David Snelling
26c7d61185
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.
564 lines
No EOL
15 KiB
JavaScript
564 lines
No EOL
15 KiB
JavaScript
#!/usr/bin/env node
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/**
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* Brainy Interactive Mode
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*
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* Professional, guided CLI experience for beginners
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*/
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import { program } from 'commander'
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import { BrainyData } from '../dist/brainyData.js'
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import chalk from 'chalk'
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import inquirer from 'inquirer'
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import ora from 'ora'
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import Table from 'cli-table3'
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import boxen from 'boxen'
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// Professional color scheme
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const colors = {
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primary: chalk.hex('#3A5F4A'), // Teal (from logo)
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success: chalk.hex('#2D4A3A'), // Deep teal
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info: chalk.hex('#4A6B5A'), // Medium teal
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warning: chalk.hex('#D67441'), // Orange (from logo)
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error: chalk.hex('#B85C35'), // Deep orange
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brain: chalk.hex('#D67441'), // Brain orange
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cream: chalk.hex('#F5E6A3'), // Cream background
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dim: chalk.dim,
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bold: chalk.bold,
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cyan: chalk.cyan,
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green: chalk.green,
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yellow: chalk.yellow,
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red: chalk.red
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}
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// Icons for consistent visual language
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const icons = {
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brain: '🧠',
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search: '🔍',
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add: '➕',
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delete: '🗑️',
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update: '🔄',
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import: '📥',
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export: '📤',
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connect: '🔗',
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question: '❓',
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success: '✅',
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error: '❌',
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warning: '⚠️',
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info: 'ℹ️',
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sparkle: '✨',
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rocket: '🚀',
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thinking: '🤔',
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chat: '💬',
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stats: '📊',
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config: '⚙️',
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cloud: '☁️'
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}
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let brainyInstance = null
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async function getBrainy() {
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if (!brainyInstance) {
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const spinner = ora('Initializing Brainy...').start()
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try {
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brainyInstance = new BrainyData()
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await brainyInstance.init()
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spinner.succeed('Brainy initialized')
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} catch (error) {
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spinner.fail('Failed to initialize Brainy')
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console.error(colors.error(error.message))
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process.exit(1)
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}
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}
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return brainyInstance
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}
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/**
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* Professional welcome screen
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*/
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function showWelcome() {
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console.clear()
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const welcomeBox = boxen(
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colors.primary(`${icons.brain} BRAINY - Neural Intelligence System\n`) +
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colors.dim('\nYour AI-Powered Second Brain\n') +
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colors.info('Version 1.6.0'),
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{
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padding: 1,
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margin: 1,
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borderStyle: 'round',
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borderColor: 'cyan',
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textAlignment: 'center'
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}
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)
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console.log(welcomeBox)
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console.log()
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}
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/**
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* Main interactive menu
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*/
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async function mainMenu() {
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const { action } = await inquirer.prompt([{
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type: 'list',
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name: 'action',
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message: colors.cyan('What would you like to do?'),
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choices: [
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new inquirer.Separator(colors.dim('── Core Operations ──')),
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{ name: `${icons.add} Add data to your brain`, value: 'add' },
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{ name: `${icons.search} Search your knowledge`, value: 'search' },
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{ name: `${icons.chat} Chat with your data`, value: 'chat' },
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{ name: `${icons.update} Update existing data`, value: 'update' },
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{ name: `${icons.delete} Delete data`, value: 'delete' },
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new inquirer.Separator(colors.dim('── Advanced Features ──')),
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{ name: `${icons.connect} Create relationships`, value: 'relate' },
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{ name: `${icons.import} Import from file/URL`, value: 'import' },
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{ name: `${icons.export} Export your brain`, value: 'export' },
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{ name: `${icons.brain} Neural operations`, value: 'neural' },
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new inquirer.Separator(colors.dim('── System ──')),
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{ name: `${icons.stats} View statistics`, value: 'stats' },
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{ name: `${icons.config} Configuration`, value: 'config' },
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{ name: `${icons.cloud} Brain Cloud`, value: 'cloud' },
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{ name: `${icons.info} Help & Documentation`, value: 'help' },
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new inquirer.Separator(),
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{ name: 'Exit', value: 'exit' }
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],
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pageSize: 20
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}])
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return action
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}
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/**
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* Neural operations submenu
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*/
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async function neuralMenu() {
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const { operation } = await inquirer.prompt([{
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type: 'list',
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name: 'operation',
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message: colors.cyan('Select neural operation:'),
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choices: [
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{ name: `${icons.brain} Calculate similarity`, value: 'similar' },
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{ name: `${icons.search} Find clusters`, value: 'cluster' },
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{ name: `${icons.connect} Find related items`, value: 'related' },
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{ name: `${icons.thinking} Build hierarchy`, value: 'hierarchy' },
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{ name: `${icons.rocket} Find semantic path`, value: 'path' },
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{ name: `${icons.warning} Detect outliers`, value: 'outliers' },
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{ name: `${icons.sparkle} Generate visualization`, value: 'visualize' },
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new inquirer.Separator(),
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{ name: '← Back to main menu', value: 'back' }
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]
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}])
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return operation
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}
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/**
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* Execute commands with beautiful feedback
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*/
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async function executeCommand(command) {
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const brain = await getBrainy()
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switch (command) {
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case 'add':
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await interactiveAdd(brain)
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break
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case 'search':
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await interactiveSearch(brain)
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break
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case 'chat':
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await interactiveChat(brain)
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break
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case 'update':
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await interactiveUpdate(brain)
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break
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case 'delete':
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await interactiveDelete(brain)
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break
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case 'relate':
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await interactiveRelate(brain)
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break
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case 'import':
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await interactiveImport(brain)
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break
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case 'export':
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await interactiveExport(brain)
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break
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case 'neural':
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const neuralOp = await neuralMenu()
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if (neuralOp !== 'back') {
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await executeNeuralOperation(neuralOp, brain)
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}
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break
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case 'stats':
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await showStatistics(brain)
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break
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case 'config':
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await interactiveConfig(brain)
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break
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case 'cloud':
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await showCloudInfo()
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break
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case 'help':
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await showHelp()
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break
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}
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}
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/**
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* Interactive add with rich prompts
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*/
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async function interactiveAdd(brain) {
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console.log(colors.primary(`\n${icons.add} Add Data\n`))
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const { inputType } = await inquirer.prompt([{
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type: 'list',
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name: 'inputType',
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message: 'How would you like to add data?',
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choices: [
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{ name: 'Type or paste text', value: 'text' },
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{ name: 'Multi-line editor', value: 'editor' },
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{ name: 'JSON object', value: 'json' },
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{ name: 'Import from clipboard', value: 'clipboard' }
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]
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}])
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let data = ''
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switch (inputType) {
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case 'text':
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const { text } = await inquirer.prompt([{
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type: 'input',
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name: 'text',
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message: 'Enter your data:',
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validate: input => input.trim() ? true : 'Please enter some data'
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}])
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data = text
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break
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case 'editor':
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const { editorText } = await inquirer.prompt([{
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type: 'editor',
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name: 'editorText',
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message: 'Enter your data (opens editor):',
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postfix: '.md'
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}])
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data = editorText
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break
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case 'json':
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const { jsonText } = await inquirer.prompt([{
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type: 'editor',
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name: 'jsonText',
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message: 'Enter JSON data:',
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postfix: '.json',
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default: '{\n \n}',
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validate: input => {
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try {
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JSON.parse(input)
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return true
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} catch (e) {
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return `Invalid JSON: ${e.message}`
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}
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}
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}])
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data = jsonText
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break
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}
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// Optional metadata
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const { addMetadata } = await inquirer.prompt([{
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type: 'confirm',
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name: 'addMetadata',
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message: 'Would you like to add metadata?',
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default: false
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}])
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let metadata = {}
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if (addMetadata) {
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const { metadataJson } = await inquirer.prompt([{
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type: 'editor',
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name: 'metadataJson',
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message: 'Enter metadata (JSON):',
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postfix: '.json',
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default: '{\n "type": "",\n "tags": [],\n "category": ""\n}',
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validate: input => {
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try {
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JSON.parse(input)
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return true
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} catch (e) {
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return `Invalid JSON: ${e.message}`
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}
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}
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}])
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metadata = JSON.parse(metadataJson)
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}
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const spinner = ora('Adding data...').start()
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try {
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const id = await brain.add(data, metadata)
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spinner.succeed(`Added successfully with ID: ${id}`)
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// Show summary
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console.log(boxen(
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colors.success(`${icons.success} Data added successfully!\n\n`) +
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colors.info(`ID: ${id}\n`) +
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colors.dim(`Size: ${data.length} characters\n`) +
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(Object.keys(metadata).length > 0 ? colors.dim(`Metadata: ${Object.keys(metadata).join(', ')}`) : ''),
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{ padding: 1, borderColor: 'green', borderStyle: 'round' }
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))
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} catch (error) {
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spinner.fail('Failed to add data')
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console.error(colors.error(error.message))
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}
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}
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/**
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* Interactive search with filters
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*/
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async function interactiveSearch(brain) {
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console.log(colors.primary(`\n${icons.search} Search\n`))
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const { query } = await inquirer.prompt([{
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type: 'input',
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name: 'query',
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message: 'Enter search query:',
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validate: input => input.trim() ? true : 'Please enter a search query'
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}])
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// Advanced options
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const { useFilters } = await inquirer.prompt([{
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type: 'confirm',
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name: 'useFilters',
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message: 'Apply filters?',
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default: false
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}])
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let searchOptions = { limit: 10 }
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if (useFilters) {
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const { limit, threshold } = await inquirer.prompt([
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{
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type: 'number',
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name: 'limit',
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message: 'Maximum results:',
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default: 10
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},
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{
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type: 'number',
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name: 'threshold',
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message: 'Similarity threshold (0-1):',
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default: 0.5,
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validate: input => input >= 0 && input <= 1 ? true : 'Must be between 0 and 1'
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}
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])
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searchOptions.limit = limit
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searchOptions.threshold = threshold
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}
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const spinner = ora('Searching...').start()
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try {
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const results = await brain.search(query, searchOptions.limit, searchOptions)
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spinner.succeed(`Found ${results.length} results`)
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if (results.length === 0) {
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console.log(colors.warning('No results found'))
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} else {
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// Display results in a table
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const table = new Table({
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head: [colors.cyan('ID'), colors.cyan('Content'), colors.cyan('Score')],
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style: { head: [], border: [] },
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colWidths: [20, 50, 10]
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})
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results.forEach(result => {
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const content = result.content || result.id
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const truncated = content.length > 47 ? content.substring(0, 47) + '...' : content
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const score = result.score ? `${(result.score * 100).toFixed(1)}%` : 'N/A'
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table.push([
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result.id.substring(0, 18),
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truncated,
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colors.green(score)
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])
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})
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console.log(table.toString())
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// Ask if user wants to see full details
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const { viewDetails } = await inquirer.prompt([{
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type: 'confirm',
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name: 'viewDetails',
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message: 'View full details of a result?',
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default: false
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}])
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if (viewDetails) {
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const { selectedId } = await inquirer.prompt([{
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type: 'list',
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name: 'selectedId',
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message: 'Select result:',
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choices: results.map(r => ({
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name: `${r.id} - ${r.content?.substring(0, 50)}...`,
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value: r.id
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}))
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}])
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const selected = results.find(r => r.id === selectedId)
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console.log(boxen(
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colors.cyan('Full Details\n\n') +
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colors.info(`ID: ${selected.id}\n\n`) +
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`Content:\n${selected.content}\n\n` +
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(selected.metadata ? `Metadata:\n${JSON.stringify(selected.metadata, null, 2)}` : ''),
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{ padding: 1, borderColor: 'cyan', borderStyle: 'round' }
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))
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}
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}
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} catch (error) {
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spinner.fail('Search failed')
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console.error(colors.error(error.message))
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}
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}
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/**
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* Show statistics with beautiful formatting
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*/
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async function showStatistics(brain) {
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const spinner = ora('Gathering statistics...').start()
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try {
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const stats = await brain.getStatistics()
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spinner.succeed('Statistics loaded')
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console.log(boxen(
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colors.primary(`${icons.stats} Database Statistics\n\n`) +
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colors.info(`Total Items: ${colors.bold(stats.total || 0)}\n`) +
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colors.info(`Nouns: ${stats.nounCount || 0}\n`) +
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colors.info(`Relationships: ${stats.verbCount || 0}\n`) +
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colors.info(`Metadata Records: ${stats.metadataCount || 0}\n\n`) +
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colors.dim(`Memory Usage: ${(process.memoryUsage().heapUsed / 1024 / 1024).toFixed(1)} MB`),
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{
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padding: 1,
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borderColor: 'blue',
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borderStyle: 'round',
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textAlignment: 'left'
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}
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))
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} catch (error) {
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spinner.fail('Failed to get statistics')
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console.error(colors.error(error.message))
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}
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}
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/**
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* Show help with examples
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*/
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async function showHelp() {
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console.log(boxen(
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colors.primary(`${icons.info} Brainy Help\n\n`) +
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colors.cyan('Common Commands:\n') +
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colors.dim(`
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brainy add "text" Add data
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brainy search "query" Search your brain
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brainy chat Interactive AI chat
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brainy status View statistics
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brainy help This help menu
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`) +
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colors.cyan('Interactive Mode:\n') +
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colors.dim(`
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brainy Start interactive mode
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brainy -i Alternative interactive mode
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`) +
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colors.cyan('Advanced Features:\n') +
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colors.dim(`
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brainy similar a b Calculate similarity
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brainy cluster Find semantic clusters
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brainy export Export your data
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brainy cloud Brain Cloud features
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`),
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{ padding: 1, borderColor: 'yellow', borderStyle: 'round' }
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))
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const { learnMore } = await inquirer.prompt([{
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type: 'confirm',
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name: 'learnMore',
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message: 'View detailed documentation?',
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default: false
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}])
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if (learnMore) {
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console.log(colors.info('\nDocumentation: https://github.com/TimeSoul/brainy'))
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console.log(colors.info('Enterprise features: Coming in future releases'))
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}
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}
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/**
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* Main interactive loop
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*/
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async function main() {
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showWelcome()
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let running = true
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while (running) {
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const action = await mainMenu()
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if (action === 'exit') {
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console.log(colors.success(`\n${icons.success} Thank you for using Brainy!\n`))
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running = false
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} else {
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await executeCommand(action)
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// Pause before returning to menu
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await inquirer.prompt([{
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type: 'input',
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name: 'continue',
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message: colors.dim('\nPress Enter to continue...'),
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prefix: ''
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}])
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}
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}
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process.exit(0)
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}
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// Handle errors gracefully
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process.on('unhandledRejection', (error) => {
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console.error(colors.error(`\n${icons.error} Unexpected error:`))
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console.error(colors.red(error.message))
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process.exit(1)
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})
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// Handle Ctrl+C gracefully
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process.on('SIGINT', () => {
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console.log(colors.info(`\n\n${icons.info} Exiting Brainy...`))
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process.exit(0)
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})
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// Run if called directly
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if (import.meta.url === `file://${process.argv[1]}`) {
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main().catch(error => {
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console.error(colors.error('Fatal error:'), error)
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process.exit(1)
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})
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}
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export { main as startInteractiveMode } |