The project implements a thinking-based approach to machine writing, where language models expand knowledge boundaries through iterative reflection and search. It integrates with various LLMs including deepseek-reasoner, qwen, and GPT models, and supports retrieval-augmented generation using RAGFlow for local document search. The system evaluates machine-written outputs using methods from the associated EMNLP 2025 paper.