Simplified molecular-input line-entry system (SMILES) descriptors are a widely used and dominant method for generating three dimensional (3D) atomic structures of molecules. Their popularity stems from their efficiency and text-based format, making them well-suited for various applications. Consequently, many deep learning-based modeling tools heavily rely on SMILES strings as both input and output formats. Software libraries like RDKit and Openbabel effectively process SMILES to build molecular structures. However, this prevalent "all-at-once" approach, where the entire structure is constructed from a single SMILES string, presents limitations. For complex molecules like polymers, it can become computationally expensive. Additionally, limited user control over the final structure restricts its adaptation to specific research questions.