Merge Memory V2 runtime facade

memory-v2-pgvector-schema.mjs

@@ -0,0 +1,78 @@
+const DEFAULT_TABLE = 'memory_embeddings';
+const DEFAULT_DIMENSIONS = 1536;
+
+function isSafeIdentifier(value) {
+  return /^[a-zA-Z_][a-zA-Z0-9_]*$/.test(String(value ?? ''));
+}
+
+function quoteIdent(value) {
+  const normalized = String(value ?? '').trim();
+  if (!isSafeIdentifier(normalized)) {
+    throw new Error(`Invalid PostgreSQL identifier: ${normalized}`);
+  }
+  return `"${normalized}"`;
+}
+
+function resolveDimensions(value) {
+  const dimensions = Number(value ?? DEFAULT_DIMENSIONS);
+  if (!Number.isInteger(dimensions) || dimensions < 1 || dimensions > 16_384) {
+    throw new Error(`Invalid pgvector dimensions: ${value}`);
+  }
+  return dimensions;
+}
+
+export function buildPgvectorMemorySchemaSql({
+  tableName = DEFAULT_TABLE,
+  dimensions = DEFAULT_DIMENSIONS,
+  createExtension = false,
+  createVectorIndex = false,
+} = {}) {
+  const table = quoteIdent(tableName);
+  const dim = resolveDimensions(dimensions);
+  const statements = [];
+  if (createExtension) {
+    statements.push('CREATE EXTENSION IF NOT EXISTS vector');
+  }
+  statements.push(`
+CREATE TABLE IF NOT EXISTS ${table} (
+  id BIGSERIAL PRIMARY KEY,
+  user_id TEXT NOT NULL,
+  content TEXT NOT NULL,
+  embedding vector(${dim}) NOT NULL,
+  type TEXT NOT NULL DEFAULT 'fact',
+  source_memory_id TEXT,
+  source_session_id TEXT,
+  source_message_id TEXT,
+  metadata JSONB NOT NULL DEFAULT '{}'::jsonb,
+  created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
+  updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
+)`.trim());
+  statements.push(
+    `CREATE INDEX IF NOT EXISTS ${quoteIdent(`${tableName}_user_created_idx`)} ON ${table} (user_id, created_at DESC)`,
+  );
+  statements.push(
+    `CREATE UNIQUE INDEX IF NOT EXISTS ${quoteIdent(`${tableName}_source_memory_id_uidx`)} ON ${table} (source_memory_id) WHERE source_memory_id IS NOT NULL`,
+  );
+  if (createVectorIndex) {
+    statements.push(
+      `CREATE INDEX IF NOT EXISTS ${quoteIdent(`${tableName}_embedding_idx`)} ON ${table} USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100)`,
+    );
+  }
+  return statements;
+}
+
+export async function ensurePgvectorMemorySchema(pool, options = {}) {
+  if (!pool?.query) {
+    throw new Error('ensurePgvectorMemorySchema requires a PostgreSQL pool with query(sql)');
+  }
+  const statements = buildPgvectorMemorySchemaSql(options);
+  for (const statement of statements) {
+    await pool.query(statement);
+  }
+  return {
+    ok: true,
+    statements: statements.length,
+    tableName: options.tableName ?? DEFAULT_TABLE,
+    dimensions: resolveDimensions(options.dimensions),
+  };
+}