final

note: tests will fail as long as the dump in genai page is on aligned store

Author: stefano-ottolenghi

modules/ROOT/pages/functions/vector.adoc

@@ -12,22 +12,18 @@ Vector functions allow you to construct xref:values-and-types/vector.adoc[`VECTO
 .Details
 |===
 | *Syntax* 3+| `vector(vectorValue, dimension, coordinateType)`
-| *Description* 3+| Constructs a `VECTOR` value.
+| *Description* 3+| Constructs a xref:values-and-types/vector.adoc[`VECTOR`] value.
 .4+| *Arguments* | *Name* | *Type* | *Description*
 | `vectorValue` | `STRING` \| `LIST<INTEGER \| FLOAT>` | The numeric values to create the vector coordinates from.
 | `dimension` | `INTEGER` | The dimension (number of coordinates) of the vector.
 | `coordinateType` | `[INTEGER64, INTEGER32, INTEGER16, INTEGER8, FLOAT64, FLOAT32]` | The type of each coordinate in the vector.
-| *Returns* 3+| `VECTOR`
+| *Returns* 3+| xref:values-and-types/vector.adoc[`VECTOR`]
 |===
 
-[NOTE]
-`VECTOR` values can be xref:values-and-types/vector.adoc#store-vector-properties[stored as properties].
-As such, the `vector()` function can be used to store the embeddings generated by Neo4j's xref:genai-integrations.adoc[GenAI plugin] as `VECTOR` property values.
-`VECTOR` properties can be semantically searched by a xref:indexes/semantic-indexes/vector-indexes.adoc[vector index].
-
 .Considerations
 |===
 
+| `VECTOR` values can be xref:values-and-types/vector.adoc#store-vector-properties[stored as properties].
 | If a `STRING` is used in `vectorValue`, it must start and end with square brackets (`[]`).
 The values inside the brackets must be comma-separated numbers, represented in either decimal or scientific notation.
 | `null`, `NaN`, and `Infinity` values are not allowed as coordinate values.
@@ -117,8 +113,6 @@ RETURN vector(null, 3, FLOAT32) AS nullVectorValue,
 | *Returns* 3+| `FLOAT`
 |===
 
-For more details, see the {link-vector-indexes}#similarity-functions[vector index documentation].
-
 .Considerations
 |===
 
@@ -133,6 +127,8 @@ For more details, see the {link-vector-indexes}#similarity-functions[vector inde
 
 |===
 
+For more details, see the {link-vector-indexes}#similarity-functions[vector index documentation].
+
 
 [[functions-similarity-euclidean]]
 == vector.similarity.euclidean()
@@ -147,7 +143,6 @@ For more details, see the {link-vector-indexes}#similarity-functions[vector inde
 | *Returns* 3+| `FLOAT`
 |===
 
-For more details, see the {link-vector-indexes}#similarity-functions[vector index documentation].
 
 .Considerations
 |===
@@ -163,6 +158,7 @@ For more details, see the {link-vector-indexes}#similarity-functions[vector inde
 
 |===
 
+For more details, see the {link-vector-indexes}#similarity-functions[vector index documentation].
 
 
 .k-Nearest Neighbors
@@ -298,8 +294,7 @@ RETURN vector_dimension_count(vector([1, 2, 3], 3, INTEGER)) AS size
 .Considerations
 |===
 
-| The smaller the returned number, the more similar the `VECTOR` values.
-The larger the number, the more distant the vectors.
+| The smaller the returned number, the more similar the vectors; the larger the number, the more distant the vectors.
 This is in contrast to the similarity functions where the closer to `1` the result is the higher the degree of similarity.
 
 |===