@article{ART003332384},
author={Tae-O Lee and KIM, TAEKOOK},
title={Implementing a Finance Chatbot using Groq API},
journal={Journal of Internet of Things and Convergence},
issn={2466-0078},
year={2026},
volume={12},
number={2},
pages={71-77}
TY - JOUR
AU - Tae-O Lee
AU - KIM, TAEKOOK
TI - Implementing a Finance Chatbot using Groq API
JO - Journal of Internet of Things and Convergence
PY - 2026
VL - 12
IS - 2
PB - The Korea Internet of Things Society
SP - 71
EP - 77
SN - 2466-0078
AB - Conventional financial chatbots based on Large Language Models (LLMs) face limitations in reflecting volatile real-time market data due to their reliance on static, pre-trained parameters. Furthermore, existing systems that integrate external information often perform searches and tool invocations regardless of the specific nature of the query, leading to unnecessary computational overhead and increased response latency. To address these efficiency challenges, this study proposes a "Conditional Tool-Augmented Generation" architecture that dynamically determines the necessity of external data access by identifying user query intent. The proposed system was implemented using the LLaMA 3.1 70B model within the Groq Cloud’s LPU (Language Processing Unit) environment. For queries requiring real-time financial information, the system retrieves the latest stock prices and historical time-series data via the Yahoo Finance API; meanwhile, queries regarding general economic concepts are processed through the model's internal knowledge using few-shot prompting techniques. Additionally, a dialogue memory module is integrated to maintain contextual consistency throughout the conversation. Experimental results demonstrate that the proposed conditional invocation strategy ensures the freshness of information while optimizing indiscriminate external API calls, thereby significantly enhancing overall response performance and cost-efficiency.
KW - Large Language Mode (LLM);Groq;Economic Chatbot;LLaMA;Stock Data;Yahoo Finance;Internet of Things (IoT)
DO -
UR -
ER -
Tae-O Lee and KIM, TAEKOOK. (2026). Implementing a Finance Chatbot using Groq API. Journal of Internet of Things and Convergence, 12(2), 71-77.
Tae-O Lee and KIM, TAEKOOK. 2026, "Implementing a Finance Chatbot using Groq API", Journal of Internet of Things and Convergence, vol.12, no.2 pp.71-77.
Tae-O Lee, KIM, TAEKOOK "Implementing a Finance Chatbot using Groq API" Journal of Internet of Things and Convergence 12.2 pp.71-77 (2026) : 71.
Tae-O Lee, KIM, TAEKOOK. Implementing a Finance Chatbot using Groq API. 2026; 12(2), 71-77.
Tae-O Lee and KIM, TAEKOOK. "Implementing a Finance Chatbot using Groq API" Journal of Internet of Things and Convergence 12, no.2 (2026) : 71-77.
Tae-O Lee; KIM, TAEKOOK. Implementing a Finance Chatbot using Groq API. Journal of Internet of Things and Convergence, 12(2), 71-77.
Tae-O Lee; KIM, TAEKOOK. Implementing a Finance Chatbot using Groq API. Journal of Internet of Things and Convergence. 2026; 12(2) 71-77.
Tae-O Lee, KIM, TAEKOOK. Implementing a Finance Chatbot using Groq API. 2026; 12(2), 71-77.
Tae-O Lee and KIM, TAEKOOK. "Implementing a Finance Chatbot using Groq API" Journal of Internet of Things and Convergence 12, no.2 (2026) : 71-77.
