312 lines
12 KiB
Python
312 lines
12 KiB
Python
from __future__ import annotations
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import asyncio
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import json
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import logging
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import re
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from dataclasses import dataclass
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from typing import Any
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logger = logging.getLogger("cs_agent")
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@dataclass
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class BrainDecision:
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action: str # reply | quote | transfer | noop
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source: str
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reply: str = ""
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transfer_msg: str = ""
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should_reply: bool = False
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need_transfer: bool = False
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payload: dict[str, Any] | None = None
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def _extract_json_obj(text: str) -> dict[str, Any] | None:
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if not text:
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return None
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m = re.search(r"\{[\s\S]*\}", text)
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if not m:
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return None
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try:
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return json.loads(m.group(0))
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except Exception:
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return None
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async def _ai_policy_brain_decide(client, data: dict, *, msg_text: str, shop_type: str) -> BrainDecision | None:
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if not client.enable_agent or not client.agent or not client.AgentDeps:
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return None
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acc_id = str(data.get("acc_id", "") or "")
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customer_id = str(data.get("from_id", "") or "")
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current_urls = client._extract_image_urls(msg_text)
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recent_urls = client._collect_recent_image_urls(customer_id, acc_id, max_count=6)
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key = client._customer_key(data)
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pending_urls = client._pending_images.get(key) or []
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try:
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order_status = client._detect_order_status(msg_text)
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has_image_url = client._msg_has_image_url(msg_text)
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refers_images = client._msg_refers_images(msg_text)
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is_price = client._msg_is_price_inquiry(msg_text)
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is_req = client._msg_is_requirement(msg_text)
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ext_contact = client._msg_requests_external_contact(msg_text)
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except Exception:
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order_status, has_image_url, refers_images, is_price, is_req, ext_contact = "", False, False, False, False, False
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deps = client.AgentDeps(
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msg_id=str(data.get("msg_id", "") or "brain_policy"),
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acc_id=acc_id,
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from_id=customer_id,
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platform=str(data.get("acc_type", "") or "AliWorkbench"),
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)
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prompt = (
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"你是淘宝客服系统的主决策Brain，只做决策，不要解释。\n"
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"你必须根据历史规则和当前上下文，输出唯一动作。\n"
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"可选动作 action: reply / quote / transfer / noop。\n"
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"历史规则（完整继承）:\n"
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"1) 客户发图/补图：先自然承接，再根据上下文决定继续收集或报价；\n"
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"2) 客户询价且有可用图片（当前或最近）时，优先 action=quote；\n"
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"3) 若有 pending 图片且客户催报价/补充需求，优先 quote_mode=flush_pending；\n"
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"4) 仅打招呼/短无意义文本：可 action=reply 简短承接，不要机械模板；\n"
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"5) 索要外部联系方式（微信/QQ/手机号）时，不外呼，站内引导；\n"
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"6) 订单已付款：可回执安排处理；未付款/待付款：提醒完成付款；\n"
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"7) 地图/政治/高风险内容：谨慎，必要时 transfer 或拒绝性 reply；\n"
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"8) 尺寸超限/不可做场景：给明确边界，不要胡乱承诺；\n"
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"9) 客户没发图却问价：先承接，再引导发图；\n"
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"10) 避免重复外发，避免同一句话反复说。\n"
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"\n"
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"quote_mode 可选: flush_pending / analyze_current_or_recent / collect_only\n"
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"只输出 JSON：\n"
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'{"action":"reply|quote|transfer|noop","reply":"","transfer_msg":"","quote_mode":"","reason":""}\n\n'
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f"店铺类型: {shop_type}\n"
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f"legacy_fast_quote_enabled: {str(bool(client._legacy_fast_quote_enabled)).lower()}\n"
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f"客户原话: {msg_text}\n"
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f"has_image_url: {has_image_url}\n"
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f"current_image_urls_count: {len(current_urls)}\n"
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f"recent_image_urls_count: {len(recent_urls)}\n"
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f"pending_image_urls_count: {len(pending_urls)}\n"
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f"refers_images: {refers_images}\n"
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f"is_price_inquiry: {is_price}\n"
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f"is_requirement: {is_req}\n"
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f"requests_external_contact: {ext_contact}\n"
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f"order_status: {order_status or 'none'}\n"
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)
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try:
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result = await client.agent.agent_natural_reply.run(prompt, deps=deps, message_history=[])
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raw = str(getattr(result, "output", "") or "").strip()
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obj = _extract_json_obj(raw)
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if not obj:
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client._activity_log(
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"brain_policy_parse_error",
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acc_id=acc_id,
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customer_id=customer_id,
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raw=raw[:300],
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)
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return None
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action = str(obj.get("action", "") or "").strip().lower()
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reply = str(obj.get("reply", "") or "").strip()
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transfer_msg = str(obj.get("transfer_msg", "") or "").strip()
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quote_mode = str(obj.get("quote_mode", "") or "").strip().lower()
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reason = str(obj.get("reason", "") or "").strip()
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payload: dict[str, Any] | None = None
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if action == "quote":
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mode = quote_mode or "analyze_current_or_recent"
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if mode == "flush_pending":
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payload = {"mode": "flush_pending", "key": key, "pre_reply": reply}
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elif mode == "collect_only":
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payload = {"mode": "collect_only", "pre_reply": reply}
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else:
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urls = current_urls or recent_urls
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payload = {"mode": "analyze_urls", "urls": urls, "pre_reply": reply}
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decision = BrainDecision(
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action=action if action in {"reply", "quote", "transfer", "noop"} else "noop",
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source="brain_ai_policy",
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reply=reply,
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transfer_msg=transfer_msg,
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should_reply=bool(reply),
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need_transfer=(action == "transfer"),
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payload=payload,
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)
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client._activity_log(
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"brain_policy_raw",
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acc_id=acc_id,
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customer_id=customer_id,
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action=decision.action,
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quote_mode=quote_mode,
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reason=reason,
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)
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return decision
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except Exception as e:
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client._activity_log(
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"brain_policy_error",
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acc_id=acc_id,
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customer_id=customer_id,
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error=str(e),
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)
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return None
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async def decide_brain_action(client, data: dict, customer_msg, *, trace_id: str, msg_text: str, shop_type: str) -> BrainDecision:
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"""统一主决策层：优先由 Brain AI 决策；失败时回退 Agent 默认决策。"""
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ai_decision = await _ai_policy_brain_decide(client, data, msg_text=msg_text, shop_type=shop_type)
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if ai_decision is not None:
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return ai_decision
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# 回退：保持可用性
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logger.info("Agent 正在处理消息...")
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client._activity_log(
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"agent_process_start",
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trace_id=trace_id,
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acc_id=data.get("acc_id", ""),
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customer_id=data.get("from_id", ""),
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msg=msg_text,
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)
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response = await client.agent.process_message(customer_msg)
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client._activity_log(
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"agent_process_done",
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trace_id=trace_id,
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acc_id=data.get("acc_id", ""),
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customer_id=data.get("from_id", ""),
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result="ok",
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should_reply=bool(response.should_reply),
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need_transfer=bool(response.need_transfer),
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)
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if response.need_transfer:
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return BrainDecision(
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action="transfer",
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source="fallback_agent",
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reply=response.reply or "",
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transfer_msg=response.transfer_msg or "",
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should_reply=bool(response.should_reply),
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need_transfer=True,
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)
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if response.should_reply and response.reply:
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return BrainDecision(
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action="reply",
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source="fallback_agent",
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reply=response.reply,
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should_reply=True,
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need_transfer=False,
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)
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return BrainDecision(action="noop", source="fallback_agent", should_reply=False, need_transfer=False)
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async def execute_brain_action(client, data: dict, *, decision: BrainDecision, trace_id: str, msg_text: str):
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"""统一执行层：只执行标准动作。"""
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customer_id = data.get("from_id", "")
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if customer_id:
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client._touch_customer_last_contact(customer_id)
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if decision.action == "transfer":
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logger.info("Agent 决定转接人工")
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client._activity_log(
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"agent_transfer",
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trace_id=trace_id,
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acc_id=data.get("acc_id", ""),
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customer_id=data.get("from_id", ""),
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transfer_msg=decision.transfer_msg,
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)
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client._fire_and_forget(
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client._post_tianwang_callback(
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"message_processed",
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data,
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extra={
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"should_reply": bool(decision.should_reply),
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"need_transfer": True,
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"agent_reply": decision.reply or "",
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"transfer_msg": decision.transfer_msg or "",
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},
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)
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)
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await client.transfer_to_human(data, decision.transfer_msg)
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client._push_chat_to_wechat_safe(
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data=data,
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customer_msg=msg_text,
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reply_msg=decision.transfer_msg or "转接",
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tag="转人工",
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)
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return
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if decision.action == "reply":
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text = (decision.reply or "").strip()
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if not text:
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return
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await asyncio.sleep(0.6)
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client._activity_log(
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"agent_reply",
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trace_id=trace_id,
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acc_id=data.get("acc_id", ""),
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customer_id=data.get("from_id", ""),
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reply=text,
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)
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await client.send_reply(data, text)
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await client._maybe_schedule_auto_quote(data)
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client._fire_and_forget(
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client._post_tianwang_callback(
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"message_processed",
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data,
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extra={
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"should_reply": True,
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"need_transfer": False,
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"agent_reply": text,
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},
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)
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)
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client._push_chat_to_wechat_safe(
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data=data,
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customer_msg=msg_text,
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reply_msg=text,
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tag="正常AI回复",
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)
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return
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if decision.action == "quote":
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payload = decision.payload or {}
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pre_reply = str(payload.get("pre_reply", "") or "").strip()
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if pre_reply:
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await client.send_reply(data, pre_reply)
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mode = str(payload.get("mode", "") or "")
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if mode == "flush_pending":
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key = str(payload.get("key", "") or "")
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if key:
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await client._flush_pending_images(key, data)
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elif mode == "analyze_urls":
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urls = payload.get("urls") or []
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if isinstance(urls, list) and urls:
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if len(urls) == 1:
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asyncio.create_task(client._analyze_single_and_reply(data, urls[0]))
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else:
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asyncio.create_task(client._analyze_multi_and_reply(data, urls))
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else:
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await client.send_reply(data, "你把要处理的图再发我一下，我马上给你看。")
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else:
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if not pre_reply:
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await client.send_reply(data, "收到，我先看一下哈，稍等哈。")
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return
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# noop
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client._activity_log(
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"agent_no_reply",
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trace_id=trace_id,
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acc_id=data.get("acc_id", ""),
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customer_id=data.get("from_id", ""),
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)
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client._fire_and_forget(
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client._post_tianwang_callback(
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"message_processed",
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data,
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extra={
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"should_reply": False,
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"need_transfer": False,
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"agent_reply": "",
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},
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)
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)
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