from transformers import pipeline import asyncio import edge_tts import tempfile

import gradio as gr import edge_tts import asyncio import tempfile import os import nest_asyncio

async def get_voices(): voices = await edge_tts.list_voices() return {f"{v['ShortName']} - {v['Locale']} ({v['Gender']})": v['ShortName'] for v in voices}

async def text_to_speech(text, voice, rate, pitch): if not text.strip(): return None, gr.Warning("Please enter text to convert.") if not voice: return None, gr.Warning("Please select a voice.")

voice_short_name = voice.split(" - ")[0]
rate_str = f"{rate:+d}%"
pitch_str = f"{pitch:+d}Hz"
communicate = edge_tts.Communicate(text, voice_short_name, rate=rate_str, pitch=pitch_str)
with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
    tmp_path = '/'+tmp_file.name
    await communicate.save(tmp_path)
return tmp_path, None

def tts_interface(text, voice, rate, pitch): audio, warning = asyncio.run(text_to_speech(text, voice, rate, pitch)) return audio, warning

async def create_app(): voices = await get_voices() app = gr.Interface( fn=tts_interface, inputs=[ gr.Textbox(label="Input Text", lines=5), gr.Dropdown(choices=[""] + list(voices.keys()), label="Select Voice", value=""), gr.Slider(minimum=-50, maximum=50, value=0, label="Speech Rate Adjustment (%)", step=1), gr.Slider(minimum=-20, maximum=20, value=0, label="Pitch Adjustment (Hz)", step=1) ], outputs=[ gr.Audio(label="Generated Audio", type="filepath"), gr.Markdown(label="Warning", visible=False) ], title="Edge TTS Text-to-Speech", ) return app

nest_asyncio.apply()

if name == "main": app = asyncio.run(create_app()) app.launch(debug=True, share=True)