初始化提交

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chenxin committed 2026-08-21 16:00:13 +08:00
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"""资料导入候选抽取测试(5b,异步后台 + mock ai_provider)。"""
from collections.abc import AsyncGenerator
import pytest
from httpx import ASGITransport, AsyncClient
from sqlalchemy import select
from app.application.imports import drain_pending_extractions
from app.db.session import AsyncSessionLocal
from app.main import app
from app.models.user import User
from app.services.auth import create_access_token
async def _get_character_id(client: AsyncClient) -> str:
"""通过已认证的 API 获取当前用户活跃角色 ID。"""
resp = await client.get("/api/v1/characters/active")
assert resp.status_code == 200
return resp.json()["id"]
class _FakeChatResult:
def __init__(self, content: str) -> None:
self.content = content
_PROFILE_RESPONSE = (
'[{"field":"background","value":"来自北京,从事设计工作",'
'"confidence":0.9,"reason":"资料明确提及","evidence":[0,1]}]'
)
_MEMORY_RESPONSE = (
'[{"type":"preference","title":"喜欢简洁回答","content":"用户偏好简洁直接的回答",'
'"importance":0.8,"sensitivity":"low","reason":"多次提及","evidence":[0]}]'
)
_PERSONALITY_RESPONSE = (
'[{"field":"expression_style","change":"温和且有条理","reason":"资料体现","evidence":[1]}]'
)
@pytest.fixture
async def client(
monkeypatch: pytest.MonkeyPatch, auth_headers: dict[str, str]
) -> AsyncGenerator[AsyncClient, None]:
async def fake_chat(messages, *, model_hint, **_kwargs):
if model_hint == "memory-extraction":
return _FakeChatResult(_MEMORY_RESPONSE)
system_text = str(messages[0].content) if messages else ""
if "人格" in system_text:
return _FakeChatResult(_PERSONALITY_RESPONSE)
return _FakeChatResult(_PROFILE_RESPONSE)
class _MockMessage:
def __init__(self, content: str):
self.content = content
class _MockManager:
async def chat(self, messages, model_hint=None):
return await fake_chat(messages, model_hint=model_hint)
def to_message_list(self, system, _messages):
return [_MockMessage(s) for s in system]
monkeypatch.setattr("app.application.imports._get_provider_manager", lambda: _MockManager())
transport = ASGITransport(app=app)
async with AsyncClient(
transport=transport, base_url="http://test", headers=auth_headers
) as http_client:
yield http_client
async def _create_import(client: AsyncClient, character_id: str) -> str:
resp = await client.post(
f"/api/v1/characters/{character_id}/imports",
json={
"material_type": "background_story",
"content": "我叫小魂,来自北京。\n\n我从事设计工作,喜欢简洁直接的回答。",
},
)
return resp.json()["id"]
@pytest.mark.asyncio
async def test_extract_profile_candidates(client: AsyncClient) -> None:
character_id = await _get_character_id(client)
import_id = await _create_import(client, character_id)
triggered = await client.post(
f"/api/v1/characters/{character_id}/imports/{import_id}/profile-candidates"
)
assert triggered.status_code == 200
assert triggered.json()["status"] == "extracting_profile"
await drain_pending_extractions()
candidates = (
await client.get(
f"/api/v1/characters/{character_id}/imports/{import_id}/profile-candidates"
)
).json()
assert len(candidates) == 1
assert candidates[0]["field"] == "background"
assert candidates[0]["status"] == "pending"
assert len(candidates[0]["evidence_ids"]) == 2 # 映射到 import_items.id
job = (await client.get(f"/api/v1/characters/{character_id}/imports/{import_id}")).json()
assert job["status"] == "reviewing"
@pytest.mark.asyncio
async def test_extract_memory_candidates(client: AsyncClient) -> None:
character_id = await _get_character_id(client)
import_id = await _create_import(client, character_id)
await client.post(f"/api/v1/characters/{character_id}/imports/{import_id}/memory-candidates")
await drain_pending_extractions()
candidates = (
await client.get(f"/api/v1/characters/{character_id}/imports/{import_id}/memory-candidates")
).json()
assert len(candidates) == 1
assert candidates[0]["type"] == "preference"
assert candidates[0]["title"] == "喜欢简洁回答"
@pytest.mark.asyncio
async def test_extract_personality_proposals(client: AsyncClient) -> None:
character_id = await _get_character_id(client)
import_id = await _create_import(client, character_id)
await client.post(
f"/api/v1/characters/{character_id}/imports/{import_id}/personality-proposals"
)
await drain_pending_extractions()
# 人格建议落入 personality_proposals(pending);无独立列表端点,以 job 进入 reviewing 验证
job = (await client.get(f"/api/v1/characters/{character_id}/imports/{import_id}")).json()
assert job["status"] == "reviewing"
@pytest.mark.asyncio
async def test_extraction_failure_marks_job_failed(monkeypatch: pytest.MonkeyPatch) -> None:
async def failing_chat(*_args, **_kwargs):
raise RuntimeError("模型不可用")
class _MockMessage:
def __init__(self, content: str):
self.content = content
class _FailingManager:
async def chat(self, messages, model_hint=None):
return await failing_chat(messages, model_hint=model_hint)
def to_message_list(self, system, _messages):
return [_MockMessage(s) for s in system]
monkeypatch.setattr("app.application.imports._get_provider_manager", lambda: _FailingManager())
transport = ASGITransport(app=app)
async with AsyncSessionLocal() as session:
result = await session.execute(select(User).where(User.is_admin.is_(True)).limit(1))
admin = result.scalar_one_or_none()
assert admin is not None
token = create_access_token(subject=admin.id, extra={"owner_scope": admin.id})
headers = {"Authorization": f"Bearer {token}"}
async with AsyncClient(transport=transport, base_url="http://test", headers=headers) as client:
character_id = await _get_character_id(client)
import_id = await _create_import(client, character_id)
await client.post(
f"/api/v1/characters/{character_id}/imports/{import_id}/profile-candidates"
)
await drain_pending_extractions()
job = (await client.get(f"/api/v1/characters/{character_id}/imports/{import_id}")).json()
assert job["status"] == "failed"
assert job["error_code"] == "extraction_failed"