/**
 * Batched analyze client.
 *
 * Companion to `analyzeResource.ts`. Posts a group of resources to the
 * backend's `/v1/analyze/batch` endpoint instead of issuing one HTTP call
 * per resource. The batched prompt amortizes the system prompt across N
 * resources, dramatically reducing per-insight cost on Mistral and even
 * more so on Anthropic models with prompt caching.
 *
 * Returns a map keyed by `stableResourceId` (the same id the caller sent),
 * so the orchestrator can map results back to original logical IDs.
 */
import type { AxiosResponse } from 'axios';
import type { CloudFormationResource, Issue } from '../../types/analysis.types';
import type { ResourceAnalysisContext } from '../analyzeResource/analyzeResource';
/** One resource within a batched analysis call. */
export interface BatchResourceInput {
    /**
     * Stable, deterministic ID the backend will use to key its response -
     * the orchestrator owns the mapping back to the original logical ID.
     */
    stableResourceId: string;
    resourceData: CloudFormationResource;
    resourceType: string;
    context?: ResourceAnalysisContext;
    existingFindings?: Issue[];
}
/** Per-resource analysis result returned for one batch entry. */
export interface BatchedAnalysisEntry {
    resourceId: string;
    resourceName?: string;
    issues: Issue[];
    /** True if the backend served this resource from cache (no Bedrock call). */
    cacheHit: boolean;
}
type AxiosClient = {
    post<TResponse>(url: string, data?: unknown, config?: unknown): Promise<AxiosResponse<TResponse>>;
    get<TResponse>(url: string, config?: unknown): Promise<AxiosResponse<TResponse>>;
};
export declare const createAnalyzeResourcesBatch: (axiosClient: AxiosClient, apiUrl: string) => (stackName: string, resources: BatchResourceInput[], authToken: string, fingerprint: string, aiModelId?: string) => Promise<Map<string, BatchedAnalysisEntry>>;
export type AnalyzeResourcesBatchFn = ReturnType<typeof createAnalyzeResourcesBatch>;
export {};