Merge remote-tracking branch 'origin/main'

# Conflicts:
#	ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/chat/service/knowledge/KnowledgeInfoServiceImpl.java

README.md

@@ -34,6 +34,23 @@
     <a href="https://github.com/ageerle/ruoyi-ai/issues">提出新特性</a>
 </p>
 
+## 快速启动
+
+1. **克隆项目**
+   ```bash
+   git clone https://github.com/alanpeng/ruoyi-ai-docker-deploy
+   cd ruoyi-ai-docker-deploy
+   ```
+
+2. **启动全套应用**
+   ```bash
+   docker-compose up -d
+   ```
+
+3. **访问应用界面**
+   - 用户界面：`http://your-server-ip:8081`
+   - 管理员界面：`http://your-server-ip:8082`
+
 ## 目录
 
 - [系统体验](#系统体验)

ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/domain/KnowledgeInfo.java

@@ -1,5 +1,6 @@
 package org.ruoyi.domain;
 
+import com.alibaba.excel.annotation.ExcelProperty;
 import com.baomidou.mybatisplus.annotation.*;
 import lombok.Data;
 import lombok.EqualsAndHashCode;
@@ -78,14 +79,19 @@ public class KnowledgeInfo extends BaseEntity {
     private Long textBlockSize;
 
     /**
-     * 向量库
+     * 向量库模型名称
      */
-    private String vector;
+    private String vectorModelName;
 
     /**
-     * 向量模型
+     * 向量化模型名称
      */
-    private String vectorModel;
+    private String embeddingModelName;
+
+    /**
+     * 系统提示词
+     */
+    private String systemPrompt;
 
     /**
      * 备注

ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/domain/bo/KnowledgeInfoBo.java

@@ -83,16 +83,22 @@ public class KnowledgeInfoBo extends BaseEntity {
     private Long textBlockSize;
 
     /**
-     * 向量库
+     * 向量库模型名称
      */
     @NotBlank(message = "向量库不能为空", groups = { AddGroup.class, EditGroup.class })
-    private String vector;
+    private String vectorModelName;
 
     /**
-     * 向量模型
+     * 向量化模型名称
      */
     @NotBlank(message = "向量模型不能为空", groups = { AddGroup.class, EditGroup.class })
-    private String vectorModel;
+    private String embeddingModelName;
+
+
+    /**
+     * 系统提示词
+     */
+    private String systemPrompt;
 
     /**
      * 备注

ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/domain/bo/QueryVectorBo.java

@@ -26,9 +26,14 @@ public class QueryVectorBo {
     private Integer maxResults;
 
     /**
-     * 模型名称
+     * 向量库模型名称
      */
-    private String modelName;
+    private String vectorModelName;
+
+    /**
+     * 向量化模型名称
+     */
+    private String embeddingModelName;
 
     /**
      * 请求key

ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/domain/bo/StoreEmbeddingBo.java

@@ -32,9 +32,14 @@ public class StoreEmbeddingBo {
     private List<String> fids;
 
     /**
-     * 模型名称
+     * 向量库模型名称
      */
-    private String modelName;
+    private String vectorModelName;
+
+    /**
+     * 向量化模型名称
+     */
+    private String embeddingModelName;
 
     /**
      * 请求key

ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/domain/vo/KnowledgeInfoVo.java

@@ -98,16 +98,20 @@ public class KnowledgeInfoVo implements Serializable {
     private Integer textBlockSize;
 
     /**
-     * 向量库
+     * 向量库模型名称
      */
-    @ExcelProperty(value = "向量库")
+    private String vectorModelName;
-    private String vector;
 
     /**
-     * 向量模型
+     * 向量化模型名称
      */
-    @ExcelProperty(value = "向量模型")
+    private String embeddingModelName;
-    private String vectorModel;
+
+
+    /**
+     * 系统提示词
+     */
+    private String systemPrompt;
 
     /**
      * 备注

ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/VectorStoreService.java

@@ -13,14 +13,14 @@ public interface VectorStoreService {
 
     void storeEmbeddings(StoreEmbeddingBo storeEmbeddingBo);
 
-    void removeByDocId(String kid,String docId);
-
-    void removeByKid(String kid);
-
     List<String> getQueryVector(QueryVectorBo queryVectorBo);
 
     void createSchema(String kid,String modelName);
 
-    void removeByKidAndFid(String kid, String fid);
+    void removeByKid(String kid,String modelName);
+
+    void removeByDocId(String kid,String docId,String modelName);
+
+    void removeByKidAndFid(String kid, String fid,String modelName);
 
 }

ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/impl/VectorStoreServiceImpl.java

@@ -1,5 +1,7 @@
 package org.ruoyi.service.impl;
 
+import cn.hutool.core.util.RandomUtil;
+import com.google.protobuf.ServiceException;
 import dev.langchain4j.data.embedding.Embedding;
 import dev.langchain4j.data.segment.TextSegment;
 import dev.langchain4j.model.embedding.EmbeddingModel;
@@ -16,6 +18,7 @@ import dev.langchain4j.store.embedding.milvus.MilvusEmbeddingStore;
 import dev.langchain4j.store.embedding.qdrant.QdrantEmbeddingStore;
 import dev.langchain4j.store.embedding.weaviate.WeaviateEmbeddingStore;
 import lombok.RequiredArgsConstructor;
+import lombok.SneakyThrows;
 import lombok.extern.slf4j.Slf4j;
 import org.ruoyi.common.core.service.ConfigService;
 import org.ruoyi.domain.bo.QueryVectorBo;
@@ -40,11 +43,10 @@ public class VectorStoreServiceImpl implements VectorStoreService {
 
     private final ConfigService configService;
 
-    Map<String,EmbeddingStore<TextSegment>> storeMap = new HashMap<>();
+    private EmbeddingStore<TextSegment> embeddingStore;
 
     @Override
     public void createSchema(String kid,String modelName) {
-        EmbeddingStore<TextSegment> embeddingStore;
         switch (modelName) {
             case "weaviate" -> {
                 String protocol = configService.getConfigValue("weaviate", "protocol");
@@ -84,88 +86,83 @@ public class VectorStoreServiceImpl implements VectorStoreService {
                 embeddingStore = new InMemoryEmbeddingStore<>();
             }
         }
-        storeMap.put(kid,embeddingStore);
     }
 
     @Override
     public void storeEmbeddings(StoreEmbeddingBo storeEmbeddingBo) {
-        EmbeddingStore<TextSegment> store = storeMap.get(storeEmbeddingBo.getKid());
+        createSchema(storeEmbeddingBo.getKid(),storeEmbeddingBo.getVectorModelName());
-        EmbeddingModel embeddingModel = getEmbeddingModel(storeEmbeddingBo.getModelName(),
+        EmbeddingModel embeddingModel = getEmbeddingModel(storeEmbeddingBo.getEmbeddingModelName(),
                 storeEmbeddingBo.getApiKey(), storeEmbeddingBo.getBaseUrl());
-        for (int i = 0; i < storeEmbeddingBo.getChunkList().size(); i++) {
+        List<String> chunkList = storeEmbeddingBo.getChunkList();
+        for (int i = 0; i < chunkList.size(); i++) {
             Map<String, Object> dataSchema = new HashMap<>();
             dataSchema.put("kid", storeEmbeddingBo.getKid());
             dataSchema.put("docId", storeEmbeddingBo.getKid());
             dataSchema.put("fid", storeEmbeddingBo.getFids().get(i));
-            Response<Embedding> response = embeddingModel.embed(storeEmbeddingBo.getChunkList().get(i));
+            Embedding embedding = embeddingModel.embed(chunkList.get(i)).content();
-            Embedding embedding = response.content();
+            TextSegment segment = TextSegment.from(chunkList.get(i));
-            TextSegment segment = TextSegment.from(storeEmbeddingBo.getChunkList().get(i));
             segment.metadata().putAll(dataSchema);
-
+            embeddingStore.add(embedding,segment);
-            store.add(embedding,segment);
         }
     }
 
     @Override
     public List<String> getQueryVector(QueryVectorBo queryVectorBo) {
-        EmbeddingStore<TextSegment> store = storeMap.get(queryVectorBo.getKid());
+        createSchema(queryVectorBo.getKid(),queryVectorBo.getVectorModelName());
-
+        EmbeddingModel embeddingModel = getEmbeddingModel(queryVectorBo.getEmbeddingModelName(),
-        EmbeddingModel embeddingModel = getEmbeddingModel(queryVectorBo.getModelName(),
                 queryVectorBo.getApiKey(), queryVectorBo.getBaseUrl());
-        Filter simpleFilter = new IsEqualTo("kid", queryVectorBo.getKid());
+       // Filter simpleFilter = new IsEqualTo("kid", queryVectorBo.getKid());
         Embedding queryEmbedding = embeddingModel.embed(queryVectorBo.getQuery()).content();
         EmbeddingSearchRequest embeddingSearchRequest = EmbeddingSearchRequest.builder()
                 .queryEmbedding(queryEmbedding)
                 .maxResults(queryVectorBo.getMaxResults())
                 // 添加过滤条件
-                .filter(simpleFilter)
+         //       .filter(simpleFilter)
                 .build();
-        List<EmbeddingMatch<TextSegment>> matches = store.search(embeddingSearchRequest).matches();
+        List<EmbeddingMatch<TextSegment>> matches = embeddingStore.search(embeddingSearchRequest).matches();
-
         List<String> results = new ArrayList<>();
-
         matches.forEach(embeddingMatch -> results.add(embeddingMatch.embedded().text()));
         return results;
     }
 
 
     @Override
-    public void removeByKid(String kid) {
+    public void removeByKid(String kid,String modelName) {
-        EmbeddingStore<TextSegment> store = storeMap.get(kid);
+        createSchema(kid,modelName);
-
         // 根据条件删除向量数据
         Filter simpleFilter = new IsEqualTo("kid", kid);
-        store.removeAll(simpleFilter);
+        embeddingStore.removeAll(simpleFilter);
     }
 
     @Override
-    public void removeByDocId(String kid, String docId) {
+    public void removeByDocId(String kid, String docId,String modelName) {
-        EmbeddingStore<TextSegment> store = storeMap.get(kid);
+        createSchema(kid,modelName);
         // 根据条件删除向量数据
         Filter simpleFilterByDocId = new IsEqualTo("docId", docId);
-        store.removeAll(simpleFilterByDocId);
+        embeddingStore.removeAll(simpleFilterByDocId);
     }
 
     @Override
-    public void removeByKidAndFid(String kid, String fid) {
+    public void removeByKidAndFid(String kid, String fid,String modelName) {
-        EmbeddingStore<TextSegment> store = storeMap.get(kid);
+        createSchema(kid,modelName);
         // 根据条件删除向量数据
         Filter simpleFilterByKid = new IsEqualTo("kid", kid);
         Filter simpleFilterFid = new IsEqualTo("fid", fid);
         Filter simpleFilterByAnd = Filter.and(simpleFilterFid, simpleFilterByKid);
-        store.removeAll(simpleFilterByAnd);
+        embeddingStore.removeAll(simpleFilterByAnd);
     }
 
     /**
      * 获取向量模型
      */
-    public EmbeddingModel getEmbeddingModel(String modelName,String apiKey,String baseUrl) {
+    @SneakyThrows
-        EmbeddingModel embeddingModel = OpenAiEmbeddingModel.builder().build();
+    public EmbeddingModel getEmbeddingModel(String modelName, String apiKey, String baseUrl) {
+        EmbeddingModel embeddingModel;
         if(TEXT_EMBEDDING_3_SMALL.toString().equals(modelName)) {
              embeddingModel = OpenAiEmbeddingModel.builder()
                     .apiKey(apiKey)
                     .baseUrl(baseUrl)
-                    .modelName(TEXT_EMBEDDING_3_SMALL)
+                    .modelName(modelName)
                     .build();
         // TODO 添加枚举
         }else if("quentinz/bge-large-zh-v1.5".equals(modelName)) {
@@ -173,6 +170,14 @@ public class VectorStoreServiceImpl implements VectorStoreService {
                     .baseUrl(baseUrl)
                     .modelName(modelName)
                     .build();
+        }else if("baai/bge-m3".equals(modelName)) {
+            embeddingModel = OpenAiEmbeddingModel.builder()
+                    .apiKey(apiKey)
+                    .baseUrl(baseUrl)
+                    .modelName(modelName)
+                    .build();
+        }else {
+            throw new ServiceException("未找到对应向量化模型!");
         }
         return embeddingModel;
     }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/chat/service/chat/impl/SseServiceImpl.java

@@ -2,6 +2,7 @@ package org.ruoyi.chat.service.chat.impl;
 
 import cn.dev33.satoken.stp.StpUtil;
 import cn.hutool.core.collection.CollectionUtil;
+import com.baomidou.mybatisplus.core.toolkit.Wrappers;
 import com.google.protobuf.ServiceException;
 import jakarta.servlet.http.HttpServletRequest;
 import lombok.RequiredArgsConstructor;
@@ -29,6 +30,8 @@ import org.ruoyi.common.redis.utils.RedisUtils;
 import org.ruoyi.domain.bo.ChatSessionBo;
 import org.ruoyi.domain.bo.QueryVectorBo;
 import org.ruoyi.domain.vo.ChatModelVo;
+import org.ruoyi.domain.vo.KnowledgeInfoVo;
+import org.ruoyi.service.IKnowledgeInfoService;
 import org.ruoyi.service.VectorStoreService;
 import org.ruoyi.service.IChatModelService;
 import org.ruoyi.service.IChatSessionService;
@@ -67,6 +70,8 @@ public class SseServiceImpl implements ISseService {
 
     private final IChatSessionService chatSessionService;
 
+    private final IKnowledgeInfoService knowledgeInfoService;
+
     private ChatModelVo chatModelVo;
 
 
@@ -148,50 +153,61 @@ public class SseServiceImpl implements ISseService {
             }
     }
 
-
     /**
      *  构建消息列表
      */
     private void buildChatMessageList(ChatRequest chatRequest){
+        String sysPrompt;
         chatModelVo = chatModelService.selectModelByName(chatRequest.getModel());
         // 获取对话消息列表
         List<Message> messages = chatRequest.getMessages();
-        String sysPrompt = chatModelVo.getSystemPrompt();
+        // 查询向量库相关信息加入到上下文
-
+        if(StringUtils.isNotEmpty(chatRequest.getKid())){
+            List<Message> knMessages = new ArrayList<>();
+            String content = messages.get(messages.size() - 1).getContent().toString();
+            // 通过kid查询知识库信息
+            KnowledgeInfoVo knowledgeInfoVo = knowledgeInfoService.queryById(Long.valueOf(chatRequest.getKid()));
+            // 查询向量模型配置信息
+            ChatModelVo chatModel = chatModelService.selectModelByName(knowledgeInfoVo.getEmbeddingModelName());
 
+            QueryVectorBo queryVectorBo = new QueryVectorBo();
+            queryVectorBo.setQuery(content);
+            queryVectorBo.setKid(chatRequest.getKid());
+            queryVectorBo.setApiKey(chatModel.getApiKey());
+            queryVectorBo.setBaseUrl(chatModel.getApiHost());
+            queryVectorBo.setVectorModelName(knowledgeInfoVo.getVectorModelName());
+            queryVectorBo.setEmbeddingModelName(knowledgeInfoVo.getEmbeddingModelName());
+            queryVectorBo.setMaxResults(knowledgeInfoVo.getRetrieveLimit());
+            List<String> nearestList = vectorStoreService.getQueryVector(queryVectorBo);
+            for (String prompt : nearestList) {
+                Message userMessage = Message.builder().content(prompt).role(Message.Role.USER).build();
+                knMessages.add(userMessage);
+            }
+            messages.addAll(knMessages);
+            // 设置知识库系统提示词
+            sysPrompt = knowledgeInfoVo.getSystemPrompt();
+            if(StringUtils.isEmpty(sysPrompt)){
+                sysPrompt ="###角色设定\n" +
+                        "你是一个智能知识助手，专注于利用上下文中的信息来提供准确和相关的回答。\n" +
+                        "###指令\n" +
+                        "当用户的问题与上下文知识匹配时，利用上下文信息进行回答。如果问题与上下文不匹配，运用自身的推理能力生成合适的回答。\n" +
+                        "###限制\n" +
+                        "确保回答清晰简洁，避免提供不必要的细节。始终保持语气友好" +
+                        "当前时间："+ DateUtils.getDate();
+            }
+        }else {
+            sysPrompt = chatModelVo.getSystemPrompt();
             if(StringUtils.isEmpty(sysPrompt)){
-            // TODO 系统默认提示词,后续会增加提示词管理
                 sysPrompt ="你是一个由RuoYI-AI开发的人工智能助手，名字叫熊猫助手。你擅长中英文对话，能够理解并处理各种问题，提供安全、有帮助、准确的回答。" +
                         "当前时间："+ DateUtils.getDate()+
                         "#注意：回复之前注意结合上下文和工具返回内容进行回复。";
             }
+        }
         // 设置系统默认提示词
         Message sysMessage = Message.builder().content(sysPrompt).role(Message.Role.SYSTEM).build();
         messages.add(0,sysMessage);
 
         chatRequest.setSysPrompt(sysPrompt);
-        // 查询向量库相关信息加入到上下文
-        if(StringUtils.isNotEmpty(chatRequest.getKid())){
-            List<Message> knMessages = new ArrayList<>();
-            String content = messages.get(messages.size() - 1).getContent().toString();
-            QueryVectorBo queryVectorBo = new QueryVectorBo();
-            queryVectorBo.setQuery(content);
-            queryVectorBo.setKid(chatRequest.getKid());
-            queryVectorBo.setApiKey(chatModelVo.getApiKey());
-            queryVectorBo.setBaseUrl(chatModelVo.getApiHost());
-            queryVectorBo.setModelName(chatModelVo.getModelName());
-            // TODO 查询向量返回条数,这里应该查询知识库配置
-            queryVectorBo.setMaxResults(3);
-            List<String> nearestList = vectorStoreService.getQueryVector(queryVectorBo);
-            for (String prompt : nearestList) {
-                Message userMessage = Message.builder().content(prompt).role(Message.Role.USER).build();
-                knMessages.add(userMessage);
-            }
-            // TODO 提示词,这里应该查询知识库配置
-            Message userMessage = Message.builder().content(content + (!nearestList.isEmpty() ? "\n\n注意：回答问题时，须严格根据我给你的系统上下文内容原文进行回答，请不要自己发挥,回答时保持原来文本的段落层级" : "")).role(Message.Role.USER).build();
-            knMessages.add(userMessage);
-            messages.addAll(knMessages);
-        }
         // 用户对话内容
         String chatString = null;
         // 获取用户对话信息

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/chat/service/knowledge/KnowledgeInfoServiceImpl.java

@@ -1,14 +1,11 @@
 package org.ruoyi.chat.service.knowledge;
 
 import cn.hutool.core.collection.CollUtil;
-import cn.hutool.core.util.ObjectUtil;
 import cn.hutool.core.util.RandomUtil;
 import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
 import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
-import com.baomidou.mybatisplus.core.conditions.update.LambdaUpdateWrapper;
 import com.baomidou.mybatisplus.core.toolkit.Wrappers;
 import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
-import java.util.stream.Collectors;
 import lombok.RequiredArgsConstructor;
 import org.ruoyi.chain.loader.ResourceLoader;
 import org.ruoyi.chain.loader.ResourceLoaderFactory;
@@ -16,8 +13,6 @@ import org.ruoyi.common.core.domain.model.LoginUser;
 import org.ruoyi.common.core.utils.MapstructUtils;
 import org.ruoyi.common.core.utils.StringUtils;
 import org.ruoyi.common.satoken.utils.LoginHelper;
-import org.ruoyi.constant.DealStatus;
-import org.ruoyi.constant.FileType;
 import org.ruoyi.core.page.PageQuery;
 import org.ruoyi.core.page.TableDataInfo;
 import org.ruoyi.domain.ChatModel;
@@ -35,15 +30,11 @@ import org.ruoyi.mapper.KnowledgeInfoMapper;
 import org.ruoyi.service.IChatModelService;
 import org.ruoyi.service.VectorStoreService;
 import org.ruoyi.service.IKnowledgeInfoService;
-import org.ruoyi.system.domain.vo.SysOssVo;
-import org.ruoyi.system.service.ISysOssService;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
-import org.springframework.scheduling.annotation.Scheduled;
 import org.springframework.stereotype.Service;
 import org.springframework.transaction.annotation.Transactional;
 import org.springframework.web.multipart.MultipartFile;
-import org.springframework.scheduling.annotation.Async;
 
 import java.io.IOException;
 import java.util.*;
@@ -71,13 +62,11 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
 
     private final IChatModelService chatModelService;
 
-  private final ISysOssService ossService;
-
     /**
      * 查询知识库
      */
     @Override
-  public KnowledgeInfoVo queryById(Long id) {
+    public KnowledgeInfoVo queryById(Long id){
         return baseMapper.selectVoById(id);
     }
 
@@ -107,18 +96,12 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
         lqw.eq(bo.getUid() != null, KnowledgeInfo::getUid, bo.getUid());
         lqw.like(StringUtils.isNotBlank(bo.getKname()), KnowledgeInfo::getKname, bo.getKname());
         lqw.eq(bo.getShare() != null, KnowledgeInfo::getShare, bo.getShare());
-    lqw.eq(StringUtils.isNotBlank(bo.getDescription()), KnowledgeInfo::getDescription,
+        lqw.eq(StringUtils.isNotBlank(bo.getDescription()), KnowledgeInfo::getDescription, bo.getDescription());
-        bo.getDescription());
+        lqw.eq(StringUtils.isNotBlank(bo.getKnowledgeSeparator()), KnowledgeInfo::getKnowledgeSeparator, bo.getKnowledgeSeparator());
-    lqw.eq(StringUtils.isNotBlank(bo.getKnowledgeSeparator()), KnowledgeInfo::getKnowledgeSeparator,
+        lqw.eq(StringUtils.isNotBlank(bo.getQuestionSeparator()), KnowledgeInfo::getQuestionSeparator, bo.getQuestionSeparator());
-        bo.getKnowledgeSeparator());
-    lqw.eq(StringUtils.isNotBlank(bo.getQuestionSeparator()), KnowledgeInfo::getQuestionSeparator,
-        bo.getQuestionSeparator());
         lqw.eq(bo.getOverlapChar() != null, KnowledgeInfo::getOverlapChar, bo.getOverlapChar());
         lqw.eq(bo.getRetrieveLimit() != null, KnowledgeInfo::getRetrieveLimit, bo.getRetrieveLimit());
         lqw.eq(bo.getTextBlockSize() != null, KnowledgeInfo::getTextBlockSize, bo.getTextBlockSize());
-    lqw.eq(StringUtils.isNotBlank(bo.getVector()), KnowledgeInfo::getVector, bo.getVector());
-    lqw.eq(StringUtils.isNotBlank(bo.getVectorModel()), KnowledgeInfo::getVectorModel,
-        bo.getVectorModel());
         return lqw;
     }
 
@@ -149,7 +132,7 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
     /**
      * 保存前的数据校验
      */
-  private void validEntityBeforeSave(KnowledgeInfo entity) {
+    private void validEntityBeforeSave(KnowledgeInfo entity){
         //TODO 做一些数据校验,如唯一约束
     }
 
@@ -158,7 +141,7 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
      */
     @Override
     public Boolean deleteWithValidByIds(Collection<Long> ids, Boolean isValid) {
-    if (isValid) {
+        if(isValid){
             //TODO 做一些业务上的校验,判断是否需要校验
         }
         return baseMapper.deleteBatchIds(ids) > 0;
@@ -168,7 +151,7 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
     @Transactional(rollbackFor = Exception.class)
     public void saveOne(KnowledgeInfoBo bo) {
         KnowledgeInfo knowledgeInfo = MapstructUtils.convert(bo, KnowledgeInfo.class);
-    if (StringUtils.isBlank(bo.getKid())) {
+        if (StringUtils.isBlank(bo.getKid())){
             String kid = RandomUtil.randomString(10);
             if (knowledgeInfo != null) {
                 knowledgeInfo.setKid(kid);
@@ -176,9 +159,9 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
             }
             baseMapper.insert(knowledgeInfo);
             if (knowledgeInfo != null) {
-        vectorStoreService.createSchema(String.valueOf(knowledgeInfo.getId()), bo.getVector());
+                vectorStoreService.createSchema(String.valueOf(knowledgeInfo.getId()),bo.getVectorModelName());
             }
-    } else {
+        }else {
             baseMapper.updateById(knowledgeInfo);
         }
     }
@@ -186,13 +169,13 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
     @Override
     @Transactional(rollbackFor = Exception.class)
     public void removeKnowledge(String id) {
-    Map<String, Object> map = new HashMap<>();
+        Map<String,Object> map = new HashMap<>();
-    map.put("kid", id);
+        map.put("kid",id);
         List<KnowledgeInfoVo> knowledgeInfoList = baseMapper.selectVoByMap(map);
         check(knowledgeInfoList);
         // 删除向量库信息
         knowledgeInfoList.forEach(knowledgeInfoVo -> {
-      vectorStoreService.removeByKid(String.valueOf(knowledgeInfoVo.getId()));
+            vectorStoreService.removeByKid(String.valueOf(knowledgeInfoVo.getId()),knowledgeInfoVo.getVectorModelName());
         });
         // 删除附件和知识片段
         fragmentMapper.deleteByMap(map);
@@ -207,12 +190,6 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
     }
 
     public void storeContent(MultipartFile file, String kid) {
-    if (file == null || file.isEmpty()) {
-      throw new IllegalArgumentException("File cannot be null or empty");
-    }
-
-    SysOssVo uploadDto = null;
-
         String fileName = file.getOriginalFilename();
         List<String> chunkList = new ArrayList<>();
         KnowledgeAttach knowledgeAttach = new KnowledgeAttach();
@@ -220,19 +197,15 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
         String docId = RandomUtil.randomString(10);
         knowledgeAttach.setDocId(docId);
         knowledgeAttach.setDocName(fileName);
-    knowledgeAttach.setDocType(fileName.substring(fileName.lastIndexOf(".") + 1));
+        knowledgeAttach.setDocType(fileName.substring(fileName.lastIndexOf(".")+1));
         String content = "";
-    ResourceLoader resourceLoader = resourceLoaderFactory.getLoaderByFileType(
+        ResourceLoader resourceLoader = resourceLoaderFactory.getLoaderByFileType(knowledgeAttach.getDocType());
-        knowledgeAttach.getDocType());
         List<String> fids = new ArrayList<>();
         try {
             content = resourceLoader.getContent(file.getInputStream());
             chunkList = resourceLoader.getChunkList(content, kid);
             List<KnowledgeFragment> knowledgeFragmentList = new ArrayList<>();
             if (CollUtil.isNotEmpty(chunkList)) {
-        // Upload file to OSS
-        uploadDto = ossService.upload(file);
-
                 for (int i = 0; i < chunkList.size(); i++) {
                     String fid = RandomUtil.randomString(10);
                     fids.add(fid);
@@ -252,22 +225,25 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
         }
         knowledgeAttach.setContent(content);
         knowledgeAttach.setCreateTime(new Date());
-
-    if (ObjectUtil.isNotEmpty(uploadDto) && ObjectUtil.isNotEmpty(uploadDto.getOssId())) {
-      knowledgeAttach.setOssId(uploadDto.getOssId());
-      //只有pdf文件 才需要拆解图片和分析图片内容
-      if (FileType.PDF.equals(knowledgeAttach.getDocType())) {
-        knowledgeAttach.setPicStatus(DealStatus.STATUS_10);
-        knowledgeAttach.setPicAnysStatus(DealStatus.STATUS_10);
-      } else {
-        knowledgeAttach.setPicStatus(DealStatus.STATUS_30);
-        knowledgeAttach.setPicAnysStatus(DealStatus.STATUS_30);
-      }
-      //所有文件上传后，都需要同步到向量数据库
-      knowledgeAttach.setVectorStatus(DealStatus.STATUS_10);
-    }
-
         attachMapper.insert(knowledgeAttach);
+
+        // 通过kid查询知识库信息
+        KnowledgeInfoVo knowledgeInfoVo = baseMapper.selectVoOne(Wrappers.<KnowledgeInfo>lambdaQuery()
+                .eq(KnowledgeInfo::getId, kid));
+
+        // 通过向量模型查询模型信息
+        ChatModelVo chatModelVo = chatModelService.selectModelByName(knowledgeInfoVo.getEmbeddingModelName());
+
+        StoreEmbeddingBo storeEmbeddingBo = new StoreEmbeddingBo();
+        storeEmbeddingBo.setKid(kid);
+        storeEmbeddingBo.setDocId(docId);
+        storeEmbeddingBo.setFids(fids);
+        storeEmbeddingBo.setChunkList(chunkList);
+        storeEmbeddingBo.setVectorModelName(knowledgeInfoVo.getVectorModelName());
+        storeEmbeddingBo.setEmbeddingModelName(knowledgeInfoVo.getEmbeddingModelName());
+        storeEmbeddingBo.setApiKey(chatModelVo.getApiKey());
+        storeEmbeddingBo.setBaseUrl(chatModelVo.getApiHost());
+        vectorStoreService.storeEmbeddings(storeEmbeddingBo);
     }
 
 
@@ -276,103 +252,13 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
      *
      * @param knowledgeInfoList 知识库列表
      */
-  public void check(List<KnowledgeInfoVo> knowledgeInfoList) {
+    public void check(List<KnowledgeInfoVo> knowledgeInfoList){
         LoginUser loginUser = LoginHelper.getLoginUser();
         for (KnowledgeInfoVo knowledgeInfoVo : knowledgeInfoList) {
-      if (!knowledgeInfoVo.getUid().equals(loginUser.getUserId())) {
+            if(!knowledgeInfoVo.getUid().equals(loginUser.getUserId())){
                 throw new SecurityException("权限不足");
             }
         }
     }
 
-  /**
-   * 定时 处理 附件上传后上传向量数据库和PDF文件图片拆解和分析内容
-   */
-  @Scheduled(fixedDelay = 3000) // 每3秒执行一次
-  public void dealKnowledgeAttach() throws Exception {
-    //处理 需要上传向量数据库的记录
-    List<KnowledgeAttach> knowledgeAttaches = attachMapper.selectList(
-        new LambdaQueryWrapper<KnowledgeAttach>()
-            .eq(KnowledgeAttach::getPicStatus, DealStatus.STATUS_30)
-            .eq(KnowledgeAttach::getPicAnysStatus, DealStatus.STATUS_30)
-            .eq(KnowledgeAttach::getVectorStatus, DealStatus.STATUS_10)
-    );
-    if (ObjectUtil.isNotEmpty(knowledgeAttaches)) {
-      for (KnowledgeAttach attachItem : knowledgeAttaches) {
-        this.dealVectorStatus(attachItem);
-      }
-    }
-  }
-
-  @Async
-  public void dealVectorStatus(KnowledgeAttach attachItem) throws Exception {
-    try {
-      //锁定数据 更改VectorStatus 到进行中
-      if (attachMapper.update(new LambdaUpdateWrapper<KnowledgeAttach>()
-          .set(KnowledgeAttach::getVectorStatus, DealStatus.STATUS_20)
-          .eq(KnowledgeAttach::getPicStatus, DealStatus.STATUS_30)
-          .eq(KnowledgeAttach::getPicAnysStatus, DealStatus.STATUS_30)
-          .eq(KnowledgeAttach::getVectorStatus, DealStatus.STATUS_10)
-          .eq(KnowledgeAttach::getId, attachItem.getId())
-      ) == 0) {
-        return;
-      }
-      // 通过kid查询知识库信息
-      KnowledgeInfoVo knowledgeInfoVo = baseMapper.selectVoOne(Wrappers.<KnowledgeInfo>lambdaQuery()
-          .eq(KnowledgeInfo::getKid, attachItem.getKid()));
-
-      // 通过向量模型查询模型信息
-      ChatModelVo chatModelVo = chatModelService.selectModelByName(
-          knowledgeInfoVo.getVectorModel());
-
-      List<KnowledgeFragment> knowledgeFragments = fragmentMapper.selectList(
-          new LambdaQueryWrapper<KnowledgeFragment>()
-              .eq(KnowledgeFragment::getKid, attachItem.getKid())
-              .eq(KnowledgeFragment::getDocId, attachItem.getDocId())
-      );
-      if (ObjectUtil.isEmpty(knowledgeFragments)) {
-        throw new Exception("文件段落为空");
-      }
-      List<String> fids = knowledgeFragments.stream()
-          .map(KnowledgeFragment::getFid)
-          .collect(Collectors.toList());
-      if (ObjectUtil.isEmpty(fids)) {
-        throw new Exception("fids 为空");
-      }
-      List<String> chunkList = knowledgeFragments.stream()
-          .map(KnowledgeFragment::getContent)
-          .collect(Collectors.toList());
-
-      if (ObjectUtil.isEmpty(chunkList)) {
-        throw new Exception("chunkList 为空");
-      }
-      StoreEmbeddingBo storeEmbeddingBo = new StoreEmbeddingBo();
-      storeEmbeddingBo.setKid(attachItem.getKid());
-      storeEmbeddingBo.setDocId(attachItem.getDocId());
-      storeEmbeddingBo.setFids(fids);
-      storeEmbeddingBo.setChunkList(chunkList);
-      storeEmbeddingBo.setModelName(knowledgeInfoVo.getVectorModel());
-      storeEmbeddingBo.setApiKey(chatModelVo.getApiKey());
-      storeEmbeddingBo.setBaseUrl(chatModelVo.getApiHost());
-      vectorStoreService.storeEmbeddings(storeEmbeddingBo);
-
-      //设置处理完成
-      attachMapper.update(new LambdaUpdateWrapper<KnowledgeAttach>()
-          .set(KnowledgeAttach::getVectorStatus, DealStatus.STATUS_30)
-          .eq(KnowledgeAttach::getPicStatus, DealStatus.STATUS_30)
-          .eq(KnowledgeAttach::getPicAnysStatus, DealStatus.STATUS_30)
-          .eq(KnowledgeAttach::getVectorStatus, DealStatus.STATUS_20)
-          .eq(KnowledgeAttach::getId, attachItem.getId()));
-    } catch (Exception e) {
-      //设置处理失败
-      attachMapper.update(new LambdaUpdateWrapper<KnowledgeAttach>()
-          .set(KnowledgeAttach::getVectorStatus, DealStatus.STATUS_10)
-          .eq(KnowledgeAttach::getPicStatus, DealStatus.STATUS_30)
-          .eq(KnowledgeAttach::getPicAnysStatus, DealStatus.STATUS_30)
-          .eq(KnowledgeAttach::getVectorStatus, DealStatus.STATUS_20)
-          .eq(KnowledgeAttach::getId, attachItem.getId()));
-      throw new RuntimeException(e);
-    }
-  }
-
 }

script/sql/update/20250514.sql

@@ -0,0 +1,6 @@
+LTER TABLE `knowledge_info`
+ADD COLUMN `system_prompt` varchar(255) NULL COMMENT '系统提示词' AFTER `vector_model`;
+
+ALTER TABLE `knowledge_info`
+    CHANGE COLUMN `vector` `vector_model_name` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL COMMENT '向量库' AFTER `text_block_size`,
+    CHANGE COLUMN `vector_model` `embedding_model_name` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL COMMENT '向量模型' AFTER `vector_model_name`;