pint-lib 0.2.9

A package for automated processing of (pubmed) text with LLM

PubMed Integrated NLP Tool (PINT)

A tool for serial processing of open-source PubMed Central papers with various Large Language Models.

Overview

PINT allows you to process academic papers from PubMed using your choice of:

• OpenAI models
• Anthropic's Claude
• External shell script integration

Dependencies

• 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

Installation

pip install pint_lib

Basic Installation

Without dependencies - you can install separately only those you need

pip install pint_lib[base]

Usage

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/Output

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

Example

A simple example using PDF files is provided in the example folder:

cd example
python -m pint_lib test_config_pdf.xlsx

Configuration

Configuration is handled via Excel or CSV files.

Notes

• You can substitute CSV files for Excel files throughout, though Excel provides better document formatting.