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3 Commits

Author SHA1 Message Date
cesnimda 50bf6d977a feat(search): hybrid semantic search via RRF fusion (RECOMMENDATIONS #4b)
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The flagship slice (docs/discovery/05): when a free-text query runs and embeddings
are available, fuse lexical top-50 (ts_rank_cd) with vector top-50 (pgvector cosine
over the structured-filtered set) using Reciprocal Rank Fusion. Placed BEFORE the
fuzzy fallback so queries with ZERO lexical hits still get semantic recall — found
and fixed during review (the fuzzy path would otherwise swallow pure-semantic
queries). Exact lexical hits keep winning (rank in both lists); deeper pages fall
through to lexical paging; ANY failure (Ollama down, nothing embedded) silently
degrades to the lexical/fuzzy path — AI can never break search.

LiveDb test proves the recall win: a 'banana' query surfaces an email with no
keyword overlap, ranked first, against real pgvector. 5 LiveDb + full suite green;
format clean.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-02 17:17:41 +02:00
cesnimda 5191dd010f feat(ai): semantic-search backfill + Ollama profile (#30)
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2026-07-02 16:59:30 +02:00
cesnimda 7dbe1469d7 ci: audit batch D — live-db tests + format gate (#23)
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2026-07-02 10:13:12 +02:00