feat: 优化通过知识库获取模型配置逻辑，修改为通过模型id查找模型配置，避免多供应商同模型映射错误。

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

@@ -83,6 +83,11 @@ public class KnowledgeInfo extends BaseEntity {
      */
     private String vectorModelName;
 
+    /**
+     * 向量化模型id
+     */
+    private Long embeddingModelId;
+
     /**
      * 向量化模型名称
      */

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

@@ -92,7 +92,11 @@ public class KnowledgeInfoBo extends BaseEntity {
     /**
      * 向量化模型名称
      */
-    @NotBlank(message = "向量模型不能为空", groups = { AddGroup.class, EditGroup.class })
+    private Long embeddingModelId;
+
+    /**
+     * 向量化模型名称
+     */
     private String embeddingModelName;
 
 

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

@@ -31,7 +31,12 @@ public class QueryVectorBo {
     private String vectorModelName;
 
     /**
-     * 向量化模型名称
+     * 向量化模型ID
+     */
+    private Long embeddingModelId;
+
+    /**
+     * 向量化模型ID
      */
     private String embeddingModelName;
 

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

@@ -36,6 +36,11 @@ public class StoreEmbeddingBo {
      */
     private String vectorModelName;
 
+    /**
+     * 向量化模型id
+     */
+    private Long embeddingModelId;
+
     /**
      * 向量化模型名称
      */

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

@@ -101,6 +101,11 @@ public class KnowledgeInfoVo implements Serializable {
      */
     private String vectorModelName;
 
+    /**
+     * 向量化模型id
+     */
+    private Long embeddingModelId;
+
     /**
      * 向量化模型名称
      */

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

@@ -28,6 +28,8 @@ import lombok.extern.slf4j.Slf4j;
 import org.ruoyi.common.core.service.ConfigService;
 import org.ruoyi.domain.bo.QueryVectorBo;
 import org.ruoyi.domain.bo.StoreEmbeddingBo;
+import org.ruoyi.embedding.BaseEmbedModelService;
+import org.ruoyi.embedding.EmbeddingModelFactory;
 import org.ruoyi.service.VectorStoreService;
 import org.springframework.stereotype.Service;
 import java.util.*;
@@ -48,6 +50,8 @@ public class VectorStoreServiceImpl implements VectorStoreService {
 //    private EmbeddingStore<TextSegment> embeddingStore;
     private WeaviateClient client;
 
+    private final EmbeddingModelFactory embeddingModelFactory;
+
 
     @Override
     public void createSchema(String kid, String modelName) {
@@ -98,18 +102,16 @@ public class VectorStoreServiceImpl implements VectorStoreService {
     @Override
     public void storeEmbeddings(StoreEmbeddingBo storeEmbeddingBo) {
         createSchema(storeEmbeddingBo.getKid(), storeEmbeddingBo.getVectorModelName());
-        EmbeddingModel embeddingModel = getEmbeddingModel(storeEmbeddingBo.getEmbeddingModelName(),
-                storeEmbeddingBo.getApiKey(), storeEmbeddingBo.getBaseUrl());
+        BaseEmbedModelService model = embeddingModelFactory.createModel(storeEmbeddingBo.getEmbeddingModelId());
         List<String> chunkList = storeEmbeddingBo.getChunkList();
         List<String> fidList = storeEmbeddingBo.getFids();
         String kid = storeEmbeddingBo.getKid();
         String docId = storeEmbeddingBo.getDocId();
-        log.info("向量存储条数记录: " + chunkList.size());
         long startTime = System.currentTimeMillis();
         for (int i = 0; i < chunkList.size(); i++) {
             String text = chunkList.get(i);
             String fid = fidList.get(i);
-            Embedding embedding = embeddingModel.embed(text).content();
+            Embedding embedding = model.embed(text).content();
             Map<String, Object> properties = Map.of(
                     "text", text,
                     "fid",fid,
@@ -137,9 +139,8 @@ public class VectorStoreServiceImpl implements VectorStoreService {
     @Override
     public List<String> getQueryVector(QueryVectorBo queryVectorBo) {
         createSchema(queryVectorBo.getKid(), queryVectorBo.getVectorModelName());
-        EmbeddingModel embeddingModel = getEmbeddingModel(queryVectorBo.getEmbeddingModelName(),
-                queryVectorBo.getApiKey(), queryVectorBo.getBaseUrl());
-        Embedding queryEmbedding = embeddingModel.embed(queryVectorBo.getQuery()).content();
+        BaseEmbedModelService model = embeddingModelFactory.createModel(queryVectorBo.getEmbeddingModelId());
+        Embedding queryEmbedding = model.embed(queryVectorBo.getQuery()).content();
         float[] vector = queryEmbedding.vector();
         List<String> vectorStrings = new ArrayList<>();
         for (float v : vector) {
@@ -246,28 +247,4 @@ public class VectorStoreServiceImpl implements VectorStoreService {
             log.error("删除失败: {}", result.getError());
         }
     }
-
-    /**
-     * 获取向量模型
-     */
-    @SneakyThrows
-    public EmbeddingModel getEmbeddingModel(String modelName, String apiKey, String baseUrl) {
-        EmbeddingModel embeddingModel;
-        if ("quentinz/bge-large-zh-v1.5".equals(modelName)) {
-            embeddingModel = OllamaEmbeddingModel.builder()
-                    .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/knowledge/KnowledgeInfoServiceImpl.java

@@ -290,7 +290,7 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
                 .eq(KnowledgeInfo::getId, kid));
 
         // 通过向量模型查询模型信息
-        ChatModelVo chatModelVo = chatModelService.selectModelByName(knowledgeInfoVo.getEmbeddingModelName());
+        ChatModelVo chatModelVo = chatModelService.queryById(knowledgeInfoVo.getEmbeddingModelId());
 
         StoreEmbeddingBo storeEmbeddingBo = new StoreEmbeddingBo();
         storeEmbeddingBo.setKid(kid);
@@ -298,7 +298,7 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
         storeEmbeddingBo.setFids(fids);
         storeEmbeddingBo.setChunkList(chunkList);
         storeEmbeddingBo.setVectorModelName(knowledgeInfoVo.getVectorModelName());
-        storeEmbeddingBo.setEmbeddingModelName(knowledgeInfoVo.getEmbeddingModelName());
+        storeEmbeddingBo.setEmbeddingModelId(knowledgeInfoVo.getEmbeddingModelId());
         storeEmbeddingBo.setApiKey(chatModelVo.getApiKey());
         storeEmbeddingBo.setBaseUrl(chatModelVo.getApiHost());
         vectorStoreService.storeEmbeddings(storeEmbeddingBo);

script/sql/update/2025-10-4-多供应商嵌入模型集成.sql

@@ -0,0 +1,13 @@
+-- 为 chat_model 表添加 provider_name 字段
+-- 变更日期: 2025-10-04
+-- 负责人: Robust_H
+-- 说明: 嵌入模型供应商 （用于实现动态选择嵌入模型实现类）
+ALTER TABLE `ruoyi-ai`.chat_model
+    ADD COLUMN `provider_name` varchar(20) DEFAULT NULL COMMENT '模型供应商' AFTER `model_name`;
+
+-- 修改 knowledge_info 中的 ‘embedding_model_name’ 为 ‘embedding_model_id’
+-- 变更日期: 2025-10-04
+-- 负责人: Robust_H
+-- 说明: 用于区分多个供应商实现同一嵌入模型的情况
+ALTER TABLE `ruoyi-ai`.knowledge_info
+    ADD COLUMN `embedding_model_id` bigint DEFAULT NULL COMMENT '模型id' AFTER `embedding_model_name`;