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eve-alpha/docs/planning/PROJECT_PLAN.md
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EVE - Personal Desktop Assistant

Comprehensive Project Plan

1. Project Overview

Vision

A sophisticated desktop assistant with AI capabilities, multimodal interaction (voice & visual), and gaming integration. The assistant features a customizable avatar and supports both local and cloud-based AI models.

Core Value Propositions

  • Multimodal Interaction: Voice-to-text and text-to-voice communication
  • Visual Presence: Interactive avatar (Live2D or Adaptive PNG)
  • Flexibility: Support for both local and remote LLM models
  • Context Awareness: Screen and audio monitoring capabilities
  • Gaming Integration: Specialized features for gaming assistance

2. Technical Architecture

2.1 System Components

Frontend Layer

  • UI Framework: Electron or Tauri for desktop application
  • Avatar System: Live2D Cubism SDK or custom PNG sprite system
  • Screen Overlay: Transparent window with always-on-top capability
  • Settings Panel: Configuration interface for models, voice, and avatar

Backend Layer

  • LLM Integration Module

    • OpenAI API support (GPT-4, GPT-3.5)
    • Anthropic Claude support
    • Local model support (Ollama, LM Studio, llama.cpp)
    • Model switching and fallback logic

  • Speech Processing Module

    • Speech-to-Text: OpenAI Whisper (local) or cloud services
    • Text-to-Speech: ElevenLabs API integration
    • Audio input/output management
    • Voice activity detection

  • Screen & Audio Capture Module

    • Screen capture API (platform-specific)
    • Audio stream capture
    • OCR integration for screen text extraction
    • Vision model integration for screen understanding

  • Gaming Support Module

    • Game state detection
    • In-game overlay support
    • Performance monitoring
    • Game-specific AI assistance

Data Layer

  • Configuration Storage: User preferences, API keys
  • Conversation History: Local SQLite or JSON storage
  • Cache System: For avatar assets, model responses
  • Session Management: Context persistence

3. Feature Breakdown & Implementation Plan

Phase 1: Foundation (Weeks 1-3)

3.1 Basic Application Structure

  • Set up project repository and development environment
  • Choose and initialize desktop framework (Electron/Tauri)
  • Create basic window management system
  • Implement settings/configuration system
  • Design and implement UI/UX wireframes

3.2 LLM Integration - Basic

  • Implement API client for OpenAI
  • Add support for basic chat completion
  • Create conversation context management
  • Implement streaming response handling
  • Add error handling and retry logic

3.3 Text Interface

  • Build chat interface UI
  • Implement message history display
  • Add typing indicators
  • Create system for user input handling

Phase 2: Voice Integration (Weeks 4-6)

3.4 Speech-to-Text (STT)

  • Integrate OpenAI Whisper API or local Whisper
  • Implement microphone input capture
  • Add voice activity detection (VAD)
  • Create push-to-talk and continuous listening modes
  • Handle audio preprocessing (noise reduction)
  • Add language detection support

3.5 Text-to-Speech (TTS)

  • Integrate ElevenLabs API
  • Implement voice selection system
  • Add audio playback queue management
  • Create voice customization options
  • Implement speech rate and pitch controls
  • Add local TTS fallback option

3.6 Voice UI/UX

  • Visual feedback for listening state
  • Waveform visualization
  • Voice command shortcuts
  • Interrupt handling (stop speaking)

Phase 3: Avatar System (Weeks 7-9)

3.7 Live2D Implementation (Option A)

  • Integrate Live2D Cubism SDK
  • Create avatar model loader
  • Implement parameter animation system
  • Add lip-sync based on TTS phonemes
  • Create emotion/expression system
  • Implement idle animations
  • Add custom model support

3.8 Adaptive PNG Implementation (Option B)

  • Design sprite sheet system
  • Create state machine for avatar states
  • Implement frame-based animations
  • Add expression switching logic
  • Create smooth transitions between states
  • Support for custom sprite sheets

3.9 Avatar Interactions

  • Click/drag avatar positioning
  • Context menu for quick actions
  • Avatar reactions to events
  • Customizable size scaling
  • Transparency controls

Phase 4: Advanced LLM Features (Weeks 10-11)

3.10 Local Model Support

  • Integrate Ollama client
  • Add LM Studio support
  • Implement llama.cpp integration
  • Create model download/management system
  • Add model performance benchmarking
  • Implement model switching UI

3.11 Advanced AI Features

  • Function/tool calling support
  • Memory/context management system
  • Personality customization
  • Custom system prompts
  • Multi-turn conversation optimization
  • RAG (Retrieval Augmented Generation) support

Phase 5: Screen & Audio Awareness (Weeks 12-14)

3.12 Screen Capture

  • Implement platform-specific screen capture (Windows/Linux/Mac)
  • Add screenshot capability
  • Create region selection tool
  • Implement OCR for text extraction (Tesseract)
  • Add vision model integration (GPT-4V, LLaVA)
  • Periodic screen monitoring option

3.13 Audio Monitoring

  • Implement system audio capture
  • Add application-specific audio isolation
  • Create audio transcription pipeline
  • Implement audio event detection
  • Add privacy controls and toggles

3.14 Context Integration

  • Feed screen context to LLM
  • Audio context integration
  • Clipboard monitoring (optional)
  • Active window detection
  • Smart context summarization

Phase 6: Gaming Support (Weeks 15-16)

3.15 Game Detection

  • Process detection for popular games
  • Game profile system
  • Performance impact monitoring
  • Gaming mode toggle

3.16 In-Game Features

  • Overlay rendering in games
  • Hotkey system for in-game activation
  • Game-specific AI prompts/personalities
  • Strategy suggestions based on game state
  • Voice command integration for games

3.17 Gaming Assistant Features

  • Build/loadout suggestions (MOBAs, RPGs)
  • Real-time tips and strategies
  • Wiki/guide lookup integration
  • Teammate communication assistance
  • Performance tracking and analysis

Phase 7: Polish & Optimization (Weeks 17-18)

3.18 Performance Optimization

  • Resource usage profiling
  • Memory leak detection and fixes
  • Startup time optimization
  • Model loading optimization
  • Audio latency reduction

3.19 User Experience

  • Keyboard shortcuts system
  • Quick settings panel
  • Notification system
  • Tutorial/onboarding flow
  • Accessibility features

3.20 Quality Assurance

  • Cross-platform testing (Windows, Linux, Mac)
  • Error handling improvements
  • Logging and debugging tools
  • User feedback collection system
  • Beta testing program

4. Technology Stack Recommendations

Frontend

  • Framework: Tauri (Rust + Web) or Electron (Node.js + Web)
  • UI Library: React + TypeScript
  • Styling: TailwindCSS + shadcn/ui
  • State Management: Zustand or Redux Toolkit
  • Avatar: Live2D Cubism Web SDK or custom canvas/WebGL

Backend/Integration

  • Language: TypeScript/Node.js or Rust
  • LLM APIs:
    • OpenAI SDK
    • Anthropic SDK
    • Ollama client
  • Speech:
    • ElevenLabs SDK
    • OpenAI Whisper
  • Screen Capture:
    • screenshots (Rust)
    • node-screenshot or native APIs
  • OCR: Tesseract.js or native Tesseract
  • Audio: Web Audio API, portaudio, or similar

Data & Storage

  • Database: SQLite (better-sqlite3 or rusqlite)
  • Config: JSON or TOML files
  • Cache: File system or in-memory

Development Tools

  • Build: Vite or Webpack
  • Testing: Vitest/Jest + Playwright
  • Linting: ESLint + Prettier
  • Version Control: Git + GitHub

5. Security & Privacy Considerations

API Key Management

  • Secure storage of API keys (OS keychain integration)
  • Environment variable support
  • Key validation on startup

Data Privacy

  • Local-first data storage
  • Optional cloud sync with encryption
  • Clear data deletion options
  • Screen/audio capture consent mechanisms
  • Privacy mode for sensitive information

Network Security

  • HTTPS for all API calls
  • Certificate pinning considerations
  • Rate limiting to prevent abuse
  • Proxy support

6. User Configuration Options

General Settings

  • Theme (light/dark/custom)
  • Language preferences
  • Startup behavior
  • Hotkeys and shortcuts

AI Model Settings

  • Model selection (GPT-4, Claude, local models)
  • Temperature and creativity controls
  • System prompt customization
  • Context length limits
  • Response streaming preferences

Voice Settings

  • STT engine selection
  • TTS voice selection (ElevenLabs voices)
  • Voice speed and pitch
  • Audio input/output device selection
  • VAD sensitivity

Avatar Settings

  • Model selection
  • Size and position
  • Transparency
  • Animation speed
  • Expression preferences

Screen & Audio Settings

  • Enable/disable screen monitoring
  • Screenshot frequency
  • Audio capture toggle
  • OCR language settings
  • Privacy filters

Gaming Settings

  • Game profiles
  • Performance mode
  • Overlay opacity
  • In-game hotkeys

7. Potential Challenges & Mitigations

Challenge 1: Audio Latency

  • Issue: Delay in STT → LLM → TTS pipeline
  • Mitigation:
    • Use streaming APIs where available
    • Optimize audio processing pipeline
    • Local models for faster response
    • Predictive loading of common responses

Challenge 2: Resource Usage

  • Issue: High CPU/memory usage from multiple subsystems
  • Mitigation:
    • Lazy loading of features
    • Efficient caching strategies
    • Option to disable resource-intensive features
    • Performance monitoring and alerts

Challenge 3: Screen Capture Performance

  • Issue: Screen capture can be resource-intensive
  • Mitigation:
    • Configurable capture rate
    • Region-based capture instead of full screen
    • On-demand capture vs. continuous monitoring
    • Hardware acceleration where available

Challenge 4: Cross-Platform Compatibility

  • Issue: Different APIs for screen/audio capture per OS
  • Mitigation:
    • Abstract platform-specific code behind interfaces
    • Use cross-platform libraries where possible
    • Platform-specific builds if necessary
    • Thorough testing on all target platforms

Challenge 5: API Costs

  • Issue: Cloud API usage can be expensive (ElevenLabs, GPT-4)
  • Mitigation:
    • Usage monitoring and caps
    • Local model alternatives
    • Caching of common responses
    • User cost awareness features

8. Future Enhancements (Post-MVP)

Advanced Features

  • Multi-language support for UI and conversations
  • Plugin/extension system
  • Cloud synchronization of settings and history
  • Mobile companion app
  • Browser extension integration
  • Automation and scripting capabilities

AI Enhancements

  • Fine-tuned models for specific use cases
  • Multi-agent conversations
  • Long-term memory system
  • Learning from user interactions
  • Personality development over time

Integration Expansions

  • Calendar and task management integration
  • Email and messaging app integration
  • Development tool integration (IDE, terminal)
  • Smart home device control
  • Music streaming service integration

Community Features

  • Sharing custom avatars
  • Prompt template marketplace
  • Community-created game profiles
  • User-generated content for personalities

9. Success Metrics

Performance Metrics

  • Response time (STT → LLM → TTS) < 3 seconds
  • Application startup time < 5 seconds
  • Memory usage < 500MB idle, < 1GB active
  • CPU usage < 5% idle, < 20% active

Quality Metrics

  • Speech recognition accuracy > 95%
  • User satisfaction rating > 4.5/5
  • Crash rate < 0.1% of sessions
  • API success rate > 99%

Adoption Metrics

  • Active daily users
  • Average session duration
  • Feature usage statistics
  • User retention rate

10. Development Timeline Summary

Total Estimated Duration: 18 weeks (4.5 months)

  • Phase 1: Foundation (3 weeks)
  • Phase 2: Voice Integration (3 weeks)
  • Phase 3: Avatar System (3 weeks)
  • Phase 4: Advanced LLM (2 weeks)
  • Phase 5: Screen & Audio Awareness (3 weeks)
  • Phase 6: Gaming Support (2 weeks)
  • Phase 7: Polish & Optimization (2 weeks)

Milestones

  • Week 3: Basic text-based assistant functional
  • Week 6: Full voice interaction working
  • Week 9: Avatar integrated and animated
  • Week 11: Local model support complete
  • Week 14: Screen/audio awareness functional
  • Week 16: Gaming features complete
  • Week 18: Production-ready release

11. Getting Started

Immediate Next Steps

  1. Environment Setup

    • Choose desktop framework (Tauri vs Electron)
    • Set up project repository
    • Initialize package management
    • Configure build tools

  2. Proof of Concept

    • Create minimal window application
    • Test OpenAI API integration
    • Verify ElevenLabs API access
    • Test screen capture on target OS

  3. Architecture Documentation

    • Create detailed technical architecture diagram
    • Define API contracts between modules
    • Document data flow
    • Set up development workflow

  4. Development Workflow

    • Set up CI/CD pipeline
    • Configure testing framework
    • Establish code review process
    • Create development, staging, and production branches

12. Resources & Dependencies

Required API Keys/Accounts

  • OpenAI API key (for GPT models and Whisper)
  • ElevenLabs API key (for TTS)
  • Anthropic API key (optional, for Claude)

Optional Services

  • Ollama (for local models)
  • LM Studio (alternative local model runner)
  • Tesseract (for OCR)

Hardware Recommendations

  • Minimum: 8GB RAM, quad-core CPU, 10GB storage
  • Recommended: 16GB RAM, 8-core CPU, SSD, 20GB storage
  • For Local Models: 32GB RAM, GPU with 8GB+ VRAM

Notes

  • This plan is flexible and should be adjusted based on user feedback and technical discoveries
  • Consider creating MVPs for each phase to validate approach
  • Regular user testing is recommended throughout development
  • Budget sufficient time for debugging and unexpected challenges
  • Consider open-source vs. proprietary licensing early on