SightFix is a lightweight diagnostic web application designed to help users understand mechanical problems quickly. By entering a short description of an issue, users receive a structured diagnostic response outlining possible faults and repair steps. The goal is clarity, speed, and accessibility.
Inspiration: The idea came from noticing how intimidating mechanical issues are for non-experts. A small problem often feels overwhelming simply because people don’t know what is wrong or where to start. SightFix aims to bridge that knowledge gap using AI-style reasoning.
What I Learned: I learned how to design a full-stack project under time pressure, integrate APIs, manage backend servers, and debug real deployment issues. Most importantly, I learned how fragile systems can be when dependencies, environments, and versions don’t align—and how to systematically fix them.
How I Built It: SightFix was built using FastAPI for the backend and a simple HTML frontend for user interaction. The backend processes user input, constructs a structured diagnostic prompt, and returns a clear response. The system is modular, allowing future AI model upgrades.
Challenges Faced: The biggest challenges were API compatibility issues, environment configuration, and server port conflicts. Debugging model errors and dependency warnings required careful reading of logs and step-by-step isolation of problems. These challenges significantly strengthened my debugging and problem-solving skills.
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