app.py

import joblib
import pandas as pd
from flask import Flask, request, jsonify
import os

# Load your model
model = joblib.load("knn_diabetes_model.pkl")

app = Flask(__name__)

@app.route("/", methods=["GET"])
def home():
    return jsonify({"status": "API is running", "endpoint": "/predict"})

@app.route("/predict", methods=["POST"])
def predict():
    data = request.json  # expects JSON with same feature names as training
    df = pd.DataFrame(data)
    predictions = model.predict(df)
    return jsonify(predictions.tolist())

if __name__ == "__main__":
    port = int(os.environ.get("PORT", 7860))
    app.run(host="0.0.0.0", port=port, debug=False)