A bionic reading tool that leverages the power of machine learning to enhance the reading experience and organization, particularly for individuals with an inability to focus.
- Folder Management: The model can create subsections such as
modified/food,modified/space,modified/politics, and more and store the respected pdf within their folder. - Text Summarization: Textboost provides the capability to summarize the text within a given PDF. Optionally, the user can turn on this feature and the summarization will appear at the last page of the PDF.
❗PLEASE NOTE THE FOLLOWING❗
Please note that this tool supports simple text extraction from PDFs. Complex elements like tables and code blocks will not be rendered properly.
The updated PDF will be automatically placed in appropriate folders based on the text context. You can find your modified file in a folder similar to./modified/space/your_file.py.
Don't forget to check your current directory for the outputted file.
- Through Github
- Install Python.
- Git clone this repository by running the command
https://github.com/boushrabettir/textboost.git - Move to the
textboostdirectory by runningcd ./textboost - Pip install requirements by running
pip install -r requirements.txt - Convert your PDF to a Markdown using this tool.
- Place your modified Markdown file in the
pre-modifiedfolder. - Run the script by typing
python ./main.py
- Through Pypi
- Install Python.
- Convert your PDF to a Markdown using this tool.
- Place your modified Markdown file in the
pre-modifiedfolder. - Run the script by typing
textboost
- Bold formatting to emphasize specific letters within words.
- Organized file locations for modified files generated by a model
- Optional text summarization generated by the model
instruction.mp4
Made with 🐱💛 by @boushrabettir