api.py

from fastapi import FastAPI
from pydantic import BaseModel
from joblib import load
import pandas as pd
import json
import uvicorn

app = FastAPI()

model = load('my-model2')

class user_input(BaseModel):
    satisfaction_level  : float
    last_evaluation     : float
    number_project      : int
    average_montly_hours: int
    time_spend_company  : int
    Work_accident       : int
   
    promotion_last_5years: int
    departments          : str
    salary              : str

def predict(data):
    departments_list = ['IT', 'RandD', 'accounting', 'hr', 'management', 'marketing', 'product_mng', 'sales', 'support', 'technical']
    data[-2] = departments_list.index(data[-2])
    salaries = ['low', 'medium', 'high']
    data[-1] = salaries.index(data[-1])

    columns = ['satisfaction_level', 'last_evaluation', 
                'number_project', 'average_montly_hours', 'time_spend_company', 
                'Work_accident', 'promotion_last_5years','departments', 'salary']
    #d = dict(zip(columns, data))
    
    prediction = model.predict( pd.DataFrame([data], columns= columns))
                                 
    
    proba = model.predict_proba(pd.DataFrame([data], columns= columns))
                                             
    return prediction, proba


@app.get('/')
async def welcome():
    return f'Welcome to HR api'


@app.post('/predict')
async def func(Input:user_input):
    data = [Input.satisfaction_level, Input.last_evaluation, Input.number_project, Input.average_montly_hours, Input.time_spend_company, Input.Work_accident, Input.promotion_last_5years, Input.departments, Input.salary]
    
 
    pred, proba = predict(data)
    output = {'prediction':int(pred[0]), 'probability':float(proba[0][1])}
    
    return json.dumps(output)
if __name__ == "__main__":
    uvicorn.run("hr_analytics_api:app", host="0.0.0.0", port=8000, log_level="info", reload=True)