from flask import Flask, request, jsonify, send_from_directory
from flask_cors import CORS
import joblib
import numpy as np
import xgboost as xgb
import math

app = Flask(__name__, static_folder='.', static_url_path='/')
CORS(app)

# Load models
try:
    rf = joblib.load("rf_model.pkl")
    xgb_model = xgb.Booster()
    xgb_model.load_model("xgb_model.json")
    print("✅ Models loaded successfully.")
except Exception as e:
    print(f"❌ Error loading models: {e}")
    raise e

# Hardcoded product catalog
tile_catalog = [
    {"name": "Travertino Light Beige", "type": "Floor", "price": 780, "coverage": 15.5, "size": "1200x1200 MM", "url": "https://arqonz.ae/products/6775"},
    {"name": "Marquina Glossy Black", "type": "Wall", "price": 620, "coverage": 12.0, "size": "600x600 MM", "url": "https://arqonz.ae/products/6776"},
    {"name": "Carrara White Polished", "type": "Floor", "price": 1100, "coverage": 23.23, "size": "1800x1200 MM", "url": "https://arqonz.ae/products/103"},
    {"name": "Noir Marble Effect", "type": "Wall", "price": 550, "coverage": 6.89, "size": "800x800 MM", "url": "https://arqonz.ae/products/104"},
    {"name": "Sandstone Beige Matte", "type": "Floor", "price": 670, "coverage": 13.78, "size": "1600x800 MM", "url": "https://arqonz.ae/products/6644"},
    {"name": "Onyx Mist Polished", "type": "Wall", "price": 890, "coverage": 15.5, "size": "1200x1200 MM", "url": "https://arqonz.ae/products/6880"},
    {"name": "Terrazzo Pearl", "type": "Floor", "price": 720, "coverage": 7.75, "size": "1200x600 MM", "url": "https://arqonz.ae/products/6878"},
    {"name": "Statuario Silver", "type": "Wall", "price": 660, "coverage": 3.87, "size": "600x600 MM", "url": "https://arqonz.ae/products/6883"},
    {"name": "Grigio Urban", "type": "Floor", "price": 500, "coverage": 2.52, "size": "1200x195 MM", "url": "https://arqonz.ae/products/6653"},
    {"name": "Calacatta Nero", "type": "Wall", "price": 740, "coverage": 10.33, "size": "800x1200 MM", "url": "https://arqonz.ae/products/6885"},
    {"name": "Ivory Rock Slate", "type": "Floor", "price": 690, "coverage": 13.0, "size": "1200x600 MM", "url": "https://arqonz.ae/products/6777"},
    {"name": "Classic White Glossy", "type": "Wall", "price": 580, "coverage": 12.0, "size": "600x600 MM", "url": "https://arqonz.ae/products/89"},
    {"name": "Dark Stone Matte", "type": "Floor", "price": 830, "coverage": 15.0, "size": "1200x600 MM", "url": "https://arqonz.ae/products/107"},
    {"name": "Polished Statuario", "type": "Wall", "price": 810, "coverage": 10.5, "size": "600x1200 MM", "url": "https://arqonz.ae/products/116"}
]

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

@app.route("/recommend", methods=["POST"])
def recommend():
    try:
        data = request.get_json()
        tile_type = data.get("tile_type", "").strip().lower()
        coverage = float(data.get("coverage", 1))
        area = float(data.get("area", 1))
        price_range = data.get("price_range", [3, 10000])
        preferred_sizes = data.get("preferred_sizes", [])

        if area <= 0 or coverage <= 0:
            return jsonify({"error": "Invalid area or coverage"}), 400

        features = prepare_features(tile_type, coverage, area, price_range)
        xgb_pred = xgb_model.predict(xgb.DMatrix(features))[0]
        rf_pred = rf.predict_proba(features)[0][1]
        score = (xgb_pred + rf_pred) / 2

        matches = filter_products(tile_type, price_range, preferred_sizes)

        return jsonify({
            "recommendation_score": round(float(score), 3),
            "recommended_products": matches[:4],
            "total_matches": len(matches)
        })
    except Exception as e:
        print("❌ /recommend error:", e)
        return jsonify({"error": "Server error"}), 500

def prepare_features(tile_type, coverage, area, price_range):
    tile_type_num = 0 if tile_type == "floor" else 1
    min_price, max_price = price_range
    price_per_sqft = max_price / coverage
    efficiency = coverage / max_price
    return np.array([[tile_type_num, area, coverage, min_price, max_price, price_per_sqft, efficiency]])

def filter_products(tile_type, price_range, preferred_sizes):
    min_price, max_price = price_range
    filtered = []
    for p in tile_catalog:
        if p["type"].lower() != tile_type:
            continue
        if not (min_price <= p["price"] <= max_price):
            continue

        size_match = False
        for size in preferred_sizes:
            if similar_size(p["size"], size):
                size_match = True
                break
        if not size_match:
            continue

        price_score = 1 - (p["price"] - min_price) / (max_price - min_price + 1e-6)
        filtered.append({**p, "recommendation_score": round(price_score, 2)})
    return sorted(filtered, key=lambda x: x["recommendation_score"], reverse=True)

def similar_size(size_a, size_b, tolerance=10):
    try:
        w1, h1 = map(int, size_a.lower().replace("mm", "").split("x"))
        w2, h2 = map(int, size_b.lower().replace("mm", "").split("x"))
        return abs(w1 - w2) <= tolerance and abs(h1 - h2) <= tolerance
    except:
        return False

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=7860)