khive_storage/
vectors.rs

1//! Vector embedding storage and similarity search capability (ADR-024).
2
3use async_trait::async_trait;
4use uuid::Uuid;
5
6use khive_types::SubstrateKind;
7
8use crate::types::{
9    BatchWriteSummary, IndexRebuildScope, StorageResult, VectorRecord, VectorSearchHit,
10    VectorSearchRequest, VectorStoreInfo,
11};
12
13#[async_trait]
14pub trait VectorStore: Send + Sync + 'static {
15    async fn insert(
16        &self,
17        subject_id: Uuid,
18        kind: SubstrateKind,
19        namespace: &str,
20        embedding: Vec<f32>,
21    ) -> StorageResult<()>;
22    async fn insert_batch(&self, records: Vec<VectorRecord>) -> StorageResult<BatchWriteSummary>;
23    async fn delete(&self, subject_id: Uuid) -> StorageResult<bool>;
24    async fn count(&self) -> StorageResult<u64>;
25    async fn search(&self, request: VectorSearchRequest) -> StorageResult<Vec<VectorSearchHit>>;
26    async fn info(&self) -> StorageResult<VectorStoreInfo>;
27    async fn rebuild(&self, scope: IndexRebuildScope) -> StorageResult<VectorStoreInfo>;
28}
khive_storage/vectors.rs

khive_storage/
vectors.rs
