import type { Embedder as EmbedderInterface, EmbedderMetadata } from './types.js';
/**
 * transformers.js-backed Embedder. Loads a sentence-embedding model from
 * Hugging Face (via EMBEDDING_MODEL or the constructor argument), probes its
 * output dim on init, and serialises embed() calls to work around the
 * single-threaded runtime.
 */
export declare class TransformersEmbedder implements EmbedderInterface {
    private extractor;
    private _dim;
    private readonly _model;
    private lastRun;
    private _metadata;
    constructor(model?: string);
    /**
     * v1.7.5+: receive resolved metadata from the metadata-resolver chain.
     * Callers must invoke this AFTER init() but BEFORE the first embed() call
     * for the prefix to be applied. If not called, embed() falls back to
     * empty prefixes (treats as symmetric — degraded but doesn't crash).
     */
    setMetadata(meta: EmbedderMetadata): void;
    /** Read back the metadata last set, or null. */
    getMetadata(): EmbedderMetadata | null;
    init(): Promise<void>;
    /**
     * Load the transformers.js pipeline, with a one-shot retry if the cached
     * ONNX file looks corrupt. A truncated download from a killed prior run
     * leaves a file that fails `Protobuf parsing` / `Load model … failed` when
     * onnxruntime tries to parse it. Nuking the model's cache subdirectory
     * and letting transformers.js re-download is the safe recovery — the
     * cache is content-addressed under the model id, so we only delete our
     * own model's subtree, not other users' models.
     */
    private loadPipelineWithCorruptCacheRecovery;
    private clearModelCache;
    /** Legacy numeric alias — new code should call dimensions(). */
    get dim(): number;
    /** Legacy string alias — new code should call modelIdentifier(). */
    get model(): string;
    dimensions(): number;
    modelIdentifier(): string;
    providerName(): string;
    embed(text: string, taskType?: 'document' | 'query'): Promise<Float32Array>;
    dispose(): Promise<void>;
    /**
     * Build a concatenated string from title + tags + first paragraph for the
     * note-level (coarse) embedding. Retained for the whole-note fallback; the
     * chunker produces its own per-chunk strings.
     *
     * @deprecated As of v1.4.0 the chunker emits per-chunk text directly. This
     * helper is only used for the note-level mean-pooled fallback vector.
     */
    static buildEmbeddingText(title: string, tags: string[], content: string): string;
}
/**
 * Back-compat alias — existing call sites import `Embedder` from this module.
 * New code should import `TransformersEmbedder` explicitly, or the
 * `Embedder` interface from `./types.js` for typing only.
 */
export { TransformersEmbedder as Embedder };