A simple Python implementation of the ReAct pattern for LLMs. I implemented the ReAct pattern (for Reason+Act) described in this paper. It's a pattern where you implement additional actions that an LLM can take - searching Wikipedia or running calculations for example - and then teach it how to request that those actions are run, then feed their results back into the LLM.
Recent articles
- My review of Claude's new Code Interpreter, released under a very confusing name - 9th September 2025
- Recreating the Apollo AI adoption rate chart with GPT-5, Python and Pyodide - 9th September 2025
- GPT-5 Thinking in ChatGPT (aka Research Goblin) is shockingly good at search - 6th September 2025