Agent Infrastructure
The MOOD MNKY agent system is built on a robust infrastructure that powers all agent capabilities across the ecosystem. This infrastructure provides the foundation for our specialized agents to deliver personalized, context-aware assistance.
Core Infrastructure Components
Knowledge Base
The central repository of knowledge that enables agents to provide accurate, relevant information
Agent Orchestration
Coordination layer that manages agent selection, handoffs, and collaboration
Memory System
Multi-layered memory architecture for maintaining conversation context and recalling past interactions
User Profiling
Personalization system that adapts agent interactions to individual users
Architecture Overview
The agent infrastructure forms a cohesive system that supports all agent interactions:Integration Points
The agent infrastructure connects with several other systems in the MOOD MNKY ecosystem:Web Platform
Web Platform
Agents are integrated throughout the web experience through chat interfaces, contextual assistance, and personalized recommendations.
Dojo Platform
Dojo Platform
The learning environment leverages agents for educational guidance, content recommendations, and progress tracking.
E-commerce System
E-commerce System
Agents assist with product selection, custom product design, and provide post-purchase support.
Content Management
Content Management
The knowledge base connects with content management systems to ensure agents have access to the latest information.
Development Guidelines
When working with the agent infrastructure, developers should follow these guidelines:1
Authentication
All interactions with agent infrastructure APIs require proper authentication using the provided developer credentials.
2
Error Handling
Implement robust error handling for agent interactions, with appropriate fallbacks when services are unavailable.
3
Request Optimization
Minimize the number of requests to agent services by batching operations and caching responses where appropriate.
4
Testing
Test agent integrations thoroughly using the provided sandbox environment before deploying to production.
Performance Considerations
The agent infrastructure is designed to support high-performance interactions:- Response Time: Agent responses should be delivered within 1-2 seconds for optimal user experience
- Concurrency: The system supports thousands of simultaneous agent conversations
- Scaling: Infrastructure automatically scales based on demand
- Availability: Designed for 99.9% uptime with fallback mechanisms for degraded service
Security and Privacy
Data Encryption
All data in transit and at rest is encrypted using industry-standard protocols
Access Controls
Role-based access controls govern all access to agent infrastructure
Privacy by Design
User data is processed according to privacy principles with explicit consent
Audit Logging
Comprehensive logging of all administrative actions for security monitoring
Implementation Technologies
The agent infrastructure leverages several key technologies:- LangChain for agent workflows and chains
- Vector databases (Pinecone) for semantic knowledge storage
- Redis for caching and short-term memory
- PostgreSQL for structured data storage
- Node.js for API services
- Docker and Kubernetes for deployment and scaling
API Access
Access to agent infrastructure APIs is managed through our developer portal. Contact the development team for API credentials and detailed documentation on available endpoints.
Future Development
The agent infrastructure roadmap includes:- Enhanced multi-agent collaboration capabilities
- Advanced reasoning through retrieval-augmented generation
- Improved personalization through sophisticated user modeling
- Expanded knowledge management with automated updates
- Integration with additional platforms and services