retoor
af080fe68e
- Approval: re-prompt unknown answers (max 3), shell-only affirmative guidance recovery; destructive actions stay strict - GoalVerifier subagent with strict JSON verdicts, bounded follow-up rounds, nonzero exit plus open turn on unverified one-shots - Retrieval eval (Hit@K/MRR/nDCG/Context Precision), FTS cascade with title weighting, query/read event logging, --eval-retrieval CLI - Supervisor caps (8 parallel, 64 records) and scheduler hardening (4 fires/tick, per-schedule lease, stated misfire policy) - Sandbox box resource trio: 2g/2.0/256 at create, best-effort update for existing boxes, rm -f recovery pointer - Research archive: 12 subjects, 667 sources, 27 conclusions; suites 979 + 16 green
52 lines
2.6 KiB
Markdown
52 lines
2.6 KiB
Markdown
# SQLite FTS5 Extension
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## Metadata
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| Field | Value |
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| Institute | Molodetz Institute — Research & Retrieval Division |
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| Subject | sqlite-rag-hybrid-search |
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| Document type | Source Dossier |
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| Tier | 1 |
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| Source title | SQLite FTS5 Extension |
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| Source URL | https://www.sqlite.org/fts5.html |
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| Source publisher / author | SQLite (Hipp Wyrick and Co.) |
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| Source type | vendor docs |
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| Source date (published) | Unknown — not stated (living documentation page) |
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| Date researched | 2026-10-18 |
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| Researched by | tai (agent), model: Muse Spark, on behalf of retoor |
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| Research method | direct page fetch |
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| Confidence | High |
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| Status | Active |
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## Summary
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The authoritative FTS5 reference, read for the BM25 tuning surface: k1 and b are hard-coded (1.2, 0.75), scores are negated so ascending sort puts best first, and per-column weights passed as extra bm25() arguments are the only ranking knob. It also documents prefix queries, NEAR, and boolean operators tai does not currently use.
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## Key findings
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- "k1 and b are both constants, hard-coded at 1.2 and 0.75 respectively."
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- "By passing extra real value arguments to the bm25() SQL function, each column of the table may be assigned a different weight", with phrase frequency computed as the weight-weighted sum across columns; missing trailing weights default to 1.0.
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- FTS5 "multiplies the result by -1 before returning it, ensuring that better matches are assigned numerically lower scores", so plain ORDER BY bm25() ascending is correct (tai does this).
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- Query syntax supports prefix queries, initial-token queries, NEAR, column filters, and boolean operators; tai uses only quoted-phrase AND across the title and body columns.
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## Pros / strengths
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- Primary specification of the exact ranking function tai runs; settles what is tunable (column weights, query shape) and what is not (k1, b).
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- Negation note confirms tai's sort direction is right and needs no change.
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## Cons / limitations / caveats
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- Reference documentation, not tuning guidance; it gives no recommended weights or query-shape advice for small corpora.
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- No discussion of evaluation; measurement guidance comes from the IR sources in this subject.
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## Relevance to tai
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Defines the entire dependency-free tuning backlog: title-over-body column weights first, then OR-fallback and prefix queries for the strict-AND recall gap. Everything else (k1/b, stemming beyond porter) is fixed by the engine, which bounds the roadmap and kills any proposal to "tune BM25 parameters" in FTS5.
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## Changelog
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| Date | Change |
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| 2026-10-18 | Initial dossier created. |
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