import type { SqlClient, ChunkSearchResult, SqlParam } from "./types.js";
import { type CompiledExcludes } from "./exclude.js";
import { type CompiledMounts } from "./mounts.js";
export declare function validateEmbedding(embedding: number[], expectedDimensions?: number): void;
export interface ChunkSearchOpts {
    path?: string;
    limit?: number;
    /** Max hits per file path (default 3) so one long page can't monopolize the top-k. */
    perFileCap?: number;
    excludes?: CompiledExcludes;
    mounts?: CompiledMounts;
}
/**
 * The version-visibility projection every version-scoped chunk operation
 * shares — searches and the maintenance passes alike: the nearest entry per
 * path along version $2's ancestor chain (so shadowed blobs and tombstoned
 * paths never count), scoped to the $3 subtree and filtered by the
 * instance's excludes/mounts. Yields (path, blob_hash, node_type); callers
 * must still keep only `node_type = 'file'` rows. References $1
 * (workspace), $2 (version) and $3 (scope ltree); the exclude/mount params
 * returned here are numbered from `paramStart`.
 */
export declare function visibleEntriesSql(excludes: CompiledExcludes | undefined, mounts: CompiledMounts | undefined, paramStart: number): {
    sql: string;
    params: SqlParam[];
};
/**
 * BM25 search at version V: lexical hits rank sections. A blob visible at
 * several paths yields one hit per (path, chunk); a blob with several
 * matching chunks yields one hit per chunk (up to the per-file cap).
 * Non-matching rows score 0 and are filtered out.
 */
export declare function chunkTextSearch(client: SqlClient, workspaceId: string, versionId: number, query: string, opts?: ChunkSearchOpts): Promise<ChunkSearchResult[]>;
/**
 * Vector search at version V: chunks ranked by cosine similarity between
 * the query embedding and the per-content cache (`fs_chunk_embeddings`,
 * filled by `indexChunkEmbeddings()`). Nearest-neighbor: it always ranks
 * something, so irrelevant queries return low-rank hits, not nothing.
 * Chunks without a cached embedding are invisible to this signal.
 */
export declare function chunkSemanticSearch(client: SqlClient, workspaceId: string, versionId: number, embedding: number[], opts?: ChunkSearchOpts): Promise<ChunkSearchResult[]>;
/**
 * Hybrid search at version V: the BM25 and vector rankings, each taken to
 * the oversample depth, fused with reciprocal-rank fusion — see `RRF_K`
 * for why ranks rather than weighted scores. Chunks without a cached
 * embedding still surface through the lexical side.
 */
export declare function chunkHybridSearch(client: SqlClient, workspaceId: string, versionId: number, query: string, embedding: number[], opts?: ChunkSearchOpts): Promise<ChunkSearchResult[]>;
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