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version](https://img.shields.io/npm/v/@agentskit/memory?color=blue)](https://www.npmjs.com/package/@agentskit/memory)\n[![npm downloads](https://img.shields.io/npm/dm/@agentskit/memory)](https://www.npmjs.com/package/@agentskit/memory)\n[![bundle size](https://img.shields.io/bundlejs/size/@agentskit/memory?label=bundle)](https://bundlejs.com/?q=@agentskit/memory)\n[![license](https://img.shields.io/badge/license-MIT-blue.svg)](../../LICENSE)\n[![stability](https://img.shields.io/badge/stability-beta-yellow)](../../docs/STABILITY.md)\n[![GitHub stars](https://img.shields.io/github/stars/AgentsKit-io/agentskit?style=social)](https://github.com/AgentsKit-io/agentskit)\n\n**Tags:** `ai` · `agents` · `llm` · `agentskit` · `ai-agents` · `memory` · `vector-db` · `embeddings` · `rag` · `sqlite` · `redis` · `vector-search`\n\n## Verified proof\n\n- Package metadata and tests live under `packages/memory/`.\n- Package guide: https://www.agentskit.io/docs/reference/packages/memory\n- Stability map: [docs/STABILITY.md](../../docs/STABILITY.md)\n\n## How this fits the ecosystem\n\n@agentskit/memory gives agents continuity: chat history, vector memory, graph memory, encrypted stores, and local or hosted backends.\n\n- **AgentsKit**: compose it with the other packages in this repo to build agents from small, swappable parts.\n- **Registry**: look for ready agents and templates that already use this layer at [registry.agentskit.io](https://registry.agentskit.io).\n- **Playbook**: learn the production patterns behind this layer at [playbook.agentskit.io](https://playbook.agentskit.io).\n- **AKOS**: run the same concepts with enterprise deployment, governance, and observability at [akos.agentskit.io](https://akos.agentskit.io).\n\nDocs: [package guide](https://www.agentskit.io/docs/reference/packages/memory) · [agent handoff](https://github.com/AgentsKit-io/agentskit/blob/main/llms.txt)\n\n## Why memory\n\n- **Conversations that survive restarts** — SQLite for local development, Redis for production; your agent remembers context across sessions with zero code changes\n- **RAG-ready vector search** — store and retrieve embeddings with `fileVectorMemory` (pure JS, no native deps) or Redis vector search for scale\n- **Plug any backend** — the `VectorStore` interface is 3 methods; bring LanceDB, Pinecone, or any custom store in minutes\n- **One interface, every deployment target** — swap from `inMemory` to `sqlite` to `redis` without touching agent code\n\n## Install\n\n<!-- readme-command:install -->\n```bash\nnpm install @agentskit/memory better-sqlite3\n# For production:  npm install redis\n# For vectors:     npm install vectra\n```\n\n## Quick example\n\n<!-- readme-example:quickstart -->\n```ts\nimport { createRuntime } from '@agentskit/runtime'\nimport { anthropic } from '@agentskit/adapters'\nimport { sqliteChatMemory } from '@agentskit/memory'\n\nconst runtime = createRuntime({\n  adapter: anthropic({ apiKey: process.env.ANTHROPIC_API_KEY, model: 'claude-sonnet-4-6' }),\n  memory: sqliteChatMemory({ path: './chat.db' }),\n})\n\n// Agent now remembers previous conversations across process restarts\nconst result = await runtime.run('What did we discuss yesterday?')\nconsole.log(result.content)\n```\n\n## With RAG\n\nUse a **vector** backend with [`@agentskit/rag`](https://www.npmjs.com/package/@agentskit/rag) `createRAG({ embed, store })` — `fileVectorMemory` and `redisVectorMemory` implement `VectorMemory` for chunk storage and search.\n\n## Features\n\n### Chat memory (4)\n\n- `fileChatMemory({ path })` — JSON on disk; zero infra.\n- `sqliteChatMemory({ path })` — WAL-mode SQLite; indexed by session.\n- `redisChatMemory({ client, keyPrefix })` — distributed, serverless-friendly.\n- `tursoChatMemory({ url, authToken? })` — hosted or local libSQL/Turso.\n\nAll on top of `createInMemoryMemory` / `createLocalStorageMemory` from\n`@agentskit/core`.\n\n### Browser Web Storage\n\nUse the browser-safe subpath when a host needs validated, bounded storage or\n`sessionStorage` instead of the legacy Core `localStorage` helper:\n\n```ts\nimport { createWebStorageMemory } from '@agentskit/memory/web-storage'\n\nconst memory = createWebStorageMemory({\n  key: 'app:chat',\n  getStorage: () => typeof sessionStorage === 'undefined' ? undefined : sessionStorage,\n  maxMessages: 20,\n  maxRecordBytes: 1_048_576,\n})\n```\n\nCanonical records are runtime validated. Oversized saves reject with\n`AK_MEMORY_SAVE_FAILED` before changing storage. `migration` may supply legacy\nkeys and a host-owned parser; a legacy key is removed only after canonical\npersistence succeeds.\n\n### Vector memory (11)\n\n- `fileVectorMemory` — pure-JS, file-persisted (good to ~10k vectors).\n- `redisVectorMemory` — Redis Stack / Redis 8+ HNSW.\n- `pgvector` — BYO SQL runner (`postgres.js`, `pg`, Drizzle, Prisma, Neon).\n- `pinecone` — managed; namespaces + metadata filters.\n- `qdrant` — self-hosted or cloud via HTTP.\n- `chroma` — Chroma v2 HTTP client with tenant, database, and token support.\n- `upstashVector` — serverless HTTP.\n- `supabaseVectorStore` — Supabase-hosted pgvector RPC.\n- `weaviateVectorStore` — Weaviate Cloud or self-hosted HTTP.\n- `milvusVectorStore` — Milvus/Zilliz REST API.\n- `mongoAtlasVectorStore` — MongoDB Atlas Vector Search with an injected collection.\n\nVector adapters follow ADR 0003: a result is included only when its score is\nstrictly greater than `threshold`. Remote HTTP adapters accept `timeoutMs` and\n`maxResponseBytes`; configure both for production workloads. File KV writes\nare atomic and serialized across instances in one process. They are not a\nmulti-process coordination primitive; use SQLite, Redis, or another external\nstore when several processes write the same file.\n\nSame 3-method `VectorStore` contract — swap without touching agent code.\n\n### Higher-order wrappers (6)\n\n- `createHierarchicalMemory` — MemGPT-style tiers: working / recall / archival. [Recipe](https://www.agentskit.io/docs/reference/recipes/hierarchical-memory).\n- `createVirtualizedMemory` — hot window + cold retriever for long sessions. [Recipe](https://www.agentskit.io/docs/reference/recipes/virtualized-memory).\n- `createAutoSummarizingMemory` *(via `@agentskit/core/auto-summarize`)* — fold oldest turns into a running summary. [Recipe](https://www.agentskit.io/docs/reference/recipes/auto-summarize).\n- `createEncryptedMemory` — AES-GCM-256 envelope over any `ChatMemory`; keys never leave the caller. [Recipe](https://www.agentskit.io/docs/reference/recipes/encrypted-memory).\n- `createInMemoryGraph` — knowledge graph (nodes + edges + BFS). [Recipe](https://www.agentskit.io/docs/reference/recipes/graph-memory).\n- `createInMemoryPersonalization` + `renderProfileContext` — per-user trait profile. [Recipe](https://www.agentskit.io/docs/reference/recipes/personalization).\n\nMemory contract v1 (ADR 0003) — substitutable across `runtime`,\n`useChat`, and every framework binding.\n\n## Ecosystem\n\n| Package | Role |\n|---------|------|\n| [@agentskit/core](https://www.npmjs.com/package/@agentskit/core) | `Memory`, `VectorMemory` types |\n| [@agentskit/rag](https://www.npmjs.com/package/@agentskit/rag) | Chunking + retrieval on top of vector memory |\n| [@agentskit/runtime](https://www.npmjs.com/package/@agentskit/runtime) | `memory` / `retriever` options |\n| [@agentskit/adapters](https://www.npmjs.com/package/@agentskit/adapters) | Embeddings for RAG |\n\n## Contributors\n\n<a href=\"https://github.com/AgentsKit-io/agentskit/graphs/contributors\">\n  <img src=\"https://contrib.rocks/image?repo=AgentsKit-io/agentskit\" alt=\"AgentsKit contributors\" />\n</a>\n\n## License\n\nMIT — see [LICENSE](../../LICENSE).\n\n## Docs\n\n[Full documentation](https://www.agentskit.io) · [GitHub](https://github.com/AgentsKit-io/agentskit)\n\n## Maturity and compatibility\n\n- Stability: **beta** — see [docs/STABILITY.md](../../docs/STABILITY.md)\n- **Node.js 20+** and **TypeScript** strict mode\n- Published as `@agentskit/memory`\n\n## Contributing\n\nSee [CONTRIBUTING.md](../../CONTRIBUTING.md) and the monorepo [LICENSE](../../LICENSE).\n","readmeFilename":"README.md"}