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Implementation Plans

Phase 1: Knowledge Base Enhancement​

1. Data Structure & Schema Implementation​

  • Timeline: Weeks 1-2
  • Objective: Complete the searchable database implementation for material specifications
  • Tasks:
    • Design comprehensive schema for material specifications including physical properties, visual attributes, and application contexts
    • Implement full-text search capabilities with relevance scoring
    • Create relationships between materials, collections, and manufacturers
    • Develop metadata templates for consistent information extraction from various sources
    • Implement validation rules for data integrity

2. Tagging & Organization System​

  • Timeline: Weeks 2-3
  • Objective: Implement complete tagging system for organizing tiles by collections/series
  • Tasks:
    • Design hierarchical taxonomy for material categorization
    • Implement tag management with parent-child relationships
    • Create tag suggestion algorithms based on existing material properties
    • Develop bulk tagging capabilities for collection management
    • Implement tag analytics to measure usage and effectiveness

3. ML Integration Layer​

  • Timeline: Weeks 3-5
  • Objective: Connect knowledge base with ML models and training systems
  • Tasks:
    • Create data pipeline between knowledge base and ML training infrastructure
    • Implement feedback loop from ML recognition results to knowledge base entries
    • Develop confidence scoring for knowledge base entries based on ML verification
    • Create labeling interface for training data generation from knowledge base
    • Implement feature vector storage for material specifications

4. PDF Processing Integration​

  • Timeline: Weeks 5-7
  • Objective: Connect PDF processing pipeline with knowledge base
  • Tasks:
    • Develop extractors for structured material data from catalogs
    • Create mapping between extracted PDF data and knowledge base schema
    • Implement validation workflows for automated extraction
    • Design reconciliation process for conflicting information
    • Build dashboards for tracking extraction quality metrics

5. Web Crawling Integration​

  • Timeline: Weeks 7-9
  • Objective: Connect web crawler data with knowledge base
  • Tasks:
    • Design parsers for common manufacturer website structures
    • Create normalization pipeline for web-extracted data
    • Implement deduplication with existing knowledge base entries
    • Develop change detection for updated specifications
    • Build source attribution and confidence scoring system

6. Versioning System​

  • Timeline: Weeks 9-10
  • Objective: Implement versioning system for knowledge base updates
  • Tasks:
    • Design temporal data model for tracking changes over time
    • Implement differential storage for efficient version history
    • Create rollback capabilities for corrupted updates
    • Develop comparison tools for version differences
    • Build audit trails for regulatory compliance

7. Index Optimization​

  • Timeline: Weeks 10-11
  • Objective: Optimize knowledge base for efficient retrieval
  • Tasks:
    • Implement specialized indexes for common query patterns
    • Create caching layer for frequently accessed data
    • Develop query analysis tools to identify optimization opportunities
    • Implement auto-scaling capabilities for search infrastructure
    • Design performance monitoring and alerting system

8. Admin Interface​

  • Timeline: Weeks 11-13
  • Objective: Develop comprehensive admin interfaces for knowledge base management
  • Tasks:
    • Build CRUD interfaces for all knowledge base entities
    • Create dashboard for monitoring knowledge base health
    • Implement batch operations for bulk updates
    • Develop approval workflows for quality control
    • Create user permission system for differentiated access levels

9. Quality Assurance System​

  • Timeline: Weeks 13-14
  • Objective: Implement robust QA for knowledge base content
  • Tasks:
    • Design automated consistency checks for material properties
    • Create statistical anomaly detection for suspect values
    • Implement user feedback collection for incorrect information
    • Develop confidence scoring for knowledge base entries
    • Build reporting system for knowledge base quality metrics

10. Integration Testing & Deployment​

  • Timeline: Weeks 14-16
  • Objective: Ensure system reliability and deploy to production
  • Tasks:
    • Create comprehensive test suite for all knowledge base functions
    • Implement performance testing under various load conditions
    • Develop migration plan for existing data
    • Design rollout strategy with feature flags
    • Create monitoring and alerting for production environment

Phase 2: Agent Framework Integration (Future Phase)​

1. Agent Framework Foundation​

  • Objective: Establish the core agent infrastructure
  • Tasks:
    • Select appropriate framework (LangChain, LlamaIndex, etc.)
    • Create development environment and CI/CD pipeline
    • Implement core agent routing system
    • Design conversation state management
    • Build logging and monitoring infrastructure

2. Knowledge Base Connector​

  • Objective: Connect agent to the knowledge base
  • Tasks:
    • Create vector representation of knowledge base content
    • Implement semantic search capabilities over knowledge base
    • Develop context retrieval strategies for queries
    • Build knowledge synthesis from multiple entries
    • Create explanation generation for retrieved information

3. ML Model Integration​

  • Objective: Enable agent to leverage existing ML capabilities
  • Tasks:
    • Create API wrappers for all ML services
    • Implement image processing pipeline for agent requests
    • Develop multi-modal reasoning (text + image)
    • Build confidence scoring for ML results
    • Create explanation generation for ML decisions

4. Natural Language Understanding​

  • Objective: Improve comprehension of domain-specific queries
  • Tasks:
    • Create tile industry ontology for entity recognition
    • Implement domain-specific intent detection
    • Develop specialized prompt engineering for material queries
    • Build query reformulation for ambiguous requests
    • Create measurement and unit standardization

5. Conversation Management​

  • Objective: Enable complex multi-turn interactions
  • Tasks:
    • Implement stateful conversation tracking
    • Create clarification workflows for ambiguous queries
    • Develop response templating system
    • Build persona management for consistent tone
    • Implement conversation summaries and bookmarks

6. UI Integration​

  • Objective: Create seamless user experience
  • Tasks:
    • Design conversational UI components
    • Implement rich result formatting
    • Create multi-modal input (text, image, file)
    • Develop responsive layouts for all devices
    • Build accessibility features for inclusive design

7. Testing & Optimization​

  • Objective: Ensure agent quality and performance
  • Tasks:
    • Create comprehensive test suite for common scenarios
    • Implement user feedback collection and analysis
    • Develop performance optimization for response time
    • Build continuous improvement pipeline
    • Create benchmark system for measuring improvements

8. Deployment & Rollout​

  • Objective: Successfully deploy to production
  • Tasks:
    • Design phased rollout strategy
    • Create user onboarding and help content
    • Implement monitoring and alerting
    • Build analytics dashboard for usage patterns
    • Develop feedback collection system