Implements five of the six enhancements from docs/kb-enhancements-proposal.htm,
closing the retrieval-quality gap identified in the qmd review.
- Cross-encoder reranking: new kb/reranker.py loads an optional reranking
model at startup (KB_RERANK_ENABLED, KB_RERANKER_MODEL,
KB_RERANK_CANDIDATES). Search degrades gracefully to plain hybrid
retrieval when the model is absent. Exposed via a "rerank" block in
/status, a rerank flag on search, and --no-rerank in the CLI.
- RRF rank fusion: FTS and vector lists now merge by reciprocal rank
fusion with a top-rank bonus, replacing the old score blend. Scores are
comparable across queries.
- Bench harness and explain traces: kb bench runs a query fixture against
each backend and reports precision@k, recall and MRR. --explain returns a
per-result score breakdown.
- Tag context descriptions: tags carry an optional one-line description
(kb tag-describe), returned as tag_contexts with search results. Adds a
tags.description column migration.
- Structured data ingestion: .json/.yaml/.toml files ingest as text via the
new "data" doc type, pretty-printing minified JSON before chunking.
Query expansion (proposal item 5) is deliberately left out pending bench
results. Requires engine v3.3.0.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
steve
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