Year: 2025
Type: preprint
Abstract: Manual document processing for PDF and DOCX files is time-consuming and error-prone, often requiring costly proprietary tools. File-Automator is an open-source project with code available for document processing that addresses this challenge by automating document management with AI-driven capabilities. It supports text extraction, classification, summarization, multilingual translation, and OCR enhancement, powered by Azure/Groq APIs. A Streamlit-based interface ensures userfriendly access, while SQLite caching optimizes performance by reducing redundant API calls. Designed for researchers, students, and small businesses, File-Automator offers a costeffective alternative to commercial systems, integrating advanced AI with an intuitive design. Key contributions include its accessible interface, seamless AI integration, and open-source code availability, enabling reproducibility and community contributions. This paper describes File-Automator's design, implementation, and practical applications, emphasizing its role in intelligent document processing.
Author: Tanisha Samant
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4415159579
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