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| title: HousingModel Server | |
| emoji: 🚀 | |
| colorFrom: red | |
| colorTo: red | |
| sdk: docker | |
| app_port: 8501 | |
| tags: | |
| - streamlit | |
| pinned: false | |
| short_description: Streamlit template space | |
| license: mit | |
| ## HousingModel Streamlit Server | |
| This service is the frontend UI for the California Housing MLOps project. | |
| It provides an interactive interface for single and batch inference by calling the backend API in `app/ml_service`. | |
| ## What This Component Does | |
| - Displays backend/API health and model status | |
| - Allows reloading the backend model alias from the UI | |
| - Supports single-record prediction | |
| - Supports batch prediction using JSON input | |
| - Validates payload shape before sending requests | |
| - Shows summary statistics and tabular batch results | |
| ## Architecture Role | |
| This server is a presentation layer only: | |
| - It does not train models | |
| - It does not host the model artifact | |
| - It communicates with FastAPI backend endpoints over HTTP | |
| Flow: | |
| 1. User submits input in Streamlit | |
| 2. Streamlit calls ml_service endpoint | |
| 3. FastAPI runs model inference | |
| 4. Streamlit renders response | |
| ## Backend API Contract | |
| Expected backend endpoints: | |
| - `GET /health` | |
| - `GET /model_info` | |
| - `POST /reload_model` | |
| - `POST /predict` | |
| - `POST /predict_batch` | |
| If any endpoint is unavailable, the UI will show a safe, user-friendly error. | |
| ## Environment Configuration | |
| For Docker Compose usage, this service reads variables from `app/app.env`. | |
| For standalone local Python runs, export variables in your shell before starting Streamlit. | |
| Primary variables: | |
| - `BACKEND_URL`: Base URL of FastAPI inference service | |
| - `API_BASE_URL`: Optional fallback for backend base URL | |
| Resolution order: | |
| 1. `BACKEND_URL` | |
| 2. `API_BASE_URL` | |
| 3. Default `http://localhost:8000` | |
| Example: | |
| ```env | |
| BACKEND_URL=https://your-ml-service.example.com | |
| ``` | |
| ## Running Locally | |
| From `app/server`: | |
| ```sh | |
| python -m pip install -r requirements.txt | |
| python -m streamlit run app.py | |
| ``` | |
| Open: | |
| - `http://localhost:8501` | |
| ## Running with Docker | |
| Build: | |
| ```sh | |
| docker build -t housing-streamlit-ui . | |
| ``` | |
| Run: | |
| ```sh | |
| docker run --rm -p 8501:8501 \ | |
| -e BACKEND_URL=http://host.docker.internal:8000 \ | |
| housing-streamlit-ui | |
| ``` | |
| ## UI Features | |
| ### Sidebar | |
| - API health check button | |
| - Reload model button | |
| - API status and model loaded metrics on one row | |
| - Model metadata (name/version) | |
| ### Single Prediction Tab | |
| - Structured numeric and categorical inputs | |
| - Sends payload to `POST /predict` | |
| - Displays formatted single prediction result | |
| ### Batch Prediction Tab | |
| - Accepts JSON array input | |
| - Validates required fields and types | |
| - Sends payload to `POST /predict_batch` | |
| - Displays min/max/average and detailed result table | |
| ## Validation and Error Handling | |
| Implemented safeguards in `app.py`: | |
| - Sanitized API error messages (no infrastructure leakage) | |
| - Request timeout handling | |
| - Connection and backend availability checks | |
| - Input shape/type validation for batch payloads | |
| - Clear warning when backend is unreachable on startup | |
| ## Troubleshooting | |
| ### "Cannot connect to backend" | |
| - Ensure `BACKEND_URL` points to running `ml_service` | |
| - Check CORS/networking/reverse proxy rules | |
| - Verify backend health endpoint manually | |
| ### "Method Not Allowed" on reload | |
| - Usually indicates redirect/method mismatch at gateway | |
| - Ensure backend exposes `POST /reload_model` and proxy preserves method on redirects | |
| ### "Backend service is not responding" | |
| - Model reload can take longer due to MLflow artifact loading | |
| - Keep backend reachable and increase request timeout if needed | |
| ## Security Notes | |
| - Do not expose internal backend URLs in UI | |
| - Do not display raw backend response bodies with sensitive content | |
| - Keep secrets in `app.env`, not source files | |
| ## Related Components | |
| - Backend inference API: `app/ml_service` | |
| - Training/promotion pipeline: `training_and_promotion` | |