/**
 * ollama_embed_search — FLAGSHIP concept-search mode.
 *
 * Claude passes a query + candidates[{id, text}]; the server embeds all of
 * them in one batch, computes cosine similarity, and returns a ranked list
 * of {id, score, preview?}. No raw vectors cross the MCP boundary — that's
 * the whole point. The sibling ollama_embed tool still returns raw vectors
 * for callers building external indexes.
 *
 * Tier: Embed.
 */
import { z } from "zod";
import type { Envelope } from "../envelope.js";
import type { RunContext } from "../runContext.js";
export declare const embedSearchSchema: z.ZodObject<{
    query: z.ZodString;
    candidates: z.ZodArray<z.ZodObject<{
        id: z.ZodString;
        text: z.ZodString;
    }, z.core.$strip>>;
    top_k: z.ZodOptional<z.ZodNumber>;
    preview_chars: z.ZodOptional<z.ZodNumber>;
}, z.core.$strip>;
export type EmbedSearchInput = z.infer<typeof embedSearchSchema>;
export interface EmbedSearchHit {
    id: string;
    score: number;
    preview?: string;
}
export interface EmbedSearchResult {
    ranked: EmbedSearchHit[];
    model_version: string;
    candidates_embedded: number;
}
export declare function handleEmbedSearch(input: EmbedSearchInput, ctx: RunContext): Promise<Envelope<EmbedSearchResult>>;
//# sourceMappingURL=embedSearch.d.ts.map