docs: add Hugging Face Spaces deployment instructions to README.

README.md

@@ -478,6 +478,47 @@ docker-compose down
 ```
 
 
+--------
+
+## Hugging Face Spaces Deployment
+
+This project is configured to run on [Hugging Face Spaces](https://huggingface.co/spaces) using Docker.
+
+### 1. Setup Space
+1. Create a new Space on Hugging Face.
+2. Select **Docker** as the SDK.
+3. Choose the **Blank** template or upload your code.
+
+### 2. Configure Secrets
+To enable the application to pull models from DagsHub via DVC, you must configure the following **Variables and Secrets** in your Space settings:
+
+| Name | Type | Description |
+|------|------|-------------|
+| `DAGSHUB_USERNAME` | Secret | Your DagsHub username. |
+| `DAGSHUB_TOKEN` | Secret | Your DagsHub access token (Settings -> Tokens). |
+
+> [!IMPORTANT]
+> These secrets are injected into the container at runtime. The `scripts/start_space.sh` script uses them to authenticate DVC and pull the required model files (`.pkl`) before starting the API and GUI.
+
+### 3. Automated Startup
+The deployment follows this automated flow:
+1. **Dockerfile**: Builds the environment, installs dependencies, and sets up Nginx.
+2. **scripts/start_space.sh**: 
+   - Configures DVC with your secrets.
+   - Pulls models from the DagsHub remote.
+   - Starts the **FastAPI** backend (port 8000).
+   - Starts the **Streamlit** frontend (port 8501).
+   - Starts **Nginx** (port 7860) as a reverse proxy to route traffic.
+
+### 4. Direct Access
+Once deployed, your Space will be available at:
+`https://huggingface.co/spaces/se4ai2526-uniba/Hopcroft`
+
+The API documentation will be accessible at:
+`https://huggingface.co/spaces/se4ai2526-uniba/Hopcroft/docs`
+
+--------
+
 ## Demo UI (Streamlit)
 
 The Streamlit GUI provides an interactive web interface for the skill classification API.