/**
 * Reflection Loop Pattern
 *
 * Enables AI agents to self-critique and iteratively improve their responses.
 * The AI generates a response, reflects on it, and regenerates based on feedback
 * until a target quality score is reached or max iterations is hit.
 *
 * @example
 * ```typescript
 * const result = await reflectionLoop({
 *   execute: async (ctx) => {
 *     const prompt = ctx.iteration === 1
 *       ? 'Write a blog post about TypeScript'
 *       : `Previous: ${ctx.previousResponse}
 *          Feedback: ${ctx.previousCritique?.feedback}
 *          Improve based on this feedback.`;
 *     return await generateText({ prompt });
 *   },
 *   reflect: async (text) => {
 *     const critique = await generateText({
 *       prompt: `Rate this (1-10) and suggest improvements: ${text}`
 *     });
 *     return {
 *       score: extractScore(critique),
 *       feedback: critique,
 *       shouldContinue: extractScore(critique) < 8
 *     };
 *   },
 *   maxIterations: 5,
 *   targetScore: 8
 * });
 * ```
 */
import type { ReflectionLoopConfig, ReflectionLoopResult, ReflectionIteration, ReflectionHistoryStorage } from "../types/reflection-loop";
/**
 * In-memory storage implementation for reflection history using GlobalStorage
 */
export declare class InMemoryReflectionStorage<TResponse> implements ReflectionHistoryStorage<TResponse> {
    private storage;
    private readonly namespace;
    constructor();
    save(sessionId: string, iteration: ReflectionIteration<TResponse>): Promise<void>;
    load(sessionId: string): Promise<ReflectionIteration<TResponse>[]>;
    delete(sessionId: string): Promise<void>;
    listSessions(): Promise<string[]>;
}
/**
 * Execute a reflection loop where the AI iteratively improves its response
 * through self-critique and regeneration.
 */
export declare function reflectionLoop<TResponse>(config: ReflectionLoopConfig<TResponse>): Promise<ReflectionLoopResult<TResponse>>;
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