This release adds 4 notable features for engineering teams evaluating rollout.
✓ No known CVEs patched in this version
Topics
+4 more
Summary
AI summaryAdded Anthropic native API support and per-component LLM routing, plus importance‑weighted buffer eviction.
Full changelog
Highlights
- Anthropic native API support — Set
ENGRAM_LLM_PROVIDER=anthropicto use Claude directly. No proxy needed. - Per-component LLM routing — Each component (gate, audit, merge, extract, etc.) can have its own provider, model, and API key. Mix cheap models for triage with strong models for judgment.
- Importance-weighted buffer eviction — Buffer overflow now evicts lowest-importance memories first instead of FIFO. Lessons and procedurals are exempt.
- Consolidation dry-run —
POST /consolidate?dry_run=truepreviews what would be promoted, decayed, and demoted without writing anything. - macOS builds — Pre-built binaries for both x86_64 and aarch64.
What's Changed
Features
ENGRAM_LLM_PROVIDERenv var:openai(default) oranthropic- Per-component env vars:
ENGRAM_{GATE,AUDIT,...}_{URL,KEY,MODEL,PROVIDER} - Tunable params:
ENGRAM_NO_FTS_PENALTY,ENGRAM_HNSW_EF_SEARCH,ENGRAM_TRIAGE_BATCH - Dry-run response includes
would_promote,would_decay,would_demote
Fixes
- Keyword affinity penalty relaxed from 0.7 to 0.85
- Initial importance for lessons/procedurals boosted from 0.5 to 0.75
- Audit interval reduced from 24h to 12h
Full Changelog: https://github.com/kael-bit/engram-rs/blob/main/CHANGELOG.md
Weekly OSS security release digest.
The CVE patches and breaking changes that affected production tools this week. One email, every Sunday.
No spam, unsubscribe anytime.
Share this release
About kael-bit/engram-rs
Hierarchical memory engine for AI agents with automatic decay, promotion, semantic dedup, and self-organizing topic tree. Single Rust binary, zero external dependencies.
Related context
Related tools
Beta — feedback welcome: [email protected]