app.py

import os
import sys
import subprocess
import time  # Added for tracking duration

# 1. Clone the repo if it doesn't exist
if not os.path.exists("LuxTTS"):
    subprocess.run(["git", "clone", "https://github.com/ysharma3501/LuxTTS.git"])

# 2. Install requirements
subprocess.run([sys.executable, "-m", "pip", "install", "-r", "LuxTTS/requirements.txt"])

# 3. Add to path
sys.path.append(os.path.abspath("LuxTTS"))

import numpy as np
import gradio as gr
import torch
from zipvoice.luxvoice import LuxTTS

# Init Model
device = "cuda" if torch.cuda.is_available() else "cpu"
# Note: 2 threads on a 2-core CPU is the bottleneck
lux_tts = LuxTTS('YatharthS/LuxTTS', device=device, threads=2)

def infer(text, audio_prompt, rms, t_shift, num_steps, speed, return_smooth):
    if audio_prompt is None or not text:
        return None, "Please provide text and reference audio."
    
    start_time = time.time()
    
    # Encode reference
    encoded_prompt = lux_tts.encode_prompt(audio_prompt, rms=rms)
    
    # Generate speech
    final_wav = lux_tts.generate_speech(
        text, 
        encoded_prompt, 
        num_steps=int(num_steps), 
        t_shift=t_shift, 
        speed=speed, 
        return_smooth=return_smooth
    )
    
    end_time = time.time()
    duration = round(end_time - start_time, 2)
    
    final_wav = final_wav.cpu().squeeze(0).numpy()
    final_wav = (np.clip(final_wav, -1.0, 1.0) * 32767).astype(np.int16)
    
    stats_msg = f"✨ Generation complete in **{duration}s**."
    return (48000, final_wav), stats_msg

# Gradio UI
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("# 🎙️ LuxTTS Voice Cloning")
    
    # Info Panel
    gr.Markdown(
        """
        > **Note:** Processing may feel slow as this instance uses a **2-core CPU** (lower specs than most modern phones). 
        > 
        > **Tip:** If you notice words are being **cut off** at the end, try **lowering the speed** further.
        """
    )
    
    with gr.Row():
        with gr.Column():
            input_text = gr.Textbox(label="Text to Synthesize", value="Hey, what's up? I'm feeling really great!")
            input_audio = gr.Audio(label="Reference Audio (.wav)", type="filepath")
            
            with gr.Row():
                rms_val = gr.Number(value=0.01, label="RMS (Loudness)")
                t_shift_val = gr.Number(value=0.9, label="T-Shift")
                steps_val = gr.Slider(1, 10, value=4, step=1, label="Num Steps")
            
            with gr.Row():
                # Default speed set to 0.8
                speed_val = gr.Slider(0.5, 2.0, value=0.8, step=0.1, label="Speed (Lower = Longer/Clearer)")
                smooth_val = gr.Checkbox(label="Return Smooth", value=False)
            
            btn = gr.Button("Generate Speech", variant="primary")
            
        with gr.Column():
            audio_out = gr.Audio(label="Result")
            status_text = gr.Markdown("Ready to generate...")

    btn.click(
        fn=infer, 
        inputs=[input_text, input_audio, rms_val, t_shift_val, steps_val, speed_val, smooth_val], 
        outputs=[audio_out, status_text]
    )

demo.launch()