repositories {
    maven("https://jitpack.io")
}

dependencies {
    implementation("com.github.kkokotero:VectorLite:1.0.0")
}

import io.github.kkokotero.vectorlite.orm.Column
import io.github.kkokotero.vectorlite.orm.DataTable
import io.github.kkokotero.vectorlite.orm.ForeignKey
import io.github.kkokotero.vectorlite.orm.Relationship
import io.github.kkokotero.vectorlite.orm.RelationshipType
import io.github.kkokotero.vectorlite.orm.VectorColumn

@DataTable("users")
data class UserEntity(
    @Column(primaryKey = true, autoIncrement = true, nullable = false)
    val id: Long = 0,

    @Column(nullable = false, unique = true)
    val email: String,

    @Column(nullable = false)
    val name: String
)

@DataTable("face_embeddings")
data class FaceEmbeddingEntity(
    @Column(primaryKey = true, autoIncrement = true, nullable = false)
    val id: Long = 0,

    @ForeignKey(entity = UserEntity::class)
    @Column(nullable = false)
    val userId: Long,

    @VectorColumn(dimensions = 512, elementSize = 4)
    val embedding: FloatArray
)

import io.github.kkokotero.vectorlite.VectorLite

val db = VectorLite.database(context) {
    entities(
        UserEntity::class,
        FaceEmbeddingEntity::class
    )

    services(
        FaceRecognitionService::class
    )
}

val users = db.crud<UserEntity>()
val embeddings = db.repository<FaceEmbeddingEntity>()
val faceService = db.service<FaceRecognitionService>()

val users = db.crud<UserEntity>()

users.create(
    UserEntity(name = "Kevin", email = "kevin@example.com")
)

val kevin = users.first {
    UserEntity::email equal "kevin@example.com"
}

val allUsers = users.findAll()

val embeddings = db.repository<FaceEmbeddingEntity>()

embeddings.insertAll(
    FaceEmbeddingEntity(userId = 1, embedding = queryVector),
    FaceEmbeddingEntity(userId = 2, embedding = otherVector)
)

import io.github.kkokotero.vectorlite.DefaultTableService
import io.github.kkokotero.vectorlite.Repository
import io.github.kkokotero.vectorlite.Service
import io.github.kkokotero.vectorlite.VectorLiteSession
import io.github.kkokotero.vectorlite.orm.Table

@Service
class FaceRecognitionService(
    table: Table<FaceEmbeddingEntity>,
    session: VectorLiteSession,
    private val embeddings: Repository<FaceEmbeddingEntity>
) : DefaultTableService<FaceEmbeddingEntity>(table, session) {

    fun storeEmbedding(userId: Long, vector: FloatArray): FaceEmbeddingEntity {
        return create(
            FaceEmbeddingEntity(
                userId = userId,
                embedding = vector
            )
        )
    }
}

val service = db.service<FaceRecognitionService>()
service.storeEmbedding(userId = 1, vector = embedding)

val users = db.crud<UserEntity>()

val kevin = users.first {
    UserEntity::name equal "Kevin"
}

val matchedUsers = users.where {
    UserEntity::email matches "%@example.com"
}

val results = db.repository<FaceEmbeddingEntity>()
    .query()
    .nearestTo(
        column = FaceEmbeddingEntity::embedding,
        vector = queryVector,
        options = io.github.kkokotero.vectorlite.orm.VectorSearchOptions(
            topK = 5,
            approximate = true
        )
    )
    .vectorSearch()

val bestMatch = results.bestMatch

val match = db.table<FaceEmbeddingEntity>().nearestNeighbor(
    vectorColumn = FaceEmbeddingEntity::embedding,
    queryVector = queryVector
)

@DataTable("users")
data class UserEntity(
    @Column(primaryKey = true, autoIncrement = true, nullable = false)
    val id: Long = 0,

    @Column(nullable = false)
    val name: String,

    @Relationship(
        targetEntity = FaceEmbeddingEntity::class,
        type = RelationshipType.ONE_TO_MANY,
        mappedBy = "userId"
    )
    var embeddings: List<FaceEmbeddingEntity> = emptyList()
)

db.transaction {
    val users = db.repository<UserEntity>()
    val embeddings = db.repository<FaceEmbeddingEntity>()

    val userId = users.insert(
        UserEntity(name = "Kevin", email = "kevin@example.com")
    )

    embeddings.insert(
        FaceEmbeddingEntity(
            userId = userId,
            embedding = queryVector
        )
    )
}

db.tableChanges("users").collect { event ->
    println("${event.tableName} changed: ${event.operation}")
}

db.triggers.afterInsert<UserEntity> {
    println("User inserted")
}

db.triggers.afterUpdate<UserEntity> {
    println("User updated")
}

db.triggers.afterDelete<UserEntity> {
    println("User deleted")
}

import java.io.File

db.exportTo(File(context.filesDir, "vectorlite-backup.db"))
db.importFrom(File(context.filesDir, "vectorlite-backup.db"))