Remove references to the legacy format in docs

Author: jimczi

docs/reference/query-dsl/semantic-query.asciidoc

@@ -117,79 +117,3 @@ GET my-index/_search
 }
 ------------------------------------------------------------
 // TEST[skip: Requires inference endpoints]
-
-
-[discrete]
-[[advanced-search]]
-==== Advanced search on `semantic_text` fields
-
-The `semantic` query uses default settings for searching on `semantic_text` fields for ease of use.
-If you want to fine-tune a search on a `semantic_text` field, you need to know the task type used by the `inference_id` configured in `semantic_text`.
-You can find the task type using the <<get-inference-api>>, and check the `task_type` associated with the {infer} service.
-Depending on the `task_type`, use either the <<query-dsl-sparse-vector-query,`sparse_vector`>> or the <<query-dsl-knn-query,`knn`>> query for greater flexibility and customization.
-
-NOTE: While it is possible to use the `sparse_vector` query or the `knn` query
-on a `semantic_text` field, it is not supported to use the `semantic_query` on a
-`sparse_vector` or `dense_vector` field type.
-
-
-[discrete]
-[[search-sparse-inference]]
-===== Search with `sparse_embedding` inference
-
-When the {infer} endpoint uses a `sparse_embedding` model, you can use a <<query-dsl-sparse-vector-query,`sparse_vector` query>> on a <<semantic-text,`semantic_text`>> field in the following way:
-
-[source,console]
-------------------------------------------------------------
-GET test-index/_search
-{
-  "query": {
-    "nested": {
-      "path": "inference_field.inference.chunks",
-      "query": {
-        "sparse_vector": {
-          "field": "inference_field.inference.chunks.embeddings",
-          "inference_id": "my-inference-id",
-          "query": "mountain lake"
-        }
-      }
-    }
-  }
-}
-------------------------------------------------------------
-// TEST[skip: Requires inference endpoints]
-
-You can customize the `sparse_vector` query to include specific settings, like <<sparse-vector-query-with-pruning-config-and-rescore-example,pruning configuration>>.
-
-
-[discrete]
-[[search-text-inferece]]
-===== Search with `text_embedding` inference
-
-When the {infer} endpoint uses a `text_embedding` model, you can use a <<query-dsl-knn-query,`knn` query>> on a `semantic_text` field in the following way:
-
-[source,console]
-------------------------------------------------------------
-GET test-index/_search
-{
-  "query": {
-    "nested": {
-      "path": "inference_field.inference.chunks",
-      "query": {
-        "knn": {
-          "field": "inference_field.inference.chunks.embeddings",
-          "query_vector_builder": {
-            "text_embedding": {
-              "model_id": "my_inference_id",
-	      "model_text": "mountain lake"
-            }
-          }
-        }
-      }
-    }
-  }
-}
-------------------------------------------------------------
-// TEST[skip: Requires inference endpoints]
-
-You can customize the `knn` query to include specific settings, like `num_candidates` and `k`.

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

@@ -157,89 +157,7 @@ GET semantic-embeddings/_search
 <2> The query text.
 
 As a result, you receive the top 10 documents that are closest in meaning to the
-query from the `semantic-embedding` index:
-
-[source,console-result]
-------------------------------------------------------------
-"hits": [
-  {
-    "_index": "semantic-embeddings",
-    "_id": "Jy5065EBBFPLbFsdh_f9",
-    "_score": 21.487484,
-    "_source": {
-      "id": 8836652,
-      "content": {
-        "text": "There are a few foods and food groups that will help to fight inflammation and delayed onset muscle soreness (both things that are inevitable after a long, hard workout) when you incorporate them into your postworkout eats, whether immediately after your run or at a meal later in the day. Advertisement. Advertisement.",
-        "inference": {
-          "inference_id": "my-elser-endpoint",
-          "model_settings": {
-            "task_type": "sparse_embedding"
-          },
-          "chunks": [
-            {
-              "text": "There are a few foods and food groups that will help to fight inflammation and delayed onset muscle soreness (both things that are inevitable after a long, hard workout) when you incorporate them into your postworkout eats, whether immediately after your run or at a meal later in the day. Advertisement. Advertisement.",
-              "embeddings": {
-                (...)
-              }
-            }
-          ]
-        }
-      }
-    }
-  },
-  {
-    "_index": "semantic-embeddings",
-    "_id": "Ji5065EBBFPLbFsdh_f9",
-    "_score": 18.211695,
-    "_source": {
-      "id": 8836651,
-      "content": {
-        "text": "During Your Workout. There are a few things you can do during your workout to help prevent muscle injury and soreness. According to personal trainer and writer for Iron Magazine, Marc David, doing warm-ups and cool-downs between sets can help keep muscle soreness to a minimum.",
-        "inference": {
-          "inference_id": "my-elser-endpoint",
-          "model_settings": {
-            "task_type": "sparse_embedding"
-          },
-          "chunks": [
-            {
-              "text": "During Your Workout. There are a few things you can do during your workout to help prevent muscle injury and soreness. According to personal trainer and writer for Iron Magazine, Marc David, doing warm-ups and cool-downs between sets can help keep muscle soreness to a minimum.",
-              "embeddings": {
-                (...)
-              }
-            }
-          ]
-        }
-      }
-    }
-  },
-  {
-    "_index": "semantic-embeddings",
-    "_id": "Wi5065EBBFPLbFsdh_b9",
-    "_score": 13.089405,
-    "_source": {
-      "id": 8800197,
-      "content": {
-        "text": "This is especially important if the soreness is due to a weightlifting routine. For this time period, do not exert more than around 50% of the level of effort (weight, distance and speed) that caused the muscle groups to be sore.",
-        "inference": {
-          "inference_id": "my-elser-endpoint",
-          "model_settings": {
-            "task_type": "sparse_embedding"
-          },
-          "chunks": [
-            {
-              "text": "This is especially important if the soreness is due to a weightlifting routine. For this time period, do not exert more than around 50% of the level of effort (weight, distance and speed) that caused the muscle groups to be sore.",
-              "embeddings": {
-                (...)
-              }
-            }
-          ]
-        }
-      }
-    }
-  }
-]
-------------------------------------------------------------
-// NOTCONSOLE
+query from the `semantic-embedding` index.
 
 [discrete]
 [[semantic-text-further-examples]]