- An override family could declare a step such as 3; sizes rounded to it
are not divisible by 8, so create_empty_latent_batch raised ValueError
at execution instead of producing a latent (Codex review on PR #108).
- validate_table now rejects a step that is not a multiple of 8 with a
message naming the latent grid; the shipped steps (16, 32, 64) already
comply, and the schema docs state the rule.
- New nodes started at a fixed 340×600, so one-entry size lists left a
large empty area between the list and the Swap button.
- The panel now reports its measured content height as both the minimum
and maximum DOM-widget height, and the extension sets the node height to
the host's computeSize() after every render, keeping the width.
- Hidden or detached panels are not measured, the first measurement is
retried for a few frames, and a ResizeObserver on the panel children
refits when the stylesheet arrives after the first render (the coverage
run exposed that race; a held-stylesheet regression test pins it).
- Workflows load at their saved width and are re-fitted on load; the spec
and docs describe the new sizing rule.
- edits show up on a page reload or Refresh node definitions, not on the
next node mount, because the frontend caches the payload per page
- the 14 count refers to shipped families; an override can add or remove
- replace the {ex} placeholder with a real override example validated against validate_table
- list the loading state among the cases that show custom
- say the override default may be a label or alias
- describe the families.json schema and the user override file with a full example
- document the warnings behaviour and resolution dropdown precedence
- add the dropdown sync rule to web/ui/README.md
- VALIDATE_INPUTS lets unknown family labels reach create()
- no size is listed under two chips; SD 1.5 3:4 gets true 3:4 sizes
- model change before the families payload loads is applied on load
- custom ratio: clear error on chip click, cap sides at 8192, accept X
- real-host assertions for model change and wired-in state
- name Flux.2 / Klein / MOSS at 1248x832 and HunyuanImage 2.1 at 2560x1536
- require saved PNG dimensions to match the node outputs, recorded in the PR
- add README tools row, section and status row
- add ui-migration row and web/ui README section
- add per-node doc with family table and manual GPU check
- google-generativeai is deprecated and emits a FutureWarning at node
load; google-genai is Google's supported replacement
- Image analysis now uses genai.Client().models.generate_content
instead of the module-level configure/GenerativeModel API
- Model listing reads supported_actions, the new SDK's name for
supported_generation_methods
- Install instructions, requirements.txt, and README updated to the
new package name
- Add auto-batching functionality to split large LoRA collections into manageable chunks
- Implement batch_size parameter to control number of LoRAs per batch (default: 25)
- Add batch_index parameter to select which batch to process
- Include batch tracking metadata in LORA_PARAMS for visualization
- Display batch info in plot parameters when available
- Update lora_list output to show batch header when auto-batching is enabled
- Add comprehensive tests for batching functionality
- Update documentation with detailed auto-batching usage instructions
This feature prevents UI disconnection issues when processing large numbers of LoRAs
by allowing users to process them in smaller batches sequentially.
- Implement film grain effect with customizable parameters (scale, strength, saturation, toe, seed)
- Use pure PyTorch operations for better GPU utilization (no OpenCV dependencies)
- Apply ITU-R BT.709 color space conversion for accurate grain distribution
- Implement screen blend mode for better highlight preservation
- Add channel-specific weighting matching real film characteristics (3x blue, 2x red)
- Preserve alpha channel when present
- Add comprehensive test suite (20 tests covering all functionality)
- Include documentation and example workflow
- Register node under ComfyAssets/image category
Improvements over reference implementation:
- More efficient memory management avoiding numpy/OpenCV conversions
- Better grain mixing algorithm with proper color science
- Improved performance through PyTorch-native operations
BREAKING CHANGE: Node categories now use emoji-based organization
Add 6 new xyz-helper nodes adapted from comfyui-essentials-nodes:
- FluxSamplerParams: FLUX-optimized parameter generator with batch support
- LoRAFolderBatch: Batch process multiple LoRAs from folders
- PlotParameters: Visualize parameter effects with graphs
- SamplerSelectHelper: Intelligent sampler selection with recommendations
- SchedulerSelectHelper: Optimal scheduler selection for samplers
- TextEncodeSamplerParams: Combined text encoding and parameter management
Changes:
- Port and enhance nodes from comfyui-essentials (now in maintenance mode)
- Add comprehensive documentation with attribution to original author (cubiq)
- Create example workflows for xyz-helpers tools
- Update all node categories to use emoji-based organization
- Fix all unit tests to pass with new category system
- Update README with xyz-helpers section and attribution
Attribution: xyz-helpers adapted from github.com/cubiq/ComfyUI_essentials
All tests passing (318 pass, 2 skip)
- Add PNG screenshots for 7 nodes in README.md
- Create missing documentation files (display_text.md, kiko_save_image.md)
- Update gemini_prompt.md with new features (model refresh, enhanced SDXL)
- Add missing example workflow JSON files for 5 nodes
- Include Display Any and Image to Multiple Of nodes in README
- Update node count from 8 to 10 in stats section
- Universal input acceptance for any data type
- Two display modes: raw value and tensor shape
- Extracts tensor shapes from nested structures
- Comprehensive unit tests with 100% coverage
- Full documentation with usage examples
- OUTPUT_NODE for UI display functionality
- Add GeminiPromptNode for AI-powered prompt engineering
- Integrates with Google's Gemini API for prompt generation
- Includes various prompt templates and generation modes
- Add comprehensive tests and documentation
- Register node in ComfyAssets category
- Add code quality tools: flake8, mypy, black, pre-commit
- Add .gitattributes for line ending consistency
- Add .secrets.baseline for secret scanning
- Update GitHub workflows for better CI/CD
- Update documentation formatting and examples
- Add CLAUDE.md for AI assistant guidance
- Add scripts directory for automation tools
- Update project configuration in pyproject.toml
- Improve type hints and code formatting across all modules
- Update test configurations and fixtures
- Add ImageToMultipleOfNode for image dimension adjustment
- Ensures image dimensions are multiples of specified values
- Supports both padding and cropping modes
- Useful for model-specific dimension requirements
- Add tests and documentation
- Register node in ComfyAssets category
Vito Sansevero