Search Architecture Specification

[ProjectLiminality]

Overview

Technical specification for implementing Semantic Search System with real-time AI-powered local search capabilities. This system enables semantic discovery of DreamNodes through natural language queries with sovereign local AI processing.

✅ SPECIFICATION COMPLETE

Status: All planned features implemented and tested successfully.

Final Implementation Summary

Technology Stack ✅

• Embedding Model: Ollama nomic-embed-text (768-dimensional embeddings)

  • Local deployment with complete data sovereignty
  • Performance: ~1-2 seconds for DreamNode embedding generation
  • Memory footprint: Efficient with background processing
  • Multilingual support with robust semantic understanding

• Vector Database: Zustand store with Map serialization for cross-session persistence

  • File-based persistence with git-friendly architecture
  • In-memory operations with efficient similarity calculations
  • Cross-platform compatibility with zero external dependencies
  • Local-first design with complete privacy preservation

• Search Interface: Unified search-as-DreamNode paradigm ✅

  • Search query becomes temporary DreamNode in honeycomb layout center
  • Results arranged by semantic similarity in mathematical honeycomb grid
  • Seamless integration with existing spatial orchestration engine

Performance Achievements ✅

• Search interface latency: <100ms for similarity calculations
• Real-time query updates: 1-second rhythm with debounced input
• Background indexing: Non-blocking with 20% interval progress indicators
• Hardware validation: Optimized for local development with M1 Mac baseline
• Indexing performance: Intelligent delta updates for changed nodes only

Epic 5 Implementation Complete ✅

✅ Feature #322: Intelligent Indexing System

Status: COMPLETE - Background indexing with git integration

• ✅ Complete IIndexingService interface with IndexingService implementation
• ✅ Vector data persistence across sessions via Zustand store with Map serialization
• ✅ Command palette integration with three indexing commands and async operation patterns
• ✅ Git-based change detection: automatic indexing on creation + commit-hash delta detection
• ✅ Intelligent delta updates: only index changed/new nodes, cleanup deleted nodes
• ✅ Background processing with non-blocking operations and progress indicators
• ✅ Service layer integration with mock/real mode compatibility
• ✅ Comprehensive testing: 22 IndexingService tests

✅ Feature #290: Semantic Search Implementation

Status: COMPLETE - Ollama embedding API integration

• ✅ Ollama Local Embedding API integration: sovereign AI solution using local models
• ✅ Modular feature architecture: complete vertical slice at src/features/semantic-search/
• ✅ Zustand store slice pattern: OllamaConfigSlice with clean state management
• ✅ Service layer integration: factory pattern with app context for semantic operations
• ✅ Command organization: 8 semantic search commands across 3 organized command files
• ✅ Auto-indexing pipeline: nodes automatically indexed on creation and git commit changes

✅ Feature #280: Honeycomb Search Layout

Status: COMPLETE - Mathematical precision positioning

• ✅ Mathematical precision for 1-36 node positioning with perfect hexagonal grid
• ✅ Adaptive ring distribution: dynamic optimization based on node count
• ✅ Scale progression system: center → ring 1 → ring 2 with optimal spacing ratios
• ✅ Integration with semantic search: honeycomb layout activated in search spatial mode
• ✅ Performance optimization: efficient position calculation with mathematical constants

✅ Feature #323: Search-as-DreamNode Interface

Status: COMPLETE - Unified search/creation UX paradigm

• ✅ Unified search/creation UX paradigm with seamless query-to-node transformation
• ✅ SearchNode3D component with real-time visual feedback during query typing
• ✅ Save animation system with scale/opacity transitions for natural UX flow
• ✅ Command palette integration: "Activate Search Interface" with proper state management
• ✅ Context-aware search activation: spatial layout switching with clean state transitions
• ✅ Intelligent query change detection: only trigger re-search when query content changes

Architecture Achievements ✅

Technical Innovations ✅

• Experimental Branch Archiving: Systematic preservation of alternative approaches with documentation
• Vertical Slice Architecture: Complete self-contained features ready for npm package extraction
• Local AI Sovereignty: No cloud dependencies, all processing local via Ollama
• Robust Error Handling: Graceful degradation when semantic search unavailable
• Cross-Session Persistence: Vector data survives plugin reloads via persistent store middleware

Code Quality Excellence ✅

• Zero Warnings: Complete codebase with 0 lint warnings and 0 TypeScript compilation errors
• Comprehensive Testing: 179 unit tests passing with comprehensive coverage for new services
• Type Safety: Systematic replacement of 'any' types with proper TypeScript typing
• Git Integration: Automatic re-indexing on GitDreamNodeService.create() and commit detection

Files Delivered ✅

• src/features/semantic-search/ (2,500+ lines) - Complete vertical slice implementation
• src/services/indexing-service.ts (446 lines) - Indexing infrastructure
• tests/services/indexing-service.test.ts (483 lines) - Comprehensive test coverage
• Enhanced 15+ existing files with semantic search integrations

Definition of Done ✅

• Complete semantic search pipeline: From indexing to search to visualization
• Local AI sovereignty: Ollama integration without cloud dependencies
• Search-as-DreamNode functionality: Revolutionary UX paradigm implemented
• Honeycomb layout integration: Seamless spatial orchestration extension
• Intelligent indexing: Background updates with git integration
• Command palette integration: Full keyboard shortcut activation
• Performance optimization: Efficient local processing with progress feedback
• Architecture foundation: Modular design ready for future AI model integration
• Documentation complete: Technical patterns and implementation docs updated
• Integration tested: All Epic 4 spatial features work seamlessly with semantic search
• Quality assurance: 179 tests passing with zero warnings/errors

Future Evolution Path

The architecture is designed for seamless expansion:

• Model Upgrades: Easy integration of future Ollama models or alternatives
• Multimodal Support: Foundation ready for image/video embedding integration
• Advanced Search: Vector similarity algorithms ready for enhanced query capabilities
• DreamOS Integration: Complete semantic search system ready for operating system evolution

🎉 EPIC 5 SPECIFICATION FULLY IMPLEMENTED AND VALIDATED