feat: Add update_mask "embedding_metadata" to MatchingEngineIndex upsert_datapoints() to support embedding metadata update.

PiperOrigin-RevId: 794412935

Author: vertex-sdk-bot

google/cloud/aiplatform/matching_engine/matching_engine_index.py

@@ -790,6 +790,7 @@ def upsert_datapoints(
  Updatable fields:
  Use `all_restricts` to update both `restricts` and
  `numeric_restricts`.
+ Use `embedding_metadata` to update `embedding_metadata`.
 
  Returns:
  MatchingEngineIndex - Index resource object

tests/system/aiplatform/test_matching_engine_index.py

@@ -18,12 +18,14 @@
 import uuid
 
 from google.cloud import aiplatform
+from google.cloud import aiplatform_v1
 from google.cloud.aiplatform.matching_engine.matching_engine_index_endpoint import (
  Namespace,
 )
-from google.cloud import aiplatform_v1
 from tests.system.aiplatform import e2e_base
 
+from google.protobuf import struct_pb2
+
 # project
 _TEST_INDEX_DISPLAY_NAME = "index_display_name"
 _TEST_STREAM_INDEX_DISPLAY_NAME = "stream_index_display_name"
@@ -219,6 +221,13 @@
  )
  ],
 )
+_TEST_DATAPOINT_4 = aiplatform_v1.types.index.IndexDatapoint(
+ datapoint_id="upsert_4",
+ feature_vector=_TEST_MATCH_QUERY,
+ embedding_metadata=struct_pb2.Struct(
+ fields={"userinfo": struct_pb2.Value(string_value="test_userinfo")}
+ ),
+)
 _TEST_STREAM_INDEX_DATAPOINTS = [
  _TEST_DATAPOINT_1,
  _TEST_DATAPOINT_2,
@@ -631,6 +640,10 @@ def test_matching_engine_stream_index(self, shared_state):
 
  # Upsert datapoint to stream index
  stream_index.upsert_datapoints(datapoints=_TEST_STREAM_INDEX_DATAPOINTS)
+ stream_index.upsert_datapoints(
+ datapoints=_TEST_DATAPOINT_4,
+ update_mask=["embedding_metadata"],
+ )
 
  # Remove datapoint upserted to stream index
  stream_index.remove_datapoints(datapoint_ids="upsert_0")