This is a guest post by Jack Simon, who built a LangChain-powered chatbot focused on appendiceal cancer, aiming to make specialized knowledge more accessible to those in need. The chatbot uses retrieval-augmented generation (RAG) to access multiple sources of knowledge, including literature reviews, clinical trial data, and academic papers. This approach allows it to generate accurate and informative responses about a rare medical condition, filling the gap left by existing models that struggle with providing information on conditions with fewer than 1,000 patients. The ultimate vision is to expand the chatbot's knowledge base to cover as many rare conditions as possible, creating an AI-driven application that can serve as a reliable source of information for patients and healthcare professionals alike. By addressing the challenges associated with rare medical conditions, Jack aims to bridge the gap between patients and the knowledge they need, revolutionizing healthcare through AI-powered chatbots.