Multi-Agent LLM System Enhances Brazilian Labor Law Q&A
A new multi-agent system leveraging Large Language Models (LLMs) has been created to enhance question-answering related to Brazil's intricate labor laws, particularly the Consolidation of Labor Laws (CLT). This innovative framework tackles the challenges and inconsistencies that Human Resources (HR) professionals encounter while navigating these regulations and ensuring compliance. Developed in collaboration with CrewAI, the system utilizes specialized agents to manage various facets of employment law and incorporates Retrieval-Augmented Generation (RAG) for improved contextual accuracy. By facilitating cooperative interactions among agents, the system validates responses, minimizing misinformation. The effectiveness of this method is assessed against a baseline, with the goal of improving accuracy and efficiency in legal Q&A tasks.
Key facts
- The Consolidation of Labor Laws (CLT) is Brazil's primary legal framework for labor relations.
- HR professionals face challenges due to the complexity of the CLT.
- Traditional methods for labor law inquiries lead to inefficiencies, delays, and inconsistencies.
- A multi-agent system powered by LLMs is introduced to improve legal Q&A.
- The system uses specialized agents for distinct aspects of employment law.
- Retrieval-Augmented Generation (RAG) is integrated to enhance contextual relevance.
- CrewAI is used to implement cooperative agent interactions for response validation.
- The framework's effectiveness is evaluated through comparison with a baseline.
Entities
Institutions
- arXiv
Locations
- Brazil