新功能：个性化推荐算法

server/tests/test_content_repository.py

@@ -0,0 +1,178 @@
+from __future__ import annotations
+
+from datetime import datetime
+
+import pytest
+
+from app.db.models.content import Content
+from app.db.models.content_profile import ContentProfile
+from app.db.models.content_risk_flag import ContentRiskFlag
+from app.features.personalized_reco.content_repository.sqlalchemy_repo import SqlAlchemyContentRepository
+
+
+def _ctx_json() -> dict:
+    return {"family": 0.5, "work": 0.5, "relationship": 0.5, "friends": 0.5, "health": 0.5}
+
+
+def _need_json() -> dict:
+    return {
+        "emotional_support": 0.5,
+        "parenting_pressure": 0.5,
+        "self_worth": 0.5,
+        "anxiety_relief": 0.5,
+        "rest_balance": 0.5,
+    }
+
+
+@pytest.mark.asyncio
+async def test_fetch_contents_by_ids_locale_no_fallback(db_session, query_counter):
+    # content 1: 只有英文
+    c1 = Content(text_en="hello", text_tc=None, author_id="a1", template_id="t1")
+    db_session.add(c1)
+    await db_session.flush()
+    db_session.add(
+        ContentProfile(
+            content_id=c1.content_id,
+            stage="general",
+            emotion_score=None,
+            context_suitability_json=_ctx_json(),
+            need_suitability_json=_need_json(),
+            personalization_power=10,
+            review_confidence=None,
+            is_safe_pool=False,
+        )
+    )
+    db_session.add(ContentRiskFlag(content_id=c1.content_id, flag="block_stage_unknown"))
+
+    # content 2: 只有繁中
+    c2 = Content(text_en=None, text_tc="繁體中文", author_id="a2", template_id="t2")
+    db_session.add(c2)
+    await db_session.flush()
+    db_session.add(
+        ContentProfile(
+            content_id=c2.content_id,
+            stage="general",
+            emotion_score=None,
+            context_suitability_json=_ctx_json(),
+            need_suitability_json=_need_json(),
+            personalization_power=0,
+            review_confidence=0.9,
+            is_safe_pool=True,
+        )
+    )
+    db_session.add(ContentRiskFlag(content_id=c2.content_id, flag="block_health_sensitive"))
+
+    await db_session.flush()
+
+    repo = SqlAlchemyContentRepository(db_session)
+    start = query_counter()
+
+    # en：只能拿到有 text_en 的内容（不允许回退到 text_tc）
+    en_items = await repo.fetch_contents_by_ids(content_ids=[c2.content_id, c1.content_id], locale="en")
+    assert [x.content_id for x in en_items] == [c1.content_id]
+    assert en_items[0].text == "hello"
+    assert en_items[0].personalization_power == 1.0
+    assert en_items[0].review_confidence == 0.7  # NULL -> 0.7
+    assert "unsafe_for_stage_unknown" in en_items[0].risk_flags
+    assert "block_stage_unknown" not in en_items[0].risk_flags
+
+    # tc：只能拿到有 text_tc 的内容（不允许回退到 text_en）
+    tc_items = await repo.fetch_contents_by_ids(content_ids=[c1.content_id, c2.content_id], locale="tc")
+    assert [x.content_id for x in tc_items] == [c2.content_id]
+    assert tc_items[0].text == "繁體中文"
+    assert tc_items[0].review_confidence == 0.9
+    assert "block_health_medical" in tc_items[0].risk_flags
+    assert "block_health_sensitive" not in tc_items[0].risk_flags
+
+    # 两次调用各自 2 次查询（主体+画像一次，flags 一次），总计应为常数级
+    end = query_counter()
+    assert (end - start) <= 4
+
+
+@pytest.mark.asyncio
+async def test_fetch_candidates_fallback_and_locale_filter(db_session, query_counter):
+    # 构造 4 条英文内容：power 0/5/10，安全池标记不同
+    contents = []
+    for i, (power, safe) in enumerate([(0, True), (5, False), (10, False), (0, False)], start=1):
+        c = Content(text_en=f"en_{i}", text_tc=None, author_id=f"a{i}", template_id=f"t{i}")
+        db_session.add(c)
+        await db_session.flush()
+        db_session.add(
+            ContentProfile(
+                content_id=c.content_id,
+                stage="general",
+                emotion_score=None,
+                context_suitability_json=_ctx_json(),
+                need_suitability_json=_need_json(),
+                personalization_power=power,
+                review_confidence=None,
+                is_safe_pool=safe,
+                # 让测试数据在候选排序中排到最前，避免依赖“库为空”
+                updated_at=datetime(2099, 1, 1, 0, 0, 0),
+            )
+        )
+        contents.append(c)
+    await db_session.flush()
+    inserted_ids = {int(c.content_id) for c in contents}
+
+    repo = SqlAlchemyContentRepository(db_session)
+
+    class _MinimalUser:
+        # need/context/emotion_score 全缺失 -> effective_fallback 至少 L1
+        need = {}
+        context = {}
+        emotion_score = None
+        stage = {"unknown": 1}
+
+    start = query_counter()
+
+    # 入参 L0，但因为缺失字段，effective_fallback=1 -> power<=5（排除 power=10）
+    items_l0 = await repo.fetch_candidates(
+        scene="feed",
+        user_profile=_MinimalUser(),
+        fallback_level=0,
+        limit=3,
+        locale="en-US",
+    )
+    powers = [x.personalization_power for x in items_l0]
+    assert 1.0 not in powers
+    assert all(x.text.startswith("en_") for x in items_l0)
+
+    # L2：强制 power=0 且 stage=general（这里都 general），只剩 power=0 的两条
+    items_l2 = await repo.fetch_candidates(
+        scene="feed",
+        user_profile=_MinimalUser(),
+        fallback_level=2,
+        limit=2,
+        locale="en",
+    )
+    assert all(x.personalization_power == 0.0 for x in items_l2)
+    assert all(x.text.startswith("en_") for x in items_l2)
+
+    # L3：只安全池（is_safe_pool=true）且 power=0
+    items_l3 = await repo.fetch_candidates(
+        scene="feed",
+        user_profile=_MinimalUser(),
+        fallback_level=3,
+        limit=1,
+        locale="en",
+    )
+    assert len(items_l3) == 1
+    assert items_l3[0].text.startswith("en_")
+    assert items_l3[0].personalization_power == 0.0
+
+    # locale 过滤：tc 请求下这些内容都没有 text_tc -> 返回空
+    items_tc = await repo.fetch_candidates(
+        scene="feed",
+        user_profile=_MinimalUser(),
+        fallback_level=0,
+        limit=10,
+        locale="tc",
+    )
+    # 不要求库为空：只断言“不会把本次插入的 en-only 测试数据返回出来”
+    assert not any(x.content_id in inserted_ids for x in items_tc)
+
+    end = query_counter()
+    # 期望为常数级（每次 fetch_candidates：1 次取 ids + 2 次补全），这里 4 次调用 -> <= 12
+    assert (end - start) <= 12
+