Odyssey is a framework that empowers LLM-based Minecraft agents with open-world skills, featuring 40 primitive skills and 183 compositional skills, enabling AI to autonomously explore, learn, and execute diverse tasks in the Minecraft universe.
An open-source reinforcement learning framework that trains multi-step agents for real-world tasks using GRPO, supporting Qwen2.5, Qwen3, Llama, and other large language models.
A benchmark for evaluating the code generation capabilities of large language models, featuring 1,140 software-engineering-oriented programming tasks with two modes (Complete and Instruct) to test models on complex instructions and diverse function call scenarios.
A modern framework for probabilistic programming and Bayesian analysis designed for research and data analytics, featuring intuitive APIs and flexible model definition capabilities。
A comprehensive platform for training, evaluating, and evolving LLM-based agents across diverse environments with standardized benchmarks.
A reinforcement learning environment for Mario AI, offering trainable agents to play Super Mario games.
A minimal yet professional demo project that showcases the best practices for building agents with the MiniMax M2.1 model, featuring a complete execution pipeline and production-grade capabilities.
A step-by-step workshop that teaches you how to build your own AI-powered coding assistant, starting from a basic chatbot and progressively adding powerful tools like file reading, shell command execution, and code search.
An open-source deep research agent optimized for research and prediction tasks, achieving 80.8% Avg@8 score on the challenging GAIA benchmark, featuring 256K context window support and up to 600 tool calls per task.
An educational project that teaches you how to build modern AI coding agents from scratch through progressive tutorials, featuring 5 versions from simple bash tools to a complete skills system.
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