/**
 * Cosine similarity of two L2-normalized vectors = their dot product. Returns 0 on a length mismatch
 * or a missing vector (an un-embedded candidate contributes no semantic boost, never an error).
 * @param {Float32Array | undefined} a
 * @param {Float32Array | undefined} b
 * @returns {number}
 */
export function cosine(a: Float32Array | undefined, b: Float32Array | undefined): number;
/**
 * Lazy wrapper over a transformers.js feature-extraction pipeline. Any object with the same
 * `async embed(text): Float32Array` shape can stand in (see {@link LiteCtx} `embedder` option) — used
 * to inject a deterministic stub in tests so the tier's wiring is covered without the real model.
 */
export class Embedder {
    /** @param {{ model?: string }} [opts] */
    constructor({ model }?: {
        model?: string;
    });
    model: string;
    /** @type {any} */
    _pipe: any;
    /** @returns {Promise<any>} the cached pipeline, importing the optional dep on first call */
    _pipeline(): Promise<any>;
    /**
     * Embed one text into an L2-normalized vector. Head-truncates to {@link HEAD_CHARS}.
     * @param {string} text
     * @returns {Promise<Float32Array>}
     */
    embed(text: string): Promise<Float32Array>;
}