0df5ec11d1
- subconscious.rs: use .get(fork_point..) instead of direct slice to avoid panic when fork_point > entries.len() - dmn.rs: batch all output injections (surface, reflection, thalamus) under a single agent lock acquisition instead of three separate ones - dmn.rs: use Store::cached() instead of Store::load() when rendering surfaced memories - Add scoring persistence analysis notes Co-Authored-By: Proof of Concept <poc@bcachefs.org>
1.5 KiB
1.5 KiB
Memory Scoring Persistence — Analysis (2026-04-07)
Problem
Scores computed by score_memories_incremental are written to
ConversationEntry::Memory::score (in-memory, serialized to
conversation.log) but never written back to the Store. This means:
Node.last_scoredstays at 0 — every restart re-scores everythingscore_weight()inops.rs:304-313exists but is never called- Scoring is wasted work on every session start
Fix
In mind/mod.rs scoring completion handler (currently ~line 341-352),
after writing scores to entries, also persist to Store:
if let Ok(ref scores) = result {
let mut ag = agent.lock().await;
// Write to entries (already done)
for (key, weight) in scores { ... }
// NEW: persist to Store
let store_arc = Store::cached().await.ok();
if let Some(arc) = store_arc {
let mut store = arc.lock().await;
for (key, weight) in scores {
store.score_weight(key, *weight as f32);
}
store.save().ok();
}
}
This calls score_weight() which updates node.weight and sets
node.last_scored = now(). The staleness check in
score_memories_incremental (learn.rs:325) then skips recently-scored
nodes on subsequent runs.
Files
src/mind/mod.rs:341-352— scoring completion handler (add Store write)src/hippocampus/store/ops.rs:304-313—score_weight()(exists, unused)src/subconscious/learn.rs:322-326— staleness check (already correct)src/hippocampus/store/types.rs:219—Node.last_scoredfield