RAG Explorer for Wikipedia & Research Paper

This repository demonstrates Retrieval-Augmented Generation (RAG) with two knowledge sources: Wikipedia and a research paper about RAG.

Features

1. Choose Wikipedia as the knowledge source.
2. Choose Research Paper as the knowledge source.
3. Retrieve live and up-to-date information from Wikipedia.
4. Retrieve focused insights about RAG from the research paper.

Setup

Installation

1. Navigate to the project directory:

cd RAG_Explorer

2. Use a virtual environment

python -m venv venv
venv\Scripts\activate

3. Install requirements needed

pip install -r requirements.txt

4. Activate the virtual environment created by Poetry:

poetry shell

5. Install project dependencies using Poetry:

poetry install

6. Create a .env file and add your own OpenAI API key in the .env file as follows:

OPENAI_API_KEY=your-key-here

Running the Application

streamlit run app.py

Once the server starts, open a web browser and follow the link displayed by Streamlit to access the application.

Usage

1. Upon launching the application, you'll be presented with a dropdown menu to select the information source: either Wikipedia or Research Paper.

2. Choose the desired source, and the app will retrieve relevant information based on your selection.

License

This project is licensed under the MIT License. See the LICENSE file for details.