Python · FastAPI · LangChain · ChromaDB · Next.js

RAG Pipeline

Retrieval-Augmented Generation app with a FastAPI backend and a Next.js frontend scaffold.

GitHub (opens in a new tab)

A full-stack RAG application scaffold FastAPI backend handling document ingestion, embedding, and retrieval, paired with a Next.js frontend for the chat interface. Built as a production-ready starting point.

Problem

Every RAG project starts by stitching together the same pieces: document ingestion, vector storage, retrieval, and a UI. This project packages that foundation so you can start building the interesting parts immediately.

Solution

A monorepo with a FastAPI backend (LangChain + ChromaDB + OpenAI) and a Next.js frontend scaffold. The backend exposes REST endpoints for document upload and querying; the frontend consumes them with a clean chat UI.

Key Features

  • Document upload and ingestion via API endpoint
  • ChromaDB vector storage with persistent collections
  • Streaming responses from OpenAI via FastAPI
  • Next.js frontend with chat interface scaffold
  • Docker Compose for local development
  • Environment-based configuration for all API keys