python==3.11.5
pandas==2.2.1
scikit_learn==1.3.2
torch==2.1.0+cu118
tqdm==4.66.1
ucimlrepo==0.0.3
fastapi==0.110.1

Install dependencies

pip install -r requirements.txt

You may also want to install uvicorn to run the web server:

pip install uvicorn[standard]

Then, create the model using

python create_model.py

If you are using uvicorn, run the web server using the following:

uvicorn main:app --reload

To make an API call, make a POST request to /predict with a body like the following:

{
  "features": [20.44,21.78,133.8,1293,0.0915,0.1131,0.09799,0.07785,0.1618,0.05557,0.5781,0.9168,4.218,72.44,0.006208,0.01906,0.02375,0.01461,0.01445,0.001906,24.31,26.37,161.2,1780,0.1327,0.2376,0.2702,0.1765,0.2609,0.06735]
}

where features is an array of 30 raw feature values.

Such a call should return a diagnosis like the following:

{
  "diagnosis": "M"
}