ai-agent

Improve LLM Memory with Awesome-Agent-Memory

Name: Improve LLM Memory with Awesome-Agent-Memory
Author: TeleAI-UAGI

Get curated systems and benchmarks for LLM memory. For founders working with AI agents.

533 stars62 forksPythonQuality 9/10Updated 7/15/2026100% free · open source

What it does

Awesome-Agent-Memory provides curated systems, benchmarks, and papers on memory for Large Language Models (LLMs) to help founders improve long-term context, retrieval, and reasoning in AI agents

Install / run

git clone https://github.com/TeleAI-UAGI/Awesome-Agent-Memory.git

When to use it

•When designing an AI agent that requires complex, long-term memory and context understanding
•When evaluating and comparing different LLM architectures for a specific use case
•When researching and implementing memory-augmented AI systems for improved reasoning and decision-making

Quick start

1Explore the curated list of papers and benchmarks in the `papers` and `benchmarks` directories
2Review the `README.md` file for an overview of the repository and its contents
3Check out the `systems` directory for examples of implemented memory-augmented LLM systems
4Use the provided links to external resources, such as research articles and GitHub repositories, to deepen your understanding of LLM memory and its applications
5Search for specific keywords or topics in the repository using `grep` or your preferred search tool

Ready-to-paste prompt

Search for papers on 'external memory' using `grep -r 'external memory' papers/`

Heads up: Note that this repository is a collection of resources and does not provide executable code, so you will need to implement and integrate the concepts and systems described in your own project

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