open-brainy/src/vfs/streams/VFSWriteStream.ts

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TypeScript
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feat: implement complete VFS with Knowledge Layer integration Add production-ready Virtual File System with intelligent Knowledge Layer: Core VFS Features: - Complete file system operations (read, write, mkdir, etc.) - Intelligent PathResolver with 4-layer caching system - Chunked storage for large files with real compression - Embedding generation for semantic operations - File relationships and metadata tracking - Import functionality from local filesystem Knowledge Layer Integration: - EventRecorder for complete file history and temporal coupling - SemanticVersioning with content-based change detection - PersistentEntitySystem for character/entity tracking across files - ConceptSystem for universal concept mapping and graphs - GitBridge for import/export between VFS and Git repositories Architecture: - KnowledgeAugmentation properly integrated into Brainy augmentation system - KnowledgeLayer wrapper provides real-time VFS operation interception - Background processing ensures VFS operations remain fast - All components use real Brainy embed() method for embeddings - Support for creative writing, coding projects, and project management Technical Implementation: - Fixed all stub/mock implementations with real working code - TypeScript compilation passes without errors - Comprehensive test suite demonstrating all features - Documentation covering architecture and usage patterns - Backwards compatible with existing Brainy functionality This enables scenarios like writing books with persistent characters, managing coding projects with concept tracking, and complete project coordination with intelligent file relationships.
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/**
* VFS Write Stream Implementation
*
* Real streaming write support for large files
*/
import { Writable } from 'stream'
import { VirtualFileSystem } from '../VirtualFileSystem.js'
import { WriteStreamOptions } from '../types.js'
export class VFSWriteStream extends Writable {
private chunks: Buffer[] = []
private size = 0
private _closed = false
constructor(
private vfs: VirtualFileSystem,
private path: string,
private options: WriteStreamOptions = {}
) {
super({
highWaterMark: 64 * 1024 // 64KB chunks
})
// Handle autoClose option
if (options.autoClose !== false) {
this.once('finish', () => this._flush())
}
}
override async _write(
feat: implement complete VFS with Knowledge Layer integration Add production-ready Virtual File System with intelligent Knowledge Layer: Core VFS Features: - Complete file system operations (read, write, mkdir, etc.) - Intelligent PathResolver with 4-layer caching system - Chunked storage for large files with real compression - Embedding generation for semantic operations - File relationships and metadata tracking - Import functionality from local filesystem Knowledge Layer Integration: - EventRecorder for complete file history and temporal coupling - SemanticVersioning with content-based change detection - PersistentEntitySystem for character/entity tracking across files - ConceptSystem for universal concept mapping and graphs - GitBridge for import/export between VFS and Git repositories Architecture: - KnowledgeAugmentation properly integrated into Brainy augmentation system - KnowledgeLayer wrapper provides real-time VFS operation interception - Background processing ensures VFS operations remain fast - All components use real Brainy embed() method for embeddings - Support for creative writing, coding projects, and project management Technical Implementation: - Fixed all stub/mock implementations with real working code - TypeScript compilation passes without errors - Comprehensive test suite demonstrating all features - Documentation covering architecture and usage patterns - Backwards compatible with existing Brainy functionality This enables scenarios like writing books with persistent characters, managing coding projects with concept tracking, and complete project coordination with intelligent file relationships.
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chunk: any,
encoding: BufferEncoding,
callback: (error?: Error | null) => void
): Promise<void> {
try {
// Convert to buffer if needed
const buffer = Buffer.isBuffer(chunk)
? chunk
: Buffer.from(chunk, encoding)
// Store chunk
this.chunks.push(buffer)
this.size += buffer.length
// For very large files, we could flush periodically
// to avoid memory issues, but for now we accumulate
callback()
} catch (error: any) {
callback(error)
}
}
override async _final(callback: (error?: Error | null) => void): Promise<void> {
feat: implement complete VFS with Knowledge Layer integration Add production-ready Virtual File System with intelligent Knowledge Layer: Core VFS Features: - Complete file system operations (read, write, mkdir, etc.) - Intelligent PathResolver with 4-layer caching system - Chunked storage for large files with real compression - Embedding generation for semantic operations - File relationships and metadata tracking - Import functionality from local filesystem Knowledge Layer Integration: - EventRecorder for complete file history and temporal coupling - SemanticVersioning with content-based change detection - PersistentEntitySystem for character/entity tracking across files - ConceptSystem for universal concept mapping and graphs - GitBridge for import/export between VFS and Git repositories Architecture: - KnowledgeAugmentation properly integrated into Brainy augmentation system - KnowledgeLayer wrapper provides real-time VFS operation interception - Background processing ensures VFS operations remain fast - All components use real Brainy embed() method for embeddings - Support for creative writing, coding projects, and project management Technical Implementation: - Fixed all stub/mock implementations with real working code - TypeScript compilation passes without errors - Comprehensive test suite demonstrating all features - Documentation covering architecture and usage patterns - Backwards compatible with existing Brainy functionality This enables scenarios like writing books with persistent characters, managing coding projects with concept tracking, and complete project coordination with intelligent file relationships.
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try {
await this._flush()
callback()
} catch (error: any) {
callback(error)
}
}
private async _flush(): Promise<void> {
if (this._closed) return
this._closed = true
// Combine all chunks
const data = Buffer.concat(this.chunks, this.size)
// Write to VFS
await this.vfs.writeFile(this.path, data, {
mode: this.options.mode,
encoding: this.options.encoding
})
// Clear chunks to free memory
this.chunks = []
}
override _destroy(error: Error | null, callback: (error?: Error | null) => void): void {
feat: implement complete VFS with Knowledge Layer integration Add production-ready Virtual File System with intelligent Knowledge Layer: Core VFS Features: - Complete file system operations (read, write, mkdir, etc.) - Intelligent PathResolver with 4-layer caching system - Chunked storage for large files with real compression - Embedding generation for semantic operations - File relationships and metadata tracking - Import functionality from local filesystem Knowledge Layer Integration: - EventRecorder for complete file history and temporal coupling - SemanticVersioning with content-based change detection - PersistentEntitySystem for character/entity tracking across files - ConceptSystem for universal concept mapping and graphs - GitBridge for import/export between VFS and Git repositories Architecture: - KnowledgeAugmentation properly integrated into Brainy augmentation system - KnowledgeLayer wrapper provides real-time VFS operation interception - Background processing ensures VFS operations remain fast - All components use real Brainy embed() method for embeddings - Support for creative writing, coding projects, and project management Technical Implementation: - Fixed all stub/mock implementations with real working code - TypeScript compilation passes without errors - Comprehensive test suite demonstrating all features - Documentation covering architecture and usage patterns - Backwards compatible with existing Brainy functionality This enables scenarios like writing books with persistent characters, managing coding projects with concept tracking, and complete project coordination with intelligent file relationships.
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// Clean up resources
this.chunks = []
this._closed = true
callback(error)
}
}