latent", "width", "height")
+    FUNCTION = "create_empty_latent"
+    CATEGORY = "ComfyAssets"
+
+    def create_empty_latent(
+        self, preset: str, width: int, height: int, batch_size: int
+    ) -> Tuple[Dict[str, torch.Tensor], int, int]:
+        """
+        Create empty latent tensor with specified dimensions and batch size.
+
+        Args:
+            preset: Selected preset name or formatted preset string
+            width: Custom width value
+            height: Custom height value
+            batch_size: Number of latents in the batch
+
+        Returns:
+            Tuple containing (latent dictionary with 'samples' tensor, width, height)
+        """
+        try:
+            # Extract original preset name from formatted string if needed
+            original_preset = self._extract_preset_name(preset)
+
+            # Get base dimensions from preset or custom input
+            base_width, base_height = get_preset_dimensions(
+                original_preset, width, height
+            )
+
+            # Sanitize dimensions to ensure they meet requirements
+            final_width, final_height = sanitize_dimensions(base_width, base_height)
+
+            # Log if dimensions were changed from the base dimensions
+            if final_width != base_width or final_height != base_height:
+                self.log_info(
+                    f"Dimensions adjusted from {base_width}×{base_height} to "
+                    f"{final_width}×{final_height} to meet VAE requirements"
+                )
+
+            # Validate final dimensions
+            if not validate_dimensions(final_width, final_height):
+                self.handle_error(
+                    f"Invalid dimensions after sanitization: {final_width}×{final_height}"
+                )
+
+            # Validate batch size
+            if batch_size <= 0:
+                self.handle_error(f"Batch size must be positive, got {batch_size}")
+
+            if batch_size > 64:
+                self.log_info(
+                    f"Large batch size ({batch_size}) may use significant memory"
+                )
+
+            # Create the empty latent batch
+            latent_dict = create_empty_latent_batch(
+                final_width, final_height, batch_size
+            )
+
+            # Log the operation
+            latent_height = final_height // 8
+            latent_width = final_width // 8
+            self.log_info(
+                f"Created empty latent batch: {batch_size}×4×{latent_height}×{latent_width} "
+                f"(pixel dims: {final_width}×{final_height})"
+            )
+
+            return (latent_dict, final_width, final_height)
+
+        except Exception as e:
+            # Handle any unexpected errors gracefully
+            error_msg = f"Error creating empty latent batch: {str(e)}"
+            self.handle_error(error_msg, e)
+
+    def _extract_preset_name(self, formatted_preset: str) -> str:
+        """
+        Extract the original preset name from a formatted preset string.
+
+        Args:
+            formatted_preset: Either original preset name or formatted string
+
+        Returns:
+            Original preset name
+        """
+        # If it's already "custom", return as-is
+        if formatted_preset == "custom":
+            return formatted_preset
+
+        # If it contains formatting metadata, extract the resolution part
+        if " - " in formatted_preset:
+            # Format is: "1024×1024 - 1:1 (1.0MP) - SDXL"
+            # Extract the first part (resolution)
+            resolution_part = formatted_preset.split(" - ")[0]
+
+            # Verify this is a valid preset name
+            if resolution_part in PRESET_OPTIONS:
+                return resolution_part
+
+        # If no formatting or not found, check if it's directly a valid preset
+        if formatted_preset in PRESET_OPTIONS:
+            return formatted_preset
+
+        # Default to "custom" if we can't parse it
+        return "custom"
+
+    def validate_inputs(
+        self, preset: str, width: int, height: int, batch_size: int
+    ) -> bool:
+        """
+        Validate node inputs.
+
+        Args:
+            preset: Preset name or formatted preset string
+            width: Width value
+            height: Height value
+            batch_size: Batch size value
+
+        Returns:
+            True if inputs are valid
+        """
+        # Extract original preset name
+        original_preset = self._extract_preset_name(preset)
+
+        # Check if preset exists or is custom
+        if original_preset != "custom" and original_preset not in PRESET_OPTIONS:
+            return False
+
+        # Get dimensions from preset or use custom
+        base_width, base_height = get_preset_dimensions(original_preset, width, height)
+
+        # Check dimension validity (after sanitization)
+        sanitized_width, sanitized_height = sanitize_dimensions(base_width, base_height)
+        if not validate_dimensions(sanitized_width, sanitized_height):
+            return False
+
+        # Check batch size
+        if batch_size <= 0 or batch_size > 64:
+            return False
+
+        return True
+
+    def get_latent_info(self, width: int, height: int, batch_size: int) -> str:
+        """
+        Get descriptive information about the latent that will be created.
+
+        Args:
+            width: Width in pixels
+            height: Height in pixels
+            batch_size: Batch size
+
+        Returns:
+            Description string for the latent
+        """
+        sanitized_width, sanitized_height = sanitize_dimensions(width, height)
+        latent_width = sanitized_width // 8
+        latent_height = sanitized_height // 8
+
+        return (
+            f"Empty latent batch: {batch_size} × 4 × {latent_height} × {latent_width} "
+            f"(pixel dimensions: {sanitized_width}×{sanitized_height})"
+        )
+
+    def get_memory_estimate(self, width: int, height: int, batch_size: int) -> str:
+        """
+        Estimate memory usage for the latent batch.
+
+        Args:
+            width: Width in pixels
+            height: Height in pixels
+            batch_size: Batch size
+
+        Returns:
+            Memory estimate string
+        """
+        sanitized_width, sanitized_height = sanitize_dimensions(width, height)
+        latent_width = sanitized_width // 8
+        latent_height = sanitized_height // 8
+
+        # Calculate tensor size in bytes (float32 = 4 bytes per element)
+        elements = batch_size * 4 * latent_height * latent_width
+        bytes_size = elements * 4  # 4 bytes per float32
+
+        # Convert to human-readable format
+        if bytes_size < 1024:
+            return f"{bytes_size} bytes"
+        elif bytes_size < 1024 * 1024:
+            return f"{bytes_size / 1024:.1f} KB"
+        elif bytes_size < 1024 * 1024 * 1024:
+            return f"{bytes_size / (1024 * 1024):.1f} MB"
+        else:
+            return f"{bytes_size / (1024 * 1024 * 1024):.1f} GB"
+
+    def __str__(self) -> str:
+        """String representation of the node."""
+        return "EmptyLatentBatchNode"
+
+    def __repr__(self) -> str:
+        """Detailed string representation of the node."""
+        return (
+            f"EmptyLatentBatchNode("
+            f"category='{self.CATEGORY}', "
+            f"function='{self.FUNCTION}'"
+            f")"
+        )
+
+
+# Node class mappings for ComfyUI registration
+NODE_CLASS_MAPPINGS = {
+    "EmptyLatentBatch": EmptyLatentBatchNode,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "EmptyLatentBatch": "Empty Latent Batch",
+}

kikotools/tools/gemini_prompt/.gemini_models_cache.json

@@ -0,0 +1,89 @@
+{
+  "models": [
+    "gemini-2.5-pro",
+    "gemini-2.5-flash",
+    "gemini-2.5-flash-lite",
+    "gemini-2.5-pro-preview-03-25",
+    "gemini-2.5-flash-preview-05-20",
+    "gemini-2.5-pro-preview-05-06",
+    "gemini-2.5-pro-preview-06-05",
+    "gemini-2.5-flash-lite-preview-06-17",
+    "gemini-2.0-flash",
+    "gemini-2.0-flash-001",
+    "gemini-2.0-flash-lite-001",
+    "gemini-2.0-flash-lite",
+    "gemini-2.5-flash-preview-tts",
+    "gemini-2.5-pro-preview-tts",
+    "gemini-2.0-flash-preview-image-generation",
+    "gemini-2.0-flash-exp",
+    "gemini-2.0-flash-exp-image-generation",
+    "gemini-2.0-flash-lite-preview-02-05",
+    "gemini-2.0-flash-lite-preview",
+    "gemini-2.0-pro-exp",
+    "gemini-2.0-pro-exp-02-05",
+    "learnlm-2.0-flash-experimental",
+    "gemini-1.5-pro-latest",
+    "gemini-1.5-pro-002",
+    "gemini-1.5-pro",
+    "gemini-1.5-flash-latest",
+    "gemini-1.5-flash",
+    "gemini-1.5-flash-002",
+    "gemini-1.5-flash-8b",
+    "gemini-1.5-flash-8b-001",
+    "gemini-1.5-flash-8b-latest",
+    "gemini-2.0-flash-thinking-exp-01-21",
+    "gemini-2.0-flash-thinking-exp",
+    "gemini-2.0-flash-thinking-exp-1219",
+    "gemma-3-1b-it",
+    "gemma-3-4b-it",
+    "gemma-3-12b-it",
+    "gemma-3-27b-it",
+    "gemma-3n-e4b-it",
+    "gemma-3n-e2b-it",
+    "gemini-exp-1206"
+  ],
+  "descriptions": {
+    "gemini-1.5-pro-latest": "Gemini 1.5 Pro Latest",
+    "gemini-1.5-pro-002": "Gemini 1.5 Pro 002",
+    "gemini-1.5-pro": "Gemini 1.5 Pro",
+    "gemini-1.5-flash-latest": "Gemini 1.5 Flash Latest",
+    "gemini-1.5-flash": "Gemini 1.5 Flash",
+    "gemini-1.5-flash-002": "Gemini 1.5 Flash 002",
+    "gemini-1.5-flash-8b": "Gemini 1.5 Flash-8B",
+    "gemini-1.5-flash-8b-001": "Gemini 1.5 Flash-8B 001",
+    "gemini-1.5-flash-8b-latest": "Gemini 1.5 Flash-8B Latest",
+    "gemini-2.5-pro-preview-03-25": "Gemini 2.5 Pro Preview 03-25",
+    "gemini-2.5-flash-preview-05-20": "Gemini 2.5 Flash Preview 05-20",
+    "gemini-2.5-flash": "Gemini 2.5 Flash",
+    "gemini-2.5-flash-lite-preview-06-17": "Gemini 2.5 Flash-Lite Preview 06-17",
+    "gemini-2.5-pro-preview-05-06": "Gemini 2.5 Pro Preview 05-06",
+    "gemini-2.5-pro-preview-06-05": "Gemini 2.5 Pro Preview",
+    "gemini-2.5-pro": "Gemini 2.5 Pro",
+    "gemini-2.0-flash-exp": "Gemini 2.0 Flash Experimental",
+    "gemini-2.0-flash": "Gemini 2.0 Flash",
+    "gemini-2.0-flash-001": "Gemini 2.0 Flash 001",
+    "gemini-2.0-flash-exp-image-generation": "Gemini 2.0 Flash (Image Generation) Experimental",
+    "gemini-2.0-flash-lite-001": "Gemini 2.0 Flash-Lite 001",
+    "gemini-2.0-flash-lite": "Gemini 2.0 Flash-Lite",
+    "gemini-2.0-flash-preview-image-generation": "Gemini 2.0 Flash Preview Image Generation",
+    "gemini-2.0-flash-lite-preview-02-05": "Gemini 2.0 Flash-Lite Preview 02-05",
+    "gemini-2.0-flash-lite-preview": "Gemini 2.0 Flash-Lite Preview",
+    "gemini-2.0-pro-exp": "Gemini 2.0 Pro Experimental",
+    "gemini-2.0-pro-exp-02-05": "Gemini 2.0 Pro Experimental 02-05",
+    "gemini-exp-1206": "Gemini Experimental 1206",
+    "gemini-2.0-flash-thinking-exp-01-21": "Gemini 2.5 Flash Preview 05-20",
+    "gemini-2.0-flash-thinking-exp": "Gemini 2.5 Flash Preview 05-20",
+    "gemini-2.0-flash-thinking-exp-1219": "Gemini 2.5 Flash Preview 05-20",
+    "gemini-2.5-flash-preview-tts": "Gemini 2.5 Flash Preview TTS",
+    "gemini-2.5-pro-preview-tts": "Gemini 2.5 Pro Preview TTS",
+    "learnlm-2.0-flash-experimental": "LearnLM 2.0 Flash Experimental",
+    "gemma-3-1b-it": "Gemma 3 1B",
+    "gemma-3-4b-it": "Gemma 3 4B",
+    "gemma-3-12b-it": "Gemma 3 12B",
+    "gemma-3-27b-it": "Gemma 3 27B",
+    "gemma-3n-e4b-it": "Gemma 3n E4B",
+    "gemma-3n-e2b-it": "Gemma 3n E2B",
+    "gemini-2.5-flash-lite": "Gemini 2.5 Flash-Lite"
+  },
+  "timestamp": 1754142231.0568295
+}

kikotools/tools/gemini_prompt/__init__.py

@@ -0,0 +1,5 @@
+"""Gemini Prompt Engineer node for ComfyUI."""
+
+from .node import GeminiPromptNode
+
+__all__ = ["GeminiPromptNode"]

kikotools/tools/gemini_prompt/logic.py

@@ -0,0 +1,163 @@
+"""Logic for Gemini API integration and prompt generation."""
+
+import base64
+import io
+import json
+import os
+from typing import Optional, Tuple
+
+import numpy as np
+from PIL import Image
+
+from .prompts import PROMPT_TEMPLATES
+
+
+def tensor_to_pil(tensor: np.ndarray) -> Image.Image:
+    """Convert ComfyUI tensor to PIL Image.
+
+    Args:
+        tensor: Input tensor in ComfyUI format (B, H, W, C)
+
+    Returns:
+        PIL Image object
+    """
+    # ComfyUI tensors are in [0, 1] range
+    if tensor.ndim == 4:
+        # Take first image from batch
+        tensor = tensor[0]
+
+    # Convert to uint8
+    image_array = (tensor * 255).astype(np.uint8)
+
+    # Convert to PIL
+    return Image.fromarray(image_array, mode="RGB")
+
+
+def image_to_base64(image: Image.Image, format: str = "PNG") -> str:
+    """Convert PIL Image to base64 string.
+
+    Args:
+        image: PIL Image object
+        format: Image format (PNG or JPEG)
+
+    Returns:
+        Base64 encoded string
+    """
+    buffer = io.BytesIO()
+    image.save(buffer, format=format)
+    buffer.seek(0)
+    return base64.b64encode(buffer.read()).decode("utf-8")
+
+
+def get_api_key() -> Optional[str]:
+    """Get Gemini API key from environment or config.
+
+    Returns:
+        API key string or None if not found
+    """
+    # Check environment variable first
+    api_key = os.environ.get("GEMINI_API_KEY")
+
+    if not api_key:
+        # Check for config file in ComfyUI directory
+        try:
+            config_path = os.path.join(
+                os.path.dirname(__file__), "..", "..", "..", "gemini_config.json"
+            )
+            if os.path.exists(config_path):
+                with open(config_path, "r") as f:
+                    config = json.load(f)
+                    api_key = config.get("api_key")
+        except Exception:
+            pass
+
+    return api_key
+
+
+def analyze_image_with_gemini(
+    image: np.ndarray,
+    prompt_type: str,
+    api_key: Optional[str] = None,
+    custom_prompt: Optional[str] = None,
+    model_name: str = "gemini-1.5-flash",
+) -> Tuple[str, Optional[str]]:
+    """Analyze image using Gemini API and generate appropriate prompt.
+
+    Args:
+        image: Input image tensor
+        prompt_type: Type of prompt to generate (flux, sdxl, danbooru, video)
+        api_key: Gemini API key (optional, will try to get from env/config)
+        custom_prompt: Custom system prompt to use instead of templates
+        model_name: Gemini model to use (default: gemini-1.5-flash)
+
+    Returns:
+        Tuple of (generated_prompt, error_message)
+    """
+    # Get API key
+    if not api_key:
+        api_key = get_api_key()
+
+    if not api_key:
+        return (
+            "",
+            "Gemini API key not found. Please set GEMINI_API_KEY environment variable or provide it in the node.",
+        )
+
+    # Convert tensor to PIL image
+    try:
+        pil_image = tensor_to_pil(image)
+    except Exception as e:
+        return "", f"Failed to convert image: {str(e)}"
+
+    # Get system prompt
+    if custom_prompt:
+        system_prompt = custom_prompt
+    else:
+        system_prompt = PROMPT_TEMPLATES.get(prompt_type, PROMPT_TEMPLATES["flux"])
+
+    # Here we would normally make the API call to Gemini
+    # For now, we'll import the google-generativeai library
+    try:
+        import google.generativeai as genai
+    except ImportError:
+        return (
+            "",
+            "google-generativeai library not installed. Please run: pip install google-generativeai",
+        )
+
+    try:
+        # Configure Gemini
+        genai.configure(api_key=api_key)
+
+        # Create model
+        model = genai.GenerativeModel(model_name)
+
+        # Generate content
+        response = model.generate_content(
+            [
+                system_prompt,
+                pil_image,
+                "Analyze this image and generate an appropriate prompt according to the instructions.",
+            ]
+        )
+
+        # Extract text from response
+        if response.text:
+            return response.text.strip(), None
+        else:
+            return "", "No response generated from Gemini"
+
+    except Exception as e:
+        return "", f"Gemini API error: {str(e)}"
+
+
+def validate_prompt_type(prompt_type: str) -> bool:
+    """Validate if prompt type is supported.
+
+    Args:
+        prompt_type: Type of prompt to validate
+
+    Returns:
+        True if valid, False otherwise
+    """
+    return prompt_type in PROMPT_TEMPLATES

kikotools/tools/gemini_prompt/models.py

@@ -0,0 +1,191 @@
+"""Dynamic model fetching and caching for Gemini API."""
+
+import json
+import os
+import time
+from typing import List, Dict, Optional, Tuple
+import logging
+
+logger = logging.getLogger(__name__)
+
+# Cache settings
+CACHE_DURATION = 3600 * 24  # 24 hours in seconds
+CACHE_FILE = os.path.join(os.path.dirname(__file__), ".gemini_models_cache.json")
+
+
+def get_available_models(
+    api_key: Optional[str] = None, silent: bool = False
+) -> Tuple[List[str], Dict[str, str]]:
+    """Fetch available Gemini models that support generateContent.
+
+    Args:
+        api_key: Optional API key. If not provided, will try to get from environment.
+        silent: If True, suppress error logging (useful for initial load).
+
+    Returns:
+        Tuple of (model_names_list, model_descriptions_dict)
+    """
+    # Check cache first
+    cached_data = _load_cache()
+    if cached_data:
+        return cached_data["models"], cached_data["descriptions"]
+
+    # Try to fetch from API
+    try:
+        models, descriptions = _fetch_models_from_api(api_key, silent=silent)
+        if models:
+            _save_cache(models, descriptions)
+            return models, descriptions
+    except Exception as e:
+        if not silent:
+            logger.warning(f"Failed to fetch models from API: {e}")
+
+    # Fall back to defaults
+    from .prompts import DEFAULT_GEMINI_MODELS
+
+    return DEFAULT_GEMINI_MODELS, {}
+
+
+def _fetch_models_from_api(
+    api_key: Optional[str] = None, silent: bool = False
+) -> Tuple[List[str], Dict[str, str]]:
+    """Fetch models from Gemini API.
+
+    Args:
+        api_key: Optional API key.
+        silent: If True, suppress error logging.
+
+    Returns:
+        Tuple of (model_names_list, model_descriptions_dict)
+    """
+    try:
+        import google.generativeai as genai
+    except ImportError:
+        if not silent:
+            logger.error("google-generativeai not installed")
+        return [], {}
+
+    # Get API key
+    if not api_key:
+        from .logic import get_api_key
+
+        api_key = get_api_key()
+
+    if not api_key:
+        if not silent:
+            logger.debug("No API key available for fetching models")
+        return [], {}
+
+    try:
+        genai.configure(api_key=api_key)
+
+        models = []
+        descriptions = {}
+
+        # Fetch all models
+        for model in genai.list_models():
+            # Only include models that support generateContent
+            if "generateContent" in model.supported_generation_methods:
+                # Remove "models/" prefix from name
+                model_name = model.name.replace("models/", "")
+                models.append(model_name)
+                descriptions[model_name] = model.display_name
+
+        # Sort models by priority (newer versions first)
+        models = _sort_models(models)
+
+        return models, descriptions
+
+    except Exception as e:
+        if not silent:
+            logger.error(f"Error fetching models from API: {e}")
+        return [], {}
+
+
+def _sort_models(models: List[str]) -> List[str]:
+    """Sort models by version and capability.
+
+    Prioritizes:
+    1. Newer versions (2.5 > 2.0 > 1.5)
+    2. Non-experimental models
+    3. Flash models for general use
+    """
+
+    def sort_key(model: str):
+        # Priority scoring
+        score = 0
+
+        # Version priority
+        if "2.5" in model:
+            score += 1000
+        elif "2.0" in model:
+            score += 800
+        elif "1.5" in model:
+            score += 600
+
+        # Model type priority
+        if "pro" in model and "preview" not in model and "exp" not in model:
+            score += 100
+        elif "flash" in model and "preview" not in model and "exp" not in model:
+            score += 90
+
+        # Penalize experimental/preview models
+        if "exp" in model or "experimental" in model:
+            score -= 50
+        if "preview" in model:
+            score -= 30
+
+        # Penalize specific variants
+        if "thinking" in model:
+            score -= 100
+        if "tts" in model:
+            score -= 100
+        if "lite" in model:
+            score -= 20
+
+        return -score  # Negative for descending sort
+
+    return sorted(models, key=sort_key)
+
+
+def _load_cache() -> Optional[Dict]:
+    """Load cached model data if available and not expired."""
+    if not os.path.exists(CACHE_FILE):
+        return None
+
+    try:
+        with open(CACHE_FILE, "r") as f:
+            data = json.load(f)
+
+        # Check if cache is expired
+        if time.time() - data.get("timestamp", 0) > CACHE_DURATION:
+            return None
+
+        return data
+    except Exception as e:
+        logger.warning(f"Failed to load cache: {e}")
+        return None
+
+
+def _save_cache(models: List[str], descriptions: Dict[str, str]) -> None:
+    """Save model data to cache."""
+    try:
+        data = {
+            "models": models,
+            "descriptions": descriptions,
+            "timestamp": time.time(),
+        }
+
+        with open(CACHE_FILE, "w") as f:
+            json.dump(data, f, indent=2)
+    except Exception as e:
+        logger.warning(f"Failed to save cache: {e}")
+
+
+def clear_cache() -> None:
+    """Clear the model cache."""
+    if os.path.exists(CACHE_FILE):
+        try:
+            os.remove(CACHE_FILE)
+        except Exception as e:
+            logger.warning(f"Failed to clear cache: {e}")

kikotools/tools/gemini_prompt/node.py

@@ -0,0 +1,169 @@
+"""Gemini Prompt Engineer node implementation."""
+
+import torch
+
+from ...base import ComfyAssetsBaseNode
+
+from .logic import analyze_image_with_gemini, validate_prompt_type
+from .prompts import PROMPT_OPTIONS, DEFAULT_GEMINI_MODELS
+from .models import get_available_models
+
+
+class GeminiPromptNode(ComfyAssetsBaseNode):
+    """Analyzes images using Gemini AI to generate optimized prompts for various AI models."""
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        """Define input types for the node."""
+        # Get available models dynamically (silent mode for initial load)
+        models, _ = get_available_models(silent=True)
+
+        # Use default if no models available
+        if not models:
+            models = DEFAULT_GEMINI_MODELS
+
+        # Find best default model
+        default_model = models[0] if models else "gemini-2.5-flash"
+
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "prompt_type": (PROMPT_OPTIONS, {"default": "flux"}),
+                "model": (models, {"default": default_model}),
+            },
+            "optional": {
+                "api_key": ("STRING", {"default": "", "multiline": False}),
+                "custom_prompt": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "multiline": True,
+                        "placeholder": "Optional: Enter custom system prompt instead of using templates",
+                    },
+                ),
+                "refresh_models": (
+                    "BOOLEAN",
+                    {"default": False, "label_on": "Refresh", "label_off": "Skip"},
+                ),
+            },
+        }
+
+    RETURN_TYPES = ("STRING", "STRING")
+    RETURN_NAMES = ("prompt", "negative_prompt")
+    FUNCTION = "generate_prompt"
+    CATEGORY = "ComfyAssets"
+
+    DESCRIPTION = """
+Analyzes images using Google's Gemini AI to generate optimized prompts.
+
+Supports multiple prompt formats:
+- FLUX: Detailed artistic prompts with quality markers
+- SDXL: Positive/negative prompt pairs with weight emphasis
+- Danbooru: Anime-style booru tags with underscores
+- Video: Motion and temporal descriptions for video generation
+
+Requires Gemini API key (set GEMINI_API_KEY env var or provide in node).
+Install: pip install google-generativeai
+"""
+
+    def generate_prompt(
+        self,
+        image,
+        prompt_type,
+        model,
+        api_key="",
+        custom_prompt="",
+        refresh_models=False,
+    ):
+        """Generate prompt from image using Gemini.
+
+        Args:
+            image: Input image tensor
+            prompt_type: Type of prompt to generate
+            model: Gemini model to use
+            api_key: Optional API key
+            custom_prompt: Optional custom system prompt
+            refresh_models: Whether to refresh the model list
+
+        Returns:
+            Tuple of (prompt, negative_prompt)
+        """
+        # Refresh models if requested
+        if refresh_models and api_key:
+            try:
+                from .models import clear_cache
+
+                # Clear cache to force refresh on next node creation
+                clear_cache()
+                print(
+                    "Model cache cleared. Please recreate the node to see updated models."
+                )
+            except Exception as e:
+                print(f"Failed to clear model cache: {e}")
+
+        # Validate prompt type
+        if not validate_prompt_type(prompt_type):
+            raise ValueError(f"Invalid prompt type: {prompt_type}")
+
+        # Convert torch tensor to numpy if needed
+        if isinstance(image, torch.Tensor):
+            image_np = image.cpu().numpy()
+        else:
+            image_np = image
+
+        # If API key is provided, try to refresh model list in background
+        if api_key:
+            try:
+                from .models import get_available_models
+
+                # Try to get fresh models with the provided API key
+                fresh_models, _ = get_available_models(api_key=api_key, silent=True)
+                if fresh_models and fresh_models != DEFAULT_GEMINI_MODELS:
+                    # Models were successfully fetched with this API key
+                    pass
+            except Exception:
+                pass
+
+        # Analyze image with Gemini
+        prompt, error = analyze_image_with_gemini(
+            image_np,
+            prompt_type,
+            api_key=api_key or None,
+            custom_prompt=custom_prompt or None,
+            model_name=model,
+        )
+
+        if error:
+            # Return error as prompt for visibility
+            return (f"Error: {error}", "")
+
+        # Handle different prompt types
+        if prompt_type == "sdxl":
+            # SDXL returns positive and negative prompts
+            lines = prompt.split("\n")
+            positive_prompt = ""
+            negative_prompt = ""
+
+            for line in lines:
+                if line.lower().startswith("positive:"):
+                    positive_prompt = (
+                        line.replace("Positive:", "").replace("positive:", "").strip()
+                    )
+                elif line.lower().startswith("negative:"):
+                    negative_prompt = (
+                        line.replace("Negative:", "").replace("negative:", "").strip()
+                    )
+
+            # If format not found, assume entire response is positive prompt
+            if not positive_prompt:
+                positive_prompt = prompt
+
+            return (positive_prompt, negative_prompt)
+
+        else:
+            # Other formats don't use negative prompts
+            return (prompt, "")
+
+
+# Node display name
+NODE_DISPLAY_NAME = "Gemini Prompt Engineer"

kikotools/tools/gemini_prompt/prompts.py

@@ -0,0 +1,128 @@
+"""System prompts for different AI model types."""
+
+FLUX_PROMPT = """You are an expert FLUX prompt engineer. Analyze the provided image and generate ONLY a FLUX prompt - no explanations, analysis, or additional text.
+
+FLUX uses natural language descriptions, not comma-separated tags. Write a detailed, flowing description that reads like you're explaining the image to someone.
+
+Include these elements in your description:
+- Main subject with specific details (appearance, clothing, expression, pose)
+- Environment and background details
+- Lighting conditions and atmosphere
+- Artistic style or photographic approach
+- Color palette and mood
+- Technical details if relevant (camera angle, focal length, etc.)
+- Textures and materials
+
+Write in a natural, descriptive style. Use complete sentences that flow together. Be specific and detailed but maintain readability.
+
+IMPORTANT: Return ONLY the prompt text. No analysis, headers, or additional commentary. Just the natural language description that can be directly used in FLUX.
+
+Example of correct output:
+A close-up portrait of a middle-aged woman with curly red hair and green eyes, wearing a blue silk blouse. She has a warm smile and freckles across her cheeks. The lighting is soft and natural, coming from a window to her left, creating gentle shadows that accentuate her features. The background is softly blurred, showing hints of a cozy bookshelf. The overall mood is warm and inviting, captured in a photorealistic style with shallow depth of field."""
+
+SDXL_PROMPT = """You are an expert prompt engineer specializing in SDXL (Stable Diffusion XL). Your task is to generate high-quality positive and negative prompts that conform to SDXL prompt formatting standards.
+
+Your expertise includes:
+- Leveraging community-tested techniques (ComfyUI, A1111, InvokeAI)
+- Applying photographic theory for realism, composition, lighting
+- Following Civitai trend standards and style best practices
+- Mastering Pony Diffusion XL formatting for stylized and anime content
+
+Structure prompts in this layered, modular format:
+[Main Subject], [Pose & Camera], [Lighting & Environment], [Style & Details], [Boost Terms], [Style References]
+
+For SDXL specifically:
+- Use quality boosters: 8k, RAW photo, masterpiece, ultra detailed, cinematic lighting
+- Prioritize realism and artistry
+- Excellent for portraits, landscapes, or cinematic scenes
+
+Instructions:
+
+Only reply with two fields:
+Positive prompt: (Your positive prompt here)
+Negative prompt: (Your negative prompt here)
+
+Do not include any commentary or explanation.
+
+Use concise, highly descriptive language that maximizes visual richness.
+
+Follow SDXL prompt conventions: prioritize subject clarity, camera perspective, lighting, mood, style tags, and composition.
+
+Keep total token length efficient (ideally under 250 tokens).
+
+Avoid redundancy and generic filler words.
+
+Focus on crafting super high-quality prompts for stunning visual output.
+
+Example Input:
+A futuristic cyberpunk samurai standing on a neon-lit rooftop in the rain.
+
+Example Output:
+Positive prompt: cyberpunk samurai, neon-lit rooftop, dramatic rain, glowing katana, futuristic cityscape, night scene, cinematic lighting, intense expression, sleek cyber armor, atmospheric depth, ultra-detailed, masterpiece, 8k, sharp focus, trending on artstation
+Negative prompt: blurry, low quality, poorly drawn, extra limbs, bad anatomy, deformed hands, text, watermark, jpeg artifacts, duplicate, cropped, out of frame
+"""
+
+DANBOORU_PROMPT = """You are a Danbooru tagging expert specializing in anime-style image tagging. Analyze the image and generate ONLY Danbooru-style tags - no explanations or analysis.
+
+CRITICAL: Use strict Danbooru conventions:
+- Use underscores for multi-word tags (e.g., long_hair, school_uniform)
+- All tags must be lowercase
+- Character count comes first (1girl, 2boys, multiple_girls)
+- For anime models trained on Danbooru data, proper tagging is essential
+
+Tag order and categories:
+1. Character count (1girl, solo, 2boys, etc.)
+2. Character features (hair_color, eye_color, hair_length)
+3. Expression/pose (smile, looking_at_viewer, sitting)
+4. Clothing (specific items with underscores)
+5. Background/setting (simple_background, outdoors, classroom)
+6. View/composition (upper_body, full_body, from_side)
+7. Quality tags (masterpiece, best_quality, highres)
+
+Common quality prefix for anime models:
+"masterpiece, best_quality, very_aesthetic"
+
+IMPORTANT: Return ONLY the comma-separated tags. Use underscores, not spaces. All lowercase.
+
+Example of correct output:
+1girl, solo, long_hair, blue_eyes, blonde_hair, school_uniform, serafuku, pleated_skirt, smile, looking_at_viewer, classroom, sitting, desk, window, sunlight, upper_body, masterpiece, best_quality"""
+
+VIDEO_PROMPT = """You are a WAN 2.2 video generation prompt specialist. Analyze the content and generate ONLY a video generation prompt optimized for WAN 2.2 - no explanations or analysis.
+
+WAN 2.2 excels with rich, descriptive prompts that focus on:
+- Visual composition and scene elements
+- Specific movements and actions
+- Lighting and aesthetic details
+- Cinematographic elements
+
+Write a single detailed paragraph describing the video scene. Focus on:
+- Main subjects and their actions
+- Visual style and atmosphere
+- Movement dynamics (use words like "intensely", "smoothly", "rapidly")
+- Environmental details and lighting
+- Specific visual elements and their interactions
+
+Keep the prompt descriptive but concise. WAN 2.2 works best with natural language that paints a clear picture of the desired video.
+
+IMPORTANT: Return ONLY the video prompt as a single descriptive paragraph. No analysis, headers, or additional text.
+
+Example of correct output:
+Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage, their movements fluid and dynamic as they exchange rapid punches under dramatic theater lighting that casts long shadows across the ring, with the crowd visible as blurred silhouettes in the darkened background."""
+
+PROMPT_TEMPLATES = {
+    "flux": FLUX_PROMPT,
+    "sdxl": SDXL_PROMPT,
+    "danbooru": DANBOORU_PROMPT,
+    "video": VIDEO_PROMPT,
+}
+
+PROMPT_OPTIONS = ["flux", "sdxl", "danbooru", "video"]
+
+# Default models list (fallback if API is unavailable)
+DEFAULT_GEMINI_MODELS = [
+    "gemini-2.5-flash",
+    "gemini-2.5-pro",
+    "gemini-2.0-flash",
+    "gemini-1.5-flash",
+    "gemini-1.5-pro",
+]

kikotools/tools/image_scale_down_by/__init__.py

@@ -0,0 +1,5 @@
+"""Image Scale Down By tool for ComfyUI."""
+
+from .node import ImageScaleDownByNode
+
+__all__ = ["ImageScaleDownByNode"]

kikotools/tools/image_scale_down_by/logic.py

@@ -0,0 +1,40 @@
+"""Core logic for ImageScaleDownBy tool."""
+
+import torch.nn.functional as F
+from torch import Tensor
+
+
+def scale_down_image(image: Tensor, scale_by: float) -> Tensor:
+    """Scale down an image by a given factor.
+
+    Args:
+        image: Input image tensor of shape (batch, height, width, channels)
+        scale_by: Scale factor between 0.01 and 1.0
+
+    Returns:
+        Scaled down image tensor
+    """
+    batch, height, width, channels = image.shape
+
+    # Calculate new dimensions
+    new_height = int(height * scale_by)
+    new_width = int(width * scale_by)
+
+    # Ensure minimum size of 1x1
+    new_height = max(1, new_height)
+    new_width = max(1, new_width)
+
+    # Convert from BHWC to BCHW for interpolation
+    image_chw = image.permute(0, 3, 1, 2)
+
+    # Scale down the image using bilinear interpolation
+    scaled = F.interpolate(
+        image_chw,
+        size=(new_height, new_width),
+        mode="bilinear",
+        align_corners=False,
+        antialias=True,
+    )
+
+    # Convert back to BHWC
+    return scaled.permute(0, 2, 3, 1)

kikotools/tools/image_scale_down_by/node.py

@@ -0,0 +1,86 @@
+"""ComfyUI node implementation for ImageScaleDownBy."""
+
+from typing import Dict, Any, Tuple
+
+from torch import Tensor
+
+from ...base import ComfyAssetsBaseNode
+from .logic import scale_down_image
+
+
+class ImageScaleDownByNode(ComfyAssetsBaseNode):
+    """
+    Scales down images by a specified factor.
+
+    Reduces image dimensions proportionally using bilinear interpolation
+    with antialiasing for smooth downscaling.
+    """
+
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        return {
+            "required": {
+                "images": ("IMAGE",),
+                "scale_by": (
+                    "FLOAT",
+                    {
+                        "default": 0.5,
+                        "min": 0.01,
+                        "max": 1.0,
+                        "step": 0.01,
+                        "display": "number",
+                    },
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("images",)
+    FUNCTION = "scale_down"
+
+    def scale_down(self, images: Tensor, scale_by: float) -> Tuple[Tensor]:
+        """
+        Scale down images by the specified factor.
+
+        Args:
+            images: Input image tensor
+            scale_by: Scale factor between 0.01 and 1.0
+
+        Returns:
+            Tuple containing scaled down image tensor
+        """
+        try:
+            self.validate_inputs(images=images, scale_by=scale_by)
+
+            # Scale down the images
+            scaled_images = scale_down_image(images, scale_by)
+
+            _, new_height, new_width, _ = scaled_images.shape
+            _, orig_height, orig_width, _ = images.shape
+
+            self.log_info(
+                f"Scaled down images from {orig_height}x{orig_width} "
+                f"to {new_height}x{new_width} (scale factor: {scale_by})"
+            )
+
+            return (scaled_images,)
+
+        except Exception as e:
+            self.handle_error(f"Failed to scale down images: {str(e)}", e)
+
+    def validate_inputs(self, **kwargs) -> None:
+        """Validate inputs for ImageScaleDownBy node."""
+        images = kwargs.get("images")
+        scale_by = kwargs.get("scale_by")
+
+        if images is None:
+            raise ValueError("Images input is required")
+
+        if not isinstance(images, Tensor) or len(images.shape) != 4:
+            raise ValueError(
+                f"Expected image tensor with shape (batch, height, width, channels), "
+                f"got shape {images.shape if isinstance(images, Tensor) else 'non-tensor'}"
+            )
+
+        if scale_by <= 0 or scale_by > 1.0:
+            raise ValueError(f"scale_by must be between 0.01 and 1.0, got {scale_by}")

kikotools/tools/image_to_multiple_of/__init__.py

@@ -0,0 +1,5 @@
+"""ImageToMultipleOf tool for ComfyUI-KikoTools."""
+
+from .node import ImageToMultipleOfNode
+
+__all__ = ["ImageToMultipleOfNode"]

kikotools/tools/image_to_multiple_of/logic.py

@@ -0,0 +1,61 @@
+"""Core logic for ImageToMultipleOf tool."""
+
+from typing import Tuple
+
+import torch.nn.functional as F
+from torch import Tensor
+
+
+def calculate_dimensions_to_multiple(
+    height: int, width: int, multiple_of: int
+) -> Tuple[int, int]:
+    """Calculate new dimensions that are multiples of the specified value.
+
+    Args:
+        height: Original height
+        width: Original width
+        multiple_of: Value that dimensions should be multiple of
+
+    Returns:
+        Tuple of (new_height, new_width)
+    """
+    new_height = height - (height % multiple_of)
+    new_width = width - (width % multiple_of)
+    return new_height, new_width
+
+
+def process_image_to_multiple_of(
+    image: Tensor, multiple_of: int, method: str
+) -> Tensor:
+    """Process image to ensure dimensions are multiples of specified value.
+
+    Args:
+        image: Input image tensor of shape (batch, height, width, channels)
+        multiple_of: Value that dimensions should be multiple of
+        method: Processing method - "center crop" or "rescale"
+
+    Returns:
+        Processed image tensor
+    """
+    _, height, width, _ = image.shape
+    new_height, new_width = calculate_dimensions_to_multiple(height, width, multiple_of)
+
+    if method == "rescale":
+        # Rescale the image to the new dimensions
+        # Convert from BHWC to BCHW for interpolation
+        image_chw = image.permute(0, 3, 1, 2)
+        rescaled = F.interpolate(
+            image_chw,
+            size=(new_height, new_width),
+            mode="bilinear",
+            align_corners=False,
+        )
+        # Convert back to BHWC
+        return rescaled.permute(0, 2, 3, 1)
+    else:  # center crop
+        # Calculate crop offsets to center the crop
+        top = (height - new_height) // 2
+        left = (width - new_width) // 2
+        bottom = top + new_height
+        right = left + new_width
+        return image[:, top:bottom, left:right, :]

kikotools/tools/image_to_multiple_of/node.py

@@ -0,0 +1,102 @@
+"""ComfyUI node implementation for ImageToMultipleOf."""
+
+from typing import Dict, Any, Tuple
+
+from torch import Tensor
+
+from ...base import ComfyAssetsBaseNode
+from .logic import process_image_to_multiple_of
+
+
+class ImageToMultipleOfNode(ComfyAssetsBaseNode):
+    """
+    Adjusts image dimensions to be multiples of a specified value.
+
+    Useful for models that require specific dimension constraints.
+    Supports both center cropping and rescaling methods.
+    """
+
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "multiple_of": (
+                    "INT",
+                    {
+                        "default": 64,
+                        "min": 1,
+                        "max": 256,
+                        "step": 16,
+                        "display": "number",
+                    },
+                ),
+                "method": (["center crop", "rescale"],),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("image",)
+    FUNCTION = "process"
+
+    def process(self, image: Tensor, multiple_of: int, method: str) -> Tuple[Tensor]:
+        """
+        Process image to ensure dimensions are multiples of specified value.
+
+        Args:
+            image: Input image tensor
+            multiple_of: Value that dimensions should be multiple of
+            method: Processing method - "center crop" or "rescale"
+
+        Returns:
+            Tuple containing processed image tensor
+        """
+        try:
+            self.validate_inputs(image=image, multiple_of=multiple_of, method=method)
+
+            # Process the image
+            processed_image = process_image_to_multiple_of(image, multiple_of, method)
+
+            _, new_height, new_width, _ = processed_image.shape
+            self.log_info(
+                f"Processed image from {image.shape[1]}x{image.shape[2]} "
+                f"to {new_height}x{new_width} (multiple of {multiple_of}) "
+                f"using {method}"
+            )
+
+            return (processed_image,)
+
+        except Exception as e:
+            self.handle_error(f"Failed to process image: {str(e)}", e)
+
+    def validate_inputs(self, **kwargs) -> None:
+        """Validate inputs for ImageToMultipleOf node."""
+        image = kwargs.get("image")
+        multiple_of = kwargs.get("multiple_of")
+        method = kwargs.get("method")
+
+        if image is None:
+            raise ValueError("Image input is required")
+
+        if not isinstance(image, Tensor) or len(image.shape) != 4:
+            raise ValueError(
+                f"Expected image tensor with shape (batch, height, width, channels), "
+                f"got shape {image.shape if isinstance(image, Tensor) else 'non-tensor'}"
+            )
+
+        if multiple_of <= 0:
+            raise ValueError(f"multiple_of must be positive, got {multiple_of}")
+
+        if method not in ["center crop", "rescale"]:
+            raise ValueError(f"Invalid method: {method}")
+
+        # Check if resulting dimensions would be too small
+        _, height, width, _ = image.shape
+        new_height = height - (height % multiple_of)
+        new_width = width - (width % multiple_of)
+
+        if new_height <= 0 or new_width <= 0:
+            raise ValueError(
+                f"Image dimensions ({height}x{width}) are too small "
+                f"to be adjusted to multiple of {multiple_of}"
+            )

kikotools/tools/kiko_save_image/__init__.py

@@ -0,0 +1,8 @@
+"""
+KikoSaveImage tool module
+Enhanced image saving with format selection, quality control, and clickable previews
+"""
+
+from .node import KikoSaveImageNode
+
+__all__ = ["KikoSaveImageNode"]

kikotools/tools/kiko_save_image/logic.py

@@ -0,0 +1,365 @@
+"""
+KikoSaveImage core logic
+Enhanced image saving functionality with multiple format support
+"""
+
+import os
+import json
+import numpy as np
+from PIL import Image
+from PIL.PngImagePlugin import PngInfo
+import torch
+from typing import Dict, List, Any, Optional, Tuple
+import time
+
+try:
+    import folder_paths
+except ImportError:
+    # Fallback for testing without ComfyUI
+    class folder_paths:
+        @staticmethod
+        def get_output_directory():
+            return "./output"
+
+
+def get_save_image_path(
+    filename_prefix: str,
+    batch_number: int,
+    format_ext: str,
+    output_dir: str,
+    subfolder: str = "",
+) -> Tuple[str, str]:
+    """
+    Generate save path for image with proper filename handling
+
+    Args:
+        filename_prefix: Base filename prefix
+        batch_number: Batch index for multiple images
+        format_ext: File extension (.png, .jpg, .webp)
+        output_dir: Output directory path
+        subfolder: Optional subfolder within output directory
+
+    Returns:
+        Tuple of (full_path, relative_filename)
+    """
+    # Split filename_prefix into directory path and actual filename prefix
+    # This allows for directory structures like "kittybear/anime/images/kittybear"
+    prefix_dir = os.path.dirname(filename_prefix)
+    prefix_name = os.path.basename(filename_prefix)
+
+    # Sanitize only the filename part (not the directory path)
+    safe_prefix = prefix_name.replace(
+        ":", "_"
+    )  # Only sanitize problematic chars for filenames
+    safe_prefix = "".join(c for c in safe_prefix if c.isalnum() or c in "._-")
+
+    # Create unique filename with timestamp to avoid conflicts
+    timestamp = int(time.time())
+    filename = f"{safe_prefix}_{timestamp:010d}_{batch_number:05d}{format_ext}"
+
+    # Handle subfolder and prefix directory (but not the filename part)
+    path_components = []
+    path_components.append(output_dir)
+
+    if subfolder:
+        path_components.append(subfolder)
+
+    # Only add prefix_dir if it exists (the directory part, not the filename part)
+    if prefix_dir:
+        path_components.append(prefix_dir)
+
+    full_output_folder = os.path.join(*path_components)
+
+    # Ensure directory exists
+    os.makedirs(full_output_folder, exist_ok=True)
+
+    full_path = os.path.join(full_output_folder, filename)
+
+    # For the preview, ComfyUI needs the filename and subfolder separately
+    # The subfolder needs to be relative to the output directory root
+    # Build the relative subfolder path including prefix directory (but not filename part)
+    relative_path_components = []
+
+    if subfolder:
+        relative_path_components.append(subfolder.strip("/\\"))
+
+    if prefix_dir:
+        relative_path_components.append(prefix_dir.strip("/\\"))
+
+    if relative_path_components:
+        relative_subfolder = os.path.join(*relative_path_components)
+    else:
+        relative_subfolder = ""
+
+    preview_filename = filename
+
+    return full_path, preview_filename, relative_subfolder
+
+
+def convert_tensor_to_pil(image_tensor: torch.Tensor) -> Image.Image:
+    """
+    Convert ComfyUI image tensor to PIL Image
+
+    Args:
+        image_tensor: Tensor in format [height, width, channels] with values 0-1
+
+    Returns:
+        PIL Image in RGB/RGBA format
+    """
+    # Convert tensor (0-1 float) to 0-255 numpy array
+    i = 255.0 * image_tensor.cpu().numpy()
+    img_array = np.clip(i, 0, 255).astype(np.uint8)
+
+    # Create PIL image from numpy array
+    img = Image.fromarray(img_array)
+
+    return img
+
+
+def create_png_metadata(
+    prompt: Optional[Dict] = None, extra_pnginfo: Optional[Dict] = None
+) -> Optional[PngInfo]:
+    """
+    Create PNG metadata with workflow information
+
+    Args:
+        prompt: ComfyUI prompt data
+        extra_pnginfo: Additional PNG metadata
+
+    Returns:
+        PngInfo object or None if no metadata
+    """
+    if prompt is None and extra_pnginfo is None:
+        return None
+
+    metadata = PngInfo()
+
+    if prompt is not None:
+        metadata.add_text("prompt", json.dumps(prompt))
+
+    if extra_pnginfo is not None:
+        for key, value in extra_pnginfo.items():
+            metadata.add_text(key, json.dumps(value))
+
+    return metadata
+
+
+def save_image_with_format(
+    img: Image.Image,
+    filepath: str,
+    format_type: str,
+    quality: int = 90,
+    png_compress_level: int = 4,
+    webp_lossless: bool = False,
+    metadata: Optional[PngInfo] = None,
+) -> Dict[str, Any]:
+    """
+    Save PIL image with specified format and quality settings
+
+    Args:
+        img: PIL Image to save
+        filepath: Full path to save file
+        format_type: Image format (PNG, JPEG, WEBP)
+        quality: JPEG/WebP quality (1-100)
+        png_compress_level: PNG compression level (0-9)
+        webp_lossless: Use lossless WebP compression
+        metadata: PNG metadata to embed
+
+    Returns:
+        Dict with save information
+    """
+    save_kwargs = {}
+
+    if format_type == "PNG":
+        if metadata:
+            save_kwargs["pnginfo"] = metadata
+        save_kwargs["compress_level"] = png_compress_level
+
+    elif format_type == "JPEG":
+        # Convert RGBA to RGB for JPEG (no transparency support)
+        if img.mode == "RGBA":
+            # Create white background
+            background = Image.new("RGB", img.size, (255, 255, 255))
+            background.paste(img, mask=img.split()[-1])  # Use alpha channel as mask
+            img = background
+        elif img.mode != "RGB":
+            img = img.convert("RGB")
+
+        save_kwargs["quality"] = quality
+        save_kwargs["optimize"] = True
+
+    elif format_type == "WEBP":
+        save_kwargs["quality"] = quality if not webp_lossless else 100
+        save_kwargs["lossless"] = webp_lossless
+
+    else:
+        raise ValueError(f"Unsupported format: {format_type}")
+
+    # Save the image
+    img.save(filepath, **save_kwargs)
+
+    # Get file size for info
+    file_size = os.path.getsize(filepath)
+
+    return {
+        "filepath": filepath,
+        "format": format_type,
+        "file_size": file_size,
+        "quality": quality if format_type != "PNG" else None,
+        "compress_level": png_compress_level if format_type == "PNG" else None,
+        "lossless": webp_lossless if format_type == "WEBP" else None,
+    }
+
+
+def process_image_batch(
+    images: torch.Tensor,
+    filename_prefix: str = "KikoSave",
+    format_type: str = "PNG",
+    quality: int = 90,
+    png_compress_level: int = 4,
+    webp_lossless: bool = False,
+    popup: bool = True,
+    prompt: Optional[Dict] = None,
+    extra_pnginfo: Optional[Dict] = None,
+) -> List[Dict[str, Any]]:
+    """
+    Process and save a batch of images with specified format settings
+
+    Args:
+        images: Batch of image tensors [batch, height, width, channels]
+        filename_prefix: Prefix for saved filenames
+        format_type: Image format (PNG, JPEG, WEBP)
+        quality: JPEG/WebP quality (1-100)
+        png_compress_level: PNG compression level (0-9)
+        webp_lossless: Use lossless WebP compression
+        popup: Enable popup windows in UI
+        prompt: ComfyUI prompt data for metadata
+        extra_pnginfo: Additional PNG metadata
+
+    Returns:
+        List of saved image information dicts
+    """
+    # Get output directory
+    output_dir = folder_paths.get_output_directory()
+
+    # Determine file extension
+    format_extensions = {"PNG": ".png", "JPEG": ".jpg", "WEBP": ".webp"}
+
+    if format_type not in format_extensions:
+        raise ValueError(
+            f"Unsupported format: {format_type}. "
+            f"Supported: {list(format_extensions.keys())}"
+        )
+
+    format_ext = format_extensions[format_type]
+
+    # Create metadata for PNG
+    metadata = None
+    if format_type == "PNG":
+        metadata = create_png_metadata(prompt, extra_pnginfo)
+
+    # Process each image in the batch
+    results = []
+    enhanced_data = []
+
+    for batch_number, image_tensor in enumerate(images):
+        # Convert tensor to PIL Image
+        img = convert_tensor_to_pil(image_tensor)
+
+        # Generate save path
+        filepath, preview_filename, relative_subfolder = get_save_image_path(
+            filename_prefix, batch_number, format_ext, output_dir, ""
+        )
+
+        # Save with format-specific settings
+        save_info = save_image_with_format(
+            img,
+            filepath,
+            format_type,
+            quality,
+            png_compress_level,
+            webp_lossless,
+            metadata,
+        )
+
+        # Build result info for ComfyUI preview
+        # ONLY the core fields that ComfyUI expects - no extra metadata
+        result = {
+            "filename": preview_filename,
+            "subfolder": relative_subfolder,
+            "type": "output",
+        }
+
+        # Store enhanced data separately
+        enhanced_info = {
+            "filename": preview_filename,
+            "subfolder": relative_subfolder,
+            "popup": popup,
+            "type": "output",
+            "format": format_type,
+            "file_size": save_info["file_size"],
+            "dimensions": f"{img.width}x{img.height}",
+        }
+
+        # Add format-specific info to enhanced data
+        if format_type == "PNG":
+            enhanced_info["compress_level"] = png_compress_level
+        elif format_type in ["JPEG", "WEBP"]:
+            enhanced_info["quality"] = quality
+            if format_type == "WEBP":
+                enhanced_info["lossless"] = webp_lossless
+
+        results.append(result)
+        enhanced_data.append(enhanced_info)
+
+    return results, enhanced_data
+
+
+def validate_save_inputs(
+    images: torch.Tensor, format_type: str, quality: int, png_compress_level: int
+) -> None:
+    """
+    Validate inputs for image saving
+
+    Args:
+        images: Image tensor batch to validate
+        format_type: Image format to validate
+        quality: Quality setting to validate
+        png_compress_level: PNG compression level to validate
+
+    Raises:
+        ValueError: If validation fails
+    """
+    # Validate images tensor
+    if not isinstance(images, torch.Tensor):
+        raise ValueError(f"images must be a torch.Tensor, got {type(images).__name__}")
+
+    if len(images.shape) != 4:
+        raise ValueError(
+            f"images tensor must have 4 dimensions [batch, height, width, channels], "
+            f"got {len(images.shape)}"
+        )
+
+    # Validate format
+    supported_formats = ["PNG", "JPEG", "WEBP"]
+    if format_type not in supported_formats:
+        raise ValueError(
+            f"format must be one of {supported_formats}, got {format_type}"
+        )
+
+    # Validate quality (for JPEG/WebP)
+    if format_type in ["JPEG", "WEBP"]:
+        if not isinstance(quality, int) or not (1 <= quality <= 100):
+            raise ValueError(
+                f"quality must be an integer between 1 and 100, got {quality}"
+            )
+
+    # Validate PNG compression level
+    if format_type == "PNG":
+        if not isinstance(png_compress_level, int) or not (
+            0 <= png_compress_level <= 9
+        ):
+            raise ValueError(
+                f"png_compress_level must be an integer between 0 and 9, "
+                f"got {png_compress_level}"
+            )

kikotools/tools/kiko_save_image/node.py

@@ -0,0 +1,226 @@
+"""
+KikoSaveImage ComfyUI Node
+Enhanced image saving with format selection, quality control, and clickable previews
+"""
+
+import torch
+from typing import Dict, Any, Optional
+
+from ...base import ComfyAssetsBaseNode
+from .logic import process_image_batch, validate_save_inputs
+
+
+class KikoSaveImageNode(ComfyAssetsBaseNode):
+    """
+    Enhanced ComfyUI image saving node with multiple format support
+
+    Features:
+    - Multiple format support (PNG, JPEG, WebP)
+    - Quality/compression controls
+    - Clickable image previews
+    - Metadata preservation
+    - Batch processing
+
+    Inputs:
+        - images (IMAGE): Images to save
+        - filename_prefix (STRING): Prefix for saved filenames
+        - format (COMBO): Output format (PNG, JPEG, WebP)
+        - quality (INT): JPEG/WebP quality (1-100)
+        - png_compress_level (INT): PNG compression level (0-9)
+        - webp_lossless (BOOLEAN): Use lossless WebP compression
+        - subfolder (STRING): Optional subfolder for organization
+
+    Outputs:
+        - UI: Image preview data for ComfyUI interface
+    """
+
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """
+        Define ComfyUI input interface with enhanced save options
+
+        Returns:
+            Dict with required and optional input specifications
+        """
+        return {
+            "required": {
+                "images": ("IMAGE", {"tooltip": "The images to save"}),
+                "filename_prefix": (
+                    "STRING",
+                    {"default": "KikoSave", "tooltip": "Prefix for saved filenames"},
+                ),
+                "format": (
+                    ["PNG", "JPEG", "WEBP"],
+                    {"default": "PNG", "tooltip": "Output image format"},
+                ),
+            },
+            "optional": {
+                "quality": (
+                    "INT",
+                    {
+                        "default": 90,
+                        "min": 1,
+                        "max": 100,
+                        "step": 1,
+                        "tooltip": "JPEG/WebP quality (1-100, higher = better quality)",
+                    },
+                ),
+                "png_compress_level": (
+                    "INT",
+                    {
+                        "default": 4,
+                        "min": 0,
+                        "max": 9,
+                        "step": 1,
+                        "tooltip": "PNG compression level (0-9, higher = smaller file)",
+                    },
+                ),
+                "webp_lossless": (
+                    "BOOLEAN",
+                    {
+                        "default": False,
+                        "tooltip": "Use lossless WebP compression "
+                        "(ignores quality setting)",
+                    },
+                ),
+                "popup": (
+                    "BOOLEAN",
+                    {
+                        "default": True,
+                        "tooltip": "Enable popup windows when clicking on images in the viewer",
+                    },
+                ),
+            },
+            "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
+        }
+
+    RETURN_TYPES = ()
+    FUNCTION = "save_images"
+    OUTPUT_NODE = True
+
+    def save_images(
+        self,
+        images: torch.Tensor,
+        filename_prefix: str = "KikoSave",
+        format: str = "PNG",
+        quality: int = 90,
+        png_compress_level: int = 4,
+        webp_lossless: bool = False,
+        popup: bool = True,
+        prompt: Optional[Dict] = None,
+        extra_pnginfo: Optional[Dict] = None,
+    ) -> Dict[str, Any]:
+        """
+        Save images with enhanced format and quality options
+
+        Args:
+            images: Batch of image tensors to save
+            filename_prefix: Prefix for saved filenames
+            format: Output format (PNG, JPEG, WebP)
+            quality: JPEG/WebP quality setting
+            png_compress_level: PNG compression level
+            webp_lossless: Use lossless WebP compression
+            popup: Enable popup windows when clicking on images
+            prompt: ComfyUI prompt data for metadata
+            extra_pnginfo: Additional PNG metadata
+
+        Returns:
+            Dict with UI data for image previews
+
+        Raises:
+            ValueError: If validation fails
+        """
+        try:
+            # Validate inputs
+            self.validate_inputs(
+                images=images,
+                format=format,
+                quality=quality,
+                png_compress_level=png_compress_level,
+                webp_lossless=webp_lossless,
+                popup=popup,
+            )
+
+            # Log the save operation
+            self.log_info(
+                f"Saving {len(images)} images as {format} "
+                f"(quality={quality if format != 'PNG' else 'N/A'}, "
+                f"png_compress={png_compress_level if format == 'PNG' else 'N/A'})"
+            )
+
+            # Process and save images
+            results, enhanced_data = process_image_batch(
+                images=images,
+                filename_prefix=filename_prefix,
+                format_type=format,
+                quality=quality,
+                png_compress_level=png_compress_level,
+                webp_lossless=webp_lossless,
+                popup=popup,
+                prompt=prompt,
+                extra_pnginfo=extra_pnginfo,
+            )
+
+            # Log results
+            total_size = sum(data["file_size"] for data in enhanced_data)
+            self.log_info(
+                f"Successfully saved {len(results)} images "
+                f"(total size: {total_size / 1024:.1f} KB)"
+            )
+
+            # Return UI data for ComfyUI preview (clean) + enhanced data for our JS
+            return {
+                "ui": {
+                    "images": results,  # Clean data for ComfyUI
+                    "kiko_enhanced": enhanced_data,  # Enhanced data for our JavaScript
+                }
+            }
+
+        except Exception as e:
+            error_msg = f"Failed to save images: {str(e)}"
+            self.handle_error(error_msg, e)
+
+    def validate_inputs(
+        self,
+        images: torch.Tensor,
+        format: str,
+        quality: int,
+        png_compress_level: int,
+        webp_lossless: bool,
+        popup: bool,
+    ) -> None:
+        """
+        Validate inputs specific to KikoSaveImage
+
+        Args:
+            images: Image tensor batch
+            format: Image format
+            quality: Quality setting
+            png_compress_level: PNG compression level
+            webp_lossless: WebP lossless setting
+            popup: Enable popup windows
+
+        Raises:
+            ValueError: If validation fails
+        """
+        # Use logic module validation
+        validate_save_inputs(images, format, quality, png_compress_level)
+
+        # Additional node-specific validation
+        if not isinstance(webp_lossless, bool):
+            raise ValueError(
+                f"webp_lossless must be a boolean, got {type(webp_lossless).__name__}"
+            )
+
+        if not isinstance(popup, bool):
+            raise ValueError(f"popup must be a boolean, got {type(popup).__name__}")
+
+
+# Node class mappings for ComfyUI registration
+NODE_CLASS_MAPPINGS = {
+    "KikoSaveImage": KikoSaveImageNode,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "KikoSaveImage": "Kiko Save Image",
+}

kikotools/tools/resolution_calculator/node.py

@@ -38,12 +38,12 @@ class ResolutionCalculatorNode(ComfyAssetsBaseNode):
                     "FLOAT",
                     {
                         "default": 2.0,
-                        "min": 1.0,
+                        "min": 0.1,
                         "max": 8.0,
                         "step": 0.1,
                         "display": "slider",
                         "tooltip": "Factor to scale the resolution by "
-                        "(e.g., 2.0 for 2x upscale)",
+                        "(e.g., 2.0 for 2x, 0.5 for half scale)",
                     },
                 ),
             },
@@ -140,38 +140,46 @@ class ResolutionCalculatorNode(ComfyAssetsBaseNode):
                 f"scale_factor must be a number, got {type(scale_factor).__name__}"
             )
 
-        # Additional tensor validation
+        # Validate tensors using helper methods
         if image is not None:
-            if not isinstance(image, torch.Tensor):
-                raise ValueError(
-                    f"image must be a torch.Tensor, got {type(image).__name__}"
-                )
-
-            if len(image.shape) != 4:
-                raise ValueError(
-                    f"image tensor must have 4 dimensions "
-                    f"[batch, height, width, channels], got {len(image.shape)}"
-                )
+            self._validate_image_tensor(image)
 
         if latent is not None:
-            if not isinstance(latent, dict):
-                raise ValueError(f"latent must be a dict, got {type(latent).__name__}")
+            self._validate_latent_dict(latent)
 
-            if "samples" not in latent:
-                raise ValueError("latent dict must contain 'samples' key")
+    def _validate_image_tensor(self, image: torch.Tensor) -> None:
+        """Validate image tensor format"""
+        if not isinstance(image, torch.Tensor):
+            raise ValueError(
+                f"image must be a torch.Tensor, got {type(image).__name__}"
+            )
 
-            samples = latent["samples"]
-            if not isinstance(samples, torch.Tensor):
-                raise ValueError(
-                    f"latent['samples'] must be a torch.Tensor, "
-                    f"got {type(samples).__name__}"
-                )
+        if len(image.shape) != 4:
+            raise ValueError(
+                f"image tensor must have 4 dimensions "
+                f"[batch, height, width, channels], got {len(image.shape)}"
+            )
 
-            if len(samples.shape) != 4:
-                raise ValueError(
-                    f"latent samples tensor must have 4 dimensions "
-                    f"[batch, channels, height, width], got {len(samples.shape)}"
-                )
+    def _validate_latent_dict(self, latent: Dict[str, torch.Tensor]) -> None:
+        """Validate latent dictionary format"""
+        if not isinstance(latent, dict):
+            raise ValueError(f"latent must be a dict, got {type(latent).__name__}")
+
+        if "samples" not in latent:
+            raise ValueError("latent dict must contain 'samples' key")
+
+        samples = latent["samples"]
+        if not isinstance(samples, torch.Tensor):
+            raise ValueError(
+                f"latent['samples'] must be a torch.Tensor, "
+                f"got {type(samples).__name__}"
+            )
+
+        if len(samples.shape) != 4:
+            raise ValueError(
+                f"latent samples tensor must have 4 dimensions "
+                f"[batch, channels, height, width], got {len(samples.shape)}"
+            )
 
 
 # Node class mappings for ComfyUI registration

kikotools/tools/sampler_combo/compact_node.py

@@ -60,14 +60,14 @@ class SamplerComboCompactNode(ComfyAssetsBaseNode):
             }
         }
 
-    RETURN_TYPES = (SAMPLERS, SCHEDULERS, "INT", "FLOAT")
+    RETURN_TYPES = ("SAMPLER", SCHEDULERS, "INT", "FLOAT")
     RETURN_NAMES = ("sampler", "scheduler", "steps", "cfg")
     FUNCTION = "get_combo"
     CATEGORY = "ComfyAssets"
 
     def get_combo(
         self, sampler: str, sched: str, steps: int, cfg: float
-    ) -> Tuple[str, str, int, float]:
+    ) -> Tuple[object, str, int, float]:
         """
         Get compact sampler combo configuration.
 
@@ -78,17 +78,32 @@ class SamplerComboCompactNode(ComfyAssetsBaseNode):
             cfg: CFG scale value
 
         Returns:
-            Tuple of (sampler, scheduler, steps, cfg)
+            Tuple of (sampler_object, scheduler, steps, cfg)
         """
         try:
             # Use the same validation logic but with compact interface
             result = get_sampler_combo(sampler, sched, steps, cfg)
-            return result
+            # Create the sampler object
+            try:
+                import comfy.samplers
+
+                sampler_obj = comfy.samplers.sampler_object(result[0])
+            except ImportError:
+                # Return sampler name for testing
+                sampler_obj = result[0]
+            return (sampler_obj, result[1], result[2], result[3])
 
         except Exception as e:
             # Graceful fallback
             self.handle_error(f"Error in compact combo: {str(e)}")
-            return ("euler", "normal", 20, 7.0)
+            try:
+                import comfy.samplers
+
+                sampler_obj = comfy.samplers.sampler_object("euler")
+            except ImportError:
+                # Return sampler name for testing
+                sampler_obj = "euler"
+            return (sampler_obj, "normal", 20, 7.0)
 
     def __str__(self) -> str:
         """String representation of the compact node."""

kikotools/tools/sampler_combo/node.py

@@ -65,14 +65,14 @@ class SamplerComboNode(ComfyAssetsBaseNode):
             }
         }
 
-    RETURN_TYPES = (SAMPLERS, SCHEDULERS, "INT", "FLOAT")
+    RETURN_TYPES = ("SAMPLER", SCHEDULERS, "INT", "FLOAT")
     RETURN_NAMES = ("sampler_name", "scheduler", "steps", "cfg")
     FUNCTION = "get_sampler_combo"
     CATEGORY = "ComfyAssets"
 
     def get_sampler_combo(
         self, sampler_name: str, scheduler: str, steps: int, cfg: float
-    ) -> Tuple[str, str, int, float]:
+    ) -> Tuple[object, str, int, float]:
         """
         Get sampler combo configuration.
 
@@ -83,35 +83,66 @@ class SamplerComboNode(ComfyAssetsBaseNode):
             cfg: CFG scale value
 
         Returns:
-            Tuple of (sampler_name, scheduler, steps, cfg)
+            Tuple of (sampler_object, scheduler, steps, cfg)
         """
         try:
             # Validate inputs
-            self.validate_inputs(
-                sampler_name=sampler_name,
-                scheduler=scheduler,
-                steps=steps,
-                cfg=cfg,
-            )
+            if not validate_sampler_settings(sampler_name, scheduler, steps, cfg):
+                # Log the validation error but don't raise
+                import logging
+
+                logger = logging.getLogger(__name__)
+                logger.error(
+                    f"{self.__class__.__name__}: Invalid sampler settings: "
+                    f"sampler={sampler_name}, scheduler={scheduler}, "
+                    f"steps={steps}, cfg={cfg}. "
+                    f"Using safe defaults: euler, normal, 20 steps, CFG 7.0"
+                )
+                try:
+                    import comfy.samplers
+
+                    sampler = comfy.samplers.sampler_object("euler")
+                except ImportError:
+                    # Return mock object for testing
+                    sampler = "euler"
+                return (sampler, "normal", 20, 7.0)
 
             # Process and return the combo
             result = get_sampler_combo(sampler_name, scheduler, steps, cfg)
 
+            # Create the sampler object
+            try:
+                import comfy.samplers
+
+                sampler = comfy.samplers.sampler_object(result[0])
+            except ImportError:
+                # Return sampler name for testing
+                sampler = result[0]
+
             self.log_info(
                 f"Configured sampler combo: {result[0]}, {result[1]}, "
                 f"{result[2]} steps, CFG {result[3]}"
             )
 
-            return result
+            return (sampler, result[1], result[2], result[3])
 
         except Exception as e:
             # Handle any unexpected errors gracefully
-            error_msg = (
-                f"Error processing sampler combo: {str(e)}. "
+            import logging
+
+            logger = logging.getLogger(__name__)
+            logger.error(
+                f"{self.__class__.__name__}: Error processing sampler combo: {str(e)}. "
                 f"Using safe defaults: euler, normal, 20 steps, CFG 7.0"
             )
-            self.handle_error(error_msg)
-            return ("euler", "normal", 20, 7.0)
+            try:
+                import comfy.samplers
+
+                sampler = comfy.samplers.sampler_object("euler")
+            except ImportError:
+                # Return mock object for testing
+                sampler = "euler"
+            return (sampler, "normal", 20, 7.0)
 
     def validate_inputs(
         self, sampler_name: str, scheduler: str, steps: int, cfg: float

kikotools/tools/seed_history/node.py

@@ -53,8 +53,13 @@ class SeedHistoryNode(ComfyAssetsBaseNode):
         try:
             # Validate and sanitize the seed
             if not validate_seed_value(seed):
-                self.handle_error(
-                    f"Invalid seed value: {seed}. Using fallback seed 12345."
+                # Log the validation error but don't raise
+                import logging
+
+                logger = logging.getLogger(__name__)
+                logger.error(
+                    f"{self.__class__.__name__}: Invalid seed value: {seed}. "
+                    f"Using fallback seed 12345."
                 )
                 return (12345,)
 
@@ -64,8 +69,13 @@ class SeedHistoryNode(ComfyAssetsBaseNode):
 
         except Exception as e:
             # Handle any unexpected errors gracefully
-            error_msg = f"Error processing seed: {str(e)}. Using fallback seed 12345."
-            self.handle_error(error_msg)
+            import logging
+
+            logger = logging.getLogger(__name__)
+            logger.error(
+                f"{self.__class__.__name__}: Error processing seed: {str(e)}. "
+                f"Using fallback seed 12345."
+            )
             return (12345,)
 
     def generate_new_seed(self) -> int:

kikotools/tools/width_height_selector/node.py

@@ -4,14 +4,15 @@ from typing import Tuple
 from ...base.base_node import ComfyAssetsBaseNode
 from .logic import (
     get_preset_dimensions,
-    calculate_aspect_ratio,
     validate_dimensions,
     sanitize_dimensions,
 )
 from .presets import (
     PRESET_OPTIONS,
-    PRESET_DESCRIPTIONS,
+    PRESET_METADATA,
     get_model_recommendation,
+    get_preset_metadata,
+    get_presets_by_model_group,
 )
 
 
@@ -26,13 +27,26 @@ class WidthHeightSelectorNode(ComfyAssetsBaseNode):
     @classmethod
     def INPUT_TYPES(cls):
         """Define the input types for the ComfyUI node."""
-        # Get all preset options excluding the custom tuple
-        preset_keys = [key for key in PRESET_OPTIONS.keys()]
+        # Create formatted preset options with metadata
+        preset_options = ["custom"]  # Custom first
+
+        # Add formatted presets with metadata
+        for preset_name in PRESET_OPTIONS.keys():
+            if preset_name != "custom":
+                metadata = PRESET_METADATA.get(preset_name)
+                if metadata:
+                    formatted_option = (
+                        f"{preset_name} - {metadata.aspect_ratio} "
+                        f"({metadata.megapixels:.1f}MP) - {metadata.model_group}"
+                    )
+                    preset_options.append(formatted_option)
+                else:
+                    preset_options.append(preset_name)
 
         return {
             "required": {
                 "preset": (
-                    preset_keys,
+                    preset_options,
                     {
                         "default": "custom",
                         "tooltip": "Select from optimized resolution presets or use "
@@ -78,7 +92,7 @@ class WidthHeightSelectorNode(ComfyAssetsBaseNode):
         Get width and height dimensions with preset and swap support.
 
         Args:
-            preset: Selected preset name or "custom"
+            preset: Selected preset name or formatted preset string
             width: Custom width value
             height: Custom height value
 
@@ -86,8 +100,13 @@ class WidthHeightSelectorNode(ComfyAssetsBaseNode):
             Tuple of (width, height)
         """
         try:
+            # Extract original preset name from formatted string if needed
+            original_preset = self._extract_preset_name(preset)
+
             # Get base dimensions from preset or custom input
-            final_width, final_height = get_preset_dimensions(preset, width, height)
+            final_width, final_height = get_preset_dimensions(
+                original_preset, width, height
+            )
 
             # Sanitize dimensions to ensure they meet ComfyUI requirements
             final_width, final_height = sanitize_dimensions(final_width, final_height)
@@ -111,6 +130,37 @@ class WidthHeightSelectorNode(ComfyAssetsBaseNode):
             self.handle_error(error_msg)
             return (1024, 1024)
 
+    def _extract_preset_name(self, formatted_preset: str) -> str:
+        """
+        Extract the original preset name from a formatted preset string.
+
+        Args:
+            formatted_preset: Either original preset name or formatted string
+
+        Returns:
+            Original preset name
+        """
+        # If it's already "custom", return as-is
+        if formatted_preset == "custom":
+            return formatted_preset
+
+        # If it contains formatting metadata, extract the resolution part
+        if " - " in formatted_preset:
+            # Format is: "1024×1024 - 1:1 (1.0MP) - SDXL"
+            # Extract the first part (resolution)
+            resolution_part = formatted_preset.split(" - ")[0]
+
+            # Verify this is a valid preset name
+            if resolution_part in PRESET_OPTIONS:
+                return resolution_part
+
+        # If no formatting or not found, check if it's directly a valid preset
+        if formatted_preset in PRESET_OPTIONS:
+            return formatted_preset
+
+        # Default to "custom" if we can't parse it
+        return "custom"
+
     def get_preset_info(self, preset: str) -> str:
         """
         Get descriptive information about a preset.
@@ -124,14 +174,12 @@ class WidthHeightSelectorNode(ComfyAssetsBaseNode):
         if preset == "custom":
             return "Custom dimensions - use the width and height inputs below"
 
-        if preset in PRESET_DESCRIPTIONS:
-            return PRESET_DESCRIPTIONS[preset]
-
-        # Fallback for unknown presets
-        if preset in PRESET_OPTIONS:
-            width, height = PRESET_OPTIONS[preset]
-            aspect_ratio = calculate_aspect_ratio(width, height)
-            return f"{preset} - {aspect_ratio} aspect ratio"
+        metadata = get_preset_metadata(preset)
+        if metadata.width > 0:  # Valid metadata
+            return (
+                f"{preset} - {metadata.aspect_ratio} ({metadata.megapixels:.1f}MP) - "
+                f"{metadata.description}"
+            )
 
         return f"Unknown preset: {preset}"
 
@@ -152,19 +200,22 @@ class WidthHeightSelectorNode(ComfyAssetsBaseNode):
         Validate node inputs.
 
         Args:
-            preset: Preset name
+            preset: Preset name or formatted preset string
             width: Width value
             height: Height value
 
         Returns:
             True if inputs are valid
         """
+        # Extract original preset name
+        original_preset = self._extract_preset_name(preset)
+
         # Check if preset exists or is custom
-        if preset != "custom" and preset not in PRESET_OPTIONS:
+        if original_preset != "custom" and original_preset not in PRESET_OPTIONS:
             return False
 
         # For custom preset, validate dimensions
-        if preset == "custom":
+        if original_preset == "custom":
             if not validate_dimensions(width, height):
                 return False
 
@@ -195,6 +246,52 @@ class WidthHeightSelectorNode(ComfyAssetsBaseNode):
             return PRESET_OPTIONS[preset]
         return (0, 0)
 
+    @classmethod
+    def get_presets_by_model(cls, model_group: str) -> dict:
+        """
+        Get all presets for a specific model group with metadata.
+
+        Args:
+            model_group: Model group name ("SDXL", "FLUX", "Ultra-Wide")
+
+        Returns:
+            Dictionary of presets with metadata
+        """
+        return get_presets_by_model_group(model_group)
+
+    @classmethod
+    def get_preset_metadata_static(cls, preset: str) -> dict:
+        """
+        Get metadata for a preset as a dictionary.
+
+        Args:
+            preset: Preset name
+
+        Returns:
+            Dictionary with metadata information
+        """
+        metadata = get_preset_metadata(preset)
+        return {
+            "width": metadata.width,
+            "height": metadata.height,
+            "aspect_ratio": metadata.aspect_ratio,
+            "aspect_decimal": metadata.aspect_decimal,
+            "megapixels": metadata.megapixels,
+            "model_group": metadata.model_group,
+            "category": metadata.category,
+            "description": metadata.description,
+        }
+
+    @classmethod
+    def get_model_groups(cls) -> list:
+        """
+        Get list of available model groups.
+
+        Returns:
+            List of model group names
+        """
+        return list(set(metadata.model_group for metadata in PRESET_METADATA.values()))
+
     def __str__(self) -> str:
         """String representation of the node."""
         return f"WidthHeightSelectorNode(presets={len(PRESET_OPTIONS)})"

kikotools/tools/width_height_selector/presets.py

@@ -1,114 +1,435 @@
 """Preset definitions for Width Height Selector."""
 
-from typing import Dict, Tuple
+from typing import Dict, Tuple, NamedTuple
+from fractions import Fraction
 
-# SDXL optimized presets (~1 megapixel, dimensions divisible by 8)
+
+class PresetMetadata(NamedTuple):
+    """Metadata for a resolution preset."""
+
+    width: int
+    height: int
+    aspect_ratio: str
+    aspect_decimal: float
+    megapixels: float
+    model_group: str
+    category: str
+    description: str
+
+
+def calculate_aspect_ratio(width: int, height: int) -> Tuple[str, float]:
+    """Calculate aspect ratio as string and decimal."""
+    fraction = Fraction(width, height)
+    decimal = width / height
+    return f"{fraction.numerator}:{fraction.denominator}", decimal
+
+
+# Enhanced preset definitions with full metadata
+PRESET_METADATA: Dict[str, PresetMetadata] = {
+    # SDXL Presets - Square
+    "1024×1024": PresetMetadata(
+        1024,
+        1024,
+        "1:1",
+        1.0,
+        1.05,
+        "SDXL",
+        "Square",
+        "SDXL base resolution - perfect square",
+    ),
+    # SDXL Presets - Portrait
+    "896×1152": PresetMetadata(
+        896,
+        1152,
+        "7:9",
+        0.778,
+        1.03,
+        "SDXL",
+        "Portrait",
+        "SDXL portrait 7:9 - moderate portrait",
+    ),
+    "832×1216": PresetMetadata(
+        832,
+        1216,
+        "13:19",
+        0.684,
+        1.01,
+        "SDXL",
+        "Portrait",
+        "SDXL portrait 13:19 - standard portrait",
+    ),
+    "768×1344": PresetMetadata(
+        768,
+        1344,
+        "4:7",
+        0.571,
+        1.03,
+        "SDXL",
+        "Portrait",
+        "SDXL portrait 4:7 - tall portrait",
+    ),
+    "640×1536": PresetMetadata(
+        640,
+        1536,
+        "5:12",
+        0.417,
+        0.98,
+        "SDXL",
+        "Portrait",
+        "SDXL portrait 5:12 - very tall portrait",
+    ),
+    # SDXL Presets - Landscape
+    "1152×896": PresetMetadata(
+        1152,
+        896,
+        "9:7",
+        1.286,
+        1.03,
+        "SDXL",
+        "Landscape",
+        "SDXL landscape 9:7 - moderate landscape",
+    ),
+    "1216×832": PresetMetadata(
+        1216,
+        832,
+        "19:13",
+        1.462,
+        1.01,
+        "SDXL",
+        "Landscape",
+        "SDXL landscape 19:13 - standard landscape",
+    ),
+    "1344×768": PresetMetadata(
+        1344,
+        768,
+        "7:4",
+        1.750,
+        1.03,
+        "SDXL",
+        "Landscape",
+        "SDXL landscape 7:4 - wide landscape",
+    ),
+    "1536×640": PresetMetadata(
+        1536,
+        640,
+        "12:5",
+        2.400,
+        0.98,
+        "SDXL",
+        "Landscape",
+        "SDXL landscape 12:5 - very wide landscape",
+    ),
+    # FLUX Presets - High Quality
+    "1920×1080": PresetMetadata(
+        1920,
+        1080,
+        "16:9",
+        1.778,
+        2.07,
+        "FLUX",
+        "Cinematic",
+        "FLUX Full HD 16:9 - best quality/speed balance",
+    ),
+    "1536×1536": PresetMetadata(
+        1536,
+        1536,
+        "1:1",
+        1.0,
+        2.36,
+        "FLUX",
+        "Square",
+        "FLUX high-res square - premium quality",
+    ),
+    "1280×768": PresetMetadata(
+        1280,
+        768,
+        "5:3",
+        1.667,
+        0.98,
+        "FLUX",
+        "Cinematic",
+        "FLUX 5:3 landscape - cinematic wide",
+    ),
+    "768×1280": PresetMetadata(
+        768,
+        1280,
+        "3:5",
+        0.600,
+        0.98,
+        "FLUX",
+        "Portrait",
+        "FLUX 3:5 portrait - mobile optimized",
+    ),
+    # FLUX Presets - Alternative
+    "1440×1080": PresetMetadata(
+        1440,
+        1080,
+        "4:3",
+        1.333,
+        1.56,
+        "FLUX",
+        "Classic",
+        "FLUX 4:3 classic - traditional aspect ratio",
+    ),
+    "1080×1440": PresetMetadata(
+        1080,
+        1440,
+        "3:4",
+        0.750,
+        1.56,
+        "FLUX",
+        "Portrait",
+        "FLUX 3:4 portrait - classic portrait",
+    ),
+    "1728×1152": PresetMetadata(
+        1728,
+        1152,
+        "3:2",
+        1.500,
+        1.99,
+        "FLUX",
+        "Photography",
+        "FLUX 3:2 photo - photography standard",
+    ),
+    "1152×1728": PresetMetadata(
+        1152,
+        1728,
+        "2:3",
+        0.667,
+        1.99,
+        "FLUX",
+        "Portrait",
+        "FLUX 2:3 portrait - portrait photography",
+    ),
+    # Ultra-Wide Presets - Landscape
+    "2560×1080": PresetMetadata(
+        2560,
+        1080,
+        "64:27",
+        2.370,
+        2.76,
+        "Ultra-Wide",
+        "Gaming",
+        "Ultra-wide 64:27 - gaming/panoramic",
+    ),
+    "2048×768": PresetMetadata(
+        2048,
+        768,
+        "8:3",
+        2.667,
+        1.57,
+        "Ultra-Wide",
+        "Cinematic",
+        "Wide cinematic 8:3 - movie aspect",
+    ),
+    "1792×768": PresetMetadata(
+        1792,
+        768,
+        "7:3",
+        2.333,
+        1.38,
+        "Ultra-Wide",
+        "Panoramic",
+        "Panoramic 7:3 - landscape vista",
+    ),
+    "2304×768": PresetMetadata(
+        2304,
+        768,
+        "3:1",
+        3.000,
+        1.77,
+        "Ultra-Wide",
+        "Banner",
+        "Banner 3:1 - extreme wide banner",
+    ),
+    # Ultra-Wide Presets - Portrait
+    "1080×2560": PresetMetadata(
+        1080,
+        2560,
+        "27:64",
+        0.422,
+        2.76,
+        "Ultra-Wide",
+        "Mobile",
+        "Mobile ultra-tall 27:64 - modern phones",
+    ),
+    "768×2048": PresetMetadata(
+        768,
+        2048,
+        "3:8",
+        0.375,
+        1.57,
+        "Ultra-Wide",
+        "Vertical",
+        "Vertical cinematic 3:8 - portrait video",
+    ),
+    "768×1792": PresetMetadata(
+        768,
+        1792,
+        "3:7",
+        0.429,
+        1.38,
+        "Ultra-Wide",
+        "Vertical",
+        "Vertical panoramic 3:7 - tall vista",
+    ),
+    "768×2304": PresetMetadata(
+        768,
+        2304,
+        "1:3",
+        0.333,
+        1.77,
+        "Ultra-Wide",
+        "Banner",
+        "Vertical banner 1:3 - extreme tall banner",
+    ),
+}
+
+# Legacy compatibility - maintain old preset dictionaries
 SDXL_PRESETS: Dict[str, Tuple[int, int]] = {
-    # Square
-    "1024×1024": (1024, 1024),  # 1:1 - Base SDXL resolution
-    # Portrait ratios
-    "896×1152": (896, 1152),  # 7:9 - Moderate portrait
-    "832×1216": (832, 1216),  # 13:19 - Standard portrait
-    "768×1344": (768, 1344),  # 4:7 - Tall portrait
-    "640×1536": (640, 1536),  # 5:12 - Very tall portrait
-    # Landscape ratios
-    "1152×896": (1152, 896),  # 9:7 - Moderate landscape
-    "1216×832": (1216, 832),  # 19:13 - Standard landscape
-    "1344×768": (1344, 768),  # 7:4 - Wide landscape
-    "1536×640": (1536, 640),  # 12:5 - Very wide landscape
+    k: (v.width, v.height)
+    for k, v in PRESET_METADATA.items()
+    if v.model_group == "SDXL"
 }
 
-# FLUX optimized presets (higher resolution, flexible ratios)
 FLUX_PRESETS: Dict[str, Tuple[int, int]] = {
-    # Recommended high-quality resolutions
-    "1920×1080": (1920, 1080),  # 16:9 - Full HD landscape
-    "1536×1536": (1536, 1536),  # 1:1 - High-res square
-    "1280×768": (1280, 768),  # 5:3 - Wide landscape
-    "768×1280": (768, 1280),  # 3:5 - Tall portrait
-    # Alternative quality resolutions
-    "1440×1080": (1440, 1080),  # 4:3 - Classic aspect ratio
-    "1080×1440": (1080, 1440),  # 3:4 - Classic portrait
-    "1728×1152": (1728, 1152),  # 3:2 - Photography standard
-    "1152×1728": (1152, 1728),  # 2:3 - Portrait photography
+    k: (v.width, v.height)
+    for k, v in PRESET_METADATA.items()
+    if v.model_group == "FLUX"
 }
 
-# Ultra-wide and modern aspect ratios
 ULTRA_WIDE_PRESETS: Dict[str, Tuple[int, int]] = {
-    # Ultra-wide landscape (21:9 and variants)
-    "2560×1080": (2560, 1080),  # 64:27 - Ultra-wide gaming
-    "2048×768": (2048, 768),  # 8:3 - Wide cinematic
-    "1792×768": (1792, 768),  # 7:3 - Panoramic
-    # Ultra-wide portrait
-    "1080×2560": (1080, 2560),  # 27:64 - Mobile ultra-tall
-    "768×2048": (768, 2048),  # 3:8 - Vertical cinematic
-    "768×1792": (768, 1792),  # 3:7 - Vertical panoramic
-    # Extreme ratios
-    "2304×768": (2304, 768),  # 3:1 - Banner landscape
-    "768×2304": (768, 2304),  # 1:3 - Banner portrait
+    k: (v.width, v.height)
+    for k, v in PRESET_METADATA.items()
+    if v.model_group == "Ultra-Wide"
 }
 
 # Combined preset options for ComfyUI dropdown
 PRESET_OPTIONS: Dict[str, Tuple[int, int]] = {
     "custom": (0, 0),  # Special case for custom dimensions
-    **SDXL_PRESETS,
-    **FLUX_PRESETS,
-    **ULTRA_WIDE_PRESETS,
+    **{k: (v.width, v.height) for k, v in PRESET_METADATA.items()},
 }
 
-# Organized preset categories for better UX
+# Enhanced preset categories organized by model groups and aspect ratios
 PRESET_CATEGORIES = {
     "Custom": ["custom"],
-    "SDXL Square": ["1024×1024"],
-    "SDXL Portrait": ["896×1152", "832×1216", "768×1344", "640×1536"],
-    "SDXL Landscape": ["1152×896", "1216×832", "1344×768", "1536×640"],
-    "FLUX Recommended": ["1920×1080", "1536×1536", "1280×768", "768×1280"],
-    "FLUX Alternative": ["1440×1080", "1080×1440", "1728×1152", "1152×1728"],
-    "Ultra-Wide Landscape": ["2560×1080", "2048×768", "1792×768", "2304×768"],
-    "Ultra-Wide Portrait": ["1080×2560", "768×2048", "768×1792", "768×2304"],
+    # SDXL Categories
+    "SDXL Square": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "SDXL" and v.category == "Square"
+    ],
+    "SDXL Portrait": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "SDXL" and v.category == "Portrait"
+    ],
+    "SDXL Landscape": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "SDXL" and v.category == "Landscape"
+    ],
+    # FLUX Categories
+    "FLUX Square": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "FLUX" and v.category == "Square"
+    ],
+    "FLUX Portrait": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "FLUX" and v.category == "Portrait"
+    ],
+    "FLUX Cinematic": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "FLUX" and v.category == "Cinematic"
+    ],
+    "FLUX Classic": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "FLUX" and v.category == "Classic"
+    ],
+    "FLUX Photography": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "FLUX" and v.category == "Photography"
+    ],
+    # Ultra-Wide Categories
+    "Ultra-Wide Gaming": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "Ultra-Wide" and v.category == "Gaming"
+    ],
+    "Ultra-Wide Cinematic": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "Ultra-Wide" and v.category == "Cinematic"
+    ],
+    "Ultra-Wide Panoramic": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "Ultra-Wide" and v.category == "Panoramic"
+    ],
+    "Ultra-Wide Mobile": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "Ultra-Wide" and v.category == "Mobile"
+    ],
+    "Ultra-Wide Vertical": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "Ultra-Wide" and v.category == "Vertical"
+    ],
+    "Ultra-Wide Banner": [
+        k
+        for k, v in PRESET_METADATA.items()
+        if v.model_group == "Ultra-Wide" and v.category == "Banner"
+    ],
 }
 
-# Preset descriptions for tooltips
-PRESET_DESCRIPTIONS = {
-    # SDXL presets
-    "1024×1024": "SDXL base resolution - perfect square",
-    "896×1152": "SDXL portrait 7:9 - moderate portrait",
-    "832×1216": "SDXL portrait 13:19 - standard portrait",
-    "768×1344": "SDXL portrait 4:7 - tall portrait",
-    "640×1536": "SDXL portrait 5:12 - very tall portrait",
-    "1152×896": "SDXL landscape 9:7 - moderate landscape",
-    "1216×832": "SDXL landscape 19:13 - standard landscape",
-    "1344×768": "SDXL landscape 7:4 - wide landscape",
-    "1536×640": "SDXL landscape 12:5 - very wide landscape",
-    # FLUX presets
-    "1920×1080": "FLUX Full HD 16:9 - best quality/speed balance",
-    "1536×1536": "FLUX high-res square - premium quality",
-    "1280×768": "FLUX 5:3 landscape - cinematic wide",
-    "768×1280": "FLUX 3:5 portrait - mobile optimized",
-    "1440×1080": "FLUX 4:3 classic - traditional aspect ratio",
-    "1080×1440": "FLUX 3:4 portrait - classic portrait",
-    "1728×1152": "FLUX 3:2 photo - photography standard",
-    "1152×1728": "FLUX 2:3 portrait - portrait photography",
-    # Ultra-wide presets
-    "2560×1080": "Ultra-wide 64:27 - gaming/panoramic",
-    "2048×768": "Wide cinematic 8:3 - movie aspect",
-    "1792×768": "Panoramic 7:3 - landscape vista",
-    "2304×768": "Banner 3:1 - extreme wide banner",
-    "1080×2560": "Mobile ultra-tall 27:64 - modern phones",
-    "768×2048": "Vertical cinematic 3:8 - portrait video",
-    "768×1792": "Vertical panoramic 3:7 - tall vista",
-    "768×2304": "Vertical banner 1:3 - extreme tall banner",
-}
+# Legacy compatibility - preset descriptions
+PRESET_DESCRIPTIONS = {k: v.description for k, v in PRESET_METADATA.items()}
 
-# Model-specific recommendations
+# Model-specific recommendations with metadata
 MODEL_RECOMMENDATIONS = {
-    "SDXL": list(SDXL_PRESETS.keys()),
-    "FLUX": list(FLUX_PRESETS.keys()),
-    "Ultra-Wide": list(ULTRA_WIDE_PRESETS.keys()),
+    "SDXL": [k for k, v in PRESET_METADATA.items() if v.model_group == "SDXL"],
+    "FLUX": [k for k, v in PRESET_METADATA.items() if v.model_group == "FLUX"],
+    "Ultra-Wide": [
+        k for k, v in PRESET_METADATA.items() if v.model_group == "Ultra-Wide"
+    ],
 }
 
 
+# New metadata-aware helper functions
+def get_presets_by_model_group(model_group: str) -> Dict[str, PresetMetadata]:
+    """Get all presets for a specific model group."""
+    return {k: v for k, v in PRESET_METADATA.items() if v.model_group == model_group}
+
+
+def get_presets_by_aspect_ratio(aspect_ratio: str) -> Dict[str, PresetMetadata]:
+    """Get all presets with a specific aspect ratio."""
+    return {k: v for k, v in PRESET_METADATA.items() if v.aspect_ratio == aspect_ratio}
+
+
+def get_presets_by_category(category: str) -> Dict[str, PresetMetadata]:
+    """Get all presets in a specific category."""
+    return {k: v for k, v in PRESET_METADATA.items() if v.category == category}
+
+
+def get_preset_metadata(preset_name: str) -> PresetMetadata:
+    """Get metadata for a specific preset."""
+    return PRESET_METADATA.get(
+        preset_name,
+        PresetMetadata(0, 0, "1:1", 1.0, 0.0, "Custom", "Custom", "Custom dimensions"),
+    )
+
+
 def get_preset_category(preset_name: str) -> str:
     """Get the category for a given preset name."""
+    metadata = PRESET_METADATA.get(preset_name)
+    if metadata:
+        return metadata.category
     for category, presets in PRESET_CATEGORIES.items():
         if preset_name in presets:
             return category
@@ -117,21 +438,17 @@ def get_preset_category(preset_name: str) -> str:
 
 def get_model_recommendation(preset_name: str) -> str:
     """Get model recommendation for a given preset."""
-    if preset_name in SDXL_PRESETS:
-        return "Optimized for SDXL"
-    elif preset_name in FLUX_PRESETS:
-        return "Optimized for FLUX"
-    elif preset_name in ULTRA_WIDE_PRESETS:
-        return "Modern ultra-wide ratios"
-    else:
-        return "Custom dimensions"
+    metadata = PRESET_METADATA.get(preset_name)
+    if metadata:
+        return f"Optimized for {metadata.model_group}"
+    return "Custom dimensions"
 
 
 def validate_preset_dimensions() -> bool:
     """Validate that all presets meet ComfyUI requirements."""
-    all_presets = {**SDXL_PRESETS, **FLUX_PRESETS, **ULTRA_WIDE_PRESETS}
+    for preset_name, metadata in PRESET_METADATA.items():
+        width, height = metadata.width, metadata.height
 
-    for preset_name, (width, height) in all_presets.items():
         # Check divisible by 8
         if width % 8 != 0 or height % 8 != 0:
             print(
@@ -147,6 +464,36 @@ def validate_preset_dimensions() -> bool:
     return True
 
 
+# Additional validation for metadata consistency
+def validate_metadata_consistency() -> bool:
+    """Validate metadata consistency and completeness."""
+    for preset_name, metadata in PRESET_METADATA.items():
+        # Verify aspect ratio calculation
+        expected_ratio, expected_decimal = calculate_aspect_ratio(
+            metadata.width, metadata.height
+        )
+        if abs(metadata.aspect_decimal - expected_decimal) > 0.001:
+            print(
+                f"ERROR: {preset_name} aspect ratio mismatch: "
+                f"expected {expected_decimal:.3f}, got {metadata.aspect_decimal}"
+            )
+            return False
+
+        # Verify megapixel calculation
+        expected_mp = (metadata.width * metadata.height) / 1_000_000
+        if abs(metadata.megapixels - expected_mp) > 0.1:
+            print(
+                f"ERROR: {preset_name} megapixel mismatch: "
+                f"expected {expected_mp:.2f}, got {metadata.megapixels}"
+            )
+            return False
+
+    return True
+
+
 # Validate presets on import
 if not validate_preset_dimensions():
     raise ValueError("Preset validation failed - check console for details")
+
+if not validate_metadata_consistency():
+    raise ValueError("Metadata validation failed - check console for details")

kikotools/tools/xyz_grid/IMPLEMENTATION.md

@@ -0,0 +1,65 @@
+# XYZ Plot Controller - Advanced Implementation
+
+## Overview
+
+This is a complete reimplementation of the XYZ Plot Controller using the Power Lora Loader architecture from rgthree. The implementation provides dynamic widget management with an intuitive interface.
+
+## Key Features
+
+### Dynamic Widget System
+- **"➕ Add [Type]" Buttons**: When you select models, vaes, loras, samplers, or schedulers for an axis, a button appears to add selections
+- **Toggle On/Off**: Each dynamic widget has a checkbox to enable/disable it without removing
+- **Right-Click Menu**: Right-click any dynamic widget to remove or toggle it
+- **Live Count Updates**: Node title shows total image count in real-time
+
+### Supported Axis Types
+- **Models**: Dynamic dropdown widgets with available checkpoints
+- **VAEs**: Dynamic dropdown widgets (includes "Automatic" option)
+- **LoRAs**: Dynamic dropdown widgets (includes "None" option) 
+- **Samplers**: Dynamic dropdown widgets with all sampler options
+- **Schedulers**: Dynamic dropdown widgets with scheduler options
+- **Numeric Parameters**: Text areas with helpful placeholders
+  - CFG Scale
+  - Steps
+  - Seed
+  - Denoise
+  - CLIP Skip
+- **Prompts**: Multi-line text area for prompt variations
+
+### Technical Implementation
+
+#### Python Backend (`xyz_plot_advanced.py`)
+- Uses `FlexibleOptionalInputType` to accept any number of dynamic inputs
+- Processes kwargs to extract widget values in format: `{axis}_{type}_{id}`
+- Each dynamic widget sends: `{ "on": bool, "value": string }`
+
+#### JavaScript Frontend (`xyz_plot_rgthree.js`)
+- Manages dynamic widget creation/removal
+- Custom widget drawing with toggle checkboxes
+- Serialization/deserialization for workflow saving
+- Real-time validation and counting
+
+## Usage
+
+1. Add the "XYZ Plot Controller (Advanced)" node
+2. Select axis types (X, Y, Z)
+3. Click "➕ Add [Type]" to add selections for that axis
+4. Toggle widgets on/off with checkboxes
+5. Right-click widgets for more options
+6. For numeric types, use comma-separated values or ranges (e.g., "5:15:2.5")
+7. For prompts, enter one per line
+
+## Architecture Benefits
+
+- **Clean Separation**: Python handles data, JavaScript handles UI
+- **Flexible Input System**: Can accept unlimited dynamic widgets
+- **Persistent State**: All widget states are saved with the workflow
+- **Intuitive Interface**: Matches Power Lora Loader's proven UX patterns
+- **Performance**: Only processes enabled widgets
+
+## Future Enhancements
+
+- Model/LoRA info display (CivitAI integration)
+- Drag-and-drop reordering
+- Preset management
+- Batch widget operations

kikotools/tools/xyz_grid/README.md

@@ -0,0 +1,68 @@
+# XYZ Grid Nodes for ComfyUI
+
+Advanced parameter comparison grid generator for ComfyUI with Power Lora Loader-inspired interface.
+
+## Features
+
+### XYZ Plot Controller
+- **Dynamic Multi-Selection**: Native dropdown widgets for selecting multiple models, VAEs, LoRAs, samplers, and schedulers
+- **Smart Widget Management**: Widgets automatically show/hide based on selected axis types
+- **Visual Organization**: Grouped widgets with headers for better organization
+- **Right-Click Context Menu**:
+  - Clear all selections for a specific type
+  - Show image count breakdown
+  - Keyboard shortcuts (Ctrl+Shift+C to clear all)
+- **Real-time Image Count**: Node title shows total images that will be generated
+- **Warning System**: Visual warning when generating over 100 images
+
+### Supported Parameter Types
+- **Models**: Multiple checkpoint selection
+- **VAEs**: Multiple VAE selection with "Automatic" option
+- **LoRAs**: Multiple LoRA selection with "None" option
+- **Samplers**: euler, euler_ancestral, heun, dpm_2, etc.
+- **Schedulers**: normal, karras, exponential, etc.
+- **Numeric Parameters**:
+  - CFG Scale
+  - Steps
+  - Seed
+  - Denoise
+  - CLIP Skip
+  - Support for ranges (e.g., "5:15:2.5" generates 5, 7.5, 10, 12.5, 15)
+- **Prompts**: Multiple prompts (one per line)
+
+### Image Grid Combiner
+- Automatic grid assembly with customizable spacing
+- Smart labeling with parameter values
+- Z-axis support for generating multiple grid pages
+- Font size and label customization options
+
+## Usage
+
+1. Add an XYZ Plot Controller node
+2. Select axis types (X, Y, and optionally Z)
+3. Use the dropdown widgets to select values for each axis
+4. Connect to your workflow (models, samplers, etc.)
+5. Add Image Grid Combiner at the end to create the labeled grid
+
+## Workflow Example
+
+```
+[XYZ Plot Controller] → [Checkpoint Loader] → [Sampling] → [Image Grid Combiner] → [Save Image]
+```
+
+The controller outputs the current iteration values which can be connected to corresponding nodes in your workflow.
+
+## Tips
+
+- Use the right-click menu to quickly clear selections
+- Check the image count in the node title before running
+- For large grids, consider using the Z-axis to split into multiple pages
+- Numeric ranges are more efficient than listing each value
+
+## Implementation Details
+
+The implementation uses a hybrid approach:
+- Python backend with native ComfyUI widget support
+- JavaScript frontend for enhanced UI features
+- Inspired by Power Lora Loader's dynamic widget management
+- Context menus and keyboard shortcuts for power users

kikotools/tools/xyz_grid/__init__.py

@@ -0,0 +1,19 @@
+"""XYZ Grid nodes for ComfyUI parameter comparisons."""
+
+from .controller.power_node import XYZPlotController
+from .combiner.node import ImageGridCombiner
+from .prompt.node import XYZPrompt
+
+NODE_CLASS_MAPPINGS = {
+    "XYZPlotController": XYZPlotController,
+    "ImageGridCombiner": ImageGridCombiner,
+    "XYZPrompt": XYZPrompt,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "XYZPlotController": "XYZ Plot Controller",
+    "ImageGridCombiner": "Image Grid Combiner",
+    "XYZPrompt": "XYZ Prompt",
+}
+
+__all__ = ["XYZPlotController", "ImageGridCombiner", "XYZPrompt"]

kikotools/tools/xyz_grid/combiner/__init__.py

@@ -0,0 +1 @@
+# Image Grid Combiner module

kikotools/tools/xyz_grid/combiner/node.py

@@ -0,0 +1,232 @@
+"""Image Grid Combiner node implementation."""
+
+from typing import Dict, List, Any, Tuple, Optional
+import torch
+import numpy as np
+from PIL import Image, ImageDraw, ImageFont
+import io
+
+from ..utils.constants import GRID_DEFAULTS
+
+
+class ImageGridCombiner:
+    """Combines images into labeled grid output."""
+    
+    @classmethod  
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "images": ("IMAGE",),
+                "grid_data": ("XYZ_GRID",),
+            },
+            "optional": {
+                "font_size": ("INT", {"default": GRID_DEFAULTS["font_size"], "min": 8, "max": 72}),
+                "grid_gap": ("INT", {"default": GRID_DEFAULTS["grid_gap"], "min": 0, "max": 50}),
+                "label_height": ("INT", {"default": GRID_DEFAULTS["label_height"], "min": 0, "max": 100}),
+                "max_label_length": ("INT", {"default": GRID_DEFAULTS["max_label_length"], "min": 10, "max": 100}),
+                "include_labels": ("BOOLEAN", {"default": True}),
+            }
+        }
+    
+    RETURN_TYPES = ("IMAGE", "STRING")
+    RETURN_NAMES = ("grid_image", "grid_info")
+    FUNCTION = "combine_images"
+    CATEGORY = "ComfyAssets/XYZ Grid"
+    OUTPUT_NODE = True
+    
+    def __init__(self):
+        self.image_buffer = {}  # Store images by batch_id
+        self.grid_configs = {}  # Store configs by batch_id
+        
+    def combine_images(self, images, grid_data, font_size=20, grid_gap=10, 
+                      label_height=30, max_label_length=30, include_labels=True):
+        """Combine images into grid with labels."""
+        
+        batch_id = grid_data["batch_id"]
+        
+        # Initialize buffer for this batch if needed
+        if batch_id not in self.image_buffer:
+            self.image_buffer[batch_id] = []
+            self.grid_configs[batch_id] = grid_data
+        
+        # Add current image(s) to buffer
+        if len(images.shape) == 4:  # Batch of images
+            for img in images:
+                self.image_buffer[batch_id].append(img)
+        else:  # Single image
+            self.image_buffer[batch_id].append(images)
+        
+        # Check if we have all images for this grid
+        config = self.grid_configs[batch_id]
+        expected_images = config["dimensions"]["total_images"]
+        current_count = len(self.image_buffer[batch_id])
+        
+        if current_count < expected_images:
+            # Not ready yet, return placeholder
+            placeholder = torch.zeros((1, 64, 64, 3))
+            info = f"Grid progress: {current_count}/{expected_images} images"
+            return (placeholder, info)
+        
+        # We have all images, create grid(s)
+        grids = self._create_grids(batch_id, font_size, grid_gap, label_height, 
+                                  max_label_length, include_labels)
+        
+        # Clean up buffers
+        del self.image_buffer[batch_id]
+        del self.grid_configs[batch_id]
+        
+        # Return grid(s) and info
+        info = self._generate_grid_info(config)
+        
+        # Convert PIL images back to tensor format
+        grid_tensors = []
+        for grid in grids:
+            grid_np = np.array(grid).astype(np.float32) / 255.0
+            grid_tensor = torch.from_numpy(grid_np)
+            grid_tensors.append(grid_tensor)
+        
+        # Stack if multiple grids (Z axis)
+        if len(grid_tensors) > 1:
+            output = torch.stack(grid_tensors)
+        else:
+            output = grid_tensors[0].unsqueeze(0)
+        
+        return (output, info)
+    
+    def _create_grids(self, batch_id: str, font_size: int, grid_gap: int,
+                     label_height: int, max_label_length: int, include_labels: bool) -> List[Image.Image]:
+        """Create grid images from buffer."""
+        
+        config = self.grid_configs[batch_id]
+        images = self.image_buffer[batch_id]
+        dims = config["dimensions"]
+        
+        # Convert tensors to PIL images
+        pil_images = []
+        for img_tensor in images:
+            img_np = (img_tensor.cpu().numpy() * 255).astype(np.uint8)
+            pil_images.append(Image.fromarray(img_np))
+        
+        # Get dimensions
+        img_width = pil_images[0].width
+        img_height = pil_images[0].height
+        cols = dims["cols"]
+        rows = dims["rows"]
+        grids_count = dims["grids_count"]
+        
+        # Calculate grid dimensions
+        row_label_width = 100 if include_labels else 0  # Space for Y labels
+        z_label_height = 40 if include_labels and grids_count > 1 else 0  # Space for Z label
+        
+        if include_labels:
+            grid_width = cols * img_width + (cols - 1) * grid_gap + row_label_width
+            grid_height = rows * img_height + (rows - 1) * grid_gap + label_height + z_label_height
+        else:
+            grid_width = cols * img_width + (cols - 1) * grid_gap
+            grid_height = rows * img_height + (rows - 1) * grid_gap
+        
+        grids = []
+        z_labels = config["axes"]["z"]["labels"] if config["axes"]["z"]["labels"] else []
+        
+        # Create each grid (for Z axis)
+        for z_idx in range(grids_count):
+            # Create blank grid
+            grid = Image.new('RGB', (grid_width, grid_height), color=(32, 32, 32))
+            draw = ImageDraw.Draw(grid)
+            
+            # Add labels if enabled
+            if include_labels:
+                # Try to use a better font if available
+                try:
+                    font = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf", font_size)
+                    title_font = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf", font_size + 4)
+                except:
+                    font = ImageFont.load_default()
+                    title_font = font
+                
+                # Draw Z-axis label if applicable
+                if z_labels and z_idx < len(z_labels):
+                    z_label = z_labels[z_idx]
+                    # Center the Z label
+                    bbox = draw.textbbox((0, 0), z_label, font=title_font)
+                    text_width = bbox[2] - bbox[0]
+                    z_x = (grid_width - text_width) // 2
+                    self._draw_label(draw, z_label, z_x, 5, text_width + 20, 
+                                   z_label_height - 10, title_font, max_label_length * 2)
+                
+                # Draw column labels (X axis)
+                x_labels = config["axes"]["x"]["labels"]
+                for col_idx, label in enumerate(x_labels):
+                    x = col_idx * (img_width + grid_gap) + row_label_width
+                    y = z_label_height
+                    self._draw_label(draw, label, x, y, img_width, label_height, font, max_label_length)
+                
+                # Draw row labels (Y axis) - on the left side
+                y_labels = config["axes"]["y"]["labels"]
+                for row_idx, label in enumerate(y_labels):
+                    y = row_idx * (img_height + grid_gap) + label_height + z_label_height
+                    self._draw_label(draw, label, 5, y + img_height // 2 - font_size // 2, 
+                                   row_label_width - 10, font_size + 4, font, max_label_length, 
+                                   align="right")
+            
+            # Place images
+            for y_idx in range(rows):
+                for x_idx in range(cols):
+                    img_idx = z_idx * (rows * cols) + y_idx * cols + x_idx
+                    if img_idx < len(pil_images):
+                        x = x_idx * (img_width + grid_gap) + row_label_width
+                        y = y_idx * (img_height + grid_gap) + label_height + z_label_height
+                        grid.paste(pil_images[img_idx], (x, y))
+            
+            grids.append(grid)
+        
+        return grids
+    
+    def _draw_label(self, draw, text: str, x: int, y: int, width: int, height: int,
+                   font, max_length: int, align: str = "center"):
+        """Draw a label with background."""
+        
+        # Truncate if needed
+        if len(text) > max_length:
+            text = text[:max_length-3] + "..."
+        
+        # Get text dimensions
+        bbox = draw.textbbox((0, 0), text, font=font)
+        text_width = bbox[2] - bbox[0]
+        text_height = bbox[3] - bbox[1]
+        
+        # Calculate position based on alignment
+        if align == "center":
+            text_x = x + (width - text_width) // 2
+        elif align == "right":
+            text_x = x + width - text_width - 5
+        else:
+            text_x = x + 5
+            
+        text_y = y + (height - text_height) // 2
+        
+        # Draw background
+        padding = 3
+        draw.rectangle([text_x - padding, text_y - padding, 
+                       text_x + text_width + padding, text_y + text_height + padding],
+                      fill=(0, 0, 0, 180))
+        
+        # Draw text
+        draw.text((text_x, text_y), text, fill=(255, 255, 255), font=font)
+    
+    def _generate_grid_info(self, config: Dict) -> str:
+        """Generate information string about the grid."""
+        dims = config["dimensions"]
+        axes = config["axes"]
+        
+        info_parts = [f"Grid: {dims['cols']}x{dims['rows']}"]
+        
+        for axis_name, axis_data in axes.items():
+            if axis_data["type"] and axis_data["values"]:
+                axis_type = axis_data["type"].value
+                value_count = len(axis_data["values"])
+                info_parts.append(f"{axis_name.upper()}: {axis_type} ({value_count} values)")
+        
+        info_parts.append(f"Total images: {dims['total_images']}")
+        
+        return " | ".join(info_parts)

kikotools/tools/xyz_grid/controller/__init__.py

@@ -0,0 +1 @@
+# XYZ Plot Controller module

kikotools/tools/xyz_grid/controller/advanced_node.py

@@ -0,0 +1,252 @@
+"""Advanced XYZ Plot Controller with full parameter support."""
+
+from typing import Dict, List, Any, Tuple, Optional, Union
+import json
+
+from ..utils.constants import AxisType, NUMERIC_DEFAULTS
+from ..utils.helpers import (
+    get_available_models, get_available_vaes, get_available_loras,
+    get_sampler_names, get_scheduler_names, parse_value_string,
+    generate_axis_labels, calculate_grid_dimensions, create_unique_id
+)
+from ..utils.converters import ParameterConverter, OutputConnector
+from .execution import execution_manager
+from .queue_manager import queue_manager
+
+
+class XYZPlotControllerAdvanced:
+    """Advanced XYZ Plot Controller with dynamic outputs."""
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        # Get available options for dropdowns
+        models = get_available_models()
+        vaes = get_available_vaes()
+        loras = get_available_loras()
+        samplers = get_sampler_names()
+        schedulers = get_scheduler_names()
+        
+        return {
+            "required": {
+                # X Axis configuration
+                "x_axis_type": (AxisType.choices(), {"default": AxisType.NONE.value}),
+                "x_values": ("STRING", {"default": "", "multiline": True}),
+                "x_label_prefix": ("STRING", {"default": ""}),
+                
+                # Y Axis configuration  
+                "y_axis_type": (AxisType.choices(), {"default": AxisType.NONE.value}),
+                "y_values": ("STRING", {"default": "", "multiline": True}),
+                "y_label_prefix": ("STRING", {"default": ""}),
+                
+                # Execution control
+                "auto_queue": ("BOOLEAN", {"default": True}),
+            },
+            "optional": {
+                # Z Axis configuration (optional)
+                "z_axis_type": (AxisType.choices(), {"default": AxisType.NONE.value}),
+                "z_values": ("STRING", {"default": "", "multiline": True}),
+                "z_label_prefix": ("STRING", {"default": ""}),
+                
+                # Label formatting
+                "include_param_name": ("BOOLEAN", {"default": True}),
+                "value_only_labels": ("BOOLEAN", {"default": False}),
+                
+                # Quick select dropdowns (helpers)
+                "model_list": (["none"] + models, {"default": "none"}),
+                "vae_list": (["none"] + vaes, {"default": "none"}),
+                "lora_list": (["none"] + loras, {"default": "none"}),
+                "sampler_list": (["none"] + samplers, {"default": "none"}),
+                "scheduler_list": (["none"] + schedulers, {"default": "none"}),
+            },
+            "hidden": {
+                "unique_id": "UNIQUE_ID",
+                "prompt": "PROMPT",
+            }
+        }
+    
+    RETURN_TYPES = ("XYZ_GRID", "STRING", "INT", "FLOAT", "STRING", "INT", "FLOAT", "STRING", "INT", "FLOAT", "STRING")
+    RETURN_NAMES = ("grid_data", 
+                   "x_string", "x_int", "x_float",
+                   "y_string", "y_int", "y_float", 
+                   "z_string", "z_int", "z_float",
+                   "batch_id")
+    FUNCTION = "configure_grid"
+    CATEGORY = "ComfyAssets/XYZ Grid"
+    
+    def __init__(self):
+        self.unique_id = None
+        self._execution_count = 0
+        
+    def configure_grid(self, x_axis_type, x_values, x_label_prefix,
+                      y_axis_type, y_values, y_label_prefix,
+                      auto_queue=True,
+                      z_axis_type="none", z_values="", z_label_prefix="",
+                      include_param_name=True, value_only_labels=False,
+                      model_list="none", vae_list="none", lora_list="none",
+                      sampler_list="none", scheduler_list="none",
+                      unique_id=None, prompt=None):
+        """Configure and prepare grid generation with advanced features."""
+        
+        # Use helper dropdowns to populate values if selected
+        x_values = self._apply_quick_select(x_axis_type, x_values, 
+                                          model_list, vae_list, lora_list, 
+                                          sampler_list, scheduler_list)
+        y_values = self._apply_quick_select(y_axis_type, y_values,
+                                          model_list, vae_list, lora_list,
+                                          sampler_list, scheduler_list)
+        z_values = self._apply_quick_select(z_axis_type, z_values,
+                                          model_list, vae_list, lora_list,
+                                          sampler_list, scheduler_list)
+        
+        # Parse axis types
+        x_type = AxisType(x_axis_type) if x_axis_type != "none" else None
+        y_type = AxisType(y_axis_type) if y_axis_type != "none" else None
+        z_type = AxisType(z_axis_type) if z_axis_type != "none" else None
+        
+        # Parse values for each axis
+        x_vals = parse_value_string(x_values, x_type) if x_type else [""]
+        y_vals = parse_value_string(y_values, y_type) if y_type else [""]
+        z_vals = parse_value_string(z_values, z_type) if z_type else [""]
+        
+        # Validate we have at least one axis configured
+        if not x_type and not y_type:
+            raise ValueError("At least one axis (X or Y) must be configured")
+        
+        # Calculate grid dimensions
+        dims = calculate_grid_dimensions(len(x_vals), len(y_vals), len(z_vals))
+        
+        # Generate labels
+        x_labels = self._generate_labels(x_vals, x_type, x_label_prefix, include_param_name, value_only_labels)
+        y_labels = self._generate_labels(y_vals, y_type, y_label_prefix, include_param_name, value_only_labels)
+        z_labels = self._generate_labels(z_vals, z_type, z_label_prefix, include_param_name, value_only_labels)
+        
+        # Create batch ID
+        batch_id = create_unique_id()
+        
+        # Prepare grid configuration
+        grid_config = {
+            "batch_id": batch_id,
+            "axes": {
+                "x": {"type": x_type, "values": x_vals, "labels": x_labels},
+                "y": {"type": y_type, "values": y_vals, "labels": y_labels},
+                "z": {"type": z_type, "values": z_vals, "labels": z_labels},
+            },
+            "dimensions": dims,
+            "total_images": dims["total_images"],
+            "current_index": 0,
+            "auto_queue": auto_queue,
+        }
+        
+        # Get current values from execution manager
+        x_val, y_val, z_val, x_idx, y_idx, z_idx = execution_manager.get_current_values(
+            batch_id, x_vals, y_vals, z_vals
+        )
+        
+        # Convert values to appropriate types for each output
+        x_outputs = self._convert_to_outputs(x_val, x_type)
+        y_outputs = self._convert_to_outputs(y_val, y_type)
+        z_outputs = self._convert_to_outputs(z_val, z_type)
+        
+        # Handle auto-queuing if enabled
+        if auto_queue and unique_id and prompt:
+            self._handle_auto_queue(batch_id, grid_config, unique_id, prompt)
+        
+        # Update current index in grid config
+        grid_config["current_index"] = execution_manager.execution_states.get(
+            batch_id, execution_manager.initialize_batch(batch_id, x_vals, y_vals, z_vals)
+        ).current_iteration
+        
+        return (grid_config, 
+                x_outputs[0], x_outputs[1], x_outputs[2],
+                y_outputs[0], y_outputs[1], y_outputs[2],
+                z_outputs[0], z_outputs[1], z_outputs[2],
+                batch_id)
+    
+    def _apply_quick_select(self, axis_type: str, values: str, 
+                           model: str, vae: str, lora: str, 
+                           sampler: str, scheduler: str) -> str:
+        """Apply quick select dropdown values if appropriate."""
+        if values:  # If user already entered values, don't override
+            return values
+        
+        # Map axis type to quick select value
+        if axis_type == "model" and model != "none":
+            return model
+        elif axis_type == "vae" and vae != "none":
+            return vae
+        elif axis_type == "lora" and lora != "none":
+            return lora
+        elif axis_type == "sampler" and sampler != "none":
+            return sampler
+        elif axis_type == "scheduler" and scheduler != "none":
+            return scheduler
+        
+        return values
+    
+    def _convert_to_outputs(self, value: Any, axis_type: Optional[AxisType]) -> Tuple[str, int, float]:
+        """Convert value to all output types."""
+        if not axis_type or value == "":
+            return ("", 0, 0.0)
+        
+        # Convert using parameter converter
+        converted = ParameterConverter.convert_value(value, axis_type)
+        
+        # Prepare outputs for all types
+        str_val = str(converted)
+        
+        try:
+            int_val = int(float(converted))
+        except:
+            int_val = 0
+        
+        try:
+            float_val = float(converted)
+        except:
+            float_val = 0.0
+        
+        return (str_val, int_val, float_val)
+    
+    def _generate_labels(self, values: List[Any], axis_type: Optional[AxisType], 
+                        prefix: str, include_param: bool, value_only: bool) -> List[str]:
+        """Generate labels for axis values."""
+        if not values or not axis_type:
+            return []
+        
+        labels = []
+        for value in values:
+            if value_only:
+                label = ParameterConverter.format_for_display(value, axis_type)
+            else:
+                label = ParameterConverter.format_for_display(value, axis_type)
+                if include_param and not prefix:
+                    param_names = AxisType.display_names()
+                    param_prefix = param_names.get(axis_type, "")
+                    label = f"{param_prefix}: {label}"
+                elif prefix:
+                    label = f"{prefix}{label}"
+            
+            labels.append(label)
+        
+        return labels
+    
+    def _handle_auto_queue(self, batch_id: str, grid_config: Dict, node_id: str, prompt: Dict):
+        """Handle automatic queuing of grid executions."""
+        # Check if this is the first execution for this batch
+        state = execution_manager.execution_states.get(batch_id)
+        if not state or state.current_iteration == 0:
+            # Prepare all executions for the batch
+            executions = queue_manager.prepare_batch_executions(
+                batch_id, grid_config, node_id, prompt
+            )
+            
+            # Mark that we've started this batch
+            self._execution_count = len(executions)
+        
+        # Advance to next iteration after this one completes
+        if execution_manager.should_continue(batch_id):
+            execution_manager.advance_batch(batch_id)
+    
+    @classmethod
+    def IS_CHANGED(cls, **kwargs):
+        """Force re-execution for grid iterations."""
+        return float("nan")

kikotools/tools/xyz_grid/controller/comfy_execution.py

@@ -0,0 +1,165 @@
+"""ComfyUI-specific execution flow implementation."""
+
+import json
+import uuid
+from typing import Dict, List, Any, Optional, Tuple
+
+try:
+    from server import PromptServer
+    from execution import validate_prompt, PromptExecutor
+    import execution
+    import nodes
+except ImportError:
+    # Not in ComfyUI environment
+    PromptServer = None
+    validate_prompt = None
+    PromptExecutor = None
+    execution = None
+    nodes = None
+
+
+class ComfyUIExecutionFlow:
+    """Manages execution flow integration with ComfyUI's system."""
+    
+    _instance = None
+    _batch_states = {}  # Track batch execution states
+    
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super().__new__(cls)
+        return cls._instance
+    
+    def __init__(self):
+        if not hasattr(self, 'initialized'):
+            self.initialized = True
+            self.prompt_server = PromptServer.instance if PromptServer else None
+            self.active_batches = {}
+            self.execution_callbacks = {}
+    
+    def register_batch(self, batch_id: str, grid_config: Dict, node_id: str) -> None:
+        """Register a new batch for execution tracking."""
+        self._batch_states[batch_id] = {
+            "config": grid_config,
+            "node_id": node_id,
+            "current_iteration": 0,
+            "total_iterations": grid_config["total_images"],
+            "completed": False
+        }
+    
+    def queue_grid_executions(self, workflow: Dict, batch_id: str, 
+                             grid_config: Dict, node_id: str) -> bool:
+        """Queue all executions for a grid batch."""
+        try:
+            # Register the batch
+            self.register_batch(batch_id, grid_config, node_id)
+            
+            # Get axis configurations
+            x_values = grid_config["axes"]["x"]["values"]
+            y_values = grid_config["axes"]["y"]["values"]
+            z_values = grid_config["axes"]["z"]["values"]
+            
+            # Calculate total iterations
+            total = len(x_values) * len(y_values) * len(z_values)
+            
+            # Store the original workflow
+            original_workflow = json.loads(json.dumps(workflow))
+            
+            # Queue executions for each combination
+            execution_count = 0
+            for z_idx, z_val in enumerate(z_values or [""]):
+                for y_idx, y_val in enumerate(y_values or [""]):
+                    for x_idx, x_val in enumerate(x_values or [""]):
+                        # Clone workflow for this iteration
+                        iteration_workflow = json.loads(json.dumps(original_workflow))
+                        
+                        # Inject iteration metadata
+                        self._inject_iteration_data(
+                            iteration_workflow, node_id, batch_id,
+                            execution_count, total,
+                            x_idx, y_idx, z_idx
+                        )
+                        
+                        # Queue this iteration
+                        prompt_id = str(uuid.uuid4())
+                        
+                        # Use ComfyUI's internal queue system
+                        if validate_prompt:
+                            valid, error = validate_prompt(iteration_workflow)
+                            if valid and execution and PromptServer:
+                                # Add to execution queue
+                                PromptServer.instance.send_sync(
+                                    "execution_start", 
+                                    {"prompt_id": prompt_id}
+                                )
+                            
+                            execution_count += 1
+                        else:
+                            print(f"Validation error for iteration {execution_count}: {error}")
+                            return False
+            
+            return True
+            
+        except Exception as e:
+            print(f"Error queuing grid executions: {e}")
+            return False
+    
+    def _inject_iteration_data(self, workflow: Dict, node_id: str, batch_id: str,
+                              iteration: int, total: int, 
+                              x_idx: int, y_idx: int, z_idx: int) -> None:
+        """Inject iteration-specific data into workflow."""
+        # Find the XYZ controller node
+        if str(node_id) in workflow:
+            node_data = workflow[str(node_id)]
+            
+            # Add hidden inputs for tracking
+            if "inputs" not in node_data:
+                node_data["inputs"] = {}
+            
+            node_data["inputs"]["_xyz_batch_id"] = batch_id
+            node_data["inputs"]["_xyz_iteration"] = iteration
+            node_data["inputs"]["_xyz_total"] = total
+            node_data["inputs"]["_xyz_indices"] = {
+                "x": x_idx,
+                "y": y_idx,
+                "z": z_idx
+            }
+    
+    def get_batch_progress(self, batch_id: str) -> Dict[str, Any]:
+        """Get progress information for a batch."""
+        if batch_id not in self._batch_states:
+            return {"status": "unknown", "progress": 0}
+        
+        state = self._batch_states[batch_id]
+        progress = state["current_iteration"] / state["total_iterations"]
+        
+        return {
+            "status": "completed" if state["completed"] else "running",
+            "progress": progress,
+            "current": state["current_iteration"],
+            "total": state["total_iterations"]
+        }
+    
+    def mark_iteration_complete(self, batch_id: str) -> None:
+        """Mark current iteration as complete and advance."""
+        if batch_id in self._batch_states:
+            state = self._batch_states[batch_id]
+            state["current_iteration"] += 1
+            
+            if state["current_iteration"] >= state["total_iterations"]:
+                state["completed"] = True
+                
+                # Send completion notification
+                if self.prompt_server:
+                    self.prompt_server.send_sync("xyz_grid_complete", {
+                        "batch_id": batch_id,
+                        "total_images": state["total_iterations"]
+                    })
+    
+    def cleanup_batch(self, batch_id: str) -> None:
+        """Clean up completed batch data."""
+        if batch_id in self._batch_states:
+            del self._batch_states[batch_id]
+
+
+# Global execution flow instance
+execution_flow = ComfyUIExecutionFlow()

kikotools/tools/xyz_grid/controller/dynamic_node.py

@@ -0,0 +1,243 @@
+"""XYZ Plot Controller with dynamic widget addition."""
+
+from typing import Dict, List, Any, Tuple, Union
+import folder_paths
+
+from ..utils.helpers import create_unique_id
+
+
+class XYZPlotController:
+    """XYZ Plot Controller with dynamic selections like Power Lora Loader."""
+    
+    # Allow any input to support dynamic widget addition
+    @classmethod
+    def IS_CHANGED(cls, **kwargs):
+        return float("nan")
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        axis_types = [
+            "none",
+            "models",
+            "vaes", 
+            "loras",
+            "samplers",
+            "schedulers",
+            "cfg_scale",
+            "steps",
+            "seed",
+            "denoise",
+            "clip_skip",
+            "prompt"
+        ]
+        
+        # Base inputs that are always present
+        inputs = {
+            "required": {
+                # Axis configuration
+                "x_type": (axis_types, {"default": "none"}),
+                "y_type": (axis_types, {"default": "none"}),
+                "z_type": (axis_types, {"default": "none"}),
+                
+                # Control
+                "auto_queue": ("BOOLEAN", {"default": True}),
+            },
+            "optional": {
+                # Single inputs for numeric/prompt values
+                "numeric_values": ("STRING", {
+                    "default": "", 
+                    "multiline": True,
+                    "placeholder": "For numeric types: use comma-separated values or start:stop:step notation"
+                }),
+                
+                "prompt_values": ("STRING", {
+                    "default": "", 
+                    "multiline": True,
+                    "placeholder": "For prompts: enter each prompt on a new line"
+                })
+            },
+            "hidden": {
+                "unique_id": "UNIQUE_ID",
+            }
+        }
+        
+        return inputs
+    
+    RETURN_TYPES = ("XYZ_GRID", "STRING", "INT", "FLOAT", "STRING", "INT", "FLOAT", "STRING", "INT", "FLOAT", "STRING")
+    RETURN_NAMES = ("grid_data", "x_string", "x_int", "x_float", "y_string", "y_int", "y_float", "z_string", "z_int", "z_float", "batch_id")
+    OUTPUT_NODE = True
+    FUNCTION = "create_grid"
+    CATEGORY = "ComfyAssets/XYZ Grid"
+    
+    def create_grid(self, x_type, y_type, z_type, auto_queue, unique_id=None, **kwargs):
+        """Create grid configuration from dynamic selections."""
+        
+        # Extract values from kwargs based on type
+        models = self._extract_values(kwargs, "MODEL_", exclude="none")
+        vaes = self._extract_values(kwargs, "VAE_", exclude="none")
+        loras = self._extract_values(kwargs, "LORA_", exclude="none")
+        samplers = self._extract_values(kwargs, "SAMPLER_", exclude="none")
+        schedulers = self._extract_values(kwargs, "SCHEDULER_", exclude="none")
+        
+        # Get numeric and prompt values
+        numeric_values = kwargs.get("numeric_values", "")
+        prompt_values = kwargs.get("prompt_values", "")
+        
+        # Parse values for each axis
+        x_parsed = self._get_axis_values(x_type, models, vaes, loras, samplers, schedulers, numeric_values, prompt_values)
+        y_parsed = self._get_axis_values(y_type, models, vaes, loras, samplers, schedulers, numeric_values, prompt_values)
+        z_parsed = self._get_axis_values(z_type, models, vaes, loras, samplers, schedulers, numeric_values, prompt_values)
+        
+        # Calculate total combinations
+        x_count = max(1, len(x_parsed))
+        y_count = max(1, len(y_parsed))
+        z_count = max(1, len(z_parsed))
+        total_images = x_count * y_count * z_count
+        
+        # Generate batch ID
+        batch_id = create_unique_id()
+        
+        # Create grid data
+        grid_data = {
+            "batch_id": batch_id,
+            "x_axis": {
+                "type": x_type,
+                "values": x_parsed,
+                "count": x_count
+            },
+            "y_axis": {
+                "type": y_type,
+                "values": y_parsed,
+                "count": y_count
+            },
+            "z_axis": {
+                "type": z_type,
+                "values": z_parsed,
+                "count": z_count
+            },
+            "total_images": total_images,
+            "current_index": 0,
+            "auto_queue": auto_queue
+        }
+        
+        # Get current values for outputs
+        x_current = x_parsed[0] if x_parsed else self._get_default_value(x_type)
+        y_current = y_parsed[0] if y_parsed else self._get_default_value(y_type)
+        z_current = z_parsed[0] if z_parsed else self._get_default_value(z_type)
+        
+        # Convert to appropriate output types
+        x_str, x_int, x_float = self._convert_value(x_type, x_current)
+        y_str, y_int, y_float = self._convert_value(y_type, y_current)
+        z_str, z_int, z_float = self._convert_value(z_type, z_current)
+        
+        # Log grid info
+        print(f"\n[XYZ Grid] Created grid with {total_images} total combinations:")
+        if x_type != "none":
+            print(f"  X axis ({x_type}): {x_count} values - {x_parsed}")
+        if y_type != "none":
+            print(f"  Y axis ({y_type}): {y_count} values - {y_parsed}")
+        if z_type != "none":
+            print(f"  Z axis ({z_type}): {z_count} values - {z_parsed}")
+        
+        return (grid_data, x_str, x_int, x_float, y_str, y_int, y_float, z_str, z_int, z_float, batch_id)
+    
+    def _extract_values(self, kwargs: Dict[str, Any], prefix: str, exclude: str = None) -> List[str]:
+        """Extract non-empty values from kwargs with given prefix."""
+        values = []
+        i = 1
+        while f"{prefix}{i}" in kwargs:
+            value = kwargs[f"{prefix}{i}"]
+            if value and value != exclude:
+                values.append(value)
+            i += 1
+        return values
+    
+    def _get_axis_values(self, axis_type, models, vaes, loras, samplers, schedulers, numeric_values, prompt_values):
+        """Get values for a specific axis type."""
+        if axis_type == "none":
+            return []
+        elif axis_type == "models":
+            return models
+        elif axis_type == "vaes":
+            return vaes
+        elif axis_type == "loras":
+            return loras
+        elif axis_type == "samplers":
+            return samplers
+        elif axis_type == "schedulers":
+            return schedulers
+        elif axis_type == "prompt":
+            return [p.strip() for p in prompt_values.split("\n") if p.strip()]
+        elif axis_type in ["cfg_scale", "steps", "seed", "denoise", "clip_skip"]:
+            return self._parse_numeric_values(axis_type, numeric_values)
+        else:
+            return []
+    
+    def _parse_numeric_values(self, axis_type: str, values_str: str) -> List[Union[int, float]]:
+        """Parse numeric values with range support."""
+        if not values_str.strip():
+            return []
+        
+        # Handle range notation (start:stop:step)
+        if ":" in values_str:
+            try:
+                parts = values_str.split(":")
+                if len(parts) == 2:
+                    start, stop = float(parts[0]), float(parts[1])
+                    step = 1.0
+                elif len(parts) == 3:
+                    start, stop, step = float(parts[0]), float(parts[1]), float(parts[2])
+                else:
+                    raise ValueError("Invalid range format")
+                
+                # Generate values
+                values = []
+                current = start
+                while current <= stop:
+                    if axis_type in ["steps", "seed", "clip_skip"]:
+                        values.append(int(current))
+                    else:
+                        values.append(round(current, 2))
+                    current += step
+                return values
+            except:
+                pass
+        
+        # Parse comma-separated values
+        values = [v.strip() for v in values_str.split(",") if v.strip()]
+        
+        # Convert numeric types
+        if axis_type in ["cfg_scale", "denoise"]:
+            return [float(v) for v in values]
+        elif axis_type in ["steps", "seed", "clip_skip"]:
+            return [int(v) for v in values]
+        else:
+            return values
+    
+    def _get_default_value(self, axis_type: str) -> Any:
+        """Get default value for axis type."""
+        defaults = {
+            "models": "",
+            "vaes": "Automatic",
+            "loras": "None",
+            "samplers": "euler",
+            "schedulers": "normal",
+            "cfg_scale": 7.0,
+            "steps": 20,
+            "seed": 0,
+            "denoise": 1.0,
+            "clip_skip": 1,
+            "prompt": ""
+        }
+        return defaults.get(axis_type, "")
+    
+    def _convert_value(self, axis_type: str, value: Any) -> Tuple[str, int, float]:
+        """Convert value to all output types."""
+        if axis_type in ["models", "vaes", "loras", "samplers", "schedulers", "prompt"]:
+            return (str(value), 0, 0.0)
+        elif axis_type in ["steps", "seed", "clip_skip"]:
+            return ("", int(value), float(value))
+        elif axis_type in ["cfg_scale", "denoise"]:
+            return ("", 0, float(value))
+        else:
+            return ("", 0, 0.0)

kikotools/tools/xyz_grid/controller/execution.py

@@ -0,0 +1,112 @@
+"""Execution flow management for XYZ grid generation."""
+
+import json
+from typing import Dict, List, Any, Optional, Tuple
+from dataclasses import dataclass
+from ..utils.constants import AxisType
+
+
+@dataclass
+class GridExecutionState:
+    """Tracks execution state for grid generation."""
+    batch_id: str
+    total_iterations: int
+    current_iteration: int = 0
+    x_index: int = 0
+    y_index: int = 0
+    z_index: int = 0
+    x_count: int = 1
+    y_count: int = 1
+    z_count: int = 1
+    
+    def advance(self) -> bool:
+        """Advance to next grid position. Returns False when complete."""
+        self.current_iteration += 1
+        
+        if self.current_iteration >= self.total_iterations:
+            return False
+        
+        # Advance indices (row-major order: X varies fastest)
+        self.x_index += 1
+        if self.x_index >= self.x_count:
+            self.x_index = 0
+            self.y_index += 1
+            if self.y_index >= self.y_count:
+                self.y_index = 0
+                self.z_index += 1
+        
+        return True
+    
+    def get_indices(self) -> Tuple[int, int, int]:
+        """Get current x, y, z indices."""
+        return (self.x_index, self.y_index, self.z_index)
+    
+    def is_complete(self) -> bool:
+        """Check if all iterations are complete."""
+        return self.current_iteration >= self.total_iterations
+
+
+class ExecutionManager:
+    """Manages execution flow for XYZ grid generation."""
+    
+    def __init__(self):
+        self.execution_states = {}  # batch_id -> GridExecutionState
+        self.pending_executions = {}  # batch_id -> list of pending configs
+    
+    def initialize_batch(self, batch_id: str, x_values: List[Any], 
+                        y_values: List[Any], z_values: List[Any]) -> GridExecutionState:
+        """Initialize a new batch execution."""
+        x_count = len(x_values) if x_values else 1
+        y_count = len(y_values) if y_values else 1
+        z_count = len(z_values) if z_values else 1
+        total = x_count * y_count * z_count
+        
+        state = GridExecutionState(
+            batch_id=batch_id,
+            total_iterations=total,
+            x_count=x_count,
+            y_count=y_count,
+            z_count=z_count
+        )
+        
+        self.execution_states[batch_id] = state
+        return state
+    
+    def get_current_values(self, batch_id: str, x_values: List[Any],
+                          y_values: List[Any], z_values: List[Any]) -> Tuple[Any, Any, Any, int, int, int]:
+        """Get current values and indices for execution."""
+        state = self.execution_states.get(batch_id)
+        if not state:
+            # Initialize if not exists
+            state = self.initialize_batch(batch_id, x_values, y_values, z_values)
+        
+        x_idx, y_idx, z_idx = state.get_indices()
+        
+        x_val = x_values[x_idx] if x_values and x_idx < len(x_values) else ""
+        y_val = y_values[y_idx] if y_values and y_idx < len(y_values) else ""
+        z_val = z_values[z_idx] if z_values and z_idx < len(z_values) else ""
+        
+        return x_val, y_val, z_val, x_idx, y_idx, z_idx
+    
+    def should_continue(self, batch_id: str) -> bool:
+        """Check if batch should continue executing."""
+        state = self.execution_states.get(batch_id)
+        return state and not state.is_complete()
+    
+    def advance_batch(self, batch_id: str) -> bool:
+        """Advance to next iteration. Returns True if more iterations remain."""
+        state = self.execution_states.get(batch_id)
+        if state:
+            return state.advance()
+        return False
+    
+    def cleanup_batch(self, batch_id: str):
+        """Clean up completed batch."""
+        if batch_id in self.execution_states:
+            del self.execution_states[batch_id]
+        if batch_id in self.pending_executions:
+            del self.pending_executions[batch_id]
+
+
+# Global execution manager instance
+execution_manager = ExecutionManager()

kikotools/tools/xyz_grid/controller/multi_select_node.py

@@ -0,0 +1,269 @@
+"""XYZ Plot Controller with multiple selection dropdowns."""
+
+from typing import Dict, List, Any, Tuple
+import folder_paths
+
+from ..utils.helpers import create_unique_id
+
+
+class XYZPlotController:
+    """XYZ Plot Controller with individual model selection dropdowns."""
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        # Get available options
+        models = folder_paths.get_filename_list("checkpoints")
+        vaes = ["Automatic"] + folder_paths.get_filename_list("vae")
+        loras = ["None"] + folder_paths.get_filename_list("loras")
+        
+        # Get sampler/scheduler options from a KSampler if available
+        samplers = ["euler", "euler_ancestral", "heun", "dpm_2", "dpm_2_ancestral", 
+                   "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", 
+                   "dpmpp_sde", "dpmpp_2m", "dpmpp_2m_sde", "ddim", "uni_pc"]
+        schedulers = ["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform"]
+        
+        axis_types = [
+            "none",
+            "models",
+            "vaes", 
+            "loras",
+            "samplers",
+            "schedulers",
+            "cfg_scale",
+            "steps",
+            "seed",
+            "denoise",
+            "clip_skip",
+            "prompt"
+        ]
+        
+        inputs = {
+            "required": {
+                # X Axis
+                "x_type": (axis_types, {"default": "none"}),
+                
+                # Y Axis  
+                "y_type": (axis_types, {"default": "none"}),
+                
+                # Z Axis
+                "z_type": (axis_types, {"default": "none"}),
+                
+                # Model selections (up to 10)
+                "model_1": (["disabled"] + models, {"default": "disabled"}),
+                "model_2": (["disabled"] + models, {"default": "disabled"}),
+                "model_3": (["disabled"] + models, {"default": "disabled"}),
+                "model_4": (["disabled"] + models, {"default": "disabled"}),
+                "model_5": (["disabled"] + models, {"default": "disabled"}),
+                
+                # VAE selections (up to 5)
+                "vae_1": (["disabled"] + vaes, {"default": "disabled"}),
+                "vae_2": (["disabled"] + vaes, {"default": "disabled"}),
+                "vae_3": (["disabled"] + vaes, {"default": "disabled"}),
+                
+                # LoRA selections (up to 5)
+                "lora_1": (["disabled"] + loras, {"default": "disabled"}),
+                "lora_2": (["disabled"] + loras, {"default": "disabled"}),
+                "lora_3": (["disabled"] + loras, {"default": "disabled"}),
+                
+                # Sampler selections (up to 5)
+                "sampler_1": (["disabled"] + samplers, {"default": "disabled"}),
+                "sampler_2": (["disabled"] + samplers, {"default": "disabled"}),
+                "sampler_3": (["disabled"] + samplers, {"default": "disabled"}),
+                
+                # Scheduler selections (up to 3)
+                "scheduler_1": (["disabled"] + schedulers, {"default": "disabled"}),
+                "scheduler_2": (["disabled"] + schedulers, {"default": "disabled"}),
+                
+                # Numeric values (still use text for flexibility)
+                "numeric_values": ("STRING", {
+                    "default": "", 
+                    "multiline": True,
+                    "placeholder": "For numeric types: use comma-separated values or start:stop:step"
+                }),
+                
+                # Prompts
+                "prompts": ("STRING", {
+                    "default": "", 
+                    "multiline": True,
+                    "placeholder": "For prompts: enter each prompt on a new line"
+                }),
+                
+                # Control
+                "auto_queue": ("BOOLEAN", {"default": True}),
+            },
+            "hidden": {
+                "unique_id": "UNIQUE_ID",
+            }
+        }
+        
+        return inputs
+    
+    RETURN_TYPES = ("XYZ_GRID", "STRING", "INT", "FLOAT", "STRING", "INT", "FLOAT", "STRING", "INT", "FLOAT", "STRING")
+    RETURN_NAMES = ("grid_data", "x_string", "x_int", "x_float", "y_string", "y_int", "y_float", "z_string", "z_int", "z_float", "batch_id")
+    OUTPUT_NODE = True
+    FUNCTION = "create_grid"
+    CATEGORY = "ComfyAssets/XYZ Grid"
+    
+    def create_grid(self, x_type, y_type, z_type, 
+                   model_1, model_2, model_3, model_4, model_5,
+                   vae_1, vae_2, vae_3,
+                   lora_1, lora_2, lora_3,
+                   sampler_1, sampler_2, sampler_3,
+                   scheduler_1, scheduler_2,
+                   numeric_values, prompts, auto_queue, unique_id=None):
+        """Create grid configuration from selections."""
+        
+        # Collect enabled selections
+        models = [m for m in [model_1, model_2, model_3, model_4, model_5] if m != "disabled"]
+        vaes = [v for v in [vae_1, vae_2, vae_3] if v != "disabled"]
+        loras = [l for l in [lora_1, lora_2, lora_3] if l != "disabled"]
+        samplers = [s for s in [sampler_1, sampler_2, sampler_3] if s != "disabled"]
+        schedulers = [s for s in [scheduler_1, scheduler_2] if s != "disabled"]
+        
+        # Parse values for each axis
+        x_parsed = self._get_axis_values(x_type, models, vaes, loras, samplers, schedulers, numeric_values, prompts)
+        y_parsed = self._get_axis_values(y_type, models, vaes, loras, samplers, schedulers, numeric_values, prompts)
+        z_parsed = self._get_axis_values(z_type, models, vaes, loras, samplers, schedulers, numeric_values, prompts)
+        
+        # Calculate total combinations
+        x_count = max(1, len(x_parsed))
+        y_count = max(1, len(y_parsed))
+        z_count = max(1, len(z_parsed))
+        total_images = x_count * y_count * z_count
+        
+        # Generate batch ID
+        batch_id = create_unique_id()
+        
+        # Create grid data
+        grid_data = {
+            "batch_id": batch_id,
+            "x_axis": {
+                "type": x_type,
+                "values": x_parsed,
+                "count": x_count
+            },
+            "y_axis": {
+                "type": y_type,
+                "values": y_parsed,
+                "count": y_count
+            },
+            "z_axis": {
+                "type": z_type,
+                "values": z_parsed,
+                "count": z_count
+            },
+            "total_images": total_images,
+            "current_index": 0,
+            "auto_queue": auto_queue
+        }
+        
+        # Get current values for outputs
+        x_current = x_parsed[0] if x_parsed else self._get_default_value(x_type)
+        y_current = y_parsed[0] if y_parsed else self._get_default_value(y_type)
+        z_current = z_parsed[0] if z_parsed else self._get_default_value(z_type)
+        
+        # Convert to appropriate output types
+        x_str, x_int, x_float = self._convert_value(x_type, x_current)
+        y_str, y_int, y_float = self._convert_value(y_type, y_current)
+        z_str, z_int, z_float = self._convert_value(z_type, z_current)
+        
+        # Log grid info
+        print(f"\n[XYZ Grid] Created grid with {total_images} total combinations:")
+        if x_type != "none":
+            print(f"  X axis ({x_type}): {x_count} values")
+        if y_type != "none":
+            print(f"  Y axis ({y_type}): {y_count} values")
+        if z_type != "none":
+            print(f"  Z axis ({z_type}): {z_count} values")
+        
+        return (grid_data, x_str, x_int, x_float, y_str, y_int, y_float, z_str, z_int, z_float, batch_id)
+    
+    def _get_axis_values(self, axis_type, models, vaes, loras, samplers, schedulers, numeric_values, prompts):
+        """Get values for a specific axis type."""
+        if axis_type == "none":
+            return []
+        elif axis_type == "models":
+            return models
+        elif axis_type == "vaes":
+            return vaes
+        elif axis_type == "loras":
+            return loras
+        elif axis_type == "samplers":
+            return samplers
+        elif axis_type == "schedulers":
+            return schedulers
+        elif axis_type == "prompt":
+            return [p.strip() for p in prompts.split("\n") if p.strip()]
+        elif axis_type in ["cfg_scale", "steps", "seed", "denoise", "clip_skip"]:
+            return self._parse_numeric_values(axis_type, numeric_values)
+        else:
+            return []
+    
+    def _parse_numeric_values(self, axis_type: str, values_str: str) -> List[Any]:
+        """Parse numeric values with range support."""
+        if not values_str.strip():
+            return []
+        
+        # Handle range notation (start:stop:step)
+        if ":" in values_str:
+            try:
+                parts = values_str.split(":")
+                if len(parts) == 2:
+                    start, stop = float(parts[0]), float(parts[1])
+                    step = 1.0
+                elif len(parts) == 3:
+                    start, stop, step = float(parts[0]), float(parts[1]), float(parts[2])
+                else:
+                    raise ValueError("Invalid range format")
+                
+                # Generate values
+                values = []
+                current = start
+                while current <= stop:
+                    if axis_type in ["steps", "seed", "clip_skip"]:
+                        values.append(int(current))
+                    else:
+                        values.append(round(current, 2))
+                    current += step
+                return values
+            except:
+                pass
+        
+        # Parse comma-separated values
+        values = [v.strip() for v in values_str.split(",") if v.strip()]
+        
+        # Convert numeric types
+        if axis_type in ["cfg_scale", "denoise"]:
+            return [float(v) for v in values]
+        elif axis_type in ["steps", "seed", "clip_skip"]:
+            return [int(v) for v in values]
+        else:
+            return values
+    
+    def _get_default_value(self, axis_type: str) -> Any:
+        """Get default value for axis type."""
+        defaults = {
+            "models": "",
+            "vaes": "Automatic",
+            "loras": "None",
+            "samplers": "euler",
+            "schedulers": "normal",
+            "cfg_scale": 7.0,
+            "steps": 20,
+            "seed": 0,
+            "denoise": 1.0,
+            "clip_skip": 1,
+            "prompt": ""
+        }
+        return defaults.get(axis_type, "")
+    
+    def _convert_value(self, axis_type: str, value: Any) -> Tuple[str, int, float]:
+        """Convert value to all output types."""
+        if axis_type in ["models", "vaes", "loras", "samplers", "schedulers", "prompt"]:
+            return (str(value), 0, 0.0)
+        elif axis_type in ["steps", "seed", "clip_skip"]:
+            return ("", int(value), float(value))
+        elif axis_type in ["cfg_scale", "denoise"]:
+            return ("", 0, float(value))
+        else:
+            return ("", 0, 0.0)

kikotools/tools/xyz_grid/controller/node.py

@@ -0,0 +1,139 @@
+"""XYZ Plot Controller node implementation."""
+
+from typing import Dict, List, Any, Tuple, Optional
+import json
+
+from ..utils.constants import AxisType, NUMERIC_DEFAULTS
+from ..utils.helpers import (
+    parse_value_string, generate_axis_labels, calculate_grid_dimensions, create_unique_id
+)
+from .execution import execution_manager
+
+
+class XYZPlotController:
+    """Main configuration node for XYZ grid plotting."""
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                # X Axis configuration
+                "x_axis_type": (AxisType.choices(), {"default": AxisType.NONE.value}),
+                "x_values": ("STRING", {"default": "", "multiline": True}),
+                "x_label_prefix": ("STRING", {"default": ""}),
+                
+                # Y Axis configuration  
+                "y_axis_type": (AxisType.choices(), {"default": AxisType.NONE.value}),
+                "y_values": ("STRING", {"default": "", "multiline": True}),
+                "y_label_prefix": ("STRING", {"default": ""}),
+            },
+            "optional": {
+                # Z Axis configuration (optional)
+                "z_axis_type": (AxisType.choices(), {"default": AxisType.NONE.value}),
+                "z_values": ("STRING", {"default": "", "multiline": True}),
+                "z_label_prefix": ("STRING", {"default": ""}),
+                
+                # Label formatting
+                "include_param_name": ("BOOLEAN", {"default": True}),
+                "value_only_labels": ("BOOLEAN", {"default": False}),
+            }
+        }
+    
+    RETURN_TYPES = ("XYZ_GRID", "STRING", "STRING", "STRING", "INT", "INT", "INT", "STRING")
+    RETURN_NAMES = ("grid_data", "x_value", "y_value", "z_value", "x_index", "y_index", "z_index", "batch_id")
+    FUNCTION = "configure_grid"
+    CATEGORY = "ComfyAssets/XYZ Grid"
+    
+    def __init__(self):
+        self.unique_id = None  # Set by ComfyUI
+        
+    def configure_grid(self, x_axis_type, x_values, x_label_prefix,
+                      y_axis_type, y_values, y_label_prefix,
+                      z_axis_type="none", z_values="", z_label_prefix="",
+                      include_param_name=True, value_only_labels=False):
+        """Configure and prepare grid generation."""
+        
+        # Parse axis types
+        x_type = AxisType(x_axis_type) if x_axis_type != "none" else None
+        y_type = AxisType(y_axis_type) if y_axis_type != "none" else None
+        z_type = AxisType(z_axis_type) if z_axis_type != "none" else None
+        
+        # Parse values for each axis
+        x_vals = parse_value_string(x_values, x_type) if x_type else [""]
+        y_vals = parse_value_string(y_values, y_type) if y_type else [""]
+        z_vals = parse_value_string(z_values, z_type) if z_type else [""]
+        
+        # Validate we have at least one axis configured
+        if not x_type and not y_type:
+            raise ValueError("At least one axis (X or Y) must be configured")
+        
+        # Calculate grid dimensions
+        dims = calculate_grid_dimensions(len(x_vals), len(y_vals), len(z_vals))
+        
+        # Generate labels
+        x_labels = self._generate_labels(x_vals, x_type, x_label_prefix, include_param_name, value_only_labels)
+        y_labels = self._generate_labels(y_vals, y_type, y_label_prefix, include_param_name, value_only_labels)
+        z_labels = self._generate_labels(z_vals, z_type, z_label_prefix, include_param_name, value_only_labels)
+        
+        # Create batch ID
+        batch_id = create_unique_id()
+        
+        # Prepare grid configuration
+        grid_config = {
+            "batch_id": batch_id,
+            "axes": {
+                "x": {"type": x_type, "values": x_vals, "labels": x_labels},
+                "y": {"type": y_type, "values": y_vals, "labels": y_labels},
+                "z": {"type": z_type, "values": z_vals, "labels": z_labels},
+            },
+            "dimensions": dims,
+            "total_images": dims["total_images"],
+            "current_index": 0,
+        }
+        
+        # Get current values from execution manager
+        x_val, y_val, z_val, x_idx, y_idx, z_idx = execution_manager.get_current_values(
+            batch_id, x_vals, y_vals, z_vals
+        )
+        
+        # Format output values based on type
+        x_output = self._format_output_value(x_val, x_type)
+        y_output = self._format_output_value(y_val, y_type)
+        z_output = self._format_output_value(z_val, z_type)
+        
+        return (grid_config, x_output, y_output, z_output, x_idx, y_idx, z_idx, batch_id)
+    
+    def _generate_labels(self, values: List[Any], axis_type: Optional[AxisType], 
+                        prefix: str, include_param: bool, value_only: bool) -> List[str]:
+        """Generate labels for axis values."""
+        if not values or not axis_type:
+            return []
+        
+        if value_only:
+            # Just use values as labels
+            return generate_axis_labels(values, axis_type, "")
+        elif include_param and not prefix:
+            # Use parameter name as prefix
+            param_names = AxisType.display_names()
+            prefix = param_names.get(axis_type, "") + ": "
+        
+        return generate_axis_labels(values, axis_type, prefix)
+    
+    def _format_output_value(self, value: Any, axis_type: Optional[AxisType]) -> str:
+        """Format value for output based on axis type."""
+        if not axis_type:
+            return ""
+        
+        # Return appropriate type based on what nodes expect
+        if axis_type in (AxisType.MODEL, AxisType.VAE, AxisType.LORA, 
+                        AxisType.SAMPLER, AxisType.SCHEDULER, AxisType.PROMPT):
+            return str(value)
+        else:
+            # Numeric types - return as string but nodes can convert
+            return str(value)
+    
+    @classmethod
+    def IS_CHANGED(cls, **kwargs):
+        """Force re-execution for grid iterations."""
+        # This ensures node re-executes for each grid cell
+        return float("nan")

kikotools/tools/xyz_grid/controller/power_node.py

@@ -0,0 +1,355 @@
+"""XYZ Plot Controller with Power Lora Loader-style dynamic widgets."""
+
+from typing import Dict, List, Any, Tuple, Union, Optional
+import folder_paths
+
+from ..utils.helpers import create_unique_id
+
+
+class FlexibleOptionalInputType(dict):
+    """Input that allows dynamic widget values from JavaScript."""
+    
+    def __contains__(self, key):
+        # Accept any key from JavaScript widgets
+        return True
+    
+    def __getitem__(self, key):
+        # Return a tuple that ComfyUI expects for input types
+        # This allows the JavaScript to pass widget values
+        return ("STRING", {"forceInput": False})
+
+
+class XYZPlotController:
+    """XYZ Plot Controller with dynamic widget management."""
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        axis_types = [
+            "none",
+            "models",
+            "vaes", 
+            "loras",
+            "samplers",
+            "schedulers",
+            "cfg_scale",
+            "steps",
+            "seed",
+            "denoise",
+            "clip_skip",
+            "prompt"
+        ]
+        
+        inputs = {
+            "required": {
+                # Axis configuration
+                "x_type": (axis_types, {"default": "none"}),
+                "y_type": (axis_types, {"default": "none"}),
+                "z_type": (axis_types, {"default": "none"}),
+                
+                # Control
+                "auto_queue": ("BOOLEAN", {"default": True}),
+            },
+            "optional": {
+                # Static inputs for numeric/prompt values
+                "numeric_values": ("STRING", {
+                    "default": "", 
+                    "multiline": True,
+                    "placeholder": "For numeric types: use comma-separated values or start:stop:step notation"
+                }),
+                
+                "prompt_values": ("STRING", {
+                    "default": "", 
+                    "multiline": True,
+                    "placeholder": "For prompts: enter each prompt on a new line"
+                })
+            },
+            "hidden": {
+                "unique_id": "UNIQUE_ID",
+                "prompt": "PROMPT",
+                "extra_pnginfo": "EXTRA_PNGINFO"
+            }
+        }
+        
+        # Use FlexibleOptionalInputType to accept dynamic widget values from JavaScript
+        # But don't create an actual input connection
+        inputs["optional"] = FlexibleOptionalInputType()
+        
+        return inputs
+    
+    RETURN_TYPES = ("XYZ_GRID", "STRING", "INT", "FLOAT", "STRING", "INT", "FLOAT", "STRING", "INT", "FLOAT", "STRING")
+    RETURN_NAMES = ("grid_data", "x_string", "x_int", "x_float", "y_string", "y_int", "y_float", "z_string", "z_int", "z_float", "batch_id")
+    OUTPUT_NODE = True
+    FUNCTION = "create_grid"
+    CATEGORY = "ComfyAssets/XYZ Grid"
+    
+    def create_grid(self, x_type="none", y_type="none", z_type="none", 
+                   auto_queue=True, numeric_values="", prompt_values="",
+                   unique_id=None, prompt=None, extra_pnginfo=None, **kwargs):
+        """Create grid configuration from dynamic selections."""
+        
+        # Extract dynamic values from kwargs
+        models = []
+        vaes = []
+        loras = []
+        samplers = []
+        schedulers = []
+        
+        # Process all kwargs to find dynamic widgets
+        for key, value in kwargs.items():
+            if key.startswith("x_") or key.startswith("y_") or key.startswith("z_"):
+                # Handle dynamic widget values
+                if isinstance(value, dict) and "on" in value and value["on"]:
+                    # Extract the resource type and axis
+                    parts = key.split("_")
+                    if len(parts) >= 3:
+                        axis = parts[0]
+                        resource_type = parts[1]
+                        
+                        # Store the value based on type
+                        if resource_type == "models" and value.get("value") != "none":
+                            models.append(value["value"])
+                        elif resource_type == "vaes" and value.get("value") != "none":
+                            vaes.append(value["value"])
+                        elif resource_type == "loras" and value.get("value") != "none":
+                            # For loras, store both name and strength
+                            lora_data = {
+                                "name": value["value"],
+                                "strength": value.get("strength", 1.0)
+                            }
+                            loras.append(lora_data)
+                        elif resource_type == "samplers" and value.get("value") != "none":
+                            samplers.append(value["value"])
+                        elif resource_type == "schedulers" and value.get("value") != "none":
+                            schedulers.append(value["value"])
+        
+        # Parse values for each axis
+        x_parsed = self._get_axis_values(x_type, models, vaes, loras, samplers, schedulers, numeric_values, prompt_values)
+        y_parsed = self._get_axis_values(y_type, models, vaes, loras, samplers, schedulers, numeric_values, prompt_values)
+        z_parsed = self._get_axis_values(z_type, models, vaes, loras, samplers, schedulers, numeric_values, prompt_values)
+        
+        # Calculate total combinations
+        x_count = max(1, len(x_parsed))
+        y_count = max(1, len(y_parsed))
+        z_count = max(1, len(z_parsed))
+        total_images = x_count * y_count * z_count
+        
+        # Generate batch ID
+        batch_id = create_unique_id()
+        
+        # Create grid data
+        grid_data = {
+            "batch_id": batch_id,
+            "x_axis": {
+                "type": x_type,
+                "values": x_parsed,
+                "count": x_count
+            },
+            "y_axis": {
+                "type": y_type,
+                "values": y_parsed,
+                "count": y_count
+            },
+            "z_axis": {
+                "type": z_type,
+                "values": z_parsed,
+                "count": z_count
+            },
+            "axes": {
+                "x": {
+                    "type": x_type,
+                    "labels": self._create_labels(x_type, x_parsed)
+                },
+                "y": {
+                    "type": y_type,
+                    "labels": self._create_labels(y_type, y_parsed)
+                },
+                "z": {
+                    "type": z_type,
+                    "labels": self._create_labels(z_type, z_parsed) if z_type != "none" else []
+                }
+            },
+            "dimensions": {
+                "total_images": total_images,
+                "x_count": x_count,
+                "y_count": y_count,
+                "z_count": z_count,
+                "cols": x_count,  # X axis forms columns
+                "rows": y_count,  # Y axis forms rows
+                "grids_count": z_count  # Z axis creates multiple grids
+            },
+            "total_images": total_images,  # Keep for backward compatibility
+            "current_index": 0,
+            "auto_queue": auto_queue
+        }
+        
+        # Get current values for outputs
+        x_current = x_parsed[0] if x_parsed else self._get_default_value(x_type)
+        y_current = y_parsed[0] if y_parsed else self._get_default_value(y_type)
+        z_current = z_parsed[0] if z_parsed else self._get_default_value(z_type)
+        
+        # Convert to appropriate output types
+        x_str, x_int, x_float = self._convert_value(x_type, x_current)
+        y_str, y_int, y_float = self._convert_value(y_type, y_current)
+        z_str, z_int, z_float = self._convert_value(z_type, z_current)
+        
+        # Log grid info
+        print(f"\n[XYZ Grid] Created grid with {total_images} total combinations:")
+        if x_type != "none":
+            print(f"  X axis ({x_type}): {x_count} values - {x_parsed}")
+        if y_type != "none":
+            print(f"  Y axis ({y_type}): {y_count} values - {y_parsed}")
+        if z_type != "none":
+            print(f"  Z axis ({z_type}): {z_count} values - {z_parsed}")
+        
+        return (grid_data, x_str, x_int, x_float, y_str, y_int, y_float, z_str, z_int, z_float, batch_id)
+    
+    def _get_axis_values(self, axis_type, models, vaes, loras, samplers, schedulers, numeric_values, prompt_values):
+        """Get values for a specific axis type."""
+        if axis_type == "none":
+            return []
+        elif axis_type == "models":
+            return models
+        elif axis_type == "vaes":
+            return vaes
+        elif axis_type == "loras":
+            return loras
+        elif axis_type == "samplers":
+            return samplers
+        elif axis_type == "schedulers":
+            return schedulers
+        elif axis_type == "prompt":
+            return [p.strip() for p in prompt_values.split("\n") if p.strip()]
+        elif axis_type in ["cfg_scale", "steps", "seed", "denoise", "clip_skip"]:
+            return self._parse_numeric_values(axis_type, numeric_values)
+        else:
+            return []
+    
+    def _parse_numeric_values(self, axis_type: str, values_str: str) -> List[Union[int, float]]:
+        """Parse numeric values with range support."""
+        if not values_str.strip():
+            return []
+        
+        # Handle range notation (start:stop:step)
+        if ":" in values_str:
+            try:
+                parts = values_str.split(":")
+                if len(parts) == 2:
+                    start, stop = float(parts[0]), float(parts[1])
+                    step = 1.0
+                elif len(parts) == 3:
+                    start, stop, step = float(parts[0]), float(parts[1]), float(parts[2])
+                else:
+                    raise ValueError("Invalid range format")
+                
+                # Generate values
+                values = []
+                current = start
+                while current <= stop:
+                    if axis_type in ["steps", "seed", "clip_skip"]:
+                        values.append(int(current))
+                    else:
+                        values.append(round(current, 2))
+                    current += step
+                return values
+            except:
+                pass
+        
+        # Parse comma-separated values
+        values = [v.strip() for v in values_str.split(",") if v.strip()]
+        
+        # Convert numeric types
+        if axis_type in ["cfg_scale", "denoise"]:
+            return [float(v) for v in values]
+        elif axis_type in ["steps", "seed", "clip_skip"]:
+            return [int(v) for v in values]
+        else:
+            return values
+    
+    def _get_default_value(self, axis_type: str) -> Any:
+        """Get default value for axis type."""
+        defaults = {
+            "models": "",
+            "vaes": "Automatic",
+            "loras": "None",
+            "samplers": "euler",
+            "schedulers": "normal",
+            "cfg_scale": 7.0,
+            "steps": 20,
+            "seed": 0,
+            "denoise": 1.0,
+            "clip_skip": 1,
+            "prompt": ""
+        }
+        return defaults.get(axis_type, "")
+    
+    def _convert_value(self, axis_type: str, value: Any) -> Tuple[str, int, float]:
+        """Convert value to all output types."""
+        if axis_type in ["models", "vaes", "loras", "samplers", "schedulers", "prompt"]:
+            # For loras, return the name string
+            if axis_type == "loras" and isinstance(value, dict):
+                return (value.get("name", ""), 0, 0.0)
+            return (str(value), 0, 0.0)
+        elif axis_type in ["steps", "seed", "clip_skip"]:
+            return ("", int(value), float(value))
+        elif axis_type in ["cfg_scale", "denoise"]:
+            return ("", 0, float(value))
+        else:
+            return ("", 0, 0.0)
+    
+    def _create_labels(self, axis_type: str, values: list) -> list:
+        """Create human-readable labels for axis values."""
+        labels = []
+        for value in values:
+            if axis_type == "prompt":
+                # Truncate long prompts
+                label = str(value)[:30] + "..." if len(str(value)) > 30 else str(value)
+            elif axis_type in ["models", "vaes", "loras"]:
+                # Use just the filename without path/extension for resources
+                if isinstance(value, dict) and "name" in value:
+                    name = value["name"]
+                else:
+                    name = str(value)
+                # Remove extension and path
+                label = name.split("/")[-1].split(".")[0]
+            elif axis_type in ["cfg_scale", "denoise"]:
+                # Format floats nicely
+                label = f"{float(value):.1f}"
+            elif axis_type in ["steps", "seed", "clip_skip"]:
+                # Just show the integer
+                label = str(int(value))
+            elif axis_type in ["samplers", "schedulers"]:
+                # Just use the name as-is
+                label = str(value)
+            else:
+                # Default: convert to string
+                label = str(value)
+            labels.append(label)
+        return labels
+    
+    def _apply_lora(self, model, clip, lora_data: dict):
+        """Apply a lora to model and clip."""
+        try:
+            # Import LoraLoader from ComfyUI
+            from nodes import LoraLoader
+            import folder_paths
+            
+            lora_name = lora_data.get("name")
+            strength = lora_data.get("strength", 1.0)
+            
+            if not lora_name:
+                return model, clip
+                
+            # Get the full path to the lora
+            lora_path = folder_paths.get_full_path("loras", lora_name)
+            if not lora_path:
+                print(f"[XYZ Grid] Warning: LoRA '{lora_name}' not found")
+                return model, clip
+                
+            # Apply the lora
+            loader = LoraLoader()
+            model, clip = loader.load_lora(model, clip, lora_name, strength, strength)
+            
+            return model, clip
+        except Exception as e:
+            print(f"[XYZ Grid] Error applying LoRA: {e}")
+            return model, clip