A Retrieval-Augmented Generation (RAG) application that leverages AI for intelligent document processing. Built with FastAPI backend, Streamlit frontend, LlamaIndex & Gemini for AI, and Qdrant for vector storage. Supports PDFs document uploads with efficient data ingestion pipelines.

• Upload PDFs documents
• AI-powered information retrieval
• Store and query vectors efficiently using Qdrant
• Dockerized setup for easy deployment

• Backend: FastAPI
• Frontend: Streamlit
• AI / RAG: LlamaIndex, Gemini
• Vector DB: Qdrant
• Containerization: Docker

git clone https://github.com/far-hana5/RAG-App

python -m venv env
source env/bin/activate  
pip install -r requirements.txt