import type { ProvidersConfig } from '../types/config.js';
import type { EmbeddingConfig, EmbeddingRequest, EmbeddingResponse, EmbeddingsProvider } from '../types/embeddings.js';
import { AuditLogger } from '../ops/audit-logger.js';
import { MetricsCollector } from '../ops/metrics.js';
import { RateLimiter } from '../ops/rate-limiter.js';
interface ManagerRuntime {
    metrics?: MetricsCollector;
    auditLogger?: AuditLogger;
    rateLimiter?: RateLimiter;
    /** Provider credentials used to auto-register adapters. */
    providers?: ProvidersConfig;
}
/**
 * Provider-neutral embeddings with routing, caching, batching, budget, retry, audit, and metrics.
 *
 * The operation family behind `ai.embed()`. It is usable standalone, and when it is reached through
 * `NexusAI` it shares that runtime's metrics collector, audit log, and rate limiter, so embedding
 * spend appears alongside completion spend instead of being invisible.
 */
export declare class EmbeddingManager {
    private readonly config;
    private readonly runtime;
    private readonly providers;
    private readonly tokenizer;
    private readonly metrics;
    private readonly auditLogger;
    private readonly rateLimiter;
    private readonly localCache?;
    private autoRegistered;
    constructor(config?: EmbeddingConfig, runtime?: ManagerRuntime);
    /** Registers a provider under a name. Returns the manager, for chaining. */
    registerEmbeddingProvider(name: string, provider: EmbeddingsProvider): this;
    /** Whether a provider is registered. */
    hasEmbeddingProvider(name: string): boolean;
    /** Every registered provider's name. */
    listEmbeddingProviders(): string[];
    /**
     * Embeds one text or a batch.
     *
     * The single-string form returns one vector at `vectors[0]`; a batch returns them in input order
     * regardless of how many provider calls the split required.
     */
    embed(request: EmbeddingRequest): Promise<EmbeddingResponse>;
    /** Embeds one text and returns the vector alone, for callers that never need the metadata. */
    embedOne(text: string, options?: Omit<EmbeddingRequest, 'input'>): Promise<number[]>;
    private resolveRoute;
    /**
     * Uses the adapter's own default model when the request named none.
     *
     * Without this a caller with a single non-OpenAI adapter would be routed to the `auto` alias
     * target, which that adapter does not serve.
     */
    private withProviderDefaultModel;
    private ensureAutoRegistered;
    private runBatches;
    private callWithRetry;
    private callProvider;
    private postProcess;
    private enforceCostBudget;
    private cacheContext;
    private readCache;
    private writeCache;
    private logAudit;
}
export {};