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core/__init__.py

@@ -3,7 +3,6 @@ import subprocess
 import sys
 from functools import lru_cache
 
-from rvc.lib.tools.model_download import model_download_pipeline
 from rvc.lib.tools.prerequisites_download import prequisites_download_pipeline
 from tts_service.utils import cache_path
 from tts_service.voices import voice_manager
@@ -29,7 +28,7 @@ def run_tts_script(
     voice = voice_manager.voices[voice_name]
     format = "wav"
 
-    output_tts_path = cache_path(voice.tts, tts_text, extension=format)
+    output_tts_path = cache_path(voice.tts, "", tts_rate, tts_text, extension=format)
     if not os.path.exists(output_tts_path):
         command_tts = [
             *map(
@@ -47,7 +46,7 @@ def run_tts_script(
         ]
         subprocess.run(command_tts)
 
-    output_rvc_path = cache_path(voice.tts, voice.name, tts_text, extension=format)
+    output_rvc_path = cache_path(voice.tts, voice.name, tts_rate, tts_text, extension=format)
     if not os.path.exists(output_rvc_path):
         infer_pipeline = import_voice_converter()
         infer_pipeline.convert_audio(
@@ -93,12 +92,6 @@ def run_tts_script(
     return "Text synthesized successfully.", str(output_rvc_path)
 
 
-# Download
-def run_download_script(model_link: str):
-    model_download_pipeline(model_link)
-    return "Model downloaded successfully."
-
-
 # Prerequisites
 def run_prerequisites_script(
     pretraineds_v1_f0: bool,

rvc/lib/tools/model_download.py

@@ -1,18 +1,16 @@
 import os
 import re
-import six
 import sys
-import wget
-import shutil
-import zipfile
+from urllib.parse import parse_qs, unquote, urlencode, urlparse
+
 import requests
+import six
+import wget
 from bs4 import BeautifulSoup
-from urllib.parse import unquote, urlencode, parse_qs, urlparse
 
 now_dir = os.getcwd()
 sys.path.append(now_dir)
 
-from rvc.lib.utils import format_title
 from rvc.lib.tools import gdown
 
 
@@ -27,21 +25,6 @@ file_path = find_folder_parent(now_dir, "logs")
 zips_path = os.path.join(file_path, "zips")
 
 
-def search_pth_index(folder):
-    pth_paths = [
-        os.path.join(folder, file)
-        for file in os.listdir(folder)
-        if os.path.isfile(os.path.join(folder, file)) and file.endswith(".pth")
-    ]
-    index_paths = [
-        os.path.join(folder, file)
-        for file in os.listdir(folder)
-        if os.path.isfile(os.path.join(folder, file)) and file.endswith(".index")
-    ]
-
-    return pth_paths, index_paths
-
-
 def download_from_url(url):
     os.makedirs(zips_path, exist_ok=True)
     if url != "":
@@ -62,18 +45,11 @@ def download_from_url(url):
                         fuzzy=True,
                     )
                 except Exception as error:
-                    error_message = str(
-                        f"An error occurred downloading the file: {error}"
-                    )
-                    if (
-                        "Too many users have viewed or downloaded this file recently"
-                        in error_message
-                    ):
+                    error_message = str(f"An error occurred downloading the file: {error}")
+                    if "Too many users have viewed or downloaded this file recently" in error_message:
                         os.chdir(now_dir)
                         return "too much use"
-                    elif (
-                        "Cannot retrieve the public link of the file." in error_message
-                    ):
+                    elif "Cannot retrieve the public link of the file." in error_message:
                         os.chdir(now_dir)
                         return "private link"
                     else:
@@ -89,9 +65,7 @@ def download_from_url(url):
             download_response = requests.get(download_url)
 
             if download_response.status_code == 200:
-                filename = parse_qs(urlparse(unquote(download_url)).query).get(
-                    "filename", [""]
-                )[0]
+                filename = parse_qs(urlparse(unquote(download_url)).query).get("filename", [""])[0]
                 if filename:
                     os.chdir(zips_path)
                     with open(filename, "wb") as f:
@@ -107,11 +81,7 @@ def download_from_url(url):
                 print(file_id)
                 response = requests.get(f"https://pixeldrain.com/api/file/{file_id}")
                 if response.status_code == 200:
-                    file_name = (
-                        response.headers.get("Content-Disposition")
-                        .split("filename=")[-1]
-                        .strip('";')
-                    )
+                    file_name = response.headers.get("Content-Disposition").split("filename=")[-1].strip('";')
                     os.makedirs(zips_path, exist_ok=True)
                     with open(os.path.join(zips_path, file_name), "wb") as newfile:
                         newfile.write(response.content)
@@ -141,9 +111,7 @@ def download_from_url(url):
 
             response = requests.get(url, stream=True)
             if response.status_code == 200:
-                content_disposition = six.moves.urllib_parse.unquote(
-                    response.headers["Content-Disposition"]
-                )
+                content_disposition = six.moves.urllib_parse.unquote(response.headers["Content-Disposition"])
                 m = re.search(r'filename="([^"]+)"', content_disposition)
                 file_name = m.groups()[0]
                 file_name = file_name.replace(os.path.sep, "_")
@@ -157,15 +125,8 @@ def download_from_url(url):
                         file.write(data)
                         progress += len(data)
                         progress_percent = int((progress / total_size_in_bytes) * 100)
-                        num_dots = int(
-                            (progress / total_size_in_bytes) * progress_bar_length
-                        )
-                        progress_bar = (
-                            "["
-                            + "." * num_dots
-                            + " " * (progress_bar_length - num_dots)
-                            + "]"
-                        )
+                        num_dots = int((progress / total_size_in_bytes) * progress_bar_length)
+                        progress_bar = "[" + "." * num_dots + " " * (progress_bar_length - num_dots) + "]"
                         print(
                             f"{progress_percent}% {progress_bar} {progress}/{total_size_in_bytes}  ",
                             end="\r",
@@ -243,121 +204,3 @@ def download_from_url(url):
 
     os.chdir(now_dir)
     return None
-
-
-def extract_and_show_progress(zipfile_path, unzips_path):
-    try:
-        with zipfile.ZipFile(zipfile_path, "r") as zip_ref:
-            for file_info in zip_ref.infolist():
-                zip_ref.extract(file_info, unzips_path)
-        os.remove(zipfile_path)
-        return True
-    except Exception as error:
-        print(f"An error occurred extracting the zip file: {error}")
-        return False
-
-
-def model_download_pipeline(url: str):
-    try:
-        verify = download_from_url(url)
-        if verify == "downloaded":
-            extract_folder_path = ""
-            for filename in os.listdir(zips_path):
-                if filename.endswith(".zip"):
-                    zipfile_path = os.path.join(zips_path, filename)
-                    print("Proceeding with the extraction...")
-
-                    model_zip = os.path.basename(zipfile_path)
-                    model_name = format_title(model_zip.split(".zip")[0])
-                    extract_folder_path = os.path.join(
-                        "logs",
-                        os.path.normpath(model_name),
-                    )
-                    success = extract_and_show_progress(
-                        zipfile_path, extract_folder_path
-                    )
-
-                    macosx_path = os.path.join(extract_folder_path, "__MACOSX")
-                    if os.path.exists(macosx_path):
-                        shutil.rmtree(macosx_path)
-
-                    subfolders = [
-                        f
-                        for f in os.listdir(extract_folder_path)
-                        if os.path.isdir(os.path.join(extract_folder_path, f))
-                    ]
-                    if len(subfolders) == 1:
-                        subfolder_path = os.path.join(
-                            extract_folder_path, subfolders[0]
-                        )
-                        for item in os.listdir(subfolder_path):
-                            s = os.path.join(subfolder_path, item)
-                            d = os.path.join(extract_folder_path, item)
-                            shutil.move(s, d)
-                        os.rmdir(subfolder_path)
-
-                    for item in os.listdir(extract_folder_path):
-                        if ".pth" in item:
-                            file_name = item.split(".pth")[0]
-                            if file_name != model_name:
-                                os.rename(
-                                    os.path.join(extract_folder_path, item),
-                                    os.path.join(
-                                        extract_folder_path, model_name + ".pth"
-                                    ),
-                                )
-                        else:
-                            if "v2" not in item:
-                                if "_nprobe_1_" in item and "_v1" in item:
-                                    file_name = item.split("_nprobe_1_")[1].split(
-                                        "_v1"
-                                    )[0]
-                                    if file_name != model_name:
-                                        new_file_name = (
-                                            item.split("_nprobe_1_")[0]
-                                            + "_nprobe_1_"
-                                            + model_name
-                                            + "_v1"
-                                        )
-                                        os.rename(
-                                            os.path.join(extract_folder_path, item),
-                                            os.path.join(
-                                                extract_folder_path,
-                                                new_file_name + ".index",
-                                            ),
-                                        )
-                            else:
-                                if "_nprobe_1_" in item and "_v2" in item:
-                                    file_name = item.split("_nprobe_1_")[1].split(
-                                        "_v2"
-                                    )[0]
-                                    if file_name != model_name:
-                                        new_file_name = (
-                                            item.split("_nprobe_1_")[0]
-                                            + "_nprobe_1_"
-                                            + model_name
-                                            + "_v2"
-                                        )
-                                        os.rename(
-                                            os.path.join(extract_folder_path, item),
-                                            os.path.join(
-                                                extract_folder_path,
-                                                new_file_name + ".index",
-                                            ),
-                                        )
-
-                    if success:
-                        print(f"Model {model_name} downloaded!")
-                    else:
-                        print(f"Error downloading {model_name}")
-                        return "Error"
-            if extract_folder_path == "":
-                print("Zip file was not found.")
-                return "Error"
-            result = search_pth_index(extract_folder_path)
-            return result
-        else:
-            return "Error"
-    except Exception as error:
-        print(f"An unexpected error occurred: {error}")
-        return "Error"

rvc/lib/utils.py

@@ -1,15 +1,14 @@
-import os, sys
+import logging
+import os
+import sys
+import warnings
+
 import librosa
-import soundfile as sf
 import numpy as np
-import re
-import unicodedata
+import soundfile as sf
 import wget
 from torch import nn
-
-import logging
 from transformers import HubertModel
-import warnings
 
 # Remove this to see warnings about transformers models
 warnings.filterwarnings("ignore")
@@ -65,16 +64,6 @@ def load_audio_infer(
     return np.array(audio).flatten()
 
 
-def format_title(title):
-    formatted_title = (
-        unicodedata.normalize("NFKD", title).encode("ascii", "ignore").decode("utf-8")
-    )
-    formatted_title = re.sub(r"[\u2500-\u257F]+", "", formatted_title)
-    formatted_title = re.sub(r"[^\w\s.-]", "", formatted_title)
-    formatted_title = re.sub(r"\s+", "_", formatted_title)
-    return formatted_title
-
-
 def load_embedding(embedder_model, custom_embedder=None):
     embedder_root = os.path.join(now_dir, "rvc", "models", "embedders")
     embedding_list = {

tabs/download/download.py

@@ -1,22 +1,13 @@
 import os
-import sys
-import json
 import shutil
-import requests
+import sys
 import tempfile
-import gradio as gr
-import pandas as pd
-
-from concurrent.futures import ThreadPoolExecutor
-from tqdm import tqdm
 
+import requests
 
 now_dir = os.getcwd()
 sys.path.append(now_dir)
 
-from core import run_download_script
-from rvc.lib.utils import format_title
-
 from assets.i18n.i18n import I18nAuto
 
 i18n = I18nAuto()
@@ -27,107 +18,6 @@ if os.path.exists(gradio_temp_dir):
     shutil.rmtree(gradio_temp_dir)
 
 
-def save_drop_model(dropbox):
-    if "pth" not in dropbox and "index" not in dropbox:
-        raise gr.Error(
-            message="The file you dropped is not a valid model file. Please try again."
-        )
-    else:
-        file_name = format_title(os.path.basename(dropbox))
-        if ".pth" in dropbox:
-            model_name = format_title(file_name.split(".pth")[0])
-        else:
-            if "v2" not in dropbox:
-                model_name = format_title(
-                    file_name.split("_nprobe_1_")[1].split("_v1")[0]
-                )
-            else:
-                model_name = format_title(
-                    file_name.split("_nprobe_1_")[1].split("_v2")[0]
-                )
-        model_path = os.path.join(now_dir, "logs", model_name)
-        if not os.path.exists(model_path):
-            os.makedirs(model_path)
-        if os.path.exists(os.path.join(model_path, file_name)):
-            os.remove(os.path.join(model_path, file_name))
-        shutil.move(dropbox, os.path.join(model_path, file_name))
-        print(f"{file_name} saved in {model_path}")
-        gr.Info(f"{file_name} saved in {model_path}")
-    return None
-
-
-def search_models(name):
-    url = f"https://cjtfqzjfdimgpvpwhzlv.supabase.co/rest/v1/models?name=ilike.%25{name}%25&order=created_at.desc&limit=15"
-    headers = {
-        "apikey": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6ImNqdGZxempmZGltZ3B2cHdoemx2Iiwicm9sZSI6ImFub24iLCJpYXQiOjE3MjY5MjYxMzQsImV4cCI6MjA0MjUwMjEzNH0.OyDXlhvH6D-IsHiWhPAGUtsPGGUvWQynfxUeQwfYToE"
-    }
-    response = requests.get(url, headers=headers)
-    data = response.json()
-    if len(data) == 0:
-        gr.Info(i18n("We couldn't find models by that name."))
-        return None
-    else:
-        df = pd.DataFrame(data)[["name", "link", "epochs", "type"]]
-        df["link"] = df["link"].apply(
-            lambda x: f'<a href="{x}" target="_blank">{x}</a>'
-        )
-        return df
-
-
-json_url = "https://huggingface.co/IAHispano/Applio/raw/main/pretrains.json"
-
-
-def fetch_pretrained_data():
-    pretraineds_custom_path = os.path.join(
-        "rvc", "models", "pretraineds", "pretraineds_custom"
-    )
-    os.makedirs(pretraineds_custom_path, exist_ok=True)
-    try:
-        with open(
-            os.path.join(pretraineds_custom_path, json_url.split("/")[-1]), "r"
-        ) as f:
-            data = json.load(f)
-    except:
-        try:
-            response = requests.get(json_url)
-            response.raise_for_status()
-            data = response.json()
-            with open(
-                os.path.join(pretraineds_custom_path, json_url.split("/")[-1]),
-                "w",
-                encoding="utf-8",
-            ) as f:
-                json.dump(
-                    data,
-                    f,
-                    indent=2,
-                    separators=(",", ": "),
-                    ensure_ascii=False,
-                )
-        except:
-            data = {
-                "Titan": {
-                    "32k": {"D": "null", "G": "null"},
-                },
-            }
-    return data
-
-
-def get_pretrained_list():
-    data = fetch_pretrained_data()
-    return list(data.keys())
-
-
-def get_pretrained_sample_rates(model):
-    data = fetch_pretrained_data()
-    return list(data[model].keys())
-
-
-def get_file_size(url):
-    response = requests.head(url)
-    return int(response.headers.get("content-length", 0))
-
-
 def download_file(url, destination_path, progress_bar):
     os.makedirs(os.path.dirname(destination_path), exist_ok=True)
     response = requests.get(url, stream=True)
@@ -136,128 +26,3 @@ def download_file(url, destination_path, progress_bar):
         for data in response.iter_content(block_size):
             file.write(data)
             progress_bar.update(len(data))
-
-
-def download_pretrained_model(model, sample_rate):
-    data = fetch_pretrained_data()
-    paths = data[model][sample_rate]
-    pretraineds_custom_path = os.path.join(
-        "rvc", "models", "pretraineds", "pretraineds_custom"
-    )
-    os.makedirs(pretraineds_custom_path, exist_ok=True)
-
-    d_url = f"https://huggingface.co/{paths['D']}"
-    g_url = f"https://huggingface.co/{paths['G']}"
-
-    total_size = get_file_size(d_url) + get_file_size(g_url)
-
-    gr.Info("Downloading pretrained model...")
-
-    with tqdm(
-        total=total_size, unit="iB", unit_scale=True, desc="Downloading files"
-    ) as progress_bar:
-        with ThreadPoolExecutor(max_workers=2) as executor:
-            futures = [
-                executor.submit(
-                    download_file,
-                    d_url,
-                    os.path.join(pretraineds_custom_path, os.path.basename(paths["D"])),
-                    progress_bar,
-                ),
-                executor.submit(
-                    download_file,
-                    g_url,
-                    os.path.join(pretraineds_custom_path, os.path.basename(paths["G"])),
-                    progress_bar,
-                ),
-            ]
-            for future in futures:
-                future.result()
-
-    gr.Info("Pretrained model downloaded successfully!")
-    print("Pretrained model downloaded successfully!")
-
-
-def update_sample_rate_dropdown(model):
-    return {
-        "choices": get_pretrained_sample_rates(model),
-        "value": get_pretrained_sample_rates(model)[0],
-        "__type__": "update",
-    }
-
-
-def download_tab():
-    with gr.Column():
-        gr.Markdown(value=i18n("## Download Model"))
-        model_link = gr.Textbox(
-            label=i18n("Model Link"),
-            placeholder=i18n("Introduce the model link"),
-            interactive=True,
-        )
-        model_download_output_info = gr.Textbox(
-            label=i18n("Output Information"),
-            info=i18n("The output information will be displayed here."),
-            value="",
-            max_lines=8,
-            interactive=False,
-        )
-        model_download_button = gr.Button(i18n("Download Model"))
-        model_download_button.click(
-            fn=run_download_script,
-            inputs=[model_link],
-            outputs=[model_download_output_info],
-        )
-        gr.Markdown(value=i18n("## Drop files"))
-        dropbox = gr.File(
-            label=i18n(
-                "Drag your .pth file and .index file into this space. Drag one and then the other."
-            ),
-            type="filepath",
-        )
-
-        dropbox.upload(
-            fn=save_drop_model,
-            inputs=[dropbox],
-            outputs=[dropbox],
-        )
-        gr.Markdown(value=i18n("## Search Model"))
-        search_name = gr.Textbox(
-            label=i18n("Model Name"),
-            placeholder=i18n("Introduce the model name to search."),
-            interactive=True,
-        )
-        search_table = gr.Dataframe(datatype="markdown")
-        search = gr.Button(i18n("Search"))
-        search.click(
-            fn=search_models,
-            inputs=[search_name],
-            outputs=[search_table],
-        )
-        search_name.submit(search_models, [search_name], search_table)
-        gr.Markdown(value=i18n("## Download Pretrained Models"))
-        pretrained_model = gr.Dropdown(
-            label=i18n("Pretrained"),
-            info=i18n("Select the pretrained model you want to download."),
-            choices=get_pretrained_list(),
-            value="Titan",
-            interactive=True,
-        )
-        pretrained_sample_rate = gr.Dropdown(
-            label=i18n("Sampling Rate"),
-            info=i18n("And select the sampling rate."),
-            choices=get_pretrained_sample_rates(pretrained_model.value),
-            value="40k",
-            interactive=True,
-            allow_custom_value=True,
-        )
-        pretrained_model.change(
-            update_sample_rate_dropdown,
-            inputs=[pretrained_model],
-            outputs=[pretrained_sample_rate],
-        )
-        download_pretrained = gr.Button(i18n("Download"))
-        download_pretrained.click(
-            fn=download_pretrained_model,
-            inputs=[pretrained_model, pretrained_sample_rate],
-            outputs=[],
-        )

tabs/plugins/plugins_core.py

@@ -1,17 +1,16 @@
-import os, sys, shutil
 import json
-import gradio as gr
-import zipfile
+import os
 import subprocess
+import sys
 
 from assets.i18n.i18n import I18nAuto
+from tabs.settings.sections.restart import restart_applio
 
 i18n = I18nAuto()
 
 now_dir = os.getcwd()
 sys.path.append(now_dir)
 
-from tabs.settings.sections.restart import restart_applio
 
 plugins_path = os.path.join(now_dir, "tabs", "plugins", "installed")
 if not os.path.exists(plugins_path):
@@ -22,7 +21,7 @@ current_folders = os.listdir(plugins_path)
 
 def get_existing_folders():
     if os.path.exists(json_file_path):
-        with open(json_file_path, "r") as file:
+        with open(json_file_path) as file:
             config = json.load(file)
             return config["plugins"]
     else:
@@ -30,7 +29,7 @@ def get_existing_folders():
 
 
 def save_existing_folders(existing_folders):
-    with open(json_file_path, "r") as file:
+    with open(json_file_path) as file:
         config = json.load(file)
         config["plugins"] = existing_folders
     with open(json_file_path, "w") as file:

tts_service/app.py

@@ -7,7 +7,6 @@ import assets.installation_checker as installation_checker
 import assets.themes.loadThemes as loadThemes
 from assets.i18n.i18n import I18nAuto
 from core import run_prerequisites_script
-from tabs.download.download import download_tab
 from tabs.plugins import plugins_core
 from tabs.tts.tts import tts_tab
 from tts_service.utils import env_bool
@@ -44,18 +43,15 @@ installation_checker.check_installation()
 my_applio = loadThemes.load_theme() or "ParityError/Interstellar"
 
 # Define Gradio interface
-with gr.Blocks(theme=my_applio, title="Applio", css="footer{display:none !important}") as Applio:
+with gr.Blocks(theme=my_applio, title="TTS Playground", css="footer{display:none !important}") as app:
     gr.Markdown("# Text-to-Speech Playground")
     gr.Markdown(i18n("Select a voice model, enter text, and press 'Convert' to synthesize speech."))
     with gr.Tab(i18n("TTS")):
         tts_tab()
 
-    with gr.Tab(i18n("Download")):
-        download_tab()
-
 
 def launch_gradio():
-    Applio.launch(
+    app.queue(status_update_rate=1).launch(
         favicon_path="assets/ICON.ico",
         share="--share" in sys.argv,
         inbrowser="--open" in sys.argv,

tts_service/cli.py

@@ -22,9 +22,9 @@ def main() -> None:
 @click.option("--share", is_flag=True, help="Share the service")
 def serve(share: bool) -> None:
     """Start the TTS Service"""
-    from tts_service.app import Applio
+    from tts_service.app import app
 
-    Applio.launch(share=share)
+    app.launch(share=share)
 
 
 @main.group()

tts_service/whitelist.py

@@ -1,3 +1,4 @@
+Applio  # unused class (assets/themes/Applio.py:12)
 _.secondary_100  # unused attribute (assets/themes/Applio.py:44)
 _.secondary_200  # unused attribute (assets/themes/Applio.py:45)
 _.secondary_300  # unused attribute (assets/themes/Applio.py:46)
@@ -12,13 +13,10 @@ _.secondary_950  # unused attribute (assets/themes/Applio.py:54)
 __getattr__  # unused function (rvc/lib/predictors/FCPE.py:799)
 _.graph  # unused attribute (rvc/lib/zluda.py:33)
 _.enabled  # unused attribute (rvc/lib/zluda.py:40)
-rvc  # unused import (rvc/train/extract/extract.py:19)
 _.nprobe  # unused attribute (rvc/train/process/extract_index.py:76)
 rvc  # unused import (rvc/train/train.py:28)
-_.deterministic  # unused attribute (rvc/train/train.py:80)
-_.benchmark  # unused attribute (rvc/train/train.py:81)
-losses_disc_g  # unused variable (rvc/train/train.py:632)
-losses_disc_r  # unused variable (rvc/train/train.py:632)
-losses_gen  # unused variable (rvc/train/train.py:651)
-components  # unused variable (tabs/report/report.py:55)
-rvc  # unused import (tts_service/app.py:19)
+_.deterministic  # unused attribute (rvc/train/train.py:78)
+_.benchmark  # unused attribute (rvc/train/train.py:79)
+losses_disc_g  # unused variable (rvc/train/train.py:630)
+losses_disc_r  # unused variable (rvc/train/train.py:630)
+losses_gen  # unused variable (rvc/train/train.py:649)

web-root/index.html

@@ -0,0 +1,17 @@
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <meta name="description" content="Description of the page" />
+    <meta name="author" content="Author Name" />
+    <script
+      type="module"
+      src="https://gradio.s3-us-west-2.amazonaws.com/4.43.0/gradio.js"
+    ></script>
+    <title>TTS Playground</title>
+  </head>
+  <body style="background-color: black">
+    <gradio-app src="https://jlopez00-tts-service.hf.space"></gradio-app>
+  </body>
+</html>