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alltalk_tts/script.py
T
erew123 4bcafc16cf update to v1.5 
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2023-12-15 22:39:36 +00:00

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import html
import json
import random
import subprocess
import time
import os
import requests
import threading
import signal
import sys
import atexit
from pathlib import Path
from datetime import datetime, timedelta
import re
import numpy as np
import soundfile as sf
import uuid
##############################################################
#### LOAD PARAMS FROM CONFIG.JSON - REQUIRED FOR BRANDING ####
##############################################################
# STARTUP VARIABLE - Create "this_dir" variable as the current script directory
this_dir = Path(__file__).parent.resolve()
# load config file in and get settings
def load_config(file_path):
with open(file_path, "r") as config_file:
config = json.load(config_file)
return config
config_file_path = this_dir / "config.json"
# Load the params dictionary from the config.json file
params = load_config(config_file_path)
# Required for sentence splitting
try:
from TTS.api import TTS
from TTS.utils.synthesizer import Synthesizer
except ModuleNotFoundError:
logger.error(
f"[{params['branding']}]\033[91mWarning\033[0m Could not find the TTS module. Make sure to install the requirements for the {params['branding']} extension."
f"[{params['branding']}]\033[91mWarning\033[0m Linux / Mac:\npip install -r extensions/alltalk_tts/requirements.txt\n"
f"[{params['branding']}]\033[91mWarning\033[0m Windows:\npip install -r extensions\\alltalk_tts\\requirements.txt\n"
f"[{params['branding']}]\033[91mWarning\033[0m If you used the one-click installer, paste the command above in the terminal window launched after running the cmd_ script. On Windows, that's cmd_windows.bat."
)
raise
# IMPORT - Attempt Importing DeepSpeed (required for displaying Deepspeed checkbox in gradio)
try:
import deepspeed
deepspeed_installed = True
except ImportError:
deepspeed_installed = False
# Import gradio if being used within text generation webUI
try:
import gradio as gr
from modules import chat, shared, ui_chat
from modules.logging_colors import logger
from modules.ui import create_refresh_button
from modules.utils import gradio
# This is set to check if the script is being run within text generation webui or as a standalone script. False is running as part of text gen web ui or a gradio interface
running_in_standalone = False
except ModuleNotFoundError:
print(f"[{params['branding']}Startup] Running script.py in standalone mode")
# This is set to check if the script is being run within text generation webui or as a standalone script. true means standalone
running_in_standalone = True
###########################
#### STARTUP VARIABLES ####
###########################
# STARTUP VARIABLE - Import languges file for Gradio to be able to display them in the interface
with open(this_dir / "languages.json", encoding="utf8") as f:
languages = json.load(f)
# Create a global lock
process_lock = threading.Lock()
# Gather the voice files
def get_available_voices():
return sorted([voice.name for voice in Path(f"{this_dir}/voices").glob("*.wav")])
#########################
#### LICENSE DISPLAY ####
#########################
# STARTUP Display Licence Information
print(f"[{params['branding']}Startup] \033[94mCoqui Public Model License\033[0m")
print(f"[{params['branding']}Startup] \033[94mhttps://coqui.ai/cpml.txt\033[0m")
############################################
#### DELETE OLD OUTPUT WAV FILES IF SET ####
############################################
def delete_old_files(folder_path, days_to_keep):
current_time = datetime.now()
print(
f"[{params['branding']}Startup] Deletion of old output folder WAV files is currently enabled and set at",
delete_output_wavs_setting,
)
for file_name in os.listdir(folder_path):
file_path = os.path.join(folder_path, file_name)
if os.path.isfile(file_path):
file_creation_time = datetime.fromtimestamp(os.path.getctime(file_path))
age = current_time - file_creation_time
if age > timedelta(days=days_to_keep):
os.remove(file_path)
# Extract settings using params dictionary
delete_output_wavs_setting = params["delete_output_wavs"]
output_folder_wav = params["output_folder_wav"]
output_folder_wav = os.path.normpath(output_folder_wav)
# Check and perform file deletion
if delete_output_wavs_setting.lower() == "disabled":
print(
"["
+ params["branding"]
+ "Startup] Old output wav file deletion is set to disabled."
)
else:
try:
days_to_keep = int(delete_output_wavs_setting.split()[0])
delete_old_files(output_folder_wav, days_to_keep)
except ValueError:
print(
f"[{params['branding']}Startup] Invalid setting for deleting old wav files. Please use 'Disabled' or 'X Days' format."
)
########################
#### STARTUP CHECKS ####
########################
# STARTUP Checks routine
def check_required_files():
this_dir = Path(__file__).parent.resolve()
download_script_path = this_dir / "modeldownload.py"
subprocess.run(["python", str(download_script_path)])
print(f"[{params['branding']}Startup] All required files are present.")
# STARTUP Call Check routine
check_required_files()
#################################################
#### SET GRADIO BUTTONS BASED ON CONFIG.JSON ####
#################################################
if params["tts_method_api_tts"] == True:
gr_modelchoice = "API TTS"
elif params["tts_method_api_local"] == True:
gr_modelchoice = "API Local"
elif params["tts_method_xtts_local"] == True:
gr_modelchoice = "XTTSv2 Local"
# Set the default for Narrated text without asterisk or quotes to be Narrator
non_quoted_text_is = True
######################
#### GRADIO STUFF ####
######################
def remove_tts_from_history(history):
for i, entry in enumerate(history["internal"]):
history["visible"][i] = [history["visible"][i][0], entry[1]]
return history
def toggle_text_in_history(history):
for i, entry in enumerate(history["visible"]):
visible_reply = entry[1]
if visible_reply.startswith("<audio"):
if params["show_text"]:
reply = history["internal"][i][1]
history["visible"][i] = [
history["visible"][i][0],
f"{visible_reply.split('</audio>')[0]}</audio>\n\n{reply}",
]
else:
history["visible"][i] = [
history["visible"][i][0],
f"{visible_reply.split('</audio>')[0]}</audio>",
]
return history
def history_modifier(history):
# Remove autoplay from the last reply
if len(history["internal"]) > 0:
history["visible"][-1] = [
history["visible"][-1][0],
history["visible"][-1][1].replace("controls autoplay>", "controls>"),
]
return history
######################################
#### SUBPROCESS/WEBSERVER STARTUP ####
######################################
base_url = f"http://{params['ip_address']}:{params['port_number']}"
script_path = this_dir / "tts_server.py"
def signal_handler(sig, frame):
print(
f"[{params['branding']}Shutdown] \033[94mReceived Ctrl+C, terminating subprocess\033[92m"
)
if process.poll() is None:
process.terminate()
process.wait() # Wait for the subprocess to finish
sys.exit(0)
# Attach the signal handler to the SIGINT signal (Ctrl+C)
signal.signal(signal.SIGINT, signal_handler)
# Start the subprocess
process = subprocess.Popen(["python", script_path])
# Check if the subprocess has started successfully
if process.poll() is None:
print(f"[{params['branding']}Startup] TTS Subprocess starting")
print(
f"[{params['branding']}Startup] Readme available here:",
f"http://{params['ip_address']}:{params['port_number']}",
)
else:
print(
f"[{params['branding']}Startup] \033[91mWarning\033[0m TTS Subprocess Webserver failing to start process"
)
print(
f"[{params['branding']}Startup] \033[91mWarning\033[0m It could be that you have something on port:",
params["port_number"],
)
print(
f"[{params['branding']}Startup] \033[91mWarning\033[0m Or you have not started in a Python environement with all the necesssary bits installed"
)
print(
f"[{params['branding']}Startup] \033[91mWarning\033[0m Check you are starting Text-generation-webui with either the start_xxxxx file or the Python environment with cmd_xxxxx file."
)
print(
f"[{params['branding']}Startup] \033[91mWarning\033[0m xxxxx is the type of OS you are on e.g. windows, linux or mac."
)
print(
f"[{params['branding']}Startup] \033[91mWarning\033[0m Alternatively, you could check no other Python processes are running that shouldnt be e.g. Restart your computer is the simple way."
)
# Cleanly kill off this script, but allow text-generation-webui to keep running, albeit without this alltalk_tts
sys.exit(1)
timeout = 60 # Adjust the timeout as needed
# Introduce a delay before starting the check loop
time.sleep(25) # Wait 25 secs before checking if the tts_server.py has started up.
start_time = time.time()
while time.time() - start_time < timeout:
try:
response = requests.get(f"{base_url}/ready")
if response.status_code == 200:
break
except requests.RequestException as e:
# Print the exception for debugging purposes
print(
f"[{params['branding']}Startup] \033[91mWarning\033[0m TTS Subprocess has NOT started up yet, Will keep trying for 60 seconds maximum. Please wait."
)
time.sleep(1)
else:
print(
f"[{params['branding']}Startup] Startup timed out. Check the server logs for more information."
)
# Cleanly kill off this script, but allow text-generation-webui to keep running, albeit without this alltalk_tts
sys.exit(1)
#####################################
#### MODEL LOADING AND UNLOADING ####
#####################################
# MODEL - Swap model based on Gradio selection API TTS, API Local, XTTSv2 Local
def send_reload_request(tts_method):
try:
params["model_loaded"] = False
url = f"{base_url}/api/reload"
payload = {"tts_method": tts_method}
response = requests.post(url, params=payload)
response.raise_for_status() # Raises an HTTPError for bad responses
json_response = response.json()
# Check if the reload operation was successful
if json_response.get("status") == "model-success":
# Update model_loaded to True if the reload was successful
params["model_loaded"] = True
# Update local script parameters based on the tts_method
if tts_method == "API TTS":
params["tts_method_api_local"] = False
params["tts_method_xtts_local"] = False
params["tts_method_api_tts"] = True
params["deepspeed_activate"] = False
audio_path = this_dir / "templates" / "apitts.wav"
elif tts_method == "API Local":
params["tts_method_api_tts"] = False
params["tts_method_xtts_local"] = False
params["tts_method_api_local"] = True
params["deepspeed_activate"] = False
audio_path = this_dir / "templates" / "apilocal.wav"
elif tts_method == "XTTSv2 Local":
params["tts_method_api_tts"] = False
params["tts_method_api_local"] = False
params["tts_method_xtts_local"] = True
audio_path = this_dir / "templates" / "xttslocal.wav"
return f'<audio src="file/{audio_path}" controls autoplay></audio>'
except requests.exceptions.RequestException as e:
# Handle the HTTP request error
print(
f"[{params['branding']}Server] \033[91mWarning\033[0m Error during request to webserver process: {e}"
)
return {"status": "error", "message": str(e)}
##################
#### LOW VRAM ####
##################
# LOW VRAM - Gradio Checkbox handling
def send_lowvram_request(low_vram):
try:
params["model_loaded"] = False
if low_vram:
audio_path = this_dir / "templates" / "lowvramenabled.wav"
else:
audio_path = this_dir / "templates" / "lowvramdisabled.wav"
url = f"{base_url}/api/lowvramsetting?new_low_vram_value={low_vram}"
headers = {"Content-Type": "application/json"}
response = requests.post(url, headers=headers)
response.raise_for_status() # Raises an HTTPError for bad responses
json_response = response.json()
# Check if the low VRAM request was successful
if json_response.get("status") == "lowvram-success":
# Update any relevant variables or perform other actions on success
params["model_loaded"] = True
return f'<audio src="file/{audio_path}" controls autoplay></audio>'
except requests.exceptions.RequestException as e:
# Handle the HTTP request error
print(
f"[{params['branding']}Server] \033[91mWarning\033[0m Error during request to webserver process: {e}"
)
return {"status": "error", "message": str(e)}
###################
#### DeepSpeed ####
###################
# DEEPSPEED - Reload the model when DeepSpeed checkbox is enabled/disabled
def send_deepspeed_request(deepspeed_param):
try:
params["model_loaded"] = False
if deepspeed_param:
audio_path = this_dir / "templates" / "deepspeedenabled.wav"
else:
audio_path = this_dir / "templates" / "deepspeeddisabled.wav"
url = f"{base_url}/api/deepspeed?new_deepspeed_value={deepspeed_param}"
headers = {"Content-Type": "application/json"}
response = requests.post(url, headers=headers)
response.raise_for_status() # Raises an HTTPError for bad responses
json_response = response.json()
# Check if the deepspeed request was successful
if json_response.get("status") == "deepspeed-success":
# Update any relevant variables or perform other actions on success
params["model_loaded"] = True
return f'<audio src="file/{audio_path}" controls autoplay></audio>'
except requests.exceptions.RequestException as e:
# Handle the HTTP request error
print(
f"[{params['branding']}Server] \033[91mWarning\033[0m Error during request to webserver process: {e}"
)
return {"status": "error", "message": str(e)}
# DEEPSPEED - Display DeepSpeed Checkbox Yes or No
deepspeed_condition = params["tts_method_xtts_local"] == "True" and deepspeed_installed
#############################################################
#### TTS STRING CLEANING & PROCESSING PRE SENDING TO TTS ####
#############################################################
def new_split_into_sentences(self, text):
sentences = self.seg.segment(text)
if params["remove_trailing_dots"]:
sentences_without_dots = []
for sentence in sentences:
if sentence.endswith(".") and not sentence.endswith("..."):
sentence = sentence[:-1]
sentences_without_dots.append(sentence)
return sentences_without_dots
else:
return sentences
Synthesizer.split_into_sentences = new_split_into_sentences
# Check model is loaded and string isnt empty, before sending a TTS request.
def before_audio_generation(string, params):
# Check Model is loaded into cuda or cpu and error if not
if not params["model_loaded"]:
print(
f"[{params['branding']}Model] \033[91mWarning\033[0m Model is still loading, please wait before trying to generate TTS"
)
return
string = html.unescape(string) or random_sentence()
if string == "":
return "*Empty string*"
return string
##################
#### Narrator ####
##################
def combine(audio_files, output_folder, state):
audio = np.array([])
for audio_file in audio_files:
audio_data, sample_rate = sf.read(audio_file)
# Ensure all audio files have the same sample rate
if audio.size == 0:
audio = audio_data
else:
audio = np.concatenate((audio, audio_data))
# Save the combined audio to a file with a specified sample rate
if "character_menu" in state:
output_file_path = os.path.join(output_folder, f'{state["character_menu"]}_{int(time.time())}_combined.wav')
else:
output_file_path = os.path.join(output_folder, f'TTSOUT_{int(time.time())}_combined.wav')
sf.write(output_file_path, audio, samplerate=sample_rate)
# Clean up unnecessary files
for audio_file in audio_files:
os.remove(audio_file)
return output_file_path
################################
#### TTS PREVIEW GENERATION ####
################################
# PREVIEW VOICE - Generate Random Sentence if Voice Preview box is empty
def random_sentence():
with open(this_dir / "harvard_sentences.txt") as f:
return random.choice(list(f))
# PREVIEW VOICE- Generate TTS Function
def voice_preview(string):
if not params["activate"]:
return string
# Clean the string, capture model not loaded, and move model to cuda if needed
cleaned_string = before_audio_generation(string, params)
if cleaned_string is None:
return
string = cleaned_string
# Setup the output file
output_file = Path(params["output_folder_wav"]) / "voice_preview.wav"
# Generate the audio
language_code = languages.get(params["language"])
# Convert the WindowsPath object to a string before using it in JSON payload
output_file_str = output_file.as_posix()
# Lock before making the generate request
with process_lock:
generate_response = send_generate_request(
string, params["voice"], language_code, output_file_str
)
# Check if lock is already acquired
if process_lock.locked():
print(
f"[{params['branding']}Model] \033[91mWarning\033[0m Audio generation is already in progress. Please wait."
)
return
if generate_response.get("status") == "generate-success":
# Handle Gradio and playback
autoplay = "autoplay" if params["autoplay"] else ""
return f'<audio src="file/{output_file_str}?{int(time.time())}" controls {autoplay}></audio>'
else:
# Handle the case where audio generation was not successful
return f"[{params['branding']}Server] Audio generation failed. Status: {generate_response.get('status')}"
#################################
#### TTS STANDARD GENERATION ####
#################################
# STANDARD VOICE - Generate TTS Function
def output_modifier(string, state):
if not params["activate"]:
return string
original_string = string
cleaned_string = before_audio_generation(string, params)
if cleaned_string is None:
return
string = cleaned_string
language_code = languages.get(params["language"])
# Create a list to store generated audio paths
audio_files = []
if process_lock.acquire(blocking=False):
try:
if params["narrator_enabled"]:
# print(original_string)
# Do Some basic stripping and remove any double CR's
processed_string = (
original_string
.replace("***", "*")
.replace("**", "*")
.replace("\n\n", "\n")
)
# Clean up two asterisks (narrators) being made between a newline, making it one sentence.
processed_string = re.sub(r'\.\*\n\*', '. ', processed_string)
# Clean up a few other bits.
processed_string = (
processed_string
.replace("&#x27;", "'")
.replace("\n", " ")
# Add special characters to the quote so that we can use it to identify things later after its been split
.replace('&quot;', '&quot;<')
# Capture new conversations which wont have things like &quote in them
.replace('"', '&quot;<')
)
#capturing another outlier in inital character paragraph
# print("processed string 1 is:", processed_string)
processed_string = processed_string.replace('&quot;<. *', '&quot;< *"')
processed_string = processed_string.replace('< *"', '< *')
processed_string = processed_string.replace('. *', '< *')
# print("processed string 2 is:", processed_string)
# Set up a tracking of the individual wav files.
audio_files_all_paragraphs = []
# Split the line using &quot; and ".* " (so end of sentences, leaving special characters added to the start of all OTHER sentences, bar possibly the first one if its starting with a *
parts = re.split(r'&quot;|\.\*', processed_string)
audio_files_paragraph = []
for i, part in enumerate(parts):
# Skip parts that are too short
if len(part.strip()) <= 1:
continue
# Figure out which type of line it is, then replace characters as necessary to avoid TTS trying to pronunce them, htmlunescape after.
# Character will always be a < with a letter immediately after it
if '<' in part and '< *' not in part and '<*' not in part and '< *' not in part and '< ' not in part and '< ' not in part:
cleaned_part = html.unescape(part.replace('<', ''))
voice_to_use = params["voice"]
#Narrator will always be an * or < with an * a position or two after it.
elif '<*' in part or '< *' in part or '< *' in part or '*' in part:
cleaned_part = html.unescape(part.replace('<*', '').replace('< *', '').replace('< *', '').replace('*', ''))
voice_to_use = params["narrator_voice"]
#If the other two dont capture it, aka, the AI gave no * or &quot; on the line, use non_quoted_text_is aka user interface, user can choose Char or Narrator
elif non_quoted_text_is:
cleaned_part = html.unescape(part.replace('< ', '').replace('< ', '').replace('< ', ''))
voice_to_use = params["voice"]
else:
cleaned_part = html.unescape(part.replace('< ', '').replace('< ', '').replace('< ', ''))
voice_to_use = params["narrator_voice"]
# Check if character name exists and if not, just call it TTSOUT_
if "character_menu" in state:
output_file = Path(f'{params["output_folder_wav"]}/{state["character_menu"]}_{int(time.time())}_{i}.wav')
else:
output_file = Path(f'{params["output_folder_wav"]}/TTSOUT_{int(time.time())}_{i}.wav')
# Generate that TTS and output to a file
output_file_str = output_file.as_posix()
generate_response = send_generate_request(
cleaned_part, voice_to_use, language_code, output_file_str
)
audio_path = generate_response.get("data", {}).get("audio_path")
audio_files_paragraph.append(audio_path)
# Accumulate audio files within the paragraph
audio_files_all_paragraphs.extend(audio_files_paragraph)
# Combine audio files across paragraphs
final_output_file = combine(
audio_files_all_paragraphs, params["output_folder_wav"], state
)
else:
processed_string = (
original_string
.replace("***", "")
.replace("**", "")
.replace("*", "")
.replace("\n\n", "\n")
.replace("&#x27;", "'")
)
cleaned_part = html.unescape(processed_string)
# Process the part and give it a non-character name if being used vai API or standalone.
if "character_menu" in state:
output_file = Path(f'{params["output_folder_wav"]}/{state["character_menu"]}_{int(time.time())}.wav')
else:
output_file = Path(f'{params["output_folder_wav"]}/TTSOUT_{int(time.time())}.wav')
output_file_str = output_file.as_posix()
output_file = get_output_filename(state)
generate_response = send_generate_request(
cleaned_part, params["voice"], language_code, output_file_str
)
audio_path = generate_response.get("data", {}).get("audio_path")
final_output_file = audio_path
finally:
# Always release the lock, whether an exception occurs or not
process_lock.release()
else:
# The lock is already acquired
print(
f"[{params['branding']}Model] \033[91mWarning\033[0m Audio generation is already in progress. Please wait."
)
return
if generate_response.get("status") == "generate-success":
audio_path = generate_response.get("data", {}).get("audio_path")
if audio_path:
# Handle Gradio and playback
autoplay = "autoplay" if params["autoplay"] else ""
string = (
f'<audio src="file/{final_output_file}" controls {autoplay}></audio>'
)
if params["show_text"]:
string += f"\n\n{original_string}"
shared.processing_message = "*Is typing...*"
return string
else:
print(
f"[{params['branding']}Server] \033[91mWarning\033[0m No audio path in the response."
)
else:
print(
f"[{params['branding']}Server] \033[91mWarning\033[0m Audio generation failed. Status:",
generate_response.get("message"),
)
def get_output_filename(state):
return Path(
f'{params["output_folder_wav"]}/{state["character_menu"]}_{str(uuid.uuid4())[:8]}.wav'
).as_posix()
###############################################
#### SEND GENERATION REQUEST TO TTS ENGINE ####
###############################################
def send_generate_request(text, voice, language, output_file):
url = f"{base_url}/api/generate"
payload = {
"text": text,
"voice": voice,
"language": language,
"output_file": output_file,
}
headers = {"Content-Type": "application/json"}
response = requests.post(url, json=payload, headers=headers)
return response.json()
################################
#### SUBPORCESS TERMINATION ####
################################
# Register the termination code to be executed at exit
atexit.register(lambda: process.terminate() if process.poll() is None else None)
######################
#### GRADIO STUFF ####
######################
def state_modifier(state):
if not params["activate"]:
return state
state["stream"] = False
return state
def update_narrator_enabled(value):
if value == "Enabled":
params["narrator_enabled"] = True
elif value == "Disabled":
params["narrator_enabled"] = False
def update_non_quoted_text_is(value):
global non_quoted_text_is
if value == "Narrator":
non_quoted_text_is = False
elif value == "Char":
non_quoted_text_is = True
def input_modifier(string, state):
if not params["activate"]:
return string
shared.processing_message = "*Is recording a voice message...*"
return string
def custom_css():
path_to_css = Path(f"{this_dir}/style.css")
return open(path_to_css, "r").read()
def ui():
with gr.Accordion(params["branding"] + " TTS (XTTSv2)"):
with gr.Row():
activate = gr.Checkbox(value=params["activate"], label="Activate TTS")
autoplay = gr.Checkbox(
value=params["autoplay"], label="Play TTS automatically"
)
with gr.Row():
show_text = gr.Checkbox(
value=params["show_text"], label="Show message text under audio player"
)
remove_trailing_dots = gr.Checkbox(
value=params["remove_trailing_dots"],
label='Remove trailing "." from text segments before generation',
)
with gr.Row():
with gr.Row():
available_voices = get_available_voices()
default_voice = params["voice"]
# Check if the default voice is in the list of available voices
if default_voice not in available_voices:
# Handle the case where the default voice is not in the list (choose a default value or update it)
default_voice = available_voices[
0
] # Choose the first available voice as the default
# Add allow_custom_value=True to the Dropdown
voice = gr.Dropdown(
available_voices,
label="Default Voice",
value=default_voice,
allow_custom_value=True,
)
create_refresh_button(
voice,
lambda: None,
lambda: {
"choices": get_available_voices(),
"value": params["voice"],
},
"refresh-button",
)
language = gr.Dropdown(
languages.keys(),
label="Language",
allow_custom_value=True,
value=params["language"],
)
with gr.Row():
with gr.Row():
narrator_voice_gr = gr.Dropdown(
get_available_voices(),
label="Narrator Voice",
allow_custom_value=True,
value=params["narrator_voice"],
)
create_refresh_button(
narrator_voice_gr,
lambda: None,
lambda: {
"choices": get_available_voices(),
"value": params["narrator_voice"],
},
"refresh-button",
)
narrator_enabled_gr = gr.Radio(
choices={"Enabled": "true", "Disabled": "false"},
label="Narrator Activation",
value="Enabled" if params.get("narrator_enabled") else "Disabled",
)
non_quoted_text_is_gr = gr.Radio(
choices={"Char": "true", "Narrator": "false"},
label='Text NOT inside of * or " is',
value="Char" if non_quoted_text_is else "Narrator",
)
with gr.Row():
low_vram = gr.Checkbox(
value=params["low_vram"], label="Low VRAM mode (Read NOTE)"
)
low_vram_play = gr.HTML(visible=False)
deepspeed_checkbox = gr.Checkbox(
value=params["deepspeed_activate"],
label="Activate DeepSpeed (Read NOTE)",
visible=deepspeed_installed,
)
deepspeed_checkbox_play = gr.HTML(visible=False)
with gr.Row():
tts_radio_buttons = gr.Radio(
choices=["API TTS", "API Local", "XTTSv2 Local"],
label="Select TTS Generation Method (Read NOTE)",
value=gr_modelchoice, # Set the default value
)
tts_radio_buttons_play = gr.HTML(visible=False)
explanation_text = gr.HTML(
f"<p>NOTE: Switching Model Type, Low VRAM & DeepSpeed takes 15 seconds. Each TTS generation method has a slightly different sound. DeepSpeed checkbox is only visible if DeepSpeed is present. Readme & Settings: <a href='http://{params['ip_address']}:{params['port_number']}'>http://{params['ip_address']}:{params['port_number']}</a>"
)
with gr.Row():
preview_text = gr.Text(
show_label=False,
placeholder="Preview text",
elem_id="silero_preview_text",
)
preview_play = gr.Button("Preview")
preview_audio = gr.HTML(visible=False)
with gr.Row():
convert = gr.Button("Permanently replace audios with the message texts")
convert_cancel = gr.Button("Cancel", visible=False)
convert_confirm = gr.Button(
"Confirm (cannot be undone)", variant="stop", visible=False
)
# Convert history with confirmation
convert_arr = [convert_confirm, convert, convert_cancel]
convert.click(
lambda: [
gr.update(visible=True),
gr.update(visible=False),
gr.update(visible=True),
],
None,
convert_arr,
)
convert_confirm.click(
lambda: [
gr.update(visible=False),
gr.update(visible=True),
gr.update(visible=False),
],
None,
convert_arr,
).then(remove_tts_from_history, gradio("history"), gradio("history")).then(
chat.save_history,
gradio("history", "unique_id", "character_menu", "mode"),
None,
).then(
chat.redraw_html, gradio(ui_chat.reload_arr), gradio("display")
)
convert_cancel.click(
lambda: [
gr.update(visible=False),
gr.update(visible=True),
gr.update(visible=False),
],
None,
convert_arr,
)
# Toggle message text in history
show_text.change(lambda x: params.update({"show_text": x}), show_text, None).then(
toggle_text_in_history, gradio("history"), gradio("history")
).then(
chat.save_history,
gradio("history", "unique_id", "character_menu", "mode"),
None,
).then(
chat.redraw_html, gradio(ui_chat.reload_arr), gradio("display")
)
# Event functions to update the parameters in the backend
activate.change(lambda x: params.update({"activate": x}), activate, None)
autoplay.change(lambda x: params.update({"autoplay": x}), autoplay, None)
low_vram.change(lambda x: params.update({"low_vram": x}), low_vram, None)
low_vram.change(lambda x: send_lowvram_request(x), low_vram, low_vram_play, None)
tts_radio_buttons.change(send_reload_request, tts_radio_buttons, tts_radio_buttons_play, None)
deepspeed_checkbox.change(send_deepspeed_request, deepspeed_checkbox, deepspeed_checkbox_play, None)
remove_trailing_dots.change(
lambda x: params.update({"remove_trailing_dots": x}), remove_trailing_dots, None
)
voice.change(lambda x: params.update({"voice": x}), voice, None)
language.change(lambda x: params.update({"language": x}), language, None)
# Narrator selection actions
narrator_enabled_gr.change(update_narrator_enabled, narrator_enabled_gr, None)
non_quoted_text_is_gr.change(update_non_quoted_text_is, non_quoted_text_is_gr, None)
narrator_voice_gr.change(lambda x: params.update({"narrator_voice": x}), narrator_voice_gr, None)
# Play preview
preview_text.submit(voice_preview, preview_text, preview_audio)
preview_play.click(voice_preview, preview_text, preview_audio)
##########################################
#### STANDALONE MODE LOOP TERMINATION ####
##########################################
## Loop to keep the script from exiting out if its being run as a standalone script and not part of text-generation-webui
if running_in_standalone:
while True:
try:
time.sleep(1) # Add a small delay to avoid high CPU usage
except KeyboardInterrupt:
break # Allow graceful exit on Ctrl+C
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