Files
noembryo-ComfyUI-noEmbryo/nodes.py
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2026-09-30 00:02:52 +03:00

722 lines
32 KiB
Python

import os, re, io
import json
import subprocess
import tempfile
from os.path import realpath, join, dirname, isabs, splitext, basename
from datetime import datetime
import folder_paths
from .image_nodes import LoadImageFromPathEnhanced, ImageComposer
from .minimax import (H3MotionContextClipStitcher, H3ClipRefiner,
H3ContextLatentConverter,
H3MotionContextClipPurge, H3AVLatentFromVideo)
MANIFEST = {"name": "noEmbryo Nodes",
"version": (1, 8, 1),
"author": "noEmbryo",
"project": "https://github.com/noembryo/ComfyUI-noEmbryo",
"description": "Nodes for ComfyUI",
"license": "MIT",
}
__author__ = "noEmbryo"
__version__ = "1.8.1"
LISTS_PATH = join(dirname(realpath(__file__)), "TermLists")
class JsonPromptLoader:
data = {}
data_labels = ["None"]
json_path = ""
def __init__(self):
super(JsonPromptLoader, self).__init__()
self.name = type(self).__name__
@classmethod
def load_data(cls, json_path):
cls.json_path = ""
if not splitext(json_path)[1].lower() == ".json":
return
if json_path:
try:
with io.open(json_path, mode="r", encoding="utf-8") as f:
cls.data.clear()
cls.data["None"] = ""
cls.data.update(json.load(f))
cls.data_labels[:] = list(cls.data.keys())
cls.json_path = json_path
except (FileNotFoundError, json.JSONDecodeError):
cls.data.clear()
cls.data.update({})
cls.data_labels[:] = ["None"]
if os.stat(json_path).st_size == 0: # empty json files
cls.json_path = json_path
else: # no path given
cls.data.clear()
cls.data.update({})
cls.data_labels[:] = ["None"]
@classmethod
def INPUT_TYPES(cls):
return {"required": {"json_path": ("STRING", {"default": "",
"tooltip": "Path to a JSON file with "
"`item`:`prompt` pairs"}),
"selected_item": (cls.data_labels, cls.data), # Options will be updated by JS
"variable": ("STRING", {"default": "{subject}",
"tooltip": "If this variable exists in the selected item's prompt,\n"
"it will be replaced with the custom_prompt text"}),
"custom_prompt": ("STRING", {"multiline": True, "default": "",
"tooltip": "Text to replace the variable in the selected prompt.\n"
"You can also use it to save a new item or update an existing one.\n"
"To do that you should use the following format:\n"
"item=... ...\n"
"value=.... .... ...\n"
"To delete an existing item, use an empty value:\n"
"item=... ...\n"
"value="}),
},
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("Prompt",)
FUNCTION = "run"
CATEGORY = "noEmbryo/Prompt"
DESCRIPTION = ("A node that can load a `.json` file with `item:prompt` pairs and outputs "
"the selected item's prompt, while combining it with a custom prompt.\n"
"It can load `.json` files from any directory, not just the node's directory.")
def run(self, json_path, selected_item, variable, custom_prompt):
self.load_data(json_path)
if custom_prompt:
message = self.edit_data(custom_prompt)
if message: # if the custom_prompt was saved successfully
return (message,)
if selected_item in self.data and selected_item != "None":
prompt = self.data[selected_item]
# if variable and "{" + variable + "}" in prompt:
if variable and variable in prompt:
prompt = prompt.replace(variable, custom_prompt)
# prompt = prompt.replace("{" + variable + "}", custom_prompt)
elif custom_prompt:
prompt += " " + custom_prompt
else:
prompt = custom_prompt
return (prompt,)
def edit_data(self, text):
""" Parses the json values from the custom_prompt and changes the json file
:type text: str
:param text: The custom_prompt text
"""
lines = text.splitlines()
if len(lines) >= 2:
if all((lines[0].startswith("item="), lines[1].startswith("value="))):
if not self.json_path:
return False
item = lines[0][5:]
lines_txt = "\n".join(lines[1:])
value = lines_txt[6:]
filename = basename(self.json_path)
if item == "None": # cannot change None
msg = f'{filename}: The item "{item}" cannot be changed!'
return msg
if not value: # delete item
if item in self.data:
del self.data[item]
msg = f'{filename}: The item "{item}" was deleted!'
self.save_json_file()
else:
msg = f'{filename}: The item "{item}" does not exist!'
else: # save/update item
if item in self.data:
msg = f'{filename}: The item "{item}" was updated!'
else:
msg = f'{filename}: The item "{item}" was added!'
self.data[item] = value
self.save_json_file()
return msg
return False
def save_json_file(self):
with io.open(self.json_path, mode="w", encoding="utf-8") as f:
data = self.data.copy()
if "None" in data:
del data["None"]
# noinspection PyTypeChecker
json.dump(data, f, ensure_ascii=False, indent=4)
class PromptTermList:
idx = 0
data = {"None": ""}
data_labels = []
has_error = False
input_error = ("Trying to store invalid input!\nUse the format:\n"
"label=... ...\nvalue=.... .... ...")
def __init__(self):
super(PromptTermList, self).__init__()
self.name = type(self).__name__
@classmethod
def load_data_from_json(cls, json_file_path):
""" Loads a json file from a path
:type json_file_path: str
:param json_file_path: The path to the json file
"""
try:
with io.open(json_file_path, mode="r", encoding="utf-8") as f:
cls.data = json.load(f)
cls.data_labels = list(cls.data.items())
except FileNotFoundError:
pass
@classmethod
def INPUT_TYPES(cls):
list_path = join(LISTS_PATH, f"TermList{cls.idx}.json")
cls.load_data_from_json(list_path)
term_list = [i[0] for i in cls.data_labels]
# noinspection SqlNoDataSourceInspection,SqlResolve
return {"required": {"terms": (term_list,{"tooltip": "Choose a term from the "
"TermList with the "
"corresponding number"}), },
"optional": {"text": ("STRING", {"forceInput": True,
"tooltip": "Input text to store in the "
"TermList\nUse the format:\n"
"label=... ...\n"
"value=.... .... ..."}),
# The round value representing the precision to round to,
# will be set to the step value by default.
# Can be set to False to disable rounding.
"strength": ("FLOAT", {"default": 1.0,
"min": 0.05,
"max": 2.0,
"step": 0.05,
"round": 0.01,
"display": "number",
"tooltip": "Controls how much the "
"image is allowed to change.\n"
"0.0 = almost no change\n"
"1.0 = maximum creativity"}),
"store_input": ("BOOLEAN",
{"default": False,
"tooltip": "Store the input text in the "
"TermList\nUse the format:\n"
"label=... ...\nvalue=.... .... ..."}),
},
}
def save_data_from_input(self, text):
""" Extracts the json values from the input text and stores them in the json file
:type text: str
:param text: The text input
"""
lines = text.splitlines()
if not len(lines) > 1:
self.has_error = True
print(f"{self.name}:", self.input_error)
return
if not all((lines[0].startswith("label="), lines[1].startswith("value="))):
self.has_error = True
print(f"{self.name}:", self.input_error)
return
label = lines[0][6:]
lines_txt = "\n".join(lines[1:])
value = lines_txt[6:]
if label == "None":
print(f'{self.name}: The label "{label}" cannot be changed!')
return
if not value:
if label in self.data:
del self.data[label]
print(f'{self.name}: The label "{label}" was deleted!')
else:
print(f'{self.name}: The label "{label}" does not exist!')
return
else:
if label in self.data:
print(f'{self.name}: The label "{label}" is updated!')
else:
print(f'{self.name}: The label "{label}" is saved!')
self.data[label] = value
with io.open(join(LISTS_PATH, "TermList{}.json".format(self.idx)), mode="w",
encoding="utf-8") as f:
# noinspection PyTypeChecker
json.dump(self.data, f, ensure_ascii=False, indent=4)
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("Term",)
# OUTPUT_NODE = True
CATEGORY = "noEmbryo/Prompt/Term Nodes"
FUNCTION = "run"
def run(self, terms, strength, store_input, text=None):
selected = terms[:len(terms)]
text_out = ""
for i in self.data_labels:
if i[0] == selected:
text_out = f"{i[1]} "
break
if selected != "None" and strength != 1.0:
text_out = f"({text_out}:{strength})"
if text:
if store_input:
self.save_data_from_input(text)
if not self.has_error:
text_out = ""
else:
self.has_error = False
text_out = self.input_error
else:
if text_out:
text_out = f"{text_out}, {text}"
else:
text_out = text
return (text_out, )
class PromptTermList1(PromptTermList):
idx = 1
class PromptTermList2(PromptTermList):
idx = 2
class PromptTermList3(PromptTermList):
idx = 3
class PromptTermList4(PromptTermList):
idx = 4
class PromptTermList5(PromptTermList):
idx = 5
class PromptTermList6(PromptTermList):
idx = 6
class ResolutionScale:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {"required": {"width": ("INT", {"default": 512}),
"height": ("INT", {"default": 512}),
"scale_factor": ("FLOAT", {"default": 2.0,
"min": 0.1,
"max": 8.0,
"step": 0.1,
"round": 0.1,
"display": "number"},),
},
"optional": {"image": ("IMAGE",), },
}
RETURN_TYPES = ("INT", "INT", "FLOAT", "INT", "INT")
RETURN_NAMES = ("Width", "Height", "Scale Factor",
"Original Width", "Original Height")
FUNCTION = "run"
CATEGORY = "noEmbryo"
# noinspection PyMethodMayBeStatic
def run(self, width, height, scale_factor, image=None):
if image is not None:
_, img_height, img_width, _ = image.shape
if width == 0:
ratio = img_width / img_height
width = height * ratio
width = int(width / 4) * 4
elif height == 0:
ratio = img_height / img_width
height = width * ratio
height = int(height / 4) * 4
else:
width = img_width
height = img_height
new_width = int(width * scale_factor)
new_height = int(height * scale_factor)
return new_width, new_height, scale_factor, width, height
class RegExTextChopper:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {"required": {"text": ("STRING", {"forceInput": True,
"tooltip": "The text that we'll parse"}),
"regex": ("STRING", {"tooltip": "The RegEx pattern"})
},
"optional": {},
}
RETURN_TYPES = ("STRING", "STRING", "STRING", "STRING", "STRING")
RETURN_NAMES = ("Part 1", "Part 2", "Part 3", "Part 4", "All parts")
FUNCTION = "run"
CATEGORY = "noEmbryo"
@staticmethod
def is_valid_regex(regex_from_user: str) -> bool:
try:
re.compile(re.escape(regex_from_user))
is_valid = True
except re.error:
is_valid = False
return is_valid
def run(self, text, regex):
if self.is_valid_regex(regex):
obj = re.compile(regex, re.MULTILINE)
result = obj.findall(text)
try:
text1 = result[0]
except IndexError:
text1 = ""
try:
text2 = result[1]
except IndexError:
text2 = ""
try:
text3 = result[2]
except IndexError:
text3 = ""
try:
text4 = result[3]
except IndexError:
text4 = ""
text_all = "\n\n".join(result)
else:
text1 = text2 = text3 = text4 = ""
text_all = text
return text1, text2, text3, text4, text_all
class AutoSaveWorkflow:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"save_directory": ("STRING", {
"default": "saved_workflows",
"tooltip": "Relative to ComfyUI output directory or absolute path"
}),
"filename": ("STRING", {
"default": "workflow_{timestamp}",
"tooltip": "Filename (include {timestamp} for unique timestamps)"
}),
"trigger": ("BOOLEAN", {
"default": True,
"label_on": "Enabled",
"label_off": "Disabled",
"tooltip": "Save the workflow if Enabled"
}),
},
"hidden": {
"prompt": "PROMPT",
"extra_pnginfo": "EXTRA_PNGINFO",
"trigger": "BOOLEAN", # Hidden trigger input
},
}
RETURN_TYPES = ("STRING", "BOOLEAN")
RETURN_NAMES = ("status", "✳️trigger")
OUTPUT_TOOLTIPS = ("Get a status report text",
"Dammy output, to trigger execution if nothing is connected")
FUNCTION = "execute"
CATEGORY = "noEmbryo"
OUTPUT_NODE = True
# noinspection PyUnusedLocal
@staticmethod
def execute(trigger, save_directory, filename, prompt=None, extra_pnginfo=None):
status = "Trigger disabled - workflow not saved"
if trigger:
try:
workflow_data = extra_pnginfo.get("workflow", {}) if extra_pnginfo else {}
# Process save directory
if isabs(save_directory):
output_dir = save_directory
else:
output_dir = join(folder_paths.get_output_directory(), save_directory)
os.makedirs(output_dir, exist_ok=True)
# Process filename with timestamp
timestamp = datetime.now().strftime("%Y%m%d-%H%M%S")
processed_filename = filename.replace("{timestamp}", timestamp)
# Ensure .json extension
if not processed_filename.lower().endswith('.json'):
processed_filename += '.json'
save_path = join(output_dir, processed_filename)
# Save workflow to JSON
with open(save_path, "w", encoding="utf-8") as f:
# noinspection PyTypeChecker
json.dump(workflow_data, f, indent=4)
status = f"Workflow saved to: {save_path}"
except Exception as e:
status = f"Error saving workflow: {str(e)}"
return (status,)
# class ReplaceAudioNoReEncode:
# """ A minimal ComfyUI custom node that replaces the audio stream of an existing
# video file with a new audio track, using ffmpeg's stream-copy mode for the
# video (`-c:v copy`). The video bitstream is remuxed losslessly and is never
# decoded/re-encoded — only the container is rewritten with a new audio stream.
#
# Requires ffmpeg to be installed and available on PATH.
#
# video_path : path to an existing encoded video file (e.g. output of
# VHS Video Combine, or any .mp4/.mov/.mkv on disk).
# audio : standard ComfyUI AUDIO type ({"waveform": tensor, "sample_rate": int}),
# e.g. from Load Audio, VHS audio output, or a generated audio node.
# """
#
# @classmethod
# def INPUT_TYPES(cls):
# return {
# "required": {
# "video_path": ("STRING", {"default": "", "multiline": False,
# "tooltip": "Path to the video file whose audio stream "
# "will be replaced (e.g. any .mp4/.mov/.mkv on disk)."}),
# "filename_prefix": ("STRING", {"default": "audio_replaced",
# "tooltip": "Prefix for the output file name.\n"
# "The result is saved in the ComfyUI output "
# "directory as:\n"
# "<prefix>_<video name>_<counter>.<ext>"}),
# "audio_codec": (["aac", "copy"], {"default": "aac",
# "tooltip": "How to encode the new audio stream:\n"
# "• aac: re-encode to AAC 192kbps (always "
# "used when the audio comes from the AUDIO "
# "tensor input)\n"
# "• copy: remux the audio file losslessly, "
# "without re-encoding (only meaningful when "
# "using the audio_path input)"}),
# },
# "optional": {
# "audio": ("AUDIO", {"tooltip": "ComfyUI AUDIO signal (e.g. from Load Audio or a "
# "generated audio node) to use as the new audio "
# "stream.\nIgnored if audio_path is set."}),
# "audio_path": ("STRING", {"default": "", "multiline": False,
# "tooltip": "Path to an audio file — or a video file, whose "
# "audio stream will be extracted — to use as the new "
# "audio stream. If set, it takes priority over the "
# "audio tensor input."}),
# "shortest": ("BOOLEAN", {"default": True,
# "tooltip": "If enabled and the audio is shorter/longer than "
# "the video, the output is trimmed to the "
# "shorter of the two streams."}),
# },
# "hidden": {
# "prompt": "PROMPT",
# "extra_pnginfo": "EXTRA_PNGINFO",
# },
# }
#
# DESCRIPTION = ("Replaces the audio stream of a video file without re-encoding the video. "
# "The new audio comes either from an AUDIO tensor input or from an audio file "
# "given by audio_path. Requires ffmpeg on the PATH.")
#
# RETURN_TYPES = ("STRING",)
# RETURN_NAMES = ("video_path",)
# OUTPUT_TOOLTIPS = ("The path of the output video file with the replaced audio stream.",)
# FUNCTION = "replace_audio"
# CATEGORY = "noEmbryo"
# OUTPUT_NODE = True
#
# @staticmethod
# def _ffm_escape(text):
# """ Escapes a string for use as a value in an ffmetadata file """
# for ch in ("\\", "=", ";", "#", "\n"):
# text = text.replace(ch, "\\" + ch) if ch != "\n" else text.replace(ch, r"\n")
# return text
#
# @staticmethod
# def write_wave_file(wave_path, waveform, sample_rate):
# """ Writes a waveform tensor to a wav file, using only the standard library
# """
# import wave
# import numpy as np
# if waveform.dim() == 1: # [samples] -> [1, samples]
# waveform = waveform.unsqueeze(0)
# # [channels, samples] -> [samples, channels]
# samples = waveform.cpu().numpy().T
# samples = np.clip(samples, -1.0, 1.0)
# pcm = (samples * 32767.0).astype(np.int16)
# with wave.open(wave_path, "wb") as wf:
# wf.setnchannels(pcm.shape[1])
# wf.setsampwidth(2) # 2 bytes = 16 bit
# wf.setframerate(sample_rate)
# wf.writeframes(pcm.tobytes())
#
# def replace_audio(self, video_path, filename_prefix, audio_codec,
# audio=None, audio_path="", shortest=True,
# prompt=None, extra_pnginfo=None):
# if not video_path or not os.path.isfile(video_path):
# raise FileNotFoundError(f"Video file not found: {video_path!r}")
#
# output_dir = folder_paths.get_output_directory()
# os.makedirs(output_dir, exist_ok=True)
#
# tmp_audio_path = None
# if audio_path:
# if not os.path.isfile(audio_path):
# raise FileNotFoundError(f"Audio file not found: {audio_path!r}")
# second_input = audio_path
# elif audio is not None:
# # --- Write the incoming AUDIO tensor to a temp wav file ---
# waveform = audio["waveform"]
# sample_rate = audio["sample_rate"]
# if waveform.dim() == 3: # [batch, channels, samples] -> take first item
# waveform = waveform[0]
# tmp_audio_fd, tmp_audio_path = tempfile.mkstemp(suffix=".wav")
# os.close(tmp_audio_fd)
# self.write_wave_file(tmp_audio_path, waveform, sample_rate)
# second_input = tmp_audio_path
# # Copying raw PCM into a container makes no sense, so force aac
# audio_codec = "aac"
# else:
# raise ValueError("No audio given: connect an AUDIO input or set audio_path.")
#
# # --- Build a unique output path ---
# base_name = os.path.splitext(os.path.basename(video_path))[0]
# ext = os.path.splitext(video_path)[1] or ".mp4"
# # Start from max existing number + 1, so deleted files don't cause name reuse.
# # The prefix may contain subdirectories (e.g. "MMH3\NewAudio"), so the scan
# # must look in the directory the files are actually written to.
# out_path = os.path.join(output_dir, f"{filename_prefix}_{base_name}_001{ext}")
# scan_dir = os.path.dirname(out_path)
# os.makedirs(scan_dir, exist_ok=True)
# # listdir() returns bare filenames, so only the last component of the
# # prefix (without the directory part) can appear in them
# prefix_name = os.path.basename(filename_prefix.replace("\\", "/"))
# counter = 1
# pattern = re.compile(rf"^{re.escape(prefix_name)}_{re.escape(base_name)}"
# rf"_(\d+){re.escape(ext)}$")
# for fname in os.listdir(scan_dir):
# m = pattern.match(fname)
# if m:
# counter = max(counter, int(m.group(1)) + 1)
# out_name = f"{filename_prefix}_{base_name}_{counter:03d}{ext}"
# out_path = os.path.join(output_dir, out_name)
#
# # --- Write the workflow metadata to a temp ffmetadata file ---
# # (avoids Windows command-line length limits that -metadata args would hit)
# meta_fd, meta_path = tempfile.mkstemp(suffix=".txt")
# os.close(meta_fd)
# with io.open(meta_path, "w", encoding="utf-8") as mf:
# mf.write(";FFMETADATA1\n")
# if prompt is not None:
# mf.write(f"prompt={self._ffm_escape(json.dumps(prompt))}\n")
# if extra_pnginfo and "workflow" in extra_pnginfo:
# mf.write(f"workflow={self._ffm_escape(json.dumps(extra_pnginfo['workflow']))}\n")
#
# # --- ffmpeg: stream-copy the video, only touch the audio ---
# cmd = [
# "ffmpeg", "-y",
# "-i", video_path,
# "-i", second_input,
# "-i", meta_path,
# "-map", "0:v:0",
# "-map", "1:a:0",
# "-map_metadata", "2",
# "-c:v", "copy",
# ]
# if audio_codec == "copy":
# cmd += ["-c:a", "copy"]
# else:
# cmd += ["-c:a", "aac", "-b:a", "192k"]
# # allow arbitrary metadata keys in these containers
# if ext.lower() in (".mp4", ".mov"):
# cmd += ["-movflags", "use_metadata_tags"]
# if shortest:
# cmd.append("-shortest")
# cmd.append(out_path)
#
# def run_ffmpeg(command):
# return subprocess.run(command, capture_output=True, text=True)
#
# try:
# result = run_ffmpeg(cmd)
# if result.returncode != 0 and audio_codec == "copy":
# # "copy" can fail when the source audio codec is incompatible with
# # the output container (e.g. PCM in an AVI -> mp4). Retry with aac.
# fallback_cmd = list(cmd)
# for i, arg in enumerate(fallback_cmd):
# if arg == "-c:a" and fallback_cmd[i + 1] == "copy":
# fallback_cmd[i + 1] = "aac"
# result = run_ffmpeg(fallback_cmd)
# if result.returncode != 0:
# raise RuntimeError(f"ffmpeg failed (exit {result.returncode}):\n{result.stderr}")
# finally:
# for tmp in (tmp_audio_path, meta_path):
# if tmp and os.path.exists(tmp):
# os.remove(tmp)
#
# return (out_path,)
NODE_CLASS_MAPPINGS = {f"JsonPromptLoader -{__author__}": JsonPromptLoader,
f"Resolution Scale -{__author__}": ResolutionScale,
f"Regex Text Chopper -{__author__}": RegExTextChopper,
f"Auto Save Workflow -{__author__}": AutoSaveWorkflow,
f"Load Image (from path) -{__author__}": LoadImageFromPathEnhanced,
f"Image Composer -{__author__}": ImageComposer,
f"H3MotionContextClipStitcher -{__author__}": H3MotionContextClipStitcher,
f"H3ClipRefiner -{__author__}": H3ClipRefiner,
f"H3MotionContextClipPurge -{__author__}": H3MotionContextClipPurge,
f"H3ContextLatentConverter -{__author__}": H3ContextLatentConverter,
f"H3AVLatentFromVideo -{__author__}": H3AVLatentFromVideo,
# f"ReplaceAudioNoReEncode -{__author__}": ReplaceAudioNoReEncode,
"PromptTermList1": PromptTermList1,
"PromptTermList2": PromptTermList2,
"PromptTermList3": PromptTermList3,
"PromptTermList4": PromptTermList4,
"PromptTermList5": PromptTermList5,
"PromptTermList6": PromptTermList6,
}
NODE_DISPLAY_NAME_MAPPINGS = {f"JsonPromptLoader -{__author__}": f"Json Prompt Loader /{__author__}",
f"Resolution Scale -{__author__}": f"Resolution Scale /{__author__}",
f"Regex Text Chopper -{__author__}": f"Regex Text Chopper /{__author__}",
f"Auto Save Workflow -{__author__}": f"Auto Save Workflow /{__author__}",
f"Load Image (from path) -{__author__}": f"Load Image (from path) /{__author__}",
f"Image Composer -{__author__}": f"Image Composer /{__author__}",
f"H3MotionContextClipStitcher -{__author__}": f"H3 Motion Context Clip Stitcher /{__author__}",
f"H3ClipRefiner -{__author__}": f"H3 Clip Refiner /{__author__}",
f"H3MotionContextClipPurge -{__author__}": f"H3 Motion Context Clip Purge /{__author__}",
f"H3ContextLatentConverter -{__author__}": f"H3 Context Latent Converter /{__author__}",
f"H3AVLatentFromVideo -{__author__}": f"H3 AV Latent from Video /{__author__}",
# f"ReplaceAudioNoReEncode -{__author__}": f"Replace Audio no ReEncode /{__author__}",
"PromptTermList1": f"PromptTermList 1 /{__author__}",
"PromptTermList2": f"PromptTermList 2 /{__author__}",
"PromptTermList3": f"PromptTermList 3 /{__author__}",
"PromptTermList4": f"PromptTermList 4 /{__author__}",
"PromptTermList5": f"PromptTermList 5 /{__author__}",
"PromptTermList6": f"PromptTermList 6 /{__author__}",
}