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21 changes: 18 additions & 3 deletions README.md
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MemOS is an open-source **Agent Memory framework** that empowers AI agents with **long-term memory, personality consistency, and contextual recall**. It enables agents to **remember past interactions**, **learn over time**, and **build evolving identities** across sessions.

Designed for **AI companions, role-playing NPCs, and multi-agent systems**, MemOS provides a unified API for **memory representation, retrieval, and update** — making it the foundation for next-generation **memory-augmented AI agents**.

🆕 **MemOS 2.0** introduces **knowledge base system**, **multi-modal memory** (images & documents), **tool memory** for Agent optimization, **memory feedback mechanism** for precise control, and **enterprise-grade architecture** with Redis Streams scheduler and advanced DB optimizations.
<div align="center">
<a href="https://memos.openmem.net/">
<img src="https://statics.memtensor.com.cn/memos/memos-banner.gif" alt="MemOS Banner">
</a>

<h1 align="center">
<img src="https://statics.memtensor.com.cn/logo/memos_color_m.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"/>
<img src="https://statics.memtensor.com.cn/logo/memos_color_m.png" alt="MemOS Logo" width="50"/> MemOS 2.0: 星尘(Stardust) <img src="https://img.shields.io/badge/status-Preview-blue" alt="Preview Badge"/>
</h1>

<p>
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<img src="https://cdn.memtensor.com.cn/img/1762436050812_3tgird_compressed.png" alt="SOTA SCORE">

**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.
**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. **MemOS 2.0** features comprehensive knowledge base management, multi-modal memory support, tool memory for Agent enhancement, and enterprise-grade architecture optimizations.

- **Website**: https://memos.openmem.net/
- **Documentation**: https://memos-docs.openmem.net/home/overview/
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Stay up to date with the latest MemOS announcements, releases, and community highlights.


- **2025-12-24** - 🎉 **MemOS v2.0: Stardust (星尘) Release**:
Major upgrade featuring comprehensive Knowledge Base system with automatic document/URL parsing and cross-project sharing; Memory feedback mechanism for correction and precise deletion; Multi-modal memory supporting images and charts; Tool Memory to enhance Agent planning; Full architecture upgrade with Redis Streams multi-level queue scheduler and DB optimizations; New streaming/non-streaming Chat interfaces; Complete MCP upgrade; Lightweight deployment modes (quick & full).
- **2025-11-06** - 🎉 MemOS v1.1.3 (Async Memory & Preference):
Millisecond-level async memory add (support plain-text-memory and
preference memory); enhanced BM25, graph recall, and mixture search; full
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- **Textual Memory**: For storing and retrieving unstructured or structured text knowledge.
- **Activation Memory**: Caches key-value pairs (`KVCacheMemory`) to accelerate LLM inference and context reuse.
- **Parametric Memory**: Stores model adaptation parameters (e.g., LoRA weights).
- **Tool Memory** 🆕: Records Agent tool call trajectories and experiences to improve planning capabilities.
- **📚 Knowledge Base System** 🆕: Build multi-dimensional knowledge bases with automatic document/URL parsing, splitting, and cross-project sharing capabilities.
- **🔧 Memory Controllability** 🆕:
- **Feedback Mechanism**: Use `add_feedback` API to correct, supplement, or replace existing memories with natural language.
- **Precise Deletion**: Delete specific memories by User ID or Memory ID via API or MCP tools.
- **👁️ Multi-Modal Support** 🆕: Support for image understanding and memory, including chart parsing in documents.
- **⚡ Advanced Architecture**:
- **DB Optimization**: Enhanced connection management and batch insertion for high-concurrency scenarios.
- **Advanced Retrieval**: Custom tag and info field filtering with complex logical operations.
- **Redis Streams Scheduler**: Multi-level queue architecture with intelligent orchestration for fair multi-tenant scheduling.
- **Stream & Non-Stream Chat**: Ready-to-use streaming and non-streaming chat interfaces.
- **🔌 Extensible**: Easily extend and customize memory modules, data sources, and LLM integrations.
- **🏂 Lightweight Deployment** 🆕: Support for quick mode and complete mode deployment options.

## 🚀 Getting Started

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