[DOCS] Simplifies semantic_text tutorial by removing copy_to field

docs/reference/search/search-your-data/semantic-search-inference.asciidoc

@@ -39,6 +39,7 @@ Create an {infer} endpoint by using the <<put-inference-api>>:
 
 include::{es-ref-dir}/tab-widgets/inference-api/infer-api-task-widget.asciidoc[]
 
+
 [discrete]
 [[infer-service-mappings]]
 ==== Create the index mapping

docs/reference/search/search-your-data/semantic-search-semantic-text.asciidoc

@@ -59,10 +59,8 @@ If using the Python client, you can set the `timeout` parameter to a higher valu
 [[semantic-text-index-mapping]]
 ==== Create the index mapping
 
-The mapping of the destination index - the index that contains the embeddings
-that the inference endpoint will generate based on your input text - must be created. The
-destination index must have a field with the <<semantic-text,`semantic_text`>>
-field type to index the output of the used inference endpoint.
+The mapping of the destination index - the index that contains the embeddings that the inference endpoint will generate based on your input text - must be created.
+The destination index must have a field with the <<semantic-text,`semantic_text`>> field type to index the output of the used inference endpoint.
 
 [source,console]
 ------------------------------------------------------------
@@ -91,6 +89,9 @@ Every time you ingest data into the related `semantic_text` field, this endpoint
 <4> The field to store the text reindexed from a source index in the  <<semantic-text-reindex-data,Reindex the data>> step.
 <5> The textual data stored in the `content` field will be copied to `semantic_text` and processed by the {infer} endpoint.
 The `semantic_text` field will store the embeddings generated based on the input data.
+Copying the `content` field content to the `semantic_text` field is not required for using `semantic_text`.
+However, it is recommended because it makes it possible to perform hybrid search during which you perform lexical search on the text field and semantic search on the semantic_text field.
+
 
 
 [discrete]
@@ -124,6 +125,11 @@ parameter set in the index mapping creation step. The copied data will be
 processed by the {infer} endpoint associated with the `semantic_text` semantic text
 field.
 
+IMPORTANT: Using `copy_to` fields is not required for performing semantic search.
+You can target the `semantic_text` field directly during ingestion.
+Using the `copy_to` field, however, makes it possible to perform hybrid search, hence it is recommended.
+To learn more about using the `copy_to` field, refer to <<copy-to-support,this section>> on the `semantic_text` documentation page.
+
 [source,console]
 ------------------------------------------------------------
 POST _reindex?wait_for_completion=false

docs/reference/tab-widgets/inference-api/infer-api-task.asciidoc

@@ -50,6 +50,14 @@ is the unique identifier of the {infer} endpoint is `elser_embeddings`.
 You don't need to download and deploy the ELSER model upfront, the API request
 above will download the model if it's not downloaded yet and then deploy it.
 
+[NOTE]
+====
+You might see a 502 bad gateway error in the response when using the {kib} Console.
+This error usually just reflects a timeout, while the model downloads in the background.
+You can check the download progress in the {ml-app} UI.
+If using the Python client, you can set the `timeout` parameter to a higher value.
+====
+
 // end::elser[]
 
 // tag::hugging-face[]