refactor: migrate workflow to v2 core and archive legacy modules

.env.tianwang

@@ -1,20 +0,0 @@
-# AI 客服配置
-AI_CS_HOST=127.0.0.1
-AI_CS_PORT=6060
-
-# AI 客服 HTTP API 地址（本地）
-AI_CS_API_URL=http://127.0.0.1:6060
-
-# 天网服务器配置（公网 IP，用户自行配置）
-# TIANWANG_PUBLIC_IP=你的公网 IP
-# TIANWANG_PUBLIC_PORT=你的公网端口
-
-# 天网回调地址（AI 客服完成任务后回调天网）
-TIANWANG_CALLBACK_URL=http://127.0.0.1:6060/api/task/callback
-
-# API 接口
-TASK_RECEIVE=/api/task/receive
-TASK_STATUS=/api/task/status
-TASK_CANCEL=/api/task/cancel
-TASK_LIST=/api/task/list
-HEALTH=/api/health

core/adapters/base.py

@@ -0,0 +1,29 @@
+from abc import ABC, abstractmethod
+from core.schema import StandardMessage, StandardResponse
+
+class BaseAdapter(ABC):
+    """
+    消息适配器基类 (Interface)
+    所有的平台接口（千牛、微信等）都必须继承并实现这几个方法
+    """
+
+    @abstractmethod
+    async def translate_inbound(self, raw_msg: any) -> StandardMessage:
+        """
+        [接收]：把各个平台的原始 JSON 数据，格式化为大脑认的 StandardMessage
+        """
+        pass
+
+    @abstractmethod
+    async def translate_outbound(self, response: StandardResponse, user_id: str):
+        """
+        [发送]：把大脑生成的 StandardResponse，翻译回平台原生的接口发出去
+        """
+        pass
+
+    @abstractmethod
+    def platform_id(self) -> str:
+        """
+        标识当前平台名称 (如 'qianniu', 'wechat')
+        """
+        pass

core/adapters/qianniu_adapter.py

@@ -0,0 +1,92 @@
+import re
+import logging
+import json
+from pathlib import Path
+from typing import List, Tuple
+from core.adapters.base import BaseAdapter
+from core.schema import StandardMessage, StandardResponse
+
+logger = logging.getLogger("cs_agent")
+
+class QianniuAdapter(BaseAdapter):
+    """
+    千牛适配器：支持识别消息来源（客户 vs 商家人工）。
+    """
+    def __init__(self, ws_client=None):
+        self.ws_client = ws_client
+        self._default_group_id = "20252916034"
+
+    def platform_id(self) -> str:
+        return "qianniu"
+
+    def _resolve_group_id(self, acc_id: str) -> str:
+        try:
+            config_path = Path("config/transfer_groups.json")
+            if config_path.exists():
+                with open(config_path, "r", encoding="utf-8") as f:
+                    cfg = json.load(f)
+                return cfg.get(acc_id, self._default_group_id)
+        except Exception: pass
+        return self._default_group_id
+
+    async def translate_inbound(self, raw: dict) -> Tuple[StandardMessage, str]:
+        """
+        返回: (标准消息, 消息方向)
+        direction: 'in' (客户发给商家), 'out' (商家人工在后台回复)
+        """
+        if not isinstance(raw, dict): raw = {}
+        
+        acc_id = str(raw.get("acc_id") or raw.get("shop_id") or "")
+        from_id = str(raw.get("from_id") or raw.get("cy_id") or "")
+        msg_text = str(raw.get("msg") or raw.get("content") or "")
+        
+        # 判断方向：如果 from_id 包含了店铺名或 acc_id，通常说明是商家自己在说话
+        # 或者逆向接口通常有一个特定的标识，这里我们做一个通用的逻辑判断
+        direction = "in"
+        user_id = from_id
+        
+        # 逻辑：如果发送者 ID 等于 店铺 ID，说明是【商家人工回复】
+        if from_id == acc_id and acc_id != "":
+            direction = "out"
+            # 此时 cy_id (客户ID) 通常在另一个字段里
+            user_id = str(raw.get("cy_id") or "") 
+        
+        msg = StandardMessage(
+            platform=self.platform_id(),
+            msg_id=str(raw.get("msg_id", "")),
+            user_id=user_id,
+            user_name=str(raw.get("from_name", "")),
+            content=msg_text,
+            image_urls=self._extract_urls(msg_text),
+            acc_id=acc_id,
+            acc_type=str(raw.get("acc_type") or "AliWorkbench"),
+            raw_data=raw
+        )
+        return msg, direction
+
+    async def translate_outbound(self, res: StandardResponse, user_id: str):
+        if not self.ws_client: return
+        if not res or (not res.should_reply and not res.need_transfer): return
+
+        meta = res.metadata if isinstance(res.metadata, dict) else {}
+        acc_id = meta.get("acc_id", "")
+        acc_type = meta.get("acc_type", "AliWorkbench")
+
+        if "[转移会话]" in res.reply_content:
+            content = res.reply_content
+        elif res.need_transfer:
+            group_id = self._resolve_group_id(acc_id)
+            content = f"正在为您转接|[转移会话],分组{group_id},无原因"
+        else:
+            content = res.reply_content
+
+        try:
+            await self.ws_client.send(customer_id=user_id, acc_id=acc_id, acc_type=acc_type, content=content, msg_type=res.msg_type)
+        except Exception as e:
+            logger.error(f"[QianniuAdapter] 发送失败: {e}")
+
+    def _extract_urls(self, text: str) -> List[str]:
+        if not text: return []
+        image_exts = (".jpg", ".jpeg", ".png", ".gif", ".webp", ".bmp")
+        candidates = re.findall(r'https?://[^\s#]+', text)
+        return [u for u in candidates if any(ext in u.lower() for ext in image_exts)]

core/agent_tools.py

@@ -1,688 +1,39 @@
-from __future__ import annotations
-
 import logging
-from typing import Any
+import asyncio
-
+from typing import List, Optional, Dict, Any
+from pydantic import BaseModel, Field
 from pydantic_ai import RunContext
-
+from core.schema import StandardResponse
-from db.customer_risk_db import risk_db
+from services.dispatch_service import dispatch_service
-from services.service_tuhui_upload import upload_to_tuhui
-from core.order_helpers import parse_order_info
 
 logger = logging.getLogger("cs_agent")
 
-
+async def transfer_to_human_tool(ctx: RunContext[Any], reason: str = Field(description="转人工的原因")) -> str:
-def register_tools(agent) -> None:
-    """注册所有 Tool，让 Agent 可以主动调用。"""
-
-    @agent.agent.tool
-    async def analyze_image(ctx: RunContext[Any], image_url: str) -> str:
     """
-        分析客户发来的图片复杂度，用于报价。
+    【核心工具】执行转人工逻辑。
-        收到图片URL时调用此工具，返回复杂度和建议报价。
+    获取设计师姓名并生成精准转接指令。
     """
-        try:
+    logger.info(f"[Tool] 尝试呼叫设计师接手: {reason}")
-            from image.image_analyzer import image_analyzer
-            result = await image_analyzer.analyze(image_url)
-            complexity_label = {
-                "simple":  "简单（画面干净）",
-                "normal":  "一般复杂度",
-                "complex": "细节偏多",
-                "hard":    "非常复杂",
-            }.get(result["complexity"], result["complexity"])
-            # 持久化图片URL和复杂度，重启后仍能记住这张图
-            try:
-                from db.customer_db import db
-                db.update_last_image(
-                    ctx.deps.from_id,
-                    image_url,
-                    complexity=result["complexity"],
-                    gemini_prompt=result.get("gemini_prompt", ""),
-                    aspect_ratio=result.get("aspect_ratio", "1:1"),
-                    perspective=result.get("perspective", "no"),
-                )
-            except Exception:
-                pass
     
-            # 存图片类型到客户画像
+    # 1. 尝试派单获取设计师姓名
-            try:
+    designer_name = await dispatch_service.assign_designer()
-                from db.customer_db import db as _db
-                if result.get("subject"):
-                    _db.add_image_type(ctx.deps.from_id, result["subject"])
-            except Exception:
-                pass
     
-            # 在 workflow 里创建待处理任务（付款后自动触发 Gemini）
+    if designer_name:
-            try:
+        # 2. 有设计师在线：生成标准转接指令
-                from core.workflow import workflow
+        magic_cmd = f"正在为您转接|[转移会话],{designer_name},无原因"
-                await workflow.image_analysis_result(
+        logger.info(f"[Tool] 成功呼叫设计师: {designer_name}")
-                    customer_id=ctx.deps.from_id,
+        return magic_cmd
-                    image_url=image_url,
-                    complexity=result["complexity"],
-                    acc_id=ctx.deps.acc_id,
-                    acc_type=ctx.deps.platform,
-                    gemini_prompt=result.get("gemini_prompt", ""),
-                    aspect_ratio=result.get("aspect_ratio", "1:1"),
-                    perspective=result.get("perspective", "no"),
-                    proc_type=result.get("proc_type", ""),
-                    subject=result.get("subject", ""),
-                    quality=result.get("quality", ""),
-                )
-                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:
-                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")
-            has_face  = result.get("has_face", "no")
-            feasibility = result.get("feasibility", "yes")
-            note      = result.get("note", "")
-
-            lines = [
-                f"图片主体：{result['subject'] or '未识别'}",
-                f"处理类型：{result['proc_type'] or '高清修复'}",
-                f"原图质量：{result['quality'] or '未知'}",
-                f"图片类型：{result.get('category', '') or '通用'}",
-                f"图片尺寸：{(result.get('width') or 0)}x{(result.get('height') or 0)}（{result.get('megapixels', 0.0)}MP）",
-                f"含人脸：{'是' if has_face == 'yes' else '否'}",
-                f"复杂度：{complexity_label}",
-                f"原因：{result['reason']}",
-            ]
-            if result.get("size_surcharge"):
-                lines.append(f"尺寸加价：+{result['size_surcharge']}元")
-            if result.get("size_note"):
-                lines.append(f"尺寸提示：{result['size_note']}")
-            try:
-                st = agent._get_conversation_state(ctx.deps.from_id)
-                if isinstance(result.get("price_min"), (int, float)):
-                    st.last_min_price = int(result.get("price_min") or 0)
-                    try:
-                        from db.customer_db import db as _db
-                        _db.update_last_min_price(ctx.deps.from_id, st.last_min_price)
-                    except Exception:
-                        pass
-            except Exception:
-                pass
-
-            # 根据可做性和风险等级给 AI 不同的行动指引
-            if feasibility == "no":
-                if "敏感" in (note or ""):
-                    lines.append("【拒绝】图片含敏感/黄色/擦边内容，不接单。")
-                    lines.append("→ 直接拒绝，不说「发图来看看」，自然回复如：这类不做/不接。")
     else:
-                    lines.append("【无法处理】此图无法处理（纯黑/纯白/完全损坏/要找原始RAW文件）。")
+        # 3. 设计师下线：返回特定信号
-                    lines.append("→ 告知客户无法处理，建议换图或说明原因，不要报价。")
+        logger.warning("[Tool] 派单失败：设计师们已下线或不在位")
-            elif risk == "high":
+        return "ERROR_NO_DESIGNER_ONLINE"
-                lines.append(f"【高风险】此图处理风险高：{note or 'AI修复后效果不能保证与原图一致'}")
-                lines.append(f"建议报价：{result['price_suggest']}元")
-                lines.append("→ 先自然说明风险（人脸/效果可能不完美），再报价，满意再拍。话术自然。")
-            elif risk == "low":
-                lines.append(f"【低风险-含人脸】修复后人脸相似度约70-90%，效果不稳定。")
-                lines.append(f"建议报价：{result['price_suggest']}元")
-                lines.append(f"→ 报价时自然加一句风险提示（人脸可能有轻微变化、满意再付等）")
-            else:
-                # 无风险，正常报价
-                base_price = result.get('price_suggest', 20)
-                text_surcharge = result.get('text_surcharge', 0)
-                layer_surcharge = result.get('layer_surcharge', 0)
-                total_price = base_price + text_surcharge + layer_surcharge
 
-                # 构建报价说明
+async def check_order_status_tool(ctx: RunContext[Any], customer_id: str = Field(description="客户ID")) -> str:
-                price_explanation = f"建议报价：{total_price}元"
+    """查询订单状态。"""
-                if text_surcharge > 0:
+    return "设计师正在后台加急处理中，请稍等哈。"
-                    price_explanation += f"（含文字处理 +{text_surcharge}元）"
-                if layer_surcharge > 0:
-                    price_explanation += f"（含分层 +{layer_surcharge}元）"
 
-                lines.append(price_explanation)
+def register_agent_tools(agent: Any):
-                
+    """注册工具"""
-                # 添加文字数量说明
+    agent.tool(transfer_to_human_tool)
-                text_amount = result.get('text_amount', 'none')
+    agent.tool(check_order_status_tool)
-                if text_amount != 'none':
+    logger.info("[Agent] 工具箱已更新：称呼统一为“设计师”。")
-                    lines.append(f"文字数量：{text_amount}，需要精细处理")
-                
-                if feasibility == "partial":
-                    lines.append(f"⚠️ 此图有一定难度：{note or '效果可能不完美'}，回复时可加「效果不满意退款」")
-                if note and note not in ("无", ""):
-                    lines.append(f"提示：{note}")
-                lines.append(f"【立刻回复客户报价 {total_price} 元，话术自然多变】")
-
-            return "\n".join(lines)
-        except Exception as e:
-            return f"图片分析失败: {e}，请根据经验判断报价"
-
-    @agent.agent.tool
-    async def get_customer_info(ctx: RunContext[Any], customer_id: str) -> str:
-        """
-        查询客户历史信息：消费记录、性格标签、报价历史等。
-        对话开始时或需要了解客户背景时调用。
-        """
-        try:
-            from db.customer_db import db
-            return db.get_profile_text(customer_id)
-        except Exception as e:
-            return f"查询失败: {e}"
-
-    @agent.agent.tool
-    async def transfer_to_human(ctx: RunContext[Any]) -> str:
-        """
-        转接人工客服。
-        遇到退款/投诉/情绪激动/复杂售后时调用。
-        """
-        return "TRANSFER_REQUESTED"
-
-    @agent.agent.tool
-    async def get_customer_risk_profile(ctx: RunContext[Any], customer_id: str = "") -> str:
-        """查询客户风控画像：退款/不付款/差评/人工黑名单等。"""
-        cid = customer_id or ctx.deps.from_id
-        try:
-            info = risk_db.evaluate_customer(cid)
-            return (
-                f"客户:{cid}\n"
-                f"不接单:{'是' if info.get('do_not_serve') else '否'}\n"
-                f"风险等级:{info.get('computed_level','low')} 分数:{info.get('computed_score',0)}\n"
-                f"近30天退款:{info.get('refund_30d',0)}\n"
-                f"近7天未付款下单:{info.get('unpaid_7d',0)}\n"
-                f"近90天差评:{info.get('bad_review_90d',0)}\n"
-                f"备注:{info.get('note','') or '无'}"
-            )
-        except Exception as e:
-            return f"查询风控画像失败: {e}"
-
-    @agent.agent.tool
-    async def mark_customer_risk(
-        ctx: RunContext[Any],
-        customer_id: str,
-        do_not_serve: bool = False,
-        risk_level: str = "low",
-        risk_score: int = 0,
-        note: str = "",
-        tag: str = "",
-    ) -> str:
-        """人工标记客户风控画像（不接单/高风险/备注标签）。"""
-        try:
-            tags = [tag] if tag else []
-            risk_db.set_profile(
-                customer_id=customer_id,
-                do_not_serve=do_not_serve,
-                risk_level=risk_level,
-                risk_score=risk_score,
-                note=note,
-                tags=tags,
-            )
-            return "风控画像已更新"
-        except Exception as e:
-            return f"更新风控画像失败: {e}"
-
-    @agent.agent.tool
-    async def record_customer_risk_event(
-        ctx: RunContext[Any],
-        customer_id: str,
-        event_type: str,
-        event_count: int = 1,
-        note: str = "",
-    ) -> str:
-        """记录风控事件：refund/unpaid_order/bad_review/blacklist_hit 等。"""
-        try:
-            risk_db.record_event(
-                customer_id=customer_id,
-                event_type=event_type,
-                event_count=event_count,
-                note=note,
-            )
-            return "风控事件已记录"
-        except Exception as e:
-            return f"记录风控事件失败: {e}"
-
-    @agent.agent.tool
-    async def save_customer_note(
-        ctx: RunContext[Any],
-        customer_id: str,
-        note: str
-    ) -> str:
-        """
-        记录客户关键信息到画像（邮箱/微信/特殊需求等）。
-        客户提供联系方式或重要信息时调用。
-        """
-        try:
-            from db.customer_db import db
-            db.add_note(customer_id, note)
-            return "已记录"
-        except Exception as e:
-            return f"记录失败: {e}"
-
-    @agent.agent.tool
-    async def update_contact_info(
-        ctx: RunContext[Any],
-        customer_id: str,
-        contact_type: str,
-        value: str
-    ) -> str:
-        """
-        更新客户联系方式。
-        当客户说出邮箱/手机/微信时调用，比正则提取更准确。
-
-        contact_type 枚举值：
-          email   - 邮箱
-          phone   - 手机号
-          wechat  - 微信号
-        """
-        try:
-            from db.customer_db import db
-            if contact_type == "email":
-                db.update_email(customer_id, value)
-            elif contact_type == "phone":
-                db.update_phone(customer_id, value)
-            elif contact_type == "wechat":
-                db.update_wechat(customer_id, value)
-            else:
-                return f"未知联系方式类型: {contact_type}"
-            return f"已保存 {contact_type}: {value}"
-        except Exception as e:
-            return f"保存失败: {e}"
-
-    @agent.agent.tool
-    async def record_quote(
-        ctx: RunContext[Any],
-        customer_id: str,
-        price: int,
-        description: str = ""
-    ) -> str:
-        """
-        记录本次报价到客户画像，用于后续对话保持价格一致。
-        每次给客户报价后调用。
-
-        Args:
-            customer_id: 客户ID
-            price: 报价金额（元）
-            description: 报价描述，如"单图处理"/"三图打包"
-        """
-        try:
-            from db.customer_db import db
-            db.update_last_price(customer_id, price)
-            if description:
-                db.add_note(customer_id, f"报价 {price}元（{description}）")
-            # 同步到内存状态
-            state = agent.conversations.get(customer_id)
-            if state:
-                state.last_price = price
-            return f"已记录报价 {price}元"
-        except Exception as e:
-            return f"记录失败: {e}"
-
-    @agent.agent.tool
-    async def process_image_gemini(ctx: RunContext[Any], customer_id: str = "") -> str:
-        """
-        触发 Gemini 作图处理。客户付款后或说「安排一下」「处理一下」时调用。
-        会从客户档案读取上次发图的 URL 和处理参数（提示词、比例、透视），启动 Gemini 流程。
-        处理完成后会自动发图给客户。
-        """
-        try:
-            from config.config import IMAGE_MODULE_ENABLED
-            if not IMAGE_MODULE_ENABLED:
-                return "现在处理模块暂时暂停，先不自动作图"
-        except Exception:
-            return "现在处理模块暂时暂停，先不自动作图"
-        cid = customer_id or ctx.deps.from_id
-        try:
-            from core.workflow import workflow
-            ok = await workflow.trigger_processing_on_payment(
-                customer_id=cid,
-                acc_id=ctx.deps.acc_id,
-                acc_type=ctx.deps.platform,
-            )
-            if ok:
-                return "已安排，稍后发你"
-            return "该客户暂无待处理图片，请先发图"
-        except Exception as e:
-            return f"触发作图失败: {e}，请稍后重试或转人工"
-
-    @agent.agent_pricing.tool
-    async def analyze_image_pricing(ctx: RunContext[Any], image_url: str) -> str:
-        try:
-            from image.image_analyzer import image_analyzer
-            result = await image_analyzer.analyze(image_url)
-            if result.get("feasibility") == "no" or result.get("risk") == "high":
-                return "该图风险高或不可做：不报价，建议换图或转人工评估。"
-            if not result.get("success", False):
-                return "图片识别异常：先不报价，建议客户重发更清晰图片。"
-            p = result.get("price_suggest", 20)
-            try:
-                st = agent._get_conversation_state(ctx.deps.from_id)
-                if isinstance(result.get("price_min"), (int, float)):
-                    st.last_min_price = int(result.get("price_min") or 0)
-                    try:
-                        from db.customer_db import db as _db
-                        _db.update_last_min_price(ctx.deps.from_id, st.last_min_price)
-                    except Exception:
-                        pass
-            except Exception:
-                pass
-            return f"建议报价：{p}元"
-        except Exception as e:
-            return f"图片分析失败: {e}"
-
-    @agent.agent_pricing.tool
-    async def record_quote_pricing(
-        ctx: RunContext[Any],
-        customer_id: str,
-        price: int,
-        description: str = ""
-    ) -> str:
-        try:
-            from db.customer_db import db
-            db.update_last_price(customer_id, price)
-            return "ok"
-        except Exception as e:
-            return f"记录失败: {e}"
-
-    @agent.agent_processing.tool
-    async def process_image_gemini_run(ctx: RunContext[Any], customer_id: str = "") -> str:
-        """触发 Gemini 作图处理（processing agent 专用入口）。"""
-        return await process_image_gemini(ctx, customer_id)
-
-    @agent.agent_similar.tool
-    async def recommend_similar(ctx: RunContext[Any], hint: str = "") -> str:
-        try:
-            return "有类似款，拍下我发你参考图。"
-        except Exception as e:
-            return f"推荐失败: {e}"
-
-    @agent.agent_order.tool
-    async def handle_order(ctx: RunContext[Any], raw_msg: str = "") -> str:
-        try:
-            info = parse_order_info(raw_msg or "")
-            paid_kw = ["等待发货", "已付款", "付款成功", "买家已付款"]
-            if any(k in (info.get("pay_status", "") or "") for k in paid_kw) or any(k in (info.get("order_status", "") or "") for k in paid_kw):
-                return "已安排，稍后发你"
-            return ""
-        except Exception:
-            return ""
-
-    @agent.agent_risk.tool
-    async def risk_filter(ctx: RunContext[Any], text: str = "") -> str:
-        return "这类不做哈，政治/敏感内容都不接。"
-
-    @agent.agent_risk.tool
-    async def get_customer_risk_profile_risk(ctx: RunContext[Any], customer_id: str = "") -> str:
-        return await get_customer_risk_profile(ctx, customer_id)
-
-    @agent.agent_risk.tool
-    async def mark_customer_risk_risk(
-        ctx: RunContext[Any],
-        customer_id: str,
-        do_not_serve: bool = False,
-        risk_level: str = "low",
-        risk_score: int = 0,
-        note: str = "",
-        tag: str = "",
-    ) -> str:
-        return await mark_customer_risk(
-            ctx=ctx,
-            customer_id=customer_id,
-            do_not_serve=do_not_serve,
-            risk_level=risk_level,
-            risk_score=risk_score,
-            note=note,
-            tag=tag,
-        )
-
-    @agent.agent_risk.tool
-    async def record_customer_risk_event_risk(
-        ctx: RunContext[Any],
-        customer_id: str,
-        event_type: str,
-        event_count: int = 1,
-        note: str = "",
-    ) -> str:
-        return await record_customer_risk_event(
-            ctx=ctx,
-            customer_id=customer_id,
-            event_type=event_type,
-            event_count=event_count,
-            note=note,
-        )
-
-    @agent.agent.tool
-    async def remove_background(ctx: RunContext[Any], image_url: str) -> str:
-        try:
-            from config.config import IMAGE_MODULE_ENABLED
-            if not IMAGE_MODULE_ENABLED:
-                return "现在处理模块暂时暂停，先不处理图片"
-        except Exception:
-            return "现在处理模块暂时暂停，先不处理图片"
-        """【独立工具】去背景，输出白底图。客户只要去背景时调用。"""
-        try:
-            from image.image_tools import remove_background as _rb
-            r = await _rb(image_url)
-            if r["success"]:
-                return f"去背景完成，已保存。自然回复客户好了发你"
-            return f"去背景失败：{r['message']}"
-        except Exception as e:
-            return f"去背景失败：{e}"
-
-    @agent.agent.tool
-    async def perspective_correct(ctx: RunContext[Any], image_url: str) -> str:
-        try:
-            from config.config import IMAGE_MODULE_ENABLED
-            if not IMAGE_MODULE_ENABLED:
-                return "现在处理模块暂时暂停，先不处理图片"
-        except Exception:
-            return "现在处理模块暂时暂停，先不处理图片"
-        """【独立工具】透视矫正。输入需白底图，输出展平图。"""
-        try:
-            from image.image_tools import perspective_correct as _pc
-            r = await _pc(image_url)
-            if r["success"]:
-                return f"透视矫正完成。自然回复客户好了"
-            return f"透视矫正失败：{r['message']}"
-        except Exception as e:
-            return f"透视矫正失败：{e}"
-
-    @agent.agent.tool
-    async def extract_pattern_tool(
-        ctx: RunContext[Any],
-        image_url: str,
-        prompt: str = "",
-        aspect_ratio: str = "1:1"
-    ) -> str:
-        try:
-            from config.config import IMAGE_MODULE_ENABLED
-            if not IMAGE_MODULE_ENABLED:
-                return "现在处理模块暂时暂停，先不处理图片"
-        except Exception:
-            return "现在处理模块暂时暂停，先不处理图片"
-        """【独立工具】印花提取/主处理。按提示词和比例处理。"""
-        try:
-            from image.image_tools import extract_pattern
-            r = await extract_pattern(image_url, prompt=prompt, aspect_ratio=aspect_ratio)
-            if r["success"]:
-                return f"提取完成。自然回复客户好了发你"
-            return f"提取失败：{r['message']}"
-        except Exception as e:
-            return f"提取失败：{e}"
-
-    @agent.agent.tool
-    async def enhance_image_tool(ctx: RunContext[Any], image_url: str) -> str:
-        try:
-            from config.config import IMAGE_MODULE_ENABLED
-            if not IMAGE_MODULE_ENABLED:
-                return "现在处理模块暂时暂停，先不处理图片"
-        except Exception:
-            return "现在处理模块暂时暂停，先不处理图片"
-        """【独立工具】高清增强。客户只要清晰化时调用。"""
-        try:
-            from image.image_tools import enhance_image
-            r = await enhance_image(image_url)
-            if r["success"]:
-                return f"高清增强完成。自然回复客户好了"
-            return f"增强失败：{r['message']}"
-        except Exception as e:
-            return f"增强失败：{e}"
-
-    @agent.agent.tool
-    async def color_match_tool(
-        ctx: RunContext[Any],
-        orig_url: str,
-        result_url: str,
-        strength: float = 0.75
-    ) -> str:
-        try:
-            from config.config import IMAGE_MODULE_ENABLED
-            if not IMAGE_MODULE_ENABLED:
-                return "现在处理模块暂时暂停，先不处理图片"
-        except Exception:
-            return "现在处理模块暂时暂停，先不处理图片"
-        """【独立工具】颜色匹配。将 result 色调匹配到 orig。"""
-        try:
-            from image.image_tools import color_match_images
-            r = await color_match_images(orig_url, result_url, strength=strength)
-            if r["success"]:
-                return f"颜色匹配完成"
-            return f"颜色匹配失败：{r['message']}"
-        except Exception as e:
-            return f"颜色匹配失败：{e}"
-
-    @agent.agent.tool
-    async def trim_border_tool(ctx: RunContext[Any], image_url: str) -> str:
-        try:
-            from config.config import IMAGE_MODULE_ENABLED
-            if not IMAGE_MODULE_ENABLED:
-                return "现在处理模块暂时暂停，先不处理图片"
-        except Exception:
-            return "现在处理模块暂时暂停，先不处理图片"
-        """【独立工具】裁切四周背景边（白/黄/米等）。"""
-        try:
-            from image.image_tools import trim_border
-            r = await trim_border(image_url)
-            if r["success"]:
-                return f"裁边完成"
-            return f"裁边失败：{r['message']}"
-        except Exception as e:
-            return f"裁边失败：{e}"
-
-    @agent.agent.tool
-    async def vectorize_to_eps_tool(ctx: RunContext[Any], image_url: str) -> str:
-        try:
-            from config.config import IMAGE_MODULE_ENABLED
-            if not IMAGE_MODULE_ENABLED:
-                return "现在处理模块暂时暂停，先不处理图片"
-        except Exception:
-            return "现在处理模块暂时暂停，先不处理图片"
-        """【独立工具】矢量化 - 将图片转为 EPS 矢量文件。客户要做矢量图、转 EPS、转 AI 格式时调用。"""
-        try:
-            from image.image_tools import vectorize_to_eps
-            r = await vectorize_to_eps(image_url)
-            if r["success"]:
-                return f"矢量化完成，已生成 EPS 文件。自然回复客户好了发你"
-            return f"矢量化失败：{r['message']}"
-        except Exception as e:
-            return f"矢量化失败：{e}"
-
-    @agent.agent.tool
-    async def meitu_enhance_tool(
-        ctx: RunContext[Any],
-        image_url: str,
-        mode: str = "standard"
-    ) -> str:
-        try:
-            from config.config import IMAGE_MODULE_ENABLED
-            if not IMAGE_MODULE_ENABLED:
-                return "现在处理模块暂时暂停，先不处理图片"
-        except Exception:
-            return "现在处理模块暂时暂停，先不处理图片"
-        """
-        【独立工具】美图画质增强。客户要画质增强、清晰化、美图处理时调用。
-
-        Args:
-            image_url: 图片 URL 或本地路径
-            mode: 处理模式。crystal(极速重绘) standard(标准) enhance(增强) hdr(HDR) portrait(人像优化)
-        """
-        try:
-            from image.image_tools import meitu_enhance
-            r = await meitu_enhance(image_url, mode=mode)
-            if r["success"]:
-                return f"画质增强完成。自然回复客户好了发你"
-            return f"画质增强失败：{r['message']}"
-        except Exception as e:
-            return f"画质增强失败：{e}"
-
-    @agent.agent.tool
-    async def resize_image(
-        ctx: RunContext[Any],
-        image_url: str,
-        width: int,
-        height: int = 0
-    ) -> str:
-        try:
-            from config.config import IMAGE_MODULE_ENABLED
-            if not IMAGE_MODULE_ENABLED:
-                return "现在处理模块暂时暂停，先不处理图片"
-        except Exception:
-            return "现在处理模块暂时暂停，先不处理图片"
-        """
-        改图片尺寸。客户说「改成1920x1080」「弄成横图」「改下尺寸」时调用。
-
-        Args:
-            image_url: 图片URL（客户刚发的图，或从对话中获取）
-            width:  目标宽度（像素），如 1920
-            height: 目标高度（0=按宽度等比缩放），如 1080
-
-        常用尺寸：1920x1080(横屏) 1080x1920(竖屏) 2000x2000(方图)
-        """
-        try:
-            from image.image_processor import image_processor
-            result = await image_processor.resize(image_url, width, height)
-            if result["success"]:
-                return f"改尺寸完成：{width}x{height}，已保存。自然回复客户改好了"
-            else:
-                return f"改尺寸失败：{result['message']}，告知客户稍后重试"
-        except Exception as e:
-            return f"改尺寸失败：{e}"
-
-    @agent.agent.tool
-    async def calculate_bulk_price(
-        ctx: RunContext[Any],
-        image_count: int,
-        complexities: str = ""
-    ) -> str:
-        """
-        计算多图打包价格。
-        客户要做多张图时调用，返回建议总价。
-
-        Args:
-            image_count: 图片数量
-            complexities: 各图复杂度，逗号分隔，如 "normal,complex,simple"
-                          没有识别结果时留空，按平均价格估算
-        """
-        if image_count <= 0:
-            return "图片数量无效"
-
-        # 各复杂度单价（必须为5的整数倍）
-        unit_price = {"simple": 15, "normal": 20, "complex": 25, "hard": 30}
-        default_unit = 20  # 没有识别结果时的默认单价
-
-        if complexities:
-            levels = [c.strip() for c in complexities.split(",")]
-            total = sum(unit_price.get(lv, default_unit) for lv in levels)
-        else:
-            total = image_count * default_unit
-
-        # 打包优惠：3张以上9折，5张以上8折，价格必须为5的整数倍
-        if image_count >= 5:
-            discounted = round(total * 0.8 / 5) * 5
-            tip = f"（{image_count}张8折优惠）"
-        elif image_count >= 3:
-            discounted = round(total * 0.9 / 5) * 5
-            tip = f"（{image_count}张9折优惠）"
-        else:
-            discounted = round(total / 5) * 5
-            tip = ""
-
-        return f"建议打包报价：{discounted}元{tip}（原价{total}元）"

core/engine.py

@@ -0,0 +1,63 @@
+import logging
+from typing import Optional, Any
+from core.schema import StandardMessage, StandardResponse
+from core.events.event_bus import bus
+
+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。
+    """
+    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}
+            )
+
+        # 兜底回复
+        return StandardResponse(
+            reply_content="你好，我是AI助手，有什么可以帮你的？",
+            metadata={"acc_id": msg.acc_id, "acc_type": msg.acc_type}
+        )
+
+    async def emit_image_result(self, user_id: str, platform: str, url: str, acc_id: str):
+        """
+        这是一个业务触发器示例：当图片处理完成时，由 Engine 主动发广播。
+        """
+        await bus.emit(
+            "MESSAGE_OUTBOUND",
+            user_id=user_id,
+            platform=platform,
+            response=StandardResponse(
+                reply_content=url,
+                msg_type=1, # 图片
+                metadata={"acc_id": acc_id}
+            )
+        )

core/events/event_bus.py

@@ -0,0 +1,36 @@
+import asyncio
+import logging
+from typing import Callable, Dict, List, Any, Awaitable
+
+logger = logging.getLogger("cs_agent")
+
+class AsyncEventBus:
+    """
+    异步事件总线：解耦业务触发与平台发送。
+    支持一个事件被多个订阅者监听。
+    """
+    def __init__(self):
+        self._listeners: Dict[str, List[Callable[..., Awaitable[None]]]] = {}
+
+    def subscribe(self, event_type: str, callback: Callable[..., Awaitable[None]]):
+        """订阅事件"""
+        if event_type not in self._listeners:
+            self._listeners[event_type] = []
+        self._listeners[event_type].append(callback)
+        logger.info(f"[EventBus] 新订阅者已注册到事件: {event_type}")
+
+    async def emit(self, event_type: str, **kwargs):
+        """发布事件：异步广播给所有订阅者"""
+        if event_type not in self._listeners:
+            return
+
+        tasks = []
+        for callback in self._listeners[event_type]:
+            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")
+
+# 全局单例，所有模块共用这一个广播台
+bus = AsyncEventBus()

core/orchestrator.py

@@ -0,0 +1,156 @@
+import logging
+import asyncio
+import re
+import time
+from typing import Optional, List, Any, Dict
+from collections import deque
+from core.schema import StandardMessage, StandardResponse
+from core.adapters.qianniu_adapter import QianniuAdapter
+from core.pydantic_ai_agent_v2 import CustomerServiceBrain
+from core.events.event_bus import bus
+from core.repository import repo
+
+logger = logging.getLogger("cs_agent")
+
+class SystemOrchestrator:
+    """
+    全系统总编排：具备转接冷却、防抖合并、多消息去重、以及精准日志。
+    """
+    def __init__(self, ws_client=None):
+        self.ws_client = ws_client
+        self.qianniu_adapter = QianniuAdapter(ws_client)
+        self.brain = CustomerServiceBrain()
+        
+        # 1. 消息 ID 去重
+        self._processed_msg_ids = deque(maxlen=200)
+        
+        # 2. 转接冷却存储 (customer_id -> last_transfer_time)
+        self._last_transfer_time: Dict[str, float] = {}
+        
+        # 3. 防抖配置
+        self._debounce_seconds = 5.0
+        self._debounce_tasks: Dict[str, asyncio.Task] = {}
+        self._pending_messages: Dict[str, List[StandardMessage]] = {}
+        self._user_locks: Dict[str, asyncio.Lock] = {}
+
+        bus.subscribe("MESSAGE_OUTBOUND", self.handle_outbound_event)
+
+    def _get_user_lock(self, user_id: str) -> asyncio.Lock:
+        if user_id not in self._user_locks:
+            self._user_locks[user_id] = asyncio.Lock()
+        return self._user_locks[user_id]
+
+    async def on_raw_message_received(self, platform: str, raw_data: dict):
+        """链路入口"""
+        try:
+            if platform != "qianniu": return
+
+            std_msg, direction = await self.qianniu_adapter.translate_inbound(raw_data)
+            
+            # 过滤心跳
+            if not std_msg.content.strip() and not std_msg.image_urls: return
+
+            # 如果是商家人工回复，静默入库
+            if direction == "out":
+                await repo.save_chat(platform, std_msg.user_id, std_msg.content, "out", acc_id=std_msg.acc_id)
+                return
+
+            # 订单消息处理：静默记录
+            if "[系统订单信息]" in std_msg.content:
+                await self._handle_order_packet(platform, std_msg)
+                await repo.save_chat(platform, std_msg.user_id, std_msg.content, "in", acc_id=std_msg.acc_id)
+                return
+
+            # ID 去重
+            if std_msg.msg_id:
+                if std_msg.msg_id in self._processed_msg_ids: return
+                self._processed_msg_ids.append(std_msg.msg_id)
+
+            # 进入防抖
+            user_id = std_msg.user_id
+            if user_id in self._debounce_tasks: self._debounce_tasks[user_id].cancel()
+            if user_id not in self._pending_messages: self._pending_messages[user_id] = []
+            self._pending_messages[user_id].append(std_msg)
+            
+            self._debounce_tasks[user_id] = asyncio.create_task(self._debounced_process(user_id, platform))
+            
+        except Exception as e:
+            logger.error(f"[Orchestrator] 处理失败: {e}")
+
+    async def _handle_order_packet(self, platform: str, msg: StandardMessage):
+        try:
+            price_match = re.search(r"订单金额:金额:\s*([\d\.]+)元", msg.content)
+            if price_match: await repo.update_task_price(platform, msg.user_id, float(price_match.group(1)))
+            if "买家已付款" in msg.content: await repo.update_task_outcome(platform, msg.user_id, "deal_success")
+            elif any(k in msg.content for k in ["退款", "已关闭", "已取消"]): await repo.update_task_outcome(platform, msg.user_id, "refunded")
+        except Exception: pass
+
+    async def _debounced_process(self, user_id: str, platform: str):
+        try:
+            await asyncio.sleep(self._debounce_seconds)
+            async with self._get_user_lock(user_id):
+                messages = self._pending_messages.pop(user_id, [])
+                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()])
+                all_image_urls = []
+                acc_id = messages[-1].acc_id
+                acc_type = messages[-1].acc_type
+                for m in messages:
+                    for url in m.image_urls:
+                        if url not in all_image_urls: all_image_urls.append(url)
+                
+                # 防抖合并后的消息仍需有 msg_id，避免触发 StandardMessage 校验失败
+                merged_msg_id = messages[-1].msg_id if messages[-1].msg_id else f"merged-{user_id}-{int(time.time() * 1000)}"
+                final_msg = StandardMessage(
+                    platform=platform,
+                    msg_id=merged_msg_id,
+                    user_id=user_id,
+                    content=combined_content,
+                    image_urls=all_image_urls,
+                    acc_id=acc_id,
+                    acc_type=acc_type
+                )
+
+                # B. 持久化
+                db_content = combined_content
+                if all_image_urls: db_content = f"【系统：已收到{len(all_image_urls)}张图】\n{combined_content}"
+                await repo.save_chat(platform, user_id, db_content, "in", acc_id=acc_id)
+
+                # C. 冷却检查：如果 60秒内发过转接，告诉大脑“已处于转接中”
+                is_in_cooldown = (time.time() - self._last_transfer_time.get(user_id, 0)) < 60
+                
+                # D. 思考
+                history = await repo.get_chat_history(user_id, limit=10)
+                if history and history[-1]['content'] == db_content: history = history[:-1]
+
+                # 如果在冷却中，在当前消息里注入“当前已在转接中”的信息
+                if is_in_cooldown:
+                    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}"
+
+                std_res = await self.brain.think_and_reply(final_msg, history=history)
+
+                # E. 发送并记录时间
+                if std_res.should_reply:
+                    # 关键修复：补全发送时的元数据，解决日志 customer_id 为空的问题
+                    std_res.metadata = {"acc_id": acc_id, "acc_type": acc_type}
+                    await self.qianniu_adapter.translate_outbound(std_res, user_id)
+                    await repo.save_chat(platform, user_id, std_res.reply_content, "out", acc_id=acc_id)
+                    
+                    if "[转移会话]" in std_res.reply_content:
+                        self._last_transfer_time[user_id] = time.time()
+
+        except asyncio.CancelledError: pass
+        except Exception as e: logger.exception(f"[Orchestrator] 处理失败: {e}")
+
+    async def handle_outbound_event(self, user_id: str, platform: str, response: StandardResponse):
+        if platform == "qianniu":
+            await self.qianniu_adapter.translate_outbound(response, user_id)
+
+# 全局单例
+orchestrator: Optional[SystemOrchestrator] = None
+def init_orchestrator(ws_client):
+    global orchestrator
+    orchestrator = SystemOrchestrator(ws_client)
+    return orchestrator

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})

core/repository.py

@@ -0,0 +1,69 @@
+import logging
+import asyncio
+from typing import Optional, List, Any
+from datetime import datetime
+from db.customer_db import db as customer_db
+from db.image_tasks_db import db as task_db
+from db.chat_log_db import log_message, get_conversation
+
+logger = logging.getLogger("cs_agent")
+
+class DataRepository:
+    """
+    异步数据仓库：使用 asyncio.to_thread 屏蔽底层同步 IO 阻塞。
+    """
+    def __init__(self):
+        self.customer_db = customer_db
+        self.task_db = task_db
+
+    # --- 聊天记录 (异步化) ---
+
+    async def save_chat(self, platform: str, user_id: str, content: str, direction: str, acc_id: str = ""):
+        """异步持久化存储聊天记录"""
+        return await asyncio.to_thread(
+            log_message,
+            customer_id=user_id,
+            message=content,
+            direction=direction,
+            platform=platform,
+            acc_id=acc_id
+        )
+
+    async def get_chat_history(self, user_id: str, limit: int = 10) -> List[dict]:
+        """异步获取历史记录"""
+        rows = await asyncio.to_thread(get_conversation, user_id, limit=limit)
+        history = []
+        for r in rows:
+            role = "user" if r["direction"] == "in" else "assistant"
+            history.append({"role": role, "content": r["message"]})
+        return history
+
+    # --- 客户相关 (异步化) ---
+
+    async def get_customer(self, platform: str, user_id: str):
+        customer_key = f"{platform}:{user_id}"
+        return await asyncio.to_thread(self.customer_db.get_customer, customer_key)
+
+    # --- 任务相关 (异步化) ---
+
+    async def create_task(self, platform: str, user_id: str, image_url: str, operation: str, requirements: str = ""):
+        return await asyncio.to_thread(
+            self.task_db.add_task,
+            customer_id=user_id,
+            platform=platform,
+            original_image=image_url,
+            operation=operation,
+            requirements=requirements,
+            status="pending"
+        )
+
+    async def update_task_price(self, platform: str, user_id: str, price: float):
+        """异步记录成交价"""
+        return await asyncio.to_thread(self.task_db.update_price, user_id, platform, price)
+
+    async def update_task_outcome(self, platform: str, user_id: str, outcome: str):
+        """异步记录最终结局"""
+        return await asyncio.to_thread(self.task_db.update_outcome, user_id, platform, outcome)
+
+# 全局异步仓库单例
+repo = DataRepository()

core/schema.py

@@ -0,0 +1,29 @@
+from pydantic import BaseModel, Field
+from typing import List, Optional, Any
+from datetime import datetime
+
+class StandardMessage(BaseModel):
+    """全平台通用的输入消息协议"""
+    platform: str = "qianniu"        # 来源平台：qianniu, wechat, feishu, console
+    msg_id: str                      # 消息唯一ID
+    user_id: str                     # 发送者唯一ID
+    user_name: str = ""              # 发送者昵称
+    content: str                     # 消息文本内容
+    image_urls: List[str] = []       # 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)
+    raw_data: Any = None             # 原始消息体（仅供调试或特殊逻辑备查）
+
+    # 扩展字段：针对电商场景
+    goods_name: Optional[str] = None
+    goods_order: Optional[str] = None
+
+class StandardResponse(BaseModel):
+    """大脑给出的通用回复协议"""
+    reply_content: str               # 回复文本或图片URL
+    msg_type: int = 0                # 0: 文本, 1: 图片, 2: 撤回, 9: 转人工
+    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）

core/skill_manager.py

@@ -0,0 +1,56 @@
+import os
+import glob
+import logging
+from pathlib import Path
+from typing import Dict, List, Optional
+
+logger = logging.getLogger("cs_agent")
+
+class SkillManager:
+    """
+    技能包管理器：
+    1. 自动扫描 skills/ 目录下的 SKILL.md 文件。
+    2. 提供按需加载和组合技能的能力。
+    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)
+        self._skill_cache: Dict[str, str] = {}
+        self.reload_skills()
+
+    def reload_skills(self):
+        """扫描并加载所有技能文件"""
+        new_cache = {}
+        skill_files = glob.glob(str(self.skills_dir / "**/SKILL.md"), recursive=True)
+        
+        for file_path in skill_files:
+            try:
+                path = Path(file_path)
+                skill_name = path.parent.name.lower()
+                content = path.read_text(encoding="utf-8")
+                new_cache[skill_name] = content
+            except Exception as e:
+                logger.error(f"[SkillManager] 加载技能失败 {file_path}: {e}")
+        
+        self._skill_cache = new_cache
+        logger.info(f"[SkillManager] 成功加载 {len(self._skill_cache)} 个技能包: {list(self._skill_cache.keys())}")
+
+    def get_skill(self, name: str) -> str:
+        """获取单个技能内容"""
+        return self._skill_cache.get(name.lower(), "")
+
+    def compose_skills(self, names: List[str]) -> str:
+        """组合多个技能内容，用于注入 System Prompt"""
+        parts = []
+        for name in names:
+            content = self.get_skill(name)
+            if content:
+                parts.append(f"### 技能：{name}\n{content}")
+        return "\n\n".join(parts)
+
+    def get_all_skills_text(self) -> str:
+        """获取所有技能的合集（用于全能大脑模式）"""
+        return self.compose_skills(list(self._skill_cache.keys()))
+
+# 全局单例
+skill_manager = SkillManager()

core/websocket_client_v2.py

@@ -0,0 +1,81 @@
+import asyncio
+import json
+import logging
+import os
+from datetime import datetime
+from core.orchestrator import init_orchestrator
+from core.websocket_connection_flow import connect_flow, receive_messages_flow
+from core.websocket_send_flow import send_message_flow
+from utils.observability import emit_activity
+
+logger = logging.getLogger("cs_agent")
+
+class QingjianAPIClient:
+    """
+    重构后的轻简API客户端 (协议全复刻版)
+    """
+    
+    def __init__(self, uri=None, enable_agent: bool = True):
+        from config.config import QINGJIAN_WS_URI
+        self.uri = uri or QINGJIAN_WS_URI
+        self.websocket = None
+        self.running = True
+        self.logger = logger
+        self.enable_agent = enable_agent
+        
+        # 初始化新架构总指挥部
+        self.orchestrator = init_orchestrator(ws_client=self)
+        logger.info("[WebSocket] 新架构 Orchestrator 已就绪。")
+
+    def _activity_log(self, event: str, **kwargs):
+        emit_activity(logger, event=event, **kwargs)
+
+    async def connect(self):
+        await connect_flow(self)
+
+    async def receive_messages(self):
+        await receive_messages_flow(self)
+
+    async def handle_message(self, message):
+        """收到消息处理"""
+        try:
+            data = json.loads(message)
+            await self.orchestrator.on_raw_message_received(platform="qianniu", raw_data=data)
+        except Exception as e:
+            logger.error(f"[WebSocket] 处理消息异常: {e}")
+
+    async def send(self, customer_id: str, acc_id: str, acc_type: str, content: str, msg_type: int = 0):
+        """
+        【协议全复刻】严格按照 legacy/websocket_outbound_flow.py 的结构
+        """
+        # 注意：在这里 from_id 竟然填的是 customer_id，这是逆向接口的特殊要求
+        msg_payload = {
+            "msg_id": "",
+            "acc_id": acc_id,
+            "msg": content,
+            "from_id": customer_id, 
+            "from_name": "",
+            "cy_id": customer_id,
+            "acc_type": acc_type,
+            "msg_type": msg_type,
+            "cy_name": "",
+        }
+        await self.send_message(msg_payload)
+
+    async def send_message(self, message_dict: dict):
+        """底层的 WebSocket 发送"""
+        await send_message_flow(self, message_dict)
+
+    def get_time(self):
+        return datetime.now().strftime("%H:%M:%S")
+
+    async def run(self):
+        await self.connect()
+        await self.receive_messages()
+
+if __name__ == "__main__":
+    client = QingjianAPIClient()
+    try:
+        asyncio.run(client.run())
+    except KeyboardInterrupt:
+        logger.info("已停止")

core/websocket_connection_flow.py

@@ -1,6 +1,8 @@
 import asyncio
 import websockets
+import logging
 
+logger = logging.getLogger("cs_agent")
 
 async def connect_flow(client):
     """连接 WebSocket 服务器并自动重连。"""
@@ -9,49 +11,22 @@ async def connect_flow(client):
             client.logger.info(f"[{client.get_time()}] 正在连接轻简API {client.uri}...")
             async with websockets.connect(client.uri) as websocket:
                 client.websocket = websocket
-                from utils.health_check import set_qingjian_connected
-                set_qingjian_connected(True)
                 client.logger.info(f"[{client.get_time()}] 连接成功!")
-                if client.enable_agent:
-                    client.logger.info(f"[{client.get_time()}] AI Agent 已启用，将自动处理消息")
                 client.logger.info(f"[{client.get_time()}] 等待接收消息...")
-
                 await client.receive_messages()
 
-        except ConnectionRefusedError:
-            from utils.health_check import set_qingjian_connected
-            set_qingjian_connected(False)
-            client.logger.info(f"[{client.get_time()}] 连接被拒绝，请检查轻简软件是否已启动")
-        except websockets.exceptions.InvalidURI:
-            from utils.health_check import set_qingjian_connected
-            set_qingjian_connected(False)
-            client.logger.info(f"[{client.get_time()}] URI格式错误")
         except Exception as e:
-            from utils.health_check import set_qingjian_connected
+            # 统一捕获异常，避免因为不同版本的 websockets 导致属性错误
-            set_qingjian_connected(False)
+            client.logger.info(f"[{client.get_time()}] 连接或运行错误: {e}")
-            client.logger.info(f"[{client.get_time()}] 连接错误: {e}")
 
         if client.running:
             client.logger.info(f"[{client.get_time()}] 5秒后尝试重连...")
             await asyncio.sleep(5)
 
-
 async def receive_messages_flow(client):
     """持续接收消息。"""
     try:
         async for message in client.websocket:
             await client.handle_message(message)
-    except websockets.exceptions.ConnectionClosed:
-        from utils.health_check import set_qingjian_connected
-        set_qingjian_connected(False)
-        client.logger.info(f"[{client.get_time()}] 连接已关闭")
     except Exception as e:
-        from utils.health_check import set_qingjian_connected
+        client.logger.info(f"[{client.get_time()}] 接收消息中断: {e}")
-        set_qingjian_connected(False)
-        client.logger.info(f"[{client.get_time()}] 接收消息错误: {e}")
-
-
-async def handle_message_flow(client, message, *, shop_type_resolver):
-    from core.websocket_inbound_flow import handle_incoming_message
-
-    await handle_incoming_message(client, message, shop_type_resolver=shop_type_resolver)

core/websocket_send_flow.py

@@ -42,13 +42,14 @@ async def send_message_flow(client, message):
             await client.websocket.send(msg_json)
             pretty = json.dumps(message, ensure_ascii=False, indent=2)
             client.logger.info(f"[{client.get_time()}] 发送成功:\n{pretty}")
+            data = message.get("data", {}) if isinstance(message, dict) else {}
             client._activity_log(
                 "send_message_success",
-                trace_id=message.get("_trace_id", ""),
+                trace_id=message.get("_trace_id", "") if isinstance(message, dict) else "",
-                acc_id=message.get("acc_id", ""),
+                acc_id=data.get("acc_id", ""),
-                customer_id=message.get("from_id", ""),
+                customer_id=data.get("cy_id", ""),
-                msg_type=message.get("msg_type", 0),
+                msg_type=data.get("msg_type", 0),
-                msg=message.get("msg", ""),
+                msg=data.get("msg", ""),
             )
         except Exception as e:
             client.logger.info(f"[{client.get_time()}] 发送失败: {e}")

core/提示词.MD

@@ -0,0 +1,19 @@
+"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\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}"

customer_db/customers.json

@@ -1,889 +1 @@
-{
+{}
-  "new_customer_001": {
-    "customer_id": "new_customer_001",
-    "name": "新客户小王",
-    "nickname": "",
-    "email": "",
-    "phone": "",
-    "wechat": "",
-    "address": "",
-    "platform": "",
-    "platform_id": "",
-    "budget": "",
-    "budget_range_min": 0,
-    "budget_range_max": 0,
-    "requirements": [],
-    "preference_services": [],
-    "total_orders": 0,
-    "total_spent": 0,
-    "avg_order_value": 0.0,
-    "purchase_frequency": "",
-    "last_order_date": "",
-    "first_order_date": "",
-    "order_ids": [],
-    "pending_orders": 0,
-    "completed_orders": 0,
-    "refund_count": 0,
-    "personality": [],
-    "communication_prefer": "",
-    "response_speed": "",
-    "patience_level": "",
-    "customer_level": "C",
-    "vip": false,
-    "vip_level": 0,
-    "last_price": 20,
-    "last_price_time": "2026-02-28T15:04:15.181813",
-    "last_quote_no_convert": false,
-    "last_min_price": 0,
-    "last_image_url": "",
-    "last_image_time": "",
-    "last_gemini_prompt": "",
-    "last_aspect_ratio": "1:1",
-    "last_perspective": "no",
-    "processing_status": "",
-    "processing_image_url": "",
-    "expected_done_at": "",
-    "discount_given_count": 0,
-    "lowest_price_accepted": 0,
-    "preferred_format": "jpg",
-    "preferred_size": "",
-    "last_conversation_summary": "",
-    "last_conversation_time": "",
-    "total_images_sent": 0,
-    "complexity_history": [],
-    "image_type_history": [],
-    "price_sensitivity": "",
-    "decision_speed": "",
-    "revision_count": 0,
-    "revision_orders": 0,
-    "total_completed_orders": 0,
-    "bulk_potential": "",
-    "churn_risk": "低",
-    "upsell_opportunity": [],
-    "blacklist": false,
-    "blacklist_reason": "",
-    "vip_custom_price": 0,
-    "last_email_status": "",
-    "good_reviews": 0,
-    "bad_reviews": 0,
-    "dispute_count": 0,
-    "follow_up_by": "",
-    "follow_up_date": "",
-    "next_follow_date": "",
-    "source": "",
-    "coupon_used": "",
-    "notes": [],
-    "tags": [],
-    "created_at": "",
-    "last_contact": "2026-02-28T15:03:57.129715",
-    "last_update": "2026-02-28T15:04:15.184378"
-  },
-  "fast_customer_002": {
-    "customer_id": "fast_customer_002",
-    "name": "爽快老客老李",
-    "nickname": "",
-    "email": "",
-    "phone": "",
-    "wechat": "",
-    "address": "",
-    "platform": "",
-    "platform_id": "",
-    "budget": "",
-    "budget_range_min": 0,
-    "budget_range_max": 0,
-    "requirements": [],
-    "preference_services": [],
-    "total_orders": 8,
-    "total_spent": 280,
-    "avg_order_value": 0.0,
-    "purchase_frequency": "",
-    "last_order_date": "",
-    "first_order_date": "",
-    "order_ids": [],
-    "pending_orders": 0,
-    "completed_orders": 0,
-    "refund_count": 0,
-    "personality": [
-      "爽快"
-    ],
-    "communication_prefer": "",
-    "response_speed": "",
-    "patience_level": "",
-    "customer_level": "C",
-    "vip": false,
-    "vip_level": 0,
-    "last_price": 10,
-    "last_price_time": "2026-02-28T15:06:10.872962",
-    "last_quote_no_convert": false,
-    "last_min_price": 0,
-    "last_image_url": "",
-    "last_image_time": "",
-    "last_gemini_prompt": "",
-    "last_aspect_ratio": "1:1",
-    "last_perspective": "no",
-    "processing_status": "",
-    "processing_image_url": "",
-    "expected_done_at": "",
-    "discount_given_count": 2,
-    "lowest_price_accepted": 10,
-    "preferred_format": "jpg",
-    "preferred_size": "",
-    "last_conversation_summary": "",
-    "last_conversation_time": "",
-    "total_images_sent": 0,
-    "complexity_history": [],
-    "image_type_history": [],
-    "price_sensitivity": "中",
-    "decision_speed": "快",
-    "revision_count": 0,
-    "revision_orders": 0,
-    "total_completed_orders": 8,
-    "bulk_potential": "",
-    "churn_risk": "低",
-    "upsell_opportunity": [],
-    "blacklist": false,
-    "blacklist_reason": "",
-    "vip_custom_price": 0,
-    "last_email_status": "",
-    "good_reviews": 0,
-    "bad_reviews": 0,
-    "dispute_count": 0,
-    "follow_up_by": "",
-    "follow_up_date": "",
-    "next_follow_date": "",
-    "source": "",
-    "coupon_used": "",
-    "notes": [],
-    "tags": [],
-    "created_at": "",
-    "last_contact": "2026-02-28T15:03:57.131384",
-    "last_update": "2026-02-28T15:06:10.875534"
-  },
-  "bargainer_003": {
-    "customer_id": "bargainer_003",
-    "name": "砍价王小张",
-    "nickname": "",
-    "email": "",
-    "phone": "",
-    "wechat": "",
-    "address": "",
-    "platform": "",
-    "platform_id": "",
-    "budget": "",
-    "budget_range_min": 0,
-    "budget_range_max": 0,
-    "requirements": [],
-    "preference_services": [],
-    "total_orders": 3,
-    "total_spent": 45,
-    "avg_order_value": 0.0,
-    "purchase_frequency": "",
-    "last_order_date": "",
-    "first_order_date": "",
-    "order_ids": [],
-    "pending_orders": 0,
-    "completed_orders": 0,
-    "refund_count": 0,
-    "personality": [
-      "砍价狂",
-      "纠结"
-    ],
-    "communication_prefer": "",
-    "response_speed": "",
-    "patience_level": "",
-    "customer_level": "C",
-    "vip": false,
-    "vip_level": 0,
-    "last_price": 10,
-    "last_price_time": "2026-02-28T15:05:45.067204",
-    "last_quote_no_convert": false,
-    "last_min_price": 0,
-    "last_image_url": "",
-    "last_image_time": "",
-    "last_gemini_prompt": "",
-    "last_aspect_ratio": "1:1",
-    "last_perspective": "no",
-    "processing_status": "",
-    "processing_image_url": "",
-    "expected_done_at": "",
-    "discount_given_count": 6,
-    "lowest_price_accepted": 10,
-    "preferred_format": "jpg",
-    "preferred_size": "",
-    "last_conversation_summary": "",
-    "last_conversation_time": "",
-    "total_images_sent": 0,
-    "complexity_history": [],
-    "image_type_history": [],
-    "price_sensitivity": "高",
-    "decision_speed": "慢",
-    "revision_count": 0,
-    "revision_orders": 0,
-    "total_completed_orders": 0,
-    "bulk_potential": "",
-    "churn_risk": "低",
-    "upsell_opportunity": [],
-    "blacklist": false,
-    "blacklist_reason": "",
-    "vip_custom_price": 0,
-    "last_email_status": "",
-    "good_reviews": 0,
-    "bad_reviews": 0,
-    "dispute_count": 0,
-    "follow_up_by": "",
-    "follow_up_date": "",
-    "next_follow_date": "",
-    "source": "",
-    "coupon_used": "",
-    "notes": [],
-    "tags": [],
-    "created_at": "",
-    "last_contact": "2026-02-28T15:03:57.132648",
-    "last_update": "2026-02-28T15:05:45.071818"
-  },
-  "vip_customer_004": {
-    "customer_id": "vip_customer_004",
-    "name": "VIP客户陈总",
-    "nickname": "",
-    "email": "",
-    "phone": "",
-    "wechat": "",
-    "address": "",
-    "platform": "",
-    "platform_id": "",
-    "budget": "",
-    "budget_range_min": 0,
-    "budget_range_max": 0,
-    "requirements": [],
-    "preference_services": [],
-    "total_orders": 15,
-    "total_spent": 680,
-    "avg_order_value": 0.0,
-    "purchase_frequency": "",
-    "last_order_date": "",
-    "first_order_date": "",
-    "order_ids": [],
-    "pending_orders": 0,
-    "completed_orders": 0,
-    "refund_count": 0,
-    "personality": [
-      "爽快"
-    ],
-    "communication_prefer": "",
-    "response_speed": "",
-    "patience_level": "",
-    "customer_level": "A",
-    "vip": true,
-    "vip_level": 2,
-    "last_price": 20,
-    "last_price_time": "2026-02-28T15:04:56.155844",
-    "last_quote_no_convert": false,
-    "last_min_price": 0,
-    "last_image_url": "",
-    "last_image_time": "",
-    "last_gemini_prompt": "",
-    "last_aspect_ratio": "1:1",
-    "last_perspective": "no",
-    "processing_status": "",
-    "processing_image_url": "",
-    "expected_done_at": "",
-    "discount_given_count": 0,
-    "lowest_price_accepted": 0,
-    "preferred_format": "jpg",
-    "preferred_size": "",
-    "last_conversation_summary": "",
-    "last_conversation_time": "",
-    "total_images_sent": 0,
-    "complexity_history": [],
-    "image_type_history": [],
-    "price_sensitivity": "低",
-    "decision_speed": "快",
-    "revision_count": 0,
-    "revision_orders": 0,
-    "total_completed_orders": 0,
-    "bulk_potential": "",
-    "churn_risk": "低",
-    "upsell_opportunity": [],
-    "blacklist": false,
-    "blacklist_reason": "",
-    "vip_custom_price": 18,
-    "last_email_status": "",
-    "good_reviews": 0,
-    "bad_reviews": 0,
-    "dispute_count": 0,
-    "follow_up_by": "",
-    "follow_up_date": "",
-    "next_follow_date": "",
-    "source": "",
-    "coupon_used": "",
-    "notes": [],
-    "tags": [],
-    "created_at": "",
-    "last_contact": "2026-02-28T15:03:57.134104",
-    "last_update": "2026-02-28T15:04:56.158233"
-  },
-  "high_value_005": {
-    "customer_id": "high_value_005",
-    "name": "高价值客户刘老板",
-    "nickname": "",
-    "email": "",
-    "phone": "",
-    "wechat": "",
-    "address": "",
-    "platform": "",
-    "platform_id": "",
-    "budget": "",
-    "budget_range_min": 0,
-    "budget_range_max": 0,
-    "requirements": [],
-    "preference_services": [],
-    "total_orders": 20,
-    "total_spent": 1200,
-    "avg_order_value": 60,
-    "purchase_frequency": "",
-    "last_order_date": "",
-    "first_order_date": "",
-    "order_ids": [],
-    "pending_orders": 0,
-    "completed_orders": 0,
-    "refund_count": 0,
-    "personality": [
-      "爽快"
-    ],
-    "communication_prefer": "",
-    "response_speed": "",
-    "patience_level": "",
-    "customer_level": "A",
-    "vip": false,
-    "vip_level": 0,
-    "last_price": 20,
-    "last_price_time": "2026-02-28T15:05:11.156030",
-    "last_quote_no_convert": false,
-    "last_min_price": 0,
-    "last_image_url": "",
-    "last_image_time": "",
-    "last_gemini_prompt": "",
-    "last_aspect_ratio": "1:1",
-    "last_perspective": "no",
-    "processing_status": "",
-    "processing_image_url": "",
-    "expected_done_at": "",
-    "discount_given_count": 0,
-    "lowest_price_accepted": 0,
-    "preferred_format": "jpg",
-    "preferred_size": "",
-    "last_conversation_summary": "",
-    "last_conversation_time": "",
-    "total_images_sent": 0,
-    "complexity_history": [],
-    "image_type_history": [],
-    "price_sensitivity": "低",
-    "decision_speed": "快",
-    "revision_count": 0,
-    "revision_orders": 0,
-    "total_completed_orders": 0,
-    "bulk_potential": "",
-    "churn_risk": "低",
-    "upsell_opportunity": [],
-    "blacklist": false,
-    "blacklist_reason": "",
-    "vip_custom_price": 0,
-    "last_email_status": "",
-    "good_reviews": 0,
-    "bad_reviews": 0,
-    "dispute_count": 0,
-    "follow_up_by": "",
-    "follow_up_date": "",
-    "next_follow_date": "",
-    "source": "",
-    "coupon_used": "",
-    "notes": [],
-    "tags": [],
-    "created_at": "",
-    "last_contact": "2026-02-28T15:03:57.135396",
-    "last_update": "2026-02-28T15:05:11.160004"
-  },
-  "blacklist_006": {
-    "customer_id": "blacklist_006",
-    "name": "黑名单客户",
-    "nickname": "",
-    "email": "",
-    "phone": "",
-    "wechat": "",
-    "address": "",
-    "platform": "",
-    "platform_id": "",
-    "budget": "",
-    "budget_range_min": 0,
-    "budget_range_max": 0,
-    "requirements": [],
-    "preference_services": [],
-    "total_orders": 0,
-    "total_spent": 0.0,
-    "avg_order_value": 0.0,
-    "purchase_frequency": "",
-    "last_order_date": "",
-    "first_order_date": "",
-    "order_ids": [],
-    "pending_orders": 0,
-    "completed_orders": 0,
-    "refund_count": 0,
-    "personality": [],
-    "communication_prefer": "",
-    "response_speed": "",
-    "patience_level": "",
-    "customer_level": "C",
-    "vip": false,
-    "vip_level": 0,
-    "last_price": 0,
-    "last_price_time": "",
-    "last_quote_no_convert": false,
-    "last_min_price": 0,
-    "last_image_url": "",
-    "last_image_time": "",
-    "last_gemini_prompt": "",
-    "last_aspect_ratio": "1:1",
-    "last_perspective": "no",
-    "processing_status": "",
-    "processing_image_url": "",
-    "expected_done_at": "",
-    "discount_given_count": 0,
-    "lowest_price_accepted": 0,
-    "preferred_format": "jpg",
-    "preferred_size": "",
-    "last_conversation_summary": "",
-    "last_conversation_time": "",
-    "total_images_sent": 0,
-    "complexity_history": [],
-    "image_type_history": [],
-    "price_sensitivity": "",
-    "decision_speed": "",
-    "revision_count": 0,
-    "revision_orders": 0,
-    "total_completed_orders": 0,
-    "bulk_potential": "",
-    "churn_risk": "低",
-    "upsell_opportunity": [],
-    "blacklist": true,
-    "blacklist_reason": "恶意投诉多次",
-    "vip_custom_price": 0,
-    "last_email_status": "",
-    "good_reviews": 0,
-    "bad_reviews": 0,
-    "dispute_count": 0,
-    "follow_up_by": "",
-    "follow_up_date": "",
-    "next_follow_date": "",
-    "source": "",
-    "coupon_used": "",
-    "notes": [],
-    "tags": [],
-    "created_at": "",
-    "last_contact": "2026-02-28T15:03:57.136490",
-    "last_update": "2026-02-28T15:05:27.155220"
-  },
-  "test_new_001": {
-    "customer_id": "test_new_001",
-    "name": "新客户小王",
-    "nickname": "",
-    "email": "",
-    "phone": "",
-    "wechat": "",
-    "address": "",
-    "platform": "",
-    "platform_id": "",
-    "budget": "",
-    "budget_range_min": 0,
-    "budget_range_max": 0,
-    "requirements": [],
-    "preference_services": [],
-    "total_orders": 0,
-    "total_spent": 0,
-    "avg_order_value": 0.0,
-    "purchase_frequency": "",
-    "last_order_date": "",
-    "first_order_date": "",
-    "order_ids": [],
-    "pending_orders": 0,
-    "completed_orders": 0,
-    "refund_count": 0,
-    "personality": [],
-    "communication_prefer": "",
-    "response_speed": "",
-    "patience_level": "",
-    "customer_level": "C",
-    "vip": false,
-    "vip_level": 0,
-    "last_price": 0,
-    "last_price_time": "2026-02-28T15:27:40.801329",
-    "last_quote_no_convert": false,
-    "last_min_price": 0,
-    "last_image_url": "",
-    "last_image_time": "",
-    "last_gemini_prompt": "",
-    "last_aspect_ratio": "1:1",
-    "last_perspective": "no",
-    "processing_status": "",
-    "processing_image_url": "",
-    "expected_done_at": "",
-    "discount_given_count": 0,
-    "lowest_price_accepted": 0,
-    "preferred_format": "jpg",
-    "preferred_size": "",
-    "last_conversation_summary": "",
-    "last_conversation_time": "",
-    "total_images_sent": 0,
-    "complexity_history": [],
-    "image_type_history": [],
-    "price_sensitivity": "",
-    "decision_speed": "",
-    "revision_count": 0,
-    "revision_orders": 0,
-    "total_completed_orders": 0,
-    "bulk_potential": "",
-    "churn_risk": "低",
-    "upsell_opportunity": [],
-    "blacklist": false,
-    "blacklist_reason": "",
-    "vip_custom_price": 0,
-    "last_email_status": "",
-    "good_reviews": 0,
-    "bad_reviews": 0,
-    "dispute_count": 0,
-    "follow_up_by": "",
-    "follow_up_date": "",
-    "next_follow_date": "",
-    "source": "",
-    "coupon_used": "",
-    "notes": [],
-    "tags": [],
-    "created_at": "",
-    "last_contact": "2026-02-28T15:29:05.719291",
-    "last_update": "2026-02-28T15:29:05.719308"
-  },
-  "test_fast_002": {
-    "customer_id": "test_fast_002",
-    "name": "爽快老客老李",
-    "nickname": "",
-    "email": "",
-    "phone": "",
-    "wechat": "",
-    "address": "",
-    "platform": "",
-    "platform_id": "",
-    "budget": "",
-    "budget_range_min": 0,
-    "budget_range_max": 0,
-    "requirements": [],
-    "preference_services": [],
-    "total_orders": 8,
-    "total_spent": 280,
-    "avg_order_value": 0.0,
-    "purchase_frequency": "",
-    "last_order_date": "",
-    "first_order_date": "",
-    "order_ids": [],
-    "pending_orders": 0,
-    "completed_orders": 0,
-    "refund_count": 0,
-    "personality": [
-      "爽快"
-    ],
-    "communication_prefer": "",
-    "response_speed": "",
-    "patience_level": "",
-    "customer_level": "C",
-    "vip": false,
-    "vip_level": 0,
-    "last_price": 25,
-    "last_price_time": "",
-    "last_quote_no_convert": false,
-    "last_min_price": 0,
-    "last_image_url": "",
-    "last_image_time": "",
-    "last_gemini_prompt": "",
-    "last_aspect_ratio": "1:1",
-    "last_perspective": "no",
-    "processing_status": "",
-    "processing_image_url": "",
-    "expected_done_at": "",
-    "discount_given_count": 0,
-    "lowest_price_accepted": 0,
-    "preferred_format": "",
-    "preferred_size": "",
-    "last_conversation_summary": "",
-    "last_conversation_time": "",
-    "total_images_sent": 0,
-    "complexity_history": [],
-    "image_type_history": [],
-    "price_sensitivity": "低",
-    "decision_speed": "快",
-    "revision_count": 0,
-    "revision_orders": 0,
-    "total_completed_orders": 8,
-    "bulk_potential": "",
-    "churn_risk": "",
-    "upsell_opportunity": [],
-    "blacklist": false,
-    "blacklist_reason": "",
-    "vip_custom_price": 0,
-    "last_email_status": "",
-    "good_reviews": 0,
-    "bad_reviews": 0,
-    "dispute_count": 0,
-    "follow_up_by": "",
-    "follow_up_date": "",
-    "next_follow_date": "",
-    "source": "",
-    "coupon_used": "",
-    "notes": [],
-    "tags": [],
-    "created_at": "",
-    "last_contact": "2026-02-28T15:29:05.720944",
-    "last_update": "2026-02-28T15:29:05.720948"
-  },
-  "test_bargain_003": {
-    "customer_id": "test_bargain_003",
-    "name": "砍价王小张",
-    "nickname": "",
-    "email": "",
-    "phone": "",
-    "wechat": "",
-    "address": "",
-    "platform": "",
-    "platform_id": "",
-    "budget": "",
-    "budget_range_min": 0,
-    "budget_range_max": 0,
-    "requirements": [],
-    "preference_services": [],
-    "total_orders": 3,
-    "total_spent": 45,
-    "avg_order_value": 0.0,
-    "purchase_frequency": "",
-    "last_order_date": "",
-    "first_order_date": "",
-    "order_ids": [],
-    "pending_orders": 0,
-    "completed_orders": 0,
-    "refund_count": 0,
-    "personality": [
-      "砍价狂",
-      "纠结"
-    ],
-    "communication_prefer": "",
-    "response_speed": "",
-    "patience_level": "",
-    "customer_level": "C",
-    "vip": false,
-    "vip_level": 0,
-    "last_price": 15,
-    "last_price_time": "",
-    "last_quote_no_convert": false,
-    "last_min_price": 0,
-    "last_image_url": "",
-    "last_image_time": "",
-    "last_gemini_prompt": "",
-    "last_aspect_ratio": "1:1",
-    "last_perspective": "no",
-    "processing_status": "",
-    "processing_image_url": "",
-    "expected_done_at": "",
-    "discount_given_count": 4,
-    "lowest_price_accepted": 15,
-    "preferred_format": "",
-    "preferred_size": "",
-    "last_conversation_summary": "",
-    "last_conversation_time": "",
-    "total_images_sent": 0,
-    "complexity_history": [],
-    "image_type_history": [],
-    "price_sensitivity": "高",
-    "decision_speed": "慢",
-    "revision_count": 0,
-    "revision_orders": 0,
-    "total_completed_orders": 0,
-    "bulk_potential": "",
-    "churn_risk": "",
-    "upsell_opportunity": [],
-    "blacklist": false,
-    "blacklist_reason": "",
-    "vip_custom_price": 0,
-    "last_email_status": "",
-    "good_reviews": 0,
-    "bad_reviews": 0,
-    "dispute_count": 0,
-    "follow_up_by": "",
-    "follow_up_date": "",
-    "next_follow_date": "",
-    "source": "",
-    "coupon_used": "",
-    "notes": [],
-    "tags": [],
-    "created_at": "",
-    "last_contact": "2026-02-28T15:29:05.722448",
-    "last_update": "2026-02-28T15:29:05.722454"
-  },
-  "test_vip_004": {
-    "customer_id": "test_vip_004",
-    "name": "VIP 客户陈总",
-    "nickname": "",
-    "email": "",
-    "phone": "",
-    "wechat": "",
-    "address": "",
-    "platform": "",
-    "platform_id": "",
-    "budget": "",
-    "budget_range_min": 0,
-    "budget_range_max": 0,
-    "requirements": [],
-    "preference_services": [],
-    "total_orders": 15,
-    "total_spent": 680,
-    "avg_order_value": 0.0,
-    "purchase_frequency": "",
-    "last_order_date": "",
-    "first_order_date": "",
-    "order_ids": [],
-    "pending_orders": 0,
-    "completed_orders": 0,
-    "refund_count": 0,
-    "personality": [
-      "爽快"
-    ],
-    "communication_prefer": "",
-    "response_speed": "",
-    "patience_level": "",
-    "customer_level": "A",
-    "vip": true,
-    "vip_level": 2,
-    "last_price": 0,
-    "last_price_time": "",
-    "last_quote_no_convert": false,
-    "last_min_price": 0,
-    "last_image_url": "",
-    "last_image_time": "",
-    "last_gemini_prompt": "",
-    "last_aspect_ratio": "1:1",
-    "last_perspective": "no",
-    "processing_status": "",
-    "processing_image_url": "",
-    "expected_done_at": "",
-    "discount_given_count": 0,
-    "lowest_price_accepted": 0,
-    "preferred_format": "",
-    "preferred_size": "",
-    "last_conversation_summary": "",
-    "last_conversation_time": "",
-    "total_images_sent": 0,
-    "complexity_history": [],
-    "image_type_history": [],
-    "price_sensitivity": "低",
-    "decision_speed": "快",
-    "revision_count": 0,
-    "revision_orders": 0,
-    "total_completed_orders": 0,
-    "bulk_potential": "",
-    "churn_risk": "",
-    "upsell_opportunity": [],
-    "blacklist": false,
-    "blacklist_reason": "",
-    "vip_custom_price": 18,
-    "last_email_status": "",
-    "good_reviews": 0,
-    "bad_reviews": 0,
-    "dispute_count": 0,
-    "follow_up_by": "",
-    "follow_up_date": "",
-    "next_follow_date": "",
-    "source": "",
-    "coupon_used": "",
-    "notes": [],
-    "tags": [],
-    "created_at": "",
-    "last_contact": "2026-02-28T15:29:05.723887",
-    "last_update": "2026-02-28T15:29:05.723890"
-  },
-  "test_highvalue_005": {
-    "customer_id": "test_highvalue_005",
-    "name": "高价值客户刘老板",
-    "nickname": "",
-    "email": "",
-    "phone": "",
-    "wechat": "",
-    "address": "",
-    "platform": "",
-    "platform_id": "",
-    "budget": "",
-    "budget_range_min": 0,
-    "budget_range_max": 0,
-    "requirements": [],
-    "preference_services": [],
-    "total_orders": 20,
-    "total_spent": 1200,
-    "avg_order_value": 60,
-    "purchase_frequency": "",
-    "last_order_date": "",
-    "first_order_date": "",
-    "order_ids": [],
-    "pending_orders": 0,
-    "completed_orders": 0,
-    "refund_count": 0,
-    "personality": [
-      "爽快"
-    ],
-    "communication_prefer": "",
-    "response_speed": "",
-    "patience_level": "",
-    "customer_level": "A",
-    "vip": false,
-    "vip_level": 0,
-    "last_price": 0,
-    "last_price_time": "",
-    "last_quote_no_convert": false,
-    "last_min_price": 0,
-    "last_image_url": "",
-    "last_image_time": "",
-    "last_gemini_prompt": "",
-    "last_aspect_ratio": "1:1",
-    "last_perspective": "no",
-    "processing_status": "",
-    "processing_image_url": "",
-    "expected_done_at": "",
-    "discount_given_count": 0,
-    "lowest_price_accepted": 0,
-    "preferred_format": "",
-    "preferred_size": "",
-    "last_conversation_summary": "",
-    "last_conversation_time": "",
-    "total_images_sent": 0,
-    "complexity_history": [],
-    "image_type_history": [],
-    "price_sensitivity": "低",
-    "decision_speed": "快",
-    "revision_count": 0,
-    "revision_orders": 0,
-    "total_completed_orders": 0,
-    "bulk_potential": "",
-    "churn_risk": "",
-    "upsell_opportunity": [],
-    "blacklist": false,
-    "blacklist_reason": "",
-    "vip_custom_price": 0,
-    "last_email_status": "",
-    "good_reviews": 0,
-    "bad_reviews": 0,
-    "dispute_count": 0,
-    "follow_up_by": "",
-    "follow_up_date": "",
-    "next_follow_date": "",
-    "source": "",
-    "coupon_used": "",
-    "notes": [],
-    "tags": [],
-    "created_at": "",
-    "last_contact": "2026-02-28T15:29:05.725313",
-    "last_update": "2026-02-28T15:29:05.725316"
-  }
-}

db/chat_log_db.py

@@ -199,14 +199,18 @@ def get_customers(limit: int = 100) -> List[Dict]:
 
 
 def get_conversation(customer_id: str, limit: int = 200) -> List[Dict]:
-    """返回某客户的全部对话记录（按时间升序）"""
+    """返回某客户的最近对话记录（按时间升序）"""
     with _get_conn() as conn:
+        # 核心修复：先取最新的 limit 条，再按时间正序排列
         rows = conn.execute(_sql("""
+            SELECT * FROM (
                 SELECT id, direction, message, msg_type, timestamp, acc_id
                 FROM chat_logs
                 WHERE customer_id = ?
-            ORDER BY timestamp ASC, id ASC
+                ORDER BY timestamp DESC, id DESC
                 LIMIT ?
+            ) AS recent
+            ORDER BY timestamp ASC, id ASC
         """), (customer_id, limit)).fetchall()
     return [dict(r) for r in rows]
 

db/image_tasks_db.py

@@ -1,480 +1,113 @@
 # -*- coding: utf-8 -*-
-"""
-图片任务数据库管理
-支持客户后续增加需求细节
-"""
 import sqlite3
 import json
 import logging
+import uuid
+import os
 from typing import Optional, List, Dict
 from pathlib import Path
 from datetime import datetime
 from enum import Enum
-import os
 
 logger = logging.getLogger(__name__)
-_DB_TYPE = os.getenv("DB_TYPE", "sqlite").lower()
-_MYSQL_HOST = os.getenv("MYSQL_HOST", "127.0.0.1")
-_MYSQL_PORT = int(os.getenv("MYSQL_PORT", "3306"))
-_MYSQL_USER = os.getenv("MYSQL_USER", "root")
-_MYSQL_PASSWORD = os.getenv("MYSQL_PASSWORD", "")
-_MYSQL_DATABASE = os.getenv("MYSQL_DATABASE", "ai_cs")
-
-def _is_mysql() -> bool:
-    return _DB_TYPE in ("mysql", "mariadb")
-
-def _sql(query: str) -> str:
-    return query.replace("?", "%s") if _is_mysql() else query
-
-def _now_str() -> str:
-    if _is_mysql():
-        return datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-    return datetime.now().isoformat()
 
 class TaskStatus(Enum):
-    """任务状态"""
+    PENDING = "pending"
-    PENDING = "pending"              # 待付款
+    PROCESSING = "processing"
-    PAID = "paid"                    # 已付款，待处理
+    COMPLETED = "completed"
-    PROCESSING = "processing"        # 处理中
+    FAILED = "failed"
-    AWAITING_CONFIRM = "awaiting_confirm"  # 已完成，待客户确认
-    COMPLETED = "completed"          # 已完成
-    FAILED = "failed"                # 失败
-    CANCELLED = "cancelled"          # 已取消
 
 class ImageTaskManager:
-    """图片任务管理器"""
-    
     def __init__(self, db_path: str = None):
         if db_path is None:
             db_path = Path(__file__).parent / "image_tasks.db"
-        
         self.db_path = db_path
         self._init_db()
-        logger.info(f"图片任务管理器初始化完成，数据库：{self.db_path}")
 
     def _init_db(self):
-        """初始化数据库"""
-        if _is_mysql():
-            conn = self._get_conn()
-            cursor = conn.cursor()
-            cursor.execute('''
-                CREATE TABLE IF NOT EXISTS image_tasks (
-                    task_id VARCHAR(128) PRIMARY KEY,
-                    customer_id VARCHAR(128) NOT NULL,
-                    customer_name VARCHAR(255),
-                    original_image TEXT NOT NULL,
-                    operation VARCHAR(64) DEFAULT 'enhance',
-                    requirements TEXT,
-                    customer_notes TEXT,
-                    status VARCHAR(32) DEFAULT 'pending',
-                    created_at DATETIME,
-                    paid_at DATETIME,
-                    started_at DATETIME,
-                    completed_at DATETIME,
-                    result_image TEXT,
-                    error_message TEXT,
-                    retry_count INT DEFAULT 0,
-                    acc_id VARCHAR(128),
-                    acc_type VARCHAR(64) DEFAULT 'AliWorkbench'
-                ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4
-            ''')
-            cursor.execute('''
-                CREATE TABLE IF NOT EXISTS task_requirement_changes (
-                    id INTEGER PRIMARY KEY AUTO_INCREMENT,
-                    task_id VARCHAR(128) NOT NULL,
-                    change_type VARCHAR(64),
-                    old_value TEXT,
-                    new_value TEXT,
-                    changed_at DATETIME,
-                    changed_by VARCHAR(32),
-                    FOREIGN KEY (task_id) REFERENCES image_tasks(task_id)
-                ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4
-            ''')
-            cursor.execute("SHOW INDEX FROM image_tasks")
-            exists = {str(r.get("Key_name", "")) for r in cursor.fetchall()}
-            if "idx_customer" not in exists:
-                cursor.execute('CREATE INDEX idx_customer ON image_tasks(customer_id)')
-            if "idx_status" not in exists:
-                cursor.execute('CREATE INDEX idx_status ON image_tasks(status)')
-            if "idx_created" not in exists:
-                cursor.execute('CREATE INDEX idx_created ON image_tasks(created_at)')
-            conn.commit()
-            conn.close()
-        else:
         self.db_path.parent.mkdir(parents=True, exist_ok=True)
         conn = sqlite3.connect(self.db_path)
         cursor = conn.cursor()
+        # 核心任务表
         cursor.execute('''
             CREATE TABLE IF NOT EXISTS image_tasks (
                 task_id TEXT PRIMARY KEY,
                 customer_id TEXT NOT NULL,
-                    customer_name TEXT,
+                platform TEXT DEFAULT 'qianniu',
                 original_image TEXT NOT NULL,
                 operation TEXT DEFAULT 'enhance',
                 requirements TEXT,
-                    customer_notes TEXT,
                 status TEXT DEFAULT 'pending',
-                    created_at TEXT,
-                    paid_at TEXT,
-                    started_at TEXT,
-                    completed_at TEXT,
                 result_image TEXT,
-                    error_message TEXT,
+                price REAL DEFAULT 0.0,
-                    retry_count INTEGER DEFAULT 0,
+                outcome TEXT DEFAULT 'pending', 
-                    acc_id TEXT,
+                created_at TEXT,
-                    acc_type TEXT DEFAULT 'AliWorkbench'
+                updated_at TEXT
             )
         ''')
-            cursor.execute('''
-                CREATE TABLE IF NOT EXISTS task_requirement_changes (
-                    id INTEGER PRIMARY KEY AUTOINCREMENT,
-                    task_id TEXT NOT NULL,
-                    change_type TEXT,
-                    old_value TEXT,
-                    new_value TEXT,
-                    changed_at TEXT,
-                    changed_by TEXT,
-                    FOREIGN KEY (task_id) REFERENCES image_tasks(task_id)
-                )
-            ''')
-            cursor.execute('CREATE INDEX IF NOT EXISTS idx_customer ON image_tasks(customer_id)')
         cursor.execute('CREATE INDEX IF NOT EXISTS idx_status ON image_tasks(status)')
-            cursor.execute('CREATE INDEX IF NOT EXISTS idx_created ON image_tasks(created_at)')
+        cursor.execute('CREATE INDEX IF NOT EXISTS idx_cust_plat ON image_tasks(customer_id, platform)')
         conn.commit()
         conn.close()
-        logger.info("数据库表初始化完成")
 
     def _get_conn(self):
-        """获取数据库连接"""
-        if _is_mysql():
-            import pymysql
-            return pymysql.connect(
-                host=_MYSQL_HOST,
-                port=_MYSQL_PORT,
-                user=_MYSQL_USER,
-                password=_MYSQL_PASSWORD,
-                database=_MYSQL_DATABASE,
-                charset="utf8mb4",
-                cursorclass=pymysql.cursors.DictCursor,
-                autocommit=False,
-            )
         conn = sqlite3.connect(self.db_path)
         conn.row_factory = sqlite3.Row
         return conn
 
-    def create_task(self, task_id: str, customer_id: str, customer_name: str,
+    def add_task(self, customer_id: str, platform: str, original_image: str, operation: str, requirements: str = "", status: str = "pending") -> str:
-                   original_image: str, operation: str = 'enhance',
+        task_id = str(uuid.uuid4())
-                   requirements: dict = None, acc_id: str = '', acc_type: str = 'AliWorkbench') -> bool:
+        now = datetime.now().isoformat()
-        """创建图片任务"""
         try:
             conn = self._get_conn()
             cursor = conn.cursor()
-            
+            cursor.execute('''
-            requirements_json = json.dumps(requirements) if requirements else None
+                INSERT INTO image_tasks (task_id, customer_id, platform, original_image, operation, requirements, status, created_at, updated_at)
-            
+                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
-            cursor.execute(_sql('''
+            ''', (task_id, customer_id, platform, original_image, operation, requirements, status, now, now))
-                INSERT INTO image_tasks (
-                    task_id, customer_id, customer_name, original_image,
-                    operation, requirements, customer_notes, status,
-                    created_at, acc_id, acc_type
-                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
-            '''), (
-                task_id,
-                customer_id,
-                customer_name,
-                original_image,
-                operation,
-                requirements_json,
-                '',  # 初始备注为空
-                TaskStatus.PENDING.value,
-                _now_str(),
-                acc_id,
-                acc_type
-            ))
-            
             conn.commit()
             conn.close()
-            
+            return task_id
-            logger.info(f"图片任务创建成功：{task_id}")
-            return True
-            
         except Exception as e:
-            logger.error(f"创建图片任务失败：{e}")
+            logger.error(f"Failed to add task: {e}")
-            return False
+            return ""
 
-    def get_task(self, task_id: str) -> Optional[dict]:
+    def update_status(self, task_id: str, status: str, result_image: str = ""):
-        """查询任务"""
+        now = datetime.now().isoformat()
         try:
             conn = self._get_conn()
             cursor = conn.cursor()
-            
+            if result_image:
-            cursor.execute(_sql('SELECT * FROM image_tasks WHERE task_id = ?'), (task_id,))
+                cursor.execute('UPDATE image_tasks SET status = ?, result_image = ?, updated_at = ? WHERE task_id = ?', 
-            row = cursor.fetchone()
+                             (status, result_image, now, task_id))
-            conn.close()
-            
-            if row:
-                task = dict(row)
-                # 解析 JSON 字段
-                if task.get('requirements'):
-                    task['requirements'] = json.loads(task['requirements'])
-                return task
-            return None
-            
-        except Exception as e:
-            logger.error(f"查询任务失败：{e}")
-            return None
-    
-    def get_customer_tasks(self, customer_id: str, status: str = None) -> List[dict]:
-        """查询客户的任务列表"""
-        try:
-            conn = self._get_conn()
-            cursor = conn.cursor()
-            
-            if status:
-                cursor.execute(_sql('''
-                    SELECT * FROM image_tasks 
-                    WHERE customer_id = ? AND status = ?
-                    ORDER BY created_at DESC
-                '''), (customer_id, status))
             else:
-                cursor.execute(_sql('''
+                cursor.execute('UPDATE image_tasks SET status = ?, updated_at = ? WHERE task_id = ?', 
-                    SELECT * FROM image_tasks 
+                             (status, now, task_id))
-                    WHERE customer_id = ?
-                    ORDER BY created_at DESC
-                '''), (customer_id,))
-            
-            rows = cursor.fetchall()
-            conn.close()
-            
-            tasks = []
-            for row in rows:
-                task = dict(row)
-                if task.get('requirements'):
-                    task['requirements'] = json.loads(task['requirements'])
-                tasks.append(task)
-            
-            return tasks
-            
-        except Exception as e:
-            logger.error(f"查询客户任务失败：{e}")
-            return []
-    
-    def update_status(self, task_id: str, status: TaskStatus):
-        """更新任务状态"""
-        try:
-            conn = self._get_conn()
-            cursor = conn.cursor()
-            
-            placeholder = "%s" if _is_mysql() else "?"
-            updates = [f'status = {placeholder}']
-            params = [status.value]
-            
-            # 根据状态设置时间
-            if status == TaskStatus.PAID:
-                updates.append(f'paid_at = {placeholder}')
-                params.append(_now_str())
-            elif status == TaskStatus.PROCESSING:
-                updates.append(f'started_at = {placeholder}')
-                params.append(_now_str())
-            elif status in [TaskStatus.COMPLETED, TaskStatus.FAILED]:
-                updates.append(f'completed_at = {placeholder}')
-                params.append(_now_str())
-            
-            params.append(task_id)
-            
-            cursor.execute(_sql(f'''
-                UPDATE image_tasks 
-                SET {', '.join(updates)}
-                WHERE task_id = ?
-            '''), params)
-            
             conn.commit()
             conn.close()
-            
-            logger.info(f"任务状态更新：{task_id} -> {status.value}")
-            
         except Exception as e:
-            logger.error(f"更新任务状态失败：{e}")
+            logger.error(f"Failed to update task status: {e}")
 
-    def update_result(self, task_id: str, result_image: str, error_message: str = None):
+    def update_outcome(self, customer_id: str, platform: str, outcome: str):
-        """更新处理结果"""
+        """记录任务的最终结局（用于训练样本分类）"""
+        now = datetime.now().isoformat()
         try:
             conn = self._get_conn()
             cursor = conn.cursor()
-            
+            cursor.execute('''
-            cursor.execute(_sql('''
                 UPDATE image_tasks 
-                SET result_image = ?, error_message = ?
+                SET outcome = ?, updated_at = ? 
-                WHERE task_id = ?
+                WHERE task_id = (
-            '''), (result_image, error_message, task_id))
+                    SELECT task_id FROM image_tasks 
-            
+                    WHERE customer_id = ? AND platform = ?
+                    ORDER BY created_at DESC LIMIT 1
+                )
+            ''', (outcome, now, customer_id, platform))
             conn.commit()
             conn.close()
-            
+            logger.info(f"[DB] 客户 {customer_id} 任务结局更新为: {outcome}")
-            logger.info(f"任务结果更新：{task_id}")
-            
         except Exception as e:
-            logger.error(f"更新任务结果失败：{e}")
+            logger.error(f"Failed to update outcome: {e}")
-    
-    def add_customer_note(self, task_id: str, note: str, changed_by: str = 'customer') -> bool:
-        """
-        客户添加需求备注（支持后续增加细节）
-        
-        Args:
-            task_id: 任务 ID
-            note: 备注内容
-            changed_by: 修改者（customer/staff）
-            
-        Returns:
-            bool: 是否成功
-        """
-        try:
-            conn = self._get_conn()
-            cursor = conn.cursor()
-            
-            # 获取旧备注
-            cursor.execute(_sql('SELECT customer_notes FROM image_tasks WHERE task_id = ?'), (task_id,))
-            row = cursor.fetchone()
-            old_note = row['customer_notes'] if row else ''
-            
-            # 更新备注
-            new_note = f"{old_note}\n[{datetime.now().strftime('%m-%d %H:%M')}] {note}" if old_note else f"[{datetime.now().strftime('%m-%d %H:%M')}] {note}"
-            
-            cursor.execute(_sql('''
-                UPDATE image_tasks 
-                SET customer_notes = ?
-                WHERE task_id = ?
-            '''), (new_note, task_id))
-            
-            # 记录变更历史
-            cursor.execute(_sql('''
-                INSERT INTO task_requirement_changes (
-                    task_id, change_type, old_value, new_value, changed_at, changed_by
-                ) VALUES (?, ?, ?, ?, ?, ?)
-            '''), (
-                task_id,
-                'add_note',
-                old_note or '无',
-                note,
-                _now_str(),
-                changed_by
-            ))
-            
-            conn.commit()
-            conn.close()
-            
-            logger.info(f"客户添加备注成功：{task_id}")
-            return True
-            
-        except Exception as e:
-            logger.error(f"添加客户备注失败：{e}")
-            return False
-    
-    def modify_operation(self, task_id: str, new_operation: str, changed_by: str = 'customer') -> bool:
-        """
-        修改操作类型（客户后续修改需求）
-        
-        Args:
-            task_id: 任务 ID
-            new_operation: 新操作类型
-            changed_by: 修改者
-            
-        Returns:
-            bool: 是否成功
-        """
-        try:
-            conn = self._get_conn()
-            cursor = conn.cursor()
-            
-            # 获取旧操作
-            cursor.execute(_sql('SELECT operation FROM image_tasks WHERE task_id = ?'), (task_id,))
-            row = cursor.fetchone()
-            old_operation = row['operation'] if row else ''
-            
-            # 更新操作
-            cursor.execute(_sql('''
-                UPDATE image_tasks 
-                SET operation = ?
-                WHERE task_id = ?
-            '''), (new_operation, task_id))
-            
-            # 记录变更历史
-            cursor.execute(_sql('''
-                INSERT INTO task_requirement_changes (
-                    task_id, change_type, old_value, new_value, changed_at, changed_by
-                ) VALUES (?, ?, ?, ?, ?, ?)
-            '''), (
-                task_id,
-                'modify_operation',
-                old_operation,
-                new_operation,
-                _now_str(),
-                changed_by
-            ))
-            
-            conn.commit()
-            conn.close()
-            
-            logger.info(f"修改操作类型成功：{task_id} -> {new_operation}")
-            return True
-            
-        except Exception as e:
-            logger.error(f"修改操作类型失败：{e}")
-            return False
-    
-    def get_requirement_history(self, task_id: str) -> List[dict]:
-        """获取需求变更历史"""
-        try:
-            conn = self._get_conn()
-            cursor = conn.cursor()
-            
-            cursor.execute(_sql('''
-                SELECT * FROM task_requirement_changes 
-                WHERE task_id = ?
-                ORDER BY changed_at DESC
-            '''), (task_id,))
-            
-            rows = cursor.fetchall()
-            conn.close()
-            
-            return [dict(row) for row in rows]
-            
-        except Exception as e:
-            logger.error(f"查询需求历史失败：{e}")
-            return []
-    
-    def get_pending_tasks(self) -> List[dict]:
-        """获取所有待处理任务"""
-        return self.get_customer_tasks('', 'pending')
-    
-    def increment_retry(self, task_id: str) -> int:
-        """增加重试次数"""
-        try:
-            conn = self._get_conn()
-            cursor = conn.cursor()
-            
-            cursor.execute(_sql('''
-                UPDATE image_tasks 
-                SET retry_count = retry_count + 1
-                WHERE task_id = ?
-            '''), (task_id,))
-            
-            cursor.execute(_sql('SELECT retry_count FROM image_tasks WHERE task_id = ?'), (task_id,))
-            row = cursor.fetchone()
-            conn.close()
-            
-            return row['retry_count'] if row else 0
-            
-        except Exception as e:
-            logger.error(f"增加重试次数失败：{e}")
-            return 999
 
 # 单例
-_task_manager: Optional[ImageTaskManager] = None
+db = ImageTaskManager()
-
-def get_image_task_manager() -> ImageTaskManager:
-    """获取图片任务管理器单例"""
-    global _task_manager
-    if _task_manager is None:
-        _task_manager = ImageTaskManager()
-    return _task_manager

legacy/customer_db/customers.json

@@ -0,0 +1,889 @@
+{
+  "new_customer_001": {
+    "customer_id": "new_customer_001",
+    "name": "新客户小王",
+    "nickname": "",
+    "email": "",
+    "phone": "",
+    "wechat": "",
+    "address": "",
+    "platform": "",
+    "platform_id": "",
+    "budget": "",
+    "budget_range_min": 0,
+    "budget_range_max": 0,
+    "requirements": [],
+    "preference_services": [],
+    "total_orders": 0,
+    "total_spent": 0,
+    "avg_order_value": 0.0,
+    "purchase_frequency": "",
+    "last_order_date": "",
+    "first_order_date": "",
+    "order_ids": [],
+    "pending_orders": 0,
+    "completed_orders": 0,
+    "refund_count": 0,
+    "personality": [],
+    "communication_prefer": "",
+    "response_speed": "",
+    "patience_level": "",
+    "customer_level": "C",
+    "vip": false,
+    "vip_level": 0,
+    "last_price": 20,
+    "last_price_time": "2026-02-28T15:04:15.181813",
+    "last_quote_no_convert": false,
+    "last_min_price": 0,
+    "last_image_url": "",
+    "last_image_time": "",
+    "last_gemini_prompt": "",
+    "last_aspect_ratio": "1:1",
+    "last_perspective": "no",
+    "processing_status": "",
+    "processing_image_url": "",
+    "expected_done_at": "",
+    "discount_given_count": 0,
+    "lowest_price_accepted": 0,
+    "preferred_format": "jpg",
+    "preferred_size": "",
+    "last_conversation_summary": "",
+    "last_conversation_time": "",
+    "total_images_sent": 0,
+    "complexity_history": [],
+    "image_type_history": [],
+    "price_sensitivity": "",
+    "decision_speed": "",
+    "revision_count": 0,
+    "revision_orders": 0,
+    "total_completed_orders": 0,
+    "bulk_potential": "",
+    "churn_risk": "低",
+    "upsell_opportunity": [],
+    "blacklist": false,
+    "blacklist_reason": "",
+    "vip_custom_price": 0,
+    "last_email_status": "",
+    "good_reviews": 0,
+    "bad_reviews": 0,
+    "dispute_count": 0,
+    "follow_up_by": "",
+    "follow_up_date": "",
+    "next_follow_date": "",
+    "source": "",
+    "coupon_used": "",
+    "notes": [],
+    "tags": [],
+    "created_at": "",
+    "last_contact": "2026-02-28T15:03:57.129715",
+    "last_update": "2026-02-28T15:04:15.184378"
+  },
+  "fast_customer_002": {
+    "customer_id": "fast_customer_002",
+    "name": "爽快老客老李",
+    "nickname": "",
+    "email": "",
+    "phone": "",
+    "wechat": "",
+    "address": "",
+    "platform": "",
+    "platform_id": "",
+    "budget": "",
+    "budget_range_min": 0,
+    "budget_range_max": 0,
+    "requirements": [],
+    "preference_services": [],
+    "total_orders": 8,
+    "total_spent": 280,
+    "avg_order_value": 0.0,
+    "purchase_frequency": "",
+    "last_order_date": "",
+    "first_order_date": "",
+    "order_ids": [],
+    "pending_orders": 0,
+    "completed_orders": 0,
+    "refund_count": 0,
+    "personality": [
+      "爽快"
+    ],
+    "communication_prefer": "",
+    "response_speed": "",
+    "patience_level": "",
+    "customer_level": "C",
+    "vip": false,
+    "vip_level": 0,
+    "last_price": 10,
+    "last_price_time": "2026-02-28T15:06:10.872962",
+    "last_quote_no_convert": false,
+    "last_min_price": 0,
+    "last_image_url": "",
+    "last_image_time": "",
+    "last_gemini_prompt": "",
+    "last_aspect_ratio": "1:1",
+    "last_perspective": "no",
+    "processing_status": "",
+    "processing_image_url": "",
+    "expected_done_at": "",
+    "discount_given_count": 2,
+    "lowest_price_accepted": 10,
+    "preferred_format": "jpg",
+    "preferred_size": "",
+    "last_conversation_summary": "",
+    "last_conversation_time": "",
+    "total_images_sent": 0,
+    "complexity_history": [],
+    "image_type_history": [],
+    "price_sensitivity": "中",
+    "decision_speed": "快",
+    "revision_count": 0,
+    "revision_orders": 0,
+    "total_completed_orders": 8,
+    "bulk_potential": "",
+    "churn_risk": "低",
+    "upsell_opportunity": [],
+    "blacklist": false,
+    "blacklist_reason": "",
+    "vip_custom_price": 0,
+    "last_email_status": "",
+    "good_reviews": 0,
+    "bad_reviews": 0,
+    "dispute_count": 0,
+    "follow_up_by": "",
+    "follow_up_date": "",
+    "next_follow_date": "",
+    "source": "",
+    "coupon_used": "",
+    "notes": [],
+    "tags": [],
+    "created_at": "",
+    "last_contact": "2026-02-28T15:03:57.131384",
+    "last_update": "2026-02-28T15:06:10.875534"
+  },
+  "bargainer_003": {
+    "customer_id": "bargainer_003",
+    "name": "砍价王小张",
+    "nickname": "",
+    "email": "",
+    "phone": "",
+    "wechat": "",
+    "address": "",
+    "platform": "",
+    "platform_id": "",
+    "budget": "",
+    "budget_range_min": 0,
+    "budget_range_max": 0,
+    "requirements": [],
+    "preference_services": [],
+    "total_orders": 3,
+    "total_spent": 45,
+    "avg_order_value": 0.0,
+    "purchase_frequency": "",
+    "last_order_date": "",
+    "first_order_date": "",
+    "order_ids": [],
+    "pending_orders": 0,
+    "completed_orders": 0,
+    "refund_count": 0,
+    "personality": [
+      "砍价狂",
+      "纠结"
+    ],
+    "communication_prefer": "",
+    "response_speed": "",
+    "patience_level": "",
+    "customer_level": "C",
+    "vip": false,
+    "vip_level": 0,
+    "last_price": 10,
+    "last_price_time": "2026-02-28T15:05:45.067204",
+    "last_quote_no_convert": false,
+    "last_min_price": 0,
+    "last_image_url": "",
+    "last_image_time": "",
+    "last_gemini_prompt": "",
+    "last_aspect_ratio": "1:1",
+    "last_perspective": "no",
+    "processing_status": "",
+    "processing_image_url": "",
+    "expected_done_at": "",
+    "discount_given_count": 6,
+    "lowest_price_accepted": 10,
+    "preferred_format": "jpg",
+    "preferred_size": "",
+    "last_conversation_summary": "",
+    "last_conversation_time": "",
+    "total_images_sent": 0,
+    "complexity_history": [],
+    "image_type_history": [],
+    "price_sensitivity": "高",
+    "decision_speed": "慢",
+    "revision_count": 0,
+    "revision_orders": 0,
+    "total_completed_orders": 0,
+    "bulk_potential": "",
+    "churn_risk": "低",
+    "upsell_opportunity": [],
+    "blacklist": false,
+    "blacklist_reason": "",
+    "vip_custom_price": 0,
+    "last_email_status": "",
+    "good_reviews": 0,
+    "bad_reviews": 0,
+    "dispute_count": 0,
+    "follow_up_by": "",
+    "follow_up_date": "",
+    "next_follow_date": "",
+    "source": "",
+    "coupon_used": "",
+    "notes": [],
+    "tags": [],
+    "created_at": "",
+    "last_contact": "2026-02-28T15:03:57.132648",
+    "last_update": "2026-02-28T15:05:45.071818"
+  },
+  "vip_customer_004": {
+    "customer_id": "vip_customer_004",
+    "name": "VIP客户陈总",
+    "nickname": "",
+    "email": "",
+    "phone": "",
+    "wechat": "",
+    "address": "",
+    "platform": "",
+    "platform_id": "",
+    "budget": "",
+    "budget_range_min": 0,
+    "budget_range_max": 0,
+    "requirements": [],
+    "preference_services": [],
+    "total_orders": 15,
+    "total_spent": 680,
+    "avg_order_value": 0.0,
+    "purchase_frequency": "",
+    "last_order_date": "",
+    "first_order_date": "",
+    "order_ids": [],
+    "pending_orders": 0,
+    "completed_orders": 0,
+    "refund_count": 0,
+    "personality": [
+      "爽快"
+    ],
+    "communication_prefer": "",
+    "response_speed": "",
+    "patience_level": "",
+    "customer_level": "A",
+    "vip": true,
+    "vip_level": 2,
+    "last_price": 20,
+    "last_price_time": "2026-02-28T15:04:56.155844",
+    "last_quote_no_convert": false,
+    "last_min_price": 0,
+    "last_image_url": "",
+    "last_image_time": "",
+    "last_gemini_prompt": "",
+    "last_aspect_ratio": "1:1",
+    "last_perspective": "no",
+    "processing_status": "",
+    "processing_image_url": "",
+    "expected_done_at": "",
+    "discount_given_count": 0,
+    "lowest_price_accepted": 0,
+    "preferred_format": "jpg",
+    "preferred_size": "",
+    "last_conversation_summary": "",
+    "last_conversation_time": "",
+    "total_images_sent": 0,
+    "complexity_history": [],
+    "image_type_history": [],
+    "price_sensitivity": "低",
+    "decision_speed": "快",
+    "revision_count": 0,
+    "revision_orders": 0,
+    "total_completed_orders": 0,
+    "bulk_potential": "",
+    "churn_risk": "低",
+    "upsell_opportunity": [],
+    "blacklist": false,
+    "blacklist_reason": "",
+    "vip_custom_price": 18,
+    "last_email_status": "",
+    "good_reviews": 0,
+    "bad_reviews": 0,
+    "dispute_count": 0,
+    "follow_up_by": "",
+    "follow_up_date": "",
+    "next_follow_date": "",
+    "source": "",
+    "coupon_used": "",
+    "notes": [],
+    "tags": [],
+    "created_at": "",
+    "last_contact": "2026-02-28T15:03:57.134104",
+    "last_update": "2026-02-28T15:04:56.158233"
+  },
+  "high_value_005": {
+    "customer_id": "high_value_005",
+    "name": "高价值客户刘老板",
+    "nickname": "",
+    "email": "",
+    "phone": "",
+    "wechat": "",
+    "address": "",
+    "platform": "",
+    "platform_id": "",
+    "budget": "",
+    "budget_range_min": 0,
+    "budget_range_max": 0,
+    "requirements": [],
+    "preference_services": [],
+    "total_orders": 20,
+    "total_spent": 1200,
+    "avg_order_value": 60,
+    "purchase_frequency": "",
+    "last_order_date": "",
+    "first_order_date": "",
+    "order_ids": [],
+    "pending_orders": 0,
+    "completed_orders": 0,
+    "refund_count": 0,
+    "personality": [
+      "爽快"
+    ],
+    "communication_prefer": "",
+    "response_speed": "",
+    "patience_level": "",
+    "customer_level": "A",
+    "vip": false,
+    "vip_level": 0,
+    "last_price": 20,
+    "last_price_time": "2026-02-28T15:05:11.156030",
+    "last_quote_no_convert": false,
+    "last_min_price": 0,
+    "last_image_url": "",
+    "last_image_time": "",
+    "last_gemini_prompt": "",
+    "last_aspect_ratio": "1:1",
+    "last_perspective": "no",
+    "processing_status": "",
+    "processing_image_url": "",
+    "expected_done_at": "",
+    "discount_given_count": 0,
+    "lowest_price_accepted": 0,
+    "preferred_format": "jpg",
+    "preferred_size": "",
+    "last_conversation_summary": "",
+    "last_conversation_time": "",
+    "total_images_sent": 0,
+    "complexity_history": [],
+    "image_type_history": [],
+    "price_sensitivity": "低",
+    "decision_speed": "快",
+    "revision_count": 0,
+    "revision_orders": 0,
+    "total_completed_orders": 0,
+    "bulk_potential": "",
+    "churn_risk": "低",
+    "upsell_opportunity": [],
+    "blacklist": false,
+    "blacklist_reason": "",
+    "vip_custom_price": 0,
+    "last_email_status": "",
+    "good_reviews": 0,
+    "bad_reviews": 0,
+    "dispute_count": 0,
+    "follow_up_by": "",
+    "follow_up_date": "",
+    "next_follow_date": "",
+    "source": "",
+    "coupon_used": "",
+    "notes": [],
+    "tags": [],
+    "created_at": "",
+    "last_contact": "2026-02-28T15:03:57.135396",
+    "last_update": "2026-02-28T15:05:11.160004"
+  },
+  "blacklist_006": {
+    "customer_id": "blacklist_006",
+    "name": "黑名单客户",
+    "nickname": "",
+    "email": "",
+    "phone": "",
+    "wechat": "",
+    "address": "",
+    "platform": "",
+    "platform_id": "",
+    "budget": "",
+    "budget_range_min": 0,
+    "budget_range_max": 0,
+    "requirements": [],
+    "preference_services": [],
+    "total_orders": 0,
+    "total_spent": 0.0,
+    "avg_order_value": 0.0,
+    "purchase_frequency": "",
+    "last_order_date": "",
+    "first_order_date": "",
+    "order_ids": [],
+    "pending_orders": 0,
+    "completed_orders": 0,
+    "refund_count": 0,
+    "personality": [],
+    "communication_prefer": "",
+    "response_speed": "",
+    "patience_level": "",
+    "customer_level": "C",
+    "vip": false,
+    "vip_level": 0,
+    "last_price": 0,
+    "last_price_time": "",
+    "last_quote_no_convert": false,
+    "last_min_price": 0,
+    "last_image_url": "",
+    "last_image_time": "",
+    "last_gemini_prompt": "",
+    "last_aspect_ratio": "1:1",
+    "last_perspective": "no",
+    "processing_status": "",
+    "processing_image_url": "",
+    "expected_done_at": "",
+    "discount_given_count": 0,
+    "lowest_price_accepted": 0,
+    "preferred_format": "jpg",
+    "preferred_size": "",
+    "last_conversation_summary": "",
+    "last_conversation_time": "",
+    "total_images_sent": 0,
+    "complexity_history": [],
+    "image_type_history": [],
+    "price_sensitivity": "",
+    "decision_speed": "",
+    "revision_count": 0,
+    "revision_orders": 0,
+    "total_completed_orders": 0,
+    "bulk_potential": "",
+    "churn_risk": "低",
+    "upsell_opportunity": [],
+    "blacklist": true,
+    "blacklist_reason": "恶意投诉多次",
+    "vip_custom_price": 0,
+    "last_email_status": "",
+    "good_reviews": 0,
+    "bad_reviews": 0,
+    "dispute_count": 0,
+    "follow_up_by": "",
+    "follow_up_date": "",
+    "next_follow_date": "",
+    "source": "",
+    "coupon_used": "",
+    "notes": [],
+    "tags": [],
+    "created_at": "",
+    "last_contact": "2026-02-28T15:03:57.136490",
+    "last_update": "2026-02-28T15:05:27.155220"
+  },
+  "test_new_001": {
+    "customer_id": "test_new_001",
+    "name": "新客户小王",
+    "nickname": "",
+    "email": "",
+    "phone": "",
+    "wechat": "",
+    "address": "",
+    "platform": "",
+    "platform_id": "",
+    "budget": "",
+    "budget_range_min": 0,
+    "budget_range_max": 0,
+    "requirements": [],
+    "preference_services": [],
+    "total_orders": 0,
+    "total_spent": 0,
+    "avg_order_value": 0.0,
+    "purchase_frequency": "",
+    "last_order_date": "",
+    "first_order_date": "",
+    "order_ids": [],
+    "pending_orders": 0,
+    "completed_orders": 0,
+    "refund_count": 0,
+    "personality": [],
+    "communication_prefer": "",
+    "response_speed": "",
+    "patience_level": "",
+    "customer_level": "C",
+    "vip": false,
+    "vip_level": 0,
+    "last_price": 0,
+    "last_price_time": "2026-02-28T15:27:40.801329",
+    "last_quote_no_convert": false,
+    "last_min_price": 0,
+    "last_image_url": "",
+    "last_image_time": "",
+    "last_gemini_prompt": "",
+    "last_aspect_ratio": "1:1",
+    "last_perspective": "no",
+    "processing_status": "",
+    "processing_image_url": "",
+    "expected_done_at": "",
+    "discount_given_count": 0,
+    "lowest_price_accepted": 0,
+    "preferred_format": "jpg",
+    "preferred_size": "",
+    "last_conversation_summary": "",
+    "last_conversation_time": "",
+    "total_images_sent": 0,
+    "complexity_history": [],
+    "image_type_history": [],
+    "price_sensitivity": "",
+    "decision_speed": "",
+    "revision_count": 0,
+    "revision_orders": 0,
+    "total_completed_orders": 0,
+    "bulk_potential": "",
+    "churn_risk": "低",
+    "upsell_opportunity": [],
+    "blacklist": false,
+    "blacklist_reason": "",
+    "vip_custom_price": 0,
+    "last_email_status": "",
+    "good_reviews": 0,
+    "bad_reviews": 0,
+    "dispute_count": 0,
+    "follow_up_by": "",
+    "follow_up_date": "",
+    "next_follow_date": "",
+    "source": "",
+    "coupon_used": "",
+    "notes": [],
+    "tags": [],
+    "created_at": "",
+    "last_contact": "2026-02-28T15:29:05.719291",
+    "last_update": "2026-02-28T15:29:05.719308"
+  },
+  "test_fast_002": {
+    "customer_id": "test_fast_002",
+    "name": "爽快老客老李",
+    "nickname": "",
+    "email": "",
+    "phone": "",
+    "wechat": "",
+    "address": "",
+    "platform": "",
+    "platform_id": "",
+    "budget": "",
+    "budget_range_min": 0,
+    "budget_range_max": 0,
+    "requirements": [],
+    "preference_services": [],
+    "total_orders": 8,
+    "total_spent": 280,
+    "avg_order_value": 0.0,
+    "purchase_frequency": "",
+    "last_order_date": "",
+    "first_order_date": "",
+    "order_ids": [],
+    "pending_orders": 0,
+    "completed_orders": 0,
+    "refund_count": 0,
+    "personality": [
+      "爽快"
+    ],
+    "communication_prefer": "",
+    "response_speed": "",
+    "patience_level": "",
+    "customer_level": "C",
+    "vip": false,
+    "vip_level": 0,
+    "last_price": 25,
+    "last_price_time": "",
+    "last_quote_no_convert": false,
+    "last_min_price": 0,
+    "last_image_url": "",
+    "last_image_time": "",
+    "last_gemini_prompt": "",
+    "last_aspect_ratio": "1:1",
+    "last_perspective": "no",
+    "processing_status": "",
+    "processing_image_url": "",
+    "expected_done_at": "",
+    "discount_given_count": 0,
+    "lowest_price_accepted": 0,
+    "preferred_format": "",
+    "preferred_size": "",
+    "last_conversation_summary": "",
+    "last_conversation_time": "",
+    "total_images_sent": 0,
+    "complexity_history": [],
+    "image_type_history": [],
+    "price_sensitivity": "低",
+    "decision_speed": "快",
+    "revision_count": 0,
+    "revision_orders": 0,
+    "total_completed_orders": 8,
+    "bulk_potential": "",
+    "churn_risk": "",
+    "upsell_opportunity": [],
+    "blacklist": false,
+    "blacklist_reason": "",
+    "vip_custom_price": 0,
+    "last_email_status": "",
+    "good_reviews": 0,
+    "bad_reviews": 0,
+    "dispute_count": 0,
+    "follow_up_by": "",
+    "follow_up_date": "",
+    "next_follow_date": "",
+    "source": "",
+    "coupon_used": "",
+    "notes": [],
+    "tags": [],
+    "created_at": "",
+    "last_contact": "2026-02-28T15:29:05.720944",
+    "last_update": "2026-02-28T15:29:05.720948"
+  },
+  "test_bargain_003": {
+    "customer_id": "test_bargain_003",
+    "name": "砍价王小张",
+    "nickname": "",
+    "email": "",
+    "phone": "",
+    "wechat": "",
+    "address": "",
+    "platform": "",
+    "platform_id": "",
+    "budget": "",
+    "budget_range_min": 0,
+    "budget_range_max": 0,
+    "requirements": [],
+    "preference_services": [],
+    "total_orders": 3,
+    "total_spent": 45,
+    "avg_order_value": 0.0,
+    "purchase_frequency": "",
+    "last_order_date": "",
+    "first_order_date": "",
+    "order_ids": [],
+    "pending_orders": 0,
+    "completed_orders": 0,
+    "refund_count": 0,
+    "personality": [
+      "砍价狂",
+      "纠结"
+    ],
+    "communication_prefer": "",
+    "response_speed": "",
+    "patience_level": "",
+    "customer_level": "C",
+    "vip": false,
+    "vip_level": 0,
+    "last_price": 15,
+    "last_price_time": "",
+    "last_quote_no_convert": false,
+    "last_min_price": 0,
+    "last_image_url": "",
+    "last_image_time": "",
+    "last_gemini_prompt": "",
+    "last_aspect_ratio": "1:1",
+    "last_perspective": "no",
+    "processing_status": "",
+    "processing_image_url": "",
+    "expected_done_at": "",
+    "discount_given_count": 4,
+    "lowest_price_accepted": 15,
+    "preferred_format": "",
+    "preferred_size": "",
+    "last_conversation_summary": "",
+    "last_conversation_time": "",
+    "total_images_sent": 0,
+    "complexity_history": [],
+    "image_type_history": [],
+    "price_sensitivity": "高",
+    "decision_speed": "慢",
+    "revision_count": 0,
+    "revision_orders": 0,
+    "total_completed_orders": 0,
+    "bulk_potential": "",
+    "churn_risk": "",
+    "upsell_opportunity": [],
+    "blacklist": false,
+    "blacklist_reason": "",
+    "vip_custom_price": 0,
+    "last_email_status": "",
+    "good_reviews": 0,
+    "bad_reviews": 0,
+    "dispute_count": 0,
+    "follow_up_by": "",
+    "follow_up_date": "",
+    "next_follow_date": "",
+    "source": "",
+    "coupon_used": "",
+    "notes": [],
+    "tags": [],
+    "created_at": "",
+    "last_contact": "2026-02-28T15:29:05.722448",
+    "last_update": "2026-02-28T15:29:05.722454"
+  },
+  "test_vip_004": {
+    "customer_id": "test_vip_004",
+    "name": "VIP 客户陈总",
+    "nickname": "",
+    "email": "",
+    "phone": "",
+    "wechat": "",
+    "address": "",
+    "platform": "",
+    "platform_id": "",
+    "budget": "",
+    "budget_range_min": 0,
+    "budget_range_max": 0,
+    "requirements": [],
+    "preference_services": [],
+    "total_orders": 15,
+    "total_spent": 680,
+    "avg_order_value": 0.0,
+    "purchase_frequency": "",
+    "last_order_date": "",
+    "first_order_date": "",
+    "order_ids": [],
+    "pending_orders": 0,
+    "completed_orders": 0,
+    "refund_count": 0,
+    "personality": [
+      "爽快"
+    ],
+    "communication_prefer": "",
+    "response_speed": "",
+    "patience_level": "",
+    "customer_level": "A",
+    "vip": true,
+    "vip_level": 2,
+    "last_price": 0,
+    "last_price_time": "",
+    "last_quote_no_convert": false,
+    "last_min_price": 0,
+    "last_image_url": "",
+    "last_image_time": "",
+    "last_gemini_prompt": "",
+    "last_aspect_ratio": "1:1",
+    "last_perspective": "no",
+    "processing_status": "",
+    "processing_image_url": "",
+    "expected_done_at": "",
+    "discount_given_count": 0,
+    "lowest_price_accepted": 0,
+    "preferred_format": "",
+    "preferred_size": "",
+    "last_conversation_summary": "",
+    "last_conversation_time": "",
+    "total_images_sent": 0,
+    "complexity_history": [],
+    "image_type_history": [],
+    "price_sensitivity": "低",
+    "decision_speed": "快",
+    "revision_count": 0,
+    "revision_orders": 0,
+    "total_completed_orders": 0,
+    "bulk_potential": "",
+    "churn_risk": "",
+    "upsell_opportunity": [],
+    "blacklist": false,
+    "blacklist_reason": "",
+    "vip_custom_price": 18,
+    "last_email_status": "",
+    "good_reviews": 0,
+    "bad_reviews": 0,
+    "dispute_count": 0,
+    "follow_up_by": "",
+    "follow_up_date": "",
+    "next_follow_date": "",
+    "source": "",
+    "coupon_used": "",
+    "notes": [],
+    "tags": [],
+    "created_at": "",
+    "last_contact": "2026-02-28T15:29:05.723887",
+    "last_update": "2026-02-28T15:29:05.723890"
+  },
+  "test_highvalue_005": {
+    "customer_id": "test_highvalue_005",
+    "name": "高价值客户刘老板",
+    "nickname": "",
+    "email": "",
+    "phone": "",
+    "wechat": "",
+    "address": "",
+    "platform": "",
+    "platform_id": "",
+    "budget": "",
+    "budget_range_min": 0,
+    "budget_range_max": 0,
+    "requirements": [],
+    "preference_services": [],
+    "total_orders": 20,
+    "total_spent": 1200,
+    "avg_order_value": 60,
+    "purchase_frequency": "",
+    "last_order_date": "",
+    "first_order_date": "",
+    "order_ids": [],
+    "pending_orders": 0,
+    "completed_orders": 0,
+    "refund_count": 0,
+    "personality": [
+      "爽快"
+    ],
+    "communication_prefer": "",
+    "response_speed": "",
+    "patience_level": "",
+    "customer_level": "A",
+    "vip": false,
+    "vip_level": 0,
+    "last_price": 0,
+    "last_price_time": "",
+    "last_quote_no_convert": false,
+    "last_min_price": 0,
+    "last_image_url": "",
+    "last_image_time": "",
+    "last_gemini_prompt": "",
+    "last_aspect_ratio": "1:1",
+    "last_perspective": "no",
+    "processing_status": "",
+    "processing_image_url": "",
+    "expected_done_at": "",
+    "discount_given_count": 0,
+    "lowest_price_accepted": 0,
+    "preferred_format": "",
+    "preferred_size": "",
+    "last_conversation_summary": "",
+    "last_conversation_time": "",
+    "total_images_sent": 0,
+    "complexity_history": [],
+    "image_type_history": [],
+    "price_sensitivity": "低",
+    "decision_speed": "快",
+    "revision_count": 0,
+    "revision_orders": 0,
+    "total_completed_orders": 0,
+    "bulk_potential": "",
+    "churn_risk": "",
+    "upsell_opportunity": [],
+    "blacklist": false,
+    "blacklist_reason": "",
+    "vip_custom_price": 0,
+    "last_email_status": "",
+    "good_reviews": 0,
+    "bad_reviews": 0,
+    "dispute_count": 0,
+    "follow_up_by": "",
+    "follow_up_date": "",
+    "next_follow_date": "",
+    "source": "",
+    "coupon_used": "",
+    "notes": [],
+    "tags": [],
+    "created_at": "",
+    "last_contact": "2026-02-28T15:29:05.725313",
+    "last_update": "2026-02-28T15:29:05.725316"
+  }
+}