Agent Memory Python v0.2.0

betterdb-agent-memory v0.2.0

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.

What's new in v0.2.0

• Opt-out anonymous usage analytics (PostHog). Disable with
  BETTERDB_TELEMETRY=false (or 0/no/off), or per-instance via options.
  Instance id is an anonymous UUID persisted in Valkey; no payload data is sent.

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.

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Installation

pip install betterdb-agent-memory

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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

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Full changelog

See the repository history for detailed changes.