app.py

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

# Load model
model = joblib.load("best_rf_model.pkl")

app = Flask(__name__)

@app.route("/")
def home():
    return jsonify({"message": "Random Forest Prediction API is running!"})

@app.route("/predict", methods=["POST"])
def predict():
    try:
        data = request.get_json()

        # Handle both dict (single row) and list of dicts
        if isinstance(data, dict):
            df = pd.DataFrame([data])  # wrap single row
        else:
            df = pd.DataFrame(data)

        predictions = model.predict(df)
        return jsonify({"predictions": predictions.tolist()})
    except Exception as e:
        return jsonify({"error": str(e)})

if __name__ == "__main__":
    port = int(os.environ.get("PORT", 7860))  # Default Hugging Face port
    app.run(host="0.0.0.0", port=port)