Compare commits
2
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 BennyKok
|
16522b5a7b | ||
|
BennyKok
|
987de97e49 |
@@ -2,8 +2,6 @@
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Open source comfyui deployment platform, a `vercel` for generative workflow infra. (serverless hosted gpu with vertical intergation with comfyui)
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Check out our latest lcoal demo -> https://github.com/comfy-deploy/comfyui-api-comfydeploy
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> [!NOTE]
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> Im looking for creative hacker to join ComfyDeploy's core team! DM me on [twitter](https://x.com/BennyKokMusic)
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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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@@ -1,4 +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": (
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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 = ("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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class ComfyUIDeployExternalSeed:
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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_seed"},
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),
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"default_value": (
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"INT",
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{"default": -1},
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),
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"min_value": (
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"INT",
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{"default": 1, "min": 1, "max": 999999999999999},
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),
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"max_value": (
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"INT",
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{"default": 4294967295, "min": 1, "max": 999999999999999},
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),
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},
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"optional": {
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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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{
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"multiline": True,
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"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',
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},
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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 = ("seed",)
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FUNCTION = "run"
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CATEGORY = "🔗ComfyDeploy"
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# Limits
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_MAX_LIMIT = 999_999_999_999_999 # 15 digits
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# Store cached seed when fixed flag is enabled
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_cached_seed = None
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@classmethod
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def IS_CHANGED(
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cls,
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input_id,
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min_value,
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max_value,
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default_value=None,
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**kwargs,
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):
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"""Inform ComfyUI whether the node output should be considered changed.
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If default_value is within range (Fixed mode), we return the inputs tuple
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so the cached result is reused until the user changes something.
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For Randomize mode, we force re-execution each queue.
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"""
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# Clamp values to allowed range for check
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min_value = max(1, min_value)
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max_value = min(cls._MAX_LIMIT, max_value)
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# Fixed mode when default_value is within range
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if (
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default_value is not None
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and default_value >= min_value
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and default_value <= max_value
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):
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return (input_id, default_value)
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# For Randomize (default_value is -1 or out of range) we force re-execution
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import random as _rnd
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return _rnd.random()
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def run(
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self,
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input_id,
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min_value: int,
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max_value: int,
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display_name=None,
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description=None,
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default_value: int = -1,
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):
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# Clamp values to allowed range
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min_value = max(1, min_value)
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max_value = min(self._MAX_LIMIT, max_value)
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# Ensure limits are in correct order after clamping
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if min_value > max_value:
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min_value, max_value = max_value, min_value
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# Fixed mode: default_value is within range
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if default_value >= min_value and default_value <= max_value:
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seed = int(default_value)
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self._cached_seed = seed
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return [seed]
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# Randomize mode: default_value is -1 or out of range
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seed = random.randint(min_value, max_value)
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self._cached_seed = seed
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return [seed]
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NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalSeed": ComfyUIDeployExternalSeed}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"ComfyUIDeployExternalSeed": "External Seed (ComfyUI Deploy)"
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}
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@@ -748,64 +748,36 @@ class ComfyUIDeployExternalVideo:
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file_parts = f.split(".")
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if len(file_parts) > 1 and (file_parts[-1] in video_extensions):
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files.append(f)
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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_video"},
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),
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"force_rate": ("INT", {"default": 0, "min": 0, "max": 60, "step": 1}),
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"force_size": (
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[
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"Disabled",
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"Custom Height",
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"Custom Width",
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"Custom",
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"256x?",
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"?x256",
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"256x256",
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"512x?",
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"?x512",
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"512x512",
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],
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),
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"custom_width": (
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"INT",
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{"default": 512, "min": 0, "max": DIMMAX, "step": 8},
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||||
),
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"custom_height": (
|
||||
"INT",
|
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{"default": 512, "min": 0, "max": DIMMAX, "step": 8},
|
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),
|
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"frame_load_cap": (
|
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"INT",
|
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{"default": 0, "min": 0, "max": BIGMAX, "step": 1},
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),
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"skip_first_frames": (
|
||||
"INT",
|
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{"default": 0, "min": 0, "max": BIGMAX, "step": 1},
|
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),
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"select_every_nth": (
|
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"INT",
|
||||
{"default": 1, "min": 1, "max": BIGMAX, "step": 1},
|
||||
),
|
||||
},
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"optional": {
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"meta_batch": ("VHS_BatchManager",),
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"vae": ("VAE",),
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"default_video": (sorted(files),),
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"display_name": (
|
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"STRING",
|
||||
{"multiline": False, "default": ""},
|
||||
),
|
||||
"description": (
|
||||
"STRING",
|
||||
{"multiline": True, "default": ""},
|
||||
),
|
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"default_value_url": ("STRING", {"image_preview": True, "default": ""}),
|
||||
},
|
||||
"hidden": {"unique_id": "UNIQUE_ID"},
|
||||
}
|
||||
return {"required": {
|
||||
"input_id": (
|
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"STRING",
|
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{"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:
|
||||
|
||||
@@ -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)"}
|
||||
+111
-934
File diff suppressed because it is too large
Load Diff
@@ -18,7 +18,6 @@ class Status(Enum):
|
||||
SUCCESS = "success"
|
||||
FAILED = "failed"
|
||||
UPLOADING = "uploading"
|
||||
CANCELLED = "cancelled"
|
||||
|
||||
|
||||
class StreamingPrompt(BaseModel):
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
[project]
|
||||
name = "comfyui-deploy"
|
||||
description = "Open source comfyui deployment platform, a vercel for generative workflow infra."
|
||||
version = "2.3.4"
|
||||
version = "2.1.0"
|
||||
license = { file = "LICENSE" }
|
||||
dependencies = ["aiofiles", "pydantic", "opencv-python", "imageio-ffmpeg", "tabulate", "brotli"]
|
||||
|
||||
|
||||
+590
-1397
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@@ -1,82 +0,0 @@
|
||||
// Snapshot Utilities
|
||||
// Centralized snapshot fetching with ComfyUI version fallback
|
||||
|
||||
/**
|
||||
* Fetches the current snapshot with ComfyUI version fallback
|
||||
* If the snapshot response has null comfyui field, it will fetch the latest ComfyUI version
|
||||
* and update the snapshot with the comfyui_hash
|
||||
*
|
||||
* @param {Function} getDataFn - Function that returns { apiKey, apiUrl } for ComfyUI version API calls
|
||||
* @returns {Promise<Object>} - The snapshot data with comfyui field populated
|
||||
*/
|
||||
export async function fetchSnapshot(getDataFn = null) {
|
||||
try {
|
||||
// Fetch the current snapshot
|
||||
const response = await fetch("/snapshot/get_current");
|
||||
if (!response.ok) {
|
||||
throw new Error(`Snapshot fetch failed: ${response.status}`);
|
||||
}
|
||||
|
||||
const snapshot = await response.json();
|
||||
|
||||
// Check if comfyui field is null and we have getDataFn for fallback
|
||||
if (snapshot.comfyui === null && getDataFn) {
|
||||
console.log(
|
||||
"ComfyUI version is null in snapshot, fetching latest version..."
|
||||
);
|
||||
|
||||
try {
|
||||
const data = getDataFn();
|
||||
if (data && data.apiKey) {
|
||||
const comfyuiVersionResponse = await fetch(
|
||||
`/comfyui-deploy/comfyui-version?api_url=${encodeURIComponent(
|
||||
data.apiUrl || "https://api.comfydeploy.com"
|
||||
)}`,
|
||||
{
|
||||
headers: {
|
||||
Authorization: `Bearer ${data.apiKey}`,
|
||||
},
|
||||
}
|
||||
);
|
||||
|
||||
if (comfyuiVersionResponse.ok) {
|
||||
const versionData = await comfyuiVersionResponse.json();
|
||||
if (versionData.comfyui_hash) {
|
||||
console.log(
|
||||
`Using ComfyUI hash from API: ${versionData.comfyui_hash}`
|
||||
);
|
||||
snapshot.comfyui = versionData.comfyui_hash;
|
||||
}
|
||||
} else {
|
||||
console.warn(
|
||||
"Failed to fetch ComfyUI version from API:",
|
||||
comfyuiVersionResponse.status
|
||||
);
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.warn("Error fetching ComfyUI version fallback:", error);
|
||||
// Continue with original snapshot even if fallback fails
|
||||
}
|
||||
}
|
||||
|
||||
return snapshot;
|
||||
} catch (error) {
|
||||
console.error("Error fetching snapshot:", error);
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Simple snapshot fetch without ComfyUI version fallback
|
||||
* Use this when you don't need the ComfyUI version fallback logic
|
||||
*
|
||||
* @returns {Promise<Object>} - The snapshot data as-is
|
||||
*/
|
||||
export async function fetchSnapshotSimple() {
|
||||
const response = await fetch("/snapshot/get_current");
|
||||
if (!response.ok) {
|
||||
throw new Error(`Snapshot fetch failed: ${response.status}`);
|
||||
}
|
||||
return response.json();
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user