semantic-memory (RecursiveIntell)

Local-first hybrid semantic search backed by authoritative SQLite state plus a vector sidecar: facts, chunked documents, conversation messages, and episodes searched via BM25 (FTS5) and vector retrieval fused with Reciprocal Rank Fusion, with explainable search.

View source on GitHub

Key takeaways

• 01

  Hybrid BM25 + vector with rank fusion beats either alone

• 02

  Keep an authoritative relational store; treat vectors as a sidecar index

• 03

  Explainable retrieval helps debug why a memory surfaced

Flows built on this research

Memory & Context

Memory Recall: Ranking and Relevance

Make recall surface the right memories: hybrid lexical+semantic search, rank fusion, and explainable retrieval.

4 steps · 90-120 minutes

Memory & Context

Vector vs Markdown Memory: Make the Decision

Choose your memory backend on evidence: when plain files win, when vectors earn their complexity, and how to test it on your own data.

3 steps · 45-60 minutes