app.py

from fastapi import FastAPI 
from pydantic import BaseModel
import joblib
import numpy as np

app = FastAPI()

class InputData(BaseModel):
    input1 : bool
    input2 : float
    input3 : float
    input4 : float
    input5 : float
    input6 : float
    input7 : float 

try: 
    model = joblib.load('random_forest_model.joblib')
    status = 'Loaded'
except:
    status = "not loaded"

@app.get('/')
def health_check():
    return {'status' : f'{status}'}

@app.post('/predict')
def predict(input : InputData):
    data = np.array([[input.input1, input.input2,
    input.input3, input.input4,
    input.input5, input.input6,
    input.input7]])
    prediction = model.predict(data).tolist()
    return {'prediction' : f'prediction[0]'}