This script is a tool for summarizing and discussing PDF documents, specifically scientific papers. It uses OpenAI's GPT-3.5-turbo model for the task of text summarization and question-answering. The primary functionality of the script involves extracting text from a PDF, generating a detailed summary of the content, and then having a back-and-forth discussion with the user about the content of the document.
Ensure you have the following Python libraries installed:
- os
- sys
- openai
- PyPDF2
- tqdm
- dotenv
You can install these using pip:
pip install openai PyPDF2 tqdm python-dotenvThis script uses the OpenAI API, so you'll need an API key from OpenAI. Once you have that, create a .env file in the same directory as your script, and add the following line:
OPENAI_API_KEY=your_openai_api_key
Replace your_openai_api_key with your actual OpenAI API key.
Clone the repository and navigate into the project directory. Make sure to create a .env file with your OpenAI API key as described in the Prerequisites section. To use the script, run the following command:
python3 paper_pundit.py pdf_path.pdf output_file_name.txtReplace pdf_path.pdf with the path to the PDF file you want to process, and output_file_name.txt with the name of the text file where you want to save the results.
There are several constants at the top of the script that you can modify to suit your needs:
WORDS_PER_SECTION: This is the number of words per section that the script will attempt to summarize at once.SECTION_OVERLAP: This is the number of words of overlap between consecutive sections.CONVERSATION_MEMORY: This is the number of previous messages (user + assistant pairs) kept as context for the model.
Please note that the cost estimate given by the script may be way off from the actual cost. It is provided only as a rough guide and should not be relied upon for exact calculations. Always verify with OpenAI's actual cost and pricing details.
This project is licensed under the MIT License.