As a full-stack developer working on increasingly large codebases, I kept running into the same problem: onboarding into an unfamiliar repo, or even my own old projects, meant hours of manually reading through files just to answer simple questions like "where is auth handled?" or "what does this function actually do?"
So I built Chat with your Codebase — a RAG-powered MERN app that lets you ask plain-language questions about any codebase and get accurate, context-aware answers.
The app is built around a classic Retrieval-Augmented Generation (RAG) pipeline:
Working on this taught me a lot about the practical side of RAG systems — how chunking strategy directly affects answer quality, why local embeddings can be a smart trade-off for cost control, and how much prompt engineering matters once you're grounding an LLM in retrieved context instead of letting it answer from general knowledge.
You can check out the live demo here: [Chat with your Codebase](https://chat-with-your-codebase-fz2b.vercel.app/)
And the code is open source on [GitHub](https://github.com/PARIKSHIT-Shah/Chat-with-your-codebase).
Would love feedback from anyone who's built something similar, or has thoughts on better chunking strategies for large repos!