refactor: extract pre-rules and find-image quote flow from agent
This commit is contained in:
200
core/agent_pre_rules.py
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200
core/agent_pre_rules.py
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from __future__ import annotations
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import random
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from datetime import datetime
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from typing import TYPE_CHECKING, Optional
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from core.rules import Rule, RuleContext, RuleEngine, RuleResult
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from services.risk_service import RiskService
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if TYPE_CHECKING:
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from core.pydantic_ai_agent import (
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AgentResponse,
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ConversationState,
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CustomerMessage,
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CustomerServiceAgent,
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)
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class AgentPreRuleService:
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"""Pre-processing rule chain for short replies, cooldown, and text risk."""
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def __init__(self, agent: "CustomerServiceAgent", risk_service: RiskService):
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self.agent = agent
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self.risk_service = risk_service
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self.engine = self._build_engine()
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async def run(
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self,
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*,
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message: "CustomerMessage",
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state: "ConversationState",
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trace_id: str,
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) -> Optional["AgentResponse"]:
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ctx = RuleContext(data={"message": message, "state": state, "trace_id": trace_id})
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result = await self.engine.run(ctx)
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if not result.stop:
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return None
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response = result.payload.get("response")
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return response
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def _build_engine(self) -> RuleEngine:
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return RuleEngine(
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rules=[
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Rule(
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name="meaningless_short_text",
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priority=10,
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predicate=self._rule_pred_meaningless_short_text,
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action=self._rule_act_meaningless_short_text,
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),
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Rule(
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name="cooldown_silent",
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priority=20,
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predicate=self._rule_pred_cooldown_silent,
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action=self._rule_act_cooldown_silent,
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),
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Rule(
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name="manual_risk_block",
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priority=30,
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predicate=self._rule_pred_manual_risk_block,
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action=self._rule_act_manual_risk_block,
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),
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Rule(
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name="text_risk_block",
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priority=40,
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predicate=self._rule_pred_text_risk_block,
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action=self._rule_act_text_risk_block,
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),
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]
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)
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async def _rule_pred_meaningless_short_text(self, ctx: RuleContext) -> bool:
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from core.pydantic_ai_agent import _is_meaningless_short_text
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message = ctx.get("message")
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return _is_meaningless_short_text(message.msg)
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async def _rule_act_meaningless_short_text(self, ctx: RuleContext) -> RuleResult:
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from core.pydantic_ai_agent import AgentResponse
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message = ctx.get("message")
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state = ctx.get("state")
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trace_id = ctx.get("trace_id", "")
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ping = random.choice(("嗯咯", "嗯啦", "嗯", "哦"))
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state.last_reply_at = datetime.now()
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self.agent._activity_log(
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"agent_ping_reply",
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trace_id=trace_id,
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customer_id=message.from_id,
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msg=message.msg,
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reply=ping,
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)
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return RuleResult(
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matched=True,
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stop=True,
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action="agent_ping_reply",
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payload={"response": AgentResponse(reply=ping, should_reply=True, need_transfer=False)},
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)
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async def _rule_pred_cooldown_silent(self, ctx: RuleContext) -> bool:
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message = ctx.get("message")
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state = ctx.get("state")
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return self.agent._in_cooldown(state, message.msg)
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async def _rule_act_cooldown_silent(self, ctx: RuleContext) -> RuleResult:
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from core.pydantic_ai_agent import AgentResponse
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message = ctx.get("message")
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state = ctx.get("state")
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trace_id = ctx.get("trace_id", "")
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elapsed = int((datetime.now() - state.last_reply_at).total_seconds()) if state.last_reply_at else 0
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print(f"[Agent] 冷却期静默（距上次回复 {elapsed}s）：{message.msg!r}")
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self.agent._activity_log(
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"agent_cooldown_silent",
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trace_id=trace_id,
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customer_id=message.from_id,
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elapsed_s=elapsed,
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)
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return RuleResult(
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matched=True,
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stop=True,
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action="agent_cooldown_silent",
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payload={"response": AgentResponse(reply="", should_reply=False, need_transfer=False)},
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)
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async def _rule_pred_manual_risk_block(self, ctx: RuleContext) -> bool:
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message = ctx.get("message")
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decision = self.risk_service.check_manual_block(message.from_id)
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ctx.set("manual_risk_decision", decision)
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return decision.blocked
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async def _rule_act_manual_risk_block(self, ctx: RuleContext) -> RuleResult:
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from core.pydantic_ai_agent import AgentResponse, TRANSFER_MESSAGE
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message = ctx.get("message")
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trace_id = ctx.get("trace_id", "")
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decision = ctx.get("manual_risk_decision")
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self.agent._activity_log(
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"agent_manual_risk_reject",
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trace_id=trace_id,
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customer_id=message.from_id,
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risk=(decision.profile if decision else {}),
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)
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return RuleResult(
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matched=True,
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stop=True,
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action="agent_manual_risk_reject",
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payload={
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"response": AgentResponse(
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reply="这边无法继续为你处理该类需求，给你转人工专员对接。",
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should_reply=True,
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need_transfer=True,
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transfer_msg=TRANSFER_MESSAGE,
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)
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},
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)
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async def _rule_pred_text_risk_block(self, ctx: RuleContext) -> bool:
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message = ctx.get("message")
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decision = await self.risk_service.check_text_block(
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message.msg,
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political_detector=self.agent._is_political_inquiry,
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map_detector=self.agent._is_map_inquiry,
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)
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ctx.set("text_risk_decision", decision)
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return decision.blocked
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async def _rule_act_text_risk_block(self, ctx: RuleContext) -> RuleResult:
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from core.pydantic_ai_agent import AgentResponse
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message = ctx.get("message")
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state = ctx.get("state")
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trace_id = ctx.get("trace_id", "")
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decision = ctx.get("text_risk_decision")
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state.pending_image_urls.clear()
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state.pending_requirements.clear()
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self.agent._sync_pending_quote_state(message.from_id, state)
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reject_text = self.risk_service.build_reject_text(decision.category if decision else "other")
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reply = await self.agent._rewrite_reply_with_ai(
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message=message,
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state=state,
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reply=reject_text,
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scene="risk_reject",
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)
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state.last_reply_at = datetime.now()
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print(f"{self.agent.C_REPLY}[REPLY->CUSTOMER]{self.agent.C_RESET} {reply}")
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self.agent._activity_log(
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"agent_risk_reject",
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trace_id=trace_id,
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customer_id=message.from_id,
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risk_category=(decision.category if decision else "other"),
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risk_source=(decision.source if decision else "unknown"),
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reply=reply,
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)
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return RuleResult(
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matched=True,
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stop=True,
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action="agent_risk_reject",
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payload={"response": AgentResponse(reply=reply, should_reply=True, need_transfer=False)},
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)
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