- Currently uses `transformers`
- Supports model management and correctly loading and unloading models
based on what your machine can support
- Includes a Text Diffusers 2 workflow to demonstrate text rendering in
SD1.5
- ComfyUI can now load EXR files.
- There are new arithmetic nodes for floats and integers.
- EXR nodes can load depth maps and be remapped with
ImageApplyColormap. This allows end users to use ground truth depth
data from video game engines or 3D graphics tools and recolor it to
the format expected by depth ControlNets: grayscale inverse depth
maps and "inferno" colored inverse depth maps.
- Fixed license notes.
- Added an additional known ControlNet model.
- Because CV2 is now used to read OpenEXR files, an environment
variable must be set early on in the application, before CV2 is
imported. This file, main_pre, is now imported early on in more
places.
- Removed /api/v1/images because you should use your own CDN style
image host and /view for maximum compatibility
- The /api/v1/prompts POST application/json response will now return
the outputs dictionary
- Caching has been removed
- More tests
- Subdirectory prefixes are now supported
- Fixed an issue where a Linux frontend and Windows backend would have
paths that could not interact with each other correctly
- Improve node loading order. It now occurs "as late as possible".
Configuration should be exposed as per the README.
- Added methods to specify custom folders and models used in examples
more robustly for custom nodes.
- Downloading models can now be gracefully interrupted.
- Progress notifications are now sent over the network for distributed
ComfyUI operations.
- Python objects have been moved around to prevent less transitive
package importing issues.
- Run comfyui workflows directly inside other python applications using
EmbeddedComfyClient.
- Optional telemetry in prompts and models using anonymity preserving
Plausible self-hosted or hosted.
- Better OpenAPI schema
- Basic support for distributed ComfyUI backends. Limitations: no
progress reporting, no easy way to start your own distributed
backend, requires RabbitMQ as a message broker.
