feat: GenAI SDK client - Enabling zero-shot prompt optimization for prompts from Android API by passing optimization_target=vertexai.types.OptimizeTarget.OPTIMIZATION_TARGET_GEMINI_NANO in the config

tests/unit/vertexai/genai/replays/test_prompt_optimizer_optimize_prompt_return_type.py

@@ -27,6 +27,20 @@ def test_optimize_prompt(client):
     assert response.raw_text_response
 
 
+# def test_optimize_prompt_w_optimization_target(client):
+#     """Tests the optimize request parameters method with optimization target."""
+#     from google.genai import types as genai_types
+#     test_prompt = "Generate system instructions for analyzing medical articles"
+#     response = client.prompt_optimizer.optimize_prompt(
+#         prompt=test_prompt,
+#         config=types.OptimizeConfig(
+#             optimization_target=types.OptimizeTarget.OPTIMIZATION_TARGET_GEMINI_NANO,
+#         ),
+#     )
+#     assert isinstance(response, types.OptimizeResponse)
+#     assert response.raw_text_response
+
+
 pytestmark = pytest_helper.setup(
     file=__file__,
     globals_for_file=globals(),

tests/unit/vertexai/genai/test_prompt_optimizer.py

@@ -69,10 +69,57 @@ def test_prompt_optimizer_optimize(self, mock_custom_job, mock_client):
     def test_prompt_optimizer_optimize_prompt(
         self, mock_custom_optimize_prompt, mock_client
     ):
-        """Test that prompt_optimizer.optimize method creates a custom job."""
+        """Test that prompt_optimizer.optimize_prompt method calls optimize_prompt API."""
         test_client = vertexai.Client(project=_TEST_PROJECT, location=_TEST_LOCATION)
         test_client.prompt_optimizer.optimize_prompt(prompt="test_prompt")
         mock_client.assert_called_once()
         mock_custom_optimize_prompt.assert_called_once()
 
-    # TODO(b/415060797): add more tests for prompt_optimizer.optimize
+    @mock.patch.object(prompt_optimizer.PromptOptimizer, "_custom_optimize_prompt")
+    def test_prompt_optimizer_optimize_prompt_with_optimization_target(
+        self, mock_custom_optimize_prompt
+    ):
+        """Test that prompt_optimizer.optimize_prompt method calls _custom_optimize_prompt with optimization_target."""
+        test_client = vertexai.Client(project=_TEST_PROJECT, location=_TEST_LOCATION)
+        config = types.OptimizeConfig(
+            optimization_target=types.OptimizeTarget.OPTIMIZATION_TARGET_GEMINI_NANO,
+        )
+        test_client.prompt_optimizer.optimize_prompt(
+            prompt="test_prompt",
+            config=config,
+        )
+        mock_custom_optimize_prompt.assert_called_once_with(
+            content=mock.ANY,
+            config=config,
+        )
+
+    @pytest.mark.asyncio
+    @mock.patch.object(prompt_optimizer.AsyncPromptOptimizer, "_custom_optimize_prompt")
+    async def test_async_prompt_optimizer_optimize_prompt(
+        self, mock_custom_optimize_prompt
+    ):
+        """Test that async prompt_optimizer.optimize_prompt method calls optimize_prompt API."""
+        test_client = vertexai.Client(project=_TEST_PROJECT, location=_TEST_LOCATION)
+        await test_client.aio.prompt_optimizer.optimize_prompt(prompt="test_prompt")
+        mock_custom_optimize_prompt.assert_called_once()
+
+    @pytest.mark.asyncio
+    @mock.patch.object(prompt_optimizer.AsyncPromptOptimizer, "_custom_optimize_prompt")
+    async def test_async_prompt_optimizer_optimize_prompt_with_optimization_target(
+        self, mock_custom_optimize_prompt
+    ):
+        """Test that async prompt_optimizer.optimize_prompt calls optimize_prompt with optimization_target."""
+        test_client = vertexai.Client(project=_TEST_PROJECT, location=_TEST_LOCATION)
+        config = types.OptimizeConfig(
+            optimization_target=types.OptimizeTarget.OPTIMIZATION_TARGET_GEMINI_NANO,
+        )
+        await test_client.aio.prompt_optimizer.optimize_prompt(
+            prompt="test_prompt",
+            config=config,
+        )
+        mock_custom_optimize_prompt.assert_called_once_with(
+            content=mock.ANY,
+            config=config,
+        )
+
+    # # TODO(b/415060797): add more tests for prompt_optimizer.optimize

vertexai/_genai/prompt_optimizer.py

@@ -167,6 +167,22 @@ def _GetCustomJobParameters_to_vertex(
     return to_object
 
 
+def _OptimizeConfig_to_vertex(
+    from_object: Union[dict[str, Any], object],
+    parent_object: Optional[dict[str, Any]] = None,
+) -> dict[str, Any]:
+    to_object: dict[str, Any] = {}
+
+    if getv(from_object, ["optimization_target"]) is not None:
+        setv(
+            parent_object,
+            ["optimizationTarget"],
+            getv(from_object, ["optimization_target"]),
+        )
+
+    return to_object
+
+
 def _OptimizeRequestParameters_to_vertex(
     from_object: Union[dict[str, Any], object],
     parent_object: Optional[dict[str, Any]] = None,
@@ -176,7 +192,11 @@ def _OptimizeRequestParameters_to_vertex(
         setv(to_object, ["content"], getv(from_object, ["content"]))
 
     if getv(from_object, ["config"]) is not None:
-        setv(to_object, ["config"], getv(from_object, ["config"]))
+        setv(
+            to_object,
+            ["config"],
+            _OptimizeConfig_to_vertex(getv(from_object, ["config"]), to_object),
+        )
 
     return to_object
 
@@ -468,7 +488,10 @@ def optimize(
         return job
 
     def optimize_prompt(
-        self, *, prompt: str, config: Optional[types.OptimizeConfig] = None
+        self,
+        *,
+        prompt: str,
+        config: Optional[types.OptimizeConfig] = None,
     ) -> types.OptimizeResponse:
         """Makes an API request to _optimize_prompt and returns the parsed response.
 
@@ -480,19 +503,21 @@ def optimize_prompt(
 
         Args:
           prompt: The prompt to optimize.
-          config: The configuration for prompt optimization. Currently, config is
-            not supported for a single prompt optimization.
+          config: Optional.The configuration for prompt optimization. To optimize
+            prompts from Android API provide
+            types.OptimizeConfig(
+                optimization_target=types.OptimizeTarget.OPTIMIZATION_TARGET_GEMINI_NANO
+            )
         Returns:
           The parsed response from the API request.
         """
-        if config is not None:
-            raise ValueError(
-                "Currently, config is not supported for a single prompt optimization."
-            )
 
         prompt = genai_types.Content(parts=[genai_types.Part(text=prompt)], role="user")
         # TODO: b/435653980 - replace the custom method with a generated method.
-        return self._custom_optimize_prompt(content=prompt)
+        return self._custom_optimize_prompt(
+            content=prompt,
+            config=config,
+        )
 
     def _custom_optimize_prompt(
         self,
@@ -511,7 +536,6 @@ def _custom_optimize_prompt(
             content=content,
             config=config,
         )
-
         request_url_dict: Optional[dict[str, str]]
         if not self._api_client.vertexai:
             raise ValueError("This method is only supported in the Vertex AI client.")
@@ -850,7 +874,6 @@ async def _custom_optimize_prompt(
             content=content,
             config=config,
         )
-
         request_url_dict: Optional[dict[str, str]]
         if not self._api_client.vertexai:
             raise ValueError("This method is only supported in the Vertex AI client.")
@@ -909,7 +932,10 @@ async def _custom_optimize_prompt(
         return final_response
 
     async def optimize_prompt(
-        self, *, prompt: str, config: Optional[types.OptimizeConfig] = None
+        self,
+        *,
+        prompt: str,
+        config: Optional[types.OptimizeConfig] = None,
     ) -> types.OptimizeResponse:
         """Makes an async request to _optimize_prompt and returns an optimized prompt.
 
@@ -920,16 +946,18 @@ async def optimize_prompt(
 
         Args:
           prompt: The prompt to optimize.
-          config: The configuration for prompt optimization. Currently, config is
-            not supported for a single prompt optimization.
+          config: Optional.The configuration for prompt optimization. To optimize
+            prompts from Android API provide
+            types.OptimizeConfig(
+                optimization_target=types.OptimizeTarget.OPTIMIZATION_TARGET_GEMINI_NANO
+            )
         Returns:
           The parsed response from the API request.
         """
-        if config is not None:
-            raise ValueError(
-                "Currently, config is not supported for a single prompt optimization."
-            )
 
         prompt = genai_types.Content(parts=[genai_types.Part(text=prompt)], role="user")
         # TODO: b/435653980 - replace the custom method with a generated method.
-        return await self._custom_optimize_prompt(content=prompt)
+        return await self._custom_optimize_prompt(
+            content=prompt,
+            config=config,
+        )

vertexai/_genai/types/__init__.py

@@ -584,6 +584,7 @@
 from .common import OptimizeResponseEndpointDict
 from .common import OptimizeResponseEndpointOrDict
 from .common import OptimizeResponseOrDict
+from .common import OptimizeTarget
 from .common import PairwiseChoice
 from .common import PairwiseMetricInput
 from .common import PairwiseMetricInputDict
@@ -1828,6 +1829,7 @@
     "RubricContentType",
     "EvaluationRunState",
     "Importance",
+    "OptimizeTarget",
     "GenerateMemoriesResponseGeneratedMemoryAction",
     "PromptData",
     "PromptDataDict",

vertexai/_genai/types/common.py

@@ -331,6 +331,13 @@ class Importance(_common.CaseInSensitiveEnum):
     """Low importance."""
 
 
+class OptimizeTarget(_common.CaseInSensitiveEnum):
+    """None"""
+
+    OPTIMIZATION_TARGET_GEMINI_NANO = "OPTIMIZATION_TARGET_GEMINI_NANO"
+    """The data driven prompt optimizer designer for prompts from Android core API."""
+
+
 class GenerateMemoriesResponseGeneratedMemoryAction(_common.CaseInSensitiveEnum):
     """The action to take."""
 
@@ -3986,6 +3993,9 @@ class OptimizeConfig(_common.BaseModel):
     http_options: Optional[genai_types.HttpOptions] = Field(
         default=None, description="""Used to override HTTP request options."""
     )
+    optimization_target: Optional[OptimizeTarget] = Field(
+        default=None, description=""""""
+    )
 
 
 class OptimizeConfigDict(TypedDict, total=False):
@@ -3994,6 +4004,9 @@ class OptimizeConfigDict(TypedDict, total=False):
     http_options: Optional[genai_types.HttpOptionsDict]
     """Used to override HTTP request options."""
 
+    optimization_target: Optional[OptimizeTarget]
+    """"""
+
 
 OptimizeConfigOrDict = Union[OptimizeConfig, OptimizeConfigDict]