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>

tests/test_lead_email_trigger.py

@@ -10,40 +10,7 @@ from app.engine.models import (
 )
 from app.engine.services.conversation import CONTACT_ASK_TRIGGER_RE, ConversationManager
 from app.engine.services import email_service
-from tests.conftest import build_jiancai_runtime
-
-
-class FakeAI:
-    """替代 GLM 的确定性桩：构造参数即每轮返回值。"""
-
-    def __init__(self, extract=None, evaluate=None):
-        self._extract_seq = extract if isinstance(extract, list) else [extract or {}]
-        self._evaluate = evaluate or {}
-        self.eval_calls = 0
-
-    async def chat(self, messages, context=""):
-        return "ok reply"
-
-    async def stream_chat(self, messages, context=""):
-        for token in ("ok ", "reply"):
-            yield token
-
-    async def extract_info(self, messages, existing_info):
-        # 第 N 轮客户消息 → seq[N-1]（messages 为 [u,a,u,a...] 全量历史）
-        idx = min(max(len(messages) // 2 - 1, 0), len(self._extract_seq) - 1)
-        return self._extract_seq[idx]
-
-    async def evaluate(self, profile, recent_messages):
-        self.eval_calls += 1
-        result = dict(self._evaluate)
-        result.setdefault("intent_level", "pending")
-        result.setdefault("reasoning", "")
-        result.setdefault("contact_info", {})
-        result.setdefault("info_sufficient", False)
-        if result["intent_level"] not in ("interested", "not_interested", "pending"):
-            result["intent_level"] = "pending"
-        return result
-
+from tests.conftest import FakeAI, build_jiancai_runtime
 
 INTERESTED = {
     "intent_level": "interested", "reasoning": "预算国家品类齐全",