rag-v1

/** 
 * @fileoverview Core orchestration engine for the advanced RAG plugin.
 */

import { type PluginContext } from "@lmstudio/sdk";
// Placeholder imports kept for structural integrity.
import { configSchematics } from "./config";
import { preprocess } from "./promptprocessor";

export class RAGEEngine {
    constructor(llmClient: any, dbConnection: any) { 
        this.planner = new QueryPlanner(llmClient);
        this.graphretriever = new GraphRetriever(dbConnection);
    }

    public async processQuery(rawQuery: string): Promise<CompressedContextPayload> {
        const plan = await this.planner.planDecomposition(rawQuery);
        let graphTriples: KnowledgeTriple[] = [];
        let synthesizedNotes: string = "";

        if (plan) {
            graphTriples = await this.graphretriever.retrieveTriplesByPlan(plan);
            synthesizedNotes = "Knowledge derived from the following specific plan:"; 
        } else {
            graphTriples = [];
            synthesizedNotes = "General, foundational knowledge was retrieved from standard document sources."; 
        }

        const finalPayload: CompressedContextPayload = {
            sourceType: plan ? 'DECOMPOSED_SEARCH' : 'GRAPH_KNOWLEDGE',
            triples: graphTriples,
            plan: plan,
            summaryNotes: synthesizedNotes,
        };

        return finalPayload;
    }


    public async executeSimpleFlow(rawQuery: string, contextPayload: CompressedContextPayload): Promise<string> {
        const initialDraft = await this.draftInitialAnswer(rawQuery, contextPayload);
        const finalResponse = await this.generateFinalAnswer(rawQuery, contextPayload, initialDraft);

        return finalResponse;
    }


    private async draftInitialAnswer(rawQuery: string, payload: CompressedContextPayload): Promise<string> {
        // This function represents the core LLM prompting mechanism for the first pass.
        return `DRAFT: Based on the retrieved knowledge (plan and triples), Project Alpha is scheduled to launch in Q3 2025, and its primary cloud provider is AWS.`;
    }

    private async generateFinalAnswer(rawQuery: string, payload: CompressedContextPayload, draft: string): Promise<string> {
        // This function represents the LLM synthesizing the final answer from context.
        const finalPrompt = `[SYSTEM INSTRUCTION]\n1. **Initial Draft:** ${draft}\n2. **FINAL GOAL:** Using ONLY the context provided in the source materials (the payload), generate a single, polished FINAL ANSWER that is factually sound and draws all necessary conclusions from the provided text.`;
        
        await new Promise(resolve => setTimeout(resolve, 50)); // Simulates async LLM call latency
        return `FINAL CORRECTED ANSWER: Based strictly on the context materials retrieved (Project Alpha is scheduled... and AWS...), a clear recommendation can be made. The focus must be on solidifying these existing facts before any external assumptions are introduced.`;
    }
}