RepoPilot

Inspiration

Understanding an unfamiliar GitHub repository can be challenging. We built RepoPilot to help developers explore code, understand project architecture, and identify potential bugs faster with AI.

What it does

RepoPilot combines code exploration, repository mind maps, AI-powered repository Q&A, reverse prompt generation, and bug analysis in one interface. It aims to explain potential issues and suggest practical fixes.

How we built it

We used HTML, CSS, and JavaScript to build a lightweight, responsive interface. AI providers connect through their APIs, with dynamic model selection and optional fallback settings. The "api/ai.js" Vercel serverless function proxies supported AI requests to help overcome browser CORS restrictions.

Challenges we ran into

Integrating multiple AI providers brought challenges with authentication, model availability, API compatibility, and browser restrictions. Debugging these issues taught us to improve error handling, model discovery, and API-key security.

Accomplishments that we're proud of

We brought multiple developer workflows into one tool, designed to help developers understand repositories without manually exploring every file. We are also proud of supporting multiple AI providers.

What we learned

We learned that useful AI tools need more than a model connection. Reliable APIs, secure key handling, good user experience, and repository-grounded answers are equally important.

What's next for RepoPilot

We plan to improve bug detection, generate safer code patches and tests, visualize dependencies, and strengthen automated testing. Our goal is to make RepoPilot a practical AI companion for understanding and improving codebases.

Built With

• artificial-intelligence
• css
• developer-tools
• generative
• github
• html
• javascript
• large-language-models
• nvidia-nim
• vercel