feat: GenAI Client(evals): Patch agent config map to agent data

tests/unit/vertexai/genai/test_evals.py

@@ -1387,6 +1387,11 @@ def test_run_inference_with_local_agent(
         )
 
         mock_agent_instance = mock.Mock()
+        mock_agent_instance.name = "mock_agent"
+        mock_agent_instance.description = "mock description"
+        mock_agent_instance.instruction = "mock instruction"
+        mock_agent_instance.tools = []
+        mock_agent_instance.sub_agents = []
         mock_llm_agent.return_value = mock_agent_instance
         mock_session_service.return_value.create_session = mock.AsyncMock()
         mock_runner_instance = mock_runner.return_value
@@ -1914,6 +1919,35 @@ def test_run_agent_internal_multi_turn_success(self, mock_run_agent):
             {"turn_index": 1, "turn_id": "t2", "events": []},
         ]
 
+    @mock.patch.object(_evals_common, "_run_agent")
+    def test_run_agent_internal_multi_turn_with_agent(self, mock_run_agent):
+        mock_run_agent.return_value = [
+            [
+                {"turn_index": 0, "turn_id": "t1", "events": []},
+            ]
+        ]
+        prompt_dataset = pd.DataFrame({"prompt": ["p1"], "conversation_plan": ["plan"]})
+        mock_agent = mock.Mock()
+        mock_agent.name = "mock_agent"
+        mock_agent.description = "mock description"
+        mock_agent.instruction = "mock instruction"
+        mock_agent.tools = []
+        mock_agent.sub_agents = []
+        mock_api_client = mock.Mock()
+        result_df = _evals_common._run_agent_internal(
+            api_client=mock_api_client,
+            agent_engine=None,
+            agent=mock_agent,
+            prompt_dataset=prompt_dataset,
+        )
+
+        assert "agent_data" in result_df.columns
+        agent_data = result_df["agent_data"][0]
+        assert agent_data["turns"] == [
+            {"turn_index": 0, "turn_id": "t1", "events": []},
+        ]
+        assert "mock_agent" in agent_data["agents"]
+
     @mock.patch("vertexai._genai._evals_common.ADK_SessionInput")  # fmt: skip
     @mock.patch("vertexai._genai._evals_common.EvaluationGenerator")  # fmt: skip
     @mock.patch("vertexai._genai._evals_common.LlmBackedUserSimulator")  # fmt: skip

vertexai/_genai/_evals_common.py

@@ -1603,18 +1603,25 @@ def _run_agent_internal(
     processed_intermediate_events = []
     processed_responses = []
     processed_agent_data = []
+    agent_data_agents = None
+    if agent:
+        agent_data_agents = types.evals.AgentData._get_agents_map(agent)
 
     for resp_item in raw_responses:
         intermediate_events_row: list[dict[str, Any]] = []
-        response_row = None
-        agent_data_row = None
+        response_row: Optional[Union[str, dict[str, Any]]] = None
+        agent_data_row: Optional[Union[str, dict[str, Any]]] = None
 
         if _is_multi_turn_agent_run(user_simulator_config, prompt_dataset):
             if isinstance(resp_item, dict) and "error" in resp_item:
-                response_row = json.dumps(resp_item)
+                agent_data_row = json.dumps(resp_item)
             else:
                 # TODO: Migrate single turn agent run result to AgentData.
-                agent_data_row = types.evals.AgentData(turns=resp_item).model_dump()
+                agent_data_row = types.evals.AgentData(
+                    turns=resp_item,
+                    agents=agent_data_agents,
+                ).model_dump()
+
         else:
             if isinstance(resp_item, list):
                 try: