Fix merge conflict

googleapis · Apr 24, 2024 · ac88c1b · ac88c1b
2 parents 3a055e9 + f34094b
commit ac88c1b
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diff --git a/.github/sync-repo-settings.yaml b/.github/sync-repo-settings.yaml
@@ -21,4 +21,8 @@ branchProtectionRules:
     - 'Presubmit - Unit Tests Python 3.11'
     - 'Presubmit - Unit Tests Python 3.12'
     - 'Presubmit - Unit Tests Ray 2.4.0'
-    - 'Presubmit - Unit Tests Ray 2.9.3'
+    - 'Presubmit - Unit Tests Ray 2.9.3'
+    - 'Presubmit - Unit Tests LangChain (Python 3.8)'
+    - 'Presubmit - Unit Tests LangChain (Python 3.9)'
+    - 'Presubmit - Unit Tests LangChain (Python 3.10)'
+    - 'Presubmit - Unit Tests LangChain (Python 3.11)'
diff --git a/.kokoro/presubmit/unit_langchain_py310.cfg b/.kokoro/presubmit/unit_langchain_py310.cfg
@@ -0,0 +1,13 @@
+# Format: //devtools/kokoro/config/proto/build.proto
+
+# Run unit tests for LangChain on Python 3.10
+env_vars: {
+    key: "NOX_SESSION"
+    value: "unit_langchain-3.10"
+}
+
+# Run unit tests in parallel, splitting up by file
+env_vars: {
+    key: "PYTEST_ADDOPTS"
+    value: "-n=auto --dist=loadscope"
+}
diff --git a/.kokoro/presubmit/unit_langchain_py311.cfg b/.kokoro/presubmit/unit_langchain_py311.cfg
@@ -0,0 +1,13 @@
+# Format: //devtools/kokoro/config/proto/build.proto
+
+# Run unit tests for LangChain on Python 3.11
+env_vars: {
+    key: "NOX_SESSION"
+    value: "unit_langchain-3.11"
+}
+
+# Run unit tests in parallel, splitting up by file
+env_vars: {
+    key: "PYTEST_ADDOPTS"
+    value: "-n=auto --dist=loadscope"
+}
diff --git a/.kokoro/presubmit/unit_langchain_py38.cfg b/.kokoro/presubmit/unit_langchain_py38.cfg
@@ -0,0 +1,13 @@
+# Format: //devtools/kokoro/config/proto/build.proto
+
+# Run unit tests for LangChain on Python 3.8
+env_vars: {
+    key: "NOX_SESSION"
+    value: "unit_langchain-3.8"
+}
+
+# Run unit tests in parallel, splitting up by file
+env_vars: {
+    key: "PYTEST_ADDOPTS"
+    value: "-n=auto --dist=loadscope"
+}
diff --git a/.kokoro/presubmit/unit_langchain_py39.cfg b/.kokoro/presubmit/unit_langchain_py39.cfg
@@ -0,0 +1,13 @@
+# Format: //devtools/kokoro/config/proto/build.proto
+
+# Run unit tests for LangChain on Python 3.9
+env_vars: {
+    key: "NOX_SESSION"
+    value: "unit_langchain-3.9"
+}
+
+# Run unit tests in parallel, splitting up by file
+env_vars: {
+    key: "PYTEST_ADDOPTS"
+    value: "-n=auto --dist=loadscope"
+}
diff --git a/.release-please-manifest.json b/.release-please-manifest.json
@@ -1,3 +1,3 @@
 {
-    ".": "1.47.0"
+    ".": "1.48.0"
 }
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,5 +1,32 @@
 # Changelog
 
+## [1.48.0](https://github.com/googleapis/python-aiplatform/compare/v1.47.0...v1.48.0) (2024-04-17)
+
+
+### Features
+
+* Add support for reading requirements from a file. ([80db7a0](https://github.com/googleapis/python-aiplatform/commit/80db7a0960b80ae0d78182687c1e99db696943f7))
+* Adding tpu_topology to Vertex SDK ([423c764](https://github.com/googleapis/python-aiplatform/commit/423c7646185b4df19985fb41f5776557d572dd9f))
+* Enable continuous upload for profile logs. ([f05924d](https://github.com/googleapis/python-aiplatform/commit/f05924d6bbd9e609f4ca98cdef7ab5a504672e58))
+* GenAI - Added the `GenerationResponse.prompt_feedback` property ([efd5a72](https://github.com/googleapis/python-aiplatform/commit/efd5a72c1856a6767bdbbba9ea83f366518bdac2))
+* GenAI - Added the `GenerationResponse.usage_metadata` property ([0654c35](https://github.com/googleapis/python-aiplatform/commit/0654c3504425d9f9bba6e3be919026229b616ec0))
+* Support `NOT_EQUAL` for `MatchingEngineIndexEndpoint` `numeric_restricts`. ([aa918e3](https://github.com/googleapis/python-aiplatform/commit/aa918e31fcc40878e9f29affa02a4527d90188aa))
+* Support referenced models in SDK. ([c9b6b8b](https://github.com/googleapis/python-aiplatform/commit/c9b6b8b3433854afd95a27065a052393768ceca8))
+
+
+### Bug Fixes
+
+* Add validation check for extra_packages when creating a reasoning engine. ([255dabc](https://github.com/googleapis/python-aiplatform/commit/255dabc77c647ef3ac33a10b06b3a36db122118a))
+* Add validation for langchain tools. ([a821d50](https://github.com/googleapis/python-aiplatform/commit/a821d50724da7136c90abd157a7086d6571f2c30))
+* Fixed the vertexai.init partial initialization issues ([636a654](https://github.com/googleapis/python-aiplatform/commit/636a654590919048f84baf343d291711f28eb03e))
+* GenAI - Workaround for streaming when content role is missing in service responses ([fa35b91](https://github.com/googleapis/python-aiplatform/commit/fa35b9169677c62a5f0fa746dc9db9a5296f44a3))
+
+
+### Documentation
+
+* Add Reasoning Engine reference documentation ([496fc4b](https://github.com/googleapis/python-aiplatform/commit/496fc4b96768c872c9e7312bacf9989ea6e979f5))
+* GenAI - Add Rapid Evaluation SDK reference documentation ([40b728b](https://github.com/googleapis/python-aiplatform/commit/40b728b28210f2bc57374c6c6d507cf3fa0be038))
+
 ## [1.47.0](https://github.com/googleapis/python-aiplatform/compare/v1.46.0...v1.47.0) (2024-04-06)
 
 

diff --git a/google/cloud/aiplatform/compat/services/__init__.py b/google/cloud/aiplatform/compat/services/__init__.py
@@ -63,12 +63,12 @@
 from google.cloud.aiplatform_v1beta1.services.model_service import (
     client as model_service_client_v1beta1,
 )
-from google.cloud.aiplatform_v1beta1.services.pipeline_service import (
-    client as pipeline_service_client_v1beta1,
-)
 from google.cloud.aiplatform_v1beta1.services.persistent_resource_service import (
     client as persistent_resource_service_client_v1beta1,
 )
+from google.cloud.aiplatform_v1beta1.services.pipeline_service import (
+    client as pipeline_service_client_v1beta1,
+)
 from google.cloud.aiplatform_v1beta1.services.prediction_service import (
     client as prediction_service_client_v1beta1,
 )
@@ -90,10 +90,20 @@
 from google.cloud.aiplatform_v1beta1.services.tensorboard_service import (
     client as tensorboard_service_client_v1beta1,
 )
+from google.cloud.aiplatform_v1beta1.services.vertex_rag_data_service import (
+    client as vertex_rag_data_service_client_v1beta1,
+)
+from google.cloud.aiplatform_v1beta1.services.vertex_rag_data_service import (
+    async_client as vertex_rag_data_service_async_client_v1beta1,
+)
+from google.cloud.aiplatform_v1beta1.services.vertex_rag_service import (
+    client as vertex_rag_service_client_v1beta1,
+)
 from google.cloud.aiplatform_v1beta1.services.vizier_service import (
     client as vizier_service_client_v1beta1,
 )
 
+
 from google.cloud.aiplatform_v1.services.dataset_service import (
     client as dataset_service_client_v1,
 )
@@ -195,9 +205,14 @@
     pipeline_service_client_v1beta1,
     prediction_service_client_v1beta1,
     prediction_service_async_client_v1beta1,
+    reasoning_engine_execution_service_client_v1beta1,
+    reasoning_engine_service_client_v1beta1,
     schedule_service_client_v1beta1,
     specialist_pool_service_client_v1beta1,
     metadata_service_client_v1beta1,
     tensorboard_service_client_v1beta1,
+    vertex_rag_service_client_v1beta1,
+    vertex_rag_data_service_client_v1beta1,
+    vertex_rag_data_service_async_client_v1beta1,
     vizier_service_client_v1beta1,
 )
diff --git a/google/cloud/aiplatform/gapic_version.py b/google/cloud/aiplatform/gapic_version.py
@@ -13,4 +13,4 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
-__version__ = "1.47.0"  # {x-release-please-version}
+__version__ = "1.48.0"  # {x-release-please-version}
diff --git a/google/cloud/aiplatform/initializer.py b/google/cloud/aiplatform/initializer.py
@@ -192,23 +192,22 @@ def init(
             ValueError:
                 If experiment_description is provided but experiment is not.
         """
-
-        if api_endpoint is not None:
-            self._api_endpoint = api_endpoint
-
+        # This method mutates state, so we need to be careful with the validation
+        # First, we need to validate all passed values
+        if api_transport:
+            VALID_TRANSPORT_TYPES = ["grpc", "rest"]
+            if api_transport not in VALID_TRANSPORT_TYPES:
+                raise ValueError(
+                    f"{api_transport} is not a valid transport type. "
+                    + f"Valid transport types: {VALID_TRANSPORT_TYPES}"
+                )
+        if location:
+            utils.validate_region(location)
         if experiment_description and experiment is None:
             raise ValueError(
                 "Experiment needs to be set in `init` in order to add experiment descriptions."
             )
 
-        if experiment_tensorboard and not isinstance(experiment_tensorboard, bool):
-            metadata._experiment_tracker.set_tensorboard(
-                tensorboard=experiment_tensorboard,
-                project=project,
-                location=location,
-                credentials=credentials,
-            )
-
         # reset metadata_service config if project or location is updated.
         if (project and project != self._project) or (
             location and location != self._location
@@ -217,10 +216,14 @@ def init(
                 logging.info("project/location updated, reset Experiment config.")
             metadata._experiment_tracker.reset()
 
+        # Then we change the main state
+        if api_endpoint is not None:
+            self._api_endpoint = api_endpoint
+        if api_transport:
+            self._api_transport = api_transport
         if project:
             self._project = project
         if location:
-            utils.validate_region(location)
             self._location = location
         if staging_bucket:
             self._staging_bucket = staging_bucket
@@ -233,22 +236,22 @@ def init(
         if service_account is not None:
             self._service_account = service_account
 
+        # Finally, perform secondary state updates
+        if experiment_tensorboard and not isinstance(experiment_tensorboard, bool):
+            metadata._experiment_tracker.set_tensorboard(
+                tensorboard=experiment_tensorboard,
+                project=project,
+                location=location,
+                credentials=credentials,
+            )
+
         if experiment:
             metadata._experiment_tracker.set_experiment(
                 experiment=experiment,
                 description=experiment_description,
                 backing_tensorboard=experiment_tensorboard,
             )
 
-        if api_transport:
-            VALID_TRANSPORT_TYPES = ["grpc", "rest"]
-            if api_transport not in VALID_TRANSPORT_TYPES:
-                raise ValueError(
-                    f"{api_transport} is not a valid transport type. "
-                    + f"Valid transport types: {VALID_TRANSPORT_TYPES}"
-                )
-            self._api_transport = api_transport
-
     def get_encryption_spec(
         self,
         encryption_spec_key_name: Optional[str],

diff --git a/google/cloud/aiplatform/jobs.py b/google/cloud/aiplatform/jobs.py
@@ -1924,6 +1924,7 @@ def from_local_script(
         encryption_spec_key_name: Optional[str] = None,
         staging_bucket: Optional[str] = None,
         persistent_resource_id: Optional[str] = None,
+        tpu_topology: Optional[str] = None,
     ) -> "CustomJob":
         """Configures a custom job from a local script.
 
@@ -2034,6 +2035,12 @@ def from_local_script(
                 on-demand short-live machines. The network, CMEK, and node pool
                 configs on the job should be consistent with those on the
                 PersistentResource, otherwise, the job will be rejected.
+            tpu_topology (str):
+                Optional. Specifies the tpu topology to be used for
+                TPU training job. This field is required for TPU v5 versions. For
+                details on the TPU topology, refer to
+                https://cloud.google.com/tpu/docs/v5e#tpu-v5e-config. The topology
+                must be a supported value for the TPU machine type.
 
         Raises:
             RuntimeError: If staging bucket was not set using aiplatform.init
@@ -2063,6 +2070,7 @@ def from_local_script(
                 boot_disk_size_gb=boot_disk_size_gb,
                 reduction_server_replica_count=reduction_server_replica_count,
                 reduction_server_machine_type=reduction_server_machine_type,
+                tpu_topology=tpu_topology,
             ).pool_specs
         )
 

diff --git a/google/cloud/aiplatform/matching_engine/matching_engine_index.py b/google/cloud/aiplatform/matching_engine/matching_engine_index.py
@@ -434,6 +434,9 @@ def create_tree_ah_index(
         encryption_spec_key_name: Optional[str] = None,
         create_request_timeout: Optional[float] = None,
         shard_size: Optional[str] = None,
+        feature_norm_type: Optional[
+            matching_engine_index_config.FeatureNormType
+        ] = None,
     ) -> "MatchingEngineIndex":
         """Creates a MatchingEngineIndex resource that uses the tree-AH algorithm.
 
@@ -477,6 +480,8 @@ def create_tree_ah_index(
                 range 1-100, inclusive. The default value is 10 (means 10%) if not set.
             distance_measure_type (matching_engine_index_config.DistanceMeasureType):
                 Optional. The distance measure used in nearest neighbor search.
+            feature_norm_type (matching_engine_index_config.FeatureNormType):
+                Optional. The feature norm type used in nearest neighbor search.
             description (str):
                 Optional. The description of the Index.
             labels (Dict[str, str]):
@@ -552,6 +557,7 @@ def create_tree_ah_index(
             algorithm_config=algorithm_config,
             approximate_neighbors_count=approximate_neighbors_count,
             distance_measure_type=distance_measure_type,
+            feature_norm_type=feature_norm_type,
             shard_size=shard_size,
         )
 
@@ -580,6 +586,9 @@ def create_brute_force_index(
         distance_measure_type: Optional[
             matching_engine_index_config.DistanceMeasureType
         ] = None,
+        feature_norm_type: Optional[
+            matching_engine_index_config.FeatureNormType
+        ] = None,
         description: Optional[str] = None,
         labels: Optional[Dict[str, str]] = None,
         project: Optional[str] = None,
@@ -623,6 +632,8 @@ def create_brute_force_index(
                 Required. The number of dimensions of the input vectors.
             distance_measure_type (matching_engine_index_config.DistanceMeasureType):
                 Optional. The distance measure used in nearest neighbor search.
+            feature_norm_type (matching_engine_index_config.FeatureNormType):
+                Optional. The feature norm type used in nearest neighbor search.
             description (str):
                 Optional. The description of the Index.
             labels (Dict[str, str]):
@@ -695,6 +706,7 @@ def create_brute_force_index(
             dimensions=dimensions,
             algorithm_config=algorithm_config,
             distance_measure_type=distance_measure_type,
+            feature_norm_type=feature_norm_type,
             shard_size=shard_size,
         )
 

diff --git a/google/cloud/aiplatform/matching_engine/matching_engine_index_config.py b/google/cloud/aiplatform/matching_engine/matching_engine_index_config.py
@@ -125,12 +125,15 @@ class MatchingEngineIndexConfig:
             independently.
         distance_measure_type (DistanceMeasureType):
             Optional. The distance measure used in nearest neighbor search.
+        feature_norm_type (FeatureNormType):
+            Optional. The feature norm type used in nearest neighbor search.
     """
 
     dimensions: int
     algorithm_config: AlgorithmConfig
     approximate_neighbors_count: Optional[int] = None
     distance_measure_type: Optional[DistanceMeasureType] = None
+    feature_norm_type: Optional[FeatureNormType] = None
     shard_size: Optional[str] = None
 
     def as_dict(self) -> Dict[str, Any]:
@@ -144,6 +147,7 @@ def as_dict(self) -> Dict[str, Any]:
             "algorithmConfig": self.algorithm_config.as_dict(),
             "approximateNeighborsCount": self.approximate_neighbors_count,
             "distanceMeasureType": self.distance_measure_type,
+            "featureNormType": self.feature_norm_type,
             "shardSize": self.shard_size,
         }
         return res