浅念
d1aed8e722
上游 ai-kefu → phase1 吸收(Task 11 unit 12): - 拷入 7 个测试文件,import/夹具按目标库重锚(app.engine.* / conftest async_db+build_jiancai_runtime / seed_profiles 提示词锚点) - 补实现(同步自上游): chat_rest 服务端可信 IP(_server_ip/ _merge_client_info,直连场景自报假 IP 不再原样落库);widget.js 与 chat.js 的 data-placeholder 读取(叠加 Task 10 管道:data-* > brand > 中性兜底,tests/test_placeholder_static.py 守卫) - 断言重锚以 jc 主线为准: ev.contact_info 存裸号+等待尾注(e164 走 _cc 派生)、source 值 fallback/customer_stated 口径、推送标注键 号码补全说明、prompt 静态锚按租户(seed_profiles)双测 - 全量回归 459 passed(基线 421 + 吸收 38) Co-Authored-By: Claude Code <noreply@anthropic.com>
108 lines
4.4 KiB
Python
108 lines
4.4 KiB
Python
"""内部状态卫生(同步自上游 ai-kefu tests/test_channel_hygiene.py)。
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上游两测分别锚 AIService.extract_info 内部 `_` 过滤与 _merge_extracted
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纯函数的出口剥离;jc 主线把这两处卫生逻辑收敛进 stream_process_message
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的调用点(入口侧 existing_info 过滤 / 出口侧 cc_reply 剥离 + `_` 回显
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丢弃,不再有独立函数)——断言按 jc 锚点重锚到 manager 整轮,语义等价:
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`_` 键不进提示词、cc_reply 消费即剥离不落 raw_info、extractor 回显的
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`_` 状态不得覆盖 Python 管理的状态机。
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"""
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import asyncio
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from app.engine.services import email_service
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from app.engine.services.conversation import ConversationManager
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from tests.conftest import build_jiancai_runtime
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KE_IP = "41.90.64.1" # 肯尼亚段(iptocc 实测 → KE)
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class FakeAI:
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"""替代 GLM 的确定性桩(仅卫生测试所需的最小面)。"""
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def __init__(self, extract=None):
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self._extract_seq = extract if isinstance(extract, list) else [extract or {}]
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async def stream_chat(self, messages, context=""):
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for token in ("ok ", "reply"):
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yield token
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async def extract_info(self, messages, existing_info):
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idx = min(max(len(messages) // 2 - 1, 0), len(self._extract_seq) - 1)
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return self._extract_seq[idx]
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async def evaluate(self, profile, recent_messages):
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return {"intent_level": "pending", "reasoning": "",
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"contact_info": {}, "info_sufficient": False}
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async def _send(manager, sid, text):
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async for _ in manager.stream_process_message(sid, text):
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pass
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def _no_email(monkeypatch):
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"""卫生测试不关心邮件侧效应——桩掉避免真实 SMTP 配置探测。"""
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async def fake_lead(*a, **k):
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return True
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monkeypatch.setattr(email_service, "send_lead_email", fake_lead)
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def test_extract_info_filters_underscore_keys(async_db, monkeypatch):
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# 入口侧(上游锚 AIService 内部过滤,jc 锚调用点): `_` 前缀内部态
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# (_cc 状态机等)绝不进 LLM 输入,正常键照常透传。
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_no_email(monkeypatch)
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captured = {}
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class RecAI(FakeAI):
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async def extract_info(self, messages, existing_info):
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captured["existing"] = existing_info
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return {}
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async def run():
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async with async_db() as db:
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manager = ConversationManager(
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db, runtime=build_jiancai_runtime(), ai_service=RecAI())
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conv = await manager.create_conversation(client_info={"ip": KE_IP})
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profile = await manager._get_profile(conv.id)
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profile.raw_info = {"name": "Sam",
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"_cc": {"whatsapp": {"e164": "+254712345678"}}}
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db.add(profile)
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await db.commit()
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await _send(manager, conv.session_id, "hello are you there")
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asyncio.run(run())
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assert captured["existing"] == {"name": "Sam"} # _cc 不进提示词,name 保留
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def test_extractor_output_strips_cc_reply_and_underscore_echo(async_db, monkeypatch):
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# 出口侧(上游锚 _merge_extracted,jc 锚 stream_process_message 内联):
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# cc_reply 提取后即剥离不落 raw_info;extractor 回显的任何 `_` 键
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# (含 _cc 状态机回显)防御性丢弃——Python 管理的状态机不被覆盖;
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# 正常键(含联系方式深合并)照常进 raw_info。
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_no_email(monkeypatch)
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async def run():
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async with async_db() as db:
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manager = ConversationManager(
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db, runtime=build_jiancai_runtime(),
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ai_service=FakeAI(extract={
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"联系方式": {"whatsapp": "0712345678"},
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"cc_reply": {"affirm": True},
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"_cc": {"whatsapp": {"e164": "HACKED"}},
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"_evil": "x",
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"name": "Sam2"}))
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conv = await manager.create_conversation(client_info={"ip": KE_IP})
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await _send(manager, conv.session_id, "my whatsapp is 0712345678")
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profile = await manager._get_profile(conv.id)
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return dict(profile.raw_info or {})
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raw = asyncio.run(run())
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assert "cc_reply" not in raw and "_evil" not in raw
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assert raw["name"] == "Sam2"
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assert raw["联系方式"]["whatsapp"] == "0712345678"
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# _cc 在场但属 Python 建态(判定树按 KE IP 补全),extractor 回显未生效
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st = raw["_cc"]["whatsapp"]
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assert st["e164"] == "+254712345678" and st["source"] == "ip_proposed"
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