This repository implements a Retrieval-Augmented Generation (RAG) approach leveraging advanced Language Models (LLMs). RAG combines the power of pre-trained LLMs with efficient information retrieval, enabling context-aware and coherent content generation.

• RAG Model: Implement a RAG model that combines a language model for generation and a retriever for content retrieval.
• Language Models Integration: Incorporate state-of-the-art language models, such as BERT, GPT, or others, for powerful text generation.
• Efficient Retrieval: Utilize an efficient retriever to gather relevant context from large document collections.
• Customization: Easily adapt the RAG model and language models for specific use cases and domains.

1. Clone the repository:

   git clone https://github.com/rushizirpe/RAG-with-LLMs.git
   cd RAG-with-LLMs

2. Install dependencies:

   pip install -r requirements.txt

python main.py

Contributions are welcome! Feel free to open issues, submit pull requests, or suggest improvements.