In the era of information overload, the demand for efficient text summarization tools has never been greater.This research paper presents a comprehensive blueprint for constructing a state-of-the-art abstractive text summarization web application using Python, Flask, and Hugging Face models.Recognizing the pressing need for streamlined information processing, we delve into the intricate nuances of text summarization, outlining the challenges, methodologies, and implications of automated summarization techniques.Leveraging the power of Python's robust ecosystem, the flexibility of Flask's web framework, and the cutting-edge capabilities of Hugging Face's pre-trained models, we provide a step-by-step guide to crafting a sophisticated web application that empowers users with the ability to distill complex text into concise and insightful summaries.From setting up the development environment to deploying the application on scalable cloud platforms, this paper offers detailed insights and practical guidance for developers and researchers looking to make a significant impact in the field of natural language processing.
Rashmi GandhiAbhishek SainiSaumya Gaikwad
Shubham DhapolaShailendra GoelDaksh RawatSatvik VatsVikrant Sharma
M AsmithaAashritha DandaHemanth BysaniRimjhim Padam SinghSneha Kanchan
Eymen Kagan TaspinarYusuf Burak YetisOnur Cihan
Shoaib HayatAvishek DasMohammed Moshiul Hoque