/**
 * Pure embedding quality metric functions.
 * No I/O, no external dependencies.
 */
import type { EmbeddingMetrics } from "@vivantel/virage-core";
export declare function cosineSimilarity(a: number[], b: number[]): number;
/**
 * TWO-NN intrinsic dimension estimator.
 * For each point, computes r1/r2 (ratio of distances to 1st and 2nd
 * nearest neighbours). ID = -1 / mean(ln(r1/r2)).
 * Reference: Facco et al. (2017).
 */
export declare function computeIntrinsicDimension(embeddings: number[][]): number;
/**
 * Mean cosine similarity between randomly sampled pairs.
 * Close to 0 is ideal (well-spread embedding space).
 */
export declare function computeAvgCosineSimRandomPairs(embeddings: number[][], sampleSize?: number): number;
/**
 * Fraction of embeddings whose L2-norm z-score exceeds 2.5.
 */
export declare function detectOutliers(embeddings: number[][]): number;
export declare function computeEmbeddingMetrics(embeddings: number[][]): Promise<EmbeddingMetrics>;
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