Riza is a tool designed to safely and efficiently execute untrusted code, particularly in the context of leveraging large language models (LLMs) like OpenAI's gpt-3.5-turbo and the newer, more cost-effective gpt-4o-mini. The ReAct pattern, which combines reasoning and acting through designated actions or functions, is employed to solve problems using these models. Simon Willison initially demonstrated this pattern by equipping the gpt-3.5-turbo model with tools for Wikipedia searches, blog searches, and Python code execution, albeit with some limitations such as using Python's eval() function, which he noted as risky. Modern advancements, including native function calling in APIs and the use of WebAssembly sandboxes like Riza, have addressed these issues, enhancing both safety and functionality. The text recounts a reimplementation of Simon's code using current API features, demonstrating the evolution and improved capabilities in executing tasks like geographic queries and calculations.