repoGitHubTrust 82 · PrimaryPublished 16d agoLive · 16d ago

qyiun666/MemHop

Embedded long-term memory database for AI agents & LLM apps. Six-layer cognitive architecture, knowledge graph, hybrid BM25 + vector search, sleep-time memory consolidation. One .meh file, zero infrastructure, pure Go.

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Why these links exist

Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.

PossiblePossibly related (embedding) · 63%MemoryOps AI: governed memory runtime for LLM agents with deletion-leakage evals and context admission [P] →
PossiblePossibly related (embedding) · 62%The biggest problem with AI memory isn't recall—it's stale facts [P] →
PossiblePossibly related (embedding) · 57%Architecting memory and storage in the AI era →

Covers

newsMemoryOps AI: governed memory runtime for LLM agents with deletion-leakage evals and context admission [P]newsThe biggest problem with AI memory isn't recall—it's stale facts [P]

Covers (incoming)

newsArchitecting memory and storage in the AI era

Related across the graph

newsArchitecting memory and storage in the AI era newsThe biggest problem with AI memory isn't recall—it's stale facts [P]newsMemoryOps AI: governed memory runtime for LLM agents with deletion-leakage evals and context admission [P]

Topics