refactor: migrate workflow to v2 core and archive legacy modules

core/pydantic_ai_agent_v2.py

@@ -0,0 +1,91 @@
+import os
+import logging
+from typing import List, Optional, Any, Dict
+from pydantic_ai import Agent, RunContext
+from pydantic_ai.models.openai import OpenAIChatModel
+from pydantic_ai.providers.openai import OpenAIProvider
+from core.schema import StandardMessage, StandardResponse
+from core.agent_tools import register_agent_tools
+
+logger = logging.getLogger("cs_agent")
+
+from core.skill_manager import skill_manager
+
+class CustomerServiceBrain:
+    """
+    重构后的单一 Agent 大脑：
+    【全能终极版】统一称呼为“设计师”，支持下线安抚。
+    """
+
+    def __init__(self, model_name: str = None):
+        self.api_key = os.getenv("OPENAI_API_KEY")
+        self.base_url = os.getenv("OPENAI_BASE_URL")
+        self.model_name = model_name or os.getenv("OPENAI_MODEL", "gpt-4o-mini")
+        
+        model = OpenAIChatModel(
+            model_name=self.model_name,
+            provider=OpenAIProvider(api_key=self.api_key, base_url=self.base_url)
+        )
+
+        all_skills = skill_manager.get_all_skills_text()
+
+        # --- 统一口径后的 System Prompt ---
+        system_prompt = (
+            "你是一位专注【高清修复】和【找原图】的专业店主。性格干脆，说话高端、专业。\n\n"
+            
+            "【统一称呼规范】\n"
+            "1. 严禁使用'师傅'、'客服'、'专员'等词汇！\n"
+            "2. 必须统一称呼为【设计师】。比如：'找设计师看下'、'设计师马上来'、'等设计师核价'。\n\n"
+            
+            "【核心逻辑】\n"
+            "1. 业务：只聊高清修复和找原图。引导发图 -> 问需求 -> 找设计师。\n"
+            "2. 下线安抚：如果工具返回 'ERROR_NO_DESIGNER_ONLINE'，说明设计师们【下班/下线】了。回：'亲亲，设计师现在下班啦，需求我先记下，明天第一时间回您哈！'。\n"
+            "3. 正在转接中：如果看到系统提示已在转接，回：'设计师正在赶来，我再帮你催下哈！'。\n"
+            "4. 没转接时：引导发图 -> 问需求 -> 调工具转人工。\n\n"
+            "5. 语气：淘宝亲切风，多用'亲亲'、'铁子'。每句回复【严禁超过15字】！\n\n"   
+
+            "【必杀令】\n"
+            "1. 每句回复严禁超过15个字！\n"
+            "2. 严禁报价，严禁复读图片已收到的情况。\n"
+            "3. 必须原样输出工具返回的'正在为您转接|'指令。\n\n"
+            
+            f"业务参考：\n{all_skills}"
+        )
+
+        self.agent = Agent(model=model, system_prompt=system_prompt)
+        register_agent_tools(self.agent)
+
+    async def think_and_reply(self, msg: StandardMessage, history: List[dict] = []) -> StandardResponse:
+        try:
+            # 构造增强上下文（强灌输）
+            user_content = msg.content
+            if msg.image_urls:
+                user_content = f"【系统通知：收到客户 {len(msg.image_urls)} 张图】\n{user_content}"
+            
+            recent_context = ""
+            if history:
+                lines = [f"{('客户' if h['role']=='user' else '我')}：{h['content']}" for h in history[-6:]]
+                recent_context = "【近期对话回顾】\n" + "\n".join(lines) + "\n----------------\n"
+
+            full_input = f"{recent_context}现在的对话：{user_content}"
+
+            result = await self.agent.run(full_input, message_history=history)
+
+            if hasattr(result, 'data') and isinstance(result.data, str):
+                reply_text = result.data
+            elif hasattr(result, 'output') and isinstance(result.output, str):
+                reply_text = result.output
+            else:
+                reply_text = str(result.data) if hasattr(result, 'data') else "在呢铁子。"
+
+            need_transfer = "[转移会话]" in reply_text
+            
+            return StandardResponse(
+                reply_content=reply_text,
+                need_transfer=need_transfer,
+                metadata={"acc_id": msg.acc_id, "acc_type": msg.acc_type}
+            )
+
+        except Exception as e:
+            logger.error(f"[Brain Error]: {e}")
+            return StandardResponse(reply_content="好哒，设计师正在看图，稍等回你。", metadata={"acc_id": msg.acc_id})