"""
Advanced modules integration for AutoPipelineDoctor.

This module provides integration for all advanced modules with the main package.
"""

from typing import Dict, List, Optional, Union, Any, Set, Callable, Type
import logging

# Import advanced modules
from autopd.advanced.neuro_behavioral_pattern_clustering import NeuroBehavioralPatternClustering
from autopd.advanced.autonomous_optimization_loop_injection import AutonomousOptimizationLoopInjection
from autopd.advanced.causal_fault_tree_analysis import CausalFaultTreeAnalysis
from autopd.advanced.latent_loss_surface_mapping import LatentLossSurfaceMapping
from autopd.advanced.synthetic_model_shadowing import SyntheticModelShadowing
from autopd.advanced.hardware_aware_learning_curve_forecasting import HardwareAwareLearningCurveForecasting
from autopd.advanced.anomaly_activated_alert_system import AnomalyActivatedAlertSystem
from autopd.advanced.llm_connected_think_tank import LLMConnectedThinkTank
from autopd.advanced.dna_tracker import DNATracker
from autopd.advanced.real_time_model_cognition import ModelCognitionVisualizer, ModelCognitionHook

logger = logging.getLogger(__name__)


class AdvancedModulesManager:
    """
    Manager for advanced modules in AutoPipelineDoctor.
    
    This class manages the initialization, configuration, and usage of all advanced
    modules in the AutoPipelineDoctor package.
    
    Attributes:
        enabled: Whether advanced modules are enabled
        modules: Dictionary of initialized advanced modules
    """
    
    def __init__(self, enable_advanced: bool = False):
        """
        Initialize the AdvancedModulesManager.
        
        Args:
            enable_advanced: Whether to enable advanced modules
        """
        self.enabled = enable_advanced
        self.modules = {}
        
        if self.enabled:
            logger.info("Advanced modules enabled")
        else:
            logger.info("Advanced modules disabled")
    
    def initialize_modules(
        self,
        model,
        optimizer,
        dataloader,
        config: Dict[str, Any] = None,
    ) -> None:
        """
        Initialize all advanced modules.
        
        Args:
            model: PyTorch model
            optimizer: PyTorch optimizer
            dataloader: PyTorch dataloader
            config: Configuration for advanced modules
        """
        if not self.enabled:
            logger.info("Advanced modules not enabled, skipping initialization")
            return
        
        config = config or {}
        
        try:
            # Initialize Neuro-Behavioral Pattern Clustering
            self.modules["nbpc"] = NeuroBehavioralPatternClustering(
                model=model,
                **config.get("nbpc", {})
            )
            logger.info("Initialized Neuro-Behavioral Pattern Clustering")
            
            # Initialize Autonomous Optimization Loop Injection
            self.modules["aoli"] = AutonomousOptimizationLoopInjection(
                model=model,
                optimizer=optimizer,
                **config.get("aoli", {})
            )
            logger.info("Initialized Autonomous Optimization Loop Injection")
            
            # Initialize Causal Fault Tree Analysis
            self.modules["cfta"] = CausalFaultTreeAnalysis(
                model=model,
                **config.get("cfta", {})
            )
            logger.info("Initialized Causal Fault Tree Analysis")
            
            # Initialize Latent Loss Surface Mapping
            self.modules["llsm"] = LatentLossSurfaceMapping(
                model=model,
                optimizer=optimizer,
                **config.get("llsm", {})
            )
            logger.info("Initialized Latent Loss Surface Mapping")
            
            # Initialize Synthetic Model Shadowing
            self.modules["sms"] = SyntheticModelShadowing(
                model=model,
                **config.get("sms", {})
            )
            logger.info("Initialized Synthetic Model Shadowing")
            
            # Initialize Hardware-Aware Learning Curve Forecasting
            self.modules["halcf"] = HardwareAwareLearningCurveForecasting(
                model=model,
                dataloader=dataloader,
                **config.get("halcf", {})
            )
            logger.info("Initialized Hardware-Aware Learning Curve Forecasting")
            
            # Initialize Anomaly-Activated Alert System
            self.modules["aaa"] = AnomalyActivatedAlertSystem(
                **config.get("aaa", {})
            )
            logger.info("Initialized Anomaly-Activated Alert System")
            
            # Initialize LLM-Connected Think Tank
            self.modules["llm_think_tank"] = LLMConnectedThinkTank(
                **config.get("llm_think_tank", {})
            )
            logger.info("Initialized LLM-Connected Think Tank")
            
            # Initialize DNA Tracker
            self.modules["dna_tracker"] = DNATracker(
                model=model,
                **config.get("dna_tracker", {})
            )
            logger.info("Initialized DNA Tracker")
            
            # Initialize Real-Time Model Cognition Visualization
            self.modules["mindscope"] = ModelCognitionVisualizer(
                model=model,
                **config.get("mindscope", {})
            )
            logger.info("Initialized Real-Time Model Cognition Visualization")
            
            logger.info("All advanced modules initialized successfully")
        
        except Exception as e:
            logger.error(f"Error initializing advanced modules: {e}")
            logger.exception(e)
    
    def get_module(self, module_name: str) -> Any:
        """
        Get an advanced module by name.
        
        Args:
            module_name: Name of the module
            
        Returns:
            The module instance or None if not found
        """
        if not self.enabled:
            logger.warning(f"Advanced modules not enabled, cannot get module {module_name}")
            return None
        
        return self.modules.get(module_name)
    
    def start_all(self) -> None:
        """Start all advanced modules."""
        if not self.enabled:
            logger.info("Advanced modules not enabled, skipping start")
            return
        
        for name, module in self.modules.items():
            try:
                if hasattr(module, "start"):
                    module.start()
                    logger.info(f"Started module {name}")
            except Exception as e:
                logger.error(f"Error starting module {name}: {e}")
                logger.exception(e)
    
    def stop_all(self) -> None:
        """Stop all advanced modules."""
        if not self.enabled:
            logger.info("Advanced modules not enabled, skipping stop")
            return
        
        for name, module in self.modules.items():
            try:
                if hasattr(module, "stop"):
                    module.stop()
                    logger.info(f"Stopped module {name}")
            except Exception as e:
                logger.error(f"Error stopping module {name}: {e}")
                logger.exception(e)
    
    def on_train_start(self) -> None:
        """Called when training starts."""
        if not self.enabled:
            return
        
        for name, module in self.modules.items():
            try:
                if hasattr(module, "on_train_start"):
                    module.on_train_start()
            except Exception as e:
                logger.error(f"Error in on_train_start for module {name}: {e}")
                logger.exception(e)
    
    def on_train_end(self) -> None:
        """Called when training ends."""
        if not self.enabled:
            return
        
        for name, module in self.modules.items():
            try:
                if hasattr(module, "on_train_end"):
                    module.on_train_end()
            except Exception as e:
                logger.error(f"Error in on_train_end for module {name}: {e}")
                logger.exception(e)
    
    def on_epoch_start(self, epoch: int) -> None:
        """
        Called when an epoch starts.
        
        Args:
            epoch: Current epoch
        """
        if not self.enabled:
            return
        
        for name, module in self.modules.items():
            try:
                if hasattr(module, "on_epoch_start"):
                    module.on_epoch_start(epoch)
            except Exception as e:
                logger.error(f"Error in on_epoch_start for module {name}: {e}")
                logger.exception(e)
    
    def on_epoch_end(self, epoch: int) -> None:
        """
        Called when an epoch ends.
        
        Args:
            epoch: Current epoch
        """
        if not self.enabled:
            return
        
        for name, module in self.modules.items():
            try:
                if hasattr(module, "on_epoch_end"):
                    module.on_epoch_end(epoch)
            except Exception as e:
                logger.error(f"Error in on_epoch_end for module {name}: {e}")
                logger.exception(e)
    
    def on_batch_start(self, batch_idx: int) -> None:
        """
        Called when a batch starts.
        
        Args:
            batch_idx: Current batch index
        """
        if not self.enabled:
            return
        
        for name, module in self.modules.items():
            try:
                if hasattr(module, "on_batch_start"):
                    module.on_batch_start(batch_idx)
            except Exception as e:
                logger.error(f"Error in on_batch_start for module {name}: {e}")
                logger.exception(e)
    
    def on_batch_end(self, batch_idx: int) -> None:
        """
        Called when a batch ends.
        
        Args:
            batch_idx: Current batch index
        """
        if not self.enabled:
            return
        
        for name, module in self.modules.items():
            try:
                if hasattr(module, "on_batch_end"):
                    module.on_batch_end(batch_idx)
            except Exception as e:
                logger.error(f"Error in on_batch_end for module {name}: {e}")
                logger.exception(e)
    
    def on_backward_end(self) -> None:
        """Called after backward pass."""
        if not self.enabled:
            return
        
        for name, module in self.modules.items():
            try:
                if hasattr(module, "on_backward_end"):
                    module.on_backward_end()
            except Exception as e:
                logger.error(f"Error in on_backward_end for module {name}: {e}")
                logger.exception(e)
    
    def get_all_reports(self) -> Dict[str, Any]:
        """
        Get reports from all advanced modules.
        
        Returns:
            Dictionary of reports from all modules
        """
        if not self.enabled:
            logger.warning("Advanced modules not enabled, cannot get reports")
            return {}
        
        reports = {}
        
        for name, module in self.modules.items():
            try:
                if hasattr(module, "get_report"):
                    reports[name] = module.get_report()
            except Exception as e:
                logger.error(f"Error getting report from module {name}: {e}")
                logger.exception(e)
        
        return reports
    
    def get_all_visualizations(self) -> Dict[str, Any]:
        """
        Get visualizations from all advanced modules.
        
        Returns:
            Dictionary of visualizations from all modules
        """
        if not self.enabled:
            logger.warning("Advanced modules not enabled, cannot get visualizations")
            return {}
        
        visualizations = {}
        
        for name, module in self.modules.items():
            try:
                if hasattr(module, "get_visualization"):
                    visualizations[name] = module.get_visualization()
            except Exception as e:
                logger.error(f"Error getting visualization from module {name}: {e}")
                logger.exception(e)
        
        return visualizations
    
    def get_all_recommendations(self) -> Dict[str, Any]:
        """
        Get recommendations from all advanced modules.
        
        Returns:
            Dictionary of recommendations from all modules
        """
        if not self.enabled:
            logger.warning("Advanced modules not enabled, cannot get recommendations")
            return {}
        
        recommendations = {}
        
        for name, module in self.modules.items():
            try:
                if hasattr(module, "get_recommendations"):
                    recommendations[name] = module.get_recommendations()
            except Exception as e:
                logger.error(f"Error getting recommendations from module {name}: {e}")
                logger.exception(e)
        
        return recommendations
    
    def apply_all_recommendations(self) -> Dict[str, Any]:
        """
        Apply recommendations from all advanced modules.
        
        Returns:
            Dictionary of results from applying recommendations
        """
        if not self.enabled:
            logger.warning("Advanced modules not enabled, cannot apply recommendations")
            return {}
        
        results = {}
        
        for name, module in self.modules.items():
            try:
                if hasattr(module, "apply_recommendations"):
                    results[name] = module.apply_recommendations()
            except Exception as e:
                logger.error(f"Error applying recommendations from module {name}: {e}")
                logger.exception(e)
        
        return results
    
    def is_enabled(self) -> bool:
        """
        Check if advanced modules are enabled.
        
        Returns:
            True if advanced modules are enabled, False otherwise
        """
        return self.enabled
