feat: add support for find_neighbors/read_index_datapoints in matchin…

…g engine public endpoint

PiperOrigin-RevId: 527357229

google/cloud/aiplatform/compat/__init__.py

@@ -41,6 +41,7 @@
     services.specialist_pool_service_client = (
         services.specialist_pool_service_client_v1beta1
     )
+    services.match_service_client = services.match_service_client_v1beta1
     services.metadata_service_client = services.metadata_service_client_v1beta1
     services.tensorboard_service_client = services.tensorboard_service_client_v1beta1
     services.index_service_client = services.index_service_client_v1beta1

google/cloud/aiplatform/compat/services/__init__.py

@@ -39,6 +39,9 @@
 from google.cloud.aiplatform_v1beta1.services.job_service import (
     client as job_service_client_v1beta1,
 )
+from google.cloud.aiplatform_v1beta1.services.match_service import (
+    client as match_service_client_v1beta1,
+)
 from google.cloud.aiplatform_v1beta1.services.metadata_service import (
     client as metadata_service_client_v1beta1,
 )
@@ -129,6 +132,7 @@
     index_service_client_v1beta1,
     index_endpoint_service_client_v1beta1,
     job_service_client_v1beta1,
+    match_service_client_v1beta1,
     model_service_client_v1beta1,
     pipeline_service_client_v1beta1,
     prediction_service_client_v1beta1,

google/cloud/aiplatform/compat/types/__init__.py

@@ -57,6 +57,7 @@
     lineage_subgraph as lineage_subgraph_v1beta1,
     machine_resources as machine_resources_v1beta1,
     manual_batch_tuning_parameters as manual_batch_tuning_parameters_v1beta1,
+    match_service as match_service_v1beta1,
     metadata_schema as metadata_schema_v1beta1,
     metadata_service as metadata_service_v1beta1,
     metadata_store as metadata_store_v1beta1,
@@ -260,6 +261,7 @@
     matching_engine_deployed_index_ref_v1beta1,
     index_v1beta1,
     index_endpoint_v1beta1,
+    match_service_v1beta1,
     metadata_service_v1beta1,
     metadata_schema_v1beta1,
     metadata_store_v1beta1,

google/cloud/aiplatform/initializer.py

@@ -279,6 +279,7 @@ def get_client_options(
         location_override: Optional[str] = None,
         prediction_client: bool = False,
         api_base_path_override: Optional[str] = None,
+        api_path_override: Optional[str] = None,
     ) -> client_options.ClientOptions:
         """Creates GAPIC client_options using location and type.
 
@@ -289,6 +290,7 @@ def get_client_options(
                 Vertex AI.
             prediction_client (str): Optional. flag to use a prediction endpoint.
             api_base_path_override (str): Optional. Override default API base path.
+            api_path_override (str): Optional. Override default api path.
         Returns:
             clients_options (google.api_core.client_options.ClientOptions):
                 A ClientOptions object set with regionalized API endpoint, i.e.
@@ -311,9 +313,12 @@ def get_client_options(
             else constants.API_BASE_PATH
         )
 
-        return client_options.ClientOptions(
-            api_endpoint=f"{region}-{service_base_path}"
+        api_endpoint = (
+            f"{region}-{service_base_path}"
+            if not api_path_override
+            else api_path_override
         )
+        return client_options.ClientOptions(api_endpoint=api_endpoint)
 
     def common_location_path(
         self, project: Optional[str] = None, location: Optional[str] = None
@@ -345,6 +350,7 @@ def create_client(
         location_override: Optional[str] = None,
         prediction_client: bool = False,
         api_base_path_override: Optional[str] = None,
+        api_path_override: Optional[str] = None,
         appended_user_agent: Optional[List[str]] = None,
     ) -> utils.VertexAiServiceClientWithOverride:
         """Instantiates a given VertexAiServiceClient with optional
@@ -358,6 +364,7 @@ def create_client(
             location_override (str): Optional. location override.
             prediction_client (str): Optional. flag to use a prediction endpoint.
             api_base_path_override (str): Optional. Override default api base path.
+            api_path_override (str): Optional. Override default api path.
             appended_user_agent (List[str]):
                 Optional. User agent appended in the client info. If more than one, it will be
                 separated by spaces.
@@ -383,6 +390,7 @@ def create_client(
                 location_override=location_override,
                 prediction_client=prediction_client,
                 api_base_path_override=api_base_path_override,
+                api_path_override=api_path_override,
             ),
             "client_info": client_info,
         }

google/cloud/aiplatform/matching_engine/matching_engine_index_endpoint.py

@@ -26,6 +26,8 @@
 from google.cloud.aiplatform.compat.types import (
     machine_resources as gca_machine_resources_compat,
     matching_engine_index_endpoint as gca_matching_engine_index_endpoint,
+    match_service_v1beta1 as gca_match_service_v1beta1,
+    index_v1beta1 as gca_index_v1beta1,
 )
 from google.cloud.aiplatform.matching_engine._protos import match_service_pb2
 from google.cloud.aiplatform.matching_engine._protos import (
@@ -127,6 +129,9 @@ def __init__(
         )
         self._gca_resource = self._get_gca_resource(resource_name=index_endpoint_name)
 
+        if self.public_endpoint_domain_name:
+            self._public_match_client = self._instantiate_public_match_client()
+
     @classmethod
     def create(
         cls,
@@ -344,6 +349,22 @@ def _create(
 
         return index_obj
 
+    def _instantiate_public_match_client(
+        self,
+    ) -> utils.MatchClientWithOverride:
+        """Helper method to instantiates match client with optional
+        overrides for this endpoint.
+        Returns:
+            match_client (match_service_client.MatchServiceClient):
+                Initialized match client with optional overrides.
+        """
+        return initializer.global_config.create_client(
+            client_class=utils.MatchClientWithOverride,
+            credentials=self.credentials,
+            location_override=self.location,
+            api_path_override=self.public_endpoint_domain_name,
+        )
+
     @property
     def public_endpoint_domain_name(self) -> Optional[str]:
         """Public endpoint DNS name."""
@@ -928,6 +949,124 @@ def description(self) -> str:
         self._assert_gca_resource_is_available()
         return self._gca_resource.description
 
+    def find_neighbors(
+        self,
+        *,
+        deployed_index_id: str,
+        queries: List[List[float]],
+        num_neighbors: int = 10,
+        filter: Optional[List[Namespace]] = [],
+    ) -> List[List[MatchNeighbor]]:
+        """Retrieves nearest neighbors for the given embedding queries on the specified deployed index which is deployed to public endpoint.
+
+        ```
+        Example usage:
+            my_index_endpoint = aiplatform.MatchingEngineIndexEndpoint(
+                index_endpoint_name='projects/123/locations/us-central1/index_endpoint/my_index_id'
+            )
+            my_index_endpoint.find_neighbors(deployed_index_id="public_test1", queries= [[1, 1]],)
+        ```
+        Args:
+            deployed_index_id (str):
+                Required. The ID of the DeployedIndex to match the queries against.
+            queries (List[List[float]]):
+                Required. A list of queries. Each query is a list of floats, representing a single embedding.
+            num_neighbors (int):
+                Required. The number of nearest neighbors to be retrieved from database for
+                each query.
+            filter (List[Namespace]):
+                Optional. A list of Namespaces for filtering the matching results.
+                For example, [Namespace("color", ["red"], []), Namespace("shape", [], ["squared"])] will match datapoints
+                that satisfy "red color" but not include datapoints with "squared shape".
+                Please refer to https://cloud.google.com/vertex-ai/docs/matching-engine/filtering#json for more detail.
+        Returns:
+            List[List[MatchNeighbor]] - A list of nearest neighbors for each query.
+        """
+
+        if not self._public_match_client:
+            raise ValueError(
+                "Please make sure index has been deployed to public endpoint, and follow the example usage to call this method."
+            )
+
+        # Create the FindNeighbors request
+        find_neighbors_request = gca_match_service_v1beta1.FindNeighborsRequest()
+        find_neighbors_request.index_endpoint = self.resource_name
+        find_neighbors_request.deployed_index_id = deployed_index_id
+
+        for query in queries:
+            find_neighbors_query = (
+                gca_match_service_v1beta1.FindNeighborsRequest.Query()
+            )
+            find_neighbors_query.neighbor_count = num_neighbors
+            datapoint = gca_index_v1beta1.IndexDatapoint(feature_vector=query)
+            for namespace in filter:
+                restrict = gca_index_v1beta1.IndexDatapoint.Restriction()
+                restrict.namespace = namespace.name
+                restrict.allow_list.extend(namespace.allow_tokens)
+                restrict.deny_list.extend(namespace.deny_tokens)
+                datapoint.restricts.append(restrict)
+            find_neighbors_query.datapoint = datapoint
+            find_neighbors_request.queries.append(find_neighbors_query)
+
+        response = self._public_match_client.find_neighbors(find_neighbors_request)
+
+        # Wrap the results in MatchNeighbor objects and return
+        return [
+            [
+                MatchNeighbor(
+                    id=neighbor.datapoint.datapoint_id, distance=neighbor.distance
+                )
+                for neighbor in embedding_neighbors.neighbors
+            ]
+            for embedding_neighbors in response.nearest_neighbors
+        ]
+
+    def read_index_datapoints(
+        self,
+        *,
+        deployed_index_id: str,
+        ids: List[str] = [],
+    ) -> List[gca_index_v1beta1.IndexDatapoint]:
+        """Reads the datapoints/vectors of the given IDs on the specified deployed index which is deployed to public endpoint.
+
+        ```
+        Example Usage:
+            my_index_endpoint = aiplatform.MatchingEngineIndexEndpoint(
+                index_endpoint_name='projects/123/locations/us-central1/index_endpoint/my_index_id'
+            )
+            my_index_endpoint.read_index_datapoints(deployed_index_id="public_test1", ids= ["606431", "896688"],)
+        ```
+
+        Args:
+            deployed_index_id (str):
+                Required. The ID of the DeployedIndex to match the queries against.
+            ids (List[str]):
+                Required. IDs of the datapoints to be searched for.
+        Returns:
+            List[gca_index_v1beta1.IndexDatapoint] - A list of datapoints/vectors of the given IDs.
+        """
+        if not self._public_match_client:
+            raise ValueError(
+                "Please make sure index has been deployed to public endpoint, and follow the example usage to call this method."
+            )
+
+        # Create the ReadIndexDatapoints request
+        read_index_datapoints_request = (
+            gca_match_service_v1beta1.ReadIndexDatapointsRequest()
+        )
+        read_index_datapoints_request.index_endpoint = self.resource_name
+        read_index_datapoints_request.deployed_index_id = deployed_index_id
+
+        for id in ids:
+            read_index_datapoints_request.ids.append(id)
+
+        response = self._public_match_client.read_index_datapoints(
+            read_index_datapoints_request
+        )
+
+        # Wrap the results and return
+        return response.datapoints
+
     def match(
         self,
         deployed_index_id: str,

google/cloud/aiplatform/utils/__init__.py

@@ -44,6 +44,7 @@
     index_service_client_v1beta1,
     index_endpoint_service_client_v1beta1,
     job_service_client_v1beta1,
+    match_service_client_v1beta1,
     metadata_service_client_v1beta1,
     model_service_client_v1beta1,
     pipeline_service_client_v1beta1,
@@ -85,6 +86,7 @@
     prediction_service_client_v1beta1.PredictionServiceClient,
     pipeline_service_client_v1beta1.PipelineServiceClient,
     job_service_client_v1beta1.JobServiceClient,
+    match_service_client_v1beta1.MatchServiceClient,
     metadata_service_client_v1beta1.MetadataServiceClient,
     tensorboard_service_client_v1beta1.TensorboardServiceClient,
     vizier_service_client_v1beta1.VizierServiceClient,
@@ -598,6 +600,12 @@ class PredictionClientWithOverride(ClientWithOverride):
     )
 
 
+class MatchClientWithOverride(ClientWithOverride):
+    _is_temporary = False
+    _default_version = compat.V1BETA1
+    _version_map = ((compat.V1BETA1, match_service_client_v1beta1.MatchServiceClient),)
+
+
 class MetadataClientWithOverride(ClientWithOverride):
     _is_temporary = True
     _default_version = compat.DEFAULT_VERSION
@@ -632,6 +640,7 @@ class VizierClientWithOverride(ClientWithOverride):
     FeaturestoreClientWithOverride,
     JobClientWithOverride,
     ModelClientWithOverride,
+    MatchClientWithOverride,
     PipelineClientWithOverride,
     PipelineJobClientWithOverride,
     PredictionClientWithOverride,