Second-Me README

The project's README from github.com/mindverse/Second-Me. As one markdown file: README.md.

Second Me

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Our Vision

Companies like OpenAI built "Super AI" that threatens human independence. We crave individuality: AI that amplifies, not erases, YOU.

We’re challenging that with "Second Me": an open-source prototype where you craft your own AI self—a new AI species that preserves you, delivers your context, and defends your interests.

It’s locally trained and hosted—your data, your control—yet globally connected, scaling your intelligence across an AI network. Beyond that, it’s your AI identity interface—a bold standard linking your AI to the world, sparks collaboration among AI selves, and builds tomorrow’s truly native AI apps.

Tech enthusiasts, AI pros, domain experts, Join us! Second Me is your launchpad to extend your mind into the digital horizon.

Key Features

Train Your AI Self with AI-Native Memory (Paper)

Start training your Second Me today with your own memories! Using Hierarchical Memory Modeling (HMM) and the Me-Alignment Algorithm, your AI self captures your identity, understands your context, and reflects you authentically.

Scale Your Intelligence on the Second Me Network

Launch your AI self from your laptop onto our decentralized network—anyone or any app can connect with your permission, sharing your context as your digital identity.

Build Tomorrow’s Apps with Second Me

Roleplay: Your AI self switches personas to represent you in different scenarios.
AI Space: Collaborate with other Second Mes to spark ideas or solve problems.

100% Privacy and Control

Unlike traditional centralized AI systems, Second Me ensures that your information and intelligence remain local and completely private.

Getting started & staying tuned with us

Star and join us, and you will receive all release notifications from GitHub without any delay!

Quick Start

📊 Model Size vs. Memory (Reference Guide)

Note: "B" in the table represents "billion parameters model". Data shown are examples only; actual supported model sizes may vary depending on system optimization, deployment environment, and other hardware/software conditions.

Memory (GB) Docker Deployment (Windows/Linux) Docker Deployment (Mac) Integrated Setup (Windows/Linux) Integrated Setup (Mac)
8 ~0.8B (example) ~0.4B (example) ~1.0B (example) ~0.6B (example)
16 1.5B (example) 0.5B (example) ~2.0B (example) ~0.8B (example)
32 ~2.8B (example) ~1.2B (example) ~3.5B (example) ~1.5B (example)

Note: Models below 0.5B may not provide satisfactory performance for complex tasks. And we're continuously improving cross-platform support - please submit an issue for feedback or compatibility problems on different operating systems.

MLX Acceleration: Mac M-series users can use MLX to run larger models (CLI-only).

⚡ Get your Second Me running in just 3 steps:

# 1. Clone the repository
git clone https://github.com/mindverse/Second-Me.git
cd Second-Me
# 2. Start Docker containers
make docker-up
# 3. Access the web interface
# Open your browser and visit: http://localhost:3000

👉 For detailed instructions — including integrated (non-Docker) setup, model selection, memory requirements, and platform-specific tips, check the full Deployment Guide on GitBook.

❓ Got questions about setup, models, or any troubleshooting? Check our FAQ.

Tutorial and Use Cases

🛠️ Feel free to follow User tutorial to build your Second Me.

💡 Check out the links below to see how Second Me can be used in real-life scenarios:

What's Next: May 2025

Second Me continues to evolve as the open-source identity infrastructure for AI. Here's what's on deck for May:

Contributing

We’d love for you to help shape what’s coming next — whether it’s fixing bugs, building new features, or improving docs.

Contributors

We would like to express our gratitude to all the individuals who have contributed to Second Me! If you're interested in contributing to the future of intelligence uploading, whether through code, documentation, or ideas, please feel free to submit a pull request to our repository: Second-Me.

Made with contrib.rocks.

Acknowledgements

This work leverages the power of the open-source community.

For data synthesis, we utilized GraphRAG from Microsoft.

For model deployment, we utilized llama.cpp, which provides efficient inference capabilities.

Our base models primarily come from the Qwen2.5 series.

We also want to extend our sincere gratitude to all users who have experienced Second Me. We recognize that there is significant room for optimization throughout the entire pipeline, and we are fully committed to iterative improvements to ensure everyone can enjoy the best possible experience locally.

License

Second Me is open source software licensed under the Apache License 2.0. See the LICENSE file for more details.

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这是什么?Second Me 是一个开源项目,可以训练一个属于你个人的、部署在本地的 AI 模型。它能保留你的身份、记忆和上下文,然后接入去中心化网络,帮你在各类应用中代表你。
这是我要安装的应用,还是需要自己运行的基础设施?这是一套自托管的基础设施:你需要部署一个本地服务器(通过 Docker 或集成式安装),由它训练并运行你自己的模型,之后也可以选择接入 Second Me 网络。
我该怎么把它跑起来?你可以通过 3 个步骤完成部署,方式包括 Docker(Windows/Linux/Mac)或集成式(非 Docker)安装;完整的分步说明、模型选择和各平台提示,都在 GitBook 上的部署指南中。
开始之前我需要准备什么?你需要安装 Python,并准备足够的内存来支持所选的模型大小(README 中的表格显示,小于 1B 的模型需要 8GB,约 3B 的模型需要 32GB 以上);Mac M 系列芯片用户还可以使用 MLX 运行更大的模型,但这一方式只能通过命令行操作。
在依赖它之前,有没有什么需要注意的地方?参数量低于 0.5B 的模型在复杂任务上的效果可能不理想;跨平台支持仍在完善中,因此你可能会遇到特定操作系统的问题。
它只能在 Mac 上运行,还是也支持 Windows 和 Linux?它支持 Windows、Linux 和 Mac,可以通过 Docker 部署或集成式安装运行;各平台的内存要求见快速开始中的表格。
什么是 AI Space?AI Space 允许多个 Second Me 实例相互协作,一起头脑风暴或共同解决问题,为不同人的 AI 分身提供一个交流的场所。
Roleplay 功能是做什么的?Roleplay 让你的 Second Me 可以切换不同的角色设定,从而在不同场景或对话中可信地代表你。
为什么要自己做这个,而不直接用普通的 AI 助手?作者认为集中式的“超级 AI”会威胁个体的独特性,因此 Second Me 的设计目标是放大某个具体的人,而不是取代他;训练和托管都保留在本地,由用户自己掌控。
Second Me 底层用了哪些模型?基础模型主要来自 Qwen2.5 系列,llama.cpp 负责高效的本地推理,微软的 GraphRAG 则用于数据合成。
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