refactor: unify core pipeline logging with cs_agent logger

core/agent_pre_rules.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import logging
 import random
 from datetime import datetime
 from typing import TYPE_CHECKING, Optional
@@ -108,7 +109,7 @@ class AgentPreRuleService:
         state = ctx.get("state")
         trace_id = ctx.get("trace_id", "")
         elapsed = int((datetime.now() - state.last_reply_at).total_seconds()) if state.last_reply_at else 0
-        print(f"[Agent] 冷却期静默（距上次回复 {elapsed}s）：{message.msg!r}")
+        logger.info("[Agent] 冷却期静默（距上次回复 %ss）：%r", elapsed, message.msg)
         self.agent._activity_log(
             "agent_cooldown_silent",
             trace_id=trace_id,
@@ -183,7 +184,7 @@ class AgentPreRuleService:
             scene="risk_reject",
         )
         state.last_reply_at = datetime.now()
-        print(f"{self.agent.C_REPLY}[REPLY->CUSTOMER]{self.agent.C_RESET} {reply}")
+        logger.info("[REPLY->CUSTOMER] %s", reply)
         self.agent._activity_log(
             "agent_risk_reject",
             trace_id=trace_id,
@@ -198,3 +199,4 @@ class AgentPreRuleService:
             action="agent_risk_reject",
             payload={"response": AgentResponse(reply=reply, should_reply=True, need_transfer=False)},
         )
+logger = logging.getLogger("cs_agent")

core/agent_tools.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import logging
 from typing import Any
 
 from pydantic_ai import RunContext
@@ -8,6 +9,8 @@ from db.customer_risk_db import risk_db
 from services.service_tuhui_upload import upload_to_tuhui
 from core.order_helpers import parse_order_info
 
+logger = logging.getLogger("cs_agent")
+
 
 def register_tools(agent) -> None:
     """注册所有 Tool，让 Agent 可以主动调用。"""
@@ -65,9 +68,15 @@ def register_tools(agent) -> None:
                     subject=result.get("subject", ""),
                     quality=result.get("quality", ""),
                 )
-                print(f"[Agent] Workflow 任务已创建 | 客户: {ctx.deps.from_id} | 比例: {result.get('aspect_ratio')} | 透视: {result.get('perspective')} | 图片: {image_url[:60]}...")
+                logger.info(
+                    "[Agent] Workflow 任务已创建 | 客户: %s | 比例: %s | 透视: %s | 图片: %s...",
+                    ctx.deps.from_id,
+                    result.get("aspect_ratio"),
+                    result.get("perspective"),
+                    image_url[:60],
+                )
             except Exception as e:
-                print(f"[Agent] Workflow 任务创建失败: {e}")
+                logger.exception("[Agent] Workflow 任务创建失败: %s", e)
 
             # 组装给 AI 的分析报告
             risk      = result.get("risk", "none")

core/ai_reply_flow.py

@@ -1,8 +1,11 @@
 from __future__ import annotations
 
+import logging
 from typing import TYPE_CHECKING, Any
 from core.post_ops import negotiation_strategy_reply
 
+logger = logging.getLogger("cs_agent")
+
 if TYPE_CHECKING:
     from core.pydantic_ai_agent import AgentDeps, ConversationState, CustomerMessage, CustomerServiceAgent
 
@@ -124,13 +127,14 @@ async def execute_ai_turn(
         for part in getattr(msg, "parts", []):
             part_type = type(part).__name__
             if "ToolCall" in part_type:
-                print(
+                logger.info(
-                    f"{agent.C_TOOL}[THINK/TOOL_CALL]{agent.C_RESET} "
+                    "[THINK/TOOL_CALL] %s(%s)",
-                    f"{getattr(part, 'tool_name', '')}({getattr(part, 'args', '')})"
+                    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}")
+                logger.info("[THINK/TOOL_RETURN] %s", ret)
 
-    print(f"{agent.C_THINK}[THINK/RAW_OUTPUT]{agent.C_RESET} {repr(reply_text)}")
+    logger.info("[THINK/RAW_OUTPUT] %r", reply_text)
     return reply_text

core/context_helpers.py

@@ -1,9 +1,12 @@
 from __future__ import annotations
 
 import os
+import logging
 from collections import Counter
 from datetime import datetime
 
+logger = logging.getLogger("cs_agent")
+
 
 def calc_avg_complexity(complexity_history: list) -> str:
     """计算平均复杂度。"""
@@ -153,7 +156,7 @@ def get_customer_profile_context(agent, customer_id: str) -> str:
 
         return "\n".join(lines)
     except Exception as e:
-        print(f"[Agent] 获取客户画像失败: {e}")
+        logger.exception("[Agent] 获取客户画像失败: %s", e)
         return ""
 
 

core/find_image_flow.py

@@ -1,8 +1,11 @@
 from __future__ import annotations
 
+import logging
 from datetime import datetime
 from typing import TYPE_CHECKING, Optional
 
+logger = logging.getLogger("cs_agent")
+
 if TYPE_CHECKING:
     from core.pydantic_ai_agent import AgentResponse, ConversationState, CustomerMessage, CustomerServiceAgent
 
@@ -55,7 +58,7 @@ async def handle_find_image_batch_flow(
                     fallback=defer_fallback,
                 )
                 state.last_reply_at = datetime.now()
-                print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {defer_reply}")
+                logger.info("[REPLY->CUSTOMER] %s", defer_reply)
                 return AgentResponse(reply=defer_reply, should_reply=True, need_transfer=False)
             quote_res = await agent._quote_pending_images(state, message)
             reply_text = agent._colloquialize_reply(quote_res.get("reply", ""))
@@ -67,7 +70,7 @@ async def handle_find_image_batch_flow(
             )
             need_transfer = bool(quote_res.get("need_transfer"))
             state.last_reply_at = datetime.now()
-            print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {reply_text}")
+            logger.info("[REPLY->CUSTOMER] %s", reply_text)
             return AgentResponse(
                 reply=reply_text,
                 should_reply=not need_transfer,
@@ -89,7 +92,7 @@ async def handle_find_image_batch_flow(
             fallback=ack_fallback,
         )
         state.last_reply_at = datetime.now()
-        print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {ack}")
+        logger.info("[REPLY->CUSTOMER] %s", ack)
         return AgentResponse(reply=ack, should_reply=True, need_transfer=False)
 
     if not state.pending_image_urls:
@@ -118,7 +121,7 @@ async def handle_find_image_batch_flow(
                 fallback=clarify_fallback,
             )
             state.last_reply_at = datetime.now()
-            print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {clarify}")
+            logger.info("[REPLY->CUSTOMER] %s", clarify)
             return AgentResponse(reply=clarify, should_reply=True, need_transfer=False)
 
         if state.quote_phase == "ready_to_quote" and state.quote_ready_turns <= 0 and short_intent in {"progress_query", "ack", "finish_signal"}:
@@ -132,7 +135,7 @@ async def handle_find_image_batch_flow(
             )
             need_transfer = bool(quote_res.get("need_transfer"))
             state.last_reply_at = datetime.now()
-            print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {reply_text}")
+            logger.info("[REPLY->CUSTOMER] %s", reply_text)
             return AgentResponse(
                 reply=reply_text,
                 should_reply=not need_transfer,
@@ -150,7 +153,7 @@ async def handle_find_image_batch_flow(
                 fallback=progress_fallback,
             )
             state.last_reply_at = datetime.now()
-            print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {progress}")
+            logger.info("[REPLY->CUSTOMER] %s", progress)
             return AgentResponse(reply=progress, should_reply=True, need_transfer=False)
 
         if agent._needs_clarification_in_collecting(text_without_urls):
@@ -163,7 +166,7 @@ async def handle_find_image_batch_flow(
                 fallback=ask_fallback,
             )
             state.last_reply_at = datetime.now()
-            print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {ask}")
+            logger.info("[REPLY->CUSTOMER] %s", ask)
             return AgentResponse(reply=ask, should_reply=True, need_transfer=False)
     if agent._is_batch_finish_intent(
         text=customer_text,
@@ -182,7 +185,7 @@ async def handle_find_image_batch_flow(
                 fallback=defer_fallback,
             )
             state.last_reply_at = datetime.now()
-            print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {defer_reply}")
+            logger.info("[REPLY->CUSTOMER] %s", defer_reply)
             return AgentResponse(reply=defer_reply, should_reply=True, need_transfer=False)
         quote_res = await agent._quote_pending_images(state, message)
         reply_text = agent._colloquialize_reply(quote_res.get("reply", ""))
@@ -194,7 +197,7 @@ async def handle_find_image_batch_flow(
         )
         need_transfer = bool(quote_res.get("need_transfer"))
         state.last_reply_at = datetime.now()
-        print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {reply_text}")
+        logger.info("[REPLY->CUSTOMER] %s", reply_text)
         return AgentResponse(
             reply=reply_text,
             should_reply=not need_transfer,
@@ -211,5 +214,5 @@ async def handle_find_image_batch_flow(
         fallback=remind_fallback,
     )
     state.last_reply_at = datetime.now()
-    print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {remind}")
+    logger.info("[REPLY->CUSTOMER] %s", remind)
     return AgentResponse(reply=remind, should_reply=True, need_transfer=False)

core/image_workflow_router.py

@@ -1,7 +1,10 @@
 from __future__ import annotations
 
+import logging
 from typing import Any
 
+logger = logging.getLogger("cs_agent")
+
 
 async def handle_image_workflow(*, workflow_router: Any, message: str, data: dict, image_urls: list) -> bool:
     """处理图片工作流（根据客户说的话判断执行哪种工作流）。"""
@@ -15,10 +18,10 @@ async def handle_image_workflow(*, workflow_router: Any, message: str, data: dic
     acc_type = data.get("acc_type", "AliWorkbench")
     image_url = image_urls[0]
 
-    print(f"[Agent] 检测到工作流类型：{workflow_type} (置信度：{confidence})")
+    logger.info("[Agent] 检测到工作流类型：%s (置信度：%s)", workflow_type, confidence)
 
     if workflow_type == "find_image":
-        print(f"[Agent] 执行查找图片工作流 | 客户：{customer_id}")
+        logger.info("[Agent] 执行查找图片工作流 | 客户：%s", customer_id)
         from core.workflow import workflow
 
         return await workflow.find_image_workflow(
@@ -28,7 +31,7 @@ async def handle_image_workflow(*, workflow_router: Any, message: str, data: dic
             acc_type=acc_type,
         )
     if workflow_type == "process_image":
-        print(f"[Agent] 执行处理图片工作流 | 客户：{customer_id}")
+        logger.info("[Agent] 执行处理图片工作流 | 客户：%s", customer_id)
         from core.workflow import workflow
 
         return await workflow.process_image_workflow(
@@ -38,7 +41,7 @@ async def handle_image_workflow(*, workflow_router: Any, message: str, data: dic
             acc_type=acc_type,
         )
     if workflow_type == "transfer_human":
-        print(f"[Agent] 执行转人工派单工作流 | 客户：{customer_id}")
+        logger.info("[Agent] 执行转人工派单工作流 | 客户：%s", customer_id)
         from core.workflow import workflow
 
         return await workflow.transfer_to_designer_workflow(

core/message_orchestrator.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import asyncio
+import logging
 from typing import Any
 
 from core.ai_reply_flow import execute_ai_turn
@@ -11,6 +12,8 @@ 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
 
+logger = logging.getLogger("cs_agent")
+
 
 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。"""
@@ -72,7 +75,7 @@ async def process_incoming_message(agent: Any, message: Any) -> Any:
         )
     except Exception as e:
         err_str = str(e)
-        print(f"[Agent] AI 调用失败: {e}，使用兜底回复")
+        logger.exception("[Agent] AI 调用失败，使用兜底回复: %s", err_str)
         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():

core/order_flow.py

@@ -1,10 +1,13 @@
 from __future__ import annotations
 
 import asyncio
+import logging
 from typing import TYPE_CHECKING, Optional
 from core.post_ops import record_deal_success
 from core.order_helpers import parse_order_info
 
+logger = logging.getLogger("cs_agent")
+
 if TYPE_CHECKING:
     from core.pydantic_ai_agent import AgentResponse, ConversationState, CustomerMessage, CustomerServiceAgent
 
@@ -53,9 +56,9 @@ async def handle_order_notification(
                 )
             )
         except Exception as e:
-            print(f"[Agent] 触发作图失败: {e}")
+            logger.exception("[Agent] 触发作图失败: %s", e)
     elif not customer_text:
-        print(f"[Agent] 订单通知静默（{pay_status or order_status}），跳过回复")
+        logger.info("[Agent] 订单通知静默（%s），跳过回复", pay_status or order_status)
         return AgentResponse(reply="", should_reply=False, need_transfer=False)
 
     return None

core/post_ops.py

@@ -1,11 +1,13 @@
 from __future__ import annotations
 
+import logging
 import re
 from typing import Any
 
 from utils.metrics_tracker import emit as metrics_emit
 
 CASE_LIBRARY_LINK = "https://www.yuque.com/zuowei-dfvpq/kge0in/mynala0g35b8cec5"
+logger = logging.getLogger("cs_agent")
 
 
 def detect_price(reply: str, state: Any) -> None:
@@ -102,9 +104,9 @@ async def record_deal_success(
             db.clear_quote_no_convert(customer_id)
         except Exception:
             pass
-        print(f"[Agent] 成交记录: {customer_id} {reason} {amount}元")
+        logger.info("[Agent] 成交记录: %s %s %s元", customer_id, reason, amount)
     except Exception as e:
-        print(f"[Agent] 成交记录失败: {e}")
+        logger.exception("[Agent] 成交记录失败: %s", e)
 
 
 async def record_deal_fail(
@@ -128,9 +130,9 @@ async def record_deal_fail(
             platform=platform or "",
         )
         db.mark_quote_no_convert(customer_id)
-        print(f"[Agent] 未成交记录: {customer_id} {reason}")
+        logger.info("[Agent] 未成交记录: %s %s", customer_id, reason)
     except Exception as e:
-        print(f"[Agent] 未成交记录失败: {e}")
+        logger.exception("[Agent] 未成交记录失败: %s", e)
 
 
 async def auto_tag(message: Any, state: Any) -> None:

core/pydantic_ai_agent.py

@@ -22,15 +22,10 @@ from pydantic_ai.models.openai import OpenAIChatModel
 from pydantic_ai.providers.openai import OpenAIProvider
 from dotenv import load_dotenv
 from utils.metrics_tracker import emit as metrics_emit
-from utils.observability import emit_activity, build_trace_id
+from utils.observability import emit_activity
 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
-from core.reply_finalize_flow import finalize_ai_reply
-from core.prompt_flow import build_prompt_bundle
 from core.order_helpers import parse_order_info, order_instruction as build_order_instruction
 from core.collection_intent_helpers import (
     append_requirement,
@@ -81,7 +76,6 @@ load_dotenv()
 
 from services.service_tuhui_upload import upload_to_tuhui
 from core.workflow_router import get_workflow_router
-from core.workflow_router import get_workflow_router
 
 # ========== 企业微信通知 ==========
 _WECHAT_WEBHOOK = os.getenv("WECHAT_WEBHOOK", "")
@@ -91,7 +85,7 @@ logger = logging.getLogger("cs_agent")
 async def _notify_wechat(content: str, tag: str = "通知"):
     """发送企业微信 markdown 通知，任何异常都发"""
     if not _WECHAT_WEBHOOK:
-        print(f"[{tag}] 未配置 WECHAT_WEBHOOK，跳过推送")
+        logger.info("[%s] 未配置 WECHAT_WEBHOOK，跳过推送", tag)
         return
     try:
         import httpx
@@ -102,11 +96,11 @@ async def _notify_wechat(content: str, tag: str = "通知"):
             })
             data = resp.json()
             if data.get("errcode") == 0:
-                print(f"[{tag}] 企业微信推送成功 ✓")
+                logger.info("[%s] 企业微信推送成功", tag)
             else:
-                print(f"[{tag}] 企业微信推送失败: {data}")
+                logger.warning("[%s] 企业微信推送失败: %s", tag, data)
     except Exception as e:
-        print(f"[{tag}] 企业微信发送异常: {e}")
+        logger.exception("[%s] 企业微信发送异常: %s", tag, e)
 
 
 async def _notify_wechat_overdue():
@@ -246,7 +240,7 @@ def load_skill_map(skills_dir: str = "skills") -> Dict[str, str]:
             else:
                 skill_map[skill_name] = content
         except Exception as e:
-            print(f"警告: 读取 {skill_file} 失败: {e}")
+            logger.warning("读取技能文件失败: %s | err=%s", skill_file, e)
     return skill_map
 
 
@@ -441,9 +435,7 @@ class CustomerServiceAgent:
     @staticmethod
     def _log_block(title: str, content: str):
         """统一的控制台分层日志输出。"""
-        print(f"{CustomerServiceAgent.C_PROMPT}[{title}]{CustomerServiceAgent.C_RESET}")
+        logger.info("[%s]\n%s\n--------------------", title, content)
-        print(content)
-        print(f"{CustomerServiceAgent.C_MUTED}────────────────────{CustomerServiceAgent.C_RESET}")
 
     @staticmethod
     def _normalize_reply_text(text: Optional[str]) -> str:
@@ -783,7 +775,7 @@ class CustomerServiceAgent:
                 return
             paid = float(m.group())
 
-            print(f"[Agent] 订单金额核查：报价 {quoted}元 vs 实付 {paid}元（客户 {customer_id}）")
+            logger.info("[Agent] 订单金额核查：报价 %s元 vs 实付 %s元（客户 %s）", quoted, paid, customer_id)
 
             # 实付金额明显低于报价（低于报价的 60%）才预警
             if paid < quoted * 0.6:
@@ -795,10 +787,10 @@ class CustomerServiceAgent:
                     f"实付：{paid}元\n"
                     f"差额：{quoted - paid:.1f}元 — 请人工核查"
                 )
-                print(f"[Agent] {msg}")
+                logger.warning("[Agent] %s", msg)
                 await self._notify_wechat(msg)
         except Exception as e:
-            print(f"[Agent] 订单金额核查失败: {e}")
+            logger.exception("[Agent] 订单金额核查失败: %s", e)
 
     def _extract_image_url(self, msg: str) -> str:
         """从消息中提取图片URL，兼容纯URL和 text#*#url 两种格式"""
@@ -887,7 +879,7 @@ class CustomerServiceAgent:
                     quality=r.get("quality", ""),
                 )
             except Exception as e:
-                print(f"[Agent] Workflow 批量任务创建失败: {e}")
+                logger.exception("[Agent] Workflow 批量任务创建失败: %s", e)
 
     _calc_requirement_surcharge = staticmethod(calc_requirement_surcharge)
     _build_batch_quote_reply = staticmethod(build_batch_quote_reply)
@@ -945,7 +937,7 @@ class CustomerServiceAgent:
                     raise RuntimeError(str(link))
                 links.append(link)
         except Exception as e:
-            print(f"[Agent] 找图自动处理失败，回退需求澄清: {e}")
+            logger.exception("[Agent] 找图自动处理失败，回退需求澄清: %s", e)
             return {
                 "reply": "这种可以做类似款。你先说下具体需求：要几张、是否改字、尺寸比例、交付格式（单图/打包链接），我按需求给你直接做。",
                 "need_transfer": False,
@@ -1064,7 +1056,7 @@ async def test_agent():
     )
 
     response = await agent.process_message(test_msg)
-    print(f"回复内容: {response.reply}")
+    logger.info("回复内容: %s", response.reply)
 
 
 if __name__ == "__main__":

core/reply_finalize_flow.py

@@ -1,12 +1,15 @@
 from __future__ import annotations
 
 import asyncio
+import logging
 from datetime import datetime
 from typing import TYPE_CHECKING
 
 from utils.metrics_tracker import emit as metrics_emit
 from core.post_ops import auto_tag, detect_discount, detect_price, record_deal_fail
 
+logger = logging.getLogger("cs_agent")
+
 if TYPE_CHECKING:
     from core.pydantic_ai_agent import AgentResponse, ConversationState, CustomerMessage, CustomerServiceAgent
 
@@ -25,7 +28,7 @@ async def finalize_ai_reply(
 
         blocked, fallback = should_block_reply(reply_text)
         if blocked:
-            print("[Agent] 敏感词拦截，使用兜底回复")
+            logger.warning("[Agent] 敏感词拦截，使用兜底回复")
             reply_text = fallback or "好的，您稍等，我帮您确认一下"
     except Exception:
         pass
@@ -88,9 +91,9 @@ async def finalize_ai_reply(
 
     if should_reply:
         state.last_reply_at = datetime.now()
-        print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {reply_text}")
+        logger.info("[REPLY->CUSTOMER] %s", reply_text)
     else:
-        print(f"{agent.C_MUTED}[REPLY->CUSTOMER]{agent.C_RESET} <静默/不发送>")
+        logger.info("[REPLY->CUSTOMER] <静默/不发送>")
 
     agent._activity_log(
         "agent_outbound_decision",