David Snelling
5be5ea5201
- Modernize BrainyInterface to only contain current API methods (add, relate, find, get) - Update all interface consumers to use modern API patterns - Make Brainy class implement clean modernized interface - Update CLI commands to use add() and relate() instead of deprecated methods - Update all source code components to use modern API consistently - Update examples and integration tests to modern patterns - Improve architectural consistency across the entire codebase BREAKING: BrainyInterface no longer contains deprecated methods Migration: Use add() instead of addNoun(), relate() instead of addVerb()
105 lines
No EOL
3 KiB
TypeScript
105 lines
No EOL
3 KiB
TypeScript
/**
|
|
* API Server Example
|
|
*
|
|
* This example shows how to expose Brainy through REST, WebSocket, and MCP APIs
|
|
* using the APIServerAugmentation.
|
|
*
|
|
* Zero-config philosophy: Just create and register the augmentation!
|
|
*/
|
|
|
|
import { BrainyData } from '../src/index.js'
|
|
import { APIServerAugmentation } from '../src/augmentations/apiServerAugmentation.js'
|
|
|
|
async function main() {
|
|
// 1. Create Brainy with zero config
|
|
const brain = new BrainyData()
|
|
await brain.init()
|
|
|
|
// 2. Add some sample data
|
|
await brain.add({ data: "The quick brown fox", type: 'content', metadata: { type: "sentence", category: "animals" } })
|
|
await brain.add({ data: "Machine learning models", type: 'content', metadata: { type: "tech", category: "AI" } })
|
|
await brain.add({ data: "Natural language processing", type: 'content', metadata: { type: "tech", category: "NLP" } })
|
|
|
|
// 3. Create and register the API Server augmentation
|
|
const apiServer = new APIServerAugmentation({
|
|
port: 3000,
|
|
host: 'localhost'
|
|
})
|
|
|
|
// Register the augmentation with Brainy
|
|
brain.augmentations.register(apiServer)
|
|
|
|
// Initialize augmentations with Brainy context
|
|
await brain.augmentations.initialize({
|
|
brain,
|
|
log: (msg: string, level?: string) => console.log(`[${level || 'info'}] ${msg}`),
|
|
config: {}
|
|
})
|
|
|
|
console.log('🚀 Brainy API Server is running!')
|
|
console.log('📡 REST API: http://localhost:3000')
|
|
console.log('🔌 WebSocket: ws://localhost:3000/ws')
|
|
console.log('🧠 MCP: http://localhost:3000/api/mcp')
|
|
console.log('')
|
|
console.log('Try these endpoints:')
|
|
console.log(' GET http://localhost:3000/health')
|
|
console.log(' POST http://localhost:3000/api/search')
|
|
console.log(' Body: { "query": "fox", "limit": 10 }')
|
|
console.log(' POST http://localhost:3000/api/add')
|
|
console.log(' Body: { "content": "New data", "metadata": {} }')
|
|
console.log('')
|
|
console.log('Press Ctrl+C to stop the server')
|
|
}
|
|
|
|
// Run the example
|
|
main().catch(console.error)
|
|
|
|
/**
|
|
* Example REST API calls:
|
|
*
|
|
* # Health check
|
|
* curl http://localhost:3000/health
|
|
*
|
|
* # Search
|
|
* curl -X POST http://localhost:3000/api/search \
|
|
* -H "Content-Type: application/json" \
|
|
* -d '{"query": "fox", "limit": 5}'
|
|
*
|
|
* # Add data
|
|
* curl -X POST http://localhost:3000/api/add \
|
|
* -H "Content-Type: application/json" \
|
|
* -d '{"content": "The cat sat on the mat", "metadata": {"type": "sentence"}}'
|
|
*
|
|
* # Get by ID
|
|
* curl http://localhost:3000/api/get/[id]
|
|
*
|
|
* # Statistics
|
|
* curl http://localhost:3000/api/stats
|
|
*/
|
|
|
|
/**
|
|
* Example WebSocket client (browser):
|
|
*
|
|
* const ws = new WebSocket('ws://localhost:3000/ws')
|
|
*
|
|
* ws.onopen = () => {
|
|
* // Subscribe to all operations
|
|
* ws.send(JSON.stringify({
|
|
* type: 'subscribe',
|
|
* operations: ['all']
|
|
* }))
|
|
*
|
|
* // Perform a search
|
|
* ws.send(JSON.stringify({
|
|
* type: 'search',
|
|
* query: 'fox',
|
|
* limit: 5,
|
|
* requestId: '123'
|
|
* }))
|
|
* }
|
|
*
|
|
* ws.onmessage = (event) => {
|
|
* const msg = JSON.parse(event.data)
|
|
* console.log('Received:', msg)
|
|
* }
|
|
*/ |