Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Awesome AI Memory | LLM Memory | A curated knowledge base on AI memory for LLMs and agents, covering long-term memory, reasoning, retrieval, and memory-native system design. Awesome-AI-Memory 是一个 集中式、持续更新的 AI 记忆知识库，系统性整理了与 大模型记忆（LLM Memory）与智能体记忆（Agent Memory） 相关的前沿研究、工程框架、系统设计、评测基准与真实应用实践。
| Date | Stars |
|---|---|
| 2026-07-24 | 1102 |
| 2026-07-25 | 1104 |
| 2026-07-28 | 1104 |
| 2026-07-30 | 1104 |
| 2026-07-31 | 1111 |
| 2026-08-06 | 1111 |
Today
— stars today
This week
+7 stars this week
This month
— stars this month
Momentum
7.0
growth rate 0.63%/day
# Awesome-AI-Memory
<p align="center">
【English | <a href="README_cn.md">中文</a></a>】
</p>
<div align="center">
<img src="assets/Gemini_Generated_Image_hretabhretabhret.png" alt="Survey Framework" width="82%">
</div>
[](https://github.com/IAAR-Shanghai/Awesome-AI-Memory)
[](https://opensource.org/licenses/MIT)
[](https://github.com/IAAR-Shanghai/Awesome-AI-Memory/papers)
[](https://github.com/IAAR-Shanghai/Awesome-AI-Memory/projects)
## 👋 Introduction
Large Language Models (LLMs) have rapidly evolved into powerful general-purpose reasoning and generation engines. Nevertheless, despite their continuously advancing capabilities, LLMs remain fundamentally constrained by a critical limitation: the finite length of their context window. This constraint defines the scope of information directly accessible during a single inference process, endowing models with only short-term memory capabilities. Consequently, they struggle to support extended conversations, personalized interactions, continuous learning, and complex multi-stage tasks.
To transcend the inherent limitations of context windows, AI memory and memory systems for LLMs have emerged as a vital and active research and engineering frontier. By introducing external, persistent, and controllable memory structures beyond model parameters, these systems enable large models to store, retrieve, compress, and manage historical information during generation processes. This capability allows models to continuously leverage long-term experiences within limited context windows, achieving cross-session consistency and continuous reasoning abilities.
Awesome-AI-Memory is a comprehensive repository dedicated to AI memory and memory systems for large language models, systematically curating relevant research papers, framework tools, and practical implementations. This repository endeavors to map the rapidly evolving research landscape in LLM memory systems, bridging multiple disciplines including natural language processing, information retrieval, intelligent agent systems, and cognitive science.
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## 🎯 Goal of Repository
Our mission is to establish a centralized, continuously evolving knowledge base that serves as a valuable reference for researchers and practitioners, ultimately accelerating the development of intelligent systems capable of long-term memory retention, sustained reasoning, and adaptive evolution over time.
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## 📏 Project Scope
This repository focuses on memory mechanisms and system designs that extend or augment the context window capabilities of large language models, rather than merely addressing model pre-training or general knowledge learning. The content encompasses both theoretical research and engineering practices.
🌀 Included Content (In Scope)
- Memory and memory system designs for large language models
- External explicit memory beyond model parameters
- Short-term memory, long-term memory, episodic memory, and semantic memory
- Retrieval-Augmented Generation (RAG) as a memory access mechanism
- Memory management strategies (writing, updating, forgetting, compression)
- Memory systems in intelligent agents (Agents)
- Shared and collaborative memory in multi-agent systems
- Memory models inspired by cognitive science and biological memory
- Evaluation methods, benchmarks, and datasets related to LLM memory
- Open-source frameworks and tools for memory-enhanced LLMs
🌀 Excluded Content (Out of Scope)
- General model pre-training or scaling research without direct memory relevance
- Purely parameterized knowledge learning without memory interaction
- Traditional databases or information retrieval systems unrelated to LLMs
- Generic memoryExcerpt of 509,365 characters
Read on GitHub
219
Ziyang Guo · Southeast University · China
37
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TerminallyLazy
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jaylfc
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Nicolò Boschi · @vectorize-io · Italy
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Max Baluev
1
Wayde
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:6efcf07323904581, topic:rag, readme:retrieval-augmented generation, readme:retrieval augmented