"""
Trixy ML Trainer Framework

A comprehensive machine learning training framework for the Trixy voice assistant
supporting multiple model formats (.pth, .pt, .onnx) and various architectures.

Features:
- Password-protected model archives
- Metadata management for model information
- State-of-the-art training mechanics
- Professional logging and error handling
- Wakeword detection training (RepCNN)
- Voice recognition training (ECAPA-TDNN, TitaNet-S, SpeakerNet-M)
- Command-line interface and server integration
- Extensible architecture for custom models
"""

# Core framework components
from .base import BaseTrainer, TrainerConfig, TrainingState
from .config import ConfigManager, ModelFormat
from .metadata import ModelMetadata, MetadataManager, ModelType
from .model_formats import ModelFormatManager
from .data_pipeline import AudioProcessingConfig, AudioProcessor, AudioDataset
from .utils import TrainerLogger, ProgressMonitor, ValidationMetrics
from .validation import ModelValidator, ValidationConfig

# Specialized trainers
from .wakeword.trainer import WakewordTrainer, create_wakeword_trainer_config
from .wakeword.models import RepCNN, ImprovedRepCNN, LightweightRepCNN, create_repcnn_model

# Voice recognition components
from .voice_recognition.trainer import VoiceRecognitionTrainer, create_voice_recognition_trainer_config
from .voice_recognition.models import (
    ECAPA_TDNN, TitaNet_S, SpeakerNet_M, create_voice_recognition_model,
    AngularMarginLoss, GE2ELoss
)

# Utility functions - available through TrainerLogger and ProgressMonitor classes

__version__ = "1.0.0"
__author__ = "Trixy Development Team"

__all__ = [
    # Core components
    "BaseTrainer",
    "TrainerConfig", 
    "TrainingState",
    "ConfigManager",
    "ModelFormat",
    "ModelMetadata",
    "MetadataManager", 
    "ModelType",
    "ModelFormatManager",
    
    # Data pipeline
    "AudioProcessingConfig",
    "AudioProcessor", 
    "AudioDataset",
    
    # Utils and validation
    "TrainerLogger",
    "ProgressMonitor",
    "ValidationMetrics", 
    "ModelValidator",
    "ValidationConfig",
    
    # Wakeword detection
    "WakewordTrainer",
    "create_wakeword_trainer_config",
    "RepCNN",
    "ImprovedRepCNN", 
    "LightweightRepCNN",
    "create_repcnn_model",
    
    # Voice recognition
    "VoiceRecognitionTrainer",
    "create_voice_recognition_trainer_config",
    "ECAPA_TDNN",
    "TitaNet_S",
    "SpeakerNet_M",
    "create_voice_recognition_model",
    "AngularMarginLoss",
    "GE2ELoss"
]