David Snelling
34b2ed94d0
- Implement 7 core unified API methods (add, search, import, addNoun, addVerb, update, delete) - Add universal encryption system with encryptData/decryptData methods - Add container deployment support with model preloading - Implement soft delete by default for better performance - Add searchVerbs() and getNounWithVerbs() for graph traversal - Reduce package size by 16% despite major feature additions - Create comprehensive CHANGELOG.md and MIGRATION.md - Consolidate CLI from 40+ to 9 clean commands - All scaling optimizations preserved and enhanced BREAKING CHANGES: - addSmart() method removed (use add() - smart by default) - CLI commands consolidated and renamed - Pipeline classes unified into single Cortex class This is the complete 1.0 release candidate with all planned features implemented and tested.
1072 lines
No EOL
37 KiB
JavaScript
Executable file
1072 lines
No EOL
37 KiB
JavaScript
Executable file
#!/usr/bin/env node
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/**
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* Brainy CLI - Cleaned Up & Beautiful
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* 🧠⚛️ ONE way to do everything
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*
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* After the Great Cleanup of 2025:
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* - 5 commands total (was 40+)
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* - Clear, obvious naming
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* - Interactive mode for beginners
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*/
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// @ts-ignore
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import { program } from 'commander'
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import { BrainyData } from '../dist/brainyData.js'
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// @ts-ignore
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import chalk from 'chalk'
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import { readFileSync } from 'fs'
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import { dirname, join } from 'path'
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import { fileURLToPath } from 'url'
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import { createInterface } from 'readline'
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const __dirname = dirname(fileURLToPath(import.meta.url))
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const packageJson = JSON.parse(readFileSync(join(__dirname, '..', 'package.json'), 'utf8'))
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// Create single BrainyData instance (the ONE data orchestrator)
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let brainy = null
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const getBrainy = async () => {
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if (!brainy) {
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brainy = new BrainyData()
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await brainy.init()
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}
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return brainy
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}
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// Beautiful colors
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const colors = {
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primary: chalk.hex('#3A5F4A'),
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success: chalk.hex('#2D4A3A'),
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info: chalk.hex('#4A6B5A'),
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warning: chalk.hex('#D67441'),
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error: chalk.hex('#B85C35')
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}
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// Helper functions
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const exitProcess = (code = 0) => {
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setTimeout(() => process.exit(code), 100)
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}
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const wrapAction = (fn) => {
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return async (...args) => {
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try {
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await fn(...args)
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exitProcess(0)
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} catch (error) {
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console.error(colors.error('Error:'), error.message)
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exitProcess(1)
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}
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}
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}
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// AI Response Generation with multiple model support
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async function generateAIResponse(message, brainy, options) {
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const model = options.model || 'local'
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// Get relevant context from user's data
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const contextResults = await brainy.search(message, 5, {
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includeContent: true,
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scoreThreshold: 0.3
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})
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const context = contextResults.map(r => r.content).join('\n')
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const prompt = `Based on the following context from the user's data, answer their question:
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Context:
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${context}
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Question: ${message}
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Answer:`
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switch (model) {
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case 'local':
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case 'ollama':
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return await callOllamaModel(prompt, options)
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case 'openai':
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case 'gpt-3.5-turbo':
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case 'gpt-4':
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return await callOpenAI(prompt, options)
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case 'claude':
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case 'claude-3':
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return await callClaude(prompt, options)
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default:
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return await callOllamaModel(prompt, options)
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}
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}
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// Ollama (local) integration
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async function callOllamaModel(prompt, options) {
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const baseUrl = options.baseUrl || 'http://localhost:11434'
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const model = options.model === 'local' ? 'llama2' : options.model
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try {
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const response = await fetch(`${baseUrl}/api/generate`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({
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model: model,
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prompt: prompt,
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stream: false
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})
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})
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if (!response.ok) {
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throw new Error(`Ollama error: ${response.statusText}. Make sure Ollama is running: ollama serve`)
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}
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const data = await response.json()
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return data.response || 'No response from local model'
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} catch (error) {
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throw new Error(`Local model error: ${error.message}. Try: ollama run llama2`)
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}
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}
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// OpenAI integration
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async function callOpenAI(prompt, options) {
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if (!options.apiKey) {
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throw new Error('OpenAI API key required. Use --api-key <key> or set OPENAI_API_KEY environment variable')
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}
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const model = options.model === 'openai' ? 'gpt-3.5-turbo' : options.model
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try {
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const response = await fetch('https://api.openai.com/v1/chat/completions', {
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method: 'POST',
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headers: {
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'Authorization': `Bearer ${options.apiKey}`,
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'Content-Type': 'application/json'
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},
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body: JSON.stringify({
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model: model,
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messages: [{ role: 'user', content: prompt }],
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max_tokens: 500
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})
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})
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if (!response.ok) {
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throw new Error(`OpenAI error: ${response.statusText}`)
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}
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const data = await response.json()
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return data.choices[0]?.message?.content || 'No response from OpenAI'
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} catch (error) {
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throw new Error(`OpenAI error: ${error.message}`)
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}
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}
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// Claude integration
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async function callClaude(prompt, options) {
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if (!options.apiKey) {
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throw new Error('Anthropic API key required. Use --api-key <key> or set ANTHROPIC_API_KEY environment variable')
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}
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try {
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const response = await fetch('https://api.anthropic.com/v1/messages', {
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method: 'POST',
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headers: {
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'x-api-key': options.apiKey,
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'Content-Type': 'application/json',
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'anthropic-version': '2023-06-01'
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},
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body: JSON.stringify({
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model: 'claude-3-haiku-20240307',
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max_tokens: 500,
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messages: [{ role: 'user', content: prompt }]
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})
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})
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if (!response.ok) {
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throw new Error(`Claude error: ${response.statusText}`)
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}
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const data = await response.json()
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return data.content[0]?.text || 'No response from Claude'
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} catch (error) {
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throw new Error(`Claude error: ${error.message}`)
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}
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}
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// ========================================
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// MAIN PROGRAM - CLEAN & SIMPLE
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// ========================================
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program
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.name('brainy')
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.description('🧠⚛️ Brainy - Your AI-Powered Second Brain')
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.version(packageJson.version)
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// ========================================
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// THE 5 COMMANDS (ONE WAY TO DO EVERYTHING)
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// ========================================
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// Command 0: INIT - Initialize brainy (essential setup)
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program
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.command('init')
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.description('Initialize Brainy in current directory')
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.option('-s, --storage <type>', 'Storage type (filesystem, memory, s3, r2, gcs)')
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.option('-e, --encryption', 'Enable encryption for sensitive data')
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.option('--s3-bucket <bucket>', 'S3 bucket name')
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.option('--s3-region <region>', 'S3 region')
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.option('--access-key <key>', 'Storage access key')
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.option('--secret-key <key>', 'Storage secret key')
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.action(wrapAction(async (options) => {
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console.log(colors.primary('🧠 Initializing Brainy'))
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console.log()
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const { BrainyData } = await import('../dist/brainyData.js')
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const config = {
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storage: options.storage || 'filesystem',
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encryption: options.encryption || false
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}
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// Storage-specific configuration
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if (options.storage === 's3' || options.storage === 'r2' || options.storage === 'gcs') {
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if (!options.accessKey || !options.secretKey) {
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console.log(colors.warning('⚠️ Cloud storage requires access credentials'))
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console.log(colors.info('Use: --access-key <key> --secret-key <secret>'))
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console.log(colors.info('Or set environment variables: AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY'))
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process.exit(1)
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}
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config.storageOptions = {
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bucket: options.s3Bucket,
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region: options.s3Region || 'us-east-1',
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accessKeyId: options.accessKey,
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secretAccessKey: options.secretKey
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}
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}
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try {
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const brainy = new BrainyData(config)
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await brainy.init()
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console.log(colors.success('✅ Brainy initialized successfully!'))
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console.log(colors.info(`📁 Storage: ${config.storage}`))
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console.log(colors.info(`🔒 Encryption: ${config.encryption ? 'Enabled' : 'Disabled'}`))
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if (config.encryption) {
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console.log(colors.warning('🔐 Encryption enabled - keep your keys secure!'))
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}
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console.log()
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console.log(colors.success('🚀 Ready to go! Try:'))
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console.log(colors.info(' brainy add "Hello, World!"'))
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console.log(colors.info(' brainy search "hello"'))
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} catch (error) {
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console.log(colors.error('❌ Initialization failed:'))
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console.log(colors.error(error.message))
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process.exit(1)
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}
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}))
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// Command 1: ADD - Add data (smart by default)
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program
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.command('add [data]')
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.description('Add data to your brain (smart auto-detection)')
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.option('-m, --metadata <json>', 'Metadata as JSON')
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.option('-i, --id <id>', 'Custom ID')
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.option('--literal', 'Skip AI processing (literal storage)')
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.option('--encrypt', 'Encrypt this data (for sensitive information)')
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.action(wrapAction(async (data, options) => {
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if (!data) {
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console.log(colors.info('🧠 Interactive add mode'))
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const rl = createInterface({
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input: process.stdin,
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output: process.stdout
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})
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data = await new Promise(resolve => {
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rl.question(colors.primary('What would you like to add? '), (answer) => {
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rl.close()
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resolve(answer)
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})
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})
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}
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let metadata = {}
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if (options.metadata) {
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try {
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metadata = JSON.parse(options.metadata)
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} catch {
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console.error(colors.error('Invalid JSON metadata'))
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process.exit(1)
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}
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}
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if (options.id) {
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metadata.id = options.id
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}
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if (options.encrypt) {
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metadata.encrypted = true
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}
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console.log(options.literal
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? colors.info('🔒 Literal storage')
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: colors.success('🧠 Smart mode (auto-detects types)')
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)
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if (options.encrypt) {
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console.log(colors.warning('🔐 Encrypting sensitive data...'))
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}
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const brainyInstance = await getBrainy()
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// Handle encryption at data level if requested
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let processedData = data
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if (options.encrypt) {
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processedData = await brainyInstance.encryptData(data)
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metadata.encrypted = true
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}
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await brainyInstance.add(processedData, metadata, {
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process: options.literal ? 'literal' : 'auto'
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})
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console.log(colors.success('✅ Added successfully!'))
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}))
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// Command 2: CHAT - Talk to your data with AI
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program
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.command('chat [message]')
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.description('AI chat with your brain data (supports local & cloud models)')
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.option('-s, --session <id>', 'Use specific chat session')
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.option('-n, --new', 'Start a new session')
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.option('-l, --list', 'List all chat sessions')
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.option('-h, --history [limit]', 'Show conversation history (default: 10)')
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.option('--search <query>', 'Search all conversations')
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.option('-m, --model <model>', 'LLM model (local/openai/claude/ollama)', 'local')
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.option('--api-key <key>', 'API key for cloud models')
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.option('--base-url <url>', 'Base URL for local models (default: http://localhost:11434)')
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.action(wrapAction(async (message, options) => {
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const { BrainyData } = await import('../dist/brainyData.js')
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const { BrainyChat } = await import('../dist/chat/BrainyChat.js')
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console.log(colors.primary('🧠💬 Brainy Chat - AI-Powered Conversation with Your Data'))
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console.log(colors.info('Talk to your brain using your data as context'))
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console.log()
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// Initialize brainy and chat
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const brainy = new BrainyData()
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await brainy.init()
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const chat = new BrainyChat(brainy)
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// Handle different options
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if (options.list) {
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console.log(colors.primary('📋 Chat Sessions'))
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const sessions = await chat.getSessions(20)
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if (sessions.length === 0) {
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console.log(colors.warning('No chat sessions found. Start chatting to create your first session!'))
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} else {
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sessions.forEach((session, i) => {
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console.log(colors.success(`${i + 1}. ${session.id}`))
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if (session.title) console.log(colors.info(` Title: ${session.title}`))
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console.log(colors.info(` Messages: ${session.messageCount}`))
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console.log(colors.info(` Last active: ${session.lastMessageAt.toLocaleDateString()}`))
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})
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}
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return
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}
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if (options.search) {
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console.log(colors.primary(`🔍 Searching conversations for: "${options.search}"`))
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const results = await chat.searchMessages(options.search, { limit: 10 })
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if (results.length === 0) {
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console.log(colors.warning('No messages found'))
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} else {
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results.forEach((msg, i) => {
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console.log(colors.success(`\n${i + 1}. [${msg.sessionId}] ${colors.info(msg.speaker)}:`))
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console.log(` ${msg.content.substring(0, 200)}${msg.content.length > 200 ? '...' : ''}`)
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})
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}
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return
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}
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if (options.history) {
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const limit = parseInt(options.history) || 10
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console.log(colors.primary(`📜 Recent Chat History (${limit} messages)`))
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const history = await chat.getHistory(limit)
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if (history.length === 0) {
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console.log(colors.warning('No chat history found'))
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} else {
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history.forEach(msg => {
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const speaker = msg.speaker === 'user' ? colors.success('You') : colors.info('AI')
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console.log(`${speaker}: ${msg.content}`)
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console.log(colors.info(` ${msg.timestamp.toLocaleString()}`))
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console.log()
|
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})
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}
|
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return
|
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}
|
||
|
||
// Start interactive chat or process single message
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if (!message) {
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console.log(colors.success('🎯 Interactive mode - type messages or "exit" to quit'))
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console.log(colors.info(`Model: ${options.model}`))
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console.log()
|
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|
||
// Auto-discover previous session
|
||
const session = options.new ? null : await chat.initialize()
|
||
if (session) {
|
||
console.log(colors.success(`📋 Resumed session: ${session.id}`))
|
||
console.log()
|
||
} else {
|
||
const newSession = await chat.startNewSession()
|
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console.log(colors.success(`🆕 Started new session: ${newSession.id}`))
|
||
console.log()
|
||
}
|
||
|
||
// Interactive chat loop
|
||
const rl = createInterface({
|
||
input: process.stdin,
|
||
output: process.stdout,
|
||
prompt: colors.primary('You: ')
|
||
})
|
||
|
||
rl.prompt()
|
||
|
||
rl.on('line', async (input) => {
|
||
if (input.trim().toLowerCase() === 'exit') {
|
||
console.log(colors.success('👋 Chat session saved to your brain!'))
|
||
rl.close()
|
||
return
|
||
}
|
||
|
||
if (input.trim()) {
|
||
// Store user message
|
||
await chat.addMessage(input.trim(), 'user')
|
||
|
||
// Generate AI response
|
||
try {
|
||
const response = await generateAIResponse(input.trim(), brainy, options)
|
||
console.log(colors.info('AI: ') + response)
|
||
|
||
// Store AI response
|
||
await chat.addMessage(response, 'assistant', { model: options.model })
|
||
console.log()
|
||
} catch (error) {
|
||
console.log(colors.error('AI Error: ') + error.message)
|
||
console.log(colors.warning('💡 Tip: Try setting --model local or providing --api-key'))
|
||
console.log()
|
||
}
|
||
}
|
||
|
||
rl.prompt()
|
||
})
|
||
|
||
rl.on('close', () => {
|
||
exitProcess(0)
|
||
})
|
||
|
||
} else {
|
||
// Single message mode
|
||
console.log(colors.success('You: ') + message)
|
||
|
||
try {
|
||
const response = await generateAIResponse(message, brainy, options)
|
||
console.log(colors.info('AI: ') + response)
|
||
|
||
// Store conversation
|
||
await chat.addMessage(message, 'user')
|
||
await chat.addMessage(response, 'assistant', { model: options.model })
|
||
|
||
} catch (error) {
|
||
console.log(colors.error('Error: ') + error.message)
|
||
console.log(colors.info('💡 Try: brainy chat --model local or provide --api-key'))
|
||
}
|
||
}
|
||
}))
|
||
|
||
// Command 3: IMPORT - Bulk/external data
|
||
program
|
||
.command('import <source>')
|
||
.description('Import bulk data from files, URLs, or streams')
|
||
.option('-t, --type <type>', 'Source type (file, url, stream)')
|
||
.option('-c, --chunk-size <size>', 'Chunk size for large imports', '1000')
|
||
.action(wrapAction(async (source, options) => {
|
||
console.log(colors.info('📥 Starting neural import...'))
|
||
console.log(colors.info(`Source: ${source}`))
|
||
|
||
// Use the unified import system from the cleanup plan
|
||
const { NeuralImport } = await import('../dist/cortex/neuralImport.js')
|
||
const importer = new NeuralImport()
|
||
|
||
const result = await importer.import(source, {
|
||
chunkSize: parseInt(options.chunkSize)
|
||
})
|
||
|
||
console.log(colors.success(`✅ Imported ${result.count} items`))
|
||
if (result.detectedTypes) {
|
||
console.log(colors.info('🔍 Detected types:'), result.detectedTypes)
|
||
}
|
||
}))
|
||
|
||
// Command 3: SEARCH - Triple-power search
|
||
program
|
||
.command('search <query>')
|
||
.description('Search your brain (vector + graph + facets)')
|
||
.option('-l, --limit <number>', 'Results limit', '10')
|
||
.option('-f, --filter <json>', 'Metadata filters (see "brainy fields" for available fields)')
|
||
.option('-d, --depth <number>', 'Relationship depth', '2')
|
||
.option('--fields', 'Show available filter fields and exit')
|
||
.action(wrapAction(async (query, options) => {
|
||
|
||
// Handle --fields option
|
||
if (options.fields) {
|
||
console.log(colors.primary('🔍 Available Filter Fields'))
|
||
console.log(colors.primary('=' .repeat(30)))
|
||
|
||
try {
|
||
const { BrainyData } = await import('../dist/brainyData.js')
|
||
const brainy = new BrainyData()
|
||
await brainy.init()
|
||
|
||
const filterFields = await brainy.getFilterFields()
|
||
if (filterFields.length > 0) {
|
||
console.log(colors.success('Available fields for --filter option:'))
|
||
filterFields.forEach(field => {
|
||
console.log(colors.info(` ${field}`))
|
||
})
|
||
console.log()
|
||
console.log(colors.primary('Usage Examples:'))
|
||
console.log(colors.info(` brainy search "query" --filter '{"type":"person"}'`))
|
||
console.log(colors.info(` brainy search "query" --filter '{"category":"work","status":"active"}'`))
|
||
} else {
|
||
console.log(colors.warning('No indexed fields available yet.'))
|
||
console.log(colors.info('Add some data with metadata to see available fields.'))
|
||
}
|
||
|
||
} catch (error) {
|
||
console.log(colors.error(`Error: ${error.message}`))
|
||
}
|
||
return
|
||
}
|
||
console.log(colors.info(`🔍 Searching: "${query}"`))
|
||
|
||
const searchOptions = {
|
||
limit: parseInt(options.limit),
|
||
depth: parseInt(options.depth)
|
||
}
|
||
|
||
if (options.filter) {
|
||
try {
|
||
searchOptions.filter = JSON.parse(options.filter)
|
||
} catch {
|
||
console.error(colors.error('Invalid filter JSON'))
|
||
process.exit(1)
|
||
}
|
||
}
|
||
|
||
const brainyInstance = await getBrainy()
|
||
const results = await brainyInstance.search(query, searchOptions.limit || 10, searchOptions)
|
||
|
||
if (results.length === 0) {
|
||
console.log(colors.warning('No results found'))
|
||
return
|
||
}
|
||
|
||
console.log(colors.success(`✅ Found ${results.length} results:`))
|
||
results.forEach((result, i) => {
|
||
console.log(colors.primary(`\n${i + 1}. ${result.content}`))
|
||
if (result.score) {
|
||
console.log(colors.info(` Relevance: ${(result.score * 100).toFixed(1)}%`))
|
||
}
|
||
if (result.type) {
|
||
console.log(colors.info(` Type: ${result.type}`))
|
||
}
|
||
})
|
||
}))
|
||
|
||
// Command 4: UPDATE - Update existing data
|
||
program
|
||
.command('update <id>')
|
||
.description('Update existing data with new content or metadata')
|
||
.option('-d, --data <data>', 'New data content')
|
||
.option('-m, --metadata <json>', 'New metadata as JSON')
|
||
.option('--no-merge', 'Replace metadata instead of merging')
|
||
.option('--no-reindex', 'Skip reindexing (faster but less accurate search)')
|
||
.option('--cascade', 'Update related verbs')
|
||
.action(wrapAction(async (id, options) => {
|
||
console.log(colors.info(`🔄 Updating: "${id}"`))
|
||
|
||
if (!options.data && !options.metadata) {
|
||
console.error(colors.error('Error: Must provide --data or --metadata'))
|
||
process.exit(1)
|
||
}
|
||
|
||
let metadata = undefined
|
||
if (options.metadata) {
|
||
try {
|
||
metadata = JSON.parse(options.metadata)
|
||
} catch {
|
||
console.error(colors.error('Invalid JSON metadata'))
|
||
process.exit(1)
|
||
}
|
||
}
|
||
|
||
const brainyInstance = await getBrainy()
|
||
|
||
const success = await brainyInstance.update(id, options.data, metadata, {
|
||
merge: options.merge !== false, // Default true unless --no-merge
|
||
reindex: options.reindex !== false, // Default true unless --no-reindex
|
||
cascade: options.cascade || false
|
||
})
|
||
|
||
if (success) {
|
||
console.log(colors.success('✅ Updated successfully!'))
|
||
if (options.cascade) {
|
||
console.log(colors.info('📎 Related verbs updated'))
|
||
}
|
||
} else {
|
||
console.log(colors.error('❌ Update failed'))
|
||
}
|
||
}))
|
||
|
||
// Command 5: DELETE - Remove data (soft delete by default)
|
||
program
|
||
.command('delete <id>')
|
||
.description('Delete data (soft delete by default, preserves indexes)')
|
||
.option('--hard', 'Permanent deletion (removes from indexes)')
|
||
.option('--cascade', 'Delete related verbs')
|
||
.option('--force', 'Force delete even if has relationships')
|
||
.action(wrapAction(async (id, options) => {
|
||
console.log(colors.info(`🗑️ Deleting: "${id}"`))
|
||
|
||
if (options.hard) {
|
||
console.log(colors.warning('⚠️ Hard delete - data will be permanently removed'))
|
||
} else {
|
||
console.log(colors.info('🔒 Soft delete - data marked as deleted but preserved'))
|
||
}
|
||
|
||
const brainyInstance = await getBrainy()
|
||
|
||
try {
|
||
const success = await brainyInstance.delete(id, {
|
||
soft: !options.hard, // Soft delete unless --hard specified
|
||
cascade: options.cascade || false,
|
||
force: options.force || false
|
||
})
|
||
|
||
if (success) {
|
||
console.log(colors.success('✅ Deleted successfully!'))
|
||
if (options.cascade) {
|
||
console.log(colors.info('📎 Related verbs also deleted'))
|
||
}
|
||
} else {
|
||
console.log(colors.error('❌ Delete failed'))
|
||
}
|
||
} catch (error) {
|
||
console.error(colors.error(`❌ Delete failed: ${error.message}`))
|
||
if (error.message.includes('has relationships')) {
|
||
console.log(colors.info('💡 Try: --cascade to delete relationships or --force to ignore them'))
|
||
}
|
||
}
|
||
}))
|
||
|
||
// Command 6: STATUS - Database health & info
|
||
program
|
||
.command('status')
|
||
.description('Show brain status and comprehensive statistics')
|
||
.option('-v, --verbose', 'Show raw JSON statistics')
|
||
.option('-s, --simple', 'Show only basic info')
|
||
.action(wrapAction(async (options) => {
|
||
console.log(colors.primary('🧠 Brain Status & Statistics'))
|
||
console.log(colors.primary('=' .repeat(50)))
|
||
|
||
try {
|
||
const { BrainyData } = await import('../dist/brainyData.js')
|
||
const brainy = new BrainyData()
|
||
await brainy.init()
|
||
|
||
// Get comprehensive stats
|
||
const stats = await brainy.getStatistics()
|
||
const memUsage = process.memoryUsage()
|
||
|
||
// Basic Health Status
|
||
console.log(colors.success('💚 Status: Healthy'))
|
||
console.log(colors.info(`🚀 Version: ${packageJson.version}`))
|
||
console.log()
|
||
|
||
if (options.simple) {
|
||
console.log(colors.info(`📊 Total Items: ${stats.total || 0}`))
|
||
console.log(colors.info(`🧠 Memory: ${(memUsage.heapUsed / 1024 / 1024).toFixed(1)} MB`))
|
||
return
|
||
}
|
||
|
||
// Core Statistics
|
||
console.log(colors.primary('📊 Core Database Statistics'))
|
||
console.log(colors.info(` Total Items: ${colors.success(stats.total || 0)}`))
|
||
console.log(colors.info(` Nouns: ${colors.success(stats.nounCount || 0)}`))
|
||
console.log(colors.info(` Verbs (Relationships): ${colors.success(stats.verbCount || 0)}`))
|
||
console.log(colors.info(` Metadata Records: ${colors.success(stats.metadataCount || 0)}`))
|
||
console.log()
|
||
|
||
// Per-Service Breakdown (if available)
|
||
if (stats.serviceBreakdown && Object.keys(stats.serviceBreakdown).length > 0) {
|
||
console.log(colors.primary('🔧 Per-Service Breakdown'))
|
||
Object.entries(stats.serviceBreakdown).forEach(([service, serviceStats]) => {
|
||
console.log(colors.info(` ${colors.success(service)}:`))
|
||
console.log(colors.info(` Nouns: ${serviceStats.nounCount}`))
|
||
console.log(colors.info(` Verbs: ${serviceStats.verbCount}`))
|
||
console.log(colors.info(` Metadata: ${serviceStats.metadataCount}`))
|
||
})
|
||
console.log()
|
||
}
|
||
|
||
// Storage Information
|
||
if (stats.storage) {
|
||
console.log(colors.primary('💾 Storage Information'))
|
||
console.log(colors.info(` Type: ${colors.success(stats.storage.type || 'Unknown')}`))
|
||
if (stats.storage.size) {
|
||
const sizeInMB = (stats.storage.size / 1024 / 1024).toFixed(2)
|
||
console.log(colors.info(` Size: ${colors.success(sizeInMB)} MB`))
|
||
}
|
||
if (stats.storage.location) {
|
||
console.log(colors.info(` Location: ${colors.success(stats.storage.location)}`))
|
||
}
|
||
console.log()
|
||
}
|
||
|
||
// Performance Metrics
|
||
if (stats.performance) {
|
||
console.log(colors.primary('⚡ Performance Metrics'))
|
||
if (stats.performance.avgQueryTime) {
|
||
console.log(colors.info(` Avg Query Time: ${colors.success(stats.performance.avgQueryTime.toFixed(2))} ms`))
|
||
}
|
||
if (stats.performance.totalQueries) {
|
||
console.log(colors.info(` Total Queries: ${colors.success(stats.performance.totalQueries)}`))
|
||
}
|
||
if (stats.performance.cacheHitRate) {
|
||
console.log(colors.info(` Cache Hit Rate: ${colors.success((stats.performance.cacheHitRate * 100).toFixed(1))}%`))
|
||
}
|
||
console.log()
|
||
}
|
||
|
||
// Vector Index Information
|
||
if (stats.index) {
|
||
console.log(colors.primary('🎯 Vector Index'))
|
||
console.log(colors.info(` Dimensions: ${colors.success(stats.index.dimensions || 'N/A')}`))
|
||
console.log(colors.info(` Indexed Vectors: ${colors.success(stats.index.vectorCount || 0)}`))
|
||
if (stats.index.indexSize) {
|
||
console.log(colors.info(` Index Size: ${colors.success((stats.index.indexSize / 1024 / 1024).toFixed(2))} MB`))
|
||
}
|
||
console.log()
|
||
}
|
||
|
||
// Memory Usage Breakdown
|
||
console.log(colors.primary('🧠 Memory Usage'))
|
||
console.log(colors.info(` Heap Used: ${colors.success((memUsage.heapUsed / 1024 / 1024).toFixed(1))} MB`))
|
||
console.log(colors.info(` Heap Total: ${colors.success((memUsage.heapTotal / 1024 / 1024).toFixed(1))} MB`))
|
||
console.log(colors.info(` RSS: ${colors.success((memUsage.rss / 1024 / 1024).toFixed(1))} MB`))
|
||
console.log()
|
||
|
||
// Active Augmentations
|
||
console.log(colors.primary('🔌 Active Augmentations'))
|
||
const augmentations = cortex.getAllAugmentations()
|
||
if (augmentations.length === 0) {
|
||
console.log(colors.warning(' No augmentations currently active'))
|
||
} else {
|
||
augmentations.forEach(aug => {
|
||
console.log(colors.success(` ✅ ${aug.name}`))
|
||
if (aug.description) {
|
||
console.log(colors.info(` ${aug.description}`))
|
||
}
|
||
})
|
||
}
|
||
console.log()
|
||
|
||
// Configuration Summary
|
||
if (stats.config) {
|
||
console.log(colors.primary('⚙️ Configuration'))
|
||
Object.entries(stats.config).forEach(([key, value]) => {
|
||
// Don't show sensitive values
|
||
if (key.toLowerCase().includes('key') || key.toLowerCase().includes('secret')) {
|
||
console.log(colors.info(` ${key}: ${colors.warning('[HIDDEN]')}`))
|
||
} else {
|
||
console.log(colors.info(` ${key}: ${colors.success(value)}`))
|
||
}
|
||
})
|
||
console.log()
|
||
}
|
||
|
||
// Available Fields for Advanced Search
|
||
console.log(colors.primary('🔍 Available Search Fields'))
|
||
try {
|
||
const filterFields = await brainy.getFilterFields()
|
||
if (filterFields.length > 0) {
|
||
console.log(colors.info(' Use these fields for advanced filtering:'))
|
||
filterFields.forEach(field => {
|
||
console.log(colors.success(` ${field}`))
|
||
})
|
||
console.log(colors.info('\n Example: brainy search "query" --filter \'{"type":"person"}\''))
|
||
} else {
|
||
console.log(colors.warning(' No indexed fields available yet'))
|
||
console.log(colors.info(' Add some data to see available fields'))
|
||
}
|
||
} catch (error) {
|
||
console.log(colors.warning(' Field discovery not available'))
|
||
}
|
||
console.log()
|
||
|
||
// Show raw JSON if verbose
|
||
if (options.verbose) {
|
||
console.log(colors.primary('📋 Raw Statistics (JSON)'))
|
||
console.log(colors.info(JSON.stringify(stats, null, 2)))
|
||
}
|
||
|
||
} catch (error) {
|
||
console.log(colors.error('❌ Status: Error'))
|
||
console.log(colors.error(`Error: ${error.message}`))
|
||
if (options.verbose) {
|
||
console.log(colors.error('Stack trace:'))
|
||
console.log(error.stack)
|
||
}
|
||
}
|
||
}))
|
||
|
||
// Command 5: CONFIG - Essential configuration
|
||
program
|
||
.command('config <action> [key] [value]')
|
||
.description('Configure brainy (get, set, list)')
|
||
.action(wrapAction(async (action, key, value) => {
|
||
const configActions = {
|
||
get: async () => {
|
||
if (!key) {
|
||
console.error(colors.error('Please specify a key: brainy config get <key>'))
|
||
process.exit(1)
|
||
}
|
||
const result = await cortex.configGet(key)
|
||
console.log(colors.success(`${key}: ${result || 'not set'}`))
|
||
},
|
||
set: async () => {
|
||
if (!key || !value) {
|
||
console.error(colors.error('Usage: brainy config set <key> <value>'))
|
||
process.exit(1)
|
||
}
|
||
await cortex.configSet(key, value)
|
||
console.log(colors.success(`✅ Set ${key} = ${value}`))
|
||
},
|
||
list: async () => {
|
||
const config = await cortex.configList()
|
||
console.log(colors.primary('🔧 Current Configuration:'))
|
||
Object.entries(config).forEach(([k, v]) => {
|
||
console.log(colors.info(` ${k}: ${v}`))
|
||
})
|
||
}
|
||
}
|
||
|
||
if (configActions[action]) {
|
||
await configActions[action]()
|
||
} else {
|
||
console.error(colors.error('Valid actions: get, set, list'))
|
||
process.exit(1)
|
||
}
|
||
}))
|
||
|
||
// Command 6: CLOUD - Premium features connection
|
||
program
|
||
.command('cloud <action>')
|
||
.description('Connect to Brain Cloud premium features')
|
||
.option('-i, --instance <id>', 'Brain Cloud instance ID')
|
||
.action(wrapAction(async (action, options) => {
|
||
console.log(colors.primary('☁️ Brain Cloud Premium Features'))
|
||
|
||
const cloudActions = {
|
||
connect: async () => {
|
||
console.log(colors.info('🔗 Connecting to Brain Cloud...'))
|
||
// Dynamic import to avoid loading premium code unnecessarily
|
||
try {
|
||
const { BrainCloudSDK } = await import('@brainy-cloud/sdk')
|
||
const connected = await BrainCloudSDK.connect(options.instance)
|
||
if (connected) {
|
||
console.log(colors.success('✅ Connected to Brain Cloud'))
|
||
console.log(colors.info(`Instance: ${connected.instanceId}`))
|
||
}
|
||
} catch (error) {
|
||
console.log(colors.warning('⚠️ Brain Cloud SDK not installed'))
|
||
console.log(colors.info('Install with: npm install @brainy-cloud/sdk'))
|
||
console.log(colors.info('Or visit: https://brain-cloud.soulcraft.com'))
|
||
}
|
||
},
|
||
status: async () => {
|
||
try {
|
||
const { BrainCloudSDK } = await import('@brainy-cloud/sdk')
|
||
const status = await BrainCloudSDK.getStatus()
|
||
console.log(colors.success('☁️ Cloud Status: Connected'))
|
||
console.log(colors.info(`Instance: ${status.instanceId}`))
|
||
console.log(colors.info(`Augmentations: ${status.augmentationCount} available`))
|
||
} catch {
|
||
console.log(colors.warning('☁️ Cloud Status: Not connected'))
|
||
console.log(colors.info('Use "brainy cloud connect" to connect'))
|
||
}
|
||
},
|
||
augmentations: async () => {
|
||
try {
|
||
const { BrainCloudSDK } = await import('@brainy-cloud/sdk')
|
||
const augs = await BrainCloudSDK.listAugmentations()
|
||
console.log(colors.primary('🧩 Available Premium Augmentations:'))
|
||
augs.forEach(aug => {
|
||
console.log(colors.success(` ✅ ${aug.name} - ${aug.description}`))
|
||
})
|
||
} catch {
|
||
console.log(colors.warning('Connect to Brain Cloud first: brainy cloud connect'))
|
||
}
|
||
}
|
||
}
|
||
|
||
if (cloudActions[action]) {
|
||
await cloudActions[action]()
|
||
} else {
|
||
console.log(colors.error('Valid actions: connect, status, augmentations'))
|
||
console.log(colors.info('Example: brainy cloud connect --instance demo-test-auto'))
|
||
}
|
||
}))
|
||
|
||
// Command 7: MIGRATE - Migration tools
|
||
program
|
||
.command('migrate <action>')
|
||
.description('Migration tools for upgrades')
|
||
.option('-f, --from <version>', 'Migrate from version')
|
||
.option('-b, --backup', 'Create backup before migration')
|
||
.action(wrapAction(async (action, options) => {
|
||
console.log(colors.primary('🔄 Brainy Migration Tools'))
|
||
|
||
const migrateActions = {
|
||
check: async () => {
|
||
console.log(colors.info('🔍 Checking for migration needs...'))
|
||
// Check for deprecated methods, old config, etc.
|
||
const issues = []
|
||
|
||
try {
|
||
const { BrainyData } = await import('../dist/brainyData.js')
|
||
const brainy = new BrainyData()
|
||
|
||
// Check for old API usage
|
||
console.log(colors.success('✅ No migration issues found'))
|
||
} catch (error) {
|
||
console.log(colors.warning(`⚠️ Found issues: ${error.message}`))
|
||
}
|
||
},
|
||
backup: async () => {
|
||
console.log(colors.info('💾 Creating backup...'))
|
||
const { BrainyData } = await import('../dist/brainyData.js')
|
||
const brainy = new BrainyData()
|
||
const backup = await brainy.createBackup()
|
||
console.log(colors.success(`✅ Backup created: ${backup.path}`))
|
||
},
|
||
restore: async () => {
|
||
if (!options.from) {
|
||
console.error(colors.error('Please specify backup file: --from <path>'))
|
||
process.exit(1)
|
||
}
|
||
console.log(colors.info(`📥 Restoring from: ${options.from}`))
|
||
const { BrainyData } = await import('../dist/brainyData.js')
|
||
const brainy = new BrainyData()
|
||
await brainy.restoreBackup(options.from)
|
||
console.log(colors.success('✅ Restore complete'))
|
||
}
|
||
}
|
||
|
||
if (migrateActions[action]) {
|
||
await migrateActions[action]()
|
||
} else {
|
||
console.log(colors.error('Valid actions: check, backup, restore'))
|
||
console.log(colors.info('Example: brainy migrate check'))
|
||
}
|
||
}))
|
||
|
||
// Command 8: HELP - Interactive guidance
|
||
program
|
||
.command('help [command]')
|
||
.description('Get help or enter interactive mode')
|
||
.action(wrapAction(async (command) => {
|
||
if (command) {
|
||
program.help()
|
||
return
|
||
}
|
||
|
||
// Interactive mode for beginners
|
||
console.log(colors.primary('🧠⚛️ Welcome to Brainy!'))
|
||
console.log(colors.info('Your AI-powered second brain'))
|
||
console.log()
|
||
|
||
const rl = createInterface({
|
||
input: process.stdin,
|
||
output: process.stdout
|
||
})
|
||
|
||
console.log(colors.primary('What would you like to do?'))
|
||
console.log(colors.info('1. Add some data'))
|
||
console.log(colors.info('2. Chat with AI using your data'))
|
||
console.log(colors.info('3. Search your brain'))
|
||
console.log(colors.info('4. Update existing data'))
|
||
console.log(colors.info('5. Delete data'))
|
||
console.log(colors.info('6. Import a file'))
|
||
console.log(colors.info('7. Check status'))
|
||
console.log(colors.info('8. Connect to Brain Cloud'))
|
||
console.log(colors.info('9. Configuration'))
|
||
console.log(colors.info('10. Show all commands'))
|
||
console.log()
|
||
|
||
const choice = await new Promise(resolve => {
|
||
rl.question(colors.primary('Enter your choice (1-10): '), (answer) => {
|
||
rl.close()
|
||
resolve(answer)
|
||
})
|
||
})
|
||
|
||
switch (choice) {
|
||
case '1':
|
||
console.log(colors.success('\n🧠 Use: brainy add "your data here"'))
|
||
console.log(colors.info('Example: brainy add "John works at Google"'))
|
||
break
|
||
case '2':
|
||
console.log(colors.success('\n💬 Use: brainy chat "your question"'))
|
||
console.log(colors.info('Example: brainy chat "Tell me about my data"'))
|
||
console.log(colors.info('Supports: local (Ollama), OpenAI, Claude'))
|
||
break
|
||
case '3':
|
||
console.log(colors.success('\n🔍 Use: brainy search "your query"'))
|
||
console.log(colors.info('Example: brainy search "Google employees"'))
|
||
break
|
||
case '4':
|
||
console.log(colors.success('\n📥 Use: brainy import <file-or-url>'))
|
||
console.log(colors.info('Example: brainy import data.txt'))
|
||
break
|
||
case '5':
|
||
console.log(colors.success('\n📊 Use: brainy status'))
|
||
console.log(colors.info('Shows comprehensive brain statistics'))
|
||
console.log(colors.info('Options: --simple (quick) or --verbose (detailed)'))
|
||
break
|
||
case '6':
|
||
console.log(colors.success('\n☁️ Use: brainy cloud connect'))
|
||
console.log(colors.info('Example: brainy cloud connect --instance demo-test-auto'))
|
||
break
|
||
case '7':
|
||
console.log(colors.success('\n🔧 Use: brainy config <action>'))
|
||
console.log(colors.info('Example: brainy config list'))
|
||
break
|
||
case '8':
|
||
program.help()
|
||
break
|
||
default:
|
||
console.log(colors.warning('Invalid choice. Use "brainy --help" for all commands.'))
|
||
}
|
||
}))
|
||
|
||
// ========================================
|
||
// FALLBACK - Show interactive help if no command
|
||
// ========================================
|
||
|
||
// If no arguments provided, show interactive help
|
||
if (process.argv.length === 2) {
|
||
program.parse(['node', 'brainy', 'help'])
|
||
} else {
|
||
program.parse(process.argv)
|
||
} |