Production-grade RAG app: React UI, Python backend, vector search, and enterprise-ready LLM integration.
This repository contains a full-stack Retrieval-Augmented Generation (RAG) application built by HERE AND NOW AI. It pairs a modern React frontend with a robust Python backend to deliver an enterprise-grade document Q&A experience powered by large language models.
The application demonstrates best practices for building production-ready RAG systems: efficient document ingestion, vector storage, semantic retrieval, and streaming LLM responses — all wrapped in a clean, responsive UI.
Whether you are studying RAG architecture or building your own LLM-powered product, this codebase serves as a practical, deployable reference implementation.
- React frontend with a responsive chat interface
- Python backend handling RAG pipeline (ingestion, retrieval, generation)
- Vector database integration for semantic search
- Streaming LLM responses for real-time UX
render.yamlfor one-click cloud deployment- Enterprise proposal and demo guide included
- Node.js 18+ and npm/yarn (frontend)
- Python 3.10+ (backend)
- An LLM API key (OpenAI or compatible)
git clone https://github.com/hereandnowai/react-python-rag-app.git
cd react-python-rag-app
# Backend
cd backend
pip install -r requirements.txt
# Frontend
cd ../frontend
npm installStart the backend:
cd backend
export OPENAI_API_KEY=your_key
python main.pyStart the frontend:
cd frontend
npm startOpen http://localhost:3000 in your browser. Refer to demo_guide.md for a full walkthrough.
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