From d460489989fdb02b30fb150dd68180b9d3e564a4 Mon Sep 17 00:00:00 2001 From: Quentin Pradet Date: Wed, 6 Nov 2024 16:33:45 +0400 Subject: [PATCH] Fix knn_search deprecation message (#3103) (cherry picked from commit 48e2d9de9de2911b8cb1cf715e4bc0a2b1f4b827) --- output/schema/schema.json | 4 ++-- specification/_global/knn_search/KnnSearchRequest.ts | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/output/schema/schema.json b/output/schema/schema.json index 8ef6a264ac..462f823a20 100644 --- a/output/schema/schema.json +++ b/output/schema/schema.json @@ -8880,7 +8880,7 @@ } }, "deprecation": { - "description": "", + "description": "The kNN search API has been replaced by the `knn` option in the search API.", "version": "8.4.0" }, "description": "Run a knn search.\n\nNOTE: The kNN search API has been replaced by the `knn` option in the search API.\n\nPerform a k-nearest neighbor (kNN) search on a dense_vector field and return the matching documents.\nGiven a query vector, the API finds the k closest vectors and returns those documents as search hits.\n\nElasticsearch uses the HNSW algorithm to support efficient kNN search.\nLike most kNN algorithms, HNSW is an approximate method that sacrifices result accuracy for improved search speed.\nThis means the results returned are not always the true k closest neighbors.\n\nThe kNN search API supports restricting the search using a filter.\nThe search will return the top k documents that also match the filter query.", @@ -26940,7 +26940,7 @@ ] }, "deprecation": { - "description": "", + "description": "The kNN search API has been replaced by the `knn` option in the search API.", "version": "8.4.0" }, "description": "Run a knn search.\n\nNOTE: The kNN search API has been replaced by the `knn` option in the search API.\n\nPerform a k-nearest neighbor (kNN) search on a dense_vector field and return the matching documents.\nGiven a query vector, the API finds the k closest vectors and returns those documents as search hits.\n\nElasticsearch uses the HNSW algorithm to support efficient kNN search.\nLike most kNN algorithms, HNSW is an approximate method that sacrifices result accuracy for improved search speed.\nThis means the results returned are not always the true k closest neighbors.\n\nThe kNN search API supports restricting the search using a filter.\nThe search will return the top k documents that also match the filter query.", diff --git a/specification/_global/knn_search/KnnSearchRequest.ts b/specification/_global/knn_search/KnnSearchRequest.ts index 2e826c9c82..c708a05440 100644 --- a/specification/_global/knn_search/KnnSearchRequest.ts +++ b/specification/_global/knn_search/KnnSearchRequest.ts @@ -39,7 +39,7 @@ import { Query } from './_types/Knn' * The search will return the top k documents that also match the filter query. * @rest_spec_name knn_search * @availability stack since=8.0.0 stability=experimental - * @deprecated 8.4.0 + * @deprecated 8.4.0 The kNN search API has been replaced by the `knn` option in the search API. * @doc_tag search */ export interface Request extends RequestBase {