feat(ai): 完善模型管理和智能体导入功能

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14 小时以前 95ae0c83d2aa58d86b4039e3f7f16ee93afb8f00

 yudao-module-ai/src/main/java/cn/iocoder/yudao/module/ai/service/model/AiModelServiceImpl.java

@@ -1,93 +1,80 @@
package cn.iocoder.yudao.module.ai.service.model;

import cn.iocoder.yudao.module.ai.enums.model.AiPlatformEnum;
import cn.iocoder.yudao.module.ai.framework.ai.core.model.AiModelFactory;
import cn.iocoder.yudao.module.ai.framework.ai.core.model.midjourney.api.MidjourneyApi;
import cn.iocoder.yudao.module.ai.framework.ai.core.model.suno.api.SunoApi;
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.model.vo.model.AiModelPageReqVO;
import cn.iocoder.yudao.module.ai.controller.admin.model.vo.model.AiModelSaveReqVO;
import cn.iocoder.yudao.module.ai.controller.admin.model.vo.model.AiModelUpdateStatusReqVO;
import cn.iocoder.yudao.module.ai.dal.dataobject.model.AiApiKeyDO;
import cn.iocoder.yudao.module.ai.dal.dataobject.model.AiModelDO;
import cn.iocoder.yudao.module.ai.dal.mysql.model.AiChatMapper;
import com.agentsflex.llm.ollama.OllamaLlm;
import com.agentsflex.llm.ollama.OllamaLlmConfig;
import com.agentsflex.llm.qwen.QwenLlm;
import com.agentsflex.llm.qwen.QwenLlmConfig;
import dev.tinyflow.core.Tinyflow;
import cn.iocoder.yudao.module.ai.dal.mysql.model.AiModelMapper;
import cn.iocoder.yudao.module.ai.enums.model.AiModelCapabilityEnum;
import cn.iocoder.yudao.module.ai.enums.model.AiModelTypeEnum;
import cn.iocoder.yudao.module.ai.enums.model.AiPlatformEnum;
import cn.iocoder.yudao.module.ai.framework.ai.config.YudaoAiProperties;
import cn.iocoder.yudao.module.ai.framework.ai.core.model.AiModelFactory;
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.milvus.MilvusVectorStore;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
import org.springframework.validation.annotation.Validated;

import java.util.List;
import java.util.Map;

import static cn.iocoder.yudao.framework.common.exception.util.ServiceExceptionUtil.exception;
import static cn.iocoder.yudao.module.ai.enums.ErrorCodeConstants.*;

/**
 * AI 模型 Service 实现类
 *
 * @author fansili
 */
@Service
@Validated
public class AiModelServiceImpl implements AiModelService {

    @Resource
    private AiApiKeyService apiKeyService;

    @Resource
    private AiChatMapper modelMapper;

    private AiModelMapper modelMapper;
    @Resource
    private AiModelFactory modelFactory;
    @Resource
    private YudaoAiProperties aiProperties;

    @Override
    @Transactional(rollbackFor = Exception.class)
    public Long createModel(AiModelSaveReqVO createReqVO) {
        // 1. 校验
        AiPlatformEnum.validatePlatform(createReqVO.getPlatform());
        apiKeyService.validateApiKey(createReqVO.getKeyId());

        // 2. 插入
        AiModelDO model = BeanUtils.toBean(createReqVO, AiModelDO.class);
        model.setCapability(resolveCapability(createReqVO.getCapability()));
        if (CommonStatusEnum.isEnable(model.getStatus())) {
            disableOtherEnabledModels(model);
        }
        modelMapper.insert(model);
        return model.getId();
    }

    @Override
    @Transactional(rollbackFor = Exception.class)
    public void updateModel(AiModelSaveReqVO updateReqVO) {
        // 1. 校验
        validateModelExists(updateReqVO.getId());
        AiModelDO existing = validateModelExists(updateReqVO.getId());
        AiPlatformEnum.validatePlatform(updateReqVO.getPlatform());
        apiKeyService.validateApiKey(updateReqVO.getKeyId());

        // 2. 更新
        AiModelDO updateObj = BeanUtils.toBean(updateReqVO, AiModelDO.class);
        modelMapper.updateById(updateObj);
        AiModelDO model = BeanUtils.toBean(updateReqVO, AiModelDO.class);
        // 未传能力时沿用原值，避免老前端提交把视觉模型降级成文本能力
        model.setCapability(resolveCapability(
                updateReqVO.getCapability() == null || updateReqVO.getCapability().isBlank()
                        ? existing.getCapability() : updateReqVO.getCapability()));
        if (CommonStatusEnum.isEnable(model.getStatus())) {
            disableOtherEnabledModels(model);
        }
        modelMapper.updateById(model);
    }

    @Override
    public void deleteModel(Long id) {
        // 校验存在
        validateModelExists(id);
        // 删除
        modelMapper.deleteById(id);
    }

    private AiModelDO validateModelExists(Long id) {
        AiModelDO model = modelMapper.selectById(id);
        if (modelMapper.selectById(id) == null) {
            throw exception(MODEL_NOT_EXISTS);
        }
        return model;
    }

    @Override
@@ -97,9 +84,16 @@

    @Override
    public AiModelDO getRequiredDefaultModel(Integer type) {
        AiModelDO model = modelMapper.selectFirstByStatus(type, CommonStatusEnum.ENABLE.getStatus());
        return getRequiredDefaultModel(type, AiModelCapabilityEnum.defaultCapability());
    }

    @Override
    public AiModelDO getRequiredDefaultModel(Integer type, String capability) {
        AiModelDO model = modelMapper.selectFirstByTypeAndCapabilityAndStatus(
                type, resolveCapability(capability), CommonStatusEnum.ENABLE.getStatus());
        if (model == null) {
            throw exception(MODEL_DEFAULT_NOT_EXISTS);
            throw exception(MODEL_NOT_ENABLED,
                    AiModelTypeEnum.getName(type), AiModelCapabilityEnum.getName(resolveCapability(capability)));
        }
        return model;
    }
@@ -110,17 +104,55 @@
    }

    @Override
    @Transactional(rollbackFor = Exception.class)
    public void updateModelStatus(AiModelUpdateStatusReqVO updateReqVO) {
        AiModelDO model = validateModelExists(updateReqVO.getId());
        model.setStatus(updateReqVO.getStatus());
        if (CommonStatusEnum.isEnable(updateReqVO.getStatus())) {
            // 启用：自动关闭同「类型 + 能力」下的其他模型，保证同组只有一个启用
            disableOtherEnabledModels(model);
        }
        modelMapper.updateById(model);
    }

    @Override
    public AiModelDO validateModel(Long id) {
        AiModelDO model = validateModelExists(id);
        if (CommonStatusEnum.isDisable(model.getStatus())) {
            throw exception(MODEL_DISABLE);
        }
        if (CommonStatusEnum.isDisable(model.getStatus())) throw exception(MODEL_DISABLE, model.getName());
        return model;
    }

    @Override
    public List<AiModelDO> getModelListByStatusAndType(Integer status, Integer type, String platform) {
        return modelMapper.selectListByStatusAndType(status, type, platform);
    }

    /**
     * 关闭同「类型 + 能力」下已启用的其他模型（不含自身）
     */
    private void disableOtherEnabledModels(AiModelDO model) {
        List<AiModelDO> sameGroup = modelMapper.selectListByTypeAndCapabilityAndStatus(
                model.getType(), resolveCapability(model.getCapability()), CommonStatusEnum.ENABLE.getStatus());
        for (AiModelDO other : sameGroup) {
            if (other.getId().equals(model.getId())) {
                continue;
            }
            AiModelDO update = new AiModelDO();
            update.setId(other.getId());
            update.setStatus(CommonStatusEnum.DISABLE.getStatus());
            modelMapper.updateById(update);
        }
    }

    private static String resolveCapability(String capability) {
        return capability == null || capability.isBlank()
                ? AiModelCapabilityEnum.defaultCapability() : capability;
    }

    private AiModelDO validateModelExists(Long id) {
        AiModelDO model = modelMapper.selectById(id);
        if (model == null) throw exception(MODEL_NOT_EXISTS);
        return model;
    }

    // ========== 与 Spring AI 集成 ==========
@@ -130,72 +162,22 @@
        AiModelDO model = validateModel(id);
        AiApiKeyDO apiKey = apiKeyService.validateApiKey(model.getKeyId());
        AiPlatformEnum platform = AiPlatformEnum.validatePlatform(apiKey.getPlatform());
        return modelFactory.getOrCreateChatModel(platform, apiKey.getApiKey(), apiKey.getUrl());
    }

    @Override
    public ImageModel getImageModel(Long id) {
        AiModelDO model = validateModel(id);
        AiApiKeyDO apiKey = apiKeyService.validateApiKey(model.getKeyId());
        AiPlatformEnum platform = AiPlatformEnum.validatePlatform(apiKey.getPlatform());
        return modelFactory.getOrCreateImageModel(platform, apiKey.getApiKey(), apiKey.getUrl());
    }

    @Override
    public MidjourneyApi getMidjourneyApi(Long id) {
        AiModelDO model = validateModel(id);
        AiApiKeyDO apiKey = apiKeyService.validateApiKey(model.getKeyId());
        return modelFactory.getOrCreateMidjourneyApi(apiKey.getApiKey(), apiKey.getUrl());
    }

    @Override
    public SunoApi getSunoApi() {
        AiApiKeyDO apiKey = apiKeyService.getRequiredDefaultApiKey(
                AiPlatformEnum.SUNO.getPlatform(), CommonStatusEnum.ENABLE.getStatus());
        return modelFactory.getOrCreateSunoApi(apiKey.getApiKey(), apiKey.getUrl());
        // temperature / maxTokens 是 AI 模型表上一直存在、却从没人读过的两列：
        // 不读 temperature，库里配的值对调用方是假的；不读 maxTokens，长输出会被静默截断
        return modelFactory.getOrCreateChatModel(platform, apiKey.getApiKey(), apiKey.getUrl(), model.getModel(),
                model.getTemperature(), model.getMaxTokens(), aiProperties.getTimeout());
    }

    @Override
    public VectorStore getOrCreateVectorStore(Long id, Map<String, Class<?>> metadataFields) {
        // 获取模型 + 密钥
        AiModelDO model = validateModel(id);
        AiApiKeyDO apiKey = apiKeyService.validateApiKey(model.getKeyId());
        AiPlatformEnum platform = AiPlatformEnum.validatePlatform(apiKey.getPlatform());

        // 创建或获取 EmbeddingModel 对象
        EmbeddingModel embeddingModel = modelFactory.getOrCreateEmbeddingModel(
                platform, apiKey.getApiKey(), apiKey.getUrl(), model.getModel());

        // 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);
    }

    // TODO @lesan：是不是返回 Llm 对象会好点哈？
    @Override
    public void getLLmProvider4Tinyflow(Tinyflow tinyflow, Long modelId) {
        AiModelDO model = validateModel(modelId);
        AiApiKeyDO apiKey = apiKeyService.validateApiKey(model.getKeyId());
        AiPlatformEnum platform = AiPlatformEnum.validatePlatform(apiKey.getPlatform());
        switch (platform) {
            // TODO @lesan 考虑到未来不需要使用agents-flex 现在仅测试通义千问
            // TODO @lesan：【重要】是不是可以实现一个 SpringAiLlm，这样的话，内部全部用它就好了。只实现 chat 部分；这样，就把 flex 作为一个 agent 框架，内部调用，还是 spring ai 相关的。成本可能低一点？！
            case TONG_YI:
                QwenLlmConfig qwenLlmConfig = new QwenLlmConfig();
                qwenLlmConfig.setApiKey(apiKey.getApiKey());
                qwenLlmConfig.setModel(model.getModel());
                // TODO @lesan：这个有点奇怪。。。如果一个链式里，有多个模型，咋整呀。。。
                tinyflow.setLlmProvider(id -> new QwenLlm(qwenLlmConfig));
                break;
            case OLLAMA:
                OllamaLlmConfig ollamaLlmConfig = new OllamaLlmConfig();
                ollamaLlmConfig.setEndpoint(apiKey.getUrl());
                ollamaLlmConfig.setModel(model.getModel());
                tinyflow.setLlmProvider(id -> new OllamaLlm(ollamaLlmConfig));
                break;
        }
        return modelFactory.getOrCreateVectorStore(MilvusVectorStore.class, embeddingModel, metadataFields);
    }

}