@juspay/neurolink/dist/evaluation/scorers/rule/contentSimilarityScorer.d.ts

The pipe layer of an AI nervous system: one interface connecting provider neurons to your application, across three inference types — generate, stream and decide. `decide` returns typed, calibrated judgements from a non-generative model (~400ms, ~$0.00002

/**
 * @file Content Similarity Scorer
 * Evaluates text similarity using various metrics (Jaccard, cosine, Levenshtein)
 */
import type { ContentSimilarityConfig, ScoreResult, ScorerInput } from "../../../types/index.js";
import { BaseScorer } from "../baseScorer.js";
/**
 * ContentSimilarityScorer evaluates how similar the response is to a reference text
 */
export declare class ContentSimilarityScorer extends BaseScorer {
    private _similarityConfig;
    constructor(config?: ContentSimilarityConfig);
    /**
     * Get similarity-specific configuration
     */
    get similarityConfig(): ContentSimilarityConfig;
    /**
     * Get reference text based on configuration
     */
    private _getReferenceText;
    /**
     * Calculate similarity between two texts
     */
    private _calculateSimilarity;
    /**
     * Normalize text for comparison
     */
    private _normalizeText;
    /**
     * Tokenize text based on configuration
     */
    private _tokenize;
    /**
     * Calculate Jaccard similarity coefficient
     * J(A,B) = |A ∩ B| / |A ∪ B|
     */
    private _jaccardSimilarity;
    /**
     * Calculate cosine similarity using term frequency vectors
     */
    private _cosineSimilarity;
    /**
     * Get term frequency map
     */
    private _getTermFrequency;
    /**
     * Calculate normalized Levenshtein similarity
     * Returns 1 - (edit_distance / max_length)
     */
    private _levenshteinSimilarity;
    /**
     * Calculate Levenshtein edit distance using space-optimized two-row DP
     */
    private _levenshteinDistance;
    /**
     * Calculate Dice coefficient (Sorensen-Dice)
     * DSC(A,B) = 2|A ∩ B| / (|A| + |B|)
     */
    private _diceSimilarity;
    /**
     * Calculate overlap coefficient
     * O(A,B) = |A ∩ B| / min(|A|, |B|)
     */
    private _overlapCoefficient;
    /**
     * Override score to add detailed similarity metrics
     */
    score(input: ScorerInput): Promise<ScoreResult>;
    /**
     * Combine multiple metric scores
     */
    private _combineMetricScores;
    /**
     * Generate reasoning from similarity details
     */
    private _generateSimilarityReasoning;
}
/**
 * Factory function for creating ContentSimilarityScorer instances
 */
export declare function createContentSimilarityScorer(config?: ContentSimilarityConfig): Promise<ContentSimilarityScorer>;