chore: fetch upstream update

This commit is contained in:
kallen 2024-11-19 15:44:51 +08:00
commit 6107d8d328
73 changed files with 44497 additions and 32734 deletions

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@ -28,7 +28,7 @@
[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](comfyui_screenshot.png)
![ComfyUI Screenshot](https://github.com/user-attachments/assets/7ccaf2c1-9b72-41ae-9a89-5688c94b7abe)
</div>
This ui will let you design and execute advanced stable diffusion pipelines using a graph/nodes/flowchart based interface. For some workflow examples and see what ComfyUI can do you can check out:

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@ -2,6 +2,7 @@ from aiohttp import web
from typing import Optional
from folder_paths import models_dir, user_directory, output_directory, folder_names_and_paths
from api_server.services.file_service import FileService
from api_server.services.terminal_service import TerminalService
import app.logger
class InternalRoutes:
@ -11,7 +12,8 @@ class InternalRoutes:
Check README.md for more information.
'''
def __init__(self):
def __init__(self, prompt_server):
self.routes: web.RouteTableDef = web.RouteTableDef()
self._app: Optional[web.Application] = None
self.file_service = FileService({
@ -19,6 +21,8 @@ class InternalRoutes:
"user": user_directory,
"output": output_directory
})
self.prompt_server = prompt_server
self.terminal_service = TerminalService(prompt_server)
def setup_routes(self):
@self.routes.get('/files')
@ -34,7 +38,28 @@ class InternalRoutes:
@self.routes.get('/logs')
async def get_logs(request):
return web.json_response(app.logger.get_logs())
return web.json_response("".join([(l["t"] + " - " + l["m"]) for l in app.logger.get_logs()]))
@self.routes.get('/logs/raw')
async def get_logs(request):
self.terminal_service.update_size()
return web.json_response({
"entries": list(app.logger.get_logs()),
"size": {"cols": self.terminal_service.cols, "rows": self.terminal_service.rows}
})
@self.routes.patch('/logs/subscribe')
async def subscribe_logs(request):
json_data = await request.json()
client_id = json_data["clientId"]
enabled = json_data["enabled"]
if enabled:
self.terminal_service.subscribe(client_id)
else:
self.terminal_service.unsubscribe(client_id)
return web.Response(status=200)
@self.routes.get('/folder_paths')
async def get_folder_paths(request):

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@ -0,0 +1,47 @@
from app.logger import on_flush
import os
class TerminalService:
def __init__(self, server):
self.server = server
self.cols = None
self.rows = None
self.subscriptions = set()
on_flush(self.send_messages)
def update_size(self):
sz = os.get_terminal_size()
changed = False
if sz.columns != self.cols:
self.cols = sz.columns
changed = True
if sz.lines != self.rows:
self.rows = sz.lines
changed = True
if changed:
return {"cols": self.cols, "rows": self.rows}
return None
def subscribe(self, client_id):
self.subscriptions.add(client_id)
def unsubscribe(self, client_id):
self.subscriptions.discard(client_id)
def send_messages(self, entries):
if not len(entries) or not len(self.subscriptions):
return
new_size = self.update_size()
for client_id in self.subscriptions.copy(): # prevent: Set changed size during iteration
if client_id not in self.server.sockets:
# Automatically unsub if the socket has disconnected
self.unsubscribe(client_id)
continue
self.server.send_sync("logs", {"entries": entries, "size": new_size}, client_id)

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@ -1,6 +1,9 @@
import io
import sys
import logging
from logging.handlers import MemoryHandler
import threading
from collections import deque
from datetime import datetime
from rich import pretty
from rich.theme import Theme
from rich.console import Console
@ -8,12 +11,52 @@ from rich.logging import RichHandler
logs = None
stdout_interceptor = None
stderr_interceptor = None
LOGFMT = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)s] %(message)s"
formatter = logging.Formatter(LOGFMT)
class LogInterceptor(io.TextIOWrapper):
def __init__(self, stream, *args, **kwargs):
buffer = stream.buffer
encoding = stream.encoding
super().__init__(buffer, *args, **kwargs, encoding=encoding, line_buffering=stream.line_buffering)
self._lock = threading.Lock()
self._flush_callbacks = []
self._logs_since_flush = []
def write(self, data):
entry = {"t": datetime.now().isoformat(), "m": data}
with self._lock:
self._logs_since_flush.append(entry)
# Simple handling for cr to overwrite the last output if it isnt a full line
# else logs just get full of progress messages
if isinstance(data, str) and data.startswith("\r") and not logs[-1]["m"].endswith("\n"):
logs.pop()
logs.append(entry)
super().write(data)
def flush(self):
super().flush()
for cb in self._flush_callbacks:
cb(self._logs_since_flush)
self._logs_since_flush = []
def on_flush(self, callback):
self._flush_callbacks.append(callback)
def get_logs():
return "\n".join([formatter.format(x) for x in logs])
return logs
def on_flush(callback):
if stdout_interceptor is not None:
stdout_interceptor.on_flush(callback)
if stderr_interceptor is not None:
stderr_interceptor.on_flush(callback)
def setup_logger(log_level: str = 'INFO', capacity: int = 300):
@ -21,6 +64,14 @@ def setup_logger(log_level: str = 'INFO', capacity: int = 300):
if logs:
return
# Override output streams and log to buffer
logs = deque(maxlen=capacity)
global stdout_interceptor
global stderr_interceptor
stdout_interceptor = sys.stdout = LogInterceptor(sys.stdout)
stderr_interceptor = sys.stderr = LogInterceptor(sys.stderr)
# Setup default global logger
logger = logging.getLogger()
logger.setLevel(log_level)
@ -28,13 +79,6 @@ def setup_logger(log_level: str = 'INFO', capacity: int = 300):
stream_handler = get_rich_hander(log_level)
logger.addHandler(stream_handler)
# Create a memory handler with a deque as its buffer
logs = deque(maxlen=capacity)
memory_handler = MemoryHandler(capacity, flushLevel=logging.INFO)
memory_handler.buffer = logs
memory_handler.setFormatter(formatter)
logger.addHandler(memory_handler)
def get_rich_hander(log_level: str = "INFO") -> RichHandler:
console = Console(

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@ -1,3 +1,4 @@
from __future__ import annotations
import json
import os
import re

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@ -190,7 +190,21 @@ class Mochi(LatentFormat):
0.9294154431013696, 1.3720942357788521, 0.881393668867029,
0.9168315692124348, 0.9185249279345552, 0.9274757570805041]).view(1, self.latent_channels, 1, 1, 1)
self.latent_rgb_factors = None #TODO
self.latent_rgb_factors =[
[-0.0069, -0.0045, 0.0018],
[ 0.0154, -0.0692, -0.0274],
[ 0.0333, 0.0019, 0.0206],
[-0.1390, 0.0628, 0.1678],
[-0.0725, 0.0134, -0.1898],
[ 0.0074, -0.0270, -0.0209],
[-0.0176, -0.0277, -0.0221],
[ 0.5294, 0.5204, 0.3852],
[-0.0326, -0.0446, -0.0143],
[-0.0659, 0.0153, -0.0153],
[ 0.0185, -0.0217, 0.0014],
[-0.0396, -0.0495, -0.0281]
]
self.latent_rgb_factors_bias = [-0.0940, -0.1418, -0.1453]
self.taesd_decoder_name = None #TODO
def process_in(self, latent):

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@ -437,7 +437,8 @@ class MMDiT(nn.Module):
pos_encoding = pos_encoding[:,from_h:from_h+h,from_w:from_w+w]
return x + pos_encoding.reshape(1, -1, self.positional_encoding.shape[-1])
def forward(self, x, timestep, context, **kwargs):
def forward(self, x, timestep, context, transformer_options={}, **kwargs):
patches_replace = transformer_options.get("patches_replace", {})
# patchify x, add PE
b, c, h, w = x.shape
@ -458,15 +459,36 @@ class MMDiT(nn.Module):
global_cond = self.t_embedder(t, x.dtype) # B, D
blocks_replace = patches_replace.get("dit", {})
if len(self.double_layers) > 0:
for layer in self.double_layers:
c, x = layer(c, x, global_cond, **kwargs)
for i, layer in enumerate(self.double_layers):
if ("double_block", i) in blocks_replace:
def block_wrap(args):
out = {}
out["txt"], out["img"] = layer(args["txt"],
args["img"],
args["vec"])
return out
out = blocks_replace[("double_block", i)]({"img": x, "txt": c, "vec": global_cond}, {"original_block": block_wrap})
c = out["txt"]
x = out["img"]
else:
c, x = layer(c, x, global_cond, **kwargs)
if len(self.single_layers) > 0:
c_len = c.size(1)
cx = torch.cat([c, x], dim=1)
for layer in self.single_layers:
cx = layer(cx, global_cond, **kwargs)
for i, layer in enumerate(self.single_layers):
if ("single_block", i) in blocks_replace:
def block_wrap(args):
out = {}
out["img"] = layer(args["img"], args["vec"])
return out
out = blocks_replace[("single_block", i)]({"img": cx, "vec": global_cond}, {"original_block": block_wrap})
cx = out["img"]
else:
cx = layer(cx, global_cond, **kwargs)
x = cx[:, c_len:]

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@ -96,7 +96,9 @@ class Flux(nn.Module):
y: Tensor,
guidance: Tensor = None,
control=None,
transformer_options={},
) -> Tensor:
patches_replace = transformer_options.get("patches_replace", {})
if img.ndim != 3 or txt.ndim != 3:
raise ValueError("Input img and txt tensors must have 3 dimensions.")
@ -114,8 +116,19 @@ class Flux(nn.Module):
ids = torch.cat((txt_ids, img_ids), dim=1)
pe = self.pe_embedder(ids)
blocks_replace = patches_replace.get("dit", {})
for i, block in enumerate(self.double_blocks):
img, txt = block(img=img, txt=txt, vec=vec, pe=pe)
if ("double_block", i) in blocks_replace:
def block_wrap(args):
out = {}
out["img"], out["txt"] = block(img=args["img"], txt=args["txt"], vec=args["vec"], pe=args["pe"])
return out
out = blocks_replace[("double_block", i)]({"img": img, "txt": txt, "vec": vec, "pe": pe}, {"original_block": block_wrap})
txt = out["txt"]
img = out["img"]
else:
img, txt = block(img=img, txt=txt, vec=vec, pe=pe)
if control is not None: # Controlnet
control_i = control.get("input")
@ -127,7 +140,16 @@ class Flux(nn.Module):
img = torch.cat((txt, img), 1)
for i, block in enumerate(self.single_blocks):
img = block(img, vec=vec, pe=pe)
if ("single_block", i) in blocks_replace:
def block_wrap(args):
out = {}
out["img"] = block(args["img"], vec=args["vec"], pe=args["pe"])
return out
out = blocks_replace[("single_block", i)]({"img": img, "vec": vec, "pe": pe}, {"original_block": block_wrap})
img = out["img"]
else:
img = block(img, vec=vec, pe=pe)
if control is not None: # Controlnet
control_o = control.get("output")
@ -141,7 +163,7 @@ class Flux(nn.Module):
img = self.final_layer(img, vec) # (N, T, patch_size ** 2 * out_channels)
return img
def forward(self, x, timestep, context, y, guidance, control=None, **kwargs):
def forward(self, x, timestep, context, y, guidance, control=None, transformer_options={}, **kwargs):
bs, c, h, w = x.shape
patch_size = 2
x = comfy.ldm.common_dit.pad_to_patch_size(x, (patch_size, patch_size))
@ -156,5 +178,5 @@ class Flux(nn.Module):
img_ids = repeat(img_ids, "h w c -> b (h w) c", b=bs)
txt_ids = torch.zeros((bs, context.shape[1], 3), device=x.device, dtype=x.dtype)
out = self.forward_orig(img, img_ids, context, txt_ids, timestep, y, guidance, control)
out = self.forward_orig(img, img_ids, context, txt_ids, timestep, y, guidance, control, transformer_options)
return rearrange(out, "b (h w) (c ph pw) -> b c (h ph) (w pw)", h=h_len, w=w_len, ph=2, pw=2)[:,:,:h,:w]

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@ -494,8 +494,9 @@ class AsymmDiTJoint(nn.Module):
packed_indices: Dict[str, torch.Tensor] = None,
rope_cos: torch.Tensor = None,
rope_sin: torch.Tensor = None,
control=None, **kwargs
control=None, transformer_options={}, **kwargs
):
patches_replace = transformer_options.get("patches_replace", {})
y_feat = context
y_mask = attention_mask
sigma = timestep
@ -515,15 +516,32 @@ class AsymmDiTJoint(nn.Module):
)
del y_mask
blocks_replace = patches_replace.get("dit", {})
for i, block in enumerate(self.blocks):
x, y_feat = block(
x,
c,
y_feat,
rope_cos=rope_cos,
rope_sin=rope_sin,
crop_y=num_tokens,
) # (B, M, D), (B, L, D)
if ("double_block", i) in blocks_replace:
def block_wrap(args):
out = {}
out["img"], out["txt"] = block(
args["img"],
args["vec"],
args["txt"],
rope_cos=args["rope_cos"],
rope_sin=args["rope_sin"],
crop_y=args["num_tokens"]
)
return out
out = blocks_replace[("double_block", i)]({"img": x, "txt": y_feat, "vec": c, "rope_cos": rope_cos, "rope_sin": rope_sin, "num_tokens": num_tokens}, {"original_block": block_wrap})
y_feat = out["txt"]
x = out["img"]
else:
x, y_feat = block(
x,
c,
y_feat,
rope_cos=rope_cos,
rope_sin=rope_sin,
crop_y=num_tokens,
) # (B, M, D), (B, L, D)
del y_feat # Final layers don't use dense text features.
x = self.final_layer(x, c) # (B, M, patch_size ** 2 * out_channels)

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@ -321,8 +321,9 @@ def model_config_from_unet(state_dict, unet_key_prefix, use_base_if_no_match=Fal
if model_config is None and use_base_if_no_match:
model_config = comfy.supported_models_base.BASE(unet_config)
scaled_fp8_weight = state_dict.get("{}scaled_fp8".format(unet_key_prefix), None)
if scaled_fp8_weight is not None:
scaled_fp8_key = "{}scaled_fp8".format(unet_key_prefix)
if scaled_fp8_key in state_dict:
scaled_fp8_weight = state_dict.pop(scaled_fp8_key)
model_config.scaled_fp8 = scaled_fp8_weight.dtype
if model_config.scaled_fp8 == torch.float32:
model_config.scaled_fp8 = torch.float8_e4m3fn

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@ -2,6 +2,25 @@ import torch
from comfy.ldm.modules.diffusionmodules.util import make_beta_schedule
import math
def rescale_zero_terminal_snr_sigmas(sigmas):
alphas_cumprod = 1 / ((sigmas * sigmas) + 1)
alphas_bar_sqrt = alphas_cumprod.sqrt()
# Store old values.
alphas_bar_sqrt_0 = alphas_bar_sqrt[0].clone()
alphas_bar_sqrt_T = alphas_bar_sqrt[-1].clone()
# Shift so the last timestep is zero.
alphas_bar_sqrt -= (alphas_bar_sqrt_T)
# Scale so the first timestep is back to the old value.
alphas_bar_sqrt *= alphas_bar_sqrt_0 / (alphas_bar_sqrt_0 - alphas_bar_sqrt_T)
# Convert alphas_bar_sqrt to betas
alphas_bar = alphas_bar_sqrt**2 # Revert sqrt
alphas_bar[-1] = 4.8973451890853435e-08
return ((1 - alphas_bar) / alphas_bar) ** 0.5
class EPS:
def calculate_input(self, sigma, noise):
sigma = sigma.view(sigma.shape[:1] + (1,) * (noise.ndim - 1))
@ -48,7 +67,7 @@ class CONST:
return latent / (1.0 - sigma)
class ModelSamplingDiscrete(torch.nn.Module):
def __init__(self, model_config=None):
def __init__(self, model_config=None, zsnr=None):
super().__init__()
if model_config is not None:
@ -61,11 +80,14 @@ class ModelSamplingDiscrete(torch.nn.Module):
linear_end = sampling_settings.get("linear_end", 0.012)
timesteps = sampling_settings.get("timesteps", 1000)
self._register_schedule(given_betas=None, beta_schedule=beta_schedule, timesteps=timesteps, linear_start=linear_start, linear_end=linear_end, cosine_s=8e-3)
if zsnr is None:
zsnr = sampling_settings.get("zsnr", False)
self._register_schedule(given_betas=None, beta_schedule=beta_schedule, timesteps=timesteps, linear_start=linear_start, linear_end=linear_end, cosine_s=8e-3, zsnr=zsnr)
self.sigma_data = 1.0
def _register_schedule(self, given_betas=None, beta_schedule="linear", timesteps=1000,
linear_start=1e-4, linear_end=2e-2, cosine_s=8e-3):
linear_start=1e-4, linear_end=2e-2, cosine_s=8e-3, zsnr=False):
if given_betas is not None:
betas = given_betas
else:
@ -83,6 +105,9 @@ class ModelSamplingDiscrete(torch.nn.Module):
# self.register_buffer('alphas_cumprod_prev', torch.tensor(alphas_cumprod_prev, dtype=torch.float32))
sigmas = ((1 - alphas_cumprod) / alphas_cumprod) ** 0.5
if zsnr:
sigmas = rescale_zero_terminal_snr_sigmas(sigmas)
self.set_sigmas(sigmas)
def set_sigmas(self, sigmas):

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@ -1,14 +1,10 @@
import torch
import comfy.model_management
import comfy.conds
import comfy.utils
def prepare_mask(noise_mask, shape, device):
"""ensures noise mask is of proper dimensions"""
noise_mask = torch.nn.functional.interpolate(noise_mask.reshape((-1, 1, noise_mask.shape[-2], noise_mask.shape[-1])), size=(shape[2], shape[3]), mode="bilinear")
noise_mask = torch.cat([noise_mask] * shape[1], dim=1)
noise_mask = comfy.utils.repeat_to_batch_size(noise_mask, shape[0])
noise_mask = noise_mask.to(device)
return noise_mask
return comfy.utils.reshape_mask(noise_mask, shape).to(device)
def get_models_from_cond(cond, model_type):
models = []

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@ -361,10 +361,26 @@ class VAE:
pixel_samples = pixel_samples.to(self.output_device).movedim(1,-1)
return pixel_samples
def decode_tiled(self, samples, tile_x=64, tile_y=64, overlap = 16):
model_management.load_model_gpu(self.patcher)
output = self.decode_tiled_(samples, tile_x, tile_y, overlap)
return output.movedim(1,-1)
def decode_tiled(self, samples, tile_x=None, tile_y=None, overlap=None):
memory_used = self.memory_used_decode(samples.shape, self.vae_dtype) #TODO: calculate mem required for tile
model_management.load_models_gpu([self.patcher], memory_required=memory_used)
dims = samples.ndim - 2
args = {}
if tile_x is not None:
args["tile_x"] = tile_x
if tile_y is not None:
args["tile_y"] = tile_y
if overlap is not None:
args["overlap"] = overlap
if dims == 1:
args.pop("tile_y")
output = self.decode_tiled_1d(samples, **args)
elif dims == 2:
output = self.decode_tiled_(samples, **args)
elif dims == 3:
output = self.decode_tiled_3d(samples, **args)
return output.movedim(1, -1)
def encode(self, pixel_samples):
pixel_samples = self.vae_encode_crop_pixels(pixel_samples)

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@ -197,6 +197,8 @@ class SDXL(supported_models_base.BASE):
self.sampling_settings["sigma_min"] = float(state_dict["edm_vpred.sigma_min"].item())
return model_base.ModelType.V_PREDICTION_EDM
elif "v_pred" in state_dict:
if "ztsnr" in state_dict: #Some zsnr anime checkpoints
self.sampling_settings["zsnr"] = True
return model_base.ModelType.V_PREDICTION
else:
return model_base.ModelType.EPS

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@ -848,3 +848,24 @@ class ProgressBar:
def update(self, value):
self.update_absolute(self.current + value)
def reshape_mask(input_mask, output_shape):
dims = len(output_shape) - 2
if dims == 1:
scale_mode = "linear"
if dims == 2:
input_mask = input_mask.reshape((-1, 1, input_mask.shape[-2], input_mask.shape[-1]))
scale_mode = "bilinear"
if dims == 3:
if len(input_mask.shape) < 5:
input_mask = input_mask.reshape((1, 1, -1, input_mask.shape[-2], input_mask.shape[-1]))
scale_mode = "trilinear"
mask = torch.nn.functional.interpolate(input_mask, size=output_shape[2:], mode=scale_mode)
if mask.shape[1] < output_shape[1]:
mask = mask.repeat((1, output_shape[1]) + (1,) * dims)[:,:output_shape[1]]
mask = comfy.utils.repeat_to_batch_size(mask, output_shape[0])
return mask

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@ -3,9 +3,6 @@ import torch
import comfy.model_management
class EmptyMochiLatentVideo:
def __init__(self):
self.device = comfy.model_management.intermediate_device()
@classmethod
def INPUT_TYPES(s):
return {"required": { "width": ("INT", {"default": 848, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
@ -15,10 +12,10 @@ class EmptyMochiLatentVideo:
RETURN_TYPES = ("LATENT",)
FUNCTION = "generate"
CATEGORY = "latent/mochi"
CATEGORY = "latent/video"
def generate(self, width, height, length, batch_size=1):
latent = torch.zeros([batch_size, 12, ((length - 1) // 6) + 1, height // 8, width // 8], device=self.device)
latent = torch.zeros([batch_size, 12, ((length - 1) // 6) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device())
return ({"samples":latent}, )
NODE_CLASS_MAPPINGS = {

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@ -26,8 +26,8 @@ class X0(comfy.model_sampling.EPS):
class ModelSamplingDiscreteDistilled(comfy.model_sampling.ModelSamplingDiscrete):
original_timesteps = 50
def __init__(self, model_config=None):
super().__init__(model_config)
def __init__(self, model_config=None, zsnr=None):
super().__init__(model_config, zsnr=zsnr)
self.skip_steps = self.num_timesteps // self.original_timesteps
@ -51,25 +51,6 @@ class ModelSamplingDiscreteDistilled(comfy.model_sampling.ModelSamplingDiscrete)
return log_sigma.exp().to(timestep.device)
def rescale_zero_terminal_snr_sigmas(sigmas):
alphas_cumprod = 1 / ((sigmas * sigmas) + 1)
alphas_bar_sqrt = alphas_cumprod.sqrt()
# Store old values.
alphas_bar_sqrt_0 = alphas_bar_sqrt[0].clone()
alphas_bar_sqrt_T = alphas_bar_sqrt[-1].clone()
# Shift so the last timestep is zero.
alphas_bar_sqrt -= (alphas_bar_sqrt_T)
# Scale so the first timestep is back to the old value.
alphas_bar_sqrt *= alphas_bar_sqrt_0 / (alphas_bar_sqrt_0 - alphas_bar_sqrt_T)
# Convert alphas_bar_sqrt to betas
alphas_bar = alphas_bar_sqrt**2 # Revert sqrt
alphas_bar[-1] = 4.8973451890853435e-08
return ((1 - alphas_bar) / alphas_bar) ** 0.5
class ModelSamplingDiscrete:
@classmethod
def INPUT_TYPES(s):
@ -100,9 +81,7 @@ class ModelSamplingDiscrete:
class ModelSamplingAdvanced(sampling_base, sampling_type):
pass
model_sampling = ModelSamplingAdvanced(model.model.model_config)
if zsnr:
model_sampling.set_sigmas(rescale_zero_terminal_snr_sigmas(model_sampling.sigmas))
model_sampling = ModelSamplingAdvanced(model.model.model_config, zsnr=zsnr)
m.add_object_patch("model_sampling", model_sampling)
return (m, )

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@ -75,6 +75,34 @@ class ModelMergeSD3_2B(comfy_extras.nodes_model_merging.ModelMergeBlocks):
return {"required": arg_dict}
class ModelMergeAuraflow(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
arg_dict["init_x_linear."] = argument
arg_dict["positional_encoding"] = argument
arg_dict["cond_seq_linear."] = argument
arg_dict["register_tokens"] = argument
arg_dict["t_embedder."] = argument
for i in range(4):
arg_dict["double_layers.{}.".format(i)] = argument
for i in range(32):
arg_dict["single_layers.{}.".format(i)] = argument
arg_dict["modF."] = argument
arg_dict["final_linear."] = argument
return {"required": arg_dict}
class ModelMergeFlux1(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@ -124,11 +152,35 @@ class ModelMergeSD35_Large(comfy_extras.nodes_model_merging.ModelMergeBlocks):
return {"required": arg_dict}
class ModelMergeMochiPreview(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
arg_dict["pos_frequencies."] = argument
arg_dict["t_embedder."] = argument
arg_dict["t5_y_embedder."] = argument
arg_dict["t5_yproj."] = argument
for i in range(48):
arg_dict["blocks.{}.".format(i)] = argument
arg_dict["final_layer."] = argument
return {"required": arg_dict}
NODE_CLASS_MAPPINGS = {
"ModelMergeSD1": ModelMergeSD1,
"ModelMergeSD2": ModelMergeSD1, #SD1 and SD2 have the same blocks
"ModelMergeSDXL": ModelMergeSDXL,
"ModelMergeSD3_2B": ModelMergeSD3_2B,
"ModelMergeAuraflow": ModelMergeAuraflow,
"ModelMergeFlux1": ModelMergeFlux1,
"ModelMergeSD35_Large": ModelMergeSD35_Large,
"ModelMergeMochiPreview": ModelMergeMochiPreview,
}

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@ -57,12 +57,24 @@ def create_blur_map(x0, attn, sigma=3.0, threshold=1.0):
attn = attn.reshape(b, -1, hw1, hw2)
# Global Average Pool
mask = attn.mean(1, keepdim=False).sum(1, keepdim=False) > threshold
ratio = 2**(math.ceil(math.sqrt(lh * lw / hw1)) - 1).bit_length()
mid_shape = [math.ceil(lh / ratio), math.ceil(lw / ratio)]
total = mask.shape[-1]
x = round(math.sqrt((lh / lw) * total))
xx = None
for i in range(0, math.floor(math.sqrt(total) / 2)):
for j in [(x + i), max(1, x - i)]:
if total % j == 0:
xx = j
break
if xx is not None:
break
x = xx
y = total // x
# Reshape
mask = (
mask.reshape(b, *mid_shape)
mask.reshape(b, x, y)
.unsqueeze(1)
.type(attn.dtype)
)

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@ -3,7 +3,9 @@ import comfy.sd
import comfy.model_management
import nodes
import torch
import re
import comfy_extras.nodes_slg
class TripleCLIPLoader:
@classmethod
def INPUT_TYPES(s):
@ -14,6 +16,8 @@ class TripleCLIPLoader:
CATEGORY = "advanced/loaders"
DESCRIPTION = "[Recipes]\n\nsd3: clip-l, clip-g, t5"
def load_clip(self, clip_name1, clip_name2, clip_name3):
clip_path1 = folder_paths.get_full_path_or_raise("text_encoders", clip_name1)
clip_path2 = folder_paths.get_full_path_or_raise("text_encoders", clip_name2)
@ -21,6 +25,7 @@ class TripleCLIPLoader:
clip = comfy.sd.load_clip(ckpt_paths=[clip_path1, clip_path2, clip_path3], embedding_directory=folder_paths.get_folder_paths("embeddings"))
return (clip,)
class EmptySD3LatentImage:
def __init__(self):
self.device = comfy.model_management.intermediate_device()
@ -39,6 +44,7 @@ class EmptySD3LatentImage:
latent = torch.zeros([batch_size, 16, height // 8, width // 8], device=self.device)
return ({"samples":latent}, )
class CLIPTextEncodeSD3:
@classmethod
def INPUT_TYPES(s):
@ -95,7 +101,8 @@ class ControlNetApplySD3(nodes.ControlNetApplyAdvanced):
CATEGORY = "conditioning/controlnet"
DEPRECATED = True
class SkipLayerGuidanceSD3:
class SkipLayerGuidanceSD3(comfy_extras.nodes_slg.SkipLayerGuidanceDiT):
'''
Enhance guidance towards detailed dtructure by having another set of CFG negative with skipped layers.
Inspired by Perturbed Attention Guidance (https://arxiv.org/abs/2403.17377)
@ -110,47 +117,12 @@ class SkipLayerGuidanceSD3:
"end_percent": ("FLOAT", {"default": 0.15, "min": 0.0, "max": 1.0, "step": 0.001})
}}
RETURN_TYPES = ("MODEL",)
FUNCTION = "skip_guidance"
FUNCTION = "skip_guidance_sd3"
CATEGORY = "advanced/guidance"
def skip_guidance(self, model, layers, scale, start_percent, end_percent):
if layers == "" or layers == None:
return (model, )
# check if layer is comma separated integers
def skip(args, extra_args):
return args
model_sampling = model.get_model_object("model_sampling")
sigma_start = model_sampling.percent_to_sigma(start_percent)
sigma_end = model_sampling.percent_to_sigma(end_percent)
def post_cfg_function(args):
model = args["model"]
cond_pred = args["cond_denoised"]
cond = args["cond"]
cfg_result = args["denoised"]
sigma = args["sigma"]
x = args["input"]
model_options = args["model_options"].copy()
for layer in layers:
model_options = comfy.model_patcher.set_model_options_patch_replace(model_options, skip, "dit", "double_block", layer)
model_sampling.percent_to_sigma(start_percent)
sigma_ = sigma[0].item()
if scale > 0 and sigma_ >= sigma_end and sigma_ <= sigma_start:
(slg,) = comfy.samplers.calc_cond_batch(model, [cond], x, sigma, model_options)
cfg_result = cfg_result + (cond_pred - slg) * scale
return cfg_result
layers = re.findall(r'\d+', layers)
layers = [int(i) for i in layers]
m = model.clone()
m.set_model_sampler_post_cfg_function(post_cfg_function)
return (m, )
def skip_guidance_sd3(self, model, layers, scale, start_percent, end_percent):
return self.skip_guidance(model=model, scale=scale, start_percent=start_percent, end_percent=end_percent, double_layers=layers)
NODE_CLASS_MAPPINGS = {

78
comfy_extras/nodes_slg.py Normal file
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@ -0,0 +1,78 @@
import comfy.model_patcher
import comfy.samplers
import re
class SkipLayerGuidanceDiT:
'''
Enhance guidance towards detailed dtructure by having another set of CFG negative with skipped layers.
Inspired by Perturbed Attention Guidance (https://arxiv.org/abs/2403.17377)
Original experimental implementation for SD3 by Dango233@StabilityAI.
'''
@classmethod
def INPUT_TYPES(s):
return {"required": {"model": ("MODEL", ),
"double_layers": ("STRING", {"default": "7, 8, 9", "multiline": False}),
"single_layers": ("STRING", {"default": "7, 8, 9", "multiline": False}),
"scale": ("FLOAT", {"default": 3.0, "min": 0.0, "max": 10.0, "step": 0.1}),
"start_percent": ("FLOAT", {"default": 0.01, "min": 0.0, "max": 1.0, "step": 0.001}),
"end_percent": ("FLOAT", {"default": 0.15, "min": 0.0, "max": 1.0, "step": 0.001})
}}
RETURN_TYPES = ("MODEL",)
FUNCTION = "skip_guidance"
EXPERIMENTAL = True
DESCRIPTION = "Generic version of SkipLayerGuidance node that can be used on every DiT model."
CATEGORY = "advanced/guidance"
def skip_guidance(self, model, scale, start_percent, end_percent, double_layers="", single_layers=""):
# check if layer is comma separated integers
def skip(args, extra_args):
return args
model_sampling = model.get_model_object("model_sampling")
sigma_start = model_sampling.percent_to_sigma(start_percent)
sigma_end = model_sampling.percent_to_sigma(end_percent)
double_layers = re.findall(r'\d+', double_layers)
double_layers = [int(i) for i in double_layers]
single_layers = re.findall(r'\d+', single_layers)
single_layers = [int(i) for i in single_layers]
if len(double_layers) == 0 and len(single_layers) == 0:
return (model, )
def post_cfg_function(args):
model = args["model"]
cond_pred = args["cond_denoised"]
cond = args["cond"]
cfg_result = args["denoised"]
sigma = args["sigma"]
x = args["input"]
model_options = args["model_options"].copy()
for layer in double_layers:
model_options = comfy.model_patcher.set_model_options_patch_replace(model_options, skip, "dit", "double_block", layer)
for layer in single_layers:
model_options = comfy.model_patcher.set_model_options_patch_replace(model_options, skip, "dit", "single_block", layer)
model_sampling.percent_to_sigma(start_percent)
sigma_ = sigma[0].item()
if scale > 0 and sigma_ >= sigma_end and sigma_ <= sigma_start:
(slg,) = comfy.samplers.calc_cond_batch(model, [cond], x, sigma, model_options)
cfg_result = cfg_result + (cond_pred - slg) * scale
return cfg_result
m = model.clone()
m.set_model_sampler_post_cfg_function(post_cfg_function)
return (m, )
NODE_CLASS_MAPPINGS = {
"SkipLayerGuidanceDiT": SkipLayerGuidanceDiT,
}

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@ -47,7 +47,12 @@ class Latent2RGBPreviewer(LatentPreviewer):
if self.latent_rgb_factors_bias is not None:
self.latent_rgb_factors_bias = self.latent_rgb_factors_bias.to(dtype=x0.dtype, device=x0.device)
latent_image = torch.nn.functional.linear(x0[0].permute(1, 2, 0), self.latent_rgb_factors, bias=self.latent_rgb_factors_bias)
if x0.ndim == 5:
x0 = x0[0, :, 0]
else:
x0 = x0[0]
latent_image = torch.nn.functional.linear(x0.movedim(0, -1), self.latent_rgb_factors, bias=self.latent_rgb_factors_bias)
# latent_image = x0[0].permute(1, 2, 0) @ self.latent_rgb_factors
return preview_to_image(latent_image)

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@ -71,6 +71,7 @@ if os.name == "nt":
if __name__ == "__main__":
if args.cuda_device is not None:
os.environ['CUDA_VISIBLE_DEVICES'] = str(args.cuda_device)
os.environ['HIP_VISIBLE_DEVICES'] = str(args.cuda_device)
logging.info("Set cuda device to: {}".format(args.cuda_device))
if args.deterministic:

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@ -290,15 +290,21 @@ class VAEDecodeTiled:
@classmethod
def INPUT_TYPES(s):
return {"required": {"samples": ("LATENT", ), "vae": ("VAE", ),
"tile_size": ("INT", {"default": 512, "min": 320, "max": 4096, "step": 64})
"tile_size": ("INT", {"default": 512, "min": 128, "max": 4096, "step": 32}),
"overlap": ("INT", {"default": 64, "min": 0, "max": 4096, "step": 32}),
}}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "decode"
CATEGORY = "_for_testing"
def decode(self, vae, samples, tile_size):
return (vae.decode_tiled(samples["samples"], tile_x=tile_size // 8, tile_y=tile_size // 8, ), )
def decode(self, vae, samples, tile_size, overlap=64):
if tile_size < overlap * 4:
overlap = tile_size // 4
images = vae.decode_tiled(samples["samples"], tile_x=tile_size // 8, tile_y=tile_size // 8, overlap=overlap // 8)
if len(images.shape) == 5: #Combine batches
images = images.reshape(-1, images.shape[-3], images.shape[-2], images.shape[-1])
return (images, )
class VAEEncode:
@classmethod
@ -896,6 +902,8 @@ class CLIPLoader:
CATEGORY = "advanced/loaders"
DESCRIPTION = "[Recipes]\n\nstable_diffusion: clip-l\nstable_cascade: clip-g\nsd3: t5 / clip-g / clip-l\nstable_audio: t5\nmochi: t5"
def load_clip(self, clip_name, type="stable_diffusion"):
if type == "stable_cascade":
clip_type = comfy.sd.CLIPType.STABLE_CASCADE
@ -924,6 +932,8 @@ class DualCLIPLoader:
CATEGORY = "advanced/loaders"
DESCRIPTION = "[Recipes]\n\nsdxl: clip-l, clip-g\nsd3: clip-l, clip-g / clip-l, t5 / clip-g, t5\nflux: clip-l, t5"
def load_clip(self, clip_name1, clip_name2, type):
clip_path1 = folder_paths.get_full_path_or_raise("text_encoders", clip_name1)
clip_path2 = folder_paths.get_full_path_or_raise("text_encoders", clip_name2)
@ -2123,6 +2133,7 @@ def init_builtin_extra_nodes():
"nodes_lora_extract.py",
"nodes_torch_compile.py",
"nodes_mochi.py",
"nodes_slg.py",
]
import_failed = []

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@ -152,7 +152,7 @@ class PromptServer():
mimetypes.types_map['.js'] = 'application/javascript; charset=utf-8'
self.user_manager = UserManager()
self.internal_routes = InternalRoutes()
self.internal_routes = InternalRoutes(self)
self.supports = ["custom_nodes_from_web"]
self.prompt_queue = None
self.loop = loop

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@ -8,7 +8,7 @@ from folder_paths import models_dir, user_directory, output_directory
@pytest.fixture
def internal_routes():
return InternalRoutes()
return InternalRoutes(None)
@pytest.fixture
def aiohttp_client_factory(aiohttp_client, internal_routes):
@ -102,7 +102,7 @@ async def test_file_service_initialization():
# Create a mock instance
mock_file_service_instance = MagicMock(spec=FileService)
MockFileService.return_value = mock_file_service_instance
internal_routes = InternalRoutes()
internal_routes = InternalRoutes(None)
# Check if FileService was initialized with the correct parameters
MockFileService.assert_called_once_with({
@ -112,4 +112,4 @@ async def test_file_service_initialization():
})
# Verify that the file_service attribute of InternalRoutes is set
assert internal_routes.file_service == mock_file_service_instance
assert internal_routes.file_service == mock_file_service_instance

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@ -1,8 +1,8 @@
var __defProp = Object.defineProperty;
var __name = (target, value) => __defProp(target, "name", { value, configurable: true });
import { d as defineComponent, bQ as useExtensionStore, u as useSettingStore, r as ref, o as onMounted, q as computed, g as openBlock, h as createElementBlock, i as createVNode, y as withCtx, z as unref, bR as script$1, A as createBaseVNode, x as createBlock, N as Fragment, O as renderList, a6 as toDisplayString, aw as createTextVNode, j as createCommentVNode, D as script$4 } from "./index-BHayQCxv.js";
import { s as script, a as script$2, b as script$3 } from "./index-CwRXxFdA.js";
import "./index-C_wOqB0f.js";
import { d as defineComponent, c6 as useExtensionStore, u as useSettingStore, r as ref, o as onMounted, q as computed, g as openBlock, h as createElementBlock, i as createVNode, y as withCtx, z as unref, bT as script$1, A as createBaseVNode, x as createBlock, N as Fragment, O as renderList, a6 as toDisplayString, aw as createTextVNode, bR as script$3, j as createCommentVNode, D as script$4 } from "./index-B6dYHNhg.js";
import { s as script, a as script$2 } from "./index-CjwCGacA.js";
import "./index-MX9DEi8Q.js";
const _hoisted_1 = { class: "extension-panel" };
const _hoisted_2 = { class: "mt-4" };
const _sfc_main = /* @__PURE__ */ defineComponent({
@ -100,4 +100,4 @@ const _sfc_main = /* @__PURE__ */ defineComponent({
export {
_sfc_main as default
};
//# sourceMappingURL=ExtensionPanel-BmKi_NKS.js.map
//# sourceMappingURL=ExtensionPanel-CfMfcLgI.js.map

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@ -1 +1 @@
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@ -45,7 +45,7 @@
--sidebar-icon-size: 1rem;
}
.side-tool-bar-container[data-v-37fd2fa4] {
.side-tool-bar-container[data-v-e0812a25] {
display: flex;
flex-direction: column;
align-items: center;
@ -58,28 +58,32 @@
background-color: var(--comfy-menu-bg);
color: var(--fg-color);
}
.side-tool-bar-end[data-v-37fd2fa4] {
.side-tool-bar-end[data-v-e0812a25] {
align-self: flex-end;
margin-top: auto;
}
[data-v-b49f20b1] .p-splitter-gutter {
[data-v-7c3279c1] .p-splitter-gutter {
pointer-events: auto;
}
.side-bar-panel[data-v-b49f20b1] {
[data-v-7c3279c1] .p-splitter-gutter:hover,[data-v-7c3279c1] .p-splitter-gutter[data-p-gutter-resizing='true'] {
transition: background-color 0.2s ease 300ms;
background-color: var(--p-primary-color);
}
.side-bar-panel[data-v-7c3279c1] {
background-color: var(--bg-color);
pointer-events: auto;
}
.bottom-panel[data-v-b49f20b1] {
.bottom-panel[data-v-7c3279c1] {
background-color: var(--bg-color);
pointer-events: auto;
}
.splitter-overlay[data-v-b49f20b1] {
.splitter-overlay[data-v-7c3279c1] {
pointer-events: none;
border-style: none;
background-color: transparent;
}
.splitter-overlay-root[data-v-b49f20b1] {
.splitter-overlay-root[data-v-7c3279c1] {
position: absolute;
top: 0px;
left: 0px;
@ -146,7 +150,7 @@
align-items: flex-start !important;
}
.node-tooltip[data-v-79ec8c53] {
.node-tooltip[data-v-c2e0098f] {
background: var(--comfy-input-bg);
border-radius: 5px;
box-shadow: 0 0 5px rgba(0, 0, 0, 0.4);
@ -162,22 +166,28 @@
z-index: 99999;
}
.p-buttongroup-vertical[data-v-444d3768] {
.p-buttongroup-vertical[data-v-94481f39] {
display: flex;
flex-direction: column;
border-radius: var(--p-button-border-radius);
overflow: hidden;
border: 1px solid var(--p-panel-border-color);
}
.p-buttongroup-vertical .p-button[data-v-444d3768] {
.p-buttongroup-vertical .p-button[data-v-94481f39] {
margin: 0;
border-radius: 0;
}
[data-v-84e785b8] .p-togglebutton::before {
.comfy-menu-hamburger[data-v-2ddd26e8] {
pointer-events: auto;
position: fixed;
z-index: 9999;
}
[data-v-9eb975c3] .p-togglebutton::before {
display: none
}
[data-v-84e785b8] .p-togglebutton {
[data-v-9eb975c3] .p-togglebutton {
position: relative;
flex-shrink: 0;
border-radius: 0px;
@ -185,14 +195,14 @@
padding-left: 0.5rem;
padding-right: 0.5rem
}
[data-v-84e785b8] .p-togglebutton.p-togglebutton-checked {
[data-v-9eb975c3] .p-togglebutton.p-togglebutton-checked {
border-bottom-width: 2px;
border-bottom-color: var(--p-button-text-primary-color)
}
[data-v-84e785b8] .p-togglebutton-checked .close-button,[data-v-84e785b8] .p-togglebutton:hover .close-button {
[data-v-9eb975c3] .p-togglebutton-checked .close-button,[data-v-9eb975c3] .p-togglebutton:hover .close-button {
visibility: visible
}
.status-indicator[data-v-84e785b8] {
.status-indicator[data-v-9eb975c3] {
position: absolute;
font-weight: 700;
font-size: 1.5rem;
@ -200,10 +210,10 @@
left: 50%;
transform: translate(-50%, -50%)
}
[data-v-84e785b8] .p-togglebutton:hover .status-indicator {
[data-v-9eb975c3] .p-togglebutton:hover .status-indicator {
display: none
}
[data-v-84e785b8] .p-togglebutton .close-button {
[data-v-9eb975c3] .p-togglebutton .close-button {
visibility: hidden
}
@ -226,35 +236,35 @@
border-bottom-left-radius: 0;
}
.comfyui-queue-button[data-v-2b80bf74] .p-splitbutton-dropdown {
.comfyui-queue-button[data-v-95bc9be0] .p-splitbutton-dropdown {
border-top-right-radius: 0;
border-bottom-right-radius: 0;
}
.actionbar[data-v-2e54db00] {
.actionbar[data-v-eb6e9acf] {
pointer-events: all;
position: fixed;
z-index: 1000;
}
.actionbar.is-docked[data-v-2e54db00] {
.actionbar.is-docked[data-v-eb6e9acf] {
position: static;
border-style: none;
background-color: transparent;
padding: 0px;
}
.actionbar.is-dragging[data-v-2e54db00] {
.actionbar.is-dragging[data-v-eb6e9acf] {
-webkit-user-select: none;
-moz-user-select: none;
user-select: none;
}
[data-v-2e54db00] .p-panel-content {
[data-v-eb6e9acf] .p-panel-content {
padding: 0.25rem;
}
[data-v-2e54db00] .p-panel-header {
[data-v-eb6e9acf] .p-panel-header {
display: none;
}
.comfyui-menu[data-v-ad2c662b] {
.comfyui-menu[data-v-d84a704d] {
width: 100vw;
background: var(--comfy-menu-bg);
color: var(--fg-color);
@ -266,13 +276,13 @@
grid-column: 1/-1;
max-height: 90vh;
}
.comfyui-menu.dropzone[data-v-ad2c662b] {
.comfyui-menu.dropzone[data-v-d84a704d] {
background: var(--p-highlight-background);
}
.comfyui-menu.dropzone-active[data-v-ad2c662b] {
.comfyui-menu.dropzone-active[data-v-d84a704d] {
background: var(--p-highlight-background-focus);
}
.comfyui-logo[data-v-ad2c662b] {
.comfyui-logo[data-v-d84a704d] {
font-size: 1.2em;
-webkit-user-select: none;
-moz-user-select: none;

4
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@ -0,0 +1,4 @@
[data-v-53e62b05] .p-steppanel {
background-color: transparent
}

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@ -1,8 +0,0 @@
[data-v-e5724e4d] .p-datatable-tbody > tr > td {
padding: 1px;
min-height: 2rem;
}
[data-v-e5724e4d] .p-datatable-row-selected .actions,[data-v-e5724e4d] .p-datatable-selectable-row:hover .actions {
visibility: visible;
}

8
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@ -0,0 +1,8 @@
[data-v-2d8b3a76] .p-datatable-tbody > tr > td {
padding: 0.25rem;
min-height: 2rem
}
[data-v-2d8b3a76] .p-datatable-row-selected .actions,[data-v-2d8b3a76] .p-datatable-selectable-row:hover .actions {
visibility: visible
}

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@ -1,8 +1,8 @@
var __defProp = Object.defineProperty;
var __name = (target, value) => __defProp(target, "name", { value, configurable: true });
import { d as defineComponent, q as computed, g as openBlock, h as createElementBlock, N as Fragment, O as renderList, i as createVNode, y as withCtx, aw as createTextVNode, a6 as toDisplayString, z as unref, aA as script, j as createCommentVNode, r as ref, bN as FilterMatchMode, M as useKeybindingStore, F as useCommandStore, aJ as watchEffect, b9 as useToast, t as resolveDirective, bO as SearchBox, A as createBaseVNode, D as script$2, x as createBlock, ao as script$4, be as withModifiers, aH as script$6, v as withDirectives, P as pushScopeId, Q as popScopeId, bJ as KeyComboImpl, bP as KeybindingImpl, _ as _export_sfc } from "./index-BHayQCxv.js";
import { s as script$1, a as script$3, b as script$5 } from "./index-CwRXxFdA.js";
import "./index-C_wOqB0f.js";
import { d as defineComponent, q as computed, g as openBlock, h as createElementBlock, N as Fragment, O as renderList, i as createVNode, y as withCtx, aw as createTextVNode, a6 as toDisplayString, z as unref, aA as script, j as createCommentVNode, r as ref, c3 as FilterMatchMode, M as useKeybindingStore, F as useCommandStore, aJ as watchEffect, be as useToast, t as resolveDirective, c4 as SearchBox, A as createBaseVNode, D as script$2, x as createBlock, ao as script$4, bi as withModifiers, bR as script$5, aH as script$6, v as withDirectives, P as pushScopeId, Q as popScopeId, b$ as KeyComboImpl, c5 as KeybindingImpl, _ as _export_sfc } from "./index-B6dYHNhg.js";
import { s as script$1, a as script$3 } from "./index-CjwCGacA.js";
import "./index-MX9DEi8Q.js";
const _hoisted_1$1 = {
key: 0,
class: "px-2"
@ -35,10 +35,11 @@ const _sfc_main$1 = /* @__PURE__ */ defineComponent({
};
}
});
const _withScopeId = /* @__PURE__ */ __name((n) => (pushScopeId("data-v-e5724e4d"), n = n(), popScopeId(), n), "_withScopeId");
const _withScopeId = /* @__PURE__ */ __name((n) => (pushScopeId("data-v-2d8b3a76"), n = n(), popScopeId(), n), "_withScopeId");
const _hoisted_1 = { class: "keybinding-panel" };
const _hoisted_2 = { class: "actions invisible" };
const _hoisted_3 = { key: 1 };
const _hoisted_2 = { class: "actions invisible flex flex-row" };
const _hoisted_3 = ["title"];
const _hoisted_4 = { key: 1 };
const _sfc_main = /* @__PURE__ */ defineComponent({
__name: "KeybindingPanel",
setup(__props) {
@ -177,7 +178,16 @@ const _sfc_main = /* @__PURE__ */ defineComponent({
createVNode(unref(script$1), {
field: "id",
header: "Command ID",
sortable: ""
sortable: "",
class: "max-w-64 2xl:max-w-full"
}, {
body: withCtx((slotProps) => [
createBaseVNode("div", {
class: "overflow-hidden text-ellipsis whitespace-nowrap",
title: slotProps.data.id
}, toDisplayString(slotProps.data.id), 9, _hoisted_3)
]),
_: 1
}),
createVNode(unref(script$1), {
field: "keybinding",
@ -188,7 +198,7 @@ const _sfc_main = /* @__PURE__ */ defineComponent({
key: 0,
keyCombo: slotProps.data.keybinding.combo,
isModified: unref(keybindingStore).isCommandKeybindingModified(slotProps.data.id)
}, null, 8, ["keyCombo", "isModified"])) : (openBlock(), createElementBlock("span", _hoisted_3, "-"))
}, null, 8, ["keyCombo", "isModified"])) : (openBlock(), createElementBlock("span", _hoisted_4, "-"))
]),
_: 1
})
@ -257,8 +267,8 @@ const _sfc_main = /* @__PURE__ */ defineComponent({
};
}
});
const KeybindingPanel = /* @__PURE__ */ _export_sfc(_sfc_main, [["__scopeId", "data-v-e5724e4d"]]);
const KeybindingPanel = /* @__PURE__ */ _export_sfc(_sfc_main, [["__scopeId", "data-v-2d8b3a76"]]);
export {
KeybindingPanel as default
};
//# sourceMappingURL=KeybindingPanel-Dm_3sBT5.js.map
//# sourceMappingURL=KeybindingPanel-DcEfyPZZ.js.map

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102
web/assets/ServerStartView-e57oVZ6V.js generated vendored Normal file
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@ -0,0 +1,102 @@
var __defProp = Object.defineProperty;
var __name = (target, value) => __defProp(target, "name", { value, configurable: true });
import { d as defineComponent, r as ref, o as onMounted, w as watch, I as onBeforeUnmount, g as openBlock, h as createElementBlock, i as createVNode, y as withCtx, A as createBaseVNode, a6 as toDisplayString, z as unref, bK as script, bL as electronAPI } from "./index-B6dYHNhg.js";
import { t, s } from "./index-B4gmhi99.js";
const _hoisted_1$1 = { class: "p-terminal rounded-none h-full w-full" };
const _hoisted_2$1 = { class: "px-4 whitespace-pre-wrap" };
const _sfc_main$1 = /* @__PURE__ */ defineComponent({
__name: "LogTerminal",
props: {
fetchLogs: { type: Function },
fetchInterval: {}
},
setup(__props) {
const props = __props;
const log = ref("");
const scrollPanelRef = ref(null);
const scrolledToBottom = ref(false);
let intervalId = 0;
onMounted(async () => {
const element = scrollPanelRef.value?.$el;
const scrollContainer = element?.querySelector(".p-scrollpanel-content");
if (scrollContainer) {
scrollContainer.addEventListener("scroll", () => {
scrolledToBottom.value = scrollContainer.scrollTop + scrollContainer.clientHeight === scrollContainer.scrollHeight;
});
}
const scrollToBottom = /* @__PURE__ */ __name(() => {
if (scrollContainer) {
scrollContainer.scrollTop = scrollContainer.scrollHeight;
}
}, "scrollToBottom");
watch(log, () => {
if (scrolledToBottom.value) {
scrollToBottom();
}
});
const fetchLogs = /* @__PURE__ */ __name(async () => {
log.value = await props.fetchLogs();
}, "fetchLogs");
await fetchLogs();
scrollToBottom();
intervalId = window.setInterval(fetchLogs, props.fetchInterval);
});
onBeforeUnmount(() => {
window.clearInterval(intervalId);
});
return (_ctx, _cache) => {
return openBlock(), createElementBlock("div", _hoisted_1$1, [
createVNode(unref(script), {
class: "h-full w-full",
ref_key: "scrollPanelRef",
ref: scrollPanelRef
}, {
default: withCtx(() => [
createBaseVNode("pre", _hoisted_2$1, toDisplayString(log.value), 1)
]),
_: 1
}, 512)
]);
};
}
});
const _hoisted_1 = { class: "font-sans flex flex-col justify-center items-center h-screen m-0 text-neutral-300 bg-neutral-900 dark-theme pointer-events-auto" };
const _hoisted_2 = { class: "text-2xl font-bold" };
const _sfc_main = /* @__PURE__ */ defineComponent({
__name: "ServerStartView",
setup(__props) {
const electron = electronAPI();
const status = ref(t.INITIAL_STATE);
const logs = ref([]);
const updateProgress = /* @__PURE__ */ __name(({ status: newStatus }) => {
status.value = newStatus;
logs.value = [];
}, "updateProgress");
const addLogMessage = /* @__PURE__ */ __name((message) => {
logs.value = [...logs.value, message];
}, "addLogMessage");
const fetchLogs = /* @__PURE__ */ __name(async () => {
return logs.value.join("\n");
}, "fetchLogs");
onMounted(() => {
electron.sendReady();
electron.onProgressUpdate(updateProgress);
electron.onLogMessage((message) => {
addLogMessage(message);
});
});
return (_ctx, _cache) => {
return openBlock(), createElementBlock("div", _hoisted_1, [
createBaseVNode("h2", _hoisted_2, toDisplayString(unref(s)[status.value]), 1),
createVNode(_sfc_main$1, {
"fetch-logs": fetchLogs,
"fetch-interval": 500
})
]);
};
}
});
export {
_sfc_main as default
};
//# sourceMappingURL=ServerStartView-e57oVZ6V.js.map

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@ -0,0 +1 @@
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36
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@ -0,0 +1,36 @@
.animated-gradient-text[data-v-12b8b11b] {
font-weight: 700;
font-size: clamp(2rem, 8vw, 4rem);
background: linear-gradient(to right, #12c2e9, #c471ed, #f64f59, #12c2e9);
background-size: 300% auto;
background-clip: text;
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
animation: gradient-12b8b11b 8s linear infinite;
}
.text-glow[data-v-12b8b11b] {
filter: drop-shadow(0 0 8px rgba(255, 255, 255, 0.3));
}
@keyframes gradient-12b8b11b {
0% {
background-position: 0% center;
}
100% {
background-position: 300% center;
}
}
.fade-in-up[data-v-12b8b11b] {
animation: fadeInUp-12b8b11b 1.5s ease-out;
animation-fill-mode: both;
}
@keyframes fadeInUp-12b8b11b {
0% {
opacity: 0;
transform: translateY(20px);
}
100% {
opacity: 1;
transform: translateY(0);
}
}

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@ -0,0 +1,33 @@
var __defProp = Object.defineProperty;
var __name = (target, value) => __defProp(target, "name", { value, configurable: true });
import { d as defineComponent, g as openBlock, h as createElementBlock, A as createBaseVNode, a6 as toDisplayString, i as createVNode, z as unref, D as script, P as pushScopeId, Q as popScopeId, _ as _export_sfc } from "./index-B6dYHNhg.js";
const _withScopeId = /* @__PURE__ */ __name((n) => (pushScopeId("data-v-12b8b11b"), n = n(), popScopeId(), n), "_withScopeId");
const _hoisted_1 = { class: "font-sans flex flex-col justify-center items-center h-screen m-0 text-neutral-300 bg-neutral-900 dark-theme pointer-events-auto" };
const _hoisted_2 = { class: "flex flex-col items-center justify-center gap-8 p-8" };
const _hoisted_3 = { class: "animated-gradient-text text-glow select-none" };
const _sfc_main = /* @__PURE__ */ defineComponent({
__name: "WelcomeView",
setup(__props) {
return (_ctx, _cache) => {
return openBlock(), createElementBlock("div", _hoisted_1, [
createBaseVNode("div", _hoisted_2, [
createBaseVNode("h1", _hoisted_3, toDisplayString(_ctx.$t("welcome.title")), 1),
createVNode(unref(script), {
label: _ctx.$t("welcome.getStarted"),
icon: "pi pi-arrow-right",
iconPos: "right",
size: "large",
rounded: "",
onClick: _cache[0] || (_cache[0] = ($event) => _ctx.$router.push("/install")),
class: "p-4 text-lg fade-in-up"
}, null, 8, ["label"])
])
]);
};
}
});
const WelcomeView = /* @__PURE__ */ _export_sfc(_sfc_main, [["__scopeId", "data-v-12b8b11b"]]);
export {
WelcomeView as default
};
//# sourceMappingURL=WelcomeView-DT4bj-QV.js.map

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@ -0,0 +1 @@
{"version":3,"file":"WelcomeView-DT4bj-QV.js","sources":[],"sourcesContent":[],"names":[],"mappings":";;;;;;;;;;;;;;;;;;;;;;;;;;;;;"}

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@ -1,7 +1,7 @@
var __defProp = Object.defineProperty;
var __name = (target, value) => __defProp(target, "name", { value, configurable: true });
import { bF as ComfyDialog, bG as $el, bH as ComfyApp, c as app, k as LiteGraph, b0 as LGraphCanvas, bI as DraggableList, ba as useToastStore, aE as useNodeDefStore, bC as api, L as LGraphGroup, bJ as KeyComboImpl, M as useKeybindingStore, F as useCommandStore, e as LGraphNode, bK as ComfyWidgets, bL as applyTextReplacements } from "./index-BHayQCxv.js";
import { mergeIfValid, getWidgetConfig, setWidgetConfig } from "./widgetInputs-DdecKYqd.js";
import { bV as ComfyDialog, bW as $el, bX as ComfyApp, c as app, k as LiteGraph, b2 as LGraphCanvas, bY as DraggableList, bf as useToastStore, bZ as serialise, aE as useNodeDefStore, b_ as deserialiseAndCreate, bH as api, L as LGraphGroup, b$ as KeyComboImpl, M as useKeybindingStore, F as useCommandStore, e as LGraphNode, c0 as ComfyWidgets, c1 as applyTextReplacements } from "./index-B6dYHNhg.js";
import { mergeIfValid, getWidgetConfig, setWidgetConfig } from "./widgetInputs-BJ21PG7d.js";
class ClipspaceDialog extends ComfyDialog {
static {
__name(this, "ClipspaceDialog");
@ -160,7 +160,7 @@ app.registerExtension({
window.comfyAPI = window.comfyAPI || {};
window.comfyAPI.clipspace = window.comfyAPI.clipspace || {};
window.comfyAPI.clipspace.ClipspaceDialog = ClipspaceDialog;
const ext$2 = {
const ext$1 = {
name: "Comfy.ContextMenuFilter",
init() {
const ctxMenu = LiteGraph.ContextMenu;
@ -178,7 +178,7 @@ const ext$2 = {
let itemCount = displayedItems.length;
requestAnimationFrame(() => {
const currentNode = LGraphCanvas.active_canvas.current_node;
const clickedComboValue = currentNode.widgets?.filter(
const clickedComboValue = currentNode?.widgets?.filter(
(w) => w.type === "combo" && w.options.values?.length === values.length
).find(
(w) => w.options.values?.every((v, i) => v === values[i])
@ -284,7 +284,7 @@ const ext$2 = {
LiteGraph.ContextMenu.prototype = ctxMenu.prototype;
}
};
app.registerExtension(ext$2);
app.registerExtension(ext$1);
function stripComments(str) {
return str.replace(/\/\*[\s\S]*?\*\/|\/\/.*/g, "");
}
@ -966,17 +966,13 @@ class GroupNodeBuilder {
}
}
}, "storeExternalLinks");
const backup = localStorage.getItem("litegrapheditor_clipboard");
try {
app.canvas.copyToClipboard(this.nodes);
const config = JSON.parse(
localStorage.getItem("litegrapheditor_clipboard")
);
const serialised = serialise(this.nodes, app.canvas.graph);
const config = JSON.parse(serialised);
storeLinkTypes(config);
storeExternalLinks(config);
return config;
} finally {
localStorage.setItem("litegrapheditor_clipboard", backup);
}
}
}
@ -1517,7 +1513,6 @@ class GroupNodeHandler {
};
this.node.convertToNodes = () => {
const addInnerNodes = /* @__PURE__ */ __name(() => {
const backup = localStorage.getItem("litegrapheditor_clipboard");
const c = { ...this.groupData.nodeData };
c.nodes = [...c.nodes];
const innerNodes = this.node.getInnerNodes();
@ -1531,9 +1526,7 @@ class GroupNodeHandler {
}
c.nodes[i] = { ...c.nodes[i], id: id2 };
}
localStorage.setItem("litegrapheditor_clipboard", JSON.stringify(c));
app.canvas.pasteFromClipboard();
localStorage.setItem("litegrapheditor_clipboard", backup);
deserialiseAndCreate(JSON.stringify(c), app.canvas);
const [x, y] = this.node.pos;
let top;
let left;
@ -1580,10 +1573,8 @@ class GroupNodeHandler {
}
}
for (const newNode of newNodes2) {
newNode.pos = [
newNode.pos[0] - (left - x),
newNode.pos[1] - (top - y)
];
newNode.pos[0] -= left - x;
newNode.pos[1] -= top - y;
}
return { newNodes: newNodes2, selectedIds: selectedIds2 };
}, "addInnerNodes");
@ -1618,10 +1609,12 @@ class GroupNodeHandler {
}
}
}, "reconnectOutputs");
app.canvas.emitBeforeChange();
const { newNodes, selectedIds } = addInnerNodes();
reconnectInputs(selectedIds);
reconnectOutputs(selectedIds);
app.graph.remove(this.node);
app.canvas.emitAfterChange();
return newNodes;
};
const getExtraMenuOptions = this.node.getExtraMenuOptions;
@ -2030,10 +2023,10 @@ function manageGroupNodes() {
new ManageGroupDialog(app).show();
}
__name(manageGroupNodes, "manageGroupNodes");
const id$3 = "Comfy.GroupNode";
const id$2 = "Comfy.GroupNode";
let globalDefs;
const ext$1 = {
name: id$3,
const ext = {
name: id$2,
commands: [
{
id: "Comfy.GroupNode.ConvertSelectedNodesToGroupNode",
@ -2103,56 +2096,18 @@ const ext$1 = {
}
}
};
app.registerExtension(ext$1);
app.registerExtension(ext);
window.comfyAPI = window.comfyAPI || {};
window.comfyAPI.groupNode = window.comfyAPI.groupNode || {};
window.comfyAPI.groupNode.GroupNodeConfig = GroupNodeConfig;
window.comfyAPI.groupNode.GroupNodeHandler = GroupNodeHandler;
function setNodeMode(node, mode) {
node.mode = mode;
node.graph.change();
node.graph?.change();
}
__name(setNodeMode, "setNodeMode");
function addNodesToGroup(group, nodes = []) {
var x1, y1, x2, y2;
var nx1, ny1, nx2, ny2;
var node;
x1 = y1 = x2 = y2 = -1;
nx1 = ny1 = nx2 = ny2 = -1;
for (var n of [group.nodes, nodes]) {
for (var i in n) {
node = n[i];
nx1 = node.pos[0];
ny1 = node.pos[1];
nx2 = node.pos[0] + node.size[0];
ny2 = node.pos[1] + node.size[1];
if (node.type != "Reroute") {
ny1 -= LiteGraph.NODE_TITLE_HEIGHT;
}
if (node.flags?.collapsed) {
ny2 = ny1 + LiteGraph.NODE_TITLE_HEIGHT;
if (node?._collapsed_width) {
nx2 = nx1 + Math.round(node._collapsed_width);
}
}
if (x1 == -1 || nx1 < x1) {
x1 = nx1;
}
if (y1 == -1 || ny1 < y1) {
y1 = ny1;
}
if (x2 == -1 || nx2 > x2) {
x2 = nx2;
}
if (y2 == -1 || ny2 > y2) {
y2 = ny2;
}
}
}
var padding = 10;
y1 = y1 - Math.round(group.font_size * 1.4);
group.pos = [x1 - padding, y1 - padding];
group.size = [x2 - x1 + padding * 2, y2 - y1 + padding * 2];
function addNodesToGroup(group, items) {
group.resizeTo([...group.children, ...items]);
}
__name(addNodesToGroup, "addNodesToGroup");
app.registerExtension({
@ -2168,11 +2123,11 @@ app.registerExtension({
if (!group) {
options.push({
content: "Add Group For Selected Nodes",
disabled: !Object.keys(app.canvas.selected_nodes || {}).length,
disabled: !this.selectedItems?.size,
callback: /* @__PURE__ */ __name(() => {
const group2 = new LGraphGroup();
addNodesToGroup(group2, this.selected_nodes);
app.canvas.graph.add(group2);
addNodesToGroup(group2, this.selectedItems);
this.graph.add(group2);
this.graph.change();
}, "callback")
});
@ -2182,9 +2137,9 @@ app.registerExtension({
const nodesInGroup = group.nodes;
options.push({
content: "Add Selected Nodes To Group",
disabled: !Object.keys(app.canvas.selected_nodes || {}).length,
disabled: !this.selectedItems?.size,
callback: /* @__PURE__ */ __name(() => {
addNodesToGroup(group, this.selected_nodes);
addNodesToGroup(group, this.selectedItems);
this.graph.change();
}, "callback")
});
@ -2203,7 +2158,8 @@ app.registerExtension({
options.push({
content: "Fit Group To Nodes",
callback: /* @__PURE__ */ __name(() => {
addNodesToGroup(group);
group.recomputeInsideNodes();
group.resizeTo(group.children);
this.graph.change();
}, "callback")
});
@ -2329,9 +2285,9 @@ app.registerExtension({
};
}
});
const id$2 = "Comfy.InvertMenuScrolling";
const id$1 = "Comfy.InvertMenuScrolling";
app.registerExtension({
name: id$2,
name: id$1,
init() {
const ctxMenu = LiteGraph.ContextMenu;
const replace = /* @__PURE__ */ __name(() => {
@ -2347,7 +2303,7 @@ app.registerExtension({
LiteGraph.ContextMenu.prototype = ctxMenu.prototype;
}, "replace");
app.ui.settings.addSetting({
id: id$2,
id: id$1,
category: ["Comfy", "Graph", "InvertMenuScrolling"],
name: "Invert Context Menu Scrolling",
type: "boolean",
@ -2379,8 +2335,8 @@ app.registerExtension({
const commandStore = useCommandStore();
const keybinding = keybindingStore.getKeybinding(keyCombo);
if (keybinding && keybinding.targetSelector !== "#graph-canvas") {
await commandStore.execute(keybinding.commandId);
event.preventDefault();
await commandStore.execute(keybinding.commandId);
return;
}
if (event.ctrlKey || event.altKey || event.metaKey) {
@ -2403,35 +2359,6 @@ app.registerExtension({
window.addEventListener("keydown", keybindListener);
}
});
const id$1 = "Comfy.LinkRenderMode";
const ext = {
name: id$1,
async setup(app2) {
app2.ui.settings.addSetting({
id: id$1,
category: ["Comfy", "Graph", "LinkRenderMode"],
name: "Link Render Mode",
defaultValue: 2,
type: "combo",
options: [
{ value: LiteGraph.STRAIGHT_LINK.toString(), text: "Straight" },
{ value: LiteGraph.LINEAR_LINK.toString(), text: "Linear" },
{ value: LiteGraph.SPLINE_LINK.toString(), text: "Spline" },
{ value: LiteGraph.HIDDEN_LINK.toString(), text: "Hidden" }
],
onChange(value) {
app2.canvas.links_render_mode = +value;
app2.canvas.setDirty(
/* fg */
false,
/* bg */
true
);
}
});
}
};
app.registerExtension(ext);
function dataURLToBlob(dataURL) {
const parts = dataURL.split(";base64,");
const contentType = parts[0].split(":")[1];
@ -3714,8 +3641,12 @@ app.registerExtension({
clipboardAction(async () => {
const data = JSON.parse(t.data);
await GroupNodeConfig.registerFromWorkflow(data.groupNodes, {});
localStorage.setItem("litegrapheditor_clipboard", t.data);
app.canvas.pasteFromClipboard();
if (!data.reroutes) {
deserialiseAndCreate(t.data, app.canvas);
} else {
localStorage.setItem("litegrapheditor_clipboard", t.data);
app.canvas.pasteFromClipboard();
}
});
}, "callback")
};
@ -4049,9 +3980,10 @@ let touchCount = 0;
app.registerExtension({
name: "Comfy.SimpleTouchSupport",
setup() {
let zoomPos;
let touchDist;
let touchTime;
let lastTouch;
let lastScale;
function getMultiTouchPos(e) {
return Math.hypot(
e.touches[0].clientX - e.touches[1].clientX,
@ -4059,63 +3991,90 @@ app.registerExtension({
);
}
__name(getMultiTouchPos, "getMultiTouchPos");
app.canvasEl.addEventListener(
function getMultiTouchCenter(e) {
return {
clientX: (e.touches[0].clientX + e.touches[1].clientX) / 2,
clientY: (e.touches[0].clientY + e.touches[1].clientY) / 2
};
}
__name(getMultiTouchCenter, "getMultiTouchCenter");
app.canvasEl.parentElement.addEventListener(
"touchstart",
(e) => {
touchCount++;
lastTouch = null;
lastScale = null;
if (e.touches?.length === 1) {
touchTime = /* @__PURE__ */ new Date();
lastTouch = e.touches[0];
} else {
touchTime = null;
if (e.touches?.length === 2) {
zoomPos = getMultiTouchPos(e);
lastScale = app.canvas.ds.scale;
lastTouch = getMultiTouchCenter(e);
touchDist = getMultiTouchPos(e);
app.canvas.pointer_is_down = false;
}
}
},
true
);
app.canvasEl.addEventListener("touchend", (e) => {
touchZooming = false;
touchCount = e.touches?.length ?? touchCount - 1;
app.canvasEl.parentElement.addEventListener("touchend", (e) => {
touchCount--;
if (e.touches?.length !== 1) touchZooming = false;
if (touchTime && !e.touches?.length) {
if ((/* @__PURE__ */ new Date()).getTime() - touchTime > 600) {
try {
e.constructor = CustomEvent;
} catch (error) {
if (e.target === app.canvasEl) {
app.canvasEl.dispatchEvent(
new PointerEvent("pointerdown", {
button: 2,
clientX: e.changedTouches[0].clientX,
clientY: e.changedTouches[0].clientY
})
);
e.preventDefault();
}
e.clientX = lastTouch.clientX;
e.clientY = lastTouch.clientY;
app.canvas.pointer_is_down = true;
app.canvas._mousedown_callback(e);
}
touchTime = null;
}
});
app.canvasEl.addEventListener(
app.canvasEl.parentElement.addEventListener(
"touchmove",
(e) => {
touchTime = null;
if (e.touches?.length === 2) {
if (e.touches?.length === 2 && lastTouch && !e.ctrlKey && !e.shiftKey) {
e.preventDefault();
app.canvas.pointer_is_down = false;
touchZooming = true;
LiteGraph.closeAllContextMenus();
LiteGraph.closeAllContextMenus(window);
app.canvas.search_box?.close();
const newZoomPos = getMultiTouchPos(e);
const midX = (e.touches[0].clientX + e.touches[1].clientX) / 2;
const midY = (e.touches[0].clientY + e.touches[1].clientY) / 2;
let scale = app.canvas.ds.scale;
const diff = zoomPos - newZoomPos;
if (diff > 0.5) {
scale *= 1 / 1.07;
} else if (diff < -0.5) {
scale *= 1.07;
const newTouchDist = getMultiTouchPos(e);
const center = getMultiTouchCenter(e);
let scale = lastScale * newTouchDist / touchDist;
const newX = (center.clientX - lastTouch.clientX) / scale;
const newY = (center.clientY - lastTouch.clientY) / scale;
if (scale < app.canvas.ds.min_scale) {
scale = app.canvas.ds.min_scale;
} else if (scale > app.canvas.ds.max_scale) {
scale = app.canvas.ds.max_scale;
}
app.canvas.ds.changeScale(scale, [midX, midY]);
const oldScale = app.canvas.ds.scale;
app.canvas.ds.scale = scale;
if (Math.abs(app.canvas.ds.scale - 1) < 0.01) {
app.canvas.ds.scale = 1;
}
const newScale = app.canvas.ds.scale;
const convertScaleToOffset = /* @__PURE__ */ __name((scale2) => [
center.clientX / scale2 - app.canvas.ds.offset[0],
center.clientY / scale2 - app.canvas.ds.offset[1]
], "convertScaleToOffset");
var oldCenter = convertScaleToOffset(oldScale);
var newCenter = convertScaleToOffset(newScale);
app.canvas.ds.offset[0] += newX + newCenter[0] - oldCenter[0];
app.canvas.ds.offset[1] += newY + newCenter[1] - oldCenter[1];
lastTouch.clientX = center.clientX;
lastTouch.clientY = center.clientY;
app.canvas.setDirty(true, true);
zoomPos = newZoomPos;
}
},
true
@ -4127,6 +4086,7 @@ LGraphCanvas.prototype.processMouseDown = function(e) {
if (touchZooming || touchCount) {
return;
}
app.canvas.pointer_is_down = false;
return processMouseDown.apply(this, arguments);
};
const processMouseMove = LGraphCanvas.prototype.processMouseMove;
@ -4539,7 +4499,9 @@ app.registerExtension({
/* name=*/
"audioUI",
audio,
{ serialize: false }
{
serialize: false
}
);
const isOutputNode = node.constructor.nodeData.output_node;
if (isOutputNode) {
@ -4633,4 +4595,4 @@ app.registerExtension({
};
}
});
//# sourceMappingURL=index-BReiUkk9.js.map
//# sourceMappingURL=index-B1vRdV2i.js.map

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const o = {
LOADING_PROGRESS: "loading-progress",
IS_PACKAGED: "is-packaged",
RENDERER_READY: "renderer-ready",
RESTART_APP: "restart-app",
REINSTALL: "reinstall",
LOG_MESSAGE: "log-message",
OPEN_DIALOG: "open-dialog",
DOWNLOAD_PROGRESS: "download-progress",
START_DOWNLOAD: "start-download",
PAUSE_DOWNLOAD: "pause-download",
RESUME_DOWNLOAD: "resume-download",
CANCEL_DOWNLOAD: "cancel-download",
DELETE_MODEL: "delete-model",
GET_ALL_DOWNLOADS: "get-all-downloads",
GET_ELECTRON_VERSION: "get-electron-version",
SEND_ERROR_TO_SENTRY: "send-error-to-sentry",
GET_BASE_PATH: "get-base-path",
GET_MODEL_CONFIG_PATH: "get-model-config-path",
OPEN_PATH: "open-path",
OPEN_LOGS_PATH: "open-logs-path",
OPEN_DEV_TOOLS: "open-dev-tools",
IS_FIRST_TIME_SETUP: "is-first-time-setup",
GET_SYSTEM_PATHS: "get-system-paths",
VALIDATE_INSTALL_PATH: "validate-install-path",
VALIDATE_COMFYUI_SOURCE: "validate-comfyui-source",
SHOW_DIRECTORY_PICKER: "show-directory-picker",
INSTALL_COMFYUI: "install-comfyui"
};
var t = /* @__PURE__ */ ((e) => (e.INITIAL_STATE = "initial-state", e.PYTHON_SETUP = "python-setup", e.STARTING_SERVER = "starting-server", e.READY = "ready", e.ERROR = "error", e.ERROR_INSTALL_PATH = "error-install-path", e))(t || {});
const s = {
"initial-state": "Loading...",
"python-setup": "Setting up Python Environment...",
"starting-server": "Starting ComfyUI server...",
ready: "Finishing...",
error: "Was not able to start ComfyUI. Please check the logs for more details. You can open it from the Help menu. Please report issues to: https://forum.comfy.org",
"error-install-path": "Installation path does not exist. Please reset the installation location."
}, a = "electronAPI", n = "https://942cadba58d247c9cab96f45221aa813@o4507954455314432.ingest.us.sentry.io/4508007940685824", r = [
{
id: "user_files",
label: "User Files",
description: "Settings and user-created workflows"
},
{
id: "models",
label: "Models",
description: "Reference model files from existing ComfyUI installations. (No copy)"
}
// TODO: Decide whether we want to auto-migrate custom nodes, and install their dependencies.
// huchenlei: This is a very essential thing for migration experience.
// {
// id: 'custom_nodes',
// label: 'Custom Nodes',
// description: 'Reference custom node files from existing ComfyUI installations. (No copy)',
// },
];
export {
r,
s,
t
};
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{"version":3,"file":"index-MX9DEi8Q.js","sources":["../../node_modules/@primevue/icons/bars/index.mjs","../../node_modules/@primevue/icons/plus/index.mjs"],"sourcesContent":["import BaseIcon from '@primevue/icons/baseicon';\nimport { openBlock, createElementBlock, mergeProps, createElementVNode } from 'vue';\n\nvar script = {\n name: 'BarsIcon',\n \"extends\": BaseIcon\n};\n\nvar _hoisted_1 = /*#__PURE__*/createElementVNode(\"path\", {\n \"fill-rule\": \"evenodd\",\n \"clip-rule\": \"evenodd\",\n d: \"M13.3226 3.6129H0.677419C0.497757 3.6129 0.325452 3.54152 0.198411 3.41448C0.0713707 3.28744 0 3.11514 0 2.93548C0 2.75581 0.0713707 2.58351 0.198411 2.45647C0.325452 2.32943 0.497757 2.25806 0.677419 2.25806H13.3226C13.5022 2.25806 13.6745 2.32943 13.8016 2.45647C13.9286 2.58351 14 2.75581 14 2.93548C14 3.11514 13.9286 3.28744 13.8016 3.41448C13.6745 3.54152 13.5022 3.6129 13.3226 3.6129ZM13.3226 7.67741H0.677419C0.497757 7.67741 0.325452 7.60604 0.198411 7.479C0.0713707 7.35196 0 7.17965 0 6.99999C0 6.82033 0.0713707 6.64802 0.198411 6.52098C0.325452 6.39394 0.497757 6.32257 0.677419 6.32257H13.3226C13.5022 6.32257 13.6745 6.39394 13.8016 6.52098C13.9286 6.64802 14 6.82033 14 6.99999C14 7.17965 13.9286 7.35196 13.8016 7.479C13.6745 7.60604 13.5022 7.67741 13.3226 7.67741ZM0.677419 11.7419H13.3226C13.5022 11.7419 13.6745 11.6706 13.8016 11.5435C13.9286 11.4165 14 11.2442 14 11.0645C14 10.8848 13.9286 10.7125 13.8016 10.5855C13.6745 10.4585 13.5022 10.3871 13.3226 10.3871H0.677419C0.497757 10.3871 0.325452 10.4585 0.198411 10.5855C0.0713707 10.7125 0 10.8848 0 11.0645C0 11.2442 0.0713707 11.4165 0.198411 11.5435C0.325452 11.6706 0.497757 11.7419 0.677419 11.7419Z\",\n fill: \"currentColor\"\n}, null, -1);\nvar _hoisted_2 = [_hoisted_1];\nfunction render(_ctx, _cache, $props, $setup, $data, $options) {\n return openBlock(), createElementBlock(\"svg\", mergeProps({\n width: \"14\",\n height: \"14\",\n viewBox: \"0 0 14 14\",\n fill: \"none\",\n xmlns: \"http://www.w3.org/2000/svg\"\n }, _ctx.pti()), _hoisted_2, 16);\n}\n\nscript.render = render;\n\nexport { script as default };\n//# sourceMappingURL=index.mjs.map\n","import BaseIcon from '@primevue/icons/baseicon';\nimport { openBlock, createElementBlock, mergeProps, createElementVNode } from 'vue';\n\nvar script = {\n name: 'PlusIcon',\n \"extends\": BaseIcon\n};\n\nvar _hoisted_1 = /*#__PURE__*/createElementVNode(\"path\", {\n d: \"M7.67742 6.32258V0.677419C7.67742 0.497757 7.60605 0.325452 7.47901 0.198411C7.35197 0.0713707 7.17966 0 7 0C6.82034 0 6.64803 0.0713707 6.52099 0.198411C6.39395 0.325452 6.32258 0.497757 6.32258 0.677419V6.32258H0.677419C0.497757 6.32258 0.325452 6.39395 0.198411 6.52099C0.0713707 6.64803 0 6.82034 0 7C0 7.17966 0.0713707 7.35197 0.198411 7.47901C0.325452 7.60605 0.497757 7.67742 0.677419 7.67742H6.32258V13.3226C6.32492 13.5015 6.39704 13.6725 6.52358 13.799C6.65012 13.9255 6.82106 13.9977 7 14C7.17966 14 7.35197 13.9286 7.47901 13.8016C7.60605 13.6745 7.67742 13.5022 7.67742 13.3226V7.67742H13.3226C13.5022 7.67742 13.6745 7.60605 13.8016 7.47901C13.9286 7.35197 14 7.17966 14 7C13.9977 6.82106 13.9255 6.65012 13.799 6.52358C13.6725 6.39704 13.5015 6.32492 13.3226 6.32258H7.67742Z\",\n fill: \"currentColor\"\n}, null, -1);\nvar _hoisted_2 = [_hoisted_1];\nfunction render(_ctx, _cache, $props, $setup, $data, $options) {\n return openBlock(), createElementBlock(\"svg\", mergeProps({\n width: \"14\",\n height: \"14\",\n viewBox: \"0 0 14 14\",\n fill: \"none\",\n xmlns: \"http://www.w3.org/2000/svg\"\n }, _ctx.pti()), _hoisted_2, 16);\n}\n\nscript.render = render;\n\nexport { script as default };\n//# sourceMappingURL=index.mjs.map\n"],"names":["script","BaseIcon","_hoisted_1","createElementVNode","_hoisted_2","render"],"mappings":";;;AAGG,IAACA,WAAS;AAAA,EACX,MAAM;AAAA,EACN,WAAWC;AACb;AAEA,IAAIC,eAA0BC,gCAAmB,QAAQ;AAAA,EACvD,aAAa;AAAA,EACb,aAAa;AAAA,EACb,GAAG;AAAA,EACH,MAAM;AACR,GAAG,MAAM,EAAE;AACX,IAAIC,eAAa,CAACF,YAAU;AAC5B,SAASG,SAAO,MAAM,QAAQ,QAAQ,QAAQ,OAAO,UAAU;AAC7D,SAAO,UAAW,GAAE,mBAAmB,OAAO,WAAW;AAAA,IACvD,OAAO;AAAA,IACP,QAAQ;AAAA,IACR,SAAS;AAAA,IACT,MAAM;AAAA,IACN,OAAO;AAAA,EACR,GAAE,KAAK,IAAG,CAAE,GAAGD,cAAY,EAAE;AAChC;AARSC;AAUTL,SAAO,SAASK;ACtBb,IAAC,SAAS;AAAA,EACX,MAAM;AAAA,EACN,WAAWJ;AACb;AAEA,IAAI,aAA0BE,gCAAmB,QAAQ;AAAA,EACvD,GAAG;AAAA,EACH,MAAM;AACR,GAAG,MAAM,EAAE;AACX,IAAI,aAAa,CAAC,UAAU;AAC5B,SAAS,OAAO,MAAM,QAAQ,QAAQ,QAAQ,OAAO,UAAU;AAC7D,SAAO,UAAW,GAAE,mBAAmB,OAAO,WAAW;AAAA,IACvD,OAAO;AAAA,IACP,QAAQ;AAAA,IACR,SAAS;AAAA,IACT,MAAM;AAAA,IACN,OAAO;AAAA,EACR,GAAE,KAAK,IAAG,CAAE,GAAG,YAAY,EAAE;AAChC;AARS;AAUT,OAAO,SAAS;","x_google_ignoreList":[0,1]}

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@ -1,6 +1,6 @@
var __defProp = Object.defineProperty;
var __name = (target, value) => __defProp(target, "name", { value, configurable: true });
import { bC as api, bG as $el } from "./index-BHayQCxv.js";
import { bH as api, bW as $el } from "./index-B6dYHNhg.js";
function createSpinner() {
const div = document.createElement("div");
div.innerHTML = `<div class="lds-ring"><div></div><div></div><div></div><div></div></div>`;
@ -126,4 +126,4 @@ window.comfyAPI.userSelection.UserSelectionScreen = UserSelectionScreen;
export {
UserSelectionScreen
};
//# sourceMappingURL=userSelection-DITGVoWz.js.map
//# sourceMappingURL=userSelection-BSkuSZyR.js.map

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@ -1,6 +1,6 @@
var __defProp = Object.defineProperty;
var __name = (target, value) => __defProp(target, "name", { value, configurable: true });
import { e as LGraphNode, c as app, bL as applyTextReplacements, bK as ComfyWidgets, bM as addValueControlWidgets, k as LiteGraph } from "./index-BHayQCxv.js";
import { e as LGraphNode, c as app, c1 as applyTextReplacements, c0 as ComfyWidgets, c2 as addValueControlWidgets, k as LiteGraph } from "./index-B6dYHNhg.js";
const CONVERTED_TYPE = "converted-widget";
const VALID_TYPES = [
"STRING",
@ -171,7 +171,7 @@ class PrimitiveNode extends LGraphNode {
if (type instanceof Array) {
type = "COMBO";
}
const size = this.size;
const [oldWidth, oldHeight] = this.size;
let widget;
if (type in ComfyWidgets) {
widget = (ComfyWidgets[type](this, "value", inputData, app) || {}).widget;
@ -218,8 +218,8 @@ class PrimitiveNode extends LGraphNode {
return r;
};
this.size = [
Math.max(this.size[0], size[0]),
Math.max(this.size[1], size[1])
Math.max(this.size[0], oldWidth),
Math.max(this.size[1], oldHeight)
];
if (!recreating) {
const sz = this.computeSize();
@ -320,7 +320,7 @@ class PrimitiveNode extends LGraphNode {
}
}
function getWidgetConfig(slot) {
return slot.widget[CONFIG] ?? slot.widget[GET_CONFIG]();
return slot.widget[CONFIG] ?? slot.widget[GET_CONFIG]?.() ?? ["*", {}];
}
__name(getWidgetConfig, "getWidgetConfig");
function getConfig(widgetName) {
@ -373,7 +373,7 @@ __name(showWidget, "showWidget");
function convertToInput(node, widget, config) {
hideWidget(node, widget);
const { type } = getWidgetType(config);
const sz = node.size;
const [oldWidth, oldHeight] = node.size;
const inputIsOptional = !!widget.options?.inputIsOptional;
const input = node.addInput(widget.name, type, {
widget: { name: widget.name, [GET_CONFIG]: () => config },
@ -382,18 +382,24 @@ function convertToInput(node, widget, config) {
for (const widget2 of node.widgets) {
widget2.last_y += LiteGraph.NODE_SLOT_HEIGHT;
}
node.setSize([Math.max(sz[0], node.size[0]), Math.max(sz[1], node.size[1])]);
node.setSize([
Math.max(oldWidth, node.size[0]),
Math.max(oldHeight, node.size[1])
]);
return input;
}
__name(convertToInput, "convertToInput");
function convertToWidget(node, widget) {
showWidget(widget);
const sz = node.size;
const [oldWidth, oldHeight] = node.size;
node.removeInput(node.inputs.findIndex((i) => i.widget?.name === widget.name));
for (const widget2 of node.widgets) {
widget2.last_y -= LiteGraph.NODE_SLOT_HEIGHT;
}
node.setSize([Math.max(sz[0], node.size[0]), Math.max(sz[1], node.size[1])]);
node.setSize([
Math.max(oldWidth, node.size[0]),
Math.max(oldHeight, node.size[1])
]);
}
__name(convertToWidget, "convertToWidget");
function getWidgetType(config) {
@ -450,7 +456,7 @@ function setWidgetConfig(slot, config, target) {
__name(setWidgetConfig, "setWidgetConfig");
function mergeIfValid(output, config2, forceUpdate, recreateWidget, config1) {
if (!config1) {
config1 = output.widget[CONFIG] ?? output.widget[GET_CONFIG]();
config1 = getWidgetConfig(output);
}
if (config1[0] instanceof Array) {
if (!isValidCombo(config1[0], config2[0])) return;
@ -753,4 +759,4 @@ export {
mergeIfValid,
setWidgetConfig
};
//# sourceMappingURL=widgetInputs-DdecKYqd.js.map
//# sourceMappingURL=widgetInputs-BJ21PG7d.js.map

1
web/assets/widgetInputs-BJ21PG7d.js.map generated vendored Normal file

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@ -0,0 +1,3 @@
// Shim for extensions/core/vintageClipboard.ts
export const serialise = window.comfyAPI.vintageClipboard.serialise;
export const deserialiseAndCreate = window.comfyAPI.vintageClipboard.deserialiseAndCreate;

4
web/index.html vendored
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@ -6,8 +6,8 @@
<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=no">
<link rel="stylesheet" type="text/css" href="user.css" />
<link rel="stylesheet" type="text/css" href="materialdesignicons.min.css" />
<script type="module" crossorigin src="./assets/index-BHayQCxv.js"></script>
<link rel="stylesheet" crossorigin href="./assets/index-BitceZ14.css">
<script type="module" crossorigin src="./assets/index-B6dYHNhg.js"></script>
<link rel="stylesheet" crossorigin href="./assets/index-BCoLUtIt.css">
</head>
<body class="litegraph grid">
<div id="vue-app"></div>

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@ -1,3 +1,2 @@
// Shim for scripts/changeTracker.ts
export const ChangeTracker = window.comfyAPI.changeTracker.ChangeTracker;
export const globalTracker = window.comfyAPI.changeTracker.globalTracker;

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@ -1,2 +1,4 @@
// Shim for scripts/defaultGraph.ts
export const defaultGraph = window.comfyAPI.defaultGraph.defaultGraph;
export const defaultGraphJSON = window.comfyAPI.defaultGraph.defaultGraphJSON;
export const blankGraph = window.comfyAPI.defaultGraph.blankGraph;

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@ -1,2 +0,0 @@
// Shim for scripts/domWidget.ts
export const addDomClippingSetting = window.comfyAPI.domWidget.addDomClippingSetting;

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@ -1,3 +0,0 @@
// Shim for scripts/workflows.ts
export const ComfyWorkflowManager = window.comfyAPI.workflows.ComfyWorkflowManager;
export const ComfyWorkflow = window.comfyAPI.workflows.ComfyWorkflow;