// End-to-end: same DB, same queries — published @mastra/libsql 1.25.1 vs the patched build.
// Usage: PATCHED=/path/to/mastra/stores/libsql/dist/index.js N=5000 RUNS=3 node compare-patched.mjs
import { mkdtempSync } from 'node:fs';
import { tmpdir } from 'node:os';
import { join } from 'node:path';
import { createClient } from '@libsql/client';
import { LibSQLVector as Published } from '@mastra/libsql';

const { LibSQLVector: Patched } = await import(process.env.PATCHED);
const N = Number(process.env.N ?? 5000);
const RUNS = Number(process.env.RUNS ?? 3);
const DIM = 2560;
const TOPK = 10;

function mulberry32(seed) {
  return () => {
    seed |= 0;
    seed = (seed + 0x6d2b79f5) | 0;
    let t = Math.imul(seed ^ (seed >>> 15), 1 | seed);
    t = (t + Math.imul(t ^ (t >>> 7), 61 | t)) ^ t;
    return ((t ^ (t >>> 14)) >>> 0) / 4294967296;
  };
}
const rnd = mulberry32(7);
const randomVector = () => Array.from({ length: DIM }, () => rnd() * 2 - 1);

const dir = mkdtempSync(join(tmpdir(), 'mastra-libsql-compare-'));
const url = `file:${join(dir, 'compare.db')}`;
const indexName = 'chunks';

{
  const setup = new Published({ url, id: 'setup' });
  await setup.createIndex({ indexName, dimension: DIM });
  const raw = createClient({ url });
  await raw.execute(`DROP INDEX IF EXISTS ${indexName}_vector_idx`); // force the brute-force path
  raw.close();
  for (let off = 0; off < N; off += 250) {
    const n = Math.min(250, N - off);
    const vectors = Array.from({ length: n }, randomVector);
    await setup.upsert({
      indexName,
      vectors,
      metadata: vectors.map((_, j) => ({ i: off + j, bucket: (off + j) % 10 })),
      ids: vectors.map((_, j) => `v${off + j}`),
    });
  }
  await setup.close();
}

const published = new Published({ url, id: 'published' });
const patched = new Patched({ url, id: 'patched' });
const median = xs => [...xs].sort((a, b) => a - b)[Math.floor(xs.length / 2)];
async function time(fn) {
  await fn();
  const ts = [];
  let out;
  for (let r = 0; r < RUNS; r++) {
    const t0 = performance.now();
    out = await fn();
    ts.push(performance.now() - t0);
  }
  return { ms: median(ts), out };
}

console.log(`N=${N} dim=${DIM} topK=${TOPK} runs=${RUNS} (median), no DiskANN index`);
const cases = [
  ['no filter', {}],
  ['filter {bucket: 3}', { filter: { bucket: 3 } }],
  ['filter {bucket: {$in: [1,2]}} + minScore 0.02', { filter: { bucket: { $in: [1, 2] } }, minScore: 0.02 }],
  ['includeVector', { includeVector: true }],
];
for (const [label, params] of cases) {
  const queryVector = randomVector();
  const a = await time(() => published.query({ indexName, queryVector, topK: TOPK, ...params }));
  const b = await time(() => patched.query({ indexName, queryVector, topK: TOPK, ...params }));
  const identical = JSON.stringify(a.out) === JSON.stringify(b.out);
  console.log(
    `${label.padEnd(46)} 1.25.1 ${a.ms.toFixed(1).padStart(8)} ms | patched ${b.ms.toFixed(1).padStart(7)} ms | ` +
      `x${(a.ms / b.ms).toFixed(0)} | ${a.out.length} results, identical (ids, scores, metadata, vectors): ${identical}`,
  );
}
await published.close();
await patched.close();