#!/usr/bin/env node
/**
 * Brainy CLI - Enterprise Neural Intelligence System
 *
 * Full TypeScript implementation with type safety and shared code
 */
import { Command } from 'commander';
import chalk from 'chalk';
import { neuralCommands } from './commands/neural.js';
import { coreCommands } from './commands/core.js';
import { utilityCommands } from './commands/utility.js';
import { version } from '../package.json';
// CLI Configuration
const program = new Command();
program
    .name('brainy')
    .description('🧠 Enterprise Neural Intelligence Database')
    .version(version)
    .option('-v, --verbose', 'Verbose output')
    .option('--json', 'JSON output format')
    .option('--pretty', 'Pretty JSON output')
    .option('--no-color', 'Disable colored output');
// ===== Core Commands =====
program
    .command('add <text>')
    .description('Add text or JSON to the neural database')
    .option('-i, --id <id>', 'Specify custom ID')
    .option('-m, --metadata <json>', 'Add metadata')
    .option('-t, --type <type>', 'Specify noun type')
    .action(coreCommands.add);
program
    .command('search <query>')
    .description('Search the neural database')
    .option('-k, --limit <number>', 'Number of results', '10')
    .option('-t, --threshold <number>', 'Similarity threshold')
    .option('--metadata <json>', 'Filter by metadata')
    .action(coreCommands.search);
program
    .command('get <id>')
    .description('Get item by ID')
    .option('--with-connections', 'Include connections')
    .action(coreCommands.get);
program
    .command('relate <source> <verb> <target>')
    .description('Create a relationship between items')
    .option('-w, --weight <number>', 'Relationship weight')
    .option('-m, --metadata <json>', 'Relationship metadata')
    .action(coreCommands.relate);
program
    .command('import <file>')
    .description('Import data from file')
    .option('-f, --format <format>', 'Input format (json|csv|jsonl)', 'json')
    .option('--batch-size <number>', 'Batch size for import', '100')
    .action(coreCommands.import);
program
    .command('export [file]')
    .description('Export database')
    .option('-f, --format <format>', 'Output format (json|csv|jsonl)', 'json')
    .action(coreCommands.export);
// ===== Neural Commands =====
program
    .command('similar <a> <b>')
    .alias('sim')
    .description('Calculate similarity between two items')
    .option('--explain', 'Show detailed explanation')
    .option('--breakdown', 'Show similarity breakdown')
    .action(neuralCommands.similar);
program
    .command('cluster')
    .alias('clusters')
    .description('Find semantic clusters in the data')
    .option('--algorithm <type>', 'Clustering algorithm (hierarchical|kmeans|dbscan)', 'hierarchical')
    .option('--threshold <number>', 'Similarity threshold', '0.7')
    .option('--min-size <number>', 'Minimum cluster size', '2')
    .option('--max-clusters <number>', 'Maximum number of clusters')
    .option('--near <query>', 'Find clusters near a query')
    .option('--show', 'Show visual representation')
    .action(neuralCommands.cluster);
program
    .command('related <id>')
    .alias('neighbors')
    .description('Find semantically related items')
    .option('-l, --limit <number>', 'Number of results', '10')
    .option('-r, --radius <number>', 'Semantic radius', '0.3')
    .option('--with-scores', 'Include similarity scores')
    .option('--with-edges', 'Include connections')
    .action(neuralCommands.related);
program
    .command('hierarchy <id>')
    .alias('tree')
    .description('Show semantic hierarchy for an item')
    .option('-d, --depth <number>', 'Hierarchy depth', '3')
    .option('--parents-only', 'Show only parent hierarchy')
    .option('--children-only', 'Show only child hierarchy')
    .action(neuralCommands.hierarchy);
program
    .command('path <from> <to>')
    .description('Find semantic path between items')
    .option('--steps', 'Show step-by-step path')
    .option('--max-hops <number>', 'Maximum path length', '5')
    .action(neuralCommands.path);
program
    .command('outliers')
    .alias('anomalies')
    .description('Detect semantic outliers')
    .option('-t, --threshold <number>', 'Outlier threshold', '0.3')
    .option('--explain', 'Explain why items are outliers')
    .action(neuralCommands.outliers);
program
    .command('visualize')
    .alias('viz')
    .description('Generate visualization data')
    .option('-f, --format <format>', 'Output format (json|d3|graphml)', 'json')
    .option('--max-nodes <number>', 'Maximum nodes', '500')
    .option('--dimensions <number>', '2D or 3D', '2')
    .option('-o, --output <file>', 'Output file')
    .action(neuralCommands.visualize);
// ===== Utility Commands =====
program
    .command('stats')
    .alias('statistics')
    .description('Show database statistics')
    .option('--by-service', 'Group by service')
    .option('--detailed', 'Show detailed stats')
    .action(utilityCommands.stats);
program
    .command('clean')
    .description('Clean and optimize database')
    .option('--remove-orphans', 'Remove orphaned items')
    .option('--rebuild-index', 'Rebuild search index')
    .action(utilityCommands.clean);
program
    .command('benchmark')
    .alias('bench')
    .description('Run performance benchmarks')
    .option('--operations <ops>', 'Operations to benchmark', 'all')
    .option('--iterations <n>', 'Number of iterations', '100')
    .action(utilityCommands.benchmark);
// ===== Interactive Mode =====
program
    .command('interactive')
    .alias('i')
    .description('Start interactive REPL mode')
    .action(async () => {
    const { startInteractiveMode } = await import('./interactive.js');
    await startInteractiveMode();
});
// ===== Error Handling =====
program.exitOverride();
try {
    await program.parseAsync(process.argv);
}
catch (error) {
    if (error.code === 'commander.helpDisplayed') {
        process.exit(0);
    }
    console.error(chalk.red('Error:'), error.message);
    if (program.opts().verbose) {
        console.error(chalk.gray(error.stack));
    }
    process.exit(1);
}
// Handle no command
if (!process.argv.slice(2).length) {
    program.outputHelp();
}
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