Developer Builds RAG Chatbot to Answer Plain-Language Questions About Codebases

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A full-stack developer has built an open-source MERN application called 'Chat with your Codebase' that uses Retrieval-Augmented Generation (RAG) to let users ask natural-language questions about any code repository. The tool was created to address the time-consuming process of manually navigating unfamiliar or large codebases during onboarding. It works by chunking code into meaningful segments, converting them into vector embeddings using local models, and storing them in MongoDB Atlas for fast semantic search. Relevant code snippets are then passed as context to Groq's Llama 3.3, which generates accurate, grounded answers rather than relying on general model knowledge. The project is live on Vercel and publicly available on GitHub, with the developer seeking community feedback on chunking strategies for large repositories.

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