feat(retrieval): TTL+LRU result cache with generation-based invalidation
TtlCache（全输入进键/惰性过期/容量逐出/命中零 DB）+ search 接线 （空结果不缓存，保住 gap 埋点）+ invalidate_cache 真实现（T-P2-10）。 实现： - packages/retrieval/cache.py（新建）：CacheKey 全输入进键（query/body_shape/ occasion/entity_types 排序归一/rule_boost 排序序列化哈希/top_k/失效代数）； TtlCache 惰性过期 + OrderedDict LRU（超限 popitem 最旧）+ hits/misses/ evictions 计数与 stats()；clock 可注入（单测免 sleep，默认 monotonic）； asyncio 单循环不加锁的前提写在模块 docstring；正确性红线（只缓存不可变 值、命中零 DB）同处。纯逻辑，不 import 任何项目内模块（值类型由 service 以 PEP 695 泛型注入，避免循环依赖）。 - packages/retrieval/service.py：__init__ 加 keyword-only cache=None（默认 禁用，行为与现状一致，既有调用点不受影响）；from_settings 按 Settings 装配进程级共享缓存（retrieval_cache_enabled=False → None；TTL/容量变化 时重建）；search() 在 embed 之前查缓存——命中直接返回（零 DB、零 embed）， 写入与命中都做防御性拷贝（results 是 list，调用方拿不到缓存内引用）， 仅有结果时写缓存（空结果不缓存，record_gap 每次都跑）；invalidate_cache() 签名不变：自增 repo.INVALIDATION_VERSION（代数失效，旧代键永不命中， 与 T12 的契约保持）+ 清空共享实例（仅为立即回收内存，失效正确性只 依赖代数）。repo.py 未做任何改动。 测试： - 单测 tests/unit/test_retrieval_cache.py（21 例，fake repo/embedding + 注入时钟，不连库）：同参二连查零 DB 且结果相等、键分量矩阵（query/ occasion/body_shape/entity_types/rule_boost/top_k 任一变化 → miss）、 TTL 过期边界（60.0 过期/59.9 命中）、LRU 逐出与命中率/计数、空结果 不缓存且 gap 埋点每次触发、invalidate_cache() 代数失效（含自增语义 保留断言）、cache=None 与现状一致、from_settings 装配开关与共享实例、 rule_boost 哈希确定性。全量单测 494 passed（基线 473 + 新增 21）。 - 集成 tests/integration/test_retrieval_cache.py（2 例，真实 PG + pgvector）： 发布新实体 + invalidate_cache() 后同参检索立即可见（失效前缓存仍只吐 旧实体，证明缓存在工作——T-P2-10 验收语义）；不失效、TTL=1s 到期 （asyncio.sleep 1.1s）后新实体自然可见（双路径验收）。集成全量 40 passed。 偏差说明：无（invalidate_cache() 在代数失效之外顺带清空共享缓存实例， 失效正确性只依赖代数，清空仅为立即释放内存）。
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"""检索缓存集成（T-P2-10）：真实 PostgreSQL + pgvector，DeterministicEmbedder 不联网.
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证明单测证明不了的两条失效路径（任务文档 §4，双路径验收）：
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1. 发布新实体 + ``invalidate_cache()`` → 同参数检索立即可见新实体；
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2. 不失效、等 TTL 自然到期（TTL=1s，sleep 1.1s）→ 新实体同样可见。
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Run: MEIDA_RUN_INTEGRATION=1 .venv/bin/pytest -m integration -q --no-cov
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"""
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from __future__ import annotations
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import asyncio
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import os
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import uuid
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from collections.abc import AsyncIterator
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from typing import Any
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import pytest
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from sqlalchemy import delete
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from packages.domain.ids import next_id
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from packages.retrieval.cache import TtlCache
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from packages.retrieval.embedding import DeterministicEmbedder
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from packages.retrieval.repo import ChunkInput, upsert_chunks
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from packages.retrieval.service import RetrievalService, invalidate_cache
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from packages.shared.db import dispose_engine, session_scope
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from packages.shared.models import KbAsset, KbChunk, KbEntity, KbGap
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def _infra_available() -> bool:
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return bool(os.getenv("MEIDA_RUN_INTEGRATION"))
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pytestmark = [
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pytest.mark.integration,
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pytest.mark.skipif(
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not _infra_available(),
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reason="set MEIDA_RUN_INTEGRATION=1 with PostgreSQL and Redis running",
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),
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]
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def _unique(name: str) -> str:
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return f"it-t14-{name}-{uuid.uuid4().hex[:10]}"
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@pytest.fixture(autouse=True)
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async def _hermetic_engine() -> AsyncIterator[None]:
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"""每个用例前后重建全局 engine：asyncpg 连接绑定创建它的事件循环，
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pytest-asyncio 给每个用例一个新 loop，复用池里旧连接会报
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"attached to a different loop"。"""
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await dispose_engine()
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yield
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await dispose_engine()
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@pytest.fixture
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async def clean_kb() -> AsyncIterator[dict[str, list[Any]]]:
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"""登记本用例造的脏数据并在结束时清掉：集成库长活，不能留假实体."""
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registry: dict[str, list[Any]] = {"entities": [], "gaps": []}
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yield registry
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async with session_scope() as session:
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if registry["entities"]:
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ids = registry["entities"]
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await session.execute(delete(KbChunk).where(KbChunk.entity_id.in_(ids)))
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await session.execute(delete(KbAsset).where(KbAsset.entity_id.in_(ids)))
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await session.execute(delete(KbEntity).where(KbEntity.entity_id.in_(ids)))
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for query_text in registry["gaps"]:
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await session.execute(delete(KbGap).where(KbGap.query_text == query_text))
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async def _publish_entity_with_chunk(
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registry: dict[str, list[Any]], embedder: DeterministicEmbedder, *, chunk_text: str
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) -> int:
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"""直接以 published 落库（任务文档允许「SQL 置 published」）.
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用例聚焦缓存失效语义，不走发布状态机；chunk 与查询同文保证向量路
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距离 0，必然被召回。
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"""
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entity_id = next_id()
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registry["entities"].append(entity_id)
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async with session_scope() as session:
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session.add(
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KbEntity(
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entity_id=entity_id,
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entity_type="item",
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name=_unique("item"),
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attrs={},
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status="published",
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)
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)
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# sessionmaker 是 autoflush=False：不显式 flush，挂起的实体 INSERT
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# 不会先于 kb_chunk 下发，FK 会拦下 chunk。
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await session.flush()
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await upsert_chunks(session, entity_id, [ChunkInput(text=chunk_text)], embedder)
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return entity_id
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def _seen_entities(outcome: Any) -> set[int]:
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return {r.entity_id for r in outcome.results}
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# --- 1. 发布 + invalidate_cache() → 新实体立即可见（T-P2-10 验收语义）---------
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async def test_publish_then_invalidate_makes_new_entity_visible(
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clean_kb: dict[str, list[Any]],
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) -> None:
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embedder = DeterministicEmbedder(dimensions=1024)
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query = _unique("invalidate-query")
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# 防御性登记：若回归导致空结果被记进 kb_gap，用例结束也能清干净。
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clean_kb["gaps"].append(query)
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entity_a = await _publish_entity_with_chunk(clean_kb, embedder, chunk_text=query)
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cache: TtlCache[Any] = TtlCache(ttl_seconds=60.0, max_entries=64)
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async with session_scope() as session:
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svc = RetrievalService(session, embedding=embedder, cache=cache)
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first = await svc.search(query)
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second = await svc.search(query)
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assert first.degraded is False and second.degraded is False
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assert _seen_entities(first) == {entity_a}
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assert second == first
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assert cache.stats()["hits"] == 1 # 第二次命中缓存：零 DB、零 embed
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entity_b = await _publish_entity_with_chunk(clean_kb, embedder, chunk_text=query)
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# 未失效前缓存照旧只吐 A —— 证明缓存真的在工作（不是每次都查库）
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async with session_scope() as session:
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svc = RetrievalService(session, embedding=embedder, cache=cache)
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stale = await svc.search(query)
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assert _seen_entities(stale) == {entity_a}
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invalidate_cache() # 发布编排（admin/T12）调用的钩子
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async with session_scope() as session:
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svc = RetrievalService(session, embedding=embedder, cache=cache)
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fresh = await svc.search(query)
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assert _seen_entities(fresh) == {entity_a, entity_b} # 新实体立即可见
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# --- 2. 不失效，等 TTL 到期 → 新实体自然可见（双保险）-------------------------
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async def test_ttl_expiry_makes_new_entity_visible_without_invalidation(
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clean_kb: dict[str, list[Any]],
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) -> None:
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embedder = DeterministicEmbedder(dimensions=1024)
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query = _unique("ttl-query")
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clean_kb["gaps"].append(query)
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entity_a = await _publish_entity_with_chunk(clean_kb, embedder, chunk_text=query)
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cache: TtlCache[Any] = TtlCache(ttl_seconds=1.0, max_entries=64)
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async with session_scope() as session:
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svc = RetrievalService(session, embedding=embedder, cache=cache)
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first = await svc.search(query)
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await svc.search(query)
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assert _seen_entities(first) == {entity_a}
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assert cache.stats()["hits"] == 1 # TTL 内命中缓存
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entity_b = await _publish_entity_with_chunk(clean_kb, embedder, chunk_text=query)
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# 不调用 invalidate_cache()：只等 TTL 自然到期（1s + 余量 0.1s）。
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# asyncio.sleep 与 TtlCache 的默认时钟同为单调时钟，无校时跳变风险。
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await asyncio.sleep(1.1)
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async with session_scope() as session:
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svc = RetrievalService(session, embedding=embedder, cache=cache)
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fresh = await svc.search(query)
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assert _seen_entities(fresh) == {entity_a, entity_b} # 到期后重新检索
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@@ -0,0 +1,359 @@
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"""检索结果缓存（TtlCache + search 接线）：repo/embedding 全打桩，不连库.
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覆盖任务文档 §4 的七组断言：命中零 DB、键分量矩阵、TTL 过期、LRU
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逐出、空结果不缓存（gap 埋点不被吞）、代数失效、cache=None 一致性；
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外加 rule_boost 哈希的确定性与 from_settings 的装配开关。
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"""
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from __future__ import annotations
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from collections.abc import Iterator
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from typing import Any
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import pytest
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from packages.retrieval import repo
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from packages.retrieval import service as service_mod
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from packages.retrieval.cache import CacheKey, TtlCache, rule_boost_hash
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from packages.retrieval.rerank import ScoredChunk
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from packages.retrieval.service import RetrievalService, UserContext
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from packages.shared.config import Settings
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class FakeEmbedder:
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"""满足 EmbeddingProvider Protocol 的最小桩：记录调用，返回固定向量."""
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model_name = "fake"
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version = "v1"
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dimensions = 4
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def __init__(self) -> None:
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self.calls: list[list[str]] = []
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async def embed(self, texts: list[str]) -> list[list[float]]:
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self.calls.append(list(texts))
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return [[0.25, 0.25, 0.25, 0.25] for _ in texts]
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class FakeSession:
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def __init__(self) -> None:
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self.commits = 0
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self.rollbacks = 0
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async def commit(self) -> None:
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self.commits += 1
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async def rollback(self) -> None:
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self.rollbacks += 1
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class FakeClock:
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"""可手动拨动的单调时钟：TTL 断言不靠真 sleep，边界精确到微秒."""
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def __init__(self) -> None:
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self.now = 1000.0
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def __call__(self) -> float:
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return self.now
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def advance(self, seconds: float) -> None:
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self.now += seconds
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@pytest.fixture
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def stubbed_repo(monkeypatch: pytest.MonkeyPatch) -> dict[str, Any]:
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"""repo 的两个 IO 函数换成计数桩：``search_calls`` 就是「DB 交互次数」."""
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calls: dict[str, Any] = {"search_calls": 0, "gaps": [], "results": []}
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async def fake_hybrid_search(
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session: Any, query_vec: Any, query_text: str, **kwargs: Any
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) -> list[ScoredChunk]:
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calls["search_calls"] += 1
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return list(calls["results"])
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async def fake_record_gap(session: Any, query_text: str, filter_ctx: Any) -> None:
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calls["gaps"].append((query_text, filter_ctx))
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monkeypatch.setattr(repo, "hybrid_search", fake_hybrid_search)
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monkeypatch.setattr(repo, "record_gap", fake_record_gap)
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return calls
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@pytest.fixture(autouse=True)
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def _hermetic_module_state() -> Iterator[None]:
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"""用例结束还原模块级全局（失效代数、共享缓存实例），不污染同进程其它用例."""
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saved_version = repo.INVALIDATION_VERSION
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yield
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repo.INVALIDATION_VERSION = saved_version
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service_mod._shared_cache = None
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def _scored(chunk_id: int = 1) -> ScoredChunk:
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return ScoredChunk(
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chunk_id=chunk_id,
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entity_id=100,
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chunk_type="text",
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text="chunk",
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vec_score=1.0,
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kw_score=0.0,
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rule_score=0.0,
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freshness_score=1.0,
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final_score=0.55,
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)
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def _key(query_text: str = "q", **overrides: Any) -> CacheKey:
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defaults: dict[str, Any] = {
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"version": 1,
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"query_text": query_text,
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"top_k": 5,
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"body_shape": None,
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"occasion": None,
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"entity_types": (),
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"rule_boost": None,
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}
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defaults.update(overrides)
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return CacheKey.build(**defaults)
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def _svc(cache: TtlCache[Any] | None = None, **kwargs: Any) -> RetrievalService:
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return RetrievalService(FakeSession(), embedding=FakeEmbedder(), cache=cache, **kwargs)
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# --- 1. 同参数二连查：命中零 DB ------------------------------------------------
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async def test_repeated_search_hits_cache_with_zero_db(stubbed_repo: dict[str, Any]) -> None:
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stubbed_repo["results"] = [_scored(1), _scored(2)]
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embedder = FakeEmbedder()
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cache: TtlCache[Any] = TtlCache(ttl_seconds=60.0, max_entries=16)
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svc = RetrievalService(FakeSession(), embedding=embedder, cache=cache)
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first = await svc.search("面试穿什么")
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second = await svc.search("面试穿什么")
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assert first == second
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assert [c.chunk_id for c in second.results] == [1, 2]
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assert stubbed_repo["search_calls"] == 1 # 第二次零 DB
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assert embedder.calls == [["面试穿什么"]] # 第二次连 embed 都跳过
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assert cache.stats() == {"hits": 1, "misses": 1, "evictions": 0, "entries": 1}
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# 返回值是缓存内容的拷贝：调用方原地改 list（哪怕改的是命中返回的对象）
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# 也不会污染缓存（红线 2）
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second.results.append(_scored(99))
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third = await svc.search("面试穿什么")
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assert [c.chunk_id for c in third.results] == [1, 2]
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# --- 2. 键分量矩阵：任一影响结果的输入变化 → miss -----------------------------
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@pytest.mark.parametrize(
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("label", "query", "ctx", "top_k"),
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[
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("query_text", "另一个完全不同的问题", None, None),
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("occasion", None, UserContext(occasion="wedding"), None),
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("body_shape", None, UserContext(body_shape="pear"), None),
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("entity_types", None, UserContext(entity_types=("item",)), None),
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("rule_boost", None, UserContext(rule_boost={7: 0.5}), None),
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("top_k", None, None, 10),
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],
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)
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async def test_any_key_component_change_is_a_miss(
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stubbed_repo: dict[str, Any],
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label: str,
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query: str | None,
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ctx: UserContext | None,
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top_k: int | None,
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) -> None:
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stubbed_repo["results"] = [_scored(1)]
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cache: TtlCache[Any] = TtlCache(ttl_seconds=60.0, max_entries=16)
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svc = _svc(cache)
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await svc.search("面试穿什么") # 填充缓存
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if top_k is not None:
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# top_k 是 service 级参数：同缓存、不同 top_k 的另一个实例
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await _svc(cache, top_k=top_k).search("面试穿什么")
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else:
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await svc.search(query or "面试穿什么", user_ctx=ctx)
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assert stubbed_repo["search_calls"] == 2, label # 键不同 → 重新检索
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assert cache.misses == 2 and cache.hits == 0, label
|
||||
assert cache.stats()["entries"] == 2, label # 两个键并存，互不覆盖
|
||||
|
||||
|
||||
# --- 3. TTL 过期 → miss（注入 clock）------------------------------------------
|
||||
async def test_ttl_expiry_is_a_miss_then_refill(stubbed_repo: dict[str, Any]) -> None:
|
||||
stubbed_repo["results"] = [_scored(1)]
|
||||
clock = FakeClock()
|
||||
cache: TtlCache[Any] = TtlCache(ttl_seconds=60.0, max_entries=16, clock=clock)
|
||||
svc = _svc(cache)
|
||||
|
||||
await svc.search("q")
|
||||
clock.advance(60.0) # 恰好到达 TTL 边界：>= ttl 视作过期
|
||||
await svc.search("q")
|
||||
assert stubbed_repo["search_calls"] == 2
|
||||
assert cache.misses == 2 and cache.hits == 0
|
||||
|
||||
clock.advance(59.9) # 重新填充后未到期 → 命中
|
||||
await svc.search("q")
|
||||
assert stubbed_repo["search_calls"] == 2
|
||||
assert cache.stats() == {"hits": 1, "misses": 2, "evictions": 0, "entries": 1}
|
||||
|
||||
|
||||
# --- 4. LRU 容量超限 → 最旧被逐、计数正确 --------------------------------------
|
||||
def test_lru_evicts_oldest_beyond_capacity() -> None:
|
||||
cache: TtlCache[int] = TtlCache(ttl_seconds=60.0, max_entries=2)
|
||||
cache.put(_key("a"), 1)
|
||||
cache.put(_key("b"), 2)
|
||||
cache.put(_key("c"), 3) # 超限：最旧的 a 被逐
|
||||
|
||||
assert cache.get(_key("a")) is None
|
||||
assert cache.get(_key("b")) == 2
|
||||
assert cache.stats() == {"hits": 1, "misses": 1, "evictions": 1, "entries": 2}
|
||||
|
||||
|
||||
def test_lru_recency_updates_on_hit() -> None:
|
||||
"""命中会把条目移到"最新"端：之后超限逐出的是另一个最旧条目."""
|
||||
cache: TtlCache[int] = TtlCache(ttl_seconds=60.0, max_entries=2)
|
||||
cache.put(_key("a"), 1)
|
||||
cache.put(_key("b"), 2)
|
||||
assert cache.get(_key("a")) == 1 # a 变为最新
|
||||
cache.put(_key("c"), 3) # 逐出的应是 b，不是 a
|
||||
|
||||
assert cache.get(_key("b")) is None
|
||||
assert cache.get(_key("a")) == 1
|
||||
assert cache.evictions == 1
|
||||
|
||||
|
||||
def test_ttl_cache_rejects_invalid_params() -> None:
|
||||
with pytest.raises(ValueError, match="ttl_seconds"):
|
||||
TtlCache(ttl_seconds=0, max_entries=8)
|
||||
with pytest.raises(ValueError, match="max_entries"):
|
||||
TtlCache(ttl_seconds=60.0, max_entries=0)
|
||||
|
||||
|
||||
# --- 5. 空结果不缓存：gap 埋点每次都跑 -----------------------------------------
|
||||
async def test_empty_results_are_not_cached(stubbed_repo: dict[str, Any]) -> None:
|
||||
stubbed_repo["results"] = []
|
||||
session = FakeSession()
|
||||
cache: TtlCache[Any] = TtlCache(ttl_seconds=60.0, max_entries=16)
|
||||
svc = RetrievalService(session, embedding=FakeEmbedder(), cache=cache)
|
||||
|
||||
first = await svc.search("不存在的知识点")
|
||||
second = await svc.search("不存在的知识点")
|
||||
|
||||
assert first.degraded and second.degraded
|
||||
assert stubbed_repo["search_calls"] == 2 # 每次都真检索
|
||||
assert len(stubbed_repo["gaps"]) == 2 # gap 埋点不被缓存吞掉
|
||||
assert cache.stats() == {"hits": 0, "misses": 2, "evictions": 0, "entries": 0}
|
||||
assert session.commits == 2 # 每次埋点都照常提交
|
||||
|
||||
|
||||
# --- 6. invalidate_cache() 后同参数 → miss（代数失效）-------------------------
|
||||
async def test_invalidate_cache_invalidates_by_generation(
|
||||
stubbed_repo: dict[str, Any],
|
||||
) -> None:
|
||||
stubbed_repo["results"] = [_scored(1)]
|
||||
cache: TtlCache[Any] = TtlCache(ttl_seconds=60.0, max_entries=16)
|
||||
svc = _svc(cache)
|
||||
|
||||
await svc.search("面试穿什么")
|
||||
await svc.search("面试穿什么")
|
||||
assert stubbed_repo["search_calls"] == 1 # 命中
|
||||
|
||||
service_mod.invalidate_cache()
|
||||
await svc.search("面试穿什么")
|
||||
assert stubbed_repo["search_calls"] == 2 # 代数失效 → 重新检索
|
||||
|
||||
await svc.search("面试穿什么")
|
||||
assert stubbed_repo["search_calls"] == 2 # 新代重新缓存，再次命中
|
||||
|
||||
|
||||
def test_invalidate_cache_bumps_generation(stubbed_repo: dict[str, Any]) -> None:
|
||||
"""自增 repo.INVALIDATION_VERSION 的既有语义保留（T12 依赖该契约）."""
|
||||
before = repo.INVALIDATION_VERSION
|
||||
service_mod.invalidate_cache()
|
||||
assert before + 1 == repo.INVALIDATION_VERSION
|
||||
|
||||
|
||||
# --- 7. cache=None → 行为与现在完全一致 ----------------------------------------
|
||||
async def test_cache_none_searches_db_every_time(stubbed_repo: dict[str, Any]) -> None:
|
||||
stubbed_repo["results"] = [_scored(1)]
|
||||
embedder = FakeEmbedder()
|
||||
svc = RetrievalService(FakeSession(), embedding=embedder) # 不传 cache
|
||||
|
||||
first = await svc.search("面试穿什么")
|
||||
second = await svc.search("面试穿什么")
|
||||
|
||||
assert first == second
|
||||
assert stubbed_repo["search_calls"] == 2
|
||||
assert len(embedder.calls) == 2
|
||||
|
||||
|
||||
async def test_cache_none_degraded_path_records_gap_every_time(
|
||||
stubbed_repo: dict[str, Any],
|
||||
) -> None:
|
||||
stubbed_repo["results"] = []
|
||||
svc = RetrievalService(FakeSession(), embedding=FakeEmbedder())
|
||||
|
||||
await svc.search("问不到")
|
||||
await svc.search("问不到")
|
||||
|
||||
assert stubbed_repo["search_calls"] == 2
|
||||
assert len(stubbed_repo["gaps"]) == 2
|
||||
|
||||
|
||||
# --- rule_boost 哈希：确定性（排序归一 + 不同值不折叠）------------------------
|
||||
def test_rule_boost_hash_is_insertion_order_insensitive() -> None:
|
||||
d1 = {1: 0.5, 2: 0.3}
|
||||
d2 = {2: 0.3}
|
||||
d2[1] = 0.5
|
||||
assert rule_boost_hash(d1) == rule_boost_hash(d2)
|
||||
|
||||
a = {1: 0.5}
|
||||
a[2] = 0.3
|
||||
b = {2: 0.3}
|
||||
b[1] = 0.5
|
||||
assert CacheKey.build(version=1, query_text="q", top_k=5, rule_boost=a) == (
|
||||
CacheKey.build(version=1, query_text="q", top_k=5, rule_boost=b)
|
||||
)
|
||||
|
||||
|
||||
def test_rule_boost_hash_distinguishes_values_and_empty() -> None:
|
||||
assert rule_boost_hash({}) != rule_boost_hash({1: 0.0})
|
||||
assert rule_boost_hash({1: 0.5}) != rule_boost_hash({1: 0.6})
|
||||
|
||||
|
||||
def test_entity_types_order_does_not_change_key() -> None:
|
||||
"""``= ANY(...)`` 与顺序无关：同集合不同顺序应共享同一条目."""
|
||||
assert _key(entity_types=("item", "style")) == _key(entity_types=("style", "item"))
|
||||
|
||||
|
||||
# --- from_settings 装配：按 Settings 开/关与参数化 -----------------------------
|
||||
def test_from_settings_disabled_yields_no_cache(stubbed_repo: dict[str, Any]) -> None:
|
||||
settings = Settings(_env_file=None, retrieval_cache_enabled=False)
|
||||
svc = RetrievalService.from_settings(FakeSession(), settings)
|
||||
assert svc._cache is None
|
||||
|
||||
|
||||
def test_from_settings_attaches_shared_cache_with_settings_params(
|
||||
stubbed_repo: dict[str, Any],
|
||||
) -> None:
|
||||
settings = Settings(
|
||||
_env_file=None,
|
||||
retrieval_cache_ttl_seconds=7,
|
||||
retrieval_cache_max_entries=9,
|
||||
)
|
||||
first = RetrievalService.from_settings(FakeSession(), settings)
|
||||
assert first._cache is not None
|
||||
assert first._cache.ttl_seconds == 7
|
||||
assert first._cache.max_entries == 9
|
||||
|
||||
# 每请求实例共享同一缓存：跨请求复用是缓存的意义所在
|
||||
second = RetrievalService.from_settings(FakeSession(), settings)
|
||||
assert second._cache is first._cache
|
||||
|
||||
# TTL/容量变化 → 按新配置重建（进程内配置恒定，重建只在测试/热改配置发生）
|
||||
changed = Settings(_env_file=None, retrieval_cache_ttl_seconds=1, retrieval_cache_max_entries=9)
|
||||
third = RetrievalService.from_settings(FakeSession(), changed)
|
||||
assert third._cache is not None
|
||||
assert third._cache is not first._cache
|
||||
assert third._cache.ttl_seconds == 1
|
||||
Reference in New Issue
Block a user