fix(autocomplete): address review findings and WebKit readiness

feat(ui): unify Display Text and Display Any output views

.comfyignore

@@ -0,0 +1,28 @@
+# Files excluded from the Comfy Registry archive (gitignore syntax).
+# Everything here is development-only; the published node needs
+# __init__.py, kikotools/, web/, examples/, README, LICENSE, pyproject.toml.
+
+# Test suite and tooling
+tests/
+scripts/
+.github/
+Makefile
+pytest.ini
+mypy.ini
+.flake8
+.pre-commit-config.yaml
+.secrets.baseline
+requirements-dev.txt
+
+# Reference / scratch code not imported by the node
+example.py
+
+# Agent and contributor docs
+CLAUDE.md
+CONTRIBUTING.md
+CODE_OF_CONDUCT.md
+
+tools/
+coverage/
+TESTING.md
+AGENTS.md

.flake8

@@ -1,7 +1,8 @@
 [flake8]
 max-line-length = 127
 max-complexity = 10
-exclude = 
+exclude =
+    node_modules,
     .git,
     __pycache__,
     .mypy_cache,
@@ -11,8 +12,9 @@ exclude =
     build,
     dist,
     *.egg-info,
-    .tox
-ignore = 
+    .tox,
+    referance
+ignore =
     # W503: line break before binary operator (conflicts with Black)
     W503,
     # E203: whitespace before ':' (conflicts with Black)
@@ -32,4 +34,4 @@ per-file-ignores =
 
 # Statistics
 count = True
-statistics = True
+statistics = True

.gitattributes

@@ -38,4 +38,4 @@
 *.safetensors binary
 *.ckpt binary
 *.pt binary
-*.pth binary
+*.pth binary

.github/branch-protection.json

@@ -0,0 +1,16 @@
+{
+  "required_status_checks": {
+    "strict": true,
+    "contexts": [
+      "py3.10 on ubuntu-latest", "py3.11 on ubuntu-latest", "py3.12 on ubuntu-latest", "py3.13 on ubuntu-latest",
+      "py3.10 on windows-latest", "py3.11 on windows-latest", "py3.12 on windows-latest", "py3.13 on windows-latest",
+      "py3.10 on macos-latest", "py3.11 on macos-latest", "py3.12 on macos-latest", "py3.13 on macos-latest",
+      "coverage gate (85%)", "frontend syntax", "frontend workflows and coverage", "code-quality"
+    ]
+  },
+  "enforce_admins": true,
+  "required_pull_request_reviews": null,
+  "restrictions": null,
+  "allow_force_pushes": false,
+  "allow_deletions": false
+}

.github/dependabot.yml

@@ -0,0 +1,14 @@
+version: 2
+updates:
+  - package-ecosystem: "pip"
+    directory: "/"
+    schedule:
+      interval: "weekly"
+  - package-ecosystem: "github-actions"
+    directory: "/"
+    schedule:
+      interval: "weekly"
+  - package-ecosystem: "npm"
+    directory: "/tools/testing"
+    schedule:
+      interval: "weekly"

.github/workflows/code-quality.yml

@@ -1,4 +1,6 @@
 name: Code Quality
+permissions:
+  contents: read
 
 on:
   push:
@@ -11,15 +13,15 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v7
 
     - name: Set up Python 3.10
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v7
       with:
         python-version: '3.10'
 
     - name: Cache pip dependencies
-      uses: actions/cache@v3
+      uses: actions/cache@v6
       with:
         path: ~/.cache/pip
         key: ${{ runner.os }}-pip-quality-${{ hashFiles('**/requirements-dev.txt') }}
@@ -29,6 +31,7 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
+        pip install torch --index-url https://download.pytorch.org/whl/cpu
         pip install -r requirements-dev.txt
 
     - name: Format check with Black
@@ -91,6 +94,14 @@ jobs:
         from kikotools.tools.kiko_save_image import KikoSaveImageNode
         from kikotools.tools.kiko_save_image.logic import process_image_batch, validate_save_inputs
 
+        # Test Model Downloader imports
+        from kikotools.tools.model_downloader import ModelDownloaderNode
+        from kikotools.tools.model_downloader.detector import URLDetector, DownloaderType
+        from kikotools.tools.model_downloader.base import BaseDownloader
+
+        # Test Text Input imports
+        from kikotools.tools.text_input import TextInputNode
+
         print('✓ All module imports successful')
         "
 
@@ -131,10 +142,10 @@ jobs:
   security:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v7
 
     - name: Set up Python 3.10
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v7
       with:
         python-version: '3.10'
 
@@ -162,16 +173,17 @@ jobs:
   architecture:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v7
 
     - name: Set up Python 3.10
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v7
       with:
         python-version: '3.10'
 
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
+        pip install torch --index-url https://download.pytorch.org/whl/cpu
         pip install -r requirements-dev.txt
 
     - name: Check architecture compliance
@@ -277,6 +289,41 @@ jobs:
             print('❌ KikoSaveImageNode missing OUTPUT_NODE = True')
             sys.exit(1)
 
+        # Test Model Downloader Node
+        from kikotools.tools.model_downloader.node import ModelDownloaderNode
+
+        if issubclass(ModelDownloaderNode, ComfyAssetsBaseNode):
+            print('✓ ModelDownloaderNode properly inherits from base class')
+        else:
+            print('❌ ModelDownloaderNode does not inherit from base class')
+            sys.exit(1)
+
+        # ModelDownloader is an output node, so it doesn't have RETURN_TYPES/RETURN_NAMES
+        download_required_attrs = ['INPUT_TYPES', 'FUNCTION', 'CATEGORY']
+        for attr in download_required_attrs:
+            if not hasattr(ModelDownloaderNode, attr):
+                print(f'❌ ModelDownloaderNode missing required attribute: {attr}')
+                sys.exit(1)
+
+        # Check that it's properly marked as an output node
+        if not hasattr(ModelDownloaderNode, 'OUTPUT_NODE') or not ModelDownloaderNode.OUTPUT_NODE:
+            print('❌ ModelDownloaderNode missing OUTPUT_NODE = True')
+            sys.exit(1)
+
+        # Test Text Input Node
+        from kikotools.tools.text_input.node import TextInputNode
+
+        if issubclass(TextInputNode, ComfyAssetsBaseNode):
+            print('✓ TextInputNode properly inherits from base class')
+        else:
+            print('❌ TextInputNode does not inherit from base class')
+            sys.exit(1)
+
+        for attr in required_attrs:
+            if not hasattr(TextInputNode, attr):
+                print(f'❌ TextInputNode missing required attribute: {attr}')
+                sys.exit(1)
+
         print('✓ All architecture checks passed for all tools')
         "
 

.github/workflows/publish.yml

@@ -18,7 +18,7 @@ jobs:
     if: ${{ github.repository_owner == 'ComfyAssets' }}
     steps:
       - name: Check out code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v7
         with:
           submodules: true
       - name: Publish Custom Node

.github/workflows/release.yml

@@ -1,5 +1,8 @@
 name: Release
 
+permissions:
+  contents: read
+
 on:
   push:
     tags:
@@ -7,53 +10,28 @@ on:
 
 jobs:
   create-release:
+    outputs:
+      version: ${{ steps.get_version.outputs.version }}
     runs-on: ubuntu-latest
+    permissions:
+      contents: write
 
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v7
 
     - name: Set up Python 3.10
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v7
       with:
         python-version: '3.10'
 
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
+        pip install torch --index-url https://download.pytorch.org/whl/cpu
         pip install -r requirements-dev.txt
 
-    - name: Run full test suite
-      run: |
-        python -c "
-        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!')
-        "
+    - name: Run full test suite and coverage gate
+      run: python -m pytest tests --cov=kikotools --cov-report=term-missing
 
     - name: Extract version from tag
       id: get_version
@@ -95,7 +73,7 @@ jobs:
         ### 📊 Technical Details
 
         - **Nodes**: 1 (Resolution Calculator)
-        - **Test Coverage**: 100%
+        - **Python Coverage Gate**: 85% combined statement/branch coverage
         - **Python Support**: 3.8+
         - **ComfyUI Compatibility**: Latest
 
@@ -109,7 +87,7 @@ jobs:
         EOF
 
     - name: Create GitHub Release
-      uses: softprops/action-gh-release@v1
+      uses: softprops/action-gh-release@v3
       with:
         tag_name: ${{ steps.get_version.outputs.version }}
         name: ComfyUI-KikoTools ${{ steps.get_version.outputs.version }}
@@ -142,4 +120,4 @@ jobs:
         echo "- Resolution Calculator tool"
         echo "- Complete documentation"
         echo "- Example workflows"
-        echo "- 100% test coverage"
+        echo "- Enforced Python coverage and frontend regression checks"

.github/workflows/tests.yml

@@ -1,5 +1,8 @@
 name: Tests
 
+permissions:
+  contents: read
+
 on:
   push:
     branches: [main, develop]
@@ -8,467 +11,135 @@ on:
 
 jobs:
   test:
-    runs-on: ubuntu-latest
+    name: py${{ matrix.python-version }} on ${{ matrix.os }}
+    runs-on: ${{ matrix.os }}
     strategy:
+      fail-fast: false
       matrix:
-        python-version: [3.8, 3.9, "3.10", "3.11", "3.12"]
+        os: [ubuntu-latest, windows-latest, macos-latest]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v7
 
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v7
         with:
           python-version: ${{ matrix.python-version }}
+          cache: pip
+          cache-dependency-path: requirements-dev.txt
 
-      - name: Cache pip dependencies
-        uses: actions/cache@v3
-        with:
-          path: ~/.cache/pip
-          key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements-dev.txt') }}
-          restore-keys: |
-            ${{ runner.os }}-pip-
+      # The default Linux torch wheel bundles CUDA (~2.5 GB); tests only need CPU.
+      # Windows and macOS default wheels are already CPU-only.
+      - name: Install CPU torch (Linux)
+        if: runner.os == 'Linux'
+        run: |
+          python -m pip install --upgrade pip
+          pip install torch --index-url https://download.pytorch.org/whl/cpu
 
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
           pip install -r requirements-dev.txt
 
-      - name: Run core functionality tests
-        run: |
-          python -c "
-          import sys
-          import os
-          sys.path.insert(0, os.getcwd())
+      - name: Run tests
+        run: python -m pytest tests --junitxml=test-results/pytest.xml
 
-          # Test imports
-          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('✓ All imports successful')
-
-          # Test base node
-          assert ComfyAssetsBaseNode.CATEGORY == 'ComfyAssets'
-          print('✓ Base node tests passed')
-
-          # Test dimension extraction
-          mock_image = torch.randn(1, 1216, 832, 3)
-          width, height = extract_dimensions(image=mock_image)
-          assert width == 832 and height == 1216
-          print('✓ Dimension extraction tests passed')
-
-          # Test scaling
-          new_width, new_height = calculate_scaled_dimensions(832, 1216, 1.5)
-          assert new_width % 8 == 0 and new_height % 8 == 0
-          print('✓ Scaling tests passed')
-
-          # Test node interface
-          node = ResolutionCalculatorNode()
-          result_width, result_height = node.calculate_resolution(1.5, image=mock_image)
-          assert isinstance(result_width, int) and isinstance(result_height, int)
-          assert result_width % 8 == 0 and result_height % 8 == 0
-          print('✓ Node interface tests passed')
-
-          # Test user scenario
-          width, height = node.calculate_resolution(1.53, image=mock_image)
-          print(f'✓ User scenario test: 832×1216 → {width}×{height} (1.53x scale)')
-
-          print('🎉 All tests passed!')
-          "
-
-      - name: Test Width Height Selector
-        run: |
-          python -c "
-          import sys
-          import os
-          sys.path.insert(0, os.getcwd())
-
-          # 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
-
-          print('✓ Width Height Selector imports successful')
-
-          # Test preset structure
-          assert len(PRESET_OPTIONS) > 0
-          assert 'custom' in PRESET_OPTIONS
-          assert len(PRESET_METADATA) > 0
-          print('✓ Preset structure tests 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')
-
-          # 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 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()
-
-          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')
-
-          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')
-
-          # 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']
-
-          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')
-
-          # 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:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Set up Python 3.10
-        uses: actions/setup-python@v4
+      - name: Upload test results
+        if: always()
+        uses: actions/upload-artifact@v7
         with:
-          python-version: "3.10"
+          name: python-${{ matrix.os }}-${{ matrix.python-version }}
+          path: test-results/
+          if-no-files-found: ignore
+          retention-days: 14
 
-      - name: Test package structure
-        run: |
-          # Check required files exist
-          test -f README.md || (echo "README.md missing" && exit 1)
-          test -f LICENSE || (echo "LICENSE missing" && exit 1)
-          test -f requirements-dev.txt || (echo "requirements-dev.txt missing" && exit 1)
-
-          # Check directory structure
-          test -d kikotools || (echo "kikotools directory missing" && exit 1)
-          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)
-
-          # 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"
-
-  test-documentation:
+  coverage:
+    name: coverage gate (85%)
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v7
 
-      - name: Test documentation completeness
+      - uses: actions/setup-python@v7
+        with:
+          python-version: "3.12"
+          cache: pip
+          cache-dependency-path: requirements-dev.txt
+
+      - name: Install dependencies
         run: |
-          # 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 "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)
+          python -m pip install --upgrade pip
+          pip install torch --index-url https://download.pytorch.org/whl/cpu
+          pip install -r requirements-dev.txt
 
-          # Check README has key sections
-          grep -q "Installation" README.md || (echo "README missing Installation section" && exit 1)
-          grep -q "Quick Start" README.md || (echo "README missing Quick Start section" && exit 1)
-          grep -q "Development" README.md || (echo "README missing Development section" && exit 1)
-          grep -q "Contributing" README.md || (echo "README missing Contributing section" && exit 1)
+      # fail_under = 85 lives in pyproject.toml [tool.coverage.report]
+      - name: Measure coverage
+        run: python -m pytest tests --cov=kikotools --cov-report=term-missing --cov-report=html --cov-report=xml
 
-          echo "✓ Documentation tests passed"
+      - name: Upload coverage reports
+        if: always()
+        uses: actions/upload-artifact@v7
+        with:
+          name: python-coverage
+          path: |
+            htmlcov/
+            coverage.xml
+          if-no-files-found: ignore
+          retention-days: 14
+
+  js-check:
+    name: frontend syntax
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v7
+
+      - uses: actions/setup-node@v7
+        with:
+          node-version: "24"
+
+      # Check every shipped module, including files without behavioral tests.
+      - name: Check all shipped JavaScript modules parse
+        run: |
+          shopt -s globstar nullglob
+          for f in web/**/*.js web/**/*.mjs; do
+            node --input-type=module --check < "$f" || { echo "Syntax error in $f"; exit 1; }
+          done
+
+  frontend:
+    name: frontend workflows and coverage
+    runs-on: ubuntu-latest
+    timeout-minutes: 15
+    steps:
+      - uses: actions/checkout@v7
+      - uses: actions/setup-python@v7
+        with:
+          python-version: "3.12"
+          cache: pip
+          cache-dependency-path: requirements-dev.txt
+      - name: Install Python test dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install torch --index-url https://download.pytorch.org/whl/cpu
+          pip install -r requirements-dev.txt
+      - uses: actions/setup-node@v7
+        with:
+          node-version: "24"
+          cache: npm
+          cache-dependency-path: tools/testing/package-lock.json
+      - run: npm ci --prefix tools/testing --ignore-scripts
+      - run: npx --prefix tools/testing playwright install --with-deps chromium firefox webkit
+      - name: JavaScript regressions, Chromium workflows, and coverage gate
+        run: npm run --prefix tools/testing test:coverage
+      - name: Firefox and WebKit workflows
+        run: npm run --prefix tools/testing test:browser -- --project firefox --project webkit
+      - name: Upload frontend reports
+        if: always()
+        uses: actions/upload-artifact@v7
+        with:
+          name: frontend-test-reports
+          path: |
+            tools/testing/test-results/
+            coverage/js/
+            !coverage/js/raw/
+          if-no-files-found: ignore
+          retention-days: 14

.gitignore

@@ -159,6 +159,19 @@ test_images/
 test_outputs/
 experiments/
 .claude/
+.serena
 
 # Gemini model cache
 .gemini_models_cache.json
+referance/
+
+# Runtime state written inside the package (repo is symlinked into custom_nodes)
+kikotools/tools/local_image_loader/config.json
+kikotools/tools/local_image_loader/selections.json
+gemini_config.json
+
+# Frontend test tooling and reports
+node_modules/
+coverage/
+playwright-report/
+test-results/

.pre-commit-config.yaml

@@ -4,10 +4,9 @@
 repos:
   # Python code formatting with Black
   - repo: https://github.com/psf/black
-    rev: 25.1.0
+    rev: 26.10.1
     hooks:
       - id: black
-        language_version: python3.10
         args: ['--line-length=88']  # Match CI configuration
 
   # Python linting with flake8
@@ -61,9 +60,27 @@ repos:
         args: ['--baseline', '.secrets.baseline']
         exclude: '^(tests/|\.git/)'
 
+  - repo: local
+    hooks:
+      - id: python-regressions
+        name: Python regression suite
+        entry: python -m pytest tests
+        language: system
+        pass_filenames: false
+        always_run: true
+        stages: [pre-push]
+      - id: frontend-regressions
+        name: JavaScript regression suite
+        entry: npm test --prefix tools/testing
+        language: system
+        pass_filenames: false
+        always_run: true
+        stages: [pre-push]
+
 # Configuration for specific hooks
+default_stages: [pre-commit]
 default_language_version:
-  python: python3.10
+  python: python3
 
 # Run hooks on all files by default
 fail_fast: false
@@ -81,4 +98,4 @@ exclude: |
     .*\.egg-info/|
     venv/|
     env/
-  )
+  )

AGENTS.md

@@ -0,0 +1,46 @@
+# Repository Guidelines
+
+## Project Structure & Module Organization
+
+`kikotools/tools/<tool>/logic.py` contains reusable logic; `node.py` defines the
+ComfyUI node. Shared classes live in `kikotools/base/`. Register nodes in
+`kikotools/__init__.py`; the root `__init__.py` exposes the plugin and API routes.
+`web/` contains browser extensions. Tests live in `tests/unit/`, `tests/js/`, and
+`tests/browser/`. Examples are in `examples/`.
+
+## Development Commands
+
+Install Python dependencies with `python -m pip install -r requirements-dev.txt`.
+Run `python -m pytest tests` or `make test` for the complete Python suite.
+Use `python -m pytest tests --cov=kikotools` for the 85% statement/branch gate.
+Format with `black .`; use `flake8 .` for lint findings.
+
+Frontend tooling needs Node.js 24 and `npm ci --prefix tools/testing
+--ignore-scripts`. Run `npm test --prefix tools/testing` for JavaScript tests,
+`npm run --prefix tools/testing test:coverage` for coverage and Chromium workflows,
+and `npm run --prefix tools/testing test:browser` for all browser projects.
+See `TESTING.md` for browser installation, environment overrides, and artifacts.
+
+## Coding Style & Naming
+
+Use four-space Python indentation and Black's 88-character formatting.
+Use `snake_case` for Python functions/modules, `PascalCase` for classes, and
+`UPPER_CASE` for constants. Keep node interfaces separate from logic. Preserve
+existing ComfyUI lifecycle hooks when extending widgets and clean up timers,
+listeners, and observers when nodes are removed.
+
+## Testing Guidelines
+
+Write regression tests first and verify failure before implementing fixes.
+Name Python tests `test_*.py` and JavaScript tests `*.test.mjs`; put browser
+workflows in `tests/browser/*.spec.mjs`. Test behavior and persistence, including
+failure recovery. Keep fixtures disposable and external services mocked.
+Never lower coverage floors to make a change pass.
+
+## Commits & Pull Requests
+
+Use Conventional Commits, such as `fix(local_image_loader): preserve error
+status`. Link the tracked issue, describe observable behavior, and report the
+commands and results used for validation. Include screenshots for visual changes.
+Required checks must pass before merging. Keep credentials and runtime files out
+of commits; restart ComfyUI after installing Python changes.

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.

CONTRIBUTING.md

@@ -357,9 +357,12 @@ Brief description of changes.
 
 ### Review Process
 
+See [TESTING.md](TESTING.md) for automated suites, coverage gates, required merge
+checks, and the remaining ComfyUI/GPU/service boundaries.
+
 1. **Automated Checks**: CI runs tests and quality checks
 2. **Code Review**: Maintainer reviews code and provides feedback
-3. **Testing**: Manual testing in ComfyUI environment
+3. **Testing**: Run relevant automated suites; use live ComfyUI checks for host, GPU, service, or visual changes
 4. **Merge**: After approval, changes are merged to main
 
 ## 🎨 Code Style Guidelines

Makefile

@@ -1,6 +1,6 @@
 # ComfyUI-KikoTools Development Makefile
 
-.PHONY: help install test test-fast lint format type-check quality-check clean setup dev-test release-test
+.PHONY: coverage frontend-test browser-test frontend-coverage help install test test-fast lint format type-check quality-check clean setup dev-test release-test
 
 # Python and virtual environment setup
 PYTHON := python3
@@ -34,7 +34,11 @@ help:
 	@echo "  quality-check  - Run all quality checks"
 	@echo ""
 	@echo "Testing:"
-	@echo "  test           - Run comprehensive tests"
+	@echo "  test           - Run the complete pytest suite"
+	@echo "  coverage       - Python statement/branch coverage (85% gate)"
+	@echo "  frontend-test  - JavaScript regression tests"
+	@echo "  browser-test   - Extension workflows in four browser configurations"
+	@echo "  frontend-coverage - JavaScript tests, browser tests, and coverage gate"
 	@echo "  test-fast      - Run core functionality tests"
 	@echo "  dev-test       - Quick development test"
 	@echo "  release-test   - Full release validation"
@@ -120,13 +124,20 @@ test-fast: $(VENV_DIR)
 	print('🎉 All core tests passed!'); \
 	"
 
-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 3: 832×1216 → 1272×1864 (scale: 1.53)"
-	@echo "✅ Error handling test passed"
-	@echo "🎉 All comprehensive tests passed!"
+test: $(VENV_DIR)
+	@$(PYTHON_CMD) -m pytest tests
+
+coverage: $(VENV_DIR)
+	@$(PYTHON_CMD) -m pytest tests --cov=kikotools --cov-report=term-missing --cov-report=html
+
+frontend-test:
+	npm test --prefix tools/testing
+
+browser-test:
+	npm run --prefix tools/testing test:browser
+
+frontend-coverage:
+	npm run --prefix tools/testing test:coverage
 
 release-test: quality-check test
 	@echo "Running release validation..."

README.md

@@ -8,12 +8,55 @@
 
 > A modular collection of essential custom ComfyUI nodes missing from the standard release.
 
-ComfyUI-KikoTools provides carefully crafted, production-ready nodes grouped under the **"ComfyAssets"** category. Each tool is designed with clean interfaces, comprehensive testing, and optimized performance for SDXL and FLUX workflows.
+ComfyUI-KikoTools provides carefully crafted, production-ready nodes under the "ComfyAssets" category.
+Each tool is built with clean interfaces, thorough testing, and optimized performance for SDXL and FLUX workflows.
+
+This project started out of frustration with keeping ComfyUI up to date and waiting for dozens of custom nodes to update—most of which I didn’t even use. After taking a hard look at my workflow, I realized I only needed one or two features from these nodes, many of which were abandoned or stuck in maintenance mode.
+
+I tried forking, patching, and submitting merge requests, but eventually decided to create my own curated collection of tools—fully supported and maintained by me. That’s how Kiko’s Tools was born.
+
+I’m sharing them here with the community, and I hope you find them as useful as I do.
 
 ## 🚀 Features
 
 ### ✨ Current Tools
 
+| Tool | Description | Category |
+|------|-------------|----------|
+| [📐 Resolution Calculator](#-resolution-calculator) | Calculate upscaled dimensions with model optimization | 🖼️ Resolution |
+| [📏 Width Height Selector](#-width-height-selector) | Preset-based dimension selection with visual swap | 🖼️ Resolution |
+| [🎲 Seed History](#-seed-history) | Advanced seed tracking with interactive history | 🌱 Seeds |
+| [⚙️ Sampler Combo](#️-sampler-combo) | Unified sampling configuration interface | 🌀 Samplers |
+| [📦 Empty Latent Batch](#-empty-latent-batch) | Create empty latent batches with preset support | 📦 Latents |
+| [💾 Kiko Save Image](#-kiko-save-image) | Enhanced image saving with popup viewer | 💾 Images |
+| [📋 Display Text](#-display-text) | Smart text display with prompt detection | 👁️ Display |
+| [🤖 Gemini Prompt Engineer](#-gemini-prompt-engineer) | AI-powered image analysis and prompt generation | 🧠 Prompts |
+| [🔍 Display Any](#-display-any) | Universal debugging tool for any data type | 👁️ Display |
+| [🖼️ Image to Multiple Of](#️-image-to-multiple-of) | Adjust dimensions to multiples for compatibility | 🖼️ Resolution |
+| [📉 Image Scale Down By](#-image-scale-down-by) | Scale images down by a factor with quality preservation | 🖼️ Resolution |
+| [🎬 Film Grain](#-film-grain) | Add realistic film grain effects to images | 💾 Images |
+| [🔤 Embedding Autocomplete](#-embedding-autocomplete) | Smart autocomplete for embeddings, LoRAs, and tags | 🔧 Utils |
+| [🧹 Kiko Purge VRAM](#-kiko-purge-vram) | Intelligent VRAM management with detailed reporting | 🛠️ Utils |
+| [📂 Local Image Loader](#-local-image-loader) | Visual gallery browser for local media files | 💾 Images |
+| [🌐 Model Downloader](#-model-downloader) | Download models from CivitAI, HuggingFace, and custom URLs | 🛠️ Utils |
+| [⏱️ Workflow Timer](#️-workflow-timer) | Real-time execution timer with customizable display | 🛠️ Utils |
+| [🗂️ Project File Path](#️-project-file-path) | Build safe, organized save prefixes like `MyProject/images/image` | 🛠️ Utils |
+
+### 🧰 xyz-helpers Tools
+
+Advanced parameter management tools adapted from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) (now in maintenance mode):
+
+| Tool | Description | Category |
+|------|-------------|----------|
+| [🎛️ Flux Sampler Params](#️-flux-sampler-params) | FLUX-optimized parameter generator with batch support | 🧰 xyz-helpers |
+| [📁 LoRA Folder Batch](#-lora-folder-batch) | Batch process multiple LoRAs from folders | 🧰 xyz-helpers |
+| [🔁 Checkpoint Folder Iterator](#-checkpoint-folder-iterator) | Load one checkpoint per queued run from a folder | 🧰 xyz-helpers |
+| [🧩 Model Compare Sheet](#-model-compare-sheet) | Save each run's image and rebuild a labeled contact sheet | 🧰 xyz-helpers |
+| [📊 Plot Parameters](#-plot-parameters) | Visualize parameter effects with graphs | 🧰 xyz-helpers |
+| [🎯 Sampler Select Helper](#-sampler-select-helper) | Intelligent sampler selection with recommendations | 🧰 xyz-helpers |
+| [📅 Scheduler Select Helper](#-scheduler-select-helper) | Optimal scheduler selection for samplers | 🧰 xyz-helpers |
+| [✍️ Text Encode Sampler Params](#️-text-encode-sampler-params) | Combined text encoding and parameter management | 🧰 xyz-helpers |
+
 #### 📐 Resolution Calculator
 Calculate upscaled dimensions from image or latent inputs with precision.
 
@@ -192,6 +235,313 @@ Adjusts image dimensions to be multiples of a specified value for model compatib
 
 ![Image to Multiple Of Example](examples/workflows/image_to_multiple_of_example.png)
 
+#### 📉 Image Scale Down By
+Efficiently scale images down by a specified factor with quality preservation.
+
+- **Proportional Scaling**: Reduces both width and height by the same factor
+- **Quality Preservation**: Uses bilinear interpolation with antialiasing
+- **Batch Support**: Process multiple images simultaneously
+- **Memory Efficient**: Optimized for large image batches
+- **Flexible Factor**: Scale from 0.01x to 1.0x with 0.01 precision
+
+**Use Cases:**
+- Create thumbnails or preview images
+- Reduce memory usage for large workflows
+- Generate image pyramids for multi-scale processing
+- Quick downsampling for performance optimization
+- Prepare images for web display or transmission
+
+#### 🎬 Film Grain
+Add realistic analog film grain effects to generated images.
+
+- **Realistic Grain Simulation**: Mimics actual film photography characteristics
+- **Grain Size Control**: Fine to coarse grain patterns (0.25x to 2.0x)
+- **Intensity Adjustment**: Variable strength from subtle to pronounced (0-10)
+- **Color Saturation**: Monochrome to full color grain (0-2)
+- **Shadow Lifting (Toe)**: Film-like shadow response curves
+- **Red Multiplier**: Adjust red channel independently for vintage looks
+- **Alpha Preservation**: Maintains transparency when present
+- **ITU-R BT.709 Color Space**: Professional color handling
+
+**Use Cases:**
+- Add vintage film aesthetic to AI-generated images
+- Create cinematic looks with authentic grain patterns
+- Simulate different film stocks (35mm, 16mm, etc.)
+- Add texture to overly smooth AI renders
+- Match grain from reference photography
+
+#### 🎛️ Flux Sampler Params
+FLUX-optimized parameter generator with intelligent batch processing capabilities.
+
+- **FLUX-Specific Tuning**: Optimized guidance, shift values, and step counts for FLUX models
+- **Batch Parameter Testing**: Generate multiple parameter sets for comparative analysis
+- **LoRA Integration**: Seamlessly combine with LoRA Folder Batch for comprehensive testing
+- **Smart Defaults**: Pre-configured optimal settings based on extensive FLUX testing
+- **Range Syntax Support**: Use `start...end+step` notation for parameter sweeps
+
+**Use Cases:**
+- Test different guidance and shift value combinations
+- Batch process with varying parameters
+- Optimize FLUX generation quality
+- Integrate with LoRA testing workflows
+
+#### 📁 LoRA Folder Batch
+Automated batch processing for multiple LoRA models from folders.
+
+- **Automatic Scanning**: Discovers all .safetensors files in specified folders
+- **Natural Epoch Sorting**: Intelligently sorts training epochs (epoch_004, epoch_020, etc.)
+- **Pattern Filtering**: Include/exclude LoRAs using powerful regex patterns
+- **Flexible Strength Control**: Single, multiple, or range-based strength values
+- **Batch Modes**: Sequential or combinatorial strength application
+- **Epoch Detection**: Automatically extracts epoch numbers from filenames
+
+**Use Cases:**
+- Test all epochs from a training run
+- Compare different LoRA versions
+- Evaluate strength variations
+- Batch process style transfers
+
+![LoRA Folder Batch Example](examples/workflows/xyz_helpers_lora_testing.png)
+
+#### 🔁 Checkpoint Folder Iterator
+Run the same prompt through every checkpoint in a folder, one model per queued run.
+
+- **folder**: relative to `models/checkpoints`, or an absolute path anywhere on disk; regex include/exclude filters
+- **index** with `control_after_generate`: set 0 + *increment*, then queue a batch count equal to the checkpoint count
+- Queuing past the last checkpoint fails that run with a clear message instead of wrapping around, so the finished sweep is never restarted or archived by accident
+- Outputs MODEL/CLIP/VAE for the indexed file plus `ckpt_name`, `label`, `index`, `count`
+- Only one checkpoint is loaded at a time, so large folders do not exhaust RAM
+
+#### 🧩 Model Compare Sheet
+Output node that pairs with Checkpoint Folder Iterator.
+
+- Saves each run's image(s) to `output/model_compare/<run_name>/<NN>_<label>.png`
+- Rebuilds `grid.png` from every tile saved so far, each labeled with its filename
+- `columns`, `tile_width`, `font_size` control the layout; the grid is also returned as IMAGE
+- The node preview (and anything else that reads it) gets `grid_preview.png`, at most 1024 px wide; `grid.png` keeps full resolution
+- After the last queued run the preview shows the complete sheet
+- Wire Project File Path into `run_name` for `project/date/sweep` folders
+- A run at index 0 moves tiles already in the folder to `<run_name>_<timestamp>`, so an interrupted sweep never leaks into the new grid
+- Rerunning a nonzero index replaces its complete batch, even when the label or batch size changes; other indexes are preserved
+- Replacement PNGs are fully written before existing tiles are changed; a failed tile write preserves the prior tiles and grid
+
+#### 📊 Plot Parameters
+Visual analysis tool for understanding parameter relationships and effects.
+
+- **Multiple Plot Types**: Line, bar, scatter, and heatmap visualizations
+- **Parameter Correlation**: Analyze relationships between settings and quality
+- **Statistical Analysis**: Calculate means, deviations, and trends
+- **Export Capabilities**: Save plots as images or CSV data
+- **Real-time Updates**: Dynamic graph generation during workflow execution
+
+**Use Cases:**
+- Visualize parameter impact on quality
+- Compare batch generation results
+- Analyze optimal parameter ranges
+- Document generation experiments
+
+#### 🎯 Sampler Select Helper
+Intelligent sampler selection with model-aware recommendations.
+
+- **Model Detection**: Automatic identification of SDXL, SD1.5, or FLUX models
+- **Quality Presets**: Fast, balanced, quality, and extreme presets
+- **Compatibility Checking**: Ensures optimal sampler-scheduler pairs
+- **Performance Profiles**: Pre-configured settings for different use cases
+- **Dynamic Discovery**: Adapts to newly available samplers
+
+**Use Cases:**
+- Automatic optimal sampler selection
+- Quick quality vs speed adjustments
+- Model-specific optimization
+- A/B testing different samplers
+
+#### 📅 Scheduler Select Helper
+Optimal scheduler selection based on sampler and model requirements.
+
+- **Sampler-Aware**: Recommends best schedulers for each sampler
+- **Noise Schedule Visualization**: Preview and compare schedule curves
+- **Model Optimization**: Specific tuning for SDXL, SD1.5, and FLUX
+- **Schedule Types**: Smooth, sharp, linear, and custom curves
+- **Beta Schedule Support**: Advanced control with custom beta values
+
+**Use Cases:**
+- Find optimal scheduler for your sampler
+- Visualize noise reduction curves
+- Compare different schedule types
+- Fine-tune generation behavior
+
+#### ✍️ Text Encode Sampler Params
+Unified interface for text encoding and sampler parameter management.
+
+- **All-in-One Node**: Combine prompt encoding with sampling configuration
+- **Template System**: Pre-configured settings for portraits, landscapes, etc.
+- **Prompt Syntax Support**: Wildcards, emphasis, and alternation
+- **Batch Processing**: Handle multiple prompts efficiently
+- **Model-Aware Encoding**: Optimize for different text encoders
+
+**Use Cases:**
+- Streamline text-to-image workflows
+- Apply consistent settings across prompts
+- Quick template-based generation
+- Batch prompt processing
+
+#### 📂 Local Image Loader
+Visual gallery browser for loading local images, videos, and audio files directly into ComfyUI workflows.
+
+- **Visual Gallery Interface**: Browse files with thumbnail previews in a masonry layout
+- **Multi-Media Support**: Load images (JPG, PNG, GIF, WebP), videos (MP4, WebM, MOV), and audio files (MP3, WAV, OGG, FLAC)
+- **Quick Navigation**: Navigate folders with breadcrumb path and parent directory button
+- **Responsive Layout**: Automatically adjusts thumbnail grid to available space
+- **Metadata Extraction**: Reads embedded prompt and workflow data from generated images
+- **Saved Paths**: Remember frequently used directories for quick access
+- **Double-Click Preview**: Open full-size media in new browser tab
+- **Smart Sorting**: Sort by name, date, or file size in ascending or descending order
+- **Pagination Support**: Efficiently browse large directories with page controls
+
+**Use Cases:**
+- Load reference images from local folders for img2img workflows
+- Browse and select from collections of generated images
+- Quickly access frequently used asset directories
+- Extract prompts and settings from previously generated images
+- Preview media files before loading into workflow
+
+#### 🌐 Model Downloader
+Download models, LoRAs, and other assets directly from CivitAI, HuggingFace, and custom URLs within ComfyUI.
+
+- **Multi-Platform Support**: CivitAI, HuggingFace, and direct download URLs
+- **Smart URL Detection**: Automatic detection of download source and file handling
+- **API Token Support**: Optional authentication for private/gated models
+- **Progress Reporting**: Real-time download progress with speed indicators
+- **Resume Support**: Skip existing files or force re-download
+- **Interrupt Handling**: Respects ComfyUI's "Cancel current run" button
+- **Automatic Cleanup**: Removes partial downloads on cancellation
+- **Custom Filenames**: Override auto-detected filenames when needed
+
+**Platform Features:**
+- **CivitAI**: Model page URLs, version-specific downloads, API authentication
+- **HuggingFace**: Blob and resolve URLs, branch/revision support, gated model access
+- **Custom URLs**: Direct download links with bearer token authentication
+
+**Use Cases:**
+- Download models without leaving ComfyUI
+- Automate asset acquisition in workflows
+- Access private or gated models with API tokens
+- Build reproducible workflows with automatic model fetching
+- Quickly test new models from the community
+
+![Model Downloader Example](examples/workflows/model_downloader_example.png)
+
+#### ⏱️ Workflow Timer
+Real-time execution timer that displays workflow duration with millisecond precision.
+
+- **Live Timing**: Updates in real-time during workflow execution (MM:SS:mmm format)
+- **Customizable Color**: Choose your preferred display color via KikoTools settings
+- **Glow Effect**: Optional pulsing glow animation (can be enabled/disabled in settings)
+- **Global Settings**: Color and glow preferences apply to all timer nodes
+- **Persistent Display**: Shows final execution time after workflow completes
+- **Multi-Node Sync**: All timer nodes stay synchronized during execution
+
+**Use Cases:**
+- Monitor workflow execution performance
+- Compare generation times across different settings
+- Identify slow nodes by adding timers at different workflow stages
+- Track optimization improvements over time
+
+**Settings (KikoTools Settings Panel):**
+- **Workflow Timer: Color** - Custom color picker for timer display
+- **Workflow Timer: Enable Glow** - Toggle pulsing glow effect on/off
+
+#### 🗂️ Project File Path
+Builds an organized save prefix to wire into a save node's `filename_prefix`.
+
+- **Structure**: `root/project_name/[YYYY-MM-DD/]subfolder/filename`, e.g. `MyProject/2026-10-13/images/image`
+- **Date Folder**: Optional toggle inserts today's date after the project; the node re-runs when the date changes
+- **Safe Paths**: Unsafe characters are removed, spaces become underscores, and `..` segments are dropped so paths stay inside the output folder
+- **Nested Folders**: Use `a/b` in `subfolder` for deeper structure
+- **Extensions**: Known file extensions (`.png`, `.mp4`, ...) are stripped from `filename`; `render_v1.5` is left as is
+- **Separator**: `auto`, `forward_slash` or `backslash`
+
+Based on the idea of the Project File Path Generator from djz-nodes.
+
+### 🔤 Embedding Autocomplete
+
+**Intelligent autocomplete for embeddings, LoRAs, and custom tags in text prompts.**
+
+<div align="center">
+  <img src="https://github.com/ComfyAssets/ComfyUI-KikoTools/blob/main/examples/ac-emb.png?raw=true" width="30%" alt="Embedding Autocomplete" />
+  <img src="https://github.com/ComfyAssets/ComfyUI-KikoTools/blob/main/examples/ac-lora.png?raw=true" width="30%" alt="LoRA Autocomplete" />
+  <img src="https://github.com/ComfyAssets/ComfyUI-KikoTools/blob/main/examples/ac-tag.png?raw=true" width="30%" alt="Tag Autocomplete" />
+</div>
+
+This feature is an enhanced fork of the autocomplete functionality from [ComfyUI-Custom-Scripts](https://github.com/pythongosssss/ComfyUI-Custom-Scripts) by pythongosssss. We've modernized the codebase, fixed existing bugs, and added robust security features.
+
+**Key Features:**
+- **Smart Triggers**: Type `embedding:` for embeddings, `<lora:` for LoRAs, or just start typing for tags
+- **Custom Word Lists**: Import CSV/TXT files or browser-accessible URLs, including [versioned Danbooru tag packs](docs/tag-packs/README.md), with local offline caching
+- **Safe Rendering**: Tag data stays plain text, with validated CSV fields and file-size limits
+- **Flexible Settings**: Customize triggers, auto-insert commas, replace underscores, and more
+- **Performance Optimized**: Handles 100,000+ tags smoothly with frequency-based sorting
+- **Visual Polish**: Clean UI with proper scrolling, keyboard navigation, and type indicators
+
+**Settings Include:**
+- Enable/disable autocomplete for embeddings, LoRAs, and custom tags
+- Configurable trigger phrases (e.g., `emb:`, `lora:`, custom shortcuts)
+- Auto-insert comma after completion
+- Replace underscores with spaces in tags
+- Choose insertion keys (Tab, Enter, or both)
+- Load custom word lists from URLs with security validation
+
+**Security Features:**
+- Validates CSV structure, tag names, categories, counts, and file size
+- Renders tag data as plain text rather than executable HTML or JavaScript
+- Rejects control characters and HTML error documents
+- File size limits to prevent memory exhaustion
+- Clear error messages for rejected content
+
+**Credits:**
+- Original autocomplete concept by [pythongosssss](https://github.com/pythongosssss/ComfyUI-Custom-Scripts)
+- Enhanced and modernized by KikoTools team
+
+### 🧹 Kiko Purge VRAM
+**Intelligent GPU memory management with threshold-based triggering and detailed reporting.**
+
+**Key Features:**
+- **4 Purge Modes**:
+  - `soft`: Basic garbage collection and cache clearing
+  - `aggressive`: Multiple GC passes with full CUDA cache clearing
+  - `models_only`: Unload all models and clear model cache
+  - `cache_only`: Clear CUDA cache without garbage collection
+- **Smart Thresholds**: Only purge when memory usage exceeds specified MB limit
+- **Detailed Reporting**: Shows before/after memory usage, freed MB, and timing
+- **Passthrough Design**: Acts as workflow checkpoint without disrupting data flow
+- **CPU Fallback**: Gracefully handles non-CUDA environments
+
+**Use Cases:**
+- Free memory between heavy processing stages
+- Prevent OOM errors in complex workflows
+- Debug memory usage patterns
+- Optimize multi-model workflows
+- Clean up after batch processing
+
+**Parameters:**
+- **anything**: Any input (passed through unchanged)
+- **mode**: Purge strategy selection
+- **report_memory**: Generate detailed memory statistics
+- **memory_threshold_mb**: Only purge if usage exceeds (0 = always purge)
+
+**Example Output:**
+```
+Memory usage (5000.0 MB) exceeds threshold (4000 MB)
+
+Memory Purge Report
+-------------------
+Mode: soft
+Memory Freed: 2500.0 MB
+Before: 5000.0 MB used (62.5%)
+After: 2500.0 MB used (31.3%)
+Time: 150.0ms
+```
+
 ### 💾 Kiko Save Image Features
 
 **Use Cases:**
@@ -213,7 +563,7 @@ Adjusts image dimensions to be multiples of a specified value for model compatib
 ### 🔧 Architecture Highlights
 
 - **Modular Design**: Each tool is self-contained and independently testable
-- **Test-Driven Development**: 100% test coverage with comprehensive unit tests
+- **Test-Driven Development**: Regression tests for Python logic, JavaScript extensions, and browser workflows
 - **Clean Interfaces**: Standardized input/output patterns across all tools
 - **Separation of Concerns**: Clear distinction between logic, UI, and integration layers
 - **SOLID Principles**: Extensible architecture following software engineering best practices
@@ -395,6 +745,21 @@ Load Image → Image to Multiple Of → VAE Encode → KSampler
 ```
 </details>
 
+<details>
+<summary><b>LoRA Testing with xyz-helpers</b></summary>
+
+```json
+{
+  "workflow": "Scan LoRA folder → Apply strength ranges → Generate grid → Plot parameters",
+  "strength_range": "0.9...1.2+0.1",
+  "batch_mode": "combinatorial",
+  "features": ["automatic epoch sorting", "parameter visualization", "batch generation"]
+}
+```
+
+Example workflow available: [xyz_helpers_lora_testing.json](examples/workflows/xyz_helpers_lora_testing.json)
+</details>
+
 ## 📚 Documentation
 
 ### Available Tools
@@ -411,6 +776,17 @@ Load Image → Image to Multiple Of → VAE Encode → KSampler
 | **Gemini Prompt Engineer** | AI-powered image analysis with dynamic model refresh | ✅ Complete | [Docs](examples/documentation/gemini_prompt.md) |
 | **Display Any** | Universal debugging tool for any data type or tensor shapes | ✅ Complete | [Docs](examples/documentation/display_any.md) |
 | **Image to Multiple Of** | Adjust image dimensions to multiples for model compatibility | ✅ Complete | [Docs](examples/documentation/image_to_multiple_of.md) |
+| **Image Scale Down By** | Efficiently scale images down by a specified factor | ✅ Complete | [Docs](examples/documentation/image_scale_down_by.md) |
+| **Film Grain** | Add realistic analog film grain effects to images | ✅ Complete | [Docs](examples/documentation/film_grain.md) |
+| **Flux Sampler Params** | FLUX-optimized parameter generator with batch support | ✅ Complete | [Docs](examples/documentation/flux_sampler_params.md) |
+| **LoRA Folder Batch** | Batch process multiple LoRAs from folders | ✅ Complete | [Docs](examples/documentation/lora_folder_batch.md) |
+| **Plot Parameters** | Visualize parameter effects with graphs | ✅ Complete | [Docs](examples/documentation/plot_parameters.md) |
+| **Sampler Select Helper** | Intelligent sampler selection with recommendations | ✅ Complete | [Docs](examples/documentation/sampler_select_helper.md) |
+| **Scheduler Select Helper** | Optimal scheduler selection for samplers | ✅ Complete | [Docs](examples/documentation/scheduler_select_helper.md) |
+| **Text Encode Sampler Params** | Combined text encoding and parameter management | ✅ Complete | [Docs](examples/documentation/text_encode_sampler_params.md) |
+| **Local Image Loader** | Visual gallery browser for local media files | ✅ Complete | [Docs](examples/documentation/local_image_loader.md) |
+| **Model Downloader** | Download models from CivitAI, HuggingFace, and custom URLs | ✅ Complete | [Docs](examples/documentation/model_downloader.md) |
+| **Workflow Timer** | Real-time execution timer with customizable display | ✅ Complete | [Docs](examples/documentation/workflow_timer.md) |
 | **Batch Image Processor** | Process multiple images with consistent settings | 🚧 Planned | Coming Soon |
 | **Advanced Prompt Utilities** | Enhanced prompt manipulation and generation | 🚧 Planned | Coming Soon |
 
@@ -651,8 +1027,8 @@ Following **Test-Driven Development (TDD)**:
 # Test structure
 tests/
 ├── unit/                    # Individual component tests
-├── integration/            # ComfyUI workflow tests
-└── fixtures/              # Test data and workflows
+├── js/                      # Extension and coverage-gate regression tests
+└── browser/                 # Browser workflows and disposable host fixtures
 ```
 
 ### Adding New Tools
@@ -693,7 +1069,7 @@ MIT License - see [LICENSE](LICENSE) file for details.
 
 ## 🏷️ Tags
 
-`comfyui` `custom-nodes` `image-processing` `ai-tools` `sdxl` `flux` `upscaling` `resolution` `batch-processing` `python` `pytorch`
+`comfyui` `custom-nodes` `image-processing` `ai-tools` `sdxl` `flux` `upscaling` `resolution` `batch-processing` `model-downloader` `civitai` `huggingface` `python` `pytorch`
 
 ## 🔗 Links
 
@@ -704,15 +1080,33 @@ MIT License - see [LICENSE](LICENSE) file for details.
 
 ## 📈 Stats
 
-- **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)
+- **Nodes**: 21 (15 core tools + 6 xyz-helpers)
+- **Features**: Embedding Autocomplete (settings-based, not a node)
+- **Categories**: 9 emoji-based categories for better organization
+- **Download Platforms**: 3 (CivitAI, HuggingFace, Custom URLs)
 - **Format Support**: 3 (PNG, JPEG, WebP with advanced controls)
 - **Presets**: 26 curated resolution presets
-- **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)
+- **Interactive Features**: 8+ (swap buttons, history UI, popup viewers, parameter visualization)
 - **AI Integration**: Gemini API with 40+ model support
-- **Test Coverage**: 100% (200+ comprehensive tests)
+- **Test Coverage**: Enforced 85% Python statement/branch coverage and per-file frontend coverage floors
 - **Python Version**: 3.8+
 - **ComfyUI Compatibility**: Latest
-- **Dependencies**: Minimal (PyTorch, NumPy, Pillow, google-generativeai for Gemini)
+- **Dependencies**: Minimal (PyTorch, NumPy, Pillow, google-genai for Gemini)
+
+## 🙏 Attribution
+
+### xyz-helpers Tools
+The xyz-helpers collection was adapted from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) by cubiq. The original project is in maintenance-only mode, and we've adopted these essential tools to ensure continued support and compatibility with modern ComfyUI workflows. We're grateful for cubiq's original work and contributions to the ComfyUI community.
+
+The following tools are based on comfyui-essentials-nodes:
+- Flux Sampler Params
+- LoRA Folder Batch
+- Plot Parameters
+- Sampler Select Helper
+- Scheduler Select Helper
+- Text Encode Sampler Params
+
+All adaptations maintain compatibility while adding new features and optimizations for the ComfyAssets ecosystem.
 
 ---
 
@@ -723,3 +1117,8 @@ 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>
+
+## Automated testing
+
+See [TESTING.md](TESTING.md) for Python and JavaScript tests, cross-browser
+workflows, coverage gates, CI reports, and required merge checks.

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!

TESTING.md

@@ -0,0 +1,129 @@
+# Testing and merge confidence
+
+Use regression tests before fixing a bug. Confirm that the test fails on the
+original implementation, then run the relevant suites after the fix.
+
+## What runs
+
+| Layer | Real components | Replaced boundaries |
+| --- | --- | --- |
+| Python | Tool logic, tensors, image files, API validation | ComfyUI services and external models where needed |
+| JavaScript | Production extension hooks and callback behavior | Minimal host objects; controlled timers for focused regressions |
+| Browser | All shipped extension imports and lifecycle registration; real plugin startup, HTTP routes, PNG thumbnails, selection persistence, and image loading | ComfyUI graph/widgets/settings/event interfaces and its saved-image serving endpoint |
+
+Browser workflows cover swaps, local image browsing/selection, pagination,
+sorting, hidden folders, directory autocomplete, saved paths,
+denied paths and network recovery, display output, seed persistence/cleanup, and
+workflow timing, autocomplete insertion, and saved-image previews. They run in Chromium, Firefox, WebKit, and touch Chromium.
+The harness binds to localhost and writes configuration, selections, and fixture
+images only inside a temporary directory. External browser requests fail tests;
+custom-word downloads are disabled in the fixture. No credentials, model
+weights, running ComfyUI, or GPU are required.
+
+## Run locally
+
+Use Python 3.10–3.13 and Node.js 24. Install the CPU PyTorch wheel on Linux if you
+do not need CUDA, then install the development dependencies:
+
+```sh
+python -m pip install torch --index-url https://download.pytorch.org/whl/cpu
+python -m pip install -r requirements-dev.txt
+python -m pytest tests
+python -m pytest tests --cov=kikotools --cov-report=term-missing
+npm ci --prefix tools/testing --ignore-scripts
+npx --prefix tools/testing playwright install --with-deps chromium firefox webkit
+npm test --prefix tools/testing
+npm run --prefix tools/testing test:coverage
+npm run --prefix tools/testing test:browser -- --project firefox --project webkit
+```
+
+`make test` runs the full pytest suite and propagates failures. `make coverage`,
+`make frontend-test`, `make browser-test`, and `make frontend-coverage` provide
+shortcuts. The Python Make targets use the existing virtual-environment setup.
+Install local commit and push hooks with `pre-commit install --hook-type
+pre-commit --hook-type pre-push`. The push hooks run Python and JavaScript
+regressions; CI additionally runs all browser workflows and coverage gates.
+For a quick browser check, use `test:browser -- --project chromium`.
+`KIKO_TEST_PYTHON` selects a Python executable with the development dependencies;
+`KIKO_TEST_PORT` changes the default port 8766. Servers are never reused.
+Unsupported Linux distributions may lack WebKit libraries; Ubuntu CI validates
+all engines.
+
+## Coverage and diagnosis
+
+Python CI checks all twelve Python/OS combinations and enforces 85% combined
+statement/branch coverage. Every production `web/*.js` file appears in frontend
+coverage, including code without behavioral coverage. V8 unit coverage and
+Chromium desktop/touch coverage are merged through c8. The committed per-file
+floors are an honest starting point, not a claim that every feature is tested.
+
+`npm run --prefix tools/testing coverage:update` reruns the suites and raises
+floors with two percentage points of runtime allowance. It cannot lower existing
+floors; new source files require 80% line coverage when added with this command.
+Missing measurements, missing baselines, and per-file regressions fail CI.
+
+CI artifacts include Python JUnit results, Python HTML/XML coverage, and
+`frontend-test-reports` with frontend HTML coverage and browser failure traces
+and screenshots. Open traces using Playwright's `show-trace` command. Local
+frontend coverage is at `coverage/js/index.html`.
+
+Real ComfyUI/LiteGraph compatibility, GPU execution, cloud inference, network
+model downloads, and visual design still need targeted live checks when changed.
+The browser host is a test double; these workflows do not run the real ComfyUI
+frontend or certify every node's UI. Type checking and security jobs retain their
+existing advisory behavior.
+
+### Actual ComfyUI frontend smoke test
+
+The Local Image Loader also has an opt-in suite using the actual ComfyUI frontend,
+graph, DOM widgets, renderer switch and palette settings. Start a local ComfyUI
+0.39.0 with frontend 1.55.14 and KikoTools installed, then run:
+
+```sh
+KIKO_COMFY_URL=http://127.0.0.1:8188/ node \
+  tools/testing/node_modules/@playwright/test/cli.js test \
+  --config tools/testing/comfyui.config.mjs
+```
+
+The suite requires those exact versions and records them in its artifacts. It
+serves the current checkout's extensions to a separate browser context and loads
+only KikoTools extensions. Media requests use the existing real Python routes
+with disposable fixture data on port 8771. Other HTTP writes are intercepted,
+so user settings, saved workflows and selections are not written to the live
+server. It does not execute a workflow or download models.
+
+Checks cover Classic/Nodes 2.0/live switching, theme changes, workflow save/reload
+and removal for the loader. Save Image additionally checks real image output,
+window close/reopen through the node control across renderer switches, theme
+changes, exclusion of the launcher from serialized values and owner removal.
+Its `/view` requests also use disposable fixture output rather than live files.
+Seed History checks keyboard-operable rows through renderer switches, list growth
+and scrolling on resize, palettes, saved history/node dimensions, serialization
+and polling cleanup on removal.
+Workflow Timer covers execution events, Classic/Nodes 2.0 switching, themes,
+custom node colors, persisted time/dimensions and the actual settings picker.
+Both dimension swap nodes cover keyboard swaps across renderers and zoom,
+responsive button sizing, palettes, native workflow values/saved sizes and
+removal cleanup. Latent batch size is preserved.
+Screenshots/traces appear in
+`tools/testing/test-results/comfyui/`. This opt-in smoke suite is separate from
+the required fixture CI job; fully provisioned, pinned ComfyUI CI and testing
+alongside other node packs remain follow-up work in issue #81.
+
+## Required merge checks
+
+The manifest in `.github/branch-protection.json` requires all Python matrix jobs,
+Python coverage, frontend syntax, frontend workflows/coverage, and the existing
+`code-quality` job (including Black and fatal lint checks). Administrators follow
+the same checks and branches must be current with main. No extra human approval
+is required. Workflows run on every pull request without path filters.
+
+After the checks pass, an administrator applies and verifies the manifest:
+
+```sh
+gh api --method PUT repos/ComfyAssets/ComfyUI-KikoTools/branches/main/protection \
+  --input .github/branch-protection.json
+gh api repos/ComfyAssets/ComfyUI-KikoTools/branches/main/protection/required_status_checks
+```
+
+Keep the manifest synchronized with job names when changing CI.

__init__.py

@@ -13,7 +13,91 @@ except ImportError:
     from kikotools import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
 
 # Tell ComfyUI where to find our JavaScript extensions
-WEB_DIRECTORY = "./web"
+import os
+
+WEB_DIRECTORY = os.path.join(os.path.dirname(os.path.abspath(__file__)), "web")
+
+# Import server components at module level to ensure they're available
+try:
+    from aiohttp import web
+    from server import PromptServer
+    import folder_paths
+
+    print("[KikoTools] Server imports successful")
+
+    # Register autocomplete endpoints directly
+    @PromptServer.instance.routes.get("/kikotools/autocomplete/embeddings")
+    async def get_embeddings(request):
+        """API endpoint for getting list of embeddings with full paths."""
+        print("[KikoTools] Embeddings endpoint called")
+        try:
+            embedding_files = folder_paths.get_filename_list("embeddings")
+            print(f"[KikoTools] Found {len(embedding_files)} embedding files")
+            # Return embeddings with their subdirectory paths, without extensions
+            embeddings = []
+            for f in embedding_files:
+                # Remove extension but keep subdirectory path
+                clean_path = os.path.splitext(f)[0]
+                embeddings.append(
+                    {
+                        "file_name": clean_path,
+                        "model_name": clean_path,
+                        "name": os.path.basename(clean_path),
+                        "path": clean_path,
+                    }
+                )
+            if len(embeddings) > 0:
+                print(f"[KikoTools] Sample embedding: {embeddings[0]}")
+            print(f"[KikoTools] Returning {len(embeddings)} embeddings with paths")
+            return web.json_response(embeddings)
+        except Exception as e:
+            print(f"[KikoTools] Error getting embeddings: {e}")
+            import traceback
+
+            traceback.print_exc()
+            return web.json_response([])
+
+    @PromptServer.instance.routes.get("/kikotools/autocomplete/loras")
+    async def get_loras(request):
+        """API endpoint for getting list of LoRAs."""
+        print("[KikoTools] LoRA endpoint called")
+        try:
+            lora_files = folder_paths.get_filename_list("loras")
+            print(f"[KikoTools] Found {len(lora_files)} LoRA files")
+            # Return LoRAs with paths
+            loras = []
+            for f in lora_files:
+                clean_path = os.path.splitext(f)[0]
+                loras.append(
+                    {
+                        "name": os.path.basename(clean_path),
+                        "path": clean_path,
+                        "file": f,
+                    }
+                )
+            print(f"[KikoTools] Returning {len(loras)} LoRAs")
+            return web.json_response(loras)
+        except Exception as e:
+            print(f"[KikoTools] Error getting LoRAs: {e}")
+            import traceback
+
+            traceback.print_exc()
+            return web.json_response([])
+
+    print("[KikoTools] Autocomplete API endpoints registered successfully")
+    print(
+        "[KikoTools] Routes available: /kikotools/autocomplete/embeddings and /kikotools/autocomplete/loras"
+    )
+
+except ImportError as e:
+    print(f"[KikoTools] Could not import server components: {e}")
+except Exception as e:
+    print(f"[KikoTools] Unexpected error setting up API: {e}")
+    import traceback
+
+    traceback.print_exc()
+
+# API endpoints are registered above at module import time
 
 
 def get_version():
@@ -21,7 +105,7 @@ def get_version():
     try:
         pyproject_path = Path(__file__).parent / "pyproject.toml"
         if pyproject_path.exists():
-            content = pyproject_path.read_text()
+            content = pyproject_path.read_text(encoding="utf-8")
             match = re.search(r'version\s*=\s*["\']([^"\']+)["\']', content)
             if match:
                 return match.group(1)
@@ -34,7 +118,10 @@ def get_version():
 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}")
+    # ASCII only: a Windows console using a legacy code page cannot print emoji,
+    # and a UnicodeEncodeError here would abort loading the whole node.
+    ascii_name = display_name.encode("ascii", "ignore").decode().strip()
+    print(f"  \033[94mLoaded:\033[0m {ascii_name}")
 print(f"\033[94mTotal: {len(NODE_CLASS_MAPPINGS)} tools loaded\033[0m")
 print()
 

docs/tag-packs/README.md

@@ -0,0 +1,48 @@
+# Autocomplete tag packs
+
+ComfyAssets prepares filtered autocomplete data from Danbooru's public
+`tags.json` and `tag_aliases.json` APIs. Dataset releases are versioned separately
+from KikoTools and stored as release assets, keeping bulk data out of Git history.
+
+## Danbooru — Illustrious / NoobAI, 2026-10-16
+
+[Download the CSV and manifest](https://github.com/ComfyAssets/ComfyUI-KikoTools/releases/tag/tags-2026-10-16).
+This snapshot contains 165,158 canonical tags, their categories, post counts, and
+aliases. The adjacent manifest records the retrieval date, model targets,
+selection filters, schema, byte size, and SHA-256 checksum.
+
+The UTF-8 CSV has no header. Columns are `tag,category,post_count,aliases`.
+Aliases share a comma-separated field; use a CSV parser that respects quoting.
+An empty alias field means no aliases. Category codes are 0 (general), 1
+(artist), 3 (copyright), 4 (character), and 5 (meta).
+
+In ComfyUI Settings, search **Embedding Autocomplete**, open its settings,
+then download the pack and choose the CSV under **Tag list file**. Enable
+**Show Custom Words** and select **Save Settings**. Importing stages the list;
+Cancel leaves the active list unchanged. The browser caches the saved file in
+IndexedDB for offline use and restores it after a refresh. Clearing browser site
+data removes this cache. There is no server-side autocomplete folder to populate.
+
+Alternatively, enter a CSV/TXT URL and select **Load URL**, then save. Remote
+servers must allow browser cross-origin requests; for GitHub release assets,
+download and import the file locally. Existing one-column word lists and
+`tag,frequency` lists remain supported. The default URL is unchanged.
+
+Parsing runs in a Web Worker with a 32 MB UTF-8 limit. Search checks canonical
+names and aliases, inserts the canonical tag, and ranks exact matches ahead of
+prefixes and substrings, then by descending post count. The number of displayed
+results is bounded by Maximum suggestions. Categories are retained in records;
+category-specific controls are not currently exposed.
+
+## Source and terms
+
+Source data: [Danbooru](https://danbooru.donmai.us/), collected 2026-10-16.
+Selection and packaging: ComfyAssets. This is an independent filtered snapshot,
+not an official Danbooru release or a guarantee of model compatibility.
+
+Refer to [Danbooru's Terms of Service](https://danbooru.donmai.us/terms) and the
+[official terms template](https://github.com/danbooru/danbooru/blob/master/app/views/static/terms_of_service.html.erb).
+The template's Copyright Infringement section identifies tags as factual
+information that is generally not copyrightable. Its API Usage section requires
+compliance with API rate limits. This reference does not claim an explicit
+dataset license or extend KikoTools' software license to upstream data.

docs/tag-packs/danbooru-illustrious-noobai-2026-10-16.manifest.json

@@ -0,0 +1,35 @@
+{
+  "source": "danbooru.donmai.us tags.json + tag_aliases.json",
+  "pulled": "2026-10-16",
+  "target_models": "Illustrious 1.0-3.x, NoobAI-XL",
+  "filters": {
+    "created_before": "2025-01-01",
+    "min_post_count": {
+      "general": 50,
+      "artist": 30,
+      "copyright": 20,
+      "character": 20
+    },
+    "artists_kept": true,
+    "deprecated_removed": true,
+    "meta_tags": "removed except small allowlist"
+  },
+  "tag_count": 165158,
+  "schema_version": 1,
+  "file": "danbooru-illustrious-noobai-2026-10-16.csv",
+  "encoding": "UTF-8",
+  "header_row": false,
+  "columns": [
+    "tag",
+    "category",
+    "post_count",
+    "aliases"
+  ],
+  "aliases_format": "Comma-separated inside a CSV-quoted field when necessary",
+  "size_bytes": 3979593,
+  "sha256": "733531a60f2e2d38925f53381b18cff21513ef14550d1f2ca670a0f55b86b798",
+  "prepared_by": "ComfyAssets",
+  "terms_url": "https://danbooru.donmai.us/terms",
+  "terms_source_url": "https://github.com/danbooru/danbooru/blob/master/app/views/static/terms_of_service.html.erb",
+  "release_tag": "tags-2026-10-16"
+}

examples/documentation/batch_prompts.md

@@ -0,0 +1,106 @@
+# Batch Prompts Node
+
+The **Batch Prompts** node loads and processes prompts from text files for batch generation workflows. It automatically cycles through prompts with each execution, making it perfect for testing multiple prompts in queue batches.
+
+## Features
+
+- **File-based prompt loading** - Load prompts from text files with `---` separators
+- **Auto-increment mode** - Automatically advance to the next prompt with each execution
+- **Positive/Negative splitting** - Automatically splits prompts at "Negative:" markers
+- **Persistent state** - Maintains position across ComfyUI restarts
+- **Wrap-around support** - Loop back to the first prompt after the last one
+- **Progress tracking** - Shows current position and total prompts
+
+## Input Parameters
+
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `prompt_file` | STRING | "prompts.txt" | Path to text file containing prompts |
+| `index` | INT | 0 | Manual prompt index (when auto_increment is off) |
+| `auto_increment` | BOOLEAN | True | Automatically advance to next prompt |
+| `wrap_around` | BOOLEAN | True | Loop back to start after last prompt |
+| `split_negative` | BOOLEAN | True | Split prompts at "Negative:" marker |
+| `reload_file` | BOOLEAN | False | Force reload file from disk |
+| `show_preview` | BOOLEAN | True | Show prompt preview in console |
+
+## Output Values
+
+| Output | Type | Description |
+|--------|------|-------------|
+| `positive` | STRING | The positive prompt text |
+| `negative` | STRING | The negative prompt text (if split) |
+| `full_prompt` | STRING | Complete prompt including negative |
+| `next_prompt` | STRING | Preview of the next prompt |
+| `current_index` | INT | Current prompt index (0-based) |
+| `total_prompts` | INT | Total number of prompts |
+| `batch_info` | STRING | Progress information string |
+
+## Prompt File Format
+
+Create a text file with prompts separated by `---` on its own line:
+
+```
+A beautiful sunset over the ocean
+Negative: blurry, dark, low quality
+---
+Mountain landscape with snow peaks
+Negative: foggy, unclear
+---
+Futuristic city at night
+Negative: old, vintage, sepia
+```
+
+## Usage Examples
+
+### Basic Queue Batch Processing
+
+1. Create a prompt file in your ComfyUI `input` folder
+2. Add the Batch Prompts node to your workflow
+3. Set `prompt_file` to your file name
+4. Enable `auto_increment` and `wrap_around`
+5. Connect `positive` to your text encoder
+6. Connect `negative` to your negative text encoder
+7. Set Queue Batch to desired number (e.g., 10)
+8. Run the queue - prompts will cycle automatically
+
+### Manual Index Control
+
+For manual control over which prompt to use:
+
+1. Set `auto_increment` to False
+2. Control the `index` parameter manually
+3. Use with other nodes that provide index values
+
+### Monitoring Progress
+
+The node provides several ways to track progress:
+
+- `batch_info` output shows "Prompt X of Y (Z% complete)"
+- Console logging shows current prompt preview (when `show_preview` is True)
+- `current_index` and `total_prompts` for custom progress displays
+
+## Tips
+
+- Place prompt files in the ComfyUI `input` folder for easy access
+- Use relative paths like "prompts.txt" for files in the input folder
+- Use absolute paths for files elsewhere on your system
+- The node maintains state across ComfyUI restarts
+- Set `reload_file` to True to force re-reading after editing the file
+- Empty sections (between `---` markers) are automatically skipped
+
+## Troubleshooting
+
+### Prompts not changing in queue batch
+- Ensure `auto_increment` is set to True
+- Check console for "[BatchPrompts] Auto-increment" messages
+- Restart ComfyUI after installing/updating the node
+
+### File not found errors
+- Check that the file exists in the ComfyUI `input` folder
+- Try using an absolute path to test
+- Ensure file has read permissions
+
+### State persistence
+- State is stored in your system's temp directory
+- Clear `/tmp/comfyui_batch_prompts/` to reset all counters
+- Use `reload_file` to reset counter for a specific file

examples/documentation/display_any.md

@@ -117,4 +117,4 @@ Config Node → Display Any (raw value) → Processing Node
 [Text Multiline] ← [Concatenate] ← "Image dimensions: "
 ```
 
-This creates a text output showing the current image dimensions that can be used elsewhere in your workflow.
+This creates a text output showing the current image dimensions that can be used elsewhere in your workflow.

examples/documentation/display_text.md

@@ -85,7 +85,7 @@ Display long text content with scrolling and word wrapping.
 
 The node intelligently detects prompt formats:
 
-1. **SDXL Format**: 
+1. **SDXL Format**:
    - Looks for "Positive prompt:" and "Negative prompt:" markers
    - Case-insensitive detection
    - Handles various formatting styles
@@ -98,7 +98,7 @@ The node intelligently detects prompt formats:
 ## Styling
 
 - **Font**: Monospace for consistent alignment
-- **Colors**: 
+- **Colors**:
   - Text: Light gray (#ddd) on dark background
   - Background: Semi-transparent dark (#1a1a1a)
   - Borders: Subtle gray (#333)
@@ -144,4 +144,4 @@ The node intelligently detects prompt formats:
    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.
+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/flux_sampler_params.md

@@ -0,0 +1,152 @@
+# Flux Sampler Params
+
+## Overview
+The **Flux Sampler Params** node provides a specialized parameter generator for FLUX model sampling. This tool was adapted from the excellent [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) project (now in maintenance mode) and enhanced for the ComfyAssets ecosystem.
+
+## Attribution
+This node is based on work from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) by cubiq. The original project is in maintenance-only mode, and we've adopted and enhanced these tools to ensure continued support and compatibility with modern ComfyUI workflows.
+
+## Features
+- **FLUX-Optimized Parameters**: Specifically tuned for FLUX model requirements
+- **Batch Processing Support**: Generate multiple parameter sets for comparative testing
+- **Interactive UI Elements**: Visual controls for quick parameter adjustments
+- **Smart Defaults**: Pre-configured optimal settings for FLUX workflows
+- **Comprehensive Parameter Control**: Fine-tune all aspects of FLUX sampling
+
+## Node Properties
+- **Category**: `ComfyAssets/🧰 xyz-helpers`
+- **Node Name**: `FluxSamplerParams`
+- **Function**: `get_value`
+
+## Inputs
+
+### Required
+| Parameter | Type | Default | Range | Description |
+|-----------|------|---------|-------|-------------|
+| `scheduler` | DROPDOWN | normal | [normal, simple, sgm_uniform] | Scheduler algorithm for sampling |
+| `steps` | INT | 20 | 1-100 | Number of sampling steps |
+| `guidance` | FLOAT | 3.5 | 0.0-100.0 | Guidance scale for conditioning |
+| `max_shift` | FLOAT | 1.0 | 0.0-100.0 | Maximum shift value for FLUX |
+| `base_shift` | FLOAT | 0.5 | 0.0-100.0 | Base shift value for FLUX |
+| `denoise` | FLOAT | 1.0 | 0.0-1.0 | Denoising strength |
+| `batch_mode` | DROPDOWN | single | [single, batch] | Single value or batch processing |
+
+### Optional
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `batch_count` | INT | 1 | Number of batch variations (1-100) |
+| `batch_seed_mode` | DROPDOWN | incremental | Seed generation mode for batches |
+| `variation_seed` | INT | None | Optional seed for variations |
+| `lora_params` | LORA_PARAMS | None | LoRA parameters from LoRAFolderBatch |
+
+## Outputs
+| Name | Type | Description |
+|------|------|-------------|
+| `sampler_params` | SAMPLER_PARAMS | Complete FLUX sampling parameters |
+| `scheduler` | STRING | Selected scheduler algorithm |
+| `steps` | INT | Number of sampling steps |
+| `guidance` | FLOAT | Guidance scale value |
+
+## Usage Examples
+
+### Basic FLUX Sampling
+```
+FluxSamplerParams → KSampler → VAE Decode → Save Image
+    scheduler: normal
+    steps: 20
+    guidance: 3.5
+```
+
+### Batch Parameter Testing
+```
+FluxSamplerParams → KSampler → Image Grid → Save
+    batch_mode: batch
+    batch_count: 5
+    guidance: 2.0...5.0
+```
+
+### With LoRA Integration
+```
+LoRAFolderBatch → FluxSamplerParams → KSampler
+    ↓                    ↓
+    lora_params → Combined parameters
+```
+
+## Best Practices
+
+### FLUX-Specific Settings
+- **Guidance**: FLUX typically works best with lower guidance (2.0-5.0)
+- **Steps**: 15-25 steps usually sufficient for FLUX
+- **Scheduler**: `normal` or `sgm_uniform` recommended for FLUX
+- **Shift Values**: Adjust for different quality/speed tradeoffs
+
+### Batch Testing Workflow
+1. Set `batch_mode` to `batch`
+2. Configure parameter ranges using `...` syntax
+3. Set appropriate `batch_count`
+4. Use with image grid nodes for comparison
+
+### Memory Optimization
+- Start with smaller batch counts for testing
+- Monitor VRAM usage with high batch counts
+- Use incremental seed mode for reproducibility
+
+## Integration with Other Nodes
+
+### Works Well With
+- **LoRA Folder Batch**: Combine multiple LoRAs with FLUX parameters
+- **Plot Parameters**: Visualize parameter effects
+- **Sampler Select Helper**: Dynamic sampler selection
+- **Text Encode Sampler Params**: Add text conditioning
+
+### Common Workflows
+1. **Parameter Sweep**: Test multiple guidance/step combinations
+2. **LoRA Testing**: Evaluate different LoRA strengths with FLUX
+3. **Quality Comparison**: Compare different shift values
+4. **Seed Exploration**: Generate variations with controlled seeds
+
+## Tips and Tricks
+
+### Optimal FLUX Settings
+```python
+# High Quality (Slower)
+scheduler: "sgm_uniform"
+steps: 25
+guidance: 3.5
+max_shift: 1.0
+base_shift: 0.5
+
+# Fast Preview
+scheduler: "simple"
+steps: 12
+guidance: 2.5
+max_shift: 0.8
+base_shift: 0.4
+```
+
+### Batch Parameter Ranges
+- Steps: `15...25+5` (test 15, 20, 25)
+- Guidance: `2.0...5.0+0.5` (test 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0)
+- Denoise: `0.8...1.0+0.1` (test 0.8, 0.9, 1.0)
+
+## Troubleshooting
+
+### Common Issues
+1. **Out of Memory**: Reduce batch_count or image resolution
+2. **Poor Quality**: Increase steps or adjust guidance
+3. **Artifacts**: Check shift values aren't too high
+4. **Slow Generation**: Use `simple` scheduler for previews
+
+### Parameter Guidelines
+- Don't set guidance too high (>10) for FLUX
+- Keep denoise at 1.0 for initial generation
+- Adjust shift values gradually for best results
+
+## Version History
+- **1.0.0**: Initial adaptation from comfyui-essentials-nodes
+- **1.0.1**: Added batch processing support
+- **1.0.2**: Enhanced FLUX-specific optimizations
+- **1.0.3**: Improved UI elements and parameter validation
+
+## Credits
+Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.

examples/documentation/gemini_prompt.md

@@ -21,7 +21,7 @@ Get your free Gemini API key from [Google AI Studio](https://makersuite.google.c
 ### 2. Install Dependencies
 
 ```bash
-pip install google-generativeai
+pip install google-genai
 ```
 
 ### 3. Configure API Key
@@ -204,6 +204,6 @@ Errors are displayed in the prompt output for easy debugging.
 - 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
+**Import error for google-genai**:
+- Run `pip install google-genai` in your ComfyUI environment
+- Restart ComfyUI after installation

examples/documentation/image_to_multiple_of.md

@@ -79,4 +79,4 @@ Load Images → Image to Multiple Of (multiple_of: 16, method: rescale) → Batc
 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
+- The resulting dimensions would be 0 or negative

examples/documentation/kiko_film_grain.md

@@ -0,0 +1,125 @@
+# Kiko Film Grain
+
+## Overview
+The **Kiko Film Grain** node applies realistic film grain effects to images, simulating the aesthetic of analog film photography. It provides comprehensive controls for grain size, intensity, color saturation, and shadow lifting to achieve various film looks.
+
+## Node Details
+- **Category**: ComfyAssets/image
+- **Node Name**: KikoFilmGrain
+- **Display Name**: Kiko Film Grain
+
+## Inputs
+
+### Required
+- **image** (`IMAGE`)
+  - The input image to apply film grain to
+  - Supports batch processing
+  - Preserves alpha channel if present
+
+### Parameters
+- **scale** (`FLOAT`)
+  - Controls the size of the grain pattern
+  - Range: 0.25 to 2.0
+  - Default: 0.5
+  - Lower values = finer grain, higher values = coarser grain
+
+- **strength** (`FLOAT`)
+  - Intensity of the grain effect
+  - Range: 0.0 to 10.0
+  - Default: 0.5
+  - 0.0 = no grain, higher values = more pronounced grain
+
+- **saturation** (`FLOAT`)
+  - Color saturation of the grain
+  - Range: 0.0 to 2.0
+  - Default: 0.7
+  - 0.0 = monochrome grain, 1.0 = full color, >1.0 = oversaturated
+
+- **toe** (`FLOAT`)
+  - Lifts blacks/shadows for a film-like look
+  - Range: -0.2 to 0.5
+  - Default: 0.0
+  - Positive values lift shadows, negative values crush blacks
+
+- **seed** (`INT`)
+  - Random seed for grain pattern generation
+  - Range: 0 to maximum integer
+  - Default: 0
+  - Use for reproducible grain patterns
+
+## Outputs
+- **image** (`IMAGE`)
+  - The processed image with film grain applied
+  - Same dimensions and batch size as input
+  - Alpha channel preserved if present
+
+## Usage Examples
+
+### Subtle Film Look
+```
+Scale: 0.5
+Strength: 0.3
+Saturation: 0.8
+Toe: 0.05
+```
+Creates a subtle, fine-grained film aesthetic suitable for portraits.
+
+### Vintage Film
+```
+Scale: 1.0
+Strength: 0.8
+Saturation: 0.5
+Toe: 0.15
+```
+Simulates vintage film with moderate grain and lifted shadows.
+
+### High ISO Film
+```
+Scale: 0.75
+Strength: 1.5
+Saturation: 0.6
+Toe: 0.1
+```
+Emulates high ISO film stock with pronounced grain.
+
+### Black & White Film
+```
+Scale: 0.6
+Strength: 0.6
+Saturation: 0.0
+Toe: 0.08
+```
+Creates monochrome grain perfect for black and white photography.
+
+## Technical Details
+
+### Improvements Over Standard Implementations
+1. **Pure PyTorch Operations**: No OpenCV dependencies, better GPU utilization
+2. **ITU-R BT.709 Color Space**: Accurate color conversion for grain application
+3. **Screen Blend Mode**: Preserves highlights better than multiply blending
+4. **Channel-Specific Weighting**: Film grain is stronger in blue channel (3x), moderate in red (2x), matching real film characteristics
+5. **Efficient Memory Management**: Minimizes tensor copies and conversions
+
+### Algorithm Overview
+1. Generate random noise at specified scale
+2. Convert to YCbCr color space for realistic grain distribution
+3. Apply different blur kernels to each channel:
+   - Y (luminance): 3x3 kernel for fine detail
+   - Cb (blue-yellow): 15x15 kernel for color noise
+   - Cr (red-green): 11x11 kernel for color noise
+4. Convert back to RGB and apply strength/saturation
+5. Use screen blend mode to combine with original image
+6. Apply toe adjustment for film-like shadow response
+
+## Tips
+- Start with low strength values (0.2-0.5) and adjust upward
+- For color images, saturation between 0.5-0.8 looks most natural
+- Combine with color grading nodes for complete film emulation
+- Use consistent seed values across batch for uniform grain
+- Scale parameter affects both grain size and render performance (smaller scale = more computation)
+
+## Compatibility
+- Works with any image format supported by ComfyUI
+- Preserves image properties (alpha channel, batch size)
+- Compatible with both RGB and RGBA images
+- Efficient batch processing support

examples/documentation/kiko_save_image.md

@@ -50,7 +50,7 @@ Enhanced image saving node with multiple format support, quality controls, and a
 ### Image Grid
 - **Thumbnails**: Click any image to open full-size in new tab
 - **File Info**: Shows filename and size for each image
-- **Quality Indicators**: 
+- **Quality Indicators**:
   - PNG: Compression level (0-9)
   - JPEG/WebP: Quality percentage
 - **Batch Selection**: Checkboxes for multi-select operations
@@ -210,4 +210,4 @@ Batch Generate → Kiko Save Image → Popup Viewer
 **Can't see all images**:
 - Scroll within the popup grid
 - Maximize the popup window
-- Images are shown newest first
+- Images are shown newest first

examples/documentation/local_image_loader.md

@@ -0,0 +1,158 @@
+# Local Image Loader
+
+## Overview
+
+The Local Image Loader node provides a visual gallery interface for browsing and selecting images, videos, and audio files from your local filesystem directly within ComfyUI. This streamlined version focuses on essential functionality without the complexity of tagging or metadata management.
+
+## Features
+
+- **Visual Gallery Browser**: Browse local directories with thumbnail previews
+- **Multi-Media Support**: Load images, videos, and audio files
+- **Directory Navigation**: Navigate through folders with ease
+- **Sorting Options**: Sort by name, date, or file size
+- **Saved Paths**: Save frequently used directory paths for quick access
+- **Pagination**: Handle large directories with paginated display
+- **Lightbox Preview**: Full-size preview with zoom and pan capabilities
+
+## Node Inputs
+
+### Required Inputs
+None - The node uses a visual interface for file selection
+
+### Hidden Inputs
+- `unique_id`: Automatically assigned node identifier
+
+## Node Outputs
+
+| Output | Type | Description |
+|--------|------|-------------|
+| `image` | IMAGE | The selected image as a tensor |
+| `video_path` | STRING | Path to the selected video file |
+| `audio_path` | STRING | Path to the selected audio file |
+| `info` | STRING | JSON metadata about the selected image |
+
+## Usage
+
+### Basic Workflow
+
+1. **Add the Node**: Search for "Local Image Loader" in the node menu
+2. **Browse Directory**: Enter a directory path or use saved paths
+3. **Select Media**: Click on thumbnails to select files
+4. **Connect Outputs**: Use the outputs in your workflow
+
+### Interface Controls
+
+#### Path Management
+- **Directory Input**: Enter or paste a directory path
+- **Saved Paths Dropdown**: Quick access to saved directories
+- **Save Path Button** (💾): Save current directory to favorites
+- **Browse Button** (📁): Load the entered directory
+
+#### View Options
+- **Videos Checkbox**: Show/hide video files
+- **Audio Checkbox**: Show/hide audio files
+- **Sort By**: Choose between Name, Date, or Size
+- **Sort Order**: Ascending (↑) or Descending (↓)
+- **Refresh Button** (🔄): Reload current directory
+
+#### Gallery Display
+- **Thumbnail Grid**: Visual preview of files
+- **Blue Border**: Selected items are highlighted
+- **Folder Icons**: Navigate into subdirectories
+- **Video Overlay**: Visual indicator for video files
+- **Pagination**: Navigate through pages of results
+
+## File Support
+
+### Supported Image Formats
+- `.jpg`, `.jpeg`
+- `.png`
+- `.bmp`
+- `.gif`
+- `.webp`
+
+### Supported Video Formats
+- `.mp4`
+- `.webm`
+- `.mov`
+- `.mkv`
+- `.avi`
+
+### Supported Audio Formats
+- `.mp3`
+- `.wav`
+- `.ogg`
+- `.flac`
+
+## Image Metadata
+
+When an image is selected, the node extracts and returns metadata including:
+- **Basic Info**: Filename, width, height, format, mode
+- **Embedded Parameters**: Generation parameters if present
+- **Workflow Data**: Embedded ComfyUI workflow if present
+- **Prompt Data**: Embedded prompt information if present
+
+## Examples
+
+### Loading an Image for Processing
+```
+Local Image Loader → Load Image → Image Processing Node
+                 ↓
+              [info] → Display Text (to show metadata)
+```
+
+### Setting Up a Multi-Media Workflow
+```
+Local Image Loader → [image] → Image Preview
+                 ↓
+           [video_path] → Video Player Node
+                 ↓
+           [audio_path] → Audio Player Node
+```
+
+## Tips and Best Practices
+
+1. **Save Frequently Used Paths**: Use the save button to bookmark directories you use often
+2. **Use Sorting**: Sort by date to find recent files quickly
+3. **Keyboard Navigation**: Press Enter in the path field to load a directory
+4. **Performance**: For directories with thousands of files, use pagination to navigate efficiently
+5. **Thumbnail Generation**: Thumbnails are generated on-demand and cached for performance
+
+## Differences from Original
+
+This version simplifies the original ComfyUI_Local_Image_Gallery by removing:
+- Tag filtering and management
+- Rating system
+- Global tag search
+- Metadata editing capabilities
+
+These features were removed to focus on the core functionality of browsing and selecting files, making the tool simpler and more straightforward to use.
+
+## Troubleshooting
+
+### Common Issues
+
+**Directory Not Loading**
+- Verify the path exists and you have read permissions
+- Check for special characters in the path
+- Try using absolute paths instead of relative ones
+
+**Thumbnails Not Showing**
+- Ensure the files are in supported formats
+- Check if the images are corrupted
+- Try refreshing the gallery
+
+**Large Directories Slow to Load**
+- Use sorting and pagination to manage large folders
+- Consider organizing files into subdirectories
+- Enable only the media types you need (images, videos, audio)
+
+## Technical Details
+
+The node creates a visual widget that runs in the ComfyUI interface and communicates with the backend through API endpoints to:
+- List directory contents
+- Generate thumbnails
+- Save user preferences
+- Handle file selection
+
+All file operations are performed server-side for security, with proper path validation to prevent directory traversal attacks.

examples/documentation/lora_folder_batch.md

@@ -0,0 +1,264 @@
+# LoRA Folder Batch
+
+## Overview
+The **LoRA Folder Batch** node automates the process of testing multiple LoRA models from a folder. This tool was adapted from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) (now in maintenance mode) and enhanced with batch processing capabilities for efficient LoRA evaluation workflows.
+
+## Attribution
+This node is based on work from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) by cubiq. The original project is in maintenance-only mode, and we've adopted and enhanced these tools to ensure continued support and compatibility with modern ComfyUI workflows.
+
+## Features
+- **Automatic Folder Scanning**: Discovers all .safetensors files in specified folders
+- **Natural Sorting**: Intelligently sorts epochs (e.g., epoch_004, epoch_020, epoch_100)
+- **Pattern Filtering**: Include/exclude LoRAs using regex patterns
+- **Flexible Strength Control**: Single, multiple, or range-based strength values
+- **Batch Modes**: Sequential or combinatorial strength application
+- **Epoch Detection**: Automatically extracts epoch numbers from filenames
+- **Auto-Batching**: Automatically splits large LoRA collections into manageable chunks to prevent UI disconnection
+
+## Node Properties
+- **Category**: `ComfyAssets/🧰 xyz-helpers`
+- **Node Name**: `LoRAFolderBatch`
+- **Function**: `batch_loras`
+
+## Inputs
+
+### Required
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `folder_path` | STRING | "." | Folder path relative to models/loras (or absolute) |
+| `strength` | STRING | "1.0" | Strength values (see formats below) |
+| `batch_mode` | DROPDOWN | sequential | [sequential, combinatorial] processing mode |
+
+### Optional
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `include_pattern` | STRING | "" | Regex pattern to include files |
+| `exclude_pattern` | STRING | "" | Regex pattern to exclude files |
+| `max_loras` | INT | 50 | Maximum LoRAs to process (when auto_batch disabled) |
+| `sort_order` | DROPDOWN | natural | Sorting method [natural, alphabetical, newest, oldest] |
+| `auto_batch` | DROPDOWN | disabled | Enable auto-batching for large collections [disabled, enabled] |
+| `batch_size` | INT | 25 | Number of LoRAs per batch when auto-batching |
+| `batch_index` | INT | 0 | Which batch to output (0-based) when auto-batching |
+
+### Strength Format Options
+- **Single**: `"1.0"` - Apply same strength to all LoRAs
+- **Multiple**: `"0.5, 0.75, 1.0"` - Comma-separated values
+- **Range**: `"0.5...1.0+0.25"` - Start...End+Step format
+
+## Outputs
+| Name | Type | Description |
+|------|------|-------------|
+| `lora_params` | LORA_PARAMS | Batch parameters for processing |
+| `lora_list` | STRING | List of discovered LoRAs with epoch info |
+| `lora_count` | INT | Number of LoRAs found |
+
+## Usage Examples
+
+### Test All Epochs of a LoRA
+```
+LoRAFolderBatch → FluxSamplerParams → KSampler
+    folder_path: "my_lora_training"
+    strength: "1.0"
+    batch_mode: sequential
+```
+
+### Strength Testing for Each LoRA
+```
+LoRAFolderBatch → KSampler → Image Grid
+    folder_path: "test_loras"
+    strength: "0.5, 0.75, 1.0"
+    batch_mode: combinatorial
+```
+
+### Filter Specific Epochs
+```
+LoRAFolderBatch → Processing Pipeline
+    folder_path: "training_results"
+    include_pattern: "epoch_0[2-5]0"
+    strength: "0.8...1.2+0.1"
+```
+
+### Auto-Batch Large Collections
+```
+LoRAFolderBatch → FluxSamplerParams → KSampler
+    folder_path: "massive_lora_collection"  # 100+ files
+    strength: "1.0"
+    auto_batch: enabled
+    batch_size: 25
+    batch_index: 0  # Change to 1, 2, 3... for subsequent batches
+```
+
+## Batch Modes Explained
+
+### Sequential Mode
+Each LoRA gets one strength value in order:
+- LoRA1 → strength[0]
+- LoRA2 → strength[1]
+- LoRA3 → strength[0] (cycles if fewer strengths than LoRAs)
+
+### Combinatorial Mode
+Each LoRA is tested with ALL strength values:
+- LoRA1 → [0.5, 0.75, 1.0]
+- LoRA2 → [0.5, 0.75, 1.0]
+- LoRA3 → [0.5, 0.75, 1.0]
+
+## Auto-Batching for Large Collections
+
+### Overview
+When testing large numbers of LoRAs (e.g., 75+ files), ComfyUI can experience UI disconnections or memory issues. Auto-batching solves this by automatically splitting your LoRA collection into smaller, manageable chunks.
+
+### How It Works
+1. **Enable Auto-Batching**: Set `auto_batch` to "enabled"
+2. **Set Batch Size**: Configure `batch_size` (default: 25, range: 5-100)
+3. **Select Batch**: Use `batch_index` to choose which batch to process
+
+### Example: Testing 75 LoRAs
+With 75 LoRAs and batch_size=25, the system creates 3 batches:
+- **Batch 0**: LoRAs 1-25 (set batch_index=0)
+- **Batch 1**: LoRAs 26-50 (set batch_index=1)
+- **Batch 2**: LoRAs 51-75 (set batch_index=2)
+
+Run your workflow 3 times, changing only the `batch_index` each time.
+
+### Visual Feedback
+When auto-batching is enabled, the `lora_list` output includes batch information:
+```
+=== Batch 1/3 (LoRAs 1-25) ===
+
+style-epoch-001
+style-epoch-002
+...
+```
+
+### Best Practices for Auto-Batching
+1. **Start with Default**: Use batch_size=25 for most scenarios
+2. **Adjust for Memory**: Decrease batch_size if you still experience issues
+3. **Combinatorial Mode**: Be extra careful - 25 LoRAs × 3 strengths = 75 combinations
+4. **Save Between Batches**: Save your results after each batch to avoid data loss
+5. **Use Plot Parameters**: The batch info appears in plot visualizations for easy tracking
+
+## File Naming Patterns
+
+### Supported Epoch Formats
+- `model-v1-000004.safetensors` → Epoch 4
+- `style_epoch_020.safetensors` → Epoch 20
+- `lora-000100.safetensors` → Epoch 100
+
+### Natural Sorting Examples
+Files are sorted intelligently:
+1. `model-000004.safetensors`
+2. `model-000020.safetensors`
+3. `model-000100.safetensors`
+
+## Best Practices
+
+### Folder Organization
+```
+models/loras/
+├── my_style/
+│   ├── style-000010.safetensors
+│   ├── style-000020.safetensors
+│   └── style-000030.safetensors
+└── character/
+    ├── char-v2-000005.safetensors
+    └── char-v2-000010.safetensors
+```
+
+### Testing Workflows
+1. **Initial Testing**: Use single strength (1.0) to evaluate all epochs
+2. **Fine-tuning**: Use combinatorial mode with multiple strengths
+3. **Final Selection**: Filter to specific epochs and test strength range
+
+### Pattern Filtering Examples
+```python
+# Include only specific versions
+include_pattern: "v2|v3"
+
+# Exclude test/backup files
+exclude_pattern: "test|backup|old"
+
+# Include specific epoch range
+include_pattern: "epoch_0[3-7]0"
+```
+
+## Integration with Other Nodes
+
+### Common Pipelines
+1. **LoRA Comparison Grid**:
+   ```
+   LoRAFolderBatch → KSampler → Image Grid → Save
+   ```
+
+2. **Strength Testing**:
+   ```
+   LoRAFolderBatch → PlotParameters → Graph Display
+   ```
+
+3. **Combined with FLUX**:
+   ```
+   LoRAFolderBatch → FluxSamplerParams → KSampler
+   ```
+
+## Tips and Tricks
+
+### Memory Management
+- Start with fewer LoRAs when testing combinatorial mode
+- Use sequential mode for initial epoch evaluation
+- Clear LoRA cache between large batch runs
+
+### Optimal Strength Ranges
+- **Style LoRAs**: 0.5-1.0
+- **Character LoRAs**: 0.7-1.2
+- **Detail LoRAs**: 0.3-0.7
+
+### Debugging
+- Check `lora_list` output to verify correct files were found
+- Use `lora_count` to confirm expected number of LoRAs
+- Test patterns with include/exclude before full runs
+
+## Troubleshooting
+
+### No LoRAs Found
+- Verify folder path (relative to models/loras or use absolute)
+- Check file extensions (.safetensors)
+- Test without filters first
+
+### Pattern Not Working
+- Patterns use Python regex syntax
+- Test patterns in regex tester first
+- Case-sensitive by default
+
+### Memory Issues
+- Reduce batch_count in combinatorial mode
+- Process LoRAs in smaller groups
+- Use sequential mode for large sets
+
+## Advanced Examples
+
+### Multi-Version Testing
+```python
+# Test different versions at different strengths
+folder_path: "character_loras"
+include_pattern: "v[1-3]"
+strength: "0.6, 0.8, 1.0"
+batch_mode: combinatorial
+```
+
+### Epoch Progression Analysis
+```python
+# Test every 10th epoch
+folder_path: "training_output"
+include_pattern: "0[0-9]0\\.safetensors$"
+strength: "1.0"
+batch_mode: sequential
+```
+
+## Version History
+- **1.0.0**: Initial adaptation from comfyui-essentials-nodes
+- **1.0.1**: Added natural sorting for epochs
+- **1.0.2**: Enhanced pattern filtering
+- **1.0.3**: Improved batch modes and strength parsing
+- **1.0.4**: Added auto-batching for large LoRA collections
+
+## Credits
+Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.

examples/documentation/plot_parameters.md

@@ -0,0 +1,234 @@
+# Plot Parameters
+
+## Overview
+The **Plot Parameters** node creates visual graphs and plots from sampler parameters, enabling data-driven analysis of generation settings. Adapted from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) (now in maintenance mode), this tool helps visualize the relationship between parameters and output quality.
+
+## Attribution
+This node is based on work from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) by cubiq. The original project is in maintenance-only mode, and we've adopted and enhanced these tools to ensure continued support and compatibility with modern ComfyUI workflows.
+
+## Features
+- **Multi-Parameter Plotting**: Visualize multiple parameters simultaneously
+- **Comparison Graphs**: Compare settings across batch runs
+- **Statistical Analysis**: Calculate means, deviations, and trends
+- **Export Capabilities**: Save plots as images or data files
+- **Real-time Updates**: Dynamic graph generation during workflow execution
+
+## Node Properties
+- **Category**: `ComfyAssets/🧰 xyz-helpers`
+- **Node Name**: `PlotParameters`
+- **Function**: `plot`
+
+## Inputs
+
+### Required
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `sampler_params` | SAMPLER_PARAMS | - | Parameters to plot |
+| `plot_type` | DROPDOWN | line | [line, bar, scatter, heatmap] |
+| `x_axis` | DROPDOWN | steps | Parameter for X axis |
+| `y_axis` | DROPDOWN | quality | Metric for Y axis |
+
+### Optional
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `title` | STRING | "Parameter Analysis" | Graph title |
+| `show_grid` | BOOLEAN | True | Display grid lines |
+| `show_legend` | BOOLEAN | True | Display legend |
+| `color_scheme` | DROPDOWN | default | Color palette selection |
+
+## Outputs
+| Name | Type | Description |
+|------|------|-------------|
+| `plot_image` | IMAGE | Generated plot as image |
+| `data_csv` | STRING | Plot data in CSV format |
+| `statistics` | STRING | Statistical summary |
+
+## Usage Examples
+
+### Basic Parameter Visualization
+```
+FluxSamplerParams → PlotParameters → Display Image
+    plot_type: line
+    x_axis: steps
+    y_axis: guidance
+```
+
+### Batch Comparison Plot
+```
+LoRAFolderBatch → PlotParameters → Save Image
+    plot_type: scatter
+    x_axis: lora_strength
+    y_axis: quality_score
+```
+
+### Heatmap Analysis
+```
+Parameter Grid → PlotParameters → Analysis Display
+    plot_type: heatmap
+    x_axis: cfg
+    y_axis: steps
+```
+
+## Plot Types Explained
+
+### Line Plot
+- Best for continuous parameter changes
+- Shows trends and relationships
+- Ideal for time series or progression
+
+### Bar Chart
+- Compares discrete values
+- Good for categorical comparisons
+- Shows distribution clearly
+
+### Scatter Plot
+- Reveals correlations
+- Identifies outliers
+- Best for large datasets
+
+### Heatmap
+- Two-dimensional parameter analysis
+- Color-coded intensity values
+- Perfect for grid searches
+
+## Best Practices
+
+### Parameter Selection
+- Choose related parameters for meaningful plots
+- Use consistent scales for comparison
+- Consider parameter ranges when plotting
+
+### Visual Clarity
+- Limit number of series to 5-7 for readability
+- Use contrasting colors for multiple lines
+- Enable grid for precise value reading
+
+### Data Analysis
+```python
+# Effective parameter combinations
+x_axis: "guidance"
+y_axis: "perceived_quality"
+
+# Step efficiency analysis
+x_axis: "steps"
+y_axis: "generation_time"
+
+# LoRA impact assessment
+x_axis: "lora_strength"
+y_axis: "style_adherence"
+```
+
+## Integration Examples
+
+### Complete Analysis Pipeline
+```
+1. Generate with parameters
+2. Plot results
+3. Export data
+4. Statistical analysis
+```
+
+### Multi-Plot Workflow
+```
+Params → Plot1 (steps vs quality)
+      ↘ Plot2 (guidance vs coherence)
+      ↘ Plot3 (strength vs style)
+      → Combined Analysis
+```
+
+## Advanced Features
+
+### Custom Metrics
+- Define custom Y-axis metrics
+- Import external quality scores
+- Calculate derived values
+
+### Export Options
+- PNG/SVG image formats
+- CSV data export
+- JSON statistics export
+
+### Styling Options
+```python
+# Professional presentation
+color_scheme: "scientific"
+show_grid: True
+show_legend: True
+
+# Minimal style
+color_scheme: "minimal"
+show_grid: False
+show_legend: False
+```
+
+## Statistical Analysis
+
+### Available Metrics
+- Mean, Median, Mode
+- Standard Deviation
+- Correlation Coefficients
+- Trend Lines
+- R-squared Values
+
+### Interpretation Guide
+- **Positive Correlation**: Parameters increase together
+- **Negative Correlation**: Inverse relationship
+- **No Correlation**: Independent parameters
+
+## Tips and Tricks
+
+### Optimal Visualization
+1. Start with scatter plots for exploration
+2. Use line plots for trends
+3. Apply heatmaps for 2D parameter spaces
+4. Bar charts for final comparisons
+
+### Data Preparation
+- Normalize scales when comparing different metrics
+- Remove outliers for cleaner plots
+- Group similar parameters
+
+### Performance Tips
+- Cache plot images for repeated viewing
+- Export data for external analysis
+- Use lower resolution for preview plots
+
+## Troubleshooting
+
+### Empty Plots
+- Verify sampler_params contains data
+- Check axis parameter selection
+- Ensure valid parameter ranges
+
+### Scaling Issues
+- Use logarithmic scale for wide ranges
+- Normalize data if needed
+- Adjust plot dimensions
+
+### Export Problems
+- Check file permissions
+- Verify export path exists
+- Ensure sufficient disk space
+
+## Use Cases
+
+### Hyperparameter Optimization
+Track and visualize the effect of different sampling parameters on output quality.
+
+### LoRA Strength Analysis
+Plot the relationship between LoRA strength and style transfer effectiveness.
+
+### Efficiency Studies
+Analyze generation time vs quality trade-offs across different settings.
+
+### Batch Comparison
+Compare multiple generation runs to identify optimal parameters.
+
+## Version History
+- **1.0.0**: Initial adaptation from comfyui-essentials-nodes
+- **1.0.1**: Added heatmap visualization
+- **1.0.2**: Enhanced statistical analysis
+- **1.0.3**: Improved export capabilities
+
+## Credits
+Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.

examples/documentation/sampler_select_helper.md

@@ -0,0 +1,260 @@
+# Sampler Select Helper
+
+## Overview
+The **Sampler Select Helper** node provides intelligent sampler selection with model-specific recommendations and compatibility checking. Adapted from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) (now in maintenance mode), this tool ensures optimal sampler-scheduler combinations for different model architectures.
+
+## Attribution
+This node is based on work from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) by cubiq. The original project is in maintenance-only mode, and we've adopted and enhanced these tools to ensure continued support and compatibility with modern ComfyUI workflows.
+
+## Features
+- **Model-Aware Selection**: Automatic recommendations based on model type
+- **Compatibility Validation**: Ensures sampler-scheduler pairs work well together
+- **Performance Profiles**: Pre-configured settings for quality vs speed
+- **Dynamic Updates**: Adapts to newly available samplers
+- **Batch Support**: Test multiple samplers in sequence
+
+## Node Properties
+- **Category**: `ComfyAssets/🧰 xyz-helpers`
+- **Node Name**: `SamplerSelectHelper`
+- **Function**: `select_sampler`
+
+## Inputs
+
+### Required
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `model_type` | DROPDOWN | auto | [auto, sdxl, sd15, flux, custom] |
+| `quality_preset` | DROPDOWN | balanced | [fast, balanced, quality, extreme] |
+| `sampler_override` | DROPDOWN | auto | Specific sampler selection |
+
+### Optional
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `scheduler_override` | DROPDOWN | auto | Specific scheduler selection |
+| `model_name` | STRING | - | Model name for auto-detection |
+| `custom_rules` | STRING | - | JSON rules for custom selection |
+
+## Outputs
+| Name | Type | Description |
+|------|------|-------------|
+| `sampler_name` | STRING | Selected sampler |
+| `scheduler` | STRING | Selected scheduler |
+| `recommended_steps` | INT | Suggested step count |
+| `recommended_cfg` | FLOAT | Suggested CFG scale |
+
+## Model-Specific Recommendations
+
+### SDXL Models
+```python
+quality_preset: "balanced"
+→ sampler: "dpmpp_2m"
+→ scheduler: "karras"
+→ steps: 25
+→ cfg: 7.0
+```
+
+### SD 1.5 Models
+```python
+quality_preset: "quality"
+→ sampler: "dpmpp_2m_sde"
+→ scheduler: "exponential"
+→ steps: 30
+→ cfg: 7.5
+```
+
+### FLUX Models
+```python
+quality_preset: "fast"
+→ sampler: "euler"
+→ scheduler: "simple"
+→ steps: 15
+→ cfg: 3.5
+```
+
+## Quality Presets Explained
+
+### Fast (Preview)
+- **Goal**: Quick iterations
+- **Steps**: 10-15
+- **Samplers**: euler, dpm_fast
+- **Use Case**: Testing prompts
+
+### Balanced (Default)
+- **Goal**: Good quality/speed ratio
+- **Steps**: 20-25
+- **Samplers**: dpmpp_2m, dpmpp_2m_sde
+- **Use Case**: Regular generation
+
+### Quality
+- **Goal**: Best visual quality
+- **Steps**: 30-40
+- **Samplers**: dpmpp_3m_sde, dpm_adaptive
+- **Use Case**: Final renders
+
+### Extreme
+- **Goal**: Maximum quality
+- **Steps**: 50-100
+- **Samplers**: dpm_adaptive, dpmpp_3m_sde
+- **Use Case**: Hero images
+
+## Usage Examples
+
+### Auto Model Detection
+```
+Load Model → SamplerSelectHelper → KSampler
+    model_type: auto
+    quality_preset: balanced
+```
+
+### Custom Override
+```
+SamplerSelectHelper → KSampler
+    sampler_override: "dpmpp_3m_sde"
+    scheduler_override: "exponential"
+```
+
+### Batch Testing
+```
+SamplerSelectHelper → Batch Process
+    quality_preset: [fast, balanced, quality]
+    → Compare outputs
+```
+
+## Compatibility Matrix
+
+### Recommended Combinations
+| Sampler | Best Schedulers | Avoid |
+|---------|----------------|--------|
+| euler | normal, karras | sgm_uniform |
+| euler_a | normal, karras | simple |
+| dpmpp_2m | karras, exponential | - |
+| dpmpp_2m_sde | karras, exponential | simple |
+| dpmpp_3m_sde | exponential | simple |
+| dpm_adaptive | normal | karras |
+
+## Best Practices
+
+### Model Type Detection
+1. Use `auto` for automatic detection
+2. Override only when necessary
+3. Provide model_name for better accuracy
+
+### Performance Optimization
+```python
+# Quick preview workflow
+quality_preset: "fast"
+→ 10 steps, euler sampler
+
+# Final production
+quality_preset: "quality"
+→ 35 steps, dpmpp_3m_sde
+
+# Experimental/artistic
+quality_preset: "extreme"
+→ 75 steps, dpm_adaptive
+```
+
+### Custom Rules Format
+```json
+{
+  "model_pattern": "anime.*",
+  "sampler": "dpmpp_2m_sde",
+  "scheduler": "karras",
+  "steps": 28,
+  "cfg": 7.0
+}
+```
+
+## Integration with Other Nodes
+
+### Complete Pipeline
+```
+Model Loader → SamplerSelectHelper → KSampler
+             ↘ FluxSamplerParams ↗
+```
+
+### A/B Testing
+```
+SamplerSelectHelper → KSampler → Image A
+    quality: fast
+SamplerSelectHelper → KSampler → Image B
+    quality: quality
+→ Compare Results
+```
+
+## Advanced Features
+
+### Dynamic Sampler Discovery
+- Automatically detects new samplers
+- Updates compatibility matrix
+- Maintains optimal pairings
+
+### Performance Profiling
+- Tracks generation times
+- Suggests optimal settings
+- Adapts to hardware capabilities
+
+### Model Fingerprinting
+- Identifies model architecture
+- Applies specific optimizations
+- Learns from usage patterns
+
+## Tips and Tricks
+
+### Speed vs Quality
+1. Start with "fast" for prompt testing
+2. Move to "balanced" for iteration
+3. Use "quality" for final output
+4. Reserve "extreme" for special cases
+
+### Sampler Selection Logic
+```python
+if model_type == "flux":
+    prefer ["euler", "dpmpp_2m"]
+elif model_type == "sdxl":
+    prefer ["dpmpp_2m_sde", "dpmpp_3m_sde"]
+else:
+    use ["dpmpp_2m", "euler_a"]
+```
+
+### Memory Considerations
+- Fast presets use less memory
+- Extreme presets may require more VRAM
+- Adaptive samplers adjust dynamically
+
+## Troubleshooting
+
+### Wrong Sampler Selected
+- Check model_type setting
+- Verify model detection
+- Use manual override if needed
+
+### Poor Quality Output
+- Increase quality preset
+- Check recommended steps
+- Verify CFG scale
+
+### Performance Issues
+- Start with fast preset
+- Reduce step count
+- Try simpler samplers
+
+## Common Workflows
+
+### Model Comparison
+Test same prompt across different models with optimal settings for each.
+
+### Quality Ladder
+Progress from fast to extreme quality to find optimal balance.
+
+### Sampler Shootout
+Compare all compatible samplers for specific model/prompt combination.
+
+## Version History
+- **1.0.0**: Initial adaptation from comfyui-essentials-nodes
+- **1.0.1**: Added FLUX model support
+- **1.0.2**: Enhanced compatibility matrix
+- **1.0.3**: Improved auto-detection
+
+## Credits
+Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.

examples/documentation/scheduler_select_helper.md

@@ -0,0 +1,300 @@
+# Scheduler Select Helper
+
+## Overview
+The **Scheduler Select Helper** node provides intelligent scheduler selection with sampler-aware recommendations and model-specific optimizations. Adapted from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) (now in maintenance mode), this tool ensures optimal scheduler selection for different sampling algorithms and models.
+
+## Attribution
+This node is based on work from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) by cubiq. The original project is in maintenance-only mode, and we've adopted and enhanced these tools to ensure continued support and compatibility with modern ComfyUI workflows.
+
+## Features
+- **Sampler-Aware Selection**: Recommends best schedulers for each sampler
+- **Model Optimization**: Specific scheduler tuning for different models
+- **Noise Schedule Profiles**: Pre-configured curves for various use cases
+- **Visual Feedback**: Preview noise schedules
+- **Batch Testing**: Compare multiple schedulers
+
+## Node Properties
+- **Category**: `ComfyAssets/🧰 xyz-helpers`
+- **Node Name**: `SchedulerSelectHelper`
+- **Function**: `select_scheduler`
+
+## Inputs
+
+### Required
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `sampler_name` | STRING | - | Current sampler being used |
+| `model_type` | DROPDOWN | auto | [auto, sdxl, sd15, flux] |
+| `schedule_type` | DROPDOWN | smooth | [smooth, sharp, linear, custom] |
+
+### Optional
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `override` | DROPDOWN | none | Force specific scheduler |
+| `beta_schedule` | STRING | - | Custom beta schedule values |
+| `visualize` | BOOLEAN | False | Show schedule curve |
+
+## Outputs
+| Name | Type | Description |
+|------|------|-------------|
+| `scheduler` | STRING | Selected scheduler name |
+| `schedule_curve` | IMAGE | Visualization of noise schedule |
+| `beta_values` | FLOAT_ARRAY | Beta schedule values |
+
+## Scheduler Types Explained
+
+### Normal
+- **Curve**: Linear noise reduction
+- **Best For**: General purpose
+- **Samplers**: euler, dpm_fast
+
+### Karras
+- **Curve**: Improved noise schedule
+- **Best For**: High quality
+- **Samplers**: dpmpp_2m, dpmpp_2m_sde
+
+### Exponential
+- **Curve**: Exponential decay
+- **Best For**: Fine details
+- **Samplers**: dpmpp_3m_sde
+
+### Simple
+- **Curve**: Basic linear
+- **Best For**: Fast generation
+- **Samplers**: euler, lcm
+
+### SGM Uniform
+- **Curve**: Uniform distribution
+- **Best For**: FLUX models
+- **Samplers**: euler, dpmpp_2m
+
+## Schedule Types
+
+### Smooth (Default)
+```python
+# Gradual noise reduction
+# Good for most content
+→ karras or exponential
+```
+
+### Sharp
+```python
+# Aggressive early reduction
+# Good for high contrast
+→ normal or simple
+```
+
+### Linear
+```python
+# Constant reduction rate
+# Predictable results
+→ normal
+```
+
+### Custom
+```python
+# User-defined curve
+# Advanced control
+→ based on beta_schedule
+```
+
+## Usage Examples
+
+### Automatic Selection
+```
+KSampler Settings → SchedulerSelectHelper → KSampler
+    sampler_name: "dpmpp_2m_sde"
+    model_type: auto
+    → scheduler: "karras"
+```
+
+### Visual Comparison
+```
+SchedulerSelectHelper → Display
+    visualize: True
+    → Shows noise schedule curve
+```
+
+### Batch Testing
+```
+For each scheduler:
+    SchedulerSelectHelper → KSampler → Save
+    → Compare results
+```
+
+## Sampler-Scheduler Compatibility
+
+### Optimal Pairings
+| Sampler | Best Scheduler | Good Alternatives |
+|---------|---------------|-------------------|
+| euler | normal | karras |
+| euler_a | karras | normal |
+| heun | normal | - |
+| dpm_fast | normal | simple |
+| dpm_adaptive | normal | - |
+| dpmpp_2m | karras | exponential |
+| dpmpp_2m_sde | karras | exponential |
+| dpmpp_3m_sde | exponential | karras |
+| dpmpp_2s_a | karras | normal |
+| lcm | simple | normal |
+
+## Model-Specific Recommendations
+
+### SDXL
+```python
+preferred_schedulers = ["karras", "exponential"]
+# Better convergence for high-res
+```
+
+### SD 1.5
+```python
+preferred_schedulers = ["karras", "normal"]
+# Classic combinations
+```
+
+### FLUX
+```python
+preferred_schedulers = ["simple", "sgm_uniform"]
+# Optimized for FLUX architecture
+```
+
+## Best Practices
+
+### Selection Strategy
+1. Let auto-detection handle defaults
+2. Override for specific artistic goals
+3. Test multiple schedulers for hero images
+4. Use visualization to understand curves
+
+### Performance Tips
+- Simple/normal for quick previews
+- Karras/exponential for quality
+- SGM uniform specifically for FLUX
+- Match scheduler to sampler type
+
+### Testing Workflow
+```python
+schedulers = ["normal", "karras", "exponential"]
+for scheduler in schedulers:
+    generate_image(scheduler)
+    save_with_metadata(scheduler)
+compare_results()
+```
+
+## Advanced Features
+
+### Beta Schedule Customization
+```python
+# Custom exponential curve
+beta_schedule = "0.00085, 0.0012, 0.0018, ..."
+
+# Sharp early reduction
+beta_schedule = "0.001, 0.002, 0.004, 0.006, ..."
+```
+
+### Schedule Visualization
+- Plots noise reduction curve
+- Shows sigma values
+- Compares with standard schedules
+- Exports schedule data
+
+### Adaptive Selection
+- Learns from user preferences
+- Adapts to hardware capabilities
+- Optimizes for generation speed
+
+## Integration Examples
+
+### Complete Pipeline
+```
+Sampler Combo → SchedulerSelectHelper → KSampler
+    ↓                    ↓
+sampler_name → Optimal scheduler selection
+```
+
+### A/B Testing
+```
+Same prompt → Different schedulers → Grid comparison
+    normal vs karras vs exponential
+```
+
+### Noise Schedule Analysis
+```
+SchedulerSelectHelper → Plot Parameters
+    visualize: True
+    → Analyze noise curves
+```
+
+## Tips and Tricks
+
+### Quality Optimization
+```python
+# For maximum quality
+if sampler in ["dpmpp_3m_sde"]:
+    use scheduler="exponential"
+elif sampler in ["dpmpp_2m_sde"]:
+    use scheduler="karras"
+```
+
+### Speed Optimization
+```python
+# For fast generation
+use scheduler="simple" or "normal"
+reduce step count by 20%
+```
+
+### Artistic Effects
+- **Sharp details**: normal scheduler
+- **Smooth gradients**: karras scheduler
+- **Fine textures**: exponential scheduler
+
+## Troubleshooting
+
+### Artifacts or Noise
+- Try different scheduler
+- Check sampler compatibility
+- Adjust step count
+
+### Slow Convergence
+- Switch from simple to karras
+- Increase step count
+- Check model compatibility
+
+### Inconsistent Results
+- Use same scheduler for batch
+- Avoid random scheduler selection
+- Fix seed for testing
+
+## Visual Guide
+
+### Noise Schedule Curves
+```
+Normal:    ████████████████
+           Linear reduction
+
+Karras:    ███████████▓▓▓░░
+           Smooth curve
+
+Exponential: ██████▓▓▓░░░░░
+            Fast early reduction
+```
+
+## Common Workflows
+
+### Scheduler Comparison
+Test same seed with different schedulers to find optimal setting.
+
+### Model Migration
+When switching models, automatically adjust scheduler for best results.
+
+### Quality Ladder
+Progress through schedulers from fast to quality for different use cases.
+
+## Version History
+- **1.0.0**: Initial adaptation from comfyui-essentials-nodes
+- **1.0.1**: Added visualization features
+- **1.0.2**: Enhanced model detection
+- **1.0.3**: Improved compatibility matrix
+
+## Credits
+Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.

examples/documentation/text_encode_sampler_params.md

@@ -0,0 +1,310 @@
+# Text Encode Sampler Params
+
+## Overview
+The **Text Encode Sampler Params** node combines text encoding with sampler parameter management, providing a unified interface for prompt processing and sampling configuration. Adapted from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) (now in maintenance mode), this tool streamlines the text-to-image pipeline setup.
+
+## Attribution
+This node is based on work from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) by cubiq. The original project is in maintenance-only mode, and we've adopted and enhanced these tools to ensure continued support and compatibility with modern ComfyUI workflows.
+
+## Features
+- **Unified Interface**: Combine text encoding and sampler params in one node
+- **Dynamic Prompt Processing**: Support for wildcards and syntax
+- **Parameter Templates**: Pre-configured settings for common scenarios
+- **Batch Text Processing**: Handle multiple prompts efficiently
+- **Model-Aware Encoding**: Optimize for different text encoders
+
+## Node Properties
+- **Category**: `ComfyAssets/🧰 xyz-helpers`
+- **Node Name**: `TextEncodeSamplerParams`
+- **Function**: `encode_and_params`
+
+## Inputs
+
+### Required
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `text` | STRING | - | Prompt text to encode |
+| `clip` | CLIP | - | CLIP model for encoding |
+| `sampler_name` | DROPDOWN | dpmpp_2m | Sampling algorithm |
+| `scheduler` | DROPDOWN | karras | Noise scheduler |
+| `steps` | INT | 20 | Sampling steps |
+| `cfg` | FLOAT | 7.0 | CFG scale |
+
+### Optional
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `negative_text` | STRING | "" | Negative prompt |
+| `seed` | INT | -1 | Random seed (-1 for random) |
+| `denoise` | FLOAT | 1.0 | Denoising strength |
+| `template` | DROPDOWN | none | Parameter template |
+
+## Outputs
+| Name | Type | Description |
+|------|------|-------------|
+| `positive` | CONDITIONING | Encoded positive prompt |
+| `negative` | CONDITIONING | Encoded negative prompt |
+| `sampler_params` | DICT | Complete sampler parameters |
+
+## Templates
+
+### Portrait Photography
+```python
+template: "portrait"
+→ steps: 25
+→ cfg: 7.5
+→ sampler: dpmpp_2m_sde
+→ scheduler: karras
+```
+
+### Landscape Art
+```python
+template: "landscape"
+→ steps: 30
+→ cfg: 8.0
+→ sampler: dpmpp_3m_sde
+→ scheduler: exponential
+```
+
+### Quick Preview
+```python
+template: "preview"
+→ steps: 12
+→ cfg: 6.0
+→ sampler: euler
+→ scheduler: normal
+```
+
+### High Detail
+```python
+template: "detailed"
+→ steps: 40
+→ cfg: 7.0
+→ sampler: dpm_adaptive
+→ scheduler: karras
+```
+
+## Usage Examples
+
+### Basic Text-to-Image
+```
+TextEncodeSamplerParams → KSampler → VAE Decode
+    text: "beautiful landscape"
+    negative_text: "ugly, blurry"
+    steps: 20
+```
+
+### Template-Based Generation
+```
+TextEncodeSamplerParams → KSampler
+    text: "portrait of a person"
+    template: "portrait"
+    → Optimized portrait settings
+```
+
+### Batch Processing
+```
+Multiple Prompts → TextEncodeSamplerParams → Batch Generate
+    → Encode all prompts with same settings
+```
+
+## Prompt Syntax Support
+
+### Wildcards
+```
+{red|blue|green} car
+→ Randomly selects color
+```
+
+### Emphasis
+```
+(important:1.2) detail
+→ Increases weight to 1.2
+```
+
+### Alternation
+```
+[cat|dog] in garden
+→ Alternates between options
+```
+
+## Best Practices
+
+### Text Encoding
+1. Keep prompts concise and descriptive
+2. Use emphasis for important elements
+3. Structure prompts logically
+4. Test negative prompts impact
+
+### Parameter Selection
+```python
+# Quality over speed
+steps: 30-40
+cfg: 7-8
+sampler: dpmpp_3m_sde
+
+# Speed over quality
+steps: 10-15
+cfg: 5-6
+sampler: euler
+```
+
+### Negative Prompts
+```python
+# Common negatives
+"ugly, tiling, poorly drawn, out of frame"
+
+# Style-specific
+"cartoon, anime" (for realism)
+"realistic, photo" (for artwork)
+```
+
+## Integration with Other Nodes
+
+### Complete Pipeline
+```
+TextEncodeSamplerParams → KSampler → VAE Decode
+         ↓                    ↑
+    All parameters      From Model Loader
+```
+
+### With LoRA
+```
+LoRAFolderBatch → TextEncodeSamplerParams → Generate
+    → Apply LoRA to encoded text
+```
+
+### Multi-Pass Processing
+```
+TextEncodeSamplerParams → First Pass (low res)
+                       ↘ Second Pass (high res)
+```
+
+## Advanced Features
+
+### Dynamic Templates
+```python
+# Load template based on prompt content
+if "portrait" in text:
+    use_template("portrait")
+elif "landscape" in text:
+    use_template("landscape")
+```
+
+### Prompt Weighting
+```python
+# Automatic weight calculation
+analyze_prompt_importance()
+apply_semantic_weights()
+```
+
+### CLIP Skip Support
+- Adjust CLIP layers used
+- Model-specific optimization
+- Quality vs style balance
+
+## Tips and Tricks
+
+### Prompt Optimization
+1. Front-load important elements
+2. Use commas for separation
+3. Avoid contradictions
+4. Test with different CFG values
+
+### Performance Tuning
+```python
+# Memory efficient
+encode_in_batches = True
+clear_cache_between = True
+
+# Speed priority
+use_half_precision = True
+minimize_conditioning = True
+```
+
+### Quality Enhancement
+- Higher CFG for prompt adherence
+- Lower CFG for creativity
+- Balance with step count
+
+## Common Workflows
+
+### Style Transfer
+```
+Reference Image → Extract Style
+                ↓
+TextEncodeSamplerParams → Apply Style
+    text: "in the style of [extracted]"
+```
+
+### Prompt Evolution
+```
+Base Prompt → Variations → TextEncodeSamplerParams
+    → Test different phrasings
+```
+
+### A/B Testing
+```
+Same prompt → Different parameters → Compare
+    template A vs template B
+```
+
+## Troubleshooting
+
+### Poor Text Adherence
+- Increase CFG scale
+- Simplify prompt
+- Check CLIP model compatibility
+
+### Over-saturation
+- Reduce CFG scale
+- Adjust negative prompt
+- Check sampler settings
+
+### Encoding Errors
+- Verify CLIP model loaded
+- Check text formatting
+- Remove special characters
+
+## Parameter Guidelines
+
+### CFG Scale Effects
+```
+Low (3-5): Creative, loose interpretation
+Medium (6-8): Balanced adherence
+High (9-12): Strict prompt following
+Very High (13+): Potential artifacts
+```
+
+### Step Count Impact
+```
+Low (10-15): Fast, rough
+Medium (20-30): Good balance
+High (40-50): Maximum quality
+Very High (50+): Diminishing returns
+```
+
+## Model-Specific Settings
+
+### SDXL
+- CFG: 6-8
+- CLIP Skip: 1-2
+- Emphasis: Moderate
+
+### SD 1.5
+- CFG: 7-9
+- CLIP Skip: 1-2
+- Emphasis: Standard
+
+### FLUX
+- CFG: 3-5
+- CLIP Skip: 0
+- Emphasis: Subtle
+
+## Version History
+- **1.0.0**: Initial adaptation from comfyui-essentials-nodes
+- **1.0.1**: Added template system
+- **1.0.2**: Enhanced prompt syntax support
+- **1.0.3**: Improved batch processing
+
+## Credits
+Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.

examples/test_prompts.txt

@@ -0,0 +1,14 @@
+A beautiful sunset over the ocean, golden hour lighting, professional photography, vibrant colors, high detail
+Negative: blurry, dark, low quality, distorted, oversaturated
+---
+Majestic mountain landscape with snow-capped peaks, dramatic clouds, alpine scenery, crystal clear air, epic composition
+Negative: foggy, flat lighting, boring composition, low contrast
+---
+Futuristic cityscape at night, neon lights, cyberpunk aesthetic, rain-slicked streets, atmospheric, blade runner style
+Negative: daylight, rural, old fashioned, low tech, empty streets
+---
+Enchanted forest with magical glowing mushrooms, fairy lights, mystical atmosphere, ancient trees, fantasy art style
+Negative: desert, urban, modern, realistic, mundane
+---
+Space station orbiting Earth, detailed mechanical structures, astronauts performing spacewalk, realistic sci-fi, NASA photography
+Negative: fantasy, medieval, underwater, cartoon style

examples/workflows/display_any_example.json

@@ -376,4 +376,4 @@
     "VHS_KeepIntermediate": true
   },
   "version": 0.4
-}
+}

examples/workflows/display_text_example.json

@@ -141,4 +141,4 @@
     "VHS_KeepIntermediate": true
   },
   "version": 0.4
-}
+}

examples/workflows/empty_latent_batch_example.json

@@ -298,4 +298,4 @@
     "VHS_KeepIntermediate": true
   },
   "version": 0.4
-}
+}

examples/workflows/gemini_prompt_example.json

@@ -204,4 +204,4 @@
     "VHS_KeepIntermediate": true
   },
   "version": 0.4
-}
+}

examples/workflows/image_to_multiple_of_example.json

@@ -549,4 +549,4 @@
     "VHS_KeepIntermediate": true
   },
   "version": 0.4
-}
+}

examples/workflows/kiko_film_grain_example.json

@@ -0,0 +1,165 @@
+{
+  "id": "kiko-film-grain-example",
+  "revision": 0,
+  "last_node_id": 4,
+  "last_link_id": 2,
+  "nodes": [
+    {
+      "id": 1,
+      "type": "LoadImage",
+      "pos": [
+        50,
+        100
+      ],
+      "size": [
+        350,
+        450
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [1],
+          "shape": 3,
+          "label": "IMAGE"
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null,
+          "shape": 3,
+          "label": "MASK"
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "example.png"
+      ]
+    },
+    {
+      "id": 2,
+      "type": "KikoFilmGrain",
+      "pos": [
+        450,
+        100
+      ],
+      "size": [
+        315,
+        202
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 1
+        }
+      ],
+      "outputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "links": [2],
+          "shape": 3,
+          "label": "image",
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "cnr_id": "kikotools",
+        "Node name for S&R": "KikoFilmGrain"
+      },
+      "widgets_values": [
+        0.5,
+        0.5,
+        0.7,
+        0.0,
+        0
+      ],
+      "color": "#223",
+      "bgcolor": "#335"
+    },
+    {
+      "id": 3,
+      "type": "PreviewImage",
+      "pos": [
+        850,
+        100
+      ],
+      "size": [
+        350,
+        450
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 2
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "PreviewImage"
+      }
+    },
+    {
+      "id": 4,
+      "type": "Note",
+      "pos": [
+        450,
+        350
+      ],
+      "size": [
+        315,
+        150
+      ],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "properties": {
+        "text": ""
+      },
+      "widgets_values": [
+        "Kiko Film Grain Example\n\nThis workflow demonstrates the film grain effect.\n\nAdjust parameters:\n- Scale: Grain size (0.25-2.0)\n- Strength: Intensity (0.0-10.0)\n- Saturation: Color amount (0.0-2.0)\n- Toe: Shadow lifting (-0.2-0.5)\n- Seed: Random pattern"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    }
+  ],
+  "links": [
+    [
+      1,
+      1,
+      0,
+      2,
+      0,
+      "IMAGE"
+    ],
+    [
+      2,
+      2,
+      0,
+      3,
+      0,
+      "IMAGE"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 1.0,
+      "offset": [0, 0]
+    }
+  },
+  "version": 0.4
+}

examples/workflows/kiko_save_image_example.json

@@ -144,4 +144,4 @@
     "VHS_KeepIntermediate": true
   },
   "version": 0.4
-}
+}

examples/workflows/resolution_calculator_example.json

@@ -352,4 +352,4 @@
     "VHS_KeepIntermediate": true
   },
   "version": 0.4
-}
+}

examples/workflows/xyz_helpers_sampler_comparison.json

@@ -0,0 +1,169 @@
+{
+  "name": "Sampler and Scheduler Comparison Workflow",
+  "description": "Compare different sampler and scheduler combinations using xyz_helpers",
+  "nodes": [
+    {
+      "id": "1",
+      "type": "SamplerSelectHelper",
+      "title": "Select Optimal Sampler",
+      "category": "ComfyAssets/🧰 xyz-helpers",
+      "inputs": {
+        "model_type": "auto",
+        "quality_preset": "balanced",
+        "sampler_override": "auto",
+        "model_name": "sdxl_model.safetensors"
+      },
+      "outputs": {
+        "sampler_name": "STRING",
+        "scheduler": "STRING",
+        "recommended_steps": "INT",
+        "recommended_cfg": "FLOAT"
+      },
+      "pos": [100, 100]
+    },
+    {
+      "id": "2",
+      "type": "SchedulerSelectHelper",
+      "title": "Optimize Scheduler",
+      "category": "ComfyAssets/🧰 xyz-helpers",
+      "inputs": {
+        "sampler_name": ["1", "sampler_name"],
+        "model_type": "sdxl",
+        "schedule_type": "smooth",
+        "visualize": true
+      },
+      "outputs": {
+        "scheduler": "STRING",
+        "schedule_curve": "IMAGE"
+      },
+      "pos": [400, 100]
+    },
+    {
+      "id": "3",
+      "type": "TextEncodeSamplerParams",
+      "title": "Setup Text and Params",
+      "category": "ComfyAssets/🧰 xyz-helpers",
+      "inputs": {
+        "text": "a majestic mountain landscape at sunset, highly detailed",
+        "negative_text": "low quality, blurry, artifacts",
+        "clip": ["model", "clip"],
+        "sampler_name": ["1", "sampler_name"],
+        "scheduler": ["2", "scheduler"],
+        "steps": ["1", "recommended_steps"],
+        "cfg": ["1", "recommended_cfg"],
+        "template": "landscape"
+      },
+      "outputs": {
+        "positive": "CONDITIONING",
+        "negative": "CONDITIONING",
+        "sampler_params": "DICT"
+      },
+      "pos": [700, 100]
+    },
+    {
+      "id": "4",
+      "type": "EmptyLatentBatch",
+      "title": "Create Test Latents",
+      "category": "ComfyAssets/📦 Latents",
+      "inputs": {
+        "preset": "1216×832 (SDXL Landscape)",
+        "batch_size": 4
+      },
+      "outputs": {
+        "latent": "LATENT"
+      },
+      "pos": [100, 300]
+    },
+    {
+      "id": "5",
+      "type": "KSampler",
+      "title": "Generate with Optimal Settings",
+      "inputs": {
+        "model": ["model", "model"],
+        "positive": ["3", "positive"],
+        "negative": ["3", "negative"],
+        "latent_image": ["4", "latent"],
+        "sampler_name": ["1", "sampler_name"],
+        "scheduler": ["2", "scheduler"],
+        "steps": ["1", "recommended_steps"],
+        "cfg": ["1", "recommended_cfg"],
+        "seed": 42
+      },
+      "outputs": {
+        "latent": "LATENT"
+      },
+      "pos": [1000, 200]
+    },
+    {
+      "id": "6",
+      "type": "PlotParameters",
+      "title": "Visualize Parameters",
+      "category": "ComfyAssets/🧰 xyz-helpers",
+      "inputs": {
+        "sampler_params": ["3", "sampler_params"],
+        "plot_type": "bar",
+        "x_axis": "parameter_name",
+        "y_axis": "value",
+        "title": "Sampler Configuration Analysis",
+        "show_grid": true
+      },
+      "outputs": {
+        "plot_image": "IMAGE"
+      },
+      "pos": [700, 400]
+    },
+    {
+      "id": "7",
+      "type": "DisplayAny",
+      "title": "Show Schedule Curve",
+      "category": "ComfyAssets/🔍 Debug",
+      "inputs": {
+        "input": ["2", "schedule_curve"],
+        "mode": "tensor shape"
+      },
+      "pos": [400, 400]
+    },
+    {
+      "id": "8",
+      "type": "VAEDecode",
+      "title": "Decode Results",
+      "inputs": {
+        "samples": ["5", "latent"],
+        "vae": ["model", "vae"]
+      },
+      "outputs": {
+        "image": "IMAGE"
+      },
+      "pos": [1300, 200]
+    },
+    {
+      "id": "9",
+      "type": "KikoSaveImage",
+      "title": "Save Comparison",
+      "category": "ComfyAssets/💾 Images",
+      "inputs": {
+        "images": ["8", "image"],
+        "filename_prefix": "sampler_comparison",
+        "format": "WEBP",
+        "quality": 90,
+        "popup": true
+      },
+      "pos": [1600, 200]
+    }
+  ],
+  "workflow_notes": {
+    "purpose": "Compare and optimize sampler/scheduler combinations for best quality",
+    "features": [
+      "Automatic sampler selection based on model",
+      "Scheduler optimization with visualization",
+      "Parameter analysis and plotting",
+      "Batch generation for comparison"
+    ],
+    "tips": [
+      "Try different quality_preset values",
+      "Use visualize=true to see noise schedules",
+      "Compare results across multiple seeds"
+    ],
+    "attribution": "xyz_helpers nodes adapted from comfyui-essentials-nodes"
+  }
+}

kikotools/__init__.py

@@ -3,19 +3,51 @@ KikoTools package initialization and node registry
 Handles automatic discovery and registration of all ComfyAssets tools
 """
 
-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.gemini_prompt import GeminiPromptNode
+from .tools.batch_list_converter import (
+    ImageBatchToImageListNode,
+    ImageListToImageBatchNode,
+    LatentBatchToLatentListNode,
+    LatentListToLatentBatchNode,
+)
+from .tools.batch_prompts import BatchPromptsNode
+from .tools.checkpoint_folder_iterator import CheckpointFolderIteratorNode
 from .tools.display_any import DisplayAnyNode
 from .tools.display_text import DisplayTextNode
+from .tools.embedding_autocomplete import KikoEmbeddingAutocomplete
+from .tools.empty_latent_batch import EmptyLatentBatchNode
+from .tools.gemini_prompt import GeminiPromptNode
+from .tools.image_scale_down_by import ImageScaleDownByNode
+from .tools.image_to_multiple_of import ImageToMultipleOfNode
+from .tools.kiko_film_grain import KikoFilmGrainNode
+from .tools.kiko_purge_vram import KikoPurgeVRAM
+from .tools.kiko_workflow_timer import KikoWorkflowTimerNode
+from .tools.kiko_save_image import KikoSaveImageNode
+from .tools.local_image_loader import LocalImageLoaderNode
+from .tools.project_file_path import ProjectFilePathNode
+from .tools.model_compare_sheet import ModelCompareSheetNode
+from .tools.model_downloader import ModelDownloaderNode
+from .tools.resolution_calculator import ResolutionCalculatorNode
+from .tools.sampler_combo import SamplerComboCompactNode, SamplerComboNode
+from .tools.seed_history import SeedHistoryNode
+from .tools.text_input import TextInputNode
+from .tools.width_height_selector import WidthHeightSelectorNode
+from .tools.width_height_to_vec2 import WidthHeightToVec2Node
+from .tools.xyz_helpers import (
+    FluxSamplerParamsNode,
+    LoRAFolderBatchNode,
+    PlotParametersNode,
+    SamplerSelectHelperNode,
+    SchedulerSelectHelperNode,
+    TextEncodeSamplerParamsNode,
+)
 
 # ComfyUI node registration mappings
 NODE_CLASS_MAPPINGS = {
+    "ImageBatchToImageList": ImageBatchToImageListNode,
+    "ImageListToImageBatch": ImageListToImageBatchNode,
+    "LatentBatchToLatentList": LatentBatchToLatentListNode,
+    "LatentListToLatentBatch": LatentListToLatentBatchNode,
+    "BatchPrompts": BatchPromptsNode,
     "ResolutionCalculator": ResolutionCalculatorNode,
     "WidthHeightSelector": WidthHeightSelectorNode,
     "SeedHistory": SeedHistoryNode,
@@ -24,12 +56,36 @@ NODE_CLASS_MAPPINGS = {
     "EmptyLatentBatch": EmptyLatentBatchNode,
     "KikoSaveImage": KikoSaveImageNode,
     "ImageToMultipleOf": ImageToMultipleOfNode,
+    "ImageScaleDownBy": ImageScaleDownByNode,
     "GeminiPrompt": GeminiPromptNode,
     "DisplayAny": DisplayAnyNode,
     "DisplayText": DisplayTextNode,
+    "TextInput": TextInputNode,
+    "KikoFilmGrain": KikoFilmGrainNode,
+    "KikoPurgeVRAM": KikoPurgeVRAM,
+    "KikoLocalImageLoader": LocalImageLoaderNode,
+    "KikoModelDownloader": ModelDownloaderNode,
+    "SamplerSelectHelper": SamplerSelectHelperNode,
+    "SchedulerSelectHelper": SchedulerSelectHelperNode,
+    "TextEncodeSamplerParams": TextEncodeSamplerParamsNode,
+    "FluxSamplerParams": FluxSamplerParamsNode,
+    "PlotParameters+": PlotParametersNode,
+    "LoRAFolderBatch": LoRAFolderBatchNode,
+    "CheckpointFolderIterator": CheckpointFolderIteratorNode,
+    "ModelCompareSheet": ModelCompareSheetNode,
+    "WidthHeightToVec2": WidthHeightToVec2Node,
+    "KikoWorkflowTimer": KikoWorkflowTimerNode,
+    "KikoProjectFilePath": ProjectFilePathNode,
+    # Note: KikoEmbeddingAutocomplete is not registered as a node
+    # It's a settings-only feature accessed through ComfyUI settings menu
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
+    "ImageBatchToImageList": "Image Batch to Image List",
+    "ImageListToImageBatch": "Image List to Image Batch",
+    "LatentBatchToLatentList": "Latent Batch to Latent List",
+    "LatentListToLatentBatch": "Latent List to Latent Batch",
+    "BatchPrompts": "Batch Prompts",
     "ResolutionCalculator": "Resolution Calculator",
     "WidthHeightSelector": "Width Height Selector",
     "SeedHistory": "Seed History",
@@ -38,9 +94,27 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "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",
+    "TextInput": "Text Input",
+    "KikoFilmGrain": "Film Grain",
+    "KikoPurgeVRAM": "Kiko Purge VRAM",
+    "KikoLocalImageLoader": "Local Image Loader",
+    "KikoModelDownloader": "Model Downloader 🌐",
+    "SamplerSelectHelper": "Sampler Select Helper",
+    "SchedulerSelectHelper": "Scheduler Select Helper",
+    "TextEncodeSamplerParams": "Text Encode for Sampler Params",
+    "FluxSamplerParams": "Flux Sampler Parameters",
+    "PlotParameters+": "Plot Parameters",
+    "LoRAFolderBatch": "LoRA Folder Batch",
+    "CheckpointFolderIterator": "Checkpoint Folder Iterator",
+    "ModelCompareSheet": "Model Compare Sheet",
+    "WidthHeightToVec2": "Width Height to VEC2",
+    "KikoWorkflowTimer": "Workflow Timer",
+    "KikoProjectFilePath": "Project File Path",
+    # KikoEmbeddingAutocomplete removed - settings only, not a node
 }
 
 __all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]

kikotools/base/any_type.py

@@ -0,0 +1,8 @@
+"""AnyType for wildcard input matching in ComfyUI nodes."""
+
+
+class AnyType(str):
+    """A special type that matches any input type in ComfyUI."""
+
+    def __ne__(self, other):
+        return False

kikotools/base/base_node.py

@@ -20,7 +20,7 @@ class ComfyAssetsBaseNode:
     - Consistent return type handling
     """
 
-    CATEGORY = "ComfyAssets"
+    CATEGORY = "🫶 ComfyAssets"
 
     def validate_inputs(self, **kwargs) -> None:
         """

kikotools/base/model_folders.py

@@ -0,0 +1,106 @@
+"""Scan ComfyUI model folders (loras, checkpoints, ...) for .safetensors files."""
+
+import logging
+import os
+import re
+from typing import Dict, List, Optional, Tuple
+
+logger = logging.getLogger(__name__)
+
+
+def get_model_roots(folder_key: str) -> List[str]:
+    """Return every configured root directory for a folder_paths key."""
+    try:
+        import folder_paths
+
+        entry = folder_paths.folder_names_and_paths.get(folder_key)
+        return list(entry[0]) if entry else []
+    except (ImportError, AttributeError, IndexError, TypeError):
+        return []
+
+
+def is_within(path: str, root: str) -> bool:
+    """True if realpath `path` equals or is inside realpath `root`."""
+    try:
+        real_path, real_root = os.path.realpath(path), os.path.realpath(root)
+        return os.path.commonpath([real_path, real_root]) == real_root
+    except ValueError:  # different drives or mixed absolute/relative
+        return False
+
+
+def resolve_scan_targets(
+    folder_path: str, folder_key: str
+) -> List[Tuple[str, Optional[str]]]:
+    """
+    Resolve a folder setting to (directory, base_root) pairs to scan.
+
+    base_root is the model root the directory lives in, or None when the
+    directory is an absolute path outside every known root.
+    """
+    roots = get_model_roots(folder_key)
+
+    if os.path.isabs(folder_path):
+        base = next((r for r in roots if is_within(folder_path, r)), None)
+        return [(folder_path, base)]
+
+    targets = []
+    for root in roots:
+        candidate = os.path.join(root, folder_path)
+        if not is_within(candidate, root):
+            logger.warning(f"Folder escapes the {folder_key} directory: {folder_path}")
+            continue
+        targets.append((candidate, root))
+    return targets
+
+
+def scan_model_entries(folder_path: str, folder_key: str) -> List[Tuple[str, str]]:
+    """Return naturally sorted (relative_name, absolute_path) for every .safetensors."""
+    entries: Dict[str, str] = {}
+    for directory, base in resolve_scan_targets(folder_path, folder_key):
+        if not os.path.isdir(directory):
+            continue
+        for root, _, files in os.walk(directory):
+            for file in files:
+                if not file.endswith(".safetensors"):
+                    continue
+                full = os.path.join(root, file)
+                try:
+                    rel = os.path.relpath(full, base or directory)
+                except ValueError:
+                    rel = os.path.relpath(full, directory)
+                entries.setdefault(rel.replace("\\", "/"), full)
+    return [(name, entries[name]) for name in natural_sort(list(entries))]
+
+
+def natural_sort(items: List[str]) -> List[str]:
+    """Sort strings so embedded numbers compare numerically (v2 < v10)."""
+
+    def natural_key(text):
+        parts = []
+        for part in re.split(r"(\d+)", text):
+            if not part:
+                continue
+            parts.append((0, int(part)) if part.isdigit() else (1, part.lower()))
+        return parts
+
+    return sorted(items, key=natural_key)
+
+
+def filter_by_pattern(
+    names: List[str], include_pattern: str = "", exclude_pattern: str = ""
+) -> List[str]:
+    """Keep names matching include_pattern (if set) and not exclude_pattern (if set)."""
+    filtered = list(names)
+    if include_pattern:
+        try:
+            include_re = re.compile(include_pattern)
+            filtered = [f for f in filtered if include_re.search(f)]
+        except re.error as e:
+            logger.error(f"Invalid include pattern: {e}")
+    if exclude_pattern:
+        try:
+            exclude_re = re.compile(exclude_pattern)
+            filtered = [f for f in filtered if not exclude_re.search(f)]
+        except re.error as e:
+            logger.error(f"Invalid exclude pattern: {e}")
+    return filtered

kikotools/tools/batch_list_converter/__init__.py

@@ -0,0 +1,15 @@
+"""Batch/List conversion tool for ComfyUI."""
+
+from .node import (
+    ImageBatchToImageListNode,
+    ImageListToImageBatchNode,
+    LatentBatchToLatentListNode,
+    LatentListToLatentBatchNode,
+)
+
+__all__ = [
+    "ImageBatchToImageListNode",
+    "ImageListToImageBatchNode",
+    "LatentBatchToLatentListNode",
+    "LatentListToLatentBatchNode",
+]

kikotools/tools/batch_list_converter/logic.py

@@ -0,0 +1,55 @@
+"""Pure tensor split/join functions for batch-list conversions."""
+
+import torch
+from typing import Dict, List
+
+
+def split_image_batch(images: torch.Tensor) -> List[torch.Tensor]:
+    """Split [B,H,W,C] image batch into list of [1,H,W,C] tensors."""
+    return [images[i : i + 1] for i in range(images.shape[0])]
+
+
+def join_image_batch(image_list: List[torch.Tensor]) -> torch.Tensor:
+    """Join list of image tensors into single [B,H,W,C] batch."""
+    return torch.cat(image_list, dim=0)
+
+
+def split_latent_batch(
+    latent: Dict[str, torch.Tensor],
+) -> List[Dict[str, torch.Tensor]]:
+    """Split latent dict into list of single-item latent dicts.
+
+    Preserves all keys (e.g. noise_mask, batch_index). Tensor values whose
+    first dimension matches the batch size of ``samples`` are sliced along
+    dim-0; all other values are copied as-is to every item.
+    """
+    samples = latent["samples"]
+    batch_size = samples.shape[0]
+    result: List[Dict[str, torch.Tensor]] = []
+    for i in range(batch_size):
+        item: Dict[str, torch.Tensor] = {}
+        for key, value in latent.items():
+            if isinstance(value, torch.Tensor) and value.shape[0] == batch_size:
+                item[key] = value[i : i + 1]
+            else:
+                item[key] = value
+        result.append(item)
+    return result
+
+
+def join_latent_batch(
+    latent_list: List[Dict[str, torch.Tensor]],
+) -> Dict[str, torch.Tensor]:
+    """Join list of latent dicts into single batched latent dict.
+
+    Tensor values that were sliced during split are concatenated along dim-0.
+    Non-tensor values are taken from the first item.
+    """
+    result: Dict[str, torch.Tensor] = {}
+    first = latent_list[0]
+    for key in first:
+        if isinstance(first[key], torch.Tensor):
+            result[key] = torch.cat([lat[key] for lat in latent_list], dim=0)
+        else:
+            result[key] = first[key]
+    return result

kikotools/tools/batch_list_converter/node.py

@@ -0,0 +1,130 @@
+"""Batch/List conversion nodes for ComfyUI."""
+
+from typing import Dict, List, Tuple
+
+import torch
+
+from ...base.base_node import ComfyAssetsBaseNode
+from .logic import (
+    split_image_batch,
+    join_image_batch,
+    split_latent_batch,
+    join_latent_batch,
+)
+
+
+class ImageBatchToImageListNode(ComfyAssetsBaseNode):
+    """Split an IMAGE batch [B,H,W,C] into a list of individual images."""
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "images": ("IMAGE",),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE", "INT")
+    RETURN_NAMES = ("images", "count")
+    OUTPUT_IS_LIST = (True, False)
+    FUNCTION = "split_batch"
+    CATEGORY = "🫶 ComfyAssets/📦 Latents"
+
+    def split_batch(self, images: torch.Tensor) -> Tuple[List[torch.Tensor], int]:
+        image_list = split_image_batch(images)
+        count = len(image_list)
+        self.log_info(f"Split image batch of {count} into list")
+        return (image_list, count)
+
+
+class ImageListToImageBatchNode(ComfyAssetsBaseNode):
+    """Join a list of IMAGE tensors into a single batched IMAGE [B,H,W,C]."""
+
+    INPUT_IS_LIST = True
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "images": ("IMAGE",),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE", "INT")
+    RETURN_NAMES = ("images", "count")
+    FUNCTION = "join_batch"
+    CATEGORY = "🫶 ComfyAssets/📦 Latents"
+
+    def join_batch(self, images: List[torch.Tensor]) -> Tuple[torch.Tensor, int]:
+        batch = join_image_batch(images)
+        count = batch.shape[0]
+        self.log_info(f"Joined {count} images into batch")
+        return (batch, count)
+
+
+class LatentBatchToLatentListNode(ComfyAssetsBaseNode):
+    """Split a LATENT batch into a list of individual latent dicts."""
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "latent": ("LATENT",),
+            }
+        }
+
+    RETURN_TYPES = ("LATENT", "INT")
+    RETURN_NAMES = ("latents", "count")
+    OUTPUT_IS_LIST = (True, False)
+    FUNCTION = "split_batch"
+    CATEGORY = "🫶 ComfyAssets/📦 Latents"
+
+    def split_batch(
+        self, latent: Dict[str, torch.Tensor]
+    ) -> Tuple[List[Dict[str, torch.Tensor]], int]:
+        latent_list = split_latent_batch(latent)
+        count = len(latent_list)
+        self.log_info(f"Split latent batch of {count} into list")
+        return (latent_list, count)
+
+
+class LatentListToLatentBatchNode(ComfyAssetsBaseNode):
+    """Join a list of LATENT dicts into a single batched LATENT."""
+
+    INPUT_IS_LIST = True
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "latents": ("LATENT",),
+            }
+        }
+
+    RETURN_TYPES = ("LATENT", "INT")
+    RETURN_NAMES = ("latent", "count")
+    FUNCTION = "join_batch"
+    CATEGORY = "🫶 ComfyAssets/📦 Latents"
+
+    def join_batch(
+        self, latents: List[Dict[str, torch.Tensor]]
+    ) -> Tuple[Dict[str, torch.Tensor], int]:
+        batch = join_latent_batch(latents)
+        count = batch["samples"].shape[0]
+        self.log_info(f"Joined {count} latents into batch")
+        return (batch, count)
+
+
+NODE_CLASS_MAPPINGS = {
+    "ImageBatchToImageList": ImageBatchToImageListNode,
+    "ImageListToImageBatch": ImageListToImageBatchNode,
+    "LatentBatchToLatentList": LatentBatchToLatentListNode,
+    "LatentListToLatentBatch": LatentListToLatentBatchNode,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ImageBatchToImageList": "Image Batch to Image List",
+    "ImageListToImageBatch": "Image List to Image Batch",
+    "LatentBatchToLatentList": "Latent Batch to Latent List",
+    "LatentListToLatentBatch": "Latent List to Latent Batch",
+}

kikotools/tools/batch_prompts/__init__.py

@@ -0,0 +1,5 @@
+"""Batch Prompts node for loading and processing prompts from text files."""
+
+from .node import BatchPromptsNode
+
+__all__ = ["BatchPromptsNode"]

kikotools/tools/batch_prompts/logic.py

@@ -0,0 +1,278 @@
+"""Logic module for Batch Prompts node."""
+
+import os
+from typing import List, Tuple, Dict, Any
+import logging
+
+logger = logging.getLogger(__name__)
+
+
+def load_prompts_from_file(file_path: str) -> List[str]:
+    """
+    Load prompts from a text file where prompts are separated by '---'.
+
+    Args:
+        file_path: Path to the text file containing prompts
+
+    Returns:
+        List of prompts (each prompt may be multi-line)
+    """
+    try:
+        with open(file_path, "r", encoding="utf-8") as f:
+            content = f.read()
+
+        # Split by --- separator
+        prompts = content.split("---")
+
+        # Clean up prompts - remove leading/trailing whitespace but preserve internal formatting
+        cleaned_prompts = []
+        for prompt in prompts:
+            prompt = prompt.strip()
+            if prompt:  # Only add non-empty prompts
+                cleaned_prompts.append(prompt)
+
+        logger.info(f"Loaded {len(cleaned_prompts)} prompts from {file_path}")
+        return cleaned_prompts
+
+    except Exception as e:
+        logger.error(f"Error loading prompts from {file_path}: {e}")
+        return []
+
+
+def get_prompt_at_index(
+    prompts: List[str], index: int, wrap: bool = True
+) -> Tuple[str, int]:
+    """
+    Get prompt at specified index with optional wrapping.
+
+    Args:
+        prompts: List of prompts
+        index: Index to retrieve
+        wrap: Whether to wrap around to beginning when index exceeds list length
+
+    Returns:
+        Tuple of (prompt text, actual index used)
+    """
+    if not prompts:
+        return ("", 0)
+
+    if wrap:
+        actual_index = index % len(prompts)
+    else:
+        actual_index = min(index, len(prompts) - 1)
+
+    return (prompts[actual_index], actual_index)
+
+
+def get_next_prompt(
+    prompts: List[str], current_index: int, wrap: bool = True
+) -> Tuple[str, int]:
+    """
+    Get the next prompt in sequence.
+
+    Args:
+        prompts: List of prompts
+        current_index: Current prompt index
+        wrap: Whether to wrap around to beginning
+
+    Returns:
+        Tuple of (next prompt text, next index)
+    """
+    if not prompts:
+        return ("", 0)
+
+    next_index = current_index + 1
+
+    if wrap:
+        next_index = next_index % len(prompts)
+    else:
+        next_index = min(next_index, len(prompts) - 1)
+
+    return (prompts[next_index], next_index)
+
+
+def get_prompt_preview(prompt: str, max_length: int = 100) -> str:
+    """
+    Get a preview of a prompt, truncated if necessary.
+
+    Args:
+        prompt: Full prompt text
+        max_length: Maximum length for preview
+
+    Returns:
+        Preview string
+    """
+    if len(prompt) <= max_length:
+        return prompt
+
+    return prompt[:max_length] + "..."
+
+
+def parse_prompt_file_list(file_list_str: str) -> List[str]:
+    """
+    Parse a comma-separated list of prompt file paths.
+
+    Args:
+        file_list_str: Comma-separated file paths
+
+    Returns:
+        List of file paths
+    """
+    if not file_list_str:
+        return []
+
+    files = []
+    for file_path in file_list_str.split(","):
+        file_path = file_path.strip()
+        if file_path:
+            files.append(file_path)
+
+    return files
+
+
+def merge_prompts_from_multiple_files(file_paths: List[str]) -> List[str]:
+    """
+    Load and merge prompts from multiple files.
+
+    Args:
+        file_paths: List of file paths
+
+    Returns:
+        Combined list of all prompts
+    """
+    all_prompts = []
+
+    for file_path in file_paths:
+        prompts = load_prompts_from_file(file_path)
+        all_prompts.extend(prompts)
+
+    logger.info(f"Merged {len(all_prompts)} prompts from {len(file_paths)} files")
+    return all_prompts
+
+
+def get_batch_info(prompts: List[str], current_index: int) -> Dict[str, Any]:
+    """
+    Get information about current batch processing state.
+
+    Args:
+        prompts: List of prompts
+        current_index: Current prompt index
+
+    Returns:
+        Dictionary with batch information
+    """
+    total = len(prompts)
+
+    return {
+        "current_index": current_index,
+        "total_prompts": total,
+        "progress": f"{current_index + 1}/{total}" if total > 0 else "0/0",
+        "percentage": (current_index / total * 100) if total > 0 else 0,
+        "remaining": total - current_index - 1 if total > 0 else 0,
+        "is_complete": current_index >= total - 1 if total > 0 else True,
+    }
+
+
+def validate_prompt_file(file_path: str) -> Tuple[bool, str]:
+    """
+    Validate that a prompt file exists and is readable.
+
+    Args:
+        file_path: Path to validate
+
+    Returns:
+        Tuple of (is_valid, error_message)
+    """
+    if not file_path:
+        return (False, "No file path provided")
+
+    if not os.path.exists(file_path):
+        return (False, f"File not found: {file_path}")
+
+    if not os.path.isfile(file_path):
+        return (False, f"Path is not a file: {file_path}")
+
+    try:
+        with open(file_path, "r", encoding="utf-8") as f:
+            f.read(1)  # Try to read one character
+        return (True, "")
+    except Exception as e:
+        return (False, f"Cannot read file: {str(e)}")
+
+
+def format_prompt_for_display(prompt: str, index: int, total: int) -> str:
+    """
+    Format a prompt for display with index information.
+
+    Args:
+        prompt: Prompt text
+        index: Current index
+        total: Total number of prompts
+
+    Returns:
+        Formatted display string
+    """
+    header = f"[Prompt {index + 1}/{total}]"
+    separator = "-" * len(header)
+
+    return f"{header}\n{separator}\n{prompt}"
+
+
+def split_prompt_into_positive_negative(
+    prompt: str, negative_prefix: str = "Negative:"
+) -> Tuple[str, str]:
+    """
+    Split a prompt into positive and negative parts.
+
+    Args:
+        prompt: Full prompt text
+        negative_prefix: Prefix that marks the negative prompt section
+
+    Returns:
+        Tuple of (positive_prompt, negative_prompt)
+    """
+    # Look for negative prompt marker
+    negative_lower = negative_prefix.lower()
+    prompt_lower = prompt.lower()
+
+    if negative_lower in prompt_lower:
+        # Find the actual position (case-insensitive search)
+        idx = prompt_lower.index(negative_lower)
+        positive = prompt[:idx].strip()
+        negative = prompt[idx + len(negative_prefix) :].strip()
+        return (positive, negative)
+
+    # No negative prompt found
+    return (prompt, "")
+
+
+def create_batch_queue(
+    prompts: List[str], batch_size: int = 1, randomize: bool = False
+) -> List[List[int]]:
+    """
+    Create a queue of prompt indices for batch processing.
+
+    Args:
+        prompts: List of prompts
+        batch_size: Number of prompts per batch
+        randomize: Whether to randomize the order
+
+    Returns:
+        List of batches, where each batch is a list of prompt indices
+    """
+    if not prompts:
+        return []
+
+    indices = list(range(len(prompts)))
+
+    if randomize:
+        import random
+
+        random.shuffle(indices)
+
+    batches = []
+    for i in range(0, len(indices), batch_size):
+        batch = indices[i : i + batch_size]
+        batches.append(batch)
+
+    return batches

kikotools/tools/batch_prompts/node.py

@@ -0,0 +1,237 @@
+"""Batch Prompts node for ComfyUI."""
+
+import os
+from typing import Tuple
+from ...base.base_node import ComfyAssetsBaseNode
+from .logic import (
+    load_prompts_from_file,
+    get_prompt_at_index,
+    get_next_prompt,
+    get_prompt_preview,
+    get_batch_info,
+    validate_prompt_file,
+    split_prompt_into_positive_negative,
+)
+from .state_manager import STATE_MANAGER
+
+
+class BatchPromptsNode(ComfyAssetsBaseNode):
+    """
+    Batch Prompts node for loading and iterating through prompts from text files.
+
+    Loads prompts from a text file where prompts are separated by '---' markers,
+    provides iteration control, and outputs both current and next prompts with
+    optional positive/negative splitting.
+    """
+
+    # Class variable to cache loaded prompts
+    _prompt_cache = {}
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        """Define the input types for the ComfyUI node."""
+        # Try to get input folder path
+        try:
+            import folder_paths
+
+            folder_paths.get_input_directory()
+        except Exception:
+            pass
+
+        return {
+            "required": {
+                "prompt_file": (
+                    "STRING",
+                    {
+                        "default": "prompts.txt",
+                        "multiline": False,
+                        "tooltip": "Path to text file containing prompts separated by '---'",
+                    },
+                ),
+                "index": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "min": 0,
+                        "max": 9999,
+                        "step": 1,
+                        "tooltip": "Current prompt index (0-based)",
+                    },
+                ),
+                "auto_increment": (
+                    "BOOLEAN",
+                    {
+                        "default": True,
+                        "tooltip": "Automatically increment index after each execution",
+                    },
+                ),
+                "wrap_around": (
+                    "BOOLEAN",
+                    {
+                        "default": True,
+                        "tooltip": "Wrap to first prompt after reaching the end",
+                    },
+                ),
+                "split_negative": (
+                    "BOOLEAN",
+                    {
+                        "default": True,
+                        "tooltip": "Split prompts into positive/negative at 'Negative:' marker",
+                    },
+                ),
+            },
+            "optional": {
+                "reload_file": (
+                    "BOOLEAN",
+                    {"default": False, "tooltip": "Force reload file from disk"},
+                ),
+                "show_preview": (
+                    "BOOLEAN",
+                    {"default": True, "tooltip": "Show prompt preview in console"},
+                ),
+            },
+        }
+
+    RETURN_TYPES = ("STRING", "STRING", "STRING", "STRING", "INT", "INT", "STRING")
+    RETURN_NAMES = (
+        "positive",
+        "negative",
+        "full_prompt",
+        "next_prompt",
+        "current_index",
+        "total_prompts",
+        "batch_info",
+    )
+    FUNCTION = "process_batch_prompts"
+    CATEGORY = "🫶 ComfyAssets/📝 Text"
+
+    def process_batch_prompts(
+        self,
+        prompt_file: str,
+        index: int,
+        auto_increment: bool,
+        wrap_around: bool,
+        split_negative: bool,
+        reload_file: bool = False,
+        show_preview: bool = True,
+    ) -> Tuple[str, str, str, str, int, int, str]:
+        """
+        Process batch prompts from file.
+
+        Args:
+            prompt_file: Path to prompt file
+            index: Current prompt index
+            auto_increment: Whether to auto-increment index
+            wrap_around: Whether to wrap around at end
+            split_negative: Whether to split positive/negative prompts
+            reload_file: Force reload from disk
+            show_preview: Show prompt preview in console
+
+        Returns:
+            Tuple of (positive, negative, full_prompt, next_prompt, current_index, total_prompts, batch_info)
+        """
+        try:
+            # Handle file path first to get a consistent key
+            if not os.path.isabs(prompt_file):
+                # Try to resolve relative to ComfyUI input directory
+                try:
+                    import folder_paths
+
+                    input_dir = folder_paths.get_input_directory()
+                    full_path = os.path.join(input_dir, prompt_file)
+                except Exception:
+                    # Fallback to current directory
+                    full_path = os.path.abspath(prompt_file)
+            else:
+                full_path = prompt_file
+
+            # Use persistent state manager for tracking execution
+            if auto_increment:
+                # Use file-based persistent state
+                actual_index = STATE_MANAGER.increment_execution_count(full_path)
+                print(
+                    f"[BatchPrompts] Auto-increment: using index {actual_index} for {os.path.basename(prompt_file)}"
+                )
+            else:
+                actual_index = index
+                print(f"[BatchPrompts] Manual mode: using index {actual_index}")
+
+            # Validate file
+            is_valid, error_msg = validate_prompt_file(full_path)
+            if not is_valid:
+                self.handle_error(f"Invalid prompt file: {error_msg}")
+
+            # Load prompts (with caching)
+            cache_key = full_path
+            if reload_file or cache_key not in self._prompt_cache:
+                prompts = load_prompts_from_file(full_path)
+                if not prompts:
+                    self.handle_error(f"No prompts found in file: {prompt_file}")
+                self._prompt_cache[cache_key] = prompts
+                # Reset execution count when reloading file
+                if reload_file:
+                    STATE_MANAGER.reset_execution_count(full_path)
+                self.log_info(f"Loaded {len(prompts)} prompts from {prompt_file}")
+            else:
+                prompts = self._prompt_cache[cache_key]
+
+            # Get current prompt using the determined index
+            current_prompt, used_index = get_prompt_at_index(
+                prompts, actual_index, wrap_around
+            )
+
+            # Get next prompt
+            next_prompt_text, next_index = get_next_prompt(
+                prompts, used_index, wrap_around
+            )
+
+            # Split positive/negative if requested
+            if split_negative:
+                positive, negative = split_prompt_into_positive_negative(current_prompt)
+            else:
+                positive = current_prompt
+                negative = ""
+
+            # Get batch info
+            batch_info_dict = get_batch_info(prompts, used_index)
+            batch_info_str = (
+                f"Prompt {batch_info_dict['current_index'] + 1} of {batch_info_dict['total_prompts']} "
+                f"({batch_info_dict['percentage']:.1f}% complete)"
+            )
+
+            # Show preview if requested
+            if show_preview:
+                preview = get_prompt_preview(positive, 80)
+                self.log_info(
+                    f"Current prompt [{used_index + 1}/{len(prompts)}]: {preview}"
+                )
+
+            # No need to manually reset - the modulo operation in get_prompt_at_index handles wrapping
+
+            return (
+                positive,
+                negative,
+                current_prompt,
+                next_prompt_text,
+                used_index,
+                len(prompts),
+                batch_info_str,
+            )
+
+        except Exception as e:
+            self.handle_error(f"Error processing batch prompts: {str(e)}")
+            # Return empty values on error
+            return ("", "", "", "", 0, 0, "Error")
+
+    @classmethod
+    def IS_CHANGED(cls, **kwargs):
+        """
+        Check if node inputs have changed.
+        This ensures the node re-executes when needed.
+        """
+        # Import time to ensure unique value each check
+        import time
+
+        # Return current timestamp to guarantee the node is seen as changed
+        # This forces re-execution on every workflow run
+        return str(time.time())

kikotools/tools/batch_prompts/state_manager.py

@@ -0,0 +1,62 @@
+"""State management for batch prompts using file persistence."""
+
+import json
+import tempfile
+from pathlib import Path
+from typing import Dict, Any
+
+
+class StateManager:
+    """Manages persistent state for batch prompt execution."""
+
+    def __init__(self):
+        # Use temp directory for state files
+        self.state_dir = Path(tempfile.gettempdir()) / "comfyui_batch_prompts"
+        self.state_dir.mkdir(exist_ok=True)
+        self.state_file = self.state_dir / "execution_state.json"
+
+    def get_state(self) -> Dict[str, Any]:
+        """Load state from file."""
+        if self.state_file.exists():
+            try:
+                with open(self.state_file, "r", encoding="utf-8") as f:
+                    return json.load(f)
+            except (json.JSONDecodeError, IOError):
+                pass
+        return {}
+
+    def save_state(self, state: Dict[str, Any]):
+        """Save state to file."""
+        try:
+            with open(self.state_file, "w", encoding="utf-8") as f:
+                json.dump(state, f)
+        except Exception as e:
+            print(f"[BatchPrompts] Failed to save state: {e}")
+
+    def get_execution_count(self, file_path: str) -> int:
+        """Get execution count for a specific file."""
+        state = self.get_state()
+        counts = state.get("execution_counts", {})
+        return counts.get(file_path, 0)
+
+    def increment_execution_count(self, file_path: str) -> int:
+        """Increment and return execution count for a file."""
+        state = self.get_state()
+        counts = state.get("execution_counts", {})
+        current = counts.get(file_path, 0)
+        counts[file_path] = current + 1
+        state["execution_counts"] = counts
+        self.save_state(state)
+        return current
+
+    def reset_execution_count(self, file_path: str):
+        """Reset execution count for a file."""
+        state = self.get_state()
+        counts = state.get("execution_counts", {})
+        counts[file_path] = 0
+        state["execution_counts"] = counts
+        self.save_state(state)
+
+
+# Global state manager instance
+STATE_MANAGER = StateManager()

kikotools/tools/checkpoint_folder_iterator/__init__.py

@@ -0,0 +1,5 @@
+"""Checkpoint Folder Iterator module."""
+
+from .node import CheckpointFolderIteratorNode
+
+__all__ = ["CheckpointFolderIteratorNode"]

kikotools/tools/checkpoint_folder_iterator/logic.py

@@ -0,0 +1,52 @@
+"""Logic for the Checkpoint Folder Iterator node."""
+
+import os
+from typing import List, Sequence, Tuple, TypeVar
+
+from ...base.model_folders import filter_by_pattern, scan_model_entries
+
+T = TypeVar("T")
+
+
+def list_checkpoint_entries(
+    folder_path: str, include_pattern: str = "", exclude_pattern: str = ""
+) -> List[Tuple[str, str]]:
+    """(name, absolute_path) pairs for every checkpoint, filtered, in natural order.
+
+    The absolute path is what gets loaded, so folders outside the configured
+    checkpoints roots work too; the name is relative to the root (or to the
+    folder itself when it lives outside every root) and is used for labels.
+    """
+    entries = scan_model_entries(folder_path, "checkpoints")
+    names = [name for name, _ in entries]
+    kept = set(filter_by_pattern(names, include_pattern, exclude_pattern))
+    return [(name, path) for name, path in entries if name in kept]
+
+
+def list_checkpoints(
+    folder_path: str, include_pattern: str = "", exclude_pattern: str = ""
+) -> List[str]:
+    """Checkpoint names (relative to the checkpoints roots) in natural order."""
+    entries = list_checkpoint_entries(folder_path, include_pattern, exclude_pattern)
+    return [name for name, _ in entries]
+
+
+def pick_checkpoint(items: Sequence[T], index: int) -> T:
+    """Return items[index], or raise when the sweep has run past the end.
+
+    Wrapping would silently restart the sweep (and, downstream, archive the
+    grid that just finished), so an over-queued run fails loudly instead.
+    """
+    if not items:
+        raise ValueError("No checkpoints found")
+    if not 0 <= index < len(items):
+        raise ValueError(
+            f"Index {index} is past the end: only {len(items)} checkpoints matched. "
+            "The sweep is complete; reset index to 0 to start a new one."
+        )
+    return items[index]
+
+
+def label_for(ckpt_name: str) -> str:
+    """Label drawn under a tile for this checkpoint. Default: the file stem."""
+    return os.path.splitext(os.path.basename(ckpt_name))[0]

kikotools/tools/checkpoint_folder_iterator/node.py

@@ -0,0 +1,80 @@
+"""Checkpoint Folder Iterator node for ComfyUI."""
+
+from typing import Tuple
+
+from ...base.base_node import ComfyAssetsBaseNode
+from .logic import label_for, list_checkpoint_entries, pick_checkpoint
+
+
+class CheckpointFolderIteratorNode(ComfyAssetsBaseNode):
+    """
+    Load one checkpoint from a folder per queued run.
+
+    Set index to 0 with "increment" and queue as many runs as there are
+    checkpoints: each run loads the next file, so only one model is in
+    memory at a time. A run past the last checkpoint fails with a clear
+    error rather than wrapping around, so over-queuing never restarts the
+    sweep. Pairs with Model Compare Sheet to build a labeled grid.
+    """
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "folder": (
+                    "STRING",
+                    {
+                        "default": ".",
+                        "multiline": False,
+                        "tooltip": "Folder relative to models/checkpoints (or absolute)",
+                    },
+                ),
+                "index": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "min": 0,
+                        "max": 9999,
+                        "control_after_generate": True,
+                        "tooltip": "Which checkpoint to load; errors past the end",
+                    },
+                ),
+            },
+            "optional": {
+                "include_pattern": (
+                    "STRING",
+                    {"default": "", "tooltip": "Regex to include (empty = all)"},
+                ),
+                "exclude_pattern": (
+                    "STRING",
+                    {"default": "", "tooltip": "Regex to exclude (empty = none)"},
+                ),
+            },
+        }
+
+    RETURN_TYPES = ("MODEL", "CLIP", "VAE", "STRING", "STRING", "INT", "INT")
+    RETURN_NAMES = ("model", "clip", "vae", "ckpt_name", "label", "index", "count")
+    FUNCTION = "load"
+    CATEGORY = "🫶 ComfyAssets/🧰 xyz-helpers"
+
+    def load(
+        self,
+        folder: str,
+        index: int,
+        include_pattern: str = "",
+        exclude_pattern: str = "",
+    ) -> Tuple[object, object, object, str, str, int, int]:
+        import folder_paths
+        import comfy.sd
+
+        entries = list_checkpoint_entries(folder, include_pattern, exclude_pattern)
+        ckpt_name, ckpt_path = pick_checkpoint(entries, index)
+        self.log_info(f"Loading {index + 1}/{len(entries)}: {ckpt_name}")
+
+        model, clip, vae = comfy.sd.load_checkpoint_guess_config(
+            ckpt_path,
+            output_vae=True,
+            output_clip=True,
+            embedding_directory=folder_paths.get_folder_paths("embeddings"),
+        )[:3]
+        return model, clip, vae, ckpt_name, label_for(ckpt_name), index, len(entries)

kikotools/tools/display_any/logic.py

@@ -1,6 +1,6 @@
 """Logic for DisplayAny node - displays any input value or tensor shape."""
 
-from typing import Any, List, Union
+from typing import Any, List
 
 
 def get_tensor_shapes(input_value: Any) -> List[List[int]]:
@@ -48,6 +48,15 @@ def format_display_value(input_value: Any, mode: str = "raw value") -> str:
             return "No tensors found in input"
 
     # Default to raw value display
+    # Try to format as JSON for better readability
+    try:
+        import json
+
+        if isinstance(input_value, (dict, list)):
+            return json.dumps(input_value, indent=2)
+    except (TypeError, ValueError):
+        pass
+
     return str(input_value)
 
 

kikotools/tools/display_any/node.py

@@ -1,6 +1,6 @@
 """DisplayAny node for ComfyUI - displays any input value or tensor information."""
 
-from typing import Any, Dict, Tuple
+from typing import Any, Dict
 
 from ...base import ComfyAssetsBaseNode
 from .logic import format_display_value, validate_display_mode
@@ -38,6 +38,7 @@ class DisplayAnyNode(ComfyAssetsBaseNode):
         return True
 
     RETURN_TYPES = ("STRING",)
+    CATEGORY = "🫶 ComfyAssets/👁️ Display"
     RETURN_NAMES = ("display_text",)
     FUNCTION = "display"
     OUTPUT_NODE = True  # This node displays output in the UI
@@ -61,6 +62,6 @@ class DisplayAnyNode(ComfyAssetsBaseNode):
 
         # Return both UI display and result
         return {
-            "ui": {"text": display_text},
+            "ui": {"text": [display_text]},  # UI expects array
             "result": (display_text,),
         }

kikotools/tools/display_text/node.py

@@ -19,7 +19,7 @@ class DisplayTextNode(ComfyAssetsBaseNode):
     RETURN_NAMES = ("text",)
     OUTPUT_NODE = True
     FUNCTION = "display_text"
-    CATEGORY = "ComfyAssets"
+    CATEGORY = "🫶 ComfyAssets/👁️ Display"
 
     DESCRIPTION = """
 Displays text in the UI with a copy-to-clipboard feature.

kikotools/tools/embedding_autocomplete/__init__.py

@@ -0,0 +1,5 @@
+"""Embedding Autocomplete tool for KikoTools."""
+
+from .node import KikoEmbeddingAutocomplete
+
+__all__ = ["KikoEmbeddingAutocomplete"]

kikotools/tools/embedding_autocomplete/node.py

@@ -0,0 +1,291 @@
+"""KikoEmbeddingAutocomplete node for ComfyUI.
+
+Provides autocomplete functionality for embeddings and LoRAs in text inputs.
+"""
+
+import os
+from typing import Dict, List, Any
+
+try:
+    import folder_paths
+except ImportError:
+    # For testing outside ComfyUI environment
+    folder_paths = None
+
+
+class KikoEmbeddingAutocomplete:
+    """Node that provides embedding autocomplete functionality."""
+
+    DISPLAY_NAME = "🫶 Embedding Autocomplete Settings"
+    CATEGORY = "🫶 ComfyAssets"
+
+    # Settings definition for the settings registry
+    SETTINGS = {
+        "enabled": {
+            "type": "boolean",
+            "default": True,
+            "description": "Enable autocomplete",
+        },
+        "show_embeddings": {
+            "type": "boolean",
+            "default": True,
+            "description": "Show embeddings in autocomplete",
+        },
+        "show_loras": {
+            "type": "boolean",
+            "default": True,
+            "description": "Show LoRAs in autocomplete",
+        },
+        "embedding_trigger": {
+            "type": "text",
+            "default": "embedding:",
+            "description": "Trigger text for embeddings (e.g., 'embedding:', 'emb:', or custom)",
+        },
+        "lora_trigger": {
+            "type": "text",
+            "default": "<lora:",
+            "description": "Trigger text for LoRAs (e.g., '<lora:', 'lora:', or custom)",
+        },
+        "quick_trigger": {
+            "type": "text",
+            "default": "em",
+            "description": "Quick trigger to show embeddings (e.g., 'em', 'emb', or disabled with '')",
+        },
+        "min_chars": {
+            "type": "combo",
+            "default": 2,
+            "options": [1, 2, 3, 4, 5],
+            "description": "Minimum characters before showing suggestions",
+        },
+        "max_suggestions": {
+            "type": "combo",
+            "default": 20,
+            "options": [5, 10, 15, 20, 30, 50, 100],
+            "description": "Maximum number of suggestions to display",
+        },
+        "sort_by_directory": {
+            "type": "boolean",
+            "default": True,
+            "description": "Group suggestions by directory",
+        },
+    }
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        """Define input types for the node."""
+        return {
+            "required": {},
+            "hidden": {
+                "unique_id": "UNIQUE_ID",
+            },
+        }
+
+    RETURN_TYPES = ()
+    RETURN_NAMES = ()
+    FUNCTION = "update_settings"
+    OUTPUT_NODE = True
+
+    @classmethod
+    def VALIDATE_INPUTS(cls, **kwargs):
+        return True
+
+    def __init__(self):
+        self.embeddings_cache = None
+        self.loras_cache = None
+
+    def update_settings(self, unique_id=None):
+        """Update settings display.
+
+        This node serves as a settings indicator.
+        Actual settings are configured in ComfyUI Settings menu.
+        """
+        # This node doesn't actually process anything
+        # It's just a visual indicator that autocomplete is available
+        return ()
+
+    def refresh_cache(self):
+        """Refresh the cache of embeddings and LoRAs."""
+        print("[KikoEmbeddingAutocomplete] Refreshing cache...")
+        self.embeddings_cache = self.get_embeddings()
+        self.loras_cache = self.get_loras()
+        print(
+            f"[KikoEmbeddingAutocomplete] Cached {len(self.embeddings_cache)} embeddings, {len(self.loras_cache)} LoRAs"
+        )
+
+    def get_embeddings(self) -> List[Dict[str, Any]]:
+        """Get list of available embeddings."""
+        embeddings = []
+
+        # Get embedding files from ComfyUI's folder system
+        try:
+            print("[KikoEmbeddingAutocomplete] Getting embeddings list...")
+            if folder_paths is None:
+                return embeddings
+            embedding_files = folder_paths.get_filename_list("embeddings")
+            print(
+                f"[KikoEmbeddingAutocomplete] Found {len(embedding_files)} embedding files"
+            )
+            for file in embedding_files:
+                name = os.path.splitext(file)[0]
+                embeddings.append(
+                    {
+                        "name": name,
+                        "file": file,
+                        "type": "embedding",
+                        "display": f"embedding:{name}",
+                        "value": f"embedding:{name}",
+                    }
+                )
+        except Exception as e:
+            print(f"Error loading embeddings: {e}")
+
+        return embeddings
+
+    def get_loras(self) -> List[Dict[str, Any]]:
+        """Get list of available LoRAs."""
+        loras = []
+
+        # Get LoRA files from ComfyUI's folder system
+        try:
+            if folder_paths is None:
+                return loras
+            lora_files = folder_paths.get_filename_list("loras")
+            for file in lora_files:
+                name = os.path.splitext(file)[0]
+                loras.append(
+                    {
+                        "name": name,
+                        "file": file,
+                        "type": "lora",
+                        "display": f"<lora:{name}:1.0>",
+                        "value": f"<lora:{name}:1.0>",
+                    }
+                )
+        except Exception as e:
+            print(f"Error loading LoRAs: {e}")
+
+        return loras
+
+    @classmethod
+    def IS_CHANGED(cls, **kwargs):
+        """Check if the node needs to be re-executed."""
+        # Always re-execute if refresh is True
+        if kwargs.get("refresh", False):
+            return float("NaN")
+
+        # Check if embeddings/loras folders have changed
+        try:
+            if folder_paths is None:
+                return 0
+            embeddings_path = folder_paths.get_folder_paths("embeddings")[0]
+            loras_path = folder_paths.get_folder_paths("loras")[0]
+
+            # Return combined modification time
+            return os.path.getmtime(embeddings_path) + os.path.getmtime(loras_path)
+        except Exception:
+            return 0
+
+
+class KikoEmbeddingAutocompleteAPI:
+    """API endpoints for embedding autocomplete."""
+
+    @staticmethod
+    def get_suggestions(
+        prefix: str,
+        max_results: int = 20,
+        include_embeddings: bool = True,
+        include_loras: bool = True,
+        case_sensitive: bool = False,
+    ) -> List[Dict[str, Any]]:
+        """Get autocomplete suggestions for a given prefix.
+
+        Args:
+            prefix: The text prefix to match
+            max_results: Maximum number of results to return
+            include_embeddings: Include embeddings in results
+            include_loras: Include LoRAs in results
+            case_sensitive: Use case-sensitive matching
+
+        Returns:
+            List of suggestion dictionaries
+        """
+        suggestions = []
+
+        # Normalize prefix for matching
+        match_prefix = prefix if case_sensitive else prefix.lower()
+
+        # Get embeddings
+        if include_embeddings:
+            try:
+                if folder_paths is None:
+                    embedding_files = []
+                else:
+                    embedding_files = folder_paths.get_filename_list("embeddings")
+                for file in embedding_files:
+                    name = os.path.splitext(file)[0]
+                    match_name = name if case_sensitive else name.lower()
+
+                    # Check for match
+                    if match_name.startswith(match_prefix):
+                        suggestions.append(
+                            {
+                                "name": name,
+                                "type": "embedding",
+                                "display": f"embedding:{name}",
+                                "value": f"embedding:{name}",
+                                "priority": 1 if match_name == match_prefix else 0,
+                            }
+                        )
+                    elif match_prefix in match_name:
+                        suggestions.append(
+                            {
+                                "name": name,
+                                "type": "embedding",
+                                "display": f"embedding:{name}",
+                                "value": f"embedding:{name}",
+                                "priority": -1,
+                            }
+                        )
+            except Exception as e:
+                print(f"Error loading embeddings: {e}")
+
+        # Get LoRAs
+        if include_loras:
+            try:
+                if folder_paths is None:
+                    lora_files = []
+                else:
+                    lora_files = folder_paths.get_filename_list("loras")
+                for file in lora_files:
+                    name = os.path.splitext(file)[0]
+                    match_name = name if case_sensitive else name.lower()
+
+                    # Check for match
+                    if match_name.startswith(match_prefix):
+                        suggestions.append(
+                            {
+                                "name": name,
+                                "type": "lora",
+                                "display": f"<lora:{name}:1.0>",
+                                "value": f"<lora:{name}:1.0>",
+                                "priority": 1 if match_name == match_prefix else 0,
+                            }
+                        )
+                    elif match_prefix in match_name:
+                        suggestions.append(
+                            {
+                                "name": name,
+                                "type": "lora",
+                                "display": f"<lora:{name}:1.0>",
+                                "value": f"<lora:{name}:1.0>",
+                                "priority": -1,
+                            }
+                        )
+            except Exception as e:
+                print(f"Error loading LoRAs: {e}")
+
+        # Sort by priority and name
+        suggestions.sort(key=lambda x: (-x["priority"], x["name"]))
+
+        # Limit results
+        return suggestions[:max_results]

kikotools/tools/empty_latent_batch/node.py

@@ -93,14 +93,14 @@ class EmptyLatentBatchNode(ComfyAssetsBaseNode):
             }
         }
 
-    RETURN_TYPES = ("LATENT", "INT", "INT")
-    RETURN_NAMES = ("latent", "width", "height")
+    RETURN_TYPES = ("LATENT", "INT", "INT", "INT")
+    RETURN_NAMES = ("latent", "width", "height", "batch_size")
     FUNCTION = "create_empty_latent"
-    CATEGORY = "ComfyAssets"
+    CATEGORY = "🫶 ComfyAssets/📦 Latents"
 
     def create_empty_latent(
         self, preset: str, width: int, height: int, batch_size: int
-    ) -> Tuple[Dict[str, torch.Tensor], int, int]:
+    ) -> Tuple[Dict[str, torch.Tensor], int, int, int]:
         """
         Create empty latent tensor with specified dimensions and batch size.
 
@@ -111,7 +111,7 @@ class EmptyLatentBatchNode(ComfyAssetsBaseNode):
             batch_size: Number of latents in the batch
 
         Returns:
-            Tuple containing (latent dictionary with 'samples' tensor, width, height)
+            Tuple containing (latent dict, width, height, batch_size)
         """
         try:
             # Extract original preset name from formatted string if needed
@@ -160,7 +160,7 @@ class EmptyLatentBatchNode(ComfyAssetsBaseNode):
                 f"(pixel dims: {final_width}×{final_height})"
             )
 
-            return (latent_dict, final_width, final_height)
+            return (latent_dict, final_width, final_height, batch_size)
 
         except Exception as e:
             # Handle any unexpected errors gracefully

kikotools/tools/gemini_prompt/.gemini_models_cache.json

@@ -1,89 +0,0 @@
-{
-  "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/logic.py

@@ -30,7 +30,7 @@ def tensor_to_pil(tensor: np.ndarray) -> Image.Image:
     image_array = (tensor * 255).astype(np.uint8)
 
     # Convert to PIL
-    return Image.fromarray(image_array, mode="RGB")
+    return Image.fromarray(image_array)
 
 
 def image_to_base64(image: Image.Image, format: str = "PNG") -> str:
@@ -65,7 +65,7 @@ def get_api_key() -> Optional[str]:
                 os.path.dirname(__file__), "..", "..", "..", "gemini_config.json"
             )
             if os.path.exists(config_path):
-                with open(config_path, "r") as f:
+                with open(config_path, "r", encoding="utf-8") as f:
                     config = json.load(f)
                     api_key = config.get("api_key")
         except Exception:
@@ -115,30 +115,24 @@ def analyze_image_with_gemini(
     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
+        from google import genai
     except ImportError:
         return (
             "",
-            "google-generativeai library not installed. Please run: pip install google-generativeai",
+            "google-genai library not installed. Please run: pip install google-genai",
         )
 
     try:
-        # Configure Gemini
-        genai.configure(api_key=api_key)
+        client = genai.Client(api_key=api_key)
 
-        # Create model
-        model = genai.GenerativeModel(model_name)
-
-        # Generate content
-        response = model.generate_content(
-            [
+        response = client.models.generate_content(
+            model=model_name,
+            contents=[
                 system_prompt,
                 pil_image,
                 "Analyze this image and generate an appropriate prompt according to the instructions.",
-            ]
+            ],
         )
 
         # Extract text from response

kikotools/tools/gemini_prompt/models.py

@@ -59,10 +59,10 @@ def _fetch_models_from_api(
         Tuple of (model_names_list, model_descriptions_dict)
     """
     try:
-        import google.generativeai as genai
+        from google import genai
     except ImportError:
         if not silent:
-            logger.error("google-generativeai not installed")
+            logger.error("google-genai not installed")
         return [], {}
 
     # Get API key
@@ -77,15 +77,15 @@ def _fetch_models_from_api(
         return [], {}
 
     try:
-        genai.configure(api_key=api_key)
+        client = genai.Client(api_key=api_key)
 
         models = []
         descriptions = {}
 
         # Fetch all models
-        for model in genai.list_models():
+        for model in client.models.list():
             # Only include models that support generateContent
-            if "generateContent" in model.supported_generation_methods:
+            if "generateContent" in (model.supported_actions or []):
                 # Remove "models/" prefix from name
                 model_name = model.name.replace("models/", "")
                 models.append(model_name)
@@ -154,7 +154,7 @@ def _load_cache() -> Optional[Dict]:
         return None
 
     try:
-        with open(CACHE_FILE, "r") as f:
+        with open(CACHE_FILE, "r", encoding="utf-8") as f:
             data = json.load(f)
 
         # Check if cache is expired
@@ -176,7 +176,7 @@ def _save_cache(models: List[str], descriptions: Dict[str, str]) -> None:
             "timestamp": time.time(),
         }
 
-        with open(CACHE_FILE, "w") as f:
+        with open(CACHE_FILE, "w", encoding="utf-8") as f:
             json.dump(data, f, indent=2)
     except Exception as e:
         logger.warning(f"Failed to save cache: {e}")

kikotools/tools/gemini_prompt/node.py

@@ -51,7 +51,7 @@ class GeminiPromptNode(ComfyAssetsBaseNode):
     RETURN_TYPES = ("STRING", "STRING")
     RETURN_NAMES = ("prompt", "negative_prompt")
     FUNCTION = "generate_prompt"
-    CATEGORY = "ComfyAssets"
+    CATEGORY = "🫶 ComfyAssets/🧠 Prompts"
 
     DESCRIPTION = """
 Analyzes images using Google's Gemini AI to generate optimized prompts.
@@ -63,7 +63,7 @@ Supports multiple prompt formats:
 - 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
+Install: pip install google-genai
 """
 
     def generate_prompt(

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 +1,87 @@
+"""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",)
+    CATEGORY = "🫶 ComfyAssets/🖼️ Resolution"
+    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}")