Book-Summarizer

NLP-based book summarizer which summarises the book chapter-wise.
In case the book does not contain chapters: the entire book is summarized.

Why summarize a book?

• The goal of writing a summary of an article, a single chapter or a whole book is to offer as accurately as possible the full sense of the original, but in a more condensed form.
• A summary restates the author's main point, purpose, intent and supporting details in your own words.

How does the summarizer work?

• The summarizer is developed using T5-small pretrained model from HuggingFace Transformers.
• Chunks are created from individual chapters.
• Then the chunks are tokenized using T5Tokenizer.
• The tokenized text is passed to T5ForConditionalGeneration model class, for summary-ids generation.
• The summary-ids are decoded to text using decode() function from the T5Tokenizer.

How to run the book summarizer:

1. Clone the repository.

git clone https://github.com/saarthdeshpande/book-summarizer.git

2. Install all the dependencies mentioned in the requirements.txt.

pip install -r requirements.txt

3. To run via CLI:

python3 bsCLI.py --path <path-to-PDF-file>

4. To run on Flask server with frontend and mail:
   1. Update the value of sender_address and sender_pass in mail.py.
   2. Run views.py.

   python3 views.py
   

Screenshots

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