/**
 * Shared ONNX text embedders — SP-100 (MiniLM), SP-156 (Granite trial).
 *
 * Embeds prompt text for HyDRA requirement projection and semantic cluster
 * matching. One ONNX session per instance; share across matchers via a single
 * factory call and coordinated dispose().
 */
import type { Encoder } from '../types/schemas.js';
export declare const EMBEDDING_DIM = 384;
/** MiniLM ONNX model (384-dim, 512-token context). */
export declare const MINILM_ONNX_MODEL = "Xenova/all-MiniLM-L6-v2";
/**
 * Granite 97M ONNX artifact for @huggingface/transformers.
 * Source weights: ibm-granite/granite-embedding-97m-multilingual-r2 (384-dim).
 */
export declare const GRANITE_ONNX_MODEL = "onnx-community/granite-embedding-97m-multilingual-r2-ONNX";
export interface TextEmbedder {
    embed(text: string): Promise<Float32Array>;
    dispose(): Promise<void>;
}
/**
 * Creates a TextEmbedder backed by @huggingface/transformers ONNX runtime.
 * Model: Xenova/all-MiniLM-L6-v2 (384-dim).
 *
 * The package is loaded dynamically — not required at compile time.
 * Install: `npm i @huggingface/transformers`
 */
export declare function createOnnxTextEmbedder(artifactCachePath: string): Promise<TextEmbedder>;
/**
 * Granite 97M long-context embedder (384-dim ONNX drop-in for SP-115 head).
 * Model: ibm-granite/granite-embedding-97m-multilingual-r2 via ONNX runtime.
 */
export declare function createGraniteOnnxTextEmbedder(artifactCachePath: string): Promise<TextEmbedder>;
/** Select ONNX text embedder by operator encoder flag. */
export declare function createTextEmbedder(encoder: Encoder | undefined, artifactCachePath: string): Promise<TextEmbedder>;
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