# FedRAG

An open-source Python framework for fine-tuning retrieval-augmented generation systems across both centralized and federated architectures.

FedRAG is a framework for fine-tuning retrieval-augmented generation (RAG) systems, supporting both centralized training and federated learning across multiple parties. It provides RAG fine-tuning methods that can be federated with relatively little extra work.

It integrates with popular frameworks including HuggingFace, LlamaIndex and LangChain, and offers lightweight abstractions intended to simplify fine-tuning while keeping full control over the process.

It is installable from PyPI or conda-forge, with optional extras such as a HuggingFace integration, and is licensed under Apache-2.0.

Website: https://vectorinstitute.github.io/fed-rag/