A tutorial on building a Retrieval-Augmented Generation (RAG) system using Groq (Llama 3.1), LangChain, and Gradio.

• Install uv (The fastest Python manager).
• Get a free API Key from Groq Cloud.

git clone https://github.com/sultan-hassan/RAG-tutorial.git
cd RAG-tutorial

Using uv, you don't need to manually create a virtual environment. Run the following command to automatically install all required packages (Pandas, LangChain, Gradio, etc.):

uv sync

To keep your API key secure, create a file named .env in the root folder of this project:

touch .env

Open the .env file and paste your Groq key:

groq_api_keys=your_gsk_key_here

To ensure Jupyter uses the correct environment and avoids "Package Not Found" errors, launch the notebook using this specific command:

uv run --with jupyter jupyter notebook tutorial.ipynb