/**
 * @octomil/browser — Federated learning client
 *
 * Participates in federated training rounds: local weight extraction,
 * delta computation, and update submission. Actual gradient computation
 * is delegated to user-provided training hooks since ONNX Runtime Web
 * has limited training support.
 */
import type { TrainingConfig, FederatedRound, WeightMap } from "./types.js";
import type { TelemetryReporter } from "./telemetry.js";
/** Extract and compare model weights stored as named Float32Arrays. */
export declare class WeightExtractor {
    /**
     * Compute element-wise delta between two weight maps.
     * `delta = after - before`
     */
    static computeDelta(before: WeightMap, after: WeightMap): WeightMap;
    /** Apply a delta to weights: `result = weights + delta`. */
    static applyDelta(weights: WeightMap, delta: WeightMap): WeightMap;
    /** Compute L2 norm of a weight map (flattened). */
    static l2Norm(weights: WeightMap): number;
}
export declare class FederatedClient {
    private readonly serverUrl;
    private readonly apiKey?;
    private readonly deviceId;
    private readonly telemetry?;
    constructor(options: {
        serverUrl: string;
        apiKey?: string;
        deviceId: string;
        telemetry?: TelemetryReporter;
    });
    /** Fetch the current training round from the server. */
    getTrainingRound(federationId: string): Promise<FederatedRound>;
    /** Join a training round. */
    joinRound(federationId: string, roundId: string): Promise<void>;
    offers(): Promise<Record<string, unknown>>;
    join(roundId: string, request?: Record<string, unknown>): Promise<Record<string, unknown>>;
    plan(planId: string): Promise<Record<string, unknown>>;
    heartbeat(roundId: string, request?: Record<string, unknown>): Promise<Record<string, unknown>>;
    uploadInitiate(roundId: string, request: Record<string, unknown>): Promise<Record<string, unknown>>;
    uploadComplete(roundId: string, uploadId: string, request: Record<string, unknown>): Promise<Record<string, unknown>>;
    /**
     * Run local training using a user-provided step function.
     *
     * Browser ONNX Runtime Web does not support training natively, so the
     * caller provides `onTrainStep` which receives the current weights and
     * a batch of data, and returns updated weights.
     */
    train(initialWeights: WeightMap, config: TrainingConfig): Promise<{
        finalWeights: WeightMap;
        delta: WeightMap;
    }>;
    /** Submit a weight update to the aggregation server. */
    submitUpdate(federationId: string, roundId: string, delta: WeightMap, metrics?: Record<string, number>): Promise<void>;
    private request;
    private cloneWeights;
}
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