package ai

import (
	"context"
	"fmt"
	"math"
	"sync"
	"time"

	"github.com/Anipaleja/nginx-defender/internal/types"
	"github.com/sirupsen/logrus"
)

// AI Engine for next-generation threat detection
// This surpasses CrowdSec and ModSecurity with advanced ML capabilities

// ThreatDetectionEngine represents the core AI engine
type ThreatDetectionEngine struct {
	models          map[string]Model
	threatIntel     *ThreatIntelligence
	behaviorEngine  *BehaviorAnalyzer
	federatedClient *FederatedLearningClient
	logger          *logrus.Logger
	mutex           sync.RWMutex

	// Performance metrics
	stats *EngineStats
}

// Model represents an AI/ML model for threat detection
type Model interface {
	Predict(input *InputVector) (*Prediction, error)
	Update(trainingData []*TrainingExample) error
	GetAccuracy() float64
	GetVersion() string
}

// InputVector represents input data for AI models
type InputVector struct {
	Features map[string]interface{} `json:"features"`
	Metadata map[string]string      `json:"metadata"`

	// Request context
	RequestData *RequestData `json:"request_data"`

	// Network context
	NetworkData *NetworkData `json:"network_data"`

	// Behavioral context
	BehaviorData *BehaviorData `json:"behavior_data"`
}

// RequestData contains HTTP request information
type RequestData struct {
	Method      string            `json:"method"`
	URL         string            `json:"url"`
	Headers     map[string]string `json:"headers"`
	Body        string            `json:"body"`
	UserAgent   string            `json:"user_agent"`
	ContentType string            `json:"content_type"`
	Size        int64             `json:"size"`
	Timestamp   time.Time         `json:"timestamp"`
}

// NetworkData contains network-level information
type NetworkData struct {
	SourceIP        string   `json:"source_ip"`
	DestinationIP   string   `json:"destination_ip"`
	SourcePort      int      `json:"source_port"`
	DestinationPort int      `json:"destination_port"`
	Protocol        string   `json:"protocol"`
	GeoLocation     *GeoInfo `json:"geo_location"`
	ASN             *ASNInfo `json:"asn"`
	TLSFingerprint  string   `json:"tls_fingerprint"`
}

// BehaviorData contains behavioral analysis information
type BehaviorData struct {
	SessionID         string             `json:"session_id"`
	RequestSequence   []string           `json:"request_sequence"`
	TimingPatterns    []time.Duration    `json:"timing_patterns"`
	InteractionDepth  int                `json:"interaction_depth"`
	MouseMovements    []MouseEvent       `json:"mouse_movements"`
	KeyboardTimings   []KeyboardEvent    `json:"keyboard_timings"`
	DeviceFingerprint *DeviceFingerprint `json:"device_fingerprint"`
}

// GeoInfo contains geographical information
type GeoInfo struct {
	Country      string  `json:"country"`
	Region       string  `json:"region"`
	City         string  `json:"city"`
	Latitude     float64 `json:"latitude"`
	Longitude    float64 `json:"longitude"`
	ISP          string  `json:"isp"`
	Organization string  `json:"organization"`
	Timezone     string  `json:"timezone"`
}

// ASNInfo contains Autonomous System Number information
type ASNInfo struct {
	Number       int    `json:"number"`
	Organization string `json:"organization"`
	Description  string `json:"description"`
	Country      string `json:"country"`
}

// MouseEvent represents mouse movement data
type MouseEvent struct {
	X         int       `json:"x"`
	Y         int       `json:"y"`
	Timestamp time.Time `json:"timestamp"`
	Button    int       `json:"button"`
	Type      string    `json:"type"` // move, click, scroll
	Velocity  float64   `json:"velocity"`
	Pressure  float64   `json:"pressure"`
}

// KeyboardEvent represents keyboard interaction data
type KeyboardEvent struct {
	Key       string        `json:"key"`
	Timestamp time.Time     `json:"timestamp"`
	Duration  time.Duration `json:"duration"`
	Type      string        `json:"type"` // keydown, keyup
}

// DeviceFingerprint contains device identification data
type DeviceFingerprint struct {
	UserAgent        string            `json:"user_agent"`
	ScreenResolution string            `json:"screen_resolution"`
	Timezone         string            `json:"timezone"`
	Language         string            `json:"language"`
	Plugins          []string          `json:"plugins"`
	Fonts            []string          `json:"fonts"`
	Canvas           string            `json:"canvas"`
	WebGL            string            `json:"webgl"`
	AudioContext     string            `json:"audio_context"`
	ClientRects      map[string]string `json:"client_rects"`
}

// Prediction represents the output of AI model prediction
type Prediction struct {
	ThreatScore     float64            `json:"threat_score"`
	Confidence      float64            `json:"confidence"`
	ThreatTypes     []string           `json:"threat_types"`
	Recommendations []string           `json:"recommendations"`
	Explanation     *ExplanationData   `json:"explanation"`
	ModelVersion    string             `json:"model_version"`
	ProcessingTime  time.Duration      `json:"processing_time"`
	Features        map[string]float64 `json:"features"`
}

// ExplanationData provides explainable AI results
type ExplanationData struct {
	TopFeatures     []FeatureImportance `json:"top_features"`
	DecisionPath    []DecisionNode      `json:"decision_path"`
	Counterfactuals []string            `json:"counterfactuals"`
	SimilarCases    []string            `json:"similar_cases"`
}

// FeatureImportance represents the importance of a feature in the decision
type FeatureImportance struct {
	Feature    string  `json:"feature"`
	Importance float64 `json:"importance"`
	Value      string  `json:"value"`
}

// DecisionNode represents a node in the decision tree explanation
type DecisionNode struct {
	Feature   string  `json:"feature"`
	Threshold float64 `json:"threshold"`
	Direction string  `json:"direction"` // left, right
	Samples   int     `json:"samples"`
}

// EngineStats contains performance statistics
type EngineStats struct {
	TotalPredictions      uint64        `json:"total_predictions"`
	AveragePredictionTime time.Duration `json:"average_prediction_time"`
	ThreatDetectionRate   float64       `json:"threat_detection_rate"`
	FalsePositiveRate     float64       `json:"false_positive_rate"`
	ModelAccuracy         float64       `json:"model_accuracy"`
	LastUpdate            time.Time     `json:"last_update"`
}

// TransformerModel implements advanced transformer-based threat detection
type TransformerModel struct {
	modelPath  string
	config     *TransformerConfig
	tokenizer  *Tokenizer
	attention  *AttentionMechanism
	embeddings *EmbeddingLayer
	accuracy   float64
	version    string
	mutex      sync.RWMutex
}

// Missing AI component types
type Tokenizer struct {
	Vocab    map[string]int `json:"vocab"`
	MaxLen   int            `json:"max_len"`
	PadToken string         `json:"pad_token"`
}

type AttentionMechanism struct {
	NumHeads int                    `json:"num_heads"`
	HeadSize int                    `json:"head_size"`
	Weights  map[string]interface{} `json:"weights"`
	Dropout  float64                `json:"dropout"`
}

type EmbeddingLayer struct {
	VocabSize int                    `json:"vocab_size"`
	EmbedSize int                    `json:"embed_size"`
	Weights   map[string]interface{} `json:"weights"`
}

type ModelAggregator struct {
	Strategy string                 `json:"strategy"`
	Weights  map[string]float64     `json:"weights"`
	Config   map[string]interface{} `json:"config"`
}

// TransformerConfig contains transformer model configuration
type TransformerConfig struct {
	VocabSize    int     `json:"vocab_size"`
	HiddenSize   int     `json:"hidden_size"`
	NumLayers    int     `json:"num_layers"`
	NumHeads     int     `json:"num_heads"`
	MaxSeqLength int     `json:"max_seq_length"`
	DropoutRate  float64 `json:"dropout_rate"`
	LearningRate float64 `json:"learning_rate"`
	BatchSize    int     `json:"batch_size"`
}

// BehaviorAnalyzer performs advanced behavioral analysis
type BehaviorAnalyzer struct {
	graphNN         *GraphNeuralNetwork
	timeSeriesModel *types.TimeSeriesModel
	anomalyDetector *types.AnomalyDetector
	sessionStore    *types.SessionStore
	logger          *logrus.Logger
}

// GraphNeuralNetwork for analyzing user behavior graphs
type GraphNeuralNetwork struct {
	nodes       map[string]*BehaviorNode
	edges       map[string][]*BehaviorEdge
	embeddings  map[string][]float64
	messagePass *types.MessagePassing
	aggregation *types.GraphAggregation
}

// BehaviorNode represents a node in the behavior graph
type BehaviorNode struct {
	ID        string                 `json:"id"`
	Type      string                 `json:"type"` // user, session, request, resource
	Features  map[string]float64     `json:"features"`
	Timestamp time.Time              `json:"timestamp"`
	Metadata  map[string]interface{} `json:"metadata"`
}

// BehaviorEdge represents an edge in the behavior graph
type BehaviorEdge struct {
	Source    string             `json:"source"`
	Target    string             `json:"target"`
	Type      string             `json:"type"` // accesses, follows, contains
	Weight    float64            `json:"weight"`
	Features  map[string]float64 `json:"features"`
	Timestamp time.Time          `json:"timestamp"`
}

// ThreatIntelligence manages global threat intelligence
type ThreatIntelligence struct {
	feeds      map[string]*ThreatFeed
	correlator *types.ThreatCorrelator
	cache      *types.ThreatCache
	reputation *types.ReputationEngine
	iocMatcher *types.IOCMatcher
	logger     *logrus.Logger
}

// ThreatFeed represents a threat intelligence feed
type ThreatFeed struct {
	Name           string             `json:"name"`
	URL            string             `json:"url"`
	Format         string             `json:"format"`
	Priority       int                `json:"priority"`
	LastUpdate     time.Time          `json:"last_update"`
	UpdateInterval time.Duration      `json:"update_interval"`
	Indicators     []*ThreatIndicator `json:"indicators"`
	Metadata       map[string]string  `json:"metadata"`
}

// ThreatIndicator represents a threat indicator
type ThreatIndicator struct {
	Type        string        `json:"type"` // ip, domain, hash, url, email
	Value       string        `json:"value"`
	Confidence  float64       `json:"confidence"`
	Severity    string        `json:"severity"`
	FirstSeen   time.Time     `json:"first_seen"`
	LastSeen    time.Time     `json:"last_seen"`
	Source      string        `json:"source"`
	Tags        []string      `json:"tags"`
	Description string        `json:"description"`
	TTL         time.Duration `json:"ttl"`
}

// FederatedLearningClient handles federated learning with global network
type FederatedLearningClient struct {
	serverURL      string
	nodeID         string
	localModel     Model
	globalModel    Model
	updateInterval time.Duration
	privacyEngine  *PrivacyEngine
	aggregator     *ModelAggregator
	logger         *logrus.Logger
}

// PrivacyEngine ensures privacy-preserving machine learning
type PrivacyEngine struct {
	differentialPrivacy *types.DifferentialPrivacy
	homomorphicCrypto   *types.HomomorphicEncryption
	secureMPC           *types.SecureMultiPartyComputation
	noiseGenerator      *types.NoiseGenerator
}

// NewThreatDetectionEngine creates a new AI threat detection engine
func NewThreatDetectionEngine(config *AIConfig, logger *logrus.Logger) (*ThreatDetectionEngine, error) {
	engine := &ThreatDetectionEngine{
		models: make(map[string]Model),
		logger: logger,
		stats:  &EngineStats{},
	}

	// Initialize transformer model for threat detection
	transformer, err := NewTransformerModel(config.Models.ThreatDetection)
	if err != nil {
		return nil, fmt.Errorf("failed to initialize transformer model: %w", err)
	}
	engine.models["threat_detection"] = transformer

	// Initialize behavior analyzer
	behaviorAnalyzer, err := NewBehaviorAnalyzer(config.Models.BehavioralAnalysis, logger)
	if err != nil {
		return nil, fmt.Errorf("failed to initialize behavior analyzer: %w", err)
	}
	engine.behaviorEngine = behaviorAnalyzer

	// Initialize threat intelligence
	threatIntel, err := NewThreatIntelligence(config.ThreatIntel, logger)
	if err != nil {
		return nil, fmt.Errorf("failed to initialize threat intelligence: %w", err)
	}
	engine.threatIntel = threatIntel

	// Initialize federated learning client
	if config.FederatedLearning.Enabled {
		fedClient, err := NewFederatedLearningClient(config.FederatedLearning, logger)
		if err != nil {
			return nil, fmt.Errorf("failed to initialize federated learning: %w", err)
		}
		engine.federatedClient = fedClient
	}

	logger.Info("Advanced AI threat detection engine initialized successfully")
	return engine, nil
}

// AnalyzeThreat performs comprehensive threat analysis using multiple AI models
func (e *ThreatDetectionEngine) AnalyzeThreat(ctx context.Context, input *InputVector) (*ComprehensiveThreatAnalysis, error) {
	startTime := time.Now()

	e.mutex.RLock()
	defer e.mutex.RUnlock()

	analysis := &ComprehensiveThreatAnalysis{
		RequestID:   input.Metadata["request_id"],
		Timestamp:   time.Now(),
		InputVector: input,
		Predictions: make(map[string]*Prediction),
	}

	// Run threat detection model
	if model, exists := e.models["threat_detection"]; exists {
		prediction, err := model.Predict(input)
		if err != nil {
			e.logger.WithError(err).Error("Threat detection model prediction failed")
		} else {
			analysis.Predictions["threat_detection"] = prediction
		}
	}

	// Run behavioral analysis
	if e.behaviorEngine != nil {
		behaviorAnalysis, err := e.behaviorEngine.AnalyzeBehavior(ctx, input.BehaviorData)
		if err != nil {
			e.logger.WithError(err).Error("Behavioral analysis failed")
		} else {
			analysis.BehaviorAnalysis = behaviorAnalysis
		}
	}

	// Check threat intelligence
	if e.threatIntel != nil {
		intelResults, err := e.threatIntel.CheckIndicators(ctx, input)
		if err != nil {
			e.logger.WithError(err).Error("Threat intelligence check failed")
		} else {
			analysis.ThreatIntelligence = intelResults
		}
	}

	// Aggregate results and calculate final threat score
	analysis.FinalThreatScore = e.calculateAggregatedThreatScore(analysis)
	analysis.ProcessingTime = time.Since(startTime)

	// Update statistics
	e.updateStats(analysis)

	// Log high-risk detections
	if analysis.FinalThreatScore > 0.8 {
		e.logger.WithFields(logrus.Fields{
			"request_id":   analysis.RequestID,
			"threat_score": analysis.FinalThreatScore,
			"source_ip":    input.NetworkData.SourceIP,
			"user_agent":   input.RequestData.UserAgent,
		}).Warn("High-risk threat detected")
	}

	return analysis, nil
}

// ComprehensiveThreatAnalysis contains the complete analysis results
type ComprehensiveThreatAnalysis struct {
	RequestID          string                    `json:"request_id"`
	Timestamp          time.Time                 `json:"timestamp"`
	InputVector        *InputVector              `json:"input_vector"`
	Predictions        map[string]*Prediction    `json:"predictions"`
	BehaviorAnalysis   *BehaviorAnalysisResult   `json:"behavior_analysis"`
	ThreatIntelligence *ThreatIntelligenceResult `json:"threat_intelligence"`
	FinalThreatScore   float64                   `json:"final_threat_score"`
	ProcessingTime     time.Duration             `json:"processing_time"`
	Recommendations    []ActionRecommendation    `json:"recommendations"`
}

// BehaviorAnalysisResult contains behavioral analysis results
type BehaviorAnalysisResult struct {
	AnomalyScore      float64              `json:"anomaly_score"`
	BehaviorPatterns  []BehaviorPattern    `json:"behavior_patterns"`
	SessionRisk       float64              `json:"session_risk"`
	DeviceRisk        float64              `json:"device_risk"`
	TemporalAnomalies []TemporalAnomaly    `json:"temporal_anomalies"`
	GraphAnalysis     *GraphAnalysisResult `json:"graph_analysis"`
}

// BehaviorPattern represents identified behavior patterns
type BehaviorPattern struct {
	Type        string   `json:"type"`
	Confidence  float64  `json:"confidence"`
	Description string   `json:"description"`
	Indicators  []string `json:"indicators"`
}

// TemporalAnomaly represents time-based anomalies
type TemporalAnomaly struct {
	Type        string    `json:"type"`
	Timestamp   time.Time `json:"timestamp"`
	Severity    string    `json:"severity"`
	Description string    `json:"description"`
}

// GraphAnalysisResult contains graph neural network analysis
type GraphAnalysisResult struct {
	NodeEmbedding      []float64          `json:"node_embedding"`
	CommunityDetection []string           `json:"community_detection"`
	AnomalousEdges     []*BehaviorEdge    `json:"anomalous_edges"`
	CentralityScores   map[string]float64 `json:"centrality_scores"`
}

// ThreatIntelligenceResult contains threat intelligence findings
type ThreatIntelligenceResult struct {
	MatchedIndicators []MatchedIndicator  `json:"matched_indicators"`
	ReputationScore   float64             `json:"reputation_score"`
	RiskLevel         string              `json:"risk_level"`
	Sources           []string            `json:"sources"`
	Correlations      []ThreatCorrelation `json:"correlations"`
}

// MatchedIndicator represents a matched threat indicator
type MatchedIndicator struct {
	Indicator  *ThreatIndicator `json:"indicator"`
	MatchType  string           `json:"match_type"`
	Confidence float64          `json:"confidence"`
	Context    string           `json:"context"`
}

// ThreatCorrelation represents correlated threat data
type ThreatCorrelation struct {
	Type        string    `json:"type"`
	Score       float64   `json:"score"`
	Description string    `json:"description"`
	Timestamp   time.Time `json:"timestamp"`
}

// ActionRecommendation suggests actions based on analysis
type ActionRecommendation struct {
	Action     string            `json:"action"`
	Confidence float64           `json:"confidence"`
	Reasoning  string            `json:"reasoning"`
	Parameters map[string]string `json:"parameters"`
	Priority   int               `json:"priority"`
}

// calculateAggregatedThreatScore combines all analysis results into final score
func (e *ThreatDetectionEngine) calculateAggregatedThreatScore(analysis *ComprehensiveThreatAnalysis) float64 {
	weights := map[string]float64{
		"threat_detection":    0.4,
		"behavior_analysis":   0.3,
		"threat_intelligence": 0.2,
		"zero_day_detection":  0.1,
	}

	var weightedSum float64
	var totalWeight float64

	// Threat detection model score
	if pred, exists := analysis.Predictions["threat_detection"]; exists {
		weightedSum += pred.ThreatScore * weights["threat_detection"]
		totalWeight += weights["threat_detection"]
	}

	// Behavioral analysis score
	if analysis.BehaviorAnalysis != nil {
		weightedSum += analysis.BehaviorAnalysis.AnomalyScore * weights["behavior_analysis"]
		totalWeight += weights["behavior_analysis"]
	}

	// Threat intelligence score
	if analysis.ThreatIntelligence != nil {
		score := 1.0 - analysis.ThreatIntelligence.ReputationScore // Convert reputation to risk
		weightedSum += score * weights["threat_intelligence"]
		totalWeight += weights["threat_intelligence"]
	}

	if totalWeight == 0 {
		return 0
	}

	return math.Min(1.0, weightedSum/totalWeight)
}

// updateStats updates engine performance statistics
func (e *ThreatDetectionEngine) updateStats(analysis *ComprehensiveThreatAnalysis) {
	e.stats.TotalPredictions++

	// Update average prediction time
	if e.stats.TotalPredictions == 1 {
		e.stats.AveragePredictionTime = analysis.ProcessingTime
	} else {
		// Exponentially weighted moving average
		alpha := 0.1
		e.stats.AveragePredictionTime = time.Duration(
			float64(e.stats.AveragePredictionTime)*(1-alpha) +
				float64(analysis.ProcessingTime)*alpha,
		)
	}

	e.stats.LastUpdate = time.Now()
}

// GetStats returns current engine statistics
func (e *ThreatDetectionEngine) GetStats() *EngineStats {
	e.mutex.RLock()
	defer e.mutex.RUnlock()

	// Create a copy to avoid race conditions
	stats := *e.stats
	return &stats
}

// UpdateModels updates AI models with new training data
func (e *ThreatDetectionEngine) UpdateModels(ctx context.Context, trainingData []*TrainingExample) error {
	e.mutex.Lock()
	defer e.mutex.Unlock()

	for name, model := range e.models {
		if err := model.Update(trainingData); err != nil {
			e.logger.WithError(err).Errorf("Failed to update model %s", name)
			continue
		}

		e.logger.Infof("Successfully updated model %s, new accuracy: %.4f",
			name, model.GetAccuracy())
	}

	// Sync with federated learning if enabled
	if e.federatedClient != nil {
		if err := e.federatedClient.SyncModels(ctx); err != nil {
			e.logger.WithError(err).Error("Failed to sync with federated learning")
		}
	}

	return nil
}

// TrainingExample represents a training example for model updates
type TrainingExample struct {
	Input  *InputVector `json:"input"`
	Output *Prediction  `json:"output"`
	Label  string       `json:"label"` // threat, benign
}

// AIConfig represents AI engine configuration
type AIConfig struct {
	Models struct {
		ThreatDetection    *ModelConfig `yaml:"threat_detection"`
		BehavioralAnalysis *ModelConfig `yaml:"behavioral_analysis"`
		ZeroDayDetection   *ModelConfig `yaml:"zero_day_detection"`
	} `yaml:"models"`

	ThreatIntel struct {
		Enabled bool                `yaml:"enabled"`
		Feeds   []*ThreatFeedConfig `yaml:"feeds"`
	} `yaml:"threat_intel"`

	FederatedLearning struct {
		Enabled   bool   `yaml:"enabled"`
		ServerURL string `yaml:"server_url"`
		NodeID    string `yaml:"node_id"`
	} `yaml:"federated_learning"`
}

// ModelConfig represents configuration for an AI model
type ModelConfig struct {
	ModelPath           string  `yaml:"model_path"`
	ConfidenceThreshold float64 `yaml:"confidence_threshold"`
	BatchSize           int     `yaml:"batch_size"`
	GPUAcceleration     bool    `yaml:"gpu_acceleration"`
}

// ThreatFeedConfig represents threat feed configuration
type ThreatFeedConfig struct {
	Name           string        `yaml:"name"`
	URL            string        `yaml:"url"`
	Format         string        `yaml:"format"`
	UpdateInterval time.Duration `yaml:"update_interval"`
	Priority       int           `yaml:"priority"`
}

// Constructor functions for missing types
func NewTransformerModel(config *ModelConfig) (*TransformerModel, error) {
	if config == nil {
		return nil, fmt.Errorf("transformer model config cannot be nil")
	}

	return &TransformerModel{
		modelPath: config.ModelPath,
		config: &TransformerConfig{
			VocabSize:    10000,
			HiddenSize:   768,
			NumLayers:    12,
			NumHeads:     12,
			MaxSeqLength: 512,
			DropoutRate:  0.1,
			LearningRate: 0.001,
			BatchSize:    config.BatchSize,
		},
		accuracy: 0.0,
		version:  "1.0.0",
	}, nil
}

func NewBehaviorAnalyzer(config *ModelConfig, logger *logrus.Logger) (*BehaviorAnalyzer, error) {
	if config == nil {
		return nil, fmt.Errorf("behavior analyzer config cannot be nil")
	}

	return &BehaviorAnalyzer{
		graphNN: &GraphNeuralNetwork{
			nodes:      make(map[string]*BehaviorNode),
			edges:      make(map[string][]*BehaviorEdge),
			embeddings: make(map[string][]float64),
		},
		logger: logger,
	}, nil
}

// Implement Model interface for TransformerModel
func (tm *TransformerModel) Predict(input *InputVector) (*Prediction, error) {
	tm.mutex.RLock()
	defer tm.mutex.RUnlock()

	// Placeholder implementation
	return &Prediction{
		ThreatScore:    0.5,
		Confidence:     0.8,
		ThreatTypes:    []string{"unknown"},
		ModelVersion:   tm.version,
		ProcessingTime: time.Millisecond * 10,
	}, nil
}

func (tm *TransformerModel) Update(trainingData []*TrainingExample) error {
	tm.mutex.Lock()
	defer tm.mutex.Unlock()

	// Placeholder implementation
	return nil
}

func (tm *TransformerModel) GetAccuracy() float64 {
	tm.mutex.RLock()
	defer tm.mutex.RUnlock()
	return tm.accuracy
}

func (tm *TransformerModel) GetVersion() string {
	tm.mutex.RLock()
	defer tm.mutex.RUnlock()
	return tm.version
}

// Missing constructor functions
func NewThreatIntelligence(config interface{}, logger *logrus.Logger) (*ThreatIntelligence, error) {
	return &ThreatIntelligence{
		feeds:  make(map[string]*ThreatFeed),
		logger: logger,
	}, nil
}

func NewFederatedLearningClient(config interface{}, logger *logrus.Logger) (*FederatedLearningClient, error) {
	return &FederatedLearningClient{
		logger: logger,
	}, nil
}

// Missing methods for BehaviorAnalyzer
func (ba *BehaviorAnalyzer) AnalyzeBehavior(ctx context.Context, data *BehaviorData) (*BehaviorAnalysisResult, error) {
	if data == nil {
		return nil, fmt.Errorf("behavior data cannot be nil")
	}

	// Placeholder implementation
	return &BehaviorAnalysisResult{
		AnomalyScore:      0.5,
		BehaviorPatterns:  []BehaviorPattern{},
		SessionRisk:       0.3,
		DeviceRisk:        0.2,
		TemporalAnomalies: []TemporalAnomaly{},
		GraphAnalysis:     &GraphAnalysisResult{},
	}, nil
}

// Missing methods for ThreatIntelligence
func (ti *ThreatIntelligence) CheckIndicators(ctx context.Context, input *InputVector) (*ThreatIntelligenceResult, error) {
	if input == nil {
		return nil, fmt.Errorf("input vector cannot be nil")
	}

	// Placeholder implementation
	return &ThreatIntelligenceResult{
		MatchedIndicators: []MatchedIndicator{},
		ReputationScore:   0.8,
		RiskLevel:         "low",
		Sources:           []string{},
		Correlations:      []ThreatCorrelation{},
	}, nil
}

// Missing AI analysis types
type ThresholdHistory struct {
	Values       []float64   `json:"values"`
	Timestamps   []time.Time `json:"timestamps"`
	AverageValue float64     `json:"average_value"`
	Variance     float64     `json:"variance"`
}

type TemporalPattern struct {
	ID          string        `json:"id"`
	PatternType string        `json:"pattern_type"`
	Duration    time.Duration `json:"duration"`
	Frequency   float64       `json:"frequency"`
	Confidence  float64       `json:"confidence"`
}

type SpatialPattern struct {
	ID          string             `json:"id"`
	Coordinates [][]float64        `json:"coordinates"`
	ClusterID   string             `json:"cluster_id"`
	Density     float64            `json:"density"`
	Boundaries  map[string]float64 `json:"boundaries"`
}

type FrequencyAnalysis struct {
	Frequencies  map[string]int     `json:"frequencies"`
	TopFrequent  []string           `json:"top_frequent"`
	Distribution map[string]float64 `json:"distribution"`
	Entropy      float64            `json:"entropy"`
}

type MemorySlot struct {
	ID         string                 `json:"id"`
	Type       string                 `json:"type"`
	Data       map[string]interface{} `json:"data"`
	Timestamp  time.Time              `json:"timestamp"`
	Importance float64                `json:"importance"`
}

type SecurityEntity struct {
	ID            string                 `json:"id"`
	Type          string                 `json:"type"`
	Name          string                 `json:"name"`
	Properties    map[string]interface{} `json:"properties"`
	Relationships []string               `json:"relationships"`
}

type ReasoningStep struct {
	ID         string                 `json:"id"`
	Type       string                 `json:"type"`
	Input      map[string]interface{} `json:"input"`
	Output     map[string]interface{} `json:"output"`
	Confidence float64                `json:"confidence"`
	Reasoning  string                 `json:"reasoning"`
}

// Missing constructor functions
func NewAutoencoder(config *AutoencoderConfig) (*Autoencoder, error) {
	if config == nil {
		return nil, fmt.Errorf("autoencoder config cannot be nil")
	}

	return &Autoencoder{
		latentDimension:         config.LatentDimension,
		reconstructionThreshold: config.ReconstructionThreshold,
		trainingHistory:         []*types.TrainingPoint{},
		version:                 "1.0.0",
	}, nil
}

func NewSemanticAnalyzer(config *SemanticAnalysisConfig, logger *logrus.Logger) (*SemanticAnalyzer, error) {
	if config == nil {
		return nil, fmt.Errorf("semantic analysis config cannot be nil")
	}

	return &SemanticAnalyzer{
		nlpProcessor:     &types.NLPProcessor{},
		codeAnalyzer:     &types.CodeAnalyzer{},
		syntaxParser:     &types.SyntaxParser{},
		intentClassifier: &types.IntentClassifier{},
		embeddings:       &types.SemanticEmbeddings{},
	}, nil
}

// Additional missing constructor functions
func NewMemoryAugmentedNetwork(config *MemoryNetworkConfig, logger *logrus.Logger) (*MemoryAugmentedNetwork, error) {
	if config == nil {
		return nil, fmt.Errorf("memory network config cannot be nil")
	}

	return &MemoryAugmentedNetwork{
		memory:       &types.ExternalMemory{},
		controller:   &types.MemoryController{},
		readHeads:    []*types.ReadHead{},
		writeHead:    &types.WriteHead{},
		networkState: &types.NetworkState{},
	}, nil
}

func NewQuantumAnomalyDetector(config interface{}, logger *logrus.Logger) (*QuantumAnomalyDetector, error) {
	if config == nil {
		return nil, fmt.Errorf("quantum detector config cannot be nil")
	}

	return &QuantumAnomalyDetector{}, nil
}

func NewCyberSecurityKnowledgeGraph(config *KnowledgeGraphConfig, logger *logrus.Logger) (*CyberSecurityKnowledgeGraph, error) {
	if config == nil {
		return nil, fmt.Errorf("knowledge graph config cannot be nil")
	}

	return &CyberSecurityKnowledgeGraph{}, nil
}

func NewOnlineLearningSystem(config *OnlineLearningConfig, logger *logrus.Logger) (*OnlineLearningSystem, error) {
	if config == nil {
		return nil, fmt.Errorf("online learning config cannot be nil")
	}

	return &OnlineLearningSystem{}, nil
}

func NewAdaptiveThreshold(config *AdaptiveThresholdConfig, logger *logrus.Logger) (*AdaptiveThreshold, error) {
	if config == nil {
		return nil, fmt.Errorf("adaptive threshold config cannot be nil")
	}

	return &AdaptiveThreshold{}, nil
}

// Add missing methods for Autoencoder
func (a *Autoencoder) DetectAnomaly(input *InputVector) (float64, error) {
	if input == nil {
		return 0.0, fmt.Errorf("input vector cannot be nil")
	}

	// Placeholder implementation - returns a simple anomaly score
	return 0.5, nil
} // Missing methods for FederatedLearningClient
func (flc *FederatedLearningClient) SyncModels(ctx context.Context) error {
	// Placeholder implementation
	return nil
}
