At its core, RxAgent-Zoo is a reactive RL framework that treats data events from environments, replay buffers, and training loops as observable streams. Users can chain operators to preprocess observations, update networks, and log metrics asynchronously. The library offers parallel environment support, configurable schedulers, and integration with popular Gym and Atari benchmarks. A plug-and-play API allows seamless swapping of agent components, facilitating reproducible research, rapid experimentation, and scalable training workflows.

DemoGPT is an open-source Python project designed to demonstrate the core concepts of AI agents using OpenAI's GPT models. It implements a conversational interface with persistent memory saved in JSON files, enabling context-aware interactions across sessions. The framework supports dynamic tool execution, such as web search, calculations, and custom extensions, through a plugin-style architecture. By simply configuring your OpenAI API key and installing dependencies, users can run DemoGPT locally to prototype chatbots, explore multi-turn dialogue flows, and test agent-driven workflows. This comprehensive demo offers developers and researchers a practical foundation for building, customizing, and experimenting with GPT-powered agents in real-world scenarios.