app.py

import io
import os
import tempfile
from typing import List

import TTS.api
import TTS.utils.manage as manage
import torch
from pydub import AudioSegment
import gradio as gr

import config

device = "cuda" if torch.cuda.is_available() else "cpu"

def ask_tos_patch(self, output_path):
    print("Automatically accepting the terms of service.")
    return True

manage.ModelManager.ask_tos = ask_tos_patch
tts = TTS.api.TTS()

models = {}
for id, model in config.models.items():
    tts.download_model_by_name(model)
    models[id] = TTS.api.TTS(model).to(device)


def synthesize_tts(
    text: str = 'Hello, World!',
    speaker_wavs: List[gr.File] = None,
    speaker_idx: str = 'Ana Florence',
    language: str = 'ja',
    temperature: float = 0.65,
    length_penalty: float = 1.0,
    repetition_penalty: float = 1.9,
    top_k: int = 50,
    top_p: float = 0.8,
    speed: float = 1.0,
    enable_text_splitting: bool = True,
):
    temp_files = []
    try:
        if speaker_wavs:
            for speaker_wav in speaker_wavs:
                with open(speaker_wav.name, "rb") as f:
                    speaker_wav_bytes = f.read()
                try:
                    audio = AudioSegment.from_file(io.BytesIO(speaker_wav_bytes))
                    wav_buffer = io.BytesIO()
                    audio.export(wav_buffer, format="wav")
                    wav_buffer.seek(0) 
                except Exception as e:
                    return f"Error processing audio file: {e}"

                temp_wav_file = tempfile.NamedTemporaryFile(suffix=".wav", delete=False)
                temp_wav_file.write(wav_buffer.read())
                temp_wav_file.close()
                temp_files.append(temp_wav_file.name)

        output_buffer = io.BytesIO()
        if temp_files:
            models['multi'].tts_to_file(
                text=text,
                speaker_wav=temp_files, 
                language=language,
                file_path=output_buffer, 
                temperature=temperature,
                length_penalty=length_penalty,
                repetition_penalty=repetition_penalty,
                top_k=top_k,
                top_p=top_p,
                speed=speed,
                enable_text_splitting=enable_text_splitting
            )
        else:
            models['multi'].tts_to_file(
                text=text,
                speaker=speaker_idx, 
                language=language,
                file_path=output_buffer, 
                temperature=temperature,
                length_penalty=length_penalty,
                repetition_penalty=repetition_penalty,
                top_k=top_k,
                top_p=top_p,
                speed=speed,
                enable_text_splitting=enable_text_splitting
            )
        
        output_buffer.seek(0)
        return output_buffer.read()

    finally:
        for temp_file in temp_files:
            if isinstance(temp_file, str) and os.path.exists(temp_file):
                os.remove(temp_file)

inputs = [
    gr.Textbox(value="Hello, World!", label="Text to Synthesize"),
    gr.File(file_types=["audio"], label="Speaker WAV files (optional)", file_count="multiple"),
    gr.Dropdown(
        choices=[
            "Claribel Dervla", "Daisy Studious", "Gracie Wise", "Tammie Ema", "Alison Dietlinde", "Ana Florence",
            "Annmarie Nele", "Asya Anara", "Brenda Stern", "Gitta Nikolina", "Henriette Usha", "Sofia Hellen",
            "Tammy Grit", "Tanja Adelina", "Vjollca Johnnie", "Andrew Chipper", "Badr Odhiambo", "Dionisio Schuyler",
            "Royston Min", "Viktor Eka", "Abrahan Mack", "Adde Michal", "Baldur Sanjin", "Craig Gutsy",
            "Damien Black", "Gilberto Mathias", "Ilkin Urbano", "Kazuhiko Atallah", "Ludvig Milivoj", "Suad Qasim",
            "Torcull Diarmuid", "Viktor Menelaos", "Zacharie Aimilios", "Nova Hogarth", "Maja Ruoho", "Uta Obando",
            "Lidiya Szekeres", "Chandra MacFarland", "Szofi Granger", "Camilla Holmström", "Lilya Stainthorpe",
            "Zofija Kendrick", "Narelle Moon", "Barbora MacLean", "Alexandra Hisakawa", "Alma María", "Rosemary Okafor",
            "Ige Behringer", "Filip Traverse", "Damjan Chapman", "Wulf Carlevaro", "Aaron Dreschner", "Kumar Dahl",
            "Eugenio Mataracı", "Ferran Simen", "Xavier Hayasaka", "Luis Moray", "Marcos Rudaski"
        ],
        value="Ana Florence", 
        label="Speaker Index"
    ),
    gr.Dropdown(
        choices=["en", "es", "fr", "de", "it", "pt", "pl", "tr", "ru", "nl", "cs", "ar", "zh", "ja", "hu", "ko"],
        value="en",
        label="Language"
    ),
    gr.Slider(0, 1, value=0.65, step=0.01, label="Temperature"),
    gr.Slider(0.5, 2, value=1.0, step=0.1, label="Length Penalty"),
    gr.Slider(1.0, 10.0, value=1.9, step=0.1, label="Repetition Penalty"),
    gr.Slider(1, 100, value=50, step=1, label="Top-K"),
    gr.Slider(0, 1, value=0.8, step=0.01, label="Top-P"),
    gr.Slider(0.5, 2, value=1.0, step=0.01, label="Speed"),
    gr.Checkbox(value=True, label="Enable Text Splitting")
]

outputs = gr.Audio(label="Generated Speech")

gr.Interface(
    fn=synthesize_tts, 
    inputs=inputs, 
    outputs=outputs, 
    title="Text-to-Speech Synthesis with Gradio"
).launch()