import type { FacetResultData, QueryVectorIndexResponse, RerankerConfig, VectorSearchClient } from "@databricks/sdk-vectorsearch/v1";
import type { EmbeddingProvider, RetrieveOptions, RetrievedChunk, Retriever } from "@fabric-harness/sdk";
import type { DatabricksRawProtocolClient } from "./raw-protocol-client.js";
export type DatabricksVectorSearchClient = Pick<VectorSearchClient, "queryVectorIndex"> & Partial<Pick<VectorSearchClient, "queryVectorIndexNextPage">>;
export type DatabricksAiSearchInputMode = "text" | "vector" | "text-and-vector";
export type DatabricksAiSearchStrategy = "ann" | "hybrid" | "full-text";
export interface DatabricksAiSearchQueryOptions extends RetrieveOptions {
    /** Override the configured input mode for this query. */
    inputMode?: DatabricksAiSearchInputMode;
    /** Override the configured retrieval algorithm for this query. */
    strategy?: DatabricksAiSearchStrategy;
    /** Precomputed query vector. Required when no embeddings provider can supply a vector input. */
    queryVector?: number[];
    /** Minimum score accepted by Databricks AI Search. */
    scoreThreshold?: number;
    /** Text columns searched for the query text. */
    queryColumns?: string[];
    /** Sort clauses such as `rating DESC`. */
    sortColumns?: string[];
    /** Facet expressions returned with the result set. */
    facets?: string[];
    /** Native Databricks reranker configuration. */
    reranker?: RerankerConfig;
    /** Columns supplied to the native reranker. */
    columnsToRerank?: string[];
}
export interface DatabricksAiSearchQueryResult {
    chunks: RetrievedChunk[];
    nextPageToken?: string;
    facetResult?: FacetResultData;
    /** Complete generated-SDK response for callers that need native result metadata. */
    response: QueryVectorIndexResponse;
}
export interface DatabricksAiSearchRetriever extends Retriever {
    readonly kind: "databricks-ai-search";
    readonly index: string;
    readonly inputMode: DatabricksAiSearchInputMode;
    readonly strategy: DatabricksAiSearchStrategy;
    query(query: string, options?: DatabricksAiSearchQueryOptions): Promise<DatabricksAiSearchQueryResult>;
    nextPage(pageToken: string, options?: {
        signal?: AbortSignal;
    }): Promise<DatabricksAiSearchQueryResult>;
}
export interface DatabricksAiSearchOptions {
    client: DatabricksVectorSearchClient;
    /**
     * Private bundle transport used only when SDK 0.21 rejects a valid floating-point score while
     * decoding a live query response. Other SDK failures remain fail-closed.
     */
    rawProtocolClient?: DatabricksRawProtocolClient;
    /** Full index name: `catalog.schema.index`. */
    index: string;
    /** Column that holds the chunk text returned to the model. */
    textColumn: string;
    /** Columns to retrieve. Defaults to `[textColumn]` plus `idColumn` when set. */
    columns?: string[];
    /** Column to surface as `RetrievedChunk.id`. */
    idColumn?: string;
    /**
     * Query representation. Text indexes default to `text`; self-managed indexes use `vector`;
     * `text-and-vector` sends both inputs where the selected Databricks strategy supports them.
     */
    inputMode?: DatabricksAiSearchInputMode;
    /**
     * Databricks retrieval algorithm. Text input defaults to `hybrid`, while vector-only input
     * defaults to `ann`.
     */
    strategy?: DatabricksAiSearchStrategy;
    /** Required for vector input unless each query supplies `queryVector`. */
    embeddings?: EmbeddingProvider;
    scoreThreshold?: number;
    queryColumns?: string[];
    sortColumns?: string[];
    facets?: string[];
    reranker?: RerankerConfig;
    columnsToRerank?: string[];
    name?: string;
}
/** Databricks AI Search as a {@link Retriever}. Runs under the bundle's Unity Catalog principal. */
export declare function databricksAiSearch(options: DatabricksAiSearchOptions): DatabricksAiSearchRetriever;
//# sourceMappingURL=vector-search.d.ts.map