ChessPrism/cline_docs/activeContext.md

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# Active Context
## Current Status
- Screen capture module successfully implemented
- Window detection and capture working correctly
- SwiftUI interface with capture controls functioning
- Error handling system properly managing states
- Resource cleanup implemented
- Metal resource management optimized
- Automatic board detection and capture implemented
- Visual capture status indicator added
- Continuous board monitoring system implemented
## Recent Changes
1. Implemented Continuous Board Monitoring:
- Added separate monitoring and capture tasks:
* Monitor constantly checks for chess boards (0.5s interval)
* Capture processes frames when active (0.1s interval)
- Auto-capture behavior:
* Starts monitoring when app launches
* Automatically starts capture when board appears
* Stops capture (but keeps monitoring) when board disappears
* Resumes capture when new board is detected
- Fixed image conversion pipeline:
* Proper NSImage → CGImage → CIImage conversion
* Efficient resource management
* Clean error handling
2. Enhanced Status Indication:
- Visual status indicator shows capture state:
* Green: Actively capturing board
* Yellow: Waiting for board
* Gray: Not capturing
- Clear error messages for different states
- Automatic status updates based on board detection
3. Resource Management Optimization:
- Implemented shared CIContext pattern:
* Prevents command queue exhaustion
* Reduces Metal resource usage
* Enables long-running captures
- Proper cleanup on task completion
- Efficient resource utilization
4. Improved Window Detection:
- Using SCShareableContent for window access
- Precise window identification:
* Exact bundle ID matching (com.chess.iphone)
* Window visibility verification (isOnScreen)
* Size validation (width > 100 && height > 100)
5. Enhanced Capture System:
- Continuous capture implementation:
* Single persistent capture stream
* Smooth frame processing (no flickering)
* Efficient resource usage
- Proper frame dimensions from window
- Clean task cancellation handling
- Main thread safety for UI updates
6. Error Handling:
- Improved error resilience:
* Continues monitoring even if capture stops
* Only stops on critical errors
* Shows error state without interrupting monitoring
- Clear error states
- Proper async/await usage
- Task cancellation management
- Thread-safe state updates
## Current Focus
1. Board Detection:
- Implement chess board recognition
- Handle different board themes
- Process captured frames efficiently
## Next Steps
1. Implement board detection:
- Pattern recognition for chess pieces
- Board coordinate mapping
- Position validation
2. Add position analysis
3. Create move detection system
4. Implement visual overlay
5. Integrate Stockfish engine
## Known Issues
- Need to handle different chess.com themes
- Need to implement piece recognition
- Position analysis pending implementation