app.py

import os
import time
import glob
from datetime import datetime, timedelta

import numpy as np
import torch
from scipy.io.wavfile import write as write_wav

from transformers import AutoProcessor, AutoModelForTextToWaveform, BarkModel

import gradio as gr
from fastapi import FastAPI
from fastapi.staticfiles import StaticFiles
import uvicorn
from apscheduler.schedulers.background import BackgroundScheduler

OUTPUT_DIR = os.environ.get("OUTPUT_DIR", "/tmp/output")
os.makedirs(OUTPUT_DIR, exist_ok=True)
os.environ.update({
    "SUNO_OFFLOAD_CPU": "True",
    "SUNO_USE_SMALL_MODELS": "True"
})

device = "cuda" if torch.cuda.is_available() else "cpu"
processor = AutoProcessor.from_pretrained("suno/bark-small")
model = (BarkModel.from_pretrained("suno/bark-small", torch_dtype=torch.float16)
         .to(device)
         .to_bettertransformer())

def create_bark_audio(text, voice_preset, device):
    inputs = processor(text, voice_preset=voice_preset)
    inputs = {k: v.to(device) if hasattr(v, 'to') else v for k, v in inputs.items()}
    audio_array = model.generate(**inputs)
    return audio_array.cpu().numpy().squeeze(), model.generation_config.sample_rate

def save_audio(audio_array, sample_rate, prefix="audio"):
    audio_array = np.clip(audio_array.astype(np.float32), -1, 1)
    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
    filename = os.path.join(OUTPUT_DIR, f"{prefix}_{timestamp}.wav")
    write_wav(filename, sample_rate, audio_array)
    return filename

def generate_speech(text, voice_preset="v2/en_speaker_6"):
    device = "cuda" if torch.cuda.is_available() else "cpu"
    audio_array, sample_rate = create_bark_audio(text, voice_preset, device)
    return save_audio(audio_array, sample_rate)

def text_to_speech_with_url(text, voice):
    audio_file = generate_speech(text, VOICES[voice])
    filename = os.path.basename(audio_file)
    base_url = os.environ.get("PUBLIC_URL", "http://localhost:7860")
    return audio_file, f"{base_url}/generated/{filename}"

def cleanup_old_files():
    cutoff_time = datetime.now() - timedelta(hours=24)
    for file in glob.glob(os.path.join(OUTPUT_DIR, "audio_*.wav")):
        if datetime.fromtimestamp(os.path.getmtime(file)) < cutoff_time:
            try:
                os.remove(file)
            except Exception as e:
                print(f"Error removing file {file}: {e}")

VOICES = {
    'Speaker 0 (EN)':'v2/en_speaker_0',
    'Speaker 1 (EN)':'v2/en_speaker_1',
    'Speaker 2 (EN)':'v2/en_speaker_2',
    'Speaker 3 (EN)':'v2/en_speaker_3',
    'Speaker 4 (EN)':'v2/en_speaker_4',
    'Speaker 5 (EN)':'v2/en_speaker_5',
    'Speaker 6 (EN)':'v2/en_speaker_6',
    'Speaker 7 (EN)':'v2/en_speaker_7',
    'Speaker 8 (EN)':'v2/en_speaker_8',
    'Speaker 9 (EN)':'v2/en_speaker_9',
    'Speaker 0 (ZH)':'v2/zh_speaker_0',
    'Speaker 1 (ZH)':'v2/zh_speaker_1',
    'Speaker 2 (ZH)':'v2/zh_speaker_2',
    'Speaker 3 (ZH)':'v2/zh_speaker_3',
    'Speaker 4 (ZH)':'v2/zh_speaker_4',
    'Speaker 5 (ZH)':'v2/zh_speaker_5',
    'Speaker 6 (ZH)':'v2/zh_speaker_6',
    'Speaker 7 (ZH)':'v2/zh_speaker_7',
    'Speaker 8 (ZH)':'v2/zh_speaker_8',
    'Speaker 9 (ZH)':'v2/zh_speaker_9',
    'Speaker 0 (FR)':'v2/fr_speaker_0',
    'Speaker 1 (FR)':'v2/fr_speaker_1',
    'Speaker 2 (FR)':'v2/fr_speaker_2',
    'Speaker 3 (FR)':'v2/fr_speaker_3',
    'Speaker 4 (FR)':'v2/fr_speaker_4',
    'Speaker 5 (FR)':'v2/fr_speaker_5',
    'Speaker 6 (FR)':'v2/fr_speaker_6',
    'Speaker 7 (FR)':'v2/fr_speaker_7',
    'Speaker 8 (FR)':'v2/fr_speaker_8',
    'Speaker 9 (FR)':'v2/fr_speaker_9',
    'Speaker 0 (DE)':'v2/de_speaker_0',
    'Speaker 1 (DE)':'v2/de_speaker_1',
    'Speaker 2 (DE)':'v2/de_speaker_2',
    'Speaker 3 (DE)':'v2/de_speaker_3',
    'Speaker 4 (DE)':'v2/de_speaker_4',
    'Speaker 5 (DE)':'v2/de_speaker_5',
    'Speaker 6 (DE)':'v2/de_speaker_6',
    'Speaker 7 (DE)':'v2/de_speaker_7',
    'Speaker 8 (DE)':'v2/de_speaker_8',
    'Speaker 9 (DE)':'v2/de_speaker_9',
    'Speaker 0 (HI)':'v2/hi_speaker_0',
    'Speaker 1 (HI)':'v2/hi_speaker_1',
    'Speaker 2 (HI)':'v2/hi_speaker_2',
    'Speaker 3 (HI)':'v2/hi_speaker_3',
    'Speaker 4 (HI)':'v2/hi_speaker_4',
    'Speaker 5 (HI)':'v2/hi_speaker_5',
    'Speaker 6 (HI)':'v2/hi_speaker_6',
    'Speaker 7 (HI)':'v2/hi_speaker_7',
    'Speaker 8 (HI)':'v2/hi_speaker_8',
    'Speaker 9 (HI)':'v2/hi_speaker_9',
    'Speaker 0 (IT)':'v2/it_speaker_0',
    'Speaker 1 (IT)':'v2/it_speaker_1',
    'Speaker 2 (IT)':'v2/it_speaker_2',
    'Speaker 3 (IT)':'v2/it_speaker_3',
    'Speaker 4 (IT)':'v2/it_speaker_4',
    'Speaker 5 (IT)':'v2/it_speaker_5',
    'Speaker 6 (IT)':'v2/it_speaker_6',
    'Speaker 7 (IT)':'v2/it_speaker_7',
    'Speaker 8 (IT)':'v2/it_speaker_8',
    'Speaker 9 (IT)':'v2/it_speaker_9',
    'Speaker 0 (JA)':'v2/ja_speaker_0',
    'Speaker 1 (JA)':'v2/ja_speaker_1',
    'Speaker 2 (JA)':'v2/ja_speaker_2',
    'Speaker 3 (JA)':'v2/ja_speaker_3',
    'Speaker 4 (JA)':'v2/ja_speaker_4',
    'Speaker 5 (JA)':'v2/ja_speaker_5',
    'Speaker 6 (JA)':'v2/ja_speaker_6',
    'Speaker 7 (JA)':'v2/ja_speaker_7',
    'Speaker 8 (JA)':'v2/ja_speaker_8',
    'Speaker 9 (JA)':'v2/ja_speaker_9',
    'Speaker 0 (KO)':'v2/ko_speaker_0',
    'Speaker 1 (KO)':'v2/ko_speaker_1',
    'Speaker 2 (KO)':'v2/ko_speaker_2',
    'Speaker 3 (KO)':'v2/ko_speaker_3',
    'Speaker 4 (KO)':'v2/ko_speaker_4',
    'Speaker 5 (KO)':'v2/ko_speaker_5',
    'Speaker 6 (KO)':'v2/ko_speaker_6',
    'Speaker 7 (KO)':'v2/ko_speaker_7',
    'Speaker 8 (KO)':'v2/ko_speaker_8',
    'Speaker 9 (KO)':'v2/ko_speaker_9',
    'Speaker 0 (PL)':'v2/pl_speaker_0',
    'Speaker 1 (PL)':'v2/pl_speaker_1',
    'Speaker 2 (PL)':'v2/pl_speaker_2',
    'Speaker 3 (PL)':'v2/pl_speaker_3',
    'Speaker 4 (PL)':'v2/pl_speaker_4',
    'Speaker 5 (PL)':'v2/pl_speaker_5',
    'Speaker 6 (PL)':'v2/pl_speaker_6',
    'Speaker 7 (PL)':'v2/pl_speaker_7',
    'Speaker 8 (PL)':'v2/pl_speaker_8',
    'Speaker 9 (PL)':'v2/pl_speaker_9',
    'Speaker 0 (PT)':'v2/pt_speaker_0',
    'Speaker 1 (PT)':'v2/pt_speaker_1',
    'Speaker 2 (PT)':'v2/pt_speaker_2',
    'Speaker 3 (PT)':'v2/pt_speaker_3',
    'Speaker 4 (PT)':'v2/pt_speaker_4',
    'Speaker 5 (PT)':'v2/pt_speaker_5',
    'Speaker 6 (PT)':'v2/pt_speaker_6',
    'Speaker 7 (PT)':'v2/pt_speaker_7',
    'Speaker 8 (PT)':'v2/pt_speaker_8',
    'Speaker 9 (PT)':'v2/pt_speaker_9',
    'Speaker 0 (RU)':'v2/ru_speaker_0',
    'Speaker 1 (RU)':'v2/ru_speaker_1',
    'Speaker 2 (RU)':'v2/ru_speaker_2',
    'Speaker 3 (RU)':'v2/ru_speaker_3',
    'Speaker 4 (RU)':'v2/ru_speaker_4',
    'Speaker 5 (RU)':'v2/ru_speaker_5',
    'Speaker 6 (RU)':'v2/ru_speaker_6',
    'Speaker 7 (RU)':'v2/ru_speaker_7',
    'Speaker 8 (RU)':'v2/ru_speaker_8',
    'Speaker 9 (RU)':'v2/ru_speaker_9',
    'Speaker 0 (ES)':'v2/es_speaker_0',
    'Speaker 1 (ES)':'v2/es_speaker_1',
    'Speaker 2 (ES)':'v2/es_speaker_2',
    'Speaker 3 (ES)':'v2/es_speaker_3',
    'Speaker 4 (ES)':'v2/es_speaker_4',
    'Speaker 5 (ES)':'v2/es_speaker_5',
    'Speaker 6 (ES)':'v2/es_speaker_6',
    'Speaker 7 (ES)':'v2/es_speaker_7',
    'Speaker 8 (ES)':'v2/es_speaker_8',
    'Speaker 9 (ES)':'v2/es_speaker_9',
    'Speaker 0 (TR)':'v2/tr_speaker_0',
    'Speaker 1 (TR)':'v2/tr_speaker_1',
    'Speaker 2 (TR)':'v2/tr_speaker_2',
    'Speaker 3 (TR)':'v2/tr_speaker_3',
    'Speaker 4 (TR)':'v2/tr_speaker_4',
    'Speaker 5 (TR)':'v2/tr_speaker_5',
    'Speaker 6 (TR)':'v2/tr_speaker_6',
    'Speaker 7 (TR)':'v2/tr_speaker_7',
    'Speaker 8 (TR)':'v2/tr_speaker_8',
    'Speaker 9 (TR)':'v2/tr_speaker_9',
}

CUSTOM_CSS = """
#component-16 { display: none !important; }
.gradio-container .main h1 { padding-top: 60px; position: relative; }
.gradio-container .main h1::before {
    content: '';
    position: absolute;
    top: 0;
    left: 50%;
    transform: translateX(-50%);
    width: 253px;
    height: 50px;
    background-image: url('public/AkashLogo.svg');
    background-repeat: no-repeat;
    background-position: center;
    background-size: contain;
}
"""

with gr.Blocks(css=CUSTOM_CSS) as gradio_audio:
    gr.Interface(
        fn=text_to_speech_with_url,
        inputs=[
            gr.Textbox(label="Text to audio", placeholder="Enter text here...", show_copy_button=False),
            gr.Dropdown(choices=list(VOICES.keys()), value="Speaker 0 (EN)", label="Voice")
        ],
        outputs=[
            gr.Audio(label="Generated Speech"),
            gr.Textbox(label="Public URL", interactive=False, show_copy_button=True)
        ],
        title="Audio Generator",
        description="""
        Transform text into natural-sounding speech using the Bark AI model. 
        Features support for multiple languages and voice styles.
        
        **How to use:**
        1. Enter your text in any supported language
        2. Select a voice preset
        3. Click submit to generate speech
        4. Get the public URL to share/download the generated audio (it will expire in 24 hours)
        """,
        article="""<div style="text-align: center">Powered by <a href="https://huggingface.co/suno/bark-small">Bark-small</a> model and <a href="https://akash.network">Akash Network</a>, created by <a href="https://github.com/alexx855">alexx855</a></div>""",
        examples=[
            ["Welcome to the news. Today's top story...", "Speaker 0 (EN)"],
            ["The quick brown fox jumps over the lazy dog.", "Speaker 1 (EN)"],
            ["你好，今天天气真不错。", "Speaker 0 (ZH)"],
            ["Bonjour, comment allez-vous aujourd'hui?", "Speaker 0 (FR)"],
            ["J'aime beaucoup voyager en France.", "Speaker 1 (FR)"],
            ["Guten Tag, wie geht es Ihnen?", "Speaker 0 (DE)"],
            ["Das Wetter ist heute sehr schön.", "Speaker 1 (DE)"],
            ["नमस्ते, आप कैसे हैं?", "Speaker 0 (HI)"],
            ["मौसम बहुत सुहावन�� है।", "Speaker 1 (HI)"],
            ["Buongiorno, come stai oggi?", "Speaker 0 (IT)"],
            ["Mi piace molto viaggiare in Italia.", "Speaker 1 (IT)"],
            ["こんにちは、お元気ですか？", "Speaker 0 (JA)"],
            ["今日はとても良い天気ですね。", "Speaker 1 (JA)"],
            ["안녕하세요, 오늘 기분이 어떠신가요?", "Speaker 0 (KO)"],
            ["날씨가 정말 좋네요.", "Speaker 1 (KO)"],
            ["Dzień dobry, jak się masz?", "Speaker 0 (PL)"],
            ["Dzisiaj jest bardzo ładna pogoda.", "Speaker 1 (PL)"],
            ["Olá, como está você hoje?", "Speaker 0 (PT)"],
            ["O tempo está muito bonito hoje.", "Speaker 1 (PT)"],
            ["Здравствуйте, как ваши дела?", "Speaker 0 (RU)"],
            ["Сегодня прекрасная погода.", "Speaker 1 (RU)"],
            ["Hola, ¿cómo estás hoy?", "Speaker 0 (ES)"],
            ["El tiempo está muy bonito hoy.", "Speaker 1 (ES)"],
            ["Merhaba, bugün nasılsınız?", "Speaker 0 (TR)"],
            ["Bugün hava çok güzel.", "Speaker 1 (TR)"]
        ]
    )

scheduler = BackgroundScheduler()
scheduler.add_job(cleanup_old_files, 'interval', hours=1)
scheduler.start()

if __name__ == "__main__":
    app = FastAPI()
    app.mount("/generated", StaticFiles(directory=OUTPUT_DIR), name="generated")
    app.mount("/public", StaticFiles(directory="public"), name="public")
    gradio_app = gr.mount_gradio_app(app, gradio_audio, path="/", favicon_path="public/favicon.ico")
    uvicorn.run(app, host="0.0.0.0", port=7860)