import { VectorStore } from "./vector-store.contract.mjs";
import { CacheDriver } from "@warlock.js/cache";

//#region ../ai/src/rag/store/cache-vector-store.d.ts
/**
 * Adapt any `@warlock.js/cache` `CacheDriver` to the {@link VectorStore}
 * narrowing the RAG pipeline depends on. The cache driver IS the vector
 * store — exactly as `SemanticMemory` and `semanticCache` already use it:
 *
 * - `upsert` → `driver.set(key, value, { vector, tags })`
 * - `query`  → `driver.similar<T>(vector, { topK, threshold, tags })`
 * - `removeNamespace` → `driver.removeNamespace(namespace)`
 *
 * Drivers without similarity support throw `CacheUnsupportedError` from
 * `set({ vector })` / `similar()`; the error surfaces unchanged so the
 * caller sees the cache layer's own message (pointing at the `pg` /
 * `redis` drivers for production-scale similarity).
 *
 * @example
 * const store = cacheVectorStore(new MemoryCacheDriver());
 * await store.upsert("ai.rag.docs.guide.0", { text: "…" }, vector);
 * const hits = await store.query(queryVector, { topK: 5, threshold: 0.5 });
 */
declare function cacheVectorStore(driver: CacheDriver<any, any>): VectorStore;
//#endregion
export { cacheVectorStore };
//# sourceMappingURL=cache-vector-store.d.mts.map