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【功能新增】AI：新增 ZhiPuAiEmbeddingModel 向量模型

This commit is contained in:
YunaiV 2025-03-11 07:49:54 +08:00
parent d7e801c438
commit 3a3607e1cb
3 changed files with 19 additions and 10 deletions
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1
yudao-module-ai/yudao-module-ai-biz/src/main/java/cn/iocoder/yudao/module/ai/controller/admin/knowledge/AiKnowledgeController.java
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@ -36,7 +36,6 @@ public class AiKnowledgeController {
@Operation(summary = "获取知识库分页")
@PreAuthorize("@ss.hasPermission('ai:knowledge:query')")
public CommonResult<PageResult<AiKnowledgeRespVO>> getKnowledgePage(@Valid AiKnowledgePageReqVO pageReqVO) {
PageResult<AiKnowledgeDO> pageResult = knowledgeService.getKnowledgePage(pageReqVO);
return success(BeanUtils.toBean(pageResult, AiKnowledgeRespVO.class));
}

6
yudao-module-ai/yudao-module-ai-biz/src/main/java/cn/iocoder/yudao/module/ai/service/model/AiModelServiceImpl.java
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@ -163,9 +163,9 @@ public class AiModelServiceImpl implements AiModelService {
// 创建或获取 VectorStore 对象
return modelFactory.getOrCreateVectorStore(SimpleVectorStore.class, embeddingModel, metadataFields);
// return modelFactory.getOrCreateVectorStore(QdrantVectorStore.class, embeddingModel, metadataFields);
// return modelFactory.getOrCreateVectorStore(RedisVectorStore.class, embeddingModel, metadataFields);
// return modelFactory.getOrCreateVectorStore(MilvusVectorStore.class, embeddingModel, metadataFields);
// return modelFactory.getOrCreateVectorStore(QdrantVectorStore.class, embeddingModel, metadataFields);
// return modelFactory.getOrCreateVectorStore(RedisVectorStore.class, embeddingModel, metadataFields);
// return modelFactory.getOrCreateVectorStore(MilvusVectorStore.class, embeddingModel, metadataFields);
}
}

22
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/cn/iocoder/yudao/framework/ai/core/factory/AiModelFactoryImpl.java
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@ -77,6 +77,7 @@ import org.springframework.ai.vectorstore.observation.VectorStoreObservationConv
import org.springframework.ai.vectorstore.qdrant.QdrantVectorStore;
import org.springframework.ai.vectorstore.redis.RedisVectorStore;
import org.springframework.ai.zhipuai.ZhiPuAiChatModel;
import org.springframework.ai.zhipuai.ZhiPuAiEmbeddingModel;
import org.springframework.ai.zhipuai.ZhiPuAiImageModel;
import org.springframework.ai.zhipuai.api.ZhiPuAiApi;
import org.springframework.ai.zhipuai.api.ZhiPuAiImageApi;
@ -231,7 +232,9 @@ public class AiModelFactoryImpl implements AiModelFactory {
return buildTongYiEmbeddingModel(apiKey, model);
case OLLAMA:
return buildOllamaEmbeddingModel(url, model);
// TODO @芋艿：各个平台的向量化能力；
// TODO @芋艿：yiyan
case ZHI_PU:
return buildZhiPuEmbeddingModel(apiKey, url, model);
default:
throw new IllegalArgumentException(StrUtil.format("未知平台({})", platform));
}
@ -240,8 +243,8 @@ public class AiModelFactoryImpl implements AiModelFactory {
@Override
public VectorStore getOrCreateVectorStore(Class<? extends VectorStore> type,
EmbeddingModel embeddingModel,
Map<String, Class<?>> metadataFields) {
EmbeddingModel embeddingModel,
Map<String, Class<?>> metadataFields) {
String cacheKey = buildClientCacheKey(VectorStore.class, embeddingModel, type);
return Singleton.get(cacheKey, (Func0<VectorStore>) () -> {
if (type == SimpleVectorStore.class) {
@ -425,17 +428,24 @@ public class AiModelFactoryImpl implements AiModelFactory {
// ========== 各种创建 EmbeddingModel 的方法 ==========
// TODO @芋艿：需要测试下
/**
* 可参考 {@link DashScopeAutoConfiguration} 的 dashscopeEmbeddingModel 方法
*/
private DashScopeEmbeddingModel buildTongYiEmbeddingModel(String apiKey, String model) {
DashScopeApi dashScopeApi = new DashScopeApi(apiKey);
DashScopeEmbeddingOptions dashScopeEmbeddingOptions = DashScopeEmbeddingOptions.builder().withModel(model)
.build();
DashScopeEmbeddingOptions dashScopeEmbeddingOptions = DashScopeEmbeddingOptions.builder().withModel(model).build();
return new DashScopeEmbeddingModel(dashScopeApi, MetadataMode.EMBED, dashScopeEmbeddingOptions);
}
/**
* 可参考 {@link ZhiPuAiAutoConfiguration} 的 zhiPuAiEmbeddingModel 方法
*/
private ZhiPuAiEmbeddingModel buildZhiPuEmbeddingModel(String apiKey, String url, String model) {
url = StrUtil.blankToDefault(url, ZhiPuAiConnectionProperties.DEFAULT_BASE_URL);
ZhiPuAiApi zhiPuAiApi = new ZhiPuAiApi(url, apiKey);
return new ZhiPuAiEmbeddingModel(zhiPuAiApi);
}
private OllamaEmbeddingModel buildOllamaEmbeddingModel(String url, String model) {
OllamaApi ollamaApi = new OllamaApi(url);
OllamaOptions ollamaOptions = OllamaOptions.builder().model(model).build();