JocelynVelarde/rag-template
Learn how to build a Retrieval-Augmented Generation (RAG) system from the ground up! In this session, you’ll break down the pipeline, see practical examples, evaluate retrieval quality, and learn tips for deploying a reliable RAG service. Ideal for developers who want to add factual, up-to-date knowledge to their AI apps.
This project helps AI application developers build systems that provide accurate, up-to-date answers to user questions based on a specific body of knowledge. Developers can input existing text documents, and the system uses Google Gemini and MongoDB Atlas to retrieve relevant information and generate context-aware responses. It is intended for developers creating AI-powered applications that need to deliver factually grounded information.
Use this if you are a developer building an AI application and need a robust way to ensure your AI provides answers based on your own specific data, rather than just its general training.
Not ideal if you are a non-developer seeking an out-of-the-box, no-code solution for question answering.
Stars
9
Forks
15
Language
Python
License
MIT
Category
Last pushed
Dec 18, 2025
Commits (30d)
0
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