import { CausalLink, TurboVector } from '../types.js';
export interface AcceleratorStatus {
    ssspNodes: number;
    ssspEdges: number;
    turboEntries: number;
    turboCompressionRatio: number;
}
export declare class HiveAccelerator {
    private sssp;
    private turbo;
    private initialized;
    constructor();
    init(): Promise<void>;
    /**
     * Rebuild the SSSP graph from causal links for O(m log^(2/3) n) traversal.
     * Each link contributes two directed edges (cause → effect).
     */
    buildCausalGraph(links: CausalLink[]): void;
    /** Run BMSSP from a source node — returns distances + predecessors. */
    traverseCausal(sourceId: string): any;
    /**
     * Store a compressed vector representation of a memory for faster SABB /
     * heatmap similarity scoring. Uses PolarQuant + QJL (3 bits/dim).
     */
    storeCompressed(id: string, vector: number[], metadata?: Record<string, unknown>): Promise<TurboVector | null>;
    /** Semantic similarity search — returns top-K matching memories. */
    similaritySearch(queryVector: number[], k?: number): Promise<Array<{
        id: string;
        score: number;
    }>>;
    /** Convert text to a simple 64-dim vector (character n-gram hash). Cheap, deterministic. */
    static textToVector(text: string, dim?: number): number[];
    /** Cosine similarity between two vectors. */
    static cosine(a: number[], b: number[]): number;
    status(): AcceleratorStatus;
}
export declare function getHiveAccelerator(): HiveAccelerator;
export declare function resetHiveAcceleratorForTests(): void;
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