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"


def is_restricted_environment():
    return (
        os.getenv("ZERO_GPU") or 
        "zero" in str(os.getenv("SPACE_ID", "")).lower() or
        os.getenv("SPACES_ZERO_GPU") or
        "spaces" in str(os.getenv("HOSTNAME", "")).lower()
    )


if is_restricted_environment():
    os.environ["UNSLOTH_DISABLE"] = "1"
    os.environ["DISABLE_UNSLOTH"] = "1" 
    os.environ["UNSLOTH_IGNORE_ERRORS"] = "1"
    os.environ["UNSLOTH_NO_COMPILE"] = "1"
    print("🚀 ZeroGPU detected - Unsloth optimizations disabled for compatibility")
else:
    print("🔧 Local environment detected - Unsloth optimizations enabled")

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 using the correct SDK structure"""
    try:
        from maliba_ai.config.settings import Speakers
        speakers_dict = {
            "Adama": Speakers.Adama,
            "Moussa": Speakers.Moussa,
            "Bourama": Speakers.Bourama,
            "Modibo": Speakers.Modibo,
            "Seydou": Speakers.Seydou,
            "Amadou": Speakers.Amadou,
            "Bakary": Speakers.Bakary,
            "Ngolo": Speakers.Ngolo,
            "Amara": Speakers.Amara,
            "Ibrahima": Speakers.Ibrahima
        }
        
        logger.info(f"🎤 Successfully loaded {len(speakers_dict)} speakers: {list(speakers_dict.keys())}")
        return speakers_dict
        
    except Exception as e:
        logger.error(f"❌ Failed to import Speakers class: {e}")
        return {}

@spaces.GPU()
def initialize_model_once():
    """Initialize model with retry logic for Unsloth failures"""
    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
    
    max_retries = 2
    retry_delay = 5  # seconds
    
    try:
        logger.info("Initializing Bambara TTS model...")
        start_time = time.time()
        
        from maliba_ai.tts.inference import BambaraTTSInference
        
        for attempt in range(max_retries):
            try:
                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:
                if "unsloth_compiled_module_qwen2" in str(e) and attempt < max_retries - 1:
                    logger.warning(f"Unsloth compilation failed, retrying in {retry_delay} seconds... (attempt {attempt + 1}/{max_retries})")
                    time.sleep(retry_delay)
                else:
                    raise e
                    
    except Exception as e:
        logger.error(f"Failed to initialize model after {max_retries} attempts: {e}")
        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."
        
        if isinstance(waveform, torch.Tensor):
            waveform = waveform.cpu().numpy()
        
        if waveform.dtype == np.float32:
            # Normalize to [-1, 1] range if needed
            if np.max(np.abs(waveform)) > 1.0:
                waveform = waveform / np.max(np.abs(waveform))
            # Keep as float32 but ensure proper range for Gradio
            waveform = np.clip(waveform, -1.0, 1.0)
        
        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)}"


def get_speaker_names():
    speakers = get_speakers_dict()
    if speakers:
        speaker_list = list(speakers.keys())

        preferred_order = ["Bourama", "Adama", "Moussa", "Modibo", "Seydou", 
                          "Amadou", "Bakary", "Ngolo", "Ibrahima", "Amara"]
        
        ordered_speakers = []
        for speaker in preferred_order:
            if speaker in speaker_list:
                ordered_speakers.append(speaker)
        
        for speaker in speaker_list:
            if speaker not in ordered_speakers:
                ordered_speakers.append(speaker)
                
        logger.info(f"Available speakers: {ordered_speakers}")
        return ordered_speakers
    else:

        logger.warning("No speakers loaded, using fallback list")
        return ["Bourama", "Adama", "Moussa", "Modibo", "Seydou"]

SPEAKER_NAMES = get_speaker_names()


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"],  
    ["To tɔ nantan ni lafiya, o ka fisa ni so fa dumuniba kɛlɛma ye.", "Amadou"],  
    ["Mali ye jamana ɲuman ye!", "Bakary"],  
    ["An ka ɲɔgɔn dɛmɛ ka baara kɛ ɲɔgɔn fɛ", "Ngolo"],  
    ["Hakili to yɔrɔ min na, sabali bɛ yen", "Ibrahima"],  
    ["Dɔnko ɲuman ye, a bɛ dɔn mɔgɔ kɔnɔ", "Amara"],  
]

def get_safe_examples():
    """Get examples with speaker fallbacks for missing speakers"""
    safe_examples = []
    
    fallback_speakers = {
        "Amadou": "Adama",    
        "Bakary": "Modibo",   
        "Ngolo": "Adama",    
        "Ibrahima": "Seydou", 
        "Amara": "Moussa"     
    }
    
    for text, speaker in examples:
        if speaker in SPEAKER_NAMES:
            safe_examples.append([text, speaker])
        elif speaker in fallback_speakers and fallback_speakers[speaker] in SPEAKER_NAMES:
            safe_examples.append([text, fallback_speakers[speaker]])
        else:
            safe_examples.append([text, SPEAKER_NAMES[0]])
    
    return safe_examples

def build_interface():
    """Build the Gradio interface - simplified like your old working version"""
    
    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="Bourama" if "Bourama" in SPEAKER_NAMES else SPEAKER_NAMES[0],
                    label="🗣️ Speaker Voice",
                    info=f"Choose from {len(SPEAKER_NAMES)} authentic Bambara 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,
            format="wav"
        )
            
        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:**")
            
            # Use safe examples with fallbacks for missing speakers
            safe_examples = get_safe_examples()
            
            for i, (text, speaker) in enumerate(safe_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
            
            **⚠️ This is an experimental Bambara TTS model.**
            - **Languages**: Bambara (bm)  
            - **Speakers**: 10 different voice options
            - **Sample Rate**: 16kHz
            
            ### 🎭 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.")

    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()