初始化提交

backend/tests/application/test_big_cycle_extraction.py

@@ -0,0 +1,76 @@
+"""大周天记忆/世界抽取生成测试（_phase_memory 阶段）。
+
+高置信度（≥0.7）低敏感度记忆候选自动落地到 memories 表；
+世界实体候选（confidence=0.6）低于阈值仍留 pending。
+"""
+
+import pytest
+
+from app.application.big_cycle import drain_pending_big_cycles, maybe_trigger_big_cycle
+from app.db.session import AsyncSessionLocal
+from app.models.memory import Memory
+from app.repositories import world as world_repo
+from app.services.characters import get_active_character_model
+
+_EXTRACTION_RESPONSE = (
+    '{"memories":[{"type":"preference","title":"喜欢简洁","content":"用户偏好简洁",'
+    '"importance":0.8,"sensitivity":"low","confidence":0.7}],'
+    '"entities":[{"type":"project","name":"项目X","attributes":{"status":"active"},'
+    '"state_type":"inference","confidence":0.6}]}'
+)
+
+
+async def _seed_memories(character_id: str, count: int) -> None:
+    async with AsyncSessionLocal() as session:
+        for i in range(count):
+            session.add(
+                Memory(
+                    character_id=character_id,
+                    type="user",
+                    title=f"记忆{i}",
+                    content=f"内容{i}",
+                )
+            )
+        await session.commit()
+
+
+@pytest.fixture
+def mock_extraction_chat(monkeypatch: pytest.MonkeyPatch) -> None:
+    async def fake_chat(*_args, **_kwargs):
+        return _EXTRACTION_RESPONSE
+
+    monkeypatch.setattr("app.application.big_cycle._call_model", fake_chat)
+
+
+@pytest.mark.asyncio
+async def test_big_cycle_extracts_memory_and_world(
+    mock_extraction_chat,  # noqa: ARG001 - pytest fixture 靠 monkeypatch 副作用生效
+) -> None:
+    async with AsyncSessionLocal() as session:
+        character = await get_active_character_model(session)
+    await _seed_memories(character.id, 20)
+
+    cycle_id = await maybe_trigger_big_cycle(character.id, trigger="test")
+    assert cycle_id is not None
+    await drain_pending_big_cycles()
+
+    async with AsyncSessionLocal() as session:
+        # 高置信度（≥0.7）低敏感度记忆自动落地到 memories 表
+        from sqlalchemy import select
+
+        result = await session.execute(
+            select(Memory).where(
+                Memory.character_id == character.id,
+                Memory.source == "big_cycle",
+            )
+        )
+        auto_memories = result.scalars().all()
+        # 世界实体候选（confidence=0.6 < 0.7）仍留 pending
+        entities, _ = await world_repo.list_entities(session, character.id, status="pending")
+
+    assert len(auto_memories) == 1
+    assert auto_memories[0].title == "喜欢简洁"
+    assert len(entities) == 1
+    assert entities[0].name == "项目X"
+    assert entities[0].status == "pending"
+    assert entities[0].state_type == "inference"