


How to integrate and use the intelligent music recommendation function of Baidu AI interface in a Java project
How to integrate and use the intelligent music recommendation function of Baidu AI interface in a Java project
With the development of artificial intelligence, the intelligent music recommendation system has become a modern music platform Indispensable part. Among them, the intelligent music recommendation function in Baidu AI interface provides developers with a convenient and efficient music recommendation solution. This article will introduce how to integrate and use the intelligent music recommendation function of Baidu AI interface in a Java project.
- Get application information of Baidu AI Music Recommendation API
Before we start, we need to go to Baidu AI Open Platform to create an application and obtain the corresponding App ID and API Key. The specific steps are as follows:
- Log in to Baidu AI Open Platform (https://ai.baidu.com/)
- Create an application and select the "Music Recommendation" service
- App ID and API Key can be found in the application details
- Import Baidu AI music recommendation SDK
In order to facilitate the use of Baidu AI music recommendation interface, we The relevant SDK needs to be imported. You can find the Java version of the music recommendation SDK in the SDK Resource Center of Baidu AI Open Platform (https://ai.baidu.com/sdk). After downloading, add the SDK jar package to the dependencies of the Java project.
- Calling Baidu AI music recommendation interface
In a Java project, using Baidu AI music recommendation interface requires creating a BaiduMusicClient object and passing in the App ID and API Key. The sample code is as follows:
import com.baidu.aip.client.BaseClient; import com.baidu.aip.http.AipRequest; import com.baidu.aip.http.EBodyFormat; public class BaiduMusicClient extends BaseClient { private static final String API_URL = "https://aip.baidubce.com/rpc/2.0/solution/v1/music_recommender/recommend"; private String accessToken; public BaiduMusicClient(String appId, String apiKey) { super(appId, apiKey); } public void setAccessToken(String accessToken) { this.accessToken = accessToken; } public JSONObject recommendMusic(String userId, int num) { AipRequest request = new AipRequest(); request.setUri(API_URL); request.setMethod(EBodyFormat.RAW_JSON); JSONObject data = new JSONObject(); data.put("userId", userId); data.put("num", num); request.setBody(data.toString()); request.addHeader("Content-Type", "application/json"); postOperation(request); } @Override public void refreshAccessToken() { // 根据百度AI开放平台的文档,实现Token刷新逻辑 } }
The above code creates a BaiduMusicClient class, in which the recommendedMusic method is used to call the Baidu AI music recommendation interface and pass in the user ID and the number of recommendations. In actual use, we also need to implement Token refresh logic. To simplify the example here, the code related to Token refresh is omitted.
- Call Baidu AI music recommendation interface and parse the returned results
The sample code for calling Baidu AI music recommendation interface in a Java project is as follows:
public class Main { public static void main(String[] args) { String appId = "your_app_id"; String apiKey = "your_api_key"; BaiduMusicClient client = new BaiduMusicClient(appId, apiKey); String userId = "your_user_id"; int num = 10; JSONObject result = client.recommendMusic(userId, num); // 处理返回结果 JSONArray songs = result.getJSONObject("result").getJSONArray("songs"); for (int i = 0; i < songs.length(); i++) { JSONObject song = songs.getJSONObject(i); String songId = song.getString("songId"); String songName = song.getString("songName"); String artist = song.getString("artist"); System.out.println("推荐歌曲:"); System.out.println("歌曲ID:" + songId); System.out.println("歌曲名:" + songName); System.out.println("歌手:" + artist); System.out.println("------------"); } } }
In this example, we create a BaiduMusicClient object and pass in the App ID and API Key. Then call the recommendMusic method, passing in the user ID and the number of songs to be recommended. Finally, we parse the returned results, obtain recommended song information, and process them.
Through the above steps, we have successfully integrated and used the function of Baidu AI music recommendation interface. In practical applications, we can call the interface to recommend music to users that they may be interested in based on their preferences and contextual information. This greatly enriches the user experience of the music platform and improves user retention.
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