With its transformative processing capabilities, Quantum computing has ushered in a new computational era, presenting unparalleled opportunities and intricate challenges. One potential beneficiary of this quantum revolution is the Digital Humanities. With quantum computing, the field has the potential to enhance its quantitative analysis dramatically. QHAna, the Quantum Humanities Analysis tool explicitly designed for Quantum Digital Humanities, emerges as a pivotal system. This thesis focuses on enhancing QHAna by integrating variational algorithms and paving the way for Variational Quantum Algorithms in a modular manner. The objective is to encapsulate components of variational algorithms as distinct, interchangeable plugins, ensuring adaptability and enabling end users to adapt the algorithms. Addressing challenges like robust plugin communication and intuitive user experience, the research delves into this modular framework’s design, implementation, and evaluation. Beyond the immediate application to Variational Quantum Algorithms, the insights and methodologies derived here lay the foundational groundwork for future modular system designs in the quantum computing domain.