The Enterprise-Grade Production-Ready Multi-Agent Orchestration Framework Join our Community: https://discord.com/servers/agora-999382051935506503

A compilation of the best multi-agent papers

SwarmZero's SDK for building AI agents, swarms of agents and much more.

A easy, reliable, fluid template for python packages complete with docs, testing suites, readme's, github workflows, linting and much much more

An open source implementation of LFMs from Liquid AI: Liquid Foundation Models

Swarming algorithms like PSO, Ant Colony, Sakana, and more in PyTorch 😊

My implementation of "Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models"

Implementation of MoE Mamba from the paper: "MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts" in Pytorch and Zeta

Implementation of the text to video model LUMIERE from the paper: "A Space-Time Diffusion Model for Video Generation" by Google Research

The next evolution of Agents

Implementation of AutoRT: "AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents"

A vast array of examples for the enterprise-grade and production-ready swarms framework.

The Agent Marketplace

tickr-agent is an enterprise-ready, scalable Python library for building swarms of financial agents that conduct comprehensive stock analysis and produce insights.

Storage server for Oxen Service Nodes

A radically simple, reliable, and high performance template to enable you to quickly get set up building multi-agent applications

Welcome to **FluidAPI**, a framework that allows you to interact with APIs using **natural language**. No more JSON, headers, or complex formats—simply describe your request in plain English, and FluidAPI will do the rest.

A Cinema 4D plugin that implements a flocking/swarming simulation for the C4D standard particle system using a distributed behavioral model.

Deploy your autonomous agents to production grade environments with 99% Uptime Guarantee, Infinite Scalability, and self-healing.

Implementation of the "the first large-scale multimodal mixture of experts models." from the paper: "Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts"