A tool for serial processing of open-source PubMed Central papers with various Large Language Models.
PINT allows you to process academic papers from PubMed using your choice of:
- OpenAI models
- Anthropic's Claude
- External shell script integration
- pdfminer.six - for reading pdf files
- openpyxl - for reading .xlsx files
- requests - to use PubMed API
- anthropic - to use anthropic's Clause API
- openai - to use OpenAI's ChatGPT API
pip install pint_libWithout dependencies - you can install separately only those you need
pip install pint_lib[base]python -m pint_lib <Config_file>The configuration file (Excel or CSV format) controls all aspects of processing:
- Which LLM to use
- Data source locations
- Prompt specifications
- Additional settings
Input:
- CSV or Excel file with a specified column containing either:
- PubMed ID (PMC number)
- Filename (if not numerical or PMC format)
Output:
- CSV file containing the ID and requested extracted data
A simple example using PDF files is provided in the example folder:
cd example
python -m pint_lib test_config_pdf.xlsxConfiguration is handled via Excel or CSV files.
- You can substitute CSV files for Excel files throughout, though Excel provides better document formatting.