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Implement a complete audit logging system to track all changes made to tracked entities, providing full compliance and accountability capabilities. Features: - Automatic tracking of create, update, and delete operations on 25+ models - Detailed field-level change tracking with old/new value comparison - User attribution with IP address, user agent, and request path logging - Web UI for viewing and filtering audit logs with pagination - REST API endpoints for programmatic access - Entity-specific history views - Comprehensive test coverage (unit, model, route, and smoke tests) Core Components: - AuditLog model with JSON-encoded value storage and decoding helpers - SQLAlchemy event listeners for automatic change detection - Audit utility module with defensive programming for table existence checks - Blueprint routes for audit log viewing and API access - Jinja2 templates for audit log list, detail, and entity history views - Database migration (044) creating audit_logs table with proper indexes Technical Implementation: - Uses SQLAlchemy 'after_flush' event listener to capture changes - Tracks 25+ models including Projects, Tasks, TimeEntries, Invoices, Clients, Users, etc. - Excludes sensitive fields (passwords) and system fields (id, timestamps) - Implements lazy import pattern to avoid circular dependencies - Graceful error handling to prevent audit logging from breaking core functionality - Transaction-safe logging that integrates with main application transactions Fixes: - Resolved login errors caused by premature transaction commits - Fixed circular import issues with lazy model loading - Added table existence checks to prevent errors before migrations - Improved error handling with debug-level logging for non-critical failures UI/UX: - Added "Audit Logs" link to admin dropdown menu - Organized admin menu into logical sections for better usability - Filterable audit log views by entity type, user, action, and date range - Color-coded action badges and side-by-side old/new value display - Pagination support for large audit log datasets Documentation: - Added comprehensive feature documentation - Included troubleshooting guide and data examples - Created diagnostic scripts for verifying audit log setup Testing: - Unit tests for AuditLog model and value encoding/decoding - Route tests for all audit log endpoints - Integration tests for audit logging functionality - Smoke tests for end-to-end audit trail verification This implementation provides a robust foundation for compliance tracking and change accountability without impacting application performance or requiring code changes in existing routes/models.