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Author SHA1 Message Date
Talmaj
54a13a0486
Merge 3b1c60b4ba into 025e6792ee 2026-05-03 08:55:16 -07:00
Jukka Seppänen
025e6792ee
Batch broadcasting in JoinImageWithAlpha node (#13686)
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* Batch broadcasting in JoinImageWithAlpha node
2026-05-03 16:30:00 +03:00
Luke Mino-Altherr
867b8d2408
fix: gracefully handle port-in-use error on server startup (#13001)
Catch EADDRINUSE OSError when binding the TCP site and exit with a clear error message instead of an unhandled traceback.
2026-05-03 20:44:20 +08:00
Alexis Rolland
d0f0b15cf5
Update ComfyUI screenshot in README (#13683)
Update ComfyUI screenshot to showcase a more modern workflow
2026-05-03 18:48:58 +08:00
Alexis Rolland
b5bb83c964
Fix issue blend images with alpha (#13615)
Make ImageBlend and ImageCompositeMasked nodes handle images with different channel counts
2026-05-03 18:17:08 +08:00
Alexis Rolland
f6d5068ac0
Update README (#13679)
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Updated the README to include a new screenshot, improved description and add Ernie Image to supported models.
2026-05-03 12:20:17 +08:00
Talmaj Marinc
3b1c60b4ba Add test that each model has unique identifiers CORE-134 2026-05-01 11:51:53 +02:00
5 changed files with 56 additions and 13 deletions

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@ -1,7 +1,7 @@
<div align="center">
# ComfyUI
**The most powerful and modular visual AI engine and application.**
**The most powerful and modular AI engine for content creation.**
[![Website][website-shield]][website-url]
@ -31,10 +31,16 @@
[github-downloads-latest-shield]: https://img.shields.io/github/downloads/comfyanonymous/ComfyUI/latest/total?style=flat&label=downloads%40latest
[github-downloads-link]: https://github.com/comfyanonymous/ComfyUI/releases
![ComfyUI Screenshot](https://github.com/user-attachments/assets/7ccaf2c1-9b72-41ae-9a89-5688c94b7abe)
<img width="1590" height="795" alt="ComfyUI Screenshot" src="https://github.com/user-attachments/assets/36e065e0-bfae-4456-8c7f-8369d5ea48a2" />
<br>
</div>
ComfyUI lets you design and execute advanced stable diffusion pipelines using a graph/nodes/flowchart based interface. Available on Windows, Linux, and macOS.
ComfyUI is the AI creation engine for visual professionals who demand control over every model, every parameter, and every output. Its powerful and modular node graph interface empowers creatives to generate images, videos, 3D models, audio, and more...
- ComfyUI natively supports the latest open-source state of the art models.
- API nodes provide access to the best closed source models such as Nano Banana, Seedance, Hunyuan3D, etc.
- It is available on Windows, Linux, and macOS, locally with our desktop application or on our cloud.
- The most sophisticated workflows can be exposed through a simple UI thanks to App Mode.
- It integrates seamlessly into production pipelines with our API endpoints.
## Get Started
@ -77,6 +83,7 @@ See what ComfyUI can do with the [newer template workflows](https://comfy.org/wo
- [Hunyuan Image 2.1](https://comfyanonymous.github.io/ComfyUI_examples/hunyuan_image/)
- [Flux 2](https://comfyanonymous.github.io/ComfyUI_examples/flux2/)
- [Z Image](https://comfyanonymous.github.io/ComfyUI_examples/z_image/)
- Ernie Image
- Image Editing Models
- [Omnigen 2](https://comfyanonymous.github.io/ComfyUI_examples/omnigen/)
- [Flux Kontext](https://comfyanonymous.github.io/ComfyUI_examples/flux/#flux-kontext-image-editing-model)

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@ -202,14 +202,11 @@ class JoinImageWithAlpha(io.ComfyNode):
@classmethod
def execute(cls, image: torch.Tensor, alpha: torch.Tensor) -> io.NodeOutput:
batch_size = min(len(image), len(alpha))
out_images = []
batch_size = max(len(image), len(alpha))
alpha = 1.0 - resize_mask(alpha, image.shape[1:])
for i in range(batch_size):
out_images.append(torch.cat((image[i][:,:,:3], alpha[i].unsqueeze(2)), dim=2))
return io.NodeOutput(torch.stack(out_images))
alpha = comfy.utils.repeat_to_batch_size(alpha, batch_size)
image = comfy.utils.repeat_to_batch_size(image, batch_size)
return io.NodeOutput(torch.cat((image[..., :3], alpha.unsqueeze(-1)), dim=-1))
class CompositingExtension(ComfyExtension):

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@ -86,6 +86,6 @@ def image_alpha_fix(destination, source):
if destination.shape[-1] < source.shape[-1]:
source = source[...,:destination.shape[-1]]
elif destination.shape[-1] > source.shape[-1]:
destination = torch.nn.functional.pad(destination, (0, 1))
destination[..., -1] = 1.0
source = torch.nn.functional.pad(source, (0, 1))
source[..., -1] = 1.0
return destination, source

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@ -1,3 +1,4 @@
import errno
import os
import sys
import asyncio
@ -1245,7 +1246,13 @@ class PromptServer():
address = addr[0]
port = addr[1]
site = web.TCPSite(runner, address, port, ssl_context=ssl_ctx)
await site.start()
try:
await site.start()
except OSError as e:
if e.errno == errno.EADDRINUSE:
logging.error(f"Port {port} is already in use on address {address}. Please close the other application or use a different port with --port.")
raise SystemExit(1)
raise
if not hasattr(self, 'address'):
self.address = address #TODO: remove this

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@ -1,9 +1,23 @@
from collections import defaultdict
import torch
from comfy.model_detection import detect_unet_config, model_config_from_unet_config
import comfy.supported_models
def _freeze(value):
"""Recursively convert a value to a hashable form so configs can be
compared/used as dict keys or set members."""
if isinstance(value, dict):
return frozenset((k, _freeze(v)) for k, v in value.items())
if isinstance(value, (list, tuple)):
return tuple(_freeze(v) for v in value)
if isinstance(value, set):
return frozenset(_freeze(v) for v in value)
return value
def _make_longcat_comfyui_sd():
"""Minimal ComfyUI-format state dict for pre-converted LongCat-Image weights."""
sd = {}
@ -110,3 +124,21 @@ class TestModelDetection:
model_config = model_config_from_unet_config(unet_config, sd)
assert model_config is not None
assert type(model_config).__name__ == "FluxSchnell"
def test_unet_config_and_required_keys_combination_is_unique(self):
"""Each model in the registry must have a unique combination of
``unet_config`` and ``required_keys``. If two models share the same
combination, ``BASE.matches`` cannot disambiguate between them and the
first one in the list will always win."""
models = comfy.supported_models.models
groups = defaultdict(list)
for model in models:
key = (_freeze(model.unet_config), _freeze(model.required_keys))
groups[key].append(model.__name__)
duplicates = {k: names for k, names in groups.items() if len(names) > 1}
assert not duplicates, (
"Found models sharing the same (unet_config, required_keys) "
"combination, which makes detection ambiguous: "
+ "; ".join(", ".join(names) for names in duplicates.values())
)