Retrieval Augmented Generation for EIC

This is a project that is currently being developed to build a RAG based system for the upcoming EIC. Refer to the Description about the project.

Installation

1. Create a virtual environment:

export RAG4EIC_PROJECT=/path/to/your/project
python -m venv $RAG4EIC_PROJECT/env_RAG4EIC-V0 
source $RAG4EIC_PROJECT/env_RAG4EIC-V0/bin/activate

2. Install Poetry:

Poetry is a dependency management tool for Python. You can install it using the following command:

curl -sSL https://install.python-poetry.org | python3 -

3. Install the project dependencies:

poetry install

4. Clone from the repository:

git clone https://github.com/ai4eic/EIC-RAG-Project.git $RAG4EIC_PROJECT/EIC-RAG-Project
cd $RAG4EIC_PROJECT/EIC-RAG-Project

5. Running the webapp

   • Ask karthik18495@gmail.com about the secrets.toml and config.toml
   • Create a folder named .streamlit in the parent directory and move the files secrets.toml and config.toml in there.
   • Now run streamlit run streamlit_app/AI4EIC-RAGAS4EIC.py. This should run on a http://localhost:8050

Updating

1. If any new library has been used in the app that requires installation through pip. Make sure to use the --format freeze when updating the requirements.txt
2. The command is pip list --format freeze > requirements.txt