RAG Retrieval-Augmented Generation Codes
I published my first RAG boilerplate — frontend + backend
3 followers
I published my first RAG boilerplate — frontend + backend
3 followers
Hey friends👋, I just finished building my first RAG boilerplate — frontend + backend all set up. It lets you: - Upload multiple PDF and chat with it like “Chat with PDF” - Use a Next.js frontend + FastAPI backend - Connect to Chroma vector DB and Gemini API
Buy it on Gumroad link at $30 --> https://arjora3.gumroad.com/l/ragbyarj
I built this because setting up Retrieval-Augmented Generation (RAG) from scratch takes a lot of time and debugging — from managing embeddings to integrating APIs and setting up the frontend/backend.
Every time I wanted to experiment with AI ideas, I spent days just setting up the basics.
So, I decided to create a plug-and-play RAG boilerplate that handles all that.
My boilerplate is end-to-end, with:
- A ready-to-use Next.js frontend
- A FastAPI backend that handles embedding and retrieval logic
- Seamless integration with Chroma vector DB and Gemini API
Basically, it’s not just code — it’s a complete developer-ready starter kit for AI-powered web apps.