API

The Insurance Prediction API provides programmatic access to the machine learning model for predicting insurance costs.

Endpoints

/predict_api (POST)

Predicts insurance costs based on input parameters.

Request Format:

POST /predict_api
Content-Type: application/json

{
  "age": 25,
  "sex": "male",
  "bmi": 22.5,
  "children": 0,
  "smoker": "no",
  "region": "southwest"
}

Parameters:

• age (integer): Patient’s age (18-65)

• sex (string): “male” or “female”

• bmi (float): Body Mass Index (15.0-55.0)

• children (integer): Number of children (0-5)

• smoker (string): “yes” or “no”

• region (string): “southwest”, “southeast”, “northwest”, or “northeast”

Response Format:

HTTP 200 OK
Content-Type: application/json

3250

Response: Integer representing expected insurance cost in dollars.

Error Responses:

• 400 Bad Request: Invalid input parameters or missing required fields

• 500 Internal Server Error: Model prediction failure

Request Examples

To send a request to the API using the example script:

python src/api_call_example.py

This will make a POST request to http://localhost:5000/predict_api with sample data and print the predicted insurance cost.

Custom Requests with curl:

curl -X POST http://localhost:5000/predict_api \
  -H "Content-Type: application/json" \
  -d '{
    "age": 35,
    "sex": "female",
    "bmi": 28.5,
    "children": 2,
    "smoker": "yes",
    "region": "northeast"
  }'

Python Requests:

import requests

url = 'http://localhost:5000/predict_api'
data = {
    'age': 35,
    'sex': 'female',
    'bmi': 28.5,
    'children': 2,
    'smoker': 'yes',
    'region': 'northeast'
}

response = requests.post(url, json=data)
prediction = response.json()
print(f'Expected insurance cost: ${prediction}')