  Current-generation Large Language Models (LLMs) have stirred enormous
interest in recent months, yielding great potential for accessibility and
automation, while simultaneously posing significant challenges and risk of
misuse. To facilitate interfacing with LLMs in the biomedical space, while at
the same time safeguarding their functionalities through sensible constraints,
we propose a dedicated, open-source framework: BioChatter. Based on open-source
software packages, we synergise the many functionalities that are currently
developing around LLMs, such as knowledge integration / retrieval-augmented
generation, model chaining, and benchmarking, resulting in an easy-to-use and
inclusive framework for application in many use cases of biomedicine. We focus
on robust and user-friendly implementation, including ways to deploy
privacy-preserving local open-source LLMs. We demonstrate use cases via two
multi-purpose web apps (https://chat.biocypher.org), and provide documentation,
support, and an open community.
