# Wax — Single-File Memory Layer for AI Agents

> Wax stores documents, embeddings, and knowledge in one portable `.wax` file, giving AI agents a local memory layer without extra servers.

## Install

Copy the content below into your project:

## Quick Use

```bash
git clone https://github.com/christopherkarani/Wax
cd Wax
swift test
```

## Intro

Wax stores documents, embeddings, and knowledge in one portable `.wax` file, giving AI agents a local memory layer without extra servers.

**Best for:** Apple-platform teams that want local RAG-style memory and portability without running a separate database fleet

**Works with:** Swift projects, Apple Silicon, local AI workflows, document and embedding persistence, file-based memory transport

**Setup time:** 10-15 minutes

### Key facts (verified)

- GitHub: 731 stars · 42 forks · pushed 2026-05-13.
- License: Apache-2.0; owner avatar verified from GitHub API for christopherkarani.
- Entry point checked from README: `swift package resolve`.

## Main

Wax matters because it shrinks the operational surface area of memory. Instead of keeping separate stores for documents, vectors, and metadata, you move one file.

That makes it attractive for local-first agent workflows, demo environments, and Apple-centric products where portability and low ceremony matter more than cluster scale.

The README framing is especially useful for engineering decisions: choose Wax when your bottleneck is setup and portability, not when you need a large distributed serving tier.

### Source-backed notes

- README defines Wax as a Swift-native persistence engine for AI agents.
- The core packaging idea is one portable `.wax` file containing documents, metadata, and indexes.
- README positions it as local-first memory tuned for Apple Silicon rather than a server-based vector stack.

### FAQ

**Q: Is Wax a hosted vector database?**
A: No. It is designed as a portable local memory engine centered on a single file.

**Q: Why is the file model important?**
A: Backup, copy, and transport become simpler because documents and indexes travel together.

**Q: Who should evaluate it first?**
A: Swift and Apple Silicon teams building local-first agent or retrieval features.

## Source & Thanks

> Source: https://github.com/christopherkarani/Wax
> License: Apache-2.0
> GitHub stars: 731 · forks: 42

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## Quick Use

```bash
git clone https://github.com/christopherkarani/Wax
cd Wax
swift test
```

## Intro

Wax 把文档、向量与结构化知识收进一个可移植的 `.wax` 文件，为 AI agent 提供 Swift 原生本地记忆层，无需额外服务器或向量数据库。

**Best for:** 想在 Apple 平台上做本地 RAG/记忆层、又不想维护额外数据库集群的团队

**Works with:** Swift 项目、Apple Silicon、本地 AI 工作流、文档与向量持久化、文件级记忆迁移

**Setup time:** 10-15 minutes

### Key facts (verified)

- GitHub：731 stars · 42 forks；最近更新 2026-05-13。
- 许可证：Apache-2.0；作者头像与仓库链接均已通过 GitHub API 复核。
- README 中核对过的入口命令：`swift package resolve`。

## Main

Wax 的价值在于把记忆层的运维面做小：文档、向量、元数据不再拆成几套系统，而是跟着一个文件走。

这对本地优先 agent 工作流、演示环境和 Apple 平台产品尤其友好，因为这里更看重可移植性与低接入成本，而不是分布式集群规模。

README 的定位也很清晰：如果你现在的瓶颈是搭建复杂度与迁移成本，Wax 值得尝试；如果你需要的是超大规模服务层，那就不是它的主战场。

### Source-backed notes

- README defines Wax as a Swift-native persistence engine for AI agents.
- The core packaging idea is one portable `.wax` file containing documents, metadata, and indexes.
- README positions it as local-first memory tuned for Apple Silicon rather than a server-based vector stack.

### FAQ

**问：Is Wax a hosted vector database?**
答：No. It is designed as a portable local memory engine centered on a single file.

**问：Why is the file model important?**
答：Backup, copy, and transport become simpler because documents and indexes travel together.

**问：Who should evaluate it first?**
答：Swift and Apple Silicon teams building local-first agent or retrieval features.

## Source & Thanks

> Source: https://github.com/christopherkarani/Wax
> License: Apache-2.0
> GitHub stars: 731 · forks: 42


---
Source: https://tokrepo.com/en/workflows/wax-single-file-memory-layer-for-ai-agents
Author: AI Open Source