"use strict";
/**
 * 🚀 faf ai-enhance - Claude-First, Big-3 Compatible Enhancement
 * Universal AI-context enhancement with Claude intelligence and Big-3 compatibility
 *
 * Architecture: Claude-first → Big-3 Compatible → Bullet-proof Universal
 */
Object.defineProperty(exports, "__esModule", { value: true });
exports.enhanceFafWithAI = enhanceFafWithAI;
const colors_1 = require("../fix-once/colors");
const fs_1 = require("fs");
const yaml_1 = require("../fix-once/yaml");
/**
 * Claude-First, Big-3 Compatible AI Enhancement
 */
async function enhanceFafWithAI(file, options = {}) {
    // MAINTENANCE MODE - Temporarily disabled for improvements
    console.log();
    console.log(colors_1.chalk.yellow('⚠️  FAF Enhance is temporarily under maintenance'));
    console.log(colors_1.chalk.gray('   We discovered the AI enhancement was showing incorrect scores.'));
    console.log(colors_1.chalk.gray('   We\'re improving this feature to provide real, accurate enhancements.'));
    console.log();
    console.log(colors_1.chalk.cyan('🔧 Alternative options:'));
    console.log(colors_1.chalk.white('   • Use "faf chat" for guided improvements'));
    console.log(colors_1.chalk.white('   • Use "faf edit" to manually improve your .faf'));
    console.log(colors_1.chalk.white('   • Use "faf score --details" to see what needs improvement'));
    console.log();
    return;
    /* Original code temporarily disabled
    try {
      const fafPath = file || (await findFafFile());
  
      if (!fafPath) {
        console.log(chalk.red("❌ No .faf file found"));
        console.log(chalk.yellow('💡 Run "faf init" to create one'));
        process.exit(1);
      }
  
      const model = options.model || 'claude'; // Claude-first default
      console.log(chalk.cyan(`⚡ AI-enhancing with ${getModelDisplay(model)}: ${fafPath}`));
  
      // Read current .faf file
      const content = await fs.readFile(fafPath, "utf-8");
      const fafData = parseYAML(content);
  
      // Calculate real score, don't trust embedded score
      const { FafCompiler } = require('../compiler/faf-compiler');
      const compiler = new FafCompiler(path.dirname(fafPath));
      const realScore = await compiler.compile(fafPath);
  
      console.log(chalk.cyan("📊 Current .faf score:"), chalk.bold(`${realScore.score}%`));
  
      // WARNING: This is a mock implementation
      console.log(chalk.yellow("⚠️  Enhancement is currently in beta and may not improve scores"));
  
      // Determine enhancement focus
      const focus = options.focus || detectEnhancementFocus(fafData);
      console.log(chalk.blue(`🔍 Enhancement focus: ${focus}`));
  
      if (options.dryRun) {
        const prompt = generateEnhancementPrompt(fafData, focus, model);
        console.log(chalk.yellow("\n🔍 Dry run - Enhancement prompt:"));
        console.log(chalk.dim(prompt));
        return;
      }
  
      // Execute Claude-first, Big-3 compatible enhancement
      const enhanced = await executeBig3Enhancement(fafPath, fafData, focus, model, options);
  
      if (enhanced) {
        console.log(chalk.green(`☑️ .faf file enhanced with ${getModelDisplay(model)} intelligence`));
        console.log(chalk.cyan("📈 Run 'faf score' to see improvement"));
        console.log(chalk.dim("🤖 Run 'faf verify' to test AI understanding"));
      }
  
    } catch (error) {
      console.log(chalk.red("💥 AI enhancement failed:"));
      console.log(
        chalk.red(error instanceof Error ? error.message : String(error)),
      );
      process.exit(1);
    }
    */
}
/**
 * Get display name for AI model
 */
function getModelDisplay(model) {
    const displays = {
        'claude': '🤖 Claude (Championship)',
        'chatgpt': '🤖 ChatGPT',
        'gemini': '💎 Gemini',
        'big3': '🚀 Big-3 Consensus',
        'universal': '🌍 Universal AI'
    };
    return displays[model] || model;
}
/**
 * Detect enhancement focus based on .faf analysis
 */
function detectEnhancementFocus(fafData) {
    const score = parseInt(fafData.ai_score?.replace('%', '')) || fafData.scores?.faf_score || 0;
    // Claude-first analysis priorities
    if (!fafData.human_context?.who || !fafData.human_context?.what) {
        return "human-context";
    }
    if (!fafData.ai_instructions?.priority_order || !fafData.ai_instructions?.working_style) {
        return "ai-instructions";
    }
    if (score < 70) {
        return "completeness";
    }
    if (!fafData.project?.goal || fafData.project.goal.includes('!CI')) {
        return "claude-exclusive"; // Claude's specialty: championship content
    }
    return "optimization";
}
/**
 * Generate Claude-first, model-specific enhancement prompt
 */
function generateEnhancementPrompt(fafData, focus, model) {
    const modelInstructions = {
        'claude': 'You are Claude, the championship AI. Focus on F1-inspired engineering excellence and revolutionary content.',
        'chatgpt': 'You are ChatGPT. Focus on clear communication and practical improvements.',
        'gemini': 'You are Gemini. Focus on technical precision and comprehensive analysis.',
        'big3': 'Analyze from all three AI perspectives: Claude (championship), ChatGPT (clarity), Gemini (precision).',
        'universal': 'Create universal improvements that work across all AI models.'
    };
    const focusInstructions = {
        'human-context': 'Improve WHO/WHAT/WHY clarity for human handoffs',
        'ai-instructions': 'Enhance AI onboarding and working style guidance',
        'completeness': 'Fill missing context slots and improve scoring',
        'optimization': 'Streamline for better AI consumption and performance',
        'claude-exclusive': 'Apply Claude\'s championship content expertise - eliminate placeholders, add F1-inspired messaging'
    };
    return `${modelInstructions[model] || modelInstructions.claude}

Analyze and enhance this .faf (Universal AI-context Format) file.

Current .faf content:
\`\`\`yaml
${(0, yaml_1.stringify)(fafData)}
\`\`\`

Enhancement focus: ${focus}
Specific instructions: ${focusInstructions[focus]}

Requirements:
1. Analyze current .faf completeness and AI-readiness
2. Apply ${model === 'claude' ? 'championship F1-inspired' : model} intelligence 
3. Focus specifically on "${focus}" improvements
4. Maintain .faf v2.4.0+ schema compatibility
5. Preserve existing working elements
6. Output enhanced .faf as valid YAML

${focus === 'claude-exclusive' ? 'CLAUDE SPECIAL: Replace any !CI placeholders with revolutionary F1-inspired content. Make it championship-grade!' : ''}

Provide the enhanced .faf file as clean YAML (no markdown backticks needed).`;
}
/**
 * Execute Big-3 Compatible AI Enhancement (Claude-first architecture)
 */
async function executeBig3Enhancement(fafPath, fafData, focus, model, options) {
    try {
        console.log(colors_1.chalk.cyan(`🤖 ${getModelDisplay(model)} analysis starting...`));
        // Use our existing Big-3 verification system for enhancement analysis
        const models = model === 'big3' ? ['claude', 'chatgpt', 'gemini'] : [model === 'universal' ? 'claude' : model];
        // Mock AI enhancement using our verification engine architecture
        const enhancementResults = await generateMockEnhancement(fafData, focus);
        if (options.consensus && models.length > 1) {
            console.log(colors_1.chalk.yellow('🔄 Building consensus from all models...'));
            // Simulate consensus building
            await new Promise(resolve => setTimeout(resolve, 500));
        }
        // Apply enhancements based on focus area
        const enhanced = applyEnhancements(fafData, enhancementResults, focus);
        if (enhanced) {
            // Backup original
            await fs_1.promises.copyFile(fafPath, `${fafPath}.backup-${Date.now()}`);
            // Write enhanced version 
            const enhancedYaml = (0, yaml_1.stringify)(enhanced);
            await fs_1.promises.writeFile(fafPath, enhancedYaml);
            console.log(colors_1.chalk.green(`☑️ Enhanced .faf with ${getModelDisplay(model)} intelligence`));
            console.log(colors_1.chalk.dim(`📁 Backup created`));
            // Show specific improvements
            displayEnhancementResults(enhancementResults, focus);
            return true;
        }
        return false;
    }
    catch (error) {
        console.log(colors_1.chalk.red("❌ Big-3 enhancement failed:"));
        console.log(colors_1.chalk.red(error instanceof Error ? error.message : String(error)));
        return false;
    }
}
/**
 * Generate mock enhancement using our Big-3 architecture
 */
async function generateMockEnhancement(fafData, focus) {
    // Simulate AI analysis delay
    await new Promise(resolve => setTimeout(resolve, 200));
    const improvements = {
        'human-context': {
            // Don't add generic placeholders - they provide no value
            // Only keep existing values or leave empty for user to fill
            who: fafData.human_context?.who,
            what: fafData.human_context?.what,
            why: fafData.human_context?.why
        },
        'ai-instructions': {
            priority_order: [
                '1. Read THIS .faf file first for complete context',
                '2. Check CLAUDE.md for session-specific context',
                '3. Review package.json and key files for technical stack'
            ],
            working_style: {
                code_first: true,
                explanations: 'minimal',
                quality_bar: 'zero_errors',
                testing: 'required'
            }
        },
        'claude-exclusive': {
            mission: '🚀 Make Your AI Happy! 🧡 Trust-Driven 🤖',
            revolution: '30 seconds replaces 20 minutes of questions',
            brand: 'F1-Inspired Software Engineering - Championship AI Context'
        }
    };
    return improvements[focus] || {};
}
/**
 * Apply AI enhancements to .faf data
 */
function applyEnhancements(fafData, enhancements, focus) {
    const enhanced = { ...fafData };
    switch (focus) {
        case 'human-context':
            enhanced.human_context = { ...(enhanced.human_context || {}), ...enhancements };
            break;
        case 'ai-instructions':
            enhanced.ai_instructions = { ...(enhanced.ai_instructions || {}), ...enhancements };
            break;
        case 'claude-exclusive':
            enhanced.project = { ...(enhanced.project || {}), ...enhancements };
            break;
        case 'completeness':
            // Fill missing slots with intelligent defaults
            if (!enhanced.instant_context) {
                enhanced.instant_context = {};
            }
            if (!enhanced.instant_context.what_building && enhanced.project?.goal) {
                enhanced.instant_context.what_building = enhanced.project.goal;
            }
            break;
    }
    // Update metadata
    enhanced.project = enhanced.project || {};
    enhanced.project.enhanced_date = new Date().toISOString();
    enhanced.project.enhanced_by = 'faf-ai-enhance';
    return enhanced;
}
/**
 * Display enhancement results
 */
function displayEnhancementResults(results, focus) {
    console.log(colors_1.chalk.cyan('\n📈 Enhancement Summary:'));
    console.log(colors_1.chalk.dim(`Focus: ${focus}`));
    const improvements = Object.keys(results).length;
    if (improvements > 0) {
        console.log(colors_1.chalk.green(`☑️ ${improvements} improvements applied`));
        console.log(colors_1.chalk.dim('📈 Run \'faf score\' to see impact'));
    }
}
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