p38192567
/
ruoyi-vue-pro1
mirror of https://gitee.com/zhijiantianya/ruoyi-vue-pro.git
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

【新增】AI 知识库：文档 token、字符数计算

This commit is contained in:
xiaoxin 2024-08-15 16:50:16 +08:00
parent d3a4c3c718
commit 238f603f69
3 changed files with 21 additions and 13 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
yudao-module-ai/yudao-module-ai-biz/src/main/java/cn/iocoder/yudao/module/ai/service/knowledge/AiEmbeddingService.java
View File

@ -21,7 +21,7 @@ public interface AiEmbeddingService {
/**
* 相似查询
*
* @param content 查询内容
* @param request 查询实体
*/
List<Document> similaritySearch(SearchRequest request);
}

3
yudao-module-ai/yudao-module-ai-biz/src/main/java/cn/iocoder/yudao/module/ai/service/knowledge/AiEmbeddingServiceImpl.java
View File

@ -4,7 +4,6 @@ import jakarta.annotation.Resource;
import org.springframework.ai.document.Document;
import org.springframework.ai.vectorstore.RedisVectorStore;
import org.springframework.ai.vectorstore.SearchRequest;
import org.springframework.scheduling.annotation.Async;
import org.springframework.stereotype.Service;
import java.util.List;
@ -21,6 +20,8 @@ public class AiEmbeddingServiceImpl implements AiEmbeddingService {
private RedisVectorStore vectorStore;
@Override
// @Async
// TODO xiaoxin 报错先注释
public void add(List<Document> documents) {
vectorStore.add(documents);
}

29
yudao-module-ai/yudao-module-ai-biz/src/main/java/cn/iocoder/yudao/module/ai/service/knowledge/AiKnowledgeDocumentServiceImpl.java
View File

@ -14,12 +14,14 @@ import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.document.Document;
import org.springframework.ai.reader.tika.TikaDocumentReader;
import org.springframework.ai.tokenizer.JTokkitTokenCountEstimator;
import org.springframework.ai.transformer.splitter.TokenTextSplitter;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
import java.util.List;
import java.util.Objects;
/**
* AI 知识库-文档 Service 实现类
@ -41,7 +43,9 @@ public class AiKnowledgeDocumentServiceImpl implements AiKnowledgeDocumentServic
@Resource
private AiEmbeddingService embeddingService;
// TODO @xin 临时测试用，后续删
private static final JTokkitTokenCountEstimator TOKEN_COUNT_ESTIMATOR = new JTokkitTokenCountEstimator();
// TODO xiaoxin 临时测试用，后续删
@Value("classpath:/webapp/test/Fel.pdf")
private org.springframework.core.io.Resource data;
@ -49,18 +53,23 @@ public class AiKnowledgeDocumentServiceImpl implements AiKnowledgeDocumentServic
@Override
@Transactional(rollbackFor = Exception.class)
public Long createKnowledgeDocument(AiKnowledgeDocumentCreateReqVO createReqVO) {
AiKnowledgeDocumentDO documentDO = BeanUtils.toBean(createReqVO, AiKnowledgeDocumentDO.class);
documentDO
//todo
.setTokens(0).setWordCount(0)
.setStatus(CommonStatusEnum.ENABLE.getStatus()).setSliceStatus(AiKnowledgeDocumentStatusEnum.SUCCESS.getStatus());
documentMapper.insert(documentDO);
// TODO xiaoxin 后续从 url 加载
TikaDocumentReader loader = new TikaDocumentReader(data);
// 加载文档
List<Document> documents = loader.get();
Document document = CollUtil.getFirst(documents);
// TODO 芋艿 文档层面有没有可能会比较大，这两个字段是否可以从分段表计算得出？
Integer tokens = Objects.nonNull(document) ? TOKEN_COUNT_ESTIMATOR.estimate(document.getContent()) : 0;
Integer wordCount = Objects.nonNull(document) ? document.getContent().length() : 0;
AiKnowledgeDocumentDO documentDO = BeanUtils.toBean(createReqVO, AiKnowledgeDocumentDO.class);
documentDO.setTokens(tokens).setWordCount(wordCount)
.setStatus(CommonStatusEnum.ENABLE.getStatus()).setSliceStatus(AiKnowledgeDocumentStatusEnum.SUCCESS.getStatus());
// 文档记录入库
documentMapper.insert(documentDO);
Long documentId = documentDO.getId();
if (CollUtil.isEmpty(documents)) {
log.info("文档内容为空");
return documentId;
}
@ -69,10 +78,8 @@ public class AiKnowledgeDocumentServiceImpl implements AiKnowledgeDocumentServic
List<AiKnowledgeSegmentDO> segmentDOList = CollectionUtils.convertList(segments,
segment -> new AiKnowledgeSegmentDO().setContent(segment.getContent()).setDocumentId(documentId)
//todo
.setTokens(0).setWordCount(0)
.setTokens(TOKEN_COUNT_ESTIMATOR.estimate(segment.getContent())).setWordCount(segment.getContent().length())
.setStatus(CommonStatusEnum.ENABLE.getStatus()));
// 分段内容入库
segmentMapper.insertBatch(segmentDOList);