app.py

import asyncio
import edge_tts
ing import GradioComponent to match huggingface space conventions
import gradio as gr

# Fetch available voices once at startup
df_voices = asyncio.run(edge_tts.list_voices())
voice_names = [v["Name"] for v in df_voices]

async def generate_tts(text: str, voice: str, rate: int, pitch: int):
    # Edge TTS parameters expect strings
    rate_str = f"{rate}%"
    pitch_str = f"{pitch}Hz"
    communicate = edge_tts.Communicate(text, voice, rate=rate_str, pitch=pitch_str)
    # Stream audio to memory
    audio_chunks = []
    async for chunk in communicate.stream():
        audio_chunks.append(chunk)
    return b"".join(audio_chunks)

# Synchronous wrapper for Gradio
def tts(text, voice, rate, pitch):
    audio = asyncio.run(generate_tts(text, voice, rate, pitch))
    return ("output.mp3", audio)

# Gradio UI
def main():
    with gr.Blocks() as demo:
        gr.Markdown("## Edge TTS Text-to-Speech Converter")
        with gr.Row():
            text_input = gr.Textbox(label="Input Text", lines=4, placeholder="Enter text to convert...")
            voice_selector = gr.Dropdown(label="Voice Model", choices=voice_names, value=voice_names[0])
        with gr.Row():
            rate_slider = gr.Slider(label="Speaking Rate (%)", minimum=10, maximum=200, step=1, value=100)
            pitch_slider = gr.Slider(label="Pitch (Hz)", minimum=-20, maximum=20, step=1, value=0)
        output_audio = gr.Audio(label="Generated Audio", type="file")
        generate_btn = gr.Button("Convert to Speech")
        generate_btn.click(fn=tts,
                            inputs=[text_input, voice_selector, rate_slider, pitch_slider],
                            outputs=output_audio)
    return demo

if __name__ == "__main__":
    main().launch()