/**
 * Signal intake pack generator.
 *
 * Produces the offline half of the fast intake path: a prose brief written for
 * the intake task and a ready round-1 question. Both are stored per user and
 * refreshed in the background, so `/i/new` can render round 1 with no model call.
 */
import type { BaseLanguageModelInput } from "@langchain/core/language_models/base";
import type { Runnable } from "@langchain/core/runnables";
/** One selectable option on the round-1 question. */
export interface IntakePackQuestionOption {
    label: string;
    description: string;
}
/** Round-1 question, shaped exactly like the frontend `QuestionPayload`. */
export interface IntakePackQuestion {
    title: string;
    prompt: string;
    options: IntakePackQuestionOption[];
    multiSelect: boolean;
}
/** Everything the generator needs about a user. */
export interface IntakePackInput {
    premises: Array<{
        text: string;
    }>;
    networkTitles: string[];
    globalContext: string | null;
}
/** Stored artifact: the brief plus the ready round-1 question. */
export interface IntakePack {
    brief: string;
    question: IntakePackQuestion;
}
/** Generates and normalizes the per-user intake pack. */
export declare class SignalIntakePackGenerator {
    private readonly model;
    /**
     * @param model - Optional injected structured model. Tests pass a stub.
     */
    constructor(model?: Runnable<BaseLanguageModelInput, IntakePack>);
    /**
     * Generate the intake pack for one user.
     *
     * @param input - Active premises, membership titles, and the global context paragraph
     * @returns Normalized brief and round-1 question
     */
    generate(input: IntakePackInput): Promise<IntakePack>;
}
/**
 * Clamp a generated pack into the shape the frontend can render.
 *
 * @param pack - Raw model output
 * @returns Normalized pack
 * @throws When the question has fewer than 2 usable options
 */
export declare function normalizeIntakePack(pack: IntakePack): IntakePack;