Initial commit: QMDSearch 分层信息检索服务

- FastAPI + Qdrant + Redis + Ollama 技术栈
- L1→L2→L3→chunk 四层分层检索（dense + sparse RRF 融合）
- 文档三级总结与 2.5 级回退
- query 解析路由与分类
- /admin 管理页面

tests/test_run_eval.py

@@ -0,0 +1,131 @@
+"""run_eval 门槛常量与报告组装纯函数单元测试"""
+
+from pathlib import Path
+from typing import Any
+
+from scripts.eval.run_eval import (
+    THRESHOLD_HALLUCINATION,
+    THRESHOLD_L1_ER,
+    THRESHOLD_L3_ER,
+    THRESHOLD_PRUNING_LOSS,
+    _build_report,
+    _fmt,
+    _mark,
+)
+
+
+class TestThresholds:
+    """Spec 规定的门槛值：L1 ER ≥ 0.85 / L3 ER ≥ 0.9 / 幻觉率 < 2% / Pruning Loss < 8%"""
+
+    def test_l1_entity_recall_threshold(self) -> None:
+        assert THRESHOLD_L1_ER == 0.85
+
+    def test_l3_entity_recall_threshold(self) -> None:
+        assert THRESHOLD_L3_ER == 0.9
+
+    def test_hallucination_threshold(self) -> None:
+        assert THRESHOLD_HALLUCINATION == 0.02
+
+    def test_pruning_loss_threshold(self) -> None:
+        assert THRESHOLD_PRUNING_LOSS == 0.08
+
+
+class TestMark:
+    def test_pass(self) -> None:
+        assert _mark(True) == "✅"
+
+    def test_fail(self) -> None:
+        assert _mark(False) == "❌"
+
+
+class TestFmt:
+    def test_none_returns_na(self) -> None:
+        assert _fmt(None) == "N/A"
+        assert _fmt(None, percent=True) == "N/A"
+
+    def test_decimal_format(self) -> None:
+        assert _fmt(0.85) == "0.8500"
+
+    def test_percent_format(self) -> None:
+        assert _fmt(0.1234, percent=True) == "12.3%"
+        assert _fmt(0.02, percent=True) == "2.0%"
+
+
+def _doc_record(**overrides: Any) -> dict:
+    record: dict[str, Any] = {
+        "id": "d1",
+        "title": "考勤制度",
+        "golden_category": "制度",
+        "category": "制度",
+        "entity_recall_l1": 0.9,
+        "entity_recall_l3": 0.95,
+        "hallucination_rate": 0.01,
+        "taxonomy_consistency": True,
+    }
+    record.update(overrides)
+    return record
+
+
+def _report_kwargs(**overrides: Any) -> dict:
+    kwargs: dict[str, Any] = {
+        "regression_path": Path("regression_set.json"),
+        "doc_records": [_doc_record()],
+        "query_summary": {"total": 4, "positive": 3, "negative": 1, "negative_false_alarm": 0},
+        "hier_metrics": {"precision@5": 0.6, "recall@10": 0.8},
+        "baseline_metrics": {"precision@5": 0.4, "recall@10": 0.7},
+        "routing": {"precision": 0.75, "recall": 0.8, "f1": 0.77},
+        "prune_loss": 0.05,
+        "judge_enabled": True,
+        "kept_data": False,
+    }
+    kwargs.update(overrides)
+    return kwargs
+
+
+class TestBuildReport:
+    def test_baseline_comparison_columns(self) -> None:
+        report = _build_report(**_report_kwargs())
+        assert "| 指标 | 分层检索 | 平铺 baseline |" in report
+        assert "| Precision@5 | 0.6000 | 0.4000 |" in report
+        assert "| Recall@10 | 0.8000 | 0.7000 |" in report
+
+    def test_doc_table_row(self) -> None:
+        report = _build_report(**_report_kwargs())
+        assert "| d1 | 考勤制度 | 制度 | 制度 | 0.9000 | 0.9500 | 1.0% | 是 |" in report
+
+    def test_threshold_pass_marks(self) -> None:
+        report = _build_report(**_report_kwargs())
+        assert "| L1 Entity Recall | 0.9000 | ≥ 0.85 | ✅ |" in report
+        assert "| L3 Entity Recall | 0.9500 | ≥ 0.9 | ✅ |" in report
+        assert "| Hallucination Rate | 1.0% | < 2% | ✅ |" in report
+        assert "| Pruning Loss | 5.0% | < 8% | ✅ |" in report
+
+    def test_threshold_fail_marks(self) -> None:
+        report = _build_report(
+            **_report_kwargs(
+                doc_records=[
+                    _doc_record(
+                        entity_recall_l1=0.8,
+                        entity_recall_l3=0.7,
+                        hallucination_rate=0.05,
+                        taxonomy_consistency=False,
+                    )
+                ],
+                prune_loss=0.2,
+            )
+        )
+        assert "| L1 Entity Recall | 0.8000 | ≥ 0.85 | ❌ |" in report
+        assert "| L3 Entity Recall | 0.7000 | ≥ 0.9 | ❌ |" in report
+        assert "| Hallucination Rate | 5.0% | < 2% | ❌ |" in report
+        assert "| Pruning Loss | 20.0% | < 8% | ❌ |" in report
+        assert " | 否 |" in report
+
+    def test_judge_skipped_renders_na(self) -> None:
+        report = _build_report(
+            **_report_kwargs(
+                doc_records=[_doc_record(hallucination_rate=None, taxonomy_consistency=None)],
+                judge_enabled=False,
+            )
+        )
+        assert "N/A" in report
+        assert "跳过" in report