Agents are All you need: Elevating Trading Dynamics with Advanced Generative AI-Driven Conversational LLM Agents and Tools

This paper presents the development of a groundbreaking LLM multi-agent system designed to optimize the Energy Exchange (EX)'s electricity trading. The system integrates cutting-edge, Generative AI, embedding-based deep learning models and LLM Agents to forecast electricity prices with heightened accuracy and facilitate interactive reporting. Our first agent performs advanced deep learning , tapping into IEX's rich databases for day-ahead and intraday market prices, alongside additional data streams such as weather and economic indicators. We eschew traditional predictive models in favor of sophisticated embedding-based models adept at discerning complex temporal patterns, enabling precise forecasts up to seven days ahead. Rigorous validation methods, including k-fold cross-validation, are applied, with accuracy gauged by metrics like Root Mean Squared Error (RMSE). The second agent is founded on a robust GenAI tools framework, translating intricate model predictions into intelligible reports and extract insights through another LLM based Agents. This interface adeptly handles energy market specifics, ensuring contextually relevant interactions. This tool's integration aims to enhance decision-making for market participants and to inject unprecedented predictive transparency into market dynamics. Our initiative heralds a transformative step toward realizing a data-centric, efficient, and customer-focused energy market in India, with potential expansion throughout the South Asian region powered by LLM and generative AI.