L2 reorg

Author: rachel-mack

source/atlas-vector-search.txt

@@ -9,7 +9,7 @@ Atlas Vector Search
    :values: reference
 
 .. meta::
-   :keywords: full text, text analyzer, meta, pipeline, scoring, Lucene, AI, artificial intelligence
+   :keywords: full text, text analyzer, meta, pipeline, scoring, Lucene, AI, artificial intelligence, code example, semantic, nearest
    :description: Learn about how to use Atlas Vector Search in the {+driver-long+}.
 
 .. contents:: On this page
@@ -18,5 +18,90 @@ Atlas Vector Search
    :depth: 2
    :class: singlecol
 
-See :atlas:`Atlas Vector Search </atlas-vector-search/vector-search-overview/>`
-in the MongoDB Atlas documentation.
+Overview
+--------
+
+In this guide, you can learn how to use the :atlas:`Atlas Vector Search
+</atlas-vector-search/vector-search-overview/>` feature
+in the {+driver-short+}. The ``Aggregates``  builders class provides the
+the ``vectorSearch()`` helper method that you can use to
+create a :atlas:`$vectorSearch </atlas-vector-search/vector-search-stage/>`
+pipeline stage. This pipeline stage allows you to perform a **semantic
+search** on your documents. A semantic search is a type of search which
+locates information that is similar in meaning, but not necessarily
+identical, to your provided search term or phrase.
+
+.. important:: Feature Compatibility
+
+   To learn what versions of MongoDB Atlas support this feature, see
+   :atlas:`Limitations </atlas-vector-search/vector-search-stage/#limitations>`
+   in the MongoDB Atlas documentation.
+
+Perform a Vector Search
+-----------------------
+
+To use this feature, you must create a vector search index and index your
+vector embeddings. To learn about how to programmatically create a
+vector search index, see the :ref:`java-search-indexes` section in the
+Indexes guide. To learn more about vector embeddings, see
+:atlas:`How to Index Vector Embeddings for Vector Search
+</atlas-search/field-types/knn-vector/>` in the Atlas documentation.
+
+After you create a vector search index on your vector embeddings, you
+can reference this index in your pipeline stage, as shown in the
+following section.
+
+Vector Search Example
+~~~~~~~~~~~~~~~~~~~~~
+
+The following example shows how to build an aggregation pipeline that uses the
+``vectorSearch()`` and ``project()`` methods to compute a vector search score:
+
+.. literalinclude:: /includes/fundamentals/code-snippets/builders/AggBuilders.java
+   :start-after: // begin vectorSearch
+   :end-before: // end vectorSearch
+   :language: java
+   :dedent:
+
+.. tip:: Query Vector Type
+
+   The preceding example creates an instance of ``BinaryVector`` to
+   serve as the query vector, but you can also create a ``List`` of
+   ``Double`` instances. However, we recommend that you use the
+   ``BinaryVector`` type to improve storage efficiency.
+
+The following example shows how you can run the aggregation and print
+the vector search meta-score from the result of the preceding
+aggregation pipeline:
+
+.. literalinclude:: /includes/fundamentals/code-snippets/builders/AggBuilders.java
+   :start-after: // begin vectorSearch-output
+   :end-before: // end vectorSearch-output
+   :language: java
+   :dedent:
+
+.. tip:: Java Driver Vector Search Examples
+    
+   Visit the :atlas:`Atlas documentation </atlas-vector-search/tutorials/>`
+   to find more tutorials on using the {+driver-short+} to perform Atlas
+   Vector Searches.
+
+API Documentation
+-----------------
+
+To learn more about the methods and types mentioned in this
+guide, see the following API documentation:
+
+- `Aggregates.vectorSearch()
+  <{+api+}/apidocs/mongodb-driver-core/com/mongodb/client/model/Aggregates.html#vectorSearch(com.mongodb.client.model.search.FieldSearchPath,java.lang.Iterable,java.lang.String,long,com.mongodb.client.model.search.VectorSearchOptions)>`__
+
+- `FieldSearchPath
+  <{+api+}/apidocs/mongodb-driver-core/com/mongodb/client/model/search/FieldSearchPath.html>`__
+
+- `VectorSearchOptions
+  <{+api+}/apidocs/mongodb-driver-core/com/mongodb/client/model/search/VectorSearchOptions.html>`__
+
+- `Projections.metaVectorSearchScore()
+  <{+api+}/apidocs/mongodb-driver-core/com/mongodb/client/model/Projections.html#metaVectorSearchScore(java.lang.String)>`__
+
+- `BinaryVector <{+api+}/apidocs/bson/org/bson/BinaryVector.html>`__

source/connection.txt

@@ -9,6 +9,7 @@ Connection Guide
    Connect to MongoDB </connection/connect>
    Connection Options </connection/connection-options>
    MongoClient Settings </connection/mongoclientsettings>
+   Stable API </connection/stable-api>
    Network Compression </connection/network-compression>
    SOCKS5 Proxy </connection/socks>
    JNDI Datasource </connection/jndi>

source/fundamentals/stable-api.txt renamed to source/connection/stable-api.txt

@@ -11,6 +11,12 @@ CRUD Operations
    Write </crud/write-operations>
    Query </crud/query-document>
    Compound Operations </crud/compound-operations>
+   Transactions </crud/transactions>
+   Builders </crud/builders>
+   Aggregation </crud/aggregation>
+   Aggregation Operations </crud/aggregation-expression-operations>
+   Collations </crud/collations>
+   Large File Storage with GridFS </crud/gridfs>
 
 CRUD (Create, Read, Update, Delete) operations enable you to work with
 data stored in MongoDB.

source/crud.txt

@@ -6,12 +6,12 @@ Builders
 
 .. toctree::
 
-   Aggregation </builders/aggregates>
-   Filters </builders/filters>
-   Indexes </builders/indexes>
-   Projection </builders/projections>
-   Sort </builders/sort>
-   Update </builders/updates>
+   Aggregation </crud/builders/aggregates>
+   Filters </crud/builders/filters>
+   Indexes </crud/builders/indexes>
+   Projection </crud/builders/projections>
+   Sort </crud/builders/sort>
+   Update </crud/builders/updates>
 
 .. contents:: On this page
    :local: