/**
 * Adaptive planning: one batched triage that decides which units earn a
 * per-unit todo pass, instead of paying for a todo request on every unit. The
 * provider call is injected so this orchestration stays deterministic and
 * unit-testable, and so a failed batch degrades to the original "plan it"
 * behavior rather than silently skipping planning.
 */
import type { DirectPlanClassificationItem } from "../prompts/direct-plan-classification.ts";
import { type ConversionUnit } from "./types.ts";
/**
 * Units per classification request. Large enough that a handful of calls covers
 * thousands of units, small enough that one request stays bounded and the model
 * keeps track of every index. Each unit contributes a length-capped excerpt.
 */
export declare const PLAN_CLASSIFICATION_BATCH_SIZE = 40;
/** Exact number of classification requests a batch of this size will issue. */
export declare function planClassificationRequestCount(eligibleUnitCount: number): number;
export interface AdaptivePlanningResult {
    /** Units the classifier (or a failed-batch fallback) says should be planned. */
    needsPlanning: Set<ConversionUnit>;
    /** Classification requests actually attempted; one per batch. */
    classificationRequests: number;
    /** Human-readable reasons a batch fell back to planning everything in it. */
    fallbacks: string[];
}
/**
 * Batch `units` and ask `classifyBatch` which of each batch's 1-based indices
 * need planning. Indices the classifier returns become planned units; a batch
 * whose classifier throws is planned in full so quality never silently drops.
 * `units` should already be the todo-eligible set — callers gate on kind first.
 */
export declare function classifyUnitsNeedingPlanning(units: readonly ConversionUnit[], classifyBatch: (items: readonly DirectPlanClassificationItem[]) => Promise<Set<number>>): Promise<AdaptivePlanningResult>;
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