refactor: split order handling and ai routing flow from agent
This commit is contained in:
135
core/ai_reply_flow.py
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135
core/ai_reply_flow.py
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@@ -0,0 +1,135 @@
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from __future__ import annotations
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from typing import TYPE_CHECKING, Any
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if TYPE_CHECKING:
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from core.pydantic_ai_agent import AgentDeps, ConversationState, CustomerMessage, CustomerServiceAgent
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def select_target_agent(agent: "CustomerServiceAgent", message: "CustomerMessage", state: "ConversationState"):
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msg_lower = message.msg.lower()
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pricing_kw = ["多少钱", "多少一张", "报价", "给个价", "几块", "价位", "能便宜点吗"]
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processing_kw = ["安排", "处理一下", "开始做", "做一下", "尽快", "加急", "付款了", "已付款"]
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similar_kw = ["有一样的", "有一样吗", "一样的吗", "类似的", "类似的吗", "同款", "相似", "类似吗"]
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order_markers = ["[系统订单信息]", "订单状态", "买家已付款"]
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risk_kw = [
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"黄色",
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"擦边",
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"色情",
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"涉黄",
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"涉政",
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"政治",
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"裸",
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"不雅",
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"天安门",
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"政治人物",
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"政治事件",
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"领导人",
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"党政",
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"习近平",
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"毛泽东",
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"邓小平",
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"江泽民",
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"胡锦涛",
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"特朗普",
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"拜登",
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"普京",
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"泽连斯基",
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"地图",
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"地形图",
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"行政区划图",
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"卫星地图",
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]
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target_agent = agent.agent_after_sale if state.stage == "售后" else agent.agent
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risk_hit = any(k in msg_lower for k in risk_kw) or agent._is_political_inquiry(message.msg) or agent._is_map_inquiry(message.msg)
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if risk_hit:
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return agent.agent_risk
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if any(k in message.msg for k in order_markers):
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return agent.agent_order
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if any(k in msg_lower for k in processing_kw):
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return agent.agent_processing
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if any(k in msg_lower for k in pricing_kw):
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return agent.agent_pricing
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if any(k in msg_lower for k in similar_kw):
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return agent.agent_similar
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return target_agent
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async def execute_ai_turn(
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agent: "CustomerServiceAgent",
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*,
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message: "CustomerMessage",
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state: "ConversationState",
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user_prompt: str,
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deps: "AgentDeps",
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history: list,
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) -> str:
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target_agent = select_target_agent(agent, message, state)
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result = await target_agent.run(user_prompt, deps=deps, message_history=history)
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agent.message_histories[message.from_id] = result.all_messages()[-30:]
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reply_text = agent._colloquialize_reply(agent._normalize_reply_text(result.output))
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strategy_reply = agent._negotiation_strategy_reply(message.msg, state)
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if strategy_reply:
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reply_text = strategy_reply
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try:
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from config.config import MIN_PRICE_FLOOR
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import re
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offer = None
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m = re.search(r"(\d{1,4})\s*(?:元|块|块钱|元钱)\b", message.msg)
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if m:
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offer = int(m.group(1))
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else:
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m2 = re.search(r"(?:能|可以|可否|能否)\s*(\d{1,4})\b", message.msg)
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offer = int(m2.group(1)) if m2 else None
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st = agent._get_conversation_state(message.from_id)
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floor = st.last_min_price if isinstance(st.last_min_price, int) and st.last_min_price > 0 else MIN_PRICE_FLOOR
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if offer is not None and offer < floor:
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reply_text = "不好意思"
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except Exception:
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pass
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try:
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from config.config import MIN_PRICE_FLOOR
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import re
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st = agent._get_conversation_state(message.from_id)
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floor = st.last_min_price if isinstance(st.last_min_price, int) and st.last_min_price > 0 else MIN_PRICE_FLOOR
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def _adjust(text: str) -> str:
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def _repl(m: Any):
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num = int(m.group(1))
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adj = max(floor, round(num / 5) * 5)
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return m.group(0).replace(str(num), str(adj))
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patterns = [
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r"按(\d{1,4})元",
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r"报价[：:]\s*(\d{1,4})\s*元",
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r"(\d{1,4})\s*元一张",
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r"打包(\d{1,4})\s*元",
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]
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t = text
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for p in patterns:
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t = re.sub(p, _repl, t)
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return t
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reply_text = _adjust(reply_text or "")
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except Exception:
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pass
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for msg in result.new_messages():
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for part in getattr(msg, "parts", []):
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part_type = type(part).__name__
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if "ToolCall" in part_type:
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print(
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f"{agent.C_TOOL}[THINK/TOOL_CALL]{agent.C_RESET} "
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f"{getattr(part, 'tool_name', '')}({getattr(part, 'args', '')})"
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)
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elif "ToolReturn" in part_type:
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ret = str(getattr(part, "content", ""))[:120]
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print(f"{agent.C_TOOL}[THINK/TOOL_RETURN]{agent.C_RESET} {ret}")
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print(f"{agent.C_THINK}[THINK/RAW_OUTPUT]{agent.C_RESET} {repr(reply_text)}")
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return reply_text
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59
core/order_flow.py
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59
core/order_flow.py
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@@ -0,0 +1,59 @@
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from __future__ import annotations
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import asyncio
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from typing import TYPE_CHECKING, Optional
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if TYPE_CHECKING:
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from core.pydantic_ai_agent import AgentResponse, ConversationState, CustomerMessage, CustomerServiceAgent
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async def handle_order_notification(
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agent: "CustomerServiceAgent",
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*,
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message: "CustomerMessage",
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state: "ConversationState",
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) -> Optional["AgentResponse"]:
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"""Handle system order notifications before normal AI dialogue."""
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from core.pydantic_ai_agent import AgentResponse
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if "系统订单信息" not in message.msg and "订单状态" not in message.msg:
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return None
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_, order_block = agent._split_customer_text(message.msg)
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customer_text, _ = agent._split_customer_text(message.msg)
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order = agent._parse_order_info(order_block or message.msg)
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pay_status = order.get("pay_status", "")
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order_status = order.get("order_status", "")
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paid_keywords = ["等待发货", "已付款", "付款成功", "买家已付款"]
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is_paid = any(kw in pay_status or kw in order_status for kw in paid_keywords)
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if is_paid:
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asyncio.create_task(agent._check_order_amount(message.from_id, order, message.acc_id))
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asyncio.create_task(
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agent._record_deal_success(
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message.from_id,
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message.from_name,
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message.acc_id,
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message.acc_type,
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order,
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state,
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)
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)
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try:
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from core.workflow import workflow
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asyncio.create_task(
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workflow.trigger_processing_on_payment(
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customer_id=message.from_id,
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acc_id=message.acc_id,
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acc_type=message.acc_type,
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)
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)
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except Exception as e:
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print(f"[Agent] 触发作图失败: {e}")
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elif not customer_text:
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print(f"[Agent] 订单通知静默（{pay_status or order_status}），跳过回复")
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return AgentResponse(reply="", should_reply=False, need_transfer=False)
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return None
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@@ -27,6 +27,8 @@ from core.quote_state_machine import QuoteStateMachine
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from services.risk_service import RiskService
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from core.agent_pre_rules import AgentPreRuleService
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from core.find_image_flow import handle_find_image_batch_flow
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from core.order_flow import handle_order_notification
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from core.ai_reply_flow import execute_ai_turn
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load_dotenv()
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@@ -1790,41 +1792,9 @@ class CustomerServiceAgent:
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state.last_update = datetime.now().isoformat()
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# 订单通知前置处理
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if "系统订单信息" in message.msg or "订单状态" in message.msg:
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_, order_block = self._split_customer_text(message.msg)
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customer_text, _ = self._split_customer_text(message.msg)
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order = self._parse_order_info(order_block or message.msg)
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pay_status = order.get("pay_status", "")
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order_status = order.get("order_status", "")
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paid_keywords = ["等待发货", "已付款", "付款成功", "买家已付款"]
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is_paid = any(kw in pay_status or kw in order_status for kw in paid_keywords)
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if is_paid:
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# 订单金额核查：对比报价和实付金额
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asyncio.create_task(self._check_order_amount(
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message.from_id, order, message.acc_id
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))
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# 成交记录：写入数据库供日报分析
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asyncio.create_task(self._record_deal_success(
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message.from_id, message.from_name, message.acc_id, message.acc_type,
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order, state
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))
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# 已付款：触发 Gemini 作图
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try:
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from core.workflow import workflow
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asyncio.create_task(workflow.trigger_processing_on_payment(
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customer_id=message.from_id,
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acc_id=message.acc_id,
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acc_type=message.acc_type,
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))
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except Exception as e:
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print(f"[Agent] 触发作图失败: {e}")
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elif not customer_text:
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# 非付款 + 没有客户文字 → 直接静默，不调用 AI
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print(f"[Agent] 订单通知静默（{pay_status or order_status}），跳过回复")
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return AgentResponse(reply="", should_reply=False, need_transfer=False)
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order_response = await handle_order_notification(self, message=message, state=state)
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if isinstance(order_response, AgentResponse):
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return order_response
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customer_text, _ = self._split_customer_text(message.msg)
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shop_type = _get_shop_type(message.acc_id or "", message.goods_name or "")
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@@ -1874,93 +1844,14 @@ class CustomerServiceAgent:
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self._log_block("PROMPT->AI 前置提示词", user_prompt)
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try:
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msg_lower = message.msg.lower()
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pricing_kw = ["多少钱", "多少一张", "报价", "给个价", "几块", "价位", "能便宜点吗"]
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processing_kw = ["安排", "处理一下", "开始做", "做一下", "尽快", "加急", "付款了", "已付款"]
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similar_kw = ["有一样的", "有一样吗", "一样的吗", "类似的", "类似的吗", "同款", "相似", "类似吗"]
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order_markers = ["[系统订单信息]", "订单状态", "买家已付款"]
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risk_kw = [
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"黄色", "擦边", "色情", "涉黄", "涉政", "政治", "裸", "不雅",
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"天安门", "政治人物", "政治事件", "领导人", "党政",
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"习近平", "毛泽东", "邓小平", "江泽民", "胡锦涛",
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"特朗普", "拜登", "普京", "泽连斯基",
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"地图", "地形图", "行政区划图", "卫星地图",
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]
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target_agent = self.agent_after_sale if state.stage == "售后" else self.agent
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risk_hit = any(k in msg_lower for k in risk_kw) or self._is_political_inquiry(message.msg) or self._is_map_inquiry(message.msg)
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if risk_hit:
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target_agent = self.agent_risk
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elif any(k in message.msg for k in order_markers):
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target_agent = self.agent_order
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elif any(k in msg_lower for k in processing_kw):
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target_agent = self.agent_processing
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elif any(k in msg_lower for k in pricing_kw):
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target_agent = self.agent_pricing
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elif any(k in msg_lower for k in similar_kw):
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target_agent = self.agent_similar
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result = await target_agent.run(user_prompt, deps=deps, message_history=history)
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# 更新历史，最多保留最近 30 条消息防止 token 超限
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self.message_histories[message.from_id] = result.all_messages()[-30:]
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reply_text = self._colloquialize_reply(self._normalize_reply_text(result.output))
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# 价格谈判与信任建立固定策略（避免只回“最低了/先拍下”）
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strategy_reply = self._negotiation_strategy_reply(message.msg, state)
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if strategy_reply:
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reply_text = strategy_reply
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# 拦截超低杀价：客户报价低于底线时，统一礼貌拒绝
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try:
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from config.config import MIN_PRICE_FLOOR
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import re
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offer = None
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m = re.search(r'(\d{1,4})\s*(?:元|块|块钱|元钱)\b', message.msg)
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if m:
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offer = int(m.group(1))
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else:
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m2 = re.search(r'(?:能|可以|可否|能否)\s*(\d{1,4})\b', message.msg)
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offer = int(m2.group(1)) if m2 else None
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st = self._get_conversation_state(message.from_id)
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floor = st.last_min_price if isinstance(st.last_min_price, int) and st.last_min_price > 0 else MIN_PRICE_FLOOR
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if offer is not None and offer < floor:
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reply_text = "不好意思"
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except Exception:
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pass
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# 降限：若AI在回复中给出小于底线的报价，提升到>=底线且为5的倍数
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try:
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from config.config import MIN_PRICE_FLOOR
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st = self._get_conversation_state(message.from_id)
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floor = st.last_min_price if isinstance(st.last_min_price, int) and st.last_min_price > 0 else MIN_PRICE_FLOOR
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def _adjust(text: str) -> str:
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import re
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def _repl(m):
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num = int(m.group(1))
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adj = max(floor, round(num / 5) * 5)
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return m.group(0).replace(str(num), str(adj))
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patterns = [
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r'按(\d{1,4})元',
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r'报价[：:]\s*(\d{1,4})\s*元',
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r'(\d{1,4})\s*元一张',
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r'打包(\d{1,4})\s*元',
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]
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t = text
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for p in patterns:
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t = re.sub(p, _repl, t)
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return t
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reply_text = _adjust(reply_text or "")
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except Exception:
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pass
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# 打印工具调用记录
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for msg in result.new_messages():
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for part in getattr(msg, 'parts', []):
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part_type = type(part).__name__
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if 'ToolCall' in part_type:
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print(f"{self.C_TOOL}[THINK/TOOL_CALL]{self.C_RESET} {getattr(part, 'tool_name', '')}({getattr(part, 'args', '')})")
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elif 'ToolReturn' in part_type:
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ret = str(getattr(part, 'content', ''))[:120]
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print(f"{self.C_TOOL}[THINK/TOOL_RETURN]{self.C_RESET} {ret}")
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print(f"{self.C_THINK}[THINK/RAW_OUTPUT]{self.C_RESET} {repr(reply_text)}")
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reply_text = await execute_ai_turn(
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self,
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message=message,
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state=state,
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user_prompt=user_prompt,
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deps=deps,
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history=history,
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)
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except Exception as e:
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err_str = str(e)
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print(f"[Agent] AI 调用失败: {e}，使用兜底回复")
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