import os
import gradio as gr
import queue
import threading
from concurrent.futures import ThreadPoolExecutor
from ai_alert_generator import AIAlertGenerator, DrowsinessDetectionSystem

class GradioWebRTCInterface:
    """Enhanced Gradio interface with WebRTC support"""
    
    def __init__(self):
        self.detection_system = None
        self.ai_alert_generator = None
        self.processing = False
        
    def initialize_system(self, gemini_key):
        """Initialize the detection system"""
        try:
            self.detection_system = DrowsinessDetectionSystem()
            self.ai_alert_generator = AIAlertGenerator(gemini_key if gemini_key.strip() else None)
            
            return "✅ System initialized successfully!", "🚀 Ready for detection"
        except Exception as e:
            return f"❌ Error: {str(e)}", "❌ Initialization failed"
    
    def process_video_stream(self, frame, gemini_key):
        """Process video stream"""
        if self.detection_system is None:
            self.detection_system = DrowsinessDetectionSystem()
            self.ai_alert_generator = AIAlertGenerator(gemini_key if gemini_key.strip() else None)
        
        try:
            # Process frame
            processed_frame, status_list, should_alert, metrics = self.detection_system.process_frame(frame)
            
            # Generate alert if needed
            alert_text = ""
            alert_audio = None
            
            if should_alert and metrics.get('indicators'):
                alert_text = self.ai_alert_generator.generate_alert_text(
                    metrics['indicators'], 
                    metrics.get('severity', 'medium')
                )
                
                # Create audio alert
                try:
                    audio_file, _ = self.ai_alert_generator.create_audio_alert(alert_text)
                    alert_audio = audio_file
                except Exception as e:
                    print(f"Audio generation error: {e}")
            
            # Format status
            status_text = "\n".join(status_list)
            
            # Get logs
            logs = self.detection_system.get_logs()
            
            return processed_frame, status_text, alert_text, alert_audio, logs
            
        except Exception as e:
            error_msg = f"Processing error: {str(e)}"
            return frame, error_msg, "", None, error_msg
    
    def create_interface(self):
        """Create the Gradio interface with WebRTC support"""
        with gr.Blocks(
            title="🚗 AI Driver Drowsiness Detection System",
            theme=gr.themes.Soft(),
            css="""
            .alert-box { 
                background-color: #ffebee; 
                border: 2px solid #f44336; 
                border-radius: 8px; 
                padding: 10px; 
            }
            .status-box { 
                background-color: #e8f5e8; 
                border: 2px solid #4caf50; 
                border-radius: 8px; 
                padding: 10px; 
            }
            .metric-display { 
                font-family: 'Courier New', monospace; 
                font-size: 14px; 
            }
            .header-text {
                text-align: center;
                background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
                color: white;
                padding: 20px;
                border-radius: 10px;
                margin-bottom: 20px;
            }
            """
        ) as interface:
            
            gr.HTML("""
            <div class="header-text">
                <h1>🚗 Drive Paddy/h1>
                <p><strong>Real-time monitoring with OpenCV, Computer Vision & AI Alerts</strong></p>
            </div>
            """)
            
            with gr.Tab("🎥 Live Detection"):
                with gr.Row():
                    with gr.Column(scale=2):
                        # WebRTC video input
                        webcam_options = gr.WebcamOptions(mirror=False)
                        video_input = gr.Video(
                            label="📹 Camera Feed (WebRTC Streaming)",
                            sources=["webcam"],
                            streaming=True,
                            webcam_options=webcam_options,
                            height=480
                        )
                        
                        # System controls
                        with gr.Row():
                            gemini_key = os.getenv("GEMINI_API_KEY")
                            init_btn = gr.Button("🚀 Initialize", variant="primary", scale=1)
                    
                    with gr.Column(scale=1):
                        # System status
                        init_status = gr.Textbox(
                            label="🔧 System Status",
                            interactive=False,
                            lines=2,
                            elem_classes=["status-box"]
                        )
                        
                        # Detection metrics
                        current_status = gr.Textbox(
                            label="📊 Detection Metrics",
                            interactive=False,
                            lines=8,
                            elem_classes=["metric-display"]
                        )
                        
                        # Alert display
                        alert_text_display = gr.Textbox(
                            label="🚨 Active Alert",
                            interactive=False,
                            lines=3,
                            elem_classes=["alert-box"]
                        )
                        
                        # Audio alert output
                        alert_audio = gr.Audio(
                            label="🔊 Alert Sound",
                            autoplay=True,
                            visible=True
                        )
                
                # System logs panel
                with gr.Row():
                    system_logs = gr.Textbox(
                        label="📝 System Activity Log",
                        lines=6,
                        interactive=False,
                        elem_classes=["metric-display"]
                    )
            
            with gr.Tab("⚙️ System Configuration"):
                with gr.Row():
                    with gr.Column():
                        gr.Markdown("""
                        ### 🔧 Detection Parameters
                        
                        **Current OpenCV-based thresholds:**
                        - **Eye Aspect Ratio (EAR)**: < 0.20 for 15+ frames
                        - **Mouth Aspect Ratio (MAR)**: > 0.8 for 10+ frames  
                        - **Head Nod Angle**: > 20° deviation for 8+ frames
                        - **Alert Cooldown**: 8 seconds between alerts
                        
                        ### 🎯 Detection Methods
                        - **Primary**: MediaPipe Face Mesh (if available)
                        - **Fallback**: OpenCV Haar Cascades
                        - **No external downloads**: Uses built-in OpenCV models
                        """)
                    
                    with gr.Column():
                        gr.Markdown("""
                        ### 📋 Easy Setup
                        
                        **Install dependencies:**
                        ```bash
                        pip install opencv-python gradio numpy scipy google-generativeai
                        
                        # Optional for better detection:
                        pip install mediapipe
                        ```
                        
                        **No model downloads required!**
                        - Uses OpenCV's built-in face detection
                        - MediaPipe auto-detects if available
                        - Gemini API key is optional for AI alerts
                        """)
                
                gr.Markdown("""
                ### 🚀 Advanced Features
                - **Real-time WebRTC Processing**: Low latency video streaming
                - **Multi-modal Detection**: Eyes, mouth, and head pose analysis
                - **AI-Powered Alerts**: Contextual voice messages via Gemini
                - **Adaptive Fallback**: Graceful degradation without external models
                - **Visual Feedback**: Live metrics overlay on video
                - **Comprehensive Logging**: Detailed activity tracking
                """)
            
            with gr.Tab("📊 Detection Info"):
                gr.Markdown("""
                ### 👁️ Eye Aspect Ratio (EAR)
                
                **How it works:**
                - Calculates ratio of eye height to width
                - Lower values indicate closed/closing eyes
                - Triggers alert when consistently low
                
                **Detection method:**
                - **MediaPipe**: Uses precise eye landmarks
                - **OpenCV**: Estimates from eye rectangles
                
                ### 👄 Mouth Aspect Ratio (MAR)
                
                **Yawn detection:**
                - Measures mouth opening relative to width
                - Higher values indicate yawning
                - Accounts for talking vs. yawning patterns
                
                ### 📐 Head Pose Estimation
                
                **Nodding detection:**
                - Tracks head tilt and position
                - Detects forward head movement
                - Uses nose-chin alignment for pose estimation
                
                ### 🧠 AI Alert Generation
                
                **Smart alerts:**
                - Context-aware messages via Gemini
                - Severity-based escalation
                - Fallback to audio beeps
                - Cooldown prevents alert spam
                """)
            
            # Event handlers
            init_btn.click(
                fn=self.initialize_system,
                inputs=[gemini_key],
                outputs=[init_status, alert_text_display]
            )
            
            # WebRTC stream processing
            video_input.stream(
                fn=self.process_video_stream,
                inputs=[video_input, gemini_key],
                outputs=[video_input, current_status, alert_text_display, alert_audio, system_logs],
                stream_every=0.1,  # 10 FPS processing
                show_progress=False
            )
            
            # Safety notice
            gr.HTML("""
            <div style="margin-top: 20px; padding: 15px; background: linear-gradient(135deg, #ffeaa7 0%, #fab1a0 100%); border-radius: 8px; border-left: 5px solid #e17055;">
                <h3>⚠️ Important Safety Notice</h3>
                <p><strong>This system is for demonstration and research purposes only.</strong></p>
                <ul style="margin: 10px 0;">
                    <li><strong>Not a substitute</strong> for responsible driving practices</li>
                    <li><strong>Pull over safely</strong> if you feel drowsy while driving</li>
                    <li><strong>Ensure proper setup</strong>: good lighting, stable camera position</li>
                    <li><strong>Use as supplementary tool</strong> alongside other safety measures</li>
                </ul>
                <p style="margin-top: 15px;"><em>Always prioritize real-world driving safety over technology assistance.</em></p>
            </div>
            """)
        
        return interface