import random import gradio as gr import numpy as np from elevenlabs import voices, generate, set_api_key, UnauthenticatedRateLimitError def generate_voice(text, voice_name, model_name, api_key): try: audio = generate(text, voice=voice_name, model=model_name, api_key=api_key) 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(audio, dtype=np.int16)) badges = """
[ ![GitHub](https://img.shields.io/badge/github-%23121011.svg?style=for-the-badge&logo=github&logoColor=white) ](https://github.com/elevenlabs-python) [ ![Twitter](https://img.shields.io/badge/Twitter-%231DA1F2.svg?style=for-the-badge&logo=Twitter&logoColor=white) ](https://twitter.com/elevenlabsio) [ ![](https://dcbadge.vercel.app/api/server/elevenlabs) ](https://discord.gg/elevenlabs)
""" 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("# ElevenLabs TTS") gr.Markdown(badges) gr.Markdown(description) input_text = gr.Textbox( label="Input Text", lines=2, value="Hi! I'm Eleven, the worlds most advanced TTS system.", elem_id="input_text" ) all_voices = voices() input_voice = gr.Dropdown( [ voice.name for voice in all_voices ], value=random.choice(all_voices).name, label="Voice", elem_id="input_voice" ) input_model = gr.Radio( ["eleven_monolingual_v1", "eleven_multilingual_v1"], label="Model", value="eleven_multilingual_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() block.launch()