betterdb-agent-memory v0.1.0

Python port of @betterdb/agent-memory. Long-term memory tier for AI agents
backed by Valkey Search — semantic recall with recency/importance ranking,
scoped capacity eviction, and consolidation. Pairs with betterdb-agent-cache.

Requires Valkey 8+ with the valkey-search module (vector index support).
Works with ElastiCache for Valkey, Memorystore for Valkey, and MemoryDB.

Built on betterdb-valkey-search-kit
and betterdb-agent-cache.

Installation

pip install betterdb-agent-memory

What's included

MemoryStore (long-term tier)

| Method | Description |
|---|---|
| ensure_index() | Create or attach to the memory vector index |
| remember(...) | Persist a memory with embedding, scope, tags, and importance |
| recall(...) | Semantic recall ranked by similarity, recency, and importance |
| recall_by_vector(...) | KNN recall from a precomputed vector |
| reinforce(id) | Bump importance / recency on an existing memory |
| forget(...) | Delete memories by id or filter |
| consolidate(...) | Merge and summarize related memories |
| get(id) / list(...) | Read-only fetch and scoped, paginated listing |
| stats() | Doc count, evictions, and live config |

Scoped capacity eviction, live config refresh, and discovery are built in.

AgentMemory facade

Convenience facade over betterdb-agent-cache combining the exact-match cache
tier with the long-term memory tier.

Observability

• OpenTelemetry spans on every memory operation
• Prometheus metrics for recall latency and eviction counts

Full changelog

See the repository history for detailed changes.