/**
 * Embedding service using Hugging Face transformers
 *
 * Generates embeddings for code chunks using local transformer models.
 * The model is cached in memory for the process lifetime.
 *
 * Requirements: 2.4, 4.1, 4.2, 4.3, 4.5, 12.1
 */
import type { Config } from '../../shared/types/index.js';
import type { Logger } from '../../shared/logging/logger.js';
/**
 * Embedding service interface
 */
export interface EmbeddingService {
    /**
     * Initialize the embedding model
     * Must be called before generating embeddings
     */
    initialize(): Promise<void>;
    /**
     * Generate embedding for a single text
     * @param text - Text to embed
     * @returns Embedding vector
     * @throws Error if model is not initialized or embedding generation fails
     */
    generateEmbedding(text: string): Promise<number[]>;
    /**
     * Generate embeddings for multiple texts in batch
     * More efficient than calling generateEmbedding multiple times
     * @param texts - Array of texts to embed
     * @returns Array of embedding vectors
     * @throws Error if model is not initialized or embedding generation fails
     */
    batchGenerateEmbeddings(texts: string[]): Promise<number[][]>;
    /**
     * Get the embedding model name
     */
    getModelName(): string;
    /**
     * Get the embedding dimensionality
     */
    getEmbeddingDimension(): number;
    /**
     * Check if the model is initialized
     */
    isInitialized(): boolean;
}
/**
 * Implementation of embedding service using Hugging Face transformers
 */
export declare class HuggingFaceEmbeddingService implements EmbeddingService {
    private model;
    private readonly modelName;
    private readonly cachePath;
    private readonly logger;
    private embeddingDimension;
    constructor(config: Config, logger: Logger);
    /**
     * Initialize the embedding model
     * Downloads and caches the model if not already cached
     * Model is cached in memory for the process lifetime
     */
    initialize(): Promise<void>;
    /**
     * Generate embedding for a single text
     */
    generateEmbedding(text: string): Promise<number[]>;
    /**
     * Generate embeddings for multiple texts in batch
     * More efficient than calling generateEmbedding multiple times
     */
    batchGenerateEmbeddings(texts: string[]): Promise<number[][]>;
    /**
     * Get the embedding model name
     */
    getModelName(): string;
    /**
     * Get the embedding dimensionality
     */
    getEmbeddingDimension(): number;
    /**
     * Check if the model is initialized
     */
    isInitialized(): boolean;
}
/**
 * Create an embedding service instance
 */
export declare function createEmbeddingService(config: Config, logger: Logger): EmbeddingService;
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