When a prompt is submitted, it can optionally include
`partial_execution_targets` as a list of ids. If it does, rather than
adding all outputs to the execution list, we add only those in the list.
* ComfyAPI Core v0.0.2
* Respond to PR feedback
* Fix Python 3.9 errors
* Fix missing backward compatibility proxy
* Reorganize types a bit
The input types, input impls, and utility types are now all available in
the versioned API. See the change in `comfy_extras/nodes_video.py` for
an example of their usage.
* Remove the need for `--generate-api-stubs`
* Fix generated stubs differing by Python version
* Fix ruff formatting issues
- add xet support and add the xet cache to manageable directories
- xet is enabled by default
- fix logging to root in various places
- improve logging about model unloading and loading
- TorchCompileNode now supports the VAE
- torchaudio missing will cause less noise in the logs
- feature flags will assume to be supporting everything in the distributed progress context
- fixes progress notifications
* Support for async execution functions
This commit adds support for node execution functions defined as async. When
a node's execution function is defined as async, we can continue
executing other nodes while it is processing.
Standard uses of `await` should "just work", but people will still have
to be careful if they spawn actual threads. Because torch doesn't really
have async/await versions of functions, this won't particularly help
with most locally-executing nodes, but it does work for e.g. web
requests to other machines.
In addition to the execute function, the `VALIDATE_INPUTS` and
`check_lazy_status` functions can also be defined as async, though we'll
only resolve one node at a time right now for those.
* Add the execution model tests to CI
* Add a missing file
It looks like this got caught by .gitignore? There's probably a better
place to put it, but I'm not sure what that is.
* Add the websocket library for automated tests
* Add additional tests for async error cases
Also fixes one bug that was found when an async function throws an error
after being scheduled on a task.
* Add a feature flags message to reduce bandwidth
We now only send 1 preview message of the latest type the client can
support.
We'll add a console warning when the client fails to send a feature
flags message at some point in the future.
* Add async tests to CI
* Don't actually add new tests in this PR
Will do it in a separate PR
* Resolve unit test in GPU-less runner
* Just remove the tests that GHA can't handle
* Change line endings to UNIX-style
* Avoid loading model_management.py so early
Because model_management.py has a top-level `logging.info`, we have to
be careful not to import that file before we call `setup_logging`. If we
do, we end up having the default logging handler registered in addition
to our custom one.
- Cosmos now fully tested
- Preliminary support for essential Cosmos prompt "upsampler"
- Lumina tests
- Tweaks to language and image resizing nodes
- Fix for #31 all the samplers are now present again
- --panics-when=torch.cuda.OutOfMemory will now correctly panic and
exit the worker, giving it time to reply that the execution failed
and better dealing with irrecoverable out-of-memory errors
- --executor-factory=ProcessPoolExecutor will use a process instead of
a thread to execute comfyui workflows when using the worker. When
this process panics and exits, it will be correctly replaced, making
a more robust worker
- export_custom_nodes() finds all the classes that inherit from
CustomNode and exports them correctly for custom node discovery to
find
- regular expressions
- additional string formatting and parsing nodes
- fix#29 str(model) no longer raises exceptions like with
HyVideoModelLoader
- don't try to format CUDA tensors because that can sometimes raise
exceptions
- cudaAllocAsync has been disabled for now due to 2.6.0 bugs
- improve florence2 support
- add support for paligemma 2. This requires the fix for transformers
that is currently staged in another repo, install with
`uv pip install --no-deps "transformers@git+https://github.com/zucchini-nlp/transformers.git#branch=paligemma-fix-kwargs"`
- triton has been updated
- fix missing __init__.py files
- use their logger when running interactively
- move the extra nodes files to where this fork expects them
- add the mochi checkpoints to known models
- add a mochi workflow test
- Adding the output paths now correctly registers a relative path,
i.e., outputs/loras and models/lorals will now be searched on all
your base paths
- Adding absolute paths with models/ works better
- All the base paths and directories are queried better
- Validation errors that occur early in the lifecycle of prompt
execution now get propagated to their callers in the
EmbeddedComfyClient. This includes error messages about missing node
classes.
- The execution context now includes the node_id and the prompt_id
- Latent previews are now sent with a node_id. This is not backwards
compatible with old frontends.
- Dependency execution errors are now modeled correctly.
- Distributed progress encodes image previews with node and prompt IDs.
- Typing for models
- The frontend was updated to use node IDs with previews
- Improvements to torch.compile experiments
- Some controlnet_aux nodes were upstreamed
Currently, if a graph partially fails validation (i.e. some outputs are
valid while others have links from missing nodes), the execution loop
could get an exception resulting in server lockup.
This isn't actually possible to reproduce via the default UI, but is a
potential issue for people using the API to construct invalid graphs.
This change fixes a bug where non-constant values could be passed to the
IS_CHANGED function. This would result in workflows taking an extra
execution before they acted as if they were cached.
The actual change is like 4 characters -- the rest is adding unit tests.
