Ai Document Summariser

Input
Code Section
Final Output

Inspiration

Reading long documents can be time-consuming, especially when users only need the key information. We wanted to create a simple AI-powered tool that could quickly convert lengthy documents into concise and meaningful summaries.

What it does

AI Document Summariser uses a Hugging Face transformer model to analyse text and generate a concise summary while preserving the important information. Users can enter or provide document content through a simple Gradio interface and receive an AI-generated summary.

How we built it

We built the project using Python and Hugging Face Transformers. We used the facebook/bart-large-cnn pretrained model for text summarisation, along with PyTorch for model execution. The user interface was created using Gradio, making the application simple and easy to use.

Challenges we ran into

One of the main challenges was handling long documents because transformer models have input-length limitations. We also had to understand how tokenization, text truncation, and generation parameters affect the quality and length of the generated summary.

Accomplishments that we're proud of

We successfully built a working AI-powered document summarisation application using a pretrained transformer model. We also created a simple interactive interface that allows users to use the summarisation system without needing to interact directly with the underlying code.

What we learned

Through this project, we learned how to work with Hugging Face Transformers and pretrained NLP models. We gained practical experience with tokenization, text generation, PyTorch, model parameters, and integrating an AI model into a user-friendly application using Gradio.

What's next for AI Document Summariser

We plan to improve the project by supporting different document formats such as PDF and DOCX, handling larger documents more efficiently, and providing options for different summary lengths. We also plan to explore multilingual summarisation and more advanced language models to improve the quality of generated summaries.