# app.py
from flask import Flask, request, jsonify
from flask_cors import CORS
import joblib
import numpy as np

app = Flask(__name__)
CORS(app)  # enable Cross-Origin for frontend

# Load the trained model
model = joblib.load('crop_predictor1.pkl')

@app.route('/')
def home():
    return "Crop Predictor API is running"

@app.route('/predict', methods=['POST'])
def predict():
    data = request.get_json()
    
    try:
        # Extract input features
        N = float(data['N'])
        P = float(data['P'])
        K = float(data['K'])
        temperature = float(data['temperature'])
        humidity = float(data['humidity'])
        rainfall=float(data['rainfall'])
        ph=float(data['ph'])

        # Predict
        features = np.array([[N, P, K, temperature, humidity,rainfall,ph]])
        prediction = model.predict(features)

        return jsonify({'predicted_crop': prediction[0]})

    except Exception as e:
        return jsonify({'error': str(e)}), 400

if __name__ == '__main__':
    app.run(debug=True)