import { BaseOptimizer, type BaseOptimizerDeps } from "../baseOptimizer.js";
import { type ReflectionSections } from "../gepaReflect.js";
import type { AgencyRunner } from "../grading/agencyRunner.js";
import type { Input } from "../grading/types.js";
import type { BaseOptimizerConfig } from "../optimizer.js";
import { type OptimizeMutationOperation, type OptimizeMutationPreview } from "../sourceMutator.js";
import { type OptimizeTargetSet } from "../targets.js";
import type { MutationProposal, OptimizeResult } from "../types.js";
export type GepaConfig = BaseOptimizerConfig & {
    minibatch: number;
    paretoSet?: Input[];
    moduleSelection?: "round-robin" | "all";
};
export type GepaDeps = BaseOptimizerDeps & {
    propose?: (runAgency: AgencyRunner, sections: ReflectionSections) => Promise<MutationProposal>;
    preview?: (targetSet: OptimizeTargetSet, operations: OptimizeMutationOperation[]) => OptimizeMutationPreview;
};
/** GEPA: reflective evolution with a Pareto candidate pool and minibatched promotion. */
export declare class Gepa extends BaseOptimizer {
    private readonly gepaDeps;
    readonly name = "gepa";
    private readonly gepaConfig;
    constructor(config: GepaConfig, gepaDeps?: GepaDeps);
    protected optimizeTargets(source: OptimizeTargetSet, inputs: Input[]): Promise<OptimizeResult>;
    /** Run the optimization loop, threading the pool. */
    private evolve;
    /** One reflective iteration: propose → validate → minibatch filter → (maybe) full eval. */
    private attempt;
    /** Round-robin one target per iteration (SelectModule); `"all"` shows every target. */
    private selectTargets;
    /** The parent's weakest minibatch inputs (by reference), weakest first; falls back to all. */
    private focus;
    /** Grade a candidate `files` map (the overlay) on `inputs`. */
    private makeCandidate;
}