app.py

import os

# Set environment variables BEFORE any imports
os.environ["TORCHDYNAMO_DISABLE"] = "1"
os.environ["TORCH_COMPILE_DISABLE"] = "1"
os.environ["PYTORCH_DISABLE_CUDNN_BENCHMARK"] = "1"
os.environ["TOKENIZERS_PARALLELISM"] = "false"

# Set CUDA environment to help with unsloth GPU detection
os.environ["CUDA_VISIBLE_DEVICES"] = "0"  # Force GPU visibility
os.environ["FORCE_CUDA"] = "1"            # Force CUDA usage

import torch
import gradio as gr
import numpy as np
import spaces
import logging
from huggingface_hub import login
import time

torch._dynamo.config.disable = True
torch._dynamo.config.suppress_errors = True

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

hf_token = os.getenv("HF_TOKEN")
if hf_token:
    login(token=hf_token)

# Check GPU availability
if torch.cuda.is_available():
    device = "cuda"
    logger.info("Using CUDA for inference.")
elif torch.backends.mps.is_available():
    device = "mps"
    logger.info("Using MPS for inference.")
else:
    device = "cpu"
    logger.info("Using CPU for inference.")

def get_speakers_dict():
    """Get speakers dictionary using the new package structure"""
    try:
        from maliba_ai.config.settings import Speakers
        return {
            "Adama": Speakers.Adama,
            "Moussa": Speakers.Moussa, 
            "Bourama": Speakers.Bourama,
            "Modibo": Speakers.Modibo,
            "Seydou": Speakers.Seydou,
            "Amadou": Speakers.Amadou,
            "Bakary": Speakers.Bakary,
            "Ngolo": Speakers.Ngolo,
            "Ibrahima": Speakers.Ibrahima,
            "Amara": Speakers.Amara
        }
    except Exception as e:
        logger.error(f"Failed to import all speakers: {e}")
        # Fallback to core speakers only
        try:
            from maliba_ai.config.settings import Speakers
            return {
                "Adama": Speakers.Adama,
                "Moussa": Speakers.Moussa, 
                "Bourama": Speakers.Bourama,
                "Modibo": Speakers.Modibo,
                "Seydou": Speakers.Seydou
            }
        except:
            logger.error("Failed to import even core speakers")
            return {}

def initialize_tts_model():
    """Initialize TTS model globally - similar to ASR space pattern"""
    try:
        logger.info("Initializing Bambara TTS model globally...")
        start_time = time.time()
        
        # Import and initialize the TTS model
        from maliba_ai.tts import BambaraTTSInference
        
        # Initialize model 
        model = BambaraTTSInference()
        
        elapsed = time.time() - start_time
        logger.info(f"TTS Model initialized successfully in {elapsed:.2f} seconds!")
        
        return model
        
    except Exception as e:
        logger.error(f"Failed to initialize TTS model: {e}")
        logger.info("Model will be initialized on first request instead")
        return None

# Initialize speakers dictionary
speakers_dict = get_speakers_dict()
logger.info(f"Available speakers: {list(speakers_dict.keys())}")

# Try to initialize model globally (like ASR space)
# If it fails due to GPU detection, it will be None and we'll init on first request
tts_model = initialize_tts_model()

def validate_inputs(text, temperature, top_k, top_p, max_tokens):
    """Validate user inputs"""
    if not text or not text.strip():
        return False, "Please enter some Bambara text."
    
    if not (0.001 <= temperature <= 2.0):
        return False, "Temperature must be between 0.001 and 2.0"
    
    if not (1 <= top_k <= 100):
        return False, "Top-K must be between 1 and 100"
    
    if not (0.1 <= top_p <= 1.0):
        return False, "Top-P must be between 0.1 and 1.0"
    
    if len(text.strip()) > 1000:
        return False, "Text is too long. Please use shorter text (max 1000 characters)."
    
    return True, ""

@spaces.GPU()
def generate_speech(text, speaker_name, use_advanced, temperature, top_k, top_p, max_tokens):
    """Generate speech - with fallback initialization if global init failed"""
    global tts_model
    
    if not text.strip():
        return None, "Please enter some Bambara text."
    
    try:
        # If global initialization failed, try to initialize here with GPU decorator
        if tts_model is None:
            logger.info("Global model initialization failed, initializing with GPU decorator...")
            from maliba_ai.tts import BambaraTTSInference
            tts_model = BambaraTTSInference()
            logger.info("Model initialized successfully with GPU decorator!")
        
        if not speakers_dict:
            return None, "❌ Speakers not properly loaded"
        
        if speaker_name not in speakers_dict:
            available_speakers = list(speakers_dict.keys())
            return None, f"❌ Speaker '{speaker_name}' not found. Available: {available_speakers}"
        
        speaker = speakers_dict[speaker_name]
        logger.info(f"Generating speech with speaker: {speaker_name}")
        
        # Validate inputs if using advanced settings
        if use_advanced:
            is_valid, error_msg = validate_inputs(text, temperature, top_k, top_p, max_tokens)
            if not is_valid:
                return None, f"❌ {error_msg}"
            
            waveform = tts_model.generate_speech(
                text=text.strip(),
                speaker_id=speaker,
                temperature=temperature,
                top_k=int(top_k),
                top_p=top_p,
                max_new_audio_tokens=int(max_tokens)
            )
        else:
            # Use default settings
            waveform = tts_model.generate_speech(
                text=text.strip(),
                speaker_id=speaker
            )
        
        if waveform is None or waveform.size == 0:
            return None, "❌ Failed to generate audio. Please try again with different text."
        
        # Ensure waveform is in correct format
        if isinstance(waveform, torch.Tensor):
            waveform = waveform.cpu().numpy()
        
        # Normalize audio to prevent clipping
        if np.max(np.abs(waveform)) > 0:
            waveform = waveform / np.max(np.abs(waveform)) * 0.9
        
        sample_rate = 16000
        return (sample_rate, waveform), f"✅ Audio generated successfully for speaker {speaker_name}"
        
    except Exception as e:
        logger.error(f"Speech generation failed: {e}", exc_info=True)
        return None, f"❌ Error: {str(e)}"

# Get available speakers for dropdown
SPEAKER_NAMES = list(speakers_dict.keys()) if speakers_dict else ["Adama", "Moussa", "Bourama", "Modibo", "Seydou"]


examples = [
    ["Aw ni ce", "Adama"],  
    ["Mali bɛna diya kɔsɛbɛ, ka a da a kan baara bɛ ka kɛ.", "Bakary"],  
    ["Ne bɛ se ka sɛbɛnni yɛlɛma ka kɛ kuma ye", "Moussa"],  
    ["I ka kɛnɛ wa?", "Ngolo"],  
    ["Lakɔli karamɔgɔw tun tɛ ka se ka sɛbɛnni kɛ ka ɲɛ walanda kan wa denmisɛnw tun tɛ ka se ka o sɛbɛnni ninnu ye, kuma tɛ ka u kalan. Denmisɛnw kɛra kunfinw ye.", "Bourama"],  
    ["sigikafɔ kɔnɔ jamanaw ni ɲɔgɔn cɛ, olu ye a haminankow ye, wa o ko ninnu ka kan ka kɛ sariya ani tilennenya kɔnɔ.", "Ibrahima"],  
    ["Aw ni ce. Ne tɔgɔ ye Adama. Awɔ, ne ye maliden de ye. Aw Sanbɛ Sanbɛ. San min tɛ ɲinan ye, an bɛɛ ka jɛ ka o seli ɲɔgɔn fɛ, hɛɛrɛ ni lafiya la. Ala ka Mali suma. Ala ka Mali yiriwa. Ala ka Mali taa ɲɛ. Ala ka an ka seliw caya. Ala ka yafa an bɛɛ ma.", "Amara"],  
    ["An dɔlakelen bɛ masike bilenman don ka tɔw gɛn.", "Modibo"],  
    ["Aw ni ce. Seidu bɛ aw fo wa aw ka yafa a ma, ka da a kan tuma dɔw la kow ka can.", "Amadou"],  
    ["Bamanankan ye kan ɲuman ye", "Seydou"],  
]

def build_interface():
    """Build the Gradio interface for Bambara TTS"""
    
    with gr.Blocks(
        title="Bambara TTS - MALIBA-AI", 
        theme=gr.themes.Soft(),
        css="""
        .main-header { text-align: center; margin-bottom: 2rem; }
        .status-box { margin-top: 1rem; }
        """
    ) as demo:
        
        with gr.Row():
            gr.Markdown(f"""
            # 🎤 Bambara Text-to-Speech
            
            **Powered by MALIBA-AI** | *First Open-Source Bambara TTS*
            
            Convert Bambara text to natural-sounding speech using our state-of-the-art neural TTS system.
            
            **Bambara** is spoken by millions of people in Mali and West Africa 🌍
            
            **Status**: {'✅ Model loaded' if tts_model is not None else '⏳ Model will load on first request'}
            """, elem_classes=["main-header"])

        with gr.Row():
            with gr.Column(scale=2):
                text_input = gr.Textbox(
                    label="📝 Bambara Text",
                    placeholder="I ni ce... (Type your Bambara text here)",
                    lines=4,
                    max_lines=8,
                    value="I ni ce"
                )
                
                speaker_dropdown = gr.Dropdown(
                    choices=SPEAKER_NAMES,
                    value=SPEAKER_NAMES[0] if SPEAKER_NAMES else "Bourama",  # Default to most stable speaker
                    label="🗣️ Speaker Voice",
                    info=f"Choose from {len(SPEAKER_NAMES)} authentic voices (Bourama recommended for best quality)"
                )
                
                generate_btn = gr.Button(
                    "🎵 Generate Speech", 
                    variant="primary", 
                    size="lg"
                )
                
            with gr.Column(scale=1):
                use_advanced = gr.Checkbox(
                    label="⚙️ Advanced Settings", 
                    value=False,
                    info="Customize generation parameters"
                )
                
                with gr.Group(visible=False) as advanced_group:
                    gr.Markdown("**🔧 Advanced Parameters:**")
                    
                    temperature = gr.Slider(
                        minimum=0.1, 
                        maximum=2.0, 
                        value=0.8, 
                        step=0.1,
                        label="Temperature",
                        info="Higher = more varied speech"
                    )
                    
                    top_k = gr.Slider(
                        minimum=1, 
                        maximum=100, 
                        value=50, 
                        step=5,
                        label="Top-K",
                        info="Vocabulary selection size"
                    )
                    
                    top_p = gr.Slider(
                        minimum=0.1, 
                        maximum=1.0, 
                        value=0.9, 
                        step=0.05,
                        label="Top-P",
                        info="Nucleus sampling threshold"
                    )
                    
                    max_tokens = gr.Slider(
                        minimum=256, 
                        maximum=4096, 
                        value=2048, 
                        step=256,
                        label="Max Audio Length",
                        info="Maximum audio duration"
                    )
        
        gr.Markdown("### 🔊 Generated Audio")
        
        audio_output = gr.Audio(
            label="Generated Speech",
            type="numpy",
            interactive=False,
            show_download_button=True
        )
            
        status_output = gr.Textbox(
            label="Status",
            interactive=False,
            show_label=False,
            container=False,
            elem_classes=["status-box"]
        )
        
        with gr.Accordion("📚 Try These Examples", open=True):
            def load_example(text, speaker):
                return text, speaker, False, 0.8, 50, 0.9, 2048
            
            gr.Markdown("**Click any example below to try it:**")
            
            with gr.Row():
                for i, (text, speaker) in enumerate(examples[:5]):
                    btn = gr.Button(
                        f"🔹 {text[:25]}{'...' if len(text) > 25 else ''}", 
                        size="sm"
                    )
                    btn.click(
                        fn=lambda t=text, s=speaker: load_example(t, s),
                        outputs=[text_input, speaker_dropdown, use_advanced, temperature, top_k, top_p, max_tokens]
                    )
            
            with gr.Row():
                for i, (text, speaker) in enumerate(examples[5:]):
                    btn = gr.Button(
                        f"🔹 {text[:25]}{'...' if len(text) > 25 else ''}", 
                        size="sm"
                    )
                    btn.click(
                        fn=lambda t=text, s=speaker: load_example(t, s),
                        outputs=[text_input, speaker_dropdown, use_advanced, temperature, top_k, top_p, max_tokens]
                    )
        
        with gr.Accordion("ℹ️ About", open=False):
            gr.Markdown(f"""
            ## About MALIBA-AI Bambara TTS
            
            - **🎯 Purpose**: First open-source Text-to-Speech system for Bambara language
            - **🗣️ Speakers**: {len(SPEAKER_NAMES)} different authentic voices  
            - **🔊 Quality**: 16kHz neural speech synthesis
            - **⚡ Performance**: Optimized for real-time generation
            - **📱 Usage**: Educational, accessibility, and cultural preservation
            
            ### 🎭 Speaker Characteristics:
            
            - **Bourama**: Most stable and accurate (recommended)
            - **Adama**: Natural conversational tone
            - **Moussa**: Clear pronunciation for educational content
            - **Modibo**: Expressive delivery for storytelling
            - **Seydou**: Balanced characteristics for general use
            - **Amadou**: Warm and friendly voice
            - **Bakary**: Deep, authoritative tone
            - **Ngolo**: Youthful and energetic
            - **Ibrahima**: Calm and measured delivery
            - **Amara**: Melodic and smooth
            
            **Model Architecture**: Built on state-of-the-art neural TTS with Bambara-specific optimizations
            
            **License**: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)
            
            ---
            
            **MALIBA-AI Mission**: Ensuring no Malian is left behind by technological advances 🇲🇱
            """)
        
        # Event handlers
        def toggle_advanced(use_adv):
            return gr.Group(visible=use_adv)
        
        use_advanced.change(
            fn=toggle_advanced,
            inputs=[use_advanced],
            outputs=[advanced_group]
        )
        
        # Generate speech on button click
        generate_btn.click(
            fn=generate_speech,
            inputs=[text_input, speaker_dropdown, use_advanced, temperature, top_k, top_p, max_tokens],
            outputs=[audio_output, status_output],
            show_progress=True
        )
        
        # Generate speech on Enter key
        text_input.submit(
            fn=generate_speech,
            inputs=[text_input, speaker_dropdown, use_advanced, temperature, top_k, top_p, max_tokens],
            outputs=[audio_output, status_output],
            show_progress=True
        )
    
    return demo

def main():
    """Main function to launch the Gradio interface"""
    logger.info("Starting MALIBA-AI Bambara TTS Gradio interface...")
    
    # Build interface
    interface = build_interface()
    
    # Launch interface
    interface.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=False,
        show_error=True
    )
    
    logger.info("Gradio interface launched successfully!")

if __name__ == "__main__":
    main()