RAG Engine

Unified search across memory layers.

Strategies

Strategy	Description	Best For
fts	Full-text search via FTS5	Short queries, keywords
mib	Binary embedding similarity	Semantic search
hybrid	FTS5 + MIB with scoring	General purpose
auto	Adaptive (fts for short, hybrid for long)	Default

Usage

from rag.engine import RAGEngine

engine = RAGEngine()

# Search
results = await engine.search(
    query="database architecture",
    user_id="u1",
    strategy="hybrid",
    limit=10
)

# Ingest
await engine.ingest(
    content="PostgreSQL is used for production...",
    user_id="u1",
    page_id=1
)

Scoring

Results scored by Scorer with weights:

• Relevance: RRF score + optional binary score
• Novelty: ITS-inspired surprise (rare = more novel)
• Type boost: bonus for relevant wiki types