feat: GenAI SDK client - Add Vertex AI Prompt Optimizer to the Gen AI SDK (experimental)

tests/unit/vertexai/genai/test_prompt_optimizer.py

@@ -13,24 +13,14 @@
 # limitations under the License.
 #
 # pylint: disable=protected-access,bad-continuation
-import copy
+
 import importlib
 from unittest import mock
 
-from google.cloud import aiplatform
 import vertexai
-from google.cloud.aiplatform import initializer as aiplatform_initializer
-from google.cloud.aiplatform.compat.services import job_service_client
-from google.cloud.aiplatform.compat.types import (
-    custom_job as gca_custom_job_compat,
-)
-from google.cloud.aiplatform.compat.types import io as gca_io_compat
-from google.cloud.aiplatform.compat.types import (
-    job_state as gca_job_state_compat,
-)
-
-# from google.cloud.aiplatform.utils import gcs_utils
-# from google.genai import client
+from vertexai._genai import prompt_optimizer
+from vertexai._genai import types
+from google.genai import client
 import pytest
 
 
@@ -42,64 +32,36 @@
 _TEST_DISPLAY_NAME = f"{_TEST_PARENT}/customJobs/12345"
 _TEST_BASE_OUTPUT_DIR = "gs://test_bucket/test_base_output_dir"
 
-_TEST_CUSTOM_JOB_PROTO = gca_custom_job_compat.CustomJob(
-    display_name=_TEST_DISPLAY_NAME,
-    job_spec={
-        "base_output_directory": gca_io_compat.GcsDestination(
-            output_uri_prefix=_TEST_BASE_OUTPUT_DIR
-        ),
-    },
-    labels={"trained_by_vertex_ai": "true"},
-)
-
-
-@pytest.fixture
-def mock_create_custom_job():
-    with mock.patch.object(
-        job_service_client.JobServiceClient, "create_custom_job"
-    ) as create_custom_job_mock:
-        custom_job_proto = copy.deepcopy(_TEST_CUSTOM_JOB_PROTO)
-        custom_job_proto.name = _TEST_DISPLAY_NAME
-        custom_job_proto.state = gca_job_state_compat.JobState.JOB_STATE_PENDING
-        create_custom_job_mock.return_value = custom_job_proto
-        yield create_custom_job_mock
-
 
 class TestPromptOptimizer:
     """Unit tests for the Prompt Optimizer client."""
 
     def setup_method(self):
-        importlib.reload(aiplatform_initializer)
-        importlib.reload(aiplatform)
         importlib.reload(vertexai)
         vertexai.init(
             project=_TEST_PROJECT,
             location=_TEST_LOCATION,
         )
 
-    # @pytest.mark.usefixtures("google_auth_mock")
-    # def test_prompt_optimizer_client(self):
-    #     test_client = vertexai.Client(project=_TEST_PROJECT, location=_TEST_LOCATION)
-    #     assert test_client is not None
-    #     assert test_client._api_client.vertexai
-    #     assert test_client._api_client.project == _TEST_PROJECT
-    #     assert test_client._api_client.location == _TEST_LOCATION
+    @pytest.mark.usefixtures("google_auth_mock")
+    def test_prompt_optimizer_client(self):
+        test_client = vertexai.Client(project=_TEST_PROJECT, location=_TEST_LOCATION)
+        assert test_client.prompt_optimizer is not None
+
+    @mock.patch.object(client.Client, "_get_api_client")
+    @mock.patch.object(prompt_optimizer.PromptOptimizer, "_create_custom_job_resource")
+    def test_prompt_optimizer_optimize(self, mock_custom_job, mock_client):
+        """Test that prompt_optimizer.optimize method creates a custom job."""
+        test_client = vertexai.Client(project=_TEST_PROJECT, location=_TEST_LOCATION)
+        test_client.prompt_optimizer.optimize(
+            method="vapo",
+            config=types.PromptOptimizerVAPOConfig(
+                config_path="gs://ssusie-vapo-sdk-test/config.json",
+                wait_for_completion=False,
+                service_account="test-service-account",
+            ),
+        )
+        mock_client.assert_called_once()
+        mock_custom_job.assert_called_once()
 
-    # @mock.patch.object(client.Client, "_get_api_client")
-    # @mock.patch.object(
-    #     gcs_utils.resource_manager_utils, "get_project_number", return_value=12345
-    # )
-    # def test_prompt_optimizer_optimize(
-    #     self, mock_get_project_number, mock_client, mock_create_custom_job
-    # ):
-    #     """Test that prompt_optimizer.optimize method creates a custom job."""
-    #     test_client = vertexai.Client(project=_TEST_PROJECT, location=_TEST_LOCATION)
-    #     test_client.prompt_optimizer.optimize(
-    #         method="vapo",
-    #         config={
-    #             "config_path": "gs://ssusie-vapo-sdk-test/config.json",
-    #             "wait_for_completion": False,
-    #         },
-    #     )
-    #     mock_create_custom_job.assert_called_once()
-    #     mock_get_project_number.assert_called_once()
+    # TODO(b/415060797): add more tests for prompt_optimizer.optimize

vertexai/_genai/client.py

@@ -148,6 +148,18 @@ def evals(self):
                 ) from e
         return self._evals.Evals(self._api_client)
 
+    @property
+    @_common.experimental_warning(
+        "The Vertex SDK GenAI prompt optimizer module is experimental, and may change in future "
+        "versions."
+    )
+    def prompt_optimizer(self):
+        if self._prompt_optimizer is None:
+            self._prompt_optimizer = importlib.import_module(
+                ".prompt_optimizer", __package__
+            )
+        return self._prompt_optimizer.PromptOptimizer(self._api_client)
+
     @property
     @_common.experimental_warning(
         "The Vertex SDK GenAI async client is experimental, "