RAG Simplified

This project provides a practical demonstration of Retrieval-Augmented Generation (RAG) technology in an accessible manner. It empowers users to explore comprehensive answers to their queries by leveraging either Wikipedia or a dedicated research paper tailored to RAG.

Features

• Users can choose between Wikipedia or Research Paper as the source of information.
• Information retrieval from Wikipedia is dynamic and can be updated with the latest content.
• The Research Paper option provides information specifically about RAG.

Setup

Installation

1. Clone this repository to your local machine:

git clone https://github.com/ShahMitul-GenAI/RAG-Simplified

2. Navigate to the project directory:

cd simplified_rag

3. Install Poetry using pip (if not already installed):

pip install poetry

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

1. After installing the dependencies, you can run the Streamlit app by executing the following command:

streamlit run app.py

2. 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.