@agentskit/memory

Profile: major-package

Persist conversations and add vector search to your agents — swap backends without changing agent code.

Tags: ai · agents · llm · agentskit · ai-agents · memory · vector-db · embeddings · rag · sqlite · redis · vector-search

Verified proof

• Package metadata and tests live under packages/memory/.
• Package guide: https://www.agentskit.io/docs/reference/packages/memory
• Stability map: docs/STABILITY.md

How this fits the ecosystem

@agentskit/memory gives agents continuity: chat history, vector memory, graph memory, encrypted stores, and local or hosted backends.

• AgentsKit: compose it with the other packages in this repo to build agents from small, swappable parts.
• Registry: look for ready agents and templates that already use this layer at registry.agentskit.io.
• Playbook: learn the production patterns behind this layer at playbook.agentskit.io.

Docs: package guide · agent handoff

Why memory

• Conversations that survive restarts — SQLite for local development, Redis for production; your agent remembers context across sessions with zero code changes
• RAG-ready vector search — store and retrieve embeddings with fileVectorMemory (pure JS, no native deps) or Redis vector search for scale
• Plug any backend — the VectorStore interface is 3 methods; bring LanceDB, Pinecone, or any custom store in minutes
• One interface, every deployment target — swap from inMemory to sqlite to redis without touching agent code

Install

npm install @agentskit/memory better-sqlite3
# For production:  npm install redis
# For vectors:     npm install vectra

Quick example

import { createRuntime } from '@agentskit/runtime'
import { anthropic } from '@agentskit/adapters'
import { sqliteChatMemory } from '@agentskit/memory'

const runtime = createRuntime({
  adapter: anthropic({ apiKey: process.env.ANTHROPIC_API_KEY, model: 'claude-sonnet-4-6' }),
  memory: sqliteChatMemory({ path: './chat.db' }),
})

// Agent now remembers previous conversations across process restarts
const result = await runtime.run('What did we discuss yesterday?')
console.log(result.content)

With RAG

Use a vector backend with @agentskit/rag createRAG({ embed, store }) — fileVectorMemory and redisVectorMemory implement VectorMemory for chunk storage and search.

Features

Chat memory (4)

• fileChatMemory({ path }) — JSON on disk; zero infra.
• sqliteChatMemory({ path }) — WAL-mode SQLite; indexed by session.
• redisChatMemory({ client, keyPrefix }) — distributed, serverless-friendly.
• tursoChatMemory({ url, authToken? }) — hosted or local libSQL/Turso.

All on top of createInMemoryMemory / createLocalStorageMemory from @agentskit/core.

Browser Web Storage

Use the browser-safe subpath when a host needs validated, bounded storage or sessionStorage instead of the legacy Core localStorage helper:

import { createWebStorageMemory } from '@agentskit/memory/web-storage'

const memory = createWebStorageMemory({
  key: 'app:chat',
  getStorage: () => typeof sessionStorage === 'undefined' ? undefined : sessionStorage,
  maxMessages: 20,
  maxRecordBytes: 1_048_576,
})

Canonical records are runtime validated. Oversized saves reject with AK_MEMORY_SAVE_FAILED before changing storage. migration may supply legacy keys and a host-owned parser; a legacy key is removed only after canonical persistence succeeds.

Vector memory (11)

• fileVectorMemory — pure-JS, file-persisted (good to ~10k vectors).
• redisVectorMemory — Redis Stack / Redis 8+ HNSW.
• pgvector — BYO SQL runner (postgres.js, pg, Drizzle, Prisma, Neon).
• pinecone — managed; namespaces + metadata filters.
• qdrant — self-hosted or cloud via HTTP.
• chroma — Chroma v2 HTTP client with tenant, database, and token support.
• upstashVector — serverless HTTP.
• supabaseVectorStore — Supabase-hosted pgvector RPC.
• weaviateVectorStore — Weaviate Cloud or self-hosted HTTP.
• milvusVectorStore — Milvus/Zilliz REST API.
• mongoAtlasVectorStore — MongoDB Atlas Vector Search with an injected collection.

Vector adapters follow ADR 0003: a result is included only when its score is strictly greater than threshold. Remote HTTP adapters accept timeoutMs and maxResponseBytes, defaulting to 15 seconds and 2 MiB; both require positive safe integers. Injected fetch and caller signal are also supported. Timeout and response-limit failures use AK_MEMORY_REMOTE_HTTP. File KV writes are atomic and serialized across instances in one process. They are not a multi-process coordination primitive; use SQLite, Redis, or another external store when several processes write the same file.

Same 3-method VectorStore contract — swap without touching agent code.

Higher-order wrappers (6)

• createHierarchicalMemory — MemGPT-style tiers: working / recall / archival. Recipe.
• createVirtualizedMemory — hot window + cold retriever for long sessions. Recipe.
• createAutoSummarizingMemory (via @agentskit/core/auto-summarize) — fold oldest turns into a running summary. Recipe.
• createEncryptedMemory — AES-GCM-256 envelope over any ChatMemory; keys never leave the caller. Recipe.
• createInMemoryGraph — knowledge graph (nodes + edges + BFS). Recipe.
• createInMemoryPersonalization + renderProfileContext — per-user trait profile. Recipe.

Memory contract v1 (ADR 0003) — substitutable across runtime, useChat, and every framework binding.

Ecosystem

Contributors

License

MIT — see LICENSE.

Docs

Full documentation · GitHub

Maturity and compatibility

• Stability: beta — see docs/STABILITY.md
• Node.js 20+ and TypeScript strict mode
• Published as @agentskit/memory

Contributing

See CONTRIBUTING.md and the monorepo LICENSE.

PostgreSQL chat memory (Node and Workers)

Install drizzle-orm and pg alongside this package. The optional @agentskit/memory/postgres subpath exports postgresChatMemory, postgresChatTable (Drizzle schema), and postgresChatMigrationSql. Neither peer is imported by the main entry.

import { Pool } from 'pg'
import { drizzle } from 'drizzle-orm/node-postgres'
import { sql } from 'drizzle-orm'
import { postgresChatMemory, postgresChatMigrationSql } from '@agentskit/memory/postgres'

const pool = new Pool() // host owns connection configuration and shutdown
const db = drizzle(pool)
// Run once in your migration tooling, not on every request:
await db.execute(sql.raw(postgresChatMigrationSql))
const memory = postgresChatMemory({ db, tenantId: 'tenant-a', sessionId: 'session-a' })
await memory.save([])
await pool.end()

In Workers, enable nodejs_compat; create and connect a pg.Client inside each request, pass drizzle(client), and close it with ctx.waitUntil(client.end()) after all memory operations (and any stream using them) have finished. The package never connects, migrates, or closes your client. A Node Pool can be shared across requests. No Neon, Hyperdrive, or Cloudflare dependency is needed; the host can supply their connection configuration when appropriate.

Every query uses both tenant and session, which form the primary key. Derive these identifiers from trusted authorization context: caller-supplied tenant names alone are not authorization. Saves atomically replace a versioned JSONB snapshot, preserving parts, tools, metadata, dates, and message order. Concurrent saves use last-writer-wins; this ChatMemory does not implement session CAS or turn leases. Schema migration is explicit; SQL/connection errors propagate and invalid records fail rather than silently discarding history.

No truncation is performed by default (CM1–CM6). Opt into maxMessages: N to keep roughly the newest N messages on each save, in their original order. Retention cuts only at a user turn boundary: the kept window always starts at a user message, so a user question is never separated from its assistant answer and a tool call is never separated from its results. When the N-newest cutoff falls inside the latest (possibly in-progress) turn, that whole turn is kept, so the result can exceed N. Leading system messages are always kept. A history with no user message is stored unchanged rather than emptied. This permanently removes older turns and counts messages, not tokens or bytes. For semantic summarization, prepare the history in the host instead. A positive safe integer is required; empty saves still persist [].

The supported Drizzle peer range is ^0.44.0 || ^0.45.3. Both lower bounds passed the real PostgreSQL contract suite and the package typecheck.

signal rejects already-aborted operations before any SQL is issued. Loads also check after SQL returns. Drizzle/pg does not cancel in-flight SQL here: a save/clear already submitted can commit after an abort and will report its actual SQL outcome. Configure query/statement timeouts on the host connection.

Optional defense-in-depth RLS (run as migration owner, access through a non-owner role without BYPASSRLS; set tenant inside a host-managed transaction):

ALTER TABLE agentskit_chat_memory ENABLE ROW LEVEL SECURITY;
ALTER TABLE agentskit_chat_memory FORCE ROW LEVEL SECURITY;
CREATE POLICY tenant_isolation ON agentskit_chat_memory
  USING (tenant_id = current_setting('app.tenant_id', true))
  WITH CHECK (tenant_id = current_setting('app.tenant_id', true));

Do not set a tenant on a shared pool connection outside a transaction. The host must enforce role permissions and set its trusted tenant with transaction-local set_config('app.tenant_id', tenant, true).

Real acceptance checks (local disposable PostgreSQL 16, trust auth on loopback; no production accounts):

docker run -d --name ak-memory-test -p 127.0.0.1:55439:5432 -e POSTGRES_HOST_AUTH_METHOD=trust postgres:16
AK_POSTGRES_TEST_PORT=55439 pnpm --filter @agentskit/memory test:postgres
AK_POSTGRES_TEST_PORT=55439 pnpm --filter @agentskit/memory test:workerd
docker rm -f ak-memory-test

CI runs test:postgres against a PostgreSQL 16 service with trust authentication and an explicit test port; no secrets are required. Locally it is skipped without its explicit test port. test:workerd runs wrangler dev --local, uses a Client per request and waitUntil shutdown, and exercises the same synthetic contract suite as the Node Pool test.