refactor: split order handling and ai routing flow from agent

core/ai_reply_flow.py

@@ -0,0 +1,135 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Any
+
+if TYPE_CHECKING:
+    from core.pydantic_ai_agent import AgentDeps, ConversationState, CustomerMessage, CustomerServiceAgent
+
+
+def select_target_agent(agent: "CustomerServiceAgent", message: "CustomerMessage", state: "ConversationState"):
+    msg_lower = message.msg.lower()
+    pricing_kw = ["多少钱", "多少一张", "报价", "给个价", "几块", "价位", "能便宜点吗"]
+    processing_kw = ["安排", "处理一下", "开始做", "做一下", "尽快", "加急", "付款了", "已付款"]
+    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"]
+    order_markers = ["[系统订单信息]", "订单状态", "买家已付款"]
+    risk_kw = [
+        "黄色",
+        "擦边",
+        "色情",
+        "涉黄",
+        "涉政",
+        "政治",
+        "裸",
+        "不雅",
+        "天安门",
+        "政治人物",
+        "政治事件",
+        "领导人",
+        "党政",
+        "习近平",
+        "毛泽东",
+        "邓小平",
+        "江泽民",
+        "胡锦涛",
+        "特朗普",
+        "拜登",
+        "普京",
+        "泽连斯基",
+        "地图",
+        "地形图",
+        "行政区划图",
+        "卫星地图",
+    ]
+    target_agent = agent.agent_after_sale if state.stage == "售后" else agent.agent
+    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)
+    if risk_hit:
+        return agent.agent_risk
+    if any(k in message.msg for k in order_markers):
+        return agent.agent_order
+    if any(k in msg_lower for k in processing_kw):
+        return agent.agent_processing
+    if any(k in msg_lower for k in pricing_kw):
+        return agent.agent_pricing
+    if any(k in msg_lower for k in similar_kw):
+        return agent.agent_similar
+    return target_agent
+
+
+async def execute_ai_turn(
+    agent: "CustomerServiceAgent",
+    *,
+    message: "CustomerMessage",
+    state: "ConversationState",
+    user_prompt: str,
+    deps: "AgentDeps",
+    history: list,
+) -> str:
+    target_agent = select_target_agent(agent, message, state)
+    result = await target_agent.run(user_prompt, deps=deps, message_history=history)
+    agent.message_histories[message.from_id] = result.all_messages()[-30:]
+    reply_text = agent._colloquialize_reply(agent._normalize_reply_text(result.output))
+
+    strategy_reply = agent._negotiation_strategy_reply(message.msg, state)
+    if strategy_reply:
+        reply_text = strategy_reply
+
+    try:
+        from config.config import MIN_PRICE_FLOOR
+        import re
+
+        offer = None
+        m = re.search(r"(\d{1,4})\s*(?:元|块|块钱|元钱)\b", message.msg)
+        if m:
+            offer = int(m.group(1))
+        else:
+            m2 = re.search(r"(?:能|可以|可否|能否)\s*(\d{1,4})\b", message.msg)
+            offer = int(m2.group(1)) if m2 else None
+        st = agent._get_conversation_state(message.from_id)
+        floor = st.last_min_price if isinstance(st.last_min_price, int) and st.last_min_price > 0 else MIN_PRICE_FLOOR
+        if offer is not None and offer < floor:
+            reply_text = "不好意思"
+    except Exception:
+        pass
+
+    try:
+        from config.config import MIN_PRICE_FLOOR
+        import re
+
+        st = agent._get_conversation_state(message.from_id)
+        floor = st.last_min_price if isinstance(st.last_min_price, int) and st.last_min_price > 0 else MIN_PRICE_FLOOR
+
+        def _adjust(text: str) -> str:
+            def _repl(m: Any):
+                num = int(m.group(1))
+                adj = max(floor, round(num / 5) * 5)
+                return m.group(0).replace(str(num), str(adj))
+
+            patterns = [
+                r"按(\d{1,4})元",
+                r"报价[：:]\s*(\d{1,4})\s*元",
+                r"(\d{1,4})\s*元一张",
+                r"打包(\d{1,4})\s*元",
+            ]
+            t = text
+            for p in patterns:
+                t = re.sub(p, _repl, t)
+            return t
+
+        reply_text = _adjust(reply_text or "")
+    except Exception:
+        pass
+
+    for msg in result.new_messages():
+        for part in getattr(msg, "parts", []):
+            part_type = type(part).__name__
+            if "ToolCall" in part_type:
+                print(
+                    f"{agent.C_TOOL}[THINK/TOOL_CALL]{agent.C_RESET} "
+                    f"{getattr(part, 'tool_name', '')}({getattr(part, 'args', '')})"
+                )
+            elif "ToolReturn" in part_type:
+                ret = str(getattr(part, "content", ""))[:120]
+                print(f"{agent.C_TOOL}[THINK/TOOL_RETURN]{agent.C_RESET} {ret}")
+
+    print(f"{agent.C_THINK}[THINK/RAW_OUTPUT]{agent.C_RESET} {repr(reply_text)}")
+    return reply_text

core/order_flow.py

@@ -0,0 +1,59 @@
+from __future__ import annotations
+
+import asyncio
+from typing import TYPE_CHECKING, Optional
+
+if TYPE_CHECKING:
+    from core.pydantic_ai_agent import AgentResponse, ConversationState, CustomerMessage, CustomerServiceAgent
+
+
+async def handle_order_notification(
+    agent: "CustomerServiceAgent",
+    *,
+    message: "CustomerMessage",
+    state: "ConversationState",
+) -> Optional["AgentResponse"]:
+    """Handle system order notifications before normal AI dialogue."""
+    from core.pydantic_ai_agent import AgentResponse
+
+    if "系统订单信息" not in message.msg and "订单状态" not in message.msg:
+        return None
+
+    _, order_block = agent._split_customer_text(message.msg)
+    customer_text, _ = agent._split_customer_text(message.msg)
+    order = agent._parse_order_info(order_block or message.msg)
+    pay_status = order.get("pay_status", "")
+    order_status = order.get("order_status", "")
+
+    paid_keywords = ["等待发货", "已付款", "付款成功", "买家已付款"]
+    is_paid = any(kw in pay_status or kw in order_status for kw in paid_keywords)
+
+    if is_paid:
+        asyncio.create_task(agent._check_order_amount(message.from_id, order, message.acc_id))
+        asyncio.create_task(
+            agent._record_deal_success(
+                message.from_id,
+                message.from_name,
+                message.acc_id,
+                message.acc_type,
+                order,
+                state,
+            )
+        )
+        try:
+            from core.workflow import workflow
+
+            asyncio.create_task(
+                workflow.trigger_processing_on_payment(
+                    customer_id=message.from_id,
+                    acc_id=message.acc_id,
+                    acc_type=message.acc_type,
+                )
+            )
+        except Exception as e:
+            print(f"[Agent] 触发作图失败: {e}")
+    elif not customer_text:
+        print(f"[Agent] 订单通知静默（{pay_status or order_status}），跳过回复")
+        return AgentResponse(reply="", should_reply=False, need_transfer=False)
+
+    return None

core/pydantic_ai_agent.py

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