【功能新增】AI:增加 QdrantVectorStore 向量库的接入

This commit is contained in:
YunaiV
2025-03-06 22:22:22 +08:00
parent 6ccd0ca61e
commit 44bcc9476d
9 changed files with 78 additions and 12 deletions

View File

@@ -54,7 +54,6 @@ public class AiKnowledgeDocumentServiceImpl implements AiKnowledgeDocumentServic
private AiKnowledgeService knowledgeService;
@Override
@Transactional(rollbackFor = Exception.class)
public Long createKnowledgeDocument(AiKnowledgeDocumentCreateReqVO createReqVO) {
// 1. 校验参数
knowledgeService.validateKnowledgeExists(createReqVO.getKnowledgeId());
@@ -74,7 +73,6 @@ public class AiKnowledgeDocumentServiceImpl implements AiKnowledgeDocumentServic
}
@Override
@Transactional(rollbackFor = Exception.class)
public List<Long> createKnowledgeDocumentList(AiKnowledgeDocumentCreateListReqVO createListReqVO) {
// 1. 校验参数
knowledgeService.validateKnowledgeExists(createListReqVO.getKnowledgeId());

View File

@@ -115,6 +115,7 @@ public class AiKnowledgeSegmentServiceImpl implements AiKnowledgeSegmentService
segmentMapper.updateById(newSegment);
// 3.2 重新向量化,必须开启状态
if (CommonStatusEnum.isEnable(oldSegment.getStatus())) {
newSegment.setKnowledgeId(oldSegment.getKnowledgeId()).setDocumentId(oldSegment.getDocumentId());
writeVectorStore(vectorStore, newSegment, new Document(newSegment.getContent()));
}
}
@@ -156,9 +157,10 @@ public class AiKnowledgeSegmentServiceImpl implements AiKnowledgeSegmentService
private void writeVectorStore(VectorStore vectorStore, AiKnowledgeSegmentDO segmentDO, Document segment) {
// 1. 向量存储
segment.getMetadata().put(VECTOR_STORE_METADATA_KNOWLEDGE_ID, segmentDO.getKnowledgeId());
segment.getMetadata().put(VECTOR_STORE_METADATA_DOCUMENT_ID, segmentDO.getDocumentId());
segment.getMetadata().put(VECTOR_STORE_METADATA_SEGMENT_ID, segmentDO.getId());
// 为什么要 toString 呢?因为部分 VectorStore 实现,不支持 Long 类型,例如说 QdrantVectorStore
segment.getMetadata().put(VECTOR_STORE_METADATA_KNOWLEDGE_ID, segmentDO.getKnowledgeId().toString());
segment.getMetadata().put(VECTOR_STORE_METADATA_DOCUMENT_ID, segmentDO.getDocumentId().toString());
segment.getMetadata().put(VECTOR_STORE_METADATA_SEGMENT_ID, segmentDO.getId().toString());
vectorStore.add(List.of(segment));
// 2. 更新向量 ID
@@ -190,7 +192,8 @@ public class AiKnowledgeSegmentServiceImpl implements AiKnowledgeSegmentService
.similarityThreshold(
ObjUtil.defaultIfNull(reqBO.getSimilarityThreshold(), knowledge.getSimilarityThreshold()))
.filterExpression(new FilterExpressionBuilder()
.eq(VECTOR_STORE_METADATA_KNOWLEDGE_ID, reqBO.getKnowledgeId()).build())
.eq(VECTOR_STORE_METADATA_KNOWLEDGE_ID, reqBO.getKnowledgeId().toString())
.build())
.build());
if (CollUtil.isEmpty(documents)) {
return ListUtil.empty();

View File

@@ -16,8 +16,8 @@ import jakarta.annotation.Resource;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.embedding.EmbeddingModel;
import org.springframework.ai.image.ImageModel;
import org.springframework.ai.vectorstore.SimpleVectorStore;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.ai.vectorstore.qdrant.QdrantVectorStore;
import org.springframework.stereotype.Service;
import org.springframework.validation.annotation.Validated;
@@ -162,7 +162,8 @@ public class AiModelServiceImpl implements AiModelService {
platform, apiKey.getApiKey(), apiKey.getUrl(), model.getModel());
// 创建或获取 VectorStore 对象
return modelFactory.getOrCreateVectorStore(SimpleVectorStore.class, embeddingModel);
// return modelFactory.getOrCreateVectorStore(SimpleVectorStore.class, embeddingModel);
return modelFactory.getOrCreateVectorStore(QdrantVectorStore.class, embeddingModel);
}
}