"""
Kokoro TTS - Example Usage Script
=================================
This script demonstrates how to use the Kokoro TTS engine programmatically.
Useful for understanding the code flow and for batch processing.

Run this script after installing dependencies:
    pip install kokoro soundfile numpy
    apt-get install espeak-ng  # Linux
"""

import numpy as np
import soundfile as sf
from kokoro import KPipeline

# ============================================================================
# EXAMPLE 1: Basic Text-to-Speech
# ============================================================================

def example_basic_tts():
    """Generate speech with default settings."""
    print("\n" + "="*50)
    print("Example 1: Basic TTS")
    print("="*50)
    
    # Initialize pipeline for American English
    pipeline = KPipeline(lang_code='a')
    
    # Text to synthesize
    text = "Hello! This is a demonstration of the Kokoro text to speech model."
    
    # Generate audio
    for i, (graphemes, phonemes, audio) in enumerate(pipeline(text, voice='af_heart')):
        print(f"Segment {i}:")
        print(f"  Text: {graphemes}")
        print(f"  Phonemes: {phonemes}")
        
        # Save audio
        audio_np = audio.numpy() if hasattr(audio, 'numpy') else audio
        sf.write(f'example1_segment{i}.wav', audio_np, 24000)
        print(f"  Saved: example1_segment{i}.wav")


# ============================================================================
# EXAMPLE 2: Speed Control
# ============================================================================

def example_speed_control():
    """Generate speech at different speeds."""
    print("\n" + "="*50)
    print("Example 2: Speed Control")
    print("="*50)
    
    pipeline = KPipeline(lang_code='a')
    text = "The quick brown fox jumps over the lazy dog."
    
    speeds = [0.7, 1.0, 1.3]
    
    for speed in speeds:
        print(f"\nGenerating at speed {speed}x...")
        
        for _, _, audio in pipeline(text, voice='af_bella', speed=speed):
            audio_np = audio.numpy() if hasattr(audio, 'numpy') else audio
            filename = f'example2_speed_{speed}.wav'
            sf.write(filename, audio_np, 24000)
            print(f"  Saved: {filename}")


# ============================================================================
# EXAMPLE 3: Different Voices
# ============================================================================

def example_different_voices():
    """Compare different voices with the same text."""
    print("\n" + "="*50)
    print("Example 3: Different Voices")
    print("="*50)
    
    # American and British pipelines
    pipelines = {
        'a': KPipeline(lang_code='a'),
        'b': KPipeline(lang_code='b'),
    }
    
    text = "Good morning! How are you doing today?"
    
    voices = [
        ('af_heart', 'American Female - Heart'),
        ('am_michael', 'American Male - Michael'),
        ('bf_emma', 'British Female - Emma'),
        ('bm_george', 'British Male - George'),
    ]
    
    for voice_id, voice_name in voices:
        print(f"\nGenerating with {voice_name}...")
        
        lang_code = voice_id[0]  # 'a' or 'b'
        pipeline = pipelines[lang_code]
        
        for _, _, audio in pipeline(text, voice=voice_id):
            audio_np = audio.numpy() if hasattr(audio, 'numpy') else audio
            filename = f'example3_{voice_id}.wav'
            sf.write(filename, audio_np, 24000)
            print(f"  Saved: {filename}")


# ============================================================================
# EXAMPLE 4: Combining Audio Segments with Pauses
# ============================================================================

def example_pause_insertion():
    """Demonstrate inserting pauses between sentences."""
    print("\n" + "="*50)
    print("Example 4: Pause Insertion")
    print("="*50)
    
    pipeline = KPipeline(lang_code='a')
    
    # Multiple sentences
    text = """First sentence of the story.
    Second sentence with more details.
    And finally, the conclusion."""
    
    # Collect all audio segments
    audio_segments = []
    
    for _, _, audio in pipeline(text, voice='af_heart'):
        audio_np = audio.numpy() if hasattr(audio, 'numpy') else audio
        audio_segments.append(audio_np)
    
    # Create pause (500ms of silence)
    sample_rate = 24000
    pause_duration = 0.5  # seconds
    silence = np.zeros(int(sample_rate * pause_duration), dtype=np.float32)
    
    # Combine with pauses
    combined = []
    for i, segment in enumerate(audio_segments):
        combined.append(segment)
        if i < len(audio_segments) - 1:  # Don't add pause after last segment
            combined.append(silence)
    
    final_audio = np.concatenate(combined)
    
    # Normalize
    max_val = np.max(np.abs(final_audio))
    if max_val > 0:
        final_audio = final_audio / max_val * 0.9
    
    filename = 'example4_with_pauses.wav'
    sf.write(filename, final_audio, 24000)
    print(f"  Saved: {filename}")
    print(f"  Duration: {len(final_audio)/24000:.2f} seconds")


# ============================================================================
# EXAMPLE 5: Custom Pronunciation
# ============================================================================

def example_custom_pronunciation():
    """Use phoneme markup for custom pronunciations."""
    print("\n" + "="*50)
    print("Example 5: Custom Pronunciation")
    print("="*50)
    
    pipeline = KPipeline(lang_code='a')
    
    # Custom pronunciation using markdown-style markup
    # [word](/phonemes/) syntax
    text_normal = "I love Kokoro text to speech."
    text_custom = "I love [Kokoro](/kˈOkəɹO/) text to speech."
    
    print("\nNormal pronunciation:")
    for _, phonemes, audio in pipeline(text_normal, voice='af_heart'):
        print(f"  Phonemes: {phonemes}")
        audio_np = audio.numpy() if hasattr(audio, 'numpy') else audio
        sf.write('example5_normal.wav', audio_np, 24000)
    
    print("\nCustom pronunciation:")
    for _, phonemes, audio in pipeline(text_custom, voice='af_heart'):
        print(f"  Phonemes: {phonemes}")
        audio_np = audio.numpy() if hasattr(audio, 'numpy') else audio
        sf.write('example5_custom.wav', audio_np, 24000)


# ============================================================================
# MAIN
# ============================================================================

if __name__ == "__main__":
    print("Kokoro TTS - Example Usage")
    print("==========================")
    print("This script generates several example audio files.")
    print("Make sure you have installed: pip install kokoro soundfile")
    print("And system dependency: apt-get install espeak-ng")
    
    try:
        example_basic_tts()
        example_speed_control()
        example_different_voices()
        example_pause_insertion()
        example_custom_pronunciation()
        
        print("\n" + "="*50)
        print("All examples completed successfully!")
        print("Check the current directory for generated .wav files")
        print("="*50)
        
    except ImportError as e:
        print(f"\nError: {e}")
        print("Please install required packages:")
        print("  pip install kokoro soundfile numpy")
        print("  apt-get install espeak-ng")
    except Exception as e:
        print(f"\nError during generation: {e}")