/**
 * Layer 1 (v1.7.5): pure HuggingFace API client. No DB. No project deps.
 *
 * Resolves embedding-model metadata from HF's REST API by reading the model's
 * `config.json`, `tokenizer_config.json`, `sentence_bert_config.json`,
 * `config_sentence_transformers.json`, and `modules.json` in parallel.
 * Optionally cross-checks the upstream `base_model` for prompts when the
 * direct repo doesn't ship a `prompts` field.
 *
 * Used at runtime when a BYOM model isn't in the bundled seed (Layer 3
 * calls this from `metadata-resolver.ts`). The release-time seed regen
 * (`scripts/build-seed.py`) reads MTEB's Python registry directly and
 * does not call this fetcher; the fetcher is BYOM-fallback-only now.
 *
 * Tier 3 README fingerprinting is intentionally NOT included in v1.7.5 —
 * its false-positive risk on long-form READMEs is too high to ship without
 * an eval harness. Deferred to v1.7.6 or beyond.
 */
/** Default per-request timeout. HF API is normally <100ms; 5s is generous. */
export declare const DEFAULT_HF_TIMEOUT_MS = 5000;
/** Default retry count for transient (5xx / network) failures. */
export declare const DEFAULT_HF_RETRIES = 2;
export type Dtype = 'fp32' | 'fp16' | 'q8' | 'q4' | 'q4f16' | 'int8' | 'uint8' | 'bnb4';
export type PrefixSource = 'metadata' | 'metadata-base' | 'readme' | 'none';
export interface HfMetadata {
    /** Canonical HF model id (org/name). */
    modelId: string;
    /** transformers `model_type` (e.g. 'bert', 'xlm-roberta', 't5'). */
    modelType: string;
    /** Hidden size from config.json — pre-Dense-projection. */
    hiddenSize: number;
    /** Number of transformer layers. */
    numLayers: number;
    /** Output embedding dim — overridden by Dense layer's `out_features` when present. */
    dim: number;
    /** True if `modules.json` declares a Dense layer (post-pooling projection). */
    hasDenseLayer: boolean;
    /** True if `modules.json` declares a Normalize layer (cosine-similarity-friendly). */
    hasNormalize: boolean;
    /** Effective max input tokens. Resolved with the priority: sentence_bert_config.max_seq_length →
     *  tokenizer_config.model_max_length → config.max_position_embeddings (xlm-roberta -2 offset). */
    maxTokens: number;
    /** From `config_sentence_transformers.json prompts.query`, or upstream `base_model`'s same JSON. */
    queryPrefix: string | null;
    /** From `config_sentence_transformers.json prompts.document` (or `passage`). */
    documentPrefix: string | null;
    /** Where the prefixes came from. 'none' → no prompts field anywhere. */
    prefixSource: PrefixSource;
    /** Upstream model id from README YAML frontmatter `base_model:`, or null. */
    baseModel: string | null;
    /** Total bytes of the requested ONNX dtype variant (q8 by default), or null. */
    sizeBytes: number | null;
    /** Diagnostic: which sources contributed to this metadata. */
    sources: {
        hadModulesJson: boolean;
        hadSentenceBertConfig: boolean;
        hadSentenceTransformersConfig: boolean;
        hadOnnxDir: boolean;
        maxTokensFrom: 'sentence_bert_config' | 'tokenizer_config' | 'config' | 'default';
    };
}
export interface HfMetadataOptions {
    /** Quantization variant whose ONNX file size we want to report. Default 'q8'. */
    dtype?: Dtype;
    /** Git revision (branch / commit / tag) to resolve files against. Default 'main'. */
    revision?: string;
    /** Per-request timeout in ms. Default DEFAULT_HF_TIMEOUT_MS. */
    timeoutMs?: number;
    /** Max retries for 5xx / network failures (4xx is permanent, no retry). Default DEFAULT_HF_RETRIES. */
    retries?: number;
    /** Injected fetch — defaults to globalThis.fetch. Lets tests substitute. */
    fetcher?: typeof fetch;
}
/**
 * Fetch metadata for a HuggingFace embedding model.
 *
 * Throws (only) when:
 *   - `config.json` is unreachable / 404 (model doesn't exist).
 *   - `config.json` has no scalar embedding dim (multimodal / vision /
 *     audio model with nested configs — Layer 1 cannot represent these).
 *
 * All other config files are best-effort — missing files fall through to
 * fallback values, never throw.
 */
export declare function getEmbeddingMetadata(modelId: string, options?: HfMetadataOptions): Promise<HfMetadata>;