This repository contains a Python script called pdf_summarization_app.py that allows users to summarize a PDF document using natural language processing. The script uses the gradio library for building a simple web interface for users to input the PDF file path and a custom prompt for summarization.
To use the pdf_summarization_app.py script, follow these steps:
- Clone this repository to your local machine using the following command:
git clone https://github.com/your_username/pdf_summarization_app.git
- Create the conda environment:
conda env create -f environment.yml
You can also just install the required libraries using the following command:
pip install -r requirements.txt
To use the pdf_summarization_app.py script, follow these steps:
-
Open a terminal and navigate to the pdf_summarization_app directory.
-
Run the script using the following command:
python pdf_summarization_app.py -
Open a web browser and navigate to http://localhost:7860/.
-
Enter the path to the PDF file and a custom prompt for summarization.
-
Click the "Summarize" button to generate the summary and the "Custom Summarize" button to generate custom summary.
This repository also contains two Jupyter notebooks entitled summarization_with_langchain.ipynb and talk_to_pdf_with_langchain.ipynb. These notebooks provide additional examples and functionality for summarizing PDF documents using natural language processing.
I added a specialized app to construct custom summaries.
I added a text chunk visualization for the summarization app:
Just run:
streamlit run ./custom_summarization_app.py
This project was built using the gradio, langchain and streamlit librairies.
- Add option to produce multiple summaries
- Create github repo
- Add custom summarization
- Add interactive tool to debug chunk size
- Add a free option
- Add an option to estimate cost in the case of using paid API like ChatGPT
- Add token count option
- Add option to create summaries for multiple papers inside a folder
- Integrate map prompt and combine prompt