import type { EmbeddingCapabilityFailureV1, EmbeddingCapabilityStatus, EmbeddingCapabilityV1, EmbeddingProfileV1, EmbeddingPurpose } from './types/embedding-capability.js';
export declare const EMBEDDING_MODEL_ID = "Xenova/all-MiniLM-L6-v2";
export declare const EMBEDDING_MODEL_REVISION = "751bff37182d3f1213fa05d7196b954e230abad9";
export declare const EMBEDDING_MODEL_DIMENSION = 384;
export declare const EMBEDDING_TOKENIZER_CONFIG_HASH = "9261e7d79b44c8195c1cada2b453e55b00aeb81e907a6664974b4d2c62a0";
export interface EmbeddingWarmupOptions {
    timeoutMs?: number;
    errorLogPath?: string;
}
/** Raw response shape accepted by provider adapters before canonicalization. */
export type EmbeddingBatchResponseV1 = ReadonlyArray<Float32Array> | ReadonlyArray<{
    index: number;
    vector: Float32Array;
}>;
export interface EmbeddingProviderContract {
    getCapability(purpose: EmbeddingPurpose): EmbeddingCapabilityV1;
    getStatus(): 'idle' | 'warming' | 'ready' | 'failed';
    warmup(options?: EmbeddingWarmupOptions): Promise<boolean>;
    embed(text: string): Promise<Float32Array>;
    /** Returns one validated vector per input, in the same order as `texts`.
     * Provider adapters may accept `EmbeddingBatchResponseV1` internally, but
     * this public contract exposes only the canonical ordered representation. */
    embedBatch(texts: string[]): Promise<Float32Array[]>;
    getLastError(): string | null;
    getLastFailure(): Error | null;
}
export type EmbeddingProfileInput = Omit<EmbeddingProfileV1, 'profileHash'>;
export declare function createEmbeddingProfile(input: EmbeddingProfileInput): EmbeddingProfileV1;
export declare function createMiniLmEmbeddingProfile(purpose: EmbeddingPurpose, generation?: number): EmbeddingProfileV1;
export declare function createEmbeddingCapability(input: {
    profile: EmbeddingProfileV1;
    status: EmbeddingCapabilityStatus;
    failure?: EmbeddingCapabilityFailureV1;
    lastTransitionAt?: number;
}): EmbeddingCapabilityV1;
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