ART
ActiveDescription
ART (Agent Reinforcement Trainer) trains multi-step agents for real-world tasks using GRPO reinforcement learning, enabling on-the-job training for models like Qwen, Llama, and more.
ART (Agent Reinforcement Trainer) trains multi-step agents for real-world tasks using GRPO reinforcement learning, enabling on-the-job training for models like Qwen, Llama, and more.
Fully-automated and zero-code LLM agent framework that enables users to build and deploy custom AI agents through natural language without writing code.
OpenRLHF is a high-performance agentic RL framework based on Ray and vLLM, offering PPO, DAPO, and REINFORCE++ algorithms for large-scale training of agents and vision-language models.
PocketFlow is a minimalist 100-line LLM framework that lets Agents build Agents, enabling complex AI agent workflows through a clean abstraction layer.
SuperAGI is a dev-first open-source autonomous AI agent framework for building, managing, and running useful autonomous agents quickly and reliably.