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

app = Flask(__name__)

MODEL_PATH = os.environ.get("MODEL_PATH", "random_over_sampling_model.pkl")

def load_model():
    try:
        return joblib.load(MODEL_PATH)
    except FileNotFoundError:
        return None

model = load_model()

def preprocess_input(data):
    data['IMAGES_AND_REVIEWS'] = ((data['IMAGES'] > 0) & (data['REVIEWS'] > 0)).astype(int)
    data['SPECS_AND_REVIEWS'] = ((data['SPECS'] > 0) & (data['REVIEWS'] > 0)).astype(int)
    data['FAQ_AND_IMAGES'] = ((data['FAQ'] > 0) & (data['IMAGES'] > 0)).astype(int)
    data['WARRANTY_AND_SPECS'] = ((data['WARRANTY'] > 0) & (data['SPECS'] > 0)).astype(int)
    data['COMPARE_SIMILAR_AND_SPONSORED_LINKS'] = ((data['COMPARE_SIMILAR'] > 0) & (data['SPONSORED_LINKS'] > 0)).astype(int)
    return data

@app.route("/")
def index():
    return render_template("index.html")

@app.route("/predict", methods=["POST"])
def predict():
    if model is None:
        return jsonify({"error": "Model not loaded. Please ensure the model file exists."}), 500

    try:
        body = request.get_json()
        features = [
            "IMAGES", "REVIEWS", "FAQ", "SPECS", "SHIPPING",
            "BRO_TOGETHER", "COMPARE_SIMILAR", "VIEW_SIMILAR",
            "WARRANTY", "SPONSORED_LINKS"
        ]
        input_data = pd.DataFrame([{f: int(body.get(f, 0)) for f in features}])
        processed = preprocess_input(input_data.copy())

        prediction = int(model.predict(processed)[0])
        probability = None
        if hasattr(model, "predict_proba"):
            proba = model.predict_proba(processed)[0]
            probability = float(proba[1]) if prediction == 1 else float(proba[0])

        return jsonify({
            "prediction": prediction,
            "probability": probability
        })
    except Exception as e:
        return jsonify({"error": str(e)}), 500

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