java框架如何利用人工智能增强现有应用？

import com.google.cloud.recommendationengine.v1beta1.CatalogServiceClient;
import com.google.cloud.recommendationengine.v1beta1.PredictRequest;
import com.google.cloud.recommendationengine.v1beta1.PredictResponse;
import com.google.protobuf.ListValue;
import com.google.protobuf.Value;

// ... (省略对 CatalogServiceClient 的实例化)

// 创建预测请求
PredictRequest predictRequest =
    PredictRequest.newBuilder()
        .setPlacement("your-placement-id")
        .setUserId("your-user-id")
        .addAllRecentItemIds(Arrays.asList("product_id1", "product_id2"))
        .putContext("page_category", Value.newBuilder().setStringValue("electronics").build())
        .build();

// 获取预测结果
PredictResponse predictResponse = catalogServiceClient.predict(predictRequest);

import io.jbot.core.chat.DefaultTextTemplateProcessor;
import io.jbot.core.chat.TextTemplateProcessor;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.CommandLineRunner;
import org.springframework.stereotype.Component;

// ... (省略其余代码)

@Component
public class CustomCommandLineRunner implements CommandLineRunner {

    @Autowired
    private TextTemplateProcessor defaultTextTemplateProcessor;

    @Override
    public void run(String... args) throws Exception {
        defaultTextTemplateProcessor.setProcessor("custom_processor", new MyCustomTextTemplateProcessor());
    }
}