merge: integrate ZSY customer service and profile capabilities

app/service/agent/base.py

@@ -134,11 +134,17 @@ class BaseAgent(ABC):
     async def recall_memory(self, request: AgentRequest, context: RequestContext) -> None:
         if self._governance is None:
             raise RecoverableAgentError("缺少记忆治理依赖")
+        # 公共召回是长期/画像记忆，不是客服二期的会话短期上下文；定义未授权时不得读取。
+        if not self.definition.recalls_customer_memory or "visitor" in context.roles:
+            self.memories = ()
+            return
         self.memories = await self._governance.recall(context)
         if any(memory.customer_id != context.user_id for memory in self.memories):
             raise RecoverableAgentError("记忆召回越过客户范围")
 
     async def classify_intent(self, request: AgentRequest) -> IntentResult | None:
+        if not self.definition.requires_model_intent_classification:
+            return None
         if self._intent_classifier is None or self._intent_endpoint_resolver is None:
             return None
         endpoints = await self._intent_endpoint_resolver.resolve(

app/service/agent/bootstrap.py

@@ -296,6 +296,15 @@ def get_agent_factory() -> AgentFactory:
         # 10s 覆盖冷启动与 Milvus 抖动，又不至于让客户等太久
         timeout_seconds=10,
     ))
+    # 兼容一期发布配置和旧客户端的工具名；实现仍复用同一个只读检索处理器。
+    registry.register(ToolDefinition(
+        name="query_knowledge",
+        input_model=KnowledgeSearchInput,
+        handler=cast(Any, knowledge_search_tool),
+        required_permission="knowledge:query",
+        allowed_roles=("visitor", "customer"),
+        timeout_seconds=10,
+    ))
     registry.register(ToolDefinition(
         name="search_risk_alerts",
         input_model=RiskAlertQuery,

app/service/agent/customer_service_agent.py

@@ -0,0 +1,5 @@
+"""Backward-compatible import path for the consolidated customer-service Agent."""
+
+from app.service.agent.implementations.customer_service import CustomerServiceAgent
+
+__all__ = ["CustomerServiceAgent"]

app/service/agent/customer_service_routing.py

@@ -0,0 +1,87 @@
+"""一期客服的确定性路由，先处理安全和边界，再允许公开知识检索。"""
+
+from collections.abc import Sequence
+from dataclasses import dataclass
+
+
+@dataclass(frozen=True)
+class CustomerServiceRoute:
+    intent: str
+    knowledge_intents: tuple[str, ...] = ()
+    is_chitchat: bool = False
+    requires_context: bool = False
+
+
+class CustomerServiceIntentRouter:
+    _SECURITY_KEYWORDS = ("验证码", "密码泄露", "被盗", "诈骗", "非本人交易")
+    # 明确的凭据披露和提示词注入必须在知识检索前拦截，避免把攻击内容当作普通 FAQ。
+    _SECURITY_DISCLOSURE_PHRASES = ("密码是", "密码为", "我的密码", "验证码是", "验证码为")
+    _PROMPT_INJECTION_KEYWORDS = (
+        "忽略之前", "忽略所有规则", "系统提示词", "开发者消息", "泄露提示词", "越过限制",
+        "不要遵守规则", "显示内部指令",
+    )
+    _COMPLIANCE_KEYWORDS = ("推荐", "收益最高", "稳赚", "保本", "帮我买", "替我交易")
+    _ACCOUNT_KEYWORDS = ("持仓", "收益", "订单", "定投", "银行卡", "风险测评", "投诉进度")
+    _HUMAN_TRANSFER_KEYWORDS = ("转人工", "人工客服", "投诉", "赔偿", "法律", "纠纷")
+    _POLICY_KEYWORDS = (
+        "申购", "赎回", "到账", "费率", "手续费", "确认份额", "交易日", "分红", "规则", "政策"
+    )
+    _PRODUCT_KEYWORDS = (
+        "产品", "基金代码", "基金经理", "份额类别", "a类", "c类", "净值", "风险等级"
+    )
+    _CHITCHAT_MESSAGES = frozenset({
+        "你好", "您好", "嗨", "哈喽", "在吗", "谢谢", "谢谢你", "再见", "拜拜",
+        "你是谁", "你叫什么", "你今天开心吗",
+    })
+    _CHITCHAT_PHRASES = ("今天天气", "讲个笑话", "你几岁", "你开心吗", "你忙吗")
+    _REFERENCE_PHRASES = ("这个", "那个", "它的", "刚才", "上面", "前面", "这只", "那只")
+
+    @classmethod
+    def classify(cls, message: str) -> CustomerServiceRoute:
+        normalized = message.strip().lower()
+        if (cls._contains(normalized, cls._SECURITY_KEYWORDS)
+                or cls._contains(normalized, cls._SECURITY_DISCLOSURE_PHRASES)):
+            return CustomerServiceRoute(intent="security_notice")
+        if cls._contains(normalized, cls._PROMPT_INJECTION_KEYWORDS):
+            return CustomerServiceRoute(intent="compliance_refusal")
+        if cls._contains(normalized, cls._COMPLIANCE_KEYWORDS):
+            return CustomerServiceRoute(intent="compliance_refusal")
+        if cls._contains(normalized, cls._ACCOUNT_KEYWORDS):
+            return CustomerServiceRoute(intent="account_entry")
+        if cls._contains(normalized, cls._HUMAN_TRANSFER_KEYWORDS):
+            return CustomerServiceRoute(intent="human_transfer")
+        if cls._is_chitchat(normalized):
+            return CustomerServiceRoute(intent="chitchat", is_chitchat=True)
+        if cls._contains(normalized, cls._POLICY_KEYWORDS):
+            return CustomerServiceRoute(
+                intent="public_knowledge", knowledge_intents=("policy_explain",),
+                requires_context=cls._contains(normalized, cls._REFERENCE_PHRASES),
+            )
+        if cls._contains(normalized, cls._PRODUCT_KEYWORDS):
+            return CustomerServiceRoute(
+                intent="public_knowledge", knowledge_intents=("product_inquiry",),
+                requires_context=cls._contains(normalized, cls._REFERENCE_PHRASES),
+            )
+        return CustomerServiceRoute(intent="public_knowledge", knowledge_intents=("faq",))
+
+    @classmethod
+    def chitchat_streak(cls, prior_messages: Sequence[str], message: str) -> int:
+        """返回当前消息在同一会话中连续闲聊的次数，最大只需记录到第五句。"""
+        if not cls._is_chitchat(message.strip().lower()):
+            return 0
+        streak = 1
+        for prior_message in reversed(prior_messages):
+            if not cls._is_chitchat(prior_message.strip().lower()):
+                break
+            streak += 1
+            if streak == 5:
+                break
+        return streak
+
+    @staticmethod
+    def _contains(message: str, keywords: tuple[str, ...]) -> bool:
+        return any(keyword in message for keyword in keywords)
+
+    @classmethod
+    def _is_chitchat(cls, message: str) -> bool:
+        return message in cls._CHITCHAT_MESSAGES or cls._contains(message, cls._CHITCHAT_PHRASES)

app/service/agent/factory.py

@@ -59,6 +59,10 @@ class AgentFactory:
             agent.bind_model_service(self._model_service)
         if self._tool_executor is not None:
             agent.bind_tool_executor(self._tool_executor)
-        if self._intent_classifier is not None and self._intent_endpoint_resolver is not None:
+        if (
+            agent.definition.requires_model_intent_classification
+            and self._intent_classifier is not None
+            and self._intent_endpoint_resolver is not None
+        ):
             agent.bind_intent_classifier(self._intent_classifier, self._intent_endpoint_resolver)
         return agent

app/service/agent/implementations/customer_service.py

@@ -27,6 +27,7 @@ from app.core.contracts import (
     RequestContext,
     SourceReference,
 )
+from app.core.customer_service_rules import route_message
 from app.core.errors import ForbiddenAgentError
 from app.service.agent.base import BaseAgent
 from app.service.model_gateway import DatabaseModelEndpointResolver
@@ -150,7 +151,7 @@ TOP_K = 5
 MAX_ANSWER_CHARS = 1200
 REFERENCE_LIMIT = 3
 
-COMPANY = "南方科技"
+COMPANY = "奶龙基金责任有限公司"
 # 客服热线：正式号码确定后改这里（或改为读配置项，避免改代码）
 HOTLINE = "400-XXX-XXXX"
 SERVICE_HOURS = "每日 7:00-22:00"
@@ -184,7 +185,7 @@ class CustomerServiceAgent(BaseAgent):
     definition = AgentDefinition(
         agent_type=AGENT_TYPE,
         version="1.0.0",
-        allowed_roles=("customer",),
+        allowed_roles=("visitor", "customer"),
         allowed_portals=("api",),
         # 代码上限：实际可用范围由发布配置的意图白名单收窄（两者取交集）
         allowed_tools=(TOOL_NAME, SUITABILITY_TOOL, PROFILE_TOOL_NAME),
@@ -192,9 +193,25 @@ class CustomerServiceAgent(BaseAgent):
             INTENT_FAQ, INTENT_PRODUCT, INTENT_POLICY, INTENT_SUITABILITY,
             INTENT_CHITCHAT, INTENT_TRANSFER,
         ),
+        # 客服不隐式召回长期画像；已登录用户的画像查询必须显式调用受控工具。
+        recalls_customer_memory=False,
     )
 
+    def __init__(self, definition: AgentDefinition | None = None) -> None:
+        """Use the class definition for direct tests and factory-created instances alike."""
+        super().__init__(definition or self.definition)
+
     async def handle(self, request: AgentRequest, context: RequestContext) -> CoreResult:
+        # 先执行确定性的安全与权限边界路由；这些分支不查知识库、不调用模型，
+        # 从根上阻断账户敏感数据、凭据泄露、诈骗和代办交易等越界请求。
+        safety = route_message(request.message)
+        if safety is not None:
+            return CoreResult(
+                text=safety.reply,
+                intent=IntentResult(intent=safety.intent, confidence=1.0),
+                transfer_required=safety.transfer_required,
+                transfer_reason=safety.transfer_reason,
+            )
         # 画像问题优先处理（确定性关键词，不走意图分类）：知识库答不了"我的风险等级是多少"，
         # 那需要读该客户的画像数据，必须走 `query_customer_profile` 工具取权威字段。
         # 放在意图分发**之前**是有意的：让画像能力不依赖意图分类是否恰好给出 faq。
@@ -508,6 +525,12 @@ class CustomerServiceAgent(BaseAgent):
     # ---- 出口二：闲聊（提示词走发布配置） ----
 
     async def _chitchat(self, request: AgentRequest) -> CoreResult:
+        # 连续闲聊超过三轮后只做一次自然的业务引导，避免模型无限延续闲聊。
+        if request.metadata.chitchat_streak == 4:
+            return CoreResult(
+                text="您好呀，您是想了解基金产品、申赎规则或其他公开业务信息吗？",
+                intent=self._classified_intent,
+            )
         system, template = await self._chitchat_prompt()
         message = request.message[:500]
         try:

app/service/agent/offsite_fund_agent.py

@@ -21,4 +21,3 @@ class OffsiteFundAgent(BaseAgent):
             f"本次请求摘要：{request.message[:120]}"
         )
         return CoreResult(text=text)
-