Multi-agent Application System in Office Collaboration Scenarios
Journal:
arXiv
Published Date:
Mar 25, 2025
Abstract
This paper introduces a multi-agent application system designed to enhance
office collaboration efficiency and work quality. The system integrates
artificial intelligence, machine learning, and natural language processing
technologies, achieving functionalities such as task allocation, progress
monitoring, and information sharing. The agents within the system are capable
of providing personalized collaboration support based on team members' needs
and incorporate data analysis tools to improve decision-making quality. The
paper also proposes an intelligent agent architecture that separates Plan and
Solver, and through techniques such as multi-turn query rewriting and business
tool retrieval, it enhances the agent's multi-intent and multi-turn dialogue
capabilities. Furthermore, the paper details the design of tools and multi-turn
dialogue in the context of office collaboration scenarios, and validates the
system's effectiveness through experiments and evaluations. Ultimately, the
system has demonstrated outstanding performance in real business applications,
particularly in query understanding, task planning, and tool calling. Looking
forward, the system is expected to play a more significant role in addressing
complex interaction issues within dynamic environments and large-scale
multi-agent systems.
