Updating project structure and README to reflect

README.md

@@ -9,17 +9,93 @@ pinned: false
 license: mit
 ---
 
-# AI Content Summariser API
+# AI Content Summariser API (Backend)
 
 This is the backend API for the AI Content Summariser, a tool that automatically generates concise summaries of articles, documents, and web content using natural language processing.
 
-## API Endpoints
-
-- POST /api/summarise - Summarize text content
-- POST /api/summarise-url - Extract and summarize content from a URL
+The frontend application is available in a separate repository: [ai-content-summariser](https://github.com/dang-w/ai-content-summariser).
 
 ## Features
 
-- Text summarization using state-of-the-art NLP models
+- Text summarization using state-of-the-art NLP models (BART-large-CNN)
 - URL content extraction and summarization
 - Adjustable parameters for summary length and style
+- Efficient API endpoints with proper error handling
+
+## API Endpoints
+
+- `POST /api/summarise` - Summarize text content
+- `POST /api/summarise-url` - Extract and summarize content from a URL
+
+## Technology Stack
+
+- **Framework**: FastAPI for efficient API endpoints
+- **NLP Models**: Transformer-based models (BART) for summarisation
+- **Web Scraping**: BeautifulSoup4 for extracting content from URLs
+- **HTTP Client**: HTTPX for asynchronous web requests
+- **Deployment**: Hugging Face Spaces or Docker containers
+
+## Getting Started
+
+### Prerequisites
+
+- Python (v3.8+)
+- pip
+
+### Installation
+
+```bash
+# Clone the repository
+git clone https://github.com/dang-w/ai-content-summariser-api.git
+cd ai-content-summariser-api
+
+# Install dependencies
+pip install -r requirements.txt
+```
+
+### Running Locally
+
+```bash
+# Start the backend server
+uvicorn main:app --reload
+```
+
+The API will be available at `http://localhost:8000`.
+
+### Running with Docker
+
+```bash
+# Build and run with Docker
+docker build -t ai-content-summariser-api .
+docker run -p 8000:8000 ai-content-summariser-api
+```
+
+## Deployment
+
+See the deployment guide in the frontend repository for detailed instructions on deploying both the frontend and backend components.
+
+### Deploying to Hugging Face Spaces
+
+1. Create a new Space on Hugging Face
+2. Choose FastAPI as the SDK
+3. Upload your backend code
+4. Configure the environment variables:
+   - `CORS_ORIGINS`: Your frontend URL
+
+## Development
+
+### Testing the API
+
+You can test the API endpoints using the built-in Swagger documentation at `/docs` when running locally.
+
+### Checking Transformers Installation
+
+To verify that the transformers library is installed correctly:
+
+```bash
+python -m app.check_transformers
+```
+
+## License
+
+This project is licensed under the MIT License.