Designing a Robust Generative AI Project Structure for LLM & RAG Applications
Modern generative AI applications—especially those built on large language models (LLMs) and Retrieval-Augmented Generation (RAG)—can become chaotic very quickly if they’re not organized well. Multiple model providers, complex prompt flows, vector databases, embeddings, caching, inference orchestration, and deployment considerations all compete for space in your codebase. Without a clear structure, your project becomes difficult to extend, debug, or hand off to other engineers. This article walks through a practical and scalable project structure for a generative AI application: ...