app.py

import gradio as gr
import torch
import numpy as np
from dia.model import Dia
import warnings

# Suppress warnings for cleaner output
warnings.filterwarnings("ignore", category=FutureWarning)
warnings.filterwarnings("ignore", category=UserWarning)

# Global model variable
model = None

def load_model_once():
    """Load the Dia model once and cache it globally"""
    global model
    if model is None:
        print("Loading Dia model... This may take a few minutes.")
        try:
            # Load model with correct parameters for Dia
            model = Dia.from_pretrained("nari-labs/Dia-1.6B", compute_dtype="float32")
            
            # Move model to GPU if available
            if torch.cuda.is_available():
                model = model.cuda()
                print(f"Model loaded on GPU: {torch.cuda.get_device_name()}")
            else:
                print("Model loaded on CPU")
                
            print("Model loaded successfully!")
            
        except Exception as e:
            print(f"Error loading model: {e}")
            raise e
            
    return model

def generate_audio(text, seed=42):
    """Generate audio from text input with error handling"""
    try:
        # Clear GPU cache before generation
        if torch.cuda.is_available():
            torch.cuda.empty_cache()
            
        current_model = load_model_once()
        
        # Validate input
        if not text or not text.strip():
            return None, "❌ Please enter some text"
            
        # Clean and format text
        text = text.strip()
        if not text.startswith('[S1]') and not text.startswith('[S2]'):
            text = '[S1] ' + text
            
        # Set seed for reproducibility
        if seed:
            torch.manual_seed(int(seed))
            if torch.cuda.is_available():
                torch.cuda.manual_seed(int(seed))
                
        print(f"Generating speech for: {text[:100]}...")
        
        # Generate audio - disable torch compile for stability
        with torch.no_grad():
            audio_output = current_model.generate(
                text,
                use_torch_compile=False,  # Disabled for T4 compatibility
                verbose=False
            )
        
        # Ensure audio_output is numpy array
        if isinstance(audio_output, torch.Tensor):
            audio_output = audio_output.cpu().numpy()
            
        # Normalize audio to prevent clipping
        if len(audio_output) > 0:
            max_val = np.max(np.abs(audio_output))
            if max_val > 1.0:
                audio_output = audio_output / max_val * 0.95
            
        print("✅ Audio generated successfully!")
        return (44100, audio_output), "✅ Audio generated successfully!"
        
    except torch.cuda.OutOfMemoryError:
        # Handle GPU memory issues
        if torch.cuda.is_available():
            torch.cuda.empty_cache()
        error_msg = "❌ GPU memory error. Try shorter text or restart the space."
        print(error_msg)
        return None, error_msg
        
    except Exception as e:
        error_msg = f"❌ Error: {str(e)}"
        print(error_msg)
        return None, error_msg

# Create the Gradio interface - simplified to avoid OAuth triggers
demo = gr.Blocks(title="Dia TTS Demo")

with demo:
    gr.HTML("""
    <div style="text-align: center; padding: 20px;">
        <h1>🎙️ Dia TTS - Ultra-Realistic Text-to-Speech</h1>
        <p style="font-size: 18px; color: #666;">
            Generate multi-speaker, emotion-aware dialogue using the Dia 1.6B model
        </p>
    </div>
    """)
    
    with gr.Row():
        with gr.Column():
            text_input = gr.Textbox(
                label="📝 Text to Speech",
                placeholder="[S1] Hello there! How are you today? [S2] I'm doing great, thanks for asking! (laughs)",
                lines=6,
                value="[S1] Welcome to the Dia TTS demo! [S2] This is amazing technology!",
                info="Use [S1] and [S2] for different speakers. Add emotions like (laughs), (sighs), etc."
            )
            
            seed_input = gr.Number(
                label="🎲 Random Seed",
                value=42,
                precision=0,
                info="Same seed = consistent voices"
            )
            
            generate_btn = gr.Button("🎵 Generate Speech", variant="primary")
            
        with gr.Column():
            audio_output = gr.Audio(
                label="🔊 Generated Audio",
                type="numpy"
            )
            
            status_text = gr.Textbox(
                label="📊 Status",
                interactive=False,
                lines=2
            )

    # Connect the button to the function
    generate_btn.click(
        fn=generate_audio,
        inputs=[text_input, seed_input],
        outputs=[audio_output, status_text]
    )
    
    # Add example buttons
    with gr.Row():
        example_btn1 = gr.Button("📻 Podcast", size="sm")
        example_btn2 = gr.Button("😄 Chat", size="sm")
        example_btn3 = gr.Button("🎭 Drama", size="sm")
    
    # Example button functions
    example_btn1.click(
        lambda: "[S1] Welcome to our podcast! [S2] Thanks for having me on the show!",
        outputs=text_input
    )
    
    example_btn2.click(
        lambda: "[S1] Did you see the game? [S2] Yes! (laughs) It was incredible!",
        outputs=text_input
    )
    
    example_btn3.click(
        lambda: "[S1] I can't believe you're leaving. (sighs) [S2] I know, it's hard. (sad)",
        outputs=text_input
    )
    
    # Usage instructions
    gr.HTML("""
    <div style="margin-top: 20px; padding: 15px; background: #f0f8ff; border-radius: 8px;">
        <h3>💡 Usage Tips:</h3>
        <ul>
            <li><strong>Speaker Tags:</strong> Use [S1] and [S2] to switch between speakers</li>
            <li><strong>Emotions:</strong> Add (laughs), (sighs), (excited), (whispers), (sad), etc.</li>
            <li><strong>Length:</strong> Keep text moderate length (5-20 seconds of speech works best)</li>
            <li><strong>Seeds:</strong> Use the same seed number for consistent voice characteristics</li>
        </ul>
        
        <p><strong>Supported Emotions:</strong> (laughs), (sighs), (gasps), (excited), (sad), (angry), 
        (surprised), (whispers), (shouts), (coughs), (clears throat), (sniffs), (chuckles), (groans)</p>
    </div>
    """)

# Launch with basic configuration
if __name__ == "__main__":
    demo.launch()