This project presents a novel AI-driven tool for aiding musical composition through the generation of chord progressions. Special care was undertaken to acquire a high-quality dataset. Its analysis uncovered intriguing patterns in chord progressions across diverse musical genres and periods. We then developed a range of deep learning models, from basic recurrent networks to sophisticated Transformer architectures, including conditional and style-based Transformers for improved controllability. Human evaluation indicates that, within the context of our specific data processing methods, the chord sequences generated by the more advanced models are practically indistinguishable from real sequences. The models are then integrated into a user-friendly open-source web application, making advanced music composition tools accessible to a broader audience. The work on this project still continues, primarily focusing on refining user experience and creating learning materials for those interested in using this tool. A