"""评审服务:保留真实失败原因,便于 internal eval 页面排障。""" import pytest from app.core.llm_call import LLMCallError from app.features.evaluation.judge_schemas import ConversationJudgeOutput from app.features.evaluation.judge_service import EvalJudgeService def _conversation_payload() -> dict: return { "emotion_carry": 10, "empathy_depth": 8, "emotion_safety": 6, "emotion_guidance": 6, "fact_mining": 8, "info_completeness_guide": 8, "info_depth_mining": 9, "persona_understanding": 7, "persona_consistency_verify": 4, "persona_expression_guide": 4, "interview_structure": 6, "context_memory": 5, "rhythm_control": 4, "question_quality": 7, "follow_up_depth": 5, "non_leading": 3, "total_score": 100.0, "rationale": "整体表现稳定。", } @pytest.mark.asyncio async def test_judge_conversation_result_preserves_validation_error( monkeypatch: pytest.MonkeyPatch, ) -> None: async def _boom(*args, **kwargs): raise LLMCallError( "validation", "pydantic validation failed: total_score mismatch", ) monkeypatch.setattr("app.features.evaluation.judge_service.allm_json_call", _boom) svc = EvalJudgeService(object()) result = await svc.judge_conversation_result(full_transcript="[Turn 1]\n用户: hi\nAI: hello") assert result.output is None assert result.error is not None assert "结果校验失败" in result.error assert "total_score mismatch" in result.error @pytest.mark.asyncio async def test_judge_conversation_wrapper_keeps_legacy_shape( monkeypatch: pytest.MonkeyPatch, ) -> None: expected = ConversationJudgeOutput.model_validate(_conversation_payload()) async def _ok(*args, **kwargs): return expected monkeypatch.setattr("app.features.evaluation.judge_service.allm_json_call", _ok) svc = EvalJudgeService(object()) out = await svc.judge_conversation(full_transcript="[Turn 1]\n用户: hi\nAI: hello") assert out == expected """Evaluation judge prompt assembly tests.""" from app.features.evaluation.judge_service import _build_memoir_judge_prompt def test_build_memoir_prompt_includes_source_and_reference_evidence() -> None: prompt = _build_memoir_judge_prompt( memoir_markdown="# 当前正文\n他后来去了南方。", source_transcript="用户: 我后来去了深圳工作。", reference_memoir_markdown="# 导出基线\n他去了深圳。", evidence_notes="必须严格核对真实性。", ) assert "【评审说明】" in prompt assert "【原始访谈/证据】" in prompt assert "用户: 我后来去了深圳工作。" in prompt assert "【参考基线/导出成稿】" in prompt assert "【当前回忆录正文】" in prompt def test_build_memoir_prompt_requires_conservative_scoring_without_evidence() -> None: prompt = _build_memoir_judge_prompt( memoir_markdown="# 当前正文\n他后来去了南方。" ) assert "无可用原始访谈证据" in prompt assert "必须保守打分" in prompt