/**
 * session-compactor.ts — summarize a session's chunks into a compact restart document.
 *
 * Uses OpenAI chat completions with a map-reduce strategy for long sessions:
 *   1. Single-pass for sessions whose estimated token count fits within the limit.
 *   2. Multi-pass for longer sessions: map each window → reduce all partials → final format.
 *
 * Environment variables:
 *   OPENAI_API_KEY               Required. Passed to the OpenAI client.
 *   OPENAI_SUMMARY_MODEL         Override model (default: "gpt-5-nano").
 *   CSM_SUMMARY_MAX_OUTPUT_TOKENS Override max output tokens (default: 5000).
 */
import type { ChunkRow } from "./database";
export interface CompactOptions {
    /** Override the summarizer model. Default: OPENAI_SUMMARY_MODEL env var or "gpt-5-nano". */
    model?: string;
    /** Override the max output token budget. Default: CSM_SUMMARY_MAX_OUTPUT_TOKENS env var or 5000. */
    maxOutputTokens?: number;
}
export interface CompactResult {
    summary: string;
    model: string;
    /** Total number of LLM passes performed (map passes + reduce + final format). */
    passes: number;
    usage: {
        inputTokens: number;
        outputTokens: number;
        totalTokens: number;
    };
}
/**
 * Summarizes the given ordered chunks into a restart document ready to paste
 * into a new AI coding session.
 *
 * @throws Error if OPENAI_API_KEY is missing or any OpenAI call fails.
 */
export declare function compactSession(chunks: ChunkRow[], options?: CompactOptions): Promise<CompactResult>;
/**
 * Builds a human-readable transcript from ordered chunk rows.
 * Groups consecutive chunks with the same section label under a single header.
 */
export declare function buildTranscript(chunks: ChunkRow[]): string;
/**
 * Splits `text` into windows of at most `windowChars` characters.
 * Splits on newline boundaries when possible.
 */
export declare function splitIntoWindows(text: string, windowChars: number): string[];
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