F1RAG - Formula 1 Retrieval Augmented Generation System

F1RAG is a retrieval-augmented generation system focused on Formula 1 racing data. The system leverages historical Formula 1 data to provide insights, answer questions, and generate content related to Formula 1 racing.

Data Source

The system uses Formula 1 World Championship data from 1950-2020, sourced from:

• Dataset: Formula 1 World Championship (1950-2020)
• Platform: Kaggle
• Credit: Rohan Rao (Dataset Creator)

Setup and Requirements

Installation

1. Clone the repository:

   git clone https://github.com/ibanrohazz/F1RAG.git
   cd F1RAG

2. Quick setup (recommended):

   # On Windows
   setup_env.bat
   
   # On any platform with Python
   python install_deps.py

3. Manual setup:

   # Create and activate a virtual environment
   python -m venv env
   
   # On Windows
   env\Scripts\activate
   
   # On macOS/Linux
   source env/bin/activate
   
   # Install required packages
   pip install torch transformers datasets scikit-learn pandas matplotlib seaborn

4. Download the dataset:

   • Download the Formula 1 dataset from Kaggle
   • Extract the CSV files into the data/raw/archive directory

Running the Project

Always activate the virtual environment first:

# On Windows
env\Scripts\activate

# On macOS/Linux
source env/bin/activate

Then follow these steps:

1. Process the race data:

   python src/data_processing.py

2. Train the model:

   python src/rag_model.py

3. Generate race summaries:

   python src/rag_model.py --generate

4. Visualize the race summaries (optional):

   python src/visualization.py

Troubleshooting

If you encounter a ModuleNotFoundError, ensure you've:

1. Activated the virtual environment
2. Installed all dependencies
3. Used the correct Python interpreter

To verify your environment, run:

python -c "import transformers; print('Transformers version:', transformers.__version__)"

If that fails, try reinstalling the transformers package:

pip install --upgrade transformers

License

This project uses data under the terms provided by Kaggle and the dataset creator. The F1 data is provided for educational and research purposes.

Acknowledgments

• Thanks to Rohan Rao for compiling and sharing the comprehensive Formula 1 dataset on Kaggle.
• Formula 1 (F1) for the exciting sport that generated this data.