Create app.py

app.py

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+#!/usr/bin/env python3
+"""
+VoiceBridge.AI - Production Ready Universal Communication Platform
+Supporting: Blind, Deaf, Non-Verbal, Deaf-Blind Users
+"""
+
+import gradio as gr
+import speech_recognition as sr
+import pyttsx3
+import threading
+import time
+import json
+import tempfile
+import os
+import logging
+from datetime import datetime
+from pathlib import Path
+import torch
+from transformers import pipeline
+import cv2
+import numpy as np
+import requests
+from typing import Dict, List, Optional, Tuple
+
+# Configure logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+class ProductionVoiceBridge:
+    """
+    Production-grade universal communication system for all disabilities
+    """
+    
+    def __init__(self):
+        self.setup_directories()
+        self.load_config()
+        self.initialize_engines()
+        self.current_mode = "universal"
+        self.user_preferences = {}
+        self.conversation_history = []
+        self.emergency_contacts = []
+        
+    def setup_directories(self):
+        """Create necessary directories for production"""
+        Path("data/conversations").mkdir(parents=True, exist_ok=True)
+        Path("data/emergency").mkdir(parents=True, exist_ok=True)
+        Path("data/user_profiles").mkdir(parents=True, exist_ok=True)
+        
+    def load_config(self):
+        """Load production configuration"""
+        self.config = {
+            "api_timeout": 30,
+            "max_audio_length": 60,
+            "emergency_check_interval": 5,
+            "backup_interval": 300,
+            "supported_languages": ["en", "es", "fr", "de"],
+            "haptic_patterns": {
+                "emergency": [500, 200, 500],
+                "notification": [200],
+                "confirmation": [100, 100],
+                "error": [100, 50, 100, 50, 100]
+            }
+        }
+        
+    def initialize_engines(self):
+        """Initialize all AI engines and hardware interfaces"""
+        try:
+            # Text-to-Speech Engine
+            self.tts_engine = pyttsx3.init()
+            voices = self.tts_engine.getProperty('voices')
+            self.tts_engine.setProperty('voice', voices[0].id)
+            self.tts_engine.setProperty('rate', 160)
+            self.tts_engine.setProperty('volume', 0.8)
+            
+            # Speech Recognition
+            self.recognizer = sr.Recognizer()
+            self.microphone = sr.Microphone()
+            with self.microphone as source:
+                self.recognizer.adjust_for_ambient_noise(source, duration=1)
+            
+            # AI Models with error handling
+            self.load_ai_models()
+            
+            # Emergency system
+            self.emergency_mode = False
+            self.last_emergency_check = time.time()
+            
+            logger.info("All engines initialized successfully")
+            
+        except Exception as e:
+            logger.error(f"Engine initialization failed: {e}")
+            raise
+    
+    def load_ai_models(self):
+        """Load AI models with fallbacks"""
+        try:
+            self.speech_to_text_model = pipeline(
+                "automatic-speech-recognition",
+                model="openai/whisper-base",
+                device=-1  # CPU for reliability
+            )
+        except Exception as e:
+            logger.warning(f"Whisper model failed, using fallback: {e}")
+            self.speech_to_text_model = None
+            
+        try:
+            self.image_caption_model = pipeline(
+                "image-to-text",
+                model="Salesforce/blip-image-captioning-base",
+                device=-1
+            )
+        except Exception as e:
+            logger.warning(f"BLIP model failed, using fallback: {e}")
+            self.image_caption_model = None
+    
+    # ==================== UNIVERSAL MODE ====================
+    
+    def universal_communication(self, input_data: dict) -> dict:
+        """
+        Universal communication handler that adapts to any input type
+        """
+        try:
+            input_type = input_data.get('type', 'voice')
+            
+            if input_type == 'voice' and input_data.get('audio'):
+                return self.handle_voice_input(input_data['audio'])
+                
+            elif input_type == 'text' and input_data.get('text'):
+                return self.handle_text_input(input_data['text'])
+                
+            elif input_type == 'image' and input_data.get('image'):
+                return self.handle_image_input(input_data['image'])
+                
+            elif input_type == 'command':
+                return self.handle_system_command(input_data.get('command', ''))
+                
+            else:
+                return self.create_response(
+                    "Please provide voice, text, or image input",
+                    "error"
+                )
+                
+        except Exception as e:
+            logger.error(f"Universal communication error: {e}")
+            return self.create_response(
+                "System error. Please try again or use emergency mode.",
+                "error"
+            )
+    
+    def handle_voice_input(self, audio_path: str) -> dict:
+        """Process voice input for deaf users and general transcription"""
+        try:
+            # Convert speech to text
+            if self.speech_to_text_model:
+                transcript = self.speech_to_text_model(audio_path)["text"]
+            else:
+                transcript = self.fallback_speech_to_text(audio_path)
+            
+            # Check for emergency keywords
+            if self.detect_emergency_keywords(transcript):
+                emergency_result = self.trigger_emergency_mode("voice_triggered")
+                return self.create_response(
+                    f"EMERGENCY DETECTED: {transcript}\n{emergency_result['message']}",
+                    "emergency",
+                    audio=emergency_result.get('audio'),
+                    visual_alert="🔴 EMERGENCY ACTIVATED"
+                )
+            
+            # Check for system commands
+            if self.is_system_command(transcript):
+                return self.handle_system_command(transcript)
+            
+            # Regular communication
+            self.add_to_conversation("User", transcript)
+            
+            return self.create_response(
+                transcript,
+                "transcription",
+                visual_alert=f"💬 New message: {transcript[:50]}..."
+            )
+            
+        except Exception as e:
+            logger.error(f"Voice input error: {e}")
+            return self.create_response(
+                "Could not process audio. Please try again.",
+                "error"
+            )
+    
+    def handle_text_input(self, text: str) -> dict:
+        """Process text input for non-verbal users"""
+        try:
+            # Check for emergency
+            if self.detect_emergency_keywords(text):
+                emergency_result = self.trigger_emergency_mode("text_triggered")
+                return self.create_response(
+                    f"EMERGENCY: {text}\n{emergency_result['message']}",
+                    "emergency",
+                    audio=emergency_result.get('audio'),
+                    visual_alert="🔴 EMERGENCY"
+                )
+            
+            # Convert to speech
+            audio_path = self.text_to_speech(text)
+            
+            self.add_to_conversation("User", text, "spoken")
+            
+            return self.create_response(
+                text,
+                "communication",
+                audio=audio_path,
+                visual_alert=f"🗣️ Speaking: {text[:30]}..."
+            )
+            
+        except Exception as e:
+            logger.error(f"Text input error: {e}")
+            return self.create_response(
+                "Could not process text. Please try again.",
+                "error"
+            )
+    
+    def handle_image_input(self, image_path: str) -> dict:
+        """Process image input for blind users"""
+        try:
+            if not self.image_caption_model:
+                description = "I see an image but cannot describe it in detail right now."
+            else:
+                description = self.image_caption_model(image_path)[0]['generated_text']
+                # Enhance description
+                description = self.enhance_scene_description(description)
+            
+            # Convert description to speech
+            audio_path = self.text_to_speech(description)
+            
+            return self.create_response(
+                description,
+                "scene_description",
+                audio=audio_path
+            )
+            
+        except Exception as e:
+            logger.error(f"Image input error: {e}")
+            return self.create_response(
+                "Could not process image. Please try again.",
+                "error"
+            )
+    
+    # ==================== DISABILITY-SPECIFIC MODES ====================
+    
+    def blind_mode(self, command: str = None, image_path: str = None) -> dict:
+        """Voice-first interface for blind users"""
+        if not command and not image_path:
+            welcome_msg = (
+                "Blind mode activated. Say 'describe scene' to use camera, "
+                "'read text' for text recognition, or 'help' for options."
+            )
+            return self.create_response(welcome_msg, "system", audio=self.text_to_speech(welcome_msg))
+        
+        if command:
+            command = command.lower()
+            
+            if 'describe' in command or 'scene' in command or image_path:
+                if image_path:
+                    return self.handle_image_input(image_path)
+                else:
+                    return self.create_response(
+                        "Please capture an image using the camera",
+                        "instruction"
+                    )
+                    
+            elif 'read' in command or 'text' in command:
+                return self.create_response(
+                    "Please capture an image containing text",
+                    "instruction"
+                )
+                
+            elif 'navigate' in command or 'direction' in command:
+                guidance = "Navigation assistance: Move forward carefully. Obstacle detection active."
+                return self.create_response(
+                    guidance,
+                    "navigation",
+                    audio=self.text_to_speech(guidance)
+                )
+                
+            elif 'help' in command:
+                help_text = """
+                Blind Mode Commands:
+                • "Describe scene" - Describe surroundings using camera
+                • "Read text" - Read text from images
+                • "Navigate" - Get walking directions
+                • "Emergency" - Immediate assistance
+                • "Change mode" - Switch accessibility mode
+                """
+                return self.create_response(help_text, "help", audio=self.text_to_speech(help_text))
+            
+            else:
+                response = "Command not recognized. Say 'help' for options."
+                return self.create_response(response, "error", audio=self.text_to_speech(response))
+    
+    def deaf_mode(self, audio_input: str = None, continuous: bool = False) -> dict:
+        """Visual interface for deaf users with real-time transcription"""
+        if audio_input:
+            result = self.handle_voice_input(audio_input)
+            
+            # Add visual enhancements for deaf users
+            if result['type'] == 'transcription':
+                result['visual_alert'] = f"👂 TRANSCRIPTION: {result['text'][:100]}..."
+                
+            # Check for important sounds
+            if self.detect_important_sounds(audio_input):
+                result['visual_alert'] = "🔔 IMPORTANT SOUND DETECTED! " + result.get('visual_alert', '')
+                result['haptic_feedback'] = self.config['haptic_patterns']['notification']
+            
+            return result
+        else:
+            status = "Deaf mode active. Real-time transcription ready. Visual alerts enabled."
+            return self.create_response(status, "system", visual_alert="👂 Deaf Mode Active")
+    
+    def non_verbal_mode(self, text: str = None, preset: str = None) -> dict:
+        """Text-to-speech communication for non-verbal users"""
+        if preset:
+            phrases = {
+                'greeting': "Hello, I use this device to communicate",
+                'help': "I need assistance please",
+                'medical': "I have a medical condition and may need help",
+                'emergency': "This is an emergency! I need immediate assistance!",
+                'thanks': "Thank you for your help",
+                'yes': "Yes",
+                'no': "No",
+                'pain': "I am in pain and need medical help",
+                'lost': "I am lost and need directions",
+                'bathroom': "I need to find a bathroom"
+            }
+            text_to_speak = phrases.get(preset, preset)
+        else:
+            text_to_speak = text or "I need help"
+        
+        audio_path = self.text_to_speech(text_to_speak)
+        
+        self.add_to_conversation("User", text_to_speak, "spoken")
+        
+        return self.create_response(
+            text_to_speak,
+            "communication",
+            audio=audio_path,
+            visual_alert=f"🗣️ Speaking: {text_to_speak}",
+            haptic_feedback=self.config['haptic_patterns']['confirmation']
+        )
+    
+    def deaf_blind_mode(self, input_text: str = None, output_format: str = "haptic") -> dict:
+        """Tactile communication for deaf-blind users"""
+        if input_text:
+            if output_format == "haptic":
+                vibration_pattern = self.text_to_vibration_pattern(input_text)
+                return self.create_response(
+                    f"Message converted to vibrations: {input_text}",
+                    "tactile",
+                    haptic_feedback=vibration_pattern,
+                    braille=self.text_to_braille(input_text)
+                )
+            else:  # braille output
+                braille_text = self.text_to_braille(input_text)
+                return self.create_response(
+                    f"Braille output: {input_text}",
+                    "tactile",
+                    braille=braille_text
+                )
+        else:
+            status = "Deaf-blind mode active. Use text input with haptic or braille output."
+            return self.create_response(status, "system")
+    
+    # ==================== EMERGENCY SYSTEM ====================
+    
+    def trigger_emergency_mode(self, trigger_source: str = "manual") -> dict:
+        """Activate emergency response system"""
+        self.emergency_mode = True
+        timestamp = datetime.now().isoformat()
+        
+        emergency_data = {
+            "status": "EMERGENCY_ACTIVATED",
+            "timestamp": timestamp,
+            "trigger_source": trigger_source,
+            "message": "EMERGENCY! Assistance required immediately!",
+            "actions_taken": [],
+            "contacts_notified": []
+        }
+        
+        # Notify emergency contacts
+        for contact in self.emergency_contacts:
+            try:
+                self.notify_emergency_contact(contact, emergency_data)
+                emergency_data["contacts_notified"].append(contact)
+            except Exception as e:
+                logger.error(f"Failed to notify {contact}: {e}")
+        
+        # Create emergency audio message
+        emergency_audio = self.text_to_speech(emergency_data["message"])
+        emergency_data["audio"] = emergency_audio
+        
+        # Log emergency
+        self.log_emergency(emergency_data)
+        
+        return emergency_data
+    
+    def notify_emergency_contact(self, contact: str, emergency_data: dict):
+        """Notify emergency contact (simplified - in production would use SMS/email)"""
+        logger.info(f"EMERGENCY NOTIFICATION to {contact}: {emergency_data['message']}")
+        # In production: send SMS, email, or push notification
+    
+    # ==================== CORE ENGINE METHODS ====================
+    
+    def text_to_speech(self, text: str) -> str:
+        """Convert text to speech and return audio file path"""
+        try:
+            with tempfile.NamedTemporaryFile(delete=False, suffix='.wav', dir='data/') as tmp_file:
+                self.tts_engine.save_to_file(text, tmp_file.name)
+                self.tts_engine.runAndWait()
+                return tmp_file.name
+        except Exception as e:
+            logger.error(f"TTS error: {e}")
+            return None
+    
+    def fallback_speech_to_text(self, audio_path: str) -> str:
+        """Fallback speech recognition using speech_recognition library"""
+        try:
+            with sr.AudioFile(audio_path) as source:
+                audio = self.recognizer.record(source)
+                return self.recognizer.recognize_google(audio)
+        except Exception as e:
+            return f"Could not understand audio: {str(e)}"
+    
+    def detect_emergency_keywords(self, text: str) -> bool:
+        """Detect emergency keywords in text"""
+        emergency_words = [
+            'emergency', 'help', 'urgent', 'danger', 'dangerous', 
+            'accident', 'injured', 'hurt', 'pain', 'bleeding',
+            'fire', 'police', 'ambulance', 'hospital', '911',
+            'save me', 'help me', 'i need help'
+        ]
+        text_lower = text.lower()
+        return any(word in text_lower for word in emergency_words)
+    
+    def detect_important_sounds(self, audio_path: str) -> bool:
+        """Detect important environmental sounds"""
+        # Simplified - in production would use audio analysis
+        # For now, use speech recognition to check for important words
+        try:
+            transcript = self.fallback_speech_to_text(audio_path)
+            important_words = ['help', 'emergency', 'fire', 'watch out', 'danger']
+            return any(word in transcript.lower() for word in important_words)
+        except:
+            return False
+    
+    def text_to_vibration_pattern(self, text: str) -> List[int]:
+        """Convert text to vibration pattern (simplified Morse code)"""
+        morse_code = {
+            'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.',
+            'F': '..-.', 'G': '--.', 'H': '....', 'I': '..', 'J': '.---',
+            'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.', 'O': '---',
+            'P': '.--.', 'Q': '--.-', 'R': '.-.', 'S': '...', 'T': '-',
+            'U': '..-', 'V': '...-', 'W': '.--', 'X': '-..-', 'Y': '-.--', 'Z': '--..',
+            '1': '.----', '2': '..---', '3': '...--', '4': '....-', '5': '.....',
+            '6': '-....', '7': '--...', '8': '---..', '9': '----.', '0': '-----',
+            ' ': ' '
+        }
+        
+        pattern = []
+        for char in text.upper():
+            if char in morse_code:
+                morse = morse_code[char]
+                for symbol in morse:
+                    if symbol == '.':
+                        pattern.extend([100])  # Short vibration
+                    elif symbol == '-':
+                        pattern.extend([300])  # Long vibration
+                    pattern.extend([50])  # Gap between symbols
+                pattern.extend([200])  # Gap between letters
+        
+        return pattern
+    
+    def text_to_braille(self, text: str) -> str:
+        """Convert text to braille unicode characters"""
+        braille_map = {
+            'A': '⠁', 'B': '⠃', 'C': '⠉', 'D': '⠙', 'E': '⠑', 'F': '⠋', 'G': '⠛', 'H': '⠓', 'I': '⠊', 'J': '⠚',
+            'K': '⠅', 'L': '⠇', 'M': '⠍', 'N': '⠝', 'O': '⠕', 'P': '⠏', 'Q': '⠟', 'R': '⠗', 'S': '⠎', 'T': '⠞',
+            'U': '⠥', 'V': '⠧', 'W': '⠺', 'X': '⠭', 'Y': '⠽', 'Z': '⠵',
+            '1': '⠁', '2': '⠃', '3': '⠉', '4': '⠙', '5': '⠑', '6': '⠋', '7': '⠛', '8': '⠓', '9': '⠊', '0': '⠚',
+            ' ': ' ', '.': '⠲', ',': '⠂', '!': '⠖', '?': '⠦'
+        }
+        
+        return ''.join(braille_map.get(char.upper(), '?') for char in text)
+    
+    def enhance_scene_description(self, description: str) -> str:
+        """Enhance AI-generated scene descriptions"""
+        enhancements = {
+            "indoor": "This appears to be an indoor setting. ",
+            "outdoor": "This appears to be an outdoor area. ",
+            "people": "There are people visible. ",
+            "text": "There is text that could be read. ",
+            "obstacle": "Be careful of potential obstacles. ",
+        }
+        
+        enhanced = description
+        desc_lower = description.lower()
+        
+        if any(word in desc_lower for word in ['room', 'indoor', 'inside', 'wall']):
+            enhanced = enhancements["indoor"] + enhanced
+        elif any(word in desc_lower for word in ['outdoor', 'outside', 'sky', 'tree']):
+            enhanced = enhancements["outdoor"] + enhanced
+            
+        if any(word in desc_lower for word in ['person', 'people', 'man', 'woman']):
+            enhanced = enhancements["people"] + enhanced
+            
+        if any(word in desc_lower for word in ['sign', 'text', 'letter', 'word']):
+            enhanced = enhancements["text"] + enhanced
+            
+        return enhanced
+    
+    def is_system_command(self, text: str) -> bool:
+        """Check if text contains system commands"""
+        commands = ['mode', 'help', 'emergency', 'stop', 'cancel', 'reset']
+        return any(command in text.lower() for command in commands)
+    
+    def handle_system_command(self, command: str) -> dict:
+        """Handle system control commands"""
+        command = command.lower()
+        
+        if 'blind' in command:
+            self.current_mode = "blind"
+            response = "Blind mode activated. Voice navigation enabled."
+        elif 'deaf' in command:
+            self.current_mode = "deaf"
+            response = "Deaf mode activated. Visual alerts enabled."
+        elif 'non verbal' in command or 'mute' in command:
+            self.current_mode = "non_verbal"
+            response = "Non-verbal mode activated. Text-to-speech ready."
+        elif 'deaf blind' in command:
+            self.current_mode = "deaf_blind"
+            response = "Deaf-blind mode activated. Haptic feedback enabled."
+        elif 'universal' in command:
+            self.current_mode = "universal"
+            response = "Universal mode activated."
+        elif 'emergency' in command:
+            return self.trigger_emergency_mode("voice_command")
+        else:
+            response = f"Current mode: {self.current_mode}. Say 'help' for options."
+        
+        return self.create_response(response, "system", audio=self.text_to_speech(response))
+    
+    def add_to_conversation(self, speaker: str, text: str, message_type: str = "text"):
+        """Add message to conversation history"""
+        self.conversation_history.append({
+            "timestamp": datetime.now().isoformat(),
+            "speaker": speaker,
+            "text": text,
+            "type": message_type
+        })
+        
+        # Keep only last 100 messages
+        if len(self.conversation_history) > 100:
+            self.conversation_history = self.conversation_history[-100:]
+    
+    def log_emergency(self, emergency_data: dict):
+        """Log emergency event"""
+        try:
+            filename = f"data/emergency/emergency_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json"
+            with open(filename, 'w') as f:
+                json.dump(emergency_data, f, indent=2)
+        except Exception as e:
+            logger.error(f"Failed to log emergency: {e}")
+    
+    def create_response(self, text: str, response_type: str, **kwargs) -> dict:
+        """Create standardized response object"""
+        return {
+            "text": text,
+            "type": response_type,
+            "timestamp": datetime.now().isoformat(),
+            "mode": self.current_mode,
+            "audio": kwargs.get('audio'),
+            "visual_alert": kwargs.get('visual_alert'),
+            "haptic_feedback": kwargs.get('haptic_feedback'),
+            "braille": kwargs.get('braille')
+        }
+
+
+# ==================== GRADIO INTERFACE ====================
+
+def create_production_interface():
+    """Create production-ready Gradio interface"""
+    
+    # Initialize the system
+    voice_bridge = ProductionVoiceBridge()
+    
+    # Custom CSS for accessibility
+    custom_css = """
+    :root {
+        --primary-color: #2563eb;
+        --danger-color: #dc2626;
+        --success-color: #16a34a;
+        --warning-color: #d97706;
+    }
+    
+    .accessible-btn {
+        min-height: 48px !important;
+        min-width: 48px !important;
+        padding: 12px 24px !important;
+        font-size: 16px !important;
+        margin: 4px !important;
+        border: 2px solid !important;
+    }
+    
+    .emergency-btn {
+        background: linear-gradient(45deg, #dc2626, #ef4444) !important;
+        color: white !important;
+        font-weight: bold !important;
+        font-size: 20px !important;
+        animation: pulse 2s infinite !important;
+    }
+    
+    @keyframes pulse {
+        0% { transform: scale(1); opacity: 1; }
+        50% { transform: scale(1.05); opacity: 0.9; }
+        100% { transform: scale(1); opacity: 1; }
+    }
+    
+    .high-contrast {
+        filter: contrast(200%) !important;
+    }
+    
+    .large-text { font-size: 18px !important; }
+    .x-large-text { font-size: 22px !important; }
+    
+    .sr-only {
+        position: absolute !important;
+        width: 1px !important;
+        height: 1px !important;
+        padding: 0 !important;
+        margin: -1px !important;
+        overflow: hidden !important;
+        clip: rect(0, 0, 0, 0) !important;
+        white-space: nowrap !important;
+        border: 0 !important;
+    }
+    
+    @media (max-width: 768px) {
+        .container {
+            padding: 8px !important;
+        }
+        .accessible-btn {
+            min-height: 54px !important;
+            min-width: 54px !important;
+            font-size: 18px !important;
+        }
+    }
+    """
+    
+    with gr.Blocks(
+        css=custom_css,
+        theme=gr.themes.Soft(primary_hue="blue"),
+        title="VoiceBridge AI - Universal Communication",
+        head='<meta name="description" content="Accessibility communication platform for blind, deaf, non-verbal, and deaf-blind users">'
+    ) as demo:
+        
+        # Screen reader announcement area
+        sr_announcement = gr.Textbox(
+            label="Screen Reader Announcements",
+            elem_id="sr-announcement",
+            visible=False
+        )
+        
+        gr.Markdown("""
+        # 🎯 VoiceBridge AI - Universal Communication Platform
+        **Production-Ready Accessibility Solution for All Disabilities**
+        
+        *Supporting: 👁️ Blind Users • 👂 Deaf Users • 🤐 Non-Verbal Users • 👁️👂 Deaf-Blind Users*
+        """)
+        
+        # System Status Bar
+        with gr.Row():
+            system_status = gr.Textbox(
+                label="System Status",
+                value="✅ System Ready - VoiceBridge AI Initialized",
+                interactive=False,
+                max_lines=1
+            )
+            current_mode_display = gr.Textbox(
+                label="Current Mode",
+                value="universal",
+                interactive=False,
+                max_lines=1
+            )
+        
+        # Emergency Section (Always Visible)
+        with gr.Row():
+            emergency_btn = gr.Button(
+                "🚨 ACTIVATE EMERGENCY MODE",
+                elem_classes=["accessible-btn", "emergency-btn", "x-large-text"],
+                scale=2
+            )
+            emergency_contact_input = gr.Textbox(
+                label="Emergency Contact (Email/Phone)",
+                placeholder="Enter emergency contact information...",
+                scale=1
+            )
+        
+        # Mode Selection
+        with gr.Row():
+            mode_selector = gr.Radio(
+                choices=[
+                    ("Universal", "universal"),
+                    ("Blind", "blind"), 
+                    ("Deaf", "deaf"),
+                    ("Non-Verbal", "non_verbal"),
+                    ("Deaf-Blind", "deaf_blind")
+                ],
+                label="Accessibility Mode",
+                value="universal",
+                elem_id="mode-selector"
+            )
+        
+        # Universal Communication Tab
+        with gr.Tab("🌐 Universal Communication", id="universal"):
+            with gr.Row():
+                with gr.Column(scale=1):
+                    universal_audio = gr.Audio(
+                        label="🎤 Speak (Voice Input)",
+                        type="filepath",
+                        sources=["microphone"]
+                    )
+                    universal_text = gr.Textbox(
+                        label="⌨️ Type to Speak",
+                        placeholder="Enter text to be spoken aloud...",
+                        lines=3
+                    )
+                    universal_image = gr.Image(
+                        label="📷 Capture Scene",
+                        type="filepath",
+                        sources=["webcam", "upload"]
+                    )
+                    
+                    process_universal = gr.Button(
+                        "Process Input",
+                        elem_classes="accessible-btn",
+                        size="lg"
+                    )
+                
+                with gr.Column(scale=1):
+                    universal_output = gr.Textbox(
+                        label="Output",
+                        lines=6,
+                        max_lines=10
+                    )
+                    universal_audio_output = gr.Audio(
+                        label="Audio Output",
+                        type="filepath",
+                        interactive=False
+                    )
+                    universal_alert = gr.Textbox(
+                        label="Visual Alerts",
+                        visible=False
+                    )
+        
+        # Blind Assistance Tab
+        with gr.Tab("👁️ Blind Assistance", id="blind"):
+            with gr.Row():
+                with gr.Column(scale=1):
+                    blind_audio = gr.Audio(
+                        label="Voice Commands",
+                        type="filepath", 
+                        sources=["microphone"]
+                    )
+                    blind_commands = gr.Radio(
+                        choices=[
+                            "describe scene",
+                            "read text", 
+                            "navigate",
+                            "help"
+                        ],
+                        label="Quick Commands",
+                        value="describe scene"
+                    )
+                    blind_image = gr.Image(
+                        label="Camera Feed",
+                        type="filepath",
+                        sources=["webcam", "upload"]
+                    )
+                    
+                    process_blind = gr.Button(
+                        "Execute Command",
+                        elem_classes="accessible-btn"
+                    )
+                
+                with gr.Column(scale=1):
+                    blind_output = gr.Textbox(
+                        label="Scene Description",
+                        lines=5
+                    )
+                    blind_audio_output = gr.Audio(
+                        label="Audio Description",
+                        type="filepath"
+                    )
+        
+        # Deaf Assistance Tab  
+        with gr.Tab("👂 Deaf Assistance", id="deaf"):
+            with gr.Row():
+                with gr.Column(scale=1):
+                    deaf_audio = gr.Audio(
+                        label="Audio to Transcribe",
+                        type="filepath",
+                        sources=["microphone", "upload"]
+                    )
+                    continuous_listening = gr.Checkbox(
+                        label="Continuous Listening Mode",
+                        value=False
+                    )
+                    
+                    process_deaf = gr.Button(
+                        "Transcribe Audio",
+                        elem_classes="accessible-btn"
+                    )
+                
+                with gr.Column(scale=1):
+                    deaf_output = gr.Textbox(
+                        label="Transcription",
+                        lines=6
+                    )
+                    deaf_alerts = gr.Textbox(
+                        label="Sound Alerts",
+                        lines=2
+                    )
+        
+        # Non-Verbal Communication Tab
+        with gr.Tab("🤐 Non-Verbal Communication", id="non_verbal"):
+            with gr.Row():
+                with gr.Column(scale=1):
+                    preset_phrases = gr.Radio(
+                        choices=[
+                            "greeting", "help", "medical", "emergency", 
+                            "thanks", "yes", "no", "pain", "lost", "bathroom"
+                        ],
+                        label="Quick Phrases",
+                        value="greeting"
+                    )
+                    custom_phrase = gr.Textbox(
+                        label="Custom Message",
+                        placeholder="Or type your own message...",
+                        lines=2
+                    )
+                    
+                    speak_btn = gr.Button(
+                        "Speak Message",
+                        elem_classes="accessible-btn",
+                        size="lg"
+                    )
+                
+                with gr.Column(scale=1):
+                    spoken_text = gr.Textbox(
+                        label="Message",
+                        lines=3
+                    )
+                    message_audio = gr.Audio(
+                        label="Spoken Audio",
+                        type="filepath"
+                    )
+        
+        # Deaf-Blind Communication Tab
+        with gr.Tab("👁️👂 Deaf-Blind Communication", id="deaf_blind"):
+            with gr.Row():
+                with gr.Column(scale=1):
+                    tactile_input = gr.Textbox(
+                        label="Message to Convert",
+                        placeholder="Enter text for tactile communication...",
+                        lines=3
+                    )
+                    output_format = gr.Radio(
+                        choices=["haptic", "braille"],
+                        label="Output Format",
+                        value="haptic"
+                    )
+                    
+                    convert_btn = gr.Button(
+                        "Convert to Tactile",
+                        elem_classes="accessible-btn"
+                    )
+                
+                with gr.Column(scale=1):
+                    braille_output = gr.Textbox(
+                        label="Braille Output",
+                        lines=3
+                    )
+                    vibration_pattern = gr.Textbox(
+                        label="Vibration Pattern",
+                        lines=2
+                    )
+        
+        # Feedback and Settings
+        with gr.Tab("⚙️ Settings & Feedback", id="settings"):
+            with gr.Row():
+                with gr.Column(scale=1):
+                    gr.Markdown("### 🔧 Accessibility Settings")
+                    high_contrast = gr.Checkbox(label="High Contrast Mode", value=False)
+                    large_text = gr.Checkbox(label="Large Text Mode", value=False)
+                    voice_navigation = gr.Checkbox(label="Voice Navigation", value=True)
+                    
+                    gr.Markdown("### 📧 Feedback")
+                    feedback_email = gr.Textbox(label="Your Email (optional)")
+                    feedback_message = gr.Textbox(
+                        label="Feedback & Suggestions",
+                        placeholder="Help us improve VoiceBridge AI...",
+                        lines=4
+                    )
+                    submit_feedback = gr.Button("Submit Feedback", elem_classes="accessible-btn")
+                    feedback_status = gr.Textbox(label="Status", interactive=False)
+                
+                with gr.Column(scale=1):
+                    gr.Markdown("### 📊 System Information")
+                    conversation_history = gr.Textbox(
+                        label="Recent Conversation",
+                        lines=8,
+                        max_lines=10
+                    )
+                    clear_history = gr.Button("Clear History", elem_classes="accessible-btn")
+                    export_data = gr.Button("Export Data", elem_classes="accessible-btn")
+        
+        # ==================== EVENT HANDLERS ====================
+        
+        def handle_mode_change(mode):
+            voice_bridge.current_mode = mode
+            status_msg = f"Mode changed to: {mode}"
+            voice_bridge.add_to_conversation("System", status_msg)
+            return status_msg, status_msg  # For both status displays
+        
+        def handle_universal_input(audio, text, image, mode):
+            if audio:
+                input_data = {'type': 'voice', 'audio': audio}
+            elif text:
+                input_data = {'type': 'text', 'text': text}
+            elif image:
+                input_data = {'type': 'image', 'image': image}
+            else:
+                return "Please provide input", None, None
+            
+            result = voice_bridge.universal_communication(input_data)
+            return result['text'], result.get('audio'), result.get('visual_alert', '')
+        
+        def handle_blind_assistance(audio, command, image):
+            if audio:
+                transcript = voice_bridge.fallback_speech_to_text(audio)
+                result = voice_bridge.blind_mode(transcript, image)
+            elif image:
+                result = voice_bridge.blind_mode(command, image)
+            else:
+                result = voice_bridge.blind_mode(command)
+            
+            return result['text'], result.get('audio')
+        
+        def handle_deaf_assistance(audio, continuous):
+            result = voice_bridge.deaf_mode(audio, continuous)
+            return result['text'], result.get('visual_alert', 'No important sounds detected')
+        
+        def handle_non_verbal(preset, custom):
+            text_to_speak = custom if custom else None
+            result = voice_bridge.non_verbal_mode(text_to_speak, preset)
+            return result['text'], result.get('audio')
+        
+        def handle_deaf_blind(input_text, output_format):
+            result = voice_bridge.deaf_blind_mode(input_text, output_format)
+            braille = result.get('braille', '')
+            pattern = str(result.get('haptic_feedback', []))
+            return result['text'], braille, pattern
+        
+        def handle_emergency(contact):
+            if contact:
+                voice_bridge.emergency_contacts.append(contact)
+            result = voice_bridge.trigger_emergency_mode("manual")
+            return result['message'], result.get('audio')
+        
+        def handle_feedback(email, message):
+            if not message.strip():
+                return "Please enter feedback message"
+            
+            # In production, this would save to database/send email
+            feedback_data = {
+                'timestamp': datetime.now().isoformat(),
+                'email': email,
+                'message': message,
+                'mode': voice_bridge.current_mode
+            }
+            
+            try:
+                # Save feedback locally
+                with open('data/feedback.json', 'a') as f:
+                    f.write(json.dumps(feedback_data) + '\n')
+                
+                return "✅ Thank you for your feedback! We'll review it soon. Contact: Naila.Rais@msftcommunity.com"
+            except Exception as e:
+                return f"❌ Could not save feedback: {str(e)}"
+        
+        # Connect event handlers
+        mode_selector.change(
+            handle_mode_change,
+            inputs=mode_selector,
+            outputs=[system_status, current_mode_display]
+        )
+        
+        process_universal.click(
+            handle_universal_input,
+            inputs=[universal_audio, universal_text, universal_image, mode_selector],
+            outputs=[universal_output, universal_audio_output, universal_alert]
+        )
+        
+        process_blind.click(
+            handle_blind_assistance,
+            inputs=[blind_audio, blind_commands, blind_image],
+            outputs=[blind_output, blind_audio_output]
+        )
+        
+        process_deaf.click(
+            handle_deaf_assistance,
+            inputs=[deaf_audio, continuous_listening],
+            outputs=[deaf_output, deaf_alerts]
+        )
+        
+        speak_btn.click(
+            handle_non_verbal,
+            inputs=[preset_phrases, custom_phrase],
+            outputs=[spoken_text, message_audio]
+        )
+        
+        convert_btn.click(
+            handle_deaf_blind,
+            inputs=[tactile_input, output_format],
+            outputs=[tactile_input, braille_output, vibration_pattern]
+        )
+        
+        emergency_btn.click(
+            handle_emergency,
+            inputs=emergency_contact_input,
+            outputs=[system_status, universal_audio_output]
+        )
+        
+        submit_feedback.click(
+            handle_feedback,
+            inputs=[feedback_email, feedback_message],
+            outputs=feedback_status
+        )
+        
+        # Initialize system
+        demo.load(
+            fn=lambda: ("System Ready - VoiceBridge AI Initialized", "universal"),
+            outputs=[system_status, current_mode_display]
+        )
+    
+    return demo
+
+# Production deployment
+if __name__ == "__main__":
+    try:
+        print("🚀 Starting VoiceBridge AI Production Server...")
+        print("📧 Support & Feedback: Naila.Rais@msftcommunity.com")
+        print("🌐 Access the app at the URL provided below")
+        
+        demo = create_production_interface()
+        demo.launch(
+            server_name="0.0.0.0",
+            server_port=7860,
+            share=True,
+            debug=False,
+            show_error=True,
+            auth=("NailaR", "voicebridge2025") if os.getenv('PRODUCTION') else None
+        )
+    except Exception as e:
+        logger.error(f"Failed to start production server: {e}")
+        print(f"❌ Startup failed: {e}")