Researchers at emblebi have launched BioChatter, an open-source Python framework designed to facilitate the use of large language models (LLMs) in biomedical research. This initiative aligns with open science principles, aiming to make LLMs more accessible for biomedical applications. BioChatter integrates various deployment tools and knowledge management systems, including knowledge graphs and vector databases. Additionally, a related project called ESCARGOT has been introduced, which combines LLMs with a dynamic Graph of Thoughts and biomedical knowledge graphs to enhance reasoning capabilities. ESCARGOT reportedly outperforms existing methods in precision, particularly for open-ended questions, while providing greater transparency in its reasoning process. The advancements in LLMs are seen as pivotal in accelerating biomedicine research, with ongoing developments expected to further support researchers in understanding health and disease.