/**
 * Semantic Embeddings for Drift Detection
 *
 * Provides optional embedding-based similarity for improved paraphrase detection.
 * Uses Ollama for local embeddings (free, no API cost) or can be extended
 * for other providers.
 */
import type { ConfidenceFactor } from './types.js';
/**
 * Interface for embedding providers.
 */
export interface EmbeddingProvider {
    /** Provider name */
    name: string;
    /** Generate embedding vector for text */
    embed(text: string): Promise<number[]>;
    /** Calculate similarity between two embedding vectors */
    similarity(a: number[], b: number[]): number;
    /** Check if the provider is available */
    isAvailable(): Promise<boolean>;
}
/**
 * Ollama-based local embeddings using nomic-embed-text model.
 * Free and runs locally without API costs.
 */
export declare class OllamaEmbeddings implements EmbeddingProvider {
    name: string;
    private baseUrl;
    private model;
    private cache;
    constructor(options?: {
        baseUrl?: string;
        model?: string;
    });
    isAvailable(): Promise<boolean>;
    embed(text: string): Promise<number[]>;
    similarity(a: number[], b: number[]): number;
    clearCache(): void;
}
/**
 * Calculate cosine similarity between two vectors.
 * Returns a value between -1 and 1, where 1 is identical.
 */
export declare function cosineSimilarity(a: number[], b: number[]): number;
/**
 * Configuration for embedding-enhanced comparison.
 */
export interface EmbeddingConfig {
    /** Whether to use embeddings (default: false) */
    enabled: boolean;
    /** Embedding provider to use */
    provider: EmbeddingProvider;
    /** Weight for embedding similarity in overall confidence (0-1) */
    weight: number;
    /** Minimum similarity to consider a match (0-1) */
    matchThreshold: number;
    /** Timeout for embedding requests in ms */
    timeout: number;
}
/**
 * Default embedding configuration.
 */
export declare const DEFAULT_EMBEDDING_CONFIG: EmbeddingConfig;
/**
 * Result of embedding-based comparison.
 */
export interface EmbeddingComparisonResult {
    /** Whether embeddings were successfully used */
    used: boolean;
    /** Cosine similarity score (0-1) */
    similarity: number;
    /** Similarity as percentage (0-100) */
    similarityPercent: number;
    /** Whether similarity meets match threshold */
    meetsThreshold: boolean;
    /** Error message if embeddings failed */
    error?: string;
}
/**
 * Compare two texts using embeddings.
 */
export declare function compareWithEmbeddings(text1: string, text2: string, config?: Partial<EmbeddingConfig>): Promise<EmbeddingComparisonResult>;
/**
 * Create a confidence factor from embedding comparison.
 */
export declare function createEmbeddingFactor(result: EmbeddingComparisonResult): ConfidenceFactor | null;
/**
 * Enhanced semantic comparator that optionally uses embeddings.
 */
export declare class EmbeddingEnhancedComparator {
    private config;
    private providerChecked;
    private providerAvailable;
    constructor(config?: Partial<EmbeddingConfig>);
    /**
     * Check provider availability (cached).
     */
    checkAvailability(): Promise<boolean>;
    /**
     * Get embedding similarity as an additional confidence factor.
     * Falls back gracefully if embeddings are unavailable.
     */
    getEmbeddingFactor(text1: string, text2: string): Promise<ConfidenceFactor | null>;
    /**
     * Determine if texts match based on embedding similarity alone.
     */
    matchesByEmbedding(text1: string, text2: string): Promise<boolean>;
}
/**
 * Check if Ollama is available and has the embedding model.
 */
export declare function checkOllamaEmbeddings(): Promise<{
    available: boolean;
    hasModel: boolean;
    modelName: string;
    error?: string;
}>;
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