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mindverse

Second-Me

Train your AI self, amplify you, bridge the world

AI EngineeringGive agent knowledgeBuild agent workflow (SDK)Python
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创建于 2025-03-16 · 更新于 2026-10-16 · 今日第 19256 名
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mindverse/Second-Me 排名第 19,256,有 15,681 个星标。

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mindverse/Second-Me 排名第 19,256,此处有 8 个同类条目;BuilderIO/gpt-crawler 排名第 19,248。

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关键参数与规格
关键参数与规格
参数值
语言Python
类别AI Engineering
子类别Give agent knowledge,Build agent workflow (SDK)
关键词AI character, LocalAI, Memory management, Retrieval
星标数15,681
分叉数1,212
贡献者34
创建日期2025-03-16
更新日期2026-10-16
1 天星标数-2
7 天星标数-13
排名19,256
上次排名18,126
排名变化-1,130
7 天星标排名18,957
上次 7 天星标排名18,865
7 天星标排名变化-92
总星标排名928
上次总星标排名927
总星标排名变化-1
README 摘录

Our Vision Companies like OpenAI built "Super AI" that threatens human independence. We crave individuality: AI that amplifies, not erases, **YOU**. 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. 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! 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. 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). ❓ Got questions about setup, models, or any troubleshooting? 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: Felix AMA (Roleplay app) Brainstorming a 15-Day European City Itinerary (Network app) Icebreaking as a Speed Dating Match (Network app) 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: 🗂️ **Version Control**: Smarter versioning of memory and identity states 🧠 **Continuous Training Pipelines**: Keep your AI self evolving over time, with ongoing updates based on new memory inputs. ⚙️ **Performance & Stability Improvements**: Enhancements across inference ability, model alignment, and base model upgrades ☁️ **Cloud Solutions**: Explore cloud-based solutions for both model training (fine-tuning) and model deployment, to reduce the hardware burden on users' local machines. 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. 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. 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

常见问题

记录了多少星标和分叉?

mindverse/Second-Me 有 15,681 个星标和 1,212 个分叉。

仓库排名是多少?

mindverse/Second-Me 排名第 19,256。

记录的语言和类别是什么?

mindverse/Second-Me 有 15,681 个星标,语言为 Python,类别为 AI Engineering。

哪个仓库排名最接近?

mindverse/Second-Me 与 BuilderIO/gpt-crawler 比较,后者排名第 19,248,有 22,397 个星标。

README

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:

  • 🗂️ Version Control: Smarter versioning of memory and identity states
  • 🧠 Continuous Training Pipelines: Keep your AI self evolving over time, with ongoing updates based on new memory inputs.
  • ⚙️ Performance & Stability Improvements: Enhancements across inference ability, model alignment, and base model upgrades
  • ☁️ Cloud Solutions: Explore cloud-based solutions for both model training (fine-tuning) and model deployment, to reduce the hardware burden on users' local machines.

Contributing

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

  • 📘 Check out our Contribution Guide to get started
  • 💻 Submit ideas, issues, or PRs on GitHub
  • 💬 Join the conversation and stay updated in our Discord — it’s where the community lives

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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