6.0 KiB
6.0 KiB
Form Filling System Updates
Summary of Changes
The LiveKit agent has been enhanced with a robust dynamic form filling system that automatically discovers and fills web forms based on user voice commands without relying on hardcoded selectors.
Key Updates Made
1. Enhanced MCP Chrome Client (mcp_chrome_client.py
)
New Methods Added:
_discover_form_fields_dynamically()
- Real-time form field discovery using MCP tools_enhanced_field_detection_with_retry()
- Multi-attempt field detection with retry logic_analyze_page_content_for_field()
- Content analysis fallback method_is_field_match()
- Intelligent field matching algorithm_extract_best_selector()
- Reliable CSS selector extraction_is_flexible_field_match()
- Flexible matching with increasing permissiveness_parse_form_content_for_field()
- Form content parsing for field discovery_generate_intelligent_selectors_from_content()
- Smart selector generation
Enhanced Existing Methods:
fill_field_by_name()
- Now uses dynamic discovery instead of hardcoded selectors- Step 1: Check cached fields
- Step 2: Dynamic MCP discovery using
chrome_get_interactive_elements
- Step 3: Enhanced detection with retry mechanism
- Step 4: Content analysis as final fallback
2. Enhanced LiveKit Agent (livekit_agent.py
)
New Function Tools:
fill_field_with_voice_command()
- Process natural language voice commandsdiscover_and_fill_field()
- Pure dynamic discovery without cache dependency
Updated Instructions:
- Added comprehensive documentation about dynamic form discovery
- Highlighted the new capabilities in agent instructions
- Updated greeting message to explain the new system
3. New Test Suite (test_dynamic_form_filling.py
)
Test Coverage:
- Dynamic field discovery functionality
- Retry mechanism testing
- Voice command processing
- Field matching algorithm validation
- Cross-website compatibility testing
4. Documentation (DYNAMIC_FORM_FILLING.md
)
Comprehensive Documentation:
- System overview and architecture
- Usage examples and API reference
- Configuration and error handling
- Testing instructions and future enhancements
Technical Implementation Details
Dynamic Discovery Process
-
MCP Tool Integration:
- Uses
chrome_get_interactive_elements
to get real-time form elements - Uses
chrome_get_content_web_form
for form-specific content analysis - Never relies on hardcoded selectors
- Uses
-
Retry Mechanism:
- 3-tier retry system with increasing flexibility
- Each attempt uses different matching criteria
- Graceful fallback to content analysis
-
Natural Language Processing:
- Intelligent mapping of voice commands to form fields
- Handles variations like "email", "mail", "e-mail"
- Type-specific matching (email fields, password fields, etc.)
Field Matching Algorithm
# Multi-attribute matching
attributes_checked = [
"name", "id", "placeholder",
"aria-label", "class", "type", "textContent"
]
# Field name variations
variations = [
original_name,
name_without_spaces,
name_without_underscores,
name_with_hyphens
]
# Special type handling
type_specific_matching = {
"email": ["email", "mail"],
"password": ["password", "pass"],
"search": ["search", "query"],
"phone": ["phone", "tel"]
}
Benefits of the New System
1. Robustness
- No hardcoded selectors - eliminates brittle dependencies
- Automatic retry - handles dynamic content and loading delays
- Multiple strategies - fallback methods ensure high success rate
2. Adaptability
- Works across websites - adapts to different form structures
- Real-time discovery - handles dynamically generated forms
- Intelligent matching - understands field relationships and context
3. User Experience
- Natural voice commands - users can speak naturally about form fields
- Reliable operation - consistent behavior across different sites
- Clear feedback - detailed status messages about what's happening
4. Maintainability
- Self-discovering - no need to maintain selector databases
- Extensible design - easy to add new discovery strategies
- Comprehensive logging - detailed debugging information
Voice Command Examples
The system now handles these natural language commands:
"fill email with john@example.com"
"enter password secret123"
"type hello world in search box"
"add user name John Smith"
"fill in the email field with test@example.com"
"search for python programming"
"enter phone number 1234567890"
Error Handling Improvements
- Graceful Degradation: Falls back to simpler methods if advanced ones fail
- Detailed Logging: All discovery attempts are logged for debugging
- User Feedback: Clear messages about what was attempted and why it failed
- Exception Safety: All exceptions are caught and handled gracefully
Testing and Validation
Run the test suite to validate the new functionality:
cd agent-livekit
python test_dynamic_form_filling.py
This tests:
- Dynamic field discovery on Google and GitHub
- Retry mechanism with different field names
- Voice command processing
- Field matching algorithm accuracy
- Cross-website compatibility
Future Enhancements
The new architecture enables future improvements:
- Machine Learning: Train models to recognize field patterns
- Visual Recognition: Use screenshots for element identification
- Context Awareness: Understand form relationships and workflows
- User Learning: Adapt to user preferences and common patterns
Migration Notes
- Backward Compatibility: All existing functionality is preserved
- No Breaking Changes: Existing voice commands continue to work
- Enhanced Performance: New system is faster and more reliable
- Improved Accuracy: Better field matching reduces errors
The updated system maintains full backward compatibility while providing significantly enhanced capabilities for dynamic form filling across any website.