# Federated Learning for Privacy-Preserving Financial Data Generation with RAG Integration This project implements a federated learning framework combined with a Retrieval-Augmented Generation (RAG) system to generate privacy-preserving synthetic financial data. ## Features - Federated Learning using TensorFlow Federated - Privacy-preserving data generation using VAE/GAN - RAG integration for enhanced data quality - Secure Multi-Party Computation (SMPC) - Differential Privacy implementation - Kubernetes-based deployment - Comprehensive monitoring and logging ## Installation ```bash pip install -r requirements.txt ``` ## Usage [Add usage instructions here] ## Project Structure [Add project structure description here] ## License MIT ## Contributing [Add contributing guidelines here]