Compare commits
| Author | SHA1 | Date | |
|---|---|---|---|
 bennykok
|
d735d8ae9c | ||
|
bennykok
|
349aee5420 |
@@ -7,19 +7,15 @@ on:
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paths:
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- "pyproject.toml"
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permissions:
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issues: write
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jobs:
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publish-node:
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name: Publish Custom Node to registry
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runs-on: ubuntu-latest
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if: ${{ github.repository_owner == 'BennyKok' }}
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steps:
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- name: Check out code
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uses: actions/checkout@v4
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- name: Publish Custom Node
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uses: Comfy-Org/publish-node-action@v1
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uses: Comfy-Org/publish-node-action@main
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with:
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## Add your own personal access token to your Github Repository secrets and reference it here.
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personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}
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personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}
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+1
-37
@@ -2,9 +2,8 @@
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@author: BennyKok
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@title: comfyui-deploy
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@nickname: Comfy Deploy
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@description:
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@description:
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"""
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import os
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import sys
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@@ -18,23 +17,19 @@ import requests
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import folder_paths
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from folder_paths import add_model_folder_path, get_filename_list, get_folder_paths
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from tqdm import tqdm
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import re
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from . import custom_routes
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# import routes
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ag_path = os.path.join(os.path.dirname(__file__))
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def get_python_files(path):
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return [f[:-3] for f in os.listdir(path) if f.endswith(".py")]
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def append_to_sys_path(path):
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if path not in sys.path:
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sys.path.append(path)
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paths = ["comfy-nodes"]
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files = []
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@@ -46,45 +41,14 @@ for path in paths:
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NODE_CLASS_MAPPINGS = {}
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NODE_DISPLAY_NAME_MAPPINGS = {}
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def split_camel_case(name):
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# Split on underscores first, then split each part on camelCase
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parts = []
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for part in name.split("_"):
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# Find all camelCase boundaries
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words = re.findall("[A-Z][^A-Z]*", part)
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if not words: # If no camelCase found, use the whole part
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words = [part]
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parts.extend(words)
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return parts
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# Import all the modules and append their mappings
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for file in files:
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module = importlib.import_module(file)
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# Check if the module has explicit mappings
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if hasattr(module, "NODE_CLASS_MAPPINGS"):
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NODE_CLASS_MAPPINGS.update(module.NODE_CLASS_MAPPINGS)
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if hasattr(module, "NODE_DISPLAY_NAME_MAPPINGS"):
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NODE_DISPLAY_NAME_MAPPINGS.update(module.NODE_DISPLAY_NAME_MAPPINGS)
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# Auto-discover classes with ComfyUI node attributes
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for name, obj in inspect.getmembers(module):
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# Check if it's a class and has the required ComfyUI node attributes
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if (
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inspect.isclass(obj)
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and hasattr(obj, "INPUT_TYPES")
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and hasattr(obj, "RETURN_TYPES")
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):
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# Use the class name as the key if not already in mappings
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if name not in NODE_CLASS_MAPPINGS:
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NODE_CLASS_MAPPINGS[name] = obj
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# Create a display name by converting camelCase to Title Case with spaces
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words = split_camel_case(name.replace("ComfyUIDeploy", ""))
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display_name = " ".join(word.capitalize() for word in words)
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# print(display_name, name)
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NODE_DISPLAY_NAME_MAPPINGS[name] = display_name
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WEB_DIRECTORY = "web-plugin"
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__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]
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@@ -1,13 +1,14 @@
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import os
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import io
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import torchaudio
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from folder_paths import get_annotated_filepath
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class ComfyUIDeployExternalAudio:
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RETURN_TYPES = ("AUDIO",)
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RETURN_NAMES = ("audio",)
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FUNCTION = "load_audio"
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CATEGORY = "🔗ComfyDeploy"
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@classmethod
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def INPUT_TYPES(cls):
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return {
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@@ -28,55 +29,30 @@ class ComfyUIDeployExternalAudio:
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"STRING",
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{"multiline": False, "default": ""},
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),
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},
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}
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}
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@classmethod
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def VALIDATE_INPUTS(s, audio_file, **kwargs):
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return True
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def load_audio(
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self,
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input_id,
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audio_file,
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default_value=None,
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display_name=None,
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description=None,
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):
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try:
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import torchaudio
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if audio_file and audio_file != "":
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if audio_file.startswith(("http://", "https://")):
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# Handle URL input
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try:
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import requests
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response = requests.get(audio_file)
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audio_data = io.BytesIO(response.content)
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waveform, sample_rate = torchaudio.load(audio_data)
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except Exception as e:
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print(f"Error loading audio from URL: {e}")
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return (default_value,)
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else:
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# Handle local file
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try:
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audio_path = get_annotated_filepath(audio_file)
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waveform, sample_rate = torchaudio.load(audio_path)
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except Exception as e:
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print(f"Error loading local audio file: {e}")
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return (default_value,)
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audio = {"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate}
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return (audio,)
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def load_audio(self, input_id, audio_file, default_value=None, display_name=None, description=None):
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if audio_file and audio_file != "":
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if audio_file.startswith(('http://', 'https://')):
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# Handle URL input
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import requests
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response = requests.get(audio_file)
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audio_data = io.BytesIO(response.content)
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waveform, sample_rate = torchaudio.load(audio_data)
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else:
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return (default_value,)
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except ImportError as e:
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print(f"Error: torchaudio not installed or cannot be imported: {e}")
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# Handle local file
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audio_path = get_annotated_filepath(audio_file)
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waveform, sample_rate = torchaudio.load(audio_path)
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audio = {"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate}
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return (audio,)
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else:
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return (default_value,)
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NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalAudio": ComfyUIDeployExternalAudio}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"ComfyUIDeployExternalAudio": "External Audio (ComfyUI Deploy)"
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}
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NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalAudio": "External Audio (ComfyUI Deploy)"}
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@@ -1,46 +0,0 @@
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class AnyType(str):
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def __ne__(self, __value: object) -> bool:
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return False
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WILDCARD = AnyType("*")
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class ComfyUIDeployExternalEnum:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"input_id": (
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"STRING",
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{"multiline": False, "default": "input_enum"},
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),
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},
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"optional": {
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"default_value": (
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"STRING",
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{"multiline": False, "default": "", "dynamic_enum": True},
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),
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"options": (
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"STRING",
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{"multiline": True, "default": ""},
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),
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"display_name": (
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"STRING",
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{"multiline": False, "default": ""},
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),
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"description": (
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"STRING",
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{"multiline": True, "default": ""},
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),
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}
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}
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RETURN_TYPES = (WILDCARD,)
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RETURN_NAMES = ("text",)
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FUNCTION = "run"
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CATEGORY = "🔗ComfyDeploy"
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def run(self, input_id, options=None, default_value=None, display_name=None, description=None):
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return [default_value]
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@@ -1,4 +1,8 @@
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import folder_paths
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from PIL import Image, ImageOps
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import numpy as np
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import torch
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import folder_paths
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class AnyType(str):
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@@ -37,10 +41,6 @@ class ComfyUIDeployExternalLora:
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"STRING",
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{"multiline": False, "default": ""},
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),
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"bearer_token": (
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"STRING",
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{"multiline": False, "default": ""},
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),
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},
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}
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@@ -57,7 +57,6 @@ class ComfyUIDeployExternalLora:
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display_name=None,
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description=None,
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lora_url=None,
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bearer_token=None,
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):
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import requests
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import os
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@@ -85,13 +84,9 @@ class ComfyUIDeployExternalLora:
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+ " to "
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+ destination_path
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)
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headers = {"User-Agent": "Mozilla/5.0"}
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if bearer_token:
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headers["Authorization"] = f"Bearer {bearer_token}"
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print("using bearer token")
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response = requests.get(
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lora_url,
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headers=headers,
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headers={"User-Agent": "Mozilla/5.0"},
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allow_redirects=True,
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)
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with open(destination_path, "wb") as out_file:
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@@ -1,54 +0,0 @@
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class ComfyUIDeployExternalNumberSliderInt:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"input_id": (
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"STRING",
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{"multiline": False, "default": "input_number_slider_int"},
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),
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},
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"optional": {
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"default_value": (
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"INT",
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{"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 1, "step": 1},
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),
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"min_value": (
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"INT",
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{"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 0, "step": 1},
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),
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"max_value": (
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"INT",
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{"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 10, "step": 1},
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),
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"display_name": (
|
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"STRING",
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{"multiline": False, "default": ""},
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),
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"description": (
|
||||
"STRING",
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{"multiline": True, "default": ""},
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),
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}
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}
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RETURN_TYPES = ("INT",)
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RETURN_NAMES = ("value",)
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FUNCTION = "run"
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CATEGORY = "🔗ComfyDeploy"
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def run(self, input_id, default_value=None, min_value=0, max_value=10, display_name=None, description=None):
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try:
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int_value = int(round(float(input_id)))
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if min_value <= int_value <= max_value:
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print("my integer", int_value)
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return [int_value]
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else:
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print("Integer out of range. Returning default value:", default_value)
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return [default_value]
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except (ValueError, TypeError):
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print("Invalid input. Returning default value:", default_value)
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return [default_value]
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NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalNumberSliderInt": ComfyUIDeployExternalNumberSliderInt}
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NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalNumberSliderInt": "External Number Slider Int (ComfyUI Deploy)"}
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@@ -1,116 +0,0 @@
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import random
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|
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|
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class ComfyUIDeployExternalSeed:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {
|
||||
"required": {
|
||||
"input_id": (
|
||||
"STRING",
|
||||
{"multiline": False, "default": "input_seed"},
|
||||
),
|
||||
"default_value": (
|
||||
"INT",
|
||||
{"default": -1},
|
||||
),
|
||||
"min_value": (
|
||||
"INT",
|
||||
{"default": 1, "min": 1, "max": 999999999999999},
|
||||
),
|
||||
"max_value": (
|
||||
"INT",
|
||||
{"default": 4294967295, "min": 1, "max": 999999999999999},
|
||||
),
|
||||
},
|
||||
"optional": {
|
||||
"display_name": (
|
||||
"STRING",
|
||||
{"multiline": False, "default": ""},
|
||||
),
|
||||
"description": (
|
||||
"STRING",
|
||||
{
|
||||
"multiline": True,
|
||||
"default": 'For default value:\n"-1" (i.e. not in range): Randomize within the min and max value range. \nin range: Fixed, always the same value\n',
|
||||
},
|
||||
),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("INT",)
|
||||
RETURN_NAMES = ("seed",)
|
||||
FUNCTION = "run"
|
||||
CATEGORY = "🔗ComfyDeploy"
|
||||
|
||||
# Limits
|
||||
_MAX_LIMIT = 999_999_999_999_999 # 15 digits
|
||||
|
||||
# Store cached seed when fixed flag is enabled
|
||||
_cached_seed = None
|
||||
|
||||
@classmethod
|
||||
def IS_CHANGED(
|
||||
cls,
|
||||
input_id,
|
||||
min_value,
|
||||
max_value,
|
||||
default_value=None,
|
||||
**kwargs,
|
||||
):
|
||||
"""Inform ComfyUI whether the node output should be considered changed.
|
||||
|
||||
If default_value is within range (Fixed mode), we return the inputs tuple
|
||||
so the cached result is reused until the user changes something.
|
||||
For Randomize mode, we force re-execution each queue.
|
||||
"""
|
||||
# Clamp values to allowed range for check
|
||||
min_value = max(1, min_value)
|
||||
max_value = min(cls._MAX_LIMIT, max_value)
|
||||
|
||||
# Fixed mode when default_value is within range
|
||||
if (
|
||||
default_value is not None
|
||||
and default_value >= min_value
|
||||
and default_value <= max_value
|
||||
):
|
||||
return (input_id, default_value)
|
||||
|
||||
# For Randomize (default_value is -1 or out of range) we force re-execution
|
||||
import random as _rnd
|
||||
|
||||
return _rnd.random()
|
||||
|
||||
def run(
|
||||
self,
|
||||
input_id,
|
||||
min_value: int,
|
||||
max_value: int,
|
||||
display_name=None,
|
||||
description=None,
|
||||
default_value: int = -1,
|
||||
):
|
||||
# Clamp values to allowed range
|
||||
min_value = max(1, min_value)
|
||||
max_value = min(self._MAX_LIMIT, max_value)
|
||||
|
||||
# Ensure limits are in correct order after clamping
|
||||
if min_value > max_value:
|
||||
min_value, max_value = max_value, min_value
|
||||
|
||||
# Fixed mode: default_value is within range
|
||||
if default_value >= min_value and default_value <= max_value:
|
||||
seed = int(default_value)
|
||||
self._cached_seed = seed
|
||||
return [seed]
|
||||
|
||||
# Randomize mode: default_value is -1 or out of range
|
||||
seed = random.randint(min_value, max_value)
|
||||
self._cached_seed = seed
|
||||
return [seed]
|
||||
|
||||
|
||||
NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalSeed": ComfyUIDeployExternalSeed}
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"ComfyUIDeployExternalSeed": "External Seed (ComfyUI Deploy)"
|
||||
}
|
||||
@@ -748,64 +748,36 @@ class ComfyUIDeployExternalVideo:
|
||||
file_parts = f.split(".")
|
||||
if len(file_parts) > 1 and (file_parts[-1] in video_extensions):
|
||||
files.append(f)
|
||||
return {
|
||||
"required": {
|
||||
"input_id": (
|
||||
"STRING",
|
||||
{"multiline": False, "default": "input_video"},
|
||||
),
|
||||
"force_rate": ("INT", {"default": 0, "min": 0, "max": 60, "step": 1}),
|
||||
"force_size": (
|
||||
[
|
||||
"Disabled",
|
||||
"Custom Height",
|
||||
"Custom Width",
|
||||
"Custom",
|
||||
"256x?",
|
||||
"?x256",
|
||||
"256x256",
|
||||
"512x?",
|
||||
"?x512",
|
||||
"512x512",
|
||||
],
|
||||
),
|
||||
"custom_width": (
|
||||
"INT",
|
||||
{"default": 512, "min": 0, "max": DIMMAX, "step": 8},
|
||||
),
|
||||
"custom_height": (
|
||||
"INT",
|
||||
{"default": 512, "min": 0, "max": DIMMAX, "step": 8},
|
||||
),
|
||||
"frame_load_cap": (
|
||||
"INT",
|
||||
{"default": 0, "min": 0, "max": BIGMAX, "step": 1},
|
||||
),
|
||||
"skip_first_frames": (
|
||||
"INT",
|
||||
{"default": 0, "min": 0, "max": BIGMAX, "step": 1},
|
||||
),
|
||||
"select_every_nth": (
|
||||
"INT",
|
||||
{"default": 1, "min": 1, "max": BIGMAX, "step": 1},
|
||||
),
|
||||
},
|
||||
"optional": {
|
||||
"meta_batch": ("VHS_BatchManager",),
|
||||
"vae": ("VAE",),
|
||||
"default_video": (sorted(files),),
|
||||
"display_name": (
|
||||
"STRING",
|
||||
{"multiline": False, "default": ""},
|
||||
),
|
||||
"description": (
|
||||
"STRING",
|
||||
{"multiline": True, "default": ""},
|
||||
),
|
||||
"default_value_url": ("STRING", {"image_preview": True, "default": ""}),
|
||||
},
|
||||
"hidden": {"unique_id": "UNIQUE_ID"},
|
||||
}
|
||||
return {"required": {
|
||||
"input_id": (
|
||||
"STRING",
|
||||
{"multiline": False, "default": "input_video"},
|
||||
),
|
||||
"force_rate": ("INT", {"default": 0, "min": 0, "max": 60, "step": 1}),
|
||||
"force_size": (["Disabled", "Custom Height", "Custom Width", "Custom", "256x?", "?x256", "256x256", "512x?", "?x512", "512x512"],),
|
||||
"custom_width": ("INT", {"default": 512, "min": 0, "max": DIMMAX, "step": 8}),
|
||||
"custom_height": ("INT", {"default": 512, "min": 0, "max": DIMMAX, "step": 8}),
|
||||
"frame_load_cap": ("INT", {"default": 0, "min": 0, "max": BIGMAX, "step": 1}),
|
||||
"skip_first_frames": ("INT", {"default": 0, "min": 0, "max": BIGMAX, "step": 1}),
|
||||
"select_every_nth": ("INT", {"default": 1, "min": 1, "max": BIGMAX, "step": 1}),
|
||||
},
|
||||
"optional": {
|
||||
"meta_batch": ("VHS_BatchManager",),
|
||||
"vae": ("VAE",),
|
||||
"default_video": (sorted(files),),
|
||||
"display_name": (
|
||||
"STRING",
|
||||
{"multiline": False, "default": ""},
|
||||
),
|
||||
"description": (
|
||||
"STRING",
|
||||
{"multiline": True, "default": ""},
|
||||
),
|
||||
},
|
||||
"hidden": {
|
||||
"unique_id": "UNIQUE_ID"
|
||||
},
|
||||
}
|
||||
|
||||
CATEGORY = "Video Helper Suite 🎥🅥🅗🅢"
|
||||
|
||||
@@ -832,21 +804,16 @@ class ComfyUIDeployExternalVideo:
|
||||
select_every_nth = kwargs.get("select_every_nth")
|
||||
meta_batch = kwargs.get("meta_batch")
|
||||
unique_id = kwargs.get("unique_id")
|
||||
default_value_url = kwargs.get("default_value_url")
|
||||
|
||||
|
||||
input_dir = folder_paths.get_input_directory()
|
||||
if input_id.startswith("http") or (
|
||||
default_value_url and default_value_url.startswith("http")
|
||||
):
|
||||
if input_id.startswith("http"):
|
||||
import requests
|
||||
|
||||
# Use input_id if it's a URL, otherwise use default_value_url
|
||||
url = input_id if input_id.startswith("http") else default_value_url
|
||||
|
||||
print("Fetching video from URL: ", url)
|
||||
response = requests.get(url, stream=True)
|
||||
print("Fetching video from URL: ", input_id)
|
||||
response = requests.get(input_id, stream=True)
|
||||
file_size = int(response.headers.get("Content-Length", 0))
|
||||
file_extension = url.split(".")[-1].split("?")[
|
||||
file_extension = input_id.split(".")[-1].split("?")[
|
||||
0
|
||||
] # Extract extension and handle URLs with parameters
|
||||
if file_extension not in video_extensions:
|
||||
|
||||
@@ -0,0 +1,60 @@
|
||||
import folder_paths
|
||||
class AnyType(str):
|
||||
def __ne__(self, __value: object) -> bool:
|
||||
return False
|
||||
|
||||
from os import walk
|
||||
|
||||
WILDCARD = AnyType("*")
|
||||
|
||||
MODEL_EXTENSIONS = {
|
||||
"safetensors": "SafeTensors file format",
|
||||
"ckpt": "Checkpoint file",
|
||||
"pth": "PyTorch serialized file",
|
||||
"pkl": "Pickle file",
|
||||
"onnx": "ONNX file",
|
||||
}
|
||||
|
||||
def fetch_files(path):
|
||||
for (dirpath, dirnames, filenames) in walk(path):
|
||||
fs = []
|
||||
if len(dirnames) > 0:
|
||||
for dirname in dirnames:
|
||||
fs.extend(fetch_files(f"{dirpath}/{dirname}"))
|
||||
for filename in filenames:
|
||||
# Remove "./models/" from the beginning of dirpath
|
||||
relative_dirpath = dirpath.replace("./models/", "", 1)
|
||||
file_path = f"{relative_dirpath}/{filename}"
|
||||
|
||||
# Only add files that are known model extensions
|
||||
file_extension = filename.split('.')[-1].lower()
|
||||
if file_extension in MODEL_EXTENSIONS:
|
||||
fs.append(file_path)
|
||||
|
||||
return fs
|
||||
allModels = fetch_files("./models")
|
||||
|
||||
class ComfyUIDeployModalList:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {
|
||||
"required": {
|
||||
"model": (allModels, ),
|
||||
}
|
||||
}
|
||||
|
||||
RETURN_TYPES = (WILDCARD,)
|
||||
RETURN_NAMES = ("model",)
|
||||
|
||||
FUNCTION = "run"
|
||||
|
||||
CATEGORY = "🔗ComfyDeploy"
|
||||
|
||||
def run(self, model=""):
|
||||
# Split the model path by '/' and select the last item
|
||||
model_name = model.split('/')[-1]
|
||||
return [model_name]
|
||||
|
||||
|
||||
NODE_CLASS_MAPPINGS = {"ComfyUIDeployModelList": ComfyUIDeployModalList}
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployModelList": "Model List (ComfyUI Deploy)"}
|
||||
@@ -1,78 +0,0 @@
|
||||
# In file: comfyui-deploy/comfy-nodes/output_exr.py
|
||||
|
||||
import os
|
||||
import numpy as np
|
||||
import folder_paths
|
||||
|
||||
# Try to set up OpenCV for EXR writing.
|
||||
try:
|
||||
os.environ["OPENCV_IO_ENABLE_OPENEXR"] = "1"
|
||||
import cv2
|
||||
OPENCV_AVAILABLE = True
|
||||
except ImportError:
|
||||
print("Warning: OpenCV not found for ComfyDeployOutputEXR. Please add opencv-python-headless to requirements.txt")
|
||||
OPENCV_AVAILABLE = False
|
||||
|
||||
# ALIGNED: Renamed class to match project conventions
|
||||
class ComfyDeployOutputEXR:
|
||||
def __init__(self):
|
||||
self.output_dir = folder_paths.get_output_directory()
|
||||
self.type = "output"
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {
|
||||
"required": {
|
||||
"images": ("IMAGE", ),
|
||||
"filename_prefix": ("STRING", {"default": "ComfyDeploy_EXR"})
|
||||
},
|
||||
# ADDED: Optional output_id for consistency with other ComfyDeploy nodes
|
||||
"optional": {
|
||||
"output_id": ("STRING", {"multiline": False, "default": "output_exr"}),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ()
|
||||
# ALIGNED: Changed function name to 'run'
|
||||
FUNCTION = "run"
|
||||
OUTPUT_NODE = True
|
||||
# ALIGNED: Matched the category name
|
||||
CATEGORY = "🔗ComfyDeploy"
|
||||
DESCRIPTION = "Saves the input images as EXR (HDR) files."
|
||||
|
||||
def run(self, images, filename_prefix="ComfyDeploy_EXR", output_id="output_exr"):
|
||||
if not OPENCV_AVAILABLE:
|
||||
raise ImportError("OpenCV is required to save EXR files. Please ensure opencv-python-headless is in requirements.txt.")
|
||||
|
||||
full_output_folder, filename, counter, subfolder, filename_prefix = (
|
||||
folder_paths.get_save_image_path(
|
||||
filename_prefix, self.output_dir, images[0].shape[1], images[0].shape[0]
|
||||
)
|
||||
)
|
||||
results = list()
|
||||
|
||||
for image in images:
|
||||
image_np = image.cpu().numpy()
|
||||
|
||||
if image_np.dtype != np.float32:
|
||||
image_np = image_np.astype(np.float32)
|
||||
|
||||
file = f"{filename}_{counter:05}.exr"
|
||||
file_path = os.path.join(full_output_folder, file)
|
||||
|
||||
image_np_bgr = cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)
|
||||
cv2.imwrite(file_path, image_np_bgr)
|
||||
|
||||
results.append({
|
||||
"filename": file,
|
||||
"subfolder": subfolder,
|
||||
"type": self.type,
|
||||
"output_id": output_id, # ADDED
|
||||
})
|
||||
counter += 1
|
||||
|
||||
return {"ui": {"images": results}}
|
||||
|
||||
# ALIGNED: Mappings are defined at the bottom of the node file in this project
|
||||
NODE_CLASS_MAPPINGS = {"ComfyDeployOutputEXR": ComfyDeployOutputEXR}
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {"ComfyDeployOutputEXR": "EXR Output (ComfyDeploy)"}
|
||||
@@ -1,99 +0,0 @@
|
||||
import os
|
||||
import json
|
||||
import folder_paths
|
||||
|
||||
|
||||
class ComfyDeployOutputText:
|
||||
def __init__(self):
|
||||
self.output_dir = folder_paths.get_output_directory()
|
||||
self.type = "output"
|
||||
self.prefix_append = ""
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {
|
||||
"required": {
|
||||
"text": (
|
||||
"STRING",
|
||||
{
|
||||
"multiline": True,
|
||||
"forceInput": True,
|
||||
"tooltip": "The text to save.",
|
||||
},
|
||||
),
|
||||
"filename_prefix": (
|
||||
"STRING",
|
||||
{
|
||||
"default": "ComfyUI",
|
||||
"tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% to include values from nodes.",
|
||||
},
|
||||
),
|
||||
"file_type": (["txt", "json", "md"], {"default": "txt"}),
|
||||
},
|
||||
"optional": {
|
||||
"output_id": (
|
||||
"STRING",
|
||||
{"multiline": False, "default": "output_text"},
|
||||
),
|
||||
},
|
||||
"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ()
|
||||
FUNCTION = "run"
|
||||
|
||||
OUTPUT_NODE = True
|
||||
CATEGORY = "🔗ComfyDeploy"
|
||||
DESCRIPTION = "Saves the input text to your ComfyUI output directory."
|
||||
|
||||
def run(
|
||||
self,
|
||||
text,
|
||||
filename_prefix="ComfyUI",
|
||||
file_type="txt",
|
||||
output_id="output_text",
|
||||
prompt=None,
|
||||
extra_pnginfo=None,
|
||||
):
|
||||
filename_prefix += self.prefix_append
|
||||
# For text, we don't need dimensions, so pass 0, 0
|
||||
full_output_folder, filename, counter, subfolder, filename_prefix = (
|
||||
folder_paths.get_save_image_path(filename_prefix, self.output_dir, 0, 0)
|
||||
)
|
||||
|
||||
results = list()
|
||||
|
||||
# Create file path
|
||||
file = f"{filename}_{counter:05}_.{file_type}"
|
||||
file_path = os.path.join(full_output_folder, file)
|
||||
|
||||
# Save the text based on file type
|
||||
if file_type == "json":
|
||||
try:
|
||||
# Try to save as JSON if the text is valid JSON
|
||||
json_data = json.loads(text) if isinstance(text, str) else text
|
||||
with open(file_path, "w", encoding="utf-8") as f:
|
||||
json.dump(json_data, f, indent=2)
|
||||
except json.JSONDecodeError:
|
||||
# Fall back to saving as plain text if not valid JSON
|
||||
with open(file_path, "w", encoding="utf-8") as f:
|
||||
f.write(text)
|
||||
else:
|
||||
# Save as plain text for txt and md
|
||||
with open(file_path, "w", encoding="utf-8") as f:
|
||||
f.write(text)
|
||||
|
||||
results.append(
|
||||
{
|
||||
"filename": file,
|
||||
"subfolder": subfolder,
|
||||
"type": self.type,
|
||||
"output_id": output_id,
|
||||
}
|
||||
)
|
||||
|
||||
return {"ui": {"text_file": results}}
|
||||
|
||||
|
||||
NODE_CLASS_MAPPINGS = {"ComfyDeployOutputText": ComfyDeployOutputText}
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {"ComfyDeployOutputText": "Text Output (ComfyDeploy)"}
|
||||
+147
-457
@@ -31,7 +31,6 @@ import torch
|
||||
import psutil
|
||||
from collections import OrderedDict
|
||||
import io
|
||||
from urllib.parse import urlencode
|
||||
|
||||
# Global session
|
||||
client_session = None
|
||||
@@ -65,14 +64,43 @@ async def ensure_client_session():
|
||||
|
||||
async def cleanup():
|
||||
global client_session
|
||||
if client_session:
|
||||
await client_session.close()
|
||||
try:
|
||||
# Cancel the monitor task if it exists
|
||||
if hasattr(upload_queue, "monitor_task") and upload_queue.monitor_task:
|
||||
if not upload_queue.monitor_task.done():
|
||||
upload_queue.monitor_task.cancel()
|
||||
try:
|
||||
await upload_queue.monitor_task
|
||||
except asyncio.CancelledError:
|
||||
pass
|
||||
except RuntimeError as e:
|
||||
# Handle case where event loop is closed
|
||||
if "Event loop is closed" in str(e):
|
||||
logger.info("Event loop closed during cleanup")
|
||||
else:
|
||||
raise
|
||||
logger.info("Upload queue monitor task cancelled")
|
||||
|
||||
# Clean up the client session
|
||||
if client_session:
|
||||
await client_session.close()
|
||||
|
||||
# Clean up the upload queue
|
||||
# await upload_queue.cleanup()
|
||||
except Exception as e:
|
||||
logger.error(f"Error during cleanup: {str(e)}")
|
||||
|
||||
|
||||
def exit_handler():
|
||||
print("Exiting the application. Initiating cleanup...")
|
||||
loop = asyncio.get_event_loop()
|
||||
loop.run_until_complete(cleanup())
|
||||
try:
|
||||
loop = asyncio.get_event_loop()
|
||||
if loop.is_closed():
|
||||
logger.warning("Event loop is already closed during exit")
|
||||
return
|
||||
loop.run_until_complete(cleanup())
|
||||
except Exception as e:
|
||||
print(f"Error during exit cleanup: {str(e)}")
|
||||
|
||||
|
||||
atexit.register(exit_handler)
|
||||
@@ -159,8 +187,6 @@ from logging import basicConfig, getLogger
|
||||
# Check for an environment variable to enable/disable Logfire
|
||||
use_logfire = os.environ.get("USE_LOGFIRE", "false").lower() == "true"
|
||||
|
||||
API_KEY_COMFY_ORG = os.environ.get("API_KEY_COMFY_ORG", None)
|
||||
|
||||
if use_logfire:
|
||||
try:
|
||||
import logfire
|
||||
@@ -265,7 +291,7 @@ def clear_current_prompt(sid):
|
||||
streaming_prompt_metadata[sid].running_prompt_ids.clear()
|
||||
|
||||
|
||||
async def post_prompt(json_data):
|
||||
def post_prompt(json_data):
|
||||
prompt_server = server.PromptServer.instance
|
||||
json_data = prompt_server.trigger_on_prompt(json_data)
|
||||
|
||||
@@ -281,58 +307,16 @@ async def post_prompt(json_data):
|
||||
|
||||
if "prompt" in json_data:
|
||||
prompt = json_data["prompt"]
|
||||
prompt_id = json_data.get("prompt_id") or str(uuid.uuid4())
|
||||
|
||||
partial_execution_targets = None
|
||||
if "partial_execution_targets" in json_data:
|
||||
partial_execution_targets = json_data["partial_execution_targets"]
|
||||
|
||||
# Handle different validate_prompt signatures (newest to oldest)
|
||||
valid = None
|
||||
last_error = None
|
||||
|
||||
# v0.3.48 (3 args)
|
||||
try:
|
||||
valid = await execution.validate_prompt(
|
||||
prompt_id, prompt, partial_execution_targets
|
||||
)
|
||||
except TypeError as e:
|
||||
last_error = e
|
||||
logger.debug(
|
||||
f"validate_prompt with 3 params not supported, trying with 2. Debug: {last_error}"
|
||||
)
|
||||
|
||||
# v0.3.45 - 0.3.47 (2 args)
|
||||
if valid is None:
|
||||
try:
|
||||
valid = await execution.validate_prompt(prompt_id, prompt)
|
||||
except TypeError as e:
|
||||
last_error = e
|
||||
logger.debug(
|
||||
f"validate_prompt with 2 params not supported, trying legacy signature. Debug: {last_error}"
|
||||
)
|
||||
|
||||
# v0.3.44 or older (1 arg)
|
||||
if valid is None:
|
||||
try:
|
||||
valid = execution.validate_prompt(prompt)
|
||||
except TypeError as e:
|
||||
last_error = e
|
||||
logger.error(
|
||||
f"validate_prompt failed with all signatures. Last error: {last_error}"
|
||||
)
|
||||
raise
|
||||
|
||||
valid = execution.validate_prompt(prompt)
|
||||
extra_data = {}
|
||||
if "extra_data" in json_data:
|
||||
extra_data = json_data["extra_data"]
|
||||
|
||||
if API_KEY_COMFY_ORG is not None:
|
||||
extra_data["api_key_comfy_org"] = API_KEY_COMFY_ORG
|
||||
|
||||
if "client_id" in json_data:
|
||||
extra_data["client_id"] = json_data["client_id"]
|
||||
if valid[0]:
|
||||
# if the prompt id is provided
|
||||
prompt_id = json_data.get("prompt_id") or str(uuid.uuid4())
|
||||
outputs_to_execute = valid[2]
|
||||
prompt_server.prompt_queue.put(
|
||||
(number, prompt_id, prompt, extra_data, outputs_to_execute)
|
||||
@@ -351,17 +335,12 @@ async def post_prompt(json_data):
|
||||
|
||||
|
||||
def randomSeed(num_digits=15):
|
||||
# Special case for SONICSampler which uses np.int32
|
||||
if num_digits == "sonic":
|
||||
return random.randint(0, 2147483647) # np.iinfo(np.int32).max
|
||||
|
||||
# Original logic for other cases
|
||||
range_start = 10 ** (num_digits - 1)
|
||||
range_end = (10**num_digits) - 1
|
||||
return random.randint(range_start, range_end)
|
||||
|
||||
|
||||
def apply_random_seed_to_workflow(workflow_api, workflow):
|
||||
def apply_random_seed_to_workflow(workflow_api):
|
||||
"""
|
||||
Applies a random seed to each element in the workflow_api that has a 'seed' input.
|
||||
|
||||
@@ -374,48 +353,6 @@ def apply_random_seed_to_workflow(workflow_api, workflow):
|
||||
# If seed is a list, it's an input from another node (generally `external number int`)
|
||||
if isinstance(workflow_api[key]["inputs"]["seed"], list):
|
||||
continue
|
||||
|
||||
# Check node type in workflow to determine if we should randomize
|
||||
node_id = key
|
||||
should_skip = (
|
||||
False # Add a flag to track if we should skip randomization
|
||||
)
|
||||
|
||||
for node in workflow["nodes"]:
|
||||
if str(node["id"]) == node_id and node["type"] == "KSampler":
|
||||
# Check if this node has widgets_values and if seed setting is not "fixed"
|
||||
if "widgets_values" in node and len(node["widgets_values"]) > 1:
|
||||
seed_mode = node["widgets_values"][1]
|
||||
if seed_mode == "fixed":
|
||||
# Skip randomization for fixed seeds
|
||||
logger.info(
|
||||
f"Skipping random seed for KSampler (node {node_id}) as it's set to fixed"
|
||||
)
|
||||
should_skip = True # Set the flag to skip randomization
|
||||
break # Exit the inner loop
|
||||
|
||||
# Apply random seed for non-fixed seeds (randomize, iter, etc.)
|
||||
workflow_api[key]["inputs"]["seed"] = randomSeed()
|
||||
logger.info(
|
||||
f"Applied random seed {workflow_api[key]['inputs']['seed']} to KSampler (node {node_id})"
|
||||
)
|
||||
should_skip = (
|
||||
True # Set the flag to skip default randomization
|
||||
)
|
||||
break # Exit the inner loop
|
||||
break # This break will skip checking other nodes if widgets_values doesn't exist
|
||||
|
||||
# Skip the rest of the code for this key if we already handled it
|
||||
if should_skip:
|
||||
continue
|
||||
|
||||
# Special case for SONICSampler
|
||||
if workflow_api[key]["class_type"] == "SONICSampler":
|
||||
workflow_api[key]["inputs"]["seed"] = randomSeed("sonic")
|
||||
logger.info(
|
||||
f"Applied random seed {workflow_api[key]['inputs']['seed']} to SONICSampler"
|
||||
)
|
||||
continue
|
||||
if workflow_api[key]["class_type"] == "PromptExpansion":
|
||||
workflow_api[key]["inputs"]["seed"] = randomSeed(8)
|
||||
logger.info(
|
||||
@@ -449,12 +386,6 @@ def apply_random_seed_to_workflow(workflow_api, workflow):
|
||||
f"Applied random noise_seed {workflow_api[key]['inputs']['noise_seed']} to SamplerCustom"
|
||||
)
|
||||
continue
|
||||
if workflow_api[key]["class_type"] == "XlabsSampler":
|
||||
workflow_api[key]["inputs"]["noise_seed"] = randomSeed()
|
||||
logger.info(
|
||||
f"Applied random noise_seed {workflow_api[key]['inputs']['noise_seed']} to SamplerCustom"
|
||||
)
|
||||
continue
|
||||
|
||||
|
||||
def apply_inputs_to_workflow(workflow_api: Any, inputs: Any, sid: str = None):
|
||||
@@ -495,9 +426,6 @@ def apply_inputs_to_workflow(workflow_api: Any, inputs: Any, sid: str = None):
|
||||
if value["class_type"] == "ComfyUIDeployExternalImageBatch":
|
||||
value["inputs"]["images"] = new_value
|
||||
|
||||
if value["class_type"] == "ComfyUIDeployExternalEnum":
|
||||
value["inputs"]["default_value"] = new_value
|
||||
|
||||
if value["class_type"] == "ComfyUIDeployExternalLora":
|
||||
value["inputs"]["lora_url"] = new_value
|
||||
|
||||
@@ -516,12 +444,6 @@ def apply_inputs_to_workflow(workflow_api: Any, inputs: Any, sid: str = None):
|
||||
if value["class_type"] == "ComfyUIDeployExternalEXR":
|
||||
value["inputs"]["exr_file"] = new_value
|
||||
|
||||
if value["class_type"] == "ComfyUIDeployExternalSeed":
|
||||
logger.info(
|
||||
f"Applied random seed {new_value} to {value['class_type']}"
|
||||
)
|
||||
value["inputs"]["default_value"] = new_value
|
||||
|
||||
|
||||
def send_prompt(sid: str, inputs: StreamingPrompt):
|
||||
# workflow_api = inputs.workflow_api
|
||||
@@ -529,7 +451,7 @@ def send_prompt(sid: str, inputs: StreamingPrompt):
|
||||
workflow = copy.deepcopy(inputs.workflow)
|
||||
|
||||
# Random seed
|
||||
apply_random_seed_to_workflow(workflow_api, workflow)
|
||||
apply_random_seed_to_workflow(workflow_api)
|
||||
|
||||
logger.info("getting inputs", inputs.inputs)
|
||||
|
||||
@@ -539,15 +461,15 @@ def send_prompt(sid: str, inputs: StreamingPrompt):
|
||||
|
||||
prompt_id = str(uuid.uuid4())
|
||||
|
||||
# prompt = {
|
||||
# "prompt": workflow_api,
|
||||
# "client_id": sid, # "comfy_deploy_instance", #api.client_id
|
||||
# "prompt_id": prompt_id,
|
||||
# "extra_data": {"extra_pnginfo": {"workflow": workflow}},
|
||||
# }
|
||||
prompt = {
|
||||
"prompt": workflow_api,
|
||||
"client_id": sid, # "comfy_deploy_instance", #api.client_id
|
||||
"prompt_id": prompt_id,
|
||||
"extra_data": {"extra_pnginfo": {"workflow": workflow}},
|
||||
}
|
||||
|
||||
try:
|
||||
# res = post_prompt(prompt)
|
||||
res = post_prompt(prompt)
|
||||
inputs.running_prompt_ids.add(prompt_id)
|
||||
prompt_metadata[prompt_id] = SimplePrompt(
|
||||
status_endpoint=inputs.status_endpoint,
|
||||
@@ -558,7 +480,7 @@ def send_prompt(sid: str, inputs: StreamingPrompt):
|
||||
except Exception as e:
|
||||
error_type = type(e).__name__
|
||||
stack_trace_short = traceback.format_exc().strip().split("\n")[-2]
|
||||
# stack_trace = traceback.format_exc().strip()
|
||||
stack_trace = traceback.format_exc().strip()
|
||||
logger.info(f"error: {error_type}, {e}")
|
||||
logger.info(f"stack trace: {stack_trace_short}")
|
||||
|
||||
@@ -615,7 +537,7 @@ async def comfy_deploy_run(request):
|
||||
workflow = data.get("workflow")
|
||||
|
||||
# Now it handles directly in here
|
||||
apply_random_seed_to_workflow(workflow_api, workflow)
|
||||
apply_random_seed_to_workflow(workflow_api)
|
||||
apply_inputs_to_workflow(workflow_api, inputs)
|
||||
|
||||
prompt = {
|
||||
@@ -634,7 +556,7 @@ async def comfy_deploy_run(request):
|
||||
)
|
||||
|
||||
try:
|
||||
res = await post_prompt(prompt)
|
||||
res = post_prompt(prompt)
|
||||
except Exception as e:
|
||||
error_type = type(e).__name__
|
||||
stack_trace_short = traceback.format_exc().strip().split("\n")[-2]
|
||||
@@ -682,7 +604,7 @@ async def stream_prompt(data, token):
|
||||
gpu_event_id = data.get("gpu_event_id", None)
|
||||
|
||||
# Now it handles directly in here
|
||||
apply_random_seed_to_workflow(workflow_api, workflow)
|
||||
apply_random_seed_to_workflow(workflow_api)
|
||||
apply_inputs_to_workflow(workflow_api, inputs)
|
||||
|
||||
prompt = {
|
||||
@@ -703,7 +625,7 @@ async def stream_prompt(data, token):
|
||||
# log('info', "Begin prompt", prompt=prompt)
|
||||
|
||||
try:
|
||||
res = await post_prompt(prompt)
|
||||
res = post_prompt(prompt)
|
||||
except Exception as e:
|
||||
error_type = type(e).__name__
|
||||
stack_trace_short = traceback.format_exc().strip().split("\n")[-2]
|
||||
@@ -1305,11 +1227,22 @@ def handle_execute(class_type, last_node_id, prompt_id, server, unique_id):
|
||||
|
||||
try:
|
||||
origin_execute = execution.execute
|
||||
is_async = asyncio.iscoroutinefunction(origin_execute)
|
||||
|
||||
if is_async:
|
||||
|
||||
async def swizzle_execute(
|
||||
def swizzle_execute(
|
||||
server,
|
||||
dynprompt,
|
||||
caches,
|
||||
current_item,
|
||||
extra_data,
|
||||
executed,
|
||||
prompt_id,
|
||||
execution_list,
|
||||
pending_subgraph_results,
|
||||
):
|
||||
unique_id = current_item
|
||||
class_type = dynprompt.get_node(unique_id)["class_type"]
|
||||
last_node_id = server.last_node_id
|
||||
result = origin_execute(
|
||||
server,
|
||||
dynprompt,
|
||||
caches,
|
||||
@@ -1319,61 +1252,12 @@ try:
|
||||
prompt_id,
|
||||
execution_list,
|
||||
pending_subgraph_results,
|
||||
pending_async_nodes,
|
||||
):
|
||||
unique_id = current_item
|
||||
class_type = dynprompt.get_node(unique_id)["class_type"]
|
||||
last_node_id = server.last_node_id
|
||||
|
||||
result = await origin_execute(
|
||||
server,
|
||||
dynprompt,
|
||||
caches,
|
||||
current_item,
|
||||
extra_data,
|
||||
executed,
|
||||
prompt_id,
|
||||
execution_list,
|
||||
pending_subgraph_results,
|
||||
pending_async_nodes,
|
||||
)
|
||||
|
||||
handle_execute(class_type, last_node_id, prompt_id, server, unique_id)
|
||||
return result
|
||||
else:
|
||||
|
||||
def swizzle_execute(
|
||||
server,
|
||||
dynprompt,
|
||||
caches,
|
||||
current_item,
|
||||
extra_data,
|
||||
executed,
|
||||
prompt_id,
|
||||
execution_list,
|
||||
pending_subgraph_results,
|
||||
):
|
||||
unique_id = current_item
|
||||
class_type = dynprompt.get_node(unique_id)["class_type"]
|
||||
last_node_id = server.last_node_id
|
||||
|
||||
result = origin_execute(
|
||||
server,
|
||||
dynprompt,
|
||||
caches,
|
||||
current_item,
|
||||
extra_data,
|
||||
executed,
|
||||
prompt_id,
|
||||
execution_list,
|
||||
pending_subgraph_results,
|
||||
)
|
||||
|
||||
handle_execute(class_type, last_node_id, prompt_id, server, unique_id)
|
||||
return result
|
||||
)
|
||||
handle_execute(class_type, last_node_id, prompt_id, server, unique_id)
|
||||
return result
|
||||
|
||||
execution.execute = swizzle_execute
|
||||
except Exception:
|
||||
except Exception as e:
|
||||
pass
|
||||
|
||||
|
||||
@@ -1439,7 +1323,7 @@ send_json = prompt_server.send_json
|
||||
|
||||
|
||||
async def send_json_override(self, event, data, sid=None):
|
||||
# logger.info(f"INTERNAL: event={event}, data={data}, sid={sid}")
|
||||
# logger.info("INTERNAL:", event, data, sid)
|
||||
prompt_id = data.get("prompt_id")
|
||||
|
||||
target_sid = sid
|
||||
@@ -1457,7 +1341,7 @@ async def send_json_override(self, event, data, sid=None):
|
||||
if prompt_id in comfy_message_queues:
|
||||
comfy_message_queues[prompt_id].put_nowait({"event": event, "data": data})
|
||||
|
||||
asyncio.create_task(update_run_ws_event(prompt_id, event, data))
|
||||
# asyncio.create_task(update_run_ws_event(prompt_id, event, data))
|
||||
|
||||
if event == "execution_start":
|
||||
if prompt_id in prompt_metadata:
|
||||
@@ -1517,15 +1401,16 @@ async def send_json_override(self, event, data, sid=None):
|
||||
logger.info(format_table(headers, table_data))
|
||||
# print("========================\n")
|
||||
|
||||
timeline = format_execution_timeline(NODE_EXECUTION_TIMES)
|
||||
logger.info(f"\nNode Execution Timeline:\n{timeline}")
|
||||
# Clear the execution times for the next run
|
||||
|
||||
# the last executing event is none, then the workflow is finished
|
||||
if event == "executing" and data.get("node") is None:
|
||||
mark_prompt_done(prompt_id=prompt_id)
|
||||
# We will now rely on the UploadQueue worker to set the final SUCCESS status
|
||||
# after all uploads are confirmed complete.
|
||||
|
||||
if not have_pending_upload(prompt_id):
|
||||
# await update_run(prompt_id, Status.SUCCESS) # <-- REMOVE/COMMENT OUT
|
||||
if prompt_id in prompt_metadata: # <-- REMOVE/COMMENT OUT THIS BLOCK
|
||||
await update_run(prompt_id, Status.SUCCESS)
|
||||
if prompt_id in prompt_metadata:
|
||||
current_time = time.perf_counter()
|
||||
if prompt_metadata[prompt_id].start_time is not None:
|
||||
elapsed_time = current_time - prompt_metadata[prompt_id].start_time
|
||||
@@ -1966,13 +1851,12 @@ async def upload_file(
|
||||
|
||||
|
||||
def have_pending_upload(prompt_id):
|
||||
# Check if there are pending uploads in the queue
|
||||
if (
|
||||
prompt_id in upload_queue.pending_uploads
|
||||
and upload_queue.pending_uploads[prompt_id]
|
||||
prompt_id in prompt_metadata
|
||||
and len(prompt_metadata[prompt_id].uploading_nodes) > 0
|
||||
):
|
||||
logger.info(
|
||||
f"Have pending upload {len(upload_queue.pending_uploads[prompt_id])}"
|
||||
f"Have pending upload {len(prompt_metadata[prompt_id].uploading_nodes)}"
|
||||
)
|
||||
return True
|
||||
|
||||
@@ -2027,11 +1911,16 @@ async def handle_error(prompt_id, data, e: Exception):
|
||||
async def update_file_status(
|
||||
prompt_id: str, data, uploading, have_error=False, node_id=None
|
||||
):
|
||||
# We're using upload_queue as the single source of truth for tracking uploads
|
||||
# The upload_queue.pending_uploads is managed by the UploadQueue class itself
|
||||
# We no longer need to track uploading_nodes in prompt_metadata
|
||||
# if 'uploading_nodes' not in prompt_metadata[prompt_id]:
|
||||
# prompt_metadata[prompt_id]['uploading_nodes'] = set()
|
||||
|
||||
# logger.info(f"Pending uploads in queue: {upload_queue.pending_uploads.get(prompt_id, set())}")
|
||||
if node_id is not None:
|
||||
if uploading:
|
||||
prompt_metadata[prompt_id].uploading_nodes.add(node_id)
|
||||
else:
|
||||
prompt_metadata[prompt_id].uploading_nodes.discard(node_id)
|
||||
|
||||
# logger.info(f"Remaining uploads: {prompt_metadata[prompt_id].uploading_nodes}")
|
||||
# Update the remote status
|
||||
|
||||
if have_error:
|
||||
@@ -2045,15 +1934,15 @@ async def update_file_status(
|
||||
return
|
||||
|
||||
# if there are still nodes that are uploading, then we set the status to uploading
|
||||
# if uploading:
|
||||
# if prompt_metadata[prompt_id].status != Status.UPLOADING:
|
||||
# await update_run(prompt_id, Status.UPLOADING)
|
||||
# await send(
|
||||
# "uploading",
|
||||
# {
|
||||
# "prompt_id": prompt_id,
|
||||
# },
|
||||
# )
|
||||
if uploading:
|
||||
if prompt_metadata[prompt_id].status != Status.UPLOADING:
|
||||
await update_run(prompt_id, Status.UPLOADING)
|
||||
await send(
|
||||
"uploading",
|
||||
{
|
||||
"prompt_id": prompt_id,
|
||||
},
|
||||
)
|
||||
|
||||
# if there are no nodes that are uploading, then we set the status to success
|
||||
elif (
|
||||
@@ -2079,7 +1968,7 @@ async def handle_upload(
|
||||
|
||||
for item in items:
|
||||
# Skipping temp files
|
||||
if isinstance(item, dict) and item.get("type") == "temp":
|
||||
if item.get("type") == "temp":
|
||||
continue
|
||||
|
||||
file_type = item.get(content_type_key, default_content_type)
|
||||
@@ -2130,30 +2019,22 @@ async def upload_in_background(
|
||||
("files", "content_type", "image/png"),
|
||||
("gifs", "format", "image/gif"),
|
||||
("model_file", "format", "application/octet-stream"),
|
||||
("result", "format", "application/octet-stream"),
|
||||
("text_file", "format", "text/plain"),
|
||||
("audio", "format", "audio/mpeg"),
|
||||
]:
|
||||
items = data.get(file_type, [])
|
||||
|
||||
for item in items:
|
||||
# if is model_file, just add it to the data
|
||||
if file_type == "model_file" or file_type == "result":
|
||||
if file_type == "model_file":
|
||||
if isinstance(item, str):
|
||||
filename = os.path.basename(item)
|
||||
# Extract folder name from the path
|
||||
folder_path = os.path.dirname(item)
|
||||
subfolder = (
|
||||
os.path.basename(folder_path) if folder_path else ""
|
||||
)
|
||||
item = {
|
||||
"filename": filename,
|
||||
"subfolder": subfolder,
|
||||
"subfolder": "",
|
||||
"type": "output",
|
||||
}
|
||||
|
||||
# Skip temp files
|
||||
if isinstance(item, dict) and item.get("type") == "temp":
|
||||
if item.get("type") == "temp":
|
||||
continue
|
||||
|
||||
# Add to the upload queue instead of uploading immediately
|
||||
@@ -2218,9 +2099,6 @@ async def update_run_with_output(
|
||||
or "files" in data
|
||||
or "gifs" in data
|
||||
or "model_file" in data
|
||||
or "result" in data
|
||||
or "text_file" in data
|
||||
or "audio" in data
|
||||
)
|
||||
if bypass_upload and have_upload_media:
|
||||
print(
|
||||
@@ -2320,8 +2198,8 @@ async def initialize_upload_queue(app=None):
|
||||
upload_queue.max_concurrent,
|
||||
)
|
||||
|
||||
# Start the queue monitoring task in the same event loop
|
||||
asyncio.create_task(monitor_upload_queue())
|
||||
# Store the monitor task reference
|
||||
upload_queue.monitor_task = asyncio.create_task(monitor_upload_queue())
|
||||
|
||||
|
||||
# Get the server's event loop and initialize there
|
||||
@@ -2531,11 +2409,6 @@ class UploadQueue:
|
||||
logger.warning(f"No upload endpoint for prompt ID: {prompt_id}")
|
||||
return
|
||||
|
||||
# Check if file_info is a valid dictionary with a filename
|
||||
if not isinstance(file_info, dict) or "filename" not in file_info:
|
||||
logger.warning(f"Invalid file_info for prompt ID {prompt_id}: {file_info}")
|
||||
return
|
||||
|
||||
filename = file_info.get("filename")
|
||||
subfolder = file_info.get("subfolder")
|
||||
file_type = file_info.get("type", "output")
|
||||
@@ -2686,12 +2559,8 @@ class UploadQueue:
|
||||
# If this was the last file for this prompt, show the stats summary
|
||||
if (
|
||||
prompt_id in self.pending_uploads
|
||||
# We now rely on the worker's finally block for the final SUCCESS update.
|
||||
# Check if the set becomes empty *after* removal in the worker.
|
||||
and len(self.pending_uploads[prompt_id]) == 1
|
||||
):
|
||||
# await update_run(prompt_id, Status.SUCCESS) # <-- REMOVE/COMMENT OUT
|
||||
|
||||
self._log_upload_stats(prompt_id)
|
||||
# Clean up stats
|
||||
del self.upload_stats[prompt_id]
|
||||
@@ -2812,8 +2681,6 @@ class UploadQueue:
|
||||
node_id = upload_task["node_id"]
|
||||
upload_id = upload_task["upload_id"]
|
||||
|
||||
print(file_info)
|
||||
|
||||
try:
|
||||
# Coordinate the actual start of the upload
|
||||
async with self.upload_lock:
|
||||
@@ -2829,57 +2696,51 @@ class UploadQueue:
|
||||
logger.error(f"Upload failed: {str(e)}")
|
||||
logger.error(traceback.format_exc())
|
||||
finally:
|
||||
async with self.lock: # Acquire lock to protect shared dict access
|
||||
if prompt_id in self.pending_uploads:
|
||||
self.pending_uploads[prompt_id].discard(upload_id)
|
||||
# Remove this upload from tracking
|
||||
if prompt_id in self.pending_uploads:
|
||||
self.pending_uploads[prompt_id].discard(upload_id)
|
||||
# Remove from node tracking if applicable
|
||||
if (
|
||||
node_id
|
||||
and prompt_id in self.node_uploads
|
||||
and node_id in self.node_uploads[prompt_id]
|
||||
):
|
||||
self.node_uploads[prompt_id][node_id].discard(upload_id)
|
||||
|
||||
if (
|
||||
node_id
|
||||
and prompt_id in self.node_uploads
|
||||
and node_id in self.node_uploads[prompt_id]
|
||||
):
|
||||
self.node_uploads[prompt_id][node_id].discard(upload_id)
|
||||
# If this was the last upload for this node, clean up node data
|
||||
if not self.node_uploads[prompt_id][node_id]:
|
||||
del self.node_uploads[prompt_id][node_id]
|
||||
if self.node_output_data[prompt_id][node_id]["data"]:
|
||||
# Send final node data to API before cleanup
|
||||
if prompt_metadata[prompt_id].status_endpoint:
|
||||
body = {
|
||||
"run_id": prompt_id,
|
||||
"output_data": self.node_output_data[
|
||||
prompt_id
|
||||
][node_id]["data"],
|
||||
"node_meta": {"node_id": node_id},
|
||||
}
|
||||
try:
|
||||
await async_request_with_retry(
|
||||
"POST",
|
||||
prompt_metadata[
|
||||
prompt_id
|
||||
].status_endpoint,
|
||||
token=prompt_metadata[prompt_id].token,
|
||||
json=body,
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"Failed to send final node data: {str(e)}"
|
||||
)
|
||||
del self.node_output_data[prompt_id][node_id]
|
||||
|
||||
if not self.node_uploads[prompt_id][node_id]:
|
||||
del self.node_uploads[prompt_id][node_id]
|
||||
|
||||
if (
|
||||
prompt_id in self.node_output_data
|
||||
and node_id in self.node_output_data[prompt_id]
|
||||
):
|
||||
node_data = self.node_output_data[prompt_id][
|
||||
node_id
|
||||
]
|
||||
if node_data["data"]:
|
||||
body = {
|
||||
"run_id": prompt_id,
|
||||
"output_data": node_data["data"],
|
||||
"node_meta": {"node_id": node_id},
|
||||
}
|
||||
try:
|
||||
await async_request_with_retry(
|
||||
"POST",
|
||||
prompt_metadata[
|
||||
prompt_id
|
||||
].status_endpoint,
|
||||
token=prompt_metadata[
|
||||
prompt_id
|
||||
].token,
|
||||
json=body,
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"Failed to send final node data: {str(e)}"
|
||||
)
|
||||
|
||||
# Safe to delete now (re-check not strictly needed with lock, but harmless)
|
||||
del self.node_output_data[prompt_id][node_id]
|
||||
# Send status update
|
||||
await self.update_queue_status(prompt_id)
|
||||
|
||||
# If no more pending uploads for this prompt and it's done, update status
|
||||
if (
|
||||
prompt_id in self.pending_uploads
|
||||
and not self.pending_uploads[prompt_id]
|
||||
and is_prompt_done(prompt_id)
|
||||
if not self.pending_uploads[prompt_id] and is_prompt_done(
|
||||
prompt_id
|
||||
):
|
||||
# Clean up all data for this prompt
|
||||
if prompt_id in self.node_uploads:
|
||||
@@ -2892,12 +2753,9 @@ class UploadQueue:
|
||||
loop.create_task(update_run(prompt_id, Status.SUCCESS))
|
||||
loop.create_task(send("success", {"prompt_id": prompt_id}))
|
||||
|
||||
# Mark task as done (outside lock to avoid holding it unnecessarily)
|
||||
# Mark task as done
|
||||
self.queue.task_done()
|
||||
|
||||
# Send status update (also outside lock)
|
||||
await self.update_queue_status(prompt_id)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in upload worker: {str(e)}")
|
||||
logger.error(traceback.format_exc())
|
||||
@@ -2968,171 +2826,3 @@ def format_execution_timeline(execution_times):
|
||||
current_time += duration
|
||||
|
||||
return format_table(headers, rows)
|
||||
|
||||
|
||||
@server.PromptServer.instance.routes.get("/comfyui-deploy/auth-response")
|
||||
async def auth_response_proxy(request):
|
||||
request_id = request.rel_url.query.get("request_id")
|
||||
api_url = request.rel_url.query.get("api_url", "https://api.comfydeploy.com")
|
||||
|
||||
if not request_id:
|
||||
return web.json_response({"error": "request_id is required"}, status=400)
|
||||
|
||||
target_url = f"{api_url}/api/platform/comfyui/auth-response?request_id={request_id}"
|
||||
|
||||
try:
|
||||
await ensure_client_session()
|
||||
async with client_session.get(target_url) as response:
|
||||
json_data = await response.json()
|
||||
return web.json_response(json_data, status=response.status)
|
||||
except Exception as e:
|
||||
return web.json_response({"error": str(e)}, status=500)
|
||||
|
||||
|
||||
@server.PromptServer.instance.routes.post("/comfyui-deploy/workflow")
|
||||
async def create_workflow_proxy(request):
|
||||
data = await request.json()
|
||||
name = data.get("name")
|
||||
workflow_json = data.get("workflow_json")
|
||||
workflow_api = data.get("workflow_api")
|
||||
api_url = data.get("api_url", "https://api.comfydeploy.com")
|
||||
|
||||
auth_header = request.headers.get("Authorization")
|
||||
if not auth_header:
|
||||
return web.json_response(
|
||||
{"error": "Authorization header is required"}, status=401
|
||||
)
|
||||
|
||||
if not name or not workflow_json or not workflow_api:
|
||||
return web.json_response(
|
||||
{"error": "name, workflow_json, workflow_api are required"}, status=400
|
||||
)
|
||||
|
||||
target_url = f"{api_url}/api/workflow"
|
||||
|
||||
request_body = {
|
||||
"name": name,
|
||||
"workflow_json": json.dumps(workflow_json),
|
||||
"workflow_api": json.dumps(workflow_api),
|
||||
}
|
||||
|
||||
try:
|
||||
await ensure_client_session()
|
||||
async with client_session.post(
|
||||
target_url,
|
||||
json=request_body,
|
||||
headers={
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": auth_header,
|
||||
},
|
||||
) as response:
|
||||
json_data = await response.json()
|
||||
return web.json_response(json_data, status=response.status)
|
||||
except Exception as e:
|
||||
return web.json_response({"error": str(e)}, status=500)
|
||||
|
||||
|
||||
@server.PromptServer.instance.routes.post("/comfyui-deploy/workflow/version")
|
||||
async def create_workflow_version_proxy(request):
|
||||
data = await request.json()
|
||||
workflow_id = data.get("workflow_id")
|
||||
workflow = data.get("workflow")
|
||||
workflow_api = data.get("workflow_api")
|
||||
comment = data.get("comment", "")
|
||||
api_url = data.get("api_url", "https://api.comfydeploy.com")
|
||||
|
||||
auth_header = request.headers.get("Authorization")
|
||||
|
||||
if not auth_header:
|
||||
return web.json_response(
|
||||
{"error": "Authorization header is required"}, status=401
|
||||
)
|
||||
|
||||
target_url = f"{api_url}/api/workflow/{workflow_id}/version"
|
||||
|
||||
request_body = {
|
||||
"workflow": workflow,
|
||||
"workflow_api": workflow_api,
|
||||
"comment": comment,
|
||||
}
|
||||
|
||||
try:
|
||||
await ensure_client_session()
|
||||
async with client_session.post(
|
||||
target_url,
|
||||
json=request_body,
|
||||
headers={
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": auth_header,
|
||||
},
|
||||
) as response:
|
||||
json_data = await response.json()
|
||||
return web.json_response(json_data, status=response.status)
|
||||
except Exception as e:
|
||||
return web.json_response({"error": str(e)}, status=500)
|
||||
|
||||
|
||||
@server.PromptServer.instance.routes.get("/comfyui-deploy/workflows")
|
||||
async def get_workflows_proxy(request):
|
||||
api_url = request.rel_url.query.get("api_url", "https://api.comfydeploy.com")
|
||||
search = request.rel_url.query.get("search", "")
|
||||
limit = request.rel_url.query.get("limit", 10)
|
||||
offset = request.rel_url.query.get("offset", 0)
|
||||
auth_header = request.headers.get("Authorization")
|
||||
|
||||
if not auth_header:
|
||||
return web.json_response(
|
||||
{"error": "Authorization header is required"}, status=401
|
||||
)
|
||||
|
||||
# Build query parameters properly
|
||||
params = {}
|
||||
if search:
|
||||
params["search"] = search
|
||||
if limit:
|
||||
params["limit"] = limit
|
||||
if offset:
|
||||
params["offset"] = offset
|
||||
|
||||
target_url = f"{api_url}/api/workflows"
|
||||
if params:
|
||||
target_url += f"?{urlencode(params)}"
|
||||
|
||||
try:
|
||||
await ensure_client_session()
|
||||
async with client_session.get(
|
||||
target_url,
|
||||
headers={
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": auth_header,
|
||||
},
|
||||
) as response:
|
||||
json_data = await response.json()
|
||||
return web.json_response(json_data, status=response.status)
|
||||
except Exception as e:
|
||||
return web.json_response({"error": str(e)}, status=500)
|
||||
|
||||
|
||||
# for getting a workflow by id
|
||||
@server.PromptServer.instance.routes.get("/comfyui-deploy/workflow")
|
||||
async def get_workflow_proxy(request):
|
||||
workflow_id = request.rel_url.query.get("workflow_id")
|
||||
api_url = request.rel_url.query.get("api_url", "https://api.comfydeploy.com")
|
||||
auth_header = request.headers.get("Authorization")
|
||||
|
||||
if not auth_header:
|
||||
return web.json_response(
|
||||
{"error": "Authorization header is required"}, status=401
|
||||
)
|
||||
|
||||
target_url = f"{api_url}/api/workflow/{workflow_id}"
|
||||
|
||||
try:
|
||||
await ensure_client_session()
|
||||
async with client_session.get(
|
||||
target_url, headers={"Authorization": auth_header}
|
||||
) as response:
|
||||
json_data = await response.json()
|
||||
return web.json_response(json_data, status=response.status)
|
||||
except Exception as e:
|
||||
return web.json_response({"error": str(e)}, status=500)
|
||||
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 156 KiB |
@@ -1,152 +0,0 @@
|
||||
{
|
||||
"id": "ed93ac94-4f26-4ed3-a57b-73cd8f4d3494",
|
||||
"revision": 0,
|
||||
"last_node_id": 5,
|
||||
"last_link_id": 1,
|
||||
"nodes": [
|
||||
{
|
||||
"id": 2,
|
||||
"type": "LoraLoader",
|
||||
"pos": [
|
||||
736.646728515625,
|
||||
628.3823852539062
|
||||
],
|
||||
"size": [
|
||||
315,
|
||||
126
|
||||
],
|
||||
"flags": {},
|
||||
"order": 2,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"name": "model",
|
||||
"type": "MODEL",
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"name": "clip",
|
||||
"type": "CLIP",
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"name": "lora_name",
|
||||
"type": "COMBO",
|
||||
"widget": {
|
||||
"name": "lora_name"
|
||||
},
|
||||
"link": 1
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "MODEL",
|
||||
"type": "MODEL",
|
||||
"links": null
|
||||
},
|
||||
{
|
||||
"name": "CLIP",
|
||||
"type": "CLIP",
|
||||
"links": null
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.3.27",
|
||||
"Node name for S&R": "LoraLoader"
|
||||
},
|
||||
"widgets_values": [
|
||||
"1-292.safetensors",
|
||||
1,
|
||||
1
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 1,
|
||||
"type": "ComfyUIDeployExternalLora",
|
||||
"pos": [
|
||||
299.6898498535156,
|
||||
624.7929077148438
|
||||
],
|
||||
"size": [
|
||||
400,
|
||||
208
|
||||
],
|
||||
"flags": {},
|
||||
"order": 0,
|
||||
"mode": 0,
|
||||
"inputs": [],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "path",
|
||||
"type": "*",
|
||||
"links": [
|
||||
1
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"cnr_id": "comfyui-deploy",
|
||||
"ver": "cd3a2ff5471828f9c840e746551592e882c05aa4",
|
||||
"Node name for S&R": "ComfyUIDeployExternalLora"
|
||||
},
|
||||
"widgets_values": [
|
||||
"input_lora",
|
||||
"HyperSD\\FLUX.1\\Hyper-FLUX.1-dev-16steps-lora.safetensors",
|
||||
"",
|
||||
"",
|
||||
"",
|
||||
""
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 5,
|
||||
"type": "Note",
|
||||
"pos": [
|
||||
302.09033203125,
|
||||
401.2951965332031
|
||||
],
|
||||
"size": [
|
||||
479.4894104003906,
|
||||
161.61924743652344
|
||||
],
|
||||
"flags": {},
|
||||
"order": 1,
|
||||
"mode": 0,
|
||||
"inputs": [],
|
||||
"outputs": [],
|
||||
"properties": {},
|
||||
"widgets_values": [
|
||||
"\"External Lora\" node will let you to use different loras from the Comfy Deploy UI or even via API.\n\n- lora_url:\n url that will be used to download your LoRA model in execution time\n\n- lora_save_name:\n when we download your model, this will be saved in your private storage, \n give it a good name :D"
|
||||
],
|
||||
"color": "#432",
|
||||
"bgcolor": "#653"
|
||||
}
|
||||
],
|
||||
"links": [
|
||||
[
|
||||
1,
|
||||
1,
|
||||
0,
|
||||
2,
|
||||
2,
|
||||
"COMBO"
|
||||
]
|
||||
],
|
||||
"groups": [],
|
||||
"config": {},
|
||||
"extra": {
|
||||
"ds": {
|
||||
"scale": 1.167184107045006,
|
||||
"offset": [
|
||||
298.431389807788,
|
||||
-207.58877445762934
|
||||
]
|
||||
},
|
||||
"VHS_latentpreview": false,
|
||||
"VHS_latentpreviewrate": 0,
|
||||
"VHS_MetadataImage": true,
|
||||
"VHS_KeepIntermediate": true
|
||||
},
|
||||
"version": 0.4
|
||||
}
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 233 KiB |
@@ -1,873 +0,0 @@
|
||||
{
|
||||
"id": "351f402b-62f2-4f62-8a5e-0b9d3510e8f9",
|
||||
"revision": 0,
|
||||
"last_node_id": 29,
|
||||
"last_link_id": 28,
|
||||
"nodes": [
|
||||
{
|
||||
"id": 11,
|
||||
"type": "JoinImageWithAlpha",
|
||||
"pos": [
|
||||
814.478271484375,
|
||||
419.3052062988281
|
||||
],
|
||||
"size": [
|
||||
264.5999755859375,
|
||||
46
|
||||
],
|
||||
"flags": {},
|
||||
"order": 5,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"name": "image",
|
||||
"type": "IMAGE",
|
||||
"link": 10
|
||||
},
|
||||
{
|
||||
"name": "alpha",
|
||||
"type": "MASK",
|
||||
"link": 12
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"links": [
|
||||
11
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.3.27",
|
||||
"Node name for S&R": "JoinImageWithAlpha"
|
||||
},
|
||||
"widgets_values": []
|
||||
},
|
||||
{
|
||||
"id": 15,
|
||||
"type": "PreviewImage",
|
||||
"pos": [
|
||||
1950,
|
||||
640
|
||||
],
|
||||
"size": [
|
||||
210,
|
||||
246
|
||||
],
|
||||
"flags": {},
|
||||
"order": 18,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"name": "images",
|
||||
"type": "IMAGE",
|
||||
"link": 16
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"properties": {
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.3.27",
|
||||
"Node name for S&R": "PreviewImage"
|
||||
},
|
||||
"widgets_values": []
|
||||
},
|
||||
{
|
||||
"id": 10,
|
||||
"type": "LoadImage",
|
||||
"pos": [
|
||||
467.8168640136719,
|
||||
422.453857421875
|
||||
],
|
||||
"size": [
|
||||
315,
|
||||
314
|
||||
],
|
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{
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||||
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|
||||
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|
||||
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|
||||
10
|
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{
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||||
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||||
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|
||||
""
|
||||
]
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||||
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|
||||
"Option 1: CREATE THE MASK FROM THE ALPHA CHANNEL (Useful for example to generate the background of an image)\n\nMake sure that you are using \"External Image Alpha\". \n"
|
||||
],
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
{
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||||
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||||
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|
||||
"links": [
|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
"link": 25
|
||||
},
|
||||
{
|
||||
"name": "vae",
|
||||
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|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"name": "mask",
|
||||
"type": "MASK",
|
||||
"link": 26
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "LATENT",
|
||||
"type": "LATENT",
|
||||
"links": null
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
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||||
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|
||||
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||||
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||||
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|
||||
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||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
}
|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
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|
||||
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|
||||
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|
||||
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|
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||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
{
|
||||
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|
||||
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|
||||
"links": [
|
||||
17
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "MASK",
|
||||
"type": "MASK",
|
||||
"links": []
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.3.27",
|
||||
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|
||||
},
|
||||
"widgets_values": [
|
||||
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|
||||
"image",
|
||||
""
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 24,
|
||||
"type": "ImageToMask",
|
||||
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|
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||||
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|
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{
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||||
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|
||||
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|
||||
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|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "MASK",
|
||||
"type": "MASK",
|
||||
"links": [
|
||||
24,
|
||||
28
|
||||
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|
||||
}
|
||||
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|
||||
"properties": {
|
||||
"cnr_id": "comfy-core",
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||||
"ver": "0.3.27",
|
||||
"Node name for S&R": "ImageToMask"
|
||||
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||||
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||||
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|
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|
||||
"type": "PreviewImage",
|
||||
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||||
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|
||||
"order": 17,
|
||||
"mode": 0,
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||||
"inputs": [
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|
||||
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|
||||
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|
||||
}
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||||
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||||
"outputs": [],
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||||
"properties": {
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"cnr_id": "comfy-core",
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||||
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||||
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||||
{
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||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
},
|
||||
{
|
||||
"name": "vae",
|
||||
"type": "VAE",
|
||||
"link": null
|
||||
},
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||||
{
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||||
"name": "mask",
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||||
"type": "MASK",
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||||
"link": 24
|
||||
}
|
||||
],
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||||
"outputs": [
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||||
{
|
||||
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|
||||
"type": "LATENT",
|
||||
"links": null
|
||||
}
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],
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"properties": {
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"ver": "0.3.27",
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6
|
||||
]
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{
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|
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|
||||
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|
||||
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|
||||
"properties": {},
|
||||
"widgets_values": [
|
||||
"Option 2: UPLOAD THE MASK AS OTHER IMAGE (useful if you require the image that is below the mask to do inpainting, in this case to generate new glasses)"
|
||||
],
|
||||
"color": "#432",
|
||||
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||||
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||||
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||||
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|
||||
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|
||||
}
|
||||
],
|
||||
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|
||||
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|
||||
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|
||||
"type": "IMAGE",
|
||||
"links": [
|
||||
22,
|
||||
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|
||||
]
|
||||
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||||
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|
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|
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|
||||
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|
||||
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|
||||
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|
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||||
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|
||||
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||||
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|
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||||
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|
||||
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||||
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|
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|
||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
"",
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||||
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|
||||
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||||
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|
||||
{
|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
"link": 11
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "image",
|
||||
"type": "IMAGE",
|
||||
"links": [
|
||||
13
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"cnr_id": "comfyui-deploy",
|
||||
"ver": "cd3a2ff5471828f9c840e746551592e882c05aa4",
|
||||
"Node name for S&R": "ComfyUIDeployExternalImageAlpha"
|
||||
},
|
||||
"widgets_values": [
|
||||
"input_image_alpha",
|
||||
"",
|
||||
""
|
||||
]
|
||||
}
|
||||
],
|
||||
"links": [
|
||||
[
|
||||
10,
|
||||
10,
|
||||
0,
|
||||
11,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
11,
|
||||
11,
|
||||
0,
|
||||
12,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
12,
|
||||
10,
|
||||
1,
|
||||
11,
|
||||
1,
|
||||
"MASK"
|
||||
],
|
||||
[
|
||||
13,
|
||||
12,
|
||||
0,
|
||||
13,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
14,
|
||||
13,
|
||||
0,
|
||||
14,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
15,
|
||||
13,
|
||||
1,
|
||||
17,
|
||||
0,
|
||||
"MASK"
|
||||
],
|
||||
[
|
||||
16,
|
||||
17,
|
||||
0,
|
||||
15,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
17,
|
||||
20,
|
||||
0,
|
||||
22,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
18,
|
||||
21,
|
||||
0,
|
||||
23,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
19,
|
||||
23,
|
||||
0,
|
||||
24,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
21,
|
||||
25,
|
||||
0,
|
||||
26,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
22,
|
||||
22,
|
||||
0,
|
||||
27,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
23,
|
||||
22,
|
||||
0,
|
||||
28,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
24,
|
||||
24,
|
||||
0,
|
||||
28,
|
||||
2,
|
||||
"MASK"
|
||||
],
|
||||
[
|
||||
25,
|
||||
13,
|
||||
0,
|
||||
29,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
26,
|
||||
13,
|
||||
1,
|
||||
29,
|
||||
2,
|
||||
"MASK"
|
||||
],
|
||||
[
|
||||
28,
|
||||
24,
|
||||
0,
|
||||
25,
|
||||
0,
|
||||
"MASK"
|
||||
]
|
||||
],
|
||||
"groups": [],
|
||||
"config": {},
|
||||
"extra": {
|
||||
"ds": {
|
||||
"scale": 0.9646149645000013,
|
||||
"offset": [
|
||||
48.66905973637718,
|
||||
-817.5683540167485
|
||||
]
|
||||
},
|
||||
"VHS_latentpreview": false,
|
||||
"VHS_latentpreviewrate": 0,
|
||||
"VHS_MetadataImage": true,
|
||||
"VHS_KeepIntermediate": true
|
||||
},
|
||||
"version": 0.4
|
||||
}
|
||||
+2
-2
@@ -1,9 +1,9 @@
|
||||
[project]
|
||||
name = "comfyui-deploy"
|
||||
description = "Open source comfyui deployment platform, a vercel for generative workflow infra."
|
||||
version = "2.2.1"
|
||||
version = "2.0.0"
|
||||
license = { file = "LICENSE" }
|
||||
dependencies = ["aiofiles", "pydantic", "opencv-python", "imageio-ffmpeg", "tabulate", "brotli"]
|
||||
dependencies = ["aiofiles", "pydantic", "opencv-python", "imageio-ffmpeg"]
|
||||
|
||||
[project.urls]
|
||||
Repository = "https://github.com/BennyKok/comfyui-deploy"
|
||||
|
||||
+307
-490
File diff suppressed because it is too large
Load Diff
@@ -1,387 +0,0 @@
|
||||
// Workflow list management
|
||||
let workflowsState = {
|
||||
workflows: [],
|
||||
offset: 0,
|
||||
limit: 20,
|
||||
loading: false,
|
||||
hasMore: true,
|
||||
initialized: false,
|
||||
currentSearch: "",
|
||||
};
|
||||
|
||||
// Make workflowsState accessible globally
|
||||
window.workflowsState = workflowsState;
|
||||
|
||||
async function fetchWorkflows(getData, offset = 0, limit = 20, search = "") {
|
||||
try {
|
||||
const data = getData();
|
||||
if (!data.apiKey) {
|
||||
throw new Error("API key not configured");
|
||||
}
|
||||
|
||||
const params = new URLSearchParams({
|
||||
offset: offset.toString(),
|
||||
limit: limit.toString(),
|
||||
api_url: data.apiUrl || "https://api.comfydeploy.com",
|
||||
...(search && { search }),
|
||||
});
|
||||
|
||||
const response = await fetch(`/comfyui-deploy/workflows?${params}`, {
|
||||
method: "GET",
|
||||
headers: {
|
||||
Authorization: `Bearer ${data.apiKey}`,
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`Failed to fetch workflows: ${response.status}`);
|
||||
}
|
||||
|
||||
const result = await response.json();
|
||||
console.log("result", result);
|
||||
return Array.isArray(result) ? result : [];
|
||||
} catch (error) {
|
||||
console.error("Error fetching workflows:", error);
|
||||
return [];
|
||||
}
|
||||
}
|
||||
|
||||
function createWorkflowItem(workflow, getTimeAgo, getData) {
|
||||
const li = document.createElement("li");
|
||||
li.style.cssText = `
|
||||
border-bottom: 1px solid #444;
|
||||
background: transparent;
|
||||
transition: all 0.2s ease;
|
||||
cursor: pointer;
|
||||
`;
|
||||
|
||||
li.addEventListener("mouseenter", () => {
|
||||
li.style.background = "#333";
|
||||
});
|
||||
|
||||
li.addEventListener("mouseleave", () => {
|
||||
li.style.background = "transparent";
|
||||
});
|
||||
|
||||
// Add click handler to fetch and load workflow data
|
||||
li.addEventListener("click", async () => {
|
||||
try {
|
||||
const data = getData();
|
||||
if (!data.apiKey) {
|
||||
console.error("No API key configured");
|
||||
return;
|
||||
}
|
||||
|
||||
// Show loading toast
|
||||
const loadingToast = window.app.extensionManager.toast.add({
|
||||
severity: "info",
|
||||
summary: "Loading workflow...",
|
||||
detail: `Loading "${workflow.name}"`,
|
||||
life: 3000,
|
||||
});
|
||||
|
||||
const params = new URLSearchParams({
|
||||
workflow_id: workflow.id,
|
||||
api_url: data.apiUrl || "https://api.comfydeploy.com",
|
||||
});
|
||||
|
||||
const response = await fetch(`/comfyui-deploy/workflow?${params}`, {
|
||||
method: "GET",
|
||||
headers: {
|
||||
Authorization: `Bearer ${data.apiKey}`,
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`Failed to fetch workflow: ${response.status}`);
|
||||
}
|
||||
|
||||
const workflowData = await response.json();
|
||||
console.log("Workflow data:", workflowData);
|
||||
|
||||
// Load the workflow into the graph
|
||||
if (workflowData.versions && workflowData.versions.length > 0) {
|
||||
const latestVersion = workflowData.versions[0];
|
||||
if (latestVersion.workflow && window.app) {
|
||||
// Load the workflow
|
||||
window.app.loadGraphData(latestVersion.workflow);
|
||||
|
||||
// Show success toast
|
||||
window.app.extensionManager.toast.add({
|
||||
severity: "success",
|
||||
summary: "Workflow loaded successfully",
|
||||
detail: `Loaded "${workflow.name}" v${latestVersion.version}`,
|
||||
life: 3000,
|
||||
});
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Error loading workflow:", error);
|
||||
// Show error toast
|
||||
window.app.extensionManager.toast.add({
|
||||
severity: "error",
|
||||
summary: "Failed to load workflow",
|
||||
detail: error.message,
|
||||
life: 5000,
|
||||
});
|
||||
} finally {
|
||||
loadingToast.close();
|
||||
}
|
||||
});
|
||||
|
||||
const updatedDate = new Date(workflow.updated_at);
|
||||
const timeAgo = getTimeAgo(updatedDate);
|
||||
|
||||
li.innerHTML = `
|
||||
<div style="padding: 12px 16px;">
|
||||
<div style="display: flex; align-items: flex-start; gap: 12px;">
|
||||
${
|
||||
workflow.cover_image
|
||||
? `<img src="${workflow.cover_image}"
|
||||
style="width: 40px; height: 40px; border-radius: 4px; object-fit: cover; flex-shrink: 0;"
|
||||
onerror="this.style.display='none'">`
|
||||
: `<div style="width: 40px; height: 40px; border-radius: 4px; background: #444; flex-shrink: 0; display: flex; align-items: center; justify-content: center; font-size: 14px; color: #888;">
|
||||
${workflow.name.charAt(0).toUpperCase()}
|
||||
</div>`
|
||||
}
|
||||
|
||||
<div style="flex: 1; min-width: 0;">
|
||||
<div style="display: flex; align-items: center; gap: 8px; margin-bottom: 4px;">
|
||||
<h4 style="margin: 0; font-size: 14px; font-weight: 400; color: #fff; white-space: nowrap; overflow: hidden; text-overflow: ellipsis;">
|
||||
${workflow.name}
|
||||
</h4>
|
||||
${
|
||||
workflow.pinned
|
||||
? `<span style="color: #ffd700; font-size: 12px;">📌</span>`
|
||||
: ""
|
||||
}
|
||||
</div>
|
||||
|
||||
${
|
||||
workflow.description
|
||||
? `<p style="margin: 0 0 8px 0; font-size: 12px; color: #bbb; line-height: 1.3; overflow: hidden; display: -webkit-box; -webkit-line-clamp: 2; -webkit-box-orient: vertical;">
|
||||
${workflow.description}
|
||||
</p>`
|
||||
: ""
|
||||
}
|
||||
|
||||
<div style="display: flex; align-items: center; gap: 8px; margin-top: 8px;">
|
||||
<img src="${workflow.user_icon}"
|
||||
style="width: 16px; height: 16px; border-radius: 50%;"
|
||||
onerror="this.style.display='none'">
|
||||
<span style="font-size: 11px; color: #888;">
|
||||
${workflow.user_name} • Updated ${timeAgo}
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
`;
|
||||
|
||||
return li;
|
||||
}
|
||||
|
||||
async function loadMoreWorkflows(element, getData, getTimeAgo) {
|
||||
if (workflowsState.loading || !workflowsState.hasMore) return;
|
||||
|
||||
workflowsState.loading = true;
|
||||
|
||||
const workflowsList = element.querySelector("#workflows-list");
|
||||
const workflowsLoading = element.querySelector("#workflows-loading");
|
||||
|
||||
// Show loading indicator
|
||||
workflowsLoading.style.display = "flex";
|
||||
|
||||
try {
|
||||
const newWorkflows = await fetchWorkflows(
|
||||
getData,
|
||||
workflowsState.offset,
|
||||
workflowsState.limit,
|
||||
workflowsState.currentSearch
|
||||
);
|
||||
|
||||
if (newWorkflows.length === 0) {
|
||||
workflowsState.hasMore = false;
|
||||
} else {
|
||||
workflowsState.workflows.push(...newWorkflows);
|
||||
workflowsState.offset += newWorkflows.length;
|
||||
|
||||
// Render new workflow items
|
||||
newWorkflows.forEach((workflow) => {
|
||||
const workflowItem = createWorkflowItem(workflow, getTimeAgo, getData);
|
||||
workflowsList.appendChild(workflowItem);
|
||||
});
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Error loading more workflows:", error);
|
||||
} finally {
|
||||
workflowsState.loading = false;
|
||||
workflowsLoading.style.display = "none";
|
||||
}
|
||||
}
|
||||
|
||||
function setupInfiniteScroll(container, element, getData, getTimeAgo) {
|
||||
let isScrolling = false;
|
||||
|
||||
container.addEventListener("scroll", () => {
|
||||
if (isScrolling) return;
|
||||
|
||||
const { scrollTop, scrollHeight, clientHeight } = container;
|
||||
|
||||
// Load more when scrolled to bottom (with 100px threshold)
|
||||
if (scrollTop + clientHeight >= scrollHeight - 100) {
|
||||
isScrolling = true;
|
||||
loadMoreWorkflows(element, getData, getTimeAgo).finally(() => {
|
||||
isScrolling = false;
|
||||
});
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
async function initializeWorkflowsList(element, getData, getTimeAgo) {
|
||||
const workflowsContainer = element.querySelector("#workflows-container");
|
||||
const workflowsList = element.querySelector("#workflows-list");
|
||||
const workflowsLoading = element.querySelector("#workflows-loading");
|
||||
|
||||
// Check if already initialized AND the DOM elements still exist
|
||||
if (
|
||||
workflowsState.initialized &&
|
||||
workflowsList &&
|
||||
workflowsList.children.length > 0
|
||||
)
|
||||
return;
|
||||
|
||||
try {
|
||||
// Reset state (always reset when reinitializing)
|
||||
workflowsState = {
|
||||
workflows: [],
|
||||
offset: 0,
|
||||
limit: 20,
|
||||
loading: false,
|
||||
hasMore: true,
|
||||
initialized: true,
|
||||
currentSearch: "",
|
||||
};
|
||||
|
||||
// Clear existing content in case of reinitialization
|
||||
if (workflowsList) {
|
||||
workflowsList.innerHTML = "";
|
||||
}
|
||||
|
||||
// Show container and loading
|
||||
workflowsContainer.style.display = "block";
|
||||
workflowsLoading.style.display = "flex";
|
||||
|
||||
// Style the workflows list for full height scrolling
|
||||
workflowsList.style.cssText = `
|
||||
list-style-type: none;
|
||||
padding: 0;
|
||||
margin: 0;
|
||||
height: calc(100vh - 350px);
|
||||
overflow-y: auto;
|
||||
scrollbar-width: thin;
|
||||
scrollbar-color: #666 transparent;
|
||||
border-top: 1px solid #444;
|
||||
`;
|
||||
|
||||
// Add webkit scrollbar styles
|
||||
const style = document.createElement("style");
|
||||
style.textContent = `
|
||||
#workflows-list::-webkit-scrollbar {
|
||||
width: 6px;
|
||||
}
|
||||
#workflows-list::-webkit-scrollbar-track {
|
||||
background: transparent;
|
||||
}
|
||||
#workflows-list::-webkit-scrollbar-thumb {
|
||||
background: #666;
|
||||
border-radius: 3px;
|
||||
}
|
||||
#workflows-list::-webkit-scrollbar-thumb:hover {
|
||||
background: #777;
|
||||
}
|
||||
`;
|
||||
document.head.appendChild(style);
|
||||
|
||||
// Setup infinite scroll
|
||||
setupInfiniteScroll(workflowsList, element, getData, getTimeAgo);
|
||||
|
||||
// Load initial workflows
|
||||
await loadMoreWorkflows(element, getData, getTimeAgo);
|
||||
|
||||
// Show the list
|
||||
workflowsList.style.display = "block";
|
||||
} catch (error) {
|
||||
console.error("Error initializing workflows list:", error);
|
||||
workflowsLoading.innerHTML = `
|
||||
<div style="text-align: center; color: #e74c3c; font-size: 12px; padding: 20px;">
|
||||
<div>Failed to load workflows</div>
|
||||
<button onclick="initializeWorkflowsList(this.closest('.comfy-menu'), getData, getTimeAgo)"
|
||||
style="margin-top: 8px; padding: 4px 8px; font-size: 11px; background: #f0f0f0; border: 1px solid #ccc; border-radius: 4px; cursor: pointer;">
|
||||
Retry
|
||||
</button>
|
||||
</div>
|
||||
`;
|
||||
}
|
||||
}
|
||||
|
||||
// Search functionality
|
||||
function addWorkflowSearch(element, getData, getTimeAgo) {
|
||||
const workflowsContainer = element.querySelector("#workflows-container");
|
||||
const h4 = workflowsContainer.querySelector("h4");
|
||||
|
||||
const searchContainer = document.createElement("div");
|
||||
searchContainer.style.cssText = "margin-bottom: 12px;";
|
||||
|
||||
const searchInput = document.createElement("input");
|
||||
searchInput.type = "text";
|
||||
searchInput.placeholder = "Search workflows...";
|
||||
searchInput.style.cssText = `
|
||||
width: 100%;
|
||||
padding: 8px 12px;
|
||||
border: 1px solid #555;
|
||||
border-radius: 6px;
|
||||
font-size: 12px;
|
||||
box-sizing: border-box;
|
||||
background: #333;
|
||||
color: #fff;
|
||||
`;
|
||||
|
||||
let searchTimeout;
|
||||
searchInput.addEventListener("input", (e) => {
|
||||
clearTimeout(searchTimeout);
|
||||
searchTimeout = setTimeout(async () => {
|
||||
const searchTerm = e.target.value.trim();
|
||||
|
||||
// Update the tracked search term
|
||||
workflowsState.currentSearch = searchTerm;
|
||||
|
||||
// Reset state for new search
|
||||
workflowsState.workflows = [];
|
||||
workflowsState.offset = 0;
|
||||
workflowsState.hasMore = true;
|
||||
|
||||
// Clear current list
|
||||
const workflowsList = element.querySelector("#workflows-list");
|
||||
workflowsList.innerHTML = "";
|
||||
|
||||
// Load with search term
|
||||
workflowsState.loading = false;
|
||||
await loadMoreWorkflows(element, getData, getTimeAgo);
|
||||
}, 300);
|
||||
});
|
||||
|
||||
searchContainer.appendChild(searchInput);
|
||||
h4.after(searchContainer);
|
||||
}
|
||||
|
||||
// Export the functions
|
||||
export {
|
||||
initializeWorkflowsList,
|
||||
addWorkflowSearch,
|
||||
workflowsState,
|
||||
fetchWorkflows,
|
||||
loadMoreWorkflows,
|
||||
};
|
||||
Reference in New Issue
Block a user