[DOC-12077] base64 Vector Embeddings (SERVER VERSION)

modules/search/pages/field-data-types-reference.adoc

@@ -80,9 +80,17 @@ For example:
 
 |vector a|
 
-The field contains an array of floating point numbers. 
+The field contains an array of floating point numbers or an array of arrays that represent a vector embedding. 
 
 Use the `vector` type to perform vector similarity searches with Vector Search. 
 
+For more information about Vector Search, see xref:vector-search:vector-search.adoc[].
+
+|(Server version 7.6.2 and later) vector_base64 a|
+
+The field contains an array of floating point numbers formatted as a base64 encoded string that represent a vector embedding.
+
+Use the `vector_base64` type to perform vector similarity searches with Vector Search. 
+
 For more information about Vector Search, see xref:vector-search:vector-search.adoc[].
 |====

modules/search/pages/search-index-params.adoc

@@ -1049,6 +1049,7 @@ The child field's type. Can be one of:
 * `disabled`
 * `ip`
 * `vector`
+* (Server version 7.6.2 and later) `vector_base64`
 
 For more information about the available field data types, see xref:field-data-types-reference.adoc[].
 

modules/search/pages/search-request-params.adoc

@@ -167,15 +167,15 @@ An object in the `knn` array can contain the following properties:
 
 Enter the total number of results that you want to return from your Vector Search query. 
 
-The Search Service returns the `k` closest vectors to the vector given in `vector`.
+The Search Service returns the `k` closest vectors to the vector given in `vector` or, if your database is running Couchbase Server version 7.6.2 or later, `vector_base64`.
 
 NOTE: The <<size-limit,size or limit property>> overrides any value set in `k`.
 
 |field |String |Yes a|
 
 The name of the field that contains the vector data you want to search. 
 
-|vector |Array of Floats |Yes a| 
+|vector |Array of Floats |Must have `vector` or `vector_base64` a| 
 
 Enter the vector that you want to compare to the vector data in `field`.
 
@@ -185,6 +185,16 @@ NOTE: The vector in your Search query must match the dimension of the vectors st
 If the dimensions do not match, your Search query does not return any results.
 For more information about the dimension value, see the xref:search-index-params.adoc#dims[dims property] or the xref:child-field-options-reference.adoc#dimension[Dimension option] in the UI. 
 
+|vector_base64 |Base64 Encoded String |Must have `vector` or `vector_base64` a|
+
+If your database is running Couchbase Server version 7.6.2 or later, enter a vector, encoded as a base64 string, that you want to compare to the vector data in `field`. 
+
+The Search Service uses the similarity metric defined in the xref:search-index-params.adoc#similarity[Search index definition] to return the `k` closest vectors from the Search index.
+
+NOTE: The vector in your Search query must match the dimension of the vectors stored in your Search index. 
+If the dimensions do not match, your Search query does not return any results.
+For more information about the dimension value, see the xref:search-index-params.adoc#dims[dims property] or the xref:child-field-options-reference.adoc#dimension[Dimension option] in the UI. 
+
 |====
 
 [#query-object]

modules/vector-search/examples/run-vector-search-payload-base64-ui.jsonc

@@ -0,0 +1,10 @@
+{
+    "fields": ["*"],
+    "knn": [
+      {
+        "field": "embedding_vector_dot",
+        "k": 3,
+        "vector_base64": "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"
+      }
+    ]
+}

modules/vector-search/examples/vector-search-base64-document-example.json

@@ -0,0 +1,15 @@
+{
+    "id": "#000080",
+    "color": "navy",
+    "brightness": 14.592,
+    "colorvect_l2": "AACA",
+    "wheel_pos": "other",
+    "verbs": [
+        "deep",
+        "rich",
+        "sophisticated"
+    ],
+    "description": "Navy is a deep, rich color that exudes sophistication. It is a dark shade of blue that is often associated with authority, stability, and elegance. Navy is a versatile color that can be both bold and understated, making it a popular choice in fashion and interior design. It is a timeless color that never goes out of style and adds a touch of sophistication to any look or space.",
+    "embedding_model": "text-embedding-ada-002-v2",
+    "embedding_vector_dot": 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"
+},