app.py

import gradio as gr
import torch
from TTS.api import TTS
import os
import tempfile
import soundfile as sf

# Set environment variable for Coqui TOS
os.environ["COQUI_TOS_AGREED"] = "1"

# Initialize device
device = "cuda" if torch.cuda.is_available() else "cpu"
print(f"Using device: {device}")

# Initialize TTS model
try:
    tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to(device)
    print("✅ XTTS v2 model loaded successfully!")
except Exception as e:
    print(f"❌ Error loading model: {e}")
    tts = None

def clone_voice(text, reference_audio):
    """
    Clone voice using XTTS v2 model
    """
    if not text or not text.strip():
        return None, "❌ Please enter some text to convert!"
    
    if not reference_audio:
        return None, "❌ Please upload a reference audio file!"
    
    if tts is None:
        return None, "❌ TTS model not loaded properly!"
    
    try:
        # Validate text length
        if len(text) > 500:
            return None, "❌ Text too long! Please keep it under 500 characters."
        
        # Create temporary output file
        with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp_file:
            output_path = tmp_file.name
        
        # Generate cloned voice
        print(f"🎤 Cloning voice for text: {text[:50]}...")
        tts.tts_to_file(
            text=text,
            speaker_wav=reference_audio,
            language="en",
            file_path=output_path
        )
        
        # Verify output file exists and has content
        if os.path.exists(output_path) and os.path.getsize(output_path) > 0:
            return output_path, f"✅ Voice cloning successful!\n🎵 Generated audio for: '{text[:100]}{'...' if len(text) > 100 else ''}'"
        else:
            return None, "❌ Failed to generate audio file!"
            
    except Exception as e:
        error_msg = str(e)
        print(f"❌ Voice cloning error: {error_msg}")
        
        if "CUDA" in error_msg:
            return None, "❌ GPU memory error! Try with shorter text or restart the space."
        elif "audio" in error_msg.lower():
            return None, "❌ Audio processing error! Please upload a clear WAV or MP3 file."
        else:
            return None, f"❌ Error: {error_msg}"

# Create Gradio interface
def create_interface():
    with gr.Blocks(
        title="🎭 Voice Cloning Studio",
        theme=gr.themes.Soft(primary_hue="blue", secondary_hue="green")
    ) as demo:
        
        # Header
        gr.HTML("""
        <div style="text-align: center; padding: 20px;">
            <h1 style="color: #2E86AB; margin-bottom: 10px;">🎭 AI Voice Cloning Studio</h1>
            <p style="color: #666; font-size: 18px;">Clone any voice with advanced AI technology</p>
        </div>
        """)
        
        with gr.Row():
            with gr.Column(scale=1):
                # Input section
                gr.HTML("<h3 style='color: #2E86AB;'>📤 Upload Reference Voice</h3>")
                reference_audio = gr.Audio(
                    label="Reference Audio (10+ seconds recommended)",
                    type="filepath",
                    sources=["upload"]
                )
                
                gr.HTML("<h3 style='color: #2E86AB;'>📝 Enter Text to Clone</h3>")
                text_input = gr.Textbox(
                    label="Text to Convert",
                    placeholder="Enter the text you want to speak in the cloned voice...",
                    lines=4,
                    max_lines=6
                )
                
                clone_button = gr.Button(
                    "🎤 Clone Voice",
                    variant="primary",
                    size="lg"
                )
            
            with gr.Column(scale=1):
                # Output section
                gr.HTML("<h3 style='color: #2E86AB;'>🎵 Cloned Voice Output</h3>")
                audio_output = gr.Audio(
                    label="Generated Audio",
                    type="filepath"
                )
                
                status_output = gr.Textbox(
                    label="Status",
                    lines=3,
                    interactive=False
                )
        
        # Examples section
        gr.HTML("<h3 style='color: #2E86AB;'>💡 Example Texts</h3>")
        examples = [
            "Hello, this is a demonstration of AI voice cloning technology.",
            "Welcome to the future of artificial intelligence and speech synthesis.",
            "This voice was generated using advanced machine learning models.",
            "Experience the power of AI-driven voice generation with natural speech patterns."
        ]
        
        gr.Examples(
            examples=examples,
            inputs=text_input,
            label="Click to try these examples:"
        )
        
        # How it works
        with gr.Accordion("🔍 How It Works", open=False):
            gr.Markdown("""
            ### The Technology
            1. **🎤 Voice Upload**: Upload 10+ seconds of clear speech
            2. **🧠 AI Analysis**: XTTS v2 model analyzes voice characteristics  
            3. **📝 Text Input**: Enter the text you want to convert
            4. **🎵 Voice Synthesis**: Generate speech that matches the uploaded voice
            
            ### Tips for Best Results
            - Use high-quality, clear audio recordings
            - Ensure 10+ seconds of continuous speech
            - Avoid background noise and music
            - Single speaker only in reference audio
            
            ### Supported Languages
            - English (primary)
            - Spanish, French, German, Italian, Portuguese
            - Chinese, Japanese, Korean
            """)
        
        # Event handlers
        clone_button.click(
            fn=clone_voice,
            inputs=[text_input, reference_audio],
            outputs=[audio_output, status_output],
            show_progress=True
        )
        
        # Auto-generate on Enter
        text_input.submit(
            fn=clone_voice,
            inputs=[text_input, reference_audio],
            outputs=[audio_output, status_output],
            show_progress=True
        )
    
    return demo

# Launch the app
if __name__ == "__main__":
    demo = create_interface()
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=False
    )