From 8e586a8c35312e66a061e214120be08f99300da1 Mon Sep 17 00:00:00 2001
From: wanghanlin <1533525126@qq.com>
Date: Sat, 27 Jun 2026 15:34:59 +0800
Subject: [PATCH] =?UTF-8?q?=E6=B1=82=E7=A7=BB=E9=99=A4=E6=9C=AA=E4=BD=BF?=
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Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 CLAUDE.md                                     |  5 +-
 DEPLOY.md                                     |  1 -
 README.md                                     |  4 +-
 .../wok/supportbot/app/ProductInfoApp.java    | 57 -------------------
 .../supportbot/config/ChatModelFactory.java   |  2 +-
 .../supportbot/config/ModelConfigLoader.java  |  1 -
 .../supportbot/controller/AiController.java   | 17 ------
 .../wok/supportbot/entity/AiModelConfig.java  |  2 +-
 .../wok/supportbot/entity/ProductInfo.java    | 14 -----
 .../service/AiModelConfigService.java         |  4 +-
 .../static/components/ModelConfigManager.js   |  5 +-
 .../SupportBotApplicationTests.java           | 32 -----------
 12 files changed, 9 insertions(+), 135 deletions(-)
 delete mode 100644 src/main/java/com/wok/supportbot/app/ProductInfoApp.java
 delete mode 100644 src/main/java/com/wok/supportbot/entity/ProductInfo.java

diff --git a/CLAUDE.md b/CLAUDE.md
index e7b69d1..6526432 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -39,11 +39,10 @@ AI 智能客服系统，基于 Spring AI Alibaba + 通义千问 + PGVector，支
 ### Spring AI 集成模式
 - **ChatClient Builder**: 所有对话通过 `ChatClient.builder(chatModelFactory.getChatModel("CHAT"))` 构建，ChatModel 由 `ChatModelFactory` 按 DB 活跃配置动态创建
 - **Advisor 链**: `MessageChatMemoryAdvisor`(记忆) → `MyLoggerAdvisor`(日志) → `QuestionAnswerAdvisor`(RAG)
-- **结构化输出**: `ProductInfoApp` 使用 `.entity(ProductInfo.class)` 提取结构化数据
 - **SSE 流式**: 三种实现 — Flux\<String\>、Flux\<ServerSentEvent\>、SseEmitter
 
 ### ChatMemory 持久化
-当前使用 `DatabaseChatMemory`（PostgreSQL 持久化），`FileBasedChatMemory`（Kryo 序列化）已注释掉。`ProductInfoApp` 单独使用 `InMemoryChatMemory`。
+当前使用 `DatabaseChatMemory`（PostgreSQL 持久化），`FileBasedChatMemory`（Kryo 序列化）已注释掉。
 
 ### RAG 双模式
 1. **QuestionAnswerAdvisor 模式**（生产使用）: 预检索优化 + `QuestionAnswerAdvisor`
@@ -69,7 +68,7 @@ AI 智能客服系统，基于 Spring AI Alibaba + 通义千问 + PGVector，支
 - **数据库自动初始化**: `DatabaseInitConfig` 在启动时检查并创建 `knowledge_category`/`knowledge_document`/`ai_model_config` 等表，对已存在的 `knowledge_document` 表会自动补加 `content_hash` 列。注意 `knowledge-base.sql` 脚本为早期版本，缺少此列，实际以 `DatabaseInitConfig` 为准
 
 ### 模型配置管理
-- **ai_model_config 表**: 存储大模型配置，支持多套配置按 App 类型（CHAT / PRODUCT_EXTRACT / EMBEDDING / RAG_REWRITE）独立管理。**所有模型参数（名称、温度、最大Token、API Key、Base URL 等）全部由此表管理，不再依赖 application.yml**
+- **ai_model_config 表**: 存储大模型配置，支持多套配置按 App 类型（CHAT / EMBEDDING / RAG_REWRITE）独立管理。**所有模型参数（名称、温度、最大Token、API Key、Base URL 等）全部由此表管理，不再依赖 application.yml**
 - **激活互斥**: 同一 App 类型只能有一个 `is_active=true` 的配置，激活操作由 Service 层 `@Transactional` 保证
 - **启动 seed**: 首次启动时使用硬编码默认值写入 DB（`qwen-turbo` / `text-embedding-v2`），用户可在前端修改。**DashScope 自动配置已禁用**（`spring.ai.dashscope.enabled=false`），api-key 可选——yml 与 DB 均未配置 api-key 不影响启动，实际调用 AI 功能前在前端「AI 大模型配置管理」页面配置即可
 - **启动校验**: `ModelConfigLoader` 在应用就绪后检查 DB 中每种 App 类型是否有活跃配置，并对 DashScope 提供商比较 DB 与 yml 的 API Key 一致性
diff --git a/DEPLOY.md b/DEPLOY.md
index 2a2c60a..6294164 100644
--- a/DEPLOY.md
+++ b/DEPLOY.md
@@ -459,7 +459,6 @@ tail -f /opt/support-bot/logs/startup.out
 | App 类型 | 用途 | 默认模型 |
 |----------|------|----------|
 | CHAT | 主对话 | qwen-turbo |
-| PRODUCT_EXTRACT | 结构化数据提取 | qwen-turbo |
 | EMBEDDING | 知识库向量化 | text-embedding-v2 |
 | RAG_REWRITE | RAG 查询重写 | qwen-turbo |
 
diff --git a/README.md b/README.md
index 49b7a07..f3dc0f9 100644
--- a/README.md
+++ b/README.md
@@ -164,8 +164,7 @@ src/main/java/com/wok/supportbot/
 │   ├── MyLoggerAdvisor.java           # 日志记录顾问
 │   └── ReReadingAdvisor.java          # 重读机制顾问
 ├── app/                               # 核心应用服务
-│   ├── AssistantApp.java              # 智能客服应用
-│   └── ProductInfoApp.java            # 商品信息提取应用
+│   └── AssistantApp.java              # 智能客服应用
 ├── chatmemory/                        # 聊天记忆管理
 │   ├── DatabaseChatMemory.java        # 数据库记忆存储
 │   └── FileBasedChatMemory.java       # 文件记忆存储
@@ -193,7 +192,6 @@ src/main/java/com/wok/supportbot/
 │       └── MyKeywordEnricher.java     # AI 关键词提取
 ├── entity/                            # 数据实体类
 │   ├── ChatMessage.java               # 聊天消息实体
-│   ├── ProductInfo.java               # 商品信息实体
 │   ├── KnowledgeDocument.java         # 知识文档实体
 │   ├── KnowledgeCategory.java         # 知识分类实体
 │   ├── CategoryNode.java              # 分类树节点 DTO
diff --git a/src/main/java/com/wok/supportbot/app/ProductInfoApp.java b/src/main/java/com/wok/supportbot/app/ProductInfoApp.java
deleted file mode 100644
index 4289a95..0000000
--- a/src/main/java/com/wok/supportbot/app/ProductInfoApp.java
+++ /dev/null
@@ -1,57 +0,0 @@
-package com.wok.supportbot.app;
-
-import com.wok.supportbot.advisor.MyLoggerAdvisor;
-import com.wok.supportbot.config.ChatModelFactory;
-import com.wok.supportbot.entity.ProductInfo;
-import lombok.extern.slf4j.Slf4j;
-import org.springframework.ai.chat.client.ChatClient;
-import org.springframework.ai.chat.client.advisor.MessageChatMemoryAdvisor;
-import org.springframework.ai.chat.memory.ChatMemory;
-import org.springframework.ai.chat.memory.InMemoryChatMemoryRepository;
-import org.springframework.ai.chat.memory.MessageWindowChatMemory;
-import org.springframework.stereotype.Component;
-
-/**
- * 电商商品信息抽取助手App - 支持多提供商动态切换
- */
-@Component
-@Slf4j
-public class ProductInfoApp {
-
-    private final ChatModelFactory chatModelFactory;
-
-    private static final String SYSTEM_PROMPT = "你是一名电商商品信息抽取助手，" +
-            "请从用户提供的商品网页内容中提取标题(title)、描述(description)、价格(price)、评分(rating)、评论数(reviewCount)、品牌(brand)、分类(category)等字段。" +
-            "请严格按照JSON格式返回，不要带任何解释和多余内容。";
-
-    public ProductInfoApp(ChatModelFactory chatModelFactory) {
-        this.chatModelFactory = chatModelFactory;
-    }
-
-    /**
-     * 商品信息结构化抽取
-     * @param rawContent 爬取的商品网页内容
-     * @return 结构化的商品信息对象
-     */
-    public ProductInfo extractProductInfo(String rawContent) {
-        ChatMemory chatMemory = MessageWindowChatMemory.builder()
-                .chatMemoryRepository(new InMemoryChatMemoryRepository())
-                .build();
-        ChatClient chatClient = ChatClient.builder(chatModelFactory.getChatModel("PRODUCT_EXTRACT"))
-                .defaultSystem(SYSTEM_PROMPT)
-                .defaultAdvisors(
-                        MessageChatMemoryAdvisor.builder(chatMemory).build(),
-                        new MyLoggerAdvisor()
-                )
-                .build();
-
-        ProductInfo productInfo = chatClient
-                .prompt()
-                .system(SYSTEM_PROMPT)
-                .user(rawContent)
-                .call()
-                .entity(ProductInfo.class);
-        log.info("Extracted product info: {}", productInfo);
-        return productInfo;
-    }
-}
diff --git a/src/main/java/com/wok/supportbot/config/ChatModelFactory.java b/src/main/java/com/wok/supportbot/config/ChatModelFactory.java
index a5e6323..65e5609 100644
--- a/src/main/java/com/wok/supportbot/config/ChatModelFactory.java
+++ b/src/main/java/com/wok/supportbot/config/ChatModelFactory.java
@@ -67,7 +67,7 @@ public class ChatModelFactory {
      * 按应用类型获取活跃的 ChatModel
      * 如果该类型无活跃配置，抛出异常（不应在缺少配置时静默回退）
      *
-     * @param appType 应用类型：CHAT / PRODUCT_EXTRACT / EMBEDDING / RAG_REWRITE
+     * @param appType 应用类型：CHAT / EMBEDDING / RAG_REWRITE
      * @return ChatModel 实例
      */
     public ChatModel getChatModel(String appType) {
diff --git a/src/main/java/com/wok/supportbot/config/ModelConfigLoader.java b/src/main/java/com/wok/supportbot/config/ModelConfigLoader.java
index 92b52ad..b857c8e 100644
--- a/src/main/java/com/wok/supportbot/config/ModelConfigLoader.java
+++ b/src/main/java/com/wok/supportbot/config/ModelConfigLoader.java
@@ -28,7 +28,6 @@ public class ModelConfigLoader implements ApplicationListener<ApplicationReadyEv
         log.info("========== AI 模型配置校验 ==========");
         try {
             checkAppTypeConfig("CHAT");
-            checkAppTypeConfig("PRODUCT_EXTRACT");
             checkAppTypeConfig("EMBEDDING");
             checkAppTypeConfig("RAG_REWRITE");
             log.info("========== AI 模型配置校验完成 ==========");
diff --git a/src/main/java/com/wok/supportbot/controller/AiController.java b/src/main/java/com/wok/supportbot/controller/AiController.java
index 0923a29..f8395ef 100644
--- a/src/main/java/com/wok/supportbot/controller/AiController.java
+++ b/src/main/java/com/wok/supportbot/controller/AiController.java
@@ -1,10 +1,7 @@
 package com.wok.supportbot.controller;
 
-import cn.hutool.json.JSONUtil;
 import com.wok.supportbot.app.AssistantApp;
-import com.wok.supportbot.app.ProductInfoApp;
 import com.wok.supportbot.config.RoleAccessConfig;
-import com.wok.supportbot.entity.ProductInfo;
 import com.wok.supportbot.service.ConversationService;
 import com.wok.supportbot.service.CustomerAccountService;
 import com.wok.supportbot.service.CustomerAccountService.AccountScope;
@@ -38,8 +35,6 @@ public class AiController {
     @Resource
     private AssistantApp assistantApp;
     @Resource
-    private ProductInfoApp productInfoApp;
-    @Resource
     private CustomerServiceRoleService customerServiceRoleService;
     @Resource
     private CustomerAccountService customerAccountService;
@@ -49,18 +44,6 @@ public class AiController {
     private RoleAccessConfig roleAccessConfig;
 
 
-    /**
-     * 同步调用 AI 提取结构化商品信息
-     *
-     * @param message
-     * @return
-     */
-    @GetMapping("/product_info_app/chat/sync")
-    public String doChatWithProductInfoAppSync(String message) {
-        ProductInfo productInfo = productInfoApp.extractProductInfo(message);
-        return JSONUtil.toJsonStr(productInfo);
-    }
-
     /**
      * 同步调用 AI 智能客服应用
      *
diff --git a/src/main/java/com/wok/supportbot/entity/AiModelConfig.java b/src/main/java/com/wok/supportbot/entity/AiModelConfig.java
index 2364b14..b33006e 100644
--- a/src/main/java/com/wok/supportbot/entity/AiModelConfig.java
+++ b/src/main/java/com/wok/supportbot/entity/AiModelConfig.java
@@ -42,7 +42,7 @@ public class AiModelConfig implements Serializable {
     private String name;
 
     /**
-     * 应用类型：CHAT / PRODUCT_EXTRACT / EMBEDDING / RAG_REWRITE
+     * 应用类型：CHAT / EMBEDDING / RAG_REWRITE
      */
     @TableField("app_type")
     private String appType;
diff --git a/src/main/java/com/wok/supportbot/entity/ProductInfo.java b/src/main/java/com/wok/supportbot/entity/ProductInfo.java
deleted file mode 100644
index 7580a2d..0000000
--- a/src/main/java/com/wok/supportbot/entity/ProductInfo.java
+++ /dev/null
@@ -1,14 +0,0 @@
-package com.wok.supportbot.entity;
-
-import lombok.Data;
-
-@Data
-public class ProductInfo {
-    private String title;
-    private String description;
-    private String price;
-    private String rating;
-    private Integer reviewCount;
-    private String brand;
-    private String category;
-}
diff --git a/src/main/java/com/wok/supportbot/service/AiModelConfigService.java b/src/main/java/com/wok/supportbot/service/AiModelConfigService.java
index 881a8ee..20a774c 100644
--- a/src/main/java/com/wok/supportbot/service/AiModelConfigService.java
+++ b/src/main/java/com/wok/supportbot/service/AiModelConfigService.java
@@ -212,7 +212,7 @@ public class AiModelConfigService {
 
     /**
      * 激活指定配置（同 app_type 互斥）
-     * 校验：Embedding 模型不能作为 CHAT / PRODUCT_EXTRACT / RAG_REWRITE 类型激活
+     * 校验：Embedding 模型不能作为 CHAT / RAG_REWRITE 类型激活
      *
      * @param id 配置ID
      */
@@ -292,7 +292,7 @@ public class AiModelConfigService {
 
     /**
      * 校验模型名称与应用类型的匹配关系
-     * Embedding 模型（模型名含 "embedding"）不能用于 CHAT / PRODUCT_EXTRACT / RAG_REWRITE 类型，
+     * Embedding 模型（模型名含 "embedding"）不能用于 CHAT / RAG_REWRITE 类型，
      * 否则调用 /chat/completions 端点会返回 404
      */
     private void validateModelTypeMatch(AiModelConfig config) {
diff --git a/src/main/resources/static/components/ModelConfigManager.js b/src/main/resources/static/components/ModelConfigManager.js
index 74fb32f..3918ce9 100644
--- a/src/main/resources/static/components/ModelConfigManager.js
+++ b/src/main/resources/static/components/ModelConfigManager.js
@@ -10,7 +10,6 @@ import { toast, formatDate } from '../js/utils.js'
 const APP_TYPE_OPTIONS = [
   { value: '', label: '全部类型' },
   { value: 'CHAT', label: '智能客服对话' },
-  { value: 'PRODUCT_EXTRACT', label: '商品信息抽取' },
   { value: 'EMBEDDING', label: '文本向量化' },
   { value: 'RAG_REWRITE', label: 'RAG查询重写' }
 ]
@@ -542,12 +541,12 @@ export default {
     // ==================== 工具函数 ====================
 
     function getAppTypeLabel(appType) {
-      const map = { CHAT: '智能客服对话', PRODUCT_EXTRACT: '商品信息抽取', EMBEDDING: '文本向量化', RAG_REWRITE: 'RAG查询重写' }
+      const map = { CHAT: '智能客服对话', EMBEDDING: '文本向量化', RAG_REWRITE: 'RAG查询重写' }
       return map[appType] || appType
     }
 
     function getAppTypeBadgeClass(appType) {
-      const map = { CHAT: 'badge-get', PRODUCT_EXTRACT: 'badge-post', EMBEDDING: '', RAG_REWRITE: '' }
+      const map = { CHAT: 'badge-get', EMBEDDING: '', RAG_REWRITE: '' }
       return map[appType] || ''
     }
 
diff --git a/src/test/java/com/wok/supportbot/SupportBotApplicationTests.java b/src/test/java/com/wok/supportbot/SupportBotApplicationTests.java
index 5e41877..caca461 100644
--- a/src/test/java/com/wok/supportbot/SupportBotApplicationTests.java
+++ b/src/test/java/com/wok/supportbot/SupportBotApplicationTests.java
@@ -1,12 +1,9 @@
 package com.wok.supportbot;
 
 import com.wok.supportbot.app.AssistantApp;
-import com.wok.supportbot.app.ProductInfoApp;
-import com.wok.supportbot.entity.ProductInfo;
 import jakarta.annotation.Resource;
 import org.junit.jupiter.api.Assertions;
 import org.junit.jupiter.api.Test;
-import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.boot.test.context.SpringBootTest;
 
 import java.util.UUID;
@@ -16,9 +13,6 @@ class SupportBotApplicationTests {
     @Resource
     private AssistantApp assistantApp;
 
-    @Autowired
-    private ProductInfoApp productInfoApp;
-
     @Test
     void testChat() {
         String chatId = UUID.randomUUID().toString();
@@ -38,32 +32,6 @@ class SupportBotApplicationTests {
         Assertions.assertNotNull(answer);
     }
 
-    @Test
-    public void testExtractProductInfo() {
-        // 模拟爬取的网页内容，建议写简洁但包含关键信息
-        String rawContent = "这是商品标题：智能手表Pro 2025，" +
-                "描述：这款智能手表支持心率监测和GPS，" +
-                "价格：299美元，评分：4.7星，评论数：1567，品牌：TechBrand，分类：电子产品。";
-        // 调用方法
-        ProductInfo productInfo = productInfoApp.extractProductInfo(rawContent);
-
-        // 断言结果不为空
-        Assertions.assertNotNull(productInfo);
-
-        // 断言关键字段合理（你也可以根据实际字段调整）
-        Assertions.assertNotNull(productInfo.getTitle());
-        Assertions.assertTrue(productInfo.getTitle().contains("智能手表"));
-
-        Assertions.assertNotNull(productInfo.getPrice());
-        Assertions.assertTrue(productInfo.getPrice().contains("299"));
-
-        Assertions.assertNotNull(productInfo.getBrand());
-        Assertions.assertEquals("TechBrand", productInfo.getBrand());
-
-        // 你可以打印结果，方便调试
-        System.out.println("提取的商品信息: " + productInfo);
-    }
-
     @Test
     void doChatWithRag() {
         String chatId = "1069b88d-eb85-47ac-bd2e-c393d118a5aa";