<![CDATA[This study presents the development of a web-based educational platform leveraging a large language model (LLM) to provide general information on diseases and medications. The platform integrates a curated database of diseases and drugs with the LLM via retrieval-augmented generation. When users enter a disease or drug name, the system retrieves relevant data and uses it as context for the LLM to produce concise responses in a friendly, accessible style. The application is built using native PHP with a MySQL backend and Bootstrap for responsive design. Safety features such as a mandatory disclaimer and filters for emergency conditions ensure that the chatbot does not offer diagnostic or prescriptive advice. Expert reviews indicated that the model-generated content aligned well with the database, and user testing showed high satisfaction with clarity and usability. These results demonstrate that combining structured medical data with a modern LLM can improve public access to reliable health education while maintaining ethical boundaries.]]>
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