DevDocs+AI

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  It is a frontend view of DevDocs+

Inspiration

I was inspired to build DevDocs+ because developers spend a lot of time navigating long technical documentation. I wanted to create a tool that simplifies learning by adding AI-powered explanations and summaries directly inside documentation pages.

What it does

DevDocs+ is an AI-powered Chrome extension designed to make reading and understanding technical documentation faster, easier, and more interactive. Whether you’re a beginner or an experienced developer, DevDocs+ helps you summarize, explain, and clarify complex documentation sections in real-time — without leaving the page. With just a click, users can get: 📄 Summaries of lengthy documentation 💡 Explanations of confusing terms or code snippets 🤖 AI-driven insights powered by LLMs like Groq APIs ⚙️ A simple, intuitive UI built for productivity and smooth workflow

How we built it

Frontend: 1.Chrome Extension built using JavaScript, HTML, and CSS 2.Injects a floating Ask DevDocs+ button when text is selected 3.Sends API requests to the backend and displays formatted AI responses

Backend: 1.Built with FastAPI ** 2.Integrated with **Groq API for intelligent code explanations and summaries 3.Uses CORS middleware to handle extension requests 4.Structured routes for modular AI endpoints

Challenges we ran into

1.API Rate Limits: Groq API has strict quota limits (HTTP 429 errors), so we implemented request throttling and retries. 2.CORS Issues: The browser extension couldn’t directly communicate with the backend initially. We solved this using FastAPI’s CORS middleware. 3.Formatting AI Responses: The responses from the API were often dense or unformatted. We used Markdown rendering and whitespace optimization to make it visually clear

Accomplishments that we're proud of

I can think of new idea by analysing problem faced by me and engineers and able to resolve it using AI

What we learned

While building this project, I learned: 1.How Chrome extension architecture works 2.Integrating FastAPI with external AI providers 3.Handling API errors and rate limits 4.Designing clean UI/UX for better developer experience 5.I also learned how to optimize prompt engineering and manage asynchronous requests.

What's next for DevDocs+AI

1.Adding multilingual support for documentation.
2.Integrating with VS Code for in-editor explanations.
3.Improving output more like for developer style

Built With

• css
• fastapi
• html
• javascript
• python
• render