Update README.md

README.md

@@ -10,5 +10,86 @@ pinned: false
 license: mit
 short_description: 📝 Text & PDF Summarizer UI
 ---
+# 📝 Text & PDF Summarizer UI
+
+A lightweight web application that allows users to paste text or upload a PDF document, then summarizes the content using a HuggingFace transformer model integrated with LangChain and displayed via a Gradio interface.
+
+## 🚀 Key Features
+
+- Input text manually or via PDF upload
+- Extracts and summarizes PDF text using NLP
+- User-friendly Gradio interface
+- Uses pre-trained `facebook/bart-large-cnn` summarization model
+
+## 🏗️ Project Architecture
+
+- **Gradio**: Frontend interface to interact with the app
+- **PyPDF2**: Extracts text from PDF files
+- **LangChain**: Framework for managing LLM-based workflows
+- **HuggingFace**: Provides transformer models like BART for summarization
+
+## 🔧 Getting Started
+
+**1- Clone the repo**
+   ```bash
+   git clone https://github.com/yourusername/text-pdf-summarizer-ui.git
+   cd text-pdf-summarizer-ui
+ ```
+
+   📁**Project Structure**  
+
+      ├── text-pdf-summarizer-ui/  
+            ├── app.py      # Application  
+            └── requirements.txt               
+            └── README.md
+
+**2- Create a virtual environment (optional)**
+   ``` python -m venv venv
+   source venv/bin/activate  # On Windows: venv\\Scripts\\activate
+ ```
+
+**3- Install dependencies**
+
+```bash
+pip install -r requirements.txt
+ ```
+
+**4- Run the app**
+```bash
+python app.py
+```
+
+
+## 🧠 About the Tools
+
+    **LangChain**: provides a modular framework for building applications with language models. Here, it's used to manage prompting and model output formatting.
+
+    **HuggingFace Transformers**: We use the facebook/bart-large-cnn model, a powerful encoder-decoder model ideal for summarization.
+
+    **Gradio**: lets us quickly build and share user-friendly web interfaces for Machine Learning apps.
+
+
+## 🔍 Implementation Details
+
+      1- Model Initialization: Using HuggingFacePipeline via LangChain
+   
+     2- PromptTemplate: Wraps text for inference
+   
+     3- PDF Handling: Reads uploaded file as bytes and extracts text using PyPDF2
+   
+     4- UI Logic: Built with Gradio Blocks to control layout, input, and output
+
+
+## ✅ Example Usage
+   - Upload a PDF or paste article text
+   - Cick “Convert PDF to Text” (if PDF)- 
+   - Click “Summarize Text”
+   - View summary below the input
+
+## 📝 License
+    MIT
+
+##  🤝 Contributions
+    Pull requests and suggestions welcome!
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference