diff --git a/ruoyi-admin/src/main/resources/application.yml b/ruoyi-admin/src/main/resources/application.yml index 5f7179e2..269da7ae 100644 --- a/ruoyi-admin/src/main/resources/application.yml +++ b/ruoyi-admin/src/main/resources/application.yml @@ -275,7 +275,7 @@ warm-flow: # 向量库配置 vector-store: - # 向量存储类型 可选(weaviate/milvus) + # 向量存储类型 可选(weaviate/milvus/qdrant) # 如需修改向量库类型，请修改此配置值! type: milvus # Weaviate配置 @@ -287,3 +287,10 @@ vector-store: milvus: url: http://localhost:19530 collectionname: LocalKnowledge + # Qdrant配置 + qdrant: + host: localhost + port: 6334 + collectionname: LocalKnowledge + api-key: + use-tls: false diff --git a/ruoyi-modules/ruoyi-chat/pom.xml b/ruoyi-modules/ruoyi-chat/pom.xml index ba2f10c0..6cb40321 100644 --- a/ruoyi-modules/ruoyi-chat/pom.xml +++ b/ruoyi-modules/ruoyi-chat/pom.xml @@ -91,6 +91,12 @@ ${langchain4j.community.version} + + dev.langchain4j + langchain4j-qdrant + ${langchain4j.community.version} + + dev.langchain4j langchain4j-mcp diff --git a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/config/VectorStoreProperties.java b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/config/VectorStoreProperties.java index de93372a..83ff47d0 100644 --- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/config/VectorStoreProperties.java +++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/config/VectorStoreProperties.java @@ -59,4 +59,37 @@ public class VectorStoreProperties { */ private String collectionname; } + + /** + * Qdrant配置 + */ + private Qdrant qdrant = new Qdrant(); + + @Data + public static class Qdrant { + /** + * 主机地址 + */ + private String host = "localhost"; + + /** + * gRPC端口 + */ + private int port = 6334; + + /** + * 集合名称 + */ + private String collectionname = "LocalKnowledge"; + + /** + * API密钥（可选） + */ + private String apiKey; + + /** + * 是否启用TLS + */ + private boolean useTls = false; + } } diff --git a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/factory/VectorStoreStrategyFactory.java b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/factory/VectorStoreStrategyFactory.java index cc750a6b..a66ea66c 100644 --- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/factory/VectorStoreStrategyFactory.java +++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/factory/VectorStoreStrategyFactory.java @@ -7,6 +7,7 @@ import lombok.extern.slf4j.Slf4j; import org.ruoyi.config.VectorStoreProperties; import org.ruoyi.service.vector.VectorStoreService; import org.ruoyi.service.vector.impl.MilvusVectorStoreStrategy; +import org.ruoyi.service.vector.impl.QdrantVectorStoreStrategy; import org.ruoyi.service.vector.impl.WeaviateVectorStoreStrategy; import org.springframework.stereotype.Component; @@ -27,6 +28,7 @@ public class VectorStoreStrategyFactory { private final VectorStoreProperties vectorStoreProperties; private final WeaviateVectorStoreStrategy weaviateStrategy; private final MilvusVectorStoreStrategy milvusStrategy; + private final QdrantVectorStoreStrategy qdrantStrategy; private Map strategies; @@ -35,6 +37,7 @@ public class VectorStoreStrategyFactory { strategies = new HashMap<>(); strategies.put("weaviate", weaviateStrategy); strategies.put("milvus", milvusStrategy); + strategies.put("qdrant", qdrantStrategy); log.info("向量库策略工厂初始化完成，支持的策略: {}", strategies.keySet()); } diff --git a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/vector/impl/QdrantVectorStoreStrategy.java b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/vector/impl/QdrantVectorStoreStrategy.java new file mode 100644 index 00000000..3bee80f4 --- /dev/null +++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/vector/impl/QdrantVectorStoreStrategy.java @@ -0,0 +1,204 @@ +package org.ruoyi.service.vector.impl; + +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 dev.langchain4j.store.embedding.EmbeddingStore; +import dev.langchain4j.store.embedding.filter.Filter; +import dev.langchain4j.store.embedding.filter.MetadataFilterBuilder; +import dev.langchain4j.store.embedding.qdrant.QdrantEmbeddingStore; +import io.qdrant.client.QdrantClient; +import io.qdrant.client.QdrantGrpcClient; +import io.qdrant.client.grpc.Collections.Distance; +import io.qdrant.client.grpc.Collections.VectorParams; +import io.qdrant.client.grpc.JsonWithInt; +import io.qdrant.client.grpc.Points.DenseVector; +import io.qdrant.client.grpc.Points.Query; +import io.qdrant.client.grpc.Points.QueryPoints; +import io.qdrant.client.grpc.Points.ScoredPoint; +import io.qdrant.client.grpc.Points.VectorInput; +import lombok.extern.slf4j.Slf4j; +import org.ruoyi.common.chat.service.chat.IChatModelService; +import org.ruoyi.common.core.exception.ServiceException; +import org.ruoyi.config.VectorStoreProperties; +import org.ruoyi.domain.bo.vector.QueryVectorBo; +import org.ruoyi.domain.bo.vector.StoreEmbeddingBo; +import org.ruoyi.factory.EmbeddingModelFactory; +import org.springframework.stereotype.Component; + +import static io.qdrant.client.VectorInputFactory.vectorInput; +import static io.qdrant.client.WithPayloadSelectorFactory.enable; + +import java.util.ArrayList; +import java.util.List; +import java.util.stream.IntStream; + +/** + * Qdrant向量库策略实现 + */ +@Slf4j +@Component +public class QdrantVectorStoreStrategy extends AbstractVectorStoreStrategy { + + private static final String VECTOR_STORE_TYPE = "qdrant"; + private static final String TEXT_SEGMENT_KEY = "text_segment"; + private static final String METADATA_FID_KEY = "fid"; + private static final String METADATA_KID_KEY = "kid"; + private static final String METADATA_DOC_ID_KEY = "docId"; + + public QdrantVectorStoreStrategy(VectorStoreProperties vectorStoreProperties, + IChatModelService chatModelService, + EmbeddingModelFactory embeddingModelFactory) { + super(vectorStoreProperties, embeddingModelFactory, chatModelService); + } + + private EmbeddingStore getQdrantStore(String collectionName) { + VectorStoreProperties.Qdrant cfg = vectorStoreProperties.getQdrant(); + QdrantEmbeddingStore.Builder builder = QdrantEmbeddingStore.builder() + .host(cfg.getHost()) + .port(cfg.getPort()) + .collectionName(collectionName) + .useTls(cfg.isUseTls()); + if (cfg.getApiKey() != null && !cfg.getApiKey().isEmpty()) { + builder.apiKey(cfg.getApiKey()); + } + return builder.build(); + } + + private QdrantClient buildQdrantClient() { + VectorStoreProperties.Qdrant cfg = vectorStoreProperties.getQdrant(); + QdrantGrpcClient.Builder grpcBuilder = QdrantGrpcClient.newBuilder(cfg.getHost(), cfg.getPort(), cfg.isUseTls()); + if (cfg.getApiKey() != null && !cfg.getApiKey().isEmpty()) { + grpcBuilder.withApiKey(cfg.getApiKey()); + } + return new QdrantClient(grpcBuilder.build()); + } + + private int getModelDimension(String modelName) { + return chatModelService.selectModelByName(modelName).getModelDimension(); + } + + @Override + public String getVectorStoreType() { + return VECTOR_STORE_TYPE; + } + + @Override + public void createSchema(String kid, String modelName) { + String collectionName = vectorStoreProperties.getQdrant().getCollectionname() + kid; + int dimension = getModelDimension(modelName); + try (QdrantClient client = buildQdrantClient()) { + Boolean exists = client.collectionExistsAsync(collectionName).get(); + if (!exists) { + VectorParams params = VectorParams.newBuilder() + .setSize(dimension) + .setDistance(Distance.Cosine) + .build(); + client.createCollectionAsync(collectionName, params).get(); + log.info("Qdrant集合创建成功: {}, dimension: {}", collectionName, dimension); + } else { + log.info("Qdrant集合已存在: {}", collectionName); + } + } catch (Exception e) { + log.error("Qdrant集合创建失败: {}", collectionName, e); + throw new ServiceException("Qdrant集合创建失败: " + collectionName); + } + } + + @Override + public void storeEmbeddings(StoreEmbeddingBo storeEmbeddingBo) { + EmbeddingModel embeddingModel = getEmbeddingModel(storeEmbeddingBo.getEmbeddingModelName()); + List chunkList = storeEmbeddingBo.getChunkList(); + List fidList = storeEmbeddingBo.getFids(); + String kid = storeEmbeddingBo.getKid(); + String docId = storeEmbeddingBo.getDocId(); + String collectionName = vectorStoreProperties.getQdrant().getCollectionname() + kid; + + EmbeddingStore embeddingStore = getQdrantStore(collectionName); + + log.info("Qdrant向量存储条数记录: {}", chunkList.size()); + long startTime = System.currentTimeMillis(); + + IntStream.range(0, chunkList.size()).forEach(i -> { + String text = chunkList.get(i); + String fid = fidList.get(i); + Metadata metadata = new Metadata(); + metadata.put(METADATA_FID_KEY, fid); + metadata.put(METADATA_KID_KEY, kid); + metadata.put(METADATA_DOC_ID_KEY, docId); + TextSegment textSegment = TextSegment.from(text, metadata); + Embedding embedding = embeddingModel.embed(text).content(); + embeddingStore.add(embedding, textSegment); + }); + + long endTime = System.currentTimeMillis(); + log.info("Qdrant向量存储完成消耗时间：{}秒", (endTime - startTime) / 1000); + } + + @Override + public List getQueryVector(QueryVectorBo queryVectorBo) { + EmbeddingModel embeddingModel = getEmbeddingModel(queryVectorBo.getEmbeddingModelName()); + Embedding queryEmbedding = embeddingModel.embed(queryVectorBo.getQuery()).content(); + String collectionName = vectorStoreProperties.getQdrant().getCollectionname() + queryVectorBo.getKid(); + + List vector = new ArrayList<>(); + for (float f : queryEmbedding.vector()) { + vector.add(f); + } + + try (QdrantClient client = buildQdrantClient()) { + QueryPoints request = QueryPoints.newBuilder() + .setCollectionName(collectionName) + .setQuery(Query.newBuilder() + .setNearest(vectorInput(vector)) + .build()) + .setLimit(queryVectorBo.getMaxResults()) + .setWithPayload(enable(true)) + .build(); + + List results = client.queryAsync(request).get(); + List resultList = new ArrayList<>(); + for (ScoredPoint point : results) { + JsonWithInt.Value textValue = point.getPayloadMap().get(TEXT_SEGMENT_KEY); + if (textValue != null && textValue.hasStringValue()) { + resultList.add(textValue.getStringValue()); + } + } + return resultList; + } catch (Exception e) { + log.error("Qdrant查询失败: {}", collectionName, e); + throw new ServiceException("Qdrant向量查询失败"); + } + } + + @Override + public void removeById(String id, String modelName) { + String collectionName = vectorStoreProperties.getQdrant().getCollectionname() + id; + try (QdrantClient client = buildQdrantClient()) { + client.deleteCollectionAsync(collectionName).get(); + log.info("Qdrant成功删除集合: {}", collectionName); + } catch (Exception e) { + log.error("Qdrant删除集合失败: {}", collectionName, e); + throw new ServiceException("失败删除向量数据!"); + } + } + + @Override + public void removeByDocId(String docId, String kid) { + String collectionName = vectorStoreProperties.getQdrant().getCollectionname() + kid; + EmbeddingStore embeddingStore = getQdrantStore(collectionName); + Filter filter = MetadataFilterBuilder.metadataKey(METADATA_DOC_ID_KEY).isEqualTo(docId); + embeddingStore.removeAll(filter); + log.info("Qdrant成功删除 docId={} 的所有向量数据", docId); + } + + @Override + public void removeByFid(String fid, String kid) { + String collectionName = vectorStoreProperties.getQdrant().getCollectionname() + kid; + EmbeddingStore embeddingStore = getQdrantStore(collectionName); + Filter filter = MetadataFilterBuilder.metadataKey(METADATA_FID_KEY).isEqualTo(fid); + embeddingStore.removeAll(filter); + log.info("Qdrant成功删除 fid={} 的所有向量数据", fid); + } +}