fix(eval): make _EvalMetricResultWithInvocation.expected_invocation optional

[giulio-leone]

Summary

Fixes #5214 — AgentEvaluator.evaluate() crashes with a pydantic ValidationError when evaluating conversation_scenario eval cases because _EvalMetricResultWithInvocation.expected_invocation is typed as required Invocation, while local_eval_service intentionally passes None for scenario-based cases.

Changes

src/google/adk/evaluation/agent_evaluator.py

1. Make expected_invocation optional (line 93):

   expected_invocation: Optional[Invocation] = None

   This aligns with the public EvalMetricResultPerInvocation model in eval_metrics.py:323.

2. Guard downstream attribute access in _print_details (lines 439–456):
   Added if per_invocation_result.expected_invocation else None guards for user_content, final_response, and intermediate_data accesses. Both _convert_content_to_text and _convert_tool_calls_to_text already handle None gracefully.

Tests

Added tests/unittests/evaluation/test_eval_metric_result_with_invocation.py with 5 regression tests:

• Construction with None / omitted / real expected_invocation
• _get_eval_metric_results_with_invocation propagates None
• _print_details does not crash with None expected invocation

All 5 tests pass. Existing eval tests unaffected (2 pre-existing failures in test_custom_metric_evaluator.py confirmed on main).

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[adk-bot]

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