异步预测接口使用示例

创建异步调用

参考以下示例代码，通过content字段，传入长文本内容，NLP自学习平台会保存长文本，并进行异步模型预测。

package com.alibaba.nlp;

import com.aliyuncs.DefaultAcsClient;
import com.aliyuncs.IAcsClient;
import com.aliyuncs.exceptions.ClientException;
import com.aliyuncs.nlp_automl.model.v20191111.CreateAsyncPredictRequest;
import com.aliyuncs.nlp_automl.model.v20191111.CreateAsyncPredictResponse;
import com.aliyuncs.profile.DefaultProfile;
import com.google.gson.Gson;

public class NlpAutomlAsync {
    public static void main(String[] args) throws ClientException {
        DefaultProfile profile = DefaultProfile.getProfile(
            "cn-hangzhou",
            "<your-access-key-id>",
            "<your-access-key-secret>");
        IAcsClient client = new DefaultAcsClient(profile);

        CreateAsyncPredictRequest request = new CreateAsyncPredictRequest();
        request.setModelId(1818);
        request.setContent(longContent);
        CreateAsyncPredictResponse response = client.getAcsResponse(request);
        System.out.println("" + new Gson().toJson(response));
    }
}
            

另外，可以通过将本地文件内容进行base64编码之后，作为字符串上传NLP自学习平台系统，NLP自学习平台支持解析base64编码的文件内容。并做文本抽取，进行模型预测调用。以下是参考示例代码。

package com.alibaba.nlp;

import com.aliyuncs.DefaultAcsClient;
import com.aliyuncs.IAcsClient;
import com.aliyuncs.exceptions.ClientException;
import com.aliyuncs.nlp_automl.model.v20191111.CreateAsyncPredictRequest;
import com.aliyuncs.nlp_automl.model.v20191111.CreateAsyncPredictResponse;
import com.aliyuncs.profile.DefaultProfile;
import com.google.gson.Gson;

import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.util.Base64;

public class NlpAutomlAsyncDaily {
    public static void main(String[] args) throws ClientException, IOException {
        DefaultProfile profile = DefaultProfile.getProfile(
            "cn-hangzhou",
            "<your-access-key-id>",
            "<your-access-key-secret>");
        IAcsClient client = new DefaultAcsClient(profile);

        InputStream in = new FileInputStream("<local-file-dir>");
        byte[] data = new byte[in.available()];
        int readSize = in.read(data);
        System.out.println("read data size=" + readSize);
        in.close();
        String base64String = Base64.getEncoder().encodeToString(data);
        System.out.println("base64 string length=" + base64String.length());

        CreateAsyncPredictRequest request = new CreateAsyncPredictRequest();
        request.setModelId(2269);
        request.setFileType("<file-type>");
        request.setFileContent(base64String);
        CreateAsyncPredictResponse response = client.getAcsResponse(request);
        System.out.println("" + new Gson().toJson(response));
    }
}

调用成功之后，NLP自学习平台返回一个asyncPredictId字段，用于查询异步预测结果信息。

{
  "requestId": "65917545-CDBF-4246-8708-CD03ED4AFDED",
  "asyncPredictId": 1669
}

通过使用asyncPredictId参考下一章节获取异步预测结果。

获取异步调用结果

通过创建GetAsyncPredictRequest请求，查询异步预测结果。

package com.alibaba.nlp;

import com.aliyuncs.DefaultAcsClient;
import com.aliyuncs.IAcsClient;
import com.aliyuncs.exceptions.ClientException;
import com.aliyuncs.nlp_automl.model.v20191111.GetAsyncPredictRequest;
import com.aliyuncs.nlp_automl.model.v20191111.GetAsyncPredictResponse;
import com.aliyuncs.profile.DefaultProfile;
import com.google.gson.Gson;

public class NlpAutomlAsync2 {
    public static void main(String[] args) throws ClientException {
        DefaultProfile profile = DefaultProfile.getProfile(
            "cn-hangzhou",
            "<your-access-key-id>",
            "<your-access-key-secret>");
        IAcsClient client = new DefaultAcsClient(profile);

        GetAsyncPredictRequest request = new GetAsyncPredictRequest();
        request.setAsyncPredictId(1669);
        GetAsyncPredictResponse response = client.getAcsResponse(request);
        System.out.println("" + new Gson().toJson(response));

    }
}