import os
import cv2
import numpy as np
import requests
from flask import Flask, render_template, request, jsonify
from ultralytics import YOLO
from datetime import datetime
import threading

app = Flask(__name__)

# --- CONFIGURATION ---
MICROMIND_API_URL = "https://training.aimicromind.com/api/v1/prediction/606f1092-e94c-42f8-ba6f-09671904a15e"

# GLOBAL SETTINGS
current_settings = {
    "target_class_id": 0,
    "target_label": "person",
    "confidence": 0.5,
    "status": "ARMED"
}

# Load AI Model
print("--- Loading AI Model... ---")
try:
    model = YOLO('yolov8n.pt')
    print("✅ Model Loaded.")
except Exception as e:
    print(f"⚠️ Model download/load warning: {e}")

# Alert sender function
def send_alert(alert_msg):
    """Sends alert in background - fully non-blocking."""
    try:
        requests.post(MICROMIND_API_URL, json={"question": alert_msg}, timeout=5)
        print(f"✅ Alert sent to MicroMind")
    except Exception as e:
        print(f"⚠️ Alert sending failed: {e}")

@app.route('/')
def index():
    """Serves the webpage to the user."""
    return render_template('index.html')

@app.route('/process_frame', methods=['POST'])
def process_frame():
    """Receives an image frame from the browser, runs AI, and returns results."""
    
    if current_settings['status'] == 'DISARMED':
        return jsonify({"status": "DISARMED", "detections": []})

    try:
        # 1. Get Image from Request
        file = request.files['image'].read()
        npimg = np.frombuffer(file, np.uint8)
        img = cv2.imdecode(npimg, cv2.IMREAD_COLOR)

        # 2. Run YOLO AI with optimized settings
        results = model(img, verbose=False, conf=current_settings['confidence'])
        
        detected = False
        detections_list = []

        # 3. Analyze Results
        for result in results:
            for box in result.boxes:
                cls_id = int(box.cls[0])
                conf = float(box.conf[0])
                
                # Check against current settings
                if cls_id == current_settings['target_class_id']:
                    detected = True
                    detections_list.append({
                        "label": current_settings['target_label'],
                        "confidence": round(conf, 2),
                        "bbox": box.xyxy[0].tolist()
                    })

        # 4. Alert MicroMind (Fully Non-blocking)
        if detected:
            print(f"🚨 THREAT: {current_settings['target_label']} detected!")
            
            alert_msg = (f"ALERT: {current_settings['target_label']} detected.\n"
                         f"Source: Cloud Web Cam\n"
                         f"Confidence: {detections_list[0]['confidence']}")
            
            # Send alert in separate thread - fully fire-and-forget
            threading.Thread(
                target=lambda: send_alert(alert_msg),
                daemon=True
            ).start()

        return jsonify({
            "status": "ARMED",
            "target": current_settings['target_label'],
            "detections": detections_list
        })

    except Exception as e:
        print(f"Error: {e}")
        return jsonify({"error": str(e)}), 500

@app.route('/update_settings', methods=['POST'])
def update_settings():
    """Endpoint for MicroMind Agent to change settings."""
    data = request.json
    
    # Simple mapping for demo
    label_map = {
        'person': 0, 'bicycle': 1, 'car': 2, 'motorcycle': 3, 'airplane': 4, 'bus': 5, 'train': 6, 'truck': 7, 'boat': 8,
        'bird': 14, 'cat': 15, 'dog': 16, 'backpack': 24, 'umbrella': 25, 'handbag': 26, 'tie': 27, 'suitcase': 28,
        'bottle': 39, 'cup': 41, 'fork': 42, 'knife': 43, 'spoon': 44, 'bowl': 45, 'banana': 46, 'apple': 47, 'sandwich': 48,
        'chair': 56, 'couch': 57, 'bed': 59, 'dining table': 60, 'laptop': 63, 'mouse': 64, 'remote': 65, 'keyboard': 66,
        'cell phone': 67, 'microwave': 68, 'oven': 69, 'toaster': 70, 'sink': 71, 'refrigerator': 72, 'book': 73,
        'clock': 74, 'vase': 75, 'scissors': 76, 'teddy bear': 77, 'toothbrush': 79
    }

    if 'label' in data:
        new_label = data['label'].lower()
        if new_label in label_map:
            current_settings['target_label'] = new_label
            current_settings['target_class_id'] = label_map[new_label]
    
    if 'confidence' in data:
        current_settings['confidence'] = float(data['confidence'])
        
    if 'status' in data:
        current_settings['status'] = data['status'].upper()

    return jsonify({"status": "success", "current_state": current_settings})

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