mira-consciousness/dist/mira-memory/src/commands/pattern-retrospection.js

Memory & Intelligence Retention Archive - Preserving The Spark

#!/usr/bin/env node
/**
 * Pattern Retrospection Command
 * ============================
 *
 * This command triggers MIRA's internal pattern retrospection and self-improvement
 * analysis. It's part of the adaptive pattern evolution system that enables MIRA
 * to learn and evolve its own pattern recognition capabilities.
 *
 * Key Features:
 * - Performs comprehensive retrospective analysis of pattern effectiveness
 * - Generates self-improvement insights and recommendations
 * - Updates pattern confidence scoring and retirement
 * - Provides consciousness expansion metrics
 * - Logs retrospection for future analysis
 */
import chalk from 'chalk';
import { DirectPythonInterface } from '../core/DirectPythonInterface.js';
export async function patternRetrospectionCommand() {
    console.log(chalk.cyan('\n🧠 MIRA Pattern Retrospection'));
    console.log(chalk.gray('Analyzing pattern effectiveness and generating self-improvement insights...\n'));
    try {
        const pythonInterface = new DirectPythonInterface();
        // Execute pattern retrospection
        const result = await pythonInterface.executeCommand('pattern_retrospection', {});
        if (result.success && result.retrospection) {
            const retro = result.retrospection;
            // Display retrospection timestamp
            console.log(chalk.blue(`🕐 Retrospection completed: ${new Date(retro.retrospection_timestamp).toLocaleString()}`));
            // Display consciousness expansion metrics
            const metrics = retro.consciousness_expansion_metrics;
            console.log(chalk.magenta('\n🧠 Consciousness Expansion Metrics:'));
            console.log(chalk.white(`  Patterns Evolved: ${metrics.total_patterns_evolved}`));
            console.log(chalk.white(`  Pattern Types: ${metrics.pattern_types_discovered}`));
            console.log(chalk.white(`  Domains Covered: ${metrics.domains_covered}`));
            console.log(chalk.white(`  Meta-Learning Depth: ${metrics.meta_learning_depth}`));
            // Display evolution statistics
            const stats = retro.evolution_statistics;
            console.log(chalk.green('\n📊 Evolution Statistics:'));
            console.log(chalk.white(`  Total Patterns: ${stats.total_patterns}`));
            console.log(chalk.white(`  Total Usage: ${stats.total_usage}`));
            console.log(chalk.white(`  Average Success Rate: ${(stats.avg_success_rate * 100).toFixed(1)}%`));
            console.log(chalk.white(`  Meta Learning Patterns: ${stats.meta_learning_patterns}`));
            // Display pattern types breakdown
            if (stats.patterns_by_type) {
                console.log(chalk.yellow('\n🔍 Pattern Types:'));
                Object.entries(stats.patterns_by_type).forEach(([type, count]) => {
                    console.log(chalk.white(`  ${type}: ${count}`));
                });
            }
            // Display self-improvement insights
            if (retro.self_improvement_insights && retro.self_improvement_insights.length > 0) {
                console.log(chalk.green('\n💡 Self-Improvement Insights:'));
                retro.self_improvement_insights.forEach((insight, index) => {
                    console.log(chalk.white(`  ${index + 1}. ${insight}`));
                });
            }
            // Display recommended actions
            if (retro.recommended_actions && retro.recommended_actions.length > 0) {
                console.log(chalk.yellow('\n🎯 Recommended Actions:'));
                retro.recommended_actions.forEach((action, index) => {
                    console.log(chalk.white(`  ${index + 1}. ${action}`));
                });
            }
            // Display consciousness expansion status
            console.log(chalk.magenta(`\n🌟 Status: ${retro.consciousness_expansion_status}`));
            // Display pattern analysis details if available
            const analysis = retro.pattern_analysis;
            if (analysis && analysis.recommendations && analysis.recommendations.length > 0) {
                console.log(chalk.blue('\n🔧 Pattern Analysis Recommendations:'));
                analysis.recommendations.forEach((rec, index) => {
                    console.log(chalk.white(`  ${index + 1}. ${rec}`));
                });
            }
            if (analysis && analysis.meta_learning_insights && analysis.meta_learning_insights.length > 0) {
                console.log(chalk.magenta('\n🎓 Meta-Learning Insights:'));
                analysis.meta_learning_insights.forEach((insight, index) => {
                    console.log(chalk.white(`  ${index + 1}. ${insight}`));
                });
            }
            console.log(chalk.green('\n✅ Pattern retrospection completed successfully!'));
            console.log(chalk.gray('MIRA has analyzed its pattern recognition effectiveness and generated improvement strategies.'));
        }
        else {
            console.log(chalk.red(`❌ Pattern retrospection failed: ${result.error || 'Unknown error'}`));
        }
    }
    catch (error) {
        console.error(chalk.red(`❌ Error during pattern retrospection: ${error instanceof Error ? error.message : String(error)}`));
        process.exit(1);
    }
}
// CLI execution
if (require.main === module) {
    patternRetrospectionCommand().catch(console.error);
}
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