import os
import datetime

# Define paths relative to IYmtg_Automation/
TRAINING_ROOT = "../IYmtg_Training"
OUTPUT_FILE = "../IYmtg_App_iOS/app_description_update.txt"

if not os.path.exists(TRAINING_ROOT) and os.path.exists("IYmtg_Training"):
    TRAINING_ROOT = "IYmtg_Training"
    OUTPUT_FILE = "IYmtg_App_iOS/app_description_update.txt"

def count_images_in_dir(directory):
    count = 0
    if os.path.exists(directory):
        for root, _, files in os.walk(directory):
            count += len([f for f in files if f.lower().endswith(('.jpg', '.jpeg', '.png'))])
    return count

def get_training_status(count, basic_threshold, advanced_threshold):
    if count == 0:
        return "❌ Inactive (0 images)"
    elif count < basic_threshold:
        # Less than 10 per category is generally unstable
        return f"⚠️ Experimental ({count} images - Needs {basic_threshold}+)"
    elif count < advanced_threshold:
        return f"✅ Basic ({count} images - Functional)"
    else:
        return f"🌟 Advanced ({count} images - High Accuracy)"

def main():
    print("Generating App Description Update...")
    
    # 1. Analyze Models
    foil_count = count_images_in_dir(os.path.join(TRAINING_ROOT, "Foil_Data"))
    stamp_count = count_images_in_dir(os.path.join(TRAINING_ROOT, "Stamp_Data"))
    cond_count = count_images_in_dir(os.path.join(TRAINING_ROOT, "Condition_Data"))
    
    # Set Symbols might be in Automation folder or Training folder
    set_sym_count = count_images_in_dir(os.path.join(TRAINING_ROOT, "Set_Symbol_Training"))
    if set_sym_count == 0:
        set_sym_count = count_images_in_dir("Set_Symbol_Training")

    # 2. Build Report
    lines = []
    lines.append(f"IYmtg System Status - {datetime.date.today().strftime('%B %d, %Y')}")
    lines.append("==================================================")
    lines.append("")
    lines.append("🧠 AI MODEL STATUS")
    # Foil: 13 Classes. Min 130 (10/class), Adv 650 (50/class)
    lines.append(f"• Foil Classification:   {get_training_status(foil_count, 130, 650)}")
    # Stamp: 2 Classes. Min 20 (10/class), Adv 100 (50/class)
    lines.append(f"• Promo Stamp Detection: {get_training_status(stamp_count, 20, 100)}")
    # Condition: 13 Classes. Min 130, Adv 650
    lines.append(f"• Condition Grading:     {get_training_status(cond_count, 130, 650)}")
    # Sets: Hundreds. Min 500, Adv 2000
    lines.append(f"• Set Symbol Recog:      {get_training_status(set_sym_count, 500, 2000)}")
    lines.append("")
    lines.append("👁️ IDENTIFICATION CAPABILITIES")
    lines.append("• Standard Cards:        ✅ Active (Vector Fingerprinting)")
    lines.append("• Alpha vs Beta:         ✅ Active (Corner Radius Detection)")
    lines.append("• Unlimited vs Revised:  ✅ Active (Saturation Analysis)")
    lines.append("• The List / Mystery:    ✅ Active (Symbol Detection)")
    lines.append("• World Champ Decks:     ✅ Active (Gold Border Detection)")
    lines.append("• Chronicles Reprints:   ✅ Active (Border Color Logic)")
    lines.append("• Serialized Cards:      ✅ Active (OCR Number Pattern)")
    lines.append("• Summer Magic (Edgar):  ✅ Active (OCR Copyright Date)")
    lines.append("")
    lines.append("📝 NOTE TO REVIEWER")
    lines.append("This build includes updated ML models based on the dataset sizes listed above.")
    lines.append("Features marked 'Inactive' will fallback to manual entry or basic heuristics.")
    
    # 3. Write to File
    try:
        with open(OUTPUT_FILE, "w", encoding="utf-8") as f:
            f.write("\n".join(lines))
        print(f"Success! Description saved to: {os.path.abspath(OUTPUT_FILE)}")
    except Exception as e:
        print(f"Error writing report: {e}")

if __name__ == "__main__":
    main()