145 lines
6.5 KiB
Python
145 lines
6.5 KiB
Python
"""奶龙基金智能助手：只处理一期公开客服范围。"""
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from app.core.config import get_settings
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from app.core.contracts import AgentDefinition, AgentRequest, CoreResult, RequestContext
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from app.core.errors import RecoverableAgentError
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from app.core.knowledge_contracts import KnowledgeSearchResult
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from app.service.agent.base import BaseAgent
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from app.service.agent.customer_service_routing import CustomerServiceIntentRouter
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def _human_service_phone() -> str:
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return get_settings().customer_service_phone
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class CustomerServiceAgent(BaseAgent):
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# 客服澄清严格限制两轮；第三次未确认即走人工，避免用户陷入循环追问。
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MAX_CLARIFICATION_ROUNDS = 2
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definition = AgentDefinition(
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agent_type="customer_service",
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version="1.0.0",
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allowed_tools=("query_knowledge",),
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allowed_roles=("visitor", "customer"),
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allowed_portals=("api",),
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requires_model_intent_classification=False,
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# 客服只处理公开知识；会话短期记忆将在独立的受控 Redis 链路中实现。
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recalls_customer_memory=False,
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supported_intents=(
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"security_notice",
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"account_entry",
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"human_transfer",
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"compliance_refusal",
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"chitchat",
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"public_knowledge",
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"faq",
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"product_inquiry",
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"policy_explain",
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),
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)
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def __init__(self) -> None:
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super().__init__(self.definition)
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async def handle(self, request: AgentRequest, context: RequestContext) -> CoreResult:
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message = request.message.strip()
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route = CustomerServiceIntentRouter.classify(message)
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if route.intent == "security_notice":
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return CoreResult(
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text=(
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"请立即停止操作，不要继续提供验证码、密码或身份证件信息，并尽快联系"
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f"人工客服 {_human_service_phone()}。"
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),
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transfer_required=True,
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transfer_reason="security_notice",
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)
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if route.intent == "compliance_refusal":
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return CoreResult(
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text=(
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"我不能推荐具体产品、承诺收益或代您交易；如需进一步了解，请联系"
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f"人工客服 {_human_service_phone()}。"
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),
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transfer_required=True,
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transfer_reason="compliance_refusal",
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)
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if route.intent == "account_entry":
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if "visitor" in context.roles:
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return CoreResult(text="我无法查询账户数据，请先登录后前往“我的账户”查看相关状态。")
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return CoreResult(text="我无法查询账户数据，请前往“我的账户”查看相关状态。")
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if route.intent == "human_transfer":
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return CoreResult(
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text=(
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f"您可以联系人工客服 {_human_service_phone()}（工作日 09:00-18:00）"
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"进一步核实。"
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),
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transfer_required=True,
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transfer_reason="human_transfer",
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)
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if route.is_chitchat:
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if request.metadata.chitchat_streak == 4:
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return CoreResult(text="和您聊天很开心呀。您是想了解相关的基金业务或公开信息吗？")
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return CoreResult(text="您好呀，我是奶龙基金智能助手，很高兴和您聊天。")
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if route.requires_context and not request.metadata.session_context:
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return self._clarify_or_transfer(
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request.metadata.clarification_round,
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"我还不确定您说的是哪只基金或产品。请提供产品名称或代码，我再为您查询公开资料。",
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)
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# `KnowledgeQuery.query` 的契约上限是 2000 字符；上下文只是一种补充，不能挤掉
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# 当前问题，也不能因异常超长输入让客服运行失败。
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knowledge_query = message[:2000]
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if route.requires_context:
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# 短期上下文仅用于补全“它的费率”等指代；不传给模型生成，也不参与账户查询。
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knowledge_query = "\n".join((
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f"当前问题：{message}",
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"当前会话已脱敏上下文（仅用于指代消解）：",
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*request.metadata.session_context,
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))[:2000]
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try:
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output = await self.call_tool(
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"query_knowledge",
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{"query": knowledge_query, "intents": route.knowledge_intents, "top_k": 5},
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intent="public_knowledge",
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context=context,
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)
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result = (
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output
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if isinstance(output, KnowledgeSearchResult)
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else KnowledgeSearchResult.model_validate(output)
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)
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except RecoverableAgentError:
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return self._knowledge_transfer("knowledge_unavailable")
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if result.degraded:
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return self._knowledge_transfer("knowledge_unavailable")
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answers = [
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hit.answer.strip()
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for hit in result.hits
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if isinstance(hit.answer, str) and hit.answer.strip()
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]
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if not answers:
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return self._clarify_or_transfer(
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request.metadata.clarification_round,
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"为了准确查询公开资料，您想了解哪一类信息？例如产品信息、交易规则或政策说明。",
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)
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return CoreResult(text=answers[0])
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@classmethod
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def _clarify_or_transfer(cls, clarification_round: int, clarification_text: str) -> CoreResult:
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"""每次只补充一个关键信息；超过两轮仍无法确认时再转人工。"""
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if clarification_round >= cls.MAX_CLARIFICATION_ROUNDS:
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return cls._knowledge_transfer("knowledge_clarification_exhausted")
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return CoreResult(text=clarification_text, clarification_required=True)
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@staticmethod
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def _knowledge_transfer(reason: str) -> CoreResult:
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phone = _human_service_phone()
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if reason == "knowledge_unavailable":
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text = (
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"您好呀，我暂时无法从公开资料中确认这个问题，请联系"
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f"人工客服 {phone} 进一步核实。"
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)
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else:
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text = (
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"您好呀，我暂时没有查到匹配的公开资料，请联系"
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f"人工客服 {phone} 进一步核实。"
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)
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return CoreResult(text=text, transfer_required=True, transfer_reason=reason)
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