README.md

metadata

title: UFO Web
emoji: 🛸
colorFrom: blue
colorTo: green
sdk: streamlit
sdk_version: 1.58.0
app_file: app.py
pinned: false

UFO Country Predictor

Session 406 machine-learning web app practice project. It predicts the likely reporting country for a UFO sighting from duration, latitude, and longitude.

Project Structure

UFO_local/
├── app.py                 # Hugging Face Spaces Streamlit app
├── backend.py             # FastAPI backend for local deployment practice
├── frontend.py            # Streamlit frontend that calls the FastAPI backend
├── requirements.txt
├── ufo-model.pkl
└── course_materials/      # Session 406 task guide and original Flask reference

Local FastAPI + Streamlit Workflow

Install dependencies:

conda activate session406
pip install -r requirements.txt

Start the FastAPI backend:

uvicorn backend:app --reload --host 127.0.0.1 --port 8001

Start the Streamlit frontend in another terminal:

streamlit run frontend.py --server.address 127.0.0.1 --server.port 8501

Open:

http://127.0.0.1:8501

Hugging Face Spaces Workflow

Hugging Face Spaces runs app.py directly as a single Streamlit app. This version loads ufo-model.pkl itself, so it does not need the FastAPI backend.

Create or open the Space:

https://huggingface.co/spaces/Coco-Spot/UFO-web

Push this project to the Space repository:

git remote add hf https://huggingface.co/spaces/Coco-Spot/UFO-web
git push hf main

When prompted, use your Hugging Face username and a write token from:

https://huggingface.co/settings/tokens

Course Materials

The original session files are kept in course_materials/session-406-ml-app/, including the UFO Flask practice guide, original solution, data file, and task roadmap.