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_judge.py

@@ -0,0 +1,99 @@
+"""LLM-as-judge 评测指标单元测试（FakeOllama 替身，不依赖真实模型）"""
+
+import pytest
+
+from scripts.eval.judge import hallucination_rate, taxonomy_consistency
+
+
+class FakeOllama:
+    """记录 prompt 并按序返回预设响应（或抛出预设异常）的 OllamaClient 替身"""
+
+    def __init__(self, responses: list[str] | None = None, error: Exception | None = None) -> None:
+        self.prompts: list[str] = []
+        self.json_modes: list[bool] = []
+        self._responses = list(responses or [])
+        self._error = error
+
+    async def generate(self, prompt: str, json_mode: bool = False) -> str:
+        self.prompts.append(prompt)
+        self.json_modes.append(json_mode)
+        if self._error is not None:
+            raise self._error
+        return self._responses.pop(0)
+
+
+def _assertions_json(*supported: bool) -> str:
+    """构造 hallucination 判定的 JSON 输出，每个 bool 对应一条断言的 supported"""
+    claims = ", ".join(f'{{"claim": "断言{i}", "supported": {str(flag).lower()}}}' for i, flag in enumerate(supported))
+    return f'{{"assertions": [{claims}]}}'
+
+
+class TestHallucinationRate:
+    async def test_all_supported_returns_zero(self) -> None:
+        ollama = FakeOllama([_assertions_json(True, True, True)])
+        assert await hallucination_rate("摘要", "原文", ollama) == 0.0  # type: ignore[arg-type]
+
+    async def test_prompt_contains_source_and_summary(self) -> None:
+        ollama = FakeOllama([_assertions_json(True)])
+        await hallucination_rate("这是摘要内容", "这是原文内容", ollama)  # type: ignore[arg-type]
+        assert len(ollama.prompts) == 1
+        assert "这是摘要内容" in ollama.prompts[0]
+        assert "这是原文内容" in ollama.prompts[0]
+        assert ollama.json_modes == [True]
+
+    async def test_two_of_five_unsupported(self) -> None:
+        ollama = FakeOllama([_assertions_json(True, False, True, False, True)])
+        rate = await hallucination_rate("摘要", "原文", ollama)  # type: ignore[arg-type]
+        assert rate == pytest.approx(0.4)
+
+    async def test_non_json_output_returns_zero(self) -> None:
+        ollama = FakeOllama(["我无法完成这个判定任务。"])
+        assert await hallucination_rate("摘要", "原文", ollama) == 0.0  # type: ignore[arg-type]
+
+    async def test_missing_assertions_field_returns_zero(self) -> None:
+        ollama = FakeOllama(['{"result": "ok"}'])
+        assert await hallucination_rate("摘要", "原文", ollama) == 0.0  # type: ignore[arg-type]
+
+    async def test_generate_error_returns_zero(self) -> None:
+        ollama = FakeOllama(error=RuntimeError("Ollama 不可用"))
+        assert await hallucination_rate("摘要", "原文", ollama) == 0.0  # type: ignore[arg-type]
+
+    async def test_noisy_output_json_extracted(self) -> None:
+        # 模型输出前后带噪声时仍能提取首个 JSON 对象
+        ollama = FakeOllama([f"先分析一下。\n{_assertions_json(True, False)}\n以上。"])
+        rate = await hallucination_rate("摘要", "原文", ollama)  # type: ignore[arg-type]
+        assert rate == pytest.approx(0.5)
+
+    async def test_claims_truncated_to_max(self) -> None:
+        # 超过 _MAX_CLAIMS(5) 的断言不计入：前 5 条全支持，第 6/7 条不支持 → 0.0
+        ollama = FakeOllama([_assertions_json(True, True, True, True, True, False, False)])
+        assert await hallucination_rate("摘要", "原文", ollama) == 0.0  # type: ignore[arg-type]
+
+
+class TestTaxonomyConsistency:
+    async def test_consistent_true(self) -> None:
+        ollama = FakeOllama(['{"consistent": true}'])
+        assert await taxonomy_consistency("摘要", "制度", ollama) is True  # type: ignore[arg-type]
+
+    async def test_consistent_false(self) -> None:
+        ollama = FakeOllama(['{"consistent": false}'])
+        assert await taxonomy_consistency("摘要", "制度", ollama) is False  # type: ignore[arg-type]
+
+    async def test_prompt_contains_category_and_summary(self) -> None:
+        ollama = FakeOllama(['{"consistent": true}'])
+        await taxonomy_consistency("这是摘要内容", "人事制度", ollama)  # type: ignore[arg-type]
+        assert "人事制度" in ollama.prompts[0]
+        assert "这是摘要内容" in ollama.prompts[0]
+        assert ollama.json_modes == [True]
+
+    async def test_non_json_output_returns_default_true(self) -> None:
+        ollama = FakeOllama(["无法判定"])
+        assert await taxonomy_consistency("摘要", "制度", ollama) is True  # type: ignore[arg-type]
+
+    async def test_missing_consistent_field_returns_default_true(self) -> None:
+        ollama = FakeOllama(['{"ok": 1}'])
+        assert await taxonomy_consistency("摘要", "制度", ollama) is True  # type: ignore[arg-type]
+
+    async def test_generate_error_returns_default_true(self) -> None:
+        ollama = FakeOllama(error=RuntimeError("Ollama 不可用"))
+        assert await taxonomy_consistency("摘要", "制度", ollama) is True  # type: ignore[arg-type]