/**
 * Utility functions for EmbeddingService
 * @module @skillsmith/core/embeddings/embedding-utils
 */
/**
 * Check if fallback mode should be used based on environment
 */
export declare function shouldUseFallback(explicit?: boolean): boolean;
/**
 * Generate a deterministic hash from text for mock embeddings.
 * Uses a simple but effective string hashing algorithm.
 */
export declare function hashText(text: string): number;
/**
 * Generate deterministic mock embedding based on text content.
 * Produces consistent vectors for the same input text.
 */
export declare function generateMockEmbedding(text: string, dimension: number): Float32Array;
/**
 * Lazily load the @huggingface/transformers module.
 * Uses dynamic import so the module is not loaded at CLI startup.
 */
export declare function loadTransformersModule(): Promise<typeof import('@huggingface/transformers') | null>;
/**
 * Check if the transformers module is available without loading it.
 * This is a synchronous check that returns the current known state.
 *
 * @returns true if module is loaded, false if loading failed, undefined if not yet attempted
 */
export declare function isTransformersAvailable(): boolean | undefined;
/**
 * Check if embeddings functionality is available.
 * Attempts to load the transformers module if not yet loaded.
 *
 * @returns true if embeddings can be used, false otherwise
 */
export declare function checkTransformersAvailability(): Promise<boolean>;
/**
 * Get the error that occurred when loading the transformers module, if any.
 */
export declare function getTransformersLoadError(): Error | null;
/**
 * Cosine similarity between two vectors of equal length.
 *
 * SMI-4577: extracted from `EmbeddingService.cosineSimilarity` so the brute-
 * force fallback in this module can call it directly without a class
 * instance, and to keep `index.ts` under the 500-line cap.
 *
 * @throws if vectors have different lengths
 * @returns 0 when either vector has zero magnitude
 */
export declare function cosineSimilarity(a: Float32Array, b: Float32Array): number;
/**
 * Brute-force top-K nearest-neighbour search over an embedding map. Used as
 * the deterministic fallback when HNSW is unavailable or explicitly disabled.
 *
 * SMI-4577: extracted from `EmbeddingService.findSimilarBruteForce` so the
 * pure search algorithm doesn't need a class instance. The wrapper method on
 * `EmbeddingService` still exists for backwards compatibility.
 */
export declare function findSimilarBruteForceFromMap(embeddings: Map<string, Float32Array>, queryEmbedding: Float32Array, topK: number): Array<{
    skillId: string;
    score: number;
}>;
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