app.py

import os

os.environ["TORCHDYNAMO_DISABLE"] = "1"
os.environ["TORCH_COMPILE_DISABLE"] = "1"
os.environ["PYTORCH_DISABLE_CUDNN_BENCHMARK"] = "1"
os.environ["TOKENIZERS_PARALLELISM"] = "false"

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

# Global variables for model caching (like your old working version)
_tts_model = None
_speakers_dict = None
_model_initialized = False
_initialization_in_progress = False

def get_speakers_dict():
    """Get speakers dictionary using the correct import structure"""
    try:
        # Try new structure first
        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 from settings: {e}")
        # Fallback to old structure (like your working version)
        try:
            from maliba_ai.config.speakers import Adame, Moussa, Bourama, Modibo, Seydou
            return {
                "Adama": Adame,
                "Moussa": Moussa, 
                "Bourama": Bourama,
                "Modibo": Modibo,
                "Seydou": Seydou
            }
        except Exception as e2:
            logger.error(f"Failed to import speakers: {e2}")
            return {}

@spaces.GPU()
def initialize_model_once():
    """Initialize model exactly like your old working version"""
    global _tts_model, _speakers_dict, _model_initialized, _initialization_in_progress
    
    if _model_initialized:
        logger.info("Model already initialized, returning existing instance")
        return _tts_model, _speakers_dict
    
    if _initialization_in_progress:
        logger.info("Initialization already in progress, waiting...")
        for _ in range(50): 
            time.sleep(0.1)
            if _model_initialized:
                return _tts_model, _speakers_dict
    
    _initialization_in_progress = True
    
    try:
        logger.info("Initializing Bambara TTS model...")
        start_time = time.time()
        
        # Use the same import as your old working version
        from maliba_ai.tts.inference import BambaraTTSInference
        
        model = BambaraTTSInference()
        speakers = get_speakers_dict()
        
        if not speakers:
            raise ValueError("Failed to load speakers dictionary")
        
        _tts_model = model
        _speakers_dict = speakers
        _model_initialized = True
        
        elapsed = time.time() - start_time
        logger.info(f"Model initialized successfully in {elapsed:.2f} seconds!")
        
        return _tts_model, _speakers_dict
        
    except Exception as e:
        logger.error(f"Failed to initialize model: {e}")
        _initialization_in_progress = False
        raise e
    finally:
        _initialization_in_progress = False

def validate_inputs(text, temperature, top_k, top_p, max_tokens):
    """Same validation as your old version"""
    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"
    
    return True, ""

@spaces.GPU()
def generate_speech(text, speaker_name, use_advanced, temperature, top_k, top_p, max_tokens):
    """Generate speech - exactly like your old working version"""
    if not text.strip():
        return None, "Please enter some Bambara text."
    
    try:
        tts, speakers = initialize_model_once()
        
        if not tts or not speakers:
            return None, "❌ Model not properly initialized"
        
        if speaker_name not in speakers:
            available_speakers = list(speakers.keys())
            return None, f"❌ Speaker '{speaker_name}' not found. Available: {available_speakers}"
        
        speaker = speakers[speaker_name]
        logger.info(f"Using speaker: {speaker_name}")
        
        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.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:
            waveform = tts.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."
        
        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}")
        return None, f"❌ Error: {str(e)}"

# Use available speakers (try to get 10, fallback to 5)
def get_speaker_names():
    speakers = get_speakers_dict()
    if speakers:
        return list(speakers.keys())
    return ["Adama", "Moussa", "Bourama", "Modibo", "Seydou"]

SPEAKER_NAMES = get_speaker_names()

# Examples with variety of lengths and speakers matched to content
examples = [
    ["Aw ni ce", "Adama"],  # Natural conversational greeting
    ["Mali bɛna diya kɔsɛbɛ, ka a da a kan baara bɛ ka kɛ.", "Bakary" if "Bakary" in SPEAKER_NAMES else "Moussa"],  
    ["Ne bɛ se ka sɛbɛnni yɛlɛma ka kɛ kuma ye", "Moussa"],  
    ["I ka kɛnɛ wa?", "Ngolo" if "Ngolo" in SPEAKER_NAMES else "Modibo"],  
    ["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" if "Ibrahima" in SPEAKER_NAMES else "Seydou"],  
    ["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" if "Amara" in SPEAKER_NAMES else "Moussa"],  
    ["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" if "Amadou" in SPEAKER_NAMES else "Modibo"],
]

def build_interface():
    """Build the Gradio interface - simplified like your old working version"""
    
    with gr.Blocks(title="Bambara TTS - MALIBA-AI") as demo:
        gr.Markdown("""
        # 🎤 Bambara Text-to-Speech
        
        **Powered by MALIBA-AI**
        
        Convert Bambara text to speech using our state-of-the-art TTS model.
        
        **Bambara** is spoken by millions of people in Mali and West Africa.
        """)

        with gr.Row():
            with gr.Column(scale=2):
                text_input = gr.Textbox(
                    label="📝 Bambara Text",
                    placeholder="Type your Bambara text here...",
                    lines=3,
                    max_lines=10,
                    value="I ni ce"
                )
                
                speaker_dropdown = gr.Dropdown(
                    choices=SPEAKER_NAMES,
                    value="Bourama" if "Bourama" in SPEAKER_NAMES else SPEAKER_NAMES[0],
                    label="🗣️ Speaker Voice",
                    info=f"Choose from {len(SPEAKER_NAMES)} authentic voices"
                )
                
                generate_btn = gr.Button("🎵 Generate Speech", variant="primary", size="lg")
                
            with gr.Column(scale=1):
                use_advanced = gr.Checkbox(
                    label="⚙️ Use Advanced Settings", 
                    value=False,
                    info="Enable to 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"
                    )
                    
                    top_k = gr.Slider(
                        minimum=1, 
                        maximum=100, 
                        value=50, 
                        step=5,
                        label="Top-K"
                    )
                    
                    top_p = gr.Slider(
                        minimum=0.1, 
                        maximum=1.0, 
                        value=0.9, 
                        step=0.05,
                        label="Top-P"
                    )
                    
                    max_tokens = gr.Slider(
                        minimum=256, 
                        maximum=4096, 
                        value=2048, 
                        step=256,
                        label="Max Length"
                    )
        
        gr.Markdown("### 🔊 Generated Audio")
        
        audio_output = gr.Audio(
            label="Generated Speech",
            type="numpy",
            interactive=False
        )
            
        status_output = gr.Textbox(
            label="Status",
            interactive=False,
            show_label=False,
            container=False
        )
        
        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:**")
            
            for i, (text, speaker) in enumerate(examples):
                btn = gr.Button(f"{text[:30]}{'...' if len(text) > 30 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("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**: Model loads once and stays in memory
            - **📱 Usage**: Educational, accessibility, and cultural preservation
            
            ### 🎭 Available Speakers:
            {', '.join(SPEAKER_NAMES)}
            
            **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 🇲🇱
            """)
        
        def toggle_advanced(use_adv):
            return gr.Group(visible=use_adv)
        
        use_advanced.change(
            fn=toggle_advanced,
            inputs=[use_advanced],
            outputs=[advanced_group]
        )
        
        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
        )
        
        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 Bambara TTS Gradio interface.")
    
    # DO NOT preload - let it initialize on first request only (like your working version)
    interface = build_interface()
    interface.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=False
    )
    
    logger.info("Gradio interface launched successfully.")

if __name__ == "__main__":
    main()