refactor: extract profile and context builders from pydantic agent

core/context_helpers.py

@@ -0,0 +1,225 @@
+from __future__ import annotations
+
+import os
+from collections import Counter
+from datetime import datetime
+
+
+def calc_avg_complexity(complexity_history: list) -> str:
+    """计算平均复杂度。"""
+    if not complexity_history:
+        return "未知"
+    level_map = {"simple": 1, "normal": 2, "complex": 3, "hard": 4}
+    label_map = {1: "简单", 2: "一般", 3: "复杂", 4: "很复杂"}
+    try:
+        avg = sum(level_map.get(c, 2) for c in complexity_history) / len(complexity_history)
+        return label_map.get(round(avg), "一般")
+    except Exception:
+        return "一般"
+
+
+def get_customer_profile_context(agent, customer_id: str) -> str:
+    """从数据库读取客户画像，注入给 AI。含个性化语气、报价策略、主动预测、近期对话。"""
+    try:
+        from db.customer_db import db
+
+        profile = db.get_customer(customer_id)
+
+        if profile.blacklist:
+            return f"【⚠️黑名单客户】原因：{profile.blacklist_reason or '已标记'}，请转接人工处理，不要自动回复"
+
+        lines = []
+        lines.append("=== 客户档案 ===")
+
+        basic_info = []
+        basic_info.append(f"客户ID: {customer_id}")
+        basic_info.append(f"姓名: {profile.name or '未知'}")
+        if profile.email:
+            basic_info.append(f"邮箱: {profile.email}")
+        if profile.phone:
+            basic_info.append(f"电话: {profile.phone}")
+        if profile.wechat:
+            basic_info.append(f"微信: {profile.wechat}")
+        lines.append(" | ".join(basic_info))
+
+        consume_info = []
+        consume_info.append(f"客户等级: {profile.customer_level}级")
+        if profile.vip:
+            consume_info.append("VIP客户")
+        consume_info.append(f"总订单: {profile.total_orders}单")
+        consume_info.append(f"总消费: {profile.total_spent}元")
+        if profile.total_orders > 0:
+            consume_info.append(f"客单价: {profile.total_spent // profile.total_orders}元")
+        lines.append("--- 消费分析 ---")
+        lines.append(" | ".join(consume_info))
+
+        price_info = []
+        if profile.vip_custom_price:
+            price_info.append(f"VIP专属价: {profile.vip_custom_price}元（直接报这个价）")
+        if profile.last_price:
+            price_info.append(f"上次报价: {profile.last_price}元")
+        if profile.lowest_price_accepted:
+            price_info.append(f"历史最低成交: {profile.lowest_price_accepted}元")
+        if profile.discount_given_count:
+            price_info.append(f"历史让价: {profile.discount_given_count}次")
+        if profile.price_sensitivity:
+            price_info.append(f"价格敏感度: {profile.price_sensitivity}")
+        if getattr(profile, "last_quote_no_convert", False):
+            price_info.append("【策略】上次报价未成交，本次可降5-10元")
+        if price_info:
+            lines.append("--- 报价历史 ---")
+            lines.append(" | ".join(price_info))
+
+        personality_info = []
+        if profile.personality:
+            personality_info.append(f"性格: {'/'.join(profile.personality)}")
+        if profile.decision_speed:
+            personality_info.append(f"决策速度: {profile.decision_speed}")
+        if profile.communication_prefer:
+            personality_info.append(f"沟通偏好: {profile.communication_prefer}")
+        if personality_info:
+            lines.append("--- 性格特征 ---")
+            lines.append(" | ".join(personality_info))
+
+        image_info = []
+        image_info.append(f"累计发图: {profile.total_images_sent}张")
+        if profile.complexity_history:
+            image_info.append(f"平均复杂度: {calc_avg_complexity(profile.complexity_history)}")
+        if profile.image_type_history:
+            top_types = Counter(profile.image_type_history).most_common(3)
+            types_str = "、".join(f"{t}({c}次)" for t, c in top_types)
+            image_info.append(f"常见类型: {types_str}")
+        if profile.preferred_format:
+            image_info.append(f"格式偏好: {profile.preferred_format}")
+        if profile.preferred_size:
+            image_info.append(f"尺寸要求: {profile.preferred_size}")
+        if profile.last_image_url:
+            image_info.append(f"最近发图: {profile.last_image_url[:60]}...")
+        lines.append("--- 图片习惯 ---")
+        lines.append(" | ".join(image_info))
+
+        if profile.processing_status:
+            task_info = []
+            task_info.append(f"状态: {profile.processing_status}")
+            if profile.processing_image_url:
+                task_info.append(f"处理中: {profile.processing_image_url[:40]}...")
+            if profile.expected_done_at:
+                task_info.append(f"预计完成: {profile.expected_done_at}")
+            lines.append("--- 当前任务 ---")
+            lines.append(" | ".join(task_info))
+
+        if profile.last_conversation_summary:
+            time_str = ""
+            if profile.last_conversation_time:
+                try:
+                    t = datetime.fromisoformat(profile.last_conversation_time)
+                    diff = datetime.now() - t
+                    if diff.days > 0:
+                        time_str = f"（{diff.days}天前）"
+                    else:
+                        h = diff.seconds // 3600
+                        time_str = f"（{h}小时前）" if h > 0 else "（刚刚）"
+                except Exception:
+                    pass
+            lines.append(f"--- 上次对话 {time_str} ---")
+            lines.append(profile.last_conversation_summary)
+
+        hints = []
+        if profile.personality:
+            if "爽快" in profile.personality:
+                hints.append("回复简洁直接，不废话，快速报价")
+            if "砍价" in profile.personality or "砍价狂" in profile.personality:
+                hints.append("报价时强调性价比，只让价一次，第二次引导去 xinhui.cloud")
+            if "纠结" in profile.personality or "墨迹" in profile.personality:
+                hints.append("多给一点说明，耐心回答")
+        if profile.price_sensitivity == "高":
+            hints.append("报价时顺带提「满意再拍」降低顾虑")
+        if profile.decision_speed == "快":
+            hints.append("直接报价推成交，少铺垫")
+        if profile.total_orders > 0 and profile.decision_speed == "快":
+            hints.append("老客爽快，直接报价成交")
+        if hints:
+            lines.append("--- 回复策略 ---")
+            lines.append("；".join(hints))
+
+        proactive = []
+        if profile.bulk_potential == "有" or (profile.total_images_sent or 0) >= 2:
+            proactive.append("可问「要做多张吗，多张有优惠」")
+        if profile.upsell_opportunity:
+            proactive.append(f"加购机会: {'、'.join(profile.upsell_opportunity)}")
+        if proactive:
+            lines.append("--- 主动推荐 ---")
+            lines.append("；".join(proactive))
+
+        return "\n".join(lines)
+    except Exception as e:
+        print(f"[Agent] 获取客户画像失败: {e}")
+        return ""
+
+
+def get_refusal_context_hint(agent, customer_id: str, current_msg: str, profile_context: str) -> str:
+    """
+    检测「刚拒绝某张图 + 客户问能找到吗」场景，注入显式提示，避免前后矛盾。
+    """
+    ask_keywords = ["能找到吗", "可以吗", "有吗", "能做吗", "可以找吗", "可以弄吗"]
+    if not any(kw in current_msg for kw in ask_keywords):
+        return ""
+    refusal_keywords = ["不做", "不接", "拒绝", "不做这类", "这类不做"]
+    if any(kw in profile_context for kw in refusal_keywords):
+        return "【重要】上一句客服刚拒绝了某张图，客户问能找到吗时须明确：能做的是哪张（如第一张），不能做的是哪张。不可只说「放心拍」「可以」，会前后矛盾。"
+    history = getattr(agent, "message_histories", {}).get(customer_id, [])
+    for msg in reversed(history[-6:]):
+        msg_str = str(msg)
+        if any(kw in msg_str for kw in refusal_keywords):
+            return "【重要】上一句客服刚拒绝了某张图，客户问能找到吗时须明确：能做的是哪张（如第一张），不能做的是哪张。不可只说「放心拍」「可以」，会前后矛盾。"
+    return ""
+
+
+def get_conversation_context(customer_id: str, acc_id: str = "", limit: int = 12, max_len: int = 80) -> str:
+    """每一次对话都从数据库加载近期对话，压缩后注入 prompt。"""
+    try:
+        try:
+            from config.config import CHAT_CONTEXT_LIMIT, CHAT_CONTEXT_TRUNCATE_LEN
+
+            limit = CHAT_CONTEXT_LIMIT
+            max_len = CHAT_CONTEXT_TRUNCATE_LEN
+        except Exception:
+            pass
+        from db.chat_log_db import get_recent_conversation
+
+        msgs = get_recent_conversation(customer_id, acc_id=acc_id, limit=limit)
+        if not msgs:
+            return ""
+        lines = []
+        for m in msgs:
+            role = "客" if m.get("direction") == "in" else "服"
+            msg_text = (m.get("message") or "").strip().replace("\n", " ")[:max_len]
+            if not msg_text:
+                continue
+            lines.append(f"{role}:{msg_text}")
+        if not lines:
+            return ""
+        return "【近期】\n" + "\n".join(lines) + "\n\n"
+    except Exception:
+        return ""
+
+
+def get_intent_emotion_hint(msg: str) -> str:
+    """语义匹配：意图/情绪识别，注入提示。EMBEDDING_MODEL 未配置时用关键词。"""
+    try:
+        from utils.intent_analyzer import detect_emotion_embedding, detect_intent_embedding, detect_intent_keywords
+
+        intent = detect_intent_embedding(msg)
+        if not intent:
+            intent = detect_intent_keywords(msg)
+        emotion = detect_emotion_embedding(msg) if os.getenv("EMBEDDING_MODEL") else None
+        parts = []
+        if intent:
+            parts.append(f"意图:{intent}")
+        if emotion:
+            parts.append(f"情绪:{emotion}")
+        if parts:
+            return f"【当前消息】{', '.join(parts)}"
+    except Exception:
+        pass
+    return ""

core/pydantic_ai_agent.py

@@ -59,6 +59,13 @@ from core.agent_prompts import (
     build_system_prompt,
 )
 from core.risk_text_helpers import is_map_inquiry, is_political_inquiry
+from core.context_helpers import (
+    calc_avg_complexity,
+    get_conversation_context,
+    get_customer_profile_context,
+    get_intent_emotion_hint,
+    get_refusal_context_hint,
+)
 
 load_dotenv()
 
@@ -1380,233 +1387,15 @@ class CustomerServiceAgent:
     _is_political_inquiry = staticmethod(is_political_inquiry)
     _is_map_inquiry = staticmethod(is_map_inquiry)
 
+    _calc_avg_complexity = staticmethod(calc_avg_complexity)
+    _get_conversation_context = staticmethod(get_conversation_context)
+    _get_intent_emotion_hint = staticmethod(get_intent_emotion_hint)
+
     def _get_customer_profile_context(self, customer_id: str) -> str:
-        """从数据库读取客户画像，注入给 AI。含个性化语气、报价策略、主动预测、近期对话。"""
+        return get_customer_profile_context(self, customer_id)
-        try:
-            from db.customer_db import db
-            profile = db.get_customer(customer_id)
-
-            if profile.blacklist:
-                return f"【⚠️黑名单客户】原因：{profile.blacklist_reason or '已标记'}，请转接人工处理，不要自动回复"
-
-            lines = []
-            lines.append("=== 客户档案 ===")
-            
-            # 基础信息
-            basic_info = []
-            basic_info.append(f"客户ID: {customer_id}")
-            basic_info.append(f"姓名: {profile.name or '未知'}")
-            if profile.email:
-                basic_info.append(f"邮箱: {profile.email}")
-            if profile.phone:
-                basic_info.append(f"电话: {profile.phone}")
-            if profile.wechat:
-                basic_info.append(f"微信: {profile.wechat}")
-            lines.append(" | ".join(basic_info))
-            
-            # 消费分析
-            consume_info = []
-            consume_info.append(f"客户等级: {profile.customer_level}级")
-            if profile.vip:
-                consume_info.append("VIP客户")
-            consume_info.append(f"总订单: {profile.total_orders}单")
-            consume_info.append(f"总消费: {profile.total_spent}元")
-            if profile.total_orders > 0:
-                consume_info.append(f"客单价: {profile.total_spent // profile.total_orders}元")
-            lines.append("--- 消费分析 ---")
-            lines.append(" | ".join(consume_info))
-            
-            # 报价历史
-            price_info = []
-            if profile.vip_custom_price:
-                price_info.append(f"VIP专属价: {profile.vip_custom_price}元（直接报这个价）")
-            if profile.last_price:
-                price_info.append(f"上次报价: {profile.last_price}元")
-            if profile.lowest_price_accepted:
-                price_info.append(f"历史最低成交: {profile.lowest_price_accepted}元")
-            if profile.discount_given_count:
-                price_info.append(f"历史让价: {profile.discount_given_count}次")
-            if profile.price_sensitivity:
-                price_info.append(f"价格敏感度: {profile.price_sensitivity}")
-            if getattr(profile, "last_quote_no_convert", False):
-                price_info.append("【策略】上次报价未成交，本次可降5-10元")
-            if price_info:
-                lines.append("--- 报价历史 ---")
-                lines.append(" | ".join(price_info))
-            
-            # 性格与决策
-            personality_info = []
-            if profile.personality:
-                personality_info.append(f"性格: {'/'.join(profile.personality)}")
-            if profile.decision_speed:
-                personality_info.append(f"决策速度: {profile.decision_speed}")
-            if profile.communication_prefer:
-                personality_info.append(f"沟通偏好: {profile.communication_prefer}")
-            if personality_info:
-                lines.append("--- 性格特征 ---")
-                lines.append(" | ".join(personality_info))
-            
-            # 图片习惯
-            image_info = []
-            image_info.append(f"累计发图: {profile.total_images_sent}张")
-            if profile.complexity_history:
-                avg_complexity = self._calc_avg_complexity(profile.complexity_history)
-                image_info.append(f"平均复杂度: {avg_complexity}")
-            if profile.image_type_history:
-                from collections import Counter
-                top_types = Counter(profile.image_type_history).most_common(3)
-                types_str = "、".join(f"{t}({c}次)" for t, c in top_types)
-                image_info.append(f"常见类型: {types_str}")
-            if profile.preferred_format:
-                image_info.append(f"格式偏好: {profile.preferred_format}")
-            if profile.preferred_size:
-                image_info.append(f"尺寸要求: {profile.preferred_size}")
-            if profile.last_image_url:
-                image_info.append(f"最近发图: {profile.last_image_url[:60]}...")
-            lines.append("--- 图片习惯 ---")
-            lines.append(" | ".join(image_info))
-            
-            # 当前任务状态
-            if profile.processing_status:
-                task_info = []
-                task_info.append(f"状态: {profile.processing_status}")
-                if profile.processing_image_url:
-                    task_info.append(f"处理中: {profile.processing_image_url[:40]}...")
-                if profile.expected_done_at:
-                    task_info.append(f"预计完成: {profile.expected_done_at}")
-                lines.append("--- 当前任务 ---")
-                lines.append(" | ".join(task_info))
-            
-            # 上次对话摘要
-            if profile.last_conversation_summary:
-                time_str = ""
-                if profile.last_conversation_time:
-                    try:
-                        t = datetime.fromisoformat(profile.last_conversation_time)
-                        diff = datetime.now() - t
-                        if diff.days > 0:
-                            time_str = f"（{diff.days}天前）"
-                        else:
-                            h = diff.seconds // 3600
-                            time_str = f"（{h}小时前）" if h > 0 else "（刚刚）"
-                    except Exception:
-                        pass
-                lines.append(f"--- 上次对话 {time_str} ---")
-                lines.append(profile.last_conversation_summary)
-            
-            # 个性化回复策略
-            hints = []
-            if profile.personality:
-                if "爽快" in profile.personality:
-                    hints.append("回复简洁直接，不废话，快速报价")
-                if "砍价" in profile.personality or "砍价狂" in profile.personality:
-                    hints.append("报价时强调性价比，只让价一次，第二次引导去 xinhui.cloud")
-                if "纠结" in profile.personality or "墨迹" in profile.personality:
-                    hints.append("多给一点说明，耐心回答")
-            if profile.price_sensitivity == "高":
-                hints.append("报价时顺带提「满意再拍」降低顾虑")
-            if profile.decision_speed == "快":
-                hints.append("直接报价推成交，少铺垫")
-            if profile.total_orders > 0 and profile.decision_speed == "快":
-                hints.append("老客爽快，直接报价成交")
-            if hints:
-                lines.append("--- 回复策略 ---")
-                lines.append("；".join(hints))
-            
-            # 主动推荐
-            proactive = []
-            if profile.bulk_potential == "有" or (profile.total_images_sent or 0) >= 2:
-                proactive.append("可问「要做多张吗，多张有优惠」")
-            if profile.upsell_opportunity:
-                proactive.append(f"加购机会: {'、'.join(profile.upsell_opportunity)}")
-            if proactive:
-                lines.append("--- 主动推荐 ---")
-                lines.append("；".join(proactive))
-            
-            return "\n".join(lines)
-        except Exception as e:
-            print(f"[Agent] 获取客户画像失败: {e}")
-            return ""
-    
-    def _calc_avg_complexity(self, complexity_history: list) -> str:
-        """计算平均复杂度"""
-        if not complexity_history:
-            return "未知"
-        level_map = {"simple": 1, "normal": 2, "complex": 3, "hard": 4}
-        label_map = {1: "简单", 2: "一般", 3: "复杂", 4: "很复杂"}
-        try:
-            avg = sum(level_map.get(c, 2) for c in complexity_history) / len(complexity_history)
-            return label_map.get(round(avg), "一般")
-        except Exception:
-            return "一般"
 
     def _get_refusal_context_hint(self, customer_id: str, current_msg: str, profile_context: str) -> str:
-        """
+        return get_refusal_context_hint(self, customer_id, current_msg, profile_context)
-        检测「刚拒绝某张图 + 客户问能找到吗」场景，注入显式提示，避免前后矛盾。
-        原因：last_conversation_summary 异步更新可能滞后，message_histories 模型可能忽略。
-        """
-        ask_keywords = ["能找到吗", "可以吗", "有吗", "能做吗", "可以找吗", "可以弄吗"]
-        if not any(kw in current_msg for kw in ask_keywords):
-            return ""
-        refusal_keywords = ["不做", "不接", "拒绝", "不做这类", "这类不做"]
-        # 检查 profile 摘要（可能因异步更新而滞后）
-        if any(kw in profile_context for kw in refusal_keywords):
-            return "【重要】上一句客服刚拒绝了某张图，客户问能找到吗时须明确：能做的是哪张（如第一张），不能做的是哪张。不可只说「放心拍」「可以」，会前后矛盾。"
-        # 检查内存历史中最近几条消息（ModelResponse 含客服回复）
-        history = self.message_histories.get(customer_id, [])
-        for msg in reversed(history[-6:]):
-            msg_str = str(msg)
-            if any(kw in msg_str for kw in refusal_keywords):
-                return "【重要】上一句客服刚拒绝了某张图，客户问能找到吗时须明确：能做的是哪张（如第一张），不能做的是哪张。不可只说「放心拍」「可以」，会前后矛盾。"
-        return ""
-
-    def _get_conversation_context(self, customer_id: str, acc_id: str = "", limit: int = 12, max_len: int = 80) -> str:
-        """
-        每一次对话都从数据库加载近期对话，压缩后注入 prompt。
-        确保模型看到上下文，同时控制 token 消耗。
-        """
-        try:
-            try:
-                from config.config import CHAT_CONTEXT_LIMIT, CHAT_CONTEXT_TRUNCATE_LEN
-                limit = CHAT_CONTEXT_LIMIT
-                max_len = CHAT_CONTEXT_TRUNCATE_LEN
-            except Exception:
-                pass
-            from db.chat_log_db import get_recent_conversation
-            msgs = get_recent_conversation(customer_id, acc_id=acc_id, limit=limit)
-            if not msgs:
-                return ""
-            lines = []
-            for m in msgs:
-                role = "客" if m.get("direction") == "in" else "服"
-                msg_text = (m.get("message") or "").strip().replace("\n", " ")[:max_len]
-                if not msg_text:
-                    continue
-                lines.append(f"{role}:{msg_text}")
-            if not lines:
-                return ""
-            return "【近期】\n" + "\n".join(lines) + "\n\n"
-        except Exception:
-            return ""
-
-    def _get_intent_emotion_hint(self, msg: str) -> str:
-        """语义匹配：意图/情绪识别，注入提示。EMBEDDING_MODEL 未配置时用关键词。"""
-        try:
-            from utils.intent_analyzer import detect_intent_embedding, detect_intent_keywords, detect_emotion_embedding
-            intent = detect_intent_embedding(msg)
-            if not intent:
-                intent = detect_intent_keywords(msg)
-            emotion = detect_emotion_embedding(msg) if os.getenv("EMBEDDING_MODEL") else None
-            parts = []
-            if intent:
-                parts.append(f"意图:{intent}")
-            if emotion:
-                parts.append(f"情绪:{emotion}")
-            if parts:
-                return f"【当前消息】{', '.join(parts)}"
-        except Exception:
-            pass
-        return ""
 
     # 简单打招呼类消息（在近期已回复后无需再回）
     _COOLDOWN_PATTERNS = [