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)


_tts_model = None
_speakers_dict = None
_model_initialized = False
_initialization_in_progress = False

def get_speakers_dict():
    """Get speakers dictionary - moved to function to avoid import issues"""
    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 e:
        logger.error(f"Failed to import speakers: {e}")
        return {}

@spaces.GPU()
def initialize_model_once():
    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()
        
        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):
    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):
    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)}"

SPEAKER_NAMES = ["Adama", "Moussa", "Bourama", "Modibo", "Seydou"]

examples = [
    ["Aw ni ce", "Adama"],
    ["Mali bɛna diya kɔsɛbɛ,  ka a da a kan baara bɛ ka kɛ.", "Moussa"],
    ["Ne bɛ se ka sɛbɛnni yɛlɛma ka kɛ kuma ye", "Bourama"],
    ["I ka kɛnɛ wa?", "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.", "Adama"],
    ["sigikafɔ kɔnɔ jamanaw ni ɲɔgɔn cɛ, olu ye a haminankow ye, wa o ko ninnu ka kan ka kɛ sariya ani tilennenya kɔnɔ.", "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.", "Moussa"],
    ["An dɔlakelen bɛ masike bilenman don ka tɔw gɛn.", "Bourama"],
    ["Aw ni ce. Seidu bɛ aw fo wa aw ka yafa a ma, ka da a kan tuma dɔw la kow ka can.", "Modibo"],
]

def build_interface():
    """Build the Gradio interface for Bambara TTS"""
    
    with gr.Blocks(title="Bambara TTS - EXPERIMENTAL") as demo:
        gr.Markdown("""
        # 🎤 Bambara Text-to-Speech ⚠️ EXPERIMENTAL
        
        **Powered by MALIBA-AI**
        
        Convert Bambara text to speech. This model is currently experimental.
        
        **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="Adama",
                    label="🗣️ Speaker Voice"
                )
                
                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("""
            **⚠️ This is an experimental Bambara TTS model.**
            - **Languages**: Bambara (bm)  
            - **Speakers**: 5 different voice options
            - **Sample Rate**: 16kHz
            
            **Model loads once on first request and stays in memory**
            """)
        
        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
    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()