from flask import Flask, request, jsonify
from sklearn.linear_model import LinearRegression
import numpy as np

app = Flask(__name__)

# 1. Create a simple dataset (X = Input, y = Output)
# We are teaching the model that y is roughly 2 times X
X = np.array([[1], [2], [3], [4], [5]])
y = np.array([2, 4, 6, 8, 10])

# 2. Train the model
model = LinearRegression()
model.fit(X, y)

@app.route('/')
def home():
    return "ML API is running! Use the /predict endpoint."

@app.route('/predict', methods=['GET'])
def predict():
    try:
        # Get the 'value' parameter from the URL (e.g., /predict?value=10)
        user_input = request.args.get('value')
        
        if user_input is None:
            return jsonify({"error": "Please provide a 'value' parameter"}), 400
            
        prediction = model.predict([[float(user_input)]])
        
        return jsonify({
            "input": user_input,
            "prediction": prediction[0]
        })
    except Exception as e:
        return jsonify({"error": str(e)}), 500

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)