RTL Chabot platform with RAG capabilities. Uses Fast API backend.

• Python 3.11+
• PostgreSQL 13+
• AWS account with Bedrock access

1. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  

2. Install dependencies:

pip install -r requirements.txt

3. Copy the environment file and update the values:

cp .env.example .env

4. Create the database:

createuser chatbot --no-createdb --no-superuser --no-createrole --pwprompt
createdb chatbot

1. Start the backend server:

uvicorn backend.app.main:app --reload

2. In a new terminal, start the frontend:

cd frontend
streamlit run app/main.py

tox

The project uses Ruff for code quality checks:

# Run them separately:
# Check linting
ruff check backend frontend

# Format code
ruff format backend frontend