feat: GenAI Client(evals) - auto-infer metric/candidate and validate inputs for generate_loss_clusters

PiperOrigin-RevId: 894079615

Author: vertex-sdk-bot

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

@@ -0,0 +1,132 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# pylint: disable=protected-access,bad-continuation,missing-function-docstring
+
+from tests.unit.vertexai.genai.replays import pytest_helper
+from vertexai._genai import types
+import pytest
+
+
+def _make_eval_result():
+    """Creates an EvaluationResult with representative data for loss analysis."""
+    return types.EvaluationResult(
+        eval_case_results=[
+            types.EvalCaseResult(
+                eval_case_index=0,
+                response_candidate_results=[
+                    types.ResponseCandidateResult(
+                        response_index=0,
+                        metric_results={
+                            "multi_turn_task_success_v1": types.EvalCaseMetricResult(
+                                score=0.0,
+                                explanation="Failed tool invocation",
+                            )
+                        },
+                    )
+                ],
+            )
+        ],
+        evaluation_dataset=[
+            types.EvaluationDataset(
+                eval_cases=[
+                    types.EvalCase(
+                        agent_data=types.evals.AgentData(
+                            agents={
+                                "travel-agent": types.evals.AgentConfig(
+                                    agent_id="travel-agent",
+                                    agent_type="ToolUseAgent",
+                                    description="A travel agent that can book flights.",
+                                )
+                            },
+                            turns=[
+                                types.evals.ConversationTurn(
+                                    turn_index=0,
+                                    events=[
+                                        types.evals.AgentEvent(
+                                            author="user",
+                                            content={
+                                                "parts": [
+                                                    {"text": "Book a flight to Paris."}
+                                                ]
+                                            },
+                                        ),
+                                        types.evals.AgentEvent(
+                                            author="travel-agent",
+                                            content={
+                                                "parts": [
+                                                    {"text": "I can help with that."}
+                                                ]
+                                            },
+                                        ),
+                                    ],
+                                )
+                            ],
+                        )
+                    )
+                ]
+            )
+        ],
+        metadata=types.EvaluationRunMetadata(candidate_names=["travel-agent"]),
+    )
+
+
+def test_gen_loss_clusters(client):
+    """Tests that generate_loss_clusters() returns GenerateLossClustersResponse."""
+    eval_result = _make_eval_result()
+    response = client.evals.generate_loss_clusters(
+        eval_result=eval_result,
+        config=types.LossAnalysisConfig(
+            metric="multi_turn_task_success_v1",
+            candidate="travel-agent",
+        ),
+    )
+    assert isinstance(response, types.GenerateLossClustersResponse)
+    assert len(response.results) >= 1
+    result = response.results[0]
+    assert result.config.metric == "multi_turn_task_success_v1"
+    assert result.config.candidate == "travel-agent"
+    assert len(result.clusters) >= 1
+    for cluster in result.clusters:
+        assert cluster.cluster_id is not None
+        assert cluster.taxonomy_entry is not None
+        assert cluster.taxonomy_entry.l1_category is not None
+
+
+pytest_plugins = ("pytest_asyncio",)
+
+
+@pytest.mark.asyncio
+async def test_gen_loss_clusters_async(client):
+    """Tests that generate_loss_clusters() async returns GenerateLossClustersResponse."""
+    eval_result = _make_eval_result()
+    response = await client.aio.evals.generate_loss_clusters(
+        eval_result=eval_result,
+        config=types.LossAnalysisConfig(
+            metric="multi_turn_task_success_v1",
+            candidate="travel-agent",
+        ),
+    )
+    assert isinstance(response, types.GenerateLossClustersResponse)
+    assert len(response.results) >= 1
+    result = response.results[0]
+    assert result.config.metric == "multi_turn_task_success_v1"
+    assert len(result.clusters) >= 1
+
+
+pytestmark = pytest_helper.setup(
+    file=__file__,
+    globals_for_file=globals(),
+    test_method="evals.generate_loss_clusters",
+)