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Add Bark small audio generation (#610)
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alexx855 authored Dec 2, 2024
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1 change: 1 addition & 0 deletions README.md
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Expand Up @@ -53,6 +53,7 @@ Also, follow [@akashnet\_](https://twitter.com/akashnet_) to stay in the loop wi
- [Auto-GPT](auto-gpt)
- [BabyAGI](babyagi)
- [BabyAGI-UI](babyagi-ui)
- [Bark small](bark-small)
- [Botpress](botpress)
- [ChatChat](chatchat)
- [Daila](daila)
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25 changes: 25 additions & 0 deletions bark-small/Dockerfile
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FROM pytorch/pytorch:2.1.0-cuda12.1-cudnn8-runtime

ENV GRADIO_SERVER_PORT=7860
ENV GRADIO_SERVER_NAME="0.0.0.0"

# Create mount point and set permissions for persistent storage
RUN mkdir -p /mnt && \
chown -R 1000:1000 /mnt && \
chmod 755 /mnt
VOLUME /mnt

WORKDIR /opt/app

# Copy requirements first for better caching
COPY requirements.txt requirements.txt

RUN apt-get update && apt-get install -y git && \
pip install -r requirements.txt

# Copy application files
COPY app.py .
COPY public/ /opt/app/public/

# Run the Gradio app
CMD ["python", "app.py"]
48 changes: 48 additions & 0 deletions bark-small/README.md
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# Bark Text-to-Speech Akash App

[Bark small](https://github.com/suno-ai/bark) transformer-based text-to-audio model created by [Suno](https://suno.com/). Bark can generate highly realistic, multilingual speech as well as other audio - including music, background noise and simple sound effects.

## Quick Start

### Running Locally

1. Install dependencies:
```bash
pip install -r requirements.txt
```

2. Run the app:
```bash
python app.py
```

The app will be available at http://localhost:7860

### Running with Docker

1. Build the Docker image:
```bash
docker build -t audio-akash .
```

2. Run the container:

```bash
docker run --gpus all -p 7860:7860 audio-akash
```

Access the app at http://localhost:7860

## Features

- Multiple voice options including English and Spanish speakers
- Simple web interface
- Example prompts included

## Documentation

- [Bark small Hugging Face](https://huggingface.co/suno/bark-small)
- [Available Voices](https://suno-ai.notion.site/8b8e8749ed514b0cbf3f699013548683)
- [Akash Network](https://akash.network/docs)


276 changes: 276 additions & 0 deletions bark-small/app.py
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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", "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)
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