/**
 * Agentic QE v3 - Nomic Embedder
 * Local, zero-cost embeddings via Ollama with nomic-embed-text model
 *
 * Features:
 * - 768-dimensional embeddings optimized for code
 * - Batch processing with progress tracking
 * - Semantic context formatting for code chunks
 * - Content-hash based caching
 * - Graceful fallback when Ollama is unavailable
 * - Error handling and retries
 */
import { EmbeddingCache } from './embedding-cache';
import { CodeChunk, EmbeddingBatchResult, ProgressCallback, CacheStats, IEmbeddingProvider } from './types';
/**
 * Configuration for NomicEmbedder
 */
export interface NomicEmbedderConfig {
    /** Ollama base URL (default: http://localhost:11434) */
    ollamaBaseUrl?: string;
    /** Batch size for processing (default: 100) */
    batchSize?: number;
    /** Maximum cache size (default: 10000) */
    maxCacheSize?: number;
    /** Enable fallback to pseudo-embeddings when Ollama unavailable */
    enableFallback?: boolean;
    /** Pre-configured cache instance (for dependency injection) */
    cache?: EmbeddingCache;
}
/**
 * Nomic Embedder for generating code embeddings via Ollama
 */
export declare class NomicEmbedder implements IEmbeddingProvider {
    private client;
    private cache;
    private batchSize;
    private enableFallback;
    private ollamaAvailable;
    /**
     * Create a NomicEmbedder instance
     *
     * @example Basic usage:
     * ```typescript
     * const embedder = new NomicEmbedder();
     * const embedding = await embedder.embed("function add(a, b) { return a + b; }");
     * ```
     *
     * @example With configuration:
     * ```typescript
     * const embedder = new NomicEmbedder({
     *   ollamaBaseUrl: 'http://localhost:11434',
     *   enableFallback: true,
     * });
     * ```
     */
    constructor(config?: NomicEmbedderConfig);
    /**
     * Generate embedding for a single text string
     */
    embed(text: string): Promise<number[]>;
    /**
     * Format code chunk for semantic embedding
     * Format: "[language] [type] [name]: [content]"
     */
    formatForEmbedding(chunk: CodeChunk): string;
    /**
     * Generate embeddings for multiple text strings (IEmbeddingProvider interface)
     */
    embedBatch(texts: string[]): Promise<number[][]>;
    /**
     * Generate embeddings for multiple code chunks with batching and progress tracking
     */
    embedCodeChunks(chunks: CodeChunk[], progressCallback?: ProgressCallback): Promise<EmbeddingBatchResult>;
    /**
     * Process a single batch of chunks
     */
    private processBatch;
    /**
     * Check if Ollama is available (cached check)
     */
    private isOllamaAvailable;
    /**
     * Reset the Ollama availability cache
     */
    resetOllamaCheck(): void;
    /**
     * Generate a pseudo-embedding based on code features
     * Used as fallback when Ollama is not available
     */
    private generatePseudoEmbedding;
    /**
     * Clear the embedding cache
     */
    clearCache(): void;
    /**
     * Get cache statistics
     */
    getCacheStats(): CacheStats;
    /**
     * Verify Ollama connection and model availability
     */
    healthCheck(): Promise<boolean>;
    /**
     * Get Ollama server information
     */
    getServerInfo(): Promise<import("./types").OllamaHealthResponse | null>;
    /**
     * Get embedding dimensions
     */
    getDimensions(): number;
    /**
     * Get configuration info
     */
    getConfig(): {
        model: "nomic-embed-text";
        dimensions: 768;
        contextWindow: 8192;
        batchSize: number;
        maxRetries: 3;
        enableFallback: boolean;
    };
}
/**
 * Create a NomicEmbedder instance
 * Factory function for convenience
 */
export declare function createNomicEmbedder(config?: NomicEmbedderConfig): NomicEmbedder;
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