suyashpradhan/rag-prompt-assembly-studio

RAG Prompt Studio is a learning project built for people who want to understand Retrieval-Augmented Generation, often shortened to RAG, and prompt engineering. RAG is a technique where an AI system pulls in outside information before generating an answer, rather than relying only on what it already knows. This project gives you a small, self-contained space to try out that idea and see how different prompts affect the results. The repository is organized into three folders. The src folder holds the main source code, examples contains sample scripts that show typical usage patterns, and tests holds the test files. Rather than being a polished, ready-to-deploy application, it reads as a personal or educational sandbox for RAG experiments and prompt strategies. According to the README, the project includes example implementations of RAG systems, utilities for working with prompts, and some testing and evaluation tools. Getting started is simple: clone or download the code, install the dependencies, and look through the examples and utilities to see how the pieces fit together. Because the README is short, it does not go into detail about which programming libraries or AI models the examples rely on, beyond noting that the project is written in TypeScript. There is no description field and no listed topics, which suggests the project is still in an early or informal stage. It looks aimed at someone who wants to learn RAG concepts hands on rather than someone looking for a production ready tool. The project is released under the MIT license, one of the most permissive open source licenses. That means you're free to use, copy, modify, and even sell code based on this project, as long as you keep the original copyright notice attached. Suyash Pradhan is listed as the author. If you're new to RAG or prompt engineering, this could be a reasonable starting point for tinkering, though you should expect a learning exercise rather than a fully built tool.