/**
 * history-extractor.ts
 *
 * 3-pass Memory Agent history extraction utilities.
 * Pass 0: truth channels → build ground-truth project state (no LLM)
 * Pass 1: activity channels (hub + deliverable + reference) → extract decisions/tasks with full context
 * Pass 2: spoke channels → connect to hub projects
 */
import type { NormalizedItem, ChannelConfig } from '../connectors/framework/types.js';
export interface HubContextEntry {
    project: string;
    workUnit?: string;
    assignedTo?: string;
    status?: string;
}
export interface ClassifiedItems {
    truth: NormalizedItem[];
    activity: NormalizedItem[];
    spoke: NormalizedItem[];
}
export interface ProjectTruth {
    projects: Record<string, {
        workUnits: Record<string, {
            status: string;
            assigned?: string;
            column?: string;
            metadata?: Record<string, string>;
        }>;
    }>;
}
export interface EntityObservationDraft {
    id: string;
    observation_type: 'generic' | 'author' | 'channel';
    entity_kind_hint: 'project' | 'person' | 'organization' | 'work_item' | null;
    surface_form: string;
    normalized_form: string;
    lang: string | null;
    script: string | null;
    context_summary: string | null;
    related_surface_forms: string[];
    timestamp_observed: number | null;
    scope_kind: 'project' | 'channel' | 'user' | 'global';
    scope_id: string | null;
    extractor_version: string;
    embedding_model_version: string | null;
    source_connector: string;
    source_raw_db_ref: string | null;
    source_raw_record_id: string;
}
export declare function buildEntityObservations(items: NormalizedItem[], options: {
    extractorVersion: string;
    embeddingModelVersion: string | null;
    rawDbRefForSource?: (source: string, item?: NormalizedItem) => string | null;
}): EntityObservationDraft[];
/**
 * Classify NormalizedItems into truth, activity, and spoke groups based on channel configs.
 * Items with role 'ignore' or no matching config are dropped.
 * Activity items (hub + deliverable + reference) are sorted by timestamp ascending.
 *
 * @param items - Normalized items to classify
 * @param channelConfigs - Keyed by source (e.g. 'chatwork'), then by channel name
 */
export declare function classifyItemsByRole(items: NormalizedItem[], channelConfigs: Record<string, Record<string, ChannelConfig>>, defaultRole?: ChannelConfig['role']): ClassifiedItems;
/**
 * Build ground-truth project state from truth-role items (Pass 0).
 * No LLM needed — directly parses structured data from kanban_card and spreadsheet_row items.
 *
 * @param truthItems - NormalizedItems with role=truth
 */
export declare function buildProjectTruth(truthItems: NormalizedItem[]): ProjectTruth;
/**
 * Group items by "${source}:${channel}" key.
 */
export declare function groupByChannel(items: NormalizedItem[]): Map<string, NormalizedItem[]>;
/**
 * Build an LLM prompt for activity channel extraction (Pass 1).
 * Includes truth context as a header so the agent can identify changes relative to ground truth.
 *
 * @param activity - Activity NormalizedItems (hub + deliverable + reference)
 * @param truth - Ground-truth project state from Pass 0
 */
export declare function buildActivityExtractionPrompt(activity: NormalizedItem[], truth: ProjectTruth): string;
/**
 * Build an LLM prompt for spoke channel extraction (Pass 2).
 * Includes hub context so the agent can connect spoke messages to known projects.
 * Optionally includes project truth for richer context.
 *
 * @param items - Spoke NormalizedItems
 * @param hubContext - Active project context from Pass 1
 * @param truth - Optional ground-truth project state for richer context
 */
export declare function buildSpokeExtractionPrompt(items: NormalizedItem[], hubContext: HubContextEntry[], truth?: ProjectTruth): string;
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