AgentsMedium impactFor DevGitHub AI Agents · May 30, 2026

Pain-weighted hybrid memory for LLM agents. FTS5 + sqlite-vec + RRF + KG. MIT, open source. Published benchmarks.

totobusnello/memoria-nox

Memoria-nox is an open-source, pain-weighted hybrid memory system for LLM agents combining FTS5, sqlite-vec, RRF, and knowledge graphs with published benchmarks.
Signal strength3.7/5·GitHub AI Agents

Memoria-nox is an open-source, pain-weighted hybrid memory system for LLM agents combining FTS5, sqlite-vec, RRF, and knowledge graphs with published benchmarks.

TL;DR

Memoria-nox is an open-source, pain-weighted hybrid memory system for LLM agents combining FTS5, sqlite-vec, RRF, and knowledge graphs with published benchmarks.

What happened

A new TypeScript-based hybrid memory system called memoria-nox has been released, integrating full-text search, vector search, reciprocal rank fusion, and knowledge graphs to enhance memory capabilities for large language model agents.

Why it matters

Hybrid memory systems addressing weighted relevance improve the performance and contextual understanding of LLM agents, enabling more effective multi-agent systems and better long-term knowledge retention.

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