newtw2

2026-03-06 13:23:32 +08:00
parent 4ba636e98c
commit afb2b78c15
29 changed files with 76 additions and 1521 deletions
--- a/core/engine.py
+++ b/core/engine.py
@@ -7,43 +7,18 @@ logger = logging.getLogger("cs_agent")

 class BusinessEngine:
    """
-    业务逻辑中枢：
-    1. 接收 StandardMessage。
-    2. 决定由哪个 AI 工具或流程处理。
-    3. 返回 StandardResponse。
-    4. 对外广播异步事件。
+    业务逻辑中枢（备用引擎，主流程由 Orchestrator + Brain 处理）。
+    仅在 Orchestrator 不可用时作为降级方案。
    """
    def __init__(self, agent_instance: Any = None):
-        """
-        :param agent_instance: 核心 AI Agent 的实例（比如重构后的 CustomerServiceAgent）
-        """
        self.agent = agent_instance

    async def handle_message(self, msg: StandardMessage) -> StandardResponse:
-        """
-        大脑的思考主入口
-        """
-        logger.info(f"[Engine] 收到来自 {msg.platform} 的消息: {msg.user_id} -> {msg.content[:50]}")
-        
-        # TODO: 这里将接入重构后的 Single Agent + Tool Calling
-        # 目前模拟一个简单的规则响应，展示 StandardResponse 的用法
-        
-        if "报价" in msg.content or msg.image_urls:
-            return StandardResponse(
-                reply_content="正在为你查看图片，请稍等...",
-                metadata={"acc_id": msg.acc_id, "acc_type": msg.acc_type}
-            )
-        
-        if "转人工" in msg.content:
-            return StandardResponse(
-                reply_content="正在为你转接设计师...",
-                need_transfer=True,
-                metadata={"acc_id": msg.acc_id, "acc_type": msg.acc_type}
-            )
+        content = (msg.content or "")
+        logger.info(f"[Engine] 收到来自 {msg.platform} 的消息: {msg.user_id} -> {content[:50]}")

-        # 兜底回复
        return StandardResponse(
-            reply_content="你好，我是AI助手，有什么可以帮你的？",
+            reply_content="稍等哈，设计师马上来。",
            metadata={"acc_id": msg.acc_id, "acc_type": msg.acc_type}
        )

--- a/core/events/event_bus.py
+++ b/core/events/event_bus.py
@@ -29,8 +29,11 @@ class AsyncEventBus:
            tasks.append(asyncio.create_task(callback(**kwargs)))
        
        if tasks:
-            await asyncio.gather(*tasks, return_exceptions=True)
-            logger.info(f"[EventBus] 事件 {event_type} 已成功广播给 {len(tasks)} 个订阅者")
+            results = await asyncio.gather(*tasks, return_exceptions=True)
+            for i, r in enumerate(results):
+                if isinstance(r, Exception):
+                    logger.error(f"[EventBus] 事件 {event_type} 订阅者 {i} 异常: {r}")
+            logger.info(f"[EventBus] 事件 {event_type} 已广播给 {len(tasks)} 个订阅者")

 # 全局单例，所有模块共用这一个广播台
 bus = AsyncEventBus()
--- a/core/orchestrator.py
+++ b/core/orchestrator.py
@@ -68,11 +68,15 @@ class SystemOrchestrator:
            # 店铺隔离：同一客户在不同店铺的对话独立处理
            session_key = f"{user_id}@{std_msg.acc_id}"

-            # 订单消息处理：静默入库并更新状态，但不触发 AI 回复
-            if "[系统订单信息]" in (std_msg.content or ""):
+            # 订单消息 / 纯金额通知：静默入库，不触发 AI 回复
+            msg_text = std_msg.content or ""
+            is_order = "[系统订单信息]" in msg_text
+            is_price_only = bool(re.match(r'^[\s\n]*金?额?[:：]?\s*[\d.]+\s*元', msg_text.strip()))
+            is_sku_only = bool(re.match(r'^[\s\n]*(备注[:：]|数量[:：]|款式[:：])', msg_text.strip()))
+            if is_order or is_price_only or is_sku_only:
                await self._handle_order_packet(platform, std_msg)
                logger.info(f"[订单消息] user={user_id} acc={std_msg.acc_id} 已入库更新状态")
-                await repo.save_chat(platform, user_id, std_msg.content, "in", acc_id=std_msg.acc_id)
+                await repo.save_chat(platform, user_id, msg_text, "in", acc_id=std_msg.acc_id)
                return

            preview = (std_msg.content or "").replace("\n", "\\n")
@@ -84,7 +88,7 @@ class SystemOrchestrator:
            )
            
            # 过滤心跳
-            if not std_msg.content.strip() and not std_msg.image_urls: return
+            if not (std_msg.content or "").strip() and not std_msg.image_urls: return

            # 如果是商家人工回复，静默入库
            if direction == "out":
@@ -180,8 +184,15 @@ class SystemOrchestrator:
                messages = self._pending_messages.pop(session_key, [])
                if not messages: return
                
-                # A. 合并与元数据修复
-                combined_content = "\n".join([m.content for m in messages if m.content.strip()])
+                # A. 合并与元数据修复（去重：同一防抖窗口内完全相同的内容只保留一条）
+                seen_contents = set()
+                unique_parts = []
+                for m in messages:
+                    c = (m.content or "").strip()
+                    if c and c not in seen_contents:
+                        seen_contents.add(c)
+                        unique_parts.append(c)
+                combined_content = "\n".join(unique_parts)
                all_image_urls = []
                acc_id = messages[-1].acc_id
                acc_type = messages[-1].acc_type
@@ -216,12 +227,15 @@ class SystemOrchestrator:
                
                # D. 思考
                history = await repo.get_chat_history(user_id, limit=10, acc_id=acc_id)
-                if history and history[-1]['content'] == db_content: history = history[:-1]
+                if history and history[-1].get('content') == db_content: history = history[:-1]

-                # 只在“明确又要转接”时注入冷却提示，普通问候/新需求不注入
-                transfer_intent = self._has_transfer_intent(combined_content)
-                if is_in_cooldown and transfer_intent:
-                    final_msg.content = f"【系统：当前已向设计师发出转接请求，请勿再次调用转接工具】\n{final_msg.content}"
+                # 冷却期内：禁止再发转接指令，避免反复转接
+                if is_in_cooldown:
+                    final_msg.content = (
+                        "【系统：设计师已收到转接通知正在赶来，严禁再次调用转人工工具！"
+                        "客户再问就回'设计师正在看了哈，稍等一下'，换着说不要重复】\n"
+                        + final_msg.content
+                    )

                std_res = await self.brain.think_and_reply(final_msg, history=history)

--- a/core/pydantic_ai_agent_v2.py
+++ b/core/pydantic_ai_agent_v2.py
@@ -1,4 +1,6 @@
 import os
+import re
+import hashlib
 import logging
 from typing import List, Optional, Any, Dict
 from pydantic_ai import Agent, RunContext
@@ -85,19 +87,26 @@ class CustomerServiceBrain:
        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:
+    async def think_and_reply(self, msg: StandardMessage, history: Optional[List[dict]] = None) -> StandardResponse:
+        if history is None:
+            history = []
        try:
-            # 构造增强上下文
-            user_content = msg.content
+            user_content = msg.content or ""
+
+            # 客户已发图：在上下文中明确告知 AI，避免再回"先发图"
            if msg.image_urls:
-                user_content = f"【系统通知：收到客户 {len(msg.image_urls)} 张图】\n{user_content}"
-            
+                user_content = (
+                    f"【系统通知：客户已发送 {len(msg.image_urls)} 张图片，不要再让客户发图！"
+                    f"请直接问客户需求（找原图还是修复），然后转接设计师】\n{user_content}"
+                )
+
            recent_context = ""
            if history:
-                lines = [
-                    f"[{_fmt_time(h.get('timestamp'))}] {('客户' if h['role']=='user' else '我')}：{h['content']}"
-                    for h in history[-6:]
-                ]
+                lines = []
+                for h in history[-6:]:
+                    role = "客户" if h.get("role") == "user" else "我"
+                    content = h.get("content", "")
+                    lines.append(f"[{_fmt_time(h.get('timestamp'))}] {role}：{content}")
                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}"
@@ -132,15 +141,20 @@ class CustomerServiceBrain:
                reply_text = found_magic
            # ----------------------------------------

-            # 清理可能的乱码/代码标记
-            import re
-            reply_text = re.sub(r'\[\]<\|[^|]+\|>', '', reply_text)  # 清理 []<|xxx|>
-            reply_text = re.sub(r'<\|[^|]+\|>', '', reply_text)  # 清理 <|xxx|>
-            reply_text = re.sub(r'\[Function[^\]]*\]', '', reply_text)  # 清理 [FunctionXxx]
-            reply_text = re.sub(r'<think[^>]*>.*', '', reply_text, flags=re.DOTALL)  # 清理 <think_xxx>内部思考泄漏
-            reply_text = re.sub(r'</?think[^>]*>', '', reply_text)  # 清理 think 标签
-            reply_text = re.sub(r'```[^`]*```', '', reply_text)  # 清理代码块
-            reply_text = re.sub(r'\{["\'][^}]+\}', '', reply_text)  # 清理 JSON
+            # 清理模型泄露的内部标记/乱码（覆盖所有已知格式）
+            reply_text = re.sub(r'\[\]<\|[^|]+\|>', '', reply_text)
+            reply_text = re.sub(r'<\|[^|]*\|>', '', reply_text)
+            reply_text = re.sub(r'\[Function[^\]]*\]', '', reply_text)
+            reply_text = re.sub(r'\[/?Tool[^\]]*\]', '', reply_text)
+            reply_text = re.sub(r'</?tool[_\-]?[^>]*>', '', reply_text, flags=re.IGNORECASE)
+            reply_text = re.sub(r'<think[^>]*>.*?</think[^>]*>', '', reply_text, flags=re.DOTALL)
+            reply_text = re.sub(r'<think[^>]*>.*', '', reply_text, flags=re.DOTALL)
+            reply_text = re.sub(r'</?think[^>]*>', '', reply_text)
+            reply_text = re.sub(r'```[^`]*```', '', reply_text)
+            reply_text = re.sub(r'\{["\'][^}]+\}', '', reply_text)
+            reply_text = re.sub(r'AgentRunResult\([^)]*\)', '', reply_text)
+            reply_text = re.sub(r'\[/?[A-Z][a-zA-Z]*(?:Call|End|Start|Result|Return)[^\]]*\]', '', reply_text)
+            reply_text = re.sub(r'[\[\]]{2,}', '', reply_text)
            reply_text = reply_text.strip()

            # 过滤"在呢铁子"
--- a/core/schema.py
+++ b/core/schema.py
@@ -10,7 +10,7 @@ class StandardMessage(BaseModel):
    user_name: str = ""              # 发送者昵称
    content: str                     # 消息文本内容
    msg_type: int = 0                # 消息类型：0 文本, 1 图片, 2 语音等
-    image_urls: List[str] = []       # 提取出来的图片链接
+    image_urls: List[str] = Field(default_factory=list)  # 提取出来的图片链接
    acc_id: str = ""                 # 商家/店铺账号ID
    acc_type: str = ""               # 平台类型标识
    timestamp: datetime = Field(default_factory=datetime.now)
@@ -27,4 +27,4 @@ class StandardResponse(BaseModel):
    should_reply: bool = True        # 是否需要发送
    need_transfer: bool = False      # 是否触发转人工
    transfer_group: str = ""         # 转人工的分组ID
-    metadata: dict = {}              # 额外元数据（如埋点、调试信息）
+    metadata: dict = Field(default_factory=dict)  # 额外元数据（如埋点、调试信息）
--- a/core/skill_manager.py
+++ b/core/skill_manager.py
@@ -14,7 +14,8 @@ class SkillManager:
    3. 支持热加载（无需重启即可更新 AI 知识）。
    """
    def __init__(self, skills_dir: str = "skills"):
-        self.skills_dir = Path(skills_dir)
+        given = Path(skills_dir)
+        self.skills_dir = given if given.is_absolute() else Path(__file__).resolve().parent.parent / skills_dir
        self._skill_cache: Dict[str, str] = {}
        self.reload_skills()

--- a/core/websocket_client_v2.py
+++ b/core/websocket_client_v2.py
@@ -1,4 +1,5 @@
 import asyncio
+import hashlib
 import json
 import logging
 import os
@@ -51,8 +52,6 @@ class QingjianAPIClient:
        if not customer_id:
            return self.worker_id == 0
            
-        import hashlib
-        # 使用稳定的哈希算法分配客户
        hash_val = int(hashlib.md5(str(customer_id).encode("utf-8")).hexdigest(), 16)
        return (hash_val % self.worker_count) == self.worker_id