Rockfall Prediction API

Simple FastAPI app that loads a scikit-learn pipeline from full_rockfall_pipeline.pkl and exposes a /predict endpoint.

Quick start

1. Create a virtual environment and install dependencies:

python -m venv .venv; .\.venv\Scripts\Activate.ps1; pip install -r requirements.txt

2. Set an API key (optional) and run on port 8002 (default):

$env:API_KEY = "changeme"; python .\main.py

3. Example request (replace with your feature JSON):

Invoke-RestMethod -Method Post -Uri http://localhost:8002/predict -Headers @{"access_token"="changeme"} -Body (@{data=@{feature1=1; feature2=2}} | ConvertTo-Json)

Notes

• Place full_rockfall_pipeline.pkl next to main.py.
• Set API_PORT to change the local port. Defaults to 8002 to avoid conflicts with other APIs.