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Files in Spaces

This document describes how Sila handles file storage, organization, and serving across the application. Files are stored using Content-Addressed Storage (CAS) and referenced through a logical file system structure.

Overview

Sila's file system provides:

  • Content-Addressed Storage (CAS): Files stored by SHA-256 hash for deduplication
  • Logical Organization: Files organized in a Files AppTree with folders and metadata
  • Reference-Based Access: Messages reference files by tree/vertex IDs, not embedded content
  • Direct File Serving: Files served via custom sila:// protocol
  • AI Integration: File content automatically included in AI conversations

Architecture

Content-Addressed Storage (CAS)

Files are stored on disk using their SHA-256 hash as the address:

  <spaceRoot>/
  space-v1/
    ops/                 # CRDT ops (jsonl)
    files/
      sha256/
        ab/
          cdef...89      # full hash split as 2+rest, binary content
    secrets              # encrypted secrets
    space.json           # metadata with space id
  • Path Structure: space-v1/files/sha256/<hash[0..1]>/<hash[2..]>
  • Deduplication: Identical files map to the same path automatically
  • Hash Collision: SHA-256 provides excellent collision resistance for practical use

Files AppTree (Logical Organization)

A dedicated app tree provides a browsable logical view of files:

  // Folder vertex properties
{
  _n: "folder",
  name: string,
  createdAt: number
}

// File vertex properties  
{
  _n: "file",
  name: string,
  hash: string,           // SHA-256 hash
  mimeType?: string,
  size?: number,
  width?: number,         // For images
  height?: number,        // For images
  alt?: string,           // Accessibility text
  tags?: string[],
  createdAt: number,
  
  // Conversion metadata (for processed files)
  originalFormat?: string,
  conversionQuality?: number,
  originalDimensions?: string,
  originalFilename?: string
}

File References

Messages store lightweight references to files:

  interface FileReference {
  tree: string;    // Files AppTree ID
  vertex: string;  // File vertex ID within the tree
}

// File structure
{
  id: string;
  kind: 'image' | 'text' | 'video' | 'pdf' | 'file';
  file: FileReference;
  alt?: string;    // Optional accessibility text
}

File Processing Pipeline

Image Processing

  1. HEIC Conversion: iPhone HEIC files automatically converted to JPEG
  2. Size Optimization: Images larger than 2048x2048 pixels are resized
  3. Quality Optimization: JPEG quality set to 85% for good size/quality balance
  4. Metadata Preservation: Original format, dimensions, and filename tracked

Text File Processing

  1. Content-Based Detection: Files validated as text using content analysis
  2. Binary Signature Detection: Common binary formats (JPEG, PNG, ZIP) rejected
  3. Language Detection: Programming language identified from file extension
  4. Metadata Extraction: Line count, character count, word count calculated

Supported File Types

Images: JPEG, PNG, GIF, WebP, SVG, AVIF, HEIC (converted to JPEG)

Text Files:

  • Plain text: .txt, .log, .csv
  • Markup: .md, .html, .css
  • Code: .js, .ts, .py, .java, .c, .cpp, .cs, .php, .rb, .go, .rs, .swift, .kt, .scala
  • Data: .json, .xml, .yaml, .toml, .ini
  • Scripts: .sh, .bash, .bat, .ps1

Other: PDF, video files (MP4, WebM, OGG), audio files

File Storage and Retrieval

FileStore API

  interface FileStore {
  putDataUrl(dataUrl: string): Promise<{ hash: string; mimeType?: string; size: number }>;
  putBytes(bytes: Uint8Array, mimeType?: string): Promise<{ hash: string; size: number }>;
  exists(hash: string): Promise<boolean>;
  getBytes(hash: string): Promise<Uint8Array>;
  getDataUrl(hash: string): Promise<string>;
  delete(hash: string): Promise<void>; // No-op in current implementation
}

FilesTreeData API

  // Create new Files AppTree
FilesTreeData.createNewFilesTree(space)

// Get or create default Files AppTree
FilesTreeData.getOrCreateDefaultFilesTree(space)

// Ensure folder path exists
FilesTreeData.ensureFolderPath(filesTree, ['YYYY', 'MM', 'DD'])

// Create a file vertex under a folder
FilesTreeData.saveFileInfo(folder, {
  name,
  hash,
  mimeType,
  size,
  width,
  height,
})

// Or from an AttachmentPreview
FilesTreeData.saveFileInfoFromAttachment(folder, attachment, hash)

File Serving

Custom Protocol

Files are served via the sila:// protocol:

  sila://spaces/{spaceId}/files/{hash}?type={mimeType}&name={fileName}

Components:

  • spaceId: Workspace identifier
  • hash: SHA-256 hash of file content
  • mimeType: Content type for proper headers
  • name: Original filename for downloads

Electron Implementation

The protocol handler in Electron:

  1. Validates the URL format and hash
  2. Resolves the file path from CAS structure
  3. Serves the file with proper content-type headers
  4. Supports range requests for large files
  5. Handles download requests with Content-Disposition

File Resolution

Client-Side Resolution

  // Resolve file reference to metadata and URL
const fileInfo = await ClientFileResolver.resolveFileReference(fileRef);

// Result includes:
{
  id: string,
  name: string,
  mimeType?: string,
  size?: number,
  width?: number,
  height?: number,
  url: string,        // sila:// URL
  hash: string
}

Server-Side Resolution

For AI processing, files are resolved to data URLs:

  // Resolve files for AI consumption
const resolvedFiles = await fileResolver.resolveFiles(files);

// Result includes data URLs for AI models
{
  id: string,
  kind: string,
  name?: string,
  alt?: string,
  dataUrl: string,    // Base64 encoded data
  mimeType?: string,
  size?: number,
  width?: number,
  height?: number
}

AI Integration

Vision-Capable Models

For models that support vision (OpenAI, Anthropic, Google, etc.):

  1. Images: Sent as base64-encoded image parts
  2. Text Files: Content extracted and sent as text parts
  3. Mixed Content: Both images and text files in single message

Text-Only Models

For models without vision capabilities:

  1. Images: Descriptive text added (e.g., "[User attached 2 image(s): photo1.jpg, photo2.png]")
  2. Text Files: Content extracted and appended to message text with file headers
  3. File Metadata: Language, line count, and other metadata included

Text File Content Loading

Text file content is loaded from CAS when needed:

  // Load text content from CAS
const fileContent = await loadTextFileContent(treeId, vertexId);

// Extract text from data URL (fallback)
const textContent = extractTextFromDataUrl(dataUrl);

File Preview System

Components

  • FilePreview.svelte: Main component that resolves file references
  • ImageFilePreview.svelte: Renders image previews with hover effects
  • RegularFilePreview.svelte: Renders file tiles with icons and metadata
  • FileGalleryModal.svelte: Full-screen file viewer with navigation

Preview Types

  interface FilePreviewConfig {
  canPreview: boolean;
  previewType: 'image' | 'video' | 'pdf' | 'text' | 'file';
  gallerySupport: boolean;
  supportedFormats: string[];
  displayName: string;
  icon: string;
}

Gallery System

  • Single File View: Current implementation focuses on single file viewing
  • Navigation: Future support for multiple files with next/previous
  • Download: Files can be downloaded from gallery view
  • Keyboard Support: ESC to close, arrow keys for navigation (future)

Data Flow

File Upload

  1. File Selection: User selects files in message form
  2. Processing: Files go through conversion pipeline (HEIC, optimization)
  3. CAS Storage: Processed files stored in CAS via FileStore
  4. Metadata Creation: File vertices created in Files AppTree
  5. Reference Creation: Message files reference file vertices
  6. Transient Data: Data URLs stored temporarily for immediate preview

File Display

  1. Reference Resolution: FilePreview resolves tree/vertex to metadata
  2. URL Generation: sila:// URL generated for file access
  3. Preview Rendering: Appropriate preview component renders file
  4. Gallery Integration: Click opens file in gallery modal

AI Processing

  1. File Resolution: FileResolver loads file content from CAS
  2. Content Extraction: Text files decoded, images converted to base64
  3. Message Construction: Content added to AI message in appropriate format
  4. Model Dispatch: Message sent to AI model with file content

Platform Support

Desktop (Electron)

  • Full CAS Support: Complete file storage and retrieval
  • Custom Protocol: sila:// protocol for file serving
  • File System Access: Direct access to workspace directories
  • Native Dialogs: File picker and save dialogs

Web (Future)

  • IndexedDB Storage: Blob storage for web environments
  • Data URL Fallback: Files served as data URLs
  • Limited Features: Some features may be restricted

Mobile (Capacitor)

  • File System Access: Native file system integration
  • Camera Integration: Direct photo capture
  • Share Support: Native sharing capabilities

Performance Considerations

Memory Management

  • Lazy Loading: File metadata loaded only when needed
  • Caching: Resolved file info cached in client state
  • Streaming: Large files served via streaming (range requests)

Network Optimization

  • Reference-Based: Only file references sent in messages
  • Deduplication: Identical files stored once
  • Compression: Images optimized for size/quality balance

Storage Efficiency

  • Content Addressing: Automatic deduplication by hash
  • Metadata Separation: File metadata separate from content
  • Garbage Collection: Future support for unreferenced file cleanup

Security

File Validation

  • Content-Based Detection: Files validated by content, not just extension
  • Binary Signature Checking: Common binary formats detected and rejected
  • Size Limits: Large files may be truncated or rejected

Access Control

  • Space Isolation: Files isolated by workspace
  • Hash Validation: File integrity verified by SHA-256
  • Protocol Security: Custom protocol validates all requests

Future Enhancements

Planned Features

  • File Search: Search within file content and metadata
  • File Sharing: Share files between workspaces
  • Version Control: File versioning and history
  • Advanced Gallery: Multi-file navigation and zoom controls
  • Thumbnail Generation: Automatic thumbnail creation for images

Performance Improvements

  • Background Processing: File processing in background threads
  • Progressive Loading: Low-res previews before full resolution
  • Smart Caching: Intelligent cache invalidation and prefetching

Testing

Test Coverage

  • Unit Tests: File processing functions, content detection
  • Integration Tests: Complete workflow from upload to AI processing
  • Performance Tests: Memory usage, loading times, file size limits
  • Edge Cases: Binary files with text extensions, empty files, large files

Test Assets

Test files stored in packages/tests/assets/:

  • Images: Various formats for testing image processing
  • Text Files: Different languages and formats
  • Binary Files: For testing rejection logic

Conclusion

Sila's file system provides a robust, scalable foundation for file handling across the application. The combination of CAS storage, logical organization, and reference-based access ensures efficient file management while maintaining excellent user experience and AI integration capabilities.