Updated firstrun better docker/colab support
In Docker or Google colab environments where people may not have access to a keyboard, just download piper (as its small) and dont wait the 60 seconds for a keypress.
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erew123 authored and GitHub committed
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@@ -1,170 +1,287 @@
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import json
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import os
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import shutil
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import sys
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import zipfile
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import requests
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from tqdm import tqdm
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from inputimeout import inputimeout, TimeoutOccurred
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from pathlib import Path
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# Setting the module search path:
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sys.path.insert(0, str(Path(__file__).parent.parent.parent.resolve()))
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from config import AlltalkTTSEnginesConfig, AlltalkConfig
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this_dir = Path(__file__).parent.resolve().parent.resolve().parent.resolve()
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def download_file(url, dest_path):
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response = requests.get(url, stream=True)
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total_size = int(response.headers.get('content-length', 0))
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block_size = 1024 # 1 Kibibyte
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t = tqdm(total=total_size, unit='iB', unit_scale=True, desc=str(dest_path))
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with open(dest_path, 'wb') as file:
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for data in response.iter_content(block_size):
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t.update(len(data))
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file.write(data)
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t.close()
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def setup_piper():
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os.makedirs(this_dir / 'models/piper', exist_ok=True)
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os.makedirs(this_dir / 'models/xtts', exist_ok=True)
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download_file("https://huggingface.co/rhasspy/piper-voices/resolve/v1.0.0/en/en_US/ljspeech/high/en_US-ljspeech-high.onnx?download=true",
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this_dir / "models/piper/en_US-ljspeech-high.onnx")
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download_file("https://huggingface.co/rhasspy/piper-voices/resolve/v1.0.0/en/en_US/ljspeech/high/en_US-ljspeech-high.onnx.json?download=true.json",
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this_dir / "models/piper/en_US-ljspeech-high.onnx.json")
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def setup_vits():
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os.makedirs(this_dir / 'models/vits', exist_ok=True)
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os.makedirs(this_dir / 'models/xtts', exist_ok=True)
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zip_path = this_dir / 'models/vits/vits.zip'
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download_file("https://coqui.gateway.scarf.sh/v0.6.1_models/tts_models--en--vctk--vits.zip", zip_path)
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with zipfile.ZipFile(zip_path, 'r') as zip_ref:
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zip_ref.extractall(this_dir / 'models/vits')
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os.remove(zip_path)
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def setup_xtts():
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os.makedirs(this_dir / 'models/xtts/xttsv2_2.0.3', exist_ok=True)
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base_url = "https://huggingface.co/coqui/XTTS-v2/resolve/v2.0.3/"
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files = [
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"LICENSE.txt",
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"README.md",
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"config.json",
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"model.pth",
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"dvae.pth",
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"mel_stats.pth",
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"speakers_xtts.pth",
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"vocab.json"
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]
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for file in files:
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download_file(base_url + file + "?download=true", this_dir / f"models/xtts/xttsv2_2.0.3/{file}")
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def update_tts_engines(engine):
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AlltalkTTSEnginesConfig.get_instance().change_engine(engine).save()
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def set_firstrun_model_false():
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config.firstrun_model = False
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config.save()
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def warning_message():
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print(f"[{branding}TTS]")
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print(f"[{branding}TTS] \033[93mIf you have you have UPGRADED from v1 ensure you have re-installed\033[0m")
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print(f"[{branding}TTS] \033[93mthe requirements. Otherwise you will get failures and errors!\033[0m")
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print(f"[{branding}TTS] \033[93mOn Linux ignore the \033[0m'sparse_attn requires a torch version' \033[93mand\033[0m")
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print(f"[{branding}TTS] \033[0m'using untested triton version' \033[93mmessages.\033[0m")
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print(f"[{branding}TTS]")
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# Load confignew.json (might be version 1 or 2):
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with open(AlltalkConfig.default_config_path(), 'r') as file:
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config_json = json.load(file)
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branding = config_json['branding']
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# Check if the config file is version 1
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if "ip_address" in config_json:
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print(f"[{branding}TTS] Detected version 1 configuration file.")
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print(f"[{branding}TTS] Upgrading to version 2 configuration file...")
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# Backup the old configuration file
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backup_path = AlltalkConfig.default_config_path() + ".backup"
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shutil.copyfile(AlltalkConfig.default_config_path(), backup_path)
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# Copy the new configuration template to replace the old config file
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new_config_template_path = this_dir / 'system/config/confignew.json'
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shutil.copyfile(new_config_template_path, AlltalkConfig.default_config_path())
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print(f"[{branding}TTS] Configuration file upgraded successfully.")
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config = AlltalkConfig.get_instance()
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branding = config.branding
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# Check if firstrun_model is true
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if config.firstrun_model:
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print(f"[{branding}TTS]")
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print(f"[{branding}TTS] \033[92mThis is the first time startup. Please download a start TTS model.\033[0m")
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print(f"[{branding}TTS]")
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# List of available models
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models = [
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{"name": "piper", "model": "piper"},
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{"name": "vits", "model": "tts_models--en--vctk--vits"},
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{"name": "xtts", "model": "xttsv2_2.0.3"},
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]
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# Display models to the user
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print(f"[{branding}TTS] \033[94mAvailable First Time Start-up models:\033[0m")
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print(f"[{branding}TTS]")
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for idx, model in enumerate(models):
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print(f"[{branding}TTS] \033[93m{idx + 1}. \033[94m{model['name']} - {model['model']}\033[0m")
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print(f"[{branding}TTS] \033[93m{len(models) + 1}.\033[94m I have my own models already\033[0m")
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print(f"[{branding}TTS]")
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print(f"[{branding}TTS] \033[94mIn \033[91m60 seconds\033[0m \033[94ma Piper model will be \033[91mdownloaded automatically.\033[0m")
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print(f"[{branding}TTS]")
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# Auto-select model after 30 seconds
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selected_model = models[0] # Default to the first model (piper)
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try:
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user_choice = inputimeout(prompt=f"[{branding}TTS] \033[92mEnter your choice 1-4: \033[0m ", timeout=60)
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except TimeoutOccurred:
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user_choice = None
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if user_choice is None:
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print(f"[{branding}TTS]")
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print(f"[{branding}TTS] No input received. Proceeding with the default model (piper).")
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elif user_choice.lower() == 'own' or (user_choice.isdigit() and int(user_choice) == len(models) + 1):
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print(f"[{branding}TTS]")
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print(f"[{branding}TTS] If you have your own XTTS models, please move them into the")
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print(f"[{branding}TTS] \033[93m/models/xtts/\033[0m folder")
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print(f"[{branding}TTS]")
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os.makedirs('models/piper', exist_ok=True)
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os.makedirs('models/vits', exist_ok=True)
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os.makedirs('models/xtts/', exist_ok=True)
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update_tts_engines('piper')
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set_firstrun_model_false()
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warning_message()
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exit()
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if user_choice is not None and user_choice.isdigit() and 1 <= int(user_choice) <= len(models):
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selected_model = models[int(user_choice) - 1]
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warning_message()
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if user_choice is None or user_choice.lower() != 'own':
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if selected_model['name'] == 'piper':
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setup_piper()
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update_tts_engines('piper')
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elif selected_model['name'] == 'vits':
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setup_vits()
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update_tts_engines('vits')
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elif selected_model['name'] == 'xtts':
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setup_xtts()
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update_tts_engines('xtts')
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print(f"[{branding}TTS] {selected_model['name']} model downloaded and configuration updated successfully.")
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# Set firstrun_model to false
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set_firstrun_model_false()
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warning_message()
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exit()
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else:
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exit()
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import json
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import os
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import shutil
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import sys
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import time
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import zipfile
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import requests
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from tqdm import tqdm
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from inputimeout import inputimeout, TimeoutOccurred
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from pathlib import Path
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from typing import Optional, Dict, List, Any
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# Setting the module search path:
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sys.path.insert(0, str(Path(__file__).parent.parent.parent.resolve()))
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from config import AlltalkTTSEnginesConfig, AlltalkConfig
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this_dir = Path(__file__).parent.resolve().parent.resolve().parent.resolve()
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def is_running_in_colab() -> bool:
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"""Check if the script is running in Google Colab."""
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try:
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import google.colab
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return True
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except ImportError:
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return False
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def is_running_in_docker() -> bool:
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"""Check if the script is running in a Docker container."""
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return os.path.exists('/.dockerenv') or (
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os.path.exists('/proc/self/cgroup') and
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any('docker' in line for line in open('/proc/self/cgroup'))
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)
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def download_file(url: str, dest_path: str, timeout: int = 30) -> bool:
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"""
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Download a file from a URL with progress bar and error handling.
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Args:
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url: URL to download from
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dest_path: Where to save the file
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timeout: Connection timeout in seconds
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Returns:
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bool: True if download was successful
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"""
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progress_bar = None
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try:
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response = requests.get(url, stream=True, timeout=timeout)
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response.raise_for_status()
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total_size = int(response.headers.get('content-length', 0))
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block_size = 1024
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progress_bar = tqdm(total=total_size, unit='iB', unit_scale=True,
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desc=f"Downloading {Path(dest_path).name}")
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Path(dest_path).parent.mkdir(parents=True, exist_ok=True)
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with open(dest_path, 'wb') as file:
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for data in response.iter_content(block_size):
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if data:
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file.write(data)
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progress_bar.update(len(data))
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if progress_bar.n != total_size and total_size > 0:
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raise requests.exceptions.RequestException(
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f"Incomplete download: {progress_bar.n}/{total_size} bytes"
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)
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return True
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except Exception as e:
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print(f"Error downloading {url}: {str(e)}")
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if Path(dest_path).exists():
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Path(dest_path).unlink()
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return False
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finally:
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if progress_bar:
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progress_bar.close()
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def setup_model(model_name: str) -> bool:
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"""
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Set up a specific TTS model.
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Args:
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model_name: Name of the model to setup ('piper', 'vits', or 'xtts')
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Returns:
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bool: True if setup was successful
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"""
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try:
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if model_name == "piper":
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os.makedirs(this_dir / 'models/piper', exist_ok=True)
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os.makedirs(this_dir / 'models/xtts', exist_ok=True)
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return all([
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download_file(
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"https://huggingface.co/rhasspy/piper-voices/resolve/v1.0.0/en/en_US/ljspeech/high/en_US-ljspeech-high.onnx?download=true",
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this_dir / "models/piper/en_US-ljspeech-high.onnx"
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),
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download_file(
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"https://huggingface.co/rhasspy/piper-voices/resolve/v1.0.0/en/en_US/ljspeech/high/en_US-ljspeech-high.onnx.json?download=true.json",
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this_dir / "models/piper/en_US-ljspeech-high.onnx.json"
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)
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])
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elif model_name == "vits":
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os.makedirs(this_dir / 'models/vits', exist_ok=True)
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os.makedirs(this_dir / 'models/xtts', exist_ok=True)
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zip_path = this_dir / 'models/vits/vits.zip'
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if not download_file(
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"https://coqui.gateway.scarf.sh/v0.6.1_models/tts_models--en--vctk--vits.zip",
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zip_path
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):
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return False
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try:
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with zipfile.ZipFile(zip_path, 'r') as zip_ref:
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zip_ref.extractall(this_dir / 'models/vits')
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os.remove(zip_path)
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return True
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except Exception as e:
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print(f"Error extracting VITS model: {str(e)}")
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return False
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elif model_name == "xtts":
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os.makedirs(this_dir / 'models/xtts/xttsv2_2.0.3', exist_ok=True)
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base_url = "https://huggingface.co/coqui/XTTS-v2/resolve/v2.0.3/"
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files = [
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"LICENSE.txt", "README.md", "config.json", "model.pth",
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"dvae.pth", "mel_stats.pth", "speakers_xtts.pth", "vocab.json"
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]
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return all(
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download_file(
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base_url + file + "?download=true",
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this_dir / f"models/xtts/xttsv2_2.0.3/{file}"
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) for file in files
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)
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return False
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except Exception as e:
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print(f"Error setting up {model_name}: {str(e)}")
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return False
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def update_tts_engines(engine: str) -> bool:
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"""Update TTS engine configuration with error handling."""
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try:
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AlltalkTTSEnginesConfig.get_instance().change_engine(engine).save()
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return True
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except Exception as e:
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print(f"Error updating TTS engine configuration: {str(e)}")
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return False
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def set_firstrun_model_false() -> bool:
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"""Set firstrun_model to false with verification."""
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try:
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# Get fresh config instance and update
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config = AlltalkConfig.get_instance()
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config.firstrun_model = False
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config.save()
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# Verify the save worked
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config_path = AlltalkConfig.default_config_path()
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with open(config_path, 'r') as f:
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saved_config = json.load(f)
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if saved_config.get('firstrun_model', True):
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print(f"Warning: Failed to save firstrun_model=False")
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# Try direct file write as fallback
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saved_config['firstrun_model'] = False
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with open(config_path, 'w') as f:
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json.dump(saved_config, f, indent=2)
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return True
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except Exception as e:
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print(f"Error saving firstrun configuration: {str(e)}")
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return False
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def warning_message(branding: str):
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"""Display warning messages about installation and compatibility."""
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print(f"[{branding}TTS]")
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print(f"[{branding}TTS] \033[93mIf you have UPGRADED from v1 ensure you have re-installed\033[0m")
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print(f"[{branding}TTS] \033[93mthe requirements. Otherwise you will get failures and errors!\033[0m")
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print(f"[{branding}TTS] \033[93mOn Linux ignore the \033[0m'sparse_attn requires a torch version' \033[93mand\033[0m")
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print(f"[{branding}TTS] \033[0m'using untested triton version' \033[93mmessages.\033[0m")
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print(f"[{branding}TTS]")
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def main():
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"""Main execution function."""
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try:
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# Load configuration
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with open(AlltalkConfig.default_config_path(), 'r') as file:
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config_json = json.load(file)
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branding = config_json['branding']
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# Handle version 1 config upgrade
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if "ip_address" in config_json:
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print(f"[{branding}TTS] Detected version 1 configuration file.")
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print(f"[{branding}TTS] Upgrading to version 2 configuration file...")
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backup_path = AlltalkConfig.default_config_path() + ".backup"
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shutil.copyfile(AlltalkConfig.default_config_path(), backup_path)
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new_config_template_path = this_dir / 'system/config/confignew.json'
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shutil.copyfile(new_config_template_path, AlltalkConfig.default_config_path())
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print(f"[{branding}TTS] Configuration file upgraded successfully.")
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config = AlltalkConfig.get_instance()
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branding = config.branding
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if not config.firstrun_model:
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return
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# Auto-select Piper for Colab/Docker
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if is_running_in_colab() or is_running_in_docker():
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print(f"[{branding}TTS] Detected Colab/Docker environment - automatically selecting Piper")
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if setup_model('piper'):
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update_tts_engines('piper')
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set_firstrun_model_false()
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warning_message(branding)
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return
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# Normal interactive setup
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models = [
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{"name": "piper", "model": "piper"},
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{"name": "vits", "model": "tts_models--en--vctk--vits"},
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{"name": "xtts", "model": "xttsv2_2.0.3"},
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]
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print(f"[{branding}TTS]")
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print(f"[{branding}TTS] \033[92mThis is the first time startup. Please download a start TTS model.\033[0m")
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print(f"[{branding}TTS]")
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print(f"[{branding}TTS] \033[94mAvailable First Time Start-up models:\033[0m")
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print(f"[{branding}TTS]")
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for idx, model in enumerate(models):
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print(f"[{branding}TTS] \033[93m{idx + 1}. \033[94m{model['name']} - {model['model']}\033[0m")
|
||||
print(f"[{branding}TTS] \033[93m{len(models) + 1}.\033[94m I have my own models already\033[0m")
|
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print(f"[{branding}TTS]")
|
||||
print(f"[{branding}TTS] \033[94mIn \033[91m60 seconds\033[0m \033[94ma Piper model will be \033[91mdownloaded automatically.\033[0m")
|
||||
print(f"[{branding}TTS]")
|
||||
|
||||
try:
|
||||
user_choice = inputimeout(
|
||||
prompt=f"[{branding}TTS] \033[92mEnter your choice 1-4: \033[0m ",
|
||||
timeout=60
|
||||
)
|
||||
except TimeoutOccurred:
|
||||
user_choice = None
|
||||
|
||||
if user_choice is None:
|
||||
print(f"[{branding}TTS] No input received. Proceeding with the default model (piper).")
|
||||
selected_model = models[0]
|
||||
elif user_choice.lower() == 'own' or (user_choice.isdigit() and int(user_choice) == len(models) + 1):
|
||||
print(f"[{branding}TTS] If you have your own XTTS models, please move them into the")
|
||||
print(f"[{branding}TTS] \033[93m/models/xtts/\033[0m folder")
|
||||
|
||||
os.makedirs('models/piper', exist_ok=True)
|
||||
os.makedirs('models/vits', exist_ok=True)
|
||||
os.makedirs('models/xtts/', exist_ok=True)
|
||||
|
||||
update_tts_engines('piper')
|
||||
set_firstrun_model_false()
|
||||
warning_message(branding)
|
||||
return
|
||||
elif user_choice.isdigit() and 1 <= int(user_choice) <= len(models):
|
||||
selected_model = models[int(user_choice) - 1]
|
||||
warning_message(branding)
|
||||
else:
|
||||
print(f"[{branding}TTS] Invalid choice. Proceeding with the default model (piper).")
|
||||
selected_model = models[0]
|
||||
|
||||
if setup_model(selected_model['name']):
|
||||
update_tts_engines(selected_model['name'])
|
||||
set_firstrun_model_false()
|
||||
print(f"[{branding}TTS] {selected_model['name']} model downloaded and configuration updated successfully.")
|
||||
warning_message(branding)
|
||||
|
||||
except Exception as e:
|
||||
print(f"Unexpected error: {str(e)}")
|
||||
sys.exit(1)
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in new issue
Block a user