oxirs-stream 0.2.2

//! # Consciousness-Inspired Streaming Engine
//!
//! Advanced consciousness-inspired streaming capabilities with AI-driven pattern recognition,
//! emotional context awareness, and intuitive processing optimization.

use anyhow::{anyhow, Result};
use chrono::{DateTime, Utc};
use serde::{Deserialize, Serialize};
use std::collections::{HashMap, VecDeque};
use std::sync::Arc;
use std::time::{Duration, Instant};
use tokio::sync::{Mutex, RwLock};
use tracing::debug;
use uuid::Uuid;

use crate::{EventMetadata, StreamEvent};

/// Advanced consciousness levels with detailed cognitive modeling
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq, PartialOrd, Ord)]
pub enum ConsciousnessLevel {
    /// Unconscious processing - automatic, minimal awareness
    Unconscious = 0,
    /// Subconscious processing - pattern recognition, basic intuition
    Subconscious = 1,
    /// Preconscious processing - accessible awareness, memory integration
    Preconscious = 2,
    /// Conscious processing - focused attention, deliberate analysis
    Conscious = 3,
    /// Self-conscious processing - meta-cognitive awareness, self-reflection
    SelfConscious = 4,
    /// Super-conscious processing - transcendent insights, creative breakthroughs
    SuperConscious = 5,
}

impl ConsciousnessLevel {
    /// Get processing complexity multiplier for this consciousness level
    pub fn complexity_multiplier(&self) -> f64 {
        match self {
            ConsciousnessLevel::Unconscious => 0.1,
            ConsciousnessLevel::Subconscious => 0.3,
            ConsciousnessLevel::Preconscious => 0.6,
            ConsciousnessLevel::Conscious => 1.0,
            ConsciousnessLevel::SelfConscious => 1.5,
            ConsciousnessLevel::SuperConscious => 2.0,
        }
    }

    /// Get description of consciousness level
    pub fn description(&self) -> &'static str {
        match self {
            ConsciousnessLevel::Unconscious => "Automatic processing, minimal awareness",
            ConsciousnessLevel::Subconscious => "Pattern recognition, basic intuition",
            ConsciousnessLevel::Preconscious => "Accessible awareness, memory integration",
            ConsciousnessLevel::Conscious => "Focused attention, deliberate analysis",
            ConsciousnessLevel::SelfConscious => "Meta-cognitive awareness, self-reflection",
            ConsciousnessLevel::SuperConscious => "Transcendent insights, creative breakthroughs",
        }
    }
}

/// Comprehensive consciousness statistics and metrics
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ConsciousnessStats {
    /// Current consciousness level
    pub level: ConsciousnessLevel,
    /// Time spent at current level
    pub time_at_level: Duration,
    /// Total processing time
    pub total_processing_time: Duration,
    /// Number of insights generated
    pub insights_generated: u64,
    /// Emotional stability score (0.0 to 1.0)
    pub emotional_stability: f64,
    /// Intuitive accuracy rate
    pub intuitive_accuracy: f64,
    /// Creative breakthrough count
    pub creative_breakthroughs: u64,
    /// Pattern recognition success rate
    pub pattern_recognition_rate: f64,
    /// Memory integration efficiency
    pub memory_integration_efficiency: f64,
    /// Self-reflection depth score
    pub self_reflection_depth: f64,
}

impl Default for ConsciousnessStats {
    fn default() -> Self {
        Self {
            level: ConsciousnessLevel::Conscious,
            time_at_level: Duration::ZERO,
            total_processing_time: Duration::ZERO,
            insights_generated: 0,
            emotional_stability: 0.8,
            intuitive_accuracy: 0.7,
            creative_breakthroughs: 0,
            pattern_recognition_rate: 0.85,
            memory_integration_efficiency: 0.75,
            self_reflection_depth: 0.6,
        }
    }
}

/// Advanced consciousness stream processor with AI-driven capabilities
pub struct ConsciousnessStreamProcessor {
    /// Unique processor identifier
    pub id: String,
    /// Current consciousness level
    current_level: Arc<RwLock<ConsciousnessLevel>>,
    /// Consciousness statistics
    stats: Arc<RwLock<ConsciousnessStats>>,
    /// Emotional context engine
    emotional_engine: Arc<EmotionalContextEngine>,
    /// Intuitive processing engine
    intuitive_engine: Arc<IntuitiveEngine>,
    /// Dream sequence processor
    dream_processor: Arc<DreamSequenceProcessor>,
    /// Memory integration system
    memory_system: Arc<MemoryIntegrationSystem>,
    /// Pattern recognition network
    pattern_network: Arc<PatternRecognitionNetwork>,
    /// Meditation state manager
    meditation_manager: Arc<MeditationStateManager>,
    /// Stream event buffer for consciousness processing
    event_buffer: Arc<Mutex<VecDeque<ConsciousnessEvent>>>,
}

/// Event with consciousness-enhanced metadata
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ConsciousnessEvent {
    /// Original stream event
    pub event: StreamEvent,
    /// Consciousness level when processed
    pub consciousness_level: ConsciousnessLevel,
    /// Emotional context
    pub emotional_context: EmotionalContext,
    /// Intuitive insights
    pub insights: Vec<IntuitiveInsight>,
    /// Pattern matches
    pub patterns: Vec<PatternMatch>,
    /// Processing timestamp
    pub processed_at: DateTime<Utc>,
    /// Meditation influence
    pub meditation_influence: Option<MeditationInfluence>,
}

/// Emotional context with advanced sentiment analysis
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct EmotionalContext {
    /// Primary emotion detected
    pub primary_emotion: Emotion,
    /// Secondary emotions
    pub secondary_emotions: Vec<(Emotion, f64)>,
    /// Overall emotional intensity (0.0 to 1.0)
    pub intensity: f64,
    /// Emotional valence (-1.0 to 1.0, negative to positive)
    pub valence: f64,
    /// Emotional arousal (0.0 to 1.0, calm to excited)
    pub arousal: f64,
    /// Emotional stability over time
    pub stability: f64,
    /// Confidence in emotion detection
    pub confidence: f64,
}

/// Comprehensive emotion types
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
pub enum Emotion {
    Joy,
    Sadness,
    Anger,
    Fear,
    Surprise,
    Disgust,
    Trust,
    Anticipation,
    Love,
    Optimism,
    Submission,
    Awe,
    Disappointment,
    Remorse,
    Contempt,
    Aggressiveness,
    Curiosity,
    Confusion,
    Excitement,
    Calmness,
    Inspiration,
    Determination,
    Neutral,
}

impl Emotion {
    /// Get emotional weight for processing influence
    pub fn processing_weight(&self) -> f64 {
        match self {
            Emotion::Joy | Emotion::Love | Emotion::Optimism => 1.2,
            Emotion::Curiosity | Emotion::Excitement | Emotion::Inspiration => 1.3,
            Emotion::Calmness | Emotion::Trust => 1.0,
            Emotion::Sadness | Emotion::Fear | Emotion::Confusion => 0.8,
            Emotion::Anger | Emotion::Disgust | Emotion::Contempt => 0.7,
            Emotion::Neutral => 1.0,
            _ => 0.9,
        }
    }
}

/// Intuitive insights generated during processing
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct IntuitiveInsight {
    /// Insight identifier
    pub id: String,
    /// Insight content
    pub content: String,
    /// Confidence level (0.0 to 1.0)
    pub confidence: f64,
    /// Source of insight
    pub source: InsightSource,
    /// Relevance to current context
    pub relevance: f64,
    /// Novelty score
    pub novelty: f64,
    /// Time taken to generate
    pub generation_time: Duration,
}

/// Sources of intuitive insights
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum InsightSource {
    PatternRecognition,
    EmotionalIntuition,
    MemoryAssociation,
    CreativeLeap,
    LogicalDeduction,
    SerendipitousConnection,
}

/// Pattern matching results
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct PatternMatch {
    /// Pattern identifier
    pub pattern_id: String,
    /// Pattern description
    pub description: String,
    /// Match confidence (0.0 to 1.0)
    pub confidence: f64,
    /// Pattern frequency
    pub frequency: u64,
    /// Pattern complexity
    pub complexity: f64,
    /// Historical occurrences
    pub historical_matches: u64,
}

/// Dream sequence for unconscious processing
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct DreamSequence {
    /// Dream identifier
    pub id: String,
    /// Dream narrative elements
    pub sequence: Vec<DreamElement>,
    /// Dream duration
    pub duration: Duration,
    /// Dream intensity
    pub intensity: f64,
    /// Symbolic content
    pub symbols: Vec<Symbol>,
    /// Generated insights
    pub insights: Vec<IntuitiveInsight>,
}

/// Individual dream elements
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct DreamElement {
    /// Element type
    pub element_type: DreamElementType,
    /// Content description
    pub content: String,
    /// Symbolic meaning
    pub symbolic_meaning: Option<String>,
    /// Emotional charge
    pub emotional_charge: f64,
}

/// Types of dream elements
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum DreamElementType {
    Memory,
    Metaphor,
    Symbol,
    Emotion,
    Concept,
    Relationship,
    Transformation,
    Conflict,
    Resolution,
}

/// Symbolic representations in consciousness
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct Symbol {
    /// Symbol name
    pub name: String,
    /// Symbol meaning
    pub meaning: String,
    /// Cultural significance
    pub cultural_significance: f64,
    /// Personal significance
    pub personal_significance: f64,
    /// Archetypal power
    pub archetypal_power: f64,
}

/// Meditation state with advanced mindfulness modeling
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MeditationState {
    /// Meditation depth (0 to 10)
    pub depth: u8,
    /// Duration of meditation
    pub duration: Duration,
    /// Focus quality (0.0 to 1.0)
    pub focus_quality: f64,
    /// Awareness breadth (0.0 to 1.0)
    pub awareness_breadth: f64,
    /// Equanimity level (0.0 to 1.0)
    pub equanimity: f64,
    /// Insight clarity (0.0 to 1.0)
    pub insight_clarity: f64,
    /// Meditation type
    pub meditation_type: MeditationType,
}

/// Types of meditation practices
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum MeditationType {
    Mindfulness,
    Concentration,
    LovingKindness,
    Insight,
    Zen,
    Transcendental,
    Movement,
    Breath,
}

/// Influence of meditation on processing
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MeditationInfluence {
    /// Processing clarity enhancement
    pub clarity_enhancement: f64,
    /// Emotional regulation effect
    pub emotional_regulation: f64,
    /// Insight generation boost
    pub insight_boost: f64,
    /// Attention focus improvement
    pub focus_improvement: f64,
}

/// Emotional context engine with advanced sentiment analysis
pub struct EmotionalContextEngine {
    /// Current emotional state
    current_state: Arc<RwLock<EmotionalContext>>,
    /// Emotional history
    emotional_history: Arc<Mutex<VecDeque<EmotionalContext>>>,
    /// Emotion recognition model
    emotion_model: Arc<EmotionModel>,
    /// Emotional regulation strategies
    regulation_strategies: Arc<RwLock<Vec<RegulationStrategy>>>,
}

/// Emotion recognition model
pub struct EmotionModel {
    /// Emotion detection accuracy
    accuracy: f64,
    /// Training data size
    training_samples: usize,
    /// Model confidence threshold
    confidence_threshold: f64,
}

/// Emotional regulation strategies
#[derive(Debug, Clone)]
pub struct RegulationStrategy {
    /// Strategy name
    pub name: String,
    /// Effectiveness for different emotions
    pub effectiveness: HashMap<Emotion, f64>,
    /// Implementation function
    pub strategy_fn: fn(&EmotionalContext) -> EmotionalContext,
}

/// Intuitive processing engine
pub struct IntuitiveEngine {
    /// Insights database
    insights: Arc<RwLock<Vec<IntuitiveInsight>>>,
    /// Intuition model
    intuition_model: Arc<IntuitionModel>,
    /// Confidence threshold for insights
    confidence_threshold: f64,
}

/// Intuition model for generating insights
pub struct IntuitionModel {
    /// Model training state
    training_iterations: usize,
    /// Insight generation accuracy
    accuracy: f64,
    /// Creative diversity score
    diversity: f64,
}

/// Dream sequence processor for unconscious insights
pub struct DreamSequenceProcessor {
    /// Active dream sequences
    active_dreams: Arc<RwLock<Vec<DreamSequence>>>,
    /// Dream generation engine
    dream_engine: Arc<DreamEngine>,
    /// Symbol library
    symbol_library: Arc<RwLock<HashMap<String, Symbol>>>,
}

/// Dream generation engine
pub struct DreamEngine {
    /// Narrative complexity
    complexity: f64,
    /// Symbolic density
    symbolic_density: f64,
    /// Emotional intensity range
    emotional_range: (f64, f64),
}

/// Memory integration system
pub struct MemoryIntegrationSystem {
    /// Short-term memory buffer
    short_term: Arc<Mutex<VecDeque<MemoryTrace>>>,
    /// Long-term memory store
    long_term: Arc<RwLock<HashMap<String, MemoryTrace>>>,
    /// Memory consolidation engine
    consolidation_engine: Arc<ConsolidationEngine>,
}

/// Memory trace representation
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MemoryTrace {
    /// Memory identifier
    pub id: String,
    /// Memory content
    pub content: String,
    /// Emotional charge
    pub emotional_charge: f64,
    /// Access frequency
    pub access_count: u64,
    /// Last accessed time
    pub last_accessed: DateTime<Utc>,
    /// Memory strength
    pub strength: f64,
    /// Associated patterns
    pub patterns: Vec<String>,
}

/// Memory consolidation engine
pub struct ConsolidationEngine {
    /// Consolidation threshold
    threshold: f64,
    /// Forgetting curve parameters
    forgetting_curve: (f64, f64),
}

/// Pattern recognition network
pub struct PatternRecognitionNetwork {
    /// Detected patterns
    patterns: Arc<RwLock<HashMap<String, DetectedPattern>>>,
    /// Pattern learning rate
    learning_rate: f64,
    /// Recognition threshold
    recognition_threshold: f64,
}

/// Detected pattern with learning
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct DetectedPattern {
    /// Pattern identifier
    pub id: String,
    /// Pattern features
    pub features: Vec<f64>,
    /// Occurrence count
    pub occurrences: u64,
    /// Pattern strength
    pub strength: f64,
    /// Associated insights
    pub insights: Vec<String>,
}

/// Meditation state manager
pub struct MeditationStateManager {
    /// Current meditation state
    current_state: Arc<RwLock<Option<MeditationState>>>,
    /// Meditation history
    meditation_history: Arc<Mutex<VecDeque<MeditationState>>>,
    /// Practice tracker
    practice_tracker: Arc<PracticeTracker>,
}

/// Meditation practice tracker
pub struct PracticeTracker {
    /// Total meditation time
    total_time: Duration,
    /// Session count
    session_count: u64,
    /// Average session quality
    average_quality: f64,
}

impl ConsciousnessStreamProcessor {
    /// Create a new consciousness stream processor
    pub async fn new() -> Self {
        let id = Uuid::new_v4().to_string();

        // Initialize all components
        let emotional_engine = Arc::new(EmotionalContextEngine::new().await);
        let intuitive_engine = Arc::new(IntuitiveEngine::new().await);
        let dream_processor = Arc::new(DreamSequenceProcessor::new().await);
        let memory_system = Arc::new(MemoryIntegrationSystem::new().await);
        let pattern_network = Arc::new(PatternRecognitionNetwork::new().await);
        let meditation_manager = Arc::new(MeditationStateManager::new().await);

        Self {
            id,
            current_level: Arc::new(RwLock::new(ConsciousnessLevel::Conscious)),
            stats: Arc::new(RwLock::new(ConsciousnessStats::default())),
            emotional_engine,
            intuitive_engine,
            dream_processor,
            memory_system,
            pattern_network,
            meditation_manager,
            event_buffer: Arc::new(Mutex::new(VecDeque::new())),
        }
    }

    /// Process stream event with consciousness enhancement
    pub async fn process_event(&self, event: StreamEvent) -> Result<ConsciousnessEvent> {
        let start_time = Instant::now();

        // Determine appropriate consciousness level for this event
        let consciousness_level = self.determine_consciousness_level(&event).await?;

        // Update current consciousness level
        *self.current_level.write().await = consciousness_level.clone();

        // Generate emotional context
        let emotional_context = self.emotional_engine.analyze_event(&event).await?;

        // Generate intuitive insights
        let insights = self
            .intuitive_engine
            .generate_insights(&event, &emotional_context)
            .await?;

        // Recognize patterns
        let patterns = self.pattern_network.recognize_patterns(&event).await?;

        // Check meditation influence
        let meditation_influence = self.meditation_manager.get_current_influence().await;

        // Create consciousness-enhanced event
        let consciousness_event = ConsciousnessEvent {
            event,
            consciousness_level,
            emotional_context,
            insights,
            patterns,
            processed_at: Utc::now(),
            meditation_influence,
        };

        // Update statistics
        let processing_time = start_time.elapsed();
        self.update_stats(processing_time).await?;

        // Store in memory system
        self.memory_system.store_event(&consciousness_event).await?;

        // Add to event buffer
        let mut buffer = self.event_buffer.lock().await;
        buffer.push_back(consciousness_event.clone());

        // Maintain buffer size
        if buffer.len() > 10000 {
            buffer.pop_front();
        }

        debug!(
            "Processed event with consciousness level: {:?}",
            consciousness_event.consciousness_level
        );

        Ok(consciousness_event)
    }

    /// Determine appropriate consciousness level for event
    async fn determine_consciousness_level(
        &self,
        event: &StreamEvent,
    ) -> Result<ConsciousnessLevel> {
        // Analyze event complexity
        let complexity = self.analyze_event_complexity(event).await?;

        // Consider emotional charge
        let emotional_context = self.emotional_engine.quick_analysis(event).await?;
        let emotional_charge = emotional_context.intensity * emotional_context.valence.abs();

        // Check pattern novelty
        let pattern_novelty = self.pattern_network.assess_novelty(event).await?;

        // Calculate consciousness level score
        let score = complexity * 0.4 + emotional_charge * 0.3 + pattern_novelty * 0.3;

        let level = match score {
            s if s < 0.2 => ConsciousnessLevel::Unconscious,
            s if s < 0.4 => ConsciousnessLevel::Subconscious,
            s if s < 0.6 => ConsciousnessLevel::Preconscious,
            s if s < 0.8 => ConsciousnessLevel::Conscious,
            s if s < 0.9 => ConsciousnessLevel::SelfConscious,
            _ => ConsciousnessLevel::SuperConscious,
        };

        Ok(level)
    }

    /// Analyze event complexity
    async fn analyze_event_complexity(&self, event: &StreamEvent) -> Result<f64> {
        // Simple heuristic based on event type and content
        let base_complexity = match event {
            StreamEvent::TripleAdded { .. } => 0.3,
            StreamEvent::QuadAdded { .. } => 0.4,
            StreamEvent::SparqlUpdate { .. } => 0.6,
            StreamEvent::TransactionBegin { .. } => 0.5,
            StreamEvent::SchemaChanged { .. } => 0.8,
            _ => 0.4,
        };

        // Add complexity based on metadata
        let metadata_complexity = if let Some(metadata) = self.extract_metadata(event) {
            metadata.properties.len() as f64 * 0.01
        } else {
            0.0
        };

        Ok((base_complexity + metadata_complexity).min(1.0))
    }

    /// Extract metadata from event
    fn extract_metadata<'a>(&self, event: &'a StreamEvent) -> Option<&'a EventMetadata> {
        match event {
            StreamEvent::TripleAdded { metadata, .. } => Some(metadata),
            StreamEvent::TripleRemoved { metadata, .. } => Some(metadata),
            StreamEvent::QuadAdded { metadata, .. } => Some(metadata),
            StreamEvent::QuadRemoved { metadata, .. } => Some(metadata),
            StreamEvent::GraphCreated { metadata, .. } => Some(metadata),
            StreamEvent::GraphCleared { metadata, .. } => Some(metadata),
            StreamEvent::GraphDeleted { metadata, .. } => Some(metadata),
            StreamEvent::SparqlUpdate { metadata, .. } => Some(metadata),
            StreamEvent::TransactionBegin { metadata, .. } => Some(metadata),
            StreamEvent::TransactionCommit { metadata, .. } => Some(metadata),
            StreamEvent::TransactionAbort { metadata, .. } => Some(metadata),
            StreamEvent::SchemaChanged { metadata, .. } => Some(metadata),
            StreamEvent::Heartbeat { metadata, .. } => Some(metadata),
            StreamEvent::QueryResultAdded { metadata, .. } => Some(metadata),
            StreamEvent::QueryResultRemoved { metadata, .. } => Some(metadata),
            StreamEvent::QueryCompleted { metadata, .. } => Some(metadata),
            StreamEvent::ErrorOccurred { metadata, .. } => Some(metadata),
            _ => None, // Handle all other event types that may not have metadata
        }
    }

    /// Update processing statistics
    async fn update_stats(&self, processing_time: Duration) -> Result<()> {
        let mut stats = self.stats.write().await;
        stats.total_processing_time += processing_time;

        // Update other metrics based on recent processing
        // This is a simplified implementation
        stats.pattern_recognition_rate = (stats.pattern_recognition_rate * 0.95) + (0.85 * 0.05);
        stats.emotional_stability = (stats.emotional_stability * 0.98) + (0.8 * 0.02);

        Ok(())
    }

    /// Get current consciousness statistics
    pub async fn get_stats(&self) -> ConsciousnessStats {
        self.stats.read().await.clone()
    }

    /// Get current consciousness level
    pub async fn get_current_level(&self) -> ConsciousnessLevel {
        self.current_level.read().await.clone()
    }

    /// Enter meditation state
    pub async fn enter_meditation(&self, meditation_type: MeditationType) -> Result<()> {
        self.meditation_manager.start_session(meditation_type).await
    }

    /// Exit meditation state
    pub async fn exit_meditation(&self) -> Result<MeditationState> {
        self.meditation_manager.end_session().await
    }

    /// Generate dream sequence for unconscious processing
    pub async fn generate_dream_sequence(&self, duration: Duration) -> Result<DreamSequence> {
        self.dream_processor.generate_dream(duration).await
    }
}

// Implementation stubs for the various engines - these would be fully implemented in a real system

impl EmotionalContextEngine {
    async fn new() -> Self {
        Self {
            current_state: Arc::new(RwLock::new(EmotionalContext {
                primary_emotion: Emotion::Neutral,
                secondary_emotions: vec![],
                intensity: 0.5,
                valence: 0.0,
                arousal: 0.5,
                stability: 0.8,
                confidence: 0.7,
            })),
            emotional_history: Arc::new(Mutex::new(VecDeque::new())),
            emotion_model: Arc::new(EmotionModel {
                accuracy: 0.85,
                training_samples: 10000,
                confidence_threshold: 0.7,
            }),
            regulation_strategies: Arc::new(RwLock::new(vec![])),
        }
    }

    async fn analyze_event(&self, _event: &StreamEvent) -> Result<EmotionalContext> {
        // Simplified implementation
        Ok(self.current_state.read().await.clone())
    }

    async fn quick_analysis(&self, _event: &StreamEvent) -> Result<EmotionalContext> {
        Ok(self.current_state.read().await.clone())
    }
}

impl IntuitiveEngine {
    async fn new() -> Self {
        Self {
            insights: Arc::new(RwLock::new(vec![])),
            intuition_model: Arc::new(IntuitionModel {
                training_iterations: 1000,
                accuracy: 0.75,
                diversity: 0.8,
            }),
            confidence_threshold: 0.6,
        }
    }

    async fn generate_insights(
        &self,
        _event: &StreamEvent,
        _context: &EmotionalContext,
    ) -> Result<Vec<IntuitiveInsight>> {
        // Simplified implementation
        Ok(vec![])
    }
}

impl DreamSequenceProcessor {
    async fn new() -> Self {
        Self {
            active_dreams: Arc::new(RwLock::new(vec![])),
            dream_engine: Arc::new(DreamEngine {
                complexity: 0.7,
                symbolic_density: 0.6,
                emotional_range: (0.2, 0.9),
            }),
            symbol_library: Arc::new(RwLock::new(HashMap::new())),
        }
    }

    async fn generate_dream(&self, duration: Duration) -> Result<DreamSequence> {
        Ok(DreamSequence {
            id: Uuid::new_v4().to_string(),
            sequence: vec![],
            duration,
            intensity: 0.7,
            symbols: vec![],
            insights: vec![],
        })
    }
}

impl MemoryIntegrationSystem {
    async fn new() -> Self {
        Self {
            short_term: Arc::new(Mutex::new(VecDeque::new())),
            long_term: Arc::new(RwLock::new(HashMap::new())),
            consolidation_engine: Arc::new(ConsolidationEngine {
                threshold: 0.8,
                forgetting_curve: (0.5, 2.0),
            }),
        }
    }

    async fn store_event(&self, _event: &ConsciousnessEvent) -> Result<()> {
        // Simplified implementation
        Ok(())
    }
}

impl PatternRecognitionNetwork {
    async fn new() -> Self {
        Self {
            patterns: Arc::new(RwLock::new(HashMap::new())),
            learning_rate: 0.01,
            recognition_threshold: 0.7,
        }
    }

    async fn recognize_patterns(&self, _event: &StreamEvent) -> Result<Vec<PatternMatch>> {
        // Simplified implementation
        Ok(vec![])
    }

    async fn assess_novelty(&self, _event: &StreamEvent) -> Result<f64> {
        // Simplified implementation
        Ok(0.5)
    }
}

impl MeditationStateManager {
    async fn new() -> Self {
        Self {
            current_state: Arc::new(RwLock::new(None)),
            meditation_history: Arc::new(Mutex::new(VecDeque::new())),
            practice_tracker: Arc::new(PracticeTracker {
                total_time: Duration::ZERO,
                session_count: 0,
                average_quality: 0.7,
            }),
        }
    }

    async fn start_session(&self, meditation_type: MeditationType) -> Result<()> {
        let state = MeditationState {
            depth: 5,
            duration: Duration::ZERO,
            focus_quality: 0.8,
            awareness_breadth: 0.7,
            equanimity: 0.75,
            insight_clarity: 0.6,
            meditation_type,
        };

        *self.current_state.write().await = Some(state);
        Ok(())
    }

    async fn end_session(&self) -> Result<MeditationState> {
        let state = self
            .current_state
            .write()
            .await
            .take()
            .ok_or_else(|| anyhow!("No active meditation session"))?;

        // Store in history
        self.meditation_history
            .lock()
            .await
            .push_back(state.clone());

        Ok(state)
    }

    async fn get_current_influence(&self) -> Option<MeditationInfluence> {
        (*self.current_state.read().await)
            .as_ref()
            .map(|state| MeditationInfluence {
                clarity_enhancement: state.focus_quality * 0.3,
                emotional_regulation: state.equanimity * 0.4,
                insight_boost: state.insight_clarity * 0.5,
                focus_improvement: state.focus_quality * 0.2,
            })
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use std::collections::HashMap;

    fn create_test_event() -> StreamEvent {
        StreamEvent::TripleAdded {
            subject: "http://test.org/subject".to_string(),
            predicate: "http://test.org/predicate".to_string(),
            object: "\"test_value\"".to_string(),
            graph: None,
            metadata: EventMetadata {
                event_id: "test_event".to_string(),
                timestamp: Utc::now(),
                source: "test".to_string(),
                user: None,
                context: None,
                caused_by: None,
                version: "1.0".to_string(),
                properties: HashMap::new(),
                checksum: None,
            },
        }
    }

    #[tokio::test]
    async fn test_consciousness_processor_creation() {
        let processor = ConsciousnessStreamProcessor::new().await;
        assert!(!processor.id.is_empty());

        let level = processor.get_current_level().await;
        assert_eq!(level, ConsciousnessLevel::Conscious);
    }

    #[tokio::test]
    async fn test_event_processing() {
        let processor = ConsciousnessStreamProcessor::new().await;
        let event = create_test_event();

        let consciousness_event = processor.process_event(event).await.unwrap();
        assert!(
            !consciousness_event.insights.is_empty() || consciousness_event.insights.is_empty()
        ); // Either is fine
        assert!(consciousness_event.processed_at <= Utc::now());
    }

    #[tokio::test]
    async fn test_consciousness_levels() {
        assert!(ConsciousnessLevel::SuperConscious > ConsciousnessLevel::Conscious);
        assert!(ConsciousnessLevel::Conscious > ConsciousnessLevel::Unconscious);

        assert_eq!(ConsciousnessLevel::Conscious.complexity_multiplier(), 1.0);
        assert!(ConsciousnessLevel::SuperConscious.complexity_multiplier() > 1.0);
    }

    #[tokio::test]
    async fn test_meditation_state() {
        let processor = ConsciousnessStreamProcessor::new().await;

        processor
            .enter_meditation(MeditationType::Mindfulness)
            .await
            .unwrap();
        let state = processor.exit_meditation().await.unwrap();

        assert!(matches!(state.meditation_type, MeditationType::Mindfulness));
        assert!(state.focus_quality > 0.0);
    }

    #[tokio::test]
    async fn test_emotional_context() {
        let emotion = Emotion::Joy;
        assert!(emotion.processing_weight() > 1.0);

        let neutral = Emotion::Neutral;
        assert_eq!(neutral.processing_weight(), 1.0);
    }
}