Building Robust Systems with An Engineer's Mindset

Instead of relying on a heavy database, I designed a lightweight, split-architecture system. When a user asks a question, the Flask server first pings the Google Cloud API to convert that text into vector data.

It then uses NumPy to perform a high-speed mathematical search against my local document store. Finally, it combines that retrieved context with a custom prompt to generate a unique, in-character response.

I engineered a full-stack solution that balances system performance with user utility. On the backend, I architected a flat-file CMS using Flask and Pandas, eliminating database latency for instant load times.

On the frontend, I developed a Smart Renovation Algorithm that validates user inputs and performs real-time cost calculations. This project demonstrates my ability to optimize server-side data structures while simultaneously implementing complex business logic in the browser.