Nebula-Nexus is a futuristic PDF question-answering assistant for research papers, powered by Retrieval-Augmented Generation (RAG). This tool allows users to upload any PDF and receive precise answers to their questions based on the content of the research paper.

• Upload a PDF of a research paper and ask questions about its content.
• Leveraging RAG to provide accurate answers directly from the paper.
• Added ability to use opensource embeddings

• Python 3.7 or above
• Streamlit
• OpenAI API Key

Follow these steps to get Nebula-Nexus running locally.

git clone https://github.com/ParamChordiya/Nebula-Nexus.git
cd Nebula-Nexus

On macOS/Linux:

python3 -m venv myenv

On Windows:

python -m venv myenv

On macOS/Linux:

source myenv/bin/activate

On Windows:

myenv\Scripts\activate

pip install -r requirements.txt

In the root directory, create a .env file and add your OpenAI API key:

OPENAI_API_KEY=your_openai_api_key_here

Start the Streamlit app with the following command:

streamlit run app.py

1. Open the provided URL in your browser.
2. Upload a research paper in PDF format.
3. Ask questions, and Nebula-Nexus will retrieve answers based on the paper’s content.