Document Points Extractor and Summarizer RAG (Retrieval-Augmented Generation)

This project extracts key points from documents and generates summaries using a Retrieval-Augmented Generation (RAG) approach. The system efficiently retrieves relevant information from a set of documents and uses language models to generate concise summaries of the extracted information.

Requirements

• Python 3.x
• The required Python packages listed in requirements.txt

Setup

1. Clone the Repository

Start by cloning this repository to your local machine:

git clone https://github.com/arya2004/summarizzer.git
cd summarizzer

2. Create a Virtual Environment (Optional but Recommended)

It is recommended to use a virtual environment to manage your dependencies:

python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install Requirements

Install the required Python packages listed in requirements.txt:

pip install -r requirements.txt

Contributing

Feel free to submit issues or pull requests for improvements or bug fixes. Follow standard Git practices, and ensure your code is well-documented.

License

This project is licensed under the CC0-1.0 license License.

Enjoy using the Document Points Extractor and Summarizer RAG!