Popular GitHub Repositories for Agentic Memory

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

A programming framework for agentic AI ? PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour

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

The Memory layer for AI Agents

10 Lessons to Get Started Building 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.

React UI + elegant infrastructure for AI Copilots, AI chatbots, and in-app AI agents. The Agentic last-mile ?

This repository contains the Hugging Face Agents Course.

A open, local Manus AI alternative. Powered with Deepseek R1. No APIs, no $456 monthly bills. Enjoy an AI agent that reason, code, and browse with no worries.

An open protocol enabling communication and interoperability between opaque agentic applications.

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

AI Native Data App Development framework with AWEL(Agentic Workflow Expression Language) and Agents

DocsGPT is an open-source genAI tool that helps users get reliable answers from knowledge source, while avoiding hallucinations. It enables private and reliable information retrieval, with tooling and agentic system capability built in.

Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view

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?

Video-based AI memory library. Store millions of text chunks in MP4 files with lightning-fast semantic search. No database needed.

Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!

The most advanced AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.