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HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency
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HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency
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Many theoretical and experimental workflows in high-energy-physics (HEP) stand to benefit from recent advances in transformer-based large language models (LLMs). While early applications of LLMs focused on text generation and code completion, modern LLMs now support orchestrated agency: the coordinated execution of complex, multi-step tasks through tool use, structured context, and iterative reasoning. We introduce the HEP Toolkit for Agentic Planning, Orchestration, and Deployment (HEPTAPOD), an orchestration framework designed to integrate external LLMs into general HEP workflows spanning theoretical calculations, simulation, and data analysis. The framework enables LLMs to interface with domain-specific tools and to construct and manage diverse HEP pipelines while preserving transparency, reproducibility, and human oversight. To demonstrate these capabilities, we present a representative case study in the context of a Beyond the Standard Model (BSM) Monte Carlo signal validation that spans model generation, event simulation, and analysis within an established, reproducible workflow. HEPTAPOD provides a structured and auditable layer between human researchers, LLMs, and computational infrastructure, establishing a foundation for human-in-the-loop, agent-assisted workflows across high-energy physics.
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