183 lines
6.5 KiB
Python
183 lines
6.5 KiB
Python
from __future__ import annotations
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import logging
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from typing import TYPE_CHECKING, Any, Optional, Tuple
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from core.post_ops import negotiation_strategy_reply
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logger = logging.getLogger("cs_agent")
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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_agent_by_intent(
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agent: "CustomerServiceAgent",
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message: "CustomerMessage",
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state: "ConversationState",
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) -> Tuple[Optional[Any], str]:
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"""
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AI 意图优先路由；识别不到时返回 (None, "intent:none")，由关键词兜底。
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"""
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try:
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from utils.intent_analyzer import detect_intent
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decision = detect_intent(message.msg or "")
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intent = (decision.intent or "").strip()
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source = decision.source or "none"
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score = float(decision.score or 0.0)
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except Exception:
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intent, source, score = "", "error", 0.0
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if not intent:
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return None, "intent:none"
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if intent in ("询价", "砍价"):
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return agent.agent_pricing, f"intent:{intent}|src:{source}|score:{score:.3f}"
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if intent in ("修改", "加急"):
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return agent.agent_processing, f"intent:{intent}|src:{source}|score:{score:.3f}"
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if intent == "售后":
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return agent.agent_after_sale, f"intent:{intent}|src:{source}|score:{score:.3f}"
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if intent == "转接":
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return agent.agent_after_sale, f"intent:{intent}|src:{source}|score:{score:.3f}"
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if intent in ("打招呼", "批量", "发图"):
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target = agent.agent_after_sale if state.stage == "售后" else agent.agent
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return target, f"intent:{intent}|src:{source}|score:{score:.3f}"
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return None, f"intent:unmapped:{intent}|src:{source}|score:{score:.3f}"
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def select_target_agent(agent: "CustomerServiceAgent", message: "CustomerMessage", state: "ConversationState") -> Tuple[Any, str]:
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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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ai_target, ai_reason = _select_agent_by_intent(agent, message, state)
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if ai_target is not None:
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return ai_target, ai_reason
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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, "keyword:risk"
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if any(k in message.msg for k in order_markers):
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return agent.agent_order, "keyword:order"
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if any(k in msg_lower for k in processing_kw):
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return agent.agent_processing, "keyword:processing"
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if any(k in msg_lower for k in pricing_kw):
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return agent.agent_pricing, "keyword:pricing"
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if any(k in msg_lower for k in similar_kw):
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return agent.agent_similar, "keyword:similar"
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return target_agent, "fallback:default"
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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, route_reason = select_target_agent(agent, message, state)
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logger.info("[路由] %s", route_reason)
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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 = 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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logger.info(
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"[THINK/TOOL_CALL] %s(%s)",
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getattr(part, "tool_name", ""),
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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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logger.info("[THINK/TOOL_RETURN] %s", ret)
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logger.info("[THINK/RAW_OUTPUT] %r", reply_text)
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return reply_text
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