use chrono::{Duration, Utc};
use std::path::PathBuf;
use super::knowledge::KnowledgeFact;
use super::memory_archive::{ArchiveConfig, MemoryStore};
const DEFAULT_DECAY_RATE: f32 = 0.01;
const LOW_CONFIDENCE_THRESHOLD: f32 = 0.3;
const STALE_DAYS: i64 = 30;
pub const DEFAULT_RECLAIM_HEADROOM_PCT: f32 = 0.25;
const SPACING_GAIN: f32 = 0.5;
const MIN_STABILITY_DAYS: f32 = 1.0;
const CONFIDENCE_FLOOR: f32 = 0.05;
pub const DEFAULT_BASE_STABILITY_DAYS: f32 = 90.0;
#[derive(Debug, Clone, Copy, PartialEq, Eq, Default)]
pub enum ForgettingModel {
#[default]
Ebbinghaus,
Linear,
}
impl ForgettingModel {
pub fn parse(s: &str) -> Self {
match s.trim().to_lowercase().as_str() {
"linear" => Self::Linear,
_ => Self::Ebbinghaus,
}
}
pub fn as_str(self) -> &'static str {
match self {
Self::Ebbinghaus => "ebbinghaus",
Self::Linear => "linear",
}
}
}
#[derive(Debug, Clone)]
pub struct LifecycleConfig {
pub decay_rate_per_day: f32,
pub low_confidence_threshold: f32,
pub stale_days: i64,
pub consolidation_similarity: f32,
pub forgetting_model: ForgettingModel,
pub base_stability_days: f32,
pub archetype_aware_decay: bool,
pub prune_unretrieved_after_days: Option<i64>,
pub reclaim_headroom_pct: f32,
pub reclaim_enabled: bool,
}
impl Default for LifecycleConfig {
fn default() -> Self {
Self {
decay_rate_per_day: DEFAULT_DECAY_RATE,
low_confidence_threshold: LOW_CONFIDENCE_THRESHOLD,
stale_days: STALE_DAYS,
consolidation_similarity: 0.85,
forgetting_model: ForgettingModel::default(),
base_stability_days: DEFAULT_BASE_STABILITY_DAYS,
archetype_aware_decay: false,
prune_unretrieved_after_days: None,
reclaim_headroom_pct: DEFAULT_RECLAIM_HEADROOM_PCT,
reclaim_enabled: true,
}
}
}
impl LifecycleConfig {
pub fn from_policy(policy: &crate::core::memory_policy::MemoryPolicy) -> Self {
Self {
decay_rate_per_day: policy.lifecycle.decay_rate,
low_confidence_threshold: policy.lifecycle.low_confidence_threshold,
stale_days: policy.lifecycle.stale_days,
consolidation_similarity: policy.lifecycle.similarity_threshold,
forgetting_model: ForgettingModel::parse(&policy.lifecycle.forgetting_model),
base_stability_days: policy.lifecycle.base_stability_days,
archetype_aware_decay: policy.lifecycle.archetype_aware_decay,
prune_unretrieved_after_days: policy.lifecycle.prune_unretrieved_after_days,
reclaim_headroom_pct: policy.lifecycle.reclaim_headroom_pct,
reclaim_enabled: policy.lifecycle.reclaim_enabled,
}
}
}
#[derive(Debug, Default)]
pub struct LifecycleReport {
pub decayed_count: usize,
pub consolidated_count: usize,
pub archived_count: usize,
pub compacted_count: usize,
pub remaining_facts: usize,
}
pub fn apply_confidence_decay(facts: &mut [KnowledgeFact], config: &LifecycleConfig) -> usize {
let now = Utc::now();
let mut count = 0;
for fact in facts.iter_mut() {
if !fact.is_current() {
continue;
}
if let Some(valid_until) = fact.valid_until
&& valid_until < now
&& fact.confidence > 0.1
{
fact.confidence = 0.1;
count += 1;
continue;
}
let days_since_confirmed = now.signed_duration_since(fact.last_confirmed).num_days() as f32;
if days_since_confirmed <= 0.0 {
continue;
}
let days_since_retrieved = fact
.last_retrieved
.map_or(3650.0, |t| now.signed_duration_since(t).num_days() as f32);
let retrieval_count = fact.retrieval_count as f32;
let net_feedback = i64::from(fact.feedback_up) - i64::from(fact.feedback_down);
let base_stability = if config.archetype_aware_decay {
config.base_stability_days * fact.archetype.stability_multiplier()
} else {
config.base_stability_days
};
let new_confidence = match config.forgetting_model {
ForgettingModel::Ebbinghaus => ebbinghaus_confidence(
fact.confidence,
days_since_confirmed,
days_since_retrieved,
retrieval_count,
net_feedback,
base_stability,
),
ForgettingModel::Linear => linear_confidence(
fact.confidence,
days_since_confirmed,
days_since_retrieved,
retrieval_count,
net_feedback,
config.decay_rate_per_day,
),
};
if (new_confidence - fact.confidence).abs() > 0.001 {
fact.confidence = new_confidence;
count += 1;
}
}
if count > 0 && config.forgetting_model == ForgettingModel::Ebbinghaus {
crate::core::introspect::tick("power_law_decay");
}
count
}
fn ebbinghaus_confidence(
confidence: f32,
days_since_confirmed: f32,
days_since_retrieved: f32,
retrieval_count: f32,
net_feedback: i64,
base_stability_days: f32,
) -> f32 {
let elapsed = days_since_confirmed.min(days_since_retrieved).max(0.0);
let spacing = 1.0 + SPACING_GAIN * retrieval_count;
let feedback_mult = match net_feedback.cmp(&0) {
std::cmp::Ordering::Greater => 1.0 + (net_feedback as f32).ln_1p(),
std::cmp::Ordering::Less => 1.0 / (1.0 + (net_feedback.unsigned_abs() as f32).ln_1p()),
std::cmp::Ordering::Equal => 1.0,
};
let stability = (base_stability_days * spacing * feedback_mult).max(MIN_STABILITY_DAYS);
let retention = (-(f64::from(elapsed)) / f64::from(stability)).exp() as f32;
(confidence * retention).max(CONFIDENCE_FLOOR)
}
fn linear_confidence(
confidence: f32,
days_since_confirmed: f32,
days_since_retrieved: f32,
retrieval_count: f32,
net_feedback: i64,
decay_rate_per_day: f32,
) -> f32 {
let freq_protect = 1.0 / (1.0 + retrieval_count.ln_1p());
let recency_protect = (1.0 - (days_since_retrieved / 30.0).min(1.0)).max(0.0);
let protect = (freq_protect * (1.0 - 0.5 * recency_protect)).max(0.05);
let feedback_factor = match net_feedback.cmp(&0) {
std::cmp::Ordering::Greater => 1.0 / (1.0 + (net_feedback as f32).ln_1p()),
std::cmp::Ordering::Less => (1.0 + (net_feedback.unsigned_abs() as f32).ln_1p()).min(4.0),
std::cmp::Ordering::Equal => 1.0,
};
let decay = decay_rate_per_day * days_since_confirmed * protect * feedback_factor;
(confidence - decay).max(CONFIDENCE_FLOOR)
}
pub fn consolidate_similar(facts: &mut Vec<KnowledgeFact>, similarity_threshold: f32) -> usize {
let mut to_remove: std::collections::HashSet<usize> = std::collections::HashSet::new();
let mut category_groups: std::collections::HashMap<String, Vec<usize>> =
std::collections::HashMap::new();
for (i, f) in facts.iter().enumerate() {
if f.is_current() {
category_groups
.entry(f.category.clone())
.or_default()
.push(i);
}
}
for indices in category_groups.values() {
for (pos_a, &i) in indices.iter().enumerate() {
if to_remove.contains(&i) {
continue;
}
for &j in &indices[pos_a + 1..] {
if to_remove.contains(&j) {
continue;
}
let sim = word_similarity(&facts[i].value, &facts[j].value);
if sim >= similarity_threshold {
if facts[i].confidence >= facts[j].confidence {
facts[i].confirmation_count += facts[j].confirmation_count;
if facts[j].last_confirmed > facts[i].last_confirmed {
facts[i].last_confirmed = facts[j].last_confirmed;
}
to_remove.insert(j);
} else {
facts[j].confirmation_count += facts[i].confirmation_count;
if facts[i].last_confirmed > facts[j].last_confirmed {
facts[j].last_confirmed = facts[i].last_confirmed;
}
to_remove.insert(i);
break;
}
}
}
}
}
let count = to_remove.len();
let mut sorted: Vec<usize> = to_remove.into_iter().collect();
sorted.sort_unstable();
for idx in sorted.into_iter().rev() {
facts.remove(idx);
}
count
}
pub fn compact(
facts: &mut Vec<KnowledgeFact>,
config: &LifecycleConfig,
) -> (usize, Vec<KnowledgeFact>) {
let mut archived: Vec<KnowledgeFact> = Vec::new();
let now = Utc::now();
let stale_threshold = now - Duration::days(config.stale_days);
let mut to_archive: Vec<usize> = Vec::new();
for (i, fact) in facts.iter().enumerate() {
let recently_retrieved = fact
.last_retrieved
.is_some_and(|t| now.signed_duration_since(t).num_days() < 14);
let frequently_retrieved = fact.retrieval_count >= 5;
if fact.confidence < config.low_confidence_threshold {
to_archive.push(i);
continue;
}
if let Some(days) = config.prune_unretrieved_after_days {
let cutoff = now - Duration::days(days);
if fact.last_confirmed < cutoff
&& fact.retrieval_count == 0
&& fact.last_retrieved.is_none()
&& fact.confirmation_count <= 1
{
to_archive.push(i);
continue;
}
}
if fact.last_confirmed < stale_threshold
&& fact.confirmation_count <= 1
&& fact.confidence < 0.5
&& !recently_retrieved
&& !frequently_retrieved
{
to_archive.push(i);
}
}
to_archive.sort_unstable();
to_archive.dedup();
for idx in to_archive.into_iter().rev() {
archived.push(facts.remove(idx));
}
(archived.len(), archived)
}
pub fn run_lifecycle(
facts: &mut Vec<KnowledgeFact>,
config: &LifecycleConfig,
) -> Result<LifecycleReport, String> {
let decayed = apply_confidence_decay(facts, config);
let consolidated = consolidate_similar(facts, config.consolidation_similarity);
let (compacted, archived) = compact(facts, config);
if !archived.is_empty() {
archive_facts(&archived)?;
}
Ok(LifecycleReport {
decayed_count: decayed,
consolidated_count: consolidated,
archived_count: archived.len(),
compacted_count: compacted,
remaining_facts: facts.len(),
})
}
pub fn archive_facts(facts: &[KnowledgeFact]) -> Result<(), String> {
crate::core::memory_archive::archive_items(
MemoryStore::Facts,
None,
facts,
&ArchiveConfig::from_env(),
)
.map(|_| ())
}
fn in_project<T>(project_root: &str, f: impl FnOnce() -> T) -> T {
crate::core::policy::runtime::REQUEST_PROJECT.sync_scope(
std::cell::RefCell::new(Some(PathBuf::from(project_root))),
f,
)
}
pub fn restore_archive(
project_root: &str,
archive_path: &str,
) -> Result<Vec<KnowledgeFact>, String> {
in_project(project_root, || {
crate::core::memory_archive::restore_items(std::path::Path::new(archive_path))
})
}
pub fn list_archives(project_root: &str) -> Vec<PathBuf> {
in_project(project_root, || {
crate::core::memory_archive::list_archives(MemoryStore::Facts, None)
})
}
pub fn reachable_archives(project_root: &str, cfg: &ArchiveConfig) -> Vec<PathBuf> {
in_project(project_root, || {
crate::core::memory_archive::reachable_archives(MemoryStore::Facts, None, cfg)
})
}
fn word_similarity(a: &str, b: &str) -> f32 {
let a_lower = a.to_lowercase();
let b_lower = b.to_lowercase();
let a_words: std::collections::HashSet<&str> = a_lower.split_whitespace().collect();
let b_words: std::collections::HashSet<&str> = b_lower.split_whitespace().collect();
if a_words.is_empty() && b_words.is_empty() {
return 1.0;
}
let intersection = a_words.intersection(&b_words).count();
let union = a_words.union(&b_words).count();
if union == 0 {
return 0.0;
}
intersection as f32 / union as f32
}
#[cfg(test)]
pub mod tests {
use super::*;
use crate::core::knowledge::KnowledgeArchetype;
fn with_temp_data_dir<T>(f: impl FnOnce() -> T) -> T {
let _lock = crate::core::data_dir::test_env_lock();
let dir = std::env::temp_dir().join(format!(
"lctx-lifecycle-{}-{}",
std::process::id(),
Utc::now().timestamp_nanos_opt().unwrap_or(0)
));
let _ = std::fs::create_dir_all(&dir);
crate::test_env::set_var("LEAN_CTX_DATA_DIR", dir.to_str().unwrap());
let out = f();
crate::test_env::remove_var("LEAN_CTX_DATA_DIR");
let _ = std::fs::remove_dir_all(&dir);
out
}
fn make_fact(category: &str, key: &str, value: &str, confidence: f32) -> KnowledgeFact {
KnowledgeFact {
anchors: Vec::new(),
review: None,
capture: Default::default(),
origin: crate::core::knowledge::FactOrigin::Local,
category: category.to_string(),
key: key.to_string(),
value: value.to_string(),
source_session: "s1".to_string(),
confidence,
created_at: Utc::now(),
last_confirmed: Utc::now(),
retrieval_count: 0,
last_retrieved: None,
valid_from: Some(Utc::now()),
valid_until: None,
supersedes: None,
confirmation_count: 1,
feedback_up: 0,
feedback_down: 0,
last_feedback: None,
privacy: crate::core::memory_boundary::FactPrivacy::default(),
sensitivity: crate::core::sensitivity::SensitivityLevel::default(),
imported_from: None,
archetype: KnowledgeArchetype::default(),
fidelity: None,
revision_count: 0,
status: None,
validity: None,
}
}
fn make_old_fact(
category: &str,
key: &str,
value: &str,
confidence: f32,
days_old: i64,
) -> KnowledgeFact {
let past = Utc::now() - Duration::days(days_old);
KnowledgeFact {
anchors: Vec::new(),
review: None,
capture: Default::default(),
origin: crate::core::knowledge::FactOrigin::Local,
category: category.to_string(),
key: key.to_string(),
value: value.to_string(),
source_session: "s1".to_string(),
confidence,
created_at: past,
last_confirmed: past,
retrieval_count: 0,
last_retrieved: None,
valid_from: Some(past),
valid_until: None,
supersedes: None,
confirmation_count: 1,
feedback_up: 0,
feedback_down: 0,
last_feedback: None,
privacy: crate::core::memory_boundary::FactPrivacy::default(),
sensitivity: crate::core::sensitivity::SensitivityLevel::default(),
imported_from: None,
archetype: KnowledgeArchetype::default(),
fidelity: None,
revision_count: 0,
status: None,
validity: None,
}
}
#[test]
fn decay_reduces_confidence() {
let config = LifecycleConfig::default();
let mut facts = vec![make_old_fact("arch", "db", "PostgreSQL", 0.9, 10)];
let count = apply_confidence_decay(&mut facts, &config);
assert_eq!(count, 1);
assert!(facts[0].confidence < 0.9);
assert!(facts[0].confidence > 0.7);
}
#[test]
fn archetype_aware_decay_protects_evidence() {
let mut evidence = make_old_fact("arch", "db", "PostgreSQL", 0.9, 30);
evidence.archetype = KnowledgeArchetype::Architecture;
let mut inference = make_old_fact("pref", "style", "tabs", 0.9, 30);
inference.archetype = KnowledgeArchetype::Preference;
let off = LifecycleConfig::default();
let mut a = vec![evidence.clone(), inference.clone()];
apply_confidence_decay(&mut a, &off);
assert!(
(a[0].confidence - a[1].confidence).abs() < 1e-6,
"flag off → archetype ignored, equal decay"
);
let on = LifecycleConfig {
archetype_aware_decay: true,
..Default::default()
};
let mut b = vec![evidence, inference];
apply_confidence_decay(&mut b, &on);
assert!(
b[0].confidence > b[1].confidence,
"evidence {} should outlast inference {}",
b[0].confidence,
b[1].confidence
);
}
#[test]
fn decay_skips_recent_facts() {
let config = LifecycleConfig::default();
let mut facts = vec![make_fact("arch", "db", "PostgreSQL", 0.9)];
let count = apply_confidence_decay(&mut facts, &config);
assert_eq!(count, 0);
}
#[test]
fn feedback_steers_decay_keep_vs_forget() {
let config = LifecycleConfig::default();
let mut praised = make_old_fact("arch", "loved", "keep me", 0.9, 10);
praised.feedback_up = 5;
let mut panned = make_old_fact("arch", "hated", "forget me", 0.9, 10);
panned.feedback_down = 5;
let neutral = make_old_fact("arch", "meh", "neutral", 0.9, 10);
let mut facts = vec![praised, panned, neutral];
apply_confidence_decay(&mut facts, &config);
let (praised_c, panned_c, neutral_c) = (
facts[0].confidence,
facts[1].confidence,
facts[2].confidence,
);
assert!(
praised_c > neutral_c,
"praised {praised_c} should outlast neutral {neutral_c}"
);
assert!(
neutral_c > panned_c,
"neutral {neutral_c} should outlast panned {panned_c}"
);
assert!(panned_c >= 0.05);
}
#[test]
fn spacing_effect_protects_frequently_retrieved() {
let config = LifecycleConfig::default();
let rarely = make_old_fact("arch", "rare", "x", 0.9, 20);
let mut often = make_old_fact("arch", "often", "y", 0.9, 20);
often.retrieval_count = 20;
let mut facts = vec![rarely, often];
apply_confidence_decay(&mut facts, &config);
assert!(
facts[1].confidence > facts[0].confidence,
"spacing effect: rehearsed {} should outlast un-rehearsed {}",
facts[1].confidence,
facts[0].confidence
);
}
#[test]
fn ebbinghaus_decay_is_deterministic() {
let config = LifecycleConfig::default();
let mut a = vec![make_old_fact("arch", "k", "v", 0.8, 15)];
let mut b = a.clone();
apply_confidence_decay(&mut a, &config);
apply_confidence_decay(&mut b, &config);
assert_eq!(a[0].confidence, b[0].confidence);
}
#[test]
fn linear_model_still_available() {
let config = LifecycleConfig {
forgetting_model: ForgettingModel::Linear,
..Default::default()
};
let mut facts = vec![make_old_fact("arch", "db", "PostgreSQL", 0.9, 10)];
let count = apply_confidence_decay(&mut facts, &config);
assert_eq!(count, 1);
assert!(facts[0].confidence < 0.9 && facts[0].confidence > 0.7);
}
#[test]
fn forgetting_model_parses() {
assert_eq!(ForgettingModel::parse("linear"), ForgettingModel::Linear);
assert_eq!(
ForgettingModel::parse("ebbinghaus"),
ForgettingModel::Ebbinghaus
);
assert_eq!(
ForgettingModel::parse("garbage"),
ForgettingModel::Ebbinghaus
);
}
#[test]
fn consolidate_similar_facts() {
let mut facts = vec![
make_fact("arch", "db", "uses PostgreSQL database", 0.8),
make_fact("arch", "db2", "uses PostgreSQL database system", 0.6),
make_fact("ops", "deploy", "docker compose up", 0.9),
];
let count = consolidate_similar(&mut facts, 0.7);
assert!(count > 0, "Should consolidate similar facts");
assert!(facts.len() < 3);
}
#[test]
fn consolidate_keeps_different_categories() {
let mut facts = vec![
make_fact("arch", "db", "PostgreSQL", 0.8),
make_fact("ops", "db", "PostgreSQL", 0.8),
];
let count = consolidate_similar(&mut facts, 0.9);
assert_eq!(count, 0, "Different categories should not consolidate");
}
#[test]
fn compact_removes_low_confidence() {
let config = LifecycleConfig::default();
let mut facts = vec![
make_fact("arch", "db", "PostgreSQL", 0.9),
make_fact("arch", "cache", "Redis", 0.1),
];
let (count, archived) = compact(&mut facts, &config);
assert_eq!(count, 1);
assert_eq!(facts.len(), 1);
assert_eq!(archived.len(), 1);
assert_eq!(archived[0].key, "cache");
}
#[test]
fn compact_is_quality_only_and_ignores_capacity() {
let config = LifecycleConfig::default();
let mut facts: Vec<KnowledgeFact> = (0..8)
.map(|i| make_fact("finding", &format!("k{i}"), &format!("value {i}"), 0.8))
.collect();
let (count, archived) = compact(&mut facts, &config);
assert_eq!(count, 0, "quality compact must not evict for capacity");
assert!(archived.is_empty());
assert_eq!(facts.len(), 8);
}
#[test]
fn run_lifecycle_never_reclaims_capacity() {
with_temp_data_dir(|| {
let config = LifecycleConfig::default();
let mut facts: Vec<KnowledgeFact> = (0..450)
.map(|i| {
make_fact(
"finding",
&format!("k{i}"),
&format!("distinct finding number {i} about module m{i}"),
0.8,
)
})
.collect();
facts[0].valid_until = Some(Utc::now() - Duration::seconds(1));
let report = run_lifecycle(&mut facts, &config).expect("lifecycle succeeds");
assert_eq!(report.archived_count, 0);
assert_eq!(facts.len(), 450);
assert_eq!(report.remaining_facts, 450);
});
}
#[test]
fn prune_unretrieved_archives_old_never_retrieved_facts() {
let config = LifecycleConfig {
prune_unretrieved_after_days: Some(30),
..Default::default()
};
let mut facts = vec![make_old_fact("arch", "x", "still confident", 0.9, 60)];
let (count, archived) = compact(&mut facts, &config);
assert_eq!(count, 1);
assert_eq!(archived.len(), 1);
assert!(facts.is_empty());
}
#[test]
fn prune_unretrieved_is_off_by_default() {
let config = LifecycleConfig::default();
let mut facts = vec![make_old_fact("arch", "x", "still confident", 0.9, 60)];
let (count, _) = compact(&mut facts, &config);
assert_eq!(count, 0);
assert_eq!(facts.len(), 1);
}
#[test]
fn prune_unretrieved_keeps_retrieved_and_confirmed_facts() {
let config = LifecycleConfig {
prune_unretrieved_after_days: Some(30),
..Default::default()
};
let mut retrieved = make_old_fact("arch", "used", "v", 0.9, 60);
retrieved.retrieval_count = 3;
let mut confirmed = make_old_fact("arch", "confirmed", "v", 0.9, 60);
confirmed.confirmation_count = 4;
let mut facts = vec![retrieved, confirmed];
let (count, _) = compact(&mut facts, &config);
assert_eq!(count, 0, "retrieved or repeatedly-confirmed facts are kept");
assert_eq!(facts.len(), 2);
}
#[test]
fn compact_archives_stale_facts() {
let config = LifecycleConfig::default();
let mut facts = vec![
make_fact("arch", "db", "PostgreSQL", 0.9),
make_old_fact("arch", "old", "ancient thing", 0.4, 60),
];
let (count, archived) = compact(&mut facts, &config);
assert_eq!(count, 1);
assert_eq!(archived[0].key, "old");
}
#[test]
fn full_lifecycle_run() {
with_temp_data_dir(|| {
let config = LifecycleConfig::default();
let mut facts = vec![
make_fact("arch", "db", "PostgreSQL", 0.9),
make_fact("arch", "cache", "Redis", 0.8),
make_old_fact("arch", "old1", "thing1", 0.2, 50),
make_old_fact("arch", "old2", "thing2", 0.15, 60),
make_fact("ops", "deploy", "docker compose", 0.7),
];
let report = run_lifecycle(&mut facts, &config).expect("lifecycle succeeds");
assert!(report.remaining_facts < 5, "the stale facts are archived");
assert!(report.decayed_count > 0 || report.compacted_count > 0);
});
}
#[test]
fn word_similarity_identical() {
assert!((word_similarity("hello world", "hello world") - 1.0).abs() < 0.01);
}
#[test]
fn word_similarity_partial() {
let sim = word_similarity("uses PostgreSQL database", "PostgreSQL database system");
assert!(sim >= 0.5, "Expected >= 0.5 but got {sim}");
assert!(sim < 1.0);
}
#[test]
fn word_similarity_different() {
let sim = word_similarity("Redis cache", "Docker compose");
assert!(sim < 0.1);
}
}