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Address findings from a code-bot adversarial review of the hybrid-search
materials:
- `hybrid-formula-decay/` (all 7 language sources + http.md +
`_description.md`): wrap the decay term in `MultExpression(mult=[0.1, ...])`
in every language. Previously the snippets summed `$score` with
`ExpDecayExpression` directly, modeling the failure mode the docs
explicitly warn against (un-weighted decay crowds out small RRF scores).
Also document the `defaults` requirement and the recommended datetime
payload index in `_description.md`. Build validated across all 6 SDKs.
- `hybrid-rrf/go.go`: add `Limit: qdrant.PtrOf(uint64(20))` to both
prefetches so the Go snippet matches the other language tabs.
- `hybrid-queries.md`:
- Reframe the weighted-RRF intro to drop "semantic search model
understands meaning better than a simple keyword matcher". On
SciFact (the corpus in the companion notebook) BM25 actually beats
dense, so the universal claim was contradicted by our own data.
- Clarify that the notebook provides a tuning helper to adapt to a
train/val split, not that it demonstrates the split itself.
- Add a one-line note that Qdrant uses zero-based rank positions so
readers can verify the RRF formula against actual scores.
- Apply brand-voice fixes: Title Case on "Multi-Stage Queries" and
"Re-Scoring Examples", replace "all the above techniques" with
"all of these techniques".
`generated/*.md` regenerated via `./docker.sh ./generate-md.py`.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>