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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, model_name, api_key):
try:
audio = generate(
text,
voice=voice_name,
model=model_name,
api_key=api_key if api_key != '' else None
)
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)
return (44100, np.frombuffer(pad_buffer(audio), dtype=np.int16))
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 Monolingual is designed to generate highly realistic voices in English, where Eleven Multilingual is a single model supporting multiple languages including English, German, Polish, Spanish, Italian, French, Portuguese, and Hindi.
"""
with gr.Blocks() as block:
gr.Markdown('[  ](https://elevenlabs.io)')
gr.Markdown(badges)
gr.Markdown(description)
input_text = gr.Textbox(
label="Input Text",
lines=2,
value="Hahaha OHH MY GOD! This is SOOO funny, I-I am Eleven and-and I am a text to speech system!!",
elem_id="input_text"
)
all_voices = voices()
input_voice = gr.Dropdown(
[ voice.name for voice in all_voices ],
value="Arnold",
label="Voice",
elem_id="input_voice"
)
input_model = gr.Radio(
["eleven_monolingual_v1", "eleven_multilingual_v1"],
label="Model",
value="eleven_monolingual_v1",
elem_id="input_model",
)
input_api_key = gr.Textbox(
label="API Key (Optional)",
lines=1,
elem_id="input_api_key"
)
run_button = gr.Button(
text="Generate Voice",
type="button"
)
out_audio = gr.Audio(
label="Generated Voice",
type="numpy",
elem_id="out_audio"
)
inputs = [input_text, input_voice, input_model, input_api_key]
outputs = [out_audio]
run_button.click(
fn=generate_voice,
inputs=inputs,
outputs=outputs,
queue=True
)
block.queue(max_size=99, concurrency_count=1).launch(debug=True) |