app.py

"""
TTS Dataset Collection Tool with Font Support and Enhanced Error Handling
"""

import os
import json
import nltk
import gradio as gr
from datetime import datetime
from pathlib import Path
import shutil
import logging
from typing import Dict, List, Tuple, Optional
import traceback

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)

# Font configurations
FONT_STYLES = {
    "english_serif": {
        "name": "Times New Roman",
        "family": "serif",
        "css": "font-family: 'Times New Roman', serif;"
    },
    "english_sans": {
        "name": "Arial",
        "family": "sans-serif",
        "css": "font-family: Arial, sans-serif;"
    },
    "nastaliq": {
        "name": "Nastaliq",
        "family": "Jameel Noori Nastaleeq",
        "css": "font-family: 'Jameel Noori Nastaleeq', serif;"
    },
    "naskh": {
        "name": "Naskh",
        "family": "Traditional Arabic",
        "css": "font-family: 'Traditional Arabic', serif;"
    }
}

class TTSDatasetCollector:
    """Manages TTS dataset collection and organization with enhanced features"""
    
    def __init__(self):
        """Initialize the TTS Dataset Collector"""
        # Initialize NLTK
        self._initialize_nltk()
        
        # Set up paths and directories
        self.root_path = Path(os.path.dirname(os.path.abspath(__file__))) / "dataset"
        self.sentences: List[str] = []
        self.current_index: int = 0
        self.current_font: str = "english_serif"
        self.setup_directories()
        
        logger.info("TTS Dataset Collector initialized")
    
    def _initialize_nltk(self) -> None:
        """Initialize NLTK with error handling"""
        try:
            nltk.download('punkt', quiet=True)
            logger.info("NLTK punkt tokenizer downloaded successfully")
        except Exception as e:
            logger.error(f"Failed to download NLTK data: {str(e)}")
            logger.error(traceback.format_exc())
            raise RuntimeError("Failed to initialize NLTK. Please check your internet connection.")
    
    def setup_directories(self) -> None:
        """Create necessary directory structure with logging"""
        try:
            # Create main dataset directory
            self.root_path.mkdir(exist_ok=True)
            
            # Create subdirectories
            for subdir in ['audio', 'transcriptions', 'metadata', 'fonts']:
                (self.root_path / subdir).mkdir(exist_ok=True)
            
            # Initialize log file
            log_file = self.root_path / 'dataset_log.txt'
            if not log_file.exists():
                with open(log_file, 'w', encoding='utf-8') as f:
                    f.write(f"Dataset collection initialized on {datetime.now().isoformat()}\n")
            
            logger.info("Directory structure created successfully")
            
        except Exception as e:
            logger.error(f"Failed to create directory structure: {str(e)}")
            logger.error(traceback.format_exc())
            raise RuntimeError("Failed to initialize directory structure")
    
    def log_operation(self, message: str, level: str = "info") -> None:
        """Log operations with timestamp and level"""
        try:
            log_file = self.root_path / 'dataset_log.txt'
            timestamp = datetime.now().isoformat()
            
            with open(log_file, 'a', encoding='utf-8') as f:
                f.write(f"[{timestamp}] [{level.upper()}] {message}\n")
            
            if level.lower() == "error":
                logger.error(message)
            else:
                logger.info(message)
                
        except Exception as e:
            logger.error(f"Failed to log operation: {str(e)}")
    
    def load_text_file(self, file) -> Tuple[bool, str]:
        """Process and load text file with enhanced error handling"""
        if not file:
            return False, "No file provided"
        
        try:
            # Validate file extension
            if not file.name.endswith('.txt'):
                return False, "Only .txt files are supported"
            
            with open(file.name, 'r', encoding='utf-8') as f:
                text = f.read()
            
            # Validate text content
            if not text.strip():
                return False, "File is empty"
            
            # Tokenize sentences
            self.sentences = nltk.sent_tokenize(text)
            if not self.sentences:
                return False, "No valid sentences found in file"
            
            self.current_index = 0
            
            # Log success
            self.log_operation(
                f"Loaded text file: {file.name} with {len(self.sentences)} sentences"
            )
            
            return True, f"Successfully loaded {len(self.sentences)} sentences"
            
        except UnicodeDecodeError:
            error_msg = "File encoding error. Please ensure the file is UTF-8 encoded"
            self.log_operation(error_msg, "error")
            return False, error_msg
        except Exception as e:
            error_msg = f"Error loading file: {str(e)}"
            self.log_operation(error_msg, "error")
            logger.error(traceback.format_exc())
            return False, error_msg

    def get_styled_text(self, text: str) -> str:
        """Get text with current font styling"""
        font_css = FONT_STYLES[self.current_font]['css']
        return f"<div style='{font_css}'>{text}</div>"


    def generate_filenames(self, dataset_name: str, speaker_id: str) -> Tuple[str, str]:
        """Generate unique filenames for audio and text files"""
        timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
        sentence_id = f"{self.current_index+1:04d}"
        base_name = f"{dataset_name}_{speaker_id}_{sentence_id}_{timestamp}"
        return f"{base_name}.wav", f"{base_name}.txt"

    def set_font(self, font_style: str) -> Tuple[bool, str]:
        """Set the current font style"""
        if font_style not in FONT_STYLES:
            return False, f"Invalid font style. Available styles: {', '.join(FONT_STYLES.keys())}"
        self.current_font = font_style
        return True, f"Font style set to {font_style}"

    def save_recording(self, audio_file, speaker_id: str, dataset_name: str) -> Tuple[bool, str]:
        """Save recording with enhanced error handling and logging"""
        if not all([audio_file, speaker_id, dataset_name]):
            missing = []
            if not audio_file: missing.append("audio recording")
            if not speaker_id: missing.append("speaker ID")
            if not dataset_name: missing.append("dataset name")
            return False, f"Missing required information: {', '.join(missing)}"
        
        try:
            # Validate inputs
            if not speaker_id.strip().isalnum():
                return False, "Speaker ID must contain only letters and numbers"
            
            if not dataset_name.strip().isalnum():
                return False, "Dataset name must contain only letters and numbers"
            
            # Generate filenames
            audio_name, text_name = self.generate_filenames(dataset_name, speaker_id)
            
            # Create speaker directories
            audio_dir = self.root_path / 'audio' / speaker_id
            text_dir = self.root_path / 'transcriptions' / speaker_id
            audio_dir.mkdir(exist_ok=True)
            text_dir.mkdir(exist_ok=True)
            
            # Save audio file
            audio_path = audio_dir / audio_name
            shutil.copy2(audio_file, audio_path)
            
            # Save transcription
            text_path = text_dir / text_name
            self.save_transcription(
                text_path,
                self.sentences[self.current_index],
                {
                    'speaker_id': speaker_id,
                    'dataset_name': dataset_name,
                    'timestamp': datetime.now().isoformat(),
                    'audio_file': audio_name,
                    'font_style': self.current_font
                }
            )
            
            # Update metadata
            self.update_metadata(speaker_id, dataset_name)
            
            # Log success
            self.log_operation(
                f"Saved recording: Speaker={speaker_id}, Dataset={dataset_name}, "
                f"Audio={audio_name}, Text={text_name}"
            )
            
            return True, f"Recording saved successfully as {audio_name}"
            
        except Exception as e:
            error_msg = f"Error saving recording: {str(e)}"
            self.log_operation(error_msg, "error")
            logger.error(traceback.format_exc())
            return False, error_msg
    
    def save_transcription(self, file_path: Path, text: str, metadata: Dict) -> None:
        """Save transcription with metadata"""
        content = f"""[METADATA]
Recording_ID: {metadata['audio_file']}
Speaker_ID: {metadata['speaker_id']}
Dataset_Name: {metadata['dataset_name']}
Timestamp: {metadata['timestamp']}
Font_Style: {metadata['font_style']}

[TEXT]
{text}
"""
        with open(file_path, 'w', encoding='utf-8') as f:
            f.write(content)
    
    def update_metadata(self, speaker_id: str, dataset_name: str) -> None:
        """Update dataset metadata with error handling"""
        metadata_file = self.root_path / 'metadata' / 'dataset_info.json'
        
        try:
            if metadata_file.exists():
                with open(metadata_file, 'r') as f:
                    metadata = json.load(f)
            else:
                metadata = {'speakers': {}, 'last_updated': None}
            
            # Update speaker data
            if speaker_id not in metadata['speakers']:
                metadata['speakers'][speaker_id] = {
                    'total_recordings': 0,
                    'datasets': {}
                }
            
            if dataset_name not in metadata['speakers'][speaker_id]['datasets']:
                metadata['speakers'][speaker_id]['datasets'][dataset_name] = {
                    'recordings': 0,
                    'sentences': len(self.sentences),
                    'first_recording': datetime.now().isoformat(),
                    'last_recording': None,
                    'font_styles_used': []
                }
            
            # Update counts and timestamps
            metadata['speakers'][speaker_id]['total_recordings'] += 1
            metadata['speakers'][speaker_id]['datasets'][dataset_name]['recordings'] += 1
            metadata['speakers'][speaker_id]['datasets'][dataset_name]['last_recording'] = \
                datetime.now().isoformat()
            
            # Update font styles
            if self.current_font not in metadata['speakers'][speaker_id]['datasets'][dataset_name]['font_styles_used']:
                metadata['speakers'][speaker_id]['datasets'][dataset_name]['font_styles_used'].append(
                    self.current_font
                )
            
            metadata['last_updated'] = datetime.now().isoformat()
            
            # Save updated metadata
            with open(metadata_file, 'w') as f:
                json.dump(metadata, f, indent=2)
            
            self.log_operation(f"Updated metadata for {speaker_id} in {dataset_name}")
            
        except Exception as e:
            error_msg = f"Error updating metadata: {str(e)}"
            self.log_operation(error_msg, "error")
            logger.error(traceback.format_exc())

    def get_navigation_info(self) -> Dict[str, Optional[str]]:
        """Get current and next sentence information"""
        if not self.sentences:
            return {
                'current': None,
                'next': None,
                'progress': "No text loaded"
            }
        
        current = self.get_styled_text(self.sentences[self.current_index])
        next_text = None
        
        if self.current_index < len(self.sentences) - 1:
            next_text = self.get_styled_text(self.sentences[self.current_index + 1])
        
        progress = f"Sentence {self.current_index + 1} of {len(self.sentences)}"
        
        return {
            'current': current,
            'next': next_text,
            'progress': progress
        }

    def navigate(self, direction: str) -> Dict[str, Optional[str]]:
        """Navigate through sentences"""
        if not self.sentences:
            return {
                'current': None,
                'next': None,
                'progress': "No text loaded",
                'status': "⚠️ Please load a text file first"
            }
        
        if direction == "next" and self.current_index < len(self.sentences) - 1:
            self.current_index += 1
        elif direction == "prev" and self.current_index > 0:
            self.current_index -= 1
        
        nav_info = self.get_navigation_info()
        nav_info['status'] = "✅ Navigation successful"
        
        return nav_info

    def get_dataset_statistics(self) -> Dict:
        """Get current dataset statistics"""
        try:
            metadata_file = self.root_path / 'metadata' / 'dataset_info.json'
            if not metadata_file.exists():
                return {}
            
            with open(metadata_file, 'r') as f:
                return json.load(f)
        except Exception as e:
            logger.error(f"Error reading dataset statistics: {str(e)}")
            return {}

def create_interface():
    """Create Gradio interface with enhanced features"""
    
    # Create custom CSS for fonts
    custom_css = """
    .gradio-container {
        max-width: 1200px !important;
    }
    .record-button {
        font-size: 1.2em !important;
        padding: 20px !important;
    }
    .sentence-display {
        font-size: 1.4em !important;
        padding: 15px !important;
        border: 1px solid #ddd !important;
        border-radius: 8px !important;
        margin: 10px 0 !important;
        min-height: 100px !important;
    }
    """
    
    # Add font-face declarations
    for font_style, font_info in FONT_STYLES.items():
        if font_style in ['nastaliq', 'naskh']:
            custom_css += f"""
            @font-face {{
                font-family: '{font_info["family"]}';
                src: url('fonts/{font_info["family"]}.ttf') format('truetype');
            }}
            """
    
    collector = TTSDatasetCollector()
    
    with gr.Blocks(title="TTS Dataset Collection Tool", css=custom_css) as interface:
        gr.Markdown("# TTS Dataset Collection Tool")
        
        with gr.Row():
            # Left column - Configuration
            with gr.Column():
                file_input = gr.File(
                    label="Upload Text File (.txt)",
                    file_types=[".txt"]
                )
                speaker_id = gr.Textbox(
                    label="Speaker ID",
                    placeholder="Enter unique speaker identifier (letters and numbers only)"
                )
                dataset_name = gr.Textbox(
                    label="Dataset Name",
                    placeholder="Enter dataset name (letters and numbers only)"
                )
                font_select = gr.Dropdown(
                    choices=list(FONT_STYLES.keys()),
                    value="english_serif",
                    label="Select Font Style"
                )
            
            # Right column - Recording
            with gr.Column():
                current_text = gr.HTML(
                    label="Current Sentence",
                    elem_classes=["sentence-display"]
                )
                audio_recorder = gr.Audio(
                    label="Record Audio",
                    type="filepath",
                    elem_classes=["record-button"]
                )
                next_text = gr.HTML(
                    label="Next Sentence",
                    elem_classes=["sentence-display"]
                )
        
        # Controls
        with gr.Row():
            prev_btn = gr.Button("Previous", variant="secondary")
            next_btn = gr.Button("Next", variant="primary")
            save_btn = gr.Button("Save Recording", variant="primary", elem_classes=["record-button"])
        
        # Status and Progress
        with gr.Row():
            progress = gr.Textbox(
                label="Progress",
                interactive=False
            )
            status = gr.Textbox(
                label="Status",
                interactive=False,
                max_lines=3
            )
        
        # Dataset Info
        with gr.Row():
            dataset_info = gr.JSON(
                label="Dataset Statistics",
                value={}
            )
        
        def update_font(font_style):
            """Update font and refresh display"""
            success, msg = collector.set_font(font_style)
            if not success:
                return {status: msg}
            
            nav_info = collector.get_navigation_info()
            return {
                current_text: nav_info['current'],
                next_text: nav_info['next'],
                status: f"Font updated to {font_style}"
            }
        
        def load_file(file):
            """Handle file loading with enhanced error reporting"""
            if not file:
                return {
                    current_text: "",
                    next_text: "",
                    progress: "",
                    status: "⚠️ No file selected",
                    dataset_info: collector.get_dataset_statistics()
                }

            success, msg = collector.load_text_file(file)
            if not success:
                return {
                    current_text: "",
                    next_text: "",
                    progress: "",
                    status: f"❌ {msg}",
                    dataset_info: collector.get_dataset_statistics()
                }
            
            nav_info = collector.get_navigation_info()
            return {
                current_text: nav_info['current'],
                next_text: nav_info['next'],
                progress: nav_info['progress'],
                status: f"✅ {msg}",
                dataset_info: collector.get_dataset_statistics()
            }
        
        def save_current_recording(audio_file, speaker_id_value, dataset_name_value):
            """Handle saving the current recording"""
            if not audio_file:
                return {status: "⚠️ Please record audio first"}
            
            success, msg = collector.save_recording(
                audio_file, speaker_id_value, dataset_name_value
            )
            
            if not success:
                return {
                    status: f"❌ {msg}",
                    dataset_info: collector.get_dataset_statistics()
                }
            
            # Auto-advance to next sentence after successful save
            nav_info = collector.navigate("next")
            
            return {
                current_text: nav_info['current'],
                next_text: nav_info['next'],
                progress: nav_info['progress'],
                status: f"✅ {msg}",
                dataset_info: collector.get_dataset_statistics()
            }
        
        def navigate_sentences(direction):
            """Handle navigation between sentences"""
            nav_info = collector.navigate(direction)
            return {
                current_text: nav_info['current'],
                next_text: nav_info['next'],
                progress: nav_info['progress'],
                status: nav_info['status']
            }
        
        # Event handlers
        file_input.upload(
            load_file,
            inputs=[file_input],
            outputs=[current_text, next_text, progress, status, dataset_info]
        )
        
        font_select.change(
            update_font,
            inputs=[font_select],
            outputs=[current_text, next_text, status]
        )
        
        save_btn.click(
            save_current_recording,
            inputs=[audio_recorder, speaker_id, dataset_name],
            outputs=[current_text, next_text, progress, status, dataset_info]
        )
        
        prev_btn.click(
            lambda: navigate_sentences("prev"),
            outputs=[current_text, next_text, progress, status]
        )
        
        next_btn.click(
            lambda: navigate_sentences("next"),
            outputs=[current_text, next_text, progress, status]
        )
        
        # Initialize dataset info
        dataset_info.value = collector.get_dataset_statistics()
        
        return interface

if __name__ == "__main__":
    try:
        # Set up any required environment variables
        os.environ["GRADIO_SERVER_NAME"] = "0.0.0.0"
        os.environ["GRADIO_SERVER_PORT"] = "7860"
        
        # Create and launch the interface
        interface = create_interface()
        interface.queue()  # Enable queuing for better handling of concurrent users
        interface.launch(
            server_name="0.0.0.0",
            server_port=7860,
            share=True,
            debug=True,
            show_error=True
        )
    except Exception as e:
        logger.error(f"Failed to launch interface: {str(e)}")
        logger.error(traceback.format_exc())
        raise