added projection sample

Author: daniel-sanche

datastore/cloud-client/vector_search.py

@@ -95,6 +95,29 @@ def vector_search_distance_result_property(db):
     # [END datastore_vector_search_distance_result_property]
     return vector_query
 
+def vector_search_distance_result_property_projection(db):
+    # [START datastore_vector_search_distance_result_property_projection]
+    from google.cloud.datastore.vector import DistanceMeasure
+    from google.cloud.datastore.vector import Vector
+    from google.cloud.datastore.vector import FindNearest
+
+    vector_query = db.query(
+        kind="coffee-beans",
+        find_nearest=FindNearest(
+            vector_property="embedding_field",
+            query_vector=Vector([3.0, 1.0, 2.0]),
+            distance_measure=DistanceMeasure.EUCLIDEAN,
+            limit=5,
+            distance_result_property="vector_distance",
+        )
+    )
+    vector_query.projection = ["color"]
+
+    for entity in vector_query.fetch():
+        print(f"{entity.id}, Distance: {entity['vector_distance']}")
+    # [END datastore_vector_search_distance_result_property_projection]
+    return vector_query
+
 
 def vector_search_distance_threshold(db):
     # [START datastore_vector_search_distance_threshold]

datastore/cloud-client/vector_search_test.py

@@ -93,12 +93,33 @@ def test_vector_search_distance_result_property(db):
     assert len(results) == 4
     assert results[0].key.name == "Liberica"
     assert results[0]["vector_distance"] == 0.0
+    assert results[0]["embedding_field"] == Vector([3.0, 1.0, 2.0])
     assert results[1].key.name == "Robusta"
     assert results[1]["vector_distance"] == 1.0
+    assert results[1]["embedding_field"] == Vector([4.0, 1.0, 2.0])
     assert results[2].key.name == "Arabica"
     assert results[2]["vector_distance"] == 7.0
+    assert results[2]["embedding_field"] == Vector([10.0, 1.0, 2.0])
     assert results[3].key.name == "Excelsa"
     assert results[3]["vector_distance"] == 8.0
+    assert results[3]["embedding_field"] == Vector([11.0, 1.0, 2.0])
+
+
+def test_vector_search_distance_result_property_projection(db):
+    vector_query = vector_search_distance_result_property_projection(db)
+    results = list(vector_query.fetch())
+
+    assert len(results) == 4
+    assert results[0].key.name == "Liberica"
+    assert results[0]["vector_distance"] == 0.0
+    assert results[1].key.name == "Robusta"
+    assert results[1]["vector_distance"] == 1.0
+    assert results[2].key.name == "Arabica"
+    assert results[2]["vector_distance"] == 7.0
+    assert results[3].key.name == "Excelsa"
+    assert results[3]["vector_distance"] == 8.0
+
+    assert all("embedding_field" not in d for d in results)
 
 
 def test_vector_search_distance_threshold(db):