2025-10 Monthly Summary: Focused on delivering a modular, maintainable PaddleNLP model conversion workflow and laying the groundwork for Qwen2 integration. No major user-facing bugs fixed this month; stability preserved while internal improvements were made to architecture, docs, and tests. Overall impact: Accelerated model conversion, improved code quality, and clearer paths for future enhancements. This sets the stage for faster feature delivery and easier onboarding for contributors and users. Technologies/skills demonstrated: Python modular architecture, code refactoring and maintainability, documentation and analysis artifact creation, and test-driven development for conversion tooling and Qwen2 compatibility.