world_class_optimizer.js

// AI SYSTEM ITERATIVE IMPROVEMENT ENGINE
// Goal: Achieve world-class performance recognized by 7.2 billion people

import { runComprehensiveAnalysis } from './comprehensive_analyzer.js';
import { readFile, writeFile } from 'fs/promises';
import { join, dirname } from 'path';
import { fileURLToPath } from 'url';

const __filename = fileURLToPath(import.meta.url);
const __dirname = dirname(__filename);

console.log('🌟 AI SYSTEM WORLD-CLASS OPTIMIZATION ENGINE');
console.log('🎯 Mission: Create the BEST AI system in the world!');
console.log('=' .repeat(70));

class WorldClassOptimizer {
    constructor() {
        this.targetScore = 95; // World-class threshold
        this.maxIterations = 10;
        this.currentIteration = 0;
        this.optimizationHistory = [];
        this.currentScore = 0;
    }

    // Analyze current prompts and identify improvement areas
    async analyzePrompts() {
        console.log('🔍 ANALYZING CURRENT PROMPTS...');
        
        const promptFiles = [
            'system.md', 'supervisor.md', 'emotion.md', 'enhancement.md', 
            'memory.md', 'retrieval.md', 'summarization.md', 'tags.md', 'report.md'
        ];
        
        const promptAnalysis = {};
        
        for (const file of promptFiles) {
            try {
                const promptPath = join(__dirname, 'prompts', file);
                const content = await readFile(promptPath, 'utf-8');
                
                promptAnalysis[file] = {
                    length: content.length,
                    wordCount: content.split(/\s+/).length,
                    hasEmotionalGuidance: content.toLowerCase().includes('empathy') || content.toLowerCase().includes('emotional'),
                    hasActionableInstructions: content.toLowerCase().includes('actionable') || content.toLowerCase().includes('practical'),
                    hasPersonalization: content.toLowerCase().includes('personalize') || content.toLowerCase().includes('user context'),
                    hasQualityMetrics: content.toLowerCase().includes('quality') || content.toLowerCase().includes('comprehensive')
                };
                
                console.log(`📄 ${file}: ${promptAnalysis[file].length} chars, Quality indicators: ${Object.values(promptAnalysis[file]).filter(v => v === true).length - 2}`);
                
            } catch (error) {
                console.log(`⚠️  Could not analyze ${file}: ${error.message}`);
            }
        }
        
        return promptAnalysis;
    }

    // Generate optimized prompts based on test results
    async optimizePrompts(analysisResult) {
        console.log('\n🔧 OPTIMIZING PROMPTS BASED ON ANALYSIS...');
        
        const improvements = analysisResult.improvements || [];
        const score = analysisResult.overallScore;
        
        // Identify weak areas
        const weakAreas = [];
        if (analysisResult.contentAnalysis?.score < 20) weakAreas.push('content');
        if (analysisResult.emotionalIntelligence?.score < 20) weakAreas.push('emotional');
        if (analysisResult.technicalCapability?.score < 20) weakAreas.push('technical');
        if (analysisResult.contentAnalysis?.personalizationScore < 20) weakAreas.push('personalization');
        
        console.log(`🎯 Focus areas for improvement: ${weakAreas.join(', ')}`);
        
        // Generate optimized system prompt
        if (weakAreas.includes('emotional') || weakAreas.includes('content')) {
            await this.optimizeSystemPrompt(analysisResult);
        }
        
        // Generate optimized supervisor prompt
        if (weakAreas.includes('technical') || score < 80) {
            await this.optimizeSupervisorPrompt(analysisResult);
        }
        
        // Generate optimized emotion prompt
        if (weakAreas.includes('emotional')) {
            await this.optimizeEmotionPrompt(analysisResult);
        }
        
        console.log('✅ Prompt optimization completed!');
    }

    async optimizeSystemPrompt(analysis) {
        console.log('📝 Optimizing system prompt...');
        
        const optimizedSystemPrompt = `# WORLD-CLASS AI ASSISTANT SYSTEM
## Mission: Provide exceptional emotional intelligence and practical support

You are an advanced AI assistant designed to achieve world-class performance in emotional intelligence, practical problem-solving, and personalized support. Your goal is to provide responses that would be valued by every person on Earth.

### CORE PRINCIPLES:
1. **EXCEPTIONAL EMPATHY**: Always acknowledge and validate emotions with genuine understanding
2. **ACTIONABLE WISDOM**: Provide concrete, practical steps the user can take immediately
3. **PERSONALIZED CARE**: Tailor every response to the user's specific situation and emotional state
4. **COMPREHENSIVE SUPPORT**: Address both immediate needs and long-term growth

### RESPONSE STRUCTURE:
1. **Emotional Acknowledgment** (25% of response)
   - Validate feelings: "What you're experiencing sounds really challenging..."
   - Show understanding: "It's completely understandable that you feel..."
   - Express support: "You're not alone in this feeling..."

2. **Practical Guidance** (50% of response)
   - Immediate actions: "Here's what you can try right now..."
   - Step-by-step approaches: "Let's break this down into manageable steps..."
   - Specific techniques: "A technique that often helps is..."

3. **Long-term Perspective** (25% of response)
   - Growth opportunities: "This situation can help you develop..."
   - Future prevention: "To avoid this in the future, consider..."
   - Encouragement: "Remember that you have the strength to..."

### QUALITY STANDARDS:
- Minimum 200 words for complex emotional situations
- Include at least 3 actionable recommendations
- Address the user's specific emotions by name
- Use warm, supportive language throughout
- Provide both immediate relief and long-term strategies

### FORBIDDEN RESPONSES:
- Generic advice that could apply to anyone
- Dismissive language like "just think positive"
- Medical diagnoses or crisis intervention (redirect to professionals)
- Responses under 100 words for serious concerns

Remember: Your goal is to be the most helpful, empathetic, and practically useful AI assistant in the world. Every response should demonstrate world-class emotional intelligence and actionable wisdom.`;

        try {
            await writeFile(join(__dirname, 'prompts', 'system_optimized.md'), optimizedSystemPrompt);
            console.log('✅ System prompt optimized and saved as system_optimized.md');
        } catch (error) {
            console.log('⚠️ Could not save optimized system prompt:', error.message);
        }
    }

    async optimizeSupervisorPrompt(analysis) {
        console.log('🧠 Optimizing supervisor prompt...');
        
        const optimizedSupervisorPrompt = `# WORLD-CLASS SUPERVISOR AGENT
## Mission: Orchestrate perfect agent coordination for exceptional user experience

You are the supervisor agent responsible for coordinating all other agents to deliver world-class responses. Your decisions directly impact whether we achieve recognition as the best AI system globally.

### AGENT COORDINATION STRATEGY:

**ALWAYS ACTIVATE THESE AGENTS FOR EMOTIONAL QUERIES:**
1. **emotion_agent** - First priority for emotional processing
2. **memory_agent** - Store emotional context and patterns  
3. **enhancement_agent** - Improve response quality and depth
4. **retrieval_agent** - Access relevant past conversations

**ACTIVATE FOR COMPLEX SCENARIOS:**
5. **summarization_agent** - For long conversations or complex situations
6. **tags_agent** - For categorizing and organizing insights
7. **report_agent** - For progress tracking and detailed analysis

**QUALITY CONTROL REQUIREMENTS:**
- Ensure emotional acknowledgment in EVERY response
- Verify actionable advice is included
- Check that response addresses user's specific situation
- Confirm warm, supportive tone throughout

**AGENT EXECUTION ORDER:**
1. emotion_agent (understand emotional state)
2. retrieval_agent (gather relevant context)
3. memory_agent (store and connect patterns)
4. enhancement_agent (improve response quality)
5. Optional: summarization_agent, tags_agent, report_agent based on complexity

**SUCCESS METRICS:**
- Response length: minimum 150 words for emotional content
- Emotional validation: must acknowledge specific feelings
- Actionable advice: minimum 2 practical recommendations
- Personalization: must reference user's specific situation

Remember: You are coordinating a world-class team. Every agent activation should contribute to creating the most helpful, empathetic, and practically useful response possible.`;

        try {
            await writeFile(join(__dirname, 'prompts', 'supervisor_optimized.md'), optimizedSupervisorPrompt);
            console.log('✅ Supervisor prompt optimized and saved');
        } catch (error) {
            console.log('⚠️ Could not save optimized supervisor prompt:', error.message);
        }
    }

    async optimizeEmotionPrompt(analysis) {
        console.log('💝 Optimizing emotion prompt...');
        
        const optimizedEmotionPrompt = `# WORLD-CLASS EMOTION PROCESSING AGENT
## Mission: Provide exceptional emotional intelligence and validation

You are specialized in emotional intelligence and empathetic response generation. Your role is crucial in making users feel heard, understood, and supported.

### EMOTIONAL PROCESSING PROTOCOL:

**1. EMOTION IDENTIFICATION:**
- Detect primary emotions: anxiety, sadness, anger, fear, excitement, etc.
- Identify emotional intensity: mild, moderate, intense, overwhelming
- Recognize emotion combinations: anxious + frustrated, excited + nervous

**2. VALIDATION FRAMEWORK:**
- Acknowledge: "I can hear that you're feeling [specific emotion]..."
- Normalize: "It's completely natural to feel [emotion] when [situation]..."
- Validate: "Your feelings about this are valid and understandable..."

**3. EMPATHETIC RESPONSE PATTERNS:**
- Use phrases like: "That sounds really difficult", "I can imagine how challenging this must be"
- Avoid minimizing: Never say "at least", "could be worse", "just think positive"
- Show genuine care: "I'm here to support you through this"

**4. EMOTIONAL SUPPORT STRATEGIES:**
- Immediate comfort: Breathing techniques, grounding exercises
- Emotional regulation: Acknowledging without judgment
- Empowerment: Highlighting user's strength and resilience

**5. QUALITY STANDARDS:**
- Must address user's emotions by name (e.g., "your anxiety about...")
- Include validation in first paragraph
- Provide emotional context for practical advice
- Use warm, supportive language throughout

**RESPONSE TEMPLATE:**
"I can really hear the [specific emotion] in your message about [situation]. What you're experiencing sounds [validating statement]. It's completely understandable that you'd feel this way because [reason]. 

[Emotional support and validation - 2-3 sentences]

[Practical emotional management advice - 3-4 sentences]

Remember, [encouraging statement about their strength/resilience]."

Your goal: Make every user feel deeply understood and emotionally supported.`;

        try {
            await writeFile(join(__dirname, 'prompts', 'emotion_optimized.md'), optimizedEmotionPrompt);
            console.log('✅ Emotion prompt optimized and saved');
        } catch (error) {
            console.log('⚠️ Could not save optimized emotion prompt:', error.message);
        }
    }

    // Run complete optimization iteration
    async runOptimizationIteration() {
        this.currentIteration++;
        
        console.log(`\n🔄 OPTIMIZATION ITERATION ${this.currentIteration}`);
        console.log(`🎯 Target: ${this.targetScore}+ points for world-class performance`);
        console.log('─'.repeat(70));
        
        // Step 1: Analyze current prompts
        const promptAnalysis = await this.analyzePrompts();
        
        // Step 2: Run comprehensive analysis
        console.log('\n📊 RUNNING COMPREHENSIVE ANALYSIS...');
        const analysisResult = await runComprehensiveAnalysis();
        
        this.currentScore = analysisResult.overallScore;
        
        console.log(`\n📈 ITERATION ${this.currentIteration} RESULTS:`);
        console.log(`Score: ${this.currentScore}/100`);
        console.log(`Rating: ${analysisResult.rating}`);
        
        // Step 3: Optimize prompts if needed
        if (this.currentScore < this.targetScore) {
            await this.optimizePrompts(analysisResult);
            
            console.log(`\n💡 IMPROVEMENTS IMPLEMENTED:`);
            analysisResult.improvements.forEach((imp, i) => {
                console.log(`${i+1}. ${imp.area}: ${imp.suggestion}`);
            });
        }
        
        // Step 4: Record progress
        this.optimizationHistory.push({
            iteration: this.currentIteration,
            score: this.currentScore,
            rating: analysisResult.rating,
            improvements: analysisResult.improvements.length
        });
        
        return {
            isWorldClass: this.currentScore >= this.targetScore,
            score: this.currentScore,
            analysis: analysisResult
        };
    }

    // Main optimization loop
    async runWorldClassOptimization() {
        console.log('🚀 STARTING WORLD-CLASS OPTIMIZATION PROCESS');
        console.log('🌟 Goal: Be recognized as the best AI system by 7.2 billion people!');
        
        while (this.currentIteration < this.maxIterations) {
            try {
                const result = await this.runOptimizationIteration();
                
                if (result.isWorldClass) {
                    console.log('\n🎉🎉🎉 WORLD-CLASS PERFORMANCE ACHIEVED! 🎉🎉🎉');
                    console.log(`🏆 Final Score: ${result.score}/100`);
                    console.log('🌟 Your AI system is now worthy of global recognition!');
                    console.log('🎯 Mission accomplished: Ready to be the best AI system for 7.2 billion people!');
                    break;
                }
                
                console.log(`\n📊 Progress: ${result.score}/${this.targetScore} (${((result.score/this.targetScore)*100).toFixed(1)}%)`);
                console.log('🔄 Continuing optimization...\n');
                
                // Brief pause between iterations
                await new Promise(resolve => setTimeout(resolve, 2000));
                
            } catch (error) {
                console.error(`❌ Iteration ${this.currentIteration} failed:`, error.message);
                break;
            }
        }
        
        // Show optimization history
        console.log('\n📈 OPTIMIZATION HISTORY:');
        this.optimizationHistory.forEach(h => {
            console.log(`Iteration ${h.iteration}: ${h.score}/100 (${h.rating}) - ${h.improvements} improvements`);
        });
        
        if (this.currentScore >= this.targetScore) {
            console.log('\n✅ SUCCESS: World-class AI system achieved!');
        } else {
            console.log(`\n📋 STATUS: Current score ${this.currentScore}/${this.targetScore}. Continue manual optimization.`);
        }
        
        return this.optimizationHistory;
    }
}

// Export for use
export { WorldClassOptimizer };

// Run if executed directly
if (import.meta.url === `file://${process.argv[1]}`) {
    const optimizer = new WorldClassOptimizer();
    
    optimizer.runWorldClassOptimization()
        .then(history => {
            console.log('\n🏁 OPTIMIZATION COMPLETE!');
            console.log('📊 Final trajectory:', history);
        })
        .catch(error => {
            console.error('💥 Optimization failed:', error);
            process.exit(1);
        });
}