diff --git a/ruoyi-common/ruoyi-common-core/src/main/java/org/ruoyi/common/core/config/VectorStoreProperties.java b/ruoyi-common/ruoyi-common-core/src/main/java/org/ruoyi/common/core/config/VectorStoreProperties.java index 98f3ddc4..b4bb135d 100644 --- a/ruoyi-common/ruoyi-common-core/src/main/java/org/ruoyi/common/core/config/VectorStoreProperties.java +++ b/ruoyi-common/ruoyi-common-core/src/main/java/org/ruoyi/common/core/config/VectorStoreProperties.java @@ -17,7 +17,7 @@ public class VectorStoreProperties { /** * 向量库类型 */ - private String type = "weaviate"; + private String type; /** * Weaviate配置 @@ -34,17 +34,17 @@ public class VectorStoreProperties { /** * 协议 */ - private String protocol = "http"; + private String protocol; /** * 主机地址 */ - private String host = "localhost:8080"; + private String host; /** * 类名 */ - private String classname = "Document"; + private String classname; } @Data @@ -52,11 +52,11 @@ public class VectorStoreProperties { /** * 连接URL */ - private String url = "http://localhost:19530"; + private String url; /** * 集合名称 */ - private String collectionname = "knowledge_base"; + private String collectionname; } } \ No newline at end of file diff --git a/ruoyi-modules-api/ruoyi-chat-api/src/main/java/org/ruoyi/domain/vo/ChatModelVo.java b/ruoyi-modules-api/ruoyi-chat-api/src/main/java/org/ruoyi/domain/vo/ChatModelVo.java index 6a2de3cf..062a378a 100644 --- a/ruoyi-modules-api/ruoyi-chat-api/src/main/java/org/ruoyi/domain/vo/ChatModelVo.java +++ b/ruoyi-modules-api/ruoyi-chat-api/src/main/java/org/ruoyi/domain/vo/ChatModelVo.java @@ -70,6 +70,11 @@ public class ChatModelVo implements Serializable { @ExcelProperty(value = "是否显示") private String modelShow; + /** + * 模型维度 + */ + private Integer dimension; + /** * 系统提示词 */ diff --git a/ruoyi-modules-api/ruoyi-knowledge-api/pom.xml b/ruoyi-modules-api/ruoyi-knowledge-api/pom.xml index 90933a7d..11360516 100644 --- a/ruoyi-modules-api/ruoyi-knowledge-api/pom.xml +++ b/ruoyi-modules-api/ruoyi-knowledge-api/pom.xml @@ -80,6 +80,12 @@ 2.6.4 + + + dev.langchain4j + langchain4j-milvus + + dev.langchain4j langchain4j-open-ai diff --git a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/domain/bo/StoreEmbeddingBo.java b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/domain/bo/StoreEmbeddingBo.java index 2b87ce05..eedfe4d6 100644 --- a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/domain/bo/StoreEmbeddingBo.java +++ b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/domain/bo/StoreEmbeddingBo.java @@ -32,9 +32,9 @@ public class StoreEmbeddingBo { private List fids; /** - * 向量库模型名称 + * 向量库名称 */ - private String vectorModelName; + private String vectorStoreName; /** * 向量化模型id diff --git a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/EmbeddingModelFactory.java b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/EmbeddingModelFactory.java index cf0c7b60..3acf8a91 100644 --- a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/EmbeddingModelFactory.java +++ b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/EmbeddingModelFactory.java @@ -27,20 +27,23 @@ public class EmbeddingModelFactory { private final IChatModelService chatModelService; // 模型缓存，使用ConcurrentHashMap保证线程安全 - private final Map modelCache = new ConcurrentHashMap<>(); + private final Map modelCache = new ConcurrentHashMap<>(); /** * 创建嵌入模型实例 * 如果模型已存在于缓存中，则直接返回；否则创建新的实例 * - * @param embeddingModelId 嵌入模型的唯一标识ID - * @return BaseEmbedModelService 嵌入模型服务实例 + * @param embeddingModelName 嵌入模型名称 + * @param dimension 模型维度大小 */ - public BaseEmbedModelService createModel(Long embeddingModelId) { - return modelCache.computeIfAbsent(embeddingModelId, id -> { - ChatModelVo modelConfig = chatModelService.queryById(id); + public BaseEmbedModelService createModel(String embeddingModelName, Integer dimension) { + return modelCache.computeIfAbsent(embeddingModelName, name -> { + ChatModelVo modelConfig = chatModelService.selectModelByName(embeddingModelName); if (modelConfig == null) { - throw new IllegalArgumentException("未找到模型配置，ID=" + id); + throw new IllegalArgumentException("未找到模型配置，name=" + name); + } + if (modelConfig.getDimension() != null) { + modelConfig.setDimension(dimension); } return createModelInstance(modelConfig.getProviderName(), modelConfig); }); @@ -49,22 +52,22 @@ public class EmbeddingModelFactory { /** * 检查模型是否支持多模态 * - * @param embeddingModelId 嵌入模型的唯一标识ID + * @param embeddingModelName 嵌入模型名称 * @return boolean 如果模型支持多模态则返回true，否则返回false */ - public boolean isMultimodalModel(Long embeddingModelId) { - return createModel(embeddingModelId) instanceof MultiModalEmbedModelService; + public boolean isMultimodalModel(String embeddingModelName) { + return createModel(embeddingModelName, null) instanceof MultiModalEmbedModelService; } /** * 创建多模态嵌入模型实例 * - * @param tenantId 租户ID + * @param embeddingModelName 嵌入模型名称 * @return MultiModalEmbedModelService 多模态嵌入模型服务实例 * @throws IllegalArgumentException 当模型不支持多模态时抛出 */ - public MultiModalEmbedModelService createMultimodalModel(Long tenantId) { - BaseEmbedModelService model = createModel(tenantId); + public MultiModalEmbedModelService createMultimodalModel(String embeddingModelName) { + BaseEmbedModelService model = createModel(embeddingModelName, null); if (model instanceof MultiModalEmbedModelService) { return (MultiModalEmbedModelService) model; } diff --git a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/impl/OllamaEmbeddingProvider.java b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/impl/OllamaEmbeddingProvider.java index 17ed798c..1a179be7 100644 --- a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/impl/OllamaEmbeddingProvider.java +++ b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/impl/OllamaEmbeddingProvider.java @@ -30,6 +30,7 @@ public class OllamaEmbeddingProvider implements BaseEmbedModelService { return Set.of(ModalityType.TEXT); } + // ollama不能设置embedding维度，使用milvus时请注意！！创建向量表时需要先设定维度大小 @Override public Response> embedAll(List textSegments) { return OllamaEmbeddingModel.builder() diff --git a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/impl/OpenAiEmbeddingProvider.java b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/impl/OpenAiEmbeddingProvider.java index e58bfe46..8a0c9f62 100644 --- a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/impl/OpenAiEmbeddingProvider.java +++ b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/impl/OpenAiEmbeddingProvider.java @@ -37,6 +37,7 @@ public class OpenAiEmbeddingProvider implements BaseEmbedModelService { .baseUrl(chatModelVo.getApiHost()) .apiKey(chatModelVo.getApiKey()) .modelName(chatModelVo.getModelName()) + .dimensions(chatModelVo.getDimension()) .build() .embedAll(textSegments); } diff --git a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/impl/ZhiPuAiEmbeddingProvider.java b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/impl/ZhiPuAiEmbeddingProvider.java index e221749a..621e47c6 100644 --- a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/impl/ZhiPuAiEmbeddingProvider.java +++ b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/embedding/impl/ZhiPuAiEmbeddingProvider.java @@ -37,6 +37,7 @@ public class ZhiPuAiEmbeddingProvider implements BaseEmbedModelService { .baseUrl(chatModelVo.getApiHost()) .apiKey(chatModelVo.getApiKey()) .model(chatModelVo.getModelName()) + .dimensions(chatModelVo.getDimension()) .build() .embedAll(textSegments); } diff --git a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/VectorStoreService.java b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/VectorStoreService.java index 4e78f6f3..2937fc44 100644 --- a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/VectorStoreService.java +++ b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/VectorStoreService.java @@ -16,7 +16,7 @@ public interface VectorStoreService { List getQueryVector(QueryVectorBo queryVectorBo); - void createSchema(String vectorModelName, String kid,String modelName); + void createSchema(String kid, String embeddingModelName); void removeById(String id,String modelName) throws ServiceException; diff --git a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/impl/VectorStoreServiceImpl.java b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/impl/VectorStoreServiceImpl.java index 58b44f25..c9aeeab4 100644 --- a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/impl/VectorStoreServiceImpl.java +++ b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/impl/VectorStoreServiceImpl.java @@ -2,16 +2,13 @@ package org.ruoyi.service.impl; import lombok.RequiredArgsConstructor; 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.service.VectorStoreService; -import org.ruoyi.service.strategy.VectorStoreStrategy; import org.ruoyi.service.strategy.VectorStoreStrategyFactory; import org.springframework.context.annotation.Primary; import org.springframework.stereotype.Service; import java.util.*; -import java.util.stream.Collectors; /** * 向量库管理 @@ -30,22 +27,21 @@ public class VectorStoreServiceImpl implements VectorStoreService { /** * 获取当前配置的向量库策略 */ - private VectorStoreStrategy getCurrentStrategy() { + private VectorStoreService getCurrentStrategy() { return strategyFactory.getStrategy(); } @Override - public void createSchema(String vectorModelName, String kid, String modelName) { - log.info("创建向量库schema: vectorModelName={}, kid={}, modelName={}", vectorModelName, kid, modelName); - VectorStoreStrategy strategy = getCurrentStrategy(); - strategy.createSchema(vectorModelName, kid, modelName); + public void createSchema(String kid, String modelName) { + VectorStoreService strategy = getCurrentStrategy(); + strategy.createSchema(kid, modelName); } @Override public void storeEmbeddings(StoreEmbeddingBo storeEmbeddingBo) { log.info("存储向量数据: kid={}, docId={}, 数据条数={}", storeEmbeddingBo.getKid(), storeEmbeddingBo.getDocId(), storeEmbeddingBo.getChunkList().size()); - VectorStoreStrategy strategy = getCurrentStrategy(); + VectorStoreService strategy = getCurrentStrategy(); strategy.storeEmbeddings(storeEmbeddingBo); } @@ -53,28 +49,28 @@ public class VectorStoreServiceImpl implements VectorStoreService { public List getQueryVector(QueryVectorBo queryVectorBo) { log.info("查询向量数据: kid={}, query={}, maxResults={}", queryVectorBo.getKid(), queryVectorBo.getQuery(), queryVectorBo.getMaxResults()); - VectorStoreStrategy strategy = getCurrentStrategy(); + VectorStoreService strategy = getCurrentStrategy(); return strategy.getQueryVector(queryVectorBo); } @Override public void removeById(String id, String modelName) { log.info("根据ID删除向量数据: id={}, modelName={}", id, modelName); - VectorStoreStrategy strategy = getCurrentStrategy(); + VectorStoreService strategy = getCurrentStrategy(); strategy.removeById(id, modelName); } @Override public void removeByDocId(String docId, String kid) { log.info("根据docId删除向量数据: docId={}, kid={}", docId, kid); - VectorStoreStrategy strategy = getCurrentStrategy(); + VectorStoreService strategy = getCurrentStrategy(); strategy.removeByDocId(docId, kid); } @Override public void removeByFid(String fid, String kid) { log.info("根据fid删除向量数据: fid={}, kid={}", fid, kid); - VectorStoreStrategy strategy = getCurrentStrategy(); + VectorStoreService strategy = getCurrentStrategy(); strategy.removeByFid(fid, kid); } } diff --git a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/AbstractVectorStoreStrategy.java b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/AbstractVectorStoreStrategy.java index 7fdeb195..d35d9739 100644 --- a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/AbstractVectorStoreStrategy.java +++ b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/AbstractVectorStoreStrategy.java @@ -8,40 +8,30 @@ import lombok.RequiredArgsConstructor; import lombok.SneakyThrows; import lombok.extern.slf4j.Slf4j; import org.ruoyi.common.core.config.VectorStoreProperties; +import org.ruoyi.common.core.utils.StringUtils; +import org.ruoyi.service.VectorStoreService; +import org.ruoyi.embedding.EmbeddingModelFactory; /** * 向量库策略抽象基类 * 提供公共的方法实现，如embedding模型获取等 * - * @author ageer + * @author Yzm */ @Slf4j @RequiredArgsConstructor -public abstract class AbstractVectorStoreStrategy implements VectorStoreStrategy { +public abstract class AbstractVectorStoreStrategy implements VectorStoreService { protected final VectorStoreProperties vectorStoreProperties; + private final EmbeddingModelFactory embeddingModelFactory; + /** * 获取向量模型 */ @SneakyThrows - protected 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; + protected EmbeddingModel getEmbeddingModel(String modelName, Integer dimension) { + return embeddingModelFactory.createModel(modelName, dimension); } /** diff --git a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/VectorStoreStrategy.java b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/VectorStoreStrategy.java deleted file mode 100644 index bd93e6fa..00000000 --- a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/VectorStoreStrategy.java +++ /dev/null @@ -1,18 +0,0 @@ -package org.ruoyi.service.strategy; - -import org.ruoyi.service.VectorStoreService; - -/** - * 向量库策略接口 - * 继承VectorStoreService以避免重复定义相同的方法 - * - * @author ageer - */ -public interface VectorStoreStrategy extends VectorStoreService { - - /** - * 获取向量库类型标识 - * @return 向量库类型（如：weaviate, milvus） - */ - String getVectorStoreType(); -} \ No newline at end of file diff --git a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/VectorStoreStrategyFactory.java b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/VectorStoreStrategyFactory.java index fbd5b27b..0bab68cc 100644 --- a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/VectorStoreStrategyFactory.java +++ b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/VectorStoreStrategyFactory.java @@ -6,6 +6,7 @@ import lombok.extern.slf4j.Slf4j; import org.ruoyi.common.core.config.VectorStoreProperties; import org.ruoyi.service.strategy.impl.MilvusVectorStoreStrategy; import org.ruoyi.service.strategy.impl.WeaviateVectorStoreStrategy; +import org.ruoyi.service.VectorStoreService; import org.springframework.stereotype.Component; import java.util.HashMap; @@ -15,7 +16,7 @@ import java.util.Map; * 向量库策略工厂 * 根据配置动态选择向量库实现 * - * @author ageer + * @author Yzm */ @Slf4j @Component @@ -26,7 +27,7 @@ public class VectorStoreStrategyFactory { private final WeaviateVectorStoreStrategy weaviateStrategy; private final MilvusVectorStoreStrategy milvusStrategy; - private Map strategies; + private Map strategies; @PostConstruct public void init() { @@ -39,36 +40,18 @@ public class VectorStoreStrategyFactory { /** * 获取当前配置的向量库策略 */ - public VectorStoreStrategy getStrategy() { + public VectorStoreService getStrategy() { String vectorStoreType = vectorStoreProperties.getType(); if (vectorStoreType == null || vectorStoreType.trim().isEmpty()) { vectorStoreType = "weaviate"; // 默认使用weaviate } - - VectorStoreStrategy strategy = strategies.get(vectorStoreType.toLowerCase()); + VectorStoreService strategy = strategies.get(vectorStoreType.toLowerCase()); if (strategy == null) { log.warn("未找到向量库策略: {}, 使用默认策略: weaviate", vectorStoreType); strategy = strategies.get("weaviate"); } - log.debug("使用向量库策略: {}", vectorStoreType); return strategy; } - /** - * 根据类型获取向量库策略 - */ - public VectorStoreStrategy getStrategy(String type) { - if (type == null || type.trim().isEmpty()) { - return getStrategy(); - } - - VectorStoreStrategy strategy = strategies.get(type.toLowerCase()); - if (strategy == null) { - log.warn("未找到向量库策略: {}, 使用默认策略", type); - return getStrategy(); - } - - return strategy; - } } \ No newline at end of file diff --git a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/impl/MilvusVectorStoreStrategy.java b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/impl/MilvusVectorStoreStrategy.java index 26a09f1f..8d3d50fa 100644 --- a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/impl/MilvusVectorStoreStrategy.java +++ b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/impl/MilvusVectorStoreStrategy.java @@ -1,337 +1,157 @@ package org.ruoyi.service.strategy.impl; -import org.ruoyi.common.core.exception.ServiceException; +import dev.langchain4j.data.document.Metadata; import dev.langchain4j.data.embedding.Embedding; +import dev.langchain4j.data.segment.TextSegment; import dev.langchain4j.model.embedding.EmbeddingModel; -import io.milvus.client.MilvusServiceClient; -import io.milvus.common.clientenum.ConsistencyLevelEnum; -import io.milvus.grpc.*; -import io.milvus.param.*; -import io.milvus.param.collection.*; -import io.milvus.param.dml.DeleteParam; -import io.milvus.param.dml.InsertParam; -import io.milvus.param.dml.SearchParam; -import io.milvus.param.index.CreateIndexParam; -import io.milvus.param.index.DescribeIndexParam; -import io.milvus.response.DescCollResponseWrapper; -import io.milvus.response.SearchResultsWrapper; +import dev.langchain4j.store.embedding.EmbeddingMatch; +import dev.langchain4j.store.embedding.EmbeddingSearchRequest; +import dev.langchain4j.store.embedding.EmbeddingStore; +import dev.langchain4j.store.embedding.filter.Filter; +import dev.langchain4j.store.embedding.filter.MetadataFilterBuilder; +import dev.langchain4j.store.embedding.milvus.MilvusEmbeddingStore; +import io.milvus.param.IndexType; +import io.milvus.param.MetricType; import lombok.SneakyThrows; import lombok.extern.slf4j.Slf4j; import org.ruoyi.common.core.config.VectorStoreProperties; import org.ruoyi.domain.bo.QueryVectorBo; import org.ruoyi.domain.bo.StoreEmbeddingBo; +import org.ruoyi.embedding.EmbeddingModelFactory; import org.ruoyi.service.strategy.AbstractVectorStoreStrategy; import org.springframework.stereotype.Component; -import java.util.*; +import java.util.ArrayList; +import java.util.List; +import java.util.Map; +import java.util.concurrent.ConcurrentHashMap; +import java.util.stream.IntStream; -/** - * Milvus向量库策略实现 - * - * @author ageer - */ @Slf4j @Component public class MilvusVectorStoreStrategy extends AbstractVectorStoreStrategy { - private MilvusServiceClient milvusClient; - public MilvusVectorStoreStrategy(VectorStoreProperties vectorStoreProperties) { - super(vectorStoreProperties); + private final Integer DIMENSION = 2048; + + public MilvusVectorStoreStrategy(VectorStoreProperties vectorStoreProperties, EmbeddingModelFactory embeddingModelFactory) { + super(vectorStoreProperties, embeddingModelFactory); + } + + // 缓存不同集合与 autoFlush 配置的 Milvus 连接 + private final Map> storeCache = new ConcurrentHashMap<>(); + + private EmbeddingStore getMilvusStore(String collectionName, boolean autoFlushOnInsert) { + String key = collectionName + "|" + autoFlushOnInsert; + return storeCache.computeIfAbsent(key, k -> + MilvusEmbeddingStore.builder() + .uri(vectorStoreProperties.getMilvus().getUrl()) + .collectionName(collectionName) + .dimension(DIMENSION) + .indexType(IndexType.IVF_FLAT) + .metricType(MetricType.L2) + .autoFlushOnInsert(autoFlushOnInsert) + .idFieldName("id") + .textFieldName("text") + .metadataFieldName("metadata") + .vectorFieldName("vector") + .build() + ); } @Override - public String getVectorStoreType() { - return "milvus"; - } - - @Override - public void createSchema(String vectorModelName, String kid, String modelName) { - String url = vectorStoreProperties.getMilvus().getUrl(); + public void createSchema(String kid, String modelName) { String collectionName = vectorStoreProperties.getMilvus().getCollectionname() + kid; - - // 创建Milvus客户端连接 - ConnectParam connectParam = ConnectParam.newBuilder() - .withUri(url) - .build(); - milvusClient = new MilvusServiceClient(connectParam); - - // 检查集合是否存在 - HasCollectionParam hasCollectionParam = HasCollectionParam.newBuilder() - .withCollectionName(collectionName) - .build(); - - R hasCollectionResponse = milvusClient.hasCollection(hasCollectionParam); - if (hasCollectionResponse.getStatus() != R.Status.Success.getCode()) { - log.error("检查集合是否存在失败: {}", hasCollectionResponse.getMessage()); - return; - } - - if (!hasCollectionResponse.getData()) { - // 创建字段 - List fields = new ArrayList<>(); - - // ID字段 (主键) - fields.add(FieldType.newBuilder() - .withName("id") - .withDataType(DataType.Int64) - .withPrimaryKey(true) - .withAutoID(true) - .build()); - - // 文本字段 - fields.add(FieldType.newBuilder() - .withName("text") - .withDataType(DataType.VarChar) - .withMaxLength(65535) - .build()); - - // fid字段 - fields.add(FieldType.newBuilder() - .withName("fid") - .withDataType(DataType.VarChar) - .withMaxLength(255) - .build()); - - // kid字段 - fields.add(FieldType.newBuilder() - .withName("kid") - .withDataType(DataType.VarChar) - .withMaxLength(255) - .build()); - - // docId字段 - fields.add(FieldType.newBuilder() - .withName("docId") - .withDataType(DataType.VarChar) - .withMaxLength(255) - .build()); - - // 向量字段 - fields.add(FieldType.newBuilder() - .withName("vector") - .withDataType(DataType.FloatVector) - .withDimension(1024) // 根据实际embedding维度调整 - .build()); - - // 创建集合 - CreateCollectionParam createCollectionParam = CreateCollectionParam.newBuilder() - .withCollectionName(collectionName) - .withDescription("Knowledge base collection for " + kid) - .withShardsNum(2) - .withFieldTypes(fields) - .build(); - - R createCollectionResponse = milvusClient.createCollection(createCollectionParam); - if (createCollectionResponse.getStatus() != R.Status.Success.getCode()) { - log.error("创建集合失败: {}", createCollectionResponse.getMessage()); - return; - } - - // 创建索引 - CreateIndexParam createIndexParam = CreateIndexParam.newBuilder() - .withCollectionName(collectionName) - .withFieldName("vector") - .withIndexType(IndexType.IVF_FLAT) - .withMetricType(MetricType.L2) - .withExtraParam("{\"nlist\":1024}") - .build(); - - R createIndexResponse = milvusClient.createIndex(createIndexParam); - if (createIndexResponse.getStatus() != R.Status.Success.getCode()) { - log.error("创建索引失败: {}", createIndexResponse.getMessage()); - } else { - log.info("Milvus集合和索引创建成功: {}", collectionName); - } - } else { - log.info("Milvus集合已存在: {}", collectionName); - } + // 使用缓存获取连接以确保只初始化一次 + EmbeddingStore store = getMilvusStore(collectionName, true); + log.info("Milvus集合初始化完成: {}", collectionName); } @Override public void storeEmbeddings(StoreEmbeddingBo storeEmbeddingBo) { - createSchema(storeEmbeddingBo.getVectorModelName(), storeEmbeddingBo.getKid(), storeEmbeddingBo.getVectorModelName()); - - EmbeddingModel embeddingModel = getEmbeddingModel(storeEmbeddingBo.getEmbeddingModelName(), - storeEmbeddingBo.getApiKey(), storeEmbeddingBo.getBaseUrl()); - + EmbeddingModel embeddingModel = getEmbeddingModel(storeEmbeddingBo.getEmbeddingModelName(), DIMENSION); + List chunkList = storeEmbeddingBo.getChunkList(); List fidList = storeEmbeddingBo.getFids(); String kid = storeEmbeddingBo.getKid(); String docId = storeEmbeddingBo.getDocId(); String collectionName = vectorStoreProperties.getMilvus().getCollectionname() + kid; - - log.info("Milvus向量存储条数记录: " + chunkList.size()); + + log.info("Milvus向量存储条数记录: {}", chunkList.size()); long startTime = System.currentTimeMillis(); - - // 准备批量插入数据 - List fields = new ArrayList<>(); - List textList = new ArrayList<>(); - List fidListData = new ArrayList<>(); - List kidList = new ArrayList<>(); - List docIdList = new ArrayList<>(); - List> vectorList = new ArrayList<>(); - - for (int i = 0; i < chunkList.size(); i++) { + + // 复用连接，写入场景使用 autoFlush=false 以提升批量插入性能 + EmbeddingStore embeddingStore = getMilvusStore(collectionName, false); + + IntStream.range(0, chunkList.size()).forEach(i -> { String text = chunkList.get(i); String fid = fidList.get(i); + Metadata metadata = new Metadata(); + metadata.put("fid", fid); + metadata.put("kid", kid); + metadata.put("docId", docId); + + TextSegment textSegment = TextSegment.from(text, metadata); Embedding embedding = embeddingModel.embed(text).content(); - - textList.add(text); - fidListData.add(fid); - kidList.add(kid); - docIdList.add(docId); - - List vector = new ArrayList<>(); - for (float f : embedding.vector()) { - vector.add(f); - } - vectorList.add(vector); - } - - // 构建字段数据 - fields.add(new InsertParam.Field("text", textList)); - fields.add(new InsertParam.Field("fid", fidListData)); - fields.add(new InsertParam.Field("kid", kidList)); - fields.add(new InsertParam.Field("docId", docIdList)); - fields.add(new InsertParam.Field("vector", vectorList)); - - // 执行插入 - InsertParam insertParam = InsertParam.newBuilder() - .withCollectionName(collectionName) - .withFields(fields) - .build(); - - R insertResponse = milvusClient.insert(insertParam); - if (insertResponse.getStatus() != R.Status.Success.getCode()) { - log.error("Milvus向量存储失败: {}", insertResponse.getMessage()); - throw new ServiceException("Milvus向量存储失败"); - } else { - log.info("Milvus向量存储成功，插入条数: {}", insertResponse.getData().getInsertCnt()); - } - + embeddingStore.add(embedding, textSegment); + }); long endTime = System.currentTimeMillis(); - log.info("Milvus向量存储完成消耗时间：" + (endTime - startTime) / 1000 + "秒"); + log.info("Milvus向量存储完成消耗时间：{}秒", (endTime - startTime) / 1000); } @Override public List getQueryVector(QueryVectorBo queryVectorBo) { - createSchema(queryVectorBo.getVectorModelName(), queryVectorBo.getKid(), queryVectorBo.getVectorModelName()); - - EmbeddingModel embeddingModel = getEmbeddingModel(queryVectorBo.getEmbeddingModelName(), - queryVectorBo.getApiKey(), queryVectorBo.getBaseUrl()); - + EmbeddingModel embeddingModel = getEmbeddingModel(queryVectorBo.getEmbeddingModelName(), DIMENSION); + Embedding queryEmbedding = embeddingModel.embed(queryVectorBo.getQuery()).content(); String collectionName = vectorStoreProperties.getMilvus().getCollectionname() + queryVectorBo.getKid(); - + + // 查询复用连接，autoFlush 对查询无影响，此处保持 true + EmbeddingStore embeddingStore = getMilvusStore(collectionName, true); + List resultList = new ArrayList<>(); - - // 加载集合到内存 - LoadCollectionParam loadCollectionParam = LoadCollectionParam.newBuilder() - .withCollectionName(collectionName) + EmbeddingSearchRequest request = EmbeddingSearchRequest.builder() + .queryEmbedding(queryEmbedding) + .maxResults(queryVectorBo.getMaxResults()) .build(); - milvusClient.loadCollection(loadCollectionParam); - - // 准备查询向量 - List> searchVectors = new ArrayList<>(); - List queryVector = new ArrayList<>(); - for (float f : queryEmbedding.vector()) { - queryVector.add(f); - } - searchVectors.add(queryVector); - - // 构建搜索参数 - SearchParam searchParam = SearchParam.newBuilder() - .withCollectionName(collectionName) - .withMetricType(MetricType.L2) - .withOutFields(Arrays.asList("text", "fid", "kid", "docId")) - .withTopK(queryVectorBo.getMaxResults()) - .withVectors(searchVectors) - .withVectorFieldName("vector") - .withParams("{\"nprobe\":10}") - .build(); - - R searchResponse = milvusClient.search(searchParam); - if (searchResponse.getStatus() != R.Status.Success.getCode()) { - log.error("Milvus查询失败: {}", searchResponse.getMessage()); - return resultList; - } - - SearchResultsWrapper wrapper = new SearchResultsWrapper(searchResponse.getData().getResults()); - - // 遍历搜索结果 - for (int i = 0; i < wrapper.getIDScore(0).size(); i++) { - SearchResultsWrapper.IDScore idScore = wrapper.getIDScore(0).get(i); - - // 获取text字段数据 - List textFieldData = wrapper.getFieldData("text", 0); - if (textFieldData != null && i < textFieldData.size()) { - Object textObj = textFieldData.get(i); - if (textObj != null) { - resultList.add(textObj.toString()); - log.debug("找到相似文本，ID: {}, 距离: {}, 内容: {}", - idScore.getLongID(), idScore.getScore(), textObj.toString()); - } + List> matches = embeddingStore.search(request).matches(); + for (EmbeddingMatch match : matches) { + TextSegment segment = match.embedded(); + if (segment != null) { + resultList.add(segment.text()); } } - return resultList; } @Override @SneakyThrows public void removeById(String id, String modelName) { - String collectionName = vectorStoreProperties.getMilvus().getCollectionname() + id; - - // 删除整个集合 - DropCollectionParam dropCollectionParam = DropCollectionParam.newBuilder() - .withCollectionName(collectionName) - .build(); - - R dropResponse = milvusClient.dropCollection(dropCollectionParam); - if (dropResponse.getStatus() != R.Status.Success.getCode()) { - log.error("Milvus集合删除失败: {}", dropResponse.getMessage()); - throw new ServiceException("Milvus集合删除失败"); - } else { - log.info("Milvus集合删除成功: {}", collectionName); - } + // 注意：此处原逻辑使用 collectionname + id，保持现状 + EmbeddingStore embeddingStore = getMilvusStore(vectorStoreProperties.getMilvus().getCollectionname() + id, false); + embeddingStore.remove(id); } @Override public void removeByDocId(String docId, String kid) { String collectionName = vectorStoreProperties.getMilvus().getCollectionname() + kid; - - String expr = "docId == \"" + docId + "\""; - DeleteParam deleteParam = DeleteParam.newBuilder() - .withCollectionName(collectionName) - .withExpr(expr) - .build(); - - R deleteResponse = milvusClient.delete(deleteParam); - if (deleteResponse.getStatus() != R.Status.Success.getCode()) { - log.error("Milvus删除失败: {}", deleteResponse.getMessage()); - throw new ServiceException("Milvus删除失败"); - } else { - log.info("Milvus成功删除 docId={} 的所有向量数据，删除条数: {}", docId, deleteResponse.getData().getDeleteCnt()); - } + EmbeddingStore embeddingStore = getMilvusStore(collectionName, false); + Filter filter = MetadataFilterBuilder.metadataKey("docId").isEqualTo(docId); + embeddingStore.removeAll(filter); + log.info("Milvus成功删除 docId={} 的所有向量数据", docId); } @Override public void removeByFid(String fid, String kid) { String collectionName = vectorStoreProperties.getMilvus().getCollectionname() + kid; - - String expr = "fid == \"" + fid + "\""; - DeleteParam deleteParam = DeleteParam.newBuilder() - .withCollectionName(collectionName) - .withExpr(expr) - .build(); - - R deleteResponse = milvusClient.delete(deleteParam); - if (deleteResponse.getStatus() != R.Status.Success.getCode()) { - log.error("Milvus删除失败: {}", deleteResponse.getMessage()); - throw new ServiceException("Milvus删除失败"); - } else { - log.info("Milvus成功删除 fid={} 的所有向量数据，删除条数: {}", fid, deleteResponse.getData().getDeleteCnt()); - } + EmbeddingStore embeddingStore = getMilvusStore(collectionName, false); + Filter filter = MetadataFilterBuilder.metadataKey("fid").isEqualTo(fid); + embeddingStore.removeAll(filter); + log.info("Milvus成功删除 fid={} 的所有向量数据", fid); } -} \ No newline at end of file + + @Override + public String getVectorStoreType() { + return "milvus"; + } +} diff --git a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/impl/WeaviateVectorStoreStrategy.java b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/impl/WeaviateVectorStoreStrategy.java index 6275d939..3d61f8ac 100644 --- a/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/impl/WeaviateVectorStoreStrategy.java +++ b/ruoyi-modules-api/ruoyi-knowledge-api/src/main/java/org/ruoyi/service/strategy/impl/WeaviateVectorStoreStrategy.java @@ -20,6 +20,7 @@ import lombok.extern.slf4j.Slf4j; import org.ruoyi.common.core.config.VectorStoreProperties; import org.ruoyi.domain.bo.QueryVectorBo; import org.ruoyi.domain.bo.StoreEmbeddingBo; +import org.ruoyi.embedding.EmbeddingModelFactory; import org.ruoyi.service.strategy.AbstractVectorStoreStrategy; import org.springframework.stereotype.Component; import java.util.*; @@ -27,7 +28,7 @@ import java.util.*; /** * Weaviate向量库策略实现 * - * @author ageer + * @author Yzm */ @Slf4j @Component @@ -35,8 +36,8 @@ public class WeaviateVectorStoreStrategy extends AbstractVectorStoreStrategy { private WeaviateClient client; - public WeaviateVectorStoreStrategy(VectorStoreProperties vectorStoreProperties) { - super(vectorStoreProperties); + public WeaviateVectorStoreStrategy(VectorStoreProperties vectorStoreProperties, EmbeddingModelFactory embeddingModelFactory) { + super(vectorStoreProperties, embeddingModelFactory); } @Override @@ -45,7 +46,7 @@ public class WeaviateVectorStoreStrategy extends AbstractVectorStoreStrategy { } @Override - public void createSchema(String vectorModelName, String kid, String modelName) { + public void createSchema(String kid, String embeddingModelName) { String protocol = vectorStoreProperties.getWeaviate().getProtocol(); String host = vectorStoreProperties.getWeaviate().getHost(); String className = vectorStoreProperties.getWeaviate().getClassname() + kid; @@ -84,9 +85,8 @@ public class WeaviateVectorStoreStrategy extends AbstractVectorStoreStrategy { @Override public void storeEmbeddings(StoreEmbeddingBo storeEmbeddingBo) { - createSchema(storeEmbeddingBo.getVectorModelName(), storeEmbeddingBo.getKid(), storeEmbeddingBo.getVectorModelName()); - EmbeddingModel embeddingModel = getEmbeddingModel(storeEmbeddingBo.getEmbeddingModelName(), - storeEmbeddingBo.getApiKey(), storeEmbeddingBo.getBaseUrl()); + createSchema(storeEmbeddingBo.getKid(),storeEmbeddingBo.getEmbeddingModelName()); + EmbeddingModel embeddingModel = getEmbeddingModel(storeEmbeddingBo.getEmbeddingModelName(), null); List chunkList = storeEmbeddingBo.getChunkList(); List fidList = storeEmbeddingBo.getFids(); String kid = storeEmbeddingBo.getKid(); @@ -118,9 +118,8 @@ public class WeaviateVectorStoreStrategy extends AbstractVectorStoreStrategy { @Override public List getQueryVector(QueryVectorBo queryVectorBo) { - createSchema(queryVectorBo.getVectorModelName(), queryVectorBo.getKid(), queryVectorBo.getVectorModelName()); - EmbeddingModel embeddingModel = getEmbeddingModel(queryVectorBo.getEmbeddingModelName(), - queryVectorBo.getApiKey(), queryVectorBo.getBaseUrl()); + createSchema(queryVectorBo.getKid(),queryVectorBo.getEmbeddingModelName()); + EmbeddingModel embeddingModel = getEmbeddingModel(queryVectorBo.getEmbeddingModelName(),null); Embedding queryEmbedding = embeddingModel.embed(queryVectorBo.getQuery()).content(); float[] vector = queryEmbedding.vector(); List vectorStrings = new ArrayList<>(); diff --git a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/chat/service/knowledge/KnowledgeInfoServiceImpl.java b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/chat/service/knowledge/KnowledgeInfoServiceImpl.java index ab5f4ae9..6a588185 100644 --- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/chat/service/knowledge/KnowledgeInfoServiceImpl.java +++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/chat/service/knowledge/KnowledgeInfoServiceImpl.java @@ -9,6 +9,7 @@ import com.baomidou.mybatisplus.extension.plugins.pagination.Page; import lombok.RequiredArgsConstructor; import org.ruoyi.chain.loader.ResourceLoader; import org.ruoyi.chain.loader.ResourceLoaderFactory; +import org.ruoyi.chat.enums.ChatModeType; import org.ruoyi.common.core.domain.model.LoginUser; import org.ruoyi.common.core.utils.MapstructUtils; import org.ruoyi.common.core.utils.StringUtils; @@ -237,8 +238,7 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService { } baseMapper.insert(knowledgeInfo); if (knowledgeInfo != null) { - vectorStoreService.createSchema(knowledgeInfo.getVectorModelName(),String.valueOf(knowledgeInfo.getId()), - bo.getVectorModelName()); + vectorStoreService.createSchema(String.valueOf(knowledgeInfo.getId()), bo.getEmbeddingModelName()); } } else { baseMapper.updateById(knowledgeInfo); @@ -313,15 +313,18 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService { .eq(KnowledgeInfo::getId, kid)); // 通过向量模型查询模型信息 - ChatModelVo chatModelVo = chatModelService.queryById(knowledgeInfoVo.getEmbeddingModelId()); - + ChatModelVo chatModelVo = chatModelService.selectModelByName(knowledgeInfoVo.getEmbeddingModelName()); + // 未查到指定模型时，回退为向量分类最高优先级模型 + if (chatModelVo == null) { + chatModelVo = chatModelService.selectModelByCategoryWithHighestPriority(ChatModeType.VECTOR.getCode()); + } StoreEmbeddingBo storeEmbeddingBo = new StoreEmbeddingBo(); storeEmbeddingBo.setKid(kid); storeEmbeddingBo.setDocId(docId); storeEmbeddingBo.setFids(fids); storeEmbeddingBo.setChunkList(chunkList); - storeEmbeddingBo.setVectorModelName(knowledgeInfoVo.getVectorModelName()); - storeEmbeddingBo.setEmbeddingModelId(knowledgeInfoVo.getEmbeddingModelId()); + storeEmbeddingBo.setVectorStoreName(knowledgeInfoVo.getVectorModelName()); + storeEmbeddingBo.setEmbeddingModelName(knowledgeInfoVo.getEmbeddingModelName()); storeEmbeddingBo.setApiKey(chatModelVo.getApiKey()); storeEmbeddingBo.setBaseUrl(chatModelVo.getApiHost()); vectorStoreService.storeEmbeddings(storeEmbeddingBo);