Essential for Java development: technical points for Baidu AI interface docking

Necessary for Java development: Technical points of Baidu AI interface docking

Baidu AI is one of the most popular artificial intelligence interfaces on the market. It provides a wealth of Functions and services, including speech recognition, image recognition, natural language processing, etc. In Java development, docking Baidu AI interface is a very common requirement. This article will introduce some technical points of docking Baidu AI interface, and provide corresponding Java code examples to help developers get started quickly.

1. Application and preparation for Baidu AI interface
To use the Baidu AI interface, you first need to apply on the Baidu AI platform and obtain the corresponding App Key and Secret Key. After the application is successful, we also need to add the corresponding dependent libraries. These libraries can be found in Baidu AI official documentation.

2. Preparations before calling the interface
Before using the Baidu AI interface, we need to make some necessary preparations, including introducing the corresponding Java package, creating an AI client and setting identity authentication information. wait.

Code example:

import com.baidu.aip.client.*; import com.baidu.aip.auth.*; import com.baidu.aip.http.*; import com.baidu.aip.nlp.*;

AipNlp client = new AipNlp(APP_ID, API_KEY, SECRET_KEY);

In the above code, we build Baidu AI’s client object AipNlp by introducing the relevant Java package, and pass in our App Key and Secret Key. Authentication.

3. Make interface calls
After completing the preparation work, we can start making interface calls. Taking Baidu AI's natural language processing interface as an example, we can call its text review service, which detects sensitive words and determines pornographic words on a text.

Code example:

HashMap options = new HashMap(); options.put("version", "1.0"); //接口版本号 String content = "今天天气真好！"; // 调用百度AI的文本审核接口 JSONObject result = client.antiSpam(content, options); System.out.println(result);

In the above code, we first create a HashMap object to set the relevant parameters of the interface, such as the interface version number, etc. Next, we define a text content to be reviewed. Finally, text review is performed by calling the antiSpam method of the AipNlp object and passing in the text content and parameter options. The return result is a JSON object, which we can process as needed, such as outputting to the console or further processing.

4. Processing the returned results of the interface
After the interface call is completed, we usually need to process the returned results. The result returned by Baidu AI interface is a JSON object, and we can directly obtain the data through Key. For complex results, we can also use the JSON parsing library for parsing.

Code example:

boolean spam = result.getJSONObject("result").getBoolean("spam"); int spamType = result.getJSONObject("result").getInt("spamType"); if (spam) { System.out.println("该文本包含敏感词！"); System.out.println("敏感词类型：" + spamType); } else { System.out.println("该文本通过审核！"); }

In the above code, we first obtain the spam field in the result through Key, which indicates whether the text contains sensitive words. Then, we obtain the spamType field, which represents the specific type of the sensitive word. Finally, perform corresponding processing based on the results, such as outputting to the console.

Summary:
This article introduces the technical points of docking Baidu AI interface and provides corresponding Java code examples. By learning and understanding these key points, developers can quickly master how to use Baidu AI interfaces to improve their efficiency and quality in Java development. I hope this article will be helpful for Java developers to connect to Baidu AI interface.

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