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A newer version of the Gradio SDK is available: 6.1.0

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metadata
title: Paper Reader Assistant
emoji: 📚
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false

📖 Paper Reader Assistant (Gradio on Hugging Face Spaces)

This Space helps you read and analyze academic papers with AI assistance.
You can upload PDF files, and the app will automatically extract text, generate summaries, identify keywords, and enable question answering using RAG (Retrieval-Augmented Generation).

🚀 Features

  • 🧾 PDF Upload → Extracts text using PyMuPDF
  • ✍️ Summarization → Uses BART for map-reduce summarization
  • 🔑 Keyword Extraction → Powered by KeyBERT
  • ❓ Q&A (RAG) → Combines FAISS + SentenceTransformers + Flan-T5
  • 🧠 All-in-one academic reading assistant

⚙️ Quick Start

  1. Create a new Space on Hugging Face with SDK = Gradio
  2. Upload three files:
    • app.py
    • requirements.txt
    • README.md (this file)
  3. Save changes — Spaces will automatically build and launch the app
  4. Once it’s live, open the Space URL to start using it

💡 Notes

  • Works best on English scientific PDFs (text-based).
  • For scanned PDFs, run OCR first (not yet included in this version).
  • Models run on CPU by default — enable GPU for faster processing.
  • You can further customize UI theme, font color, or add dark mode by editing app.py.

🧰 Tech Stack

Component Description
Gradio Front-end interface
PyMuPDF PDF text extraction
Transformers (BART) Summarization
KeyBERT Keyword extraction
Sentence-Transformers + FAISS Vector retrieval for Q&A
Flan-T5 Natural language generation

Author: WENIor
License: MIT
Version: 1.0.0