app.py

from fastapi import FastAPI, Form, Depends, Request
from fastapi.encoders import jsonable_encoder
from fastapi.responses import JSONResponse
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
import pickle

app = FastAPI()

# Add CORS middleware
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],  
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# Load the pre-trained model
with open('insurance_model.pkl', 'rb') as model_file:
    model = pickle.load(model_file, encoding='bytes')

class Req(BaseModel):
    age: int
    sex: int
    smoker: int
    bmi: float
    children: int
    region: int

class Resp(BaseModel):
    age: int
    sex: str
    smoker: str
    bmi: float
    children: int
    region: str
    insurance_cost: float

@app.get("/")
async def root():
    return {"message": "Hello World. Welcome to FastAPI!"}

def form_req(age: str = Form(...), sex: str = Form(...), smoker: str = Form(...),
             bmi: str = Form(...), children: str = Form(...), region: str = Form(...)):
    sBmi = bmi.replace(",", ".")
    return Req(age=int(age), sex=int(sex), smoker=int(smoker), bmi=float(sBmi), children=int(children), region=int(region))

def get_region_name(region_code):
    region_mapping = {
        0: "Northeast",
        1: "Northwest",
        2: "Southeast",
        3: "Southwest"
    }
    return region_mapping.get(region_code, "Unknown")

@app.post("/predict")
async def predict(request: Request, requess: Req = Depends(form_req)):
    '''
    Predict the insurance cost based on user inputs
    and render the result to the html page
    '''
    age = requess.age
    sex = requess.sex
    smoker = requess.smoker
    bmi = requess.bmi
    children = requess.children
    region = requess.region
    data = []

    data.append(int(age))
    data.extend([int(sex)])
    data.extend([float(bmi)])
    data.extend([int(children)])
    data.extend([int(smoker)])
    data.extend([int(region)])

    prediction = model.predict([data])
    output = round(prediction[0], 2)

    sex = "Male" if requess.sex == 1 else "Female"
    smoker = "Yes" if requess.smoker == 1 else "No"

    # Render index.html with prediction results
    json_compatible_resp_data = jsonable_encoder(Resp(
        age=requess.age,
        sex=sex,
        smoker=smoker, 
        bmi=requess.bmi,
        children=requess.children,
        region=get_region_name(requess.region),
        insurance_cost=output
    ))
    return JSONResponse(content=json_compatible_resp_data)