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Add documentation about setting a default model for neural search #5121
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Add documentation about setting a default model for neural search
kolchfa-aws 2d22bd6
Add new processor to the processor list
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More tweaks
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Refactor search pipeline documentation
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Refactor retrieving search pipelines
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Add working examples
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Add responses to documentation
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Merge branch 'main' into default-neural-model
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Update _search-plugins/search-pipelines/neural-query-enricher.md
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156 changes: 156 additions & 0 deletions
156
_search-plugins/search-pipelines/creating-search-pipeline.md
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,156 @@ | ||
| --- | ||
| layout: default | ||
| title: Creating a search pipeline | ||
| nav_order: 10 | ||
| has_children: false | ||
| parent: Search pipelines | ||
| grand_parent: Search | ||
| --- | ||
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| # Creating a search pipeline | ||
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| Search pipelines are stored in the cluster state. To create a search pipeline, you must configure an ordered list of processors in your OpenSearch cluster. You can have more than one processor of the same type in the pipeline. Each processor has a `tag` identifier that distinguishes it from the others. Tagging a specific processor can be helpful when debugging error messages, especially if you add multiple processors of the same type. | ||
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| #### Example request | ||
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| The following request creates a search pipeline with a `filter_query` request processor that uses a term query to return only public messages and a response processor that renames the field `message` to `notification`: | ||
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| ```json | ||
| PUT /_search/pipeline/my_pipeline | ||
| { | ||
| "request_processors": [ | ||
| { | ||
| "filter_query" : { | ||
| "tag" : "tag1", | ||
| "description" : "This processor is going to restrict to publicly visible documents", | ||
| "query" : { | ||
| "term": { | ||
| "visibility": "public" | ||
| } | ||
| } | ||
| } | ||
| } | ||
| ], | ||
| "response_processors": [ | ||
| { | ||
| "rename_field": { | ||
| "field": "message", | ||
| "target_field": "notification" | ||
| } | ||
| } | ||
| ] | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
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| ## Ignoring processor failures | ||
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| By default, a search pipeline stops if one of its processors fails. If you want the pipeline to continue running when a processor fails, you can set the `ignore_failure` parameter for that processor to `true` when creating the pipeline: | ||
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| ```json | ||
| "filter_query" : { | ||
| "tag" : "tag1", | ||
| "description" : "This processor is going to restrict to publicly visible documents", | ||
| "ignore_failure": true, | ||
| "query" : { | ||
| "term": { | ||
| "visibility": "public" | ||
| } | ||
| } | ||
| } | ||
| ``` | ||
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| If the processor fails, OpenSearch logs the failure and continues to run all remaining processors in the search pipeline. To check whether there were any failures, you can use [search pipeline metrics]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/search-pipeline-metrics/). | ||
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| ## Updating a search pipeline | ||
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| To update a search pipeline dynamically, replace the search pipeline using the Search Pipeline API. | ||
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| #### Example request | ||
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| The following example request upserts `my_pipeline` by adding a `filter_query` request processor and a `rename_field` response processor: | ||
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| ```json | ||
| PUT /_search/pipeline/my_pipeline | ||
| { | ||
| "request_processors": [ | ||
| { | ||
| "filter_query": { | ||
| "tag": "tag1", | ||
| "description": "This processor returns only publicly visible documents", | ||
| "query": { | ||
| "term": { | ||
| "visibility": "public" | ||
| } | ||
| } | ||
| } | ||
| } | ||
| ], | ||
| "response_processors": [ | ||
| { | ||
| "rename_field": { | ||
| "field": "message", | ||
| "target_field": "notification" | ||
| } | ||
| } | ||
| ] | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
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| ## Search pipeline versions | ||
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| When creating your pipeline, you can specify a version for it in the `version` parameter: | ||
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| ```json | ||
| PUT _search/pipeline/my_pipeline | ||
| { | ||
| "version": 1234, | ||
| "request_processors": [ | ||
| { | ||
| "script": { | ||
| "source": """ | ||
| if (ctx._source['size'] > 100) { | ||
| ctx._source['explain'] = false; | ||
| } | ||
| """ | ||
| } | ||
| } | ||
| ] | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
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| The version is provided in all subsequent responses to `get pipeline` requests: | ||
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| ```json | ||
| GET _search/pipeline/my_pipeline | ||
| ``` | ||
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| The response contains the pipeline version: | ||
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| <details open markdown="block"> | ||
| <summary> | ||
| Response | ||
| </summary> | ||
| {: .text-delta} | ||
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| ```json | ||
| { | ||
| "my_pipeline": { | ||
| "version": 1234, | ||
| "request_processors": [ | ||
| { | ||
| "script": { | ||
| "source": """ | ||
| if (ctx._source['size'] > 100) { | ||
| ctx._source['explain'] = false; | ||
| } | ||
| """ | ||
| } | ||
| } | ||
| ] | ||
| } | ||
| } | ||
| ``` | ||
| </details> | ||
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Should we include a link to the search pipeline API documentation?
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There's really not a separate API page for this and I think in this case I'm just referring to the /_search/pipeline endpoint so it should be understandable.