added readme descriptions

README.md

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+---
+title: NLP Assignment RAG App
+emoji: 🧠
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: "4.44.0"
+app_file: app.py
+pinned: false
+---
+
+# NLP Assignment – Research Paper RAG Assistant
+
+This app retrieves and summarizes academic papers related to your research query using a **Retrieval-Augmented Generation (RAG)** pipeline built with:
+
+- **FAISS** vector search (`index.faiss`, `index.pkl`)
+- **SentenceTransformer CrossEncoder** reranker
+- **Google Gemini (via LangChain)** as the LLM
+- **Gradio** UI frontend
+- **uv** package manager (modern, fast, Python-native)
+
+---
+
+## 🚀 How to Run Locally
+
+You can run this project locally using **uv** (recommended) or plain **Python**.
+
+### 🧩 Prerequisites
+
+- Python 3.12 or higher  
+- [uv](https://docs.astral.sh/uv/) installed:
+
+```sh
+  pip install uv
+```
+
+1. Clone the repository
+
+```sh
+git clone https://huggingface.co/spaces/njayman/nlp-assignment
+cd nlp-assignment
+```
+
+2. Add your FAISS index files
+
+Make sure your FAISS index folder is structured like this:
+
+```sh
+faiss_index/
+├── index.faiss
+└── index.pkl
+```
+
+3. Set up environment
+
+Set your Gemini API key (replace with your own key):
+
+Linux/macOS:
+
+```sh
+export GOOGLE_API_KEY="your_google_api_key_here"
+```
+
+Windows (PowerShell):
+
+```sh
+$env:GOOGLE_API_KEY="your_google_api_key_here"
+```
+
+Or add a `.env` file
+
+```sh
+GOOGLE_API_KEY="your_google_api_key_here"
+```
+
+4. Create a virtual env and install dependencies using uv
+
+```sh
+uv venv
+uv sync
+```
+
+5. Run the Gradio app
+
+```sh
+uv run main.py
+```
+
+Then open the link printed in your terminal — usually:
+
+```sh
+http://127.0.0.1:7860
+```

faiss_index/index.faiss

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faiss_index/index.pkl

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