lib/tools/model_fetcher.py

import os
import requests
from tqdm import tqdm
import subprocess
import shutil
import platform
import logging
logger = logging.getLogger(__name__)

URL_BASE = "https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main"
models_download = [
    ("pretrained/", [
        "D32k.pth", "D40k.pth", "D48k.pth",
        "G32k.pth", "G40k.pth", "G48k.pth",
        "f0D32k.pth", "f0D40k.pth", "f0D48k.pth",
        "f0G32k.pth", "f0G40k.pth", "f0G48k.pth",
    ]),
    ("pretrained_v2/", [
        "D32k.pth", "D40k.pth", "D48k.pth",
        "G32k.pth", "G40k.pth", "G48k.pth",
        "f0D32k.pth", "f0D40k.pth", "f0D48k.pth",
        "f0G32k.pth", "f0G40k.pth", "f0G48k.pth",
    ]),
    ("uvr5_weights/", [
        "HP2_all_vocals.pth", "HP3_all_vocals.pth",
        "HP5_only_main_vocal.pth", "VR-DeEchoAggressive.pth",
        "VR-DeEchoDeReverb.pth", "VR-DeEchoNormal.pth",
    ]),
    ("", ["ffmpeg.exe", "ffprobe.exe"]),  # ffmpeg and ffprobe go to the main folder
]

# List of individual files with their respective local and remote paths
individual_files = [
    ("hubert_base.pt", "assets/hubert/"),
    ("rmvpe.pt", "assets/rmvpe/"),
    ("rmvpe.onnx", "assets/rmvpe/"),
]

# Create a dictionary to map remote folders to local folders
folder_mapping = {
    "pretrained/": "assets/pretrained/",
    "pretrained_v2/": "assets/pretrained_v2/",
    "uvr5_weights/": "assets/uvr5_weights/",
    "": "",  # Default folder for files without a remote folder
}

# Function to download a file with tqdm progress bar
def download_file_with_progress(url, destination_path):
    response = requests.get(url, stream=True)
    total_size = int(response.headers.get("content-length", 0))
    block_size = 1024  # 1 KB blocks

    with open(destination_path, 'wb') as file, tqdm(
            desc=os.path.basename(destination_path),
            total=total_size,
            unit='B',
            unit_scale=True,
            unit_divisor=1024,
    ) as bar:
        for data in response.iter_content(block_size):
            file.write(data)
            bar.update(len(data))

# Download torch crepe if not exists
if not os.path.exists("torchcrepe"):
    os_name = platform.system()
    # Cloning the GitHub repository into the temporary directory
    print("Cloning the GitHub repository into the temporary directory...")
    subprocess.run(["git", "clone", "https://github.com/maxrmorrison/torchcrepe.git", "temp_torchcrepe"])

    # Copying the torchcrepe folder to a different location
    print("Copying the torchcrepe folder...")
    shutil.copytree("temp_torchcrepe/torchcrepe", "./torchcrepe")

    # Removing the temporary directory
    print("Removing the temporary directory...")
    print(os_name)
    if os_name == "Windows":
        subprocess.run("rmdir /s /q temp_torchcrepe", shell=True)
    if os_name == "Linux":
        shutil.rmtree("temp_torchcrepe")

# Download files that do not exist
for remote_folder, file_list in models_download:
    local_folder = folder_mapping.get(remote_folder, "")
    for file in file_list:
        destination_path = os.path.join(local_folder, file)
        url = f"{URL_BASE}/{remote_folder}{file}"
        if not os.path.exists(destination_path):
            print(f"Downloading {url} to {destination_path}...")
            download_file_with_progress(url, destination_path)  # Use the function tdqm

# Download individual files
for file_name, local_folder in individual_files:
    destination_path = os.path.join(local_folder, file_name)
    url = f"{URL_BASE}/{file_name}"
    if not os.path.exists(destination_path):
        print(f"Downloading {url} to {destination_path}...")
        download_file_with_progress(url, destination_path)  # Use the function tdqm
        
os.system('cls' if os.name == 'nt' else 'clear')
logger.info("Applio download suscessfully continuing...")