Simplifying Table Parsing using TAPAS API and Django web Application: Review
Sagar Bhilaji Shinde, Aparna Pande, Ketan More, Ashay Chaudhari, Niraj Mate, Mr. Shivam D. Rokade · 2024
The proposed work introduces the combination of Google's Table parsing model (TAPAS), facilitated through Hugging Face, with a Django-backed web application. The paper explores the seamless incorporation of TAPAS into a business enterprise-level application, highlighting the development of APIs for greater accessibility. This implementation empowers users to efficiently extract and manage tabular data, using a tokenized storage system. As the existing methodology needs expertise and this proposed work will overcome this barrier. The web application not only offers a person-pleasant interface for interacting with TAPAS but also offers APIs for developers to integrate this effective model into their applications. This proposed work simplifies the table operations by utilizing the available resources and the adaptability of TAPAS in handling complex table-related inquiries positions it as a valuable tool for both enterprise and end-user applications, showcasing its potential for revolutionizing data extraction and analysis.