README.md

📚 AutoFlashcards

Give me your highlighted book before you go to bed, and you'll have fresh, finely processed flashcards by the morning!

✨ Features

• 🔍 Extracts highlights from PDF files
• 📝 Generates context around highlights
• 🤖 Creates flashcards using LLMs (Gemini, OpenaI, Anthropic)
• 📥 Exports flashcards to Anki
• 🔄 Automatically updates flashcards when PDFs are moved or renamed
• 💾 Stores highlights in a SQLite database to avoid duplicates

🔑 Safely storing API_KEY

1. Create a .env file in the project root directory
2. Set your API key and preferred LLM provider in the .env file:

   API_KEY=yourSuperSecretKey
   LLM_PROVIDER=gemini  # Options: gemini, openai, anthropic

3. Include .env in your .gitignore file

🛠️ Working on a virtual environment

Using venv

Run in the main directory of the project:

python3 -m venv venv
source venv/bin/activate

To install all dependencies:

pip install -r requirements.txt

If you change the dependencies, update requirements.txt:

pip freeze > requirements.txt

To exit the virtual environment:

deactivate

Using conda

Run in the main directory of the project:

conda env create -f environment.yml
conda activate myenv

To install all dependencies:

conda install --file requirements.txt

If you change the dependencies, update environment.yml:

conda env export --name myenv --file environment.yml

To exit the conda environment:

conda deactivate

🚀 Usage

1. Ensure your virtual environment is activated and dependencies are installed.
2. Run the main script with your PDF file:

   python main.py your_highlighted_book.pdf

📝 Notes

• Ensure that the directory you want to monitor has the necessary read/write permissions.
• You can modify the DATABASE_PATH and TABLE_NAME variables in the scripts to customize the database location and table name.