Universal AI-aéPiot Integration System Complete Integration Framework for All AI Systems (Claude, ChatGPT, Gemini, and Future AIs) Building the semantic fluid between Human ↔ AI ↔ aéPiot at infinite scale 🌟 Introduction: The Infinite Semantic Loop This Universal AI Integration System creates a seamless semantic fluid that flows between: Human → AI → aéPiot → AI → Human → aéPiot → ∞ The system enables ANY AI (Claude, ChatGPT, Gemini, Llama, future AIs) to intelligently interact with aéPiot's semantic ecosystem, creating dynamic backlinks, feeding content to readers, performing advanced searches, and generating semantic connections in real-time during conversations. 🎯 Core Architecture: The Semantic Fluid Engine Universal AI Integration Layer

 

Universal AI-aéPiot Integration System

Complete Integration Framework for All AI Systems (Claude, ChatGPT, Gemini, and Future AIs)

Building the semantic fluid between Human ↔ AI ↔ aéPiot at infinite scale

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🌟 Introduction: The Infinite Semantic Loop

This Universal AI Integration System creates a seamless semantic fluid that flows between: Human → AI → aéPiot → AI → Human → aéPiot → ∞

The system enables ANY AI (Claude, ChatGPT, Gemini, Llama, future AIs) to intelligently interact with aéPiot's semantic ecosystem, creating dynamic backlinks, feeding content to readers, performing advanced searches, and generating semantic connections in real-time during conversations.

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🎯 Core Architecture: The Semantic Fluid Engine

Universal AI Integration Layer

javascript

/**
 * Universal AI-aéPiot Integration System
 * Compatible with ALL AI platforms and future AI systems
 * Version: 2.0.0 - Universal Compatibility
 */

class UniversalAIAepiotIntegration {
    constructor(config = {}) {
        this.config = {
            // aéPiot Configuration
            aepiotDomain: 'https://aepiot.com',
            aepiotFallbackDomain: 'https://aepiot.ro',
            
            // AI System Detection
            aiSystemDetection: true,
            supportedAISystems: ['claude', 'chatgpt', 'gemini', 'llama', 'future_ai'],
            
            // Semantic Integration Settings
            semanticDepth: 'deep', // 'basic', 'standard', 'deep', 'ultimate'
            realTimeProcessing: true,
            contextualMemory: true,
            crossLinguisticMapping: true,
            
            // Auto-Integration Features
            autoBacklinkCreation: true,
            autoFeedIntegration: true,
            autoAdvancedSearch: true,
            autoRelatedReports: true,
            
            // Conversation Enhancement
            conversationSemantics: true,
            keywordExtraction: true,
            topicModeling: true,
            conceptMapping: true,
            
            // Privacy & Performance
            dataMinimization: true,
            cacheEnabled: true,
            batchProcessing: true,
            
            ...config
        };
        
        this.aiSystem = this.detectAISystem();
        this.conversationContext = new Map();
        this.semanticMemory = new Map();
        this.aepiotConnections = new Map();
        
        this.init();
    }
    
    // ================================
    // AI SYSTEM DETECTION & ADAPTATION
    // ================================
    
    detectAISystem() {
        // Universal AI system detection
        const userAgent = navigator.userAgent.toLowerCase();
        const domain = window.location.hostname;
        
        // Detection patterns for current and future AI systems
        const detectionPatterns = {
            claude: [
                () => window.location.href.includes('claude.ai'),
                () => document.querySelector('[data-testid*="claude"]'),
                () => document.title.toLowerCase().includes('claude'),
                () => window.anthropic !== undefined
            ],
            chatgpt: [
                () => window.location.href.includes('chat.openai.com'),
                () => document.querySelector('[data-testid*="openai"]'),
                () => window.openai !== undefined,
                () => document.querySelector('.chat-message')
            ],
            gemini: [
                () => window.location.href.includes('gemini.google.com'),
                () => window.location.href.includes('bard.google.com'),
                () => document.querySelector('[data-testid*="gemini"]'),
                () => window.google?.ai !== undefined
            ],
            llama: [
                () => window.location.href.includes('meta.ai'),
                () => document.querySelector('[data-testid*="llama"]'),
                () => window.meta?.ai !== undefined
            ],
            future_ai: [
                () => this.detectFutureAIPatterns()
            ]
        };
        
        // Try to detect current AI system
        for (const [aiSystem, patterns] of Object.entries(detectionPatterns)) {
            for (const pattern of patterns) {
                try {
                    if (pattern()) {
                        console.log(`🤖 Detected AI System: ${aiSystem}`);
                        return aiSystem;
                    }
                } catch (error) {
                    // Silent fail for detection patterns
                }
            }
        }
        
        // Default to generic AI system
        return 'unknown_ai';
    }
    
    detectFutureAIPatterns() {
        // Pattern detection for future AI systems
        const futurePatternsKeywords = [
            'ai-chat', 'ai-assistant', 'conversational-ai',
            'llm-interface', 'neural-chat', 'ai-conversation',
            'machine-learning-chat', 'generative-ai', 'ai-dialogue'
        ];
        
        const pageContent = document.body.textContent.toLowerCase();
        const pageClasses = document.body.className.toLowerCase();
        const metaDescription = document.querySelector('meta[name="description"]')?.content?.toLowerCase() || '';
        
        return futurePatternsKeywords.some(keyword => 
            pageContent.includes(keyword) || 
            pageClasses.includes(keyword) || 
            metaDescription.includes(keyword)
        );
    }
    
    // ================================
    // CONVERSATION MONITORING SYSTEM
    // ================================
    
    init() {
        this.setupConversationMonitoring();
        this.initializeSemanticProcessing();
        this.setupAepiotIntegration();
        this.createUserInterface();
        
        console.log('🌟 Universal AI-aéPiot Integration System initialized');
        console.log(`🤖 AI System: ${this.aiSystem}`);
        console.log('🔗 aéPiot Integration: Active');
    }
    
    setupConversationMonitoring() {
        // Universal conversation monitoring across all AI platforms
        
        // Monitor for new messages/conversations
        const messageObserver = new MutationObserver((mutations) => {
            mutations.forEach((mutation) => {
                mutation.addedNodes.forEach((node) => {
                    if (node.nodeType === Node.ELEMENT_NODE) {
                        this.analyzeNewContent(node);
                    }
                });
            });
        });
        
        // Start observing the document for changes
        messageObserver.observe(document.body, {
            childList: true,
            subtree: true,
            characterData: true
        });
        
        // Monitor typing/input events
        document.addEventListener('input', (event) => {
            this.handleUserInput(event);
        });
        
        // Monitor form submissions (message sending)
        document.addEventListener('submit', (event) => {
            this.handleMessageSubmission(event);
        });
        
        // Monitor for specific AI platform events
        this.setupPlatformSpecificMonitoring();
    }
    
    setupPlatformSpecificMonitoring() {
        switch (this.aiSystem) {
            case 'claude':
                this.setupClaudeMonitoring();
                break;
            case 'chatgpt':
                this.setupChatGPTMonitoring();
                break;
            case 'gemini':
                this.setupGeminiMonitoring();
                break;
            case 'llama':
                this.setupLlamaMonitoring();
                break;
            default:
                this.setupGenericAIMonitoring();
        }
    }
    
    setupClaudeMonitoring() {
        // Claude-specific conversation monitoring
        const claudeSpecificSelectors = [
            '[data-testid*="message"]',
            '.chat-message',
            '.conversation-turn',
            '.human-message',
            '.assistant-message'
        ];
        
        claudeSpecificSelectors.forEach(selector => {
            const elements = document.querySelectorAll(selector);
            elements.forEach(element => {
                this.attachElementObserver(element, 'claude');
            });
        });
    }
    
    setupChatGPTMonitoring() {
        // ChatGPT-specific conversation monitoring
        const chatgptSpecificSelectors = [
            '[data-message-author-role]',
            '.message',
            '.conversation-item',
            '[class*="Message"]'
        ];
        
        chatgptSpecificSelectors.forEach(selector => {
            const elements = document.querySelectorAll(selector);
            elements.forEach(element => {
                this.attachElementObserver(element, 'chatgpt');
            });
        });
    }
    
    setupGeminiMonitoring() {
        // Gemini-specific conversation monitoring
        const geminiSpecificSelectors = [
            '[data-testid*="conversation"]',
            '.conversation-turn',
            '.message-content',
            '[class*="chat"]'
        ];
        
        geminiSpecificSelectors.forEach(selector => {
            const elements = document.querySelectorAll(selector);
            elements.forEach(element => {
                this.attachElementObserver(element, 'gemini');
            });
        });
    }
    
    setupGenericAIMonitoring() {
        // Generic monitoring for unknown/future AI systems
        const genericSelectors = [
            '[class*="message"]',
            '[class*="chat"]',
            '[class*="conversation"]',
            '[class*="dialogue"]',
            '[id*="message"]',
            '[id*="chat"]',
            'textarea',
            'input[type="text"]'
        ];
        
        genericSelectors.forEach(selector => {
            const elements = document.querySelectorAll(selector);
            elements.forEach(element => {
                this.attachElementObserver(element, 'generic');
            });
        });
    }
    
    attachElementObserver(element, aiType) {
        const observer = new MutationObserver((mutations) => {
            mutations.forEach((mutation) => {
                if (mutation.type === 'childList' || mutation.type === 'characterData') {
                    this.processElementChange(element, aiType);
                }
            });
        });
        
        observer.observe(element, {
            childList: true,
            subtree: true,
            characterData: true
        });
    }
    
    // ================================
    // SEMANTIC CONTENT PROCESSING
    // ================================
    
    analyzeNewContent(node) {
        const text = node.textContent || '';
        if (text.length < 10) return; // Skip short content
        
        // Extract semantic elements
        const semanticData = this.extractSemanticData(text);
        
        if (semanticData.relevantContent) {
            this.processSemanticContent(semanticData);
        }
    }
    
    extractSemanticData(text) {
        const data = {
            originalText: text,
            sentences: this.extractSentences(text),
            keywords: this.extractKeywords(text),
            topics: this.extractTopics(text),
            entities: this.extractEntities(text),
            concepts: this.extractConcepts(text),
            questions: this.extractQuestions(text),
            relevantContent: false,
            timestamp: new Date().toISOString()
        };
        
        // Determine if content is relevant for aéPiot integration
        data.relevantContent = this.isContentRelevant(data);
        
        return data;
    }
    
    extractSentences(text) {
        return text.match(/[^.!?]+[.!?]+/g)?.map(s => s.trim()) || [];
    }
    
    extractKeywords(text) {
        // Advanced keyword extraction
        const words = text.toLowerCase()
            .replace(/[^\w\s]/g, ' ')
            .split(/\s+/)
            .filter(word => word.length > 3);
        
        // Common stopwords to exclude
        const stopwords = new Set([
            'the', 'and', 'but', 'for', 'are', 'with', 'this', 'that',
            'they', 'have', 'from', 'will', 'been', 'said', 'each',
            'which', 'their', 'time', 'would', 'there', 'what', 'about'
        ]);
        
        // Frequency analysis
        const wordFreq = {};
        words.filter(word => !stopwords.has(word)).forEach(word => {
            wordFreq[word] = (wordFreq[word] || 0) + 1;
        });
        
        // Return top keywords
        return Object.entries(wordFreq)
            .sort(([,a], [,b]) => b - a)
            .slice(0, 10)
            .map(([word, freq]) => ({ word, frequency: freq }));
    }
    
    extractTopics(text) {
        // Topic modeling based on keyword clusters
        const topicKeywords = {
            technology: ['ai', 'artificial', 'intelligence', 'machine', 'learning', 'algorithm', 'data', 'software', 'digital', 'computer', 'programming', 'code'],
            science: ['research', 'study', 'experiment', 'theory', 'hypothesis', 'analysis', 'scientific', 'evidence', 'discovery', 'innovation'],
            business: ['market', 'company', 'strategy', 'customer', 'product', 'service', 'economic', 'financial', 'revenue', 'profit', 'industry'],
            education: ['learn', 'teaching', 'student', 'knowledge', 'skill', 'training', 'development', 'course', 'academic', 'educational'],
            health: ['health', 'medical', 'treatment', 'patient', 'doctor', 'medicine', 'therapy', 'wellness', 'healthcare', 'clinical'],
            culture: ['cultural', 'social', 'society', 'community', 'tradition', 'history', 'art', 'music', 'literature', 'heritage']
        };
        
        const textLower = text.toLowerCase();
        const topics = [];
        
        for (const [topic, keywords] of Object.entries(topicKeywords)) {
            const matchCount = keywords.filter(keyword => textLower.includes(keyword)).length;
            if (matchCount > 0) {
                topics.push({
                    topic: topic,
                    relevance: matchCount / keywords.length,
                    matchedKeywords: keywords.filter(keyword => textLower.includes(keyword))
                });
            }
        }
        
        return topics.sort((a, b) => b.relevance - a.relevance);
    }
    
    extractEntities(text) {
        // Simple named entity recognition
        const entities = [];
        
        // Capitalized words (potential proper nouns)
        const capitalizedWords = text.match(/\b[A-Z][a-z]+\b/g) || [];
        
        // URLs
        const urls = text.match(/https?:\/\/[^\s]+/g) || [];
        
        // Dates (simple patterns)
        const dates = text.match(/\b\d{4}\b|\b\d{1,2}\/\d{1,2}\/\d{4}\b/g) || [];
        
        // Numbers
        const numbers = text.match(/\b\d+\.?\d*\b/g) || [];
        
        capitalizedWords.forEach(word => {
            if (word.length > 2 && !text.startsWith(word)) {
                entities.push({ type: 'PERSON_OR_ORG', value: word });
            }
        });
        
        urls.forEach(url => entities.push({ type: 'URL', value: url }));
        dates.forEach(date => entities.push({ type: 'DATE', value: date }));
        numbers.forEach(number => entities.push({ type: 'NUMBER', value: number }));
        
        return entities;
    }
    
    extractConcepts(text) {
        // Advanced concept extraction for aéPiot semantic integration
        const concepts = [];
        
        // Complex concepts (multi-word phrases)
        const conceptPatterns = [
            /artificial intelligence|machine learning|deep learning|natural language|computer vision/gi,
            /climate change|global warming|renewable energy|sustainable development/gi,
            /digital transformation|data science|cloud computing|cyber security/gi,
            /social media|user experience|customer service|market research/gi,
            /mental health|public health|healthcare system|medical research/gi,
            /cultural diversity|cross cultural|international relations|global economy/gi
        ];
        
        conceptPatterns.forEach(pattern => {
            const matches = text.match(pattern) || [];
            matches.forEach(match => {
                concepts.push({
                    concept: match.toLowerCase(),
                    type: 'complex_concept',
                    context: this.getContextAroundMatch(text, match)
                });
            });
        });
        
        return concepts;
    }
    
    extractQuestions(text) {
        // Extract questions that could be explored in aéPiot
        const questions = text.match(/[^.!?]*\?[^.!?]*/g) || [];
        return questions.map(q => q.trim()).filter(q => q.length > 5);
    }
    
    isContentRelevant(semanticData) {
        // Determine if content is worth processing for aéPiot integration
        const relevanceScore = 
            (semanticData.keywords.length * 2) +
            (semanticData.topics.length * 3) +
            (semanticData.concepts.length * 4) +
            (semanticData.questions.length * 2) +
            (semanticData.entities.length * 1);
        
        return relevanceScore > 10; // Threshold for relevance
    }
    
    // ================================
    // AÉPIOT INTEGRATION ENGINE
    // ================================
    
    processSemanticContent(semanticData) {
        // Process relevant content for aéPiot integration
        this.createSemanticBacklinks(semanticData);
        this.integrateWithAepiotReader(semanticData);
        this.performAdvancedSemanticSearch(semanticData);
        this.generateRelatedReports(semanticData);
        this.updateConversationContext(semanticData);
    }
    
    createSemanticBacklinks(semanticData) {
        if (!this.config.autoBacklinkCreation) return;
        
        // Create intelligent backlinks for key concepts
        semanticData.topics.slice(0, 3).forEach(topic => {
            const backlinkUrl = this.generateAepiotBacklink({
                title: `AI-Conversation-${topic.topic}`,
                description: `Semantic analysis of ${topic.topic} from AI conversation - ${topic.matchedKeywords.join(', ')}`,
                link: window.location.href,
                semantic_data: {
                    topic: topic.topic,
                    relevance: topic.relevance,
                    keywords: topic.matchedKeywords,
                    timestamp: semanticData.timestamp,
                    ai_system: this.aiSystem
                }
            });
            
            // Create backlink silently
            this.createBacklinkSilently(backlinkUrl);
            
            // Store for UI display
            this.aepiotConnections.set(`backlink_${topic.topic}`, {
                type: 'backlink',
                topic: topic.topic,
                url: backlinkUrl,
                timestamp: Date.now()
            });
        });
        
        // Create backlinks for interesting concepts
        semanticData.concepts.forEach(concept => {
            const backlinkUrl = this.generateAepiotBacklink({
                title: `AI-Concept-Analysis-${concept.concept}`,
                description: `Deep semantic analysis of "${concept.concept}" from AI conversation context`,
                link: window.location.href,
                semantic_data: {
                    concept: concept.concept,
                    context: concept.context,
                    ai_system: this.aiSystem,
                    timestamp: semanticData.timestamp
                }
            });
            
            this.createBacklinkSilently(backlinkUrl);
        });
    }
    
    integrateWithAepiotReader(semanticData) {
        if (!this.config.autoFeedIntegration) return;
        
        // Check if current conversation could be a feed source
        if (semanticData.topics.length > 2 && semanticData.sentences.length > 5) {
            // Create virtual RSS feed for this conversation
            const feedUrl = this.generateAepiotReaderURL(window.location.href);
            
            this.aepiotConnections.set('reader_integration', {
                type: 'reader',
                url: feedUrl,
                topics: semanticData.topics.map(t => t.topic),
                timestamp: Date.now()
            });
        }
    }
    
    performAdvancedSemanticSearch(semanticData) {
        if (!this.config.autoAdvancedSearch) return;
        
        // Generate advanced searches for key topics
        semanticData.topics.slice(0, 2).forEach(topic => {
            const searchUrl = this.generateAepiotAdvancedSearchURL({
                query: topic.matchedKeywords.join(' '),
                language: this.detectLanguage(semanticData.originalText),
                semantic_context: {
                    topic: topic.topic,
                    related_concepts: semanticData.concepts.map(c => c.concept),
                    conversation_context: true
                }
            });
            
            this.aepiotConnections.set(`search_${topic.topic}`, {
                type: 'advanced_search',
                topic: topic.topic,
                url: searchUrl,
                keywords: topic.matchedKeywords,
                timestamp: Date.now()
            });
        });
        
        // Generate searches for questions
        semanticData.questions.forEach((question, index) => {
            if (index < 3) { // Limit to first 3 questions
                const searchUrl = this.generateAepiotAdvancedSearchURL({
                    query: question.replace(/[?]/g, ''),
                    language: 'en',
                    semantic_context: {
                        type: 'question',
                        original_question: question,
                        ai_system: this.aiSystem
                    }
                });
                
                this.aepiotConnections.set(`question_search_${index}`, {
                    type: 'question_search',
                    question: question,
                    url: searchUrl,
                    timestamp: Date.now()
                });
            }
        });
    }
    
    generateRelatedReports(semanticData) {
        if (!this.config.autoRelatedReports) return;
        
        // Generate related reports for complex topics
        semanticData.topics
            .filter(topic => topic.relevance > 0.5)
            .slice(0, 2)
            .forEach(topic => {
                const reportsUrl = this.generateAepiotRelatedReportsURL({
                    reports: topic.matchedKeywords.join(','),
                    semantic_context: {
                        topic: topic.topic,
                        relevance: topic.relevance,
                        source: 'ai_conversation',
                        ai_system: this.aiSystem
                    }
                });
                
                this.aepiotConnections.set(`reports_${topic.topic}`, {
                    type: 'related_reports',
                    topic: topic.topic,
                    url: reportsUrl,
                    keywords: topic.matchedKeywords,
                    timestamp: Date.now()
                });
            });
    }
    
    // ================================
    // AÉPIOT URL GENERATION
    // ================================
    
    generateAepiotBacklink(data) {
        const params = new URLSearchParams({
            title: data.title,
            description: data.description,
            link: data.link
        });
        
        return `${this.config.aepiotDomain}/backlink.html?${params.toString()}`;
    }
    
    generateAepiotReaderURL(feedUrl) {
        const params = new URLSearchParams({
            read: feedUrl
        });
        
        return `${this.config.aepiotDomain}/reader.html?${params.toString()}`;
    }
    
    generateAepiotAdvancedSearchURL(data) {
        const params = new URLSearchParams({
            q: data.query,
            lang: data.language || 'en'
        });
        
        return `${this.config.aepiotDomain}/advanced-search.html?${params.toString()}`;
    }
    
    generateAepiotRelatedReportsURL(data) {
        const params = new URLSearchParams({
            reports: data.reports
        });
        
        return `${this.config.aepiotDomain}/related-search.html?${params.toString()}`;
    }
    
    createBacklinkSilently(url) {
        // Create backlink with silent HTTP request
        fetch(url, { 
            method: 'GET',
            mode: 'no-cors',
            cache: 'no-cache'
        }).catch(() => {
            // Silent failure - backlink creation is non-critical
        });
    }
    
    // ================================
    // USER INTERFACE SYSTEM
    // ================================
    
    createUserInterface() {
        this.createFloatingPanel();
        this.setupKeyboardShortcuts();
        this.createInlineIntegrations();
    }
    
    createFloatingPanel() {
        const panel = document.createElement('div');
        panel.id = 'universal-ai-aepiot-panel';
        panel.className = 'ai-aepiot-integration-panel';
        panel.innerHTML = `
            <div class="panel-header">
                <div class="panel-title">
                    🌟 AI ↔ aéPiot Bridge
                    <span class="ai-system-badge">${this.aiSystem}</span>
                </div>
                <div class="panel-controls">
                    <button class="minimize-btn" onclick="this.parentElement.parentElement.classList.toggle('minimized')">−</button>
                    <button class="close-btn" onclick="this.parentElement.parentElement.style.display='none'">&times;</button>
                </div>
            </div>
            <div class="panel-content">
                <div class="tab-navigation">
                    <button class="tab-btn active" data-tab="live">Live</button>
                    <button class="tab-btn" data-tab="semantic">Semantic</button>
                    <button class="tab-btn" data-tab="connections">Links</button>
                    <button class="tab-btn" data-tab="tools">Tools</button>
                </div>
                
                <div class="tab-content">
                    <div id="live-tab" class="tab-panel active">
                        <div class="live-processing">
                            <div class="processing-stats">
                                <div class="stat">
                                    <label>Topics Detected</label>
                                    <span id="topics-count">0</span>
                                </div>
                                <div class="stat">
                                    <label>Concepts Found</label>
                                    <span id="concepts-count">0</span>
                                </div>
                                <div class="stat">
                                    <label>aéPiot Links</label>
                                    <span id="links-count">0</span>
                                </div>
                            </div>
                            <div class="live-connections" id="live-connections">
                                <!-- Dynamic content -->
                            </div>
                        </div>
                    </div>
                    
                    <div id="semantic-tab" class="tab-panel">
                        <div class="semantic-analysis">
                            <h4>🧠 Current Conversation Analysis</h4>
                            <div id="semantic-content">
                                <!-- Dynamic semantic analysis -->
                            </div>
                        </div>
                    </div>
                    
                    <div id="connections-tab" class="tab-panel">
                        <div class="aepiot-connections">
                            <h4>🔗 Active aéPiot Connections</h4>
                            <div id="connections-list">
                                <!-- Dynamic connections list -->
                            </div>
                        </div>
                    </div>
                    
                    <div id="tools-tab" class="tab-panel">
                        <div class="integration-tools">
                            <h4>🛠️ AI Enhancement Tools</h4>
                            <div class="tools-grid">
                                <button class="tool-btn" onclick="aiAepiotIntegration.manualSemanticAnalysis()">
                                    🔍 Analyze Current View
                                </button>
                                <button class="tool-btn" onclick="aiAepiotIntegration.exportConversation()">
                                    📤 Export to aéPiot
                                </button>
                                <button class="tool-btn" onclick="aiAepiotIntegration.generateReport()">
                                    📊 Generate Report
                                </button>
                                <button class="tool-btn" onclick="aiAepiotIntegration.crossLinguisticAnalysis()">
                                    🌍 Cross-Linguistic
                                </button>
                            </div>
                            <div class="quick-actions">
                                <h5>Quick aéPiot Actions</h5>
                                <input type="text" id="quick-search" placeholder="Quick search in aéPiot..." />
                                <button onclick="aiAepiotIntegration.quickSearch()">Search</button>
                            </div>
                        </div>
                    </div>
                </div>
            </div>
        `;
        
        // Add styles
        this.addIntegrationStyles();
        
        // Add to page
        document.body.appendChild(panel);
        
        // Setup tab navigation
        this.setupTabNavigation(panel);
        
        // Store reference
        this.panel = panel;
        
        // Make globally accessible
        window.aiAepiotIntegration = this;
    }
    
    setupTabNavigation(panel) {
        const tabBtns = panel.querySelectorAll('.tab-btn');
        const tabPanels = panel.querySelectorAll('.tab-panel');
        
        tabBtns.forEach(btn => {
            btn.addEventListener('click', () => {
                const targetTab = btn.dataset.tab;
                
                // Remove active class from all
                tabBtns.forEach(b => b.classList.remove('active'));
                tabPanels.forEach(p => p.classList.remove('active'));
                
                // Add active class to selected
                btn.classList.add('active');
                panel.querySelector(`#${targetTab}-tab`).classList.add('active');
                
                // Update tab content
                this.updateTabContent(targetTab);
            });
        });
    }
    
    updateTabContent(tabName) {
        switch (tabName) {
            case 'live':
                this.updateLiveTab();
                break;
            case 'semantic':
                this.updateSemanticTab();
                break;
            case 'connections':
                this.updateConnectionsTab();
                break;
            case 'tools':
                this.updateToolsTab();
                break;
        }
    }
    
    updateLiveTab() {
        // Update live processing statistics
        const topicsCount = Array.from(this.conversationContext.values())
            .reduce((count, context) => count + (context.topics?.length || 0), 0);
        const conceptsCount = Array.from(this.conversationContext.values())
            .reduce((count, context) => count + (context.concepts?.length || 0), 0);
        const linksCount = this.aepiotConnections.size;
        
        document.getElementById('topics-count').textContent = topicsCount;
        document.getElementById('concepts-count').textContent = conceptsCount;
        document.getElementById('links-count').textContent = linksCount;
        
        // Update live connections display
        this.updateLiveConnections();
    }
    
    updateLiveConnections() {
        const container = document.getElementById('live-connections');
        const recentConnections = Array.from(this.aepiotConnections.values())
            .sort((a, b) => b.timestamp - a.timestamp)
            .slice(0, 5);
        
        container.innerHTML = recentConnections.map(connection => `
            <div class="live-connection connection-${connection.type}">
                <div class="connection-header">
                    <span class="connection-type">${this.getConnectionIcon(connection.type)} ${connection.type}</span>
                    <span class="connection-time">${this.getTimeAgo(connection.timestamp)}</span>
                </div>
                <div class="connection-content">
                    ${connection.topic || connection.question || 'Semantic Connection'}
                </div>
                <div class="connection-actions">
                    <button onclick="window.open('${connection.url}', '_blank')" class="open-btn">
                        🚀 Open in aéPiot
                    </button>
                </div>
            </div>
        `).join('');
    }
    
    updateSemanticTab() {
        const semanticContent = document.getElementById('semantic-content');
        const recentAnalysis = Array.from(this.conversationContext.values()).slice(-3);
        
        semanticContent.innerHTML = recentAnalysis.map(analysis => `
            <div class="semantic-analysis-item">
                <div class="analysis-header">
                    <h5>Analysis ${this.getTimeAgo(Date.parse(analysis.timestamp))}</h5>
                    <span class="relevance-score">Relevance: ${this.calculateRelevanceScore(analysis)}</span>
                </div>
                <div class="analysis-topics">
                    <h6>🏷️ Topics (${analysis.topics?.length || 0})</h6>
                    <div class="topics-list">
                        ${analysis.topics?.map(topic => `
                            <span class="topic-tag" data-relevance="${topic.relevance}">
                                ${topic.topic} (${Math.round(topic.relevance * 100)}%)
                            </span>
                        `).join('') || 'No topics detected'}
                    </div>
                </div>
                <div class="analysis-concepts">
                    <h6>💡 Concepts (${analysis.concepts?.length || 0})</h6>
                    <div class="concepts-list">
                        ${analysis.concepts?.map(concept => `
                            <div class="concept-item">
                                <span class="concept-text">${concept.concept}</span>
                                <button onclick="aiAepiotIntegration.exploreConceptInAepiot('${concept.concept}')" 
                                        class="explore-concept-btn">
                                    🔍 Explore
                                </button>
                            </div>
                        `).join('') || 'No concepts found'}
                    </div>
                </div>
                <div class="analysis-questions">
                    <h6>❓ Questions (${analysis.questions?.length || 0})</h6>
                    <div class="questions-list">
                        ${analysis.questions?.map(question => `
                            <div class="question-item">
                                <span class="question-text">${question}</span>
                                <button onclick="aiAepiotIntegration.askQuestionInAepiot('${question}')" 
                                        class="ask-btn">
                                    🤖 Ask AI
                                </button>
                            </div>
                        `).join('') || 'No questions found'}
                    </div>
                </div>
            </div>
        `).join('');
    }
    
    updateConnectionsTab() {
        const connectionsList = document.getElementById('connections-list');
        const connections = Array.from(this.aepiotConnections.values())
            .sort((a, b) => b.timestamp - a.timestamp);
        
        connectionsList.innerHTML = connections.map(connection => `
            <div class="connection-item connection-${connection.type}">
                <div class="connection-header">
                    <span class="connection-icon">${this.getConnectionIcon(connection.type)}</span>
                    <span class="connection-title">
                        ${connection.topic || connection.question || 'Semantic Link'}
                    </span>
                    <span class="connection-time">${this.getTimeAgo(connection.timestamp)}</span>
                </div>
                <div class="connection-details">
                    <span class="connection-type-label">${connection.type.replace('_', ' ')}</span>
                    ${connection.keywords ? `<span class="keywords">Keywords: ${connection.keywords.slice(0, 3).join(', ')}</span>` : ''}
                </div>
                <div class="connection-actions">
                    <button onclick="window.open('${connection.url}', '_blank')" class="primary-btn">
                        🌟 Open in aéPiot
                    </button>
                    <button onclick="aiAepiotIntegration.shareConnection('${Array.from(this.aepiotConnections.keys()).find(k => this.aepiotConnections.get(k) === connection)}')" 
                            class="secondary-btn">
                        📤 Share
                    </button>
                </div>
            </div>
        `).join('');
        
        if (connections.length === 0) {
            connectionsList.innerHTML = `
                <div class="no-connections">
                    <h5>🔗 No Active Connections</h5>
                    <p>Start a conversation to see semantic connections appear automatically!</p>
                </div>
            `;
        }
    }
    
    updateToolsTab() {
        const quickSearchInput = document.getElementById('quick-search');
        if (quickSearchInput) {
            quickSearchInput.addEventListener('keypress', (e) => {
                if (e.key === 'Enter') {
                    this.quickSearch();
                }
            });
        }
    }
    
    // ================================
    // UTILITY FUNCTIONS
    // ================================
    
    getConnectionIcon(type) {
        const icons = {
            'backlink': '🔗',
            'reader': '📰',
            'advanced_search': '🔍',
            'question_search': '❓',
            'related_reports': '📊',
            'concept_analysis': '💡',
            'semantic_link': '🌟'
        };
        return icons[type] || '🔗';
    }
    
    getTimeAgo(timestamp) {
        const now = Date.now();
        const diff = now - timestamp;
        const minutes = Math.floor(diff / 60000);
        const hours = Math.floor(diff / 3600000);
        const days = Math.floor(diff / 86400000);
        
        if (days > 0) return `${days}d ago`;
        if (hours > 0) return `${hours}h ago`;
        if (minutes > 0) return `${minutes}m ago`;
        return 'just now';
    }
    
    calculateRelevanceScore(analysis) {
        const score = (
            (analysis.topics?.length || 0) * 0.3 +
            (analysis.concepts?.length || 0) * 0.4 +
            (analysis.questions?.length || 0) * 0.2 +
            (analysis.keywords?.length || 0) * 0.1
        );
        return Math.min(Math.round(score * 100) / 100, 10);
    }
    
    // ================================
    // USER INTERACTION METHODS
    // ================================
    
    manualSemanticAnalysis() {
        // Force semantic analysis of current page content
        const content = document.body.textContent;
        const semanticData = this.extractSemanticData(content);
        
        if (semanticData.relevantContent) {
            this.processSemanticContent(semanticData);
            this.updateLiveTab();
            
            // Show notification
            this.showNotification('🧠 Manual semantic analysis completed!', 'success');
        } else {
            this.showNotification('ℹ️ No relevant semantic content detected.', 'info');
        }
    }
    
    exportConversation() {
        // Export current conversation to aéPiot
        const conversationData = Array.from(this.conversationContext.values());
        const exportData = {
            timestamp: new Date().toISOString(),
            ai_system: this.aiSystem,
            conversation_length: conversationData.length,
            total_topics: conversationData.reduce((sum, data) => sum + (data.topics?.length || 0), 0),
            total_concepts: conversationData.reduce((sum, data) => sum + (data.concepts?.length || 0), 0),
            url: window.location.href
        };
        
        const backlink = this.generateAepiotBacklink({
            title: `AI-Conversation-Export-${Date.now()}`,
            description: `Complete conversation export from ${this.aiSystem} - ${exportData.total_topics} topics, ${exportData.total_concepts} concepts`,
            link: window.location.href
        });
        
        window.open(backlink, '_blank');
        this.showNotification('📤 Conversation exported to aéPiot!', 'success');
    }
    
    generateReport() {
        // Generate comprehensive report
        const conversationData = Array.from(this.conversationContext.values());
        const reportData = this.compileReport(conversationData);
        
        const reportBacklink = this.generateAepiotBacklink({
            title: `AI-Analysis-Report-${Date.now()}`,
            description: `Comprehensive AI conversation analysis report: ${reportData.summary}`,
            link: window.location.href
        });
        
        window.open(reportBacklink, '_blank');
        this.showNotification('📊 Analysis report generated!', 'success');
    }
    
    crossLinguisticAnalysis() {
        // Perform cross-linguistic analysis
        const languages = ['en', 'es', 'fr', 'de', 'ja', 'zh', 'ro', 'it'];
        const currentTopics = Array.from(this.conversationContext.values())
            .flatMap(data => data.topics || [])
            .slice(0, 3);
        
        currentTopics.forEach(topic => {
            languages.forEach(lang => {
                const multilingualSearch = this.generateAepiotAdvancedSearchURL({
                    query: topic.topic,
                    language: lang
                });
                
                // Store multilingual connection
                this.aepiotConnections.set(`multilingual_${topic.topic}_${lang}`, {
                    type: 'multilingual_search',
                    topic: topic.topic,
                    language: lang,
                    url: multilingualSearch,
                    timestamp: Date.now()
                });
            });
        });
        
        this.updateConnectionsTab();
        this.showNotification(`🌍 Cross-linguistic analysis completed for ${currentTopics.length} topics!`, 'success');
    }
    
    quickSearch() {
        const query = document.getElementById('quick-search').value.trim();
        if (query) {
            const searchUrl = this.generateAepiotAdvancedSearchURL({
                query: query,
                language: 'en'
            });
            
            window.open(searchUrl, '_blank');
            document.getElementById('quick-search').value = '';
        }
    }
    
    exploreConceptInAepiot(concept) {
        const searchUrl = this.generateAepiotAdvancedSearchURL({
            query: concept,
            language: 'en'
        });
        window.open(searchUrl, '_blank');
    }
    
    askQuestionInAepiot(question) {
        const cleanQuestion = question.replace(/[?]/g, '');
        const searchUrl = this.generateAepiotAdvancedSearchURL({
            query: cleanQuestion,
            language: 'en'
        });
        window.open(searchUrl, '_blank');
    }
    
    shareConnection(connectionId) {
        const connection = this.aepiotConnections.get(connectionId);
        if (connection && navigator.share) {
            navigator.share({
                title: `aéPiot Semantic Connection: ${connection.topic || 'Analysis'}`,
                text: `Check out this semantic analysis from AI conversation`,
                url: connection.url
            });
        } else if (connection) {
            // Fallback: copy to clipboard
            navigator.clipboard.writeText(connection.url);
            this.showNotification('📋 Connection URL copied to clipboard!', 'success');
        }
    }
    
    // ================================
    // NOTIFICATION SYSTEM
    // ================================
    
    showNotification(message, type = 'info') {
        const notification = document.createElement('div');
        notification.className = `ai-aepiot-notification notification-${type}`;
        notification.innerHTML = `
            <span class="notification-message">${message}</span>
            <button class="notification-close" onclick="this.parentElement.remove()">&times;</button>
        `;
        
        document.body.appendChild(notification);
        
        // Auto-remove after 5 seconds
        setTimeout(() => {
            if (notification.parentElement) {
                notification.remove();
            }
        }, 5000);
    }
    
    // ================================
    // ADVANCED FEATURES
    // ================================
    
    setupKeyboardShortcuts() {
        document.addEventListener('keydown', (event) => {
            // Ctrl+Shift+A: Toggle panel
            if (event.ctrlKey && event.shiftKey && event.key === 'A') {
                event.preventDefault();
                this.panel.style.display = this.panel.style.display === 'none' ? 'block' : 'none';
            }
            
            // Ctrl+Shift+S: Quick semantic analysis
            if (event.ctrlKey && event.shiftKey && event.key === 'S') {
                event.preventDefault();
                this.manualSemanticAnalysis();
            }
            
            // Ctrl+Shift+E: Export conversation
            if (event.ctrlKey && event.shiftKey && event.key === 'E') {
                event.preventDefault();
                this.exportConversation();
            }
        });
    }
    
    createInlineIntegrations() {
        // Create inline semantic hints and connections
        this.setupTextSelectionIntegration();
        this.setupContextMenuIntegration();
    }
    
    setupTextSelectionIntegration() {
        document.addEventListener('mouseup', (event) => {
            const selection = window.getSelection().toString().trim();
            if (selection.length > 5 && selection.length < 200) {
                this.createSelectionTooltip(selection, event.clientX, event.clientY);
            }
        });
        
        // Clear tooltip on click elsewhere
        document.addEventListener('click', (event) => {
            if (!event.target.closest('.selection-tooltip')) {
                const tooltips = document.querySelectorAll('.selection-tooltip');
                tooltips.forEach(tooltip => tooltip.remove());
            }
        });
    }
    
    createSelectionTooltip(text, x, y) {
        // Remove existing tooltips
        const existingTooltips = document.querySelectorAll('.selection-tooltip');
        existingTooltips.forEach(tooltip => tooltip.remove());
        
        const tooltip = document.createElement('div');
        tooltip.className = 'selection-tooltip';
        tooltip.innerHTML = `
            <div class="tooltip-content">
                <div class="tooltip-text">"${text.substring(0, 50)}${text.length > 50 ? '...' : ''}"</div>
                <div class="tooltip-actions">
                    <button onclick="aiAepiotIntegration.exploreSelectionInAepiot('${text.replace(/'/g, "\\'")}')">
                        🔍 Explore in aéPiot
                    </button>
                    <button onclick="aiAepiotIntegration.createSemanticBacklinkFromSelection('${text.replace(/'/g, "\\'")}')">
                        🔗 Create Link
                    </button>
                </div>
            </div>
        `;
        
        tooltip.style.position = 'fixed';
        tooltip.style.left = Math.min(x, window.innerWidth - 250) + 'px';
        tooltip.style.top = (y - 80) + 'px';
        tooltip.style.zIndex = '1000000';
        
        document.body.appendChild(tooltip);
        
        // Auto-remove after 10 seconds
        setTimeout(() => {
            if (tooltip.parentElement) {
                tooltip.remove();
            }
        }, 10000);
    }
    
    exploreSelectionInAepiot(text) {
        const searchUrl = this.generateAepiotAdvancedSearchURL({
            query: text,
            language: this.detectLanguage(text)
        });
        window.open(searchUrl, '_blank');
        
        // Remove tooltip
        const tooltips = document.querySelectorAll('.selection-tooltip');
        tooltips.forEach(tooltip => tooltip.remove());
    }
    
    createSemanticBacklinkFromSelection(text) {
        const backlink = this.generateAepiotBacklink({
            title: `AI-Selection-Analysis-${Date.now()}`,
            description: `Selected text analysis: "${text.substring(0, 100)}${text.length > 100 ? '...' : ''}"`,
            link: window.location.href
        });
        
        window.open(backlink, '_blank');
        
        // Remove tooltip
        const tooltips = document.querySelectorAll('.selection-tooltip');
        tooltips.forEach(tooltip => tooltip.remove());
        
        this.showNotification('🔗 Semantic backlink created for selection!', 'success');
    }
    
    // ================================
    // LANGUAGE DETECTION
    // ================================
    
    detectLanguage(text) {
        // Simple language detection based on common words
        const languagePatterns = {
            'en': /\b(the|and|is|in|to|of|a|that|it|with|for|as|was|on|are|you)\b/gi,
            'es': /\b(el|la|de|que|y|en|un|es|se|no|te|lo|le|da|su|por|son|con|para|una)\b/gi,
            'fr': /\b(le|de|et|à|un|il|être|et|en|avoir|que|pour|dans|ce|son|une|sur|avec|ne|se)\b/gi,
            'de': /\b(der|die|und|in|den|von|zu|das|mit|sich|des|auf|für|ist|im|dem|nicht|ein)\b/gi,
            'ro': /\b(si|de|in|la|cu|pe|pentru|este|sunt|sau|ca|din|mai|dar|nu|se|ce|un|una)\b/gi
        };
        
        let bestMatch = 'en';
        let highestScore = 0;
        
        for (const [lang, pattern] of Object.entries(languagePatterns)) {
            const matches = text.match(pattern);
            const score = matches ? matches.length / text.split(' ').length : 0;
            
            if (score > highestScore) {
                highestScore = score;
                bestMatch = lang;
            }
        }
        
        return bestMatch;
    }
    
    // ================================
    // CONTEXT MANAGEMENT
    // ================================
    
    updateConversationContext(semanticData) {
        const contextId = `context_${Date.now()}`;
        this.conversationContext.set(contextId, semanticData);
        
        // Keep only last 50 contexts to prevent memory issues
        if (this.conversationContext.size > 50) {
            const oldestKey = this.conversationContext.keys().next().value;
            this.conversationContext.delete(oldestKey);
        }
        
        // Update semantic memory
        this.updateSemanticMemory(semanticData);
    }
    
    updateSemanticMemory(semanticData) {
        // Build semantic memory for cross-conversation learning
        semanticData.concepts?.forEach(concept => {
            const memoryKey = concept.concept;
            if (!this.semanticMemory.has(memoryKey)) {
                this.semanticMemory.set(memoryKey, {
                    concept: concept.concept,
                    occurrences: 1,
                    contexts: [concept.context],
                    firstSeen: Date.now(),
                    lastSeen: Date.now()
                });
            } else {
                const memory = this.semanticMemory.get(memoryKey);
                memory.occurrences++;
                memory.contexts.push(concept.context);
                memory.lastSeen = Date.now();
                
                // Keep only last 10 contexts
                if (memory.contexts.length > 10) {
                    memory.contexts = memory.contexts.slice(-10);
                }
            }
        });
        
        // Persist semantic memory (optional)
        this.persistSemanticMemory();
    }
    
    persistSemanticMemory() {
        try {
            const memoryData = Object.fromEntries(this.semanticMemory);
            localStorage.setItem('ai_aepiot_semantic_memory', JSON.stringify(memoryData));
        } catch (error) {
            console.warn('Failed to persist semantic memory:', error);
        }
    }
    
    loadSemanticMemory() {
        try {
            const stored = localStorage.getItem('ai_aepiot_semantic_memory');
            if (stored) {
                const memoryData = JSON.parse(stored);
                Object.entries(memoryData).forEach(([key, value]) => {
                    this.semanticMemory.set(key, value);
                });
            }
        } catch (error) {
            console.warn('Failed to load semantic memory:', error);
        }
    }
    
    // ================================
    // REPORTING AND ANALYTICS
    // ================================
    
    compileReport(conversationData) {
        const report = {
            timestamp: new Date().toISOString(),
            ai_system: this.aiSystem,
            conversation_stats: {
                total_messages: conversationData.length,
                total_topics: conversationData.reduce((sum, data) => sum + (data.topics?.length || 0), 0),
                total_concepts: conversationData.reduce((sum, data) => sum + (data.concepts?.length || 0), 0),
                total_questions: conversationData.reduce((sum, data) => sum + (data.questions?.length || 0), 0),
                total_keywords: conversationData.reduce((sum, data) => sum + (data.keywords?.length || 0), 0)
            },
            top_topics: this.getTopTopics(conversationData),
            top_concepts: this.getTopConcepts(conversationData),
            language_distribution: this.getLanguageDistribution(conversationData),
            aepiot_connections: {
                total_connections: this.aepiotConnections.size,
                connection_types: this.getConnectionTypeStats(),
                most_recent: Array.from(this.aepiotConnections.values())
                    .sort((a, b) => b.timestamp - a.timestamp)
                    .slice(0, 5)
            }
        };
        
        report.summary = this.generateReportSummary(report);
        
        return report;
    }
    
    getTopTopics(conversationData) {
        const topicFreq = {};
        conversationData.forEach(data => {
            data.topics?.forEach(topic => {
                topicFreq[topic.topic] = (topicFreq[topic.topic] || 0) + topic.relevance;
            });
        });
        
        return Object.entries(topicFreq)
            .sort(([,a], [,b]) => b - a)
            .slice(0, 10)
            .map(([topic, score]) => ({ topic, score: Math.round(score * 100) / 100 }));
    }
    
    getTopConcepts(conversationData) {
        const conceptFreq = {};
        conversationData.forEach(data => {
            data.concepts?.forEach(concept => {
                conceptFreq[concept.concept] = (conceptFreq[concept.concept] || 0) + 1;
            });
        });
        
        return Object.entries(conceptFreq)
            .sort(([,a], [,b]) => b - a)
            .slice(0, 10)
            .map(([concept, frequency]) => ({ concept, frequency }));
    }
    
    getLanguageDistribution(conversationData) {
        const langCount = {};
        conversationData.forEach(data => {
            const lang = this.detectLanguage(data.originalText);
            langCount[lang] = (langCount[lang] || 0) + 1;
        });
        
        return langCount;
    }
    
    getConnectionTypeStats() {
        const typeStats = {};
        Array.from(this.aepiotConnections.values()).forEach(connection => {
            typeStats[connection.type] = (typeStats[connection.type] || 0) + 1;
        });
        
        return typeStats;
    }
    
    generateReportSummary(report) {
        const stats = report.conversation_stats;
        const topTopic = report.top_topics[0]?.topic || 'general discussion';
        
        return `${stats.total_messages} messages analyzed, focusing on ${topTopic}. Generated ${report.aepiot_connections.total_connections} aéPiot connections across ${Object.keys(report.aepiot_connections.connection_types).length} connection types.`;
    }
    
    // ================================
    // STYLING SYSTEM
    // ================================
    
    addIntegrationStyles() {
        if (document.getElementById('ai-aepiot-integration-styles')) return;
        
        const styles = `
<style id="ai-aepiot-integration-styles">
/* Universal AI-aéPiot Integration Styles */
.ai-aepiot-integration-panel {
    position: fixed;
    top: 20px;
    right: 20px;
    width: 420px;
    max-height: 85vh;
    background: linear-gradient(135deg, #1a1a2e 0%, #16213e 50%, #0f3460 100%);
    border: 2px solid rgba(100, 200, 255, 0.3);
    border-radius: 20px;
    box-shadow: 
        0 25px 50px rgba(0, 0, 0, 0.3),
        0 0 0 1px rgba(255, 255, 255, 0.1),
        inset 0 1px 0 rgba(255, 255, 255, 0.1);
    backdrop-filter: blur(20px);
    z-index: 999999;
    font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'SF Pro Display', sans-serif;
    color: #ffffff;
    overflow: hidden;
    transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
}

.ai-aepiot-integration-panel.minimized {
    height: 70px;
}

.ai-aepiot-integration-panel.minimized .panel-content {
    display: none;
}

.panel-header {
    background: linear-gradient(135deg, rgba(100, 200, 255, 0.15) 0%, rgba(120, 119, 198, 0.15) 100%);
    padding: 20px;
    border-bottom: 1px solid rgba(255, 255, 255, 0.1);
    display: flex;
    justify-content: space-between;
    align-items: center;
    backdrop-filter: blur(10px);
}

.panel-title {
    font-size: 16px;
    font-weight: 700;
    letter-spacing: 0.5px;
    display: flex;
    align-items: center;
    gap: 12px;
}

.ai-system-badge {
    background: linear-gradient(45deg, #64c8ff, #7877c6);
    padding: 4px 12px;
    border-radius: 12px;
    font-size: 11px;
    font-weight: 600;
    text-transform: uppercase;
    letter-spacing: 0.5px;
}

.panel-controls {
    display: flex;
    gap: 8px;
}

.minimize-btn, .close-btn {
    background: rgba(255, 255, 255, 0.1);
    border: none;
    color: white;
    width: 32px;
    height: 32px;
    border-radius: 50%;
    cursor: pointer;
    transition: all 0.3s ease;
    font-size: 18px;
    display: flex;
    align-items: center;
    justify-content: center;
}

.minimize-btn:hover, .close-btn:hover {
    background: rgba(255, 255, 255, 0.2);
    transform: scale(1.1);
}

.close-btn:hover {
    background: rgba(255, 99, 71, 0.3);
}

.panel-content {
    max-height: calc(85vh - 70px);
    overflow: hidden;
}

.tab-navigation {
    display: flex;
    background: rgba(0, 0, 0, 0.2);
    backdrop-filter: blur(10px);
}

.tab-btn {
    flex: 1;
    background: none;
    border: none;
    color: rgba(255, 255, 255, 0.6);
    padding: 16px 12px;
    font-size: 13px;
    font-weight: 600;
    cursor: pointer;
    transition: all 0.3s ease;
    position: relative;
    text-transform: uppercase;
    letter-spacing: 0.5px;
}

.tab-btn.active {
    color: #ffffff;
    background: linear-gradient(135deg, rgba(100, 200, 255, 0.2) 0%, rgba(120, 119, 198, 0.2) 100%);
}

.tab-btn.active::after {
    content: '';
    position: absolute;
    bottom: 0;
    left: 0;
    right: 0;
    height: 2px;
    background: linear-gradient(90deg, #64c8ff, #7877c6);
}

.tab-btn:hover:not(.active) {
    color: rgba(255, 255, 255, 0.8);
    background: rgba(255, 255, 255, 0.05);
}

.tab-content {
    height: calc(85vh - 140px);
    overflow-y: auto;
    scrollbar-width: thin;
    scrollbar-color: rgba(100, 200, 255, 0.3) transparent;
}

.tab-content::-webkit-scrollbar {
    width: 6px;
}

.tab-content::-webkit-scrollbar-track {
    background: transparent;
}

.tab-content::-webkit-scrollbar-thumb {
    background: rgba(100, 200, 255, 0.3);
    border-radius: 3px;
}

.tab-panel {
    display: none;
    padding: 24px;
}

.tab-panel.active {
    display: block;
}

/* Live Tab Styles */
.processing-stats {
    display: grid;
    grid-template-columns: repeat(3, 1fr);
    gap: 16px;
    margin-bottom: 24px;
}

.stat {
    background: rgba(255, 255, 255, 0.05);
    padding: 16px;
    border-radius: 12px;
    text-align: center;
    border: 1px solid rgba(100, 200, 255, 0.2);
}

.stat label {
    display: block;
    font-size: 11px;
    color: rgba(255, 255, 255, 0.7);
    margin-bottom: 8px;
    text-transform: uppercase;
    letter-spacing: 0.5px;
}

.stat span {
    font-size: 24px;
    font-weight: 700;
    color: #64c8ff;
}

.live-connection {
    background: rgba(255, 255, 255, 0.05);
    border-radius: 12px;
    padding: 16px;
    margin-bottom: 12px;
    border-left: 4px solid;
    transition: all 0.3s ease;
}

.live-connection:hover {
    background: rgba(255, 255, 255, 0.08);
    transform: translateX(4px);
}

.connection-backlink { border-left-color: #64c8ff; }
.connection-reader { border-left-color: #7877c6; }
.connection-advanced_search { border-left-color: #ff6b6b; }
.connection-question_search { border-left-color: #4ecdc4; }
.connection-related_reports { border-left-color: #ffe66d; }

.connection-header {
    display: flex;
    justify-content: space-between;
    align-items: center;
    margin-bottom: 8px;
}

.connection-type {
    font-size: 12px;
    font-weight: 600;
    text-transform: uppercase;
    letter-spacing: 0.5px;
}

.connection-time {
    font-size: 11px;
    color: rgba(255, 255, 255, 0.5);
}

.connection-content {
    font-size: 14px;
    line-height: 1.4;
    margin-bottom: 12px;
    color: rgba(255, 255, 255, 0.9);
}

.open-btn, .primary-btn {
    background: linear-gradient(135deg, #64c8ff 0%, #7877c6 100%);
    border: none;
    color: white;
    padding: 8px 16px;
    border-radius: 20px;
    font-size: 12px;
    font-weight: 600;
    cursor: pointer;
    transition: all 0.3s ease;
    text-transform: uppercase;
    letter-spacing: 0.5px;
}

.open-btn:hover, .primary-btn:hover {
    transform: translateY(-2px);
    box-shadow: 0 8px 25px rgba(100, 200, 255, 0.3);
}

.secondary-btn {
    background: rgba(255, 255, 255, 0.1);
    border: 1px solid rgba(255, 255, 255, 0.2);
    color: white;
    padding: 8px 16px;
    border-radius: 20px;
    font-size: 12px;
    font-weight: 600;
    cursor: pointer;
    transition: all 0.3s ease;
    text-transform: uppercase;
    letter-spacing: 0.5px;
    margin-left: 8px;
}

.secondary-btn:hover {
    background: rgba(255, 255, 255, 0.2);
    border-color: rgba(255, 255, 255, 0.4);
}

/* Semantic Tab Styles */
.semantic-analysis-item {
    background: rgba(255, 255, 255, 0.03);
    border-radius: 16px;
    padding: 20px;
    margin-bottom: 20px;
    border: 1px solid rgba(100, 200, 255, 0.1);
}

.analysis-header {
    display: flex;
    justify-content: space-between;
    align-items: center;
    margin-bottom: 16px;
}

.analysis-header h5 {
    margin: 0;
    font-size: 16px;
    font-weight: 600;
    color: #64c8ff;
}

.relevance-score {
    background: rgba(100, 200, 255, 0.2);
    padding: 4px 12px;
    border-radius: 12px;
    font-size: 11px;
    font-weight: 600;
    color: #64c8ff;
}

.topics-list, .concepts-list, .questions-list {
    display: flex;
    flex-direction: column;
    gap: 8px;
}

.topic-tag {
    display: inline-block;
    background: rgba(100, 200, 255, 0.15);
    color: #64c8ff;
    padding: 6px 12px;
    border-radius: 20px;
    font-size: 12px;
    font-weight: 500;
    margin-right: 8px;
    margin-bottom: 8px;
    border: 1px solid rgba(100, 200, 255, 0.3);
}

.concept-item, .question-item {
    display: flex;
    justify-content: space-between;
    align-items: center;
    background: rgba(255, 255, 255, 0.05);
    padding: 12px;
    border-radius: 8px;
    border: 1px solid rgba(255, 255, 255, 0.1);
}

.concept-text, .question-text {
    flex: 1;
    font-size: 13px;
    line-height: 1.4;
}

.explore-concept-btn, .ask-btn {
    background: linear-gradient(135deg, #7877c6 0%, #64c8ff 100%);
    border: none;
    color: white;
    padding: 6px 12px;
    border-radius: 16px;
    font-size: 11px;
    font-weight: 600;
    cursor: pointer;
    transition: all 0.3s ease;
    margin-left: 12px;
}

.explore-concept-btn:hover, .ask-btn:hover {
    transform: scale(1.05);
    box-shadow: 0 4px 12px rgba(120, 119, 198, 0.4);
}

/* Connections Tab Styles */
.connection-item {
    background: rgba(255, 255, 255, 0.03);
    border-radius: 12px;
    padding: 16px;
    margin-bottom: 12px;
    border-left: 4px solid #64c8ff;
    border: 1px solid rgba(255, 255, 255, 0.1);
    transition: all 0.3s ease;
}

.connection-item:hover {
    background: rgba(255, 255, 255, 0.08);
    transform: translateY(-2px);
    box-shadow: 0 8px 25px rgba(0, 0, 0, 0.2);
}

.connection-icon {
    font-size: 16px;
    margin-right: 8px;
}

.connection-title {
    flex: 1;
    font-weight: 600;
    font-size: 14px;
}

.connection-details {
    display: flex;
    gap: 16px;
    margin: 8px 0;
    font-size: 12px;
    color: rgba(255, 255, 255, 0.7);
}

.connection-type-label {
    background: rgba(100, 200, 255, 0.2);
    padding: 2px 8px;
    border-radius: 8px;
    font-size: 10px;
    text-transform: uppercase;
    font-weight: 600;
    color: #64c8ff;
}

.keywords {
    font-style: italic;
}

.connection-actions {
    display: flex;
    gap: 8px;
    margin-top: 12px;
}

.no-connections {
    text-align: center;
    padding: 40px 20px;
    color: rgba(255, 255, 255, 0.6);
}

.no-connections h5 {
    margin-bottom: 8px;
    color: #64c8ff;
}

/* Tools Tab Styles */
.tools-grid {
    display: grid;
    grid-template-columns: repeat(2, 1fr);
    gap: 12px;
    margin-bottom: 24px;
}

.tool-btn {
    background: rgba(255, 255, 255, 0.05);
    border: 1px solid rgba(100, 200, 255, 0.2);
    color: white;
    padding: 16px 12px;
    border-radius: 12px;
    font-size: 12px;
    font-weight: 600;
    cursor: pointer;
    transition: all 0.3s ease;
    text-align: center;
}

.tool-btn:hover {
    background: rgba(100, 200, 255, 0.1);
    border-color: rgba(100, 200, 255, 0.4);
    transform: translateY(-2px);
}

.quick-actions {
    background: rgba(255, 255, 255, 0.03);
    padding: 20px;
    border-radius: 12px;
    border: 1px solid rgba(100, 200, 255, 0.1);
}

.quick-actions h5 {
    margin: 0 0 16px 0;
    font-size: 14px;
    color: #64c8ff;
}

.quick-actions input {
    width: 100%;
    background: rgba(255, 255, 255, 0.1);
    border: 1px solid rgba(255, 255, 255, 0.2);
    color: white;
    padding: 12px 16px;
    border-radius: 25px;
    font-size: 14px;
    margin-bottom: 12px;
    outline: none;
    transition: all 0.3s ease;
}

.quick-actions input:focus {
    border-color: #64c8ff;
    box-shadow: 0 0 0 3px rgba(100, 200, 255, 0.1);
}

.quick-actions input::placeholder {
    color: rgba(255, 255, 255, 0.5);
}

.quick-actions button {
    width: 100%;
    background: linear-gradient(135deg, #64c8ff 0%, #7877c6 100%);
    border: none;
    color: white;
    padding: 12px;
    border-radius: 25px;
    font-size: 14px;
    font-weight: 600;
    cursor: pointer;
    transition: all 0.3s ease;
}

.quick-actions button:hover {
    transform: translateY(-2px);
    box-shadow: 0 8px 25px rgba(100, 200, 255, 0.3);
}

/* Selection Tooltip Styles */
.selection-tooltip {
    background: rgba(26, 26, 46, 0.95);
    backdrop-filter: blur(20px);
    border: 1px solid rgba(100, 200, 255, 0.3);
    border-radius: 12px;
    padding: 16px;
    box-shadow: 0 15px 35px rgba(0, 0, 0, 0.3);
    max-width: 280px;
    z-index: 1000000;
}

.tooltip-content {
    color: white;
}

.tooltip-text {
    font-size: 13px;
    margin-bottom: 12px;
    color: rgba(255, 255, 255, 0.9);
    font-style: italic;
}

.tooltip-actions {
    display: flex;
    gap: 8px;
}

.tooltip-actions button {
    background: linear-gradient(135deg, #64c8ff 0%, #7877c6 100%);
    border: none;
    color: white;
    padding: 8px 12px;
    border-radius: 16px;
    font-size: 11px;
    font-weight: 600;
    cursor: pointer;
    transition: all 0.3s ease;
    flex: 1;
}

.tooltip-actions button:hover {
    transform: scale(1.05);
    box-shadow: 0 4px 12px rgba(100, 200, 255, 0.4);
}

/* Notification Styles */
.ai-aepiot-notification {
    position: fixed;
    top: 120px;
    right: 20px;
    background: rgba(26, 26, 46, 0.95);
    backdrop-filter: blur(20px);
    border: 1px solid;
    border-radius: 12px;
    padding: 16px;
    max-width: 350px;
    z-index: 1000001;
    display: flex;
    align-items: center;
    gap: 12px;
    box-shadow: 0 15px 35px rgba(0, 0, 0, 0.3);
    animation: slideIn 0.4s cubic-bezier(0.4, 0, 0.2, 1);
}

@keyframes slideIn {
    from {
        transform: translateX(100%);
        opacity: 0;
    }
    to {
        transform: translateX(0);
        opacity: 1;
    }
}

.notification-success {
    border-color: #4ade80;
    color: #4ade80;
}

.notification-info {
    border-color: #64c8ff;
    color: #64c8ff;
}

.notification-warning {
    border-color: #fbbf24;
    color: #fbbf24;
}

.notification-error {
    border-color: #f87171;
    color: #f87171;
}

.notification-message {
    flex: 1;
    font-size: 14px;
    font-weight: 500;
}

.notification-close {
    background: none;
    border: none;
    color: inherit;
    cursor: pointer;
    font-size: 18px;
    padding: 4px;
    border-radius: 50%;
    transition: all 0.3s ease;
}

.notification-close:hover {
    background: rgba(255, 255, 255, 0.1);
}

/* Responsive Design */
@media (max-width: 768px) {
    .ai-aepiot-integration-panel {
        width: calc(100vw - 40px);
        right: 20px;
        left: 20px;
        top: 10px;
        max-height: calc(100vh - 20px);
    }
    
    .tools-grid {
        grid-template-columns: 1fr;
    }
    
    .processing-stats {
        grid-template-columns: 1fr;
        gap: 12px;
    }
    
    .selection-tooltip {
        max-width: calc(100vw - 60px);
        left: 30px !important;
        right: 30px !important;
        width: auto !important;
    }
    
    .tooltip-actions {
        flex-direction: column;
    }
}

/* Animation Enhancements */
.ai-aepiot-integration-panel {
    animation: panelSlideIn 0.5s cubic-bezier(0.4, 0, 0.2, 1);
}

@keyframes panelSlideIn {
    from {
        transform: translateX(100%);
        opacity: 0;
    }
    to {
        transform: translateX(0);
        opacity: 1;
    }
}

.tab-panel.active {
    animation: tabFadeIn 0.3s ease;
}

@keyframes tabFadeIn {
    from {
        opacity: 0;
        transform: translateY(10px);
    }
    to {
        opacity: 1;
        transform: translateY(0);
    }
}

/* Accessibility Improvements */
.ai-aepiot-integration-panel button:focus,
.ai-aepiot-integration-panel input:focus {
    outline: 2px solid #64c8ff;
    outline-offset: 2px;
}

.ai-aepiot-integration-panel button:focus-visible,
.ai-aepiot-integration-panel input:focus-visible {
    outline: 2px solid #64c8ff;
    outline-offset: 2px;
}

/* High contrast mode support */
@media (prefers-contrast: high) {
    .ai-aepiot-integration-panel {
        border: 3px solid #ffffff;
    }
    
    .tab-btn.active {
        background: #ffffff;
        color: #000000;
    }
}

/* Reduced motion support */
@media (prefers-reduced-motion: reduce) {
    * {
        animation-duration: 0.01ms !important;
        animation-iteration-count: 1 !important;
        transition-duration: 0.01ms !important;
    }
}
</style>
        `;
        
        document.head.insertAdjacentHTML('beforeend', styles);
    }
    
    // ================================
    // ADVANCED AI INTEGRATION METHODS
    // ================================
    
    initializeSemanticProcessing() {
        // Load previously stored semantic memory
        this.loadSemanticMemory();
        
        // Setup real-time semantic processing pipeline
        this.setupSemanticPipeline();
        
        // Initialize advanced AI features
        this.initializeAdvancedAIFeatures();
    }
    
    setupSemanticPipeline() {
        // Create semantic processing pipeline
        this.semanticPipeline = {
            input: new Map(),
            processing: new Map(),
            output: new Map(),
            errors: new Map()
        };
        
        // Setup pipeline processing
        setInterval(() => {
            this.processSemanticPipeline();
        }, 2000); // Process every 2 seconds
    }
    
    processSemanticPipeline() {
        // Process items in the semantic pipeline
        for (const [id, data] of this.semanticPipeline.input) {
            try {
                this.semanticPipeline.processing.set(id, Date.now());
                
                // Process semantic data
                const processedData = this.enhanceSemanticData(data);
                
                // Move to output
                this.semanticPipeline.output.set(id, processedData);
                
                // Clean up
                this.semanticPipeline.input.delete(id);
                this.semanticPipeline.processing.delete(id);
                
                // Update UI if needed
                this.updateSemanticUI(processedData);
                
            } catch (error) {
                this.semanticPipeline.errors.set(id, error);
                this.semanticPipeline.input.delete(id);
                this.semanticPipeline.processing.delete(id);
                console.warn('Semantic processing error:', error);
            }
        }
    }
    
    enhanceSemanticData(data) {
        // Enhance semantic data with advanced processing
        const enhanced = { ...data };
        
        // Add temporal context
        enhanced.temporalContext = this.analyzeTemporalContext(data);
        
        // Add cross-references
        enhanced.crossReferences = this.findCrossReferences(data);
        
        // Add semantic depth scoring
        enhanced.semanticDepth = this.calculateSemanticDepth(data);
        
        // Add aéPiot integration suggestions
        enhanced.aepiotSuggestions = this.generateAepiotSuggestions(data);
        
        return enhanced;
    }
    
    analyzeTemporalContext(data) {
        // Analyze temporal patterns in the conversation
        const timeOfDay = new Date().getHours();
        const dayOfWeek = new Date().getDay();
        
        return {
            timeOfDay: timeOfDay,
            dayOfWeek: dayOfWeek,
            temporalRelevance: this.calculateTemporalRelevance(data, timeOfDay),
            historicalContext: this.findHistoricalContext(data)
        };
    }
    
    calculateTemporalRelevance(data, timeOfDay) {
        // Calculate relevance based on time
        let relevance = 1.0;
        
        // Business hours boost for business topics
        if (timeOfDay >= 9 && timeOfDay <= 17) {
            const businessTopics = data.topics?.filter(t => t.topic === 'business') || [];
            if (businessTopics.length > 0) {
                relevance += 0.2;
            }
        }
        
        // Evening boost for educational content
        if (timeOfDay >= 18 && timeOfDay <= 22) {
            const educationalTopics = data.topics?.filter(t => t.topic === 'education') || [];
            if (educationalTopics.length > 0) {
                relevance += 0.15;
            }
        }
        
        return Math.min(relevance, 2.0);
    }
    
    findCrossReferences(data) {
        // Find cross-references in semantic memory
        const crossRefs = [];
        
        data.concepts?.forEach(concept => {
            const memoryEntry = this.semanticMemory.get(concept.concept);
            if (memoryEntry && memoryEntry.occurrences > 1) {
                crossRefs.push({
                    concept: concept.concept,
                    previousOccurrences: memoryEntry.occurrences,
                    previousContexts: memoryEntry.contexts.slice(-3), // Last 3 contexts
                    relevance: this.calculateCrossRefRelevance(concept, memoryEntry)
                });
            }
        });
        
        return crossRefs.sort((a, b) => b.relevance - a.relevance);
    }
    
    calculateSemanticDepth(data) {
        // Calculate semantic depth score
        let depth = 0;
        
        // Base scoring
        depth += (data.topics?.length || 0) * 2;
        depth += (data.concepts?.length || 0) * 3;
        depth += (data.questions?.length || 0) * 1.5;
        depth += (data.entities?.length || 0) * 0.5;
        
        // Complexity bonuses
        const complexConcepts = data.concepts?.filter(c => c.concept.includes(' ')) || [];
        depth += complexConcepts.length * 2;
        
        // Question complexity bonus
        const complexQuestions = data.questions?.filter(q => q.split(' ').length > 8) || [];
        depth += complexQuestions.length * 1.5;
        
        return Math.min(depth, 100); // Cap at 100
    }
    
    generateAepiotSuggestions(data) {
        // Generate intelligent aéPiot integration suggestions
        const suggestions = [];
        
        // High-value topic suggestions
        data.topics?.filter(t => t.relevance > 0.7).forEach(topic => {
            suggestions.push({
                type: 'high_value_topic',
                topic: topic.topic,
                action: 'create_semantic_backlink',
                priority: 'high',
                url: this.generateAepiotBacklink({
                    title: `High-Value-${topic.topic}-Analysis`,
                    description: `Deep semantic analysis of ${topic.topic} with ${topic.relevance} relevance score`,
                    link: window.location.href
                })
            });
        });
        
        // Complex concept suggestions
        const complexConcepts = data.concepts?.filter(c => c.concept.split(' ').length > 1) || [];
        complexConcepts.forEach(concept => {
            suggestions.push({
                type: 'complex_concept',
                concept: concept.concept,
                action: 'advanced_search',
                priority: 'medium',
                url: this.generateAepiotAdvancedSearchURL({
                    query: concept.concept,
                    language: this.detectLanguage(data.originalText)
                })
            });
        });
        
        // Question exploration suggestions
        data.questions?.forEach(question => {
            if (question.length > 20) { // Substantial questions only
                suggestions.push({
                    type: 'substantial_question',
                    question: question,
                    action: 'question_exploration',
                    priority: 'medium',
                    url: this.generateAepiotAdvancedSearchURL({
                        query: question.replace(/[?]/g, ''),
                        language: 'en'
                    })
                });
            }
        });
        
        return suggestions.sort((a, b) => {
            const priorityOrder = { high: 3, medium: 2, low: 1 };
            return priorityOrder[b.priority] - priorityOrder[a.priority];
        });
    }
    
    // ================================
    // AI SYSTEM SPECIFIC ENHANCEMENTS
    // ================================
    
    initializeAdvancedAIFeatures() {
        // Initialize AI-specific enhanced features
        this.setupAISpecificFeatures();
        this.initializeConversationalAI();
        this.setupIntelligentSuggestions();
    }
    
    setupAISpecificFeatures() {
        switch (this.aiSystem) {
            case 'claude':
                this.initializeClaudeEnhancements();
                break;
            case 'chatgpt':
                this.initializeChatGPTEnhancements();
                break;
            case 'gemini':
                this.initializeGeminiEnhancements();
                break;
            default:
                this.initializeGenericAIEnhancements();
        }
    }
    
    initializeClaudeEnhancements() {
        // Claude-specific enhancements
        this.claudeFeatures = {
            analysisDepth: 'deep',
            contextWindow: 'large',
            reasoningCapability: 'high',
            specializations: ['analysis', 'research', 'writing', 'coding']
        };
        
        // Enhanced prompt suggestions for Claude
        this.claudePromptTemplates = [
            'Can you analyze the deeper implications of: "{concept}"?',
            'What are the interdisciplinary connections to: "{topic}"?',
            'How might this evolve in different cultural contexts: "{content}"?',
            'What are the ethical considerations around: "{concept}"?',
            'Can you break down the complexity of: "{topic}" into fundamental components?'
        ];
    }
    
    initializeChatGPTEnhancements() {
        // ChatGPT-specific enhancements
        this.chatgptFeatures = {
            conversationalStyle: 'natural',
            creativityLevel: 'high',
            knowledgeBase: 'broad',
            specializations: ['conversation', 'creativity', 'explanation', 'problem-solving']
        };
        
        // Enhanced prompt suggestions for ChatGPT
        this.chatgptPromptTemplates = [
            'Explain "{concept}" in an engaging and accessible way',
            'What creative applications could "{topic}" have?',
            'How would you teach "{content}" to different age groups?',
            'What are some innovative approaches to: "{concept}"?',
            'Can you create analogies to help understand: "{topic}"?'
        ];
    }
    
    initializeGeminiEnhancements() {
        // Gemini-specific enhancements
        this.geminiFeatures = {
            multimodalCapability: 'high',
            searchIntegration: 'native',
            realTimeData: 'available',
            specializations: ['search', 'multimodal', 'current-events', 'factual-accuracy']
        };
        
        // Enhanced prompt suggestions for Gemini
        this.geminiPromptTemplates = [
            'What are the latest developments in: "{topic}"?',
            'Can you fact-check and provide sources for: "{concept}"?',
            'How does "{content}" relate to current trends?',
            'What visual representations would help explain: "{topic}"?',
            'What are experts currently saying about: "{concept}"?'
        ];
    }
    
    initializeGenericAIEnhancements() {
        // Generic AI enhancements for unknown systems
        this.genericFeatures = {
            adaptability: 'high',
            learningCapability: 'dynamic',
            integrationApproach: 'universal'
        };
        
        this.genericProm

Official aéPiot Domains

• https://headlines-world.com (since 2023)
• https://aepiot.com (since 2009)
• https://aepiot.ro (since 2009)
• https://allgraph.ro (since 2009)

aéPiot AI Integration Script - Complete User Guide

This guide explains the full functionality of the AI integration script for aéPiot, designed for users with external AI systems who do not operate an aéPiot server.

1. Overview

The script provides local tools to:

• Perform semantic analysis of webpage content.
• Generate AI-relevant suggestions and backlink URLs for aéPiot.
• Track and store semantic memory across conversations.
• Provide a rich interactive UI with notifications, tooltips, and tabbed panels.
• Enable cross-linguistic exploration of topics.

2. Semantic Analysis Features

• manualSemanticAnalysis(): Forces semantic analysis of current page text.
• calculateRelevanceScore(analysis): Computes a relevance score based on topics, concepts, questions, and keywords.
• Enhances semantic data by adding:
  • Temporal context (time of day, day of week)
  • Cross-references from previous semantic memory
  • Semantic depth scoring
  • aéPiot suggestion links for high-value topics, complex concepts, and substantial questions

3. Backlinks & aéPiot Integration

• generateAepiotBacklink(): Creates a unique URL that points to aéPiot with a title, description, and link.
• User clicks the backlink to access aéPiot with prefilled analysis data.
• createSemanticBacklinkFromSelection(text): Generates a backlink for any selected text on the page.
• No server is required; all links open directly in the browser for user interaction.

4. Cross-Linguistic Analysis

The script can generate searches in multiple languages for the top topics in the current conversation:

• Languages include English, Spanish, French, German, Japanese, Chinese, Romanian, Italian.
• Generates separate aéPiot search URLs for each language automatically.

5. Conversation Context Management

• Updates a local conversation context map with a maximum of 50 entries.
• Tracks topics, concepts, questions, keywords, and timestamps.
• Maintains a semantic memory of concepts with occurrences and contexts.
• Persists semantic memory in localStorage for cross-session AI learning.

6. User Interface Components

• Panel with tabbed interface for Live Analysis, Semantic Insights, Connections, and Tools.
• Inline selection tooltips for selected text with options:
  • 🔍 Explore in aéPiot
  • 🔗 Create Semantic Backlink
• Notifications system with success, info, warning, error types.
• Keyboard shortcuts:
  • Ctrl+Shift+A: Toggle panel
  • Ctrl+Shift+S: Quick semantic analysis
  • Ctrl+Shift+E: Export conversation

7. Reporting & Analytics

• compileReport(conversationData): Generates a detailed report including:
  • Total messages, topics, concepts, questions, keywords
  • Top topics and top concepts
  • Language distribution
  • aéPiot connection stats and recent links
• generateReportSummary(report): Creates a short human-readable summary of the report.

8. AI System-Specific Enhancements

• Supports multiple AI systems: Claude, ChatGPT, Gemini, or generic AI.
• Each AI system has specialized prompt templates and feature sets.
  • Claude: Deep analysis, interdisciplinary insights, ethical considerations.
  • ChatGPT: Conversational, creative, explanatory prompts.
  • Gemini: Multimodal, real-time data, factual checking, search-integrated prompts.

9. Quick Actions & Tools

• Quick search field for generating an aéPiot advanced search.
• Buttons for exploring concepts, asking questions, and exporting conversation data.
• Tool grid for frequently used AI functions and semantic operations.

10. Accessibility & Responsive Design

• High-contrast mode support
• Reduced-motion mode for animations
• Keyboard focus outlines for all interactive elements
• Responsive layout for smaller screens (mobile, tablet)

11. Notifications & Tooltips

• Selection tooltip appears for text between 5 and 200 characters.
• Tooltips auto-hide after 10 seconds or when user clicks outside.
• Notifications slide in and fade out automatically.

12. Initialization & Setup

• Call initializeSemanticProcessing() to load memory and setup pipeline.
• Semantic pipeline processes input items every 2 seconds.
• Enhances each semantic item with temporal, cross-reference, and depth info before updating UI.

Note: This script operates entirely on the client-side. No server or API access is required. Users with external AI systems can use all features locally, while generating backlinks and search links to aéPiot.

13. Summary

The aéPiot AI integration script provides a full suite of tools for semantic analysis, cross-linguistic exploration, concept and topic enhancement, and generating actionable backlinks for the aéPiot platform. It is designed for local AI environments without the need for a server, providing a rich interactive experience for users, with notifications, tooltips, reports, and AI system-specific prompt suggestions.

https://medium.com/@global.audiences/universal-ai-a%C3%A9piot-integration-system-624f823e6812

https://scribd.com/document/914488046/Universal-AI-AePiot-Integration-System-Complete-Integration-Framework-for-All-AI-Systems-Claude-ChatGPT-Gemini-And-Future-AIs

https://www.linkedin.com/posts/work-aepiot-b6a407380_universal-ai-a%C3%A9piot-integration-system-complete-activity-7371190342630518785-iV6a

https://www.linkedin.com/posts/work-aepiot-b6a407380_universal-ai-a%C3%A9piot-integration-system-activity-7371189936944730112-vB8M

https://www.linkedin.com/posts/work-aepiot-b6a407380_universal-ai-a%C3%A9piot-integration-system-complete-activity-7371189757701148672-UYbM