Development of a ChatBot with generative artificial intelligence to answer questions related to the field of public procurement
This work focuses on the development of a chatbot based on generative artificial intelligence, designed to answer questions related to the field of public procurement. The main objective is to provide an interactive tool capable of interpreting natural language queries and delivering accurate, conte...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad del País Vasco |
| Repositorio: | Addi. Archivo Digital para la Docencia y la Investigación |
| OAI Identifier: | oai:addi.ehu.eus:10810/75410 |
| Acceso en línea: | http://hdl.handle.net/10810/75410 |
| Access Level: | acceso abierto |
| Palabra clave: | artificial ntelligence Chatbot public procurement language models Machine Learning RAG Fine-tuning natural language processing |
| Sumario: | This work focuses on the development of a chatbot based on generative artificial intelligence, designed to answer questions related to the field of public procurement. The main objective is to provide an interactive tool capable of interpreting natural language queries and delivering accurate, context-aware answers based on current regulations and procedures. To achieve this, two different approaches were implemented and evaluated: (1) fine-tuning a large language model (LLM) using question–answer pairs extracted from FAQ documents, and (2) applying a Retrieval-Augmented Generation (RAG) architecture that combines document retrieval with generative response generation.After comparing both methods, the RAG solution was selected as the most suitable one, and a functional web interface was developed specifically for this final version. The system was tested in realistic scenarios, and the results obtained help identify the advantages and limitations of each approach, as well as propose possible improvements and future lines of work. |
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