AT2 API Repository (placeholder)

This repository contains the FastAPI application for serving the trained models for the AT2 assignment.

Structure:

• app/main.py : FastAPI application (endpoints per brief)
• models/ : place trained joblib models here (rain_class_baseline.joblib and precip_reg_baseline.joblib)
• requirements.txt, Dockerfile

Quick start (local):

1. Create virtualenv and install: python3 -m venv .venv source .venv/bin/activate pip install -r requirements.txt

2. Run the API: uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

Endpoints:

• GET / -> project overview
• GET /health/ -> health check
• GET /predict/rain/?date=YYYY-MM-DD -> classification prediction for date+7
• GET /predict/precipitation/fall?date=YYYY-MM-DD -> precipitation prediction (next 3 days)

Deployment:

• Build Docker image: docker build -t at2-api .
• Run: docker run -p 8000:8000 at2-api

Notes:

• Place trained models into models/ before deploying for real inference.
• This template returns deterministic placeholders if models are not present.