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301 changes: 254 additions & 47 deletions solutions/images/elasticsearch-reference-semantic-options.svg
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8 changes: 6 additions & 2 deletions solutions/search/semantic-search.md
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Expand Up @@ -38,13 +38,17 @@ This diagram summarizes the relative complexity of each workflow:

### Option 1: `semantic_text` [_semantic_text_workflow]

The simplest way to use NLP models in the {{stack}} is through the [`semantic_text` workflow](semantic-search/semantic-search-semantic-text.md). We recommend using this approach because it abstracts away a lot of manual work. All you need to do is create an {{infer}} endpoint and an index mapping to start ingesting, embedding, and querying data. There is no need to define model-related settings and parameters, or to create {{infer}} ingest pipelines. For more information about the supported services, refer to [](/explore-analyze/elastic-inference/inference-api.md) and the [{{infer}} API](https://www.elastic.co/docs/api/doc/elasticsearch/group/endpoint-inference) documentation .
The simplest way to use NLP models in the {{stack}} is through the [`semantic_text` workflow](semantic-search/semantic-search-semantic-text.md). We recommend using this approach because it abstracts away a lot of manual work. All you need to do is create an index mapping to start ingesting, embedding, and querying data. There is no need to define model-related settings and parameters, or to create {{infer}} ingest pipelines.

{applies_to}`stack: ga 9.1` We recommend using the ELSER model hosted on Elastic Inference Service (EIS) by setting the `inference_id` to `.elser-2-elastic` in your index mapping. For more details, see the ELSER on EIS guide.

To learn more about supported services, refer to [](/explore-analyze/elastic-inference/inference-api.md) and the [{{infer}} API](https://www.elastic.co/docs/api/doc/elasticsearch/group/endpoint-inference) documentation.

For an end-to-end tutorial, refer to [Semantic search with `semantic_text`](semantic-search/semantic-search-semantic-text.md).

### Option 2: Inference API [_infer_api_workflow]

The {{infer}} API workflow is more complex but offers greater control over the {{infer}} endpoint configuration. You need to create an {{infer}} endpoint, provide various model-related settings and parameters, define an index mapping, and set up an {{infer}} ingest pipeline with the appropriate settings.
The {{infer}} API workflow is more complex but offers greater control over the {{infer}} endpoint configuration. You need to create an {{infer}} endpoint, provide various model-related settings and parameters, and define an index mapping. Optionally you can also set up an {{infer}} ingest pipeline for automatic embedding during data ingestion, or alternatively, you can manually call the {{infer}} API.

For an end-to-end tutorial, refer to [Semantic search with the {{infer}} API](semantic-search/semantic-search-inference.md).

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