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import random
import gradio as gr
import numpy as np
from elevenlabs import voices, generate, set_api_key, UnauthenticatedRateLimitError
def pad_buffer(audio):
# Pad buffer to multiple of 2 bytes
buffer_size = len(audio)
element_size = np.dtype(np.int16).itemsize
if buffer_size % element_size != 0:
audio = audio + b'\0' * (element_size - (buffer_size % element_size))
return audio
def generate_voice(text, voice_name):
try:
audio = generate(
text[:250], # Limit to 250 characters
voice=voice_name,
model="eleven_multilingual_v2"
)
return (44100, np.frombuffer(pad_buffer(audio), dtype=np.int16))
except UnauthenticatedRateLimitError as e:
raise gr.Error("Thanks for trying out ElevenLabs TTS! You've reached the free tier limit. Please provide an API key to continue.")
except Exception as e:
raise gr.Error(e)
badges = """
<div style="display: flex">
<span style="margin-right: 5px">
[  ](https://github.com/elevenlabs/elevenlabs-python)
</span>
<span style="margin-right: 5px">
[  ](https://twitter.com/elevenlabsio)
</span>
<span>
[  ](https://discord.gg/elevenlabs)
</span>
</div>
"""
description = """
A demo of the world's most advanced TTS systems, made by [ElevenLabs](https://elevenlabs.io). Eleven Multilingual V2 is a single foundational model supporting 28 languages including: English, Chinese, Spanish, Hindi, Portuguese, French, German, Japanese, Arabic, Korean, Indonesian, Italian, Dutch, Turkish, Polish, Swedish, Filipino, Malay, Romanian, Ukrainian, Greek, Czech, Danish, Finnish, Bulgarian, Croatian, Slovak, and Tamil. Sign up on [ElevenLabs](https://elevenlabs.io) to get fast access, long-form generation, voice cloning, API keys, and more!
"""
with gr.Blocks() as block:
gr.Markdown('[  ](https://elevenlabs.io)')
gr.Markdown(badges)
gr.Markdown(description)
input_text = gr.Textbox(
label="Input Text (250 characters max)",
lines=2,
value="Hello! 你好! Hola! नमस्ते! Bonjour! こんにちは! مرحبا! 안녕하세요! Ciao! Cześć! Привіт! Γειά σας! Здравей! வணக்கம்!",
elem_id="input_text"
)
all_voices = voices()
input_voice = gr.Dropdown(
[ voice.name for voice in all_voices ],
value="Bella",
label="Voice",
elem_id="input_voice"
)
run_button = gr.Button(
text="Generate Voice",
type="button"
)
out_audio = gr.Audio(
label="Generated Voice",
type="numpy",
elem_id="out_audio",
format="mp3"
)
inputs = [input_text, input_voice]
outputs = [out_audio]
run_button.click(
fn=generate_voice,
inputs=inputs,
outputs=outputs,
queue=True
)
block.queue(concurrency_count=5).launch(debug=True) |