feat(memory-v2): close Phase A with auto-review, product events, and H5 recall UI.

Add candidate auto-review pipeline, shadow audit tooling, admin metrics page, and user-visible memory recall hints in chat with phase-a readiness checks. Co-authored-by: Cursor <cursoragent@cursor.com>
2026-08-01 17:14:06 +08:00
parent 666db0b939
commit 6f3e53a56a
50 changed files with 3730 additions and 38 deletions
@@ -0,0 +1,76 @@
+#!/usr/bin/env node
+import { pathToFileURL } from 'node:url';
+import { ensurePgvectorMemorySchema } from '../memory-v2-pgvector-schema.mjs';
+import { runPgvectorMemorySmoke } from '../memory-v2-pgvector-smoke.mjs';
+import { loadMemindEnvFiles } from './memind-runtime-profile.mjs';
+
+function usage() {
+  return [
+    'Usage: node scripts/setup-memory-v2-pgvector-local.mjs [--dimensions 3] [--skip-smoke]',
+    '',
+    'Ensures local pgvector schema exists and runs a read/write smoke test.',
+  ].join('\n');
+}
+
+function parseArgs(argv) {
+  const args = { dimensions: 3, skipSmoke: false };
+  for (let i = 2; i < argv.length; i += 1) {
+    const arg = argv[i];
+    if (arg === '--dimensions' && argv[i + 1]) args.dimensions = Number(argv[++i]);
+    else if (arg === '--skip-smoke') args.skipSmoke = true;
+    else if (arg === '--help' || arg === '-h') {
+      console.log(usage());
+      process.exit(0);
+    } else {
+      console.error(`Unknown argument: ${arg}`);
+      console.error(usage());
+      process.exit(2);
+    }
+  }
+  return args;
+}
+
+async function createPgPool(connectionString) {
+  const imported = await import('pg');
+  const PgPool = imported?.Pool ?? imported?.default?.Pool;
+  if (typeof PgPool !== 'function') throw new Error('pg module does not export Pool');
+  return new PgPool({ connectionString, max: 3 });
+}
+
+async function main() {
+  const args = parseArgs(process.argv);
+  loadMemindEnvFiles(process.cwd());
+  const connectionString = String(process.env.MEMORY_PGVECTOR_DATABASE_URL ?? '').trim()
+    || 'postgresql://john@127.0.0.1:5432/memind_memory';
+  const tableName = String(process.env.MEMORY_PGVECTOR_TABLE ?? 'memory_embeddings').trim()
+    || 'memory_embeddings';
+  const pool = await createPgPool(connectionString);
+  try {
+    const schema = await ensurePgvectorMemorySchema(pool, {
+      tableName,
+      dimensions: args.dimensions,
+      createExtension: true,
+    });
+    console.log(`pgvector schema ready: table=${schema.tableName} dimensions=${schema.dimensions}`);
+    if (!args.skipSmoke) {
+      const smoke = await runPgvectorMemorySmoke({
+        pool,
+        tableName,
+        dimensions: args.dimensions,
+        cleanup: true,
+        embedQuery: async () => Array.from({ length: args.dimensions }, (_, index) => (index + 1) * 0.1),
+      });
+      console.log(`pgvector smoke: ${smoke.ok ? 'ok' : 'failed'} inserted=${smoke.inserted} queried=${smoke.queried}`);
+      if (!smoke.ok) process.exit(1);
+    }
+  } finally {
+    await pool.end();
+  }
+}
+
+if (process.argv[1] && import.meta.url === pathToFileURL(process.argv[1]).href) {
+  main().catch((err) => {
+    console.error(err instanceof Error ? err.message : err);
+    process.exit(1);
+  });
+}