fix: correct typo in README major updates section
🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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README.md
143
README.md
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@ -11,28 +11,37 @@
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</div>
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## 🔥 MAJOR UPDATE: TensorFlow.js → Transformers.js Migration (v0.46+)
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## 🔥 MAJOR UPDATES: What's New in v0.46+ & v0.48+
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**We've completely replaced TensorFlow.js with Transformers.js for better performance and true offline operation!**
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### 🚀 **v0.48: MongoDB-Style Metadata Filtering**
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### Why We Made This Change
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**Powerful querying with familiar syntax - filter DURING search for maximum performance!**
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**The Honest Truth About TensorFlow.js:**
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```javascript
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const results = await brainy.search("wireless headphones", 10, {
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metadata: {
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category: { $in: ["electronics", "audio"] },
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price: { $lte: 200 },
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rating: { $gte: 4.0 },
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brand: { $ne: "Generic" }
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}
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})
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```
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- 📦 **Massive Package Size**: 12.5MB+ packages with complex dependency trees
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- 🌐 **Hidden Network Calls**: Even "local" models triggered fetch() calls internally
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- 🐛 **Dependency Hell**: Constant `--legacy-peer-deps` issues with Node.js updates
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- 🔧 **Maintenance Burden**: 47+ dependencies to keep compatible across environments
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- 💾 **Huge Models**: 525MB Universal Sentence Encoder models
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- ✅ **15+ MongoDB Operators**: `$gt`, `$in`, `$regex`, `$and`, `$or`, `$includes`, etc.
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- ✅ **Automatic Indexing**: Zero configuration, maximum performance
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- ✅ **Nested Fields**: Use dot notation for complex objects
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- ✅ **100% Backward Compatible**: Your existing code works unchanged
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### What You Get Now
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### ⚡ **v0.46: Transformers.js Migration**
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- ✅ **95% Smaller Package**: 643 kB vs 12.5 MB (and it actually works better!)
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- ✅ **84% Smaller Models**: 87 MB vs 525 MB all-MiniLM-L6-v2 vs USE
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- ✅ **True Offline Operation**: Zero network calls after initial model download
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- ✅ **5x Fewer Dependencies**: Clean dependency tree, no more peer dep issues
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- ✅ **Same API**: Drop-in replacement - your existing code just works
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- ✅ **Better Performance**: ONNX Runtime is faster than TensorFlow.js in most cases
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**Replaced TensorFlow.js for better performance and true offline operation!**
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- ✅ **95% Smaller Package**: 643 kB vs 12.5 MB
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- ✅ **84% Smaller Models**: 87 MB vs 525 MB models
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- ✅ **True Offline**: Zero network calls after initial download
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- ✅ **5x Fewer Dependencies**: Clean tree, no peer dependency issues
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- ✅ **Same API**: Drop-in replacement, existing code works unchanged
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### Migration (It's Automatic!)
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@ -60,7 +69,9 @@ RUN npm run download-models # Download during build for offline production
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**One API. Every environment. Zero configuration.**
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Brainy is the **AI-native database** that combines vector search and knowledge graphs in one unified API. Write your code once, and it runs everywhere - browsers, Node.js, serverless, edge workers - with automatic optimization for each environment.
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Brainy is the **AI-native database** that combines vector search and knowledge graphs in one unified API. Write your
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code once, and it runs everywhere - browsers, Node.js, serverless, edge workers - with automatic optimization for each
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environment.
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```javascript
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// This same code works EVERYWHERE
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@ -89,7 +100,8 @@ const results = await brainy.search("AI", 10) // Semantic search
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environment and optimizes itself
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- **🌍 True Write-Once, Run-Anywhere** - Same code runs in Angular, React, Vue, Node.js, Deno, Bun, serverless, edge
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workers, and web workers with automatic environment detection
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- **⚡ Scary Fast** - Handles millions of vectors with sub-millisecond search. GPU acceleration for embeddings, optimized CPU for distance calculations
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- **⚡ Scary Fast** - Handles millions of vectors with sub-millisecond search. GPU acceleration for embeddings, optimized
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CPU for distance calculations
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- **🎯 Self-Learning** - Like having a database that goes to the gym. Gets faster and smarter the more you use it
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- **🔮 AI-First Design** - Built for the age of embeddings, RAG, and semantic search. Your LLMs will thank you
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- **🎮 Actually Fun to Use** - Clean API, great DX, and it does the heavy lifting so you can build cool stuff
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@ -145,6 +157,17 @@ const contextual = await brainy.search("Who leads AI companies?", 5, {
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includeVerbs: true, // Include relationships in results
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nounTypes: ["person"], // Filter to specific entity types
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})
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// 5️⃣ NEW! MongoDB-style metadata filtering
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const filtered = await brainy.search("AI research", 10, {
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metadata: {
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type: "academic",
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year: { $gte: 2020 },
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status: { $in: ["published", "peer-reviewed"] },
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impact: { $gt: 100 }
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}
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})
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// Filters DURING search for maximum performance!
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```
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**🎯 That's it!** Vector search + graph database + works everywhere. No config needed.
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@ -213,18 +236,19 @@ import { BrainyData } from '@soulcraft/brainy'
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})
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export class SearchComponent implements OnInit {
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brainy = new BrainyData()
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async ngOnInit() {
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await this.brainy.init()
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// Add your data...
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}
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async search(query: string) {
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const results = await this.brainy.search(query, 5)
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// Display results...
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}
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}
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```
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</details>
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<details>
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@ -256,36 +280,39 @@ function Search() {
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return <input onChange={(e) => search(e.target.value)} placeholder="Search..." />
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}
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```
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</details>
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<details>
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<summary>📦 Full Vue Example</summary>
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```vue
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<script setup>
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import { BrainyData } from '@soulcraft/brainy'
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import { ref, onMounted } from 'vue'
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import { BrainyData } from '@soulcraft/brainy'
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import { ref, onMounted } from 'vue'
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const brainy = ref(null)
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const results = ref([])
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const brainy = ref(null)
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const results = ref([])
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onMounted(async () => {
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const db = new BrainyData()
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await db.init()
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// Add your data...
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brainy.value = db
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})
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onMounted(async () => {
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const db = new BrainyData()
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await db.init()
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// Add your data...
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brainy.value = db
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})
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const search = async (query) => {
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const results = await brainy.value?.search(query, 5) || []
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setResults(results)
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}
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const search = async (query) => {
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const results = await brainy.value?.search(query, 5) || []
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setResults(results)
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}
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</script>
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<template>
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<input @input="search($event.target.value)" placeholder="Search..." />
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</template>
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```
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</details>
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### 🟢 Node.js / Serverless / Edge
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@ -306,13 +333,12 @@ const results = await brainy.search("programming languages", 5)
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// Optional: Production with S3/R2 storage (auto-detected in cloud environments)
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const productionBrainy = new BrainyData({
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storage: {
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storage: {
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s3Storage: { bucketName: process.env.BUCKET_NAME }
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}
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})
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```
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**That's it! Same code, everywhere. Zero-to-Smart™**
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Brainy automatically detects and optimizes for:
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@ -397,6 +423,7 @@ console.log(`Instance ${health.instanceId}: ${health.status}`)
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### Core Capabilities
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- **Vector Search** - Find semantically similar content using embeddings
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- **MongoDB-Style Metadata Filtering** 🆕 - Advanced filtering with `$gt`, `$in`, `$regex`, `$and`, `$or` operators
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- **Graph Relationships** - Connect data with meaningful relationships
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- **JSON Document Search** - Search within specific fields with prioritization
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- **Distributed Mode** - Scale horizontally with automatic coordination between instances
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@ -871,11 +898,12 @@ const products = await brainy.getVerbsBySource(openai)
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<summary>🔍 See Framework Examples</summary>
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### React
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```jsx
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function App() {
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const [brainy] = useState(() => new BrainyData())
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useEffect(() => brainy.init(), [])
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const search = async (query) => {
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return await brainy.search(query, 10)
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}
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@ -884,19 +912,24 @@ function App() {
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```
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### Vue 3
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```vue
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<script setup>
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const brainy = new BrainyData()
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await brainy.init()
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// Same API as above
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const brainy = new BrainyData()
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await brainy.init()
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// Same API as above
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</script>
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```
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### Angular
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```typescript
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@Component({})
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export class AppComponent {
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brainy = new BrainyData()
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async ngOnInit() {
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await this.brainy.init()
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// Same API as above
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@ -905,24 +938,26 @@ export class AppComponent {
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```
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### Node.js / Deno / Bun
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```javascript
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const brainy = new BrainyData()
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await brainy.init()
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// Same API as above
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```
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</details>
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### 🌍 Framework-First, Runs Everywhere
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**Brainy automatically detects your environment and optimizes everything:**
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| Environment | Storage | Optimization |
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|------------|---------|-------------|
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| 🌐 Browser | OPFS | Web Workers, Memory Cache |
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| 🟢 Node.js | FileSystem / S3 | Worker Threads, Clustering |
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| ⚡ Serverless | S3 / Memory | Cold Start Optimization |
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| 🔥 Edge Workers | Memory / KV | Minimal Footprint |
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| 🦕 Deno/Bun | FileSystem / S3 | Native Performance |
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| Environment | Storage | Optimization |
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|-----------------|-----------------|----------------------------|
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| 🌐 Browser | OPFS | Web Workers, Memory Cache |
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| 🟢 Node.js | FileSystem / S3 | Worker Threads, Clustering |
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| ⚡ Serverless | S3 / Memory | Cold Start Optimization |
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| 🔥 Edge Workers | Memory / KV | Minimal Footprint |
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| 🦕 Deno/Bun | FileSystem / S3 | Native Performance |
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## 🌐 Deploy to Any Cloud
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<summary>☁️ See Cloud Platform Examples</summary>
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### Cloudflare Workers
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```javascript
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import { BrainyData } from '@soulcraft/brainy'
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@ -937,7 +973,7 @@ export default {
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async fetch(request) {
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const brainy = new BrainyData()
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await brainy.init()
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const url = new URL(request.url)
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const results = await brainy.search(url.searchParams.get('q'), 10)
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return Response.json(results)
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@ -946,32 +982,35 @@ export default {
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```
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### AWS Lambda
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```javascript
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import { BrainyData } from '@soulcraft/brainy'
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export const handler = async (event) => {
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const brainy = new BrainyData()
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await brainy.init()
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const results = await brainy.search(event.query, 10)
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return { statusCode: 200, body: JSON.stringify(results) }
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}
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```
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### Google Cloud Functions
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```javascript
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import { BrainyData } from '@soulcraft/brainy'
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export const searchHandler = async (req, res) => {
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const brainy = new BrainyData()
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await brainy.init()
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const results = await brainy.search(req.query.q, 10)
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res.json(results)
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}
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```
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### Vercel Edge Functions
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```javascript
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import { BrainyData } from '@soulcraft/brainy'
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@ -980,14 +1019,14 @@ export const config = { runtime: 'edge' }
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export default async function handler(request) {
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const brainy = new BrainyData()
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await brainy.init()
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const { searchParams } = new URL(request.url)
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const results = await brainy.search(searchParams.get('q'), 10)
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return Response.json(results)
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}
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```
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</details>
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</details>
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### Docker Container
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