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# 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]
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