/**
 * task-embedder.ts — Shared lazy task embedder + LRU cache (ADR-149 iter 9).
 *
 * The cost-optimal neural router (ADR-149) fires only when `route(task, embedding)`
 * is called with a real embedding. Two call sites in the dispatcher chain need
 * embeddings: `agent-tools.ts` (initial routing) and `agent-execute-core.ts`
 * (the fallback chain on 429/5xx). Before this module they each loaded their
 * own @xenova/transformers MiniLM pipeline and recomputed embeddings on every
 * call — including for repeated prompts.
 *
 * This module:
 *   1. Loads the pipeline once per process (`loadTaskEmbedder`).
 *   2. Caches embeddings per task text via an LRU of configurable size
 *      (default 500 entries ≈ 1.5 MB at 384-dim).
 *   3. Hashes by FNV-1a-32 + length to keep the key compact and collision-safe
 *      for typical prompt sizes.
 *   4. Returns `undefined` on any failure so callers gracefully fall back to
 *      the heuristic+bandit path.
 *
 * @module task-embedder
 */
/**
 * Compute (or fetch from cache) the 384-dim MiniLM embedding for `task`.
 * Returns `undefined` on any failure (missing @xenova/transformers, ONNX
 * runtime error, etc.) so callers can gracefully fall back to the
 * heuristic+bandit path. Best-effort and never throws.
 *
 * Cache hit-rate accumulates across the process lifetime and is observable
 * via `embedderStats()` for diagnostics.
 */
export declare function embedTaskWithCache(task: string): Promise<number[] | undefined>;
/**
 * Batch counterpart to `embedTaskWithCache`. For each task, returns the
 * cached embedding when present, else schedules a fresh inference. The
 * fresh-inference set is computed in a SINGLE ONNX pass via
 * @xenova/transformers' array-input mode, amortizing tensor setup +
 * model-load overhead across the batch. Order of the output array
 * matches the input order.
 *
 * Returns `undefined` for any task that failed to embed (missing dep,
 * runtime error). Cache state updates as if each task had been called
 * separately through embedTaskWithCache (hits/misses counters update
 * accordingly).
 */
export declare function embedTaskWithCacheBatch(tasks: string[]): Promise<Array<number[] | undefined>>;
/** Diagnostic surface — hit/miss counters + cache state. */
export declare function embedderStats(): {
    size: number;
    maxSize: number;
    hits: number;
    misses: number;
    hitRate: number;
};
/** Test seam — clear LRU + counters so tests get a fresh baseline. */
export declare function __resetTaskEmbedderForTests(): void;
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