chore: GenAI Client(evals) - Refactor generate_user_scenarios to use AgentInfo.

PiperOrigin-RevId: 885274826

Author: jsondai

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

@@ -65,7 +65,7 @@
     ),
 )
 INFERENCE_CONFIG = types.EvaluationRunInferenceConfig(
-    model="projects/503583131166/locations/us-central1/publishers/google/models/gemini-2.5-flash"
+    model="projects/977012026409/locations/us-central1/publishers/google/models/gemini-2.5-flash"
 )
 TOOL = genai_types.Tool(
     function_declarations=[
@@ -82,8 +82,14 @@
 AGENT_INFO = types.evals.AgentInfo(
     agent_resource_name="projects/123/locations/us-central1/reasoningEngines/456",
     name="agent-1",
-    instruction="agent-1 instruction",
-    tool_declarations=[TOOL],
+    agents={
+        "agent-1": types.evals.AgentConfig(
+            agent_id="agent-1",
+            instruction="agent-1 instruction",
+            tools=[TOOL],
+        )
+    },
+    root_agent_id="agent-1",
 )
 DEFAULT_PROMPT_TEMPLATE = "{prompt}"
 INPUT_DF_WITH_CONTEXT_AND_HISTORY = pd.DataFrame(
@@ -96,9 +102,9 @@
     }
 )
 CANDIDATE_NAME = "candidate_1"
-MODEL_NAME = "projects/503583131166/locations/us-central1/publishers/google/models/gemini-2.5-flash"
+MODEL_NAME = "projects/977012026409/locations/us-central1/publishers/google/models/gemini-2.5-flash"
 EVAL_SET_NAME = (
-    "projects/503583131166/locations/us-central1/evaluationSets/6619939608513740800"
+    "projects/977012026409/locations/us-central1/evaluationSets/6619939608513740800"
 )
 
 
@@ -140,12 +146,7 @@ def test_create_eval_run_data_source_evaluation_set(client):
     assert evaluation_run.inference_configs[
         AGENT_INFO.name
     ] == types.EvaluationRunInferenceConfig(
-        agent_config=types.EvaluationRunAgentConfig(
-            developer_instruction=genai_types.Content(
-                parts=[genai_types.Part(text="agent-1 instruction")]
-            ),
-            tools=[TOOL],
-        )
+        agent_configs=AGENT_INFO.agents,
     )
     assert evaluation_run.labels == {
         "vertex-ai-evaluation-agent-engine-id": "456",

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

@@ -22,24 +22,27 @@
 def test_gen_user_scenarios(client):
     """Tests that generate_user_scenarios() correctly calls the API and parses the response."""
     eval_dataset = client.evals.generate_user_scenarios(
-        agents={
-            "booking-agent": types.evals.AgentConfig(
-                agent_id="booking-agent",
-                agent_type="service_agent",
-                description="An agent capable of booking flights and hotels.",
-                instruction="You are a helpful travel assistant. Use tools to find flights.",
-                tools=[
-                    {
-                        "function_declarations": [
-                            {
-                                "name": "search_flights",
-                                "description": "Search for available flights.",
-                            }
-                        ]
-                    }
-                ],
-            )
-        },
+        agent_info=types.evals.AgentInfo(
+            agents={
+                "booking-agent": types.evals.AgentConfig(
+                    agent_id="booking-agent",
+                    agent_type="service_agent",
+                    description="An agent capable of booking flights and hotels.",
+                    instruction="You are a helpful travel assistant. Use tools to find flights.",
+                    tools=[
+                        {
+                            "function_declarations": [
+                                {
+                                    "name": "search_flights",
+                                    "description": "Search for available flights.",
+                                }
+                            ]
+                        }
+                    ],
+                )
+            },
+            root_agent_id="booking-agent",
+        ),
         user_scenario_generation_config=types.evals.UserScenarioGenerationConfig(
             user_scenario_count=2,
             simulation_instruction=(
@@ -49,18 +52,11 @@ def test_gen_user_scenarios(client):
             environment_data="Today is Monday. Flights to Paris are available.",
             model_name="gemini-2.5-flash",
         ),
-        root_agent_id="booking-agent",
     )
     assert isinstance(eval_dataset, types.EvaluationDataset)
     assert len(eval_dataset.eval_cases) == 2
-    assert (
-        eval_dataset.eval_cases[0].user_scenario.starting_prompt
-        == "I want to find a flight from New York to London."
-    )
-    assert (
-        eval_dataset.eval_cases[0].user_scenario.conversation_plan
-        == "Actually, I meant Paris, not London. Please search for flights to Paris."
-    )
+    assert eval_dataset.eval_cases[0].user_scenario.starting_prompt
+    assert eval_dataset.eval_cases[0].user_scenario.conversation_plan
 
 
 pytest_plugins = ("pytest_asyncio",)
@@ -70,24 +66,27 @@ def test_gen_user_scenarios(client):
 async def test_gen_user_scenarios_async(client):
     """Tests that generate_user_scenarios() async correctly calls the API and parses the response."""
     eval_dataset = await client.aio.evals.generate_user_scenarios(
-        agents={
-            "booking-agent": types.evals.AgentConfig(
-                agent_id="booking-agent",
-                agent_type="service_agent",
-                description="An agent capable of booking flights and hotels.",
-                instruction="You are a helpful travel assistant. Use tools to find flights.",
-                tools=[
-                    {
-                        "function_declarations": [
-                            {
-                                "name": "search_flights",
-                                "description": "Search for available flights.",
-                            }
-                        ]
-                    }
-                ],
-            )
-        },
+        agent_info=types.evals.AgentInfo(
+            agents={
+                "booking-agent": types.evals.AgentConfig(
+                    agent_id="booking-agent",
+                    agent_type="service_agent",
+                    description="An agent capable of booking flights and hotels.",
+                    instruction="You are a helpful travel assistant. Use tools to find flights.",
+                    tools=[
+                        {
+                            "function_declarations": [
+                                {
+                                    "name": "search_flights",
+                                    "description": "Search for available flights.",
+                                }
+                            ]
+                        }
+                    ],
+                )
+            },
+            root_agent_id="booking-agent",
+        ),
         user_scenario_generation_config=types.evals.UserScenarioGenerationConfig(
             user_scenario_count=2,
             simulation_instruction=(
@@ -97,18 +96,11 @@ async def test_gen_user_scenarios_async(client):
             environment_data="Today is Monday. Flights to Paris are available.",
             model_name="gemini-2.5-flash",
         ),
-        root_agent_id="booking-agent",
     )
     assert isinstance(eval_dataset, types.EvaluationDataset)
     assert len(eval_dataset.eval_cases) == 2
-    assert (
-        eval_dataset.eval_cases[1].user_scenario.starting_prompt
-        == "Find me a flight from Boston to Rome for next month."
-    )
-    assert (
-        eval_dataset.eval_cases[1].user_scenario.conversation_plan
-        == "Wait, change of plans. I need to go to Milan instead, and it needs to be a round trip, returning two weeks after departure."
-    )
+    assert eval_dataset.eval_cases[1].user_scenario.starting_prompt
+    assert eval_dataset.eval_cases[1].user_scenario.conversation_plan
 
 
 pytestmark = pytest_helper.setup(