APPLICATION OF A LARGE LANGUAGE MODEL FOR AIR POLLUTION ANALYSIS BY USING A RAG SYSTEM

The paper examines the application of an LLM (Large Language Model) for analysing text information about air pollution using a RAG (Retrieval-Augmented Generation) system. It describes what RAG systems are and how they help increase the credibility of the text generated by LLM models (reducing their hallucinations) using information retrieval from reliable sources. An approach for the development of a RAG system suitable for answering queries on imported text documents by the user is presented. The realisation of this approach is the development of a RAG chatbot using the Python language, answering queries (questions) towards a database of uploaded text documents by the user. Some results from experiments on a selected database of scientific publications related to air pollution are presented.