MemOS and Awesome-Agent-Memory
About MemOS
MemTensor/MemOS
AI memory OS for LLM and Agent systems(moltbot,clawdbot,openclaw), enabling persistent Skill memory for cross-task skill reuse and evolution.
This project helps AI developers build AI agents and large language models (LLMs) that can remember past interactions, skills, and knowledge over long periods. It provides a unified system for storing and retrieving diverse information like text, images, and tool usage history, allowing agents to learn from experience. AI developers can use this to create more personalized and effective AI assistants and automated systems.
About Awesome-Agent-Memory
TeleAI-UAGI/Awesome-Agent-Memory
Curated systems, benchmarks, and papers etc. on memory for LLMs/MLLMs --- long-term context, retrieval, and reasoning.
This project offers a comprehensive collection of resources on memory mechanisms for large language models (LLMs) and multimodal language models (MLLMs). It helps AI developers and researchers understand and implement solutions for long-term context, efficient retrieval, and robust reasoning in AI agents. You can explore systems, benchmarks, and academic papers to find effective approaches for improving AI memory.
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