Developed a code chunking framework for the DS4SD/docling-core repository, focusing on language-specific strategies to improve the relevance and scalability of code processing. The work centered on designing a modular architecture using Python, enabling the system to process code items into manageable chunks tailored to different programming languages. By implementing multiple chunking strategies and leveraging strategy patterns, the framework supports scalable processing and lays the foundation for future language extensions. The approach emphasized data modeling and unit testing to ensure maintainability and extensibility, resulting in a robust solution that enhances readiness for downstream analysis without introducing major bugs during the development period.