from machine import Pin
import time

# ---------------------------------------------------------
# 1. HARDWARE SETUP
# ---------------------------------------------------------
# Button: GP22 to GND (PULL_UP logic)
button = Pin(  22, Pin.IN, Pin.PULL_UP)
# LEDs: GP27 (Red) and GP17 (Green)
red_led = Pin(27, Pin.OUT)
green_led = Pin(17, Pin.OUT)

file_name = "attendance.csv"

# ---------------------------------------------------------
# 2. DRINKS DATABASE (Numeric & Categorical)
# ---------------------------------------------------------
drinks = [
    {"Name": "Orange Juice", "Type": "Fruit", "Sugar": 20, "Cals": 120},
    {"Name": "Apple Juice", "Type": "Fruit", "Sugar": 25, "Cals": 130},
    {"Name": "Green Tea", "Type": "Tea", "Sugar": 0, "Cals": 5},
    {"Name": "Coffee", "Type": "Coffee", "Sugar": 2, "Cals": 10},
    {"Name": "Chocolate Milk", "Type": "Milk", "Sugar": 22, "Cals": 150},
    {"Name": "Water", "Type": "None", "Sugar": 0, "Cals": 0}
]

# ---------------------------------------------------------
# 3. AI & ANALYSIS FUNCTIONS
# ---------------------------------------------------------

# Feature: Analyze popularity from previous logs
def get_popular_drinks():
    popularity = {}
    try:
        with open(file_name, "r") as f:
            for line in f:
                parts = line.strip().split(",")
                if len(parts) >= 4:
                    # Assuming the 4th column (index 3) is the choice
                    chosen = parts[3] 
                    popularity[chosen] = popularity.get(chosen, 0) + 1
    except:
        pass # If file doesn't exist yet
    return popularity

# Feature: Multi-factor Recommendation Engine
def smart_recommend(pref_type, health_pref):
    pop_data = get_popular_drinks()
    recommendations = []
    
    # Normalize inputs for better matching
    p_type = pref_type.lower().strip()
    h_pref = health_pref.lower().strip()

    for d in drinks:
        score = 0
        reasons = []

        # Logic A: Preference Match (+3 pts)
        if p_type in d["Type"].lower():
            score += 3
            reasons.append("Matches your style")

        # Logic B: Health Logic (Numeric Analysis) (+3 pts)
        if h_pref == "low sugar" and d["Sugar"] < 5:
            score += 3
            reasons.append("Healthy low-sugar option")
        elif h_pref == "low calories" and d["Cals"] < 50:
            score += 3
            reasons.append("Low-calorie choice")
        elif h_pref == "low" and (d["Sugar"] < 5 or d["Cals"] < 50):
            score += 2
            reasons.append("General healthy pick")

        # Logic C: Social Proof (Popularity Boost) (+1 pt)
        if d["Name"] in pop_data:
            score += 1
            reasons.append("Popular among guests")

        recommendations.append({
            "Name": d["Name"],
            "Score": score,
            "Reason": " & ".join(reasons) if reasons else "Safe choice"
        })

    # Sort: Highest score first
    recommendations.sort(key=lambda x: x["Score"], reverse=True)
    return recommendations[:3]

# ---------------------------------------------------------
# 4. MAIN OPERATIONAL LOOP
# ---------------------------------------------------------
print("="*45)
print("  SMART AI GUEST SYSTEM - FULL VERSION")
print("="*45)

while True:
    # --- STANDBY MODE ---
    green_led.value(0) 
    red_led.value(1)   
    print("\n[READY] System Waiting... Press the button to start.")

    # Wait for button press (Value 0 means connected to GND)
    while button.value() == 1:
        time.sleep(0.05)

    # --- ACTIVE MODE ---
    red_led.value(0)
    green_led.value(1)
    print("\n[EVENT] Guest detected! Initializing AI Analysis...")

    # Data Input
    name = input("  > Guest Name: ").strip()
    p_drink = input("  > Drink Pref (Fruit/Tea/Milk/Coffee): ")
    p_health = input("  > Health (Low Sugar/Low Calories/None): ")

    # Run AI Logic
    results = smart_recommend(p_drink, p_health)
    top_pick = results[0]["Name"]

    # Save to CSV
    try:
        with open(file_name, "a") as f:
            f.write("{},{},{},{}\n".format(name, p_drink, p_health, top_pick))
        print("✅ Data successfully logged to attendance.csv")
    except Exception as e:
        print("❌ Data Error:", e)

    # Display Smart Recommendations
    print("\n" + "-"*40)
    print("AI TOP RECOMMENDATIONS FOR {}:".format(name.upper()))
    for i, res in enumerate(results, 1):
        print("{}. {} (Score: {})".format(i, res["Name"], res["Score"]))
        print("   Reason: {}".format(res["Reason"]))
    print("-" * 40)

    # Finish Animation (Green Blinking)
    print("\nProcessing complete. Resetting...")
    for _ in range(3):
        green_led.value(0); time.sleep(0.2)
        green_led.value(1); time.sleep(0.2)
    
    time.sleep(1) # Pause before returning to Red LED