From 1183a35e3543a53dc0c2c6cbf4ba29e86193700f Mon Sep 17 00:00:00 2001 From: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com> Date: Mon, 15 Jul 2024 14:36:28 -0400 Subject: [PATCH] Remove model requirement from hybrid search documentation (#7511) * Remove model requirement from hybrid search documentation Signed-off-by: Fanit Kolchina * Review comment Signed-off-by: Fanit Kolchina * Revised sentence Signed-off-by: Fanit Kolchina * Update _search-plugins/hybrid-search.md Co-authored-by: Nathan Bower Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com> --------- Signed-off-by: Fanit Kolchina Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com> Co-authored-by: Nathan Bower Signed-off-by: Sander van de Geijn --- _query-dsl/compound/hybrid.md | 6 +----- _search-plugins/hybrid-search.md | 2 +- 2 files changed, 2 insertions(+), 6 deletions(-) diff --git a/_query-dsl/compound/hybrid.md b/_query-dsl/compound/hybrid.md index e573d17676..22b3a17fc1 100644 --- a/_query-dsl/compound/hybrid.md +++ b/_query-dsl/compound/hybrid.md @@ -12,11 +12,7 @@ You can use a hybrid query to combine relevance scores from multiple queries int ## Example -Before using a `hybrid` query, you must set up a machine learning (ML) model, ingest documents, and configure a search pipeline with a [`normalization-processor`]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/normalization-processor/). - -To learn how to set up an ML model, see [Choosing a model]({{site.url}}{{site.baseurl}}/ml-commons-plugin/integrating-ml-models/#choosing-a-model). - -Once you set up an ML model, learn how to use the `hybrid` query by following the steps in [Using hybrid search]({{site.url}}{{site.baseurl}}/search-plugins/hybrid-search/#using-hybrid-search). +Learn how to use the `hybrid` query by following the steps in [Using hybrid search]({{site.url}}{{site.baseurl}}/search-plugins/hybrid-search/#using-hybrid-search). For a comprehensive example, follow the [Neural search tutorial]({{site.url}}{{site.baseurl}}/ml-commons-plugin/semantic-search#tutorial). diff --git a/_search-plugins/hybrid-search.md b/_search-plugins/hybrid-search.md index b0fb4d5bef..7f08d63d0f 100644 --- a/_search-plugins/hybrid-search.md +++ b/_search-plugins/hybrid-search.md @@ -12,7 +12,7 @@ Introduced 2.11 Hybrid search combines keyword and neural search to improve search relevance. To implement hybrid search, you need to set up a [search pipeline]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/index/) that runs at search time. The search pipeline you'll configure intercepts search results at an intermediate stage and applies the [`normalization_processor`]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/normalization-processor/) to them. The `normalization_processor` normalizes and combines the document scores from multiple query clauses, rescoring the documents according to the chosen normalization and combination techniques. **PREREQUISITE**
-Before using hybrid search, you must set up a text embedding model. For more information, see [Choosing a model]({{site.url}}{{site.baseurl}}/ml-commons-plugin/integrating-ml-models/#choosing-a-model). +To follow this example, you must set up a text embedding model. For more information, see [Choosing a model]({{site.url}}{{site.baseurl}}/ml-commons-plugin/integrating-ml-models/#choosing-a-model). If you have already generated text embeddings, ingest the embeddings into an index and skip to [Step 4](#step-4-configure-a-search-pipeline). {: .note} ## Using hybrid search