!3 修改readme一些解释,增加dbName等字段配置

Merge pull request !3 from Mose-X/main
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xgc 2024-05-29 10:28:53 +00:00 committed by Gitee
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6 changed files with 52 additions and 32 deletions

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@ -66,14 +66,14 @@ milvus:
token: x'x'x'x
enable: true
packages:
- io.github.javpower.milvus.demo.model
- com.example.entity
```
- `milvus`定义了与Milvus服务相关的配置。
- `uri`Milvus服务的URI应用程序通过这个URI与Milvus服务进行通信。
- `token`用于验证和授权的令牌Token确保访问Milvus服务的安全性。
- `enable`一个布尔值用于指示Milvus模块是否应该被启用。
- `packages`这些包包含了自定义注解对应的Java类。
- `packages`这些包包含了自定义注解对应的Java类,你可以认为这是你自定义的实体类所在的包
## 应用场景

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@ -29,7 +29,7 @@ Core
<dependency>
<groupId>io.github.javpower</groupId>
<artifactId>milvus-plus-core</artifactId>
<version>2.4.0-SNAPSHOT</version>
<version>2.4.0</version>
</dependency>
```
@ -40,7 +40,7 @@ Spring
<dependency>
<groupId>io.github.javpower</groupId>
<artifactId>milvus-plus-boot-starter</artifactId>
<version>2.4.0-SNAPSHOT</version>
<version>2.4.0</version>
</dependency>
```
@ -50,7 +50,7 @@ Solon
<dependency>
<groupId>io.github.javpower</groupId>
<artifactId>milvus-plus-solon-plugin</artifactId>
<version>2.4.0-SNAPSHOT</version>
<version>2.4.0</version>
</dependency>
```
@ -79,29 +79,29 @@ Example usage:
```java
@Data
@MilvusCollection(name = "face_collection") // 指定Milvus集合的名称
@MilvusCollection(name = "face_collection") // Specifies the name of the Milvus collection
public class Face {
@MilvusField(
name = "person_id", // 字段名称
dataType = DataType.Int64, // 数据类型为64位整数
isPrimaryKey = true, // 标记为主键
name = "person_id", // Field Name
dataType = DataType.Int64, // Data type is 64-bit integer
isPrimaryKey = true // Mark as Primary Key
)
private Long personId; // 人员的唯一标识符
private Long personId; // Unique identifier of the person
@MilvusField(
name = "face_vector", // 字段名称
dataType = DataType.FloatVector, // 数据类型为浮点型向量
dimension = 128, // 向量维度,假设人脸特征向量的维度是128
name = "face_vector", // Field Name
dataType = DataType.FloatVector, // The data type is a floating point vector
dimension = 128 // Vector dimension, assuming that the dimension of the face feature vector is 128
)
@MilvusIndex(
indexType = IndexParam.IndexType.IVF_FLAT, // 使用IVF_FLAT索引类型
metricType = IndexParam.MetricType.L2, // 使用L2距离度量类型
indexName = "face_index", // 索引名称
extraParams = { // 指定额外的索引参数
@ExtraParam(key = "nlist", value = "100") // 例如IVF的nlist参数
indexType = IndexParam.IndexType.IVF_FLAT, // Using the IVF FLAT index type
metricType = IndexParam.MetricType.L2, // Using the L 2 Distance Metric Type
indexName = "face_index", // Index Name
extraParams = { // Specify additional index parameters
@ExtraParam(key = "nlist", value = "100") // For example, the nlist parameter for IVF
}
)
private List<Float> faceVector; // 存储人脸特征的向量
private List<Float> faceVector; // Storing vectors of face features
}
```
```
@ -124,50 +124,58 @@ public class ApplicationRunnerTest implements ApplicationRunner {
Face face=new Face();
List<Float> vector = new ArrayList<>();
for (int i = 0; i < 128; i++) {
vector.add((float) (Math.random() * 100)); // 这里仅作为示例使用随机数
vector.add((float) (Math.random() * 100)); // Using random numbers here as an example only
}
face.setPersonId(1l);
face.setFaceVector(vector);
//新增
// add
List<Face> faces=new ArrayList<>();
for (int i = 1; i < 10 ;i++){
Face face1=new Face();
face1.setPersonId(Long.valueOf(i));
List<Float> vector1 = new ArrayList<>();
for (int j = 0; j < 128; j++) {
vector1.add((float) (Math.random() * 100)); // 这里仅作为示例使用随机数
vector1.add((float) (Math.random() * 100)); // Using random numbers here as an example only
}
face1.setFaceVector(vector1);
faces.add(face1);
}
MilvusResp<InsertResp> insert = mapper.insert(faces.toArray(faces.toArray(new Face[0]))); log.info("insert--{}", JSONObject.toJSONString(insert));
//id查询
// id query
MilvusResp<List<MilvusResult<Face>>> query = mapper.getById(9l);
log.info("query--getById---{}", JSONObject.toJSONString(query));
//向量查询
// VECTOR QUERY
MilvusResp<List<MilvusResult<Face>>> query1 = mapper.queryWrapper()
.vector(Face::getFaceVector, vector)
.ne(Face::getPersonId, 1L)
.topK(3)
.query();
log.info("向量查询 query--queryWrapper---{}", JSONObject.toJSONString(query1));
//标量查询
log.info("VectorQuery query--queryWrapper---{}", JSONObject.toJSONString(query1));
// SCALAR QUERY
MilvusResp<List<MilvusResult<Face>>> query2 = mapper.queryWrapper()
.eq(Face::getPersonId, 2L)
.limit(3)
.query();
log.info("标量查询 query--queryWrapper---{}", JSONObject.toJSONString(query2));
//更新
log.info("ScalarQuery query--queryWrapper---{}", JSONObject.toJSONString(query2));
// update
vector.clear();
for (int i = 0; i < 128; i++) {
vector.add((float) (Math.random() * 100)); // 这里仅作为示例使用随机数
vector.add((float) (Math.random() * 100)); // Using random numbers here as an example only
}
MilvusResp<UpsertResp> update = mapper.updateById(face);log.info("update--{}", JSONObject.toJSONString(update));
//id查询
// id Query
MilvusResp<List<MilvusResult<Face>>> query3 = mapper.getById(1L);log.info("query--getById---{}", JSONObject.toJSONString(query3));
//删除
// del
MilvusResp<DeleteResp> remove = mapper.removeById(1L);log.info("remove--{}", JSONObject.toJSONString(remove));
//查询
// query
MilvusResp<List<MilvusResult<Face>>> query4 = mapper.getById(1L);log.info("query--{}", JSONObject.toJSONString(query4));
}

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@ -15,6 +15,9 @@ import java.util.List;
public class MilvusProperties {
private boolean enable;
private String uri;
private String dbName;
private String username;
private String password;
private String token;
private List<String> packages;
}

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@ -11,6 +11,9 @@ import java.util.List;
public class MilvusProperties {
private boolean enable;
private String uri;
private String dbName;
private String username;
private String password;
private String token;
private List<String> packages;
}

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@ -38,6 +38,9 @@ public abstract class AbstractMilvusClientBuilder implements MilvusClientBuilder
ConnectConfig connectConfig = ConnectConfig.builder()
.uri(properties.getUri())
.token(properties.getToken())
.dbName(properties.getDbName())
.username(properties.getUsername())
.password(properties.getPassword())
.build();
client = new MilvusClientV2(connectConfig);
// 初始化逻辑

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@ -15,6 +15,9 @@ import java.util.List;
public class MilvusProperties {
private boolean enable;
private String uri;
private String dbName;
private String username;
private String password;
private String token;
private List<String> packages;
}