Geolog-IA: Conversational System for Academic Theses
This tool provides an intuitive web-based interface to support education, training, and research for directors, teachers, students, and administrative staff at the Central University of Ecuador, though it is incremental as it applies existing methods to a new domain-specific dataset.
The study tackled the problem of providing accurate and up-to-date information about geology theses by developing Geolog-IA, a conversational AI system using Llama 3.1 and Gemini 2.5 models with RAG and SQLite, which achieved a BLEU score of 0.87, indicating high consistency and accuracy in responses.
This study presents the development of Geolog-IA, a novel conversational system based on artificial intelligence that responds naturally to questions about geology theses from the Central University of Ecuador. Our proposal uses the Llama 3.1 and Gemini 2.5 language models, which are complemented by a Retrieval Augmented Generation (RAG) architecture and an SQLite database. This strategy allows us to overcome problems such as hallucinations and outdated knowledge. The evaluation of Geolog-IA's performance with the BLEU metric reaches an average of 0.87, indicating high consistency and accuracy in the responses generated. The system offers an intuitive, web-based interface that facilitates interaction and information retrieval for directors, teachers, students, and administrative staff at the institution. This tool can be a key support in education, training, and research and establishes a basis for future applications in other disciplines.