CHECKPOINT: Brainy 2.0 API refactor - pre-fixes state

Current state:
- Unified augmentation system to BrainyAugmentation interface
- Changed methods to specific noun/verb naming (addNoun, getNoun, etc)
- Made old methods private
- Combined getNouns into single unified method
- Neural API exists and is complete
- Triple Intelligence uses correct Brainy operators (not MongoDB)

Issues identified:
- Documentation incorrectly shows MongoDB operators (code is correct)
- Need to ensure all features are properly exposed
- Need to verify nothing was lost in simplification

This commit serves as a rollback point before applying fixes.
This commit is contained in:
David Snelling 2025-08-25 09:52:32 -07:00
commit 26c7d61185
279 changed files with 177945 additions and 0 deletions

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#!/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 ora from 'ora'
import { BrainyData } from '../brainyData.js'
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: any) {
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()
}