Report Summarizer: Full-Stack NLP Application
/ 1 min read
Table of Contents
Project Links
Project Overview
Developed a full-stack application capable of summarizing long-form texts and documents (PDF, DOCX, TXT)The system offers a choice between Extractive summarization for speed and Abstractive summarization for human-like synthesis.
Key Insights & Impact
Hybrid Summarization Engine: Implemented a dual-logic backend using TF-IDF for identifying key sentences and Hugging Face BART transformers for generating original, context-aware summaries[cite: 11, 23]. Full-Stack Architecture: Built a robust Flask API to handle file uploads and summarization requests, paired with a responsive frontend for seamless user interaction. DevOps & Containerization: Orchestrated the entire environment using Docker and Docker Compose, ensuring consistent deployment across different infrastructures. Performance & Versatility: Optimized the system to process multiple file formats and provide a history of generated summaries for easy retrieval and download.