Struct PatternDetector 

pub struct PatternDetector { /* private fields */ }

Pattern detector for triggering memory replay

Monitors incoming memories and detects patterns that should trigger consolidation rather than waiting for fixed intervals.

Implementations

impl PatternDetector

pub fn new() -> Self

pub fn register_memory(&mut self, memory: PatternMemory)

Register a new memory for pattern tracking

Call this when a memory is created to enable pattern detection.

pub fn detect_patterns(&mut self) -> PatternDetectionResult

Detect all patterns and return triggers

This is the main entry point for pattern detection. Call periodically (e.g., every 5 minutes) or after significant events.

pub fn check_salience_spike( &mut self, memory: &PatternMemory, ) -> Option<ReplayTrigger>

Check for salience spike (call when storing a new memory)

Returns Some(trigger) if the memory is surprising enough to warrant immediate replay.

pub fn detect_semantic_clusters( &mut self, similarities: &[(String, String, f32)], ) -> Vec<ReplayTrigger>

Detect semantic clusters from similarity data

Call this with pre-computed similarity data (from vector search). Returns cluster triggers if dense clusters are found.

pub fn check_behavioral_change( &mut self, new_topic: Option<&str>, new_project: Option<&str>, correction_detected: bool, correction_keywords: &[String], ) -> Option<ReplayTrigger>

Check for behavioral pattern change

Call when user behavior signals are detected (from feedback system).

pub fn stats(&self) -> PatternDetectorStats

Get recent pattern detection statistics

pub fn cleanup(&mut self)

Clear processed patterns to prevent memory growth

Removes patterns that have triggered replay (consumed). This is event-based cleanup, not time-based, aligning with the neuroscience-inspired philosophy: patterns persist until processed.

Trait Implementations

impl Default for PatternDetector

fn default() -> Self

Returns the “default value” for a type.