import Exa from "exa-js";

const exa = new Exa(process.env.EXA_API_KEY);

// Tier 1: Metadata only (cheapest, fastest)
async function searchMetadataOnly(query: string) {
  return exa.search(query, {
    type: "auto",
    numResults: 10,
    // No content options — returns URLs, titles, scores only
  });
}

// Tier 2: Highlights only (balanced cost/value)
async function searchWithHighlights(query: string) {
  return exa.searchAndContents(query, {
    numResults: 10,
    highlights: {
      maxCharacters: 500,
      query: query,  // focus highlights on the original query
    },
  });
}

// Tier 3: Full text with character limit
async function searchWithText(query: string, maxChars = 2000) {
  return exa.searchAndContents(query, {
    numResults: 5,
    text: { maxCharacters: maxChars },
    highlights: { maxCharacters: 300 },
  });
}

// Tier 4: Structured summary (LLM-generated per result)
async function searchWithSummary(query: string) {
  return exa.searchAndContents(query, {
    numResults: 5,
    summary: { query: query },
    // summary returns a concise LLM-generated summary per result
  });
}

import { LRUCache } from "lru-cache";
import { createHash } from "crypto";

const searchCache = new LRUCache<string, any>({
  max: 500,
  ttl: 1000 * 60 * 60, // 1 hour default
});

function cacheKey(query: string, options: any): string {
  return createHash("sha256")
    .update(JSON.stringify({ query, ...options }))
    .digest("hex");
}

async function cachedSearch(query: string, options: any = {}, ttlMs?: number) {
  const key = cacheKey(query, options);
  const cached = searchCache.get(key);
  if (cached) return cached;

  const results = await exa.searchAndContents(query, options);
  searchCache.set(key, results, { ttl: ttlMs });
  return results;
}

interface ProcessedResult {
  url: string;
  title: string;
  score: number;
  snippet: string;
  tokenEstimate: number;
}

function processForRAG(results: any[], maxSnippetLength = 500): ProcessedResult[] {
  return results.map(r => {
    const snippet = (r.text || r.highlights?.join(" ") || r.summary || "")
      .slice(0, maxSnippetLength);
    return {
      url: r.url,
      title: r.title || "Untitled",
      score: r.score,
      snippet,
      tokenEstimate: Math.ceil(snippet.length / 4),
    };
  });
}

function fitToTokenBudget(results: ProcessedResult[], maxTokens: number) {
  const sorted = [...results].sort((a, b) => b.score - a.score);
  const selected: ProcessedResult[] = [];
  let tokenCount = 0;

  for (const result of sorted) {
    if (tokenCount + result.tokenEstimate > maxTokens) break;
    selected.push(result);
    tokenCount += result.tokenEstimate;
  }

  return { selected, tokenCount, dropped: sorted.length - selected.length };
}

// Usage: fit search results into a 4K token context window
const results = await exa.searchAndContents("query", {
  numResults: 15,
  text: { maxCharacters: 1500 },
});
const processed = processForRAG(results.results);
const { selected, tokenCount } = fitToTokenBudget(processed, 4000);

function deduplicateResults(results: any[]): any[] {
  const seen = new Map<string, any>();

  for (const result of results) {
    const domain = new URL(result.url).hostname;
    const key = `${domain}:${result.title}`;
    if (!seen.has(key) || result.score > seen.get(key).score) {
      seen.set(key, result);
    }
  }

  return Array.from(seen.values());
}

// Use summary.schema for structured data extraction
const results = await exa.searchAndContents(
  "YC-backed AI startups Series A 2025",
  {
    numResults: 10,
    category: "company",
    summary: {
      query: "company name, funding amount, what they do",
      // schema can define JSON structure for the summary output
    },
  }
);

// Each result.summary contains a structured summary
for (const r of results.results) {
  console.log(`${r.title}: ${r.summary}`);
}

async function ragSearch(query: string, tokenBudget = 4000) {
  const results = await cachedSearch(query, {
    numResults: 15,
    type: "neural",
    text: { maxCharacters: 1500 },
    highlights: { maxCharacters: 300, query },
  });

  const deduped = deduplicateResults(results.results);
  const processed = processForRAG(deduped);
  const { selected, tokenCount } = fitToTokenBudget(processed, tokenBudget);

  return {
    context: selected.map((r, i) =>
      `[${i + 1}] ${r.title} (${r.url})\n${r.snippet}`
    ).join("\n\n---\n\n"),
    sources: selected.map(r => ({ title: r.title, url: r.url })),
    tokenCount,
  };
}