R2GQA: Retriever-Reader-Generator Question Answering System to Support Students Understanding Legal Regulations in Higher Education

🔍 Introduction

R2GQA is an automated question answering system designed to assist students in comprehending legal regulations related to higher education. It leverages a combination of modern information retrieval and natural language processing techniques to deliver accurate and user-friendly answers in Vietnamese.

The system consists of three main components working together:

1. Retriever Combines BM25 and SBERT to identify and fetch the most relevant legal text passages from a large corpus based on the user’s question.

2. Reader Utilizes transformer-based models such as XLM-RoBERTa-large to extract precise answers from the retrieved documents.

3. Generator Synthesizes the extracted answers into natural, concise, and user-friendly responses tailored for Vietnamese legal language.

Installation

Requirements

• Libraries listed in requirements.txt

Installation Steps

Clone repository:

git clone https://github.com/dpptinh/R2GQA-system
cd R2GQA

Install dependencies:

pip install -r requirements.txt

3. Create .env file with the following environment variables:

FULL_DATA_PATH=<path to data file>
DOCUMENTS_LINK_PATH=<path to links file>
EMBEDDING_MODEL_PATH=<path to embedding model>
EXTRACTIVE_MODEL_PATH=<path to extractive model>
ABSTRACTIVE_MODEL_PATH=<path to abstractive model>

Usage

Run the application:

python main.py

Contributing

Contributions are welcome. Please:

1. Fork the repository
2. Create a new branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Create a Pull Request

License

This project is distributed under the CC BY-NC-SA 4.0 License for research purposes only. See LICENSE for more information.