Contrato360 2.0: A Document and Database-Driven Question-Answer System using Large Language Models and Agents

• URL: http://arxiv.org/abs/2412.17942v1
• Date: Mon, 23 Dec 2024 19:54:28 GMT
• Title: Contrato360 2.0: A Document and Database-Driven Question-Answer System using Large Language Models and Agents
• Authors: Antony Seabra, Claudio Cavalcante, Joao Nepomuceno, Lucas Lago, Nicolaas Ruberg, Sergio Lifschitz,
• Abstract summary: We present a question-and-answer (Q&A) application designed to support the contract management process.<n>Data is processed by a large language model (LLM) to provide precise and relevant answers.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present a question-and-answer (Q\&A) application designed to support the contract management process by leveraging combined information from contract documents (PDFs) and data retrieved from contract management systems (database). This data is processed by a large language model (LLM) to provide precise and relevant answers. The accuracy of these responses is further enhanced through the use of Retrieval-Augmented Generation (RAG), text-to-SQL techniques, and agents that dynamically orchestrate the workflow. These techniques eliminate the need to retrain the language model. Additionally, we employed Prompt Engineering to fine-tune the focus of responses. Our findings demonstrate that this multi-agent orchestration and combination of techniques significantly improve the relevance and accuracy of the answers, offering a promising direction for future information systems.

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