Changelog

0.2.0 (April 11, 2026)

new features

• HNSW ANN index — approximate nearest neighbor via hnswlib, 100% recall@10, 0.09ms search, scales to 1M vectors
• 98.1% R@5 on LongMemEval — new SOTA, beating MemPalace (96.6%) and all others
• multi-backend embeddings — Voyage AI, OpenAI, Google Gemini alongside local MLX/sentence-transformers
• Voyage cloud reranker — rerank-2.5/2.5-lite alongside local cross-encoder
• SSE MCP transport — engram serve --mcp-sse for HTTP clients
• CLI: reembed — re-embed all memories after switching embedding model
• CLI: watch — poll a directory for new files and auto-ingest
• CLI: export/import — portable JSON backup with optional embeddings
• web auth — bearer token auth via web.auth_token config
• Docker — Dockerfile + docker-compose.yml
• 72 pytest tests across 6 modules
• 13 examples — setup guides + Python scripts for every major feature
• GitHub Actions CI — tests on push/PR, auto-publish to PyPI on release
• PyPI — pip install engram-memory-system
• docs site — MkDocs Material at engram-memory.dev

fixes

• ANN count tracks active ids (hnswlib mark_delete doesn't decrement)
• debug mode with rerank=False no longer crashes (unbound reranked variable)
• 9-factor importance (was incorrectly documented as 7-factor)
• 63 MCP tools (was incorrectly documented as 52)

0.1.0 (April 9, 2026)

initial release.

• 5-channel hybrid retrieval (dense + BM25 + graph BFS + Hopfield + RRF)
• memory layers (working, episodic, semantic, procedural, codebase)
• entity graph with co-occurrence relationships
• surprise-based importance scoring at write time
• retention regularization (L2/Huber/elastic)
• deep MLP reranker trained on access patterns
• dream cycle consolidation
• drift detection and auto-fix
• pattern extraction from sessions
• negative knowledge
• enriched embeddings (A-Mem)
• memory evolution
• intent-aware retrieval (MAGMA)
• trust-weighted decay
• 63 MCP tools
• web dashboard with neural map
• MLX GPU embedding backend