refactor: extract process_message orchestration from agent

core/message_orchestrator.py

@@ -0,0 +1,110 @@
+from __future__ import annotations
+
+import asyncio
+from typing import Any
+
+from core.ai_reply_flow import execute_ai_turn
+from core.find_image_flow import handle_find_image_batch_flow
+from core.order_flow import handle_order_notification
+from core.prompt_flow import build_prompt_bundle
+from core.reply_finalize_flow import finalize_ai_reply
+from utils.metrics_tracker import emit as metrics_emit
+from utils.observability import build_trace_id
+
+
+async def process_incoming_message(agent: Any, message: Any) -> Any:
+    """主消息处理编排：预处理 -> 业务流 -> AI -> 收尾。"""
+    trace_id = build_trace_id(message.acc_id, message.from_id, message.msg_id, message.msg[:64])
+    agent._activity_log(
+        "agent_inbound",
+        trace_id=trace_id,
+        acc_id=message.acc_id,
+        customer_id=message.from_id,
+        msg=message.msg,
+        msg_type=message.msg_type,
+    )
+    metrics_emit("inbound_msg", customer_id=message.from_id, acc_id=message.acc_id)
+
+    state = agent._get_conversation_state(message.from_id)
+    pre_response = await agent.pre_rule_service.run(message=message, state=state, trace_id=trace_id)
+    if pre_response is not None:
+        return pre_response
+
+    new_stage = agent._detect_stage(message.msg)
+    if new_stage != state.stage:
+        state.stage = new_stage
+
+    from datetime import datetime
+
+    state.last_update = datetime.now().isoformat()
+
+    order_response = await handle_order_notification(agent, message=message, state=state)
+    if order_response is not None:
+        return order_response
+
+    customer_text, _ = agent._split_customer_text(message.msg)
+    shop_type = agent._get_shop_type(message.acc_id or "", message.goods_name or "")
+    flow_response = await handle_find_image_batch_flow(
+        agent,
+        message=message,
+        state=state,
+        customer_text=customer_text,
+        shop_type=shop_type,
+    )
+    if flow_response is not None:
+        return flow_response
+
+    prompt_bundle = build_prompt_bundle(agent, message=message, state=state)
+    user_prompt = prompt_bundle.user_prompt
+    deps = prompt_bundle.deps
+    history = prompt_bundle.history
+
+    agent._log_block("PROMPT->AI 前置提示词", user_prompt)
+
+    try:
+        reply_text = await execute_ai_turn(
+            agent,
+            message=message,
+            state=state,
+            user_prompt=user_prompt,
+            deps=deps,
+            history=history,
+        )
+    except Exception as e:
+        err_str = str(e)
+        print(f"[Agent] AI 调用失败: {e}，使用兜底回复")
+        agent._activity_log("agent_ai_error", customer_id=message.from_id, acc_id=message.acc_id, error=err_str)
+        metrics_emit("ai_call_failed", customer_id=message.from_id, acc_id=message.acc_id)
+        if "AccountOverdueError" in err_str or "overdue" in err_str.lower():
+            asyncio.create_task(agent._notify_wechat_overdue())
+        else:
+            asyncio.create_task(
+                agent._notify_wechat(
+                    f"⚠️ **AI调用异常**\n"
+                    f"客户：{message.from_id}\n"
+                    f"店铺：{message.acc_id}\n"
+                    f"错误：{err_str[:200]}",
+                    tag="AI异常",
+                )
+            )
+        reply_text = None
+    else:
+        metrics_emit("ai_call_success", customer_id=message.from_id, acc_id=message.acc_id)
+
+    if not reply_text:
+        fallback_text = await agent._rewrite_reply_with_ai(
+            message=message,
+            state=state,
+            reply="好嘞，你稍等下，我这边看一下",
+            scene="fallback_reply",
+        )
+        from core.pydantic_ai_agent import AgentResponse
+
+        return AgentResponse(reply=fallback_text, should_reply=True, need_transfer=False)
+
+    return await finalize_ai_reply(
+        agent,
+        message=message,
+        state=state,
+        reply_text=reply_text,
+    )