88 lines
3.8 KiB
Python
88 lines
3.8 KiB
Python
"""Phase 1 回归用例 R1/R2/R3 — 固化三个反复出现的问题（适配 chat.py 拆分后）。
|
||
|
||
R1: 技能列表不得被硬性截断为 15 条（微信 Bot 曾只返回 15 个技能）。
|
||
R2: 显式选中技能/MCP 时，system prompt 必须注入「最高优先级覆盖规则」。
|
||
R3: 媒体生成（图像/视频）必须有超时保护，超时后回写用户可懂的提示而非永久挂起。
|
||
|
||
Phase 1 已将 chat.py 巨石拆分为 chat_{utils,media,agents,skill,mcp,context,knowledge,service}.py，
|
||
因此本文件采用「扫描整个 app/api 包」做源码契约守卫，并对行为级用例从正确的子模块导入。
|
||
"""
|
||
import asyncio
|
||
import os
|
||
import glob
|
||
from unittest.mock import MagicMock
|
||
|
||
import pytest
|
||
|
||
_HERE = os.path.dirname(os.path.abspath(__file__))
|
||
API_DIR = os.path.abspath(os.path.join(_HERE, "..", "app", "api"))
|
||
|
||
|
||
def _read_api_package():
|
||
parts = []
|
||
for p in sorted(glob.glob(os.path.join(API_DIR, "chat*.py"))):
|
||
with open(p, "r", encoding="utf-8") as f:
|
||
parts.append(f.read())
|
||
return "\n".join(parts)
|
||
|
||
|
||
# ---------- R1 ----------
|
||
def test_r1_skill_list_not_hard_capped_at_15():
|
||
"""微信 Bot 技能列表曾因 limit(15) 只返回 15 个，必须防止回归。"""
|
||
src = _read_api_package()
|
||
assert "limit(15)" not in src, "检测到 limit(15)，技能列表可能被硬性截断"
|
||
assert "LIMIT 15" not in src, "检测到 LIMIT 15，技能列表可能被硬性截断"
|
||
|
||
|
||
# ---------- R2 ----------
|
||
def test_r2_explicit_selection_override_rule_present():
|
||
"""显式选中技能/MCP 时，system prompt 必须包含最高优先级覆盖规则。
|
||
|
||
注：_build_system_prompt 已随 Phase 1 拆分迁入 chat_context.py，故扫描整个 api 包。
|
||
"""
|
||
src = _read_api_package()
|
||
assert "最高优先级覆盖规则" in src, "显式选中工具的覆盖规则文本缺失"
|
||
assert "只基于上文提供的该工具具体资料作答" in src, "覆盖规则应要求只基于已选工具资料作答"
|
||
assert "平台知识库" in src and "不要引用" in src, "覆盖规则应明确禁止引用平台知识库通用描述"
|
||
|
||
|
||
# ---------- R3 ----------
|
||
@pytest.mark.asyncio
|
||
async def test_r3_media_generation_timeout_returns_user_message(monkeypatch):
|
||
"""媒体生成超时必须回写用户可懂的超时提示，而非让前端永远『生成中…』。
|
||
|
||
_generate_media_task 位于 chat_media（经 _send_message_core 的 asyncio.create_task 调用），
|
||
本身是 fire-and-forget、返回 None，超时保护体现在把提示回写到消息 content。
|
||
"""
|
||
from app.api import chat_media as media_mod
|
||
|
||
class FakeModel:
|
||
id = "m_test"
|
||
capabilities = ["image"] # 图像 -> 90s 超时
|
||
|
||
msg_mock = MagicMock() # 捕获被回写的消息对象
|
||
fake_session = MagicMock()
|
||
|
||
def _query_side_effect(model_cls):
|
||
q = MagicMock()
|
||
if model_cls is media_mod.AIModel:
|
||
q.filter.return_value.first.return_value = FakeModel()
|
||
elif model_cls is media_mod.Message:
|
||
q.filter.return_value.first.return_value = msg_mock
|
||
return q
|
||
|
||
fake_session.query.side_effect = _query_side_effect
|
||
monkeypatch.setattr(media_mod, "SessionLocal", lambda: fake_session)
|
||
|
||
# 内部生成调用直接抛出 TimeoutError，等价模拟「生成耗时超过超时阈值」
|
||
async def _hang(db, ai_model, prompt, user_id):
|
||
raise asyncio.TimeoutError()
|
||
|
||
monkeypatch.setattr(media_mod, "_generate_media", _hang)
|
||
|
||
await media_mod._generate_media_task("msg1", "m_test", "画一只猫", "u1")
|
||
|
||
# 副作用：消息 content 被回写为用户可懂的超时提示
|
||
assert msg_mock.content is not None, "超时后必须回写消息内容，不能让前端永远『生成中…』"
|
||
assert "超时" in str(msg_mock.content), "媒体生成超时应回写用户可懂的超时提示"
|