directus-task-management/stories/6.3.story.md

Story 6.3: Build Context Management System

Story Information

• Epic/Task: Task 6 - Develop AI Integration Layer
• Story Number: 6.3
• Title: Build Context Management System
• Status: Ready
• Complexity: High
• Priority: Medium
• Dependencies: Tasks 6.1, 6.2 (6.1 completed, 6.2 ready)

Story Statement

As the Directus Task Management system, I need a robust context management system that maintains conversation history, tracks user preferences, manages project-specific context, and enables intelligent context-aware responses so that AI agents can provide relevant and consistent assistance across multiple interactions and sessions.

Acceptance Criteria

1. Context storage system persists conversation history across sessions
2. User preference tracking maintains individual settings and patterns
3. Project context management links tasks to relevant project information
4. Session management handles multiple concurrent user sessions
5. Context retrieval achieves sub-100ms response time for recent contexts
6. Memory pruning prevents unlimited context growth (configurable limits)
7. Context versioning allows rollback to previous states
8. Privacy controls enable users to manage their stored context
9. Context export/import functionality for backup and migration
10. Integration tests validate context persistence and retrieval

Dev Notes

Architecture Context References

• [Source: Story 6.1] - AI Task Service with context tracking implemented
• [Source: architecture.md#task_ai_contexts] - Context storage schema defined
• [Source: Story 6.2] - NLP system will generate context-rich data

Previous Story Insights

• Story 6.1: Established TaskAIContextEntity for storing AI context
• LangChain memory management patterns already implemented
• Redis caching available for fast context retrieval
• Token usage tracking helps manage context size

Context Management Architecture

Core Components:

interface ContextManagementSystem {
  // Storage layer
  contextStore: ContextStorageService;
  
  // Memory management
  conversationMemory: ConversationMemoryService;
  workingMemory: WorkingMemoryService;
  longTermMemory: LongTermMemoryService;
  
  // Retrieval and search
  contextRetriever: ContextRetrievalService;
  semanticSearch: SemanticSearchService;
  
  // Lifecycle management
  contextLifecycle: ContextLifecycleService;
  pruningEngine: MemoryPruningService;
}

Context Types:

• Conversation Context: Chat history, Q&A pairs, command history
• User Context: Preferences, patterns, frequently used features
• Project Context: Active projects, task relationships, dependencies
• System Context: Current state, active workflows, pending operations
• Temporal Context: Time-based relevance, deadline awareness

Memory Hierarchy

1. Working Memory (Redis): Active session, last 10 interactions
2. Short-term Memory (PostgreSQL): Recent 7 days, frequently accessed
3. Long-term Memory (PostgreSQL + compression): Historical data, searchable
4. Archive (S3/File storage): Exported contexts, backups

File Locations

Based on existing project structure:

• Context Services: src/services/context/ - Context management services
• Memory Services: src/services/context/memory/ - Memory implementations
• Storage: src/services/context/storage/ - Storage adapters
• Retrieval: src/services/context/retrieval/ - Retrieval services
• Tests: tests/services/context/ - Context service tests

Technical Constraints

• Must integrate with existing TaskAIContextEntity
• Maintain sub-100ms retrieval for active contexts
• Implement GDPR-compliant data management
• Use existing Redis and PostgreSQL infrastructure
• Handle concurrent multi-user sessions
• Respect token limits for AI models

Testing Requirements

• Unit tests for each context component
• Performance tests for retrieval speed
• Concurrency tests for multi-user scenarios
• Memory leak tests for long-running sessions
• Data integrity tests for persistence
• Privacy compliance tests

Tasks / Subtasks

Task 1: Set up Context Management Infrastructure (AC: 1)

• Create src/services/context/context-management.service.ts
• Define context interfaces and types
• Set up context configuration with environment variables
• Implement base context storage adapter pattern
• Add context-specific error handling

Task 2: Implement Conversation Memory Service (AC: 1, 4)

• Create src/services/context/memory/conversation-memory.service.ts
• Implement conversation history tracking
• Add message pairing (user input + AI response)
• Create session isolation for concurrent users
• Implement conversation summarization for long chats

Task 3: Build Working Memory System (AC: 5)

• Create src/services/context/memory/working-memory.service.ts
• Implement Redis-based fast memory store
• Add LRU cache for most recent contexts
• Create memory snapshots for persistence
• Implement memory merge strategies

Task 4: Develop Long-term Memory Service (AC: 1, 6)

• Create src/services/context/memory/long-term-memory.service.ts
• Implement PostgreSQL storage with compression
• Add memory indexing for fast retrieval
• Create memory pruning algorithms
• Implement importance scoring for retention

Task 5: Create Context Retrieval System (AC: 5)

• Create src/services/context/retrieval/context-retrieval.service.ts
• Implement multi-tier retrieval strategy
• Add semantic similarity search using embeddings
• Create relevance ranking algorithms
• Implement context aggregation from multiple sources

Task 6: Build User Preference Tracking (AC: 2)

• Create src/services/context/user-preference.service.ts
• Implement preference learning from interactions
• Add pattern recognition for user behavior
• Create preference persistence and retrieval
• Implement preference-based customization

Task 7: Implement Project Context Management (AC: 3)

• Create src/services/context/project-context.service.ts
• Link tasks to project contexts
• Implement project state tracking
• Add cross-project context sharing
• Create project context inheritance

Task 8: Add Context Versioning System (AC: 7)

• Create src/services/context/versioning/context-version.service.ts
• Implement version tracking for context changes
• Add rollback functionality
• Create diff generation between versions
• Implement version pruning policies

Task 9: Implement Privacy Controls (AC: 8)

• Create src/services/context/privacy/privacy-control.service.ts
• Add user consent management
• Implement context deletion on request
• Create anonymization functions
• Add audit logging for privacy operations

Task 10: Build Export/Import System (AC: 9)

• Create src/services/context/migration/export-import.service.ts
• Implement context export to JSON/CSV
• Add import with validation
• Create backup scheduling
• Implement migration between systems

Task 11: Create Context API Endpoints

• Add GET /api/context/conversation/:sessionId
• Add POST /api/context/save
• Add DELETE /api/context/clear/:userId
• Add GET /api/context/export/:userId
• Implement proper authentication and authorization

Task 12: Write Tests (AC: 10)

• Create unit tests for memory services
• Create integration tests for context persistence
• Add performance tests for retrieval
• Create concurrency tests
• Achieve 80% code coverage

Task 13: Documentation and Monitoring

• Create context management guide
• Add monitoring metrics for memory usage
• Document privacy compliance
• Create troubleshooting guide
• Add performance tuning documentation

Project Structure Notes

• Extends AI infrastructure from Stories 6.1 and 6.2
• Uses existing Redis and PostgreSQL setup
• Maintains TypeORM entity patterns
• Integrates with LangChain memory management

Dev Agent Record

To be filled by implementing agent

File List

Created:

Modified:

Implementation Notes

To be filled during implementation

Challenges Encountered

To be filled during implementation

Technical Decisions

To be filled during implementation

Completion Notes

To be filled upon completion

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Story created by: Bob (Scrum Master) Date: 2025-08-12