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README.md

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-# Paper Reader Assistant (Gradio on Hugging Face Spaces)
-
-Features:
-- Upload PDFs → extract text (PyMuPDF)
-- Summarization (BART map-reduce)
-- Keyword extraction (KeyBERT)
-- RAG QA with FAISS + sentence-transformers + Flan-T5
-
-Quick Start:
-1. Create a new **Space** with SDK = **Gradio**.
-2. Upload three files: `app.py`, `requirements.txt`, `README.md`.
-3. Wait for auto-build to finish. Open the Space URL.
+---
+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