在Java中添加模型到MLFlow Registry的解决方案如下：

1. 创建MLFow客户端

MLFlow客户端用于与MLFlow服务器通信。可以使用以下代码创建客户端：

MlflowClient client = new MlflowClientFactory()
                            .setTrackingUri(trackingURI)
                            .setToken(token)
                            .build();

2. 注册模型

要将模型添加到MLFlow Registry，请执行以下操作：

RegisteredModel registeredModel = client.createRegisteredModel(modelName);

modelName参数是您想在MLFlow Registry中注册的模型的名称。

3. 创建新版本

要将新版本添加到注册模型，请执行以下操作：

ModelVersion modelVersion = client.createModelVersion(
                            modelName,
                            uri,
                            runId,
                            modelMetadata);

uri参数是模型的位置，例如“ file: / path / to / model”或“ s3: // bucket / path / to / model”。runId参数是与该模型相关联的运行的ID。modelMetadata参数是一个Map，其中包含与模型相关的其他元数据。

完整代码示例：

import org.mlflow.api.proto.ModelRegistry.*;
import org.mlflow.api.proto.Service.*;
import org.mlflow.tracking.MlflowClient;
import org.mlflow.tracking.MlflowClientFactory;

public class MlflowRegistryClient {
    public static void main(String[] args) {
        String trackingURI = "http://localhost:5000";
        String token = "token";

        MlflowClient client = new MlflowClientFactory()
                                    .setTrackingUri(trackingURI)
                                    .setToken(token)
                                    .build();

        // Register model
        String modelName = "MyModel";
        RegisteredModel registeredModel = client.createRegisteredModel(modelName);

        // Create new version
        String uri = "file:/path/to/my/model";
        String runId = "run_id";
        ModelVersionMetadata modelMetadata = new ModelVersionMetadata();
        modelMetadata.setSignature("{\"signature\": \"classifier\"}");
        ModelVersion modelVersion = client.createModelVersion(
                                            modelName,
                                            uri,
                                            runId,
                                            modelMetadata);

        // Print model version data
        System.out.println("Model version ID: " + modelVersion.getVersion());
        System.out.println("Model version status: " + modelVersion.getStatus().toString());
        System.out.println("Model version status message: " + modelVersion.getStatusMessage());
    }
}