Popular GitHub Repositories for Memory Systems

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

A high-throughput and memory-efficient inference and serving engine for LLMs

Finetune Llama 3.3, DeepSeek-R1 & Reasoning LLMs 2x faster with 70% less memory! ?

OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.

The Memory layer for AI Agents

Agno is a lightweight library for building Multimodal Agents. It exposes LLMs as a unified API and gives them superpowers like memory, knowledge, tools and reasoning.

FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily develop and deploy complex question-answering systems without the need for extensive setup or configuration.

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contextually rich responses.

Letta (formerly MemGPT) is the stateful agents framework with memory, reasoning, and context management.

Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research

This repository provides tutorials and implementations for various Generative AI Agent techniques, from basic to advanced. It serves as a comprehensive guide for building intelligent, interactive AI systems.

Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

? CAMEL: Finding the Scaling Law of Agents. The first and the best multi-agent framework. https://www.camel-ai.org

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?

? Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading

A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"

Build, Manage and Deploy AI/ML Systems