Blog (draft): Hybrid search ranking — Part 1 of 2 - #3652
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Part 1 of a 2-part "Search result quality & ordering" series: hybrid alpha, fusion, reranking, and the Boost API on a DocChunk RAG example. Snippets checked against the current Python client and a local Weaviate. Open publish TODOs (hero image, Boost GA/version stamp, publish date, Part 2 link) tracked inline; opening as draft.
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Address review of the ranking post: concrete RAG opening, question/keyword headings, three Mermaid diagrams (pipeline, hybrid fusion, over-fetch flow), inline jargon definitions, an faq block, and the primary keyword "hybrid search ranking" in title/description/headings/slug. Code snippets and the load-bearing facts are unchanged; Boost GA/version TODOs preserved.
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Revised after review (2nd commit). Changes: concrete RAG failure as the opening hook; question/keyword-framed headings; three Mermaid diagrams (retrieval→ranking→presentation pipeline, hybrid fusion, over-fetch→rerank→boost flow); inline definitions for jargon (cross-encoder, bi-encoder, RRF, min-max normalization, over-fetch); an |
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Part 1 of a 2-part "Search result quality & ordering" series
A practical, runnable tour of Weaviate's query-time ranking dials, threaded through a documentation / RAG
DocChunkexample (chunked pages, near-duplicates, stale versions — "relevant-ish but wrong order"):alpha— the vector-vs-keyword weight (default0.75), with an alpha-sweep snippet + a compact BM25 sidebar (per-propertyANDgotcha).relativeScoreFusion(the server default) vs.rankedFusion(RRF,k=60hardcoded); when to pick which.hybrid → rerank → boostquery and a symptom → tool decision table. Teases Part 2.~2,050 words. Every snippet was checked against the current Python client; the alpha-sweep, both fusion modes, and the Boost call ran against a local Weaviate 1.38.
Open before publish (tracked as inline TODOs — opening as draft)
./img/hero.png) + restore theimage:frontmatter linePart 2 to follow as a separate PR.