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YantrikDB

v0.6.5 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

agent-memory ai-agents anthropic claude-code cognitive-memory database
+12 more
embeddings hnsw knowledge-graph llm llm-memory mcp memory persistent-memory python rust semantic-memory vector-db

Summary

AI summary

Promotes insert_vector and encrypt_embedding_pub to public APIs enabling per-row HNSW backfill on replication followers.

Full changelog

v0.6.5 — public insert_vector + encrypt_embedding_pub for piecewise HNSW backfill

Promotes two methods from pub(crate) to pub:

  • pub fn insert_vector(&self, rid, embedding): wraps vec_index.write().insert
  • pub fn encrypt_embedding_pub(&self, blob): wraps the existing pub(crate) encrypt_embedding

RFC 022 §2 (yantrikos/yantrikdb-server). Server's replication followers
now do per-row HNSW insert in backfill instead of full rebuild_vec_index
at the end of every batch. Drops follower recall lag from
minutes-to-hours to seconds, and starts working for encrypted clusters
for the first time (was 100% broken because encrypt_embedding was pub(crate)).

Empirical motivation: 2026-05-01 cross-lane skill_recall/skill_get bug,
diagnosed via 90-second test against live cluster — leader is already
RYW-consistent; follower-side full rebuild was the actual lag source.

Purely additive API. 1319 tests pass. No behavior change for existing
callers. Composable with v0.6.4 read connection pool.

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Related context

Earlier breaking changes

  • v0.7.20 `correct()` now mutates in place, preserving rid and adding revision history (BREAKING CHANGE).
  • v0.7.9 Pure-additive; existing engines keep English models on v0.1.0.

Beta — feedback welcome: [email protected]