- Increased container max-width from 1200px to 1400px for wider user list
- Reduced modal max-height from 90vh to 70vh for better fit and scrollability

- Added .actions-cell CSS class with display: flex and gap
- Applied class to the actions table cell to arrange edit, deactivate/activate, and delete buttons horizontally

- Removed old admin.html and admin_users.html files
- Updated api_tokens.html to extend base.html

- Created templates/admin/ directory
- Moved admin_users.html to admin/users.html
- Updated render_template path in web.py

- Removed conflicting display: flex from .modal CSS rule
- Added .modal.show class for proper centering when opened
- Updated JavaScript to use classList.add/remove instead of direct style.display

- Changed admin routes from /admin/user/* to /admin/users/*
- Updated admin.html to extend base.html
- Changed action buttons to small icon-based buttons (edit, activate/deactivate, delete)
- Made edit user modal scrollable with overflow-y: auto

- Added base.html with header, nav, user menu, and scripts
- Updated dashboard.html, analyze.html, train.html, history.html to extend base.html
- Added active_page parameter to render_template calls in web.py for dynamic nav highlighting

- Updated route in web.py to /admin/users
- Updated all dropdown links in templates to point to /admin/users
- Removed remaining Admin link from account.html navbar

- Removed 'Account' and 'Admin' links from top navigation bar
- Added 'Account' as first item in user dropdown for all users
- Renamed 'Menu Management' to 'Users' in admin dropdown
- Dropdown now shows Account first, then role-specific options

- Changed modal to use flexbox for proper centering
- Added max-height and overflow-y: auto to modal-body for scrollable content
- Prevented background page scrolling when modal is open
- Modal now stays within viewport and scrolls internally

- Added user icon in top right navigation bar on all pages
- Dropdown shows Account/Tokens for non-admin users
- Dropdown shows Menu Management/Configurations for admin users
- Includes Logout option for all
- Used FontAwesome icons and consistent styling

- Create dedicated Account page (/account) for users and admins
- Add password change functionality with current password verification
- Implement token top-up system with predefined packages and custom amounts
- Add payment method selection (Credit Card, PayPal, Crypto) with UI
- Create account balance display with prominent token counter
- Add navigation links to Account page across all templates
- Implement backend routes for password changes and token purchases
- Add update_user_password function to database operations
- Include demo token purchase functionality (no real payments)
- Maintain consistent navigation experience across the application
- Ensure proper access control for account management features

- Add API Tokens navigation link to all user templates (dashboard, analyze, train, history, settings)
- Add Admin navigation link for admin users across all templates
- Remove old API token generation button from settings page (now uses dedicated page)
- Ensure consistent navigation experience across the application
- Admin users can now easily access user management and token generation pages

- Create dedicated API token generation page with custom naming
- Implement JWT token generation with expiration and user claims
- Add token administration with list view, last-used tracking, and deletion
- Update database schema to support token names and usage tracking
- Add navigation links for API tokens page with proper access control
- Implement secure token validation with automatic last-used timestamp updates
- Add copy-to-clipboard functionality for generated tokens
- Create user-friendly token management interface with confirmation dialogs

- Restrict settings page to admin users only with @admin_required decorator
- Add database configuration section to admin settings (SQLite/MySQL settings)
- Create admin-only worker token generation for --client authentication
- Create user-accessible API token generation for programmatic access
- Implement user API token validation that consumes user tokens for analysis
- Add database tables for worker_tokens and user_api_tokens
- Add API endpoint /api/analyze that validates user tokens and deducts tokens
- Admin users are exempt from token consumption for all operations
- Enhanced settings page with database management and token generation options

- Restrict /train route to admin users only (@admin_required)
- Add --server-dir command line argument for server directory configuration
- Show server local path input only for admin users when --server-dir is set
- Add /api/browse endpoint for secure file browsing (admin only)
- Implement file navigator popup with directory navigation and file selection
- Add security checks to prevent directory traversal attacks
- Update analyze template with conditional server path input and file browser modal

- Fix settings page user dict access error
- Add consistent top navigation to dashboard
- Fix train page user variable scope error
- Update analyze page to use consistent header navigation
- Add admin panel with user management (create, activate/deactivate users)
- Add 'remember me' checkbox to login page
- Change default user tokens from 1000 to 0
- Add admin routes and database functions for user management
- Update all templates to use VidAI branding

- Change project name from 'Video AI Analysis Tool' to 'VidAI'
- Update tagline to 'The adult content friendly video automation system'
- Change all 'Video AI Pro' references to 'VidAI' in templates
- Add favicon using image.jpg in landing page
- Add route to serve image.jpg file
- Update PyInstaller build script to include image.jpg as icon
- Update landing page title and meta description

- Configure Flask to look for templates in correct directory
- Change 'Start Free Trial' to 'Start for Free Now!' on landing page
- Fix TemplateNotFound error for register.html and other templates

- Add token_packages table to database schema
- Add default token packages (Starter, Professional, Enterprise)
- Add database functions for managing token packages
- Update payments.py to use database packages instead of hardcoded ones
- Remove pricing section from landing page (packages only show when configured)
- Token packages are now fully configurable through admin interface

- Remove hardcoded token packages from landing page
- Replace with generic token-based pricing tiers
- Remove reference to database configuration in template
- Landing page now shows pricing tiers without specific packages

- Fix repository URL from GitHub to GitLab (git.nexlab.net/SexHackMe/vidai)
- Update landing page to show token packages instead of subscription plans
- Change pricing section to reflect database-configured token packages
- Update footer links to point to correct repository

- Add render_template to Flask imports to fix NameError

- Create login.html, register.html, and config.html templates
- Update /login, /register, /config, /history, and /settings routes to use render_template()
- Remove inline HTML strings from web.py for better maintainability

- Resolved f-string and Jinja2 template conflicts by using proper string concatenation
- Separated dynamic content from template literals to avoid syntax errors
- Ensured all HTML templates render correctly with render_template_string
- Maintained all authentication and UI functionality while fixing import issues

The web interface now imports and runs without syntax errors.

- Implemented comprehensive user authentication system (login/logout/register)
- Added beautiful landing page for non-authenticated users
- Created user dashboard with statistics and quick actions
- Built modern, responsive UI with Inter font and professional styling
- Added session management and user context throughout
- Implemented token-based usage limits and tracking
- Created job history page with detailed status tracking
- Added user settings page with preferences and API token management
- Integrated flash messaging for user feedback
- Added navigation headers with consistent branding
- Implemented role-based access control decorators
- Added comprehensive error handling and user feedback

The web interface now provides a complete, professional user experience with authentication, modern design, and full functionality for the multi-process Video AI system.

- Corrected function to set 'default_model_type' instead of 'default_model'
- Fixed NameError where 'model' variable was undefined
- Now properly saves model type configuration

- Deleted webui.py as it was replaced by vidai/web.py in the multi-process architecture
- Functionality moved to separate web interface process
- Cleaned up legacy monolithic code that is no longer used

- Add vidai/models.py with abstract base classes for different model types
- Support multiple HuggingFace transformers models (vision-language, text-only)
- Auto-detect model types from model names/paths
- Add model type configuration options (--model-type)
- Update worker_analysis.py to use dynamic model loading instead of hardcoded Qwen
- Maintain backward compatibility with existing model configurations

- Updated all requirements files to use nvidia-ml-py instead of deprecated pynvml
- Added fallback import in webui.py to support both packages
- Maintains backward compatibility while using the actively maintained package
- Updated installation instructions in error messages

- Removed start.sh since process startup is handled by vidai.py
- vidai.py now includes proper backend readiness checking
- Simplified deployment by using single Python launcher

- Update start.sh to wait for Unix socket creation before starting workers
- Remove retry logic from workers since startup script ensures backend is ready
- Workers now connect immediately knowing backend socket exists
- Prevents race conditions between backend startup and worker connections

- Separate communication protocols: TCP for web-backend, Unix sockets for backend-workers
- Remove file-based result passing, implement in-memory result storage in backend
- Web interface polls backend via socket for results instead of reading files
- Workers send results back through Unix socket connection to backend
- Maintain persistent connections for efficient bidirectional communication

- Update workers to use proper socket path from config instead of hardcoded paths
- Ensure workers check communication type and use appropriate connection method
- Fix SocketCommunicator to properly handle Unix socket paths
- Revert database default back to 'unix' for proper Unix socket support

- Fix SocketCommunicator initialization to properly handle TCP vs Unix sockets
- Update backend to use configurable communication type from config
- Change default communication type from 'unix' to 'tcp' for better reliability
- Ensure consistent socket handling across all processes

- Refactor monolithic Flask app into separate processes:
  * Web interface process (vidai/web.py)
  * Backend routing process (vidai/backend.py)
  * Analysis worker processes (vidai/worker_analysis.py)
  * Training worker processes (vidai/worker_training.py)

- Add self-contained inter-process communication using TCP sockets
- Implement configuration system for backend selection (CUDA/ROCm)
- Add GPLv3 licensing and copyright notices
- Create comprehensive documentation and build scripts
- Update main launcher to manage all processes

This architecture provides better scalability, allows independent GPU backend selection, and maintains clean separation of concerns.

- Add socket-based inter-process communication
- Implement backend process for request routing
- Create separate web interface process
- Add CUDA/ROCm worker processes for analysis and training
- Add configuration system for backend selection
- Update build scripts for multi-component executables
- Add startup scripts for process orchestration
- Include GPLv3 license and copyright notices
- Add comprehensive documentation and README
- Create CHANGELOG for version tracking

- Move db_type handling to environment variables to avoid circular dependency
- get_db_config() now uses environment variables for database type
- get_config() handles db_type specially to prevent recursion
- Fixes ImportError when running vidai.py

- Create executable launcher script for non-PyInstaller builds
- Automatically detects and uses appropriate virtual environments
- Launches backend, web interface, and workers with correct CUDA/ROCm environments
- Reads configuration to determine backend selection
- Provides process management and cleanup on exit