From 3bc859bbd23db1085af94e68f0286cc00f3b5738 Mon Sep 17 00:00:00 2001 From: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com> Date: Thu, 3 Aug 2023 10:18:41 -0400 Subject: [PATCH] Clarify Neural Search ingest pipeline (#4539) Signed-off-by: Fanit Kolchina --- _search-plugins/neural-search.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/_search-plugins/neural-search.md b/_search-plugins/neural-search.md index 4f85b52fa7..aa93a1acd5 100644 --- a/_search-plugins/neural-search.md +++ b/_search-plugins/neural-search.md @@ -19,7 +19,7 @@ The Neural Search plugin comes bundled with OpenSearch. For more information, se ## Ingest data with Neural Search -In order to ingest vectorized documents, you need to create a Neural Search _pipeline_. A pipeline consists of a series of processors that manipulate documents during ingestion, allowing the documents to be vectorized. The following API operation creates a Neural Search pipeline: +In order to ingest vectorized documents, you need to create a Neural Search ingest _pipeline_. An ingest pipeline consists of a series of processors that manipulate documents during ingestion, allowing the documents to be vectorized. The following API operation creates a Neural Search ingest pipeline: ``` PUT _ingest/pipeline/ @@ -29,7 +29,7 @@ In the pipeline request body, The `text_embedding` processor, the only processor ### Path parameter -Use `pipeline_name` to create a name for your Neural Search pipeline. +Use `pipeline_name` to create a name for your Neural Search ingest pipeline. ### Request fields @@ -78,7 +78,7 @@ In order to use the text embedding processor defined in your pipelines, create a ### Example request -The following example request creates an index that attaches to a Neural Search pipeline. Because the index maps to k-NN vector fields, the index setting field `index-knn` is set to `true`. Furthermore, `mapping` settings use [k-NN method definitions]({{site.url}}{{site.baseurl}}/search-plugins/knn/knn-index/#method-definitions) to match the maps defined in the Neural Search pipeline. +The following example request creates an index that attaches to a Neural Search ingest pipeline. Because the index maps to k-NN vector fields, the index setting field `index-knn` is set to `true`. Furthermore, `mapping` settings use [k-NN method definitions]({{site.url}}{{site.baseurl}}/search-plugins/knn/knn-index/#method-definitions) to match the maps defined in the Neural Search ingest pipeline. ```json PUT /my-nlp-index-1 @@ -130,7 +130,7 @@ POST /my-nlp-index-1/_doc } ``` -With the text_embedding processor in place through a Neural Search pipeline, the example indexes "Hello world" as a `text_field` and converts "Hello world" into an associated k-NN vector field. +With the text_embedding processor in place through a Neural Search ingest pipeline, the example indexes "Hello world" as a `text_field` and converts "Hello world" into an associated k-NN vector field. ## Search a neural index