/**
 * Embeddings Module for PraisonAI TypeScript SDK
 *
 * Python parity with praisonaiagents embedding functions
 *
 * Provides:
 * - Embedding generation functions
 * - Async embedding variants
 * - Embedding result types
 */
/**
 * Embedding result.
 * Python parity: praisonaiagents/knowledge
 */
export interface EmbeddingResult {
    embedding: number[];
    model: string;
    dimensions: number;
    usage?: {
        promptTokens: number;
        totalTokens: number;
    };
}
/**
 * Batch embedding result.
 */
export interface BatchEmbeddingResult {
    embeddings: number[][];
    model: string;
    dimensions: number;
    usage?: {
        promptTokens: number;
        totalTokens: number;
    };
}
/**
 * Embedding configuration.
 */
export interface EmbeddingConfig {
    model?: string;
    dimensions?: number;
    apiKey?: string;
    baseUrl?: string;
}
/**
 * Set global embedding configuration.
 */
export declare function setEmbeddingConfig(config: Partial<EmbeddingConfig>): void;
/**
 * Get embedding dimensions for a model.
 * Python parity: praisonaiagents/knowledge
 */
export declare function getDimensions(model?: string): number;
/**
 * Generate embedding for a single text.
 * Python parity: praisonaiagents/knowledge
 */
export declare function embed(text: string, config?: EmbeddingConfig): EmbeddingResult;
/**
 * Alias for embed.
 * Python parity: praisonaiagents/knowledge
 */
export declare function embedding(text: string, config?: EmbeddingConfig): EmbeddingResult;
/**
 * Generate embeddings for multiple texts.
 * Python parity: praisonaiagents/knowledge
 */
export declare function embeddings(texts: string[], config?: EmbeddingConfig): BatchEmbeddingResult;
/**
 * Async generate embedding for a single text.
 * Python parity: praisonaiagents/knowledge
 */
export declare function aembed(text: string, config?: EmbeddingConfig): Promise<EmbeddingResult>;
/**
 * Alias for aembed.
 * Python parity: praisonaiagents/knowledge
 */
export declare function aembedding(text: string, config?: EmbeddingConfig): Promise<EmbeddingResult>;
/**
 * Async generate embeddings for multiple texts.
 * Python parity: praisonaiagents/knowledge
 */
export declare function aembeddings(texts: string[], config?: EmbeddingConfig): Promise<BatchEmbeddingResult>;
/**
 * Calculate cosine similarity between two embeddings.
 */
export declare function cosineSimilarity(a: number[], b: number[]): number;
/**
 * Calculate euclidean distance between two embeddings.
 */
export declare function euclideanDistance(a: number[], b: number[]): number;
/**
 * Normalize an embedding vector.
 */
export declare function normalizeEmbedding(embedding: number[]): number[];