/**
 * PipelineOrchestrator — Sequential pipeline runner
 *
 * Sequences 8 agents through three phases (UNDERSTAND → BUILD → VERIFY),
 * manages artifact handoffs, enforces iteration budgets, handles the
 * conversational gate, and persists state to disk for resumability.
 */
import type { KnowledgeGraph } from '../knowledge-graph/index.js';
import type { PipelineConfig, PipelineState } from './types.js';
export declare class PipelineOrchestrator {
    private config;
    private knowledgeGraph;
    private store;
    private learningBridge;
    constructor(config: PipelineConfig, knowledgeGraph: KnowledgeGraph);
    /**
     * Load code guidelines and docs into the artifact store as context.
     */
    private loadCodeContext;
    /**
     * If an existing component matches componentName, load its source files
     * as input artifacts so agents can modify rather than rewrite.
     */
    private loadExistingComponent;
    /**
     * Run the full pipeline from a text brief.
     */
    run(brief: string, componentName: string): Promise<PipelineState>;
    /**
     * Resume a pipeline paused at a conversational gate.
     */
    resume(stateId: string, gateDecision?: {
        approved: boolean;
        modifications?: string;
    }): Promise<PipelineState>;
    /**
     * Persist the in-memory learning history to the canonical
     * .eddie-brain/learning.json so pipeline outcomes feed the correction
     * flywheel (#1021). The graph's learningHistory was hydrated from that file
     * at load, so writing it back is a superset — never a wipe.
     */
    private persistLearnings;
    /** Create the initial pipeline state */
    private createInitialState;
    /** Save pipeline state to disk */
    private saveState;
    /** Load pipeline state from disk */
    private loadState;
    /** Write final output files to the output directory */
    private writeOutputFiles;
}
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