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.github/CONTRIBUTING

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Please read https://memos.openmem.net/docs/contribution/overview to learn how to contribute to this repository. 🌟
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Please read https://memos-docs.openmem.net/contribution/overview to learn how to contribute to this repository. 🌟
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请阅读 https://memos.openmem.net/docs/contribution/overview 了解如何为此项目贡献代码。🌟
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请阅读 https://memos-docs.openmem.net/contribution/overview 了解如何为此项目贡献代码。🌟

README.md

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<div align="center">
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<a href="https://memos.openmem.net/">
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<img src="docs/assets/banner_new.gif" alt="MemOS Banner">
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<img src="https://statics.memtensor.com.cn/memos/memos-banner.gif" alt="MemOS Banner">
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</a>
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<h1 align="center">
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<img src="docs/assets/memos_logo.png" alt="MemOS Logo" width="50"/> MemOS 1.0: 星河 (Stellar) <img src="https://img.shields.io/badge/status-Preview-blue" alt="Preview Badge"/>
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</h1>
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<a href="https://pypi.org/project/MemoryOS">
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<img src="https://img.shields.io/pypi/pyversions/MemoryOS.svg" alt="Supported Python versions">
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</a>
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<a href="https://memos.openmem.net/docs/home">
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<a href="https://memos-docs.openmem.net/home/overview/">
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<img src="https://img.shields.io/badge/Documentation-view-blue.svg" alt="Documentation">
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</a>
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<a href="https://arxiv.org/abs/2507.03724">
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---
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<a href="https://memos.openmem.net/">
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<img src="docs/assets/sota_score.jpg" alt="SOTA SCORE">
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</a>
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<img src="docs/assets/sota_score.jpg" alt="SOTA SCORE">
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**MemOS** is an operating system for Large Language Models (LLMs) that enhances them with long-term memory capabilities. It allows LLMs to store, retrieve, and manage information, enabling more context-aware, consistent, and personalized interactions.
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- **Website**: <a href="https://memos.openmem.net/" target="_blank">https://memos.openmem.net/</a>
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- **Documentation**: <a href="https://memos.openmem.net/docs/home" target="_blank">https://memos.openmem.net/docs/home</a>
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- **API Reference**: <a href="https://memos.openmem.net/docs/api/info" target="_blank">https://memos.openmem.net/docs/api/info</a>
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- **Source Code**: <a href="https://github.com/MemTensor/MemOS" target="_blank">https://github.com/MemTensor/MemOS</a>
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- **Website**: https://memos.openmem.net/
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- **Documentation**: https://memos-docs.openmem.net/home/overview/
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- **API Reference**: https://memos-docs.openmem.net/docs/api/info/
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- **Source Code**: https://github.com/MemTensor/MemOS
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## 📈 Performance Benchmark
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> 💡 **Temporal reasoning accuracy improved by 159% compared to the OpenAI baseline.**
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### Details of End-to-End Evaluation on LOCOMO
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> [!NOTE]
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> Comparison of LLM Judge Scores across five major tasks in the LOCOMO benchmark. Each bar shows the mean evaluation score judged by LLMs for a given method-task pair, with standard deviation as error bars. MemOS-0630 consistently outperforms baseline methods (LangMem, Zep, OpenAI, Mem0) across all task types, especially in multi-hop and temporal reasoning scenarios.
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<a href="https://memos.openmem.net/">
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<img src="docs/assets/score_all_end2end.jpg" alt="END2END SCORE">
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</a>
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<img src="docs/assets/score_all_end2end.jpg" alt="END2END SCORE">
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## ✨ Key Features
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## 🙌 Contributing
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We welcome contributions from the community! Please read our [contribution guidelines](https://memos.openmem.net/docs/contribution/overview) to get started.
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We welcome contributions from the community! Please read our [contribution guidelines](https://memos-docs.openmem.net/contribution/overview) to get started.
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## 📄 License
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docs/assets/banner_new.gif

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