brainy/docs/guides/import-anything.md

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# Import Anything - ONE Method, Infinite Intelligence 🚀
Brainy's import is **ONE magical method** that understands EVERYTHING:
- 📊 Data (objects, arrays, strings)
- 📁 Files (auto-detects by path)
- 🌐 URLs (auto-fetches with authentication support)
- 📄 Formats (JSON, CSV, Excel, PDF, YAML, DOCX, Markdown - all auto-detected)
## The Ultimate Simplicity
```javascript
import { Brainy } from '@soulcraft/brainy'
const brain = new Brainy()
await brain.init()
// ONE method for EVERYTHING:
await brain.import(anything)
```
## Import Examples - It Just Works™
### 📊 Import JSON Data
```javascript
// Array of objects? No problem.
const people = [
{ name: 'Alice', role: 'Engineer', company: 'TechCorp' },
{ name: 'Bob', role: 'Designer', company: 'TechCorp' }
]
await brain.import(people)
// ✨ Automatically detected as Person entities with Organization relationships!
```
### 📄 Import CSV - File or String
```javascript
// From file? Just pass the path!
await brain.import('customers.csv')
// ✨ Auto-detects encoding, delimiter, types - creates entities!
// Or pass CSV content directly
const csv = `name,age,city
John,30,NYC
Jane,25,SF`
await brain.import(csv, { format: 'csv' })
// ✨ Smart CSV parsing handles quotes, escapes, everything!
```
### 📊 Import Excel - Multi-Sheet Support
```javascript
// Import entire Excel workbook — every sheet is processed automatically
await brain.import('sales-report.xlsx')
// ✨ Processes all sheets, preserves structure, infers types!
// Mirror the workbook into the VFS, grouped by sheet
await brain.import('data.xlsx', {
vfsPath: '/imports/data',
groupBy: 'sheet'
})
// ✨ Multi-sheet data becomes interconnected entities!
```
### 📑 Import PDF - Text & Tables
```javascript
// Import PDF documents — text and tables are extracted automatically
await brain.import('research-paper.pdf')
// ✨ Extracts text, detects tables, preserves metadata!
```
### 📝 Import YAML - File or String
```javascript
// From file? Auto-detected!
await brain.import('config.yaml')
// ✨ Knows it's a file, reads it, parses YAML!
// Or directly:
const yaml = `
project: AI Assistant
team:
- name: Alice
role: Lead
- name: Bob
role: Dev
`
await brain.import(yaml, { format: 'yaml' })
// ✨ Hierarchical data becomes a connected graph!
```
### 📄 Import Word Documents (DOCX) -
```javascript
// From file path
await brain.import('research-paper.docx')
// ✨ Extracts text, headings, tables, and metadata!
// Or from buffer
const buffer = fs.readFileSync('document.docx')
await brain.import(buffer, { format: 'docx' })
// ✨ Uses heading hierarchy for entity organization!
// With neural extraction
await brain.import('report.docx', {
enableNeuralExtraction: true,
enableHierarchicalRelationships: true
})
// ✨ Extracts entities from paragraphs and creates relationships within sections!
```
### 🌐 Import from URLs - Auto-Detected!
```javascript
// Just pass the URL - it knows!
await brain.import('https://api.example.com/data.json')
// ✨ Auto-detects URL, fetches, parses, processes!
// Works with any URL
await brain.import('https://data.gov/census.csv')
// ✨ Fetches CSV from web, parses, imports!
// With authentication
await brain.import({
type: 'url',
data: 'https://api.example.com/private/data.xlsx',
auth: {
username: 'user',
password: 'pass'
}
})
// ✨ Supports basic authentication for protected resources!
// With custom headers
await brain.import({
type: 'url',
data: 'https://api.example.com/data.json',
headers: {
'Authorization': 'Bearer TOKEN',
'X-API-Key': 'your-key'
}
})
// ✨ Full HTTP header customization support!
```
### 📖 Import Plain Text
```javascript
// Even unstructured text works
const article = `Artificial Intelligence is transforming industries.
Machine learning enables predictive analytics.
Natural language processing powers chatbots.`
await brain.import(article, { format: 'text' })
// ✨ Extracts concepts, creates semantic connections!
```
## The Magic Behind the Scenes
When you import data, Brainy:
1. **Auto-detects format** - CSV, Excel, PDF, JSON, YAML, DOCX, Markdown, or by file extension
2. **Intelligent parsing** - CSV (encoding/delimiter), Excel (multi-sheet), PDF (text/tables), DOCX (headings/paragraphs)
3. **Identifies entity types** - Uses AI to classify as Person, Document, Product, etc. (31 types!)
4. **Finds relationships** - Detects connections like "belongsTo", "createdBy", "references" (40 types!)
5. **Scores confidence & weight** - Every entity and relationship gets quality metrics
6. **Creates embeddings** - Makes everything semantically searchable
7. **Indexes metadata** - Enables lightning-fast filtering with range queries
## Intelligent Type Detection
Brainy automatically detects what TYPE of data you're importing:
```javascript
// This becomes a Person entity
{ name: 'John', email: 'john@example.com' }
// This becomes an Organization
{ companyName: 'Acme', employees: 500 }
// This becomes a Document
{ title: 'Report', content: '...', author: 'Jane' }
// This becomes a Location
{ latitude: 37.7, longitude: -122.4, city: 'SF' }
```
**42 noun types and 127 verb types** cover EVERYTHING!
## Relationship Detection
Brainy finds connections in your data:
```javascript
const data = [
{ id: 'u1', name: 'Alice', managerId: 'u2' },
{ id: 'u2', name: 'Bob', departmentId: 'd1' },
{ id: 'd1', name: 'Engineering' }
]
await brain.import(data)
// ✨ Automatically creates:
// - Alice "reportsTo" Bob
// - Bob "memberOf" Engineering
```
## Confidence & Weight Scoring -
Every entity and relationship gets confidence and weight scores:
```javascript
// Import with confidence threshold
await brain.import(data, {
confidenceThreshold: 0.8 // Only extract entities with >80% confidence
})
// Query high-confidence entities using range queries
const highConfidence = await brain.find({
where: {
confidence: { gte: 0.8 } // Get entities with confidence >= 0.8
}
})
// Range query operators: gt, gte, lt, lte, between
const mediumConfidence = await brain.find({
where: {
confidence: { between: [0.6, 0.8] }
}
})
```
**What do confidence scores mean?**
- **High (>0.8)**: Very confident entity classification
- **Medium (0.6-0.8)**: Reasonable confidence
- **Low (<0.6)**: Uncertain classification (filtered by default)
**Weights** indicate importance/relevance within the document context.
## Per-Sheet Excel Extraction -
Excel files with multiple sheets can be organized by sheet:
```javascript
// Group entities by sheet in VFS
await brain.import('multi-sheet-data.xlsx', {
groupBy: 'sheet' // Creates separate directories for each sheet
})
// Result VFS structure:
// /imports/data/
// ├── Sheet1/
// │ ├── entity1.json
// │ └── entity2.json
// └── Sheet2/
// ├── entity3.json
// └── entity4.json
// Other groupBy options:
// - 'type': Group by entity type (Person, Place, etc.)
// - 'flat': All entities in one directory
// - 'custom': Use custom grouping function
```
## Query Your Imported Data
Once imported, use Triple Intelligence to query:
```javascript
// Vector search
feat(8.0): API simplification — remove neural()/Db.search, one storage `path` key, integration→0 8.0 RC cleanup toward "one place per thing, zero-config, no deprecation": - Remove the `brain.neural()` clustering namespace (ImprovedNeuralAPI + the dead legacy NeuralAPI + the neural CLI + neural-only types). Similarity is `find({vector})` / `similar({to})`; attribute grouping is the aggregation `GROUP BY` engine. The separate entity-extraction / smart-import feature (NeuralImport, NeuralEntityExtractor, SmartExtractor, NaturalLanguageProcessor, `brain.extract()`/`brain.nlp()`) is kept. - Remove `Db.search()`; `find()` is the one query verb (accepts a bare string or FindParams). Fix the bundled MCP client, which called a non-existent `brain.search(query, limit)` → now `find({ query, limit })`. - Storage config: collapse to one canonical top-level `path` key. The pre-8.0 aliases (`rootDirectory`, `options.*`, `fileSystemStorage.*`) are removed and now THROW with the exact rename instead of silently defaulting to `./brainy-data` on upgrade. A single resolver feeds createStorage, the 7.x→8.0 migration probe, and the plugin-factory handoff, so a native storage provider resolves the identical root (no split-brain). - Fix `similar({ threshold })`: the min-similarity filter was silently dropped; it is now applied as a post-filter on `result.score` (the documented way to bound semantic results). - Fix `vfs.rename()` on a directory: child path updates spread the entity vector into `update()` and failed dimension validation; they are metadata-only updates now. - Fix `vfs.move()`: copy+delete orphaned the content-addressed content blob (the destination shared the source hash, then unlink removed it). `move()` now delegates to `rename()` — an in-place path change that preserves the blob and the entity id, for files and directories. - Fix streaming import: the bulk fast path never flushed mid-import nor signalled queryability. Entity writes are now chunked by a progressive flush interval (100 → 1000 → 5000); each chunk flushes and emits `progress.queryable`, so imported data is queryable during the import. - Sweep all docs, comments, and JSDoc for the removed/changed APIs. Integration suite: 49 files / 588 passed / 0 failed. Unit: 80 files / 1456 passed, no type errors.
2026-06-20 13:31:11 -07:00
const similar = await brain.find('engineers')
// Natural language
const results = await brain.find('people in engineering who joined this year')
// Graph traversal + filters
const connected = await brain.find({
like: 'Alice',
connected: { depth: 2 },
where: { department: 'Engineering' }
})
```
## Import Options (Optional!)
Everything works with zero config, but you can customize:
```javascript
await brain.import(data, {
// Format detection
format: 'excel', // Force specific format (auto-detected if not specified)
// VFS & Organization
vfsPath: '/imports/my-data', // Where to store in VFS (auto-generated if not specified)
groupBy: 'type', // Group entities by: 'type' | 'sheet' | 'flat' | 'custom'
preserveSource: true, // Keep original source file in VFS (default: true)
// Entity & Relationship Creation
createEntities: true, // Create entities in knowledge graph (default: true)
createRelationships: true, // Create relationships in knowledge graph (default: true)
// Neural Intelligence
enableNeuralExtraction: true, // Use AI to extract entities (default: true)
enableRelationshipInference: true, // Use AI to infer relationships (default: true)
enableConceptExtraction: true, // Extract concepts from text (default: true)
confidenceThreshold: 0.6, // Minimum confidence for entities (0-1, default: 0.6)
// Deduplication
enableDeduplication: true, // Check for duplicate entities (default: true)
deduplicationThreshold: 0.85, // Similarity threshold for duplicates (0-1, default: 0.85)
// Notes: false disables BOTH the inline merge and the background pass that
// runs ~5 min after the last import (merged duplicates are deleted).
// The inline pass auto-disables for imports >100 entities (O(n²) cost);
// the background pass still covers those unless the flag is false.
// Performance
chunkSize: 100, // Batch size for processing (default: varies by operation)
// History & Progress
enableHistory: true, // Track import history (default: true)
onProgress: (progress) => { // Progress callback
console.log(progress.stage, progress.message)
}
})
```
## Error Handling
Import continues even if some items fail:
```javascript
const results = await brain.import(problematicData)
// Returns IDs of successful imports
// Logs warnings for failures
// Never crashes your app!
```
## Performance
- **Parallel processing** - Fast imports with concurrent operations
- **Batch operations** - Memory efficient chunk processing
- **Lazy loading** - Import system loads only when needed
- **Smart caching** - Type detection and format parsing results cached
## Use Cases
### 🏢 Business Data
```javascript
// Import ANY source - ONE method!
await brain.import('customers.csv') // File
await brain.import('https://api.co/orders') // URL
await brain.import(productsArray) // Data
// Now query across all of it!
await brain.find('customers who bought products in Q4')
```
### 🔬 Research Data
```javascript
// Import research papers
await brain.import(papers)
// Import citations
await brain.import(citations)
// Find connections
await brain.find('papers citing machine learning from 2024')
```
### 📱 Application Data
```javascript
// Import users
await brain.import(users)
// Import posts
await brain.import(posts)
// Import comments
await brain.import(comments)
// Query the social graph
await brain.find('posts by users following Alice with >10 comments')
```
## The Philosophy
**Zero Configuration**: Works perfectly out of the box
**Maximum Intelligence**: AI understands your data's meaning
**Universal Protocol**: 42 nouns × 127 verbs = ANY data model
**Delightful DX**: Simple, clean, modern API
## The ONE Method Philosophy
```javascript
// ONE method that understands EVERYTHING:
await brain.import(data) // Objects, arrays, strings
await brain.import('file.csv') // Files (auto-detected)
await brain.import('http://..') // URLs (auto-fetched)
// It ALWAYS knows what to do! ✨
```
**Why ONE method?**
- 🎯 **Simpler** - No need to remember different methods
- 🧠 **Smarter** - Auto-detects what you're importing
-**Magical** - It just works, every time
That's the power of the Universal Knowledge Protocol™ - infinite intelligence, zero complexity!