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Increase maximum side navigation depth by one level (#2454)

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* Break up Text Search guide into multiple pages

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Abdon Pijpelink
2026-06-29 15:37:30 +02:00
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qdrant-landing/content/documentation/tutorials-search-engineering/multi-representation-search.md
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@@ -14,7 +14,7 @@ A document is rarely well-represented by a single embedding. A paper has a title
This tutorial builds retrieval that uses each representation deliberately: named vectors per representation, fused via the Query API and grouped back to the document level for presentation.
This tutorial assumes you've built hybrid (dense plus sparse) search before, that you're comfortable with [named vectors](/documentation/manage-data/vectors/#named-vectors), the [Query API](/documentation/search/hybrid-queries/), Reciprocal Rank Fusion (RRF), and Best Matching 25 (BM25). If hybrid search is new, start with the [hybrid search section of the Text Search guide](/documentation/search/text-search/#combining-semantic-and-lexical-search-with-hybrid-search) first.
This tutorial assumes you've built hybrid (dense plus sparse) search before, that you're comfortable with [named vectors](/documentation/manage-data/vectors/#named-vectors), the [Query API](/documentation/search/hybrid-queries/), Reciprocal Rank Fusion (RRF), and Best Matching 25 (BM25). If hybrid search is new, start with the [hybrid search section of the Text Search guide](/documentation/search/text-search/hybrid-search/) first.
If you'd rather read the code, the [accompanying notebook](https://githubtocolab.com/qdrant/examples/blob/master/multi-representation-search/multi-representation-search.ipynb) walks through this pipeline step by step with eval numbers at each stage.