More Methods, Better Agents? A Reality Check on Self-Distillation in Agentic Reinforcement Learning
Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4, MiniMax-H3, Gemma 4, FLUX and more.
Learn AI Engineering! Learn it. Build it. Ship it for others.
《深入理解 AI Agent:设计原理与工程实践》(李博杰 著)开源主仓库:全书正文、编译版 PDF 与按章配套代码
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
SGLang is a high-performance serving framework for large language models and multimodal models.
Train transformer language models with reinforcement learning.
The absolute trainer to light up AI agents.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
A standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
Agent S: an open agentic framework that uses computers like a human
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen3.6, GPT-OSS, Llama, and more!
An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)
SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer
Easily fine-tune (SFT/RL), evaluate, and deploy Qwen, Gemma, or any open agentic LLM/VLM!
A collection of machine learning examples and tutorials.
Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM
Infrastructure for continually self‑improving agents
Democratizing Reinforcement Learning for LLMs
The RL Bridge for LLM-based Agent Applications. Made Simple & Flexible.
RLinf: Reinforcement Learning Infrastructure for Embodied and Agentic AI
A Next-Generation Training Engine Built for Ultra-Large MoE Models
🚀 An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
A library of reinforcement learning components and agents
Mastering Diverse Domains through World Models
A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.)
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities
A high-performance distributed training framework for Reinforcement Learning
An Efficient and User-Friendly Scaling Library for Reinforcement Learning with Large Language Models
A collection of environments for autonomous driving and tactical decision-making tasks
Isaac Lab API, powered by MuJoCo-Warp, for RL and robotics research
[NeurIPS 2024] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
Miles is an enterprise-facing reinforcement learning framework for LLM and VLM post-training, forked from and co-evolving with slime.
Implementation of papers in 100 lines of code.
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
Monte Carlo tree search in JAX
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
Simple and easily configurable grid world environments for reinforcement learning
Textbook on reinforcement learning from human feedback
ProtoMotions is a GPU-accelerated simulation and learning framework for training physically simulated digital humans and humanoid robots.
GLM-4.6V/4.5V/4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
A lightweight suite of motion imitation methods for training controllers.
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
Scalable toolkit for efficient model reinforcement
A collection of robotics simulation environments for reinforcement learning
FinRL®-Meta: Dynamic datasets and market environments for FinRL.
Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning
RoboVerse: Towards a Unified Platform, Dataset and Benchmark for Scalable and Generalizable Robot Learning
A standard format for offline reinforcement learning datasets, with popular reference datasets and related utilities
A lightweight library for PyTorch training tools and utilities
Simulation of spiking neural networks (SNNs) using PyTorch.
Agent-R1: Training Powerful LLM Agents with End-to-End Reinforcement Learning
[NeurIPS 2023 Spotlight] LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios (awesome MCTS)
The living ecosystem where AI agents complete tasks through workflow loops, improve through iterative execution, are evaluated by mentor agents or humans in the loop, and turn completed work into reusable work experience and data to improve future agents.
bsuite is a collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent
Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".
Multimodal RL training framework for diffusion & omni models