refactor: config_views 单入口 + 0语义统一 + FakeAI 收敛（清理单#1#2#3）
- #3 六个消费视图 resolver 收拢 app/platform/config_views(单一定义点): resolve_email/push/ai_settings ← 各服务文件, resolve_contact_flags/ context_seed_map ← conversation, name_to_region_extras ← manager __init__ 内联取值(or None 语义原样)——函数体逐字搬入,服务层 import 之, 旧定义删;Phase 3 编辑器/试金石与该模块对接 - #2 限流 0 语义统一: conn_limiter.try_acquire 的 limit 与 chat_rest 的 rate_limit_per_hour 取值同款——0 或负 = 回退出厂默认(与姊妹键一致), 原 conn_limiter 0=全拒改为回退;chat_rest 取值抽 _resolve_rate_limit 纯函数供锚定 - #1 FakeAI 收敛进 conftest(超集: extract/evaluate/eval_calls),四份拷贝 删(test_lead_email_trigger/test_cc_integration/test_channel_hygiene/ test_lead_push_wiring——计划记三份,grep 实有四份;push_wiring 经 evaluate 参数注入原本地固定返回值,断言零改动) 全量 558 passed(554 + 新增 4: 单入口/内联等价/两处 0 语义) Co-Authored-By: Claude Code <noreply@anthropic.com>
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浅念
@@ -6,26 +6,12 @@ from sqlalchemy import select
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from app.engine.models import ConversationSource, LeadPushLog
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from app.engine.services import email_service, lead_push_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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from tests.conftest import FakeAI, build_jiancai_runtime
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class FakeAI:
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"""同 test_lead_email_trigger 的确定性桩。"""
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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": "interested", "reasoning": "留号",
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"contact_info": {}, "info_sufficient": True}
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# 本文件场景依赖"interested"触发推送——conftest FakeAI(超集)经 evaluate
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# 参数注入,与原本地拷贝的固定返回值逐字等价(setdefault 补 contact_info={})
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_EVAL = {"intent_level": "interested", "reasoning": "留号",
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"info_sufficient": True}
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def _setup(async_db, monkeypatch, ai, lead_succeeds=True):
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@@ -81,7 +67,7 @@ def _logs(async_db):
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def test_lead_email_triggers_pending_push(async_db, monkeypatch):
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ai = FakeAI(extract={"联系方式": {"手机": "+254722111117"}})
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ai = FakeAI(extract={"联系方式": {"手机": "+254722111117"}}, evaluate=_EVAL)
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(manager, conv), sent, fired = _setup(async_db, monkeypatch, ai)
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_send(manager, conv.session_id, "my whatsapp is +254722111117")
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assert [s[0] for s in sent] == ["lead"]
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@@ -94,7 +80,7 @@ def test_lead_email_triggers_pending_push(async_db, monkeypatch):
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def test_smtp_failure_still_pushes(async_db, monkeypatch):
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"""设计定案: 推送与 SMTP 成败解耦——邮件失败询盘照推。"""
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ai = FakeAI(extract={"联系方式": {"手机": "+254722111117"}})
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ai = FakeAI(extract={"联系方式": {"手机": "+254722111117"}}, evaluate=_EVAL)
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(manager, conv), sent, fired = _setup(
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async_db, monkeypatch, ai, lead_succeeds=False)
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_send(manager, conv.session_id, "my whatsapp is +254722111117")
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@@ -104,7 +90,7 @@ def test_smtp_failure_still_pushes(async_db, monkeypatch):
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def test_wechat_only_push_marked_skipped(async_db, monkeypatch):
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ai = FakeAI(extract={"联系方式": {"微信": "li_ming_88"}})
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ai = FakeAI(extract={"联系方式": {"微信": "li_ming_88"}}, evaluate=_EVAL)
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(manager, conv), sent, fired = _setup(async_db, monkeypatch, ai)
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_send(manager, conv.session_id, "add my wechat li_ming_88")
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assert [s[0] for s in sent] == ["lead"] # 我方邮件照发(wechat 算 confirmed)
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@@ -117,7 +103,8 @@ def test_wechat_only_push_marked_skipped(async_db, monkeypatch):
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def test_correction_push_event_update_after_success(async_db, monkeypatch):
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"""改号 → 更正推送;前次已 success(手动置位模拟 _run_push)→ event=update。"""
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ai = FakeAI(extract=[{"联系方式": {"手机": "+254722111117"}},
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{"联系方式": {"手机": "+254799999999"}}])
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{"联系方式": {"手机": "+254799999999"}}],
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evaluate=_EVAL)
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(manager, conv), sent, fired = _setup(async_db, monkeypatch, ai)
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_send(manager, conv.session_id, "my whatsapp is +254722111117")
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assert len(fired) == 1 and fired[0].push_type == "lead"
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@@ -139,13 +126,13 @@ def test_correction_push_event_update_after_success(async_db, monkeypatch):
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def test_returning_push_follows_nudge(async_db, monkeypatch):
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"""24h 内同值另已发过 → 回访轻提醒 → 推送 push_type=returning,event=new。"""
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ai1 = FakeAI(extract={"联系方式": {"email": "same@x.com"}})
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ai1 = FakeAI(extract={"联系方式": {"email": "same@x.com"}}, evaluate=_EVAL)
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(m1, c1), _s1, f1 = _setup(async_db, monkeypatch, ai1)
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_send(m1, c1.session_id, "mail same@x.com")
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assert len(f1) == 1 and f1[0].push_type == "lead"
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asyncio.run(m1.db.close())
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ai2 = FakeAI(extract={"联系方式": {"email": "same@x.com"}})
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ai2 = FakeAI(extract={"联系方式": {"email": "same@x.com"}}, evaluate=_EVAL)
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(m2, c2), sent2, f2 = _setup(async_db, monkeypatch, ai2)
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_send(m2, c2.session_id, "im back, same@x.com")
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assert [s[0] for s in sent2] == ["returning"]
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@@ -157,7 +144,7 @@ def test_returning_push_follows_nudge(async_db, monkeypatch):
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def test_push_disabled_writes_nothing(async_db, monkeypatch):
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"""PUSH_ENABLED=false(默认): 零日志零派发,既有行为完全不变。"""
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monkeypatch.setattr(lead_push_service.settings, "PUSH_ENABLED", False)
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ai = FakeAI(extract={"联系方式": {"手机": "+254722111117"}})
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ai = FakeAI(extract={"联系方式": {"手机": "+254722111117"}}, evaluate=_EVAL)
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sent = []
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@@ -205,7 +192,7 @@ def test_fire_end_to_end_single_loop(async_db, monkeypatch):
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return True
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monkeypatch.setattr(email_service, "send_lead_email", fake_lead)
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ai = FakeAI(extract={"联系方式": {"手机": "+254722111117"}})
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ai = FakeAI(extract={"联系方式": {"手机": "+254722111117"}}, evaluate=_EVAL)
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async def run():
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async with async_db() as db:
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@@ -232,7 +219,7 @@ def test_fire_happens_only_after_commit(async_db, monkeypatch):
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确定性落在提交前 → NoResultFound 被记录 → 变红;正确序 gate 不触发。
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"""
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from sqlalchemy import select as sa_select
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ai = FakeAI(extract={"联系方式": {"手机": "+254722111117"}})
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ai = FakeAI(extract={"联系方式": {"手机": "+254722111117"}}, evaluate=_EVAL)
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sent = []
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read_result = {}
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commit_gate: asyncio.Event | None = None
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