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@article{169383,
author = {Aum Shankar Javalgikar and Amey Shankar Chavan and Mahesh Shivaji Kadam and Monali Bansode},
title = {AI Agent Standardization using an Agent Package Manager},
journal = {International Journal of Innovative Research in Technology},
year = {2024},
volume = {11},
number = {6},
pages = {1698-1701},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=169383},
abstract = {As AI systems grow in complexity, the need for reusable, modular AI components has become essential. However, the field lacks standardization, with AI agents and tools developed across diverse frameworks, each with unique dependency structures, communication protocols, and functionality. We propose a system that standardizes the development, sharing, and reuse of AI agents and components, aiming to streamline AI development and foster ecosystem interoperability. By introducing a centralized package manager, this framework allows developers to package agents with defined input-output schemas, dependencies, and versioning information, enabling seamless integration across different applications and environments. Key features include a dependency resolution engine that addresses conflicts between frameworks, semantic versioning for backward compatibility, and a registry for discovering and installing agents. This system promotes modularity, reduces development time, and enhances collaboration by allowing components to be readily reused, configured, and deployed. Through standardization, the system lays the groundwork for scalable, multi-agent workflows and democratizes access to sophisticated AI capabilities, empowering developers and organizations to leverage AI with greater efficiency and flexibility. This paper presents the theoretical framework, benefits, and anticipated challenges of the proposed package manager, underscoring its potential to transform AI system design through an AI agent package manager.},
keywords = {Agents, Packages, Components, Standardization},
month = {November},
}
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