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feat: GenAI Client(evals): Add candidate name to local ADK agent scraping #6390

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feat: GenAI Client(evals): Add candidate name to local ADK agent scraping #6390

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2 changes: 1 addition & 1 deletion tests/unit/vertexai/genai/replays/test_evaluate_instances.py
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Original file line number Diff line number Diff line change
Expand Up @@ -180,7 +180,7 @@ def test_run_inference_with_agent(client):
agent="projects/977012026409/locations/us-central1/reasoningEngines/7188347537655332864",
src=test_df,
)
assert inference_result.candidate_name is None
assert inference_result.candidate_name == "agent_engine_0"
assert inference_result.gcs_source is None


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6 changes: 3 additions & 3 deletions tests/unit/vertexai/genai/test_evals.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1236,7 +1236,7 @@ def test_run_inference_with_agent_engine_and_session_inputs_dict(
}
),
)
assert inference_result.candidate_name is None
assert inference_result.candidate_name == "agent_engine_0"
assert inference_result.gcs_source is None

@mock.patch.object(_evals_utils, "EvalDatasetLoader")
Expand Down Expand Up @@ -1315,7 +1315,7 @@ def test_run_inference_with_agent_engine_and_session_inputs_literal_string(
}
),
)
assert inference_result.candidate_name is None
assert inference_result.candidate_name == "agent_engine_0"
assert inference_result.gcs_source is None

@mock.patch.object(_evals_utils, "EvalDatasetLoader")
Expand Down Expand Up @@ -1499,7 +1499,7 @@ def run_async_side_effect(*args, **kwargs):
),
expected_df.sort_values(by="prompt").reset_index(drop=True),
)
assert inference_result.candidate_name is None
assert inference_result.candidate_name == "mock_agent"
assert inference_result.gcs_source is None

def test_run_inference_with_litellm_string_prompt_format(
Expand Down
8 changes: 8 additions & 0 deletions vertexai/_genai/_evals_common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1143,6 +1143,13 @@ def _execute_inference(
candidate_name=candidate_name,
)
elif agent_engine or agent:
candidate_name = None
if agent_engine:
candidate_name = "agent_engine_0"
elif agent:
agent_config = types.evals.AgentConfig.from_agent(agent)
candidate_name = agent_config.agent_id or "agent_0"

if (
agent_engine
and not isinstance(agent_engine, str)
Expand Down Expand Up @@ -1181,6 +1188,7 @@ def _execute_inference(

evaluation_dataset = types.EvaluationDataset(
eval_dataset_df=results_df,
candidate_name=candidate_name,
)
else:
raise ValueError("Either model, agent_engine or agent must be provided.")
Expand Down
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