/**
 * AssociationDiscovery — vector-based cross-reference discovery.
 *
 * Uses cosine similarity on BGE embeddings to find semantically related entries.
 * Replaces the previous keyword/lexical-overlap approach.
 *
 * Entries without embeddings are gracefully skipped.
 */
import type { KnowledgeEntry } from '../types/index.js';
import type { KnowledgeRepository } from '../repository/index.js';
import type { AssociationType } from './association-types.js';
import { AssociationStore } from './association-store.js';
export interface DiscoveryCandidate {
    sourceId: string;
    targetId: string;
    type: AssociationType;
    strength: number;
    reason: string;
}
export interface DiscoveryOptions {
    /** Cosine similarity threshold (default: 0.75) */
    similarityThreshold?: number;
    maxCandidates?: number;
    maxScanEntries?: number;
    autoCommit?: boolean;
    /** Pre-loaded embeddings map: entryId → Float32Array vector */
    embeddings?: Map<string, Float32Array>;
}
/**
 * Compute cosine similarity between two vectors.
 * Returns 0 if either vector is zero-length or has zero magnitude.
 */
export declare function cosineSimilarity(a: Float32Array, b: Float32Array): number;
export declare class AssociationDiscovery {
    private readonly repository;
    private readonly store;
    constructor(repository: KnowledgeRepository, store: AssociationStore);
    /**
     * Discover semantically related entries using cosine similarity on embeddings.
     *
     * Requires embeddings to be provided via options.embeddings (pre-loaded from DB).
     * Entries without embeddings are skipped.
     */
    discoverForEntry(entry: KnowledgeEntry, options?: DiscoveryOptions): Promise<DiscoveryCandidate[]>;
    /**
     * Batch discovery: find all semantic associations across all entries.
     * More efficient than calling discoverForEntry one by one.
     */
    discoverAll(options?: DiscoveryOptions): Promise<DiscoveryCandidate[]>;
    /**
     * Classify the association type based on semantic similarity and entry metadata.
     *
     * - similarity >= 0.9 + same domain + same type + newer → supersedes
     * - similarity >= 0.85 + same domain + same type → conflicts (potential duplicate)
     * - similarity >= 0.75 + same domain → supplements
     * - similarity >= 0.75 (cross-domain) → depends_on (semantic dependency)
     */
    private classifyAssociation;
}
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