const { Document } = require('../models');
const embeddingService = require('./embeddingService');
const logger = require('../utils/logger');

class GraphRagService {
  constructor() {
    this.similarityThreshold = parseFloat(process.env.GRAPH_RAG_SIM_THRESHOLD || '0.2');
    this.maxNeighbors = parseInt(process.env.GRAPH_RAG_MAX_NEIGHBORS || '10');
    this.maxResults = parseInt(process.env.GRAPH_RAG_MAX_RESULTS || '10');
  }

  scoreSimilarity(a, b) {
    return embeddingService.cosineSimilarity(a, b);
  }

  tagOverlap(tagsA = [], tagsB = []) {
    const setA = new Set((tagsA || []).map((t) => (t || '').toLowerCase()));
    const setB = new Set((tagsB || []).map((t) => (t || '').toLowerCase()));
    let overlap = 0;
    setA.forEach((t) => {
      if (setB.has(t)) overlap += 1;
    });
    return overlap;
  }

  buildGraph(nodes) {
    // nodes: [{ id, embedding, tags }]
    const edges = new Map(); // id -> [{ id, score, reason }]
    for (let i = 0; i < nodes.length; i++) {
      for (let j = i + 1; j < nodes.length; j++) {
        const ni = nodes[i];
        const nj = nodes[j];
        const sim = this.scoreSimilarity(ni.embedding, nj.embedding);
        const tagScore = this.tagOverlap(ni.tags, nj.tags);
        const hybrid = sim + Math.min(tagScore, 3) * 0.05; // light tag bonus
        if (hybrid >= this.similarityThreshold) {
          if (!edges.has(ni.id)) edges.set(ni.id, []);
          if (!edges.has(nj.id)) edges.set(nj.id, []);
          edges.get(ni.id).push({ id: nj.id, score: hybrid, reason: { sim, tagScore } });
          edges.get(nj.id).push({ id: ni.id, score: hybrid, reason: { sim, tagScore } });
        }
      }
    }
    // Trim neighbors
    edges.forEach((arr, k) => {
      arr.sort((a, b) => b.score - a.score);
      edges.set(k, arr.slice(0, this.maxNeighbors));
    });
    return edges;
  }

  async graphSearch({ query, category }) {
    const queryEmbedding = await embeddingService.embedText(query);

    // Load candidate docs
    const where = { is_indexed: true };
    if (category) where.category = category;
    const docs = await Document.findAll({
      where,
      attributes: ['id', 'original_filename', 'extracted_text', 'embeddings', 'tags', 'category', 'created_at']
    });

    const nodes = docs
      .filter((d) => Array.isArray(d.embeddings) && d.embeddings.length > 0)
      .map((d) => ({ id: d.id, embedding: d.embeddings, tags: d.tags || [], ref: d }));

    if (nodes.length === 0) {
      return { results: [] };
    }

    // Seed scores by query similarity
    const seedScores = nodes.map((n) => ({
      id: n.id,
      score: this.scoreSimilarity(queryEmbedding, n.embedding)
    }));
    
    // Log similarity scores for debugging
    logger.info('Similarity scores:', seedScores.map(s => ({ id: s.id, score: s.score.toFixed(4) })));
    
    seedScores.sort((a, b) => b.score - a.score);
    const seeds = seedScores.slice(0, Math.min(5, seedScores.length)).map((s) => s.id);

    const graph = this.buildGraph(nodes);

    // Expand neighborhoods from seeds
    const visited = new Set();
    const scored = new Map();

    const pushScore = (id, add, meta) => {
      const prev = scored.get(id) || { score: 0, hops: Infinity, reasons: [] };
      const combined = {
        score: Math.max(prev.score, add),
        hops: Math.min(prev.hops, meta.hops),
        reasons: prev.reasons.length < 3 ? [...prev.reasons, meta] : prev.reasons
      };
      scored.set(id, combined);
    };

    const queue = [];
    seeds.forEach((id) => queue.push({ id, hops: 0, via: null }));

    while (queue.length > 0 && scored.size < 200) {
      const { id, hops, via } = queue.shift();
      if (visited.has(id) || hops > 2) continue;
      visited.add(id);

      // Base score: similarity to query
      const node = nodes.find((n) => n.id === id);
      const base = this.scoreSimilarity(queryEmbedding, node.embedding);
      pushScore(id, base, { type: 'seed', hops });

      const neighbors = graph.get(id) || [];
      neighbors.forEach((nbr) => {
        const pathScore = (base + nbr.score) / 2;
        pushScore(nbr.id, pathScore, { type: 'edge', hops: hops + 1, via: id, edgeScore: nbr.score });
        if (!visited.has(nbr.id)) {
          queue.push({ id: nbr.id, hops: hops + 1, via: id });
        }
      });
    }

    // Format results
    const ranked = Array.from(scored.entries())
      .map(([id, info]) => {
        const ref = nodes.find((n) => n.id === id)?.ref;
        return {
          id,
          original_filename: ref?.original_filename,
          snippet: (ref?.extracted_text || '').slice(0, 400),
          category: ref?.category,
          created_at: ref?.created_at,
          score: Number(info.score.toFixed(4)),
          hops: info.hops,
          reasons: info.reasons
        };
      })
      .sort((a, b) => b.score - a.score)
      .slice(0, this.maxResults);

    return { results: ranked };
  }
}

module.exports = new GraphRagService();