!20 【新增】AI 知识库: 段落召回、段落启禁用、配置自定义

Merge pull request !20 from 小新/master-jdk21-ai
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芋道源码 2024-09-07 11:29:40 +00:00 committed by Gitee
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19 changed files with 277 additions and 124 deletions

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@ -25,4 +25,11 @@ public class AiKnowledgeCreateMyReqVO {
@NotNull(message = "嵌入模型不能为空")
private Long modelId;
@Schema(description = "相似性阈值", requiredMode = Schema.RequiredMode.REQUIRED, example = "0.5")
@NotNull(message = "相似性阈值不能为空")
private Double similarityThreshold;
@Schema(description = "topK", requiredMode = Schema.RequiredMode.REQUIRED, example = "3")
@NotNull(message = "topK 不能为空")
private Integer topK;
}

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@ -23,4 +23,23 @@ public class AiKnowledgeDocumentCreateReqVO {
@URL(message = "文档 URL 格式不正确")
private String url;
@Schema(description = "每个文本块的目标 token 数", requiredMode = Schema.RequiredMode.REQUIRED, example = "800")
@NotNull(message = "每个文本块的目标 token 数不能为空")
private Integer defaultChunkSize;
@Schema(description = "每个文本块的最小字符数", requiredMode = Schema.RequiredMode.REQUIRED, example = "350")
@NotNull(message = "每个文本块的最小字符数不能为空")
private Integer minChunkSizeChars;
@Schema(description = "丢弃阈值", requiredMode = Schema.RequiredMode.REQUIRED, example = "5")
@NotNull(message = "丢弃阈值不能为空")
private Integer minChunkLengthToEmbed;
@Schema(description = "最大块数", requiredMode = Schema.RequiredMode.REQUIRED, example = "10000")
@NotNull(message = "最大块数不能为空")
private Integer maxNumChunks;
@Schema(description = "分块是否保留分隔符", requiredMode = Schema.RequiredMode.REQUIRED, example = "true")
@NotNull(message = "分块是否保留分隔符不能为空")
private Boolean keepSeparator;
}

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@ -0,0 +1,17 @@
package cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.segment;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
@Schema(description = "管理后台 - AI 知识库段落召回 Request VO")
@Data
public class AiKnowledgeSegmentSearchReqVO {
@Schema(description = "知识库编号", requiredMode = Schema.RequiredMode.REQUIRED, example = "24790")
private Long knowledgeId;
@Schema(description = "内容", requiredMode = Schema.RequiredMode.REQUIRED, example = "Java 学习路线")
private String content;
}

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@ -52,6 +52,18 @@ public class AiKnowledgeDO extends BaseDO {
* 模型标识
*/
private String model;
/**
* topK
*/
private Integer topK;
/**
* 相似度阈值
*/
private Double similarityThreshold;
/**
* 状态
* <p>

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@ -23,7 +23,7 @@ public class AiKnowledgeDocumentDO extends BaseDO {
private Long id;
/**
* 知识库编号
*
* <p>
* 关联 {@link AiKnowledgeDO#getId()}
*/
private Long knowledgeId;
@ -47,6 +47,26 @@ public class AiKnowledgeDocumentDO extends BaseDO {
* 字符数
*/
private Integer wordCount;
/**
* 每个文本块的目标 token
*/
private Integer defaultChunkSize;
/**
* 每个文本块的最小字符数
*/
private Integer minChunkSizeChars;
/**
* 低于此值的块会被丢弃
*/
private Integer minChunkLengthToEmbed;
/**
* 最大块数
*/
private Integer maxNumChunks;
/**
* 分块是否保留分隔符
*/
private Boolean keepSeparator;
/**
* 切片状态
* <p>

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@ -2,6 +2,8 @@ package cn.iocoder.yudao.module.ai.dal.dataobject.knowledge;
import cn.iocoder.yudao.framework.common.enums.CommonStatusEnum;
import cn.iocoder.yudao.framework.mybatis.core.dataobject.BaseDO;
import com.baomidou.mybatisplus.annotation.FieldStrategy;
import com.baomidou.mybatisplus.annotation.TableField;
import com.baomidou.mybatisplus.annotation.TableId;
import com.baomidou.mybatisplus.annotation.TableName;
import lombok.Data;
@ -25,16 +27,17 @@ public class AiKnowledgeSegmentDO extends BaseDO {
/**
* 向量库的编号
*/
@TableField(updateStrategy = FieldStrategy.ALWAYS)
private String vectorId;
/**
* 知识库编号
*
* <p>
* 关联 {@link AiKnowledgeDO#getId()}
*/
private Long knowledgeId;
/**
* 文档编号
*
* <p>
* 关联 {@link AiKnowledgeDocumentDO#getId()}
*/
private Long documentId;
@ -52,7 +55,7 @@ public class AiKnowledgeSegmentDO extends BaseDO {
private Integer tokens;
/**
* 状态
*
* <p>
* 枚举 {@link CommonStatusEnum}
*/
private Integer status;

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@ -7,6 +7,8 @@ import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.segment.AiKnowle
import cn.iocoder.yudao.module.ai.dal.dataobject.knowledge.AiKnowledgeSegmentDO;
import org.apache.ibatis.annotations.Mapper;
import java.util.List;
/**
* AI 知识库-分片 Mapper
*
@ -22,4 +24,10 @@ public interface AiKnowledgeSegmentMapper extends BaseMapperX<AiKnowledgeSegment
.likeIfPresent(AiKnowledgeSegmentDO::getContent, reqVO.getKeyword())
.orderByDesc(AiKnowledgeSegmentDO::getId));
}
default List<AiKnowledgeSegmentDO> selectList(List<String> vectorIdList) {
return selectList(new LambdaQueryWrapperX<AiKnowledgeSegmentDO>()
.in(AiKnowledgeSegmentDO::getVectorId, vectorIdList)
.orderByDesc(AiKnowledgeSegmentDO::getId));
}
}

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@ -9,15 +9,11 @@ import cn.iocoder.yudao.framework.common.util.object.BeanUtils;
import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.document.AiKnowledgeDocumentPageReqVO;
import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.document.AiKnowledgeDocumentUpdateReqVO;
import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.knowledge.AiKnowledgeDocumentCreateReqVO;
import cn.iocoder.yudao.module.ai.dal.dataobject.knowledge.AiKnowledgeDO;
import cn.iocoder.yudao.module.ai.dal.dataobject.knowledge.AiKnowledgeDocumentDO;
import cn.iocoder.yudao.module.ai.dal.dataobject.knowledge.AiKnowledgeSegmentDO;
import cn.iocoder.yudao.module.ai.dal.dataobject.model.AiChatModelDO;
import cn.iocoder.yudao.module.ai.dal.mysql.knowledge.AiKnowledgeDocumentMapper;
import cn.iocoder.yudao.module.ai.dal.mysql.knowledge.AiKnowledgeSegmentMapper;
import cn.iocoder.yudao.module.ai.enums.knowledge.AiKnowledgeDocumentStatusEnum;
import cn.iocoder.yudao.module.ai.service.model.AiApiKeyService;
import cn.iocoder.yudao.module.ai.service.model.AiChatModelService;
import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.document.Document;
@ -48,24 +44,16 @@ public class AiKnowledgeDocumentServiceImpl implements AiKnowledgeDocumentServic
@Resource
private AiKnowledgeSegmentMapper segmentMapper;
@Resource
private TokenTextSplitter tokenTextSplitter;
@Resource
private TokenCountEstimator tokenCountEstimator;
@Resource
private AiApiKeyService apiKeyService;
@Resource
private AiKnowledgeService knowledgeService;
@Resource
private AiChatModelService chatModelService;
@Override
@Transactional(rollbackFor = Exception.class)
public Long createKnowledgeDocument(AiKnowledgeDocumentCreateReqVO createReqVO) {
// 0. 校验
AiKnowledgeDO knowledge = knowledgeService.validateKnowledgeExists(createReqVO.getKnowledgeId());
AiChatModelDO model = chatModelService.validateChatModel(knowledge.getModelId());
// 0. 校验并获取向量存储实例
VectorStore vectorStore = knowledgeService.getVectorStoreById(createReqVO.getKnowledgeId());
// 1.1 下载文档
TikaDocumentReader loader = new TikaDocumentReader(downloadFile(createReqVO.getUrl()));
@ -82,6 +70,9 @@ public class AiKnowledgeDocumentServiceImpl implements AiKnowledgeDocumentServic
return documentId;
}
// 2 构造文本分段器
TokenTextSplitter tokenTextSplitter = new TokenTextSplitter(createReqVO.getDefaultChunkSize(), createReqVO.getMinChunkSizeChars(), createReqVO.getMinChunkLengthToEmbed(),
createReqVO.getMaxNumChunks(), createReqVO.getKeepSeparator());
// 2.1 文档分段
List<Document> segments = tokenTextSplitter.apply(documents);
// 2.2 分段内容入库
@ -92,8 +83,6 @@ public class AiKnowledgeDocumentServiceImpl implements AiKnowledgeDocumentServic
.setStatus(CommonStatusEnum.ENABLE.getStatus()));
segmentMapper.insertBatch(segmentDOList);
// 3.1 获取向量存储实例
VectorStore vectorStore = apiKeyService.getOrCreateVectorStore(model.getKeyId());
// 3.2 向量化并存储
segments.forEach(segment -> segment.getMetadata().put(AiKnowledgeSegmentDO.FIELD_KNOWLEDGE_ID, createReqVO.getKnowledgeId()));
vectorStore.add(segments);

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@ -2,10 +2,13 @@ package cn.iocoder.yudao.module.ai.service.knowledge;
import cn.iocoder.yudao.framework.common.pojo.PageResult;
import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.segment.AiKnowledgeSegmentPageReqVO;
import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.segment.AiKnowledgeSegmentSearchReqVO;
import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.segment.AiKnowledgeSegmentUpdateReqVO;
import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.segment.AiKnowledgeSegmentUpdateStatusReqVO;
import cn.iocoder.yudao.module.ai.dal.dataobject.knowledge.AiKnowledgeSegmentDO;
import java.util.List;
/**
* AI 知识库段落 Service 接口
*
@ -35,4 +38,13 @@ public interface AiKnowledgeSegmentService {
*/
void updateKnowledgeSegmentStatus(AiKnowledgeSegmentUpdateStatusReqVO reqVO);
/**
* 段落召回
*
* @param reqVO 召回请求信息
* @return 召回的段落
*/
List<AiKnowledgeSegmentDO> similaritySearch(AiKnowledgeSegmentSearchReqVO reqVO);
}

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@ -1,16 +1,34 @@
package cn.iocoder.yudao.module.ai.service.knowledge;
import cn.hutool.core.collection.CollUtil;
import cn.hutool.core.collection.ListUtil;
import cn.iocoder.yudao.framework.common.enums.CommonStatusEnum;
import cn.iocoder.yudao.framework.common.pojo.PageResult;
import cn.iocoder.yudao.framework.common.util.object.BeanUtils;
import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.segment.AiKnowledgeSegmentPageReqVO;
import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.segment.AiKnowledgeSegmentSearchReqVO;
import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.segment.AiKnowledgeSegmentUpdateReqVO;
import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.segment.AiKnowledgeSegmentUpdateStatusReqVO;
import cn.iocoder.yudao.module.ai.dal.dataobject.knowledge.AiKnowledgeDO;
import cn.iocoder.yudao.module.ai.dal.dataobject.knowledge.AiKnowledgeSegmentDO;
import cn.iocoder.yudao.module.ai.dal.dataobject.model.AiChatModelDO;
import cn.iocoder.yudao.module.ai.dal.mysql.knowledge.AiKnowledgeSegmentMapper;
import cn.iocoder.yudao.module.ai.service.model.AiApiKeyService;
import cn.iocoder.yudao.module.ai.service.model.AiChatModelService;
import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.document.Document;
import org.springframework.ai.vectorstore.SearchRequest;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.ai.vectorstore.filter.FilterExpressionBuilder;
import org.springframework.stereotype.Service;
import java.util.List;
import java.util.Objects;
import static cn.iocoder.yudao.framework.common.exception.util.ServiceExceptionUtil.exception;
import static cn.iocoder.yudao.module.ai.enums.ErrorCodeConstants.KNOWLEDGE_SEGMENT_NOT_EXISTS;
/**
* AI 知识库分片 Service 实现类
*
@ -23,6 +41,13 @@ public class AiKnowledgeSegmentServiceImpl implements AiKnowledgeSegmentService
@Resource
private AiKnowledgeSegmentMapper segmentMapper;
@Resource
private AiKnowledgeService knowledgeService;
@Resource
private AiChatModelService chatModelService;
@Resource
private AiApiKeyService apiKeyService;
@Override
public PageResult<AiKnowledgeSegmentDO> getKnowledgeSegmentPage(AiKnowledgeSegmentPageReqVO pageReqVO) {
return segmentMapper.selectPage(pageReqVO);
@ -30,13 +55,80 @@ public class AiKnowledgeSegmentServiceImpl implements AiKnowledgeSegmentService
@Override
public void updateKnowledgeSegment(AiKnowledgeSegmentUpdateReqVO reqVO) {
segmentMapper.updateById(BeanUtils.toBean(reqVO, AiKnowledgeSegmentDO.class));
// TODO @xin 重新向量化
// 0 校验
AiKnowledgeSegmentDO oldKnowledgeSegment = validateKnowledgeSegmentExists(reqVO.getId());
// 2.1 获取知识库向量实例
VectorStore vectorStore = knowledgeService.getVectorStoreById(oldKnowledgeSegment.getKnowledgeId());
// 2.2 删除原向量
vectorStore.delete(List.of(oldKnowledgeSegment.getVectorId()));
// 2.3 重新向量化
Document document = new Document(reqVO.getContent());
document.getMetadata().put(AiKnowledgeSegmentDO.FIELD_KNOWLEDGE_ID, oldKnowledgeSegment.getKnowledgeId());
vectorStore.add(List.of(document));
// 2.1 更新段落内容
AiKnowledgeSegmentDO knowledgeSegment = BeanUtils.toBean(reqVO, AiKnowledgeSegmentDO.class);
knowledgeSegment.setVectorId(document.getId());
segmentMapper.updateById(knowledgeSegment);
}
@Override
public void updateKnowledgeSegmentStatus(AiKnowledgeSegmentUpdateStatusReqVO reqVO) {
segmentMapper.updateById(BeanUtils.toBean(reqVO, AiKnowledgeSegmentDO.class));
// TODO @xin 1.禁用删除向量 2.启用重新向量化
// 0 校验
AiKnowledgeSegmentDO oldKnowledgeSegment = validateKnowledgeSegmentExists(reqVO.getId());
// 1 获取知识库向量实例
VectorStore vectorStore = knowledgeService.getVectorStoreById(oldKnowledgeSegment.getKnowledgeId());
AiKnowledgeSegmentDO knowledgeSegment = BeanUtils.toBean(reqVO, AiKnowledgeSegmentDO.class);
if (Objects.equals(reqVO.getStatus(), CommonStatusEnum.ENABLE.getStatus())) {
// 2.1 启用重新向量化
Document document = new Document(oldKnowledgeSegment.getContent());
document.getMetadata().put(AiKnowledgeSegmentDO.FIELD_KNOWLEDGE_ID, oldKnowledgeSegment.getKnowledgeId());
vectorStore.add(List.of(document));
knowledgeSegment.setVectorId(document.getId());
} else {
// 2.2 禁用删除向量
vectorStore.delete(List.of(oldKnowledgeSegment.getVectorId()));
knowledgeSegment.setVectorId(null);
}
// 3 更新段落状态
segmentMapper.updateById(knowledgeSegment);
}
@Override
public List<AiKnowledgeSegmentDO> similaritySearch(AiKnowledgeSegmentSearchReqVO reqVO) {
// 0. 校验
AiKnowledgeDO knowledge = knowledgeService.validateKnowledgeExists(reqVO.getKnowledgeId());
AiChatModelDO model = chatModelService.validateChatModel(knowledge.getModelId());
// 1.1 获取向量存储实例
VectorStore vectorStore = apiKeyService.getOrCreateVectorStore(model.getKeyId());
// 1.2 向量检索
List<Document> documentList = vectorStore.similaritySearch(SearchRequest.query(reqVO.getContent())
.withTopK(knowledge.getTopK())
.withSimilarityThreshold(knowledge.getSimilarityThreshold())
.withFilterExpression(new FilterExpressionBuilder().eq(AiKnowledgeSegmentDO.FIELD_KNOWLEDGE_ID, reqVO.getKnowledgeId()).build()));
if (CollUtil.isEmpty(documentList)) {
return ListUtil.empty();
}
// 2.1 段落召回
return segmentMapper.selectList(CollUtil.getFieldValues(documentList, "id", String.class));
}
/**
* 校验段落是否存在
*
* @param id 文档编号
* @return 段落信息
*/
private AiKnowledgeSegmentDO validateKnowledgeSegmentExists(Long id) {
AiKnowledgeSegmentDO knowledgeSegment = segmentMapper.selectById(id);
if (knowledgeSegment == null) {
throw exception(KNOWLEDGE_SEGMENT_NOT_EXISTS);
}
return knowledgeSegment;
}
}

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@ -5,6 +5,7 @@ import cn.iocoder.yudao.framework.common.pojo.PageResult;
import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.knowledge.AiKnowledgeCreateMyReqVO;
import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.knowledge.AiKnowledgeUpdateMyReqVO;
import cn.iocoder.yudao.module.ai.dal.dataobject.knowledge.AiKnowledgeDO;
import org.springframework.ai.vectorstore.VectorStore;
/**
* AI 知识库-基础信息 Service 接口
@ -47,4 +48,12 @@ public interface AiKnowledgeService {
* @return 知识库分页
*/
PageResult<AiKnowledgeDO> getKnowledgePageMy(Long userId, PageParam pageReqVO);
/**
* 根据知识库编号获取向量存储实例
*
* @param knowledgeId 知识库编号
* @return 向量存储实例
*/
VectorStore getVectorStoreById(Long knowledgeId);
}

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@ -10,9 +10,11 @@ import cn.iocoder.yudao.module.ai.controller.admin.knowledge.vo.knowledge.AiKnow
import cn.iocoder.yudao.module.ai.dal.dataobject.knowledge.AiKnowledgeDO;
import cn.iocoder.yudao.module.ai.dal.dataobject.model.AiChatModelDO;
import cn.iocoder.yudao.module.ai.dal.mysql.knowledge.AiKnowledgeMapper;
import cn.iocoder.yudao.module.ai.service.model.AiApiKeyService;
import cn.iocoder.yudao.module.ai.service.model.AiChatModelService;
import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.stereotype.Service;
import static cn.iocoder.yudao.framework.common.exception.util.ServiceExceptionUtil.exception;
@ -32,6 +34,10 @@ public class AiKnowledgeServiceImpl implements AiKnowledgeService {
@Resource
private AiKnowledgeMapper knowledgeMapper;
@Resource
private AiChatModelService chatModelService;
@Resource
private AiApiKeyService apiKeyService;
@Override
public Long createKnowledgeMy(AiKnowledgeCreateMyReqVO createReqVO, Long userId) {
@ -75,4 +81,11 @@ public class AiKnowledgeServiceImpl implements AiKnowledgeService {
return knowledgeMapper.selectPageByMy(userId, pageReqVO);
}
@Override
public VectorStore getVectorStoreById(Long knowledgeId) {
AiKnowledgeDO knowledge = validateKnowledgeExists(knowledgeId);
AiChatModelDO model = chatModelService.validateChatModel(knowledge.getModelId());
return apiKeyService.getOrCreateVectorStore(model.getKeyId());
}
}

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@ -2,7 +2,6 @@ package cn.iocoder.yudao.module.ai.service.model;
import cn.iocoder.yudao.framework.ai.core.enums.AiPlatformEnum;
import cn.iocoder.yudao.framework.ai.core.factory.AiModelFactory;
import cn.iocoder.yudao.framework.ai.core.factory.AiVectorStoreFactory;
import cn.iocoder.yudao.framework.ai.core.model.midjourney.api.MidjourneyApi;
import cn.iocoder.yudao.framework.ai.core.model.suno.api.SunoApi;
import cn.iocoder.yudao.framework.common.enums.CommonStatusEnum;
@ -39,8 +38,6 @@ public class AiApiKeyServiceImpl implements AiApiKeyService {
@Resource
private AiModelFactory modelFactory;
@Resource
private AiVectorStoreFactory vectorFactory;
@Override
public Long createApiKey(AiApiKeySaveReqVO createReqVO) {
@ -149,7 +146,7 @@ public class AiApiKeyServiceImpl implements AiApiKeyService {
public VectorStore getOrCreateVectorStore(Long id) {
AiApiKeyDO apiKey = validateApiKey(id);
AiPlatformEnum platform = AiPlatformEnum.validatePlatform(apiKey.getPlatform());
return vectorFactory.getOrCreateVectorStore(getEmbeddingModel(id), platform, apiKey.getApiKey(), apiKey.getUrl());
return modelFactory.getOrCreateVectorStore(getEmbeddingModel(id), platform, apiKey.getApiKey(), apiKey.getUrl());
}
}

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@ -46,11 +46,13 @@
</dependency>
<!-- 向量化,基于 Redis 存储Tika 解析内容 -->
<dependency>
<groupId>${spring-ai.groupId}</groupId>
<artifactId>spring-ai-transformers-spring-boot-starter</artifactId>
<version>${spring-ai.version}</version>
</dependency>
<!-- 暂不做经济型,先注释 -->
<!-- <dependency>-->
<!-- <groupId>${spring-ai.groupId}</groupId>-->
<!-- <artifactId>spring-ai-transformers-spring-boot-starter</artifactId>-->
<!-- <version>${spring-ai.version}</version>-->
<!-- </dependency>-->
<dependency>
<groupId>${spring-ai.groupId}</groupId>
<artifactId>spring-ai-tika-document-reader</artifactId>

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@ -2,8 +2,6 @@ package cn.iocoder.yudao.framework.ai.config;
import cn.iocoder.yudao.framework.ai.core.factory.AiModelFactory;
import cn.iocoder.yudao.framework.ai.core.factory.AiModelFactoryImpl;
import cn.iocoder.yudao.framework.ai.core.factory.AiVectorStoreFactory;
import cn.iocoder.yudao.framework.ai.core.factory.AiVectorStoreFactoryImpl;
import cn.iocoder.yudao.framework.ai.core.model.deepseek.DeepSeekChatModel;
import cn.iocoder.yudao.framework.ai.core.model.deepseek.DeepSeekChatOptions;
import cn.iocoder.yudao.framework.ai.core.model.midjourney.api.MidjourneyApi;
@ -38,11 +36,6 @@ public class YudaoAiAutoConfiguration {
return new AiModelFactoryImpl();
}
@Bean
public AiVectorStoreFactory aiVectorFactory() {
return new AiVectorStoreFactoryImpl();
}
// ========== 各种 AI Client 创建 ==========
@ -89,7 +82,7 @@ public class YudaoAiAutoConfiguration {
// TODO @xin 免费版本
// @Bean
// @Lazy // TODO 芋艿临时注释避免无法启动
// public EmbeddingModel transformersEmbeddingClient() {
// public TransformersEmbeddingModel transformersEmbeddingClient() {
// return new TransformersEmbeddingModel(MetadataMode.EMBED);
// }
@ -98,23 +91,24 @@ public class YudaoAiAutoConfiguration {
*/
// @Bean
// @Lazy // TODO 芋艿临时注释避免无法启动
// public RedisVectorStore vectorStore(TongYiTextEmbeddingModel tongYiTextEmbeddingModel, RedisVectorStoreProperties properties,
// public RedisVectorStore vectorStore(TransformersEmbeddingModel embeddingModel, RedisVectorStoreProperties properties,
// RedisProperties redisProperties) {
// var config = RedisVectorStore.RedisVectorStoreConfig.builder()
// .withIndexName(properties.getIndex())
// .withPrefix(properties.getPrefix())
// .withMetadataFields(new RedisVectorStore.MetadataField("knowledgeId", Schema.FieldType.NUMERIC))
// .build();
//
// RedisVectorStore redisVectorStore = new RedisVectorStore(config, tongYiTextEmbeddingModel,
// RedisVectorStore redisVectorStore = new RedisVectorStore(config, embeddingModel,
// new JedisPooled(redisProperties.getHost(), redisProperties.getPort()),
// properties.isInitializeSchema());
// redisVectorStore.afterPropertiesSet();
// return redisVectorStore;
// }
@Bean
@Lazy // TODO 芋艿临时注释避免无法启动
public TokenTextSplitter tokenTextSplitter() {
//TODO @xin 配置提取
return new TokenTextSplitter(500, 100, 5, 10000, true);
}

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@ -6,6 +6,7 @@ import cn.iocoder.yudao.framework.ai.core.model.suno.api.SunoApi;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.embedding.EmbeddingModel;
import org.springframework.ai.image.ImageModel;
import org.springframework.ai.vectorstore.VectorStore;
/**
* AI Model 模型工厂的接口类
@ -92,4 +93,17 @@ public interface AiModelFactory {
*/
EmbeddingModel getOrCreateEmbeddingModel(AiPlatformEnum platform, String apiKey, String url);
/**
* 基于指定配置获得 VectorStore 对象
* <p>
* 如果不存在则进行创建
*
* @param embeddingModel 嵌入模型
* @param platform 平台
* @param apiKey API KEY
* @param url API URL
* @return VectorStore 对象
*/
VectorStore getOrCreateVectorStore(EmbeddingModel embeddingModel, AiPlatformEnum platform, String apiKey, String url);
}

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@ -13,6 +13,7 @@ import cn.iocoder.yudao.framework.ai.core.model.deepseek.DeepSeekChatModel;
import cn.iocoder.yudao.framework.ai.core.model.midjourney.api.MidjourneyApi;
import cn.iocoder.yudao.framework.ai.core.model.suno.api.SunoApi;
import cn.iocoder.yudao.framework.ai.core.model.xinghuo.XingHuoChatModel;
import cn.iocoder.yudao.framework.common.util.spring.SpringUtils;
import com.alibaba.cloud.ai.tongyi.TongYiAutoConfiguration;
import com.alibaba.cloud.ai.tongyi.TongYiConnectionProperties;
import com.alibaba.cloud.ai.tongyi.chat.TongYiChatModel;
@ -54,13 +55,18 @@ import org.springframework.ai.qianfan.api.QianFanApi;
import org.springframework.ai.qianfan.api.QianFanImageApi;
import org.springframework.ai.stabilityai.StabilityAiImageModel;
import org.springframework.ai.stabilityai.api.StabilityAiApi;
import org.springframework.ai.vectorstore.RedisVectorStore;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.ai.zhipuai.ZhiPuAiChatModel;
import org.springframework.ai.zhipuai.ZhiPuAiImageModel;
import org.springframework.ai.zhipuai.api.ZhiPuAiApi;
import org.springframework.ai.zhipuai.api.ZhiPuAiImageApi;
import org.springframework.boot.autoconfigure.data.redis.RedisProperties;
import org.springframework.retry.support.RetryTemplate;
import org.springframework.web.client.ResponseErrorHandler;
import org.springframework.web.client.RestClient;
import redis.clients.jedis.JedisPooled;
import redis.clients.jedis.search.Schema;
import java.util.List;
@ -191,6 +197,25 @@ public class AiModelFactoryImpl implements AiModelFactory {
});
}
@Override
public VectorStore getOrCreateVectorStore(EmbeddingModel embeddingModel, AiPlatformEnum platform, String apiKey, String url) {
String cacheKey = buildClientCacheKey(VectorStore.class, platform, apiKey, url);
return Singleton.get(cacheKey, (Func0<VectorStore>) () -> {
String prefix = StrUtil.format("{}#{}:", platform.getPlatform(), apiKey);
var config = RedisVectorStore.RedisVectorStoreConfig.builder()
.withIndexName(cacheKey)
.withPrefix(prefix)
.withMetadataFields(new RedisVectorStore.MetadataField("knowledgeId", Schema.FieldType.NUMERIC))
.build();
RedisProperties redisProperties = SpringUtils.getBean(RedisProperties.class);
RedisVectorStore redisVectorStore = new RedisVectorStore(config, embeddingModel,
new JedisPooled(redisProperties.getHost(), redisProperties.getPort()),
true);
redisVectorStore.afterPropertiesSet();
return redisVectorStore;
});
}
private static String buildClientCacheKey(Class<?> clazz, Object... params) {
if (ArrayUtil.isEmpty(params)) {
return clazz.getName();

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@ -1,28 +0,0 @@
package cn.iocoder.yudao.framework.ai.core.factory;
import cn.iocoder.yudao.framework.ai.core.enums.AiPlatformEnum;
import org.springframework.ai.embedding.EmbeddingModel;
import org.springframework.ai.vectorstore.VectorStore;
// TODO @xin也放到 AiModelFactory 里面好了后续改成 AiFactory
/**
* AI Vector 模型工厂的接口类
*
* @author xiaoxin
*/
public interface AiVectorStoreFactory {
/**
* 基于指定配置获得 VectorStore 对象
* <p>
* 如果不存在则进行创建
*
* @param embeddingModel 嵌入模型
* @param platform 平台
* @param apiKey API KEY
* @param url API URL
* @return VectorStore 对象
*/
VectorStore getOrCreateVectorStore(EmbeddingModel embeddingModel, AiPlatformEnum platform, String apiKey, String url);
}

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@ -1,52 +0,0 @@
package cn.iocoder.yudao.framework.ai.core.factory;
import cn.hutool.core.lang.Singleton;
import cn.hutool.core.lang.func.Func0;
import cn.hutool.core.util.ArrayUtil;
import cn.hutool.core.util.StrUtil;
import cn.iocoder.yudao.framework.ai.core.enums.AiPlatformEnum;
import cn.iocoder.yudao.framework.common.util.spring.SpringUtils;
import org.springframework.ai.embedding.EmbeddingModel;
import org.springframework.ai.vectorstore.RedisVectorStore;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.boot.autoconfigure.data.redis.RedisProperties;
import redis.clients.jedis.JedisPooled;
/**
* AI Vector 模型工厂的实现类
* 使用 redisVectorStore 实现 VectorStore
*
* @author xiaoxin
*/
public class AiVectorStoreFactoryImpl implements AiVectorStoreFactory {
@Override
public VectorStore getOrCreateVectorStore(EmbeddingModel embeddingModel, AiPlatformEnum platform, String apiKey, String url) {
String cacheKey = buildClientCacheKey(VectorStore.class, platform, apiKey, url);
return Singleton.get(cacheKey, (Func0<VectorStore>) () -> {
// TODO 芋艿 @xin 这两个配置取哪好呢
// TODO 不同模型的向量维度可能会不一样目前看貌似是以 index 来做区分的维度不一样存不到一个 index
// TODO 回复好的哈
String index = "default-index";
String prefix = "default:";
var config = RedisVectorStore.RedisVectorStoreConfig.builder()
.withIndexName(index)
.withPrefix(prefix)
.build();
RedisProperties redisProperties = SpringUtils.getBean(RedisProperties.class);
RedisVectorStore redisVectorStore = new RedisVectorStore(config, embeddingModel,
new JedisPooled(redisProperties.getHost(), redisProperties.getPort()),
true);
redisVectorStore.afterPropertiesSet();
return redisVectorStore;
});
}
private static String buildClientCacheKey(Class<?> clazz, Object... params) {
if (ArrayUtil.isEmpty(params)) {
return clazz.getName();
}
return StrUtil.format("{}#{}", clazz.getName(), ArrayUtil.join(params, "_"));
}
}