Inspiration & References

Acknowledgments

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Thanks to the following projects, communities, and individuals for their inspiration and support.

Inspiration & References

Memos

Thank you to the Memos project for providing a comprehensive, standardized open-source note-taking service that has provided valuable inspiration for our memory system design.

Nemori

Thank you to the Nemori project for providing a self-organising long-term memory substrate for agentic LLM workflows that has provided valuable inspiration for our memory system design.

Open Source Libraries

EverMemOS is built on top of excellent open-source libraries and frameworks:

Core Framework

• FastAPI - Modern, fast web framework for building APIs
• Python - Programming language
• uv - Fast Python package manager

Storage & Search

• MongoDB - Document database
• Elasticsearch - Search and analytics engine
• Milvus - Vector database
• Redis - In-memory data store

AI/ML

• OpenAI - LLM APIs
• DeepInfra - Embedding and reranking services

Development Tools

• Docker - Containerization platform
• Beanie - Async ODM for MongoDB

Contributors

Thanks to all the developers who have contributed to this project!

See the full list of contributors on GitHub.

Community

Thanks to our community for their valuable feedback, bug reports, and feature suggestions:

• GitHub Issues & Discussions - For bug reports and feature requests
• Discord - Join our Discord server
• Reddit Community - r/EverMindAI
• X/Twitter - @EverMindAI

Supporting Organizations

• Shanda Group - For supporting the development of EverMemOS

Special Thanks

• To everyone who has starred the repository
• To those who have shared EverMemOS with others
• To researchers and developers using EverMemOS in their projects

Want to Contribute?

We welcome contributions! See our Contributing Guide to get started.

See Also

• Citation
• Changelog
• Contributing Guide