/**
 * Context Engine Service
 * 
 * Source: https://github.com/Eskapeum/Context-Engine
 * 
 * Provides intelligent context retrieval for enhanced AI responses:
 * - File indexing and caching
 * - Semantic search across codebase
 * - Q&A memory for persistent knowledge
 */

import { getLogger } from "@/lib/logger";

const log = getLogger("context-engine");

export interface ContextEngineConfig {
    projectRoot: string;
    enableIndexing?: boolean;
    enableVectors?: boolean;
}

export interface RetrievedContext {
    content: string;
    sources: ContextSource[];
    relevanceScore: number;
}

export interface ContextSource {
    file: string;
    line?: number;
    symbol?: string;
    type: "code" | "documentation" | "memory" | "qa";
}

export interface IndexStats {
    filesIndexed: number;
    symbolsFound: number;
    lastUpdated: number;
}

// Singleton instance
let instance: ContextEngineService | null = null;

export class ContextEngineService {
    private config: ContextEngineConfig;
    private initialized: boolean = false;
    private stats: IndexStats = { filesIndexed: 0, symbolsFound: 0, lastUpdated: 0 };
    private memoryCache: Map<string, { question: string; answer: string; timestamp: number }> = new Map();

    constructor(config: ContextEngineConfig) {
        this.config = config;
    }

    /**
     * Initialize the context engine
     */
    async initialize(): Promise<void> {
        if (this.initialized) return;

        log.info("Context Engine initializing...", { projectRoot: this.config.projectRoot });

        // In a full implementation, this would:
        // 1. Scan the project directory
        // 2. Build Tree-sitter AST for each file
        // 3. Create embeddings for semantic search

        this.initialized = true;
        log.info("Context Engine initialized");
    }

    /**
     * Retrieve relevant context for a query
     */
    async retrieve(query: string, options?: { maxTokens?: number }): Promise<RetrievedContext> {
        if (!this.initialized) {
            await this.initialize();
        }

        log.info("Retrieving context for query", { query: query.substring(0, 50) });

        // Search memory cache first
        const memorySuggestions = this.searchMemory(query);

        // In a full implementation, this would:
        // 1. Vectorize the query
        // 2. Search the index for relevant files/symbols
        // 3. Rank results by relevance
        // 4. Return top matches within token budget

        return {
            content: memorySuggestions.join("\n\n"),
            sources: [],
            relevanceScore: 0
        };
    }

    /**
     * Index or re-index the project
     */
    async index(options?: { force?: boolean }): Promise<IndexStats> {
        log.info("Indexing project...", { force: options?.force });

        // In a full implementation, this would:
        // 1. Walk the file tree
        // 2. Parse each file with Tree-sitter
        // 3. Extract symbols and documentation
        // 4. Generate embeddings

        this.stats = {
            filesIndexed: 0,
            symbolsFound: 0,
            lastUpdated: Date.now()
        };

        return this.stats;
    }

    /**
     * Get current index stats
     */
    getStats(): IndexStats {
        return this.stats;
    }

    /**
     * Add to Q&A memory
     */
    async remember(question: string, answer: string): Promise<void> {
        const id = `qa_${Date.now()}`;
        this.memoryCache.set(id, {
            question,
            answer,
            timestamp: Date.now()
        });
        log.info("Remembered Q&A", { question: question.substring(0, 50) });
    }

    /**
     * Search Q&A memory
     */
    searchMemory(query: string): string[] {
        const results: string[] = [];
        const queryLower = query.toLowerCase();

        for (const [, entry] of this.memoryCache) {
            if (entry.question.toLowerCase().includes(queryLower) ||
                entry.answer.toLowerCase().includes(queryLower)) {
                results.push(`Q: ${entry.question}\nA: ${entry.answer}`);
            }
        }

        return results.slice(0, 5);
    }

    /**
     * Search Q&A memory (async version)
     */
    async recall(query: string): Promise<{ question: string; answer: string }[]> {
        log.info("Recalling from memory", { query: query.substring(0, 50) });

        const results: { question: string; answer: string }[] = [];
        const queryLower = query.toLowerCase();

        for (const [, entry] of this.memoryCache) {
            if (entry.question.toLowerCase().includes(queryLower) ||
                entry.answer.toLowerCase().includes(queryLower)) {
                results.push({ question: entry.question, answer: entry.answer });
            }
        }

        return results.slice(0, 10);
    }
}

/**
 * Get or create context engine instance
 */
export function getContextEngine(config?: ContextEngineConfig): ContextEngineService {
    if (!instance && config) {
        instance = new ContextEngineService(config);
    }
    if (!instance) {
        throw new Error("Context engine not initialized. Provide config on first call.");
    }
    return instance;
}

/**
 * Initialize context engine for a workspace
 */
export async function initializeContextEngine(projectRoot: string): Promise<ContextEngineService> {
    const service = getContextEngine({ projectRoot });
    await service.initialize();
    return service;
}

export default {
    ContextEngineService,
    getContextEngine,
    initializeContextEngine,
};
