VectorDBExtensions.cs 是一个包含多个扩展方法的静态类，这些方法主要用于操作和管理 Milvus 向量数据库。这些方法包括：
- 建立 Milvus 客户端连接
- 对集合创建索引并加载
- 检查当前连接是否正常
- 创建测试集合，如果集合已经存在则删除集合
- 向字段列表添加字段
- 根据结构和 JSON 集合数据生成可用的向量字段数据
- 获取向向量库添加的数据，通过字段列表，对向列表，进行转换
- 输入向量数据，及对应的字段，进行向量查询
- 查询结果，根据向量查询结果，对结果对应索引数据进行查询
- 将搜索及对应查询进行合并
VectorDBExtensions.cs is a static class containing multiple extension methods mainly for operating and managing the Milvus vector database. These methods include:
- Establishing a Milvus client connection
- Creating an index for a collection and loading it
- Checking if the current connection is healthy
- Creating a test collection, if the collection already exists, it is dropped
- Adding fields to a field list
- Generating usable vector field data based on structure and JSON collection data
- Getting data to be added to the vector library, converting through the field list and vector list
- Inputting vector data and corresponding fields for vector query
- Querying results, based on vector query results, querying corresponding index data for results
- Combining search and corresponding query
public async Task AccessClientTest()
{
Random Random = new Random();
//建立連線
var db = new Milvus.ClientProfile("11.11.11.160", 19530, false).BuildClient();
//檢查連線是否正常
await db.IsHealthyAsync();
//建立Collection
var colSchema = new List<Milvus.Client.FieldSchema>();
//設定欄位
colSchema = colSchema
.AddCreateCollectionFields(FieldSchema.Create<long>("art_id", isPrimaryKey: true))
.AddCreateCollectionFields(FieldSchema.CreateVarchar("art_des", 1500))
.AddCreateCollectionFields(FieldSchema.CreateFloatVector("art_vector", 6));
//建立Collection
var collection = await db.CreateCollectionAsync("test", colSchema);
//建立資料
var data = Enumerable.Range(0, 1000).Select(x => new
{
art_id = x,
art_des = $"test{x}case",
art_vector = ""
}).ToList();
//將資料加入Collection
var datawithEmb = colSchema
.GetDataWithEmbeding(data, new("art_des", "art_vector"), embFunc);
//將資料加入Collection
await collection.InsertAsync(datawithEmb);
//建立索引
await collection.CreateIndexThenLoadAsync("art_vector", IndexType.AutoIndex);
//模拟函数, 生成随机向量
float[] embFunc(string q)
=> [Random.Next(), 2, 3, 4, 5, Random.Next()];
}
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent