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ABSTRACT
Automated generation of block diagrams from textual descriptions presents a significant challenge in system architecture visualization and design. In this study, we address this challenge by developing a web-based block diagram generator application that leverages natural language processing models to interpret textual descriptions and generate corresponding block diagrams automatically. The aim of this research is to streamline the process of creating visual representations of system architectures, software designs, and business processes by providing a user-friendly and efficient solution for diagram generation. To achieve this aim, we integrate state-of-the-art natural language processing models from the OpenAI API into our web-based application. The application utilizes Python programming language for backend development, Streamlit framework for frontend interface design, and PlantWeb library for rendering generated block diagrams into visual representations. Through rigorous testing and evaluation methodologies, including functionality testing, performance assessment, and user satisfaction analysis, we validate the effectiveness and reliability of the block diagram generator in accurately interpreting textual descriptions and generating coherent block diagrams. The outcomes of this research demonstrate the successful development and deployment of a robust and intuitive block diagram generator application. The application exhibits high accuracy and fidelity in translating textual descriptions into meaningful block diagrams, with robust performance characteristics and positive user feedback regarding usability and overall experience. This research contributes to the advancement of automated diagram generation technologies, 6 offering a valuable tool for communication, collaboration, and decision-making in various domains and industries.
