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CEO (Context/Execution Orchestrator) Component ​

Overview: CEO serves as the "cognitive executive" of Mnemoverse orchestration, bridging the gap between human communication patterns and machine-optimized context assembly. It translates high-level user intents into structured resource allocation decisions while maintaining computational efficiency.

Component Architecture ​

Core Responsibilities ​

1. Intent Interpretation ​

  • Function: Parse and understand user queries at semantic level
  • Scope: Natural language → structured intent with entities and operations
  • Features: Context-aware parsing, ambiguity resolution, intent classification
  • Output: Structured intent objects with confidence scores

2. Resource Budget Management ​

  • Function: Allocate computational resources based on query complexity
  • Scope: Token budgets, time constraints, cost management
  • Features: Dynamic budget sizing, priority-based allocation, overspend protection
  • Output: Budget constraints for downstream components

3. Risk Assessment & Privacy Control ​

  • Function: Evaluate request safety and privacy implications
  • Scope: Content filtering, privacy mode selection, security validation
  • Features: Risk profiling, privacy policy enforcement, audit logging
  • Output: Risk profiles and privacy directives

4. Orchestration Coordination ​

  • Function: Coordinate multi-component workflow execution
  • Scope: ACS communication, error handling, response assembly
  • Features: Retry logic, fallback strategies, quality assurance
  • Output: Final user-facing responses

Key Features ​

Intent Processing Pipeline ​

typescript
interface IntentProcessing {
  // Stage 1: Raw input analysis
  parseQuery(input: string): ParsedQuery;
  
  // Stage 2: Semantic understanding  
  extractIntent(query: ParsedQuery): Intent;
  
  // Stage 3: Context enrichment
  enrichContext(intent: Intent): EnrichedIntent;
  
  // Stage 4: Resource planning
  planBudgets(intent: EnrichedIntent): BudgetPlan;
}

Budget Allocation Strategy ​

  • Token Budget: Dynamic sizing based on query complexity (1K-8K tokens)
  • Time Budget: Adaptive timeouts based on urgency indicators (300ms-2s)
  • Cost Budget: Spending limits with provider cost optimization
  • Quality Budget: Trade-off management between speed and thoroughness

Error Recovery Framework ​

  • Graceful Degradation: Maintain functionality under component failures
  • Intelligent Retry: Context-aware retry strategies with backoff
  • Option Presentation: Structured choices when automatic recovery fails
  • User Feedback Loop: Learning from user decisions for future improvements

Integration Points ​

Upstream Interfaces ​

  • HTTP API: Receives requests from external clients
  • User Context: Session management and personalization data
  • Authentication: User identity and authorization context

Downstream Interfaces ​

  • ACS Communication: ../api/internal.md render_request.v0
  • HCS Coordination: Future streaming and delivery coordination
  • Audit Logging: Security and compliance event recording

Data Flow ​

typescript
// Incoming request processing
interface CEOWorkflow {
  input: UserRequest;
  
  // Processing stages
  intent: Intent = this.parseIntent(input);
  budget: Budget = this.calculateBudget(intent);
  risk: RiskProfile = this.assessRisk(intent);
  
  // ACS coordination
  acsRequest: ACSRequest = this.buildACSRequest(intent, budget, risk);
  acsResponse: ACSResponse = await this.callACS(acsRequest);
  
  // Response assembly
  output: UserResponse = this.assembleResponse(acsResponse);
}

Performance Characteristics ​

Latency Targets ​

  • Intent Processing: < 50ms (p95)
  • Budget Planning: < 20ms (p95)
  • Error Handling: < 100ms (p95)
  • End-to-End: < 200ms excluding ACS processing

Throughput Capacity ​

  • Single Instance: 500+ requests/second
  • Resource Usage: Low CPU, minimal memory footprint
  • Scaling: Stateless horizontal scaling supported

Quality Metrics ​

  • Intent Accuracy: > 95% correct classification
  • Budget Efficiency: < 10% resource waste
  • Error Recovery: > 90% successful automatic recovery

Current Implementation Status ​

✅ Completed (v0) ​

  • Core architecture specification (32,000+ lines)
  • Intent processing framework design
  • Budget allocation algorithms
  • Risk assessment patterns
  • API contract definitions

🚧 In Progress ​

  • Intent classification implementation
  • Budget optimization algorithms
  • Error recovery logic implementation
  • Performance testing and validation

📋 Planned (v0.1+) ​

  • Machine learning intent models
  • Advanced budget prediction
  • Personalization features
  • Multi-modal input support

Documentation References ​

Technical Specifications ​

Integration Guides ​

Getting Started ​

For Component Developers ​

  1. Review the comprehensive architecture.md specification
  2. Study the API contracts in ../api/internal.md
  3. Understand error handling patterns in ../errors.md
  4. Examine end-to-end examples in ../../walkthrough.md

For Integration Partners ​

  1. Start with HTTP API documentation in ../api/http.md
  2. Review request/response schemas in /architecture/contracts/schemas
  3. Test with example payloads and error scenarios
  4. Implement client-side error handling for graceful degradation

Component Status: Architecture Complete → Implementation In Progress → Production Ready (Target: v0.1)