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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
|