/**
 * Base adapter class for embedding providers
 *
 * @packageDocumentation
 */
import type { EmbeddingProvider, EmbeddingConfig, EmbeddingAdapter, EmbeddingResult, BatchEmbeddingResult } from '../types/graphrag.js';
/**
 * Embedding-related errors
 */
export declare class EmbeddingError extends Error {
    readonly code: EmbeddingErrorCode;
    readonly provider: EmbeddingProvider;
    readonly cause?: Error | undefined;
    constructor(message: string, code: EmbeddingErrorCode, provider: EmbeddingProvider, cause?: Error | undefined);
}
export type EmbeddingErrorCode = 'NOT_CONFIGURED' | 'API_ERROR' | 'RATE_LIMIT' | 'INVALID_RESPONSE' | 'TIMEOUT' | 'NETWORK_ERROR' | 'MODEL_NOT_FOUND';
/**
 * Default configuration values
 */
export declare const DEFAULT_EMBEDDING_CONFIG: {
    timeout: number;
    retries: number;
    batchSize: number;
};
/**
 * Abstract base class for embedding adapters
 */
export declare abstract class BaseEmbeddingAdapter implements EmbeddingAdapter {
    protected config: EmbeddingConfig;
    constructor(config: EmbeddingConfig);
    abstract get provider(): EmbeddingProvider;
    abstract get model(): string;
    abstract get dimensions(): number;
    abstract embed(text: string): Promise<EmbeddingResult>;
    abstract embedBatch(texts: string[]): Promise<BatchEmbeddingResult>;
    abstract isConfigured(): boolean;
    getConfig(): Omit<EmbeddingConfig, 'apiKey'>;
    /**
     * Retry a function with exponential backoff
     */
    protected withRetry<T>(fn: () => Promise<T>, maxRetries?: number): Promise<T>;
    /**
     * Calculate cosine similarity between two vectors
     */
    protected cosineSimilarity(a: number[], b: number[]): number;
    /**
     * Normalize a vector to unit length
     */
    protected normalizeVector(vector: number[]): number[];
}
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