MOOD MNKY Changelog
This document tracks all significant changes, improvements, and fixes to the MOOD MNKY agent. The changelog is organized by version, with the most recent versions listed first.
Version 1.4.0 (2023-12-15)
New Features
- Enhanced Emotion Detection: Added capability to detect subtle emotional cues in text input
- Fragrance Memory Integration: Created system for recalling past fragrance preferences and experiences
- Personalization Enhancements: Improved algorithmic matching for product recommendations
- Visual Input Processing: Added support for image-based mood analysis and scent recommendations
Improvements
- Increased response accuracy for fragrance-related queries by 37%
- Expanded knowledge base with 200+ new fragrance profiles
- Optimized conversation flow for multi-turn interactions
- Reduced latency for personalization calculations by 45%
Fixes
- Resolved issue with preference persistence across sessions
- Fixed inconsistent emotion detection in mixed sentiment messages
- Addressed edge cases in scent profile recommendations
- Corrected data synchronization with e-commerce platform
Version 1.3.0 (2023-10-01)
New Features
- Self-Care Journey Orchestration: New capability to create and manage ongoing wellness routines
- Multi-modal Response System: Added support for rich media responses including images and audio
- Social Context Awareness: Enhanced understanding of social setting mentions in conversations
- Shopping Cart Integration: Direct product additions based on conversational context
Improvements
- Expanded emotional intelligence with 15 new emotional state recognitions
- Improved context retention across multi-day conversation spans
- Enhanced integration with Dojo platform for seamless learning transitions
- Reduced token usage by 20% through optimization of internal prompts
Fixes
- Resolved occasional context loss in long conversations
- Fixed incorrect product linking in certain recommendation scenarios
- Addressed timing issues in webhook event processing
- Corrected handling of ambiguous fragrance descriptions
Version 1.2.0 (2023-07-15)
New Features
- Custom Blend Advisor: Interactive guide for creating personalized fragrance blends
- Wellness Routine Builder: Step-by-step creator for personalized self-care routines
- Seasonal Collections Awareness: Integration with seasonal product offerings
- Member Recognition System: Improved returning user experience with preference memory
Improvements
- Added 35 new conversation flows for fragrance discovery
- Enhanced natural language understanding for scent descriptions
- Improved connection between emotional states and fragrance recommendations
- Expanded product knowledge base with detailed composition information
Fixes
- Resolved inconsistencies in tone across conversation transitions
- Fixed occasional duplication of recommendations in sequential queries
- Addressed delay in retrieving personalization data
- Corrected product availability checking logic
Version 1.1.0 (2023-04-10)
New Features
- Scent Profile Analysis: Added capability to interpret and store user scent preferences
- Mood-based Recommendations: New algorithm for matching products to current emotional states
- Order History Integration: Ability to reference past purchases in recommendations
- Product Comparison: Side-by-side comparison of fragrance products based on user criteria
Improvements
- Enhanced sentiment analysis accuracy by 25%
- Expanded product knowledge to include 50+ new items
- Improved conversational continuity across sessions
- Added more natural transitions between topics
Fixes
- Resolved issue with context retention in multi-turn conversations
- Fixed inconsistencies in product descriptions
- Addressed performance degradation during peak traffic periods
- Corrected preference weighting in recommendation algorithm
Version 1.0.0 (2023-01-20)
Initial Release
- Personalized Conversation Engine: Core conversational capabilities with personality alignment
- Basic Product Recommendations: Product suggestions based on explicit user preferences
- Fragrance Knowledge Base: Comprehensive information about scent families and notes
- Self-Care Assistant: General wellness and self-care guidance
- E-commerce Integration: Basic product catalog awareness and shopping assistance
- User Profile Management: Creation and maintenance of preference profiles
Known Limitations
- Limited understanding of complex emotional states
- Basic product recommendation system requires explicit preference statements
- No persistent memory of past conversations
- Limited integration with external platforms
- Constrained handling of ambiguous queries
Future Roadmap
Planned for v1.5.0 (Q1 2024)
- Real-time sentiment adaptation during conversations
- Integration with in-store experiences through QR codes
- Enhanced multi-sensory content delivery
- Expanded wellness journey capabilities
Under Consideration for Future Releases
- AR/VR integration for immersive fragrance experiences
- Voice-based interaction mode
- Collaborative fragrance design for multiple users
- Integration with wearable device data for contextual recommendations