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kael-bit/engram-rs

v0.12.1 Feature

This release adds 3 notable features for engineering teams evaluating rollout.

✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

agents ai ai-agents ai-memory claudecode mcp
+4 more
mcp-server openclaw rust sqlite

Summary

AI summary

Introduced a self‑organizing topic tree with hierarchical clustering, LLM naming, and a new 4‑segment resume format.

Full changelog

What's New

Topiary: Self-Organizing Topic Tree

  • Hierarchical memory clustering via k-means with L2-normalized centroids
  • Background worker with 5s debounce, triggered by embed flush, consolidation, and memory deletion
  • LLM-powered topic naming (batch 30, dirty flag tracking)
  • Cached in DB for zero-latency resume reads

4-Segment Resume

  • New format: Core → Recent → Topics → Triggers
  • Topics section: named topic index with drill-down IDs
  • Triggers section: aggregated from all layers

API

  • POST /topic — retrieve full memories for specific topics by ID
  • Resume JSON includes topics and triggers fields

Web UI

  • Resume page adapted to 4-segment format
  • New Topics page with click-to-expand drill-down
  • LLM Usage: added naming and embed_queue descriptions

Bug Fixes

  • Fix triggers not showing in resume (JSON array parse bug)
  • Fix Topics header showing only Working+Buffer counts (now includes Core)
  • Trigger topiary rebuild on memory delete (single + batch)
  • Remove redundant inline trigger tags from Core section

MCP

Full Changelog: https://github.com/kael-bit/engram-rs/compare/v0.12.0...v0.12.1

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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.

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Beta — feedback welcome: [email protected]