feat: rag初始版

model/entity/dataset_index.go

@@ -0,0 +1,46 @@
+package entity
+
+import "gitea.com/red-future/common/beans"
+
+type datasetIndexCol struct {
+	beans.SQLBaseCol
+	Status       string
+	VectorStatus string
+	DatasetId    string
+	Name         string
+	Collection   string
+	Dimension    string
+	FieldType    string
+	MetricType   string
+	VectorCount  string
+	Description  string
+}
+
+var DatasetIndexCol = datasetIndexCol{
+	SQLBaseCol:   beans.DefSQLBaseCol,
+	Status:       "status",
+	VectorStatus: "vector_status",
+	DatasetId:    "dataset_id",
+	Name:         "name",
+	Collection:   "collection",
+	Dimension:    "dimension",
+	FieldType:    "field_type",
+	MetricType:   "metric_type",
+	VectorCount:  "vector_count",
+	Description:  "description",
+}
+
+// DatasetIndex 数据集索引实体
+type DatasetIndex struct {
+	beans.SQLBaseDO `orm:",inline"`
+
+	DatasetId   int64  `orm:"dataset_id" json:"datasetId" dc:"数据集ID"`
+	Name        string `orm:"name" json:"name" dc:"索引名称"`
+	Collection  string `orm:"collection" json:"collection" dc:"向量集合名称"`
+	Dimension   int    `orm:"dimension" json:"dimension" dc:"向量维度"`
+	FieldType   string `orm:"field_type" json:"fieldType" dc:"字段类型: float, binary"`
+	MetricType  string `orm:"metric_type" json:"metricType" dc:"度量类型: L2, IP, COSINE"`
+	Status      *int8  `orm:"status" json:"status" dc:"状态: creating, ready, error"`
+	VectorCount int64  `orm:"vector_count" json:"vectorCount" dc:"向量数量"`
+	Description string `orm:"description" json:"description" dc:"描述"`
+}