A Practical Approach for Building Production-Grade Conversational Agents with Workflow Graphs

• URL: http://arxiv.org/abs/2505.23006v1
• Date: Thu, 29 May 2025 02:30:27 GMT
• Title: A Practical Approach for Building Production-Grade Conversational Agents with Workflow Graphs
• Authors: Chiwan Park, Wonjun Jang, Daeryong Kim, Aelim Ahn, Kichang Yang, Woosung Hwang, Jihyeon Roh, Hyerin Park, Hyosun Wang, Min Seok Kim, Jihoon Kang,
• Abstract summary: Large Language Models (LLMs) have led to significant improvements in various service domains.<n>Applying state-of-the-art (SOTA) research to industrial settings presents challenges.
• Score: 2.7905014064567344
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The advancement of Large Language Models (LLMs) has led to significant improvements in various service domains, including search, recommendation, and chatbot applications. However, applying state-of-the-art (SOTA) research to industrial settings presents challenges, as it requires maintaining flexible conversational abilities while also strictly complying with service-specific constraints. This can be seen as two conflicting requirements due to the probabilistic nature of LLMs. In this paper, we propose our approach to addressing this challenge and detail the strategies we employed to overcome their inherent limitations in real-world applications. We conduct a practical case study of a conversational agent designed for the e-commerce domain, detailing our implementation workflow and optimizations. Our findings provide insights into bridging the gap between academic research and real-world application, introducing a framework for developing scalable, controllable, and reliable AI-driven agents.

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