231 lines
8.3 KiB
Python
231 lines
8.3 KiB
Python
"""`query_knowledge` 工具单测（Task 7）：声明自洽、只读、出参形状与序列化、端点筛选。
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全部用 fake retrieval service / fake session —— **不连真 Milvus、不连 MySQL**。
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"""
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from __future__ import annotations
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import json
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from typing import Any
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import pytest
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from app.core.contracts import RequestContext
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from app.core.knowledge_contracts import KnowledgeHit, KnowledgeQuery, KnowledgeSearchResult
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from app.service import knowledge_tool
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#: 与 `app/service/knowledge_tool.py` 的契约逐字对照的期望值（不从被测模块取，避免自证）。
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EXPECTED_NAME = "query_knowledge"
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EXPECTED_PERMISSION = "knowledge:query"
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EXPECTED_ROLES = ("customer", "operator", "advisor", "risk_operator", "admin")
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# --- fakes -------------------------------------------------------------------
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class FakeEndpoint:
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def __init__(self, code: str, capabilities: list[str]) -> None:
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self.endpoint_code = code
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self.capabilities = capabilities
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self.timeout_ms = 5000
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class FakeScalars:
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def __init__(self, rows: list[Any]) -> None:
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self._rows = rows
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def __iter__(self) -> Any:
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return iter(self._rows)
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class FakeSession:
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def __init__(self, rows: list[Any]) -> None:
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self._rows = rows
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async def __aenter__(self) -> FakeSession:
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return self
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async def __aexit__(self, *args: object) -> None:
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return None
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async def scalars(self, statement: Any) -> FakeScalars:
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del statement
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return FakeScalars(self._rows)
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class FakeService:
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"""鸭子类型的检索服务：记录 search 实参，返回预置结果。"""
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def __init__(self, result: KnowledgeSearchResult) -> None:
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self.result = result
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self.embedder = object()
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self.calls: list[dict[str, Any]] = []
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async def search(
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self,
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query: KnowledgeQuery,
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*,
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embedding_endpoints: Any = None,
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embedder: Any = None,
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) -> KnowledgeSearchResult:
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self.calls.append(
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{"query": query, "embedding_endpoints": embedding_endpoints, "embedder": embedder}
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)
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return self.result
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def hit(**overrides: Any) -> KnowledgeHit:
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payload: dict[str, Any] = {
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"knowledge_id": "101",
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"collection": "fin_faq_collection",
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"title": "场内基金申购费率",
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"snippet": "正文：场内基金申购费率按成交金额收取。",
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"score": 0.83,
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"tags": ("费率", "申购"),
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"version": "v1",
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"intent": "faq",
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}
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payload.update(overrides)
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return KnowledgeHit(**payload)
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def context() -> RequestContext:
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return RequestContext(user_id="9001", trace_id="task7-trace", roles=("customer",))
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def wire(
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monkeypatch: pytest.MonkeyPatch,
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*,
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result: KnowledgeSearchResult | None = None,
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endpoints: list[Any] | None = None,
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service: FakeService | None = None,
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) -> tuple[FakeService, list[Any]]:
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"""把 `_build_service` / `_embedding_endpoints` 换成 fake，返回服务与端点记录。"""
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active = service or FakeService(
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result if result is not None else KnowledgeSearchResult(hits=(hit(),))
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)
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seen_endpoints: list[Any] = endpoints if endpoints is not None else [FakeEndpoint("e1", [])]
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def build(config: Any, client: Any = None) -> FakeService:
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del config, client
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return active
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async def embedding_endpoints() -> list[Any]:
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return seen_endpoints
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monkeypatch.setattr(knowledge_tool, "_build_service", build)
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monkeypatch.setattr(knowledge_tool, "_embedding_endpoints", embedding_endpoints)
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return active, seen_endpoints
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# --- ① 声明自洽 ---------------------------------------------------------------
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def test_contract_constants_match_dispatch_contract() -> None:
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assert knowledge_tool.TOOL_NAME == EXPECTED_NAME
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assert knowledge_tool.REQUIRED_PERMISSION == EXPECTED_PERMISSION
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assert knowledge_tool.ALLOWED_ROLES == EXPECTED_ROLES
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assert knowledge_tool.TIMEOUT_SECONDS > 0
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def test_bootstrap_registers_tool_with_contract_permission_and_roles() -> None:
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"""工具必须真的进生产注册表：注册只声明上限，键名/权限/角色错一个字都会失败关闭。"""
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from app.service.agent.bootstrap import get_agent_factory
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registry = get_agent_factory()._tool_executor.registry
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definition = registry.get(EXPECTED_NAME)
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assert definition.input_model is KnowledgeQuery
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assert definition.required_permission == EXPECTED_PERMISSION
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assert tuple(definition.allowed_roles) == EXPECTED_ROLES
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# 注册表本身拒绝非只读工具，这里再显式断言一次（验收要求）。
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assert definition.read_only is True
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assert definition.timeout_seconds == knowledge_tool.TIMEOUT_SECONDS
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# --- ② handler 出参 ----------------------------------------------------------
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async def test_handler_returns_json_serializable_payload_with_one_hit(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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service, endpoints = wire(monkeypatch)
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query = KnowledgeQuery(query="申购费率是多少", intents=("faq",))
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output = await knowledge_tool.query_knowledge_tool(query, context())
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# 出参必须能直接 JSON 化（Agent 结果与审计都要序列化它）。
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dumped = json.loads(json.dumps(output, ensure_ascii=False))
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assert dumped["degraded"] is False
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assert dumped["degradation_reason"] is None
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assert dumped["hits"][0]["knowledge_id"] == "101"
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assert dumped["hits"][0]["collection"] == "fin_faq_collection"
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assert dumped["hits"][0]["title"] == "场内基金申购费率"
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assert dumped["hits"][0]["score"] == pytest.approx(0.83)
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assert dumped["hits"][0]["tags"] == ["费率", "申购"] # tuple → JSON 数组
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assert dumped["hits"][0]["intent"] == "faq"
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# 入参与端点原样透传给检索服务，工具自身不改写集合路由。
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assert service.calls[0]["query"] is query
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assert service.calls[0]["embedding_endpoints"] == endpoints
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assert service.calls[0]["embedder"] is service.embedder
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async def test_handler_shape_is_stable_on_empty_result(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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result = KnowledgeSearchResult(hits=(), searched_collections=("fin_faq_collection",))
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wire(monkeypatch, result=result)
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output = await knowledge_tool.query_knowledge_tool(
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KnowledgeQuery(query="不存在的知识", intents=("faq",)), context()
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)
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assert output == {
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"hits": [],
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"degraded": False,
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"degradation_reason": None,
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"searched_collections": ["fin_faq_collection"],
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}
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async def test_handler_surfaces_degradation_flag(monkeypatch: pytest.MonkeyPatch) -> None:
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"""Milvus 不可用时检索降级为 MySQL LIKE：调用方必须能看见，不能静默当完整召回。"""
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result = KnowledgeSearchResult(
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hits=(hit(intent=None, score=None),),
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degraded=True,
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degradation_reason="知识向量检索失败：fin_faq_collection",
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searched_collections=("fin_faq_collection",),
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)
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wire(monkeypatch, result=result)
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output = await knowledge_tool.query_knowledge_tool(
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KnowledgeQuery(query="申购费率是多少", intents=("faq",)), context()
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)
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assert output["degraded"] is True
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assert output["degradation_reason"]
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assert output["hits"][0]["score"] is None
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assert output["hits"][0]["intent"] is None
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# --- ③ 端点筛选 ---------------------------------------------------------------
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async def test_embedding_endpoints_filters_out_non_embedding_capability(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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"""不筛能力会把向量化请求打到聊天端点上（真库同时存在 chat / embedding 端点）。"""
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rows = [
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FakeEndpoint("chat-primary", ["chat"]),
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FakeEndpoint("embedding-primary", ["embedding"]),
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FakeEndpoint("no-capability", []),
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]
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# 生产契约：`_session_factory()` 返回的是**会话工厂本身**（`SessionFactory`），
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# 调用处再调一次拿到会话。所以替身也必须返回"可调用的工厂"，不是会话对象 ——
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# 否则这个替身会掩盖"少调一层"的真实缺陷（该缺陷曾让 query_knowledge 100% 失败）。
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monkeypatch.setattr(knowledge_tool, "_session_factory", lambda: (lambda: FakeSession(rows)))
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endpoints = await knowledge_tool._embedding_endpoints()
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assert [endpoint.endpoint_code for endpoint in endpoints] == ["embedding-primary"]
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