/**
 * Semantic / hybrid search orchestration.
 *
 * Wraps the Phase 1 `IndexerAdapter.search` with the embedding-generation
 * step. When `mode: "semantic" | "hybrid"`, this helper embeds the query
 * via the configured `EmbeddingProvider`, attaches the vector to the
 * `SearchRequest` as `query_embedding`, and delegates to the adapter.
 *
 * Callers that already have a query embedding (an upstream agent that
 * vectorized the user's intent) can skip embedding by passing
 * `query_embedding` directly — `executeSemanticSearch` honors a
 * caller-supplied vector and skips the embed call.
 *
 * See `docs/architecture/catalog-architecture.md` for the design.
 */
import type { IndexerAdapter, IndexerSlice, SearchRequest, SearchResults } from "@voyant-travel/catalog-contracts/indexer/contract";
import type { EmbeddingProvider } from "../embeddings/contract.js";
export interface SemanticSearchOptions {
    /** Adapter to query. */
    adapter: IndexerAdapter;
    /**
     * Embedding provider — used to vectorize the query string when the mode
     * needs vectors. Optional: callers running pure-keyword searches can omit
     * this. `executeSemanticSearch` throws a clear error if mode is
     * `semantic` / `hybrid` and no provider is configured.
     */
    embeddings?: EmbeddingProvider;
    /** The variant slice (vertical, locale, audience, market) to search. */
    slice: IndexerSlice;
    /** The search request. `mode` controls keyword/hybrid/semantic blending. */
    request: SearchRequest;
}
/**
 * Run a search request that may need a query embedding generated.
 *
 * Behavior by mode:
 *   - `keyword`   — adapter.search called directly; no embedding work.
 *   - `hybrid`    — query string is embedded (unless caller supplied
 *                   `query_embedding`), adapter blends keyword + vector
 *                   scores.
 *   - `semantic`  — query string is embedded, adapter does pure vector
 *                   similarity. (Engines that don't support pure-semantic
 *                   typically fall back to hybrid with the keyword weight
 *                   set very low.)
 *
 * Verifies adapter capabilities at runtime: requesting `semantic` /
 * `hybrid` against an adapter without `supportsVectorFields` throws
 * a clear error rather than silently degrading to keyword-only.
 */
export declare function executeSemanticSearch(options: SemanticSearchOptions): Promise<SearchResults>;
/**
 * Helper for callers (typically AI agents) that have already vectorized
 * a query upstream and want to bypass the embedding step entirely. The
 * vector is attached to the request as-is.
 */
export declare function executeBYOVectorSearch(options: {
    adapter: IndexerAdapter;
    slice: IndexerSlice;
    request: SearchRequest & {
        query_embedding: number[];
    };
}): Promise<SearchResults>;