Add long-term user memory system
...
Architecture:
- navi/memory/store.py: MemoryStore backed by SQLite (memory_facts,
memory_summary, session_memory_state tables in navi.db)
- navi/memory/extractor.py: LLM-based fact extraction from sessions +
summary regeneration (triggered after session goes idle >30 min)
- Fact upsert uses UNIQUE(category, key) — same key always overwrites,
no duplicates or stale contradictions
- Keyword search across category + key + value (LIKE-based, no extra deps)
Context injection:
- Memory summary injected as an ephemeral system message on every LLM call
via Agent._with_memory() — never persisted to session.context
Tools (all profiles):
- memory_search(query): keyword search against fact DB; persona instructs
model to call it at session start and before personal-context questions
- memory_forget(key, category?): delete a specific fact on user request
Extraction trigger:
- On new session creation, fire-and-forget background task checks all
sessions idle >30 min with unprocessed messages → runs extraction
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Eugene Sukhodolskiy
committed
on 9 Apr
