Interactive Flashcards TUI - Implementation Roadmap

✅ Phase 1: Core System + AI Integration (COMPLETE)

Completed Features

• CSV file processing and parsing
• Full quiz system with navigation and state management
• TUI interface with menu, quiz, and summary screens
• Advanced AI integration with persistent workers
• Timeout handling and error recovery
• Integrated AI feedback UI
• Session History Menu - Browse, resume, and delete past quiz sessions
• Session Assessment - AI-powered post-quiz analysis with grade, mastery level, strengths, weaknesses, and suggestions
• Session Resume Fixes - Restore last viewed question, preserve skipped questions, and persist out-of-order answers
• Comprehensive test suite (127 tests)
• Production-ready with robust error handling

Technical Achievements

• Zero external dependencies for core functionality
• Modular architecture with 19 focused files
• Persistent AI worker threads with automatic recovery
• Integrated UI design (AI feedback in quiz flow)
• 30-second evaluation timeouts with user feedback
• JSON cleaning for robust AI response handling
• Session persistence and resume functionality
• SQLite-based session history with date formatting
• Post-quiz AI session assessment with historical comparison
• Chat popup markdown spacing normalization

🚧 Phase 2: Document Support (NEXT)

Planned Features

• PDF/TXT/MD file parsing for custom flashcards
• Document upload and processing interface
• Automatic format detection
• Rich text rendering in quiz interface
• Document metadata extraction

Technical Implementation

• File format detection library
• PDF parsing (pdf-extract or similar)
• Markdown/HTML rendering support
• Document chunking for large files
• Progress indicators for parsing operations

🔮 Phase 3: RAG Integration (FUTURE)

Planned Features

• Vector embeddings for document context
• Context-aware answer evaluation
• Document-based question generation
• Semantic search within documents
• Multi-document quiz sessions

Technical Implementation

• Embedding model integration (OpenAI or local)
• Vector database (Qdrant or in-memory)
• Context retrieval algorithms
• RAG prompt engineering
• Performance optimization for large documents

🎯 Phase 4: Advanced Features (FUTURE)

Planned Features

• Score tracking and progress analytics
• Spaced repetition algorithms
• Custom difficulty ratings
• Session persistence and resume
• Study streak tracking

Technical Implementation

• SQLite or JSON-based persistence
• Algorithm implementations (SM-2, etc.)
• Statistics dashboard UI
• Export/import functionality
• Backup and sync capabilities

🎨 Phase 5: User Experience (FUTURE)

Planned Features

• Settings screen for AI model selection
• Progress visualization and statistics
• Keyboard shortcut customization
• Theme/color scheme options
• Accessibility improvements

Technical Implementation

• Configuration file management
• Theme system with CSS-like styling
• Keyboard mapping system
• Accessibility compliance (screen reader support)
• Performance monitoring and analytics

Architecture Principles

Current Architecture (19 Files)

• Modular Design: Clear separation of concerns
• Test-Driven: 127 comprehensive tests
• Error Resilient: Graceful failure handling
• Extensible: Easy to add new features
• Performance Optimized: Sub-second responsiveness

Future-Proof Design

• Public library API enables GUI/web ports
• Plugin architecture for new file formats
• Configurable AI model selection
• Extensible UI component system

Success Metrics

• ✅ Phase 1: 74 tests, zero warnings, production-ready with polished UI
• ✅ Phase 1.5: 82 tests, async optimization, zero CPU usage, immediate AI responses
• ✅ Phase 1.6: 118 tests, SQLite migration, Refinery migrations, crash-safe data persistence
• ✅ Phase 1.7: 121 tests, Session History Menu with browse/resume/delete functionality
• ✅ Phase 1.8: 127 tests, Session Assessment with AI-powered post-quiz analysis, historical comparison
• 🚧 Phase 2: Document parsing, multi-format support
• 🔮 Phase 3: AI context awareness, semantic evaluation
• 🎯 Phase 4: Learning algorithm implementation
• 🎨 Phase 5: Advanced user experience features

Database Schema

See DB.md for full documentation on:

• Table relationships (sessions → flashcards)
• Column definitions and data types
• Data flow and session lifecycle
• AIFeedback JSON schema
• Migration management with Refinery

Getting Started

# Clone and build
git clone <repository>
cd interactive-flashcards
cargo build --release

# Run with AI evaluation
OPENROUTER_API_KEY="your-key" cargo run

# Run tests
cargo test

CSV decks live in ~/.local/share/interactive-flashcards/flashcards/ (Windows: %USERPROFILE%\.local\share\interactive-flashcards\flashcards).

Current Status: Phase 1.8 complete with Session Assessment feature, Phase 2 ready for implementation.